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Genetic engineering of fungi to enhance the production and elucidate the biosynthesis of bioactive secondary metabolites

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Genetic engineering of fungi to enhance the production and elucidate the biosynthesis of bioactive secondary metabolites

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Genetic engineering of fungi to enhance the
production and elucidate the biosynthesis of
bioactive secondary metabolites

Dissertation by:
Michelle Grau

Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
In Partial Fulfillment of the Requirements for the Degree of
DOCTOR OF PHILOSOPHY (MOLECULAR PHARMACOLOGY AND TOXICOLOGY)

UNIVERSITY OF SOUTHERN CALIFORNIA
Los Angeles, California

August 2019
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© 2019
Michelle Grau
ORCID: https://orcid.org/0000-0001-5930-5552
All rights reserved
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To my family, friends, and those
that have helped and inspired me
along the way.

I couldn’t have done this without you.

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Acknowledgements

It has been a privilege working for my mentor and supervisor, Professor Clay C. C. Wang. His
encouragement and continued faith in my abilities have allowed me to grow and given me the
confidence I struggled to find. His curiosity and enthusiasm about the world of fungal natural
products have been contagious, and I continue to be inspired by his scientific vision and
creativity. The dissertation work I present here is a direct result of Dr. Wang’s guidance and
expertise.
I would also like to thank our collaborators for their expertise and invaluable contributions
to my PhD thesis. Professor Berl R. Oakley from the University of Kansas has been more than
just a collaborator but a crucial advisor. Despite his busy schedule, Dr. Oakley has never failed
to contribute his time—from giving me feedback on manuscripts to answering my many
questions as I prepared for my qualifying exam. I am fortunate for the guidance I have received
from Professor Richard B. Todd from Kansas State University. I am grateful for his advice and
support and am inspired by his genuine concern and work ethic. I have great respect for the
contributions Dr. Wang, Dr. Oakley and Dr. Todd have made to the field of fungal genetics and
natural products, and it has been an honor to work with them.
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I would like to thank the members of my dissertation committee—Professors Curtis
Okamoto, Yong Zhang, Ian Haworth, and Travis Williams. My committee members, with their
diverse areas of expertise, have given me a greater perspective and provided me with essential
feedback and support throughout my graduate career.
I am incredibly lucky to have had the privilege to learn and receive training from Professor
Yi-Ming Chiang. He has contributed significantly to my problem-solving ability and critical
thinking skills. Dr. Chiang never ceases to amaze me with his extensive experience and
comprehensive knowledge. He has helped shape me into the scientist I have become.
I am thankful to my former lab members—Dr. Chun-Jun Guo, Dr. Junko Yaegashi, Dr. James
Sanchez, Dr. John Gallagher, Dr. Tzu-Shyang Lin, Yien Liao, Dr. Johannes van Dijk, Dr. Jillian
Romsdahl, Dr. Adriana Blachowicz—for imparting their knowledge and experience, for their
assistance and training, and for showing me the way. I thank Dr. Romsdahl for training me
when I began in the Wang lab. She taught me many techniques and was a vital companion. I
will forever be grateful for Dr. Blachowicz who has been more to me than just a colleague and a
great friend—I consider her as family. She has been a constant and reliable source of help and
support throughout my PhD, and I thank her for always challenging me.
I appreciate my current lab members—Patrick Lehman, Bo Yuan, Chris Rabot, Sujeung Lim,
Ngan Pham, Jingyi Wang, Gujie Xu, and Dr. Ming-Shian Lee—for helping to make the Wang lab a
great working environment. I look forward to the future work of these talented scientists. A
special thanks to Bo Yuan for her assistance and training. I continue to be inspired by her innate
laboratory skills and diligence.
Besides those mentioned, I have built other relationships along the way that have been
pivotal to my success. I express my sincerest gratitude to Steven Glenn who has been a solid
source of help and support to me. He has expanded my horizons, taught me true compassion,
and helped me to become not only a better scientist but a better person. I am also fortunate
for the friendships I have cultivated with Xianhui Chen and Dr. Hsuan-Yao Wang. They have
both been a wonderful source of advice and support.
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Thank you to the USC School of Pharmacy and the USC Graduate School for supporting me
with fellowships and assistantships that have made it possible for me to earn a PhD. I am
grateful to the hardworking members of the USC School of Pharmacy Graduate Affairs Office
who have provided me with valuable opportunities and assistance while here.
Most importantly, I would like to send out a heartfelt thank you to my family who has
relentlessly supported me in my educational endeavors. My PhD and previous successes would
not have been possible without them.
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Abstract

Natural products have been important in drug discovery from ancient history to modern-day.
They are resources for compounds with functional and chemical diversity unsurpassed by any
synthetic library. Secondary metabolites have been developed into many important commercial
drugs ranging from antibiotics and antifungals to immunotherapies and cholesterol-lowering
agents.
Recent advancements in whole genome sequencing technologies have revolutionized
research into fungal secondary metabolism. Genomes can be sequenced quickly and
inexpensively due to next generation sequencing platforms, generating a wealth of publicly
available fungal genomes. Genetic studies on fungi have established that the genes to produce a
secondary metabolite are arranged contiguously within the genome, forming secondary
metabolite biosynthetic gene clusters. The rapid development of bioinformatic algorithms that
predict secondary metabolite gene clusters has shown that the potential for natural product drug
discovery is much greater than we had anticipated. Most secondary metabolite gene clusters are
unexpressed in normal laboratory conditions, prompting the development of techniques to
access the fungal metabolome.
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The work described in this thesis details the approaches we have taken to understand
secondary metabolite regulation, activate silent gene cluster expression, establish the genes
necessary to produce a specific metabolite, and deduce the functions of the biosynthetic
enzymes and proteins encoded by these genes. Chapter 1 is an overview of fungal secondary
metabolites, emphasizing their importance in drug discovery, the enzymes involved, and the
game-changing genomic and bioinformatic advances driving the production of these valuable
compounds.
Enzymes, known as ‘global’ or ‘master’ regulators, can influence the expression of multiple
secondary metabolite gene clusters. In chapter 2, we genetically engineered strains of Aspergillus
nidulans to overexpress one of these regulators, LlmG, resulting in the upregulation of several
secondary metabolite gene clusters and the production of 30 different compounds. In chapters
3 and 4, we engineered a strain of A. nidulans to express a hybrid transcription factor that was
cluster-specific and efficient at facilitating the transcription of the genes necessary to produce
the antibiotic, (+)-asperlin. We established the genes involved in (+)-asperlin biosynthesis,
characterized the accumulated intermediates from single-gene deletion strains, and proposed
the biosynthetic steps required to produce this bioactive metabolite. Chapter 5 describes our
efforts to characterize the genome of a radiation-exposed fungal isolate of Scopulariopsis candida
that was collected from the Chernobyl Exclusion Zone and shown to inhibit Candida albicans
growth. Through genome annotation and secondary metabolite cluster prediction, we
established the gene cluster for the antifungal compound hymeglusin. The genes necessary for
the biosynthesis of hymeglusin were determined using CRISPR/Cas9 targeted gene deletions
followed by metabolic analysis of the deletion strains. Finally, in chapter 6 I summarize our
findings, explain their significance, and discuss future experiments to build upon this work.
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TABLE OF CONTENTS

Acknowledgements ............................................................................................................. v
Abstract ...............................................................................................................................vii
Table of Contents ................................................................................................................ix
List of Figures ...................................................................................................................... xii
List of Tables ....................................................................................................................... xv
Nomenclature .................................................................................................................... xvi
Chapter 1: Introduction ....................................................................................................... 1
1.1 Natural products for drug discovery .................................................................... 1
1.2 Secondary metabolite gene clusters ................................................................... 3
1.3 Fungal genome sequencing and bioinformatic advances ................................... 6
1.4 Regulation of secondary metabolism .................................................................. 8
1.5 Approaches to activate silent gene clusters in fungi ......................................... 12
Chapter 2: Overexpression of an LaeA-like methyltransferase upregulates secondary
metabolite production in Aspergillus nidulans .......................................................... 18
2.1 Abstract .............................................................................................................. 18
2.2 Introduction ....................................................................................................... 19
2.3 Results and Discussion ....................................................................................... 21
2.3.1 LlmG is a positive regulator of secondary metabolite production ....... 21
2.3.2 LlmG overexpression results in the upregulation of several additional
SMs under different culture conditions .............................................. 24
2.3.3 Identification of unknown (23) as an intermediate of cichorine
biosynthesis .......................................................................................... 28
2.4 Conclusion .......................................................................................................... 30
2.5 Methods ............................................................................................................. 30
2.5.1 Molecular genetic procedures .............................................................. 30
2.5.2 Culturing and HPLC-DAD-MS analysis ................................................... 31
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2.5.3 Compound isolation and purification ................................................... 32
2.5.4 Structural characterization ................................................................... 33
2.6 Supporting Information ..................................................................................... 34
Chapter 3: Hybrid transcription factor engineering activates the silent secondary
metabolite gene cluster for (+)-asperlin in Aspergillus nidulans ............................... 47
3.1 Abstract .............................................................................................................. 47
3.2 Introduction ....................................................................................................... 48
3.3 Results and Discussion ....................................................................................... 52
3.3.1 Induction of AN11199 and AN11191 results in the production of
(2Z,4Z,6E)-octa-2,4,6-trienoic acid ....................................................... 52
3.3.2 Construction and expression of a synthetic hybrid transcription
factor drives expression of the AN11191 gene cluster ........................ 53
3.3.3 Reannotation of AN9221 ...................................................................... 62
3.3.4 Hybrid transcription factor expression drives production of
(+)-asperlin (2) ...................................................................................... 63
3.4 Conclusion .......................................................................................................... 65
3.5 Methods ............................................................................................................. 67
3.5.1 Bioinformatic analysis of transcription factors ..................................... 67
3.5.2 Fermentation and LC/MS analysis ....................................................... 67
3.5.3 Compound spectral data ....................................................................... 68
3.5.4 Transformation procedures and construction of transforming
molecules .............................................................................................. 68
3.5.5 RNA-seq ................................................................................................ 69
3.6 Supporting Information ..................................................................................... 69
Chapter 4: Hybrid transcription factor expressing strains help to elucidate the (+)-
asperlin biosynthetic pathway ................................................................................... 84
4.1 Abstract .............................................................................................................. 84
4.2 Introduction ....................................................................................................... 85
4.3 Results and Discussion ....................................................................................... 87
4.3.1 Identification, purification and structural elucidation of
intermediates and shunt products from hybrid transcription factor
expressing single gene deletion strains ............................................... 87
4.3.2 Proposed biosynthesis of (+)-asperlin ................................................... 90
4.4 Conclusion .......................................................................................................... 91
4.5 Methods ............................................................................................................. 92
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4.5.1 Fermentation and HPLC-DAD-MS analysis ........................................... 92
4.5.2 Isolation and purification of metabolites.............................................. 92
4.5.3 Compound spectral data ....................................................................... 93
4.6 Supporting Information ..................................................................................... 94
Chapter 5: Discovery of the biosynthetic pathway for the antifungal hymeglusin in
Scopulariopsis candida ............................................................................................. 112
5.1 Abstract ............................................................................................................ 112
5.2 Introduction ..................................................................................................... 113
5.3 Results and Discussion ..................................................................................... 115
5.3.1 Anti-Candida activity observed by Scopulariopsis candida
IMV00968 ........................................................................................... 115
5.3.2 Identification of the hymeglusin gene cluster in IMV00968 .............. 117
5.3.3 CRISPR/Cas9 facilitated gene disruptions help to confirm the
hymeglusin gene cluster boundaries ................................................ 119
5.4 Conclusion ........................................................................................................ 121
5.5 Methods ........................................................................................................... 122
5.5.1 Isolation and identification of the IMV isolates .................................. 122
5.5.2 Coculture screening of IMV strains ..................................................... 122
5.5.3 Disk-diffusion test with IMV00968 culture extract ............................. 122
5.5.4 HPLC-DAD-MS analysis ........................................................................ 123
5.5.5 Genome sequencing, assembly and annotation of IMV00968 .......... 124
5.5.6 CRISPR/Cas9 plasmid construction ..................................................... 125
5.5.7 Protoplasting and transformation of IMV00968 ................................ 125
5.6 Supporting Information ..................................................................................... 127
Chapter 6: Conclusions and perspectives ....................................................................... 131
Bibliography ..................................................................................................................... 134

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LIST OF FIGURES

Number Page
1.1 Examples of secondary metabolites produced by fungi ..................................................... 2
1.2 All new approved drugs from 1981-2010 ........................................................................... 3
1.3 Biosynthetic gene clusters and fungal secondary metabolism core enzymes ................... 4
1.4 Environmental stimuli that can contribute to the production of secondary metabolites
in fungi ................................................................................................................................ 9
1.5 Pathway-specific transcriptional regulation of a biosynthetic gene cluster ..................... 9
1.6 Regulation of secondary metabolism in various fungi in response to environmental
stimuli through global regulatory proteins ...................................................................... 10
1.7 Cultivation-based approaches to activate secondary metabolite biosynthetic gene
clusters to produce novel natural products ..................................................................... 13
1.8 Molecular approaches to activate silent secondary metabolite biosynthetic gene
clusters .............................................................................................................................. 14
2.1 Replacement of the native llmG promoter with a strong constitutive promoter ............ 21
2.2 HPLC paired profile scans of llmG overexpression and mcrA deletion strains compared
to the control strain on GMM(s) and YAG plates ............................................................. 23
2.3 HPLC paired profile scans of llmG overexpression and mcrA deletion strains compared
to the control strain in GMM and YG liquid media .......................................................... 26
2.4 Chemical structures of compounds that were upregulated in the gpdA(p)llmG, mcrA ,
and gpdA(p)llmG::mcrA  strains ...................................................................................... 27
2.5 Enhanced production of compound 23 observed in a multicluster deletion, mcrA ,
gpdA(p)llmG strain ............................................................................................................ 29
2.6 UV-Vis and ESIMS spectra of new and unknown compounds identified in this study ..... 39
2.7
1
H NMR spectrum of 7-methoxy-1-methyl-1,3-dihydroisobenzofuran-1,5-diol (23) in
CD 3OD (400 MHz) .............................................................................................................. 43
2.8
13
C NMR spectrum of 7-methoxy-1-methyl-1,3-dihydroisobenzofuran-1,5-diol (23) in
CD 3OD (400 MHz) .............................................................................................................. 44
2.9 HMBC correlations (H → C) of compound 23 ................................................................... 45
2.10 Proposed cichorine biosynthesis including compounds 22-23, 41 and 47 ...................... 46
3.1 Organization of the (+)-asperlin biosynthetic gene cluster in A. nidulans ....................... 51
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3.2 PDA and EIC+ = m/z 213 traces of alnR, alnA + alnB, and hybrid transcription factor
overexpression strains ...................................................................................................... 54
3.3 DNA binding specificity and function of the AfoA, FacB, and hybrid FacB-AfoA
transcription factors ......................................................................................................... 57
3.4 Protein, DNA binding specificity, and compound produced when the expression of
afoA, AN9221, alnR, and the hybrid alnR::afoA is induced with the alcA(p); molecular
construction of an AlnR-AfoA hybrid transcription factor expressing strain ................... 59
3.5 RNA-seq transcript alignments of genes surrounding alnA for the hybrid transcription
factor (HyTF) expressing A. nidulans strain; EIC = m/z 213 chromatograms of A.
nidulans single gene deletion HyTF expressing strains .................................................... 64
3.6 The deduced functions of each ORF based on the AspGD gene designations and an
overview of (+)-asperlin biosynthesis ............................................................................... 65
3.7 Correct coding sequence for afoA and corresponding amino acid sequence of its
protein product (AfoA)...................................................................................................... 71
3.8 Corrected annotation of AN11200 ................................................................................... 74
3.9 CAGE RNA-seq data showing the transcription start site for alnR .................................. 74
3.10 Coding sequence of alnR along with predicted amino acid sequence ............................ 75
3.11 Coding sequence of alnG and amino acid sequence of its predicted product ................ 76
3.12 HRESIMS spectra of (2Z,4Z,6E)-octa-2,4,6-trienoic acid (1) and (+)-asperlin (2) .............. 78
3.13 (2Z,4Z,6E)-octa-2,4,6-trienoic acid (1) and (+)-asperlin (2)
1
H and
13
C assignments ........ 79
3.14
1
H NMR of (2Z,4Z,6E)-octa-2,4,6-trienoic acid (1) in CDCl 3 (400 MHz) ............................ 80
3.15
13
C NMR of (2Z,4Z,6E)-octa-2,4,6-trienoic acid (1) in CDCl 3 (100 MHz) ........................... 81
3.16
1
H NMR of (+)-asperlin (2) in CDCl 3 (400 MHz) ................................................................. 82
3.17
13
C NMR of (+)-asperlin (2) in CDCl 3 (100 MHz) ................................................................ 83
4.1 Organization of the aln gene cluster in A. nidulans .......................................................... 88
4.2 MS analysis of the intermediates and shunt products generated by hybrid
transcription factor expressing single aln gene deletion strains ..................................... 89
4.3 Proposed biosynthetic pathway for (+)-asperlin (2) and related shunt products ............ 90
4.4 ESIMS spectra of compounds 3-6 ..................................................................................... 96
4.5 Total scan PDA traces of the hybrid transcription factor expressing parental strain
and intermediate-producing deletion strains ................................................................... 97
4.6 TIC traces of the hybrid transcription factor expressing parental strain and
intermediate-producing deletion strains .......................................................................... 98
4.7
1
H NMR spectrum of the LO11157 (alnDΔ) crude extract in CDCl 3 (400 MHz) ................ 99
4.8
1
H NMR spectrum of the LO11293 (alnGΔ) crude extract in CDCl 3 (400 MHz) .............. 100
4.9
1
H NMR spectrum of the LO11192 (alnFΔ) crude extract in CDCl 3 (400 MHz) ............... 101
4.10
1
H NMR spectrum of the LO11289 (alnHΔ) crude extract in CDCl 3 (400 MHz) .............. 102
4.11
1
H NMR spectrum of the LO11302 (alnIΔ) crude extract in CDCl 3 (400 MHz) ................ 103
4.12
1
H NMR spectrum of (+)-phomalactone (3) in CDCl 3 (400 MHz) .................................... 104
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4.13
13
C NMR spectrum of (+)-phomalactone (3) in CDCl 3 (100 MHz) ................................... 105
4.14
1
H NMR spectrum of (+)-acetylphomalactone (4) in CDCl 3 (400 MHz) .......................... 106
4.15
13
C NMR spectrum of (+)-acetylphomalactone (4) in CDCl 3 (100 MHz) ......................... 107
4.16
1
H NMR spectrum of catenioblin A (5) in CDCl 3 (400 MHz) ............................................ 108
4.17
13
C NMR spectrum of catenioblin A (5) in CDCl 3 (100 MHz) ........................................... 109
4.18
1
H NMR spectrum of musacin D (6) in CDCl 3 (400 MHz) ................................................ 110
4.19
13
C NMR spectrum of musacin D (6) in CDCl 3 (100 MHz) ............................................... 111
5.1 Anti-Candida activity observed by Scopulariopsis candida IMV00968 results from the
production of the antimicrobial hymeglusin .................................................................. 116
5.2 Putative hymeglusin gene clusters in S. candida IMV00968 and F. solani FSSC 5 v1.0. 118
5.3 Metabolic DAD total scan HPLC profiles of S. candida IMV00968 wild-type and single
gene deletion strains ...................................................................................................... 120
5.4 UV-Vis and ESIMS spectra of hymeglusin (1), fusaridioic acid A (2), and unknown (3) . 127
5.5 Agarose gel images of PCR amplified fragments 1 and 2 for Gibson Assembly with
pFC334 ............................................................................................................................ 128
5.6 Agarose gel images of Gibson Assembly results for fragments 1 and 2 with pFC334 ... 128
5.7 Colony check PRC arose gel images of an amplified region of pFC334 plasmids with
gene-specific sgRNA from E. coli DH5  transformants .................................................. 129
5.8 Agarose gel images of a PCR amplified region of propagated pFC334 plasmids with
gene-specific sgRNA ........................................................................................................ 129

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LIST OF TABLES

Number Page
1.1 Tools and techniques for mining the fungal secondary metabolome ............................... 7
2.1 Strains used in this study .................................................................................................. 22
2.2 Fold change values of secondary metabolites produced by llmG overexpression and
mcrA deletion strains compared to the control strain (llmG
+
, mcrA
+
) in GMM(s) ........... 35
2.3 Fold change values of secondary metabolites produced by llmG overexpression and
mcrA deletion strains compared to the control strain (llmG
+
, mcrA
+
) in YAG .................. 36
2.4 Fold change values of secondary metabolites produced by llmG overexpression and
mcrA deletion strains compared to the control strain (llmG
+
, mcrA
+
) in GMM(l) ............ 37
2.5 Fold change values of secondary metabolites produced by llmG overexpression and
mcrA deletion strains compared to the control strain (llmG
+
, mcrA
+
) in YG ................... 38
2.6 Primers used in this study ................................................................................................. 42
2.7 NMR spectroscopic data (400 MHz, CD 3OD) for compound 23 ....................................... 45
3.1 Strains used in this study .................................................................................................. 53
3.2 Hybrid transcription factor induction of the (+)-asperlin gene cluster ............................ 61
4.1 Putative functions of genes within the (+)-asperlin gene cluster and their homologs .... 88
4.2 Strains used in this study .................................................................................................. 94
4.3 NMR spectroscopic data (400 MHz, CDCl 3) for compounds 3-6 ...................................... 95
5.1 Putative functions of genes within the Scopulariopsis candida IMV00968 hymeglusin
gene cluster and their Fusarium solani FSSC 5 v1.0 homologues .................................. 118
5.2 Protospacer sequences for genes targeted by CRISPR/Cas9 in S. candida IMV00968 .. 129
5.3 Primers used for plasmid construction ........................................................................... 130
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Nomenclature

4’-PP 4’-phosphopantetheine
A adenylation
ACP acyl-carrier protein
AntiSMASH antibiotics and secondary metabolite analysis shell
AT acyltransferase
BGC biosynthetic gene cluster
C condensation
CASSIS cluster assignment by islands of sites
CoIN co-inducible nitrate
CRISPR/Cas9 clustered regularly interspaced short palindromic repeats/CRISPR-associated
protein 9
DH dehydratase
DNA deoxyribonucleic acid
E epimerization
ER enoyl reductase
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ESMIS electron spray ionization mass spectrometry
FAC fungal artificial chromosome
FGSC Fungal Genetics Stock Center
GARLIC global alignment for natural products cheminformatics
GMM glucose minimal media
GRAPE Gene-Ranking Analysis of Pathway Expression
HeX heterologous expression
HMG-CoA 3-hydroxy-3-methyl-glutaryl-coenzyme A
HPLC-DAD-MS high performance liquid chromatography-diode array detector-mass
spectrometry
HRESIMS high resolution electron spray ionization mass spectrometry
HR-PKS highly reducing polyketide synthase
HyTF hybrid transcription factor
IMG-ABC Integrated Microbial Genomes-Atlas of Biosynthetic Gene Clusters
IMV Institute for Microbiology and Virology (Academy of Sciences), Kiyv, Ukraine
ITS internal transcribed spacer
JGI Joint Genome Institute
KR β-ketoacyl reductase
KS ketoacyl synthase
LBNL Lawrence Berkeley National Laboratory
LC-MS liquid chromatography mass spectrometry
LMM lactose minimal media
MeCN acetonitrile
MEK methyl ethyl ketone
MiBiG Minimum Information about a Biosynthetic Gene Cluster
MIDDAS motif-independent de novo detection of secondary metabolite gene clusters
MS mass spectrometry
- xviii -

MT methyltransferase
NMR nuclear magnetic resonance
NP natural product
NRPS nonribosomal peptide synthetase
OSMAC one species many compounds
PCP peptidyl carrier protein
PKS polyketide synthase
PPT 4’-phosphopantetheine transferase
PRISM PRediction Informatics for Secondary Metabolomes
SAGA-ADA Spt-Ada-Gcn5-acetyltransferase-ADA
SAT starter acyl-carrier protein transacylase
SeMPI secondary metabolite prediction and identification
SM secondary metabolite
SMIPS secondary metabolites by InterProScan
SMURF secondary metabolite unknown region finder
TC terpene cyclase
TE thioesterase
TS terpene synthase
UV ultraviolet
WT wild type
YAG yeast agar glucose media
YES yeast extract sucrose media
YG yeast glucose media

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Chapter 1
Introduction

1.1 Natural products for drug discovery
All living beings are comprised of organic molecules that make up the building blocks
necessary for life. In some cases, these compounds are acquired from an organism’s
surroundings, but mostly, the metabolites necessary for basic cellular function are produced
by the cell. While there are significant differences between a single-celled organism and a
human being, the primary metabolite chemicals found within a cell from either organism have
a high degree of similarity. What differs drastically between living organisms is the production
of a diverse array of small molecules seemingly unnecessary for cellular viability. These
secondary metabolites (SMs), or natural products, function as chemical signals for
communication, as defense from competing species, or as protection from harmful
environmental elements.
1,2
For a SM to inhibit the growth of a competing organism, it must
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Figure 1.1: Examples of SMs produced by fungi. Penicillin G is a clinically used antibiotic produced by
Penicillium chrysogenum.
3,4
Cylosporine A is a clinically used immunosuppressant produced by
Tolypocladium inflatum.
5
Lovastatin is a clinically used cholesterol-reducing drug produced by
Aspergillus terreus.
6
Aflatoxin B1, produced by Aspergillus flavus, and gliotoxin, produced by
Aspergillus fumigates, are SMs with adverse toxic activities.
7,8
Aspyridone A, produced by Aspergillus
nidulans, is a SM with moderate cytotoxic activity.
9
Gibberellin A3 is a plant hormone produced by
fungi such as Fusarium fujikuroi.
10
Ergotamine is an ergot alkaloid produced by many fungi, including,
Claviceps purpurea.
11
Figure adapted from REF
12
, Nature Reviews
interact with one or more receptors in that competitor. For this reason, SMs have important
pharmacological applications. In its environment, a fungal species will interact and compete
with bacteria, viruses, plants, and other fungal species. To survive this competition, some fungi
produce SMs with antibacterial, antiviral, phytotoxic, and/or antifungal activities. A literature
survey from 1993 to 2001 showed that of the 1,500 compounds isolated from fungi, more than
half displayed antibacterial, antifungal, or antitumor activity.
13
Examples of some well-known
bioactive fungal SMs are included in Figure 1.1. Technological advances have helped shape our
understanding of the potential that exists for fungal natural product drug discovery. We have
only begun to scratch the surface. While some synthetic small molecule drugs have resulted in
- 3 -

successful pharmaceuticals, the
human mind’s abilities fall short of
evolution’s creativity. We continue to
discover bioactive natural products
with chemical scaffolds never seen
through synthetic methods. A study
from 1981 to 2010 highlights the
crucial role of natural products for
drug development, with 64% of all
approved small molecule drugs being
inspired by, derived from, or
themselves, natural products (Figure
1.2).
14
1.2 Secondary metabolite gene clusters
While the genes required for the synthesis of a primary metabolite are dispersed throughout the
fungal genome, the genes required for the synthesis of a SM are clustered together into
biosynthetic gene clusters (BGCs).
15
SM biosynthesis involves the polymerization of primary
metabolites by backbone or core enzymes. The chemical class of the SM produced is defined by
the core enzyme. Polyketide synthases (PKSs) use malonyl building blocks, provided by malonyl-
CoA, to construct polyketide SMs. Non-ribosomal peptide synthases (NRPSs) use amino acid
building blocks to generate non-ribosomal peptides, and terpene synthases and terpene cyclases
(TSs and TCs) use activated isoprene units to produce terpene SMs. PKSs and NRPSs are very large
enzymes made up of one to many modules containing multiple domains (Figure 1.3). Each
module facilitates one discrete chain elongation step, and within the module are specific domains
that are responsible for determining which extender unit or building block is selected to add to
the growing chain in addition to catalyzing the steps necessary for polymerization (Figure 1.3).

Figure 1.2: All new approved drugs from 1981-2010; n =
1355.

- 4 -

In a PKS, three domains are required in each elongation module; an acetyltransferase (AT)
domain, a ketoacyl synthase (KS) domain, and an acyl-carrier protein (ACP) domain. In addition,
the enzyme is flanked by a starter ACP transacylase (SAT) domain and a thioesterase (TE)
termination domain (Figure 1.3). Catalyzed by the starter module’s AT domain, the starter unit is
loaded onto the SAT domain of the starter module. The polyketide chain is transferred from the
SAT domain or the previous module’s ACP domain to the KS domain of the next module. The
extender unit is loaded onto the next module’s ACP domain, catalyzed by the AT domain within
the same module. The AT domain selects the extender unit to add onto the growing polyketide
and transfers it to the ACP domain. This domain features a serine-attached 4’-
phosphopantetheine (4’PP) group which forms a thioester bond with the growing polyketide
backbone. The ACP-bound extender unit reacts with the KS-bound polyketide chain, resulting in
a free KS domain and an ACP-bound elongated polyketide chain. In highly reducing PKSs (HR-
Figure 1.3: Biosynthetic gene clusters and fungal secondary metabolism core enzymes. PKS-
containing gene cluster and PKS domain architecture (left) and NRPS-containing gene cluster and NRPS
domain architecture (right). Starter ACP transacylase (SAT); ketoacyl synthase (KS); acyltransferase
(AT); acyl-carrier protein (ACP); enoyl reductase (ER); dehydratase (DH); β-ketoacyl reductase (KR);
thiosesterase (TE); peptidyl carrier protein (PCP); condensation (C); adenylation (A); methyltransferase
(MT); epimerization (E); 4’-phosphopantetheine transferase (PPT). Figure adapted from REF
12
, Nature
Reviews.
- 5 -

PKSs), additional reductive domains including β-ketoreductase (KR), enoylreductase (ER), and
dehydratase (DH) domains, can tailor the growing polyketide by catalyzing reduction reactions
(Figure 1.3). The termination TE domain facilitates the release of the product from the last
module’s ACP domain.
In an NRPS, three domains are required in each elongation module: an adenylation (A)
domain, a peptidyl carrier protein (PCP) domain, and a condensation (C) domain. The enzyme is
flanked by a starter PCP domain and either a TE domain or a condensation-like (C T) domain
(Figure 1.3). Additionally, in NRPS gene clusters, a 4’-PP transferase (PPT) domain is encoded by
a gene within the cluster that catalyzes the serine attachment of the 4’-PP group to the PCP
domain (Figure 1.3). This allows the PCP domain to form a thioester bond with the growing
peptide chain. The first amino acid is activated with ATP by a starter A domain which then
transfers the amino acid to the starter PCP domain. A second amino acid is activated by the A
domain of the first elongation module and then transferred to the PCP domain of the same
module. The C domain of the elongation module then catalyzes the amide bond formation
between the first amino acid on the starter PCP domain to the amino acid of the PCP domain of
the elongation module. This cycle repeats until the final module in the NRPS where the peptide
chain is released from the enzyme. While some NRPSs contain a TE domain that catalyzes the
cyclization and release of the peptide, recent genome sequencing efforts have established that a
majority of NRPSs (60-90%) found in filamentous fungi terminate with a C T domain which often
performs a macrocyclization reaction. Furthermore, additional domains are often present in
NRPS modules such as methyltransferase (MT) domains and epimerization (E) domains which
modify the loaded amino acid prior to it being transferred to the growing peptide chain (Figure
1.3).
Once the PKS or NRPS products are released from the core enzyme, additional diversity is
incorporated in the SM by tailoring enzymes encoded within the BGC. Tailoring enzymes can
catalyze a vast array of different reactions on a SM. These tailoring enzymes include but are not
limited to: monooxygenases, acetyltransferases, glycosyltransferases, dehydrogenases,
methyltransferases, and cyclases. In many cases, BGCs will include a gene encoding a membrane
- 6 -

transporter which facilitates the export of the SM from the cell. Finally, bioinformatic analysis
suggests that roughly 60% of BGCs contain a regulatory gene. Most-often this is a gene that
encodes a cluster-specific transcription factor. When this transcription factor is expressed, it
activates the expression of all subsequent genes within the cluster.
1.3 Fungal genome sequencing and bioinformatic advances
The first fungal genome was sequenced in 1996 of the model yeast species, Saccharomyces
cerevisiae.
16
This effort involved over 600 scientists across the globe. Since then, we have
witnessed exponential reductions in DNA sequencing costs as we have improved genotyping
methods and developed whole genome sequencing strategies. More recently, larger sequencing
initiatives have been implemented; the 300 Aspergillus genomes project will help to improve the
knowledge of the genus
17
, and the “1000 Fungal Genomes Project” introduced in 2014 by the
Joint Genome Institute of the Department of Energy plans to sequence more than 1000 fungal
genomes across at least 500 families of fungi.
18
Today, thousands of fungal genomes are publicly
available and these data have helped to document the biodiversity and genetic diversity that
exists within the fungal kingdom.
Since the penicillin BGC was discovered nearly 30 years ago, what was considered a rare event
– the contiguous arrangement of genes necessary to produce a single metabolite – is now known
to be commonplace in filamentous fungal genomes. With the increasing number of available
genome sequences, rapid progress has been made in recognizing the putative genes dedicated
to SM production. There are now algorithms that can predict SMBGCs based on the identification
of the conserved domains present in PKSs, NRPSs, and TCs. Together with the predicted function
of neighboring genes, the entire region of a BGC involved in the formation of a SM can be
established. Some of these bioinformatic algorithms include PRISM
19
, SMURF
20
, and antiSMASH
21

among others (Table 1.1). Using these recent bioinformatic tools, many different fungal genomes
have been annotated. Analysis of this data has shed light on the fact that a majority of the BGCs
identified have not been linked to the production of a SM. These gene clusters are referred to as
silent, cryptic or orphan. In fact, roughly 80% of SMBGC products that are currently unknown. In
- 7 -

Table 1.1: Tools and techniques for mining the fungal secondary metabolome

Genetic and bioinformatic tool Feature Refs
Endogenous expression systems
Targeted promoter exchange Synthetic promoter
22

Transcription factor OE Synthetic promoter
23–25

Epigenetic remodeling Chromatin in repressed state
26–37

Global regulator OE Synthetic promoter
38,39

Expression methods for heterologous hosts
Yeast stitching Synthetic BGC, universal host
40

FAC Scalable expression in Aspergillus
41

CoIN Co-induction of sterigmatocystin promoters
42

HEx Scalable expression in Saccharomyces
43

BGC mining algorithms
SMURF
Synthases (NRPS, PKS, DMATS and NRPS-PKS) and
coordinates of genes
20

AntiSMASH Synthases and substrate predictors
21

PRISM NRPS, PKS, and NRPS-PKS dereplication
19

SMIPS and CASSIS DNA regulatory site
44

MIDDAS Gene annotation, proteins and transcriptome data
45

FunGeneClusterS NRPS, PKS, DMATS and co-expression data
46

SeMPI Modular PKS
47

DEREPLICATOR+ Dereplication strategies
48

Databases with fungal and bacterial BGCs
ClusterMine360 297 BGCs
49

IMG-ABC 2,489 BGCs
50

MIBiG 1,393 BGCs
51

Substrate predictors
AntiSMASH Incorporates NRPS predictor
21

NP.searcher Bacteria, output chemical structure
52

Pep2Path MassSpec guided peptidic natural products
53

PRISM NRPS, PKS and NRPS-PKS dereplication
19

GRAPE Works with PRISM, retrobiosynthesis PKs and NRPs
54

GARLIC
Compares PRISM and GRAPE outputs for likelihood
of backbone prediction
54

SeMPI Modular PKS
47

NRPS predictor A domain specificity
55

- 8 -

A. fumigates, SMs from only 9 of the 36 BCGs have been identified, and in A. niger, only products
from 6 out of the 89 BGCs have been discovered. Considering the valuable bioactivities of SMs
and the reality that only a small fraction of SMs have been discovered from the massive amount
of BGCs that exist, the interest in exploiting the fungal secondary metabolome as a method for
drug discovery has drastically escalated in the past 10 years.
In recent years, there have been extensive efforts to discover the metabolites produced by
these cryptic clusters, which we will discuss later in section 1.5. One major pitfall, however, is the
rediscovery of SMs. The same gene cluster can exist in multiple different species, and oftentimes
a SM that one discovers in a certain species has already been isolated in a different one. With the
major goal being the discovery of new bioactive molecules, the isolation of known SMs can be a
waste of time and resources. In attempts to avoid rediscovery, additional bioinformatic programs
have been developed with dereplication strategies such as DEREPLICATOR+
48
, or substrate
predictors such as Pep2Path
53
and GRAPE/GARLIC
54
(Table 1.1).
1.4 Regulation of secondary metabolism
Before diving into the approaches used to
activate silent BGCs for SM expression, it is useful
to understand how fungi regulate SM production.
A fungus in its natural habitat has adapted to
sense and respond to environmental conditions
like light and radiation exposure, temperature,
nutrient availability, pH stress, and competition,
through the production (and sometimes
repression) of SMs (Figures 1.4 and 1.5). An
external stimulus results in SM expression
through various signal transduction cascades
(Figure 1.5). Regulatory proteins respond to
these environmental stimuli, by modulating the expression of the genes within one or multiple
Figure 1.4: Environmental stimuli that can
contribute to the production of SMs in fungi.
- 9 -

SMBGCs (Figure 1.5).
Important discoveries in the
field of fungal SM regulation
have revealed a more
comprehensive view of
biosynthetic pathway
regulation that is complex and
involves several
interconnected regulatory
networks. Two broad
mechanisms fungi use to manipulate SM expression is through transcriptional regulation and
chromatin-mediated regulation.
More than half of fungal SM gene clusters contain a gene encoding a transcription factor, and
these are known as cluster-specific regulators.
52,56,57
The BGC for gliotoxin contains 13 genes.
58–
60
One of these genes, gliZ, when expressed, produces the transcription factor, GliZ, which
regulates the expression of other genes within the cluster.
61
An experiment found that when gliZ
was deleted, the production of gliotoxin was lost, and when gliZ was overexpressed, gliotoxin
production levels significantly increased.
61
A cluster-specific transcription factor can activate the
expression of all the genes within the cluster. For example, AfoA regulates all of the genes within
the asperfuranone BGC in A. nidualans. When the promoter of afoA is replaced with an inducible
promoter, the result is the upregulation of afoB- afoG, and the subsequent production of
asperfuranone.
57
In other cases, a cluster-specific transcription factor can upregulate most of the
genes in the BGC necessary to make the metabolite, but not all the genes. This is observed in the
gliotoxin BGC. When GliZ is expressed, it facilitates the transcription of all the gli genes except
gliT, which encodes a gliotoxin oxidase to protect the fungus from gliotoxin toxicity. In a gliZ
deletion strain, glitoxin production is lost, but gliT will still be expressed in the presence gliotoxin
when added exogenously to the culture. Figure 1.6 describes the activation of a BGC with a
cluster-specific transcription factor.
62

Figure 1.5: Pathway-specific transcriptional regulation of a BGC.
Roughly 60% of SM biosynthesis clusters contain a gene encoding
a transcription factor that is responsible for the activation all the
genes in the cluster necessary to produce the SM. Figure adapted
from REF
12
, Nature Reviews.
- 10 -

Another type of regulation observed in fungi is achieved by globally acting transcriptional
regulators. These transcription factors do not belong to any specific BGC, and they often regulate
multiple genes—some of these genes belong to multiple gene clusters while others are not
involved in SM production. Several environmental cues are known to induce SM biosynthesis,
and some of these stimuli (i.e. carbon and nitrogen sources, and pH) are associated with specific
global transcription factors (Figure 1.5). The global carbon regulator, CreA
63
(homologue of Cre1),
has been shown to mediate carbon catabolite repression (CCR) in fungi, a process by which the
fungus selects the most energetically favorable carbon source in an environment. CCR prevents
to fungus from using poorly metabolized carbon sources. Fungi generally grow better with
glucose, and thus when glucose is available, CreA will repress the production of enzymes involved
in the breakdown of alternative carbon sources. In addition, CreA may also be involved in
secondary metabolism since changes in SM production levels are affected by different levels and
Figure 1.6: Regulation of secondary metabolism in various fungi in response to environmental stimuli
through global regulatory proteins. Loss of aflR expression A (LaeA); Spt-Ada-Gcn5-acetyltransferase-
ADA (SAGA-ADA); master cluster regulator A (McrA); restorer of secondary metabolism A (RsmA);
cephalosporin C regulator 1 (CpcR1); CCAAT-binding complex (CBC). Figure adapted from REF
12
, Nature
Reviews.
- 11 -

types of carbon sources.
64,65
In Acremonium chrysogenum, production levels of the antibiotic,
cephalosporin are reduced at high glucose concentrations, thought to be mediated in part by the
repression of creA. In general, suppressing the fungus of a preferred type or amount of a carbon
source, or of other types of nutrients can lead to an increase in SM production. Suboptimal
growth conditions resulting in SM activation may reflect a fungus’s natural environmental growth
conditions. This could explain why a majority of SMBGCs are silent in laboratory conditions where
optimal growth conditions are supplied.
While many SM transcriptional regulators function by binding to specific sequences in the
DNA, pleotropic regulators are not DNA-binding proteins but, instead modify the chromosomal
architecture. Most of a chromosome is histone proteins that function to wrap the DNA and highly
condense it into chromatin within the nucleus. In a nucleosome, DNA wraps around 8 histone
proteins (histone octamer) that function like a spool. Histone proteins are susceptible to a variety
of modifications including :methylation, acetylation, phosphorylation, and ubiquitylation. Some
of these histone modifications have been associated with SMBGC regulation.
27,37,66,67
The type of
histone modification can promote either a loosely-packed (euchromatic) or a tightly-packed
(heterochromatic) chromatin architecture.
68
Recent discoveries suggest that SMBGCs are
silenced when DNA is tightly-packed as heterochromatin, and activated when DNA is loosely-
packed as euchromatin. The formation of heterochromatin is facilitated by histone
methylation
69,70
, while histone acetylation has been found to drive the formation of
euchromatin.
71,72

The global regulator of SM production, LaeA (Figure 1.5), is predicted to have
methyltransferase activity due to its sequence similarity to histone and arginine
methyltransferases.
66,73
In A. nidulans, the deletion of laeA resulted in the downregulation of the
sterigmatocystin and penicillin BGCs among other SM gene clusters.
73,74
In an A. fumigatus laeA
mutant, transcriptional profiles revealed that out of 22 SM gene clusters, the genes from 13 were
substantially downregulated compared to a control strain.
75
It is suggested that LaeA initiates a
process that converts heterochromatin into euchromatin by counteracting the establishment of
heterochromatic marks (methylation or deacetylation).
32
In contrast to DNA methylation, DNA
- 12 -

acetylation plays an activating role in SM regulation. A study in 2011 demonstrated how
Streptomyces rapamycinicus induced the expression of the silent BGC for orsellinic acid in A.
nidulans. Data suggested that this induction was mediated through the activation of the histone
acetyltransferase, GcnE, which is associated with the histone acetyltransferase SAGA-ADA
complex (Figure 1.5).
67
The SAGA-ADA complex is also responsible for activating the expression
of sterigmatocystin biosynthesis genes.
76

1.5 Approaches to activate silent gene clusters in fungi
With the wealth of sequenced genomes and the availability of inexpensive bioinformatic
tools, we now know that a large majority of fungal SMBGCs have yet to be explored.
77
In recent
years, there have been widespread efforts to activate these silent genes clusters. Two major
strategies include cultivation based approaches (environmental cues, co-cultivation, OSMAC
approach), and molecular approaches (genetic engineering, epigenetic remodeling) to activate
SM production.
78,79

Earlier we mentioned how variations in carbon sources can affect SM production. In fact,
small changes in growth media and conditions can increase SM production levels and activate
previously silent SMBCGs.
80–82
Coined by Zeeck and associates, the OSMAC (one species many
compounds) approach (Figure 1.7) describes the ability of a single strain, when grown in different
conditions, to produce a variety of SMs.
80
The OSMAC approach can involve countless
modifications to culture conditions. Some of these include: culturing the fungi in different types
of media that use a variety of carbon sources, varying the incubation temperature, modifying the
culture aeration, addition or suppression of certain metals or nutrients, and altering the pH
(Figure 1.7). A review covers how changes in carbon sources has had a dramatic effect on the
production of SMs in wide range of fungi and other microorganisms.
83
A. ochraceus was originally
known to only produce the SM aspinonene; however, Zeeck and associates were able to isolate
15 additional SM from this species when grown in different culture conditions (i.e. variations in
temperature, salinity, aeration, and flask shape).
80

- 13 -

Considering that fungi produce SMs as a means of chemical warfare against competing
species, it makes sense that simulating physiological conditions in the lab, such as microbial
interactions, could activate silent SMBGCs to produce novel bioactive compounds (Figure 1.7).
The co-cultivation of different species that can communicate or interact with each other has been
shown to be a successful way of enhancing known compound production and discovering new
bioactive SMs.
76,84–88
As a consequence of coculturing the marine fungus, Libertella sp. with a
marine alpha-proteobacterium, the BGC was activated for the production of four diterpenoids,
libertellenones A-D, which is cytotoxic against the HCT-116 human adenocarcinoma cell line.
89

When the coral bacterium Bacillus amyloliquefaciens GA40 was grown in the presence of A.
fumigatus and A. niger, it induced the production of lipopeptide antifungal metabolites in the
fungis.
90
In addition to stress from other species, other sources of environmental stress resulting
from extreme temperatures, radiation exposure, and high or low salinity exposure, can result in
the activation of cryptic SMs (Figure 1.7). A recent study found that the production of aflatoxins
is induced in A. flavus under water stress in non-ionic solutes, while high NaCl levels activate the
production of ochratoxin A in P. norcordium.
91

Figure 1.7: Cultivation-based approaches to activate SMBGCs to produce novel NPs.
- 14 -

While cultivation-based approaches have
been successful in many cases for activating
silent SM gene clusters, the reality is,
determining the external stimuli necessary to
activate a majority of BGCs may never be
achievable. With the recent advancements in
genetic technologies many molecular-based
strategies have been developed to facilitate SM
production. One popular molecular approach
involves replacing the native promoters of all
the genes in a BGC with inducible promoters
(Figure 1.8). In A. nidulans, the introduction of
ethanol in the culture medium induces
expression of the transcriptional activator, alcR,
which then activates expression of alcA, an
alcohol dehydrogenase gene, by binding to the
alcA promoter and facilitating its transcription.
92

Serial promoter replacements with an alcA(p)
for all the genes in the inp BGC resulted in the
production of a proteasome inhibitor,
fellutamide B.
22
In this example, all of the genes in the BGC were activated within the same
fungus, or endogenously. Entire BGCs from one species can be expressed with inducible
promoters in a more suitable heterologous host. For example, a silent gene cluster in A. terreus
was cloned and in a strain of A. nidulans, with each gene under the control of an alcA(p). When
cultured in inducing conditions, the A. nidulans strain heterologously expressed the A. terreus
silent gene cluster, and produced the SM asperfuranone.
93

Taking advantage of cluster-specific transcriptional regulation, a preferred method of
activating entire gene clusters is to replace the native promoter of a cluster-specific transcription
factor with a regulatable promoter (Figure 1.8). This has been successful in many cases.
9,24,57,94

Figure 1.8: Molecular approaches to activate
silent SMBGCs.
- 15 -

The first report of the activation of a silent SMBGC was in 2007 by Bergmann and associates. In
this experiment, they replaced the native promoter of the cluster-specific transcription factor,
adpR, belonging to a PKS-NRPS hybrid gene cluster, with the inducible alcA(p). When cultured in
inducing conditions, the fungus was found to produce two novel metabolites that displayed
moderate cytotoxicity, aspyridones A and B.
9

As we discussed earlier, in addition to cluster-specific transcription factors, there are global
regulators that can affect the expression of multiple SM gene clusters (Figure 1.5). For positive
global regulators such as LaeA, overexpression results in the upregulation of many different SM-
related genes (Figure 1.8). One study overexpressed laeA using the inducible alcA(p) in both A.
terreus, and A. nidulans. Activation of LaeA resulted in the upregulation of genes involved in
monocolin J, penicillin, and lovastatin production. The production of these SMs was correlated
with transcript levels: monocolin J production increased by ~400%, lovastatin production was
enhanced 400-700%, and high levels of penicillin were produced compared to a wild-type strain
presenting with no penicillin activity.
66
In contrast to positive global regulation, there is ample
evidence of negative regulators of secondary metabolism. Experiments have revealed that
inactivation of these negative regulators can elicit the activation of SM gene clusters (Figure
1.8).
95–100
A recent study on the global or master negative regulator, McrA, discovered that
multiple secondary metabolite gene clusters were upregulated in A. nidulans following the
deletion of the mcrA gene.
38
They observed the production of SMs from the prenyl xanthone,
nidulanin A, aspercryptin, cichorine, and F9775A/B pathways when mcrA was deleted that were
not produced in the control strain. When the mcrA homologue was deleted in both A. terreus
and P. canescens, SM production was affected, causing a small number of SMs to be
downregulated, and many more SMs to be upregulated in comparison to the controls.
38

Modifying the chromosomal architecture has also proven to be a successful way to drive SM
production. As we discussed in the previous section, histone acetylation of tightly packed
heterochromatin can facilitate the formation of more loosely-packed euchromatin, providing
transcriptional access to SMBGCs. An experiment in 2012 overexpressed the histone 4
acetyltransferase EsaA in A. nidulans, to see if it would upregulate SM biosynthesis genes.
- 16 -

Overexpression of esaA resulted in the upregulation of EsaA, in addition to the activation of genes
involved in penicillin, sterigmatocystin, and terrequinone production.
33

We have described many approaches scientists use to activate SM production in fungi. In the
work that follows, I present the techniques we have used to activate SM biosynthesis in fungi for
the discovery of bioactive compounds. In chapter 2 we investigated the effects of upregulating a
putative global regulator, LaeA-like methyltransferase G (LlmG), and found that overexpression
of llmG activated multiple SM gene clusters in A. nidulans. In chapter 3 and 4 we describe the
activation of the entire silent SMBGC and solved the biosynthesis of the antibiotic, (+)- asperlin,
in A. nidulans, through the engineering and expression of a highly active hybrid transcription
factor. In chapter 5, efforts to discover antifungal metabolite-producing fungi that could inhibit
Candida albicans are described. Among the positive hits was IMV00968, Scopulariopsis candida,
that produced the antifungal metabolite, hymeglusin. We report our efforts to sequence and
annotate the IMV00968 genome, discover the BGC, and solve the biosynthesis of hymeglusin. In
chapter 6 I summarize our findings, draw general conclusions and discuss avenues for future
directions.
Chapter 2 is incorporated from Grau, M. F., Entwistle, R., Oakley, C. E., C. C. C., Oakley, B. R.
Overexpression of an LaeA-like methyltransferase upregulates secondary metabolite production
in Aspergillus nidulans, which is currently in submission in ACS Chemical Biology.
The author has made the most contributions to this study. Dr. R. Entwistle and C. E. Oakley
engineered the llmG overexpression strains.
Chapter 3 is incorporated from Grau, M. F., Entwistle, R., Chiang, Y.-M., Ahuja, M., Oakley, C.
E., Akashi, T., Wang, C. C. C., Todd, R. B., Oakley, B. R. Hybrid Transcription Factor Engineering
Activates the Silent Secondary Metabolite Gene Cluster for (+)-Asperlin in Aspergillus Nidulans.
ACS Chemical Biology 2018, 13 (11), 3193–3205. DOI: 10.1021/acschembio.8b00679.
The author analyzed the metabolic profiles, helped establish the boundaries of the (+)-asperlin
cluster, prepared figures and contributed to the results and discussion section. The hybrid
transcription factor was designed by Dr. R. B. Todd. Characterization of OTA and metabolic
- 17 -

analysis of the alnR and alnA::alnB overexpression strains was conducted by Dr. Y. M. Chiang.
Strains were engineered by Dr. R. Entwistle. RNAseq was conducted by Dr. T. Akashi. Acetate
utilization studies were conducted by C. E. Oakley. Dr. T. Akashi, Dr. R. B. Todd, and Dr. B. R.
Oakley all contributed to the re-annotation efforts.
Chapter 4 is incorporated from Grau, M. F., Entwistle, R., Chiang, Y.-M., Ahuja, M., Oakley, C.
E., Akashi, T., Wang, C. C. C., Todd, R. B., Oakley, B. R. Hybrid transcription factor expressing
strains help to elucidate the (+)-asperlin biosynthetic pathway, which is currently in preparation
for submission to Chemical Science.
The author has made the most contributions to this study. Dr. R. Entwistle and C. E. Oakley
engineered the hybrid transcription factor expressing strains. Dr. Y. M. Chiang assisted in NMR
structural characterization of the (+)-asperlin intermediates.
Chapter 5 is incorporated from Grau, M. F., Yuan, B., Chen, S. A., Stajich J.E., Torok, T., Hsueh,
Y. P., Wang, C. C. C. Discovery of the biosynthetic pathway for the antifungal hymeglusin in
Scopulariopsis candida, which is currently in preparation for submission to Organic Letters.
The author has made the most contributions to this study. B. Yuan assisted in plasmid
construction. Dr. Y. P. Hsueh and S. Chen performed the whole-genome sequencing on
IMV00968. Genome annotation and analysis was conducted by J. E. Stajich. Strains were provided
by Dr. T. Torok.

- 18 -

Chapter 2 is incorporated from Grau, M. F., Entwistle, R., Oakley, C. E., C. C. C., Oakley, B. R.
Overexpression of an LaeA-like methyltransferase upregulates secondary metabolite production in
Aspergillus nidulans, which is currently in submission in ACS Chemical Biology.
The author has made the most contributions to this study. Dr. R. Entwistle and C. E. Oakley engineered
the llmG overexpression strains.

Chapter 2
Overexpression of an LaeA-like
methyltransferase upregulates
secondary metabolite production in
Aspergillus nidulans

2.1 Abstract
Fungal secondary metabolites (SMs) include medically valuable compounds as well as
compounds that are toxic, carcinogenic and/or contributors to fungal pathogenesis. It is
consequently important to understand the regulation of fungal secondary metabolism. McrA is a
recently discovered transcription factor that negatively regulates fungal secondary metabolism.
Deletion of mcrA (mcrAΔ), the gene encoding McrA, results in upregulation of many SMs and
alters the expression of more than 1000 genes. One gene strongly upregulated by the deletion
of mcrA is llmG, a putative methyl transferase related to LaeA, a major regulator of secondary
metabolism. We have artificially upregulated llmG by replacing its promoter with strong
constitutive promoters in strains carrying either wild-type mcrA or mcrAΔ. Upregulation of llmG,
on various media, resulted in increased production of the important toxin sterigmatocystin and
- 19 -

compounds from at least six major SM pathways. llmG is, thus, a master SM regulator. mcrAΔ
generally resulted in greater upregulation of SMs than upregulation of llmG, indicating that the
full effects of mcrA on secondary metabolism involve genes in addition to llmG. However, the
combination of mcrAΔ and upregulation of llmG generally resulted in greater compound
production than mcrAΔ alone (in one case more than 460 times greater than the control). This
result indicates that deletion of mcrA and/or upregulation of llmG can likely be combined with
other strategies for eliciting SM production to greater levels than can be obtained with any single
strategy.
2.2 Introduction
Fungal secondary metabolites (SMs) are compounds that are not essential for viability, but
they provide a selective advantage to the producing fungi, often by inhibiting biologically
important activities in their competitors. These inhibitory activities are, in some cases, medically
useful, making fungal SMs a rich source of medically valuable compounds, and they provide
structural inspiration that has allowed the production of synthetic or semi-synthetic compounds
of great medical value
74,98,101–103
. On the other hand, many fungal SMs are extremely toxic and/or
important to fungal pathogenesis against humans, animals and plants
98,104–109
. The sequencing of
fungal genomes, coupled with extensive studies of SM production in cultured fungi, has revealed
that fungal genomes contain many clusters of genes that encode enzymes of fungal SM
biosynthetic pathways. The expression of the genes of these clusters is usually coordinately
regulated. The vast majority of fungal SM biosynthetic gene clusters (SMBGCs) are not expressed
under normal laboratory growth conditions and in order to exploit the greater fungal secondary
metabolome (all of the SMs produced by all 1,000,000+ species of fungi), procedures need to be
developed to activate expression of these silent, cryptic SMBGCs. While a great deal of progress
has been made in this area
12,93,110–114
, much remains to be learned. In addition, understanding
the regulation of fungal secondary metabolite production is important in understanding and
combatting fungal pathogenesis.
McrA is a transcription factor that is a conserved master negative regulator of secondary
metabolite production
115
. Deletion of mcrA in Aspergillus nidulans, the organism in which it was
- 20 -

discovered, or its homologs in other fungi results in upregulation of many SMs
115
. At the level of
transcription, deletion of mcrA significantly alters the expression of 1352 genes, upregulating 623
genes (including many genes of SMBGS) at least 5X and downregulating 99 genes more than 5X.
The fact that mcrA regulates so many genes raises the question of how it exerts its effects on
secondary metabolism. The answer is likely to be complex. It may affect expression of some SM
genes directly and affect the expression of others by regulating their regulators.
With respect to the second possibility, we were intrigued by the fact that deletion of mcrA
increased expression of llmG (AN5874 using the AspGD/FungiDB gene designation
(http://www.aspgd.org/ and https://fungidb.org/fungidb/ respectively) 12.21 X. llmG has been
identified as one of several genes encoding LaeA-like putative methyl transferases
116
. LaeA is a
master positive regulator of secondary metabolism
117
as part of a complex with VeA and VelB
116
.
llmG was transcribed at low levels and deletion of llmG had little impact on production of the
major secondary metabolite sterigmatocystin
116
. These results left open the possibility, however,
that LlmG is a positive regulator of secondary metabolism and the conditions used in the previous
study were not conducive to llmG transcription. We have consequently artificially upregulated
LlmG by replacing its promoter with the strong constitutive gpdA promoter
118
, as well as a strong
constitutive hybrid promoter based on the nmtA gene (AN8009). We find that upregulation of
LlmG results in increased production of secondary metabolites from the sterigmatocystin,
terrequinone A, nidulanin A, cichorine, and emodin/monodictyphenone/prenyl xanthone
pathways under the conditions we employed. This result indicates that LlmG is a master positive
regulator of SMBGCs in A. nidulans. The levels of production, however, were higher in a wild-type
llmG strain carrying an mcrA deletion. Since deletion of mcrA results in upregulation of llmG, the
effects of McrA on secondary metabolite production are likely mediated, in part, through
regulation of llmG, but the full effects of mcrA on secondary metabolite production involve
additional genes. Finally, combining overexpression of llmG and deletion of mcrA resulted in even
higher levels of SM production. This suggests that the strategy of combining the mcrA deletion
with other strategies for eliciting SM production may be more effective than the individual
strategies alone.
- 21 -

2.3 Results and Discussion
2.3.1 LlmG is a positive regulator of secondary metabolite production
To study the effects of llmG overexpression on SM production, we used a gene targeting
technique (Figure 2.1) to replace the promoter of llmG (at its chromosomal locus) with two
different strong constitutive promoters, gpdA(p)
118
and a hybrid promoter, that we designate
hnmtA(p), created by deleting the riboswitch of the nmtA promoter (AN8009) and adding a short
sequence from the gpdA promoter immediately upstream of the start codon (C. Jenkinson, T.
Akashi and B. Oakley, in preparation). We engineered two sets of llmG overexpression strains
(Table 2.1) with the first set using LO1362 (=TN02A7
119
) as the parental strain, and the second
set using an mcrA (AN8694) deletion strain, LO8158
115
, as the parental strain. For purposes of
media consistency, LO1362 and LO8158 were transformed with the AtpyrG gene replacing the
mutant pyrG89 gene and generating the pyrimidine prototrophic control strains LO11174 and
LO11177, respectively.
Figure 2.1: Replacement of the native llmG promoter with a strong constitutive promoter. A. Four
fragments are separately amplified by PCR (primers are given in Table 2.6). The four fragments
consisted of a 1080 bp fragment amplified from upstream of the llmG (AN5874) coding sequence (nt
minus 1510- to nt minus 430)., a 1491 bp fragment containing the Aspergillus terreus pyrG gene
(AtpyrG), a fragment containing the constitutive promoter (a 1231 bp fragment in the case of the gpdA
promoter and a 502 bp fragment in the case of the hybrid nmtA promoter) and a 1141 bp fragment
extending from the start codon of llmG into the llmG coding sequence. B. The four fragments were
fused together by fusion PCR using nested primers creating a transforming fragment. B and C. The
fusion PCR fragment is used to transform the A. nidulans host strain with AtpyrG as the selectable
marker. Homologous recombination results in llmG transcription being driven by the constitutive
promoter.

- 22 -

Table 2.1: Strains used in this study

We examined the effects of llmG overexpression, deletion of mcrA, and the combination of
llmG overexpression and mcrA deletion on SM production in solid GMM [GMM(s)], liquid GMM
[GMM(l)], YAG and YG. SMs were extracted from agar plates or liquid culture media as described
in the experimental section and analyzed by HPLC-diode array detector (DAD)-MS. Many SMs
from A. nidulans have previously been characterized, allowing us to identify many of the
compounds produced in this study by comparing their HPLC retention time, UV-Vis absorbance,
and mass spectra to those of previously identified compounds.
We first analyzed the metabolites produced by the gpdA(p)llmG strain and the hnmtA(p)llmG
strain compared to the control strain, LO11174, cultivated on GMM plates (Figure 2.2A, i and ii).
Similar results were obtained with both the gpdA(p)llmG strain (LO10860) and the hnmtA(p)llmG
strain (LO10864). We will show HPLC traces from the gpdA(p)llmG strains. Numerical values for
SM production for strains carrying each promoter are given in Table 2.2. Ten metabolites were
identified in the LO11174 control strain, including: sterigmatocystin (1), metabolites from the
Strain Genotype Reference
FGSCA442 facB101, riboB2, chaA1, sE15, nirA14 Fungal Genetics
Stock Center
LO1362 pyroA4, riboB2, pyrG89, nkuA::argB [
119
]
LO8158 pyroA4, riboB2, pyrG89, nkuA::argB, mcrA::AfpyroA [
115
]
LO8030 pyroA4, riboB2, pyrG89, nkuA::argB, stc(AN7804-AN7825)Δ,
eas(AN2545-AN2549)Δ, afo(AN1036-AN1029)Δ, mdp(AN10023-
AN10021)Δ, tdi(AN8513-AN8520)Δ, aus(AN8379-AN8384, AN9246-
AN9259)Δ, ors(AN7906-AN7915)Δ, apt(AN6000-AN6002)Δ
[
120
]
LO8112 mcrA::AfpyroA in LO8030 (note: a sister transformant of LO8111) [
115
]
LO11172-LO11174 pyrG89::AtpyrG in LO1362 This work
LO11175-LO11177 pyrG89::AtpyrG in LO8158 This work
LO10859-LO10860 AtpyrG-gpdA(p)llmG in LO1362 This work
LO10863-LO10864 AtpyrG-hnmtA(p)llmG in LO1362 This work
LO10867-LO10868 AtpyrG-hnmtA(p)llmG in LO8158 This work
LO10881-LO10882 AtpyrG-gpdA(p)llmG in LO8158 This work
LO11505-LO11509 AtpyrG-gpdA(p)llmG in LO8112 This work
LO11510-LO11514 pyrG89::AtpyrG in LO8112 This work
- 23 -

austinol pathway
121
; neoaustinone (2), austinol (3), dehydroaustinol (4), and austinolide
(5),terrequinone A (6)
122
, emericellin (7)
123
, and three unknowns (8-10) (Figure 2.2A i). Structures
are shown in Figure 3. In addition to compounds 1-10, ten additional metabolites (11-20) were
Figure 2.2: HPLC paired profile scans of llmG overexpression and mcrA deletion strains compared to
the control strain on A. GMM(s) and B. YAG plates. (i) Control strain (LO11174), (ii) gpdA(p)llmG strain
(LO10860), (iii) mcrA  strain (LO11177), and (iv) mcrA ::gpdA(p)llmG strain (LO10881).

- 24 -

detected in the llmG overexpression strains (Figure 2.2A ii and Table 2.2). Metabolites from the
sterigmatocystin pathway; 3’-hydroxyversiconol (11), versiconol (12), nidurufin (13)
124
, averufin
(14)
124
, and additional unknown sterigmatocystin intermediates (15-17) were upregulated in the
llmG overexpression strains compared to LO11174, along with nidulanin A and its derivatives (18-
20)
111,115
. While sterigmatocystin (1), terrequinone (6) and emericellin (7) were detected in
LO11174, these compounds were upregulated in the llmG overexpression strains along with
compounds (11-20). The same compounds that were upregulated in the llmG overexpression
strains were also upregulated in the mcrAΔ strain (LO11177), the mcrAΔ, gpdA(p)llmG strain
(LO10881) (Figure 2.2A, iii and iv and Table 2.2) and the mcrAΔ, hnmtA(p)llmG strain (LO10868)
(Table 2.2), but to a much greater degree. Furthermore, while the presence of the mcrA deletion
significantly enhanced SM upregulation compared to the overexpression of llmG, strains carrying
both mcrAΔ and llmG overexpression constructs produced even greater amounts of SMs than
the strain carrying mcrAΔ alone (LO11177) (Table 2.2). We generally saw greater levels of
upregulated SMs in strains carrying gpdA(p)llmG (LO10860 and LO10881) than in equivalent
hnmtA(p)llmG strains (LO10864 and LO10868) although the difference was often slight and there
were exceptions (Table 2.2).
2.3.2 LlmG overexpression results in the upregulation of several additional SMs
under different culture conditions
Many have reported that fungi, like other microbes, produce different SMs under different
growth conditions
80
. We were curious as to whether the overexpression of llmG in different
culture media would result in the production of additional SMs. We consequently analyzed the
metabolites produced by the llmG overexpression strains cultivated on YAG plates in comparison
with LO11174 (Figure 2.2B, i and ii, Table 2.3). Three metabolites were identified in the LO11174
control strain, including, 2,ω-dihydroxyemodin (21)
123
, 3-methylorsellinic acid (22), and an
unknown compound (23). Compounds 21-23 were upregulated in the llmG overexpression
strains along with twelve additional metabolites (1, 14, 18-19 and 24-31), including
sterigmatocystin (1) and its intermediates; averufin (14)
124
, versicolorin B(24)
124
, averantin
(25)
125
, metabolites from the emodin/mondictyphenone pathway
99
; monodictyphenone (26), ω-
- 25 -

hydroxyemodin (27), 2-hydroxyemodin (28), emodin (29), and chrysophanol (30), nidulanins (18
and 19)
111,115
, 3-methylorsellinic acid (22)
25
, and an unknown (31) (Figure 2B, ii-iv). As was the
case for GMM(s), we observed an even greater increase in production of the same SMs in the
mcrAΔ strain than in the llmG overexpression strains, and, notably, the gpdA(p)llmG, mcrAΔ
strain demonstrated enhanced SM production in comparison with the mcrAΔ strain (Figure 2.2B,
iii and iv, Table 2.3).
Finally, we analyzed the metabolites produced in liquid media by the llmG overexpression,
mcrAΔ, and double mutant strains in comparison with LO11174, GMM(l) and YG (GMM and YAG
without agar) (Figure 2.3A, i-iv, Figure 2.3B, i-iv and Tables 2.4 and 2.5). Similar to GMM(s), in the
llmG overexpression and mcrAΔ strains, we observed upregulation of SMs from the
sterigmatocystin, terrequinone A, and nidulanin A pathways in GMM(l), as well as metabolites
from the cichorine pathway (Figure 2.3A, i-iv). Additional sterigmatocystin intermediates were
detected in GMM(l) including compounds 35-38, along with an additional nidulanin A derivative
(32)
111,115
, and cichorine pathway metabolites; O-methyl-3-methylorsellinaldehyde dimer (39)
115

and cichorine (40)
126
(Figure 2.3A i-iv and Table 2.4). Metabolites from the same pathways were
upregulated in the llmG overexpression and mcrAΔ strains when cultured in YG compared to YAG,
including the monodictyphenone/emodin, nidulanin A and cichorine pathways, while no
sterigmatocystin-related compounds were detected under this condition (Figure 2.3B i-iv and
Table 2.5). In the gpdA(p)llmG and hnmtA(p)llmG strains, we detected the emodin intermediate,
atrochrysone (44)
93
, a nidulanin A derivative (45)
111,115
, and a cichorine intermediate, nidulol
(46)
126
(Figure 2.3B i and ii and Table 2.5). In the mcrAΔ, the mcrAΔ, gpdA(p)llmG and
hnmtA(p)llmG strains we observed the production of emodin derivatives [(cis/trans)-emodin-
physicon bianthrone (47 and 48)
127
, and unknowns (49-53) (Figure 2.3B iii and iv and Table 2.5)].
Relative to the control strain, LO11174, we observed as much as 98 times greater production of
some of these unknowns in the gpdA(p)llmG strain, up to 435 times greater production in the
mcrA  strain and more than 460 times greater production in the gpdA(p)llmG, mcrA  strain
(Table 2.5). We should note that metabolites from the F-9775A/B pathway
25,99
[orsellinic acid
(41), F-9775A (42), and F-9775B (43)] were detected in the control strain, LO11174, the llmG
overexpression, and mcrAΔ, llmG overexpression strains at relatively consistent levels (Figure
- 26 -

2.3B ii-iv and Table 2.5). Also, although these metabolites are difficult to detect with the DAD,
further analysis of the MS data indicated the expression of multiple emericellamides in varying
media conditions, whereas the overexpression of llmG or the deletion of mcrA did not affect the
Figure 2.3: HPLC paired profile scans of llmG overexpression and mcrA deletion strains compared to
the control strain in liquid media. A. GMM(l) and B. YG. (i) llmG
+
, mcrA
+
(LO11174), (ii) gpdA(p)llmG,
mcrA
+
(LO10860), (iii) llmG
+
, mcrAΔ (LO11177), and (iv) gpdA(p)llmG, mcrAΔ (LO10881).

- 27 -

level of production of these compounds (Tables 2.2, 2.4 and 2.5). The results of the SM
production analysis with both solid and liquid media indicate that LlmG is a positive regulator of
Figure 2.4: Chemical structures of compounds that were upregulated in the gpdA(p)llmG (LO10860,
LO10864), mcrA  (LO11177) and gpdA(p)llmG::mcrA  (LO10868, LO10881) strains. Sterigmatocystin
(1), terrequinone A (6), emericellin (7), 3’-hydroxyversiconol (11), versiconol (12), nidurufin (13),
averufin (14), nidulanin A (18), 2,ω-dihydroxyemodin (21), 3-methylorsellinic acid (22), cichorine
intermediate (23), versicolorin B (24), averantin (25), monodictyphenone (26), ω-hydroxyemodin (27),
2-hydroxyemodin (28), emodin (29), chrysophanol (30), O-methyl-3-methylorsellinaldehyde dimer
(39), cichorine (40), atrochrysone (44), nidulol (46), trans-emodin-physicon bianthrone (47), cis-
emodin-physicon-bianthrone (48).

- 28 -

SM production that is responsible for upregulating metabolites from the sterigmatocystin,
terrequinone A, nidulanin A, monodictyphenone/emodin and prenyl xanthone pathways. The
austinol, F-9775A/B, and emericellamide pathways are not affected by either the overexpression
of llmG or the deletion of mcrAΔ. While overexpression of llmG increases production of SMs from
the pathways listed above, the deletion of mcrA results in even greater levels of SM upregulation.
This observation suggests that the increased expression of llmG resulting from the deletion of
mcrA is only partially responsible for the full amount of SM production observed by an mcrAΔ
strain, and that other genes must play a part in fully upregulating SM expression. Importantly,
for many compounds, strong constitutive expression of llmG in combination with deletion of
mcrA resulted in higher production (and in some cases much higher production) than the deletion
of mcrA or constitutive overexpression of llmG alone. This was particularly true in liquid media
(Tables 2.4 and 2.5).
2.3.3 Identification of unknown (23) as an intermediate of cichorine biosynthesis
Earlier work developing methods to delete entire A. nidulans SM clusters facilitated the
engineering of a genetic dereplication strain LO8030
93,120
. Most of the SM gene clusters often
expressed in A. nidulans are deleted in LO8030, and the SMs produced by these deleted clusters
include: sterigmatocystin, the emericellamides, asperfuranone, monodictyphenone,
terrequinone, F9775A and B, asperthecin, austinol and dehydroaustinol
120
. These deletions
provide a clean SM background making it easier to detect SMs from other clusters. We
questioned whether unknowns (23 and 31), which are produced in significant amounts in strains
carrying an mcrA deletion, were potentially new compounds as their identities could not be
determined based on UV-absorbance, MS, and retention time data alone. In an earlier study
115

AN8694 was deleted in strain LO8030 to create strain LO8112. In this investigation, using LO8112
as a parental strain, we replaced the llmG promoter with the gpdA promoter creating strain
LO11505. Culturing LO11505 on YAG plates, we observed enhanced production of unknown (23)
compared to strain LO10881 (gpdA(p)llmG, mcrA  with SM clusters intact), while the production
of unknown (31) was completely abolished (Figure 2.5A, i and ii). This indicated that unknown
(31) must belong to one of the pathways that were deleted when engineering strain LO8030. To
- 29 -

characterize unknown (23), we isolated the compound from a large-scale culture of LO11505 (see
Methods section). The structure of 23, elucidated from NMR spectroscopic data (Figures 2.7-2.9
and Table 2.7), is shown in Figure 2.5B. While unknown (23) is a compound new to science, based
on its chemical structure it is likely to be an intermediate of the cichorine biosynthesis
pathway
126
. We propose a biosynthetic pathway for cichorine that includes unknown (23) in
Figure 2.10.

Figure 2.5: Enhanced production of compound 23 observed in a multicluster deletion, mcrA ,
gpdA(p)llmG strain. A. (i) HPLC profile of a mcrA , gpdA(p)llmG strain (LO10881) on YAG, indicating
the production of unknown 23. (ii) HPLC profile, on YAG, of LO11505 in which mcrA was deleted and
llmG was upregulated in strain LO8030, that was engineered to have multiple SM gene clusters
deleted. Enhanced production of compound 23 was observed in LO11505 compared to LO10881. B.
The structure of compound 23. Based on structural similarities observed between compound 23 and
cichorine (41), we predict that compound 23 is an intermediate of the cichorine biosynthetic pathway.

- 30 -

2.4 Conclusion
We constructed llmG overexpression strains and compared their secondary metabolite profiles
to a control strain lacking llmG overexpression in varying culture conditions. We also compared
SM production levels of these strains to mcrAΔ and combined mcrA  and llmG overexpression
strains. We observed that llmG overexpression upregulates the production of metabolites from
the sterigmatocystin, terrequinone A, nidulanin A, cichorine, monodictyphenone/emodin and
prenyl xanthone pathways, while not affecting SM production from the austinol, F-9775A/B,
and emericellamide pathways. The upregulation of multiple SMs from several SMBGCs
indicates that llmG is a master SM regulatory gene. One of the upregulated metabolites,
unknown (23), was characterized and determined to be a compound new to science belonging
to the cichorine biosynthetic pathway. The deletion of mcrA had a greater impact on SM
upregulation than llmG overexpression alone. This result highlights how multiple regulatory
genes in addition to llmG are likely to be involved in generating the production of SMs at levels
that are observed when mcrA is deleted. The combination of overexpression of llmG and
deletion of mcrA, however, resulted in even greater metabolite production than mcrAΔ alone.
This result raises the exciting possibility that deletion of mcrA, and, perhaps, overexpression of
llmG, can be used in combination with other strategies to elicit greater SM production than any
of these strategies can produce alone and, thereby, facilitate the discovery and production of
valuable new SMs.
2.5 Methods
2.5.1 Molecular genetic procedures
Transformation procedures and production of linear molecules for transformations by fusion
PCR were as previously described
119,128,129
. Strains LO1362, LO8112 and LO8158, which carry
pyrG89, were transformed to pyrG
+
to produce strains LO11172-11174, LO11510-LO11514, and
LO11175-LO11177 respectively. The transforming fragment was created by fusion PCR and
consisted of a 1006 bp fragment upstream of AnpyrG (AN6157), a 1491 bp fragment carrying the
Aspergillus terreus pyrG gene (ATEG_09675) and a 978 bp fragment 3’ to AnpyrG. The upstream
- 31 -

fragment was amplified with primers LizP6853 and LizP6855, the AtpyrG fragment was amplified
from plasmid pLO103
130
with primers LizP2018 and LizP2019 and the 3’ fragment was amplified
with primers LizP6856 and LizP6858. Fusion PCR was carried out with nested primers LizP6854
and LizP6857. pyrG+ transformants were selected on YAG medium without uridine and uracil.
Transformants were verified by three diagnostic PCR’s using the following primer combinations:
LizP6852 and LizP6859 (both are outside the transforming fragment), LizP6852 and 4139
(LizP4139 is a reverse primer inside the AtpyrG gene), and LizP6398 and 6858 (LizP6398 is a
forward primer inside the AtpyrG gene). Primers are listed in Table 2.6.
The gpdA promoter was amplified from genomic DNA using forward primer LizP4800 (which
has a ‘tail’ to facilitate fusion PCR) and reverse primer LizP2273, to produce a 1231 bp fragment
that is immediately 5’ to the gpdA start codon. The fragment that was used to replace the
promoter of llmG (AN5874) with the gpdA promoter was created by fusion PCR. It consisted of
1) a 1080 bp fragment upstream of llmG amplified with primers LizP7021 and LizP7023, 2) the A.
terreus pyrG fragment described above, 3) the gpdA promoter fragment and 4) a 1141 bp
fragment starting with the start codon from llmG (amplified with primers LizP7025 and LizP7027).
Nested primers LizP7022 and LizP7026 were used for the fusion PCR reaction, creating a 4.7 kb
transforming fragment. This fragment was used to transform host LO1362 (creating LO10860),
host LO8158 (creating LO10881) and host LO8112 (creating LO11505). Transformants were
verified using the following primer pairs: LizP7020 and LizP7028, which are upstream and
downstream of llmG and outside of the transforming fragment, LizP7020 and LizP4139 or
LizP6399 (LizP4139 and LizP6399 are reverse primers within the AtpyrG gene) and LizP6398
(forward primer within AtpyrG) and LizP7028. The replacement of the llmG promoter with a
hybrid nmtA promoter was carried out using the same strategy.
2.5.2 Culturing and HPLC-DAD-MS analysis
For agar plate cultures, A. nidulans strains were incubated at 37°C on GMM(s) (10 g L
-1
D-
glucose, 6 g L
-1
NaNO 3, 0.52 g L
-1
KCl, 0.52 g L
-1
MgSO 4 7H 2O, 1.52 g L
-1
KH 2PO 4, 15 g L
-1
agar, and
1 ml L
-1
Hutner’s trace element solution
131
), or YAG (5 g L
-1
yeast extract, 20 g L
-1
D-glucose, 15 g
L
-1
agar, and 1 ml L
-1
Hutner’s trace element solution
131
) plates supplemented with riboflavin (2.5
- 32 -

mg L
-1
) and/or pyridoxine (0.5 mg L
-1
) when necessary. Plates were inoculated with 1.0  10
7

spores per 10-cm plate. After 3 days, three plugs (7-mm diameter) were cut out and transferred
to a 7 ml screw-cap vial. The material was extracted with 3 ml of methanol followed by 3 ml of
1:1 dichloromethane-methanol with 1 hr of sonication. The extract was transferred to a clean vial
and the solvent was evaporated by TurboVap LV (Caliper LifeSciences). The residues were re-
dissolved in 5 ml of EtOAc and 5 ml of water, the EtOAc layer was collected and the solvent was
evaporated by TurboVap LV. The crude extract was re-dissolved in 0.3 ml of DMSO:MeOH (1:4)
and 10μl was injected to LC-DAD-MS analysis as previously described
99
.
For liquid culture, 3  10
7
spores were grown in 30 ml GMM(l) or YG liquid medium (recipes
same as above except no agar was added) in 125 ml Erlenmeyer flasks at 37°C with shaking at
180 rpm. After 5 days, culture media and hyphae were collected by filtration. Culture media were
extracted with an equal volume of EtOAc. In order to extract the most acidic phenolic
compounds, the water layer was extracted with an equal volume of EtOAc again after
acidification (pH = 2). Both EtOAc extracts were then evaporated by TurboVap LV. The residues
were re-dissolved in 0.5 ml of DMSO:MeOH (1:4) and analyzed by LC-DAD-MS as described above.
LC-MS spectra were obtained using a ThermoFinnigan LCQ Advantage ion trap mass
spectrometer with a reverse phase C 18 column (Alltech Prevail C 18; particle size, 3 μm; column,
2.1 by 100 mm) at a flow rate of 125 μL min
-1
. The solvent gradient for LC-MS was 5% MeCN–H 2O
(solvent A) and 95% MeCN–H 2O (solvent B), both of which contained 0.05% formic acid, as
follows: 100% solvent A from 0 to 5 min, 0 to 25% solvent B from 5 min to 6 min, 25% to 100%
solvent B from 6 to 35 min, 100% solvent B from 35 to 40 min, 100% to 0% solvent B from 40 to
45 min, and re-equilibration with 100% solvent A from 45 to 50 min. Conditions for MS included
a capillary voltage of 5.0 kV, a sheath gas flow rate at 60 arbitrary units, an auxiliary gas flow rate
at 10 arbitrary units, and the ion transfer capillary temperature at 350 °C.
2.5.3 Compound isolation and purification
LO11505 was cultivated in 25 Petri dishes (150 mm diameter) containing a total of 2 L of YAG
medium supplemented with riboflavin (2.5 mg L
-1
) for 3 days at 37°C. The agar was then chopped
- 33 -

up and sonicated in the same manner as above. The organic material was evaporated and
extracted twice with ethyl acetate. The crude material was subjected to silica gel column
chromatography, using ethyl acetate and hexanes as the eluent. The material was further
separated by preparative HPLC [Phenomenex Luna 5 μm C18 (2), 250 x 21.2] with a flow rate of
5.0 mL min
-1
and measured by a UV detector at 280 nm.
2.5.4 Structural characterization
NMR spectral data were collected on a Varian Mercury Plus 400 spectrometer. High-
resolution electrospray ionization mass spectrum (HRESIMS) was obtained on Thermo Scientific
Q Exactive Hybrid Quadrupole-Orbitrap mass spectrometer with an Eclipse XDB-C 18 column
(Agilent 5 μm 4.6 x 150 mm) at a flow rate of 125 μL min
-1
. Conditions for MS included a spray
voltage of 3.5 kV, sheath gas flow rate 20 au, auxiliary gas flow rate at 5 au, sweep gas flow rate
at 1 au, capillary temperature at 275 °C, s-lens RF level 55, auxiliary gas heat temperature at
325°C, scan range of 100-600 m/z, resolution 140,000, AGC target 3 x 10
6
, and maximum injection
time of 200 ms.
7-methoxy-6-methyl-1,3-dihydroisobenzofuran-1,5-diol (23): white powder; UV  max
MeOH
nm:
233, 281;
1
H NMR (CD 3OD): δ = 2.06 (3H, s), 3.86 (3H, s), 4.94 (2H, dddq), 6.27 (1H, d), 6.43 (1H,
s);
13
C NMR (CD 3OD): δ = 8.9, 60.3, 72.9, 102.6, 108.0, 116.5, 119.5, 141.3, 155.9, 159.4. For UV
and ESIMS spectrum, see Figure 2.6; HRESIMS obtained m/z [M – H] = 195.0654 (calcd 195.0657
for C 10H 11O 4) (See Supporting Information for a detailed structural characterization of compound
23).s

- 34 -

2.6 Supporting Information
Detailed structural characterization of compound 23
Compound 23 was isolated as a white amorphous powder. The molecular formula was found
to be C 10H 12O 4 by its
1
H NMR,
13
C NMR (Figures 2.7 and 2.8) and HRESIMS spectral data,
representing five indices of hydrogen deficiency (IHD).
1
H,
13
C, gHSQC NMR spectra indicated
compound 2 contains one methyl group [δ H 2.06 (3H, s), δ C 8.9], one methoxy group [δ H 3.86 (3H,
s), δ C 60.3], one oxymethylene group [δ H 4.84-4.89 (1H) and 5.02 (1H, br d, J = 12.5 Hz), δ C 72.9],
two tertiary olefinic or hemiacetal moieties [δ H 6.27 (1H, s), δ C 108.0 and δ H 6.43 (1H, s), δ C 102.6]
and five quaternary carbons (δ C 116.5, 119.5, 141.3, 155.9 and 159.4) that exhibit chemical shifts
in the aromatic region. Assuming that six of these carbons belong to an aromatic ring accounts
for four IHD, while the last IHD must be due to the presence of a second ring since no alkene,
aldehyde or ester carbons were detected by NMR. The two most downfield shifted aromatic
carbons (δ C 155.9 and 159.4) are attached to a hydroxyl and the methoxy group accounting for
two of the four oxygens. Because of the downfield shift of the methyl group [δ H 2.06 (3H, s), δ C
8.9] we predicted it to be a substituent of the aromatic ring. With the second ring forming
attachments to two of the aromatic carbons, it leaves one of the tertiary carbons [δ H 6.27 (1H,
s), δ C 108.0 and δ H 6.43 (1H, s), δ C 102.6] to belong to the aromatic ring, and the other to belong
to the second ring. The penta-substituted aromatic ring could be assigned unambiguously by the
long-rang 1H-13C gHMBC correlations (Figure 2.9) The remainder of the two carbons (δ C 72.9 CH 2
and 108.0, CH) on the second ring was attributed to an oxymethylene and a hemiacetal functional
groups. gHSQC and long-range gHMBC correlations (Figure 2.9) allowed the full assignment of
the structure (Table 2.7).
- 35 -

Table 2.2: Fold change values of secondary metabolites produced by llmG overexpression and mcrA
deletion strains compared to the control strain LO11174 (llmG
+
, mcrA
+
) in GMM(s). LO10860 =
gpdA(p)llmG, mcrA
+
; LO10864 = hnmtA(p)llmG, mcrA
+
; LO11177 = llmG
+
, mcrAΔ; LO10868 =
hnmtA(p)llmG, mcrAΔ; LO10881 = gpdA(p)llmG, mcrAΔ.

GMM(s)
Pathway Compound
Fold D from LO11174
LO10860 LO10864 LO11177 LO10868 LO10881
Sterigmatocystin Sterigmatocystin (1)
2.41 2.22 4.00 5.00 5.97
Sterigmatocystin 3'-hydroxyversiconol (11)
2.55 2.26 3.93 4.41 4.19
Sterigmatocystin Versiconol (12)
1.52 1.26 3.65 4.16 4.49
Sterigmatocystin Nidurufin (13)
1.05 0.50 3.59 4.51 5.45
Sterigmatocystin Averufin (14)
3.30 3.65 11.83 14.83 15.03
Sterigmatocystin Sterigmatocystin intermediate (15)
1.85 1.68 5.95 6.87 7.39
Sterigmatocystin Sterigmatocystin intermediate (16)
2.10 1.66 5.26 6.36 8.69
Sterigmatocystin Sterigmatocystin intermediate (17)
1.50 1.40 4.19 4.95 5.28
Austinol Neoaustinone (2)
1.37 1.32 1.06 1.12 1.31
Austinol Austinol (3)
1.26 1.20 1.22 1.29 1.57
Austinol Dehydroaustinol (4)
1.32 1.25 1.37 1.34 1.48
Austinol Austinolide (5)
1.15 1.16 1.21 1.31 1.33
Terrequinone Terrequinone A (6)
1.12 1.16 2.81 3.83 3.70
Prenyl Xanthone Emericellin (7)
4.56 5.58 93.24 111.60 124.21
Unknown Unknown (8)
1.12 0.74 1.38 1.22 1.60
Unknown Unknown (9)
1.88 1.75 1.65 1.70 1.72
Unknown Unknown (10)
1.42 1.34 0.20 0.20 0.35
Nidulanin Nidulanin A (18)
1.40 1.31 3.04 3.61 4.83
Nidulanin Nidulanin A analog (19)
1.50 1.42 3.39 3.75 4.40
Nidulanin Nidulanin A + O (20)
1.74 1.42 3.77 4.57 5.49

- 36 -

Table 2.3: Fold change values of secondary metabolites produced by llmG overexpression and mcrA
deletion strains compared to the control strain LO11174 (llmG
+
, mcrA
+
) in YAG. LO10860 = gpdA(p)llmG,
mcrA
+
; LO10864 = hnmtA(p)llmG, mcrA
+
; LO11177 = llmG
+
, mcrAΔ; LO10868 = hnmtA(p)llmG, mcrAΔ;
LO10881 = gpdA(p)llmG, mcrAΔ.

YAG
Pathway Compound
Fold from LO11174
LO10860 LO10864 LO11177 LO10868 LO10881
Sterigmatocystin Sterigmatocystin (1)
15.11 12.98 39.78 55.63 37.59
Sterigmatocystin Averufin (14)
4.55 3.32 4.62 6.04 6.11
Sterigmatocystin Versicolorin B (24)
24.74 21.33 37.46 45.94 39.51
Sterigmatocystin Averantin (25)
4.42 3.93 6.32 8.31 7.62
Monodictyphenone/Emodin 2,ω-dihydroxyemodin (21)
1.64 1.21 3.66 2.93 2.14
Monodictyphenone/Emodin Monodictyphenone (26)
3.86 3.86 13.34 5.84 5.57
Monodictyphenone/Emodin ω-hydroxyemodin (27)
15.62 11.10 37.39 46.54 39.33
Monodictyphenone/Emodin 2-hydroxyemodin (28)
8.46 8.02 13.98 14.90 13.49
Monodictyphenone/Emodin Emodin (29)
3.87 3.63 6.25 7.35 7.11
Monodictyphenone/Emodin Chrysophanol (30)
3.68 4.43 5.43 6.50 6.75
Nidulanin Nidulanin A (18)
2.02 1.29 7.05 11.50 13.22
Nidulanin Nidulanin A analog (19)
3.08 2.11 11.94 21.75 23.86
Cichorine 3-methylorsellinic acid (22)
1.78 1.31 2.01 2.36 2.96
Cichorine Cichorine intermediate (23)
3.09 2.93 4.28 4.06 3.98
Unknown Unknown (31)
1.66 1.45 5.86 3.06 2.39
- 37 -

Table 2.4: Fold change values of secondary metabolites produced by llmG overexpression and mcrA
deletion strains compared to the control strain LO11174 (llmG
+
, mcrA
+
) in GMM(l). LO10860 =
gpdA(p)llmG, mcrA
+
; LO10864 = hnmtA(p)llmG, mcrA
+
; LO11177 = llmG
+
, mcrAΔ; LO10868 =
hnmtA(p)llmG, mcrAΔ; LO10881 = gpdA(p)llmG, mcrAΔ.

GMM(l)
Pathway Compound
Fold D from LO11174
LO10860 LO10864 LO11177 LO10868 LO10881
Sterigmatocystin Sterigmatocystin (1)
96.32 101.29 100.10 190.12 219.35
Sterigmatocystin Versiconol (12)
1.81 1.45 2.89 6.03 6.02
Sterigmatocystin Nidurufin (13)
6.18 5.75 7.83 11.32 14.47
Sterigmatocystin Sterigmatocystin intermediate (15)
2.92 2.22 4.00 9.01 8.04
Sterigmatocystin Sterigmatocystin intermediate (16)
5.15 2.59 5.56 12.91 8.58
Sterigmatocystin Sterigmatocystin intermediate (35)
1.77 1.60 10.21 18.27 20.50
Sterigmatocystin Sterigmatocystin intermediate (36)
1.81 1.59 2.61 4.41 4.64
Sterigmatocystin Sterigmatocystin intermediate (37)
3.45 2.71 7.59 9.36 12.14
Sterigmatocystin Sterigmatocystin intermediate (38)
1.92 1.49 2.45 2.85 2.54
Terrequinone Terrequinone A (6)
11.98 8.81 26.39 28.75 42.33
Nidulanin Nidulanin A (18)
1.93 1.65 1.38 2.52 1.09
Nidulanin Nidulanin A analog (19)
0.93 1.07 0.90 1.65 1.24
Nidulanin Nidulanin A + O (20)
1.47 2.77 1.03 1.60 0.98
Nidulanin Nidulanin A analog (32)
1.40 1.37 1.34 2.50 1.31
Cichorine Cichorine Intermediate (23)
1.29 1.44 18.02 23.94 28.66
Cichorine Cichorine (40)
2.06 2.19 2.63 5.20 4.00
Cichorine
O-Methyl-3-methylorsellinaldehyde
dimer (39)
3.29 1.64 39.82 28.54 74.91
Unknown Unknown (9)
0.98 1.14 1.00 1.32 1.01
Unknown Unknown (33)
1.39 0.98 1.21 1.55 1.43
Unknown Unknown (34)
0.99 1.21 1.46 1.49 1.79

- 38 -

Table 2.5: Fold change values of secondary metabolites produced by llmG overexpression and mcrA
deletion strains compared to the control strain LO11174 (llmG
+
, mcrA
+
) in YG. LO10860 = gpdA(p)llmG,
mcrA
+
; LO10864 = hnmtA(p)llmG, mcrA
+
; LO11177 = llmG
+
, mcrAΔ; LO10868 = hnmtA(p)llmG, mcrAΔ;
LO10881 = gpdA(p)llmG, mcrAΔ.

YG
Pathway Compound
Fold from LO11174
LO10860 LO10864 LO11177 LO10868 LO10881
Monodictyphenone/Emodin 2,ω-dihydroxyemodin (21) 7.77 5.23 154.44 206.81 208.77
Monodictyphenone/Emodin Monodictyphenone (26) 4.44 3.78 18.17 28.45 32.77
Monodictyphenone/Emodin ω-hydroxyemodin (27) 9.29 10.37 16.78 36.72 62.89
Monodictyphenone/Emodin 2-hydroxyemodin (28) 12.15 20.67 34.68 51.57 58.25
Monodictyphenone/Emodin Emodin (29) 23.21 22.87 36.28 52.36 46.66
Monodictyphenone/Emodin Atrochrysone (44) 2.31 2.67 2.83 5.16 6.80
Monodictyphenone/Emodin
(cis/trans)-emodin-physicon
bianthrone (47)
9.71 7.92 50.87 51.89 58.20
Monodictyphenone/Emodin
(cis/trans)-emodin-physicon
bianthrone (48)
4.99 4.57 66.32 89.14 82.87
Nidulanin Nidulanin A (18) 4.34 2.12 6.26 10.19 8.34
Nidulanin Nidulanin A + O (20) 4.23 2.52 7.22 7.29 8.21
Nidulanin Nidulanin A analog (32) 7.04 4.11 16.45 23.38 33.29
Nidulanin Nidulanin A - prenyl (45) 3.31 2.43 4.32 4.80 5.77
F-9775A/F-9775B Orsellinic acid (41) 1.36 3.07 2.07 1.91 2.68
F-9775A/F-9775B F-9775A (42) 2.16 2.55 1.32 1.26 1.85
F-9775A/F-9775B F-9775B (43) 1.07 1.89 1.45 1.40 1.97
Cichorine 3-methylorsellinic acid (22) 4.16 3.49 5.77 7.58 9.09
Cichorine Cichorine Intermediate (23) 4.64 4.16 9.23 12.36 17.01
Cichorine Nidulol (46) 2.50 3.52 4.66 7.45 8.94
Unknown Unknown (49) 72.17 44.55 281.04 365.93 463.65
Unknown Unknown (50) 3.53 4.46 42.87 52.12 48.40
Unknown Unknown (51) 57.65 43.96 435.18 445.75 456.49
Unknown Unknown (52) 97.78 83.08 328.77 378.11 431.57
Unknown Unknown (53) 8.45 10.81 44.46 42.99 49.28
- 39 -

Figure 2.6: UV-Vis and ESIMS (positive or negative mode) spectra of new and unknown compounds
identified in this study.

- 40 -

- 41 -

- 42 -

Table 2.6: Primers used in this study.

Note: The lower-case letters designate “tails,” i.e. sequences that are not part of the genomic sequences
amplified, but used for fusing fragments together.

LizP2018 caatgctcttcaccctcttcTGGGCGGGTTCTTTTGGTTT
LizP2019 ctgtctgagaggaggcactACTATCAAGTAGTACGAGTTAC
LizP2273 TGTGATGTCTGCTCAAGCGG
LizP4139 ATGTGCGCCCACTCGGAG
LizP4800 gcatcagtgcctcctctcagacagcCACCTTCAGTGGACTCGAG
LizP6398 CAGAAGCAGTACCATGGCG
LizP6399 CGGCAAGGATGAGCAGGC
LizP6852 CGTCAACTTCGGAACACGG
LizP6853 TCCGGATGGACTAACTGC C
LizP6854 CGTCTTCCGAGAACGTCAG
LizP6855 cgaagagggtgaagagcattgATTGGGCTGGATTAAACTGAC
LIzP6856 gcatcagtgcctcctctcagacagCCATATGTTTATTGCAGCCAG
LizP6857 TTATCCGCAGAGCTCTAATTC
LizP6858 AAGACAATGGAGAGGTGACC
LizP6859 CGATGCGATTGTCAAGTGAG
LizP7020 GCTATCCTCAATCTGGCTTG
LizP7021 CCACAAGCTCGTGTCACATC
LizP7022 GTGAACCAAGCACACAGGAG
LizP7023 cgaagagggtgaagagcattgGCTCCATACCTCGAGATCTC
LizP7025 ccgcttgagcagacatcacaATGACGTACGCATCTCTCCAAC
LizP7026 CTCATGAGCTGCGAGCTCC
LizP7027 GGTAGAGGGATCATCTTTGC
LizP7028 CTCTGACTTGTGTTGACGTC

- 43 -

Figure 2.7:
1
H NMR spectrum of 7-methoxy-1-methyl-1,3-dihydroisobenzofuran-1,5-diol (23) in CD 3OD (400 MHz).

- 44 -

Figure 2.8:
13
C NMR spectrum of 7-methoxy-1-methyl-1,3-dihydroisobenzofuran-1,5-diol (23) in CD 3OD (400 MHz).

- 45 -

Figure 2.9: HMBC correlations (H → C) of compound 23.

Table 2.7: NMR spectroscopic data (400 MHz, CD 3OD) for compound 23.

*Signal overlaps with HOD signal

- 46 -

Figure 2.10: Proposed cichorine biosynthesis including compounds 22-23, 41 and 47.

- 47 -

Chapter 3 is incorporated from Grau, M. F., Entwistle, R., Chiang, Y.-M., Ahuja, M., Oakley, C. E., Akashi,
T., Wang, C. C. C., Todd, R. B., Oakley, B. R. Hybrid Transcription Factor Engineering Activates the Silent
Secondary Metabolite Gene Cluster for (+)-Asperlin in Aspergillus Nidulans. ACS Chemical Biology 2018,
13 (11), 3193–3205. DOI: 10.1021/acschembio.8b00679.
The author analyzed the metabolic profiles, helped establish the boundaries of the (+)-asperlin cluster,
prepared figures and contributed to the results and discussion section. The hybrid transcription factor was
designed by Dr. R. B. Todd. Characterization of OTA and metabolic analysis of the alnR and alnA::alnB
overexpression strains was conducted by Dr. Y. M. Chiang. Strains were engineered by Dr. R. Entwistle.
RNAseq was conducted by Dr. T. Akashi. Acetate utilization studies were conducted by C. E. Oakley. Dr. T.
Akashi, Dr. R. B. Todd, and Dr. B. R. Oakley all contributed to the re-annotation efforts.

Chapter 3
Hybrid transcription factor engineering
activates the silent secondary
metabolite gene cluster for (+)-asperlin
in Aspergillus nidulans

3.1 Abstract
Fungi are a major source of valuable bioactive secondary metabolites (SMs). These
compounds are synthesized by enzymes encoded by genes that are clustered in the genome. The
vast majority of SM biosynthetic gene clusters are not expressed under normal growth
conditions, and their products are unknown. Developing methods for activation of these silent
gene clusters offers the potential for discovering many valuable new fungal SMs. While a number
of useful approaches have been developed, they each have limitations and additional tools are

- 48 -

needed. One approach, upregulation of SM gene cluster-specific transcription factors that are
associated with many SM gene clusters, has worked extremely well in some cases, but it has
failed more often than it has succeeded. Taking advantage of transcription factor domain
modularity, we have developed a new approach. We have fused the DNA-binding domain of a
transcription factor associated with a silent SM gene cluster with the activation domain of a
robust SM transcription factor, AfoA. Expression of this hybrid transcription factor activated
transcription of the genes in the target cluster and production of the antibiotic (+)-asperlin.
Deletion of cluster genes confirmed that the cluster is responsible for (+)-asperlin production,
and we designate it the aln cluster. Separately, co-induction of expression of two aln cluster
genes revealed the pathway intermediate (2Z,4Z,6E)-octatrienoic acid, a compound with
photoprotectant properties. Our findings demonstrate the potential of our novel synthetic hybrid
transcription factor strategy to discover the products of other silent fungal SM gene clusters.
3.2 Introduction
Secondary metabolites (SMs) are a rich source of medically important compounds. These
compounds are not strictly required for viability, but they confer a selective advantage for the
producing organisms, often by inhibiting important biological processes in their competitors in
their native environments. These inhibitory activities are often medically useful. Some SMs have
been used as medicines without modification (e.g. penicillin and lovastatin), other medically
valuable compounds are derived from SMs, and yet additional compounds are inspired by SMs
(e.g. with pharmacophores based on SMs).
Fungi have been an excellent source of medically valuable SMs
102
and, although many
thousands of fungal SMs have been isolated, genome sequencing has revealed that the vast
majority of fungal SMs have yet to be identified. Fungal genome projects have confirmed
previous conclusions that the genes encoding the biosynthetic enzymes required to produce
particular compounds are clustered together in the genome and coordinately regulated. They
have also revealed that for nearly all fungi examined the number of SM biosynthetic gene clusters
greatly exceeds the number of compounds known to be produced by the fungus
17,77,132,133
.

- 49 -

The reason is that most SM gene clusters are silent under normal lab growth conditions, and
developing strategies for stimulating expression of these clusters, such that their products can
be isolated, has become an important research focus
134
. A number of strategies have been
developed
12,110,135–137
. These include alteration of the media on which the fungi are grown
111
,
deletion or overexpression of genes involved in chromatin packing
33,138
, chemical perturbation of
proteins that modify chromatin
26,27,31,139
, isolation of mutations in, or over expression of, genes
such as mcrA and laeA that affect the production of many secondary metabolites
38,117
, co-
incubation with other microorganisms
87
, and replacement of the promoters of SM biosynthetic
gene cluster genes with regulatable promoters
22,25
. All of these strategies have had notable
successes, but none of them have proved to be universally effective. All of these strategies have
been applied to Aspergillus nidulans, the fungus in which the secondary metabolome has been
most extensively explored, resulting in the discovery of scores of compounds new to A. nidulans
or new to science
137
. Nevertheless, many, probably more than half, of the compounds produced
by this organism have yet to be discovered.
One approach, that has been successful in some instances, takes advantage of the fact that
many SM biosynthetic gene clusters contain a gene encoding a transcription factor that drives
expression of all of the genes of the cluster. In some cases replacement of the promoter of the
transcription factor with a regulatable promoter, and subsequent upregulation of expression of
the transcription factor, results in strong expression of the genes of the cluster and high levels of
production of the compound produced by the pathway
9,57
. This approach can work spectacularly
well, resulting in very high yields of secondary metabolites [e.g. > 2 g/L of asperbenzaldehyde
140
],
but the approach often fails. This approach was tried with 18 SM biosynthetic gene clusters in A.
nidulans
25
. In three of these cases the approach was highly successful, but in the other cases no
compounds, or unanalyzably small amounts of compound were produced.
There are several potential causes for failure of this approach. Some are intellectually trivial,
but practically consequential. For example, the induction conditions may have been inadequate
to stimulate the required level of production, or the transcription factor may have been
incorrectly annotated such that the promoter was not driving expression or was driving

- 50 -

expression of only a portion of the transcription factor. These problems are compounded by the
fact that transcription factors may work as heterodimers and if either of the two required
transcription factors is inadequately expressed or incorrectly annotated, SM production will fail.
These problems will undoubtedly be addressed by better annotation algorithms and data and by
better expression systems. Other potential limitations of this approach are related to normal SM
regulation. One theoretical, but logical, possibility is that interaction of the transcription factor
with an unknown natural inducer might be required for strong activation. Another, well
documented, factor is that the activity of transcription factors that drive expression of SMs can
be regulated post-translationally and, when this is the case, simple upregulation is unlikely to
result in high levels of expression of the genes of the regulated cluster. The best studied example
of this is the AflR transcription factor that drives expression of the sterigmatocystin gene cluster
of A. nidulans. Regulation of AflR is complex and occurs at multiple levels, but phosphorylation
of AflR by protein kinase A inactivates AflR such that it no longer drives expression of the
cluster
141
. If the activity of a transcription factor that drives expression of an SM cluster is
regulated by post-translational modifications, overexpression of the transcription factor may
never lead to expression of the genes of the cluster or production of the corresponding SM
product.
One theoretical approach to circumventing these problems is to create synthetic
transcription factors that are not subject to inhibition by post-translational modification and do
not require an unknown natural inducer. To evaluate the efficacy of this approach we have
targeted a silent A. nidulans SM biosynthetic gene cluster (Figure 3.1) containing the highly
reducing polyketide synthase gene AN11191 (using the gene designation shared by the
Aspergillus Genome Database [AspGD, http://www.aspergillusgenome.org/] and Fungal and
Oomycete Genomics Resource [Fungidb, http://fungidb.org/fungidb/]). Previous efforts to
activate this gene cluster by upregulating the transcription factor in the cluster were not
successful
22
. We initially replaced the promoters of two of the genes in the cluster with an
inducible promoter, and upregulation of the two genes resulted in the production of (2Z,4Z 6E)-

- 51 -

octa-2,4,6-trienoic acid. This compound is of interest as a possible feedstock compound for
organic syntheses and as a tanning agent in human skin because it promotes melanogenesis and
antioxidant defense in melanocytes
142
. This result suggested that the final product of the cluster
might be of interest.
We now report that we have implemented the hybrid, or synthetic, transcription factor
approach successfully to activate this gene cluster. We have added an activation domain from
AfoA, the transcription factor that drives expression of the asperfuranone gene cluster, to the
transcription factor from the cluster. Upregulation of the hybrid transcription factor results in
expression of genes in the silent cluster responsible for the biosynthesis of an anti-inflammatory,
antitumor antibiotic, (+)-asperlin
143–147
. The production of (+)-asperlin was previously reported in
A. nidulans, A. caespitosus, and A. versicolor
143–145,148
, but the specific gene cluster for this
polyketide has never been identified.

Figure 3.1: Organization of the (+)-asperlin biosynthetic gene cluster in A. nidulans. The original
annotation of the genes in this pathway is included as the top cluster. RNA-seq and CAGE RNA-seq
data revealed that AN9221 was incorrectly annotated. We designate the AN9221-exons 1-2 gene as
alnG (see Supporting Information Figure S5 for the correctly annotated alnG sequence), and designate
the AN9221-exon 3 gene, encoding a Zn(II)2Cys6 binuclear cluster, as the transcription factor gene
alnR (see Supporting Information Figure S4 for the correctly annotated alnG sequence). The cluster
below represents the re-annotated (+)-asperlin biosynthetic gene cluster with the aln gene
designations included. Predicted gene functions are color-coded.

- 52 -

3.3 Results and Discussion
3.3.1 Induction of AN11199 and AN11191 results in the production of (2Z,4Z,6E)-octa-
2,4,6-trienoic acid
One strategy our labs have used to elicit SM production is to replace the promoters of
transcription factor genes associated with SM gene clusters with the inducible alcA promoter
[alcA(p)] followed by induction of expression. We previously found, however, that the
replacement of the promoter of AN9221, a transcription factor gene associated with the SM gene
cluster containing the highly reducing polyketide synthase gene AN11191, with alcA(p) did not
result in production of a detectable product
25
. Another strategy we have used is to simply replace
the promoters of SM cluster genes individually with alcA(p) and induce expression
22,25
. We
consequently replaced the promoter of AN11191 with the alcA promoter using an approach we
have previously reported
22
. We also replaced the promoter of AN11199, a gene that we
hypothesized might be required for release of product from AN11191. The resulting strain was
LO4912 (genotypes of strains in Table 3.1). Induction of expression of these genes resulted in
production of compound 1 (2Z,4Z,6E)-octa-2,4,6-trienoic acid (Figure 3.2) (details of purification
and structure elucidation are in the Supporting Information). (2Z,4Z,6E)-octa-2,4,6-trienoic acid
is a particularly interesting compound because of its potential as a natural tanning agent for
human skin
142
. It is a promoter of melanogenesis and antioxidant defense in melanocytes in vitro
and in vivo, topically and systemically. Pigmentation is a powerful protectant from UV damage
and skin cancer, and octatrienoic acid is an attractive natural photoprotectant. The alternating
double bonds in this molecule also suggest that it has potential as a feedstock for organic
syntheses. Since only two of the genes of the biosynthetic gene cluster were upregulated, we
believed it was likely that this compound was an intermediate rather than the final product of
the biosynthetic pathway, and we wished to develop a method for activating expression of the
entire pathway.

- 53 -

Table 3.1: Strains used in this study
*An ATG start codon was inserted; AN9221(250-652) was reannotated as AlnR(5-407)
3.3.2 Construction and expression of a synthetic transcription factor drives
expression of the AN11191 gene cluster
Although individual replacement of promoters can be a very powerful tool for eliciting
production of SMs
22
, there are inherent limitations. The most obvious is that one must carry out
Strains Genotype Reference
FGSC442 facB101, riboB2, chaA1, sE15, nirA14 Fungal Genetics
Stock Center
TN02A7
(LO1362)
pyroA4, riboB2, pyrG89, nukA::argB [
119
]
LO2026 stcJΔ::AfriboB in LO1362 [
138
], [
56
]
LO3632 AN9221(alnG-alnR)::AfpyrG-alcA(p)-AN9221 in LO2026 [
25
]
LO4054 alnA::AfpyrG-alcA(p)alnA in LO2026 This work
LO4387 stcWΔ::AfpyrG in LO2026 This work
LO4389 stc(AN7804-AN7825)Δ in LO4387 [
25
]
LO4912 alnB::AfpyroA-alcA(p)alnB in LO4054 This work
LO8030 pyroA4, riboB2, pyrG89, nukA::argB, stc(AN7804-AN7825)Δ,
eas(AN2545-AN2549)Δ, afo(AN1039-AN1029)Δ,
mdp(AN10023-AN10021)Δ, tdi(AN8512-AN8520)Δ,
aus(AN8379-AN8384, AN9246-AN9259)Δ, ors(AN7906-
AN7915)Δ, apt(AN6000-AN6002)Δ
[
120
]
LO9577 yA::AfpyroA-aldA(p)afoA in LO8030 This work
LO9721 yA::AtpyrG-alcA(p)alnR(250-652)-afoA(130-666)* in LO8030 This work
LO9886-LO9888 facB::facB(1-142)-afoA(130-666)-AtpyrG in LO4389 This work
LO11147 yA::AtpyrG-alcA(p)AN9221 in LO9577 This work
LO11280 yA::AfpyrG-alcA(p)alnR in LO8030 This work
LO11153 AN9216Δ::AfriboB in LO9721 This work
LO11156 alnDΔ::AfriboB in LO9721 This work
LO11160 alnEΔ::AfriboB in LO9721 This work
LO11164 AN9214Δ::AfriboB in LO9721 This work
LO11168 AN12145Δ::AfriboB in LO9721 This work
LO11178 alnAΔ::AfriboB in LO9721 This work
LO11181 alnBΔ::AfriboB in LO9721 This work
LO11184 AN9213Δ::AfriboB in LO9721 This work
LO11190 AN9215Δ::AfriboB in LO9721 This work
LO11192 alnFΔ::AfriboB in LO9721 This work
LO11261 alnCΔ::AfriboB in LO9721 This work
LO11289 alnHΔ::AfriboB in LO9721 This work
LO11293 AN9221(alnG-alnR)Δ::AfriboB in LO9721 This work
LO11302 alnIΔ::AfriboB in LO9721 This work

- 54 -

several transformations to replace the
promoters of all target genes. Our
molecular genetic methods are efficient,
however, and these transformations can be
carried out relatively quickly. Another,
more serious, problem is that if any of the
genes of the target cluster is incorrectly annotated, promoter replacement for that gene will be
non-productive. The gene will not be expressed or only a gene fragment will be expressed. In
addition, although progress has been made, defining the boundaries of gene clusters from
genomic sequence alone is still an inexact process
17
. We searched, therefore, for a new approach
that would allow expression of entire clusters.
One potential approach that might overcome post-translational inactivation of SM
transcription factors, and/or requirement of an unknown natural inducer for SM transcription
Figure 3.2: (A) Diode array detector (DAD)
total scan HPLC profiles and (B) extracted ion
chromatograms (EIC) for compound 2 (EIC =
m/z 213) of culture media extracts of A.
nidulans strains in which we induced the alcA
promoter driving expression of the native
cluster-specific transcription factor gene
(alnR) (top), the HR-PKS (AN11191 = alnA) and
esterase (AN11199 = alnB) genes (middle),
and the hybrid alnR-afoA transcription factor
gene (HyTF) (bottom) under the control of the
alcA promoter. 1 is (2Z,4Z,6E)-octa-2,4,6-
trienoic acid, and 2 is (+)-asperlin. (C)
Chemical structures of 1 and 2 as determined
by NMR. *From RNA-seq experiments, we
have corrected the originally annotated
sequence of the AN9221 transcription factor
gene and put the reannotated sequence
(alnR) under the control of the alcA promoter.
†
At the same retention time as 1, trace
amounts of unknown metabolites could also
be detected in the hybrid transcription factor-
expressing strain.

- 55 -

factors, is to exploit the domain modularity of transcription factors
149,150
. Synthetic hybrid
transcription activators may be constructed by fusing an active transcription activation domain
from a transcription factor known to function in late stationary growth phase to a target SM
transcription factor or its DNA binding domain (DBD), which provides the DNA sequence
specificity tethering the activation domain to SM gene cluster promoters. There are a number of
factors to consider in designing such a synthetic transcription factor. Transcription initiation is
complex and different transcription factors may be more or less potent in different contexts. In
our experience, SMs are not produced at high levels during log phase growth even if the SM
biosynthetic genes are under control of promoters that drive high levels of expression in log
phase. The likely explanation is that the precursors required for SM biosynthesis are limiting in
log growth. In late stationary phase, however, SM production, particularly polyketide production,
can be driven to very high levels, revealing that precursors are plentiful. A suitable transcription
factor must be able to drive high levels of transcription at that time. The afoA gene drives
expression of the asperfuranone biosynthetic cluster
57
, and upregulation of afoA has allowed us
to obtain very high levels of production of asperbenzaldehyde, an intermediate in asperfuranone
biosynthesis
140
(> 2 g/L of purified product). AfoA (the protein encoded by the afoA gene), is,
thus, capable of driving high levels of expression in late stationary phase cultures when SM
precursors are abundant, and it is not negatively regulated post-translationally to any significant
extent. We, therefore, chose afoA as the source for our activation domain.
We note that in these experiments our replacement of the promoter of afoA (AN1029) with
the alcA promoter, was based on the AspGD version 3 gene annotation (AN1029.3)
25
. This
annotation of AN1029 was identical to the previous version 2 annotation. Upregulation of the
alcA promoter drove expression of a functional transcription factor that resulted in a successful
upregulation of asperfuranone production
25
and, with an appropriate pathway deletion,
asperbenzaldehyde production.
26
These results indicate that the version 3 annotation was
correct, at least with respect to the annotation of the start codon. The current gene annotation
for afoA in the AspGD and FungiDB databases (http://www.Aspergillusgenome.org;
http://fungidb.org) is version 5. In this version afoA is shortened at the 5’ end relative to the
version 3 annotation, omitting exon 1 and the DBD. We do not believe that the version 5

- 56 -

annotation is correct because the DBD would be required for function and because promoter
replacements based on the longer, version 3 annotation drive expression of a functional
transcription factor. We have consequently based our analyses on the version 3 annotation. We
have included the version 3 nucleotide and amino acid sequences for afoA and AfoA in the
supporting information (Figure 3.7). The identical version 2 annotation (AN1029.2) is still
available at the National Center for Biotechnology Information (https://www.ncbi.nlm.nih.gov/).
The AfoA transcription factor harbors a Zn(II)2Cys6 DNA binding motif. The DNA-binding
specificity of Zn(II)2Cys6 transcription factors is typically provided by the specificity region and
heptad repeat coiled-coil forming dimerization motif immediately following the Zn(II)2Cys6
motif, whereas the activation domain is C-terminal to the heptad repeats
150,151
. The predicted
Zn(II)2Cys6 DNA-binding motif is at residues 16-43, and a potential coiled-coil dimerization motif
is at residues 55-80. A second predicted coiled coil at 98-129 could contribute to dimerization. A
putative nuclear localization signal (NLS) of the SV40 Large T-antigen-type is found at residues
236-242.
To verify that AfoA residues C-terminal to the DBD contained the activation domain and could
activate gene expression in a hybrid transcription factor context we replaced amino acids 143-
867 of the transcription factor FacB with amino acids 130-666 of AfoA (Figure 3.3). N-terminal
residues 1-142 of FacB are sufficient for DNA binding and are known to provide DNA binding
specificity for acetate utilization gene promoters when fused to the activation domain of other
Zn(II)2Cys6 transcription factors
152–155
. Fusion of putative ADs to the FacB DBD in strains lacking
native facB provides a simple assay for activation function assessed by growth on acetate as a
sole carbon source. The hybrid FacB(1-142)-AfoA(130-666) transcription factor activated
transcription of acetate utilization genes as growth on acetate was supported albeit below wild-
type growth rates (Figure 3.3).
Having established that the afoA activation domain can activate expression in the context of
a hybrid transcription factor, we attempted to create a hybrid transcription factor that would
drive expression of the SM gene cluster containing AN11191 and AN11199. We fused the

- 57 -

transcription activation domain (residues 130-666) of AfoA to amino acids 250 through 652 of
AN9221, as annotated in the AspGD and FungiDB databases. (We have subsequently found that
Figure 3.3: (A) The primary structure of the transcription factors AfoA and FacB, and the hybrid
FacB(1-142)-AfoA(130-666) transcription factor are shown with the relevant functional domains. The
DNA Binding Domain (DBD) consists of the Zn(II)2Cys6 zinc binuclear cluster (wide diagonal stripe) and
the heptad repeats coiled-coil dimerization region (narrow diagonal stripe). The putative nuclear
localization signal (NLS) in AfoA is indicated. The activation domain, which is located in the C-terminal
portion for this class of transcription factor, is not precisely defined but is located within AfoA residues
130-666. The FacB activation domain is C-terminal to residue 625
41
. AfoA sequences are shown in
green, whereas FacB sequences are shown in purple. The DNA binding specificity and function of each
transcription factor is indicated. The fusion point in the hybrid transcription factor is indicated by an
arrow head with the amino acid coordinates separated by two colons. (B) The ability of the FacB(1-
142)-AfoA(130-666) hybrid transcription factor to activate FacB-dependent acetate utilization genes
was assessed qualitatively by gene replacement of wild type facB with the hybrid transcription factor
gene containing sequences encoding the FacB DNA binding domain (codons 1-142) and the AfoA
activation domain (codons 130 – 666), followed by growth on acetate as a sole carbon source. Growth
(37˚C, 2 d) of transformants expressing FacB(1-142)-AfoA(130-666) (LO9886, LO9887, and LO9888) are
shown relative to the wild type (LO4389) and the facB101 complete loss-of-function mutant (FGSC
442), which truncates FacB at residue 619 deleting the activation domain
47
. Growth on glucose is
independent of facB activity. Note that the color difference observed for FGSC 442 is due to the chaA1
conidial color mutation in the background genotype and is unrelated to facB.

- 58 -

AN9221 was mis-annotated, as we will discuss.) This region included the AN9221 Zn(II)2Cys6
motif, specificity region, and heptad repeats (residues 269-352) predicted to provide DNA-
binding specificity for promoters in the cluster regulated by AN9221 (Figure 3.4). We omitted
AN9221 N-terminal residues 2-249 to avoid predicted transmembrane domains, but retained the
AN9221 sequences C-terminal to the DNA-binding domain in the fusion protein as they may
contribute to activation, particularly if an intermediate in the regulated pathway acts as an
inducer, as is known for some other transcription factors of this class (e.g. LeuB
156
, AmyR
157
). The
resultant hybrid transcription factor, consisting of AN9221 residues 250-652, and AfoA residues
130-666, was put under control of the alcA promoter (with a start codon created during the
fusion PCR process) and inserted at the yA locus using the Aspergillus terreus pyrG pyrimidine
prototrophic selectable marker (Figure 3.4). The recipient strain LO9577 is derived from LO8030,
which carries deletions of eight of the most highly expressed gene clusters in A. nidulans including
the asperfuranone biosynthetic gene cluster
120
. Removal of these gene clusters lowers the SM
background and facilitates detection of newly induced metabolites. LO9577 also carries a
replacement of the yA gene with a fragment containing the Aspergillus fumigatus pyroA gene
(AfpyroA) as well as the aldA promoter driving expression of afoA. This facilitated construction
and identification of correct transformants as shown (Figure 3.4). In particular, correct
transformants with the alcA(p)-driven hybrid transcription factor gene targeted in single copy at
yA and replacing AfpyroA-aldA(p)afoA will be pyrimidine prototrophs and pyridoxine auxotrophs.
Transformants were analyzed by diagnostic PCR, and we subsequently have worked with a
correct transformant designated LO9721.
We next wished to determine if the hybrid transcription factor drove expression of the target
gene cluster and, if so, whether this led to the production of the SM product of the cluster. We
examined expression of cluster genes using RNA-seq. Our samples were grown in liquid culture
with lactose minimal medium. Lactose is a non-repressing carbon source that allows expression
from the alcA promoter. The alcA promoter is induced by a number of compounds. For induction
of expression of the hybrid transcription factor from the alcA promoter in these experiments, we
used 50 mM methyl-ethyl ketone (MEK). We carried out RNA-seq (in triplicate) for LO1362, a
control strain wild-type for SM gene clusters, LO9721 under non-repressing conditions, which is

- 59 -

Figure 3.4: (A) The induction system used, transcription factor domain structure, DNA binding
specificity, and product observed in inducing conditions are summarized from previous experiments
and this work. Expression of the AfoA transcription factor from the alcA(p) promoter conferred
asperfuranone production
25
, whereas expression of AN9221 from the alcA(p) promoter failed to yield
a SM product
22
. The protein expressed from the AN9221 sequence was, due to misannotation, not the
predicted transcription factor but instead was the transmembrane (TM) protein AlnG, which lacks a
DBD. Expression of the reannotated transcription factor AlnR, which contains the AN9221 DBD, from
alcA(p) also failed to produce a SM product. Expression of the hybrid AN9221(250-652)-AfoA(130-166)
transcription factor, which was reannotated as AlnR(5-407)-AfoA(130-666), conferred production of
(+)-asperlin (2). The transcription factors/proteins products are shown with the relevant functional
domains: the DBD consists of the Zn(II)2Cys6 zinc binuclear cluster (wide diagonal stripe) and the
heptad repeats coiled-coil dimerization region (narrow diagonal stripe), the putative NLS in AfoA, and

- 60 -

predicted to give some expression of the hybrid transcription factor, and LO9721 under inducing
conditions, which is predicted to give strong expression of the hybrid transcription factor.
We first verified that the hybrid transcription factor was expressed by looking for afoA
sequence reads. As the wild-type afoA gene in the asperfuranone gene cluster has been deleted
in LO9721, any afoA reads will be from the hybrid transcription factor. afoA reads are quantified
in Table 2. There are almost no afoA reads in the control strain, in which the asperfuranone gene
cluster is intact. This reflects the fact that the native afoA promoter is essentially completely off
in control strains with wild-type regulation of the asperfuranone gene cluster. In LO9721 under
non-repressing conditions for the alcA promoter, there were moderate numbers of afoA reads
as expected and induction with MEK substantially boosted the afoA reads. We also noted a very
large increase in AN9221 reads, consistent with the fact that the hybrid transcription factor
includes a portion of AN9221. These data reveal that the hybrid transcription factor is expressed
and responds to induction of the alcA promoter as expected.
Next, we asked if expression of the hybrid transcription factor resulted in expression of the
target gene cluster. Results are shown in Figure 3.5 and quantified in Table 3.2. The genes in the
region extending from AN11200 through AN11191 are strongly upregulated by expression of

Figure 3.4 (cont.): transmembrane region (TM). The activation domain is not precisely defined but
is located within AfoA residues 130-666. No obvious NLS is found in AlnR. AfoA sequences are shown
in green, whereas AN9221-derived sequences including AlnG and AlnR are shown in yellow. The
fusion point in the hybrid transcription factor is indicated by an arrow head with the amino acid
coordinates separated by two colons. (B) i. A transforming fragment was created by fusing three
DNA fragments using fusion PCR. The first fragment consists of 5' flanking DNA from the yA locus, the
Aspergillus terreus pyrG gene (AtpyrG) and the promoter from the alcohol dehydrogenase gene
[alcA(p)]. This fragment was a cassette previously made by fusion PCR. The second fragment consists
of the DNA binding domain from AN9221 (AN9221 DBD) and the third fragment consists of the
activation domain of afoA (AN1029) (afoA AD). ii. The three fragments were fused by fusion PCR
creating the transforming fragment shown. The recipient strain (LO9577) carried a replacement of
the yA locus by the Aspergillus fumigatus pyroA gene (AfpyroA), the aldehyde dehydrogenase
promoter [aldA(p)] and the asperfuranone gene cluster transcription factor, afoA (AN1029). iii.
Homologous recombination during transformation results in a hybrid transcription factor driven by
the alcA promoter. Note that AfpyroA is replaced by AtpyrG resulting in a strain that does not require
added pyrimidines for growth but does require added pyridoxine.

- 61 -

Table 3.2: Hybrid transcription factor induction of the (+)-asperlin gene cluster.
Gene
Control
(LO1362)
a,b
Hybrid TF
(LO9721)
a

P value
c

(induced vs
control) non-repressing induced
AN1029 (afoA) 0.30 ± 0.02 125.66 ± 32.93 891.77 ± 67.24 2.17E-25
AN9223 0.29 ± 0.03 0.26 ± 0.06 0.22 ± 0.04 --
AN12146 0.29 ± 0.03 0.25 ± 0.06 0.22 ± 0.04 --
AN11200 (alnI) 2.30 ± 0.51 46.59 ± 4.29 18.95 ± 1.74 5.19E-10
AN11192 (alnH) 0.29 ± 0.03 743.55 ± 118.12 2845.53 ± 526.75 2.33E-36
AN9221
d

(alnG and alnR)
14.72 ± 5.69 130.20 ± 11.77 576.91 ± 83.50 0
AN9220 (alnF) 0.29 ± 0.03 1384.18 ± 194.59 4989.54 ± 303.36 1.17E-40
AN9219 (alnE) 0.29 ± 0.03 1589.13 ± 150.41 4247.82 ± 655.08 2.86E-39
AN9218 (alnD) 0.29 ± 0.03 47.56 ± 12.70 768.20 ± 99.45 2.60E-28
AN11198 (alnC) 0.29 ± 0.03 38.71 ± 8.74 271.65 ± 28.41 1.69E-22
AN11199 (alnB) 0.29 ± 0.03 166.57 ± 37.65 2181.88 ± 106.70 4.75E-35
AN11191 (alnA) 0.29 ± 0.03 49.09 ± 15.45 1885.98 ± 342.46 1.13E-33
AN9216 3.57 ± 3.42 5.07 ± 2.11 3.10 ± 1.61 --
AN9215 0.29 ± 0.03 0.25 ± 0.06 0.22 ± 0.04 --
the hybrid transcription factor. Adjacent genes are not upregulated. These data reveal that the
hybrid transcription factor does, as anticipated, drive expression of the SM cluster genes. They
also define the boundaries of the cluster since the genes that are not upregulated are unlikely to
be components of the cluster. We designate this cluster the (+)-asperlin cluster after the product
of the cluster (see below) and the genes of this cluster alnA-alnI plus alnR (Figures 3.1 and 3.6

a
Values are mean ± standard deviation of reads per million for three replicates. The control strain
LO1362 and LO9721, the strain carrying the hybrid transcription factor, were grown in lactose minimal
medium which is non-repressing for the alcA promoter. After 36 hours of growth, 50 mM MEK was
added to half the flasks containing LO9721 to induce expression of the hybrid transcription factor. The
remaining LO9721 flasks served as a non-repressing control. MEK was added in parallel to the control
strain, LO1362. The hybrid transcription factor drives expression of AN11200-AN11191 (but not other
genes in this region) even in non-repressing medium.
b
Several of the genes have the same value in the
control strain because of a minor quirk of the SeqMonk analysis package. The package normalizes
reads per million as base 2 logarithms and 0 cannot be expressed with complete accuracy as a base 2
log (i.e. 0 = 2
-∞
). Conversion from log base 2 values back to numbers results in small fractions of a read
in instances in which there were no raw reads. For the Control lane, instances in which there were no
raw reads resulted in normalized reads of 0.29.
c
P values in the column at the right reveal that the
increase in expression in the induced strain vs the control strain is highly significant. P values were
obtained using total reads with the R statistical package.
d
AN9221 is incorrectly annotated in the
available databases and is actually two genes that we have designated alnG and alnR. Induction with
MEK results in a substantial additional increase in expression.

- 62 -

and Table 2). Interestingly, differences in the levels of induction of the genes within the cluster is
observed. This likely reflects different DNA-binding affinities of the hybrid transcription factor for
different aln gene promoters due to either sequence differences in the different AlnR DNA-
binding sites or different numbers of AlnR DNA-binding sites in the promoters. It is tempting to
speculate that these expression differences may represent the optimal relative levels, arising
from DNA-binding site evolution, for operation of the pathway and biosynthesis of the final
product.
Our analyses of RNA-seq data also reveal that AN11200 is slightly longer than indicated by
the AspGD and FungiDB annotations. AN11200 contains an intron and additional sequence
upstream of the current annotation. The corrected coding sequence is in the Supporting
Information Figure 3.8. It is also worth noting that induction of the hybrid transcription factor
upregulates the antisense strand of AN11200 as well as the sense strand. Finally, although
AN11200 and AN11192 are very close, with the termination codon of AN11200 being less than
250 bp from the start codon of AN11192, our RNA-seq data indicate that they are indeed,
separate genes.
3.3.3 Reannotation of AN9221
One unexpected outcome of our RNA sequencing was a realization that AN9221 is mis-
annotated in the databases. We noted in a number of RNA-seq experiments that AN9221 is
expressed at very low levels in strains that do not carry the hybrid transcription factor. However,
it is expressed enough that a clear pattern in the RNA-seq reads emerged. The reads were
confined to what was annotated as exon 3. Reads from exons 1 and 2 were almost completely
absent. The fact that transcription of exon 3 was apparently regulated independently of exons 1
and 2 suggested that it is a separate gene. We consequently carried out CAGE RNA-seq, which
reveals transcription start sites. The results (Supporting Information Figure 3.9) revealed that
there is a distinct transcription start site at the beginning of exon 3. These data, in combination,
reveal exon 3 is a separate transcription unit (i.e. gene) from exons 1 and 2. The coding sequences
of these genes along with the amino acid sequences of the predicted products are listed in the
Supporting Information Figures 3.10 and 3.11. The region containing the sequences previously

- 63 -

annotated as exons 1 and 2 appears to be a separate gene encoding transmembrane domains
that is upregulated by the hybrid transcription factor. These results indicate that the genes
formerly called AN9221 need to be given new designations. We designate the exon 3 gene alnR
(R denoting that as a transcription factor it is a regulatory gene). Its nucleotide and predicted
amino acid sequences are shown in Supporting Information Figure 3.10. The predicted AlnR
protein contains a Zn(II)2Cys6 zinc binuclear cluster at residues 24-51 and putative heptad
repeats at residues 81-108. We designate the former exons 1 and 2 alnG. Our RNA-seq data
further indicate that the intron in alnG is misannotated in the current AspGD and FungiDB
databases. The actual intron is shorter, and the correct alnG sequence is given in Supporting
Information Figure 3.11.
Reannotation of AN9221 has important consequences for this study. One is that, in all
likelihood, the previously published replacement of the promoter of AN9221 with the alcA
promoter
25
was doomed to failure because the transcription factor was not actually being
upregulated. Instead, the adjacent transmembrane domain encoding-gene, alnG, was likely
upregulated. The second is that in our hybrid transcription factor construction, we actually
included most of AlnR (residues 5-407), lacking only the four N-terminal amino acids. This raised
the possibility that the activation of the cluster was simply due to upregulation of alnR and that
the AfoA activation domain was not needed. To test this possibility we placed alnR under control
of the alcA promoter and upregulated it. The resulting HPLC profile (Figure 3.2) showed that, in
inducing conditions, overexpression of alnR alone was not sufficient to stimulate SM production
by the aln gene cluster. The hybrid transcription factor, including the AfoA activation domain,
therefore, was required for activation of the cluster.
3.3.4 Hybrid transcription factor expression drives production of (+)-asperlin (2)
Strong expression of the hybrid transcription factor resulted in the production of compound
2, (+)-asperlin, which we believe to be the final product of the target gene cluster (Figures 3.2
and 3.6). (+)-Asperlin was purified from large-scale cultures using preparative Thin Layer
Chromatography, and the structure was confirmed by NMR (details of purification and structure
elucidation are in the Supporting Information).

- 64 -

Our RNA-seq analysis provided a clear prediction as to the genes involved in (+)-asperlin
biosynthesis, but to test the prediction we individually deleted twelve genes (AN11200-AN9213)
Figure 3.5: (A) RNA-seq transcript read alignments to genes surrounding the HR-PKS, AN11191, for
the hybrid AlnR-AfoA transcription factor (HyTF) expressing A. nidulans strain compared to a strain
lacking a hybrid transcription factor. Gene color indicates direction of transcription; genes transcribed
from right to left (blue), and genes transcribed from left to right (orange). (B) Extracted ion
chromatograms for compound 2 (EIC = m/z 213) of culture media extracted from A. nidulans hybrid
transcription factor expressing strains carrying a single gene deletion of genes surrounding AN11191.
*Original annotation of AN9221 suggested 3 exons, however, RNA-seq data indicates that AN9221 is
actually two separate transcription units; one gene contains exons 1 and 2 and the other gene contains
exon 3.

- 65 -

and examined the effects of the deletions on the biosynthesis of (+)-asperlin (Figure 3.5). The
deletant strains were cultivated under inducing conditions and their metabolite profiles
examined by LC-MS. Analysis of the deletants shows that deletions of alnA, alnB, alnC, alnD, alnF,
alnH and alnI fully eliminated production while deletion of alnE and AN9221 (=alnR + alnG)
diminished production. AN9216Δ, AN9215Δ, AN12145Δ, AN9214Δ, AN9213Δ strains all produced
(+)-asperlin in substantial amounts, revealing that they are not functional components of the (+)-
asperlin gene cluster. The deletion and RNA-seq data are consistent with each other and,
together, reveal that the genes involved in the biosynthesis of (+)-asperlin (2) include; alnA
(AN11191), alnB (AN11199), alnC (AN11198), alnD (AN9218), alnE (AN9219), alnF (AN9220), alnG
(AN9221 exons 1-2), alnR (AN9221 exon3), alnH (AN11192), and alnI (AN11200) (Table 2 and
Figure 5).
3.4 Conclusion
Earlier attempts to upregulate entire silent gene clusters in A. nidulans by expressing
pathway-specific transcription factors with an inducible promoter have proven to be largely
unsuccessful, resulting in the upregulation of less than 20% of gene clusters tested
25
. To improve
Figure 3.6: (A) The deduced functions of each ORF based on the AspGD gene designations. (B)
Proposed biosynthesis of (2Z,4Z,6E)-octa-2,4,6-trienoic acid (1) by AlnA with cleavage of the PKS
product by AlnB, and downstream production of the pathway product, (+)-asperlin (2). *Original
annotation of AN9221 suggested 3 exons, however, RNA-seq data indicates that AN9221 is actually
two separate transcription units; alnG contains exon 1-2 and the other gene, alnR, contains exon 3. KS,
β-ketoacyl synthase; MAT, malonyl-CoA:acyl carrier protein transacylase; DH, dehydratase; ER,
enoylreductase; KR, ketoreductase; ACP, acyl carrier protein.

- 66 -

upon this approach, we designed a synthetic hybrid transcription factor to drive expression of
the AN11191 cluster. By exploiting the domain modularity of transcription factors, we fused the
potent transcription AD of AfoA, the asperfuranone cluster transcription factor, with the DBD of
AN9221 (AlnR), the transcription factor of the AN11191 cluster, and placed the synthetic
construct under the control of the alcA promoter. Induction of expression of this hybrid
transcription factor activated expression of AN11191-AN11200 and production of the polyketide,
(+)-asperlin (2). We confirmed that these genes, but not other genes nearby in the genome, are
required for (+)-asperlin (2) biosynthesis through a series of gene deletions. Our results also
revealed that the putative native transcription factor for this cluster, AN9221 was misannotated
previously and is actually two separate genes. However, induction of expression of the
reannotated transcription factor, alnR, did not result in significant (+)-asperlin (2) production.
This result demonstrates the value of the hybrid transcription factor approach for activation of
expression of the (+)-asperlin (2) gene cluster. These results, taken together, show the potential
of the synthetic hybrid transcription factor strategy we have developed to upregulate the genes
and identify the products of other cryptic clusters.
Cluster-specific transcription factors are often associated with SM gene clusters in
Ascomycetes. In A. nidulans alone, 48 of 71 putative SM clusters contain identifiable transcription
factors
133
. One-half to two-thirds of putative SM clusters in related Aspergillus species contain
identifiable transcription factor genes; Aspergillus oryzae: 40 of 75, Aspergillus fumigatus: 27 of
39, Aspergillus niger: 54 of 81, Aspergillus flavus: 35 of 55
133,158
. Moreover, most of these
transcription factors belong to the Zn(II)2Cys6 DBD class, and the majority of SM products from
these clusters are unknown. This indicates the potential scope of application of hybrid
transcription factor technology for SM discovery. The success of our hybrid transcription factor
strategy relied on the Zn(II)2Cys6 DBD of AlnR. This class of transcription factors usually binds
DNA as homodimers
150,151
. The hybrid transcription factor approach should be applicable to other
DBD classes. Hybrid transcription factors that tether an active activation domain to the DBD of a
SM cluster transcription factor have the advantage of providing cluster activation specificity
without needing to know whether a natural inducer or post-translational modification of the
activation domain of the native transcription factor is necessary for activation. In some cases,

- 67 -

however, the success of this approach may be hampered by the requirement of an unknown
heterodimerization partner or other DNA-binding partner for promoter binding, by post-
translational regulation of the DBD of the cluster-specific transcription factor, or by the
availability of the necessary metabolic precursors. Future efforts with respect to the (+)-asperlin
(2) cluster will focus on identifying intermediates of and fully elucidating the stepwise
biosynthetic pathway for (+)-asperlin (2).
3.5 Methods
3.5.1 Bioinformatic analysis of transcription factors
The location of predicted structural features of the transcription factors was determined
following analysis using ScanProsite (https://prosite.expasy.org/ )
159
for the Zn(II)2Cys6 domain,
Lupas coiled-coil prediction (http://toolkit.tuebingen.mpg.de/pcoils )
160
for the dimerization
motif, and PSORTII (https://psort.hgc.jp/ )
161
for the Nuclear Localization Signals (NLSs). The
transmembrane domains in the mis-annotated AN9221 sequences were analyzed using the
TMHMM Server v. 2.0 for prediction of transmembrane helices in proteins
(http://www.cbs.dtu.dk/services/TMHMM/ )
162
.
3.5.2 Fermentation and HPLC-DAD-MS analysis
For all strains, 3 x 10
7
spores were grown in 30 mL lactose minimum media (LMM) (15 g L
-1
D-
lactose, 6 g L
-1
NaNO 3, 0.52 g L
-1
KCl, 0.52 g L
-1
MgSO 47H 2O, 1.52 g L
-1
KH 2PO 4, and 1 mL L
-1
Hutner’s
trace element solution
163
) or glucose minimum media (GMM) (10 g L
-1
D-glucose, 6 g L
-1
NaNO 3,
0.52 g L
-1
KCl, 0.52 g L
-1
MgSO 47H 2O, 1.52 g L
-1
KH 2PO 4, and 1 mL L
-1
Hutner’s trace element
solution), and, where appropriate, supplemented with 0.5 mg L
-1
pyridoxine, and 2.5 mg L
-1

riboflavin, in 125 mL flasks at 37 °C with shaking at 180 rpm. For alcA(p) induction, 50 mM of MEK
was added to the culture 42 h after inoculation
132
. Culture medium and hyphae were collected
72 h after induction by filtration and extracted twice with a volume of EtOAc equal to the culture
volume. The combined EtOAc layers were evaporated in vacuo, redissolved in 1 mL of MeOH and
10 μL was injected for HPLC-DAD-MS analysis. LC-MS spectra were obtained using a
ThermoFinnigan LCQ Advantage ion trap mass spectrometer with a reverse phase C 18 column

- 68 -

(Alltech Prevail C 18; particle size, 3 μm; column, 2.1 by 100 mm) at a flow rate of 125 μL min
-1
.
The solvent gradient for LC-MS was 95% MeCN–H 2O (solvent B) in 5% MeCN–H 2O (solvent A),
both of which contained 0.05% formic acid, as follows: 0% solvent B from 0 to 5 min, 0 to 100%
solvent B from 5 min to 35 min, 100% solvent B from 35 to 40 min, 100 to 0% solvent B from 40
to 45 min, and reequilibration with 0% solvent B from 45 to 50 min. Conditions for MS included
a capillary voltage of 5.0 kV, a sheath gas flow rate at 60 arbitrary units, an auxiliary gas flow rate
at 10 arbitrary units, and the ion transfer capillary temperature at 350 °C.
3.5.3 Compound spectral data
NMR spectral data were collected on a Varian Mercury Plus 400 spectrometer. High
resolution electrospray ionization mass spectrum (HRESIMS) was obtained on ThermoScientific
Q Exactive hybrid quadrupole-Orbitrap mass spectrometer with an Eclipse XDB-C 18 column
(Agilent 5 μm 4.6 x 150 mm) at a flow rate of 125 μL min
-1
. Conditions for MS included a spray
voltage of 3.5 kV, sheath gas flow rate 20 au, auxiliary gas flow rate at 5 au, sweep gas flow rate
at 1 au, capillary temperature at 275 °C, s-lens RF level 55, auxiliary gas heat temperature at 325
°C, scan range of 100-600 m/z, resolution 140,000, AGC target 3 x 10
6
, and maximum injection
time of 200 ms.
(2Z,4Z,6E)-octa-2,4,6-trienoic acid (1): White amorphous powder; for UV-Vis and HRESIMS
spectra see Supporting Information Figure 3.12; for
1
H and
13
C NMR data (CDCl 3), see Supporting
Information Figure 3.13-3.15; HRESIMS, [M – H]
+
m/z found 139.0753.
(+)-Asperlin (2): Colorless oil; for UV-Vis and HRESIMS spectra see Supporting Information
Figure 3.12; for
1
H and
13
C NMR data (CDCl 3), see Supporting Information Figure 3.13, 3.16-3.17;
HRESIMS, [M – H]
+
m/z found 213.0754.
3.5.4 Transformation procedures and construction of transforming molecules
Transforming molecules were constructed by fusion PCR as previously described
119,128,129
. The
selectable markers used were the Aspergillus fumigatus pyrG gene (AfpyrG)
164
, the Aspergillus
terreus pyrG gene (AtpyrG)
130
, the A. fumigatus riboB gene AfriboB
119
and the A. fumigatus pyroA

- 69 -

gene
119
. The markers used for each construct are specified in the strain list. All constructs were
verified by diagnostic PCR. Transformation procedures were as previously described
128,129
.
3.5.5 RNA-seq
Conidia of a control strain (LO1362 = TNO2A7) and of LO9721, which carries the hybrid
transcription factor under control of the alcA promoter, were inoculated into 50 mL of lactose
minimal medium in 250 mL Erlenmeyer flasks at a density of 2 X 10
4
conidia mL
-1
. The medium
was supplemented with riboflavin, pyridoxine, uridine and uracil to supplement the nutritional
markers carried by the control strain. The flasks were incubated at 37 °C in a rotary shaker at 100
RPM. After 36 h incubation, MEK was added to a final concentration of 50 mM to flasks containing
the control strain and to half the flasks containing LO9721. The remaining LO9721 flasks were
incubated without MEK. After four hours of further incubation, hyphae were harvested by
filtration through miracloth. They were then frozen with liquid nitrogen and reduced to a frozen
powder with a Multi-beads Shocker (Yasui Kikai Co., Ltd., Japan). Library preparation, sequencing
and data analysis procedures were as previously described
38
with minor modifications (for
example, HISAT2 was used instead of HISAT for read mapping).
3.6 Supporting Information
Isolation of secondary metabolites
For scaling up to isolate compound 1, 1 L of LMM (20 125-mL flasks were used containing 50
mL of medium each) inoculated with 1.0 x 10
9
spores L
-1
of A. nidulans strain LO4909 was
incubated at 37°C with shaking at 180 rpm. For alcA(p) induction, 50mM of MEK was added to
the culture(s) 42 h after inoculation. Culture medium were collected 72 h after induction by
vacuum filtration. The culture medium partitioned with ethyl acetate (EtOAc; 1 L) after
acidification by 1N HCl to pH = 3. The EtOAc layer was collected and evaporated in vacuo to yield
compound 1 without further purification.
For scaling up to isolate compound 2, 2 L of LMM (2 2-Liter flasks were used containing 1 L of
medium each) inoculated with 1.0 x 10
9
spores L
-1
of A. nidulans strain LO9721 was incubated at

- 70 -

37°C with shaking at 180 rpm. For alcA(p) induction, 50 mM of MEK was added to the culture(s)
42 h after inoculation. Culture medium and hyphae were collected 72 h after induction by
vacuum filtration. The culture medium partitioned with ethyl acetate (EtOAc; 2 L), and the EtOAc
layer was evaporated in vacuo (crude extract 184.7 mg). Thin Layer Chromatography was carried
out (Merck TLC Silica Gel 60 RP-C 18 F 254S glass plates 20 x 20 cm) on the crude extract, with the
correct compound identified by UV visualization. A razor blade was used to scrape the silica
containing the product off the plate. The silica was placed in a fritted funnel and flushed with
EtOAc. The filtrate was collected and the solvent was removed in vacuo resulting in the isolation
of (2) (114.4 mg).
Detailed structural characterization
Compound 1 was isolated as a white amorphous powder. The molecular formula was found
to be C 8H 10O 2 by its
1
H NMR,
13
C NMR (Figures 3.13-3.15) and HRESIMS spectral data (Figure
3.12), representing four indices of hydrogen deficiency (IHD). The
1
H and
13
C NMR in CDCl 3
exhibited signals for three disubstituted olefins [δ H 5.67, 5.97, 6.37, 6.62, 7.15, and 7.18 (each
1H); δ C 116.0, 122.0, 126.0, 136.1, 138.7, 141.0], one carboxylic acid [δ H 10.87 (1H, br s); δ C 172.3],
and one methyl group [1.85 (3H, br d, J = 6.8 Hz)]. This together with the molecular formula of 1
indicated that 1 is a linear trienoic acid. 2D NMR correlations (
1
H-
1
H COSY, gHMQC and gHMBC)
also support the structure (data not shown). The double bond configurations were determined
to be 2Z, 4Z, and 6E based on the coupling constants of H-2 and H-3 (J = 11.3 Hz), H-3 and H-4 (J
= 11.1 Hz), and H-4 and H-5 (J = 14.6 Hz). Therefore, compound 1 was assigned as (2Z,4Z,6E)-octa-
2,4,6-trienoic acid.
Compound 2 was isolated as a colorless oil. The molecular formula was found to be C 10H 14O 6
from HRESIMS (Figure 3.12) and both
1
H and
13
C NMR data (Figures 3.13, and 3.16-3.17),
indicating 2 has four IHD.
13
C NMR spectrum of 2 exhibited one olefin (δ C 124.8 and 140.5) and
two ester or carboxylic acid carbonyl carbons (δ C 161.46 and 169.70) in the down-field region.
1
H,
13
C, gHSQC NMR spectra indicated compound 2 contains two methyl [δ H 1.36 (3H, d, J = 5.2
Hz), δ C 17.0 (q) and δ H 2.11 (3H, s), δ C 20.5 (q)] and four oxymethine groups [δ H 3.03 (1H, dd, J =
7.0, 2.1 Hz), δ C 54.9 (d); δ H 3.06 (1H, dq, J = 5.2, 2.1 Hz), δ C 54.5 (d); δ H 4.09 (1H, dd, J =7.2, 2.8

- 71 -

Hz), δ C 78.8 (d); and δ H 5.29 (1H, dd, J = 5.7, 2.8 Hz), δ C 62.1 (d)]. Because compound 2 has four
IHD but only contains one olefin and two ester or carboxylic acid carbonyl carbons, 2 must contain
a cyclic ether or an epoxide moiety. This, together with the fact that two oxymethine groups (δ H
3.03, δ C 54.8 and δ H 3.06, δ C 54.5) coupling to each other has a relatively high field chemical shift,
indicated that 2 has an epoxide functional group. HSQC and long-range HMBC correlations
allowed full assignment of the structure (Figure 3.13). Comparison of
1
H and
13
C NMR data of 2
with (+)-Asperlin in the literature
144
confirmed the identity of compound 2.
Figure 3.7: Correct coding sequence for afoA and corresponding amino acid sequence of its protein
product (AfoA). Intron sequences are shown in red.
M A C P T R R G R Q Q P G F A C E
ATGGCGTGTC CCACCAGACG AGGACGACAG CAGCCCGGCT TTGCATGCGA
1 ---------+ ---------+ ---------+ ---------+ ---------+ 50
E C R R R K A R C D R V R P K C G
GGAGTGTCGC CGCCGCAAAG CGCGCTGTGA TCGCGTGCGT CCGAAATGCG
51 ---------+ ---------+ ---------+ ---------+ ---------+ 100
F C T E N E L Q C V F V D K R Q
GGTTCTGCAC TGAGAATGAG CTGCAGTGTG TGTTCGTTGA CAAGAGGCAG
101 ---------+ ---------+ ---------+ ---------+ ---------+ 150
Q R G P I K G Q I T S M Q S Q L A
CAGAGGGGTC CGATCAAAGG GCAGATCACC TCGATGCAGT CGCAGCTGGG
151 ---------+ ---------+ ---------+ ---------+ ---------+ 200
TAGGTGTTTG TCTTGTCTCA TTGTATCTCG TCTCGTCTGC GCTTTTGTGA
201 ---------+ ---------+ ---------+ ---------+ ---------+ 250
TTATGGGGCT GCCATGTTTC CGGTCCGGAC ACAGGCATCT GCAAGGCCCG
251 ---------+ ---------+ ---------+ ---------+ ---------+ 300
CCGCTGTGCT CCCCCGATCT GCAGGGACCA ATGCAGCTGG TTCTGGAGCT
301 ---------+ ---------+ ---------+ ---------+ ---------+ 350
TGTGCTGTGC TGCTTCCCTG TCTTTCCACA TGGTCGAGTC GAGCGAGCTA
351 ---------+ ---------+ ---------+ ---------+ ---------+ 400
T L R W Q L D
GCTAACATGG GATGCCTCAT GCTTTCAGCA ACGCTTCGAT GGCAGCTTGA
401 ---------+ ---------+ ---------+ ---------+ ---------+ 450
R Y L R H R P P P S I T M A G E L
TCGATACCTG CGACATCGAC CTCCCCCGTC CATAACCATG GCCGGCGAGC
451 ---------+ ---------+ ---------+ ---------+ ---------+ 500
D E P P A D I Q T M L D D F D V
TCGATGAGCC ACCAGCGGAT ATCCAGACGA TGCTGGATGA CTTTGATGTA
501 ---------+ ---------+ ---------+ ---------+ ---------+ 550
Q V A A L K Q D A T A T T T M S T
CAGGTCGCCG CGCTGAAGCA GGATGCCACG GCAACCACCA CAATGTCGAC
551 ---------+ ---------+ ---------+ ---------+ ---------+ 600
S T A L M P A P A I S S K D A A P
GTCGACAGCT CTCATGCCTG CCCCAGCCAT CTCATCTAAA GATGCTGCTC
601 ---------+ ---------+ ---------+ ---------+ ---------+ 650

- 72 -

A G A G L S W P D P T W L D R Q
CTGCTGGTGC TGGTTTATCG TGGCCTGACC CAACCTGGCT GGATCGCCAG
651 ---------+ ---------+ ---------+ ---------+ ---------+ 700
W Q D V S S T S L V P P S D L T V
TGGCAGGATG TCAGCAGTAC CAGCCTCGTC CCTCCATCAG ACCTGACAGT
701 ---------+ ---------+ ---------+ ---------+ ---------+ 750
S S A T T L T D P L S F D L L N E
CTCGTCGGCC ACTACCCTAA CCGACCCTCT CAGCTTCGAC CTTTTGAACG
751 ---------+ ---------+ ---------+ ---------+ ---------+ 800
T P P P P S T T T T T S T T R R
AGACTCCTCC TCCTCCTTCT ACGACGACAA CAACGTCGAC GACGAGGCGA
801 ---------+ ---------+ ---------+ ---------+ ---------+ 850
D S C T K V M L T D L I R A E L
GACTCATGTA CTAAGGTCAT GTTAACTGAC CTCATCCGGG CTGAATTGTA
851 ---------+ ---------+ ---------+ ---------+ ---------+ 900
CACTACCTAA CTGATTTGTC TACCATGACA CCTGACTGAC AATGTGCAGA
901 ---------+ ---------+ ---------+ ---------+ ---------+ 950
D Q L Y F D R V H A F C P I I H R
GACCAACTCT ACTTCGACCG GGTCCACGCC TTCTGCCCCA TCATCCACCG
951 ---------+ ---------+ ---------+ ---------+ ---------+ 1000
R R Y F A R V A R D S H T P A Q A
GCGACGGTAC TTTGCGCGGG TCGCCCGAGA TAGCCATACC CCAGCACAGG
1001 ---------+ ---------+ ---------+ ---------+ ---------+ 1050
C L Q F A M R T L A A A M S A H
CATGTCTGCA GTTCGCCATG CGAACGCTCG CAGCGGCAAT GTCTGCTCAC
1051 ---------+ ---------+ ---------+ ---------+ ---------+ 1100
C H L S E H L Y A E T K A L L E T
TGCCATCTTA GCGAGCATCT CTATGCCGAG ACCAAGGCCC TCTTGGAGAC
1101 ---------+ ---------+ ---------+ ---------+ ---------+ 1150
H S Q T P A T P R D K V P L E H I
GCACAGCCAG ACGCCCGCCA CACCGCGAGA CAAGGTCCCG CTCGAGCACA
1151 ---------+ ---------+ ---------+ ---------+ ---------+ 1200
Q A W L L L S H Y E L L R I G V
TCCAGGCCTG GCTGTTGTTA AGCCACTACG AGCTGCTGCG GATCGGCGTG
1201 ---------+ ---------+ ---------+ ---------+ ---------+ 1250
H Q A M L T A G R A F R L V Q M A
CACCAGGCTA TGCTCACGGC TGGCCGGGCC TTTCGTCTCG TGCAGATGGC
1251 ---------+ ---------+ ---------+ ---------+ ---------+ 1300
R L S E L D A G S D R Q L S P P S
ACGACTGTCA GAGCTGGATG CCGGGTCAGA TCGACAGCTC TCGCCGCCGT
1301 ---------+ ---------+ ---------+ ---------+ ---------+ 1350
S S P P S S L T L S P S G E N A
CTTCGTCGCC GCCGTCTTCG CTAACCCTAT CTCCTTCGGG GGAGAATGCT
1351 ---------+ ---------+ ---------+ ---------+ ---------+ 1400
E N F V D A E E G R R T F W L A Y
GAGAACTTCG TCGACGCCGA AGAAGGCCGG CGGACGTTCT GGCTTGCTTA
1401 ---------+ ---------+ ---------+ ---------+ ---------+ 1450
C F D R L L C L Q N E W P L T L Q
TTGCTTTGAT CGTTTGCTTT GCTTGCAGAA TGAGTGGCCG TTAACGTTAC
1451 ---------+ ---------+ ---------+ ---------+ ---------+ 1500
E E M
AAGAAGAGAT GGTACGTCGC GCTTCTTTTA TTCTATTTAC CTCAGAATTT
1501 ---------+ ---------+ ---------+ ---------+ ---------+ 1550

- 73 -

I L T R L P
ATATTCAGTT ATTTTTTATT CTAACCCTGC TAGATATTAA CCCGCCTCCC
1551 ---------+ ---------+ ---------+ ---------+ ---------+ 1600
S L E H N Y Q N N L P A R T P F L
CTCCCTCGAA CACAACTACC AGAACAATCT CCCCGCACGC ACGCCCTTTC
1601 ---------+ ---------+ ---------+ ---------+ ---------+ 1650
T E A M A Q T G Q S T M S P F A
TCACTGAAGC CATGGCCCAG ACCGGGCAGA GCACAATGTC CCCGTTTGCC
1651 ---------+ ---------+ ---------+ ---------+ ---------+ 1700
E C I I M A T L H G R C M T H R R
GAATGCATTA TCATGGCCAC CCTTCACGGC CGATGTATGA CGCACCGCCG
1701 ---------+ ---------+ ---------+ ---------+ ---------+ 1750
F Y A N S N S T A S G S E F E S G
CTTCTACGCA AACAGCAACT CGACTGCGTC CGGCTCCGAG TTCGAGTCTG
1751 ---------+ ---------+ ---------+ ---------+ ---------+ 1800
A A T R D F C I R Q N W L S N A
GCGCCGCGAC GCGAGACTTC TGTATCCGCC AGAATTGGCT GTCGAATGCA
1801 ---------+ ---------+ ---------+ ---------+ ---------+ 1850
V D R R V Q M L Q Q V S S P A V D
GTGGACCGGC GAGTCCAGAT GCTACAGCAG GTCTCCTCGC CCGCTGTTGA
1851 ---------+ ---------+ ---------+ ---------+ ---------+ 1900
S D P M L L F T Q T L G Y R A T M
CAGCGACCCG ATGCTGCTCT TCACGCAGAC GCTCGGCTAC CGCGCGACCA
1901 ---------+ ---------+ ---------+ ---------+ ---------+ 1950
H L S D T V Q Q V S W R A L A S
TGCACCTGAG CGATACCGTC CAGCAAGTCT CCTGGCGGGC TCTCGCCAGC
1951 ---------+ ---------+ ---------+ ---------+ ---------+ 2000
S P V D Q Q L L S P G A T M S L S
TCGCCCGTTG ACCAGCAGCT ACTGAGCCCG GGCGCGACGA TGTCGCTGTC
2001 ---------+ ---------+ ---------+ ---------+ ---------+ 2050
A A A Y H Q M A S H A A G E I V R
GGCCGCCGCG TACCACCAGA TGGCCAGCCA CGCAGCCGGC GAGATCGTCC
2051 ---------+ ---------+ ---------+ ---------+ ---------+ 2100
L A K A V P S L S P F K A H P F
GCCTGGCGAA GGCCGTCCCC TCGCTGAGTC CGTTCAAGGC GCACCCGTTC
2101 ---------+ ---------+ ---------+ ---------+ ---------+ 2150
L P D T L A C A A T F L S T G S P
CTACCCGATA CGTTGGCGTG CGCCGCCACG TTCCTCTCGA CGGGCAGTCC
2151 ---------+ ---------+ ---------+ ---------+ ---------+ 2200
D P T G G E G V Q H L L R V L S E
CGATCCCACG GGCGGCGAGG GGGTGCAGCA TCTGCTACGA GTGTTAAGCG
2201 ---------+ ---------+ ---------+ ---------+ ---------+ 2250
L R D T H S L A R D Y L Q G L S
AGCTGCGCGA TACACACAGC CTGGCGCGGG ATTATTTGCA GGGGTTGTCG
2251 ---------+ ---------+ ---------+ ---------+ ---------+ 2300
V Q T Q D E D H R Q D T R W Y C T
GTGCAGACGC AGGACGAAGA TCATAGACAG GATACGAGGT GGTATTGTAC
2301 ---------+ ---------+ ---------+ ---------+ ---------+ 2350
ATAG
2351 ---- 2354
TATC

- 74 -

Figure 3.8: Corrected annotation of AN11200. Intron is shown in red.
ATGTTCTCAA GTACCCGGCG GGTAAGTAAC TCTTTCCATC ATCTGGCCCA TCTTCTTTTC TTTTTTGTTT TCAATTGTAA
GCTCTCGACT AACGACGCCC GGCACCTAGG CAGAAGGCCC CTGTGCAACC GAACTGACGC AGGTATCATC GCTGCTACCT
CCGCGCGGGC CATACGAGTT CAGCCTCCTG CCAACACTCA CTCGACCGTT AGAGGACCTC TCGAAATGCA TCGAAGGTGC
GAGACAGACC TCTGCGACTG CAAATGGTTA CAGCCCCACA GGGCTCGTCC CGCTAGCGGA TTCGATTCTG GAAATCTGTC
AGGCTGCTTG TACAGCTTAT GGTCTTGTTG ACGGTGCTAT TGCTGCAGGT GTGGGTACAG GAAGCAGTGA TAATAGCCCT
ACTGCCACAG GAATAGGAGC AGCAGGACTT ACAGGAGACC GCCCCTCCTC TTCCGGCGCA TCGACCTGGC GCTGTGTAAA
AACCCCCATG ACGCTGGGAT CGCTTACGCT ACAGAATGAA GAAGAGTCGC TGCTCGCAAG GCAGATCGTG TACGCCGTGT
TGACAAGCTT GAGCGCATTA CTGCGAGAAG TTTATGTTCG AGAGAAGGAC GTTGTTTCAG AGACTGATGT GGTGGGGGAA
GGAGGGGTAG GAGCTGGAGC GGCACTGTAT GGGCGTGAAG GGGCTGGAGC CGTTAGTCAG TGTCTCTCGA GGGTTTTAGC
GCTCTTGGGA AAGATAGTAC CTGAGTGA

Figure 3.9: CAGE RNA-seq data showing the transcription start site for alnR. The AspGD gene models for
AN11192 and AN9221 are shown. Blue genes are transcribed right to left and orange genes are transcribed
left to right. In CAGE RNA-seq the 5’ cap structures of mRNAs are captured and used for library
construction. Sequencing of the library reveals transcription start sites. The CAGE RNA-seq library used in
the current study was made from a mixture of mRNAs from two sources, wild-type hyphae cultured for
one day at 37ºC in liquid glucose minimal medium and hyphae carrying a deletion of the mcrA gene grown
for four days at 37ºC in liquid glucose minimal medium. Deletion of mcrA upregulates many genes
including secondary metabolism genes.
38
Deletion of mcrA did not upregulate the (+)-asperlin cluster but
there were enough reads in the region of the gene annotated as AN9221 to allow us to determine the
transcription start site. The CAGE RNA-seq reads are shown as blue or orange lines below the gene models.
The great majority of the reads in AN9221 map to the beginning of what was annotated as the third exon.
This result indicates that the third exon is a separate transcription unit (i.e. gene). These and additional
RNA-seq data reveal that AN9221 is actually two genes that we are now designating alnR and alnG.

- 75 -

Figure 3.10: Coding sequence of alnR along with predicted amino acid sequence. The position of the
Zn(II)2Cys6 zinc binuclear cluster DNA-binding domain is underlined with the cysteine residues in bold.

M S T V N Q S S T R S E L A G N W
1 ATGAGCACGG TGAACCAATC TTCCACGCGT TCAGAGCTAG CCGGTAACTG 50

E R L R K S C D T C Q E A K V K C
51 GGAACGCCTG CGCAAGTCCT GCGATACCTG TCAGGAGGCC AAGGTCAAAT 100

S Q H K P S C H R C L R H R Q P
101 GCAGTCAACA CAAGCCGTCC TGCCACCGAT GCCTTCGACA TCGTCAGCCC 150

C V Y S P Q R R S G R P P K R P S
151 TGCGTCTACA GCCCGCAACG TCGGTCGGGA CGTCCTCCCA AGAGGCCCAG 200

P S S R L G P E S N N S G D D I H
201 TCCCTCCAGT CGCTTAGGAC CTGAATCAAA CAATTCCGGA GATGACATTC 250

N E N T I Q R T N L N A N D S A
251 ACAATGAAAA CACCATACAG CGAACGAATC TAAATGCCAA TGACTCTGCC 300

M T D A G A V D P R V L T G D F A
301 ATGACTGACG CCGGGGCAGT CGATCCCCGG GTGCTAACCG GCGACTTCGC 350

A S T G I D P V D D I F Q T S F E
351 CGCAAGTACT GGCATAGATC CTGTCGACGA TATCTTCCAA ACATCCTTTG 400

S F L A A S L S P K G G L L P G
401 AATCCTTCCT CGCAGCCTCA TTGTCTCCTA AAGGTGGACT CCTGCCAGGA 450

S H S N P T T P N G F S M N S P S
451 TCTCATAGCA ATCCAACCAC ACCCAACGGC TTCTCGATGA ATTCGCCCTC 500

I T D P F G A F P F L I T D H N L
501 CATCACTGAT CCATTCGGCG CCTTTCCGTT TCTCATAACG GACCACAACT 550

P I A A L S S H V P P I D Q L P
551 TGCCTATCGC CGCGCTCTCA TCGCATGTTC CTCCAATTGA TCAGCTACCC 600

V L S T G A S N T S S E C G D C G
601 GTACTAAGCA CCGGAGCCTC AAATACAAGC AGCGAGTGCG GCGACTGCGG 650

A K C Y S S L L Q H L L F L R Q T
651 TGCGAAGTGC TACAGCTCAC TATTACAGCA CCTTTTGTTC CTCCGCCAGA 700

L P E S T R P S I D V I M Q A E
701 CGCTCCCCGA GTCCACCAGG CCATCAATAG ACGTGATAAT GCAGGCTGAG 750

G H V R A L L D R V L G C N A C L
751 GGCCATGTGC GTGCTTTACT TGATCGGGTA TTAGGCTGCA ACGCATGCCT 800

- 76 -

G N R S S I L L I S A I T E R I V
801 TGGCAATCGG TCGTCTATCC TGCTCATATC AGCGATAACA GAGCGCATAG 850

Q M L D W I I E E K T L L D T E
851 TCCAGATGTT AGACTGGATC ATCGAGGAGA AGACTCTTTT GGATACCGAG 900

N M R Y N R R T F S S W G R P P R
901 AATATGCGTT ACAACCGACG AACGTTTAGT TCATGGGGTC GCCCTCCCCG 950

L P P H G L N G M R R N V C H V S
951 GTTACCACCT CATGGCCTTA ATGGTATGCG GAGGAACGTC TGCCACGTTT 1000

L R V G N T E L D E D A K Q Y F
1001 CACTTCGCGT GGGTAATACT GAATTGGATG AGGACGCCAA ACAGTATTTT 1050
L K N F I L L R L K K L A V K V Q

1051 CTTAAGAATT TCATTTTGCT TCGACTAAAG AAACTCGCAG TTAAGGTGCA 1100

E V R R T A T T R P G D C I Y R A
1101 GGAAGTGCGA CGGACAGCTA CCACCCGTCC TGGCGATTGC ATATACCGCG 1150

A E L V L A D S I Q R L D Y L R
1151 CTGCGGAATT GGTGCTGGCG GATTCGATTC AACGACTGGA TTATCTTCGT 1200

G Q C Q L W E *
1201 GGCCAGTGTC AGTTATGGGA GTGA 1224

Figure 3.11: Coding sequence of alnG and amino acid sequence of its predicted product. The intron is
shown in red.

M T R Q I P L L A L S W L E L I F
1 ATGACGCGGC AAATCCCGCT CCTAGCGCTA TCGTGGCTTG AATTGATTTT 50

F S C Y Y G G L A G L G Y H S L W
51 CTTCAGCTGC TACTACGGCG GACTAGCGGG ACTGGGATAC CATTCCCTCT 100

R I A L R R R N V A P A I K S V
101 GGAGGATTGC ACTTCGCCGA AGGAATGTGG CACCCGCTAT CAAGTCTGTT 150

L Q T G R F A D G T P L T R R Y T
151 CTGCAGACTG GGCGCTTTGC GGATGGAACG CCCCTAACGC GCCGGTATAC 200

N L E F L D K K L V P A V I F Y D
201 TAACTTGGAA TTTTTGGATA AGAAATTGGT TCCTGCGGTA ATCTTCTACG 250

G L L T G A C P L Y R L L L V D
251 ACGGATTGTT GACTGGAGCA TGCCCACTTT ATCGCTTGTT ACTGGTGGAC 300

- 77 -

I H S T M Q A M A L C M L V S T R
301 ATCCATTCGA CCATGCAAGC GATGGCACTC TGCATGCTTG TCAGCACCAG 350

S K S L S T I S L L
351 ATCCAAGTCG TTATCGACTA TATCTTTGCT GTGAGTCGGG TCCTTCTGCC 400

L P T
401 TTTGAGTATA ACGAAGCTCT AATAATCTAC CGAGGGACAG CTTGCCAACT 450

F W N V F N Q F Y G A A F V Y P L
451 TTTTGGAATG TCTTCAACCA GTTTTACGGT GCTGCCTTCG TCTACCCCCT 500

Y L L L E A V T T G F N P L Y P V
501 CTACCTCTTA TTAGAGGCAG TAACGACTGG CTTTAACCCT CTGTATCCGG 550

E T E T S R S A L L V S A M I G
551 TCGAGACCGA GACATCTCGT TCTGCGTTAC TGGTGAGCGC TATGATCGGC 600

S F L P F T F L W P A F L R S G T
601 TCTTTTTTAC CGTTCACCTT TCTCTGGCCA GCTTTTCTTC GGTCTGGCAC 650

E S R Q R A I A L Y R F A P V V F
651 GGAGAGCCGA CAACGTGCTA TTGCATTATA CCGATTTGCT CCGGTAGTGT 700

S L L Q I V G E K V L G A Q M I
701 TCTCACTTCT GCAGATTGTT GGAGAGAAGG TGCTGGGCGC GCAGATGATC 750

P Q P T S Q A S P Y L V A G C A A
751 CCTCAGCCAA CTTCTCAGGC TAGCCCTTAT TTGGTTGCCG GCTGCGCTGC 800

T V G H W Y A L G G A L G L A M R
801 CACAGTGGGG CATTGGTACG CTCTTGGGGG AGCTTTAGGT CTCGCCATGC 850

L S H R K G R L G A L T L V L K
851 GGCTGTCTCA CAGAAAGGGC CGCTTGGGGG CTCTCACCTT AGTCCTCAAA 900

R L Y L P R S A E E T T R L D A S
901 CGGCTTTATC TGCCTCGCTC GGCTGAAGAA ACTACTCGCT TGGACGCCTC 950

V L A R A A H E F L Q Y D V L V L
951 TGTACTCGCT CGCGCAGCGC ACGAATTTCT GCAATACGAT GTCCTCGTGC 1000

I A A Y I P Y A Y Y L L A P L N
1001 TCATTGCAGC TTATATTCCG TACGCATACT ATCTGCTCGC GCCCCTCAAT 1050

L A S P F A M V V S L V L G T I F
1051 CTGGCATCGC CCTTTGCGAT GGTTGTGTCC CTTGTACTTG GCACCATTTT 1100

L G P G A V L A F A Y R V R W H L
1101 TTTAGGGCCG GGGGCGGTTC TGGCTTTCGC GTACCGGGTT CGCTGGCATC 1150

A I S D *
1151 TAGCTATCTC AGATTAG 1167

- 78 -

Figure 3.12: HRESIMS spectra of (2Z,4Z,6E)-octa-2,4,6-trienoic acid (1) (negative mode) and (+)-asperlin
(2) (positive mode).

- 79 -

Figure 3.13: (2Z,4Z,6E)-octa-2,4,6-trienoic acid (1) and (+)-asperlin (2)
1
H and
13
C assignments.

- 80 -

Figure 3.14:
1
H NMR of (2Z,4Z,6E)-octa-2,4,6-trienoic acid (1) in CDCl 3 (400 MHz).

- 81 -

Figure 3.15:
13
C NMR of (2Z,4Z,6E)-octa-2,4,6-trienoic acid (1) in CDCl 3 (100 MHz).

- 82 -

Figure 3.16:
1
H NMR of (+)-asperlin (2) in CDCl 3 (400 MHz).

- 83 -

Figure 3.17:
13
C NMR of (+)-asperlin (2) in CDCl 3 (100 MHz).

- 84 -

Chapter 4 is incorporated from Grau, M. F., Entwistle, R., Chiang, Y.-M., Ahuja, M., Oakley, C. E., Akashi,
T., Wang, C. C. C., Todd, R. B., Oakley, B. R. Hybrid transcription factor expressing strains help to elucidate
the (+)-asperlin biosynthetic pathway, which is currently in preparation for submission to Chemical
Science.
The author has made the most contributions to this study. Dr. R. Entwistle and C. E. Oakley engineered
the hybrid transcription factor expressing strains. Dr. Y. M. Chiang assisted in NMR structural
characterization of the (+)-asperlin intermediates.

Chapter 4
Hybrid transcription factor expressing
strains help to elucidate the (+)-asperlin
biosynthesis pathway

4.1 Abstract
Earlier efforts to activate a silent secondary metabolite biosynthetic gene cluster containing
a highly reducing PKS (alnA) in A. nidulans involved the engineering of a hybrid transcription
factor consisting of a DNA binding domain from the cluster specific transcription factor, alnR, and
a highly active activation domain from the asperfuranone transcription factor, afoA. Expression
of the hybrid transcription factor resulted in the production of (+)-asperlin. Considering the anti-
inflammatory, antitumor, and antibiotic activities demonstrated by (+)-asperlin, we were curious
whether any intermediates produced during the biosynthesis of (+)-asperlin also had any

- 85 -

interesting known bioactivities. Using targeted gene deletions in the hybrid transcription factor
expressing strain, we isolated and characterized the intermediates and shunt products involved
in the biosynthesis of (+)-asperlin in significant quantities. We discovered a strong insecticidal,
herbicidal, antibiotic (+)-phomalactone that is produced as an intermediate in (+)-asperlin
biosynthesis. Here we demonstrate the success of using hybrid transcription factor expressing
strains to isolate intermediates of a silent secondary metabolite gene cluster. Our results allowed
us to deduce the biosynthesis of (+)-asperlin and assign the function of each individual gene in
the (+)-asperlin biosynthetic gene cluster.
4.2 Introduction
Filamentous fungi are excellent producers of a vast range of diverse chemical compounds
known as secondary metabolites (SMs). The production of SMs increases ecological fitness by
providing a means to compete with other species in the environment.
113,165,166
The antibiotic,
antifungal, herbicidal, insecticidal and other activities demonstrated by SMs have led to a
growing interest into these bioactive compounds by the pharmaceutical and agricultural
industries.
167
The genes encoding the enzymatic activities necessary to produce a SM are grouped
together within the fungal genome and are known as biosynthetic gene clusters (BGCs). Recent
advances in genome sequencing and bioinformatic algorithms have resulted in a significant
increase in the number of publicly available annotated genomes, revealing that the SM
production potential is far greater than the number of compounds currently known to be
produced by filamentous fungi.
17,77,132,133
This knowledge has led to a revitalization of efforts to
develop strategies to stimulate expression of these gene clusters that are silent under normal
growth conditions.
168

Cultivation-based approaches to activate silent gene clusters include culturing the fungus on
various types of media
111,169
or coincubating the fungus with other microorganisms.
87,169

Technologies based on genetic engineering have also had success in activating silent gene cluster,
and some of these include; regulatable promoter exchange of SM biosynthesis genes,
22,25

heterologous expression of entire silent gene clusters under the control of regulatable

- 86 -

promoters,
40,170,171
manipulating the expression of genes involved in chromatic packing,
33,138
and
deletion of, overexpression of, or mutations in regulatory genes such as mcrA and laeA that
control the expression of multiple SMBGCs.
38,39,117
Available genome information suggests that
roughly 60% of SMBGCs contain a putative transcription factor that regulates the expression of
all the genes within the cluster. Activation of a pathway-specific regulator is a method that has
worked very well in some cases,
9,57,140
but the approach often fails. Upregulation of the pathway-
specific transcription factor of eighteen SMBGCs in Aspergillus nidulans was successful in three
cases, but for the other BGCs, no detectable amount of compound was produced.
25
There are
many explanations for the failure of this approach. It is possible that an unknown natural inducer
is required to achieve strong activation, or that the activity of the transcription factor is inhibited
by a post-translational modification.
141

In earlier work we demonstrated an approach in which we engineered a hybrid transcription
factor that could not be inhibited by a post-translational modification and would not require an
unknown inducer to activate the expression of an entire BGC.
172
This hybrid transcription factor
targeted a silent SMBGC containing the highly reducing polyketide synthase gene, alnA, and a
cluster-specific transcription factor, alnR, in A. nidulans. Previous efforts to activate the aln
cluster by upregulating alnR were unsuccessful,
25
so we initially replaced the promoters of alnA,
and a nearby esterase gene, alnB, resulting in the production of (2Z,4Z,6E)-octa-2,4,6-trienoic
acid (1).
172
To overexpress the entire aln gene cluster and produce the final product of this
pathway, we exploited the domain modularity of transcription factors and fused the DNA binding
domain of alnR to the activation domain of a highly active transcription factor, afoA from the
asperfuranone gene cluster in A. nidulans. We placed the hybrid transcription factor under the
control of the alcA promoter, and in inducing conditions, we observed the upregulation of genes,
alnA-alnI, and the production of the pathway product, the anti-inflammatory, antitumor,
antibiotic, (+)-asperlin.
143–147,172

We previously generated hybrid transcription factor expressing single gene deletion strains
for alnA-alnI to confirm the boundaries of the (+)-asperlin BGC.
172
In this work, we analyzed the
1
H NMR and HPLC-MS traces of the crude extracts from gene deletion strains for the production

- 87 -

of intermediates or shunt products. We performed large-scale cultivations on several of the
deletion strains and obtained ample amounts (150-400 mg) of various intermediates and shunt
products that we isolated and characterized by spectroscopic methods. In combination with
bioinformatic analyses of the aln gene functions, we have proposed a biosynthetic pathway for
(+)-asperlin.
4.3 Results and Discussion
4.3.1 Identification, purification and structural elucidation of intermediates and
shunt products from hybrid transcription factor expressing single gene deletion
strains
A schematic diagram of the aln gene cluster and the putative function of each gene is included
in Table 4.1 and Figure 4.1. The genes required for the synthesis of (+)-asperlin (2) include alnA-
alnI, since the deletion of these genes either abolished or greatly reduced the production of (+)-
asperlin.
172
Using the hybrid transcription factor expressing strain as the recipient strain, single-
gene deletions were generated for alnA-alnI
172
(Table 4.2). While the conjugated double bonds
in the HR-PKS product, (2Z,4Z,6E)-octa-2,4,6-trienoic acid (1) make the compound detectible by
the diode array detector (DAD), the detection of (+)-asperlin (2) or the intermediates/shunt
products by DAD or TIC is less obvious (Figure 4.5 and 4.6). In order to clarify if the less obvious
HPLC profile obtained was due to the insensitivity or the low yield of the intermediates/shunt
products in the (+)-asperlin (2) biosynthesis pathway, besides analyzing the culture medium by
HPLC-DAD-MS, we also took the
1
H NMR of the crude extract from each single-gene deletion
strain (Figure 4.6-4.11). While the HPLC-DAD-MS data of each deletion strains showed less
obvious peaks detected, signals from
1
H NMR of the crude extract clearly indicated one or two
major metabolites from each deletion strains with good yield. Strains carrying deletions of five
individual genes, alnD, alnF, alnG, alnH, and alnI, accumulated detectable intermediates or shunt
products (Figure 4.2), and these strains were subjected to large-scale cultivation. The culture
media for each scale-up was extracted with an equal amount of ethyl acetate, the target
compounds were isolated by semi-preparatory HPLC, and their structures elucidated from NMR
(Figure 4.3 and 4.12-4.19) and HRESIMS data. Only a 1 L culture of each scaled-up deletant strain

- 88 -

was required to generate more than enough of each isolated compound (150-400 mg) to obtain
NMR, indicating the benefits of using a hybrid transcription factor to upregulate the production
of both pathway final products and pathway intermediates.
Among the isolated compounds were three -lactones, one -lactone and a linear trienoic
acid: the alnD deletant yielded (2Z,4Z,6E)-octa-2,4,6-trienoic acid
172
(1), (+)-phomalactone
173
(3)
and catenioblin A
174
(5) were isolated from the alnF deletant, both (+)-phomalactone
173
(3) and
(+)-acetylphomalactone
145
(4) were isolated from the alnH and alnI* deletants, and musacin
Gene
Amino acids
(base pairs)
Protein homologue, origin
(NCBI accession number)
Similarity/
identity (%)
Proposed function
alnA 458 (7700) LovF, Aspergillus terreus (Q9Y7D5) 58/41 Highly-reducing PKS
alnB 284 (935)
MMYC01_200221, Madurella
mycetomatis (KXX83199)
61/43 Esterase
alnC 452 (1406)
HK57_00312, Aspergillus ustus
(KIA75907)
60/45
NADH-cytochrome b5
reductase
alnD 533 (1733)
HK57_00311, Aspergillus ustus
(KIA75906)
92/86 Cytochrome P450
alnE 553 (2132) AflT, Aspergillus parasiticus (AY371490) 48/27
MFS membrane
transporter
alnF 415 (1732)
SirH, Leptosphaeria maculans
(XP_003842428)
41/24 Acetyltransferase
alnG 368 (1104)
HK57_00309, Aspergillus ustus
(KIA75904)
85/80 Hypothetical Protein
alnR 407 (1224) AflR, Aspergillus fumigatus (XP_753610) 69/59
Zn(II)Cys6 transcription
factor
alnH 560 (3485) FtmE, Aspergillus fumigatus (Q4WAW8) 46/30 Cytochrome P450
alnI 219 (895)
AFUA_5G10300, Aspergillus fumigatus
(XP_753611)
55/42 Hypothetical protein
Table 4.1: Putative functions of genes within the (+)-asperlin gene cluster and their homologs.

Figure 4.1: Organization of the aln gene cluster in A. nidulans. Each arrow indicates the direction of
transcription and relative sizes of the ORFs deduced from analysis of nucleotide sequences.

- 89 -

D
175
(6) was isolated from the alnG deletant. The production of these metabolites has been
discovered in Paecilomyces, Streptomyces, Nigrospora, and Aspergillus species
145,172–177
, but the
biosynthesis of (+)-asperlin remain uncertain.
Based on the molecular weight of metabolites identified from each deletion strains, we
analyzed the extracted ion current (EIC) in the positive-mode at m/z 139, 155, 157, 197 and 213
for the deletion strains (Figure 4.2). The deletion of alnA, alnB, and alnC* lacked production of
any detectable compounds, and the deletion of alnE, a putative MFS membrane transporter,
produced the same compounds as the parent hybrid transcription factor expressing strain,
however at much lower levels (Figure 4.2).

Figure 4.2: MS analysis of the intermediates and shunt products generated by hybrid transcription
factor expressing (alcA(p)_HyTF) single aln gene deletion strains. The positive mode extracted ion
currents (EICs) measured include m/z 213 (grey), 139 (red), 155 (blue), 157 (yellow), and 197 (green).
Structures and molecular weights of compounds 1-6 are provided.*

- 90 -

4.3.2 Proposed biosynthesis of (+)-asperlin
Earlier work has already established that AlnA and AlnB are necessary to produce and release
the HR-PKS product, (2Z,4Z,6E)-octa-2,4,6-trienoic acid (1).
172
Here we show that five genes, alnD,
alnF, alnG, alnH, and alnI* are required for the conversion of (2Z,4Z,6E)-octa-2,4,6-trienoic acid
(1) to (+)-asperlin (2), and we were able to deduce the steps of the biosynthetic pathway from
the intermediates/shunt products identified. Deletion of alnH and alnI* resulted in the
accumulation of (+)-phomalactone (3) and (+)-acetylphomalactone (4), indicating that AlnH, a
putative cytochrome P450 monooxygenase, and AlnI*, a hypothetical protein, are required for
the conversion of 3 or 4 to 2. The alnF deletion strain accumulates 3 and catenioblin A (5), but
not 4, indicating that AlnF, a putative acetyltransferase, is required for the acetylation of 3 to 4,
and that AlnH and AlnI are both required for the epoxidation of 4 to 2 (Figure 4.3). (+)-
Phomalactone (3) has been reported to exhibit broad biological activities, including antibacterial,

Figure 4.3: Proposed biosynthetic pathway for (+)-asperlin (2) and related shunt products. All natural
products isolated from this study are indicated by shaded boxes. Brackets and unshaded structures
indicate hypothetical parts of the pathway.*

- 91 -

insecticidal, herbicidal, and antifungal
173,177,178
. Since no other deletions resulted in the
production of 5, catenioblin A (5) could be a shunt product of (+)-phomalactone (3) when it builds
up inside the cell, with the reduction of the double bond catalyzed by an enzyme outside of the
(+)-asperlin (2) gene cluster to reduce the toxicity to the fungus.
The accumulation of musacin D (6) was observed in the alnG deletion strain. The difference
between 3 and 6 is the size of the lactone ring present in the molecule which results from a 6-
endo and 5-exo cyclization, repectively
179,180
. In the absence of AlnG, the 5-exo cyclization
product 6 is the dominant product following Baldwin’s rules. The conversion of the same
upstream intermediate into 6-endo product 3 requires the presence of AlnG. We observe the
accumulation of (2Z,4Z,6E)-octa-2,4,6-trienoic acid (1) in the remaining alnD deletion strain, and
since AlnD is a putative cytochrome P450 monooxygenase, we propose that AlnD catalyzes the
epoxidation of 1 to form an unstable epoxide intermediate which is readily converted into the 5-
exo cyclization product in the absence of alnG. (Figure 4.3). Thus, when alnG is intact, the likely
function of the hypothetical protein, AlnG, is to convert the epoxide into the kinetically
unfavorable 6-endo-tet cyclization product, compound 3 (Figure 4.3).
4.4 Conclusion
Earlier work focused on engineering a hybrid transcription factor expressing A. nidulans strain
that could overexpress all the genes within the aln gene cluster. Expression of this hybrid
transcription factor resulted in the production of (+)-asperlin which was believed to be the final
product of the pathway. A series of hybrid transcription factor expressing gene deletion strains
were screened for (+)-asperlin production, helping to establish the boundaries of the gene
cluster, alnA-alnI. In this work, we identified the intermediates and shunt products generated by
various aln deletions, while bioinformatics data helped to assign putative functions to several aln
gene protein products. The combined data allowed us to propose a biosynthetic pathway for (+)-
asperlin that is initiated by the production of the alnA HR-PKS product, (2Z,4Z,6E)-octa-2,4,6-
trienoic acid.

- 92 -

4.5 Methods
4.5.1 Fermentation and HPLC-DAD-MS analysis
For all strains, 3 x 10
7
spores were grown in 30 mL lactose minimum media (LMM) (15 g L
-1
D-
lactose, 6 g L
-1
NaNO 3, 0.52 g L
-1
KCl, 0.52 g L
-1
MgSO 47H 2O, 1.52 g L
-1
KH 2PO 4, and 1 mL L
-1
Hutner’s
trace element solution
181
), and, where appropriate, supplemented with 0.5 mg L
-1
pyridoxine,
and 2.5 mg L
-1
riboflavin, in 125 mL flasks at 37 °C with shaking at 180 rpm. For alcA(p) induction,
50 mM of MEK was added to the culture 42 h after inoculation
132
. Culture media were collected
72 h after induction by filtration and 10 μL was injected for HPLC-DAD-MS analysis as previously
described
108
.
LC-MS spectra were obtained using a ThermoFinnigan LCQ Advantage ion trap mass
spectrometer with a reverse phase C 18 column (Alltech Prevail C 18; particle size, 3 μm; column,
2.1 by 100 mm) at a flow rate of 125 μL min
-1
. The solvent gradient for LC-MS was 5% MeCN–H 2O
(solvent A) and 95% MeCN–H 2O (solvent B), both of which contained 0.05% formic acid, as
follows: 100% solvent A from 0 to 5 min, 0 to 25% solvent B from 5 min to 6 min, 25% to 100%
solvent B from 6 to 35 min, 100% solvent B from 35 to 40 min, 100% to 0% solvent B from 40 to
45 min, and re-equilibration with 100% solvent A from 45 to 50 min. Conditions for MS included
a capillary voltage of 5.0 kV, a sheath gas flow rate at 60 au, an auxiliary gas flow rate at 10 au,
and the ion transfer capillary temperature at 350 °C.
4.5.2 Isolation and purification of metabolites
The LO9721 (alcA_HyTF), LO11156 (alcA_HyTF _alnD ), LO11192 (alcA_HyTF _alnF ),
LO11293 (alcA_HyTF _alnG -alnR ), LO11298 (alcA_HyTF _alnH ), and LO11302 (alcA_HyTF
_alnG ) strains were each cultivated in 1 L of LMM (see above for media recipe) with the required
supplements at 37 °C with shaking at 180 rpm. For alcA(p) induction, 50 mM of MEK was added
to the culture 42 h after inoculation
132
. Culture medium were collected 72 h after induction by
vacuum filtration and extracted twice with a volume of EtOAc equal to the culture volume. The
combined EtOAc layers were evaporated in vacuo. The major compounds from the crude extract

- 93 -

were separated by preparative HPLC [Phenomenex Luna 5 μm C 18 (2), 250 x 21.2] with a flow rate
of 5.0 mL min
-1
and measured by a UV detector at 230 nm.
4.5.3 Compound spectral data
NMR spectral data were collected on a Varian Mercury Plus 400 spectrometer. High
resolution electrospray ionization mass spectra (HRESIMS) were obtained on ThermoScientific Q
Exactive hybrid quadrupole-Orbitrap mass spectrometer with an Eclipse XDB-C 18 column (Agilent
5 μm 4.6 x 150 mm) at a flow rate of 125 μL min
-1
. Conditions for MS included a spray voltage of
3.5 kV, sheath gas flow rate 20 au, auxiliary gas flow rate at 5 au, sweep gas flow rate at 1 au,
capillary temperature at 275 °C, s-lens RF level 55, auxiliary gas heat temperature at 325 °C, scan
range of 100-600 m/z, resolution 140,000, AGC target 3 x 10
6
, and maximum injection time of
200 ms.
(+)-Phomalactone (3): Colorless oil;
1
H NMR (CDCl 3, 400MHz) see Table S2;
13
C NMR (CDCl 3,
400MHz) see Table S2; ESIMS spectra (positive) see Figure S1; HRESIMS obtained m/z [M + H] =
155.0658 (calcd 155.0708 for C 8H 10O 3).
(+)-Acetylphomalactone (4): Colorless oil;
1
H NMR (CDCl 3, 400MHz) see Table S2;
13
C NMR
(CDCl 3, 400MHz) see Table S2; ESIMS spectra (positive) see Figure S1; HRESIMS obtained m/z [M
+ H] = 197.0786 (calcd 197.0813 for C 8H 10O 3).
Catenioblin A (5): Colorless oil;
1
H NMR (CDCl 3, 400MHz) see Table S2;
13
C NMR (CDCl 3,
400MHz) see Table S2; ESIMS spectra (positive) see Figure S1; HRESIMS obtained m/z [M - H] =
155.0712 (calcd 155.0708 for C 8H 10O 3).
Musacin D (6): Colorless oil;
1
H NMR (CDCl 3, 400MHz) see Table S2;
13
C NMR (CDCl 3, 400MHz)
see Table S2; ESIMS spectra (positive) see Figure S1; HRESIMS obtained m/z [M + H] = 155.0692
(calcd 155.0708 for C 8H 10O 3).
*NOTE: Prior to publication, our collaborators realized there was an issue with the alnC and alnI
deletion strains. It is possible that the alnC deletion removed most of the promotor of alnB,
essentially deleting alnB. The same thing may have occurred for the alnI deletion. We are
currently re-making these strains and they will be re-screened for intermediate production.

- 94 -

4.6 Supporting Information

Table 4.2: Strains used in this study

Strain Genotype Ref
FGSC442 facB101, riboB2, chaA1, sE15, nirA14 Fungal Genetics
Stock Center
LO1362 pyroA4, riboB2, pyrG89, nukA∆::argB [
119
]
LO8030 pyroA4, riboB2, pyrG89, nukA::argB, stc(AN7804-AN7825)Δ, eas(AN2545-AN2549)Δ, afo(AN1036-
AN1029)Δ, mdp(AN10023-AN10021)Δ, tdi(AN8513-AN8520)Δ, aus(AN8379-AN8384, AN9246-AN9259)Δ,
ors(AN7906-AN7915)Δ, apt(AN6000-AN6002)Δ
[
120
]
LO9721 yA::AtpyrG-alcA(p)AN9221(250-652)::afoA(130-666)* in LO8030 This work
LO11280-LO11283 yA::AfpyrG-alcA(p)alnR in LO8030 This work
LO11156-LO11159 alnD∆::AfriboB in LO9721 This work
LO11160-LO11163 alnE∆::AfriboB in LO9721 This work
LO11178-LO11180 alnA∆::AfriboB in LO9721 This work
LO11181-LO11183 alnB∆::AfriboB in LO9721 This work
LO11192-LO11195 alnF∆::AfriboB in LO9721 This work
LO11261-LO11265 alnC∆::AfriboB in LO9721 This work
LO11288-LO11292 alnH∆::AfriboB in LO9721 This work
LO11293-LO11297 AN9221(alnG-alnR)∆::AfriboB in LO9721 This work
LO11302-LO11306 alnI∆::AfriboB in LO9721 This work
* an ATG start codon was inserted; AN9221(250-652) was reannotated as AlnR(5-407)

- 95 -

Table 4.3: NMR spectroscopic data (400 MHz, CDCl 3) for compounds 3-6.

- 96 -

Figure 4.4: ESIMS (positive mode) spectra of compounds 3-6.

- 97 -

Figure 4.5: Total scan PDA traces of the hybrid transcription factor expressing parental strain and
intermediate-producing deletion strains.

- 98 -

Figure 4.6: TIC traces of the hybrid transcription factor expressing parental strain and intermediate-
producing deletion strains.

- 99 -

Figure 4.7:
1
H NMR spectrum of the LO11157 (alnDΔ) crude extract in CDCl 3 (400 MHz).

- 100 -

Figure 4.8:
1
H NMR spectrum of the LO11293 (alnGΔ) crude extract in CDCl 3 (400 MHz).

- 101 -

Figure 4.9:
1
H NMR spectrum of the LO11192 (alnFΔ) crude extract in CDCl 3 (400 MHz).

- 102 -

Figure 4.10:
1
H NMR spectrum of the LO11289 (alnHΔ) crude extract in CDCl 3 (400 MHz).

- 103 -

Figure 4.11:
1
H NMR spectrum of the LO11302 (alnIΔ) crude extract in CDCl 3 (400 MHz).

- 104 -

Figure 4.12:
1
H NMR spectrum of (+)-phomalactone (3) in CDCl 3 (400 MHz).

- 105 -

Figure 4.13:
13
C NMR spectrum of (+)-phomalactone (3) in CDCl 3 (100 MHz).

- 106 -

Figure 4.14:
1
H NMR spectrum of (+)-acetylphomalactone (4) in CDCl 3 (400 MHz).

- 107 -

Figure 4.15:
13
C NMR spectrum of (+)-acetylphomalactone (4) in CDCl 3 (100 MHz).

- 108 -

Figure 4.16:
1
H NMR spectrum of catenioblin A (5) in CDCl 3 (400 MHz).

- 109 -

Figure 4.17:
13
C NMR spectrum of catenioblin A (5) in CDCl 3 (100 MHz).

- 110 -

Figure 4.18:
1
H NMR spectrum of musacin D (6) in CDCl 3 (400 MHz).

- 111 -

Figure 4.19:
13
C NMR spectrum of musacin D (6) in CDCl 3 (100 MHz).

- 112 -

Chapter 5 is incorporated from Grau, M. F., Yuan, B., Chen, S. A., Stajich J.E., Torok, T., Hsueh, Y. P., Wang,
C. C. C. Discovery of the biosynthetic pathway for the antifungal hymeglusin in Scopulariopsis candida,
which is currently in preparation for submission to Organic Letters.
The author has made the most contributions to this study. B. Yuan assisted in plasmid construction. Dr. Y.
P. Hsueh and S. Chen performed the whole-genome sequencing on IMV00968. Genome annotation and
analysis was conducted by J. E. Stajich. Strains were provided by Dr. T. Torok.

Chapter 5
Discovery of the biosynthetic pathway
for the antifungal hymeglusin in
Scopulariopsis candida

5.1 Abstract
Filamentous fungi are prolific producers of bioactive secondary metabolites (SMs) which we
exploit for human health. Fungi from extreme environments are a great resource of interesting
SMs, some of which help them thrive in harsh conditions. Among their many bioactivities, SMs
can be powerful antifungal agents. Recent collective efforts have focused on developing
antifungals that target invasive yeasts such as Candida, as these species have become major
threats to susceptible patients. This work details our efforts to screen a library of irradiated,
Chernobyl nuclear accident-associated, fungal strains for their activity against Candida albicans.

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One of the most potent strains demonstrating anti-Candida activity was Scopulariopsis candida
IMV00968 which was found to produce significant levels of the HMG-CoA synthase inhibitor,
hymeglusin. The antimicrobial activity of hymeglusin has previously been reported, yet no group
has identified the its biosynthesis genes. Whole-genome sequencing data for IMV00968 were
collected, assembled, and annotated. SM prediction then revealed 21 putative biosynthetic gene
clusters within the genome. Our detailed analysis showed one polyketide synthase gene cluster
included an HMG-CoA synthase gene, and we predicted this to be the cluster responsible for
hymeglusin production. CRISPR/Cas9 technology facilitated deletions of genes encoding a
polyketide synthase (hmnA), an HMG-CoA synthase (hmnB), and a cytochrome P450
monooxygenase (hmnC) that were all necessary for hymeglusin production. These experiments
lay the foundation for additional characterization of the hymeglusin biosynthetic pathway and
identification of intermediates with antifungal activity.
5.2 Introduction
Candida albicans is an opportunistic fungus that can be deadly in immunocompromised
patients. Candida yeasts are very invasive species; some strains of Candida demonstrate
mortality rates up to 70%.
182
Despite major advances in antifungal therapies, only a limited
number of drugs, which are associated with toxicity and resistance, are available. The resulting
efforts to discover antifungals with anti-Candida activity are widespread.
183–185

Within their natural environments, microorganisms have evolved to compete for resources
through the production of natural products (also known as secondary metabolites (SMs)) capable
of killing or inhibiting the growth of their competition.
1,186
Bioactive SMs have been exploited for
thousands of years due to their medicinal properties, and today, more than 60% of approved
small molecule drugs are either natural products themselves or derived thereof.
14
Fungi are
responsible for the production of many clinically used antibiotics, antifungals, antivirals, and
immunotherapies.
184,187–189
Notably, fungi from extreme environments have been a great source
of novel natural products.
190–194
Through genetic and epigenetic modifications, fungi that thrive
survive in extreme habitats develop strategies to grow, reproduce, and adapt.
195,196
Some of

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these modifications manifest in the production of new SMs or the enhanced production of known
valuable compounds.
Over 2,000 fungal isolates that grew in extremely high levels of radiation were collected from
the Chernobyl Nuclear Power Plant Exclusion Zone in Ukraine by our collaborator, Dr. Tamas
Torok and associates, from the Lawrence Berkeley National Laboratory. With access to this library
of extremophilic fungi, we selected over 150 strains to screen for anti-Candida activity. We
analyzed the metabolic profiles of 23 strains exhibiting a range of C. albicans growth inhibition
and observed the production of a known antifungal metabolite, hymeglusin (1), from one of the
most potent isolates against C. albicans, Scopulariopsis candida strain IMV00968. Researchers
have explored hymeglusin’s bioactivity in numerous experiments.
197–212
Hymeglusin is a specific
β-lactone inhibitor of eukaryotic 3-hydroxy-3-methylglutary coenzyme A (HMG-CoA) synthase, a
key enzyme involved in cholesterol biosynthesis. Hymeglusin inhibits HMG-CoA synthase through
covalent modification of the Cys
129
residue in the enzyme active site through the formation of a
thioester adduct.
197,202,213,214

Although hymeglusin production has been reported in Cephalosporium
215
, Scopulariopsis,
and Fusarium
207,211,212
species, the biosynthetic gene cluster for this metabolite has yet to be
described. Rapid advancements in genome sequencing have resulted in the production of fast,
easy, and cost-effective whole genome sequencing (WGS) platforms. We sequenced the genome
of S. candida IMV00968 using paired-end sequencing on an Illumina platform and the reads were
de novo assembled. Annotation of the assembled genome and prediction of putative SM gene
clusters were performed using bioinformatic tools. We predicted the hymeglusin cluster based
on the inclusion of an HMG-CoA synthase resistance gene. Additionally, through a comparative
genomic analysis of a known hymeglusin-producing species, F. solani, we identified a gene cluster
with high homology to the cluster found in S. candida. We developed a transformation protocol
and used CRISPR/Cas9 technology to target genes of interest in S. candida IMV00968 to confirm
this cluster was involved in hymeglusin biosynthesis. We successfully targeted three predicted
hmn-cluster genes for deletion; a putative highly-reducing polyketide synthase (HR-PKS) (hmnA),
a putative HMG-CoA synthase (hmnB), and a putative cytochrome P450 monooxygenase (hmnC).

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Out metabolic analysis of the deletion strains revealed an elimination of hymeglusin production.
We propose a negative feedback mechanism that suppresses hymeglusin biosynthesis upon
deletion of hmnB.
5.3 Results and Discussion
5.3.1 Anti-Candida activity observed by Scopulariopsis candida IMV00968
We screened over 150 fungal strains isolated from regions surrounding the Chernobyl nuclear
powerplant disaster for antifungal activity against C. albicans ATCC 90028. We selected these
strains, designated by IMV (Institute of Microbiology and Virology- Kiev, Ukraine) strain numbers,
for screening from the collection of over 2,000 isolates based on their SM production potential.
For speciation of IMV strains, we used classical cell and colony morphology-based identification
techniques and ITS (internal transcribed spacer) region sequencing. We then conducted agar-
plug diffusion tests to select for IMV isolates with antifungal activity against C. albicans.
216,217
This
involved cultivating IMV strains on both YES and YAG media for 4 days, and then transferring a
plug to the surface of a 3 cm Mueller Hinton Agar (MHA) plate pre-inoculated with C. albicans.
We observed zones of inhibition after 48 h of incubation, and 23 of the 150 screened IMV isolates,
presented with anti-Candida activity. From cocultures and monocultures of hit strains, we
extracted metabolites and analyzed them by HPLC-DAD-MS. One of the most potent fungal
isolates against C. albicans ATCC 90028 was Scopulariopsis candida strain IMV00968 when
cultivated on YES media (coculture screen presented in Figure 5.1A), which we selected for
further analysis. Our comparison of the coculture (data not shown) and monoculture HPLC traces
(Figure 5.1C) suggests that no additional metabolites were induced during the co-incubation,
indicating the monoculture was sufficient to produce the antifungal metabolites. To confirm this,
we cultivated IMV00968 on a large-scale using YES media, and metabolites were extracted from
the agar plates. We tested this crude extract for anti-Candida activity using the disk diffusion
method (Figure 5.1B).
218
Disks containing 50 μg of crude extract were added to a 3 cm plate that
we pre-inoculated with C. albicans. The zone of inhibition we observed after 48 h indicated the
potency of IMV00968’s crude extract (Figure 5.1B).

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HPLC-MS analysis revealed the production of two major metabolites; compound 1 (mw: 324)
and compound 2 (mw: 342). A database search for compounds produced by S. candida, revealed
the putative identity of compound 1 to be hymeglusin (Figure 5.1D) based on the molecular
weight, UV spectrum
219
, and bioactivity data
208
. First discovered in Cephalosporium sp.
215
and
later in Fusarium and Scopulariopsis sp.
207
, hymeglusin (1233A, F-244, or L-659699) is an
antimicrobial β-lactone which inhibits an enzyme involved in an early step of cholesterol
biosynthesis, 3-hydroxyl-3-methylglutaryl coenzyme A (HMG-CoA) synthase.
206–209
Inhibitory
Figure 5.1: Anti-Candida activity observed by Scopulariopsis candida IMV00968 results from the
production of the antimicrobial hymeglusin. (A) Coculturing screening of S. candida IMV00968 against
Candida albicans ATCC 90028. (B) Anti-Candida activity observed from a disk containing 50 μg of a
metabolic extract from S. candida IMV00968. (C) Metabolic diode array detector (DAD) total scan HPLC
profiles of S. candida IMV00968 culture extract. (D) Structures of the major compounds produced by
S. candida IMV00968; Hymeglusin (1), Fusaridioic acid A (2).

- 117 -

activity results from the formation of a thioester adduct to a cysteine in the active site of the
HMG-CoA synthase enzyme.
202
The antimicrobial activity of hymeglusin has been reported in
several species of bacteria and fungi, including C. albicans (MIC: 12.5 μg ml
-1
).
208

A recent study observed the production of hymeglusin and novel alkenoic acid derivatives
like fusaridioic acid A, from the marine-derived fungus, F. solani H915.
211,212
We proposed the
identity of compound 2 to be fusaridioic acid A (Figure 5.1D) based on molecular weight and UV
spectrum identity. We concluded that both S. candida IMV00968 and F. solani H915 must contain
the biosynthetic genes required to produce hymeglusin and related alkenoic acids; however, the
hymeglusin BGC has yet to be reported.
5.3.2 Identification of the putative hymeglusin gene cluster in IMV00968
To identify the hymeglusin BGC in S. candida IMV00968, we performed whole genome
sequencing (WGS) and used paired-end reads in de novo genome assembly. We used
funannotate (v1.5.0-760de7c)
220
for annotation of the assembled genome and AntiSMASH
(v.4.1.0)
21
for SMBGC prediction. AntiSMASH predicted 21 putative SMBGCs in the S. candida
genome. Based on the structure of hymeglusin, we hypothesized it was the product of a PKS-
containing gene cluster. Of the 21 gene clusters, 5 of them contained a putative PKS as the
backbone enzyme. Since its structure has fully reduced ketides, we expected the hymeglusin PKS
to contain reductive domains. We noticed such domains in the PKSs of cluster 2, 5, and 18.
Further analysis of the genes surrounding these PKSs revealed that cluster 5 contains a gene
encoding a putative HMG-CoA synthase. We anticipated that cluster 5 was likely to be the BGC
for hymeglusin based on the hypothesis that the HMG-CoA synthase gene was co-expressed with
hymeglusin biosynthesis genes as a resistance mechanism against the antifungal activity of the
metabolite.
Considering that F. solani H915 produces hymeglusin, we were interested in identifying a F.
solani gene cluster homologous to cluster 5 in IMV00968. Although the F. solani H915 genome
has not been sequenced, an annotated genome for the F. solani strain FSSC 5 v1.0 was publicly
available from the Joint Genome Institute (JGI) database. We BLASTed the putative amino acid
sequence of the PKS gene, IMV00968_008082, against FSSC 5 v1.0. The top hit had high homology

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(Table 5.1); both genes contain enoyl reductase, dehydratase, and β-ketoacyl reductase domains
characteristic of HR-PKSs. The two genes directly downstream from the HR-PKS in S. candida,
IMV00968_008083 and IMV00968_008084, encoded a putative HMG-CoA synthase and a
Gene
IMV00968_XXXXXX
Amino acids
(base pairs)
Fusarium solani FSSC 5 v1.0
homologues (Protein ID)
Similarity/
identity (%)
Proposed function
008080 1159 (4353)

Hydrolase
008081 265 (1222)

Hypothetical protein
008082
(hmnA)
3993 (11011) 389943 87/80 HR-PKS
008083
(hmnB)
475 (1691) 533856 93/82 HMG-CoA synthase
008084
(hmnC)
302 (1263) 533855 89/78 Cytochrome P450
008085 522 (1568)

Hypothetical protein
008086 202 (1590)

Hypothetical protein
Table 5.1: Putative functions of genes within the Scopulariopsis candida IMV00968 hymeglusin gene
cluster and their Fusarium solani FSSC 5 v1.0 homologues

Figure 5.2: Putative hymeglusin gene clusters in S. candida IMV00968 (top) and F. solani FSSC 5 v1.0
(bottom). Hymeglusin biosynthesis genes are given hmn gene designations. Predicted gene functions
are provided; red: HR-PKS, blue: cytochrome P450 monooxygenase, green: HMG-CoA synthase,
yellow: transcription factor, grey: gene not involved in hymeglusin biosynthesis.

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putative cytochrome P450 monooxygenase. In F. solani, there too were genes proximal to the
HR-PKS that encoded a putative HMG-CoA synthase and a putative cytochrome P450
monooxygenase. These genes presented with high homology to the corresponding genes in S.
candida (Table 5.1). No other genes surrounding the HR-PKS in S. candida had homology to genes
in F. solani. The putative hymeglusin BGCs in S. candida IMV00968 and F. solani FSSC 5 v1.0 are
shown in Figure 5.2. The only discrepancy we observed between these two clusters was the
inclusion of a regulatory gene in F. solani that was not present in the S. candida gene cluster.
5.3.3 CRISPR/Cas9 facilitated gene disruptions help to confirm the hymeglusin gene
cluster boundaries
To confirm cluster 5 was responsible for hymeglusin production, we developed a
transformation protocol and a CRISPR/Cas9 based system for targeted genetic modifications in
S. candida IMV00968. This system facilitated the efficient deletion of the putative HR-PKS gene
IMV00968_008082, designated as hmnA. Our analysis of the hmnAΔ strain’s metabolite profile
revealed that hymeglusin (1) and fusaridioic acid A (2) production was eliminated, along with the
production of many additional metabolites likely related to or involved in hymeglusin
biosynthesis (marked with *, Figure 5.3). These data confirmed our hypothesis that hmnA is the
HR-PKS necessary for hymeglusin production.
Based on the homology of the predicted proteins in the S. candida IMV00968 and F. solani
FSSC 5 v1.0 putative hymeglusin gene clusters (Table 5.1 and Figure 5.2), we next targeted the
gene encoding a predicted HMG-CoA synthase (IMV00968_008083) and a predicted cytochrome
P450 monooxygenase (IMV00968_008084) for deletion using CRISPR/Cas9. Although the
putative hydrolase enzyme encoded by gene IMV00968_008080, was not homologous to any
predicted proteins surrounding the hymeglusin HR-PKS in F. solani FSSC 5 v1.0, we deleted this
gene for to confirm it was not involved in hymeglusin biosynthesis. Additional genes encoding
hypothetical proteins surrounding the HR-PKS in IMV00968 were not disrupted because they
lacked any conserved domains characteristic of known proteins involved in SM biosynthesis

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and there was no homology between these hypothetic proteins and those encoded by genes
surrounding the hymeglusin HR-PKS in F. solani.
Metabolite profile analysis of the deletion strains confirmed that IMV00968_008083 and
IMV00968_008084, designated as hmnB and hmnC, were involved in hymeglusin biosynthesis
after the compound could not be detected in the hmnBΔ and hmnCΔ strains (Figure 5.3).
Fusaridioic acid A (2) production was eliminated by the deletion of the putative cytochrome P450
gene, alnC, and reduced by 80% with the deletion of the putative HMG-CoA synthase gene, hmnB
(Figure 5.3). Additionally, the peaks representing predicted hymeglusin-related metabolites
(marked with *, Figure 5.3) could not be detected when hmnB and hmnC were deleted. One
potential intermediate of hymeglusin biosynthesis, compound 3, could be detected in the wild-
Figure 5.3: Metabolic DAD total scan HPLC profiles of S. candida IMV00968 wild-type (WT) and single
gene deletion strains. IMV00968_008082 (hmnA): putative HR-PKS; IMV00968_008083 (hmnB):
putative HMG-CoA synthase; IMV00968_008084 (hmnC): putative cytochrome P450 monooxygenase;
IMV00968_008080: putative hydrolase.

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type (WT) and hmnCΔ strains. Future efforts will focus on characterizing compound 3 to better
understand the stepwise biosynthesis of hymeglusin (1). The putative hydrolase gene is likely not
involved in hymeglusin production since the metabolite profile of the IMV00968_008080
deletion strain is nearly identical to the WT strain. Taken together, these data provide strong
evidence that the hymeglusin BGC in S. candida IMV00968 includes three genes, hmnA, hmnB,
and hmnC, that must all be functional to observe hymeglusin production.
Since the putative product of hmnB, an HMG-CoA synthase, is likely not involved in the
biosynthesis of hymeglusin, but produced as a resistance mechanism, we initially predicted that
the hmnBΔ strain would still produce hymeglusin when cultivated in hymeglusin-producing
conditions but with inhibited growth. The absence of hymeglusin and suppressed fusaridioic acid
A levels in addition to the normal growth patterns observed by the hmnBΔ deletion strain
compared to the WT strain indicated our initial assumption was incorrect. The data instead
suggest that the deletion of hmnB suppresses the expression of hmnA and hmnC, which are
necessary to produce hymeglusin and related metabolites. This hypothesis implies that negative
feedback from the deletion of hmnB prevents the expression of hymeglusin biosynthesis genes
when the strain is grown in hymeglusin-producing conditions. Future work will involve the
collection and analysis of RNAseq data to support this hypothesis.
5.4 Conclusion
23 strains of irradiated fungi isolated from the Chernobyl Nuclear Power Plant Exclusion Zone
presented with antifungal activity against C. albicans ATCC 90028. One of the most potent hit
strains, S. candida IMV00968, was found to produce the antimicrobial compound, hymeglusin, a
known HMG-CoA synthase inhibitor. We performed WGS of IMV00968 in the interest of
identifying the hymeglusin BGC and discovering related antifungal metabolites produced by this
pathway. From the annotated IMV00968 genome, 21 SMBGCs were predicted and further
analysis revealed that 1 of the 5 PKS gene clusters contained a putative HMG-CoA synthase gene
that could serve as a resistance mechanism against hymeglusin production. We established the
hymeglusin BGC through CRISPR/Cas9 targeted deletions of three genes, encoding a PKS (hmnA),

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HMG-CoA synthase (hmnB), and a cytochrome P450 (hmnC). Each deletant abolished hymeglusin
production. Since the hmnB deletion strain prevents hymeglusin production, we propose that the
absence of this enzyme in hymeglusin-producing conditions results in negative feedback
preventing the expression of hymeglusin biosynthesis genes.
5.5 Methods
5.5.1 Isolation and identification of the IMV isolates
IMV strains were isolated from soil samples collected in regions of Ukraine surrounding the
Chernobyl nuclear powerplant disaster. These strains were kindly provided by Dr. Tamas Torok
at the Lawrence Berkeley National Laboratory who collected the isolates and characterized the
species through cell and colony morphology-based identification techniques and ITS region
sequencing.
5.5.2 Coculture screening of IMV strains
We performed antimicrobial tests for selected IMV strains against C. albicans ATCC 90028
using the agar plug diffusion method.
216,217
IMV strains were incubated on YES (20 g L
-1
yeast
extract, 100 g L
-1
sucrose, 15 g L
-1
agar, and 1 ml L
-1
Hutner’s trace element solution
131
) and YAG
(5 g L
-1
yeast extract, 20 g L
-1
D-glucose, 15 g L
-1
agar, and 1 ml L
-1
Hutner’s trace element
solution
131
) plates inoculated with 1.0  10
7
spores per 10-cm plate at 26 °C. After 4 days, we cut
an agar plug (7 mm diameter) with a sterile 1 ml pipette tip and transferred it to the center of a
3 cm well containing 7.5 ml of MHA with 2% D-glucose (2 g L
-1
beef extract, 17.5 g L
-1
casein acid
hydrolysate, 20 g L
-1
D-glucose, 1.5 g L
-1
starch, and 17.5 g L
-1
agar) previously inoculated with 60
μl of a fresh C. albicans suspension at OD 600 = 0.4. We measured Inhibition halos after 48 h of
incubation at 26 °C. IMV monocultures were incubated alongside the cocultures for the full
duration of 6 days for LC-MS comparison to the cocultures.
5.5.3 Disk-diffusion test with IMV00968 culture extract
We performed antimicrobial tests against C. albicans ATCC 90028 with the crude extract of
IMV00968 using the disk diffusion method.
221
To obtain the crude extract, a large-scale

- 123 -

cultivation was performed by incubating IMV00968 on 1 L of YES media (see recipe above) plates
inoculated with 1.0  10
7
spores per 10 cm plate at 26 °C for 5 days. After incubation, we cut up
the agar and sonicated in MeOH for 1 h followed by 1 h of sonication in 1:1 DCM-MeOH. Both
extracts were combined, and the organic layer was evaporated. We extracted the residue twice
with EtOAc and evaporated the combined EtOAc extracts in vacuo to yield the crude extract. 10
μl of a 2.5 g L
-1
solution of crude extract dissolved in MeOH was pipetted onto an autoclaved filter
paper disk (5 mm diameter). Once dry, we transferred the disk to the center of a 3 cm well
containing 7.5 ml of MHA with 2% D-glucose (see recipe above) we previously inoculated by the
pour plate technique with 130 μl of a fresh C. albicans suspension at OD 600 = 0.2. We measured
inhibition halos after 48 h of incubation at 26 °C.
5.5.4 HPLC-DAD-MS analysis
For HPLC-DAD-MS analysis of IMV monocultures and IMV00968 deletion strains, we cut out
three plugs (7 mm diameter) after incubation and transferred them to a 7 ml screw-cap vial. The
material was extracted with 3 ml of MeOH followed by 3 ml of 1:1 DCM-MeOH with 1 h of
sonication. We then transferred the extract to a clean vial and evaporated the solvent by
TurboVap LV (Caliper LifeSciences). In 5 ml of EtOAc and 5 ml of water, we re-dissolved the
residues, collecting the EtOAc layer and evaporating the solvent by TurboVap LV. We re-dissolved
the crude extract in 0.3 ml of DMSO:MeOH (1:4) and injected 10 μl into the HPLC-DAD-MS for
analysis as previously described
99
.
For cocultures, following incubation we cut up the 3 cm agar well (including the agar disk)
and transferred to a 40 ml glass vial. We extracted the material with 20 ml of MeOH followed by
20 ml of 1:1 DCM-MeOH with 1 h of sonication. We then transferred the extract to a clean vial
and evaporated the solvent by TurboVap LV (Caliper LifeSciences). We re-dissolved the residues
in 5 ml of EtOAc and 5 ml of water, collected the EtOAc layer, and evaporated the solvent by
TurboVap LV. We re-dissolved the crude extract in 0.3 ml of DMSO:MeOH (1:4) and injected 10
μl into the HPLC-DAD-MS for analysis as previously described
99
.

- 124 -

We used a ThermoFinnigan LCQ Advantage ion trap mass spectrometer with a reverse phase
C 18 column (Alltech Prevail C 18; particle size, 3 μm; column, 2.1 by 100 mm) at a flow rate of 125
μL min
-1
for HPLC-DAD-MS spectra. The solvent gradient for LC-MS began with 5% MeCN–H 2O
(solvent A) and 95% MeCN–H 2O (solvent B), both of which contained 0.05% formic acid, follows:
100% solvent A from 0 to 5 min, 0 to 25% solvent B from 5 min to 6 min, 25% to 100% solvent B
from 6 to 35 min, 100% solvent B from 35 to 40 min, 100% to 0% solvent B from 40 to 45 min,
and re-equilibration with 100% solvent A from 45 to 50 min. Conditions for MS included a
capillary voltage of 5.0 kV, a sheath gas flow rate of 60 arbitrary units, an auxiliary gas flow rate
of 10 arbitrary units, and an ion transfer capillary temperature at 350 °C.
5.5.5 Genome sequencing, assembly, and annotation of IMV00968
We prepared the IMV00968 DNA for whole genome sequencing (WGS) using the Illumina
TruSeq DNA PCR free HT library preparation kit and quantified with the KAPA library
quantification kit. We sequenced generated libraries with 150 bp paired-end sequencing
protocols on the Illumina NextSeq 500 platform. The library of reads was converted into a FASTQ
using Illumina package Bcl2fastq 2.17. We filtered the data for high-quality vector- and adaptor-
free reads for the genome assembly using Qiagen CLC Genomics Workbench (cutoff read length
for high quality 80%; cutoff quality score, 20), and 26,488,726 vector-filter reads were obtained
after quality check. De novo assembly used high-quality vector-filtered reads with the CLC
Genomics Workbench genome assembler. The final assembly consisted of 961 scaffolds with a
total size of 30,633,635 bp. There was no random “N” joining of the contigs to maintain high
assembly quality. Quality check of the final assembly was performed using the CLC Genome
Finishing Module. The number of N’s detected was less than 9 per 100 kb, which represents a
very good assembly. The assembled genome was annotated using funannotate (v1.5.0-
760de7c)
220
and then analyzed by AntiSMASH (v.4.1.0)
21
which predicted 21 putative SMBGCs in
the S. candida genome.

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5.5.6 CRISPR-Cas9 plasmid construction
Our collaborators from the Mortensen lab, who have kindly provided us with plasmids
pFC332 and pFC334 for this experiment, have recently described a plasmid-facilitated
CRISPR/Cas9 system for filamentous fungi
222
. We selected 20-nucleotide protospacers (Table
5.2) for targeting putative hymeglusin biosynthesis genes. Protospacers were immediately
upstream PAM sequences (NGG), and generally located within exons near the N-terminus of the
protein. Then we created the sgRNA cassettes specific for targeting genes of interest by PCR
amplification of overlapping fragments 1 and 2 (Figure 5.5) with primers containing the 20-
nucleotide protospacer and 6-nucleotide ribozyme inverted repeat overlapping the end of the
protospacer. The primers used to generate fragments 1 and 2 for each of the CRISPR/Cas9
targeting constructs are included in Table 5.3. We combined fragments 1 and 2 with PacI(10 
CutSmart buffer, New England Biolabs, Ipswich, MA)-digested pFC334 to generate pFC334-
target-sgRNA plasmids with Gibson Assembly
223
Master Mix (New England Biolabs, Ipswich, MA)
(Figure X5.6). Assembled plasmids were transformed into DH5  E. coli, transformants were
analyzed by colony check PCR (Figure 5.7). Plasmids from correct transformants were propagated
and then subsequently purified (QIAprep Spin Miniprep Kit, QIAGEN) (Figure 5.8).
5.5.7 Protoplasting and transformation
6 50 ml of YES (20 g L
-1
yeast extract, 100 g L
-1
sucrose, and 1 ml L
-1
Hutner’s trace element
solution
131
) medium was inoculated with 1  10
8
spores of IMV00968 in a 250 ml flask and
incubated at 30 °C with shaking at 110 rpm for 16 h. Hyphae were harvested and
resuspended in 20 ml of freshly made 1  protoplasting solution (2 g of Vino Taste Pro
digestion enzyme was added to 20 ml of KCl, citric acid solution
128
) and incubated at 30 °C
with shaking at 100 rpm for 8 h. We separated protoplasts from undigested hyphae and
purified as previously described.
128
After resuspending the protoplast pellet in 400 μl of 0.6
M KCl, 50 mM CaCl 2, we transferred 100 μl aliquots into 4 sterile microcentrifuge tubes
(enough for 4 transformations).
7 We performed protoplast transformations directly following protoplast purification
(protoplasts lyse if stored at -80 °C). We thoroughly mixed 1 μg of plasmid DNA with 100 μl

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protoplast suspension by vortexing 3 times for 1 s at max speed. To this protoplast and
plasmid suspension, we added 50 μl of room temperature freshly filtered PEG solution
128
,
vortexed 3 times for 1 s at max speed, and placed on ice for 25 min. We then added 100 μl
more of the PEG solution to the protoplast suspension, mixed by gently pipetting up and
down, and left at room temperature for 25 min. We plated the transformed protoplasts using
the agar overlay method: the protoplast suspension was added to 12 ml of melted GMM (10
g L
-1
D-glucose, 6 g L
-1
NaNO 3, 0.52 g L
-1
KCl, 0.52 g L
-1
MgSO 4 7H 2O, 1.52 g L
-1
KH 2PO 4, 8 g L
-1

agar, and 1 ml L
-1
Hutner’s trace element solution
131
) supplemented with 0.6 M KCl and 0.4
g L
-1
hygromycin at 50 °C, mixed gently by inversion, and poured into a 10 cm plate. After
solidifying, we gently poured 16 ml of melted GMM supplemented with 0.6 M KCl and 0.4 g
L
-1
hygromycin at 50 °C on top of the first layer. We incubated plates at 30 °C; transformed
colonies were generally visible after 12-14 days. We re-streaked transformant colonies onto
5 cm GMM plates supplemented with 0.4 g L
-1
hygromycin and incubated at 30 °C for 5-6
days. After streaking onto 5 cm YES (see recipe above) plates, we incubated them for 5 days
at 26 °C. We performed HPLC-DAD-MS metabolite analysis for each transformant strain as
described above.

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7.1 Supporting Information

Figure 5.4: UV-Vis and ESIMS (positive and negative mode) spectra of hymeglusin (1), fusaridioic acid
A (2), and unknown (3).

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Figure 5.5: Agarose gel images of PCR amplified fragments 1 and 2 for Gibson Assembly with pFC334.
IMV00968_008082 (hmnA): putative HR-PKS; IMV00968_008083 (hmnB): putative HMG-CoA
synthase; IMV00968_008084 (hmnC): putative cytochrome P450 monooxygenase;
IMV00968_008080: putative hydrolase.
Figure 5.6: Agarose gel images of Gibson Assembly results for fragments 1 and 2 with pFC334. Bands
represent PCR amplified sgRNA region of pFC334 using primers pFC33X, Frag1 F and pFC33X, Frag2 R.
008082 (hmnA): putative HR-PKS; 008083 (hmnB): putative HMG-CoA synthase; 008084 (hmnC):
putative cytochrome P450 monooxygenase; 008080: putative hydrolase.

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Gene

IMV00968_XXXXXX

Protospacer sequence

PAM

Strand

GC %

008080

GAAGGGAACCAAGGCCGAGA

AGG

Sense

60

008082

GAGCCTTGAACGCATCGTAC

TGG

Antisense

55

008083

GAGCCATCGTCACGCCCGAC

CGG

Antisense

70

008084

CTCGCCCATCTTCATCCCAA

AGG

Sense

55

Figure 5.7: Colony check PRC arose gel images of an amplified region of pFC334 plasmids with gene-
specific sgRNA from E. coli DH5  transformants. Bands represent PCR amplified sgRNA region of
pFC334 using primers pFC33X, Frag1 F and pFC33X, Frag2 R. 008082 (hmnA): putative HR-PKS; 008083
(hmnB): putative HMG-CoA synthase; 008084 (hmnC): putative cytochrome P450 monooxygenase;
008080: putative hydrolase.
Figure 5.8: Agarose gel images of a PCR amplified region of propagated pFC334 plasmids containing
gene-specific sgRNA. Bands represent PCR amplified sgRNA region of pFC334 using primers pFC33X,
Frag1 F and pFC33X, Frag2 R. 008082 (hmnA): putative HR-PKS; 008083 (hmnB): putative HMG-CoA
synthase; 008084 (hmnC): putative cytochrome P450 monooxygenase; 008080: putative hydrolase.
Table 5.2: Protospacer sequences for genes targeted by CRISPR/Cas9 in S. candida IMV00968

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Primer name

Sequence (5’-3’)

Target

Purpose

pFC33X, Frag1 F

TCATAGCTGTTTCCGCTGA pFC334-Cas9 sgRNA vectors

GA: pFC33X-Cas9 targeting constructs

pFC33X, Frag2 R

ATTCTGCTGTCTCGGCTG pFC334-Cas9 sgRNA vectors

GA: pFC33X-Cas9 targeting construct

Sc008080, Frag1 R

TCTCGGCCTTGGTTCCCTTCGACGAGCTTACTCGTTTCGTCCTCACGGACTCATCAG
GAAGGGCGGTGATGTCTGCTCAAG
pFC334-Cas9 sgRNA vectors

GA: pFC334-Cas9-Sc008080 sgRNA

Sc008080, Frag2 F

TCGTCGAAGGGAACCAAGGCCGAGAGTTTTAGAGCTAGAAATAGCAAGTTAAA

pFC334-Cas9 sgRNA vectors

GA: pFC334-Cas9-Sc008080 sgRNA

Sc008082, Frag1 R

GTACGATGCGTTCAAGGCTCGACGAGCTTACTCGTTTCGTCCTCACGGACTCATCA

GGAGCCTCGGTGATGTCTGCTCAAG

pFC334-Cas9 sgRNA vectors

GA: pFC334-Cas9-Sc008082 sgRNA

Sc008082, Frag2 F

TCGTCGAGCCTTGAACGCATCGTACGTTTTAGAGCTAGAAATAGCAAGTTAAA

pFC334-Cas9 sgRNA vectors

GA: pFC334-Cas9-Sc008082 sgRNA

Sc008083, Frag1 R

GTCGGGCGTGACGATGGCTCGACGAGCTTACTCGTTTCGTCCTCACGGACTCATC

AGGAGCCACGGTGATGTCTGCTCAAG

pFC334-Cas9 sgRNA vectors

GA: pFC334-Cas9-Sc008083 sgRNA

Sc008083, Frag2 F

TCGTCGAGCCATCGTCACGCCCGACGTTTTAGAGCTAGAAATAGCAAGTTAAA

pFC334-Cas9 sgRNA vectors

GA: pFC334-Cas9-Sc008083 sgRNA

Sc008084, Frag1 R

TTGGGATGAAGATGGGCGAGGACGAGCTTACTCGTTTCGTCCTCACGGACTCATC

AGCTCGCCCGGTGATGTCTGCTCAAG

pFC334-Cas9 sgRNA vectors

GA: pFC334-Cas9-Sc008084 sgRNA

Sc008084, Frag2 F

TCGTCCTCGCCCATCTTCATCCCAAGTTTTAGAGCTAGAAATAGCAAGTTAAA pFC334-Cas9 sgRNA vectors

GA: pFC334-Cas9-Sc008084 sgRNA

Table 5.3: Primers used for plasmid construction
Gibson Assembly (GA), Protospacer, Hammerhead (HH) ribozyme, HH IR or IR’ in protospacer, gpdA gene, sgRNA backbone

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Chapter 6
Conclusions and perspectives

The work described in this dissertation was only possible due to past discoveries and
developments. Advances in genome sequencing and bioinformatic technologies have
revolutionized the fields of natural product drug discovery and fungal genetics. Better
understanding the fungal genome will unlock novel bioactive metabolites and drive the
discoveries of tomorrow. This thesis describes the ways we used and benefitted from the
innovative tools now available. Furthermore, we have contributed knowledge to the field and
have proposed new approaches to drive and to understand SM production.
Fungal SM gene regulation is a popular and established area of research. In chapter 2, we
examined the effects of overexpressing a gene encoding a putative positive regulator of SM
production in Aspergillus nidulans, LaeA-like methyltransferase G (LlmG). We discovered that

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llmG overexpression upregulates the production of SMs from several gene clusters. In addition,
combining llmG overexpression with the deletion of mcrA, a negative regulator of secondary
metabolism, further enhances SM production, sometimes considerably. We propose that the
combination of an mcrA deletion with additional strategies could elicit SM production for the
discovery of compounds naturally produced in minute amounts.
In chapters 3 and 4, we described the design and implementation of a synthetic hybrid
transcription factor that upregulated a silent SM gene cluster when expressed in A. nidulans. By
combining the DNA binding domain from the cluster-specific transcription factor with the strong
activation domain of the asperfuranone cluster transcription factor, we engineered a strain that
can produce the hybrid transcription factor. Expression of the hybrid transcription factor resulted
in the biosynthesis of the antibiotic (+)-asperlin, known to be produced by A. nidulans, but from
an unknown biosynthetic gene cluster. RNAseq data of the hybrid transcription factor expressing
strain established the boundaries of the (+)-asperlin and metabolic analyses of single-gene
deletion strains confirmed them. Isolation and characterization of the intermediates produced
by the deletion strains allowed us to propose the steps involved in (+)-asperlin production. This
is the first report of a fungal hybrid transcription factor design that successfully upregulates an
entire silent gene cluster. Preliminary data from our group show that this approach can be
successful for activating additional silent gene clusters in A. nidulans. Other groups can use this
approach to access their cryptic clusters of interest. This method could lead to new natural
products with interesting bioactivities fueling the drug discovery pipeline.
Many recent experiments have focused on discovering antifungals effective against drug-
resistant species. The work in chapter 5 details our efforts to explore antifungal natural product
drug discovery from fungi isolated from an extreme environment. We discovered a strain of S.
candida, IMV00968, that was a potent inhibitor of Candida albicans growth. Through metabolic
analysis, we found that this strain produced the antifungal hymeglusin. To identify the gene
cluster necessary for its biosynthesis, we sequenced and annotated the genome of S. candida
IMV00968. Analysis of the predicted gene clusters allowed us to establish a putative gene cluster
responsible for hymeglusin production. Using the recent CRISPR/Cas9 gene targeting technology,

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we successfully and efficiently deleted several genes to determine the hymeglusin cluster
boundaries. Future work will focus on discovering antifungal SMs from extremophilic fungi and
working out the biosynthesis of discovered compounds and hymeglusin.
While progress has taken us far in the field of fungal genetics and secondary metabolism,
there is still a great deal we have left to learn. The development of new tools and approaches to
manipulate the production of natural products will contribute to and are necessary for the
advancement of biomedical research and drug discovery. The work described in this thesis has
contributed to this endeavor and laid the foundation for future progress.

- 134 -

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Abstract (if available)

Abstract Natural products have been important in drug discovery from ancient history to modern-day. They are resources for compounds with functional and chemical diversity unsurpassed by any synthetic library. Secondary metabolites have been developed into many important commercial drugs ranging from antibiotics and antifungals to immunotherapies and cholesterol-lowering agents. ❧ Recent advancements in whole genome sequencing technologies have revolutionized research into fungal secondary metabolism. Genomes can be sequenced quickly and inexpensively due to next generation sequencing platforms, generating a wealth of publicly available fungal genomes. Genetic studies on fungi have established that the genes to produce a secondary metabolite are arranged contiguously within the genome, forming secondary metabolite biosynthetic gene clusters. The rapid development of bioinformatic algorithms that predict secondary metabolite gene clusters has shown that the potential for natural product drug discovery is much greater than we had anticipated. Most secondary metabolite gene clusters are unexpressed in normal laboratory conditions, prompting the development of techniques to access the fungal metabolome. ❧ The work described in this thesis details the approaches we have taken to understand secondary metabolite regulation, activate silent gene cluster expression, establish the genes necessary to produce a specific metabolite, and deduce the functions of the biosynthetic enzymes and proteins encoded by these genes. Chapter 1 is an overview of fungal secondary metabolites, emphasizing their importance in drug discovery, the enzymes involved, and the game-changing genomic and bioinformatic advances driving the production of these valuable compounds. ❧ Enzymes, known as ‘global’ or ‘master’ regulators, can influence the expression of multiple secondary metabolite gene clusters. In chapter 2, we genetically engineered strains of Aspergillus nidulans to overexpress one of these regulators, LlmG, resulting in the upregulation of several secondary metabolite gene clusters and the production of 30 different compounds. In chapters 3 and 4, we engineered a strain of A. nidulans to express a hybrid transcription factor that was cluster-specific and efficient at facilitating the transcription of the genes necessary to produce the antibiotic, (+)-asperlin. We established the genes involved in (+)-asperlin biosynthesis, characterized the accumulated intermediates from single-gene deletion strains, and proposed the biosynthetic steps required to produce this bioactive metabolite. Chapter 5 describes our efforts to characterize the genome of a radiation-exposed fungal isolate of Scopulariopsis candida that was collected from the Chernobyl Exclusion Zone and shown to inhibit Candida albicans growth. Through genome annotation and secondary metabolite cluster prediction, we established the gene cluster for the antifungal compound hymeglusin. The genes necessary for the biosynthesis of hymeglusin were determined using CRISPR/Cas9 targeted gene deletions followed by metabolic analysis of the deletion strains. Finally, in chapter 6 I summarize our findings, explain their significance, and discuss future experiments to build upon this work.

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Asset Metadata

Creator Grau, Michelle Francine (author)

Core Title Genetic engineering of fungi to enhance the production and elucidate the biosynthesis of bioactive secondary metabolites

School School of Pharmacy

Degree Doctor of Philosophy

Degree Program Molecular Pharmacology and Toxicology

Publication Date 07/31/2019

Defense Date 06/17/2019

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Aspergillus nidulans,asperlin,bioactive metabolite,biosynthetic pathway,cluster-specific transcription factor,CRISPR/Cas9,filamentous fungi,gene deletion,gene over-expression,gene targeting,genetic engineering,hybrid transcription factor,hymeglusin,master regulatory gene,natural product,OAI-PMH Harvest,Scopulariopsis candida,secondary metabolite,silent gene cluster,whole genome sequencing

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Okamoto, Curtis (committee chair), Haworth, Ian (committee member), Wang, Clay C. C. (committee member), Williams, Travis (committee member), Zhang, Yong (committee member)

Creator Email mgrau@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-202232

Unique identifier UC11663573

Identifier etd-GrauMichel-7701.pdf (filename),usctheses-c89-202232 (legacy record id)

Legacy Identifier etd-GrauMichel-7701.pdf

Dmrecord 202232

Document Type Dissertation

Format application/pdf (imt)

Rights Grau, Michelle Francine

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA