Page 26 |
Save page Remove page | Previous | 26 of 199 | Next |
|
small (250x250 max)
medium (500x500 max)
Large (1000x1000 max)
Extra Large
large ( > 500x500)
Full Resolution
All (PDF)
|
This page
All
|
21
Amplicon sequencing
Microbial diversity was sampled before nutrients were
added, and at the end of the final temperature fluctuation
cycle. Cells were filtered (1.2 μm polycarbonate) and stored
in liquid nitrogen. Extractions used the DNeasy Power Soil
kit (Qiagen, Hilden, Germany) modified to include a 10-min
65 °C incubation before vortexing. Amplification and
sequencing of the V4-V5 hypervariable region of the 16S
rRNA gene was done using the primers 515F-Y (5′-
GTGYCAGCMGCCGCGGTAA-3′) and 926R (5′-
CCGYCAATTYMTTTRAGTTT-3′), as described in [48].
These primers successfully amplify large proportions of
known prokaryotes, and chloroplasts (via the 16S rRNA
gene), as well as eukaryotes (via the 18S rRNA) [48]. These
primers have been previously used to describe microbial
communities at this study site [49]. Library prep and
sequencing was done at Molecular Research DNA labs (MR
DNA; Shallowater, TX, USA) on the Illumina Miseq plat-form
producing 2 × 300 bp paired-end reads. DNA samples
from the spring experiment were treated the same way as
summer and fall DNA samples, but were sequenced on a
different date. To avoid potential sequencing run-specific
batch effects, each season was analyzed individually. The
quality of DNA from one replicate in the spring future-constant
treatment was low and consequently contained
few reads. This replicate was excluded from sequence
analysis.
Sequence data analysis
Our processing workflow is shown in Fig. S2. In short,
raw sequence reads were demultiplexed using Sabre
(github.com/najoshi/sabre, version 1.0) and primers
removed with usearch’s fastx_truncate (version 9.2)
command to cut the first 20 bases from forward and first
19 from reverse reads. These were analyzed with the
DADA2 pipeline, version 1.6.0 [50]. Default settings
were used except where noted following DADA2’s stan-dard
workflow, version 1.8 (https://benjjneb.github.io/da
da2/tutorial.html). The 18S rRNA gene region that is
amplified by these primers is typically longer than our 2 ×
300 paired-end sequencing protocol spans, and hence
would be discarded by the merge step our analysis pipe-line
[48]. We gathered all nonmerged reads and separated
out putative 18S rRNA gene sequences from reads
rejected due to quality issues using the number of mis-matched
base pairs. We found that sequences with >35
mismatches typically matched eukaryotic 18S rRNA gene
sequences when BLASTed against NCBI’s nonredundant
nucleotide (nr/nt) database (Table S1). Because of this
correlation, all reads with >35 mismatches were assumed
to be eukaryotic 18S rRNA gene sequences. These were
concatenated with ten ambiguous, “n” bases and pro-cessed
with the merged, 16S rRNA reads. Amplicon
sequence variants (ASVs) identified by the Silva132
database [51] as chloroplasts were removed and separately
assigned taxonomy using PhytoREF, a curated database
of phytoplankton chloroplast 16S rRNA sequences [52].
ASVs derived from putative 18S rRNA gene sequences
were identified using the Protist Ribosomal Reference
database, PR2 [53]. Previous work with these primers at
SPOT observed that estimates of phytoplankton diversity
were typically similar using reads assigned to either 16S
or 18S rRNA amplicons [49]. For this study we chose to
rely on the 16S rRNA plastid gene sequences to describe
the eukaryotic phytoplankton community. 18S rRNA gene
copy number varies considerably between taxa based on
genome size [54], whereas plastid numbers can vary based
on environmental variables (e.g. nutrient availability)
which we control for in our experiments. Putative-18S
assigned taxonomy was used to check for the presence of
metazoan grazers (which should have been largely
removed with our prefiltering during sampling), and for
dinoflagellates, whose plastid 16S rRNA gene sequences
are highly divergent [55] and not amplified with these
primers. For the highest level of taxonomic resolution, we
BLASTed all bacterial ASVs that comprised >10% and
eukaryotic ASVs comprising >5% of recovered reads in
any given sample against the NCBI’s nr/nt database,
excluding uncultured sample sequences. We used percent
similarity thresholds to assign taxonomic rank following
published values for primers amplifying the V4 rRNA
region [56]. For dominant phytoplankton ASVs we con-firmed
their taxonomic identity by also BLASTing the
corresponding 18S rRNA sequences. Because these pri-mers
produce relatively fewer 18S rRNA amplicons and
the natural differences in copy numbers of each gene, we
paired sequences by comparing the relative abundance of
recovered 18S and plastid 16S rRNA sequences. ASVs of
each gene that had the strongest correlation (highest
Spearman’s correlational coefficient) were considered to
belong to the same organism.
Analysis of read counts including calculations of
diversity, ecological distance, and all ordinations was
done in R [57] and RStudio [58] using the Phyloseq [59]
and Vegan [60] packages. For ordinations, the ASV count
matrix was first transformed using the variance stabilizing
transformation within DESeq2 [61], Euclidean distances
were calculated (Vegan), and we tested for significance
between groups using a permutational ANOVA (Vegan),
after confirming an equal amount of variance between
groups using the betadisper function (Vegan). Sig-nificance
of temperature treatment effects on major taxo-nomic
groups was tested using both one-way ANOVA
and t test, and DESeq2 was used to test for differential
J. D. Kling et al.
Object Description
| Title | Thermal diversity within marine phytoplankton communities |
| Author | Kling, Joshua David |
| Author email | Joshuakl@usc.edu;Joshuakl@berkeley.edu |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Biology (Marine Biology and Biological Oceanography) |
| School | College of Letters, Arts and Sciences |
| Date defended/completed | 2020-08-11 |
| Date submitted | 2020-08-11 |
| Date approved | 2020-08-11 |
| Restricted until | 2020-08-11 |
| Date published | 2020-08-11 |
| Advisor (committee chair) | Hutchins, David |
| Advisor (committee member) |
Levine, Naomi Heidelberg, John Ehrenreich, Ian |
| Abstract | Marine photosynthetic carbon fixation in the sunlit upper reaches of the ocean is almost entirely carried out by chlorophyll-containing, single-celled microorganisms, and is responsible for half of the net primary production on the planet. Because of this connection to the marine carbon cycle, it is essential to assess the responses of marine phytoplankton to global change. However, this work is challenged by the dazzling diversity of both eukaryotic and prokaryotic lineages which coexist in complex phytoplankton assemblages. My dissertation contributes to this effort by investigating how the diversity of phytoplankton influences their resilience to rising temperatures. In my first study, I used natural California coastal communities collected across three seasons to show that the phytoplankton assemblage as a whole was able to maintain growth well above typical temperature ranges. However, either steady or fluctuating temperatures exceeding the maximum threshold recorded in a decade-long observational dataset caused drastic rearrangements in the phytoplankton community, including the appearance of novel dominant species. My dissertation work also highlights that there are still unrecognized but environmentally-important taxa with bizarre and unexpected life histories and thermal responses, even in the most well-studied environments. In my second study, I characterized a recently isolated nanoplanktonic diatom from the Narragansett Bay Time Series that occupies a distinct low-light, low-temperature niche. This isolate demonstrated an unusual sensitivity to light, whereby its ability to respond to what should be favorable increases in temperature is constrained by light intensity. Six years of amplicon sequencing data from the time series site suggest that this diatom is a temperate wintertime/early spring specialist, and will likely not fare well in a warmer and more stratified future ocean. In addition to expanding knowledge of functional diversity at the species level, my work also examines the potential of intra-specific diversity to house hidden adaptations to rising temperatures. Natural microbial populations are composed of distinct individual strains, whose relative abilities to contribute to the success of the whole population in a changing environment have not been well-studied. In my third study, I compared the thermal responses of 11 strains of the marine unicellular cyanobacterium Synechococcus simultaneously isolated from a single estuarine water sample to explore this cryptic intra-specific diversity. Surprisingly, these nearly genetically-identical strains showed distinct low and high temperature phenotypes. This study indicates that strain-level variation could be a key yet understudied element in the responses of phytoplankton to global change. Together, these studies highlight that the diversity of marine phytoplankton at the species and individual level includes both functional variability and redundancy relative to temperature. We can expect community composition to change over time in a warming ocean, reflecting the increasing abundance of preadapted groups or individual strains; however, wherever there are winners there are also losers. Besides providing new insights into the contribution of diversity to climate resilience, this dissertation also highlights the need to expand our knowledge of functional thermal traits, especially for typically under-studied pico- and nanoplankton which are often only known from sequence data. |
| Keyword | thermal response; phytoplankton; community ecology |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m |
| Contributing entity | University of Southern California |
| Rights | Kling, Joshua David |
| Physical access | 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 author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given. |
| Repository name | University of Southern California Digital Library |
| Repository address | USC Digital Library, University of Southern California, University Park Campus MC 7002, 106 University Village, Los Angeles, California 90089-7002, USA |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-KlingJoshu-8915.pdf |
| Archival file | Volume13/etd-KlingJoshu-8915.pdf |
Description
| Title | Page 26 |
| Full text | 21 Amplicon sequencing Microbial diversity was sampled before nutrients were added, and at the end of the final temperature fluctuation cycle. Cells were filtered (1.2 μm polycarbonate) and stored in liquid nitrogen. Extractions used the DNeasy Power Soil kit (Qiagen, Hilden, Germany) modified to include a 10-min 65 °C incubation before vortexing. Amplification and sequencing of the V4-V5 hypervariable region of the 16S rRNA gene was done using the primers 515F-Y (5′- GTGYCAGCMGCCGCGGTAA-3′) and 926R (5′- CCGYCAATTYMTTTRAGTTT-3′), as described in [48]. These primers successfully amplify large proportions of known prokaryotes, and chloroplasts (via the 16S rRNA gene), as well as eukaryotes (via the 18S rRNA) [48]. These primers have been previously used to describe microbial communities at this study site [49]. Library prep and sequencing was done at Molecular Research DNA labs (MR DNA; Shallowater, TX, USA) on the Illumina Miseq plat-form producing 2 × 300 bp paired-end reads. DNA samples from the spring experiment were treated the same way as summer and fall DNA samples, but were sequenced on a different date. To avoid potential sequencing run-specific batch effects, each season was analyzed individually. The quality of DNA from one replicate in the spring future-constant treatment was low and consequently contained few reads. This replicate was excluded from sequence analysis. Sequence data analysis Our processing workflow is shown in Fig. S2. In short, raw sequence reads were demultiplexed using Sabre (github.com/najoshi/sabre, version 1.0) and primers removed with usearch’s fastx_truncate (version 9.2) command to cut the first 20 bases from forward and first 19 from reverse reads. These were analyzed with the DADA2 pipeline, version 1.6.0 [50]. Default settings were used except where noted following DADA2’s stan-dard workflow, version 1.8 (https://benjjneb.github.io/da da2/tutorial.html). The 18S rRNA gene region that is amplified by these primers is typically longer than our 2 × 300 paired-end sequencing protocol spans, and hence would be discarded by the merge step our analysis pipe-line [48]. We gathered all nonmerged reads and separated out putative 18S rRNA gene sequences from reads rejected due to quality issues using the number of mis-matched base pairs. We found that sequences with >35 mismatches typically matched eukaryotic 18S rRNA gene sequences when BLASTed against NCBI’s nonredundant nucleotide (nr/nt) database (Table S1). Because of this correlation, all reads with >35 mismatches were assumed to be eukaryotic 18S rRNA gene sequences. These were concatenated with ten ambiguous, “n” bases and pro-cessed with the merged, 16S rRNA reads. Amplicon sequence variants (ASVs) identified by the Silva132 database [51] as chloroplasts were removed and separately assigned taxonomy using PhytoREF, a curated database of phytoplankton chloroplast 16S rRNA sequences [52]. ASVs derived from putative 18S rRNA gene sequences were identified using the Protist Ribosomal Reference database, PR2 [53]. Previous work with these primers at SPOT observed that estimates of phytoplankton diversity were typically similar using reads assigned to either 16S or 18S rRNA amplicons [49]. For this study we chose to rely on the 16S rRNA plastid gene sequences to describe the eukaryotic phytoplankton community. 18S rRNA gene copy number varies considerably between taxa based on genome size [54], whereas plastid numbers can vary based on environmental variables (e.g. nutrient availability) which we control for in our experiments. Putative-18S assigned taxonomy was used to check for the presence of metazoan grazers (which should have been largely removed with our prefiltering during sampling), and for dinoflagellates, whose plastid 16S rRNA gene sequences are highly divergent [55] and not amplified with these primers. For the highest level of taxonomic resolution, we BLASTed all bacterial ASVs that comprised >10% and eukaryotic ASVs comprising >5% of recovered reads in any given sample against the NCBI’s nr/nt database, excluding uncultured sample sequences. We used percent similarity thresholds to assign taxonomic rank following published values for primers amplifying the V4 rRNA region [56]. For dominant phytoplankton ASVs we con-firmed their taxonomic identity by also BLASTing the corresponding 18S rRNA sequences. Because these pri-mers produce relatively fewer 18S rRNA amplicons and the natural differences in copy numbers of each gene, we paired sequences by comparing the relative abundance of recovered 18S and plastid 16S rRNA sequences. ASVs of each gene that had the strongest correlation (highest Spearman’s correlational coefficient) were considered to belong to the same organism. Analysis of read counts including calculations of diversity, ecological distance, and all ordinations was done in R [57] and RStudio [58] using the Phyloseq [59] and Vegan [60] packages. For ordinations, the ASV count matrix was first transformed using the variance stabilizing transformation within DESeq2 [61], Euclidean distances were calculated (Vegan), and we tested for significance between groups using a permutational ANOVA (Vegan), after confirming an equal amount of variance between groups using the betadisper function (Vegan). Sig-nificance of temperature treatment effects on major taxo-nomic groups was tested using both one-way ANOVA and t test, and DESeq2 was used to test for differential J. D. Kling et al. |
