Coupling Metaproteomics with Taxonomy to Determine Responses of Bacterioplankton to Organic Perturbations in the Western Arctic Ocean

Understanding how the functionality of marine microbial communities change over time and space, and which taxonomic groups dominate distinct metabolic pathways, are essential to understanding the ecology of these microbiomes and the factors contributing to their regulation of elemental cycles in the oceans. The primary goal of this dissertation was to investigate the community metabolic and taxonomic responses and the degradation potential of two compositionally distinct marine microbiomes within the shallow shelf ecosystem of the Chukchi Sea after rapid fluctuations in algal organic matter availability. Novel bioinformatics tools were collaboratively developed and used together with community proteomics (metaproteomics) to characterize and quantify changes in bacterial community functioning and taxonomic composition over time. 16S rRNA sequencing was employed to confirm bacterial taxonomic dynamics. These approaches were linked to particulate analyses for lipids and amino acids in order to track temporal changes in organic substrate composition. Results obtained using these improved methodological standards and the multidisciplinary approach demonstrated that organic perturbations within these systems stimulated changes to microbial taxonomic composition and functionality. The removal of organic particles seen within the control initiated a divergence between the two microbiomes while substrate abundance, as algal inputs, led to a convergence in community function. Despite the functional and taxonomic overlap seen as dominant features characterizing the responses to rapid influxes of algal organic matter, unique metabolic traits differentiated the major bacterial groups of each microbiome. This was most apparent in the recycling of nitrogen and carbon as well as substrate acquisition, suggesting that conditions which select for certain bacterial groups in the western Arctic Ocean may impact local chemical gradients. The large dataset of information obtained from this dissertation provides insight into the timing and characterization of Arctic bacterial community responses to environmental perturbations and in turn how they influence changes in substrate composition through selective degradation of labile lipid classes. In addition, this work demonstrates the applicability of trait-based methodologies to inform on how environmental conditions may drive niche formation within complex microbial communities

MS Analysis of a Dilution Series of Bacteria: Phytoplankton to Improve Detection of Low Abundance Bacterial Peptides

Assigning links between microbial activity and biogeochemical cycles in the ocean is a primary objective for ecologists and oceanographers. Bacteria represent a small ecosystem component by mass, but act as the nexus for both nutrient transformation and organic matter recycling. There are limited methods to explore the full suite of active bacterial proteins largely responsible for degradation. Mass spectrometry (MS)-based proteomics now has the potential to document bacterial physiology within these complex systems. Global proteome profiling using MS, known as data dependent acquisition (DDA), is limited by the stochastic nature of ion selection, decreasing the detection of low abundance peptides. The suitability of MS-based proteomics methods in revealing bacterial signatures outnumbered by phytoplankton proteins was explored using a dilution series of pure bacteria (Ruegeria pomeroyi) and diatoms (Thalassiosira pseudonana). Two common acquisition strategies were utilized: DDA and selected reaction monitoring (SRM). SRM improved detection of bacterial peptides at low bacterial cellular abundance that were undetectable with DDA from a wide range of physiological processes (e.g. amino acid synthesis, lipid metabolism, and transport). We demonstrate the benefits and drawbacks of two different proteomic approaches for investigating species-specific physiological processes across relative abundances of bacteria that vary by orders of magnitude

MetaGOmics: A Web-Based Tool for Peptide-Centric Functional and Taxonomic Analysis of Metaproteomics Data

Metaproteomics is the characterization of all proteins being expressed by a community of organisms in a complex biological sample at a single point in time. Applications of metaproteomics range from the comparative analysis of environmental samples (such as ocean water and soil) to microbiome data from multicellular organisms (such as the human gut). Metaproteomics research is often focused on the quantitative functional makeup of the metaproteome and which organisms are making those proteins. That is: What are the functions of the currently expressed proteins? How much of the metaproteome is associated with those functions? And, which microorganisms are expressing the proteins that perform those functions? However, traditional protein-centric functional analysis is greatly complicated by the large size, redundancy, and lack of biological annotations for the protein sequences in the database used to search the data. To help address these issues, we have developed an algorithm and web application (dubbed MetaGOmics ) that automates the quantitative functional (using Gene Ontology) and taxonomic analysis of metaproteomics data and subsequent visualization of the results. MetaGOmics is designed to overcome the shortcomings of traditional proteomics analysis when used with metaproteomics data. It is easy to use, requires minimal input, and fully automates most steps of the analysis-including comparing the functional makeup between samples

An Alignment-Free Metapeptide Strategy for Metaproteomic Characterization of Microbiome Samples Using Shotgun Metagenomic Sequencing

In principle, tandem mass spectrometry can be used to detect and quantify the peptides present in a microbiome sample, enabling functional and taxonomic insight into microbiome metabolic activity. However, the phylogenetic diversity constituting a particular microbiome is often unknown, and many of the organisms present may not have assembled genomes. In ocean microbiome samples, with particularly diverse and uncultured bacterial communities, it is difficult to construct protein databases that contain the bulk of the peptides in the sample without losing detection sensitivity due to the overwhelming number of candidate peptides for each tandem mass spectrum. We describe a method for deriving metapeptides (short amino acid sequences that may be represented in multiple organisms) from shotgun metagenomic sequencing of microbiome samples. In two ocean microbiome samples, we constructed site-specific metapeptide databases to detect more than one and a half times as many peptides as by searching against predicted genes from an assembled metagenome and roughly three times as many peptides as by searching against the NCBI environmental proteome database. The increased peptide yield has the potential to enrich the taxonomic and functional characterization of sample metaproteomes

Metaproteomics Reveal That Rapid Perturbations in Organic Matter Prioritize Functional Restructuring Over Taxonomy In Western Arctic Ocean Microbiomes

We examined metaproteome profiles from two Arctic microbiomes during 10-day shipboard incubations to directly track early functional and taxonomic responses to a simulated algal bloom and an oligotrophic control. Using a novel peptide-based enrichment analysis, significant changes (p-value \u3c 0.01) in biological and molecular functions associated with carbon and nitrogen recycling were observed. Within the first day under both organic matter conditions, Bering Strait surface microbiomes increased protein synthesis, carbohydrate degradation, and cellular redox processes while decreasing C1 metabolism. Taxonomic assignments revealed that the core microbiome collectively responded to algal substrates by assimilating carbon before select taxa utilize and metabolize nitrogen intracellularly. Incubations of Chukchi Sea bottom water microbiomes showed similar, but delayed functional responses to identical treatments. Although 24 functional terms were shared between experimental treatments, the timing, and degree of the remaining responses were highly variable, showing that organic matter perturbation directs community functionality prior to alterations to the taxonomic distribution at the microbiome class level. The dynamic responses of these two oceanic microbial communities have important implications for timing and magnitude of responses to organic perturbations within the Arctic Ocean and how community-level functions may forecast biogeochemical gradients in oceans

Bacterial community succession and metabolism during the early stages of POC degradation in the Western Arctic Ocean

Marine bacterial community structure and function have been observed to shift during fluctuating environmental conditions, suggesting that distinct members of the community adapt to the abundance and composition of available nutrients and carbon. We measured changes in bacterial diversity and metabolic response of natural microbial consortia during early degradation of complex sources of particulate organic carbon (POC) in polar waters. The bacterial populations were representative of spatially disconnected communities, having been collected from the chlorophyll maximum and bottom waters of the Bering Strait and Chukchi Sea, respectively. Shifts in community composition, nitrogen assimilation and proteomic expression of the free-living Arctic bacteria were followed in ten-day, parallel incubation experiments with natural and isotopically labeled algal amendments under near in situ conditions. Based upon 16S rRNA gene sequencing and detailed biochemical composition, we are examining if initial bacterial community structure and succession impact early POC degradation kinetics. Additionally, we are investigating if there are phylogenetic niches for metabolic function driving POC degradation by western arctic marine bacteria

Fluorescence Tracking of Dissolved and Particulate Organic Matter Quality in a River-Dominated Estuary

Excitation–emission matrix (EEM) fluorescence was combined with parallel factor analysis (PARAFAC) to model base-extracted particulate (POM) and dissolved (DOM) organic matter quality in the Neuse River Estuary (NRE), North Carolina, before and after passage of Hurricane Irene in August 2011. Principle components analysis was used to determine that four of the PARAFAC components (C1–C3 and C6) were terrestrial sources to the NRE. One component (C4), prevalent in DOM of nutrient-impacted streams and estuaries and produced in phytoplankton cultures, was enriched in the POM and in surface sediment pore water DOM. One component (C5) was related to recent autochthonous production. Photoexposure of unfiltered Neuse River water caused an increase in slope ratio values (<i>S</i>_R) which corresponded to an increase in the ratio C2:C3 for DOM, and the production of C4 fluorescence in both POM and DOM. Changes to the relative abundance of C4 in POM and DOM indicated that advection of pore water DOM from surface sediments into overlying waters could increase the autochthonous quality of DOM in shallow microtidal estuaries. Modeling POM and DOM simultaneously with PARAFAC is an informative technique that is applicable to assessments of estuarine water quality