Characterizing Microbial Community and Geochemical Dynamics at Hydrothermal Vents Using Osmotically Driven Continuous Fluid Samplers

Microbes play a key role in mediating aquatic biogeochemical cycles. However, our understanding of the relationships between microbial phylogenetic/physiological diversity and habitat physicochemical characteristics is restrained by our limited capacity to concurrently collect microbial and geochemical samples at appropriate spatial and temporal scales. Accordingly, we have developed a low-cost, continuous fluid sampling system (the Biological OsmoSampling System, or BOSS) to address this limitation. The BOSS does not use electricity, can be deployed in harsh/remote environments, and collects/preserves samples with daily resolution for >1 year. Here, we present data on the efficacy of DNA and protein preservation during a 1.5 year laboratory study as well as the results of two field deployments at deep-sea hydrothermal vents, wherein we examined changes in microbial diversity, protein expression, and geochemistry over time. Our data reveal marked changes in microbial composition co-occurring with changes in hydrothermal fluid composition as well as the temporal dynamics of an enigmatic sulfide-oxidizing symbiont in its free-living state. We also present the first data on in situ protein preservation and expression dynamics highlighting the BOSS’s potential utility in meta-proteomic studies. These data illustrate the value of using BOSS to study relationships among microbial and geochemical phenomena and environmental conditions

Difference in expression between cellulose and glucose cultures for transporters, secretion systems, effluxes, and exporters genes.

<p>All type II and III secretion systems had higher expression in the cellulose cultures than the glucose cultures suggesting they may have a role in secreting the carbohydrate active enzymes into the extracellular medium. RPKM = Reads Per Kilobase per Million mapped reads.</p

(A) Average number of carbohydrate active enzymes (CAZymes) and (B) average abundance of CAZymes observed from a given fraction. (C) Percent of CAZymes to total proteins and (D) percent CAZymes abundance to total protein abundance.

<p>The number and percentages of CAZymes and abundance of CAZymes was largest for the extracellular medium fraction. EM = extracellular medium, OM = outer membrane, PE = periplasm.</p

TEM images of <i>F</i>. <i>succinogenes</i> S85 harvested during mid-exponential growth on cellulose (A, B), cellulose stationary growth (C, D), glucose mid-exponential growth (E) and glucose stationary growth (F).

<p>Grooves in the cellulose were observed in the cellulose mid-exponential and stationary phases. Vesicles were present in only the cellulose stationary phase (arrows in D). Scale bars are 1 μm (A,C) and 0.5 μm (B-F). Vesicles are indicated by arrows. Grooves are indicated by curves.</p

Expression of pilin transcripts in <i>F</i>. <i>succinogenes</i> S85 cellulose and glucose cultures.

<p>There is a higher expression of pilin proteins in the cellulose cultures than the glucose cultures for 3 out of the 4 pilin proteins observed. RPKM = Reads Per Kilobase per Million mapped reads.</p

Expression of fibro-slime genes in <i>F</i>. <i>succinogenes</i> S85 cellulose and glucose cultures.

<p>The cellulose cultures showed an increased expression for 8 out of 10 fibro-slime proteins relative to the glucose cultures. RPKM = Reads Per Kilobase per Million mapped reads.</p

Identifying Aspects of the Post-Transcriptional Program Governing the Proteome of the Green Alga <i>Micromonas pusilla</i>

<div><p><i>Micromonas</i> is a unicellular motile alga within the Prasinophyceae, a green algal group that is related to land plants. This picoeukaryote (<2 μm diameter) is widespread in the marine environment but is not well understood at the cellular level. Here, we examine shifts in mRNA and protein expression over the course of the day-night cycle using triplicated mid-exponential, nutrient replete cultures of <i>Micromonas pusilla</i> CCMP1545. Samples were collected at key transition points during the diel cycle for evaluation using high-throughput LC-MS proteomics. In conjunction, matched mRNA samples from the same time points were sequenced using pair-ended directional Illumina RNA-Seq to investigate the dynamics and relationship between the mRNA and protein expression programs of <i>M</i>. <i>pusilla</i>. Similar to a prior study of the marine cyanobacterium <i>Prochlorococcus</i>, we found significant divergence in the mRNA and proteomics expression dynamics in response to the light:dark cycle. Additionally, expressional responses of genes and the proteins they encoded could also be variable within the same metabolic pathway, such as we observed in the oxygenic photosynthesis pathway. A regression framework was used to predict protein levels from both mRNA expression and gene-specific sequence-based features. Several features in the genome sequence were found to influence protein abundance including codon usage as well as 3’ UTR length and structure. Collectively, our studies provide insights into the regulation of the proteome over a diel cycle as well as the relationships between transcriptional and translational programs in the widespread marine green alga <i>Micromonas</i>.</p></div

Suite of Activity-Based Probes for Cellulose-Degrading Enzymes

Microbial glycoside hydrolases play a dominant role in the biochemical conversion of cellulosic biomass to high-value biofuels. Anaerobic cellulolytic bacteria are capable of producing multicomplex catalytic subunits containing cell-adherent cellulases, hemicellulases, xylanases, and other glycoside hydrolases to facilitate the degradation of highly recalcitrant cellulose and other related plant cell wall polysaccharides. <i>Clostridium thermocellum</i> is a cellulosome-producing bacterium that couples rapid reproduction rates to highly efficient degradation of crystalline cellulose. Herein, we have developed and applied a suite of difluoromethylphenyl aglycone, <i>N</i>-halogenated glycosylamine, and 2-deoxy-2-fluoroglycoside activity-based protein profiling (ABPP) probes to the direct labeling of the <i>C. thermocellum</i> cellulosomal secretome. These activity-based probes (ABPs) were synthesized with alkynes to harness the utility and multimodal possibilities of click chemistry and to increase enzyme active site inclusion for liquid chromatography–mass spectrometry (LC–MS) analysis. We directly analyzed ABP-labeled and unlabeled global MS data, revealing ABP selectivity for glycoside hydrolase (GH) enzymes, in addition to a large collection of integral cellulosome-containing proteins. By identifying reactivity and selectivity profiles for each ABP, we demonstrate our ability to widely profile the functional cellulose-degrading machinery of the bacterium. Derivatization of the ABPs, including reactive groups, acetylation of the glycoside binding groups, and mono- and disaccharide binding groups, resulted in considerable variability in protein labeling. Our probe suite is applicable to aerobic and anaerobic microbial cellulose-degrading systems and facilitates a greater understanding of the organismal role associated with biofuel development

Comparison of protein and mRNA expression patterns across the time course.

<p><b>(A)</b> Comparison of the degree of the correlation (Pearson, R_P) between the mRNA and protein expression profiles, per gene (Z-transformed). Less than 10% of the genes considered were correlated over the course of the experiment (using a threshold of 0.75); while 26% were delayed by 1 time point (1 TPT) and 9% by 2 time points (2 TPTs). <b>(B)</b> Concordance of Gene Set Enrichment Analysis (GSEA) of pairwise correlation (as measured by <i>CS</i>_<i>p</i>; see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155839#sec002" target="_blank">Methods</a>) indicates there is considerable concordance between the expression programs of several key metabolic pathways, such as the Oxygenic Photosynthesis and TCA pathways. Note this is limited to those pathways that are concordant. Concordant pathways from a similar analysis of log-ratios include many of the same critical pathways (Fig M in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155839#pone.0155839.s001" target="_blank">S1 File</a>). Complete representations of all pathways from the analysis of abundances and log-ratios are also provided (Figs N and O in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155839#pone.0155839.s001" target="_blank">S1 File</a>). <b>(C)</b> A global comparison of the expression dynamics observed in the mRNA and protein expression programs.</p

Coverage of the Oxygenic Photosynthesis (OP) Pathway by the joint expression clusters.

<p><b>(A)</b> Cartoon of the OP pathway, with selected interactions color-coded to indicate cluster membership. Light-dependent reactions are indicated by yellow background. Of the 17 interactions in the pathway, 15 were mediated by genes in the high confidence data set (Tables E-G in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155839#pone.0155839.s001" target="_blank">S1 File</a>). Note that within the light-independent reactions of the Calvin-Bensen-Bassham Cycle we identified two fructose-bisphosphate aldolase (FBA) proteins, wlab.223910 (Class I, Cluster 6) and wlab.149815 (Class II, Cluster 3), both with predicted chloroplast transit peptides. The Class II FBA of the cyanobacterium <i>Synechococcus</i> shows higher reactivity for sedoheptulose-1,7-bisphosphate than for fructose-1,6-bisphosphate than its Class I FBA [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155839#pone.0155839.ref094" target="_blank">94</a>] and thus, although they have not been experimentally characterized, the <i>M</i>. <i>pusilla</i> FBAs depicted here may also partition within the pathway. <b>(B)</b> Joint mRNA and protein expression profiles of the clusters enriched with OP pathway genes (Clusters 6, 7, & 15). Cluster 6 displays considerable correlation (R² = 0.643) between the mRNA and protein expression patterns, while Cluster 7 and 15 display either marginal (R = 0.161) or inverse (-0.446) correlation. Profiles for Clusters 2 and 3 are show in Figure P in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155839#pone.0155839.s001" target="_blank">S1 File</a>.</p