Progress and Challenges in Ocean Metaproteomics and Proposed Best Practices for Data Sharing

Metaproteomics as a Powerful Tool for an Extensive Characterization of Ambient Bioaerosols

Bioaerosols are of great health and environmental concern. Current techniques for their characterization are generally designed to detect individual species or oppositely unspecific molecular tracers. Metaproteomics on the other hand features the possibility to cover a broad range of taxonomies in a single analysis. This work presents a successful application of metaproteomics to characterize the biological fraction of airborne particulate matter (PM). A bottom-up proteomic strategy was employed, including protein extraction by ultrasonication in aqueous buffer, in-solution tryptic digestion, and nanoflow liquid chromatography-high-resolution mass spectrometry analysis. Extraction parameters were optimized to enhance proteins' recovery. The method was validated on Escherichia coli extracts before its application on ambient PM10 samples collected over 12 weeks in Strasbourg, France. A total of 1,087 peptides were detected across all samples, with a weekly average of 223 ± 104 peptides corresponding to 111 ± 40 proteins. Peptides from species belonging to animals, plants, fungi, bacteria, and archaea kingdoms were inventoried. Many of them proved to be very relevant, as they were related to human allergens and pathogens, plant pathogens, or ecological indicators. In this work, the major benefits of metaproteomics, yet rather unexploited, as well as its pitfalls and challenges for a broader application in atmospheric chemistry, are discussed.

Integrative multi-omics analysis of autism spectrum disorder reveals unique microbial macromolecules interactions

INTRODUCTION

Gut microbiota alterations have been implicated in Autism Spectrum Disorder (ASD), yet the mechanisms linking these changes to ASD pathophysiology remain unclear.

OBJECTIVES

This study utilized a multi-omics approach to uncover mechanisms linking gut microbiota to ASD by examining microbial diversity, bacterial metaproteins, associated metabolic pathways and host proteome.

METHODS

The gut microbiota of 30 children with severe ASD and 30 healthy controls was analyzed. Microbial diversity was assessed using 16S rRNA V3 and V4 sequencing. A novel metaproteomics pipeline identified bacterial proteins, while untargeted metabolomics explored altered metabolic pathways. Finally, multi-omics integration was employed to connect macromolecular changes to neurodevelopmental deficits.

RESULTS

Children with ASD exhibited significant alterations in gut microbiota, including lower diversity and richness compared to controls. Tyzzerella was uniquely associated with the ASD group. Microbial network analysis revealed rewiring and reduced stability in ASD. Major metaproteins identified were produced by Bifidobacterium and Klebsiella (e.g., xylose isomerase and NADH peroxidase). Metabolomics profiling identified neurotransmitters (e.g., glutamate, DOPAC), lipids, and amino acids capable of crossing the blood-brain barrier, potentially contributing to neurodevelopmental and immune dysregulation. Host proteome analysis revealed altered proteins, including kallikrein (KLK1) and transthyretin (TTR), involved in neuroinflammation and immune regulation. Finally, multi-omics integration supported single-omics findings and reinforced the hypothesis that gut microbiota and their macromolecular products may contribute to ASD-associated symptoms.

CONCLUSIONS

The integration of multi-omics data provided critical evidence that alteration in gut microbiota and associated macromolecule production may play a role in ASD-related symptoms and co-morbidities. Key bacterial metaproteins and metabolites were identified as potential contributors to neurological and immune dysregulation in ASD, underscoring possible novel targets for therapeutic intervention.

Unveiling the influence of heating temperature on biofilm formation in shower hoses through multi-omics

Shower systems provide unique environments that are conducive to biofilm formation and the proliferation of pathogens. The water heating temperature is a delicate decision that can impact microbial growth, balancing safety and energy consumption. This study investigated the impact of different heating temperatures (39 °C, 45 °C, 51 °C and 58 °C) on the shower hose biofilm (exposed to a final water temperature of 39 °C) using controlled full-scale shower setups. Whole metagenome sequencing and metaproteomics were employed to unveil the microbial composition and protein expression profiles. Overall, the genes and enzymes associated with disinfectant resistance and biofilm formation appeared largely unaffected. However, metagenomic analysis revealed a sharp decline in the number of total (86,371 to 34,550) and unique genes (32,279 to 137) with the increase in hot water temperature, indicating a significant reduction of overall microbial complexity. None of the unique proteins were detected in the proteomics experiments, suggesting smaller variation among biofilms on the proteome level compared to genomic data. Furthermore, out of 43 pathogens detected by metagenomics, only 5 could actually be detected by metaproteomics. Most interestingly, our study indicates that 45 °C heating temperature may represent an optimal balance. It minimizes active biomass (ATP) and reduces the presence of pathogens while saving heating energy. Our study offered new insights into the impact of heating temperature on shower hose biofilm formation and proposed optimal parameters that ensure biosafety while conserving energy.

SMMP: A Deep-Coverage Marine Metaproteome Method for Microbial Community Analysis throughout the Water Column Using 1 L of Seawater

Marine microbes drive pivotal transformations in planetary-scale elemental cycles and have crucial impacts on global biogeochemical processes. Metaproteomics is a powerful tool for assessing the metabolic diversity and function of marine microbes. However, hundreds of liters of seawater are required for normal metaproteomic analysis due to the sparsity of microbial populations in seawater, which poses a substantial challenge to the widespread application of marine metaproteomics, particularly for deep seawater. Herein, a sensitive marine metaproteomics workflow, named sensitive marine metaproteome analysis (SMMP), was developed by integrating polycarbonate filter-assisted microbial enrichment, solid-phase alkylation-based anti-interference sample preparation, and narrow-bore nanoLC column for trace peptide separation and characterization. The method provided more than 8500 proteins from 1 L of bathypelagic seawater samples, which covered diverse microorganisms and crucial functions, e.g., the detection of key enzymes associated with the Wood-Ljungdahl pathway. Then, we applied SMMP to investigate vertical variations in the metabolic expression patterns of marine microorganisms from the euphotic zone to the bathypelagic zone. Methane oxidation and carbon monoxide (CO) oxidation were active processes, especially in the bathypelagic zone, which provided a remarkable energy supply for the growth and proliferation of heterotrophic microorganisms. In addition, marker protein profiles detected related to ammonia transport, ammonia oxidation, and carbon fixation highlighted that Thaumarchaeota played a critical role in primary production based on the coupled carbon-nitrogen process, contributing to the storage of carbon and nitrogen in the bathypelagic regions. SMMP has low microbial input requirements and yields in-depth metaproteome analysis, making it a prospective approach for comprehensive marine metaproteomic investigations.

Novel functional insights into the microbiome inhabiting marine plastic debris: critical considerations to counteract the challenges of thin biofilms using multi-omics and comparative metaproteomics

BACKGROUND

Microbial functioning on marine plastic surfaces has been poorly documented, especially within cold climates where temperature likely impacts microbial activity and the presence of hydrocarbonoclastic microorganisms. To date, only two studies have used metaproteomics to unravel microbial genotype-phenotype linkages in the marine 'plastisphere', and these have revealed the dominance of photosynthetic microorganisms within warm climates. Advancing the functional representation of the marine plastisphere is vital for the development of specific databases cataloging the functional diversity of the associated microorganisms and their peptide and protein sequences, to fuel biotechnological discoveries. Here, we provide a comprehensive assessment for plastisphere metaproteomics, using multi-omics and data mining on thin plastic biofilms to provide unique insights into plastisphere metabolism. Our robust experimental design assessed DNA/protein co-extraction and cell lysis strategies, proteomics workflows, and diverse protein search databases, to resolve the active plastisphere taxa and their expressed functions from an understudied cold environment.

RESULTS

For the first time, we demonstrate the predominance and activity of hydrocarbonoclastic genera (Psychrobacter, Flavobacterium, Pseudomonas) within a primarily heterotrophic plastisphere. Correspondingly, oxidative phosphorylation, the citrate cycle, and carbohydrate metabolism were the dominant pathways expressed. Quorum sensing and toxin-associated proteins of Streptomyces were indicative of inter-community interactions. Stress response proteins expressed by Psychrobacter, Planococcus, and Pseudoalteromonas and proteins mediating xenobiotics degradation in Psychrobacter and Pseudoalteromonas suggested phenotypic adaptations to the toxic chemical microenvironment of the plastisphere. Interestingly, a targeted search strategy identified plastic biodegradation enzymes, including polyamidase, hydrolase, and depolymerase, expressed by rare taxa. The expression of virulence factors and mechanisms of antimicrobial resistance suggested pathogenic genera were active, despite representing a minor component of the plastisphere community.

CONCLUSION

Our study addresses a critical gap in understanding the functioning of the marine plastisphere, contributing new insights into the function and ecology of an emerging and important microbial niche. Our comprehensive multi-omics and comparative metaproteomics experimental design enhances biological interpretations to provide new perspectives on microorganisms of potential biotechnological significance beyond biodegradation and to improve the assessment of the risks associated with microorganisms colonizing marine plastic pollution. Video Abstract.

Metaproteomics for Coinfections in the Upper Respiratory Tract: The Case of COVID-19

The upper respiratory tract (URT) is home to a diverse range of microbial species. Respiratory infections disturb the microbial flora in the URT, putting people at risk of secondary infections. The potential dangers and clinical effects of bacterial and fungal coinfections with SARS-CoV-2 support the need to investigate the microbiome of the URT using clinical samples. Mass spectrometry (MS)-based metaproteomics analysis of microbial proteins is a novel approach to comprehensively assess the clinical specimens with complex microbial makeup. The coronavirus that causes severe acute respiratory syndrome (SARS-CoV-2) is responsible for the COVID-19 pandemic resulting in a plethora of microbial coinfections impeding therapy, prognosis, and overall disease management. In this chapter, the corresponding workflows for MS-based shotgun proteomics and metaproteomic analysis are illustrated.

Biodiversity Analysis of Metaproteomics Samples with Unipept: A Comprehensive Tutorial

Metaproteomics has become a crucial omics technology for studying microbiomes. In this area, the Unipept ecosystem, accessible at https://unipept.ugent.be , has emerged as a valuable resource for analyzing metaproteomic data. It offers in-depth insights into both taxonomic distributions and functional characteristics of complex ecosystems. This tutorial explains essential concepts like Lowest Common Ancestor (LCA) determination and the handling of peptides with missed cleavages. It also provides a detailed, step-by-step guide on using the Unipept Web application and Unipept Desktop for thorough metaproteomics analyses. By integrating theoretical principles with practical methodologies, this tutorial empowers researchers with the essential knowledge and tools needed to fully utilize metaproteomics in their microbiome studies.

Metaproteogenomic Profile of a Mesopelagic Adenylylsulfate Reductase: Course-Based Discovery Using the Ocean Protein Portal

Adenylylsulfate reductase (Apr) is a flavoprotein with a dissimilatory sulfate reductase function. Its ability to catalyze the reverse reaction in sulfur oxidizers has propelled a complex phylogenetic history of transfers with sulfate reducers and made this enzyme an important protein in ocean sulfur cycling. As part of a graduate course, we analyzed metaproteomic data from the Ocean Protein Portal and observed evidence of Apr alpha (AprA) and beta (AprB) subunits in the Central Pacific Ocean. The protein was originally taxonomically attributed toChlorobium tepidum TLS, a green sulfur bacterium. However, our phylogenomic and oceanographic contextual analysis contradicted this label, instead showing that this protein is consistent with the genomic material from the newly discovered Candidatus Lambdaproteobacteriaclass, implying that the ecological role of this lineage in oxygen minimum twilight zones is underappreciated. This study illustrates how metaproteogenomic analysis can contribute to more accurate metagenomic/proteomic annotations and comprehensive ocean biogeochemical processes conducive to course-based research experiences.

A bibliometric analysis of the global impact of metaproteomics research

Background

Metaproteomics is a subfield in meta-omics that is used to characterize the proteome of a microbial community. Despite its importance and the plethora of publications in different research area, scientists struggle to fully comprehend its functional impact on the study of microbiomes. In this study, bibliometric analyses are used to evaluate the current state of metaproteomic research globally as well as evaluate the specific contribution of Africa to this burgeoning research area. In this study, we use bibliometric analyses to evaluate the current state of metaproteomic research globally, identify research frontiers and hotspots, and further predict future trends in metaproteomics. The specific contribution of Africa to this research area was evaluated.

Methods

Relevant documents from 2004 to 2022 were extracted from the Scopus database. The documents were subjected to bibliometric analyses and visualization using VOS viewer and Biblioshiny package in R. Factors such as the trends in publication, country and institutional cooperation networks, leading scientific journals, author's productivity, and keywords analyses were conducted. The African publications were ranked using Field-Weighted Citation Impact (FWCI) scores.

Results

A total of 1,138 documents were included and the number of publications increased drastically from 2004 to 2022 with more publications (170) reported in 2021. In terms of publishers, Frontiers in Microbiology had the highest number of total publications (62). The United States of America (USA), Germany, China, and Canada, together with other European countries were the most productive. Institution-wise, the Helmholtz Zentrum für Umweltforschung, Germany had more publications while Max Plank Institute had the highest total collaborative link strength. Jehmlich N. was the most productive author whereas Hettich RL had the highest h-index of 63. Regarding Africa, only 2.2% of the overall publications were from the continent with more publication outputs from South Africa. More than half of the publications from the continent had an FWCI score ≥ 1.

Conclusion

The scientific outputs of metaproteomics are rapidly evolving with developed countries leading the way. Although Africa showed prospects for future progress, this could only be accelerated by providing funding, increased collaborations, and mentorship programs.

A Galaxy of informatics resources for MS-based proteomics

INTRODUCTION

Continuous advances in mass spectrometry (MS) technologies have enabled deeper and more reproducible proteome characterization and a better understanding of biological systems when integrated with other 'omics data. Bioinformatic resources meeting the analysis requirements of increasingly complex MS-based proteomic data and associated multi-omic data are critically needed. These requirements included availability of software that would span diverse types of analyses, scalability for large-scale, compute-intensive applications, and mechanisms to ease adoption of the software.

AREAS COVERED

The Galaxy ecosystem meets these requirements by offering a multitude of open-source tools for MS-based proteomics analyses and applications, all in an adaptable, scalable, and accessible computing environment. A thriving global community maintains these software and associated training resources to empower researcher-driven analyses.

EXPERT OPINION

The community-supported Galaxy ecosystem remains a crucial contributor to basic biological and clinical studies using MS-based proteomics. In addition to the current status of Galaxy-based resources, we describe ongoing developments for meeting emerging challenges in MS-based proteomic informatics. We hope this review will catalyze increased use of Galaxy by researchers employing MS-based proteomics and inspire software developers to join the community and implement new tools, workflows, and associated training content that will add further value to this already rich ecosystem.

Microbial functional diversity across biogeochemical provinces in the central Pacific Ocean

Enzymes catalyze key reactions within Earth's life-sustaining biogeochemical cycles. Here, we use metaproteomics to examine the enzymatic capabilities of the microbial community (0.2 to 3 µm) along a 5,000-km-long, 1-km-deep transect in the central Pacific Ocean. Eighty-five percent of total protein abundance was of bacterial origin, with Archaea contributing 1.6%. Over 2,000 functional KEGG Ontology (KO) groups were identified, yet only 25 KO groups contributed over half of the protein abundance, simultaneously indicating abundant key functions and a long tail of diverse functions. Vertical attenuation of individual proteins displayed stratification of nutrient transport, carbon utilization, and environmental stress. The microbial community also varied along horizontal scales, shaped by environmental features specific to the oligotrophic North Pacific Subtropical Gyre, the oxygen-depleted Eastern Tropical North Pacific, and nutrient-rich equatorial upwelling. Some of the most abundant proteins were associated with nitrification and C1 metabolisms, with observed interactions between these pathways. The oxidoreductases nitrite oxidoreductase (NxrAB), nitrite reductase (NirK), ammonia monooxygenase (AmoABC), manganese oxidase (MnxG), formate dehydrogenase (FdoGH and FDH), and carbon monoxide dehydrogenase (CoxLM) displayed distributions indicative of biogeochemical status such as oxidative or nutritional stress, with the potential to be more sensitive than chemical sensors. Enzymes that mediate transformations of atmospheric gases like CO, CO₂, NO, methanethiol, and methylamines were most abundant in the upwelling region. We identified hot spots of biochemical transformation in the central Pacific Ocean, highlighted previously understudied metabolic pathways in the environment, and provided rich empirical data for biogeochemical models critical for forecasting ecosystem response to climate change.

Ecosystem-specific microbiota and microbiome databases in the era of big data

The rapid development of sequencing methods over the past decades has accelerated both the potential scope and depth of microbiota and microbiome studies. Recent developments in the field have been marked by an expansion away from purely categorical studies towards a greater investigation of community functionality. As in-depth genomic and environmental coverage is often distributed unequally across major taxa and ecosystems, it can be difficult to identify or substantiate relationships within microbial communities. Generic databases containing datasets from diverse ecosystems have opened a new era of data accessibility despite costs in terms of data quality and heterogeneity. This challenge is readily embodied in the integration of meta-omics data alongside habitat-specific standards which help contextualise datasets both in terms of sample processing and background within the ecosystem. A special case of large genomic repositories, ecosystem-specific databases (ES-DB's), have emerged to consolidate and better standardise sample processing and analysis protocols around individual ecosystems under study, allowing independent studies to produce comparable datasets. Here, we provide a comprehensive review of this emerging tool for microbial community analysis in relation to current trends in the field. We focus on the factors leading to the formation of ES-DB's, their comparison to traditional microbial databases, the potential for ES-DB integration with meta-omics platforms, as well as inherent limitations in the applicability of ES-DB's.

Metabolic tuning of a stable microbial community in the surface oligotrophic Indian Ocean revealed by integrated meta-omics

Understanding the mechanisms, structuring microbial communities in oligotrophic ocean surface waters remains a major ecological endeavor. Functional redundancy and metabolic tuning are two mechanisms that have been proposed to shape microbial response to environmental forcing. However, little is known about their roles in the oligotrophic surface ocean due to less integrative characterization of community taxonomy and function. Here, we applied an integrated meta-omics-based approach, from genes to proteins, to investigate the microbial community of the oligotrophic northern Indian Ocean. Insignificant spatial variabilities of both genomic and proteomic compositions indicated a stable microbial community that was dominated by Prochlorococcus, Synechococcus, and SAR11. However, fine tuning of some metabolic functions that are mainly driven by salinity and temperature was observed. Intriguingly, a tuning divergence occurred between metabolic potential and activity in response to different environmental perturbations. Our results indicate that metabolic tuning is an important mechanism for sustaining the stability of microbial communities in oligotrophic oceans. In addition, integrated meta-omics provides a powerful tool to comprehensively understand microbial behavior and function in the ocean.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-021-00119-6.

Microbial metabolites in the marine carbon cycle

One-quarter of photosynthesis-derived carbon on Earth rapidly cycles through a set of short-lived seawater metabolites that are generated from the activities of marine phytoplankton, bacteria, grazers and viruses. Here we discuss the sources of microbial metabolites in the surface ocean, their roles in ecology and biogeochemistry, and approaches that can be used to analyse them from chemistry, biology, modelling and data science. Although microbial-derived metabolites account for only a minor fraction of the total reservoir of marine dissolved organic carbon, their flux and fate underpins the central role of the ocean in sustaining life on Earth.

Metaexoproteomics Reveals Microbial Behavior in the Ocean's Interior

The proteins present in the extracellular environment of cells, named the "exoproteome," are critical for microbial survival, growth, and interaction with their surroundings. However, little is known about microbial exoproteomes in natural marine environments. Here, we used a metaproteomic approach to characterize the exoprotein profiles (10 kDa-0.2 μm) throughout a water column in the South China Sea. Viruses, together with Alpha- and Gammaproteobacteria were the predominant contributors. However, the exoprotein-producing microbial communities varied with depth: SAR11 in the shallow waters, Pseudomonadales and Nitrososphaeria in the mesopelagic layer, and Alteromonadales, Rhizobiales, and Betaproteobacteria in the bathypelagic layer. Besides viral and unknown proteins, diverse transporters contributed substantially to the exoproteomes and varied vertically in their microbial origins, but presented similar patterns in their predicted substrate identities throughout the water column. Other microbial metabolic processes subject to vertical zonation included proteolysis, the oxidation of ammonia, nitrite and carbon monoxide, C1 metabolism, and the degradation of sulfur-containing dissolved organic matter (DOM). Our metaexoproteomic study provides insights into the depth-variable trends in the in situ ecological traits of the marine microbial community hidden in the non-cellular world, including nutrient cycling, niche partitioning and DOM remineralization.

Communication Lower-Bounds for Distributed-Memory Computations for Mass Spectrometry based Omics Data

Mass spectrometry (MS) based omics data analysis require significant time and resources. To date, few parallel algorithms have been proposed for deducing peptides from mass spectrometry-based data. However, these parallel algorithms were designed, and developed when the amount of data that needed to be processed was smaller in scale. In this paper, we prove that the communication bound that is reached by the existing parallel algorithms is Ω ( m n + 2 r q p ) , where m and n are the dimensions of the theoretical database matrix, q and r are dimensions of spectra, and p is the number of processors. We further prove that communication-optimal strategy with fast-memory M = m n + 2 q r p can achieve Ω ( 2 m n q p ) but is not achieved by any existing parallel proteomics algorithms till date. To validate our claim, we performed a meta-analysis of published parallel algorithms, and their performance results. We show that sub-optimal speedups with increasing number of processors is a direct consequence of not achieving the communication lower-bounds. We further validate our claim by performing experiments which demonstrate the communication bounds that are proved in this paper. Consequently, we assert that next-generation of provable, and demonstrated superior parallel algorithms are urgently needed for MS based large systems-biology studies especially for meta-proteomics, proteogenomic, microbiome, and proteomics for non-model organisms. Our hope is that this paper will excite the parallel computing community to further investigate parallel algorithms for highly influential MS based omics problems.

The Metaproteomics Initiative: a coordinated approach for propelling the functional characterization of microbiomes

Through connecting genomic and metabolic information, metaproteomics is an essential approach for understanding how microbiomes function in space and time. The international metaproteomics community is delighted to announce the launch of the Metaproteomics Initiative (www.metaproteomics.org), the goal of which is to promote dissemination of metaproteomics fundamentals, advancements, and applications through collaborative networking in microbiome research. The Initiative aims to be the central information hub and open meeting place where newcomers and experts interact to communicate, standardize, and accelerate experimental and bioinformatic methodologies in this field. We invite the entire microbiome community to join and discuss potential synergies at the interfaces with other disciplines, and to collectively promote innovative approaches to gain deeper insights into microbiome functions and dynamics. Video Abstract.

Diel Protein Regulation of Marine Picoplanktonic Communities Assessed by Metaproteomics

The diel cycle is of enormous biological importance in that it imposes temporal structure on ecosystem productivity. In the world’s oceans, microorganisms form complex communities that carry out about half of photosynthesis and the bulk of life-sustaining nutrient cycling. How the functioning of microbial communities is impacted by day and night periods in surface seawater remains to be elucidated. In this study, we compared the day and night metaproteomes of the free-living and the particle-attached bacterial fractions from picoplanktonic communities sampled from the northwest Mediterranean Sea surface. Our results showed similar taxonomic distribution of free-living and particle-attached bacterial populations, with Alphaproteobacteria, Gammaproteobacteria and Cyanobacteria being the most active members. Comparison of the day and night metaproteomes revealed that free-living and particle-attached bacteria were more active during the day and the night, respectively. Interestingly, protein diel variations were observed in the photoautotroph Synechococcales and in (photo)-heterotrophic bacteria such as Flavobacteriales, Pelagibacterales and Rhodobacterales. Moreover, our data demonstrated that diel cycle impacts light-dependent processes such as photosynthesis and UV-stress response in Synechococcales and Rhodobacterales, respectively, while the protein regulation from the ubiquitous Pelagibacterales remained stable over time. This study unravels, for the first time, the diel variation in the protein expression of major free-living and particle-attached microbial players at the sea surface, totaling an analysis of eight metaproteomes.

Why Environmental Biomarkers Work: Transcriptome-Proteome Correlations and Modeling of Multistressor Experiments in the Marine Bacterium Trichodesmium

Ocean microbial communities are important contributors to the global biogeochemical reactions that sustain life on Earth. The factors controlling these communities are being increasingly explored using metatranscriptomic and metaproteomic environmental biomarkers. Using published proteomes and transcriptomes from the abundant colony-forming cyanobacterium Trichodesmium (strain IMS101) grown under varying Fe and/or P limitation in low and high CO₂, we observed robust correlations of stress-induced proteins and RNAs (i.e., involved in transport and homeostasis) that yield useful information on the nutrient status under low and/or high CO₂. Conversely, transcriptional and translational correlations of many other central metabolism pathways exhibit broad discordance. A cellular RNA and protein production/degradation model demonstrates how biomolecules with small initial inventories, such as environmentally responsive proteins, achieve large increases in fold-change units as opposed to those with a higher basal expression and inventory such as metabolic systems. Microbial cells, due to their immersion in the environment, tend to show large adaptive responses in both RNA and protein that result in transcript-protein correlations. These observations and model results demonstrate multi-omic coherence for environmental biomarkers and provide the underlying mechanism for those observations, supporting the promise for global application in detecting responses to environmental stimuli in a changing ocean.

Online Nanoflow Two-Dimension Comprehensive Active Modulation Reversed Phase-Reversed Phase Liquid Chromatography High-Resolution Mass Spectrometry for Metaproteomics of Environmental and Microbiome Samples

Metaproteomics is a powerful analytical approach that can assess the functional capabilities deployed by microbial communities in both environmental and biomedical microbiome settings. Yet, the mass spectra resulting from these mixed biological communities are challenging to obtain due to the high number of low intensity peak features. The use of multiple dimensions of chromatographic separation prior to mass spectrometry analyses has been applied to proteomics previously but can require increased sampling handling and instrument time. Here, we demonstrate an automated online comprehensive active modulation two-dimensional liquid chromatography method for metaproteome sample analysis. A high pH PLRP-S column was used in the first dimension followed by low pH separation in the second dimension using dual modulating C18 traps and a C18 column. This method increased the number of unique peptides found in ocean metaproteome samples by more than 50% when compared to a one-dimension separation while using the same amount of sample and instrument time.

Amino Acid Analog Induces Stress Response in Marine Synechococcus

Characterizing the cell-level metabolic trade-offs that phytoplankton exhibit in response to changing environmental conditions is important for predicting the impact of these changes on marine food web dynamics and biogeochemical cycling. The time-selective proteome-labeling approach, bioorthogonal noncanonical amino acid tagging (BONCAT), has potential to provide insight into differential allocation of resources at the cellular level, especially when coupled with proteomics. However, the application of this technique in marine phytoplankton remains limited. We demonstrate that the marine cyanobacteria Synechococcus sp. and two groups of eukaryotic algae take up the modified amino acid l-homopropargylglycine (HPG), suggesting that BONCAT can be used to detect translationally active phytoplankton. However, the impact of HPG addition on growth dynamics varied between groups of phytoplankton. In addition, proteomic analysis of Synechococcus cells grown with HPG revealed a physiological shift in nitrogen metabolism, general protein stress, and energy production, indicating a potential limitation for the use of BONCAT in understanding the cell-level response of Synechococcus sp. to environmental change. Variability in HPG sensitivity between algal groups and the impact of HPG on Synechococcus physiology indicates that particular considerations should be taken when applying this technique to other marine taxa or mixed marine microbial communities. IMPORTANCE Phytoplankton form the base of the marine food web and substantially impact global energy and nutrient flow. Marine picocyanobacteria of the genus Synechococcus comprise a large portion of phytoplankton biomass in the ocean and therefore are important model organisms. The technical challenges of environmental proteomics in mixed microbial communities have limited our ability to detect the cell-level adaptations of phytoplankton communities to a changing environment. The proteome labeling technique, bioorthogonal noncanonical amino acid tagging (BONCAT), has potential to address some of these challenges by simplifying proteomic analyses. This study explores the ability of marine phytoplankton to take up the modified amino acid, l-homopropargylglycine (HPG), required for BONCAT, and investigates the proteomic response of Synechococcus to HPG. We not only demonstrate that cyanobacteria can take up HPG but also highlight the physiological impact of HPG on Synechococcus, which has implications for future applications of this technique in the marine environment.

Mechanisms and heterogeneity of in situ mineral processing by the marine nitrogen fixer Trichodesmium revealed by single-colony metaproteomics

The keystone marine nitrogen fixer Trichodesmium thrives in high-dust environments. While laboratory investigations have observed that Trichodesmium colonies can access the essential nutrient iron from dust particles, less clear are the biochemical strategies underlying particle-colony interactions in nature. Here we demonstrate that Trichodesmium colonies engage with mineral particles in the wild with distinct molecular responses. We encountered particle-laden Trichodesmium colonies at a sampling location in the Southern Caribbean Sea; microscopy and synchrotron-based imaging then demonstrated heterogeneous associations with iron oxide and iron-silicate minerals. Metaproteomic analysis of individual colonies by a new low-biomass approach revealed responses in biogeochemically relevant proteins including photosynthesis proteins and metalloproteins containing iron, nickel, copper, and zinc. The iron-storage protein ferritin was particularly enriched implying accumulation of mineral-derived iron, and multiple iron acquisition pathways including Fe(II), Fe(III), and Fe-siderophore transporters were engaged. While the particles provided key trace metals such as iron and nickel, there was also evidence that Trichodesmium was altering its strategy to confront increased superoxide production and metal exposure. Chemotaxis regulators also responded to mineral presence suggesting involvement in particle entrainment. These molecular responses are fundamental to Trichodesmium's ecological success and global biogeochemical impact, and may contribute to the leaching of particulate trace metals with implications for global iron and carbon cycling.

Selective DNA and Protein Isolation From Marine Macrophyte Surfaces

Studies of unculturable microbes often combine methods, such as 16S rRNA sequencing, metagenomics, and metaproteomics. To apply these techniques to the microbial community inhabiting the surfaces of marine macrophytes, it is advisable to perform a selective DNA and protein isolation prior to the analysis to avoid biases due to the host material being present in high quantities. Two protocols for DNA and protein isolation were adapted for selective extractions of DNA and proteins from epiphytic communities inhabiting the surfaces of two marine macrophytes, the seagrass Cymodocea nodosa and the macroalga Caulerpa cylindracea. Protocols showed an almost complete removal of the epiphytic community regardless of the sampling season, station, settlement, or host species. The obtained DNA was suitable for metagenomic and 16S rRNA sequencing, while isolated proteins could be identified by mass spectrometry. Low presence of host DNA and proteins in the samples indicated a high specificity of the protocols. The procedures are based on universally available laboratory chemicals making the protocols widely applicable. Taken together, the adapted protocols ensure an almost complete removal of the macrophyte epiphytic community. The procedures are selective for microbes inhabiting macrophyte surfaces and provide DNA and proteins applicable in 16S rRNA sequencing, metagenomics, and metaproteomics.

A community-supported metaproteomic pipeline for improving peptide identifications in hydrothermal vent microbiota

Microorganisms in deep-sea hydrothermal vents provide valuable insights into life under extreme conditions. Mass spectrometry-based proteomics has been widely used to identify protein expression and function. However, the metaproteomic studies in deep-sea microbiota have been constrained largely by the low identification rates of protein or peptide. To improve the efficiency of metaproteomics for hydrothermal vent microbiota, we firstly constructed a microbial gene database (HVentDB) based on 117 public metagenomic samples from hydrothermal vents and proposed a metaproteomic analysis strategy, which takes the advantages of not only the sample-matched metagenome, but also the metagenomic information released publicly in the community of hydrothermal vents. A two-stage false discovery rate method was followed up to control the risk of false positive. By applying our community-supported strategy to a hydrothermal vent sediment sample, about twice as many peptides were identified when compared with the ways against the sample-matched metagenome or the public reference database. In addition, more enriched and explainable taxonomic and functional profiles were detected by the HVentDB-based approach exclusively, as well as many important proteins involved in methane, amino acid, sugar, glycan metabolism and DNA repair, etc. The new metaproteomic analysis strategy will enhance our understanding of microbiota, including their lifestyles and metabolic capabilities in extreme environments. The database HVentDB is freely accessible from http://lilab.life.sjtu.edu.cn:8080/HventDB/main.html.

Anthropogenic and Environmental Constraints on the Microbial Methane Cycle in Coastal Sediments

Large amounts of methane, a potent greenhouse gas, are produced in anoxic sediments by methanogenic archaea. Nonetheless, over 90% of the produced methane is oxidized via sulfate-dependent anaerobic oxidation of methane (S-AOM) in the sulfate-methane transition zone (SMTZ) by consortia of anaerobic methane-oxidizing archaea (ANME) and sulfate-reducing bacteria (SRB). Coastal systems account for the majority of total marine methane emissions and typically have lower sulfate concentrations, hence S-AOM is less significant. However, alternative electron acceptors such as metal oxides or nitrate could be used for AOM instead of sulfate. The availability of electron acceptors is determined by the redox zonation in the sediment, which may vary due to changes in oxygen availability and the type and rate of organic matter inputs. Additionally, eutrophication and climate change can affect the microbiome, biogeochemical zonation, and methane cycling in coastal sediments. This review summarizes the current knowledge on the processes and microorganisms involved in methane cycling in coastal sediments and the factors influencing methane emissions from these systems. In eutrophic coastal areas, organic matter inputs are a key driver of bottom water hypoxia. Global warming can reduce the solubility of oxygen in surface waters, enhancing water column stratification, increasing primary production, and favoring methanogenesis. ANME are notoriously slow growers and may not be able to effectively oxidize methane upon rapid sedimentation and shoaling of the SMTZ. In such settings, ANME-2d (Methanoperedenaceae) and ANME-2a may couple iron- and/or manganese reduction to AOM, while ANME-2d and NC10 bacteria (Methylomirabilota) could couple AOM to nitrate or nitrite reduction. Ultimately, methane may be oxidized by aerobic methanotrophs in the upper millimeters of the sediment or in the water column. The role of these processes in mitigating methane emissions from eutrophic coastal sediments, including the exact pathways and microorganisms involved, are still underexplored, and factors controlling these processes are unclear. Further studies are needed in order to understand the factors driving methane-cycling pathways and to identify the responsible microorganisms. Integration of the knowledge on microbial pathways and geochemical processes is expected to lead to more accurate predictions of methane emissions from coastal zones in the future.

Benefits of Iterative Searches of Large Databases to Interpret Large Human Gut Metaproteomic Data Sets

The gut microbiota are increasingly considered as a main partner of human health. Metaproteomics enables us to move from the functional potential revealed by metagenomics to the functions actually operating in the microbiome. However, metaproteome deciphering remains challenging. In particular, confident interpretation of a myriad of MS/MS spectra can only be pursued with smart database searches. Here, we compare the interpretation of MS/MS data sets from 48 individual human gut microbiomes using three interrogation strategies of the dedicated Integrated nonredundant Gene Catalog (IGC 9.9 million genes from 1267 individual fecal samples) together with the Homo sapiens database: the classical single-step interrogation strategy and two iterative strategies (in either two or three steps) aimed at preselecting a reduced-sized, more targeted search space for the final peptide spectrum matching. Both iterative searches outperformed the single-step classical search in terms of the number of peptides and protein clusters identified and the depth of taxonomic and functional knowledge, and this was the most convincing with the three-step approach. However, iterative searches do not help in reducing variability of repeated analyses, which is inherent to the traditional data-dependent acquisition mode, but this variability did not affect the hierarchical relationship between replicates and all other samples.

Fish Pathology Research and Diagnosis in Aquaculture of Farmed Fish; a Proteomics Perspective

One of the main constraints in aquaculture production is farmed fish vulnerability to diseases due to husbandry practices or external factors like pollution, climate changes, or even the alterations in the dynamic of product transactions in this industry. It is though important to better understand and characterize the intervenients in the process of a disease outbreak as these lead to huge economical losses in aquaculture industries. High-throughput technologies like proteomics can be an important characterization tool especially in pathogen identification and the virulence mechanisms related to host-pathogen interactions on disease research and diagnostics that will help to control, prevent, and treat diseases in farmed fish. Proteomics important role is also maximized by its holistic approach to understanding pathogenesis processes and fish responses to external factors like stress or temperature making it one of the most promising tools for fish pathology research.

Development of an Ocean Protein Portal for Interactive Discovery and Education

Proteins are critical in catalyzing chemical reactions, forming key cellular structures, and in regulating cellular processes. Investigation of marine microbial proteins by metaproteomics methods enables the discovery of numerous aspects of microbial biogeochemical processes. However, these datasets present big data challenges as they often involve many samples collected across broad geospatial and temporal scales, resulting in thousands of protein identifications, abundances, and corresponding annotation information. The Ocean Protein Portal (OPP) was created to enable data sharing and discovery among multiple scientific domains and serve both research and education functions. The portal focuses on three use case questions: "Where is my protein of interest?", "Who makes it?", and "How much is there?" and provides profile and section visualizations, real-time taxonomic analysis, and links to metadata, sequence analysis, and other external resources to enable connections to be made between biogeochemical and proteomics datasets.

A rapid and innovative extraction and enrichment method for the metaproteomic characterization of dissolved organic matter in groundwater samples

Metaproteomic analysis of aquifer systems provides valuable information on the microbial populations, their influence on drinking water quality, and the effect on human health. In the present paper, an extraction and enrichment method by C18 extra-wide pore cartridge was developed, optimized, and applied for the first time to the metaproteomic characterization of dissolved organic matter in groundwater samples. In particular, three elution procedures were tested and compared on water spiked with a yeast protein extract to maximize the recovery of proteins from a complex matrix. The maximum protein recovery was obtained by the use of two sequential elution buffers, one employing a denaturing agent and the other one containing an acidified organic solvent. A comprehensive metaproteomic analysis of the dissolved organic matter of groundwater was then performed by nano-high performance liquid chromatography coupled to high-resolution mass spectrometry. A total of 239 proteins was identified; in agreement with the current knowledge on proteins in aquifer systems, most identified sequences derived from bacteria, protobacteria, and ciliates. The paper is the first metaproteomic study applied to groundwater samples with particular emphasis on the need for sample pretreatment to obtain comprehensive information on the proteome in dissolved organic matter.

Revealing ocean-scale biochemical structure with a deep-diving vertical profiling autonomous vehicle

Vast and diverse microbial communities exist within the ocean. To better understand the global influence of these microorganisms on Earth's climate, we developed a robot capable of sampling dissolved and particulate seawater biochemistry across ocean basins while still capturing the fine-scale biogeochemical processes therein. Carbon and other nutrients are acquired and released by marine microorganisms as they build and break down organic matter. The scale of the ocean makes these processes globally relevant and, at the same time, challenging to fully characterize. Microbial community composition and ocean biochemistry vary across multiple physical scales up to that of the ocean basins. Other autonomous underwater vehicles are optimized for moving continuously and, primarily, horizontally through the ocean. In contrast, Clio, the robot that we describe, is designed to efficiently and precisely move vertically through the ocean, drift laterally in a Lagrangian manner to better observe water masses, and integrate with research vessel operations to map large horizontal scales to a depth of 6000 meters. We present results that show how Clio conducts high-resolution sensor surveys and sample return missions, including a mapping of 1144 kilometers of the Sargasso Sea to a depth of 1000 meters. We further show how the samples obtain filtered biomass from seawater that enable genomic and proteomic measurements not possible through in situ sensing. These results demonstrate a robotic oceanography approach for global-scale surveys of ocean biochemistry.

Insects' potential: Understanding the functional role of their gut microbiome

The study of insect-associated microbial communities is a field of great importance in agriculture, principally because of the role insects play as pests. In addition, there is a recent focus on the potential of the insect gut microbiome in areas such as biotechnology, given some microorganisms produce molecules with biotechnological and industrial applications, and also in biomedicine, since some bacteria and fungi are a reservoir of antibiotic resistance genes (ARGs). To date, most studies aiming to characterize the role of the gut microbiome of insects have been based on high-throughput sequencing of the 16S rRNA gene and/or metagenomics. However, recently functional approaches such as metatranscriptomics, metaproteomics and metabolomics have also been employed. Besides providing knowledge about the taxonomic distribution of microbial populations, these techniques also reveal their functional and metabolic capabilities. This information is essential to gain a better understanding of the role played by microbes comprising the microbial communities in their hosts, as well as to indicate their possible exploitation. This review provides an overview of how far we have come in characterizing insect gut functionality through omics, as well as the challenges and future perspectives in this field.

Quantitative models of nitrogen-fixing organisms

Nitrogen-fixing organisms are of importance to the environment, providing bioavailable nitrogen to the biosphere. Quantitative models have been used to complement the laboratory experiments and in situ measurements, where such evaluations are difficult or costly. Here, we review the current state of the quantitative modeling of nitrogen-fixing organisms and ways to enhance the bridge between theoretical and empirical studies.

The Mycobiota of the Deep Sea: What Omics Can Offer

The deep sea (>1000 m below sea level) represents one of the most extreme environments of the ocean. Despite exhibiting harsh abiotic conditions such as low temperatures, high hydrostatic pressure, high salinity concentrations, a low input of organic matter, and absence of light, the deep sea encompasses a great fungal diversity. For decades, most knowledge on the fungal diversity of the deep sea was obtained through culture-dependent techniques. More recently, with the latest advances of high-throughput next generation sequencing platforms, there has been a rapid increment in the number of studies using culture-independent techniques. This review brings into the spotlight the progress of the techniques used to assess the diversity and ecological role of the deep-sea mycobiota and provides an overview on how the omics technologies have contributed to gaining knowledge about fungi and their activity in poorly explored marine environments. Finally, current challenges and suggested coordinated efforts to overcome them are discussed.

METATRYP v 2.0: Metaproteomic Least Common Ancestor Analysis for Taxonomic Inference Using Specialized Sequence Assemblies-Standalone Software and Web Servers for Marine Microorganisms and Coronaviruses

We present METATRYP version 2 software that identifies shared peptides across the predicted proteomes of organisms within environmental metaproteomics studies to enable accurate taxonomic attribution of peptides during protein inference. Improvements include ingestion of complex sequence assembly data categories (metagenomic and metatranscriptomic assemblies, single cell amplified genomes, and metagenome assembled genomes), prediction of the least common ancestor (LCA) for a peptide shared across multiple organisms, increased performance through updates to the backend architecture, and development of a web portal (https://metatryp.whoi.edu). Major expansion of the marine METATRYP database with predicted proteomes from environmental sequencing confirms a low occurrence of shared tryptic peptides among disparate marine microorganisms, implying tractability for targeted metaproteomics. METATRYP was designed to facilitate ocean metaproteomics and has been integrated into the Ocean Protein Portal (https://oceanproteinportal.org); however, it can be readily applied to other domains. We describe the rapid deployment of a coronavirus-specific web portal (https://metatryp-coronavirus.whoi.edu/) to aid in use of proteomics on coronavirus research during the ongoing pandemic. A coronavirus-focused METATRYP database identified potential SARS-CoV-2 peptide biomarkers and indicated very few shared tryptic peptides between SARS-CoV-2 and other disparate taxa analyzed, sharing <1% peptides with taxa outside of the betacoronavirus group, establishing that taxonomic specificity is achievable using tryptic peptide-based proteomic diagnostic approaches.

An optimized metaproteomics protocol for a holistic taxonomic and functional characterization of microbial communities from marine particles

This study aimed to establish a robust and reliable metaproteomics protocol for an in-depth characterization of marine particle-associated (PA) bacteria. To this end, we compared six well-established protein extraction protocols together with different MS-sample preparation techniques using particles sampled during a North Sea spring algae bloom in 2009. In the final optimized workflow, proteins are extracted using a combination of SDS-containing lysis buffer and cell disruption by bead-beating, separated by SDS-PAGE, in-gel digested and analysed by LC-MS/MS, before MASCOT search against a metagenome-based database and data processing/visualization with the in-house-developed bioinformatics tools Prophane and Paver. As an application example, free-living (FL) and particulate communities sampled in April 2009 were analysed, resulting in an as yet unprecedented number of 9354 and 5034 identified protein groups for FL and PA bacteria, respectively. Our data suggest that FL and PA communities appeared similar in their taxonomic distribution, with notable exceptions: eukaryotic proteins and proteins assigned to Flavobacteriia, Cyanobacteria, and some proteobacterial genera were found more abundant on particles, whilst overall proteins belonging to Proteobacteria were more dominant in the FL fraction. Furthermore, our data points to functional differences including proteins involved in polysaccharide degradation, sugar- and phosphorus uptake, adhesion, motility, and stress response.

Sampling Device-Dependence of Prokaryotic Community Structure on Marine Particles: Higher Diversity Recovered by in situ Pumps Than by Oceanographic Bottles

Microbes associated with sinking marine particles play key roles in carbon sequestration in the ocean. The sampling of particle-attached microorganisms is often done with sediment traps or by filtration of water collected with oceanographic bottles, both involving a certain time lapse between collection and processing of samples that may result in changes in particle-attached microbial communities. Conversely, in situ water filtration through submersible pumps allows a faster storage of sampled particles, but it has rarely been used to study the associated microbial communities and has never been compared to other particle-sampling methods in terms of the recovery of particle microbial diversity. Here we compared the prokaryotic communities attached to small (1–53 μm) and large (>53 μm) particles collected from the mesopelagic zone (100–300 m) of two Antarctic polynyas using in situ pumps (ISP) and oceanographic bottles (BTL). Each sampling method retrieved largely different particle-attached communities, suggesting that they capture different kinds of particles. These device-driven differences were greater for large particles than for small particles. Overall, the ISP recovered 1.5- to 3-fold more particle-attached bacterial taxa than the BTL, and different taxonomic groups were preferentially recovered by each method. In particular, typical particle-attached groups such as Planctomycetes and Deltaproteobacteria recovered with ISP were nearly absent from BTL samples. Our results suggest that the method used to sample marine particles has a strong influence in our view of their associated microbial communities.

Acquiring and Analyzing Data Independent Acquisition Proteomics Experiments without Spectrum Libraries

Data independent acquisition (DIA) is an attractive alternative to standard shotgun proteomics methods for quantitative experiments. However, most DIA methods require collecting exhaustive, sample-specific spectrum libraries with data dependent acquisition (DDA) to detect and quantify peptides. In addition to working with non-human samples, studies of splice junctions, sequence variants, or simply working with small sample yields can make developing DDA-based spectrum libraries impractical. Here we illustrate how to acquire, queue, and validate DIA data without spectrum libraries, and provide a workflow to efficiently generate DIA-only chromatogram libraries using gas-phase fractionation (GPF). We present best-practice methods for collecting DIA data using Orbitrap-based instruments and develop an understanding for why DIA using an Orbitrap mass spectrometer should be approached differently than when using time-of-flight instruments. Finally, we discuss several methods for analyzing DIA data without libraries.

Bacterioplankton reveal years-long retention of Atlantic deep-ocean water by the Tropic Seamount

Seamounts, often rising hundreds of metres above surrounding seafloor, obstruct the flow of deep-ocean water. While the retention of deep-water by seamounts is predicted from ocean circulation models, its empirical validation has been hampered by large scale and slow rate of the interaction. To overcome these limitations we use the growth of planktonic bacteria to assess the retention time of deep-ocean water by a seamount. The selected Tropic Seamount in the North-Eastern Atlantic is representative for the majority of isolated seamounts, which do not affect the surface ocean waters. We prove deep-water is retained by the seamount by measuring 2.4× higher bacterial concentrations in the seamount-associated or 'sheath'-water than in deep-ocean water unaffected by seamounts. Genomic analyses of flow-sorted, dominant sheath-water bacteria confirm their planktonic origin, whilst proteomic analyses of the sheath-water bacteria, isotopically labelled in situ, indicate their slow growth. According to our radiotracer experiments, it takes the sheath-water bacterioplankton 1.5 years to double their concentration. Therefore, the seamount should retain the deep-ocean water for 1.8 years for the deep-ocean bacterioplankton to grow to the 2.4× higher concentration in the sheath-water. We propose that turbulent mixing of the seamount sheath-water stimulates bacterioplankton growth by increasing cell encounter rate with ambient dissolved organic molecules.

Deciphering the Functioning of Microbial Communities: Shedding Light on the Critical Steps in Metaproteomics

Unraveling the complex structure and functioning of microbial communities is essential to accurately predict the impact of perturbations and/or environmental changes. From all molecular tools available today to resolve the dynamics of microbial communities, metaproteomics stands out, allowing the establishment of phenotype-genotype linkages. Despite its rapid development, this technology has faced many technical challenges that still hamper its potential power. How to maximize the number of protein identification, improve quality of protein annotation, and provide reliable ecological interpretation are questions of immediate urgency. In our study, we used a robust metaproteomic workflow combining two protein fractionation approaches (gel-based versus gel-free) and four protein search databases derived from the same metagenome to analyze the same seawater sample. The resulting eight metaproteomes provided different outcomes in terms of (i) total protein numbers, (ii) taxonomic structures, and (iii) protein functions. The characterization and/or representativeness of numerous proteins from ecologically relevant taxa such as Pelagibacterales, Rhodobacterales, and Synechococcales, as well as crucial environmental processes, such as nutrient uptake, nitrogen assimilation, light harvesting, and oxidative stress response, were found to be particularly affected by the methodology. Our results provide clear evidences that the use of different protein search databases significantly alters the biological conclusions in both gel-free and gel-based approaches. Our findings emphasize the importance of diversifying the experimental workflow for a comprehensive metaproteomic study.

Cyanobacteria and cyanophage contributions to carbon and nitrogen cycling in an oligotrophic oxygen-deficient zone

Up to half of marine N losses occur in oxygen-deficient zones (ODZs). Organic matter flux from productive surface waters is considered a primary control on N₂ production. Here we investigate the offshore Eastern Tropical North Pacific (ETNP) where a secondary chlorophyll a maximum resides within the ODZ. Rates of primary production and carbon export from the mixed layer and productivity in the primary chlorophyll a maximum were consistent with oligotrophic waters. However, sediment trap carbon and nitrogen fluxes increased between 105 and 150 m, indicating organic matter production within the ODZ. Metagenomic and metaproteomic characterization indicated that the secondary chlorophyll a maximum was attributable to the cyanobacterium Prochlorococcus, and numerous photosynthesis and carbon fixation proteins were detected. The presence of chemoautotrophic ammonia-oxidizing archaea and the nitrite oxidizer Nitrospina and detection of nitrate oxidoreductase was consistent with cyanobacterial oxygen production within the ODZ. Cyanobacteria and cyanophage were also present on large (>30 μm) particles and in sediment trap material. Particle cyanophage-to-host ratio exceeded 50, suggesting that viruses help convert cyanobacteria into sinking organic matter. Nitrate reduction and anammox proteins were detected, congruent with previously reported N₂ production. We suggest that autochthonous organic matter production within the ODZ contributes to N₂ production in the offshore ETNP.

Challenges and promise at the interface of metaproteomics and genomics: an overview of recent progress in metaproteogenomic data analysis

INTRODUCTION

The study of microbial communities based on the combined analysis of genomic and proteomic data - called metaproteogenomics - has gained increased research attention in recent years. This relatively young field aims to elucidate the functional and taxonomic interplay of proteins in microbiomes and its implications on human health and the environment. Areas covered: This article reviews bioinformatics methods and software tools dedicated to the analysis of data from metaproteomics and metaproteogenomics experiments. In particular, it focuses on the creation of tailored protein sequence databases, on the optimal use of database search algorithms including methods of error rate estimation, and finally on taxonomic and functional annotation of peptide and protein identifications. Expert opinion: Recently, various promising strategies and software tools have been proposed for handling typical data analysis issues in metaproteomics. However, severe challenges remain that are highlighted and discussed in this article; these include: (i) robust false-positive assessment of peptide and protein identifications, (ii) complex protein inference against a background of highly redundant data, (iii) taxonomic and functional post-processing of identification data, and finally, (iv) the assessment and provision of metrics and tools for quantitative analysis.