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WU E, QIAO L. [Microbial metaproteomics--From sample processing to data acquisition and analysis]. Se Pu 2024; 42:658-668. [PMID: 38966974 PMCID: PMC11224941 DOI: 10.3724/sp.j.1123.2024.02009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Indexed: 07/06/2024] Open
Abstract
Microorganisms are closely associated with human diseases and health. Understanding the composition and function of microbial communities requires extensive research. Metaproteomics has recently become an important method for throughout and in-depth study of microorganisms. However, major challenges in terms of sample processing, mass spectrometric data acquisition, and data analysis limit the development of metaproteomics owing to the complexity and high heterogeneity of microbial community samples. In metaproteomic analysis, optimizing the preprocessing method for different types of samples and adopting different microbial isolation, enrichment, extraction, and lysis schemes are often necessary. Similar to those for single-species proteomics, the mass spectrometric data acquisition modes for metaproteomics include data-dependent acquisition (DDA) and data-independent acquisition (DIA). DIA can collect comprehensive peptide information from a sample and holds great potential for future development. However, data analysis for DIA is challenged by the complexity of metaproteome samples, which hinders the deeper coverage of metaproteomes. The most important step in data analysis is the construction of a protein sequence database. The size and completeness of the database strongly influence not only the number of identifications, but also analyses at the species and functional levels. The current gold standard for metaproteome database construction is the metagenomic sequencing-based protein sequence database. A public database-filtering method based on an iterative database search has been proven to have strong practical value. The peptide-centric DIA data analysis method is a mainstream data analysis strategy. The development of deep learning and artificial intelligence will greatly promote the accuracy, coverage, and speed of metaproteomic analysis. In terms of downstream bioinformatics analysis, a series of annotation tools that can perform species annotation at the protein, peptide, and gene levels has been developed in recent years to determine the composition of microbial communities. The functional analysis of microbial communities is a unique feature of metaproteomics compared with other omics approaches. Metaproteomics has become an important component of the multi-omics analysis of microbial communities, and has great development potential in terms of depth of coverage, sensitivity of detection, and completeness of data analysis.
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Nebauer DJ, Pearson LA, Neilan BA. Critical steps in an environmental metaproteomics workflow. Environ Microbiol 2024; 26:e16637. [PMID: 38760994 DOI: 10.1111/1462-2920.16637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 04/30/2024] [Indexed: 05/20/2024]
Abstract
Environmental metaproteomics is a rapidly advancing field that provides insights into the structure, dynamics, and metabolic activity of microbial communities. As the field is still maturing, it lacks consistent workflows, making it challenging for non-expert researchers to navigate. This review aims to introduce the workflow of environmental metaproteomics. It outlines the standard practices for sample collection, processing, and analysis, and offers strategies to overcome the unique challenges presented by common environmental matrices such as soil, freshwater, marine environments, biofilms, sludge, and symbionts. The review also highlights the bottlenecks in data analysis that are specific to metaproteomics samples and provides suggestions for researchers to obtain high-quality datasets. It includes recent benchmarking studies and descriptions of software packages specifically built for metaproteomics analysis. The article is written without assuming the reader's familiarity with single-organism proteomic workflows, making it accessible to those new to proteomics or mass spectrometry in general. This primer for environmental metaproteomics aims to improve accessibility to this exciting technology and empower researchers to tackle challenging and ambitious research questions. While it is primarily a resource for those new to the field, it should also be useful for established researchers looking to streamline or troubleshoot their metaproteomics experiments.
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Affiliation(s)
- Daniel J Nebauer
- School of Environmental and Life Sciences, The University of Newcastle, Callaghan, New South Wales, Australia
- Centre of Excellence in Synthetic Biology, Australian Research Council, Sydney, New South Wales, Australia
| | - Leanne A Pearson
- School of Environmental and Life Sciences, The University of Newcastle, Callaghan, New South Wales, Australia
- Centre of Excellence in Synthetic Biology, Australian Research Council, Sydney, New South Wales, Australia
| | - Brett A Neilan
- School of Environmental and Life Sciences, The University of Newcastle, Callaghan, New South Wales, Australia
- Centre of Excellence in Synthetic Biology, Australian Research Council, Sydney, New South Wales, Australia
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Wu E, Mallawaarachchi V, Zhao J, Yang Y, Liu H, Wang X, Shen C, Lin Y, Qiao L. Contigs directed gene annotation (ConDiGA) for accurate protein sequence database construction in metaproteomics. MICROBIOME 2024; 12:58. [PMID: 38504332 PMCID: PMC10949615 DOI: 10.1186/s40168-024-01775-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 02/05/2024] [Indexed: 03/21/2024]
Abstract
BACKGROUND Microbiota are closely associated with human health and disease. Metaproteomics can provide a direct means to identify microbial proteins in microbiota for compositional and functional characterization. However, in-depth and accurate metaproteomics is still limited due to the extreme complexity and high diversity of microbiota samples. It is generally recommended to use metagenomic data from the same samples to construct the protein sequence database for metaproteomic data analysis. Although different metagenomics-based database construction strategies have been developed, an optimization of gene taxonomic annotation has not been reported, which, however, is extremely important for accurate metaproteomic analysis. RESULTS Herein, we proposed an accurate taxonomic annotation pipeline for genes from metagenomic data, namely contigs directed gene annotation (ConDiGA), and used the method to build a protein sequence database for metaproteomic analysis. We compared our pipeline (ConDiGA or MD3) with two other popular annotation pipelines (MD1 and MD2). In MD1, genes were directly annotated against the whole bacterial genome database; in MD2, contigs were annotated against the whole bacterial genome database and the taxonomic information of contigs was assigned to the genes; in MD3, the most confident species from the contigs annotation results were taken as reference to annotate genes. Annotation tools, including BLAST, Kaiju, and Kraken2, were compared. Based on a synthetic microbial community of 12 species, it was found that Kaiju with the MD3 pipeline outperformed the others in the construction of protein sequence database from metagenomic data. Similar performance was also observed with a fecal sample, as well as in silico mixed datasets of the simulated microbial community and the fecal sample. CONCLUSIONS Overall, we developed an optimized pipeline for gene taxonomic annotation to construct protein sequence databases. Our study can tackle the current taxonomic annotation reliability problem in metagenomics-derived protein sequence database and can promote the in-depth metaproteomic analysis of microbiome. The unique metagenomic and metaproteomic datasets of the 12 bacterial species are publicly available as a standard benchmarking sample for evaluating various analysis pipelines. The code of ConDiGA is open access at GitHub for the analysis of microbiota samples. Video Abstract.
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Affiliation(s)
- Enhui Wu
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, 200000, China
| | - Vijini Mallawaarachchi
- School of Computing, College of Engineering, Computing and Cybernetics, The Australian National University, Canberra, ACT, 2600, Australia
- Flinders Accelerator for Microbiome Exploration, College of Science and Engineering, Flinders University, Bedford Park, SA, 5042, Australia
| | - Jinzhi Zhao
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, 200000, China
| | - Yi Yang
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, 200000, China
| | - Hebin Liu
- Shanghai Omicsolution Co., Ltd, Shanghai, 200000, China
| | - Xiaoqing Wang
- Shanghai Omicsolution Co., Ltd, Shanghai, 200000, China
| | - Chengpin Shen
- Shanghai Omicsolution Co., Ltd, Shanghai, 200000, China
| | - Yu Lin
- School of Computing, College of Engineering, Computing and Cybernetics, The Australian National University, Canberra, ACT, 2600, Australia
| | - Liang Qiao
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, 200000, China.
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Law SR, Mathes F, Paten AM, Alexandre PA, Regmi R, Reid C, Safarchi A, Shaktivesh S, Wang Y, Wilson A, Rice SA, Gupta VVSR. Life at the borderlands: microbiomes of interfaces critical to One Health. FEMS Microbiol Rev 2024; 48:fuae008. [PMID: 38425054 PMCID: PMC10977922 DOI: 10.1093/femsre/fuae008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 02/12/2024] [Accepted: 02/27/2024] [Indexed: 03/02/2024] Open
Abstract
Microbiomes are foundational components of the environment that provide essential services relating to food security, carbon sequestration, human health, and the overall well-being of ecosystems. Microbiota exert their effects primarily through complex interactions at interfaces with their plant, animal, and human hosts, as well as within the soil environment. This review aims to explore the ecological, evolutionary, and molecular processes governing the establishment and function of microbiome-host relationships, specifically at interfaces critical to One Health-a transdisciplinary framework that recognizes that the health outcomes of people, animals, plants, and the environment are tightly interconnected. Within the context of One Health, the core principles underpinning microbiome assembly will be discussed in detail, including biofilm formation, microbial recruitment strategies, mechanisms of microbial attachment, community succession, and the effect these processes have on host function and health. Finally, this review will catalogue recent advances in microbiology and microbial ecology methods that can be used to profile microbial interfaces, with particular attention to multi-omic, advanced imaging, and modelling approaches. These technologies are essential for delineating the general and specific principles governing microbiome assembly and functions, mapping microbial interconnectivity across varying spatial and temporal scales, and for the establishment of predictive frameworks that will guide the development of targeted microbiome-interventions to deliver One Health outcomes.
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Affiliation(s)
- Simon R Law
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture and Food, Canberra, ACT 2601, Australia
| | - Falko Mathes
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Environment, Floreat, WA 6014, Australia
| | - Amy M Paten
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Environment, Canberra, ACT 2601, Australia
| | - Pamela A Alexandre
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture and Food, St Lucia, Qld 4072, Australia
| | - Roshan Regmi
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture and Food, Urrbrae, SA 5064, Australia
| | - Cameron Reid
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Environment, Urrbrae, SA 5064, Australia
| | - Azadeh Safarchi
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Health and Biosecurity, Westmead, NSW 2145, Australia
| | - Shaktivesh Shaktivesh
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Data 61, Clayton, Vic 3168, Australia
| | - Yanan Wang
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Health and Biosecurity, Adelaide SA 5000, Australia
| | - Annaleise Wilson
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Health and Biosecurity, Geelong, Vic 3220, Australia
| | - Scott A Rice
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture, and Food, Westmead, NSW 2145, Australia
| | - Vadakattu V S R Gupta
- CSIRO MOSH-Future Science Platform, Australia
- CSIRO Agriculture and Food, Urrbrae, SA 5064, Australia
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Messer LF, Lee CE, Wattiez R, Matallana-Surget S. 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. MICROBIOME 2024; 12:36. [PMID: 38389111 PMCID: PMC10882806 DOI: 10.1186/s40168-024-01751-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 01/03/2024] [Indexed: 02/24/2024]
Abstract
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.
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Affiliation(s)
- Lauren F Messer
- Division of Biological and Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling, FK9 4LA, Scotland
| | - Charlotte E Lee
- Division of Biological and Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling, FK9 4LA, Scotland
| | - Ruddy Wattiez
- Proteomics and Microbiology Department, University of Mons, Mons, 7000, Belgium
| | - Sabine Matallana-Surget
- Division of Biological and Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling, FK9 4LA, Scotland.
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Wu E, Yang Y, Zhao J, Zheng J, Wang X, Shen C, Qiao L. High-Abundance Protein-Guided Hybrid Spectral Library for Data-Independent Acquisition Metaproteomics. Anal Chem 2024; 96:1029-1037. [PMID: 38180447 DOI: 10.1021/acs.analchem.3c03255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2024]
Abstract
Metaproteomics offers a direct avenue to identify microbial proteins in microbiota, enabling the compositional and functional characterization of microbiota. Due to the complexity and heterogeneity of microbial communities, in-depth and accurate metaproteomics faces tremendous limitations. One challenge in metaproteomics is the construction of a suitable protein sequence database to interpret the highly complex metaproteomic data, especially in the absence of metagenomic sequencing data. Herein, we present a high-abundance protein-guided hybrid spectral library strategy for in-depth data independent acquisition (DIA) metaproteomic analysis (HAPs-hyblibDIA). A dedicated high-abundance protein database of gut microbial species is constructed and used to mine the taxonomic information on microbiota samples. Then, a sample-specific protein sequence database is built based on the taxonomic information using Uniprot protein sequence for subsequent analysis of the DIA data using hybrid spectral library-based DIA analysis. We evaluated the accuracy and sensitivity of the method using synthetic microbial community samples and human gut microbiome samples. It was demonstrated that the strategy can successfully identify taxonomic compositions of microbiota samples and that the peptides identified by HAPs-hyblibDIA overlapped greatly with the peptides identified using a metagenomic sequencing-derived database. At the peptide and species level, our results can serve as a complement to the results obtained using a metagenomic sequencing-derived database. Furthermore, we validated the applicability of the HAPs-hyblibDIA strategy in a cohort of human gut microbiota samples of colorectal cancer patients and controls, highlighting its usability in biomedical research.
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Affiliation(s)
- Enhui Wu
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai 200000, China
| | - Yi Yang
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai 200000, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 310000, China
| | - Jinzhi Zhao
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai 200000, China
| | - Jianxujie Zheng
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai 200000, China
| | - Xiaoqing Wang
- Shanghai Omicsolution Co., Ltd., Shanghai 200000, China
| | - Chengpin Shen
- Shanghai Omicsolution Co., Ltd., Shanghai 200000, China
| | - Liang Qiao
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai 200000, China
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Bihani S, Gupta A, Mehta S, Rajczewski A, Griffin T, Jagtap P, Srivastava S. Metaproteomics for Coinfections in the Upper Respiratory Tract: The Case of COVID-19. Methods Mol Biol 2024; 2820:165-185. [PMID: 38941023 DOI: 10.1007/978-1-0716-3910-8_15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2024]
Abstract
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.
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Affiliation(s)
- Surbhi Bihani
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India
| | - Aryan Gupta
- Department of Chemistry, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India
| | - Subina Mehta
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
| | - Andrew Rajczewski
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
| | - Timothy Griffin
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
| | - Pratik Jagtap
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA.
| | - Sanjeeva Srivastava
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India.
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Ray AE, Tribbia DZ, Cowan DA, Ferrari BC. Clearing the air: unraveling past and guiding future research in atmospheric chemosynthesis. Microbiol Mol Biol Rev 2023; 87:e0004823. [PMID: 37914532 PMCID: PMC10732025 DOI: 10.1128/mmbr.00048-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2023] Open
Abstract
SUMMARY Atmospheric chemosynthesis is a recently proposed form of chemoautotrophic microbial primary production. The proposed process relies on the oxidation of trace concentrations of hydrogen (≤530 ppbv), carbon monoxide (≤90 ppbv), and methane (≤1,870 ppbv) gases using high-affinity enzymes. Atmospheric hydrogen and carbon monoxide oxidation have been primarily linked to microbial growth in desert surface soils scarce in liquid water and organic nutrients, and low in photosynthetic communities. It is well established that the oxidation of trace hydrogen and carbon monoxide gases widely supports the persistence of microbial communities in a diminished metabolic state, with the former potentially providing a reliable source of metabolic water. Microbial atmospheric methane oxidation also occurs in oligotrophic desert soils and is widespread throughout copiotrophic environments, with established links to microbial growth. Despite these findings, the direct link between trace gas oxidation and carbon fixation remains disputable. Here, we review the supporting evidence, outlining major gaps in our understanding of this phenomenon, and propose approaches to validate atmospheric chemosynthesis as a primary production process. We also explore the implications of this minimalistic survival strategy in terms of nutrient cycling, climate change, aerobiology, and astrobiology.
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Affiliation(s)
- Angelique E. Ray
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Sydney, Australia
- Australian Centre for Astrobiology, UNSW Sydney, Sydney, Australia
| | - Dana Z. Tribbia
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Sydney, Australia
- Australian Centre for Astrobiology, UNSW Sydney, Sydney, Australia
| | - Don A. Cowan
- Centre for Microbial Ecology and Genomics, Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria, South Africa
| | - Belinda C. Ferrari
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Sydney, Australia
- Australian Centre for Astrobiology, UNSW Sydney, Sydney, Australia
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Ramos-Nascimento A, Grenga L, Haange SB, Himmelmann A, Arndt FS, Ly YT, Miotello G, Pible O, Jehmlich N, Engelmann B, von Bergen M, Mulder E, Frings-Meuthen P, Hellweg CE, Jordan J, Rolle-Kampczyk U, Armengaud J, Moeller R. Human gut microbiome and metabolite dynamics under simulated microgravity. Gut Microbes 2023; 15:2259033. [PMID: 37749878 PMCID: PMC10524775 DOI: 10.1080/19490976.2023.2259033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 09/11/2023] [Indexed: 09/27/2023] Open
Abstract
The Artificial Gravity Bed Rest - European Space Agency (AGBRESA) study was the first joint bed rest study by ESA, DLR, and NASA that examined the effect of simulated weightlessness on the human body and assessed the potential benefits of artificial gravity as a countermeasure in an analog of long-duration spaceflight. In this study, we investigated the impact of simulated microgravity on the gut microbiome of 12 participants during a 60-day head-down tilt bed rest at the :envihab facilities. Over 60 days of simulated microgravity resulted in a mild change in the gut microbiome, with distinct microbial patterns and pathway expression in the feces of the countermeasure group compared to the microgravity simulation-only group. Additionally, we found that the countermeasure protocols selectively increased the abundance of beneficial short-chain fatty acids in the gut, such as acetate, butyrate, and propionate. Some physiological signatures also included the modulation of taxa reported to be either beneficial or opportunistic, indicating a mild adaptation in the microbiome network balance. Our results suggest that monitoring the gut microbial catalog along with pathway clustering and metabolite profiling is an informative synergistic strategy to determine health disturbances and the outcome of countermeasure protocols for future space missions.
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Affiliation(s)
- Ana Ramos-Nascimento
- Institute of Aerospace Medicine, German Aerospace Center (DLR e.V.), Cologne, Germany
| | - Lucia Grenga
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, Bagnols sur Cèze, France
| | - Sven-Bastiaan Haange
- Department of Metabolomics, UFZ-Helmholtz Centre for Environmental Research Leipzig, Leipzig, Germany
| | - Alexandra Himmelmann
- Institute of Aerospace Medicine, German Aerospace Center (DLR e.V.), Cologne, Germany
| | - Franca Sabine Arndt
- Institute of Aerospace Medicine, German Aerospace Center (DLR e.V.), Cologne, Germany
| | - Yen-Tran Ly
- Institute of Aerospace Medicine, German Aerospace Center (DLR e.V.), Cologne, Germany
| | - Guylaine Miotello
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, Bagnols sur Cèze, France
| | - Olivier Pible
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, Bagnols sur Cèze, France
| | - Nico Jehmlich
- Department of Metabolomics, UFZ-Helmholtz Centre for Environmental Research Leipzig, Leipzig, Germany
| | - Beatrice Engelmann
- Department of Metabolomics, UFZ-Helmholtz Centre for Environmental Research Leipzig, Leipzig, Germany
| | - Martin von Bergen
- Department of Metabolomics, UFZ-Helmholtz Centre for Environmental Research Leipzig, Leipzig, Germany
| | - Edwin Mulder
- Institute of Aerospace Medicine, German Aerospace Center (DLR e.V.), Cologne, Germany
| | - Petra Frings-Meuthen
- Institute of Aerospace Medicine, German Aerospace Center (DLR e.V.), Cologne, Germany
| | | | - Jens Jordan
- Institute of Aerospace Medicine, German Aerospace Center (DLR e.V.), Cologne, Germany
| | - Ulrike Rolle-Kampczyk
- Department of Metabolomics, UFZ-Helmholtz Centre for Environmental Research Leipzig, Leipzig, Germany
| | - Jean Armengaud
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, Bagnols sur Cèze, France
| | - Ralf Moeller
- Institute of Aerospace Medicine, German Aerospace Center (DLR e.V.), Cologne, Germany
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10
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Zhu YG, Peng J, Chen C, Xiong C, Li S, Ge A, Wang E, Liesack W. Harnessing biological nitrogen fixation in plant leaves. TRENDS IN PLANT SCIENCE 2023; 28:1391-1405. [PMID: 37270352 DOI: 10.1016/j.tplants.2023.05.009] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 05/11/2023] [Accepted: 05/15/2023] [Indexed: 06/05/2023]
Abstract
The importance of biological nitrogen fixation (BNF) in securing food production for the growing world population with minimal environmental cost has been increasingly acknowledged. Leaf surfaces are one of the biggest microbial habitats on Earth, harboring diverse free-living N2-fixers. These microbes inhabit the epiphytic and endophytic phyllosphere and contribute significantly to plant N supply and growth. Here, we summarize the contribution of phyllosphere-BNF to global N cycling, evaluate the diversity of leaf-associated N2-fixers across plant hosts and ecosystems, illustrate the ecological adaptation of N2-fixers to the phyllosphere, and identify the environmental factors driving BNF. Finally, we discuss potential BNF engineering strategies to improve the nitrogen uptake in plant leaves and thus sustainable food production.
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Affiliation(s)
- Yong-Guan Zhu
- State Key Laboratory of Urban and Regional Ecology, Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China.
| | - Jingjing Peng
- State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, 100193, China
| | - Cai Chen
- Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
| | - Chao Xiong
- College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Shule Li
- Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
| | - Anhui Ge
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, SIBS, Chinese Academy of Sciences, Shanghai, 200032, China
| | - Ertao Wang
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, SIBS, Chinese Academy of Sciences, Shanghai, 200032, China
| | - Werner Liesack
- Max Planck Institute for Terrestrial Microbiology, Marburg, 35043, Germany
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11
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Kleikamp HBC, Grouzdev D, Schaasberg P, van Valderen R, van der Zwaan R, Wijgaart RVD, Lin Y, Abbas B, Pronk M, van Loosdrecht MCM, Pabst M. Metaproteomics, metagenomics and 16S rRNA sequencing provide different perspectives on the aerobic granular sludge microbiome. WATER RESEARCH 2023; 246:120700. [PMID: 37866247 DOI: 10.1016/j.watres.2023.120700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 09/29/2023] [Accepted: 10/04/2023] [Indexed: 10/24/2023]
Abstract
The tremendous progress in sequencing technologies has made DNA sequencing routine for microbiome studies. Additionally, advances in mass spectrometric techniques have extended conventional proteomics into the field of microbial ecology. However, systematic studies that provide a better understanding of the complementary nature of these 'omics' approaches, particularly for complex environments such as wastewater treatment sludge, are urgently needed. Here, we describe a comparative metaomics study on aerobic granular sludge from three different wastewater treatment plants. For this, we employed metaproteomics, whole metagenome, and 16S rRNA amplicon sequencing to study the same granule material with uniform size. We furthermore compare the taxonomic profiles using the Genome Taxonomy Database (GTDB) to enhance the comparability between the different approaches. Though the major taxonomies were consistently identified in the different aerobic granular sludge samples, the taxonomic composition obtained by the different omics techniques varied significantly at the lower taxonomic levels, which impacts the interpretation of the nutrient removal processes. Nevertheless, as demonstrated by metaproteomics, the genera that were consistently identified in all techniques cover the majority of the protein biomass. The established metaomics data and the contig classification pipeline are publicly available, which provides a valuable resource for further studies on metabolic processes in aerobic granular sludge.
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Affiliation(s)
- Hugo B C Kleikamp
- Department of Biotechnology, Delft University of Technology, Delft, the Netherlands.
| | | | - Pim Schaasberg
- Department of Biotechnology, Delft University of Technology, Delft, the Netherlands
| | - Ramon van Valderen
- Department of Biotechnology, Delft University of Technology, Delft, the Netherlands
| | - Ramon van der Zwaan
- Department of Biotechnology, Delft University of Technology, Delft, the Netherlands
| | - Roel van de Wijgaart
- Department of Biotechnology, Delft University of Technology, Delft, the Netherlands
| | - Yuemei Lin
- Department of Biotechnology, Delft University of Technology, Delft, the Netherlands
| | - Ben Abbas
- Department of Biotechnology, Delft University of Technology, Delft, the Netherlands
| | - Mario Pronk
- Department of Biotechnology, Delft University of Technology, Delft, the Netherlands
| | | | - Martin Pabst
- Department of Biotechnology, Delft University of Technology, Delft, the Netherlands.
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12
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Klaes S, Madan S, Deobald D, Cooper M, Adrian L. GroEL-Proteotyping of Bacterial Communities Using Tandem Mass Spectrometry. Int J Mol Sci 2023; 24:15692. [PMID: 37958676 PMCID: PMC10649880 DOI: 10.3390/ijms242115692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 10/24/2023] [Accepted: 10/25/2023] [Indexed: 11/15/2023] Open
Abstract
Profiling bacterial populations in mixed communities is a common task in microbiology. Sequencing of 16S small subunit ribosomal-RNA (16S rRNA) gene amplicons is a widely accepted and functional approach but relies on amplification primers and cannot quantify isotope incorporation. Tandem mass spectrometry proteotyping is an effective alternative for taxonomically profiling microorganisms. We suggest that targeted proteotyping approaches can complement traditional population analyses. Therefore, we describe an approach to assess bacterial community compositions at the family level using the taxonomic marker protein GroEL, which is ubiquitously found in bacteria, except a few obligate intracellular species. We refer to our method as GroEL-proteotyping. GroEL-proteotyping is based on high-resolution tandem mass spectrometry of GroEL peptides and identification of GroEL-derived taxa via a Galaxy workflow and a subsequent Python-based analysis script. Its advantage is that it can be performed with a curated and extendable sample-independent database and that GroEL can be pre-separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to reduce sample complexity, improving GroEL identification while simultaneously decreasing the instrument time. GroEL-proteotyping was validated by employing it on a comprehensive raw dataset obtained through a metaproteome approach from synthetic microbial communities as well as real human gut samples. Our data show that GroEL-proteotyping enables fast and straightforward profiling of highly abundant taxa in bacterial communities at reasonable taxonomic resolution.
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Affiliation(s)
- Simon Klaes
- Department of Environmental Biotechnology, Helmholtz Centre for Environmental Research (UFZ), 04318 Leipzig, Germany; (S.K.); (D.D.)
- Faculty III Process Sciences, Institute of Biotechnology, Chair of Geobiotechnology, Technische Universität Berlin, 13355 Berlin, Germany
| | - Shobhit Madan
- Department of Environmental Biotechnology, Helmholtz Centre for Environmental Research (UFZ), 04318 Leipzig, Germany; (S.K.); (D.D.)
- Faculty of Engineering, Ansbach University of Applied Sciences, 91522 Ansbach, Germany
| | - Darja Deobald
- Department of Environmental Biotechnology, Helmholtz Centre for Environmental Research (UFZ), 04318 Leipzig, Germany; (S.K.); (D.D.)
| | - Myriel Cooper
- Faculty III Process Sciences, Institute of Environmental Technology, Chair of Environmental Microbiology, Technische Universität Berlin, 10587 Berlin, Germany
| | - Lorenz Adrian
- Department of Environmental Biotechnology, Helmholtz Centre for Environmental Research (UFZ), 04318 Leipzig, Germany; (S.K.); (D.D.)
- Faculty III Process Sciences, Institute of Biotechnology, Chair of Geobiotechnology, Technische Universität Berlin, 13355 Berlin, Germany
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13
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Reichart NJ, Steiger AK, Van Fossen EM, McClure R, Overkleeft HS, Wright AT. Selection and enrichment of microbial species with an increased lignocellulolytic phenotype from a native soil microbiome by activity-based probing. ISME COMMUNICATIONS 2023; 3:106. [PMID: 37777628 PMCID: PMC10542759 DOI: 10.1038/s43705-023-00305-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 08/22/2023] [Accepted: 09/06/2023] [Indexed: 10/02/2023]
Abstract
Multi-omic analyses can provide information on the potential for activity within a microbial community but often lack specificity to link functions to cell, primarily offer potential for function or rely on annotated databases. Functional assays are necessary for understanding in situ microbial activity to better describe and improve microbiome biology. Targeting enzyme activity through activity-based protein profiling enhances the accuracy of functional studies. Here, we introduce a pipeline of coupling activity-based probing with fluorescence-activated cell sorting, culturing, and downstream activity assays to isolate and examine viable populations of cells expressing a function of interest. We applied our approach to a soil microbiome using two activity-based probes to enrich for communities with elevated activity for lignocellulose-degradation phenotypes as determined by four fluorogenic kinetic assays. Our approach efficiently separated and identified microbial members with heightened activity for glycosyl hydrolases, and by expanding this workflow to various probes for other function, this process can be applied to unique phenotype targets of interest.
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Affiliation(s)
- Nicholas J Reichart
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
| | - Andrea K Steiger
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Elise M Van Fossen
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Ryan McClure
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | | | - Aaron T Wright
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
- Department of Biology, Baylor University, Waco, TX, USA.
- Department of Chemistry and Biochemistry, Baylor University, Waco, TX, USA.
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14
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Mehta S, Bernt M, Chambers M, Fahrner M, Föll MC, Gruening B, Horro C, Johnson JE, Loux V, Rajczewski AT, Schilling O, Vandenbrouck Y, Gustafsson OJR, Thang WCM, Hyde C, Price G, Jagtap PD, Griffin TJ. A Galaxy of informatics resources for MS-based proteomics. Expert Rev Proteomics 2023; 20:251-266. [PMID: 37787106 DOI: 10.1080/14789450.2023.2265062] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 09/06/2023] [Indexed: 10/04/2023]
Abstract
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.
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Affiliation(s)
- Subina Mehta
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
| | - Matthias Bernt
- Helmholtz Centre for Environmental Research - UFZ, Department Computational Biology, Leipzig, Germany
| | | | - Matthias Fahrner
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Melanie Christine Föll
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA
| | - Bjoern Gruening
- Bioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, Freiburg, Germany
| | - Carlos Horro
- Proteomics Unit, Department of Biomedicine, University of Bergen, Bergen, Norway
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - James E Johnson
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, USA
| | - Valentin Loux
- Université Paris-Saclay, INRAE, MaIAGE, Jouy-en-Josas, France
- Université Paris-Saclay, INRAE, BioinfOmics, MIGALE bioinformatics facility, Jouy-en-Josas, France
| | - Andrew T Rajczewski
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
| | - Oliver Schilling
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | | | - W C Mike Thang
- Queensland Cyber Infrastructure Foundation (QCIF), Australia
- Institute of Molecular Bioscience, University of Queensland, St Lucia, Australia
| | - Cameron Hyde
- Queensland Cyber Infrastructure Foundation (QCIF), Australia
- Sippy Downs, University of the Sunshine Coast, Australia
| | - Gareth Price
- Queensland Cyber Infrastructure Foundation (QCIF), Australia
- Institute of Molecular Bioscience, University of Queensland, St Lucia, Australia
| | - Pratik D Jagtap
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
| | - Timothy J Griffin
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
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15
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Geller AM, Levy A. "What I cannot create, I do not understand": elucidating microbe-microbe interactions to facilitate plant microbiome engineering. Curr Opin Microbiol 2023; 72:102283. [PMID: 36868050 DOI: 10.1016/j.mib.2023.102283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Revised: 01/22/2023] [Accepted: 01/24/2023] [Indexed: 03/05/2023]
Abstract
Plant-microbe interactions are important for both physiological and pathological processes. Despite the significance of plant-microbe interactions, microbe-microbe interactions themselves represent an important, complex, dynamic network that warrants deeper investigation. To understand how microbe-microbe interactions affect plant microbiomes, one approach is to systematically understand all the factors involved in successful engineering of a microbial community. This follows the physicist Richard Feynman's declaration: "what I cannot create, I do not understand". This review highlights recent studies that focus on aspects that we believe are important for building (ergo understanding) microbe-microbe interactions in the plant environment, including pairwise screening, intelligent application of cross-feeding models, spatial distributions of microbes, and understudied interactions between bacteria and fungi, phages, and protists. We offer a framework for systematic collection and centralized integration of data of plant microbiomes that could organize all the factors that can help ecologists understand microbiomes and help synthetic ecologists engineer beneficial microbiomes.
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Affiliation(s)
- Alexander M Geller
- Department of Plant Pathology and Microbiology, Institute of Environmental Science, Robert H. Smith Faculty of Agriculture, Food, and Environment, The Hebrew University of Jerusalem, Rehovot 7610001, Israel
| | - Asaf Levy
- Department of Plant Pathology and Microbiology, Institute of Environmental Science, Robert H. Smith Faculty of Agriculture, Food, and Environment, The Hebrew University of Jerusalem, Rehovot 7610001, Israel.
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16
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Armengaud J. Metaproteomics to understand how microbiota function: The crystal ball predicts a promising future. Environ Microbiol 2023; 25:115-125. [PMID: 36209500 PMCID: PMC10091800 DOI: 10.1111/1462-2920.16238] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Accepted: 09/30/2022] [Indexed: 01/21/2023]
Abstract
In the medical, environmental, and biotechnological fields, microbial communities have attracted much attention due to their roles and numerous possible applications. The study of these communities is challenging due to their diversity and complexity. Innovative methods are needed to identify the taxonomic components of individual microbiota, their changes over time, and to determine how microoorganisms interact and function. Metaproteomics is based on the identification and quantification of proteins, and can potentially provide this full picture. Due to the wide molecular panorama and functional insights it provides, metaproteomics is gaining momentum in microbiome and holobiont research. Its full potential should be unleashed in the coming years with progress in speed and cost of analyses. In this exploratory crystal ball exercise, I discuss the technical and conceptual advances in metaproteomics that I expect to drive innovative research over the next few years in microbiology. I also debate the concepts of 'microbial dark matter' and 'Metaproteomics-Assembled Proteomes (MAPs)' and present some long-term prospects for metaproteomics in clinical diagnostics and personalized medicine, environmental monitoring, agriculture, and biotechnology.
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Affiliation(s)
- Jean Armengaud
- Département Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, Bagnols-sur-Cèze, France
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17
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Pible O, Petit P, Steinmetz G, Rivasseau C, Armengaud J. Taxonomical composition and functional analysis of biofilms sampled from a nuclear storage pool. Front Microbiol 2023; 14:1148976. [PMID: 37125163 PMCID: PMC10133526 DOI: 10.3389/fmicb.2023.1148976] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 03/27/2023] [Indexed: 05/02/2023] Open
Abstract
Sampling small amounts of biofilm from harsh environments such as the biofilm present on the walls of a radioactive material storage pool offers few analytical options if taxonomic characterization and estimation of the different biomass contributions are the objectives. Although 16S/18S rRNA amplification on extracted DNA and sequencing is the most widely applied method, its reliability in terms of quantitation has been questioned as yields can be species-dependent. Here, we propose a tandem-mass spectrometry proteotyping approach consisting of acquiring peptide data and interpreting then against a generalist database without any a priori. The peptide sequence information is transformed into useful taxonomical information that allows to obtain the different biomass contributions at different taxonomical ranks. This new methodology is applied for the first time to analyze the composition of biofilms from minute quantities of material collected from a pool used to store radioactive sources in a nuclear facility. For these biofilms, we report the identification of three genera, namely Sphingomonas, Caulobacter, and Acidovorax, and their functional characterization by metaproteomics which shows that these organisms are metabolic active. Differential expression of Gene Ontology GOslim terms between the two main microorganisms highlights their metabolic specialization.
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Affiliation(s)
- Olivier Pible
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, Bagnols-sur-Cèze, France
| | - Pauline Petit
- Université Grenoble Alpes, CEA, CNRS, IRIG, Grenoble, France
| | - Gérard Steinmetz
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, Bagnols-sur-Cèze, France
| | - Corinne Rivasseau
- Université Grenoble Alpes, CEA, CNRS, IRIG, Grenoble, France
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), Gif-sur-Yvette, France
| | - Jean Armengaud
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, Bagnols-sur-Cèze, France
- *Correspondence: Jean Armengaud,
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18
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Unique Insights into How Plants and Soil Microbiomes Interact Are at Our Fingertips. mSystems 2022; 7:e0058922. [PMID: 35975919 PMCID: PMC9600158 DOI: 10.1128/msystems.00589-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Global warming endangers our world, with probably a drastic drop in food production as one of the first vital consequences for humanity. To maintain or improve quality and sustainable yields, the burning imperative for agriculture is to rapidly integrate the essential component for plant development and soil regeneration, namely, the soil microbiome. Although enormous progress has been made in identifying the components of this microbiome, the way in which they interact with each other and with plants remains poorly understood. Lidbury I, Raguideau S, Borsetto C, Murphy A, et al. (mSystems 7:e00025-22, 2022, https://doi.org/10.1128/mSystems.00025-22) illustrate how metaproteomics helps define key interactions between plants and microorganisms at the rhizospheric interface. The many extracellular proteins identified and quantified by this methodology uniquely explain the observed phenotype. This study shows that the adoption of metaproteomics is no longer an option that microbiologists should consider but a must!
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19
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Hardouin P, Pible O, Marchandin H, Culotta K, Armengaud J, Chiron R, Grenga L. Quick and wide-range taxonomical repertoire establishment of the cystic fibrosis lung microbiota by tandem mass spectrometry on sputum samples. Front Microbiol 2022; 13:975883. [PMID: 36312921 PMCID: PMC9608366 DOI: 10.3389/fmicb.2022.975883] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 09/15/2022] [Indexed: 11/19/2022] Open
Abstract
Microorganisms proteotyping by tandem mass spectrometry has been recently shown as a powerful methodology to identify the wide-range taxonomy and biomass of microbiota. Sputum is the recommended specimen for routine microbiological monitoring of Cystic Fibrosis (CF) patients but has been rarely submitted to tandem mass spectrometry-based proteotyping. In this study, we compared the microbial components of spontaneous and induced sputum samples from three cystic fibrosis patients. Although the presence of microbial proteins is much lower than host proteins, we report that the microbiota’s components present in the samples can be identified, as well as host biomarkers and functional insights into the microbiota. No significant difference was found in microorganism abundance between paired spontaneous and induced sputum samples. Microbial proteins linked to resistance, iron uptake, and biofilm-forming ability were observed in sputa independently of the sampling method. This unbiased and enlarged view of the CF microbiome could be highly complementary to culture and relevant for the clinical management of CF patients by improving knowledge about the host-pathogen dynamics and CF pathophysiology.
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Affiliation(s)
- Pauline Hardouin
- Département Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SPI, Bagnols-sur-Cèze, France
- Université de Montpellier, Laboratoire Innovations Technologiques pour la Détection et le Diagnostic (Li2D), Bagnols-sur-Cèze, France
| | - Olivier Pible
- Département Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SPI, Bagnols-sur-Cèze, France
| | - Hélène Marchandin
- HydroSciences Montpellier, CNRS, IRD, Service de Microbiologie et Hygiène Hospitalière, Université de Montpellier, CHU de Nîmes, Nîmes, France
| | - Karen Culotta
- Département Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SPI, Bagnols-sur-Cèze, France
| | - Jean Armengaud
- Département Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SPI, Bagnols-sur-Cèze, France
| | - Raphaël Chiron
- HydroSciences Montpellier, CNRS, IRD, Centre de Ressources et de Compétences de la Mucoviscidose, Université de Montpellier, CHU de Montpellier, Montpellier, France
| | - Lucia Grenga
- Département Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SPI, Bagnols-sur-Cèze, France
- *Correspondence: Lucia Grenga,
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20
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Carper DL, Appidi MR, Mudbhari S, Shrestha HK, Hettich RL, Abraham PE. The Promises, Challenges, and Opportunities of Omics for Studying the Plant Holobiont. Microorganisms 2022; 10:microorganisms10102013. [PMID: 36296289 PMCID: PMC9609723 DOI: 10.3390/microorganisms10102013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 10/03/2022] [Accepted: 10/05/2022] [Indexed: 11/16/2022] Open
Abstract
Microorganisms are critical drivers of biological processes that contribute significantly to plant sustainability and productivity. In recent years, emerging research on plant holobiont theory and microbial invasion ecology has radically transformed how we study plant–microbe interactions. Over the last few years, we have witnessed an accelerating pace of advancements and breadth of questions answered using omic technologies. Herein, we discuss how current state-of-the-art genomics, transcriptomics, proteomics, and metabolomics techniques reliably transcend the task of studying plant–microbe interactions while acknowledging existing limitations impeding our understanding of plant holobionts.
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Affiliation(s)
- Dana L. Carper
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Manasa R. Appidi
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- Graduate School of Genome Science and Technology, University of Tennessee-Knoxville, Knoxville, TN 37996, USA
| | - Sameer Mudbhari
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- Graduate School of Genome Science and Technology, University of Tennessee-Knoxville, Knoxville, TN 37996, USA
| | - Him K. Shrestha
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- Graduate School of Genome Science and Technology, University of Tennessee-Knoxville, Knoxville, TN 37996, USA
| | - Robert L. Hettich
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Paul E. Abraham
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- Correspondence:
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21
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Stimulation of Distinct Rhizosphere Bacteria Drives Phosphorus and Nitrogen Mineralization in Oilseed Rape under Field Conditions. mSystems 2022; 7:e0002522. [PMID: 35862821 PMCID: PMC9426549 DOI: 10.1128/msystems.00025-22] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Advances in DNA sequencing technologies have drastically changed our perception of the structure and complexity of the plant microbiome. By comparison, our ability to accurately identify the metabolically active fraction of soil microbiota and its specific functional role in augmenting plant health is relatively limited. Important ecological interactions being performed by microbes can be investigated by analyzing the extracellular protein fraction. Here, we combined a unique protein extraction method and an iterative bioinformatics pipeline to capture and identify extracellular proteins (metaexoproteomics) synthesized in the rhizosphere of Brassica spp. We first validated our method in the laboratory by successfully identifying proteins related to a host plant (Brassica rapa) and its bacterial inoculant, Pseudomonas putida BIRD-1. This identified numerous rhizosphere specific proteins linked to the acquisition of plant-derived nutrients in P. putida. Next, we analyzed natural field-soil microbial communities associated with Brassica napus L. (oilseed rape). By combining metagenomics with metaexoproteomics, 1,885 plant, insect, and microbial proteins were identified across bulk and rhizosphere samples. Metaexoproteomics identified a significant shift in the metabolically active fraction of the soil microbiota responding to the presence of B. napus roots that was not apparent in the composition of the total microbial community (metagenome). This included stimulation of rhizosphere-specialized bacteria, such as Gammaproteobacteria, Betaproteobacteria, and Flavobacteriia, and the upregulation of plant beneficial functions related to phosphorus and nitrogen mineralization. Our metaproteomic assessment of the “active” plant microbiome at the field-scale demonstrates the importance of moving beyond metagenomics to determine ecologically important plant-microbe interactions underpinning plant health. IMPORTANCE Plant-microbe interactions are critical to ecosystem function and crop production. While significant advances have been made toward understanding the structure of the plant microbiome, learning about its full functional role is still in its infancy. This is primarily due to an incomplete ability to determine in situ plant-microbe interactions actively operating under field conditions. Proteins are the functional entities of the cell. Therefore, their identification and relative quantification within a microbial community provide the best proxy for which microbes are the most metabolically active and which are driving important plant-microbe interactions. Here, we provide the first metaexoproteomics assessment of the plant microbiome using field-grown oilseed rape as the model crop species, identifying key taxa responsible for specific ecological interactions. Gaining a mechanistic understanding of the plant microbiome is central to developing engineered plant microbiomes to improve sustainable agricultural approaches and reduce our reliance on nonrenewable resources.
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22
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Lee JY, Mitchell HD, Burnet MC, Wu R, Jenson SC, Merkley ED, Nakayasu ES, Nicora CD, Jansson JK, Burnum-Johnson KE, Payne SH. Uncovering Hidden Members and Functions of the Soil Microbiome Using De Novo Metaproteomics. J Proteome Res 2022; 21:2023-2035. [PMID: 35793793 PMCID: PMC9361346 DOI: 10.1021/acs.jproteome.2c00334] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
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Metaproteomics has
been increasingly utilized for high-throughput
characterization of proteins in complex environments and has been
demonstrated to provide insights into microbial composition and functional
roles. However, significant challenges remain in metaproteomic data
analysis, including creation of a sample-specific protein sequence
database. A well-matched database is a requirement for successful
metaproteomics analysis, and the accuracy and sensitivity of PSM identification
algorithms suffer when the database is incomplete or contains extraneous
sequences. When matched DNA sequencing data of the sample is unavailable
or incomplete, creating the proteome database that accurately represents
the organisms in the sample is a challenge. Here, we leverage a de novo peptide sequencing approach to identify the sample
composition directly from metaproteomic data. First, we created a
deep learning model, Kaiko, to predict the peptide sequences from
mass spectrometry data and trained it on 5 million peptide–spectrum
matches from 55 phylogenetically diverse bacteria. After training,
Kaiko successfully identified organisms from soil isolates and synthetic
communities directly from proteomics data. Finally, we created a pipeline
for metaproteome database generation using Kaiko. We tested the pipeline
on native soils collected in Kansas, showing that the de novo sequencing model can be employed as an alternative and complementary
method to construct the sample-specific protein database instead of
relying on (un)matched metagenomes. Our pipeline identified all highly
abundant taxa from 16S rRNA sequencing of the soil samples and uncovered
several additional species which were strongly represented only in
proteomic data.
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Affiliation(s)
- Joon-Yong Lee
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Hugh D Mitchell
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Meagan C Burnet
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Ruonan Wu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Sarah C Jenson
- Signature Sciences and Technology Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Eric D Merkley
- Signature Sciences and Technology Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Ernesto S Nakayasu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Carrie D Nicora
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Janet K Jansson
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Kristin E Burnum-Johnson
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Samuel H Payne
- Biology Department, Brigham Young University, Provo, Utah 84602, United States
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23
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Omics-based ecosurveillance for the assessment of ecosystem function, health, and resilience. Emerg Top Life Sci 2022; 6:185-199. [PMID: 35403668 PMCID: PMC9023019 DOI: 10.1042/etls20210261] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 03/17/2022] [Accepted: 03/22/2022] [Indexed: 12/15/2022]
Abstract
Current environmental monitoring efforts often focus on known, regulated contaminants ignoring the potential effects of unmeasured compounds and/or environmental factors. These specific, targeted approaches lack broader environmental information and understanding, hindering effective environmental management and policy. Switching to comprehensive, untargeted monitoring of contaminants, organism health, and environmental factors, such as nutrients, temperature, and pH, would provide more effective monitoring with a likely concomitant increase in environmental health. However, even this method would not capture subtle biochemical changes in organisms induced by chronic toxicant exposure. Ecosurveillance is the systematic collection, analysis, and interpretation of ecosystem health-related data that can address this knowledge gap and provide much-needed additional lines of evidence to environmental monitoring programs. Its use would therefore be of great benefit to environmental management and assessment. Unfortunately, the science of ‘ecosurveillance’, especially omics-based ecosurveillance is not well known. Here, we give an overview of this emerging area and show how it has been beneficially applied in a range of systems. We anticipate this review to be a starting point for further efforts to improve environmental monitoring via the integration of comprehensive chemical assessments and molecular biology-based approaches. Bringing multiple levels of omics technology-based assessment together into a systems-wide ecosurveillance approach will bring a greater understanding of the environment, particularly the microbial communities upon which we ultimately rely to remediate perturbed ecosystems.
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