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1. Using high-abundance proteins as guides for fast and effective peptide/protein identification from human gut metaproteomic data

   https://doi.org/10.1186/s40168-021-01035-8  

   Stamboulian, Moses; Li, Sujun; Ye, Yuzhen (December 2021, Microbiome)

   null (Ed.)

   Abstract Background A few recent large efforts significantly expanded the collection of human-associated bacterial genomes, which now contains thousands of entities including reference complete/draft genomes and metagenome assembled genomes (MAGs). These genomes provide useful resource for studying the functionality of the human-associated microbiome and their relationship with human health and diseases. One application of these genomes is to provide a universal reference for database search in metaproteomic studies, when matched metagenomic/metatranscriptomic data are unavailable. However, a greater collection of reference genomes may not necessarily result in better peptide/protein identification because the increase of search space often leads to fewer spectrum-peptide matches, not to mention the drastic increase of computation time. Methods Here, we present a new approach that uses two steps to optimize the use of the reference genomes and MAGs as the universal reference for human gut metaproteomic MS/MS data analysis. The first step is to use only the high-abundance proteins (HAPs) (i.e., ribosomal proteins and elongation factors) for metaproteomic MS/MS database search and, based on the identification results, to derive the taxonomic composition of the underlying microbial community. The second step is to expand the search database by including all proteins from identified abundant species. We call our approach HAPiID (HAPs guided metaproteomics IDentification). Results We tested our approach using human gut metaproteomic datasets from a previous study and compared it to the state-of-the-art reference database search method MetaPro-IQ for metaproteomic identification in studying human gut microbiota. Our results show that our two-steps method not only performed significantly faster but also was able to identify more peptides. We further demonstrated the application of HAPiID to revealing protein profiles of individual human-associated bacterial species, one or a few species at a time, using metaproteomic data. Conclusions The HAP guided profiling approach presents a novel effective way for constructing target database for metaproteomic data analysis. The HAPiID pipeline built upon this approach provides a universal tool for analyzing human gut-associated metaproteomic data. 

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2. Evaluation of Protein Extraction Methods for Metaproteomic Analyses of Root-Associated Microbes

   https://doi.org/10.1094/MPMI-05-22-0116-TA  

   Salvato, Fernanda; Vintila, Simina; Finkel, Omri M.; Dangl, Jeffery L.; Kleiner, Manuel (November 2022, Molecular Plant-Microbe Interactions®)

   Metaproteomics is a powerful tool for the characterization of metabolism, physiology, and functional interactions in microbial communities, including plant-associated microbiota. However, the metaproteomic methods that have been used to study plant-associated microbiota are very laborious and require large amounts of plant tissue, hindering wider application of these methods. We optimized and evaluated different protein extraction methods for metaproteomics of plant-associated microbiota in two different plant species ( Arabidopsis and maize). Our main goal was to identify a method that would work with low amounts of input material (40 to 70 mg) and that would maximize the number of identified microbial proteins. We tested eight protocols, each comprising a different combination of physical lysis method, extraction buffer, and cell-enrichment method on roots from plants grown with synthetic microbial communities. We assessed the performance of the extraction protocols by liquid chromatography-tandem mass spectrometry–based metaproteomics and found that the optimal extraction method differed between the two species. For Arabidopsis roots, protein extraction by beating whole roots with small beads provided the greatest number of identified microbial proteins and improved the identification of proteins from gram-positive bacteria. For maize, vortexing root pieces in the presence of large glass beads yielded the greatest number of microbial proteins identified. Based on these data, we recommend the use of these two methods for metaproteomics with Arabidopsis and maize. Furthermore, detailed descriptions of the eight tested protocols will enable future optimization of protein extraction for metaproteomics in other dicot and monocot plants. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license . 

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3. Evaluation of RNA later as a Field-Compatible Preservation Method for Metaproteomic Analyses of Bacterium-Animal Symbioses

   https://doi.org/10.1128/Spectrum.01429-21  

   Jensen, Marlene; Wippler, Juliane; Kleiner, Manuel (October 2021, Microbiology Spectrum)

   Gralnick, Jeffrey A. (Ed.)

   ABSTRACT Field studies are central to environmental microbiology and microbial ecology, because they enable studies of natural microbial communities. Metaproteomics, the study of protein abundances in microbial communities, allows investigators to study these communities “ in situ ,” which requires protein preservation directly in the field because protein abundance patterns can change rapidly after sampling. Ideally, a protein preservative for field deployment works rapidly and preserves the whole proteome, is stable in long-term storage, is nonhazardous and easy to transport, and is available at low cost. Although these requirements might be met by several protein preservatives, an assessment of their suitability under field conditions when targeted for metaproteomic analyses is currently lacking. Here, we compared the protein preservation performance of flash freezing and the preservation solution RNA later using the marine gutless oligochaete Olavius algarvensis and its symbiotic microbes as a test case. In addition, we evaluated long-term RNA later storage after 1 day, 1 week, and 4 weeks at room temperature (22°C to 23°C). We evaluated protein preservation using one-dimensional liquid chromatography-tandem mass spectrometry. We found that RNA later and flash freezing preserved proteins equally well in terms of total numbers of identified proteins and relative abundances of individual proteins, and none of the test time points was altered, compared to time zero. Moreover, we did not find biases against specific taxonomic groups or proteins with particular biochemical properties. Based on our metaproteomic data and the logistical requirements for field deployment, we recommend RNA later for protein preservation of field-collected samples targeted for metaproteomic analyses. IMPORTANCE Metaproteomics, the large-scale identification and quantification of proteins from microbial communities, provide direct insights into the phenotypes of microorganisms on the molecular level. To ensure the integrity of the metaproteomic data, samples need to be preserved immediately after sampling to avoid changes in protein abundance patterns. In laboratory setups, samples for proteomic analyses are most commonly preserved by flash freezing; however, liquid nitrogen or dry ice is often unavailable at remote field locations, due to their hazardous nature and transport restrictions. Our study shows that RNA later can serve as a low-hazard, easy-to-transport alternative to flash freezing for field preservation of samples for metaproteomic analyses. We show that RNA later preserves the metaproteome equally well, compared to flash freezing, and protein abundance patterns remain stable during long-term storage for at least 4 weeks at room temperature. 

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4. Strain Structure and Dynamics Revealed by Targeted Deep Sequencing of the Honey Bee Gut Microbiome

   https://doi.org/10.1128/mSphere.00694-20  

   Bobay, Louis-Marie; Wissel, Emily F.; Raymann, Kasie (August 2020, mSphere)

   Campbell, Barbara J. (Ed.)

   ABSTRACT Host-associated microbiomes can be critical for the health and proper development of animals and plants. The answers to many fundamental questions regarding the modes of acquisition and microevolution of microbiome communities remain to be established. Deciphering strain-level dynamics is essential to fully understand how microbial communities evolve, but the forces shaping the strain-level dynamics of microbial communities remain largely unexplored, mostly because of methodological issues and cost. Here, we used targeted strain-level deep sequencing to uncover the strain dynamics within a host-associated microbial community using the honey bee gut microbiome as a model system. Our results revealed that amplicon sequencing of conserved protein-coding gene regions using species-specific primers is a cost-effective and accurate method for exploring strain-level diversity. In fact, using this method we were able to confirm strain-level results that have been obtained from whole-genome shotgun sequencing of the honey bee gut microbiome but with a much higher resolution. Importantly, our deep sequencing approach allowed us to explore the impact of low-frequency strains (i.e., cryptic strains) on microbiome dynamics. Results show that cryptic strain diversity is not responsible for the observed variations in microbiome composition across bees. Altogether, the findings revealed new fundamental insights regarding strain dynamics of host-associated microbiomes. IMPORTANCE The factors driving fine-scale composition and dynamics of gut microbial communities are poorly understood. In this study, we used metagenomic amplicon deep sequencing to decipher the strain dynamics of two key members of the honey bee gut microbiome. Using this high-throughput and cost-effective approach, we were able to confirm results from previous large-scale whole-genome shotgun (WGS) metagenomic sequencing studies while also gaining additional insights into the community dynamics of two core members of the honey bee gut microbiome. Moreover, we were able to show that cryptic strains are not responsible for the observed variations in microbiome composition across bees. 

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5. Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

   https://doi.org/10.1038/s41467-021-27542-8  

   Van Den Bossche, Tim; Kunath, Benoit J.; Schallert, Kay; Schäpe, Stephanie S.; Abraham, Paul E.; Armengaud, Jean; Arntzen, Magnus Ø.; Bassignani, Ariane; Benndorf, Dirk; Fuchs, Stephan; et al (December 2021, Nature Communications)

   Abstract Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments. 

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