Pseudo-pac site sequences used by phage P22 in generalized transduction of Salmonella.

Salmonella enterica Serovar Typhimurium (Salmonella) and its bacteriophage P22 are a model system for the study of horizontal gene transfer by generalized transduction. Typically, the P22 DNA packaging machinery initiates packaging when a short sequence of DNA, known as the pac site, is recognized on the P22 genome. However, sequences similar to the pac site in the host genome, called pseudo-pac sites, lead to erroneous packaging and subsequent generalized transduction of Salmonella DNA. While the general genomic locations of the Salmonella pseudo-pac sites are known, the sequences themselves have not been determined. We used visualization of P22 sequencing reads mapped to host Salmonella genomes to define regions of generalized transduction initiation and the likely locations of pseudo-pac sites. We searched each genome region for the sequence with the highest similarity to the P22 pac site and aligned the resulting sequences. We built a regular expression (sequence match pattern) from the alignment and used it to search the genomes of two P22-susceptible Salmonella strains-LT2 and 14028S-for sequence matches. The final regular expression successfully identified pseudo-pac sites in both LT2 and 14028S that correspond with generalized transduction initiation sites in mapped read coverages. The pseudo-pac site sequences identified in this study can be used to predict locations of generalized transduction in other P22-susceptible hosts or to initiate generalized transduction at specific locations in P22-susceptible hosts with genetic engineering. Furthermore, the bioinformatics approach used to identify the Salmonella pseudo-pac sites in this study could be applied to other phage-host systems.

Metabolically-versatile Ca. Thiodiazotropha symbionts of the deep-sea lucinid clam Lucinoma kazani have the genetic potential to fix nitrogen.

Lucinid clams are one of the most diverse and widespread symbiont-bearing animal groups in both shallow and deep-sea chemosynthetic habitats. Lucinids harbor Ca. Thiodiazotropha symbionts that can oxidize inorganic and organic substrates such as hydrogen sulfide and formate to gain energy. The interplay between these key metabolic functions, nutrient uptake and biotic interactions in Ca. Thiodiazotropha is not fully understood. We collected Lucinoma kazani individuals from next to a deep-sea brine pool in the eastern Mediterranean Sea, at a depth of 1150 m and used Oxford Nanopore and Illumina sequencing to obtain high-quality genomes of their Ca. Thiodiazotropha gloverae symbiont. The genomes served as the basis for transcriptomic and proteomic analyses to characterize the in situ gene expression, metabolism and physiology of the symbionts. We found genes needed for N2 fixation in the deep-sea symbiont's genome, which, to date, were only found in shallow-water Ca. Thiodiazotropha. However, we did not detect the expression of these genes and thus the potential role of nitrogen fixation in this symbiosis remains to be determined. We also found the high expression of carbon fixation and sulfur oxidation genes, which indicate chemolithoautotrophy as the key physiology of Ca. Thiodiazotropha. However, we also detected the expression of pathways for using methanol and formate as energy sources. Our findings highlight the key traits these microbes maintain to support the nutrition of their hosts and interact with them.

A Complete Metaproteomic Workflow for Arabidopsis Roots Inoculated by Synthetic Bacteria.

Root metaproteome analysis can reveal the functions that govern plant-microbe and microbe-microbe interactions under specific environmental conditions. Efficient protein extraction method from microbes associated with plant roots is crucial for the comprehensive analysis of the metaproteome. In this chapter, a straightforward protein extraction method for roots of Arabidopsis inoculated with a microbial community that uses only milligrams of tissue is outlined. In addition, the plant inoculation using a synthetic community (SynCom) and the methods for a nanoflow liquid chromatography coupled to a high-resolution/high-accuracy mass spectrometer (LC-MS/MS) are described.

Enterococcal quorum-controlled protease alters phage infection.

Increased prevalence of multidrug resistant bacterial infections has sparked interest in alternative antimicrobials, including bacteriophages (phages). Limited understanding of the phage infection process hampers our ability to utilize phages to their full therapeutic potential. To understand phage infection dynamics we performed proteomics on Enterococcus faecalis infected with the phage VPE25. We discovered numerous uncharacterized phage proteins are produced during phage infection of Enterococcus faecalis. Additionally, we identified hundreds of changes in bacterial protein abundances during infection. One such protein, enterococcal gelatinase (GelE), an fsr quorum sensing regulated protease involved in biofilm formation and virulence, was reduced during VPE25 infection. Plaque assays showed that mutation of either the fsrA or gelE resulted in plaques with a "halo" morphology and significantly larger diameters, suggesting decreased protection from phage infection. GelE-associated protection during phage infection is dependent on the murein hydrolase regulator LrgA and antiholin-like protein LrgB, whose expression have been shown to be regulated by GelE. Our work may be leveraged in the development of phage therapies that can modulate the production of GelE thereby altering biofilm formation and decreasing E. faecalis virulence.

Dietary protein source strongly alters gut microbiota composition and function.

The source of protein in a persons diet affects their total life expectancy. However, the mechanisms by which dietary protein sources differentially impact human health and life expectancy are poorly understood. Dietary choices have major impacts on the composition and function of the intestinal microbiota that ultimately mediate host health. This raises the possibility that health outcomes based on dietary protein sources might be driven by interactions between dietary protein and the gut microbiota. In this study, we determine the effects of seven different sources of dietary protein on the gut microbiota in mice. We apply an integrated metagenomics-metaproteomics approach to simultaneously investigate the effects of these dietary protein sources on the gut microbiotas composition and function. The protein abundances measured by metaproteomics can provide microbial species abundances, and evidence for the phenotype of microbiota members on the molecular level because measured proteins allow us to infer the metabolic and physiological processes used by a microbial community. We showed that dietary protein source significantly altered the species composition and overall function of the gut microbiota. Different dietary protein sources led to changes in the abundance of microbial amino acid degrading proteins and proteins involved in the degradation of glycosylations on dietary protein. In particular, brown rice and egg white protein increased the abundance of amino acid degrading enzymes and egg white protein increased the abundance of bacteria and proteins usually associated with the degradation of the intestinal mucus barrier. These results show that dietary protein source can change the gut microbiotas metabolism, which could have major implications in the context of gut microbiota mediated diseases.

Pseudo-pac site sequences used by phage P22 in generalized transduction of Salmonella.

Salmonella enterica Serovar Typhimurium (Salmonella) and its bacteriophage P22 are a model system for the study of horizontal gene transfer by generalized transduction. Typically, the P22 DNA packaging machinery initiates packaging when a short sequence of DNA, known as the pac site, is recognized on the P22 genome. However, sequences similar to the pac site in the host genome, called pseudo-pac sites, lead to erroneous packaging and subsequent generalized transduction of Salmonella DNA. While the general genomic locations of the Salmonella pseudo-pac sites are known, the sequences themselves have not been determined. We used visualization of P22 sequencing reads mapped to host Salmonella genomes to define regions of generalized transduction initiation and the likely locations of pseudo-pac sites. We searched each genome region for the sequence with the highest similarity to the P22 pac site and aligned the resulting sequences. We built a regular expression (sequence match pattern) from the alignment and used it to search the genomes of two P22-susceptible Salmonella strains- LT2 and 14028S- for sequence matches. The final regular expression successfully identified pseudo-pac sites in both LT2 and 14028S that correspond with generalized transduction initiation sites in mapped read coverages. The pseudo-pac site sequences identified in this study can be used to predict locations of generalized transduction in other P22-susceptible hosts or to initiate generalized transduction at specific locations in P22-susceptible hosts with genetic engineering. Furthermore, the bioinformatics approach used to identify the Salmonella pseudo-pac sites in this study could be applied to other phage-host systems.

Metaproteomics and DNA metabarcoding as tools to assess dietary intake in humans.

Objective biomarkers of food intake are a sought-after goal in nutrition research. Most biomarker development to date has focused on metabolites detected in blood, urine, skin or hair, but detection of consumed foods in stool has also been shown to be possible via DNA sequencing. An additional food macromolecule in stool that harbors sequence information is protein. However, the use of protein as an intake biomarker has only been explored to a very limited extent. Here, we evaluate and compare measurement of residual food-derived DNA and protein in stool as potential biomarkers of intake. We performed a pilot study of DNA sequencing-based metabarcoding (FoodSeq) and mass spectrometry-based metaproteomics in five individuals' stool sampled in short, longitudinal bursts accompanied by detailed diet records (n=27 total samples). Dietary data provided by stool DNA, stool protein, and written diet record independently identified a strong within-person dietary signature, identified similar food taxa, and had significantly similar global structure in two of the three pairwise comparisons between measurement techniques (DNA-to-protein and DNA-to-diet record). Metaproteomics identified proteins including myosin, ovalbumin, and beta-lactoglobulin that differentiated food tissue types like beef from dairy and chicken from egg, distinctions that were not possible by DNA alone. Overall, our results lay the groundwork for development of targeted metaproteomic assays for dietary assessment and demonstrate that diverse molecular components of food can be leveraged to study food intake using stool samples.

IPD3, a master regulator of arbuscular mycorrhizal symbiosis, affects genes for immunity and metabolism of non-host Arabidopsis when restored long after its evolutionary loss.

Arbuscular mycorrhizal symbiosis (AM) is a beneficial trait originating with the first land plants, which has subsequently been lost by species scattered throughout the radiation of plant diversity to the present day, including the model Arabidopsis thaliana. To explore if elements of this apparently beneficial trait are still present and could be reactivated we generated Arabidopsis plants expressing a constitutively active form of Interacting Protein of DMI3, a key transcription factor that enables AM within the Common Symbiosis Pathway, which was lost from Arabidopsis along with the AM host trait. We characterize the transcriptomic effect of expressing IPD3 in Arabidopsis with and without exposure to the AM fungus (AMF) Rhizophagus irregularis, and compare these results to the AM model Lotus japonicus and its ipd3 knockout mutant cyclops-4. Despite its long history as a non-AM species, restoring IPD3 in the form of its constitutively active DNA-binding domain to Arabidopsis altered expression of specific gene networks. Surprisingly, the effect of expressing IPD3 in Arabidopsis and knocking it out in Lotus was strongest in plants not exposed to AMF, which is revealed to be due to changes in IPD3 genotype causing a transcriptional state, which partially mimics AMF exposure in non-inoculated plants. Our results indicate that molecular connections to symbiosis machinery remain in place in this nonAM species, with implications for both basic science and the prospect of engineering this trait for agriculture.

Evaluation of ready-to-use freezer stocks of a synthetic microbial community for maize root colonization.

IMPORTANCE: Synthetic communities (SynComs) are an invaluable tool to characterize and model plant-microbe interactions. Multimember SynComs approximate intricate real-world interactions between plants and their microbiome, but the complexity and time required for their construction increase enormously for each additional member added to the SynCom. Therefore, researchers who study a diversity of microbiomes using SynComs are looking for ways to simplify the use of SynComs. In this manuscript, we evaluate the feasibility of creating ready-to-use freezer stocks of a well-studied seven-member SynCom for maize roots. The frozen ready-to-use SynCom stocks work according to the principle of "just add buffer and apply to sterilized seeds or seedlings" and thus can save time applied in multiple days of laborious growing and combining of multiple microorganisms. We show that ready-to-use SynCom stocks provide comparable results to those of freshly constructed SynComs and thus allow for significant time savings when working with SynComs.

Metabolic handoffs between multiple symbionts may benefit the deep-sea bathymodioline mussels.

Bathymodioline mussels rely on thiotrophic and/or methanotrophic chemosynthetic symbionts for nutrition, yet, secondary heterotrophic symbionts are often present and play an unknown role in the fitness of the organism. The bathymodioline Idas mussels that thrive in gas seeps and on sunken wood in the Mediterranean Sea and the Atlantic Ocean, host at least six symbiont lineages that often co-occur. These lineages include the primary symbionts chemosynthetic methane- and sulfur-oxidizing gammaproteobacteria, and the secondary symbionts, Methylophagaceae, Nitrincolaceae and Flavobacteriaceae, whose physiology and metabolism are obscure. Little is known about if and how these symbionts interact or exchange metabolites. Here we curated metagenome-assembled genomes of Idas modiolaeformis symbionts and used genome-centered metatranscriptomics and metaproteomics to assess key symbiont functions. The Methylophagaceae symbiont is a methylotrophic autotroph, as it encoded and expressed the ribulose monophosphate and Calvin-Benson-Bassham cycle enzymes, particularly RuBisCO. The Nitrincolaceae ASP10-02a symbiont likely fuels its metabolism with nitrogen-rich macromolecules and may provide the holobiont with vitamin B12. The Urechidicola (Flavobacteriaceae) symbionts likely degrade glycans and may remove NO. Our findings indicate that these flexible associations allow for expanding the range of substrates and environmental niches, via new metabolic functions and handoffs.

De novo phytosterol synthesis in animals.

Sterols are vital for nearly all eukaryotes. Their distribution differs in plants and animals, with phytosterols commonly found in plants whereas most animals are dominated by cholesterol. We show that sitosterol, a common sterol of plants, is the most abundant sterol in gutless marine annelids. Using multiomics, metabolite imaging, heterologous gene expression, and enzyme assays, we show that these animals synthesize sitosterol de novo using a noncanonical C-24 sterol methyltransferase (C24-SMT). This enzyme is essential for sitosterol synthesis in plants, but not known from most bilaterian animals. Our phylogenetic analyses revealed that C24-SMTs are present in representatives of at least five animal phyla, indicating that the synthesis of sterols common to plants is more widespread in animals than currently known.

Re-engineering a lost trait: IPD3, a master regulator of arbuscular mycorrhizal symbiosis, affects genes for immunity and metabolism of non-host Arabidopsis when restored long after its evolutionary loss.

Arbuscular mycorrhizal symbiosis (AM) is a beneficial trait originating with the first land plants, which has subsequently been lost by species scattered throughout the radiation of plant diversity to the present day, including the model Arabidopsis thaliana. To explore why an apparently beneficial trait would be repeatedly lost, we generated Arabidopsis plants expressing a constitutively active form of Interacting Protein of DMI3, a key transcription factor that enables AM within the Common Symbiosis Pathway, which was lost from Arabidopsis along with the AM host trait. We characterize the transcriptomic effect of expressing IPD3 in Arabidopsis with and without exposure to the AM fungus (AMF) Rhizophagus irregularis, and compare these results to the AM model Lotus japonicus and its ipd3 knockout mutant cyclops-4. Despite its long history as a non-AM species, restoring IPD3 in the form of its constitutively active DNA-binding domain to Arabidopsis altered expression of specific gene networks. Surprisingly, the effect of expressing IPD3 in Arabidopsis and knocking it out in Lotus was strongest in plants not exposed to AMF, which is revealed to be due to changes in IPD3 genotype causing a transcriptional state which partially mimics AMF exposure in non-inoculated plants. Our results indicate that despite the long interval since loss of AM and IPD3 in Arabidopsis, molecular connections to symbiosis machinery remain in place in this nonAM species, with implications for both basic science and the prospect of engineering this trait for agriculture.

Ultra-sensitive isotope probing to quantify activity and substrate assimilation in microbiomes.

BACKGROUND: Stable isotope probing (SIP) approaches are a critical tool in microbiome research to determine associations between species and substrates, as well as the activity of species. The application of these approaches ranges from studying microbial communities important for global biogeochemical cycling to host-microbiota interactions in the intestinal tract. Current SIP approaches, such as DNA-SIP or nanoSIMS allow to analyze incorporation of stable isotopes with high coverage of taxa in a community and at the single cell level, respectively, however they are limited in terms of sensitivity, resolution or throughput. RESULTS: Here, we present an ultra-sensitive, high-throughput protein-based stable isotope probing approach (Protein-SIP), which cuts cost for labeled substrates by 50-99% as compared to other SIP and Protein-SIP approaches and thus enables isotope labeling experiments on much larger scales and with higher replication. The approach allows for the determination of isotope incorporation into microbiome members with species level resolution using standard metaproteomics liquid chromatography-tandem mass spectrometry (LC-MS/MS) measurements. At the core of the approach are new algorithms to analyze the data, which have been implemented in an open-source software ( https://sourceforge.net/projects/calis-p/ ). We demonstrate sensitivity, precision and accuracy using bacterial cultures and mock communities with different labeling schemes. Furthermore, we benchmark our approach against two existing Protein-SIP approaches and show that in the low labeling range used our approach is the most sensitive and accurate. Finally, we measure translational activity using 18O heavy water labeling in a 63-species community derived from human fecal samples grown on media simulating two different diets. Activity could be quantified on average for 27 species per sample, with 9 species showing significantly higher activity on a high protein diet, as compared to a high fiber diet. Surprisingly, among the species with increased activity on high protein were several Bacteroides species known as fiber consumers. Apparently, protein supply is a critical consideration when assessing growth of intestinal microbes on fiber, including fiber-based prebiotics. CONCLUSIONS: We demonstrate that our Protein-SIP approach allows for the ultra-sensitive (0.01 to 10% label) detection of stable isotopes of elements found in proteins, using standard metaproteomics data.

Dietary protein and the intestinal microbiota: An understudied relationship.

Diet has a profound impact on the microbial community in the gastrointestinal tract, the intestinal microbiota, to the benefit or detriment of human health. To understand the influence of diet on the intestinal microbiota, research has focused on individual macronutrients. Some macronutrients (e.g. fiber) have been studied in great detail and have been found to strongly influence the intestinal microbiota. The relationship between dietary protein, a vital macronutrient, and the intestinal microbiota has gone largely unexplored. Emerging evidence suggests that dietary protein strongly impacts intestinal microbiota composition and function and that protein-microbiota interactions can have critical impacts on host health. In this review, we focus on recent studies investigating the impact of dietary protein quantity and source on the intestinal microbiota and resulting host health consequences. We highlight major open questions critical to understanding health outcomes mediated by interactions between dietary protein and the microbiota.

Fidelity varies in the symbiosis between a gutless marine worm and its microbial consortium.

BACKGROUND: Many animals live in intimate associations with a species-rich microbiome. A key factor in maintaining these beneficial associations is fidelity, defined as the stability of associations between hosts and their microbiota over multiple host generations. Fidelity has been well studied in terrestrial hosts, particularly insects, over longer macroevolutionary time. In contrast, little is known about fidelity in marine animals with species-rich microbiomes at short microevolutionary time scales, that is at the level of a single host population. Given that natural selection acts most directly on local populations, studies of microevolutionary partner fidelity are important for revealing the ecological and evolutionary processes that drive intimate beneficial associations within animal species. RESULTS: In this study on the obligate symbiosis between the gutless marine annelid Olavius algarvensis and its consortium of seven co-occurring bacterial symbionts, we show that partner fidelity varies across symbiont species from strict to absent over short microevolutionary time. Using a low-coverage sequencing approach that has not yet been applied to microbial community analyses, we analysed the metagenomes of 80 O. algarvensis individuals from the Mediterranean and compared host mitochondrial and symbiont phylogenies based on single-nucleotide polymorphisms across genomes. Fidelity was highest for the two chemoautotrophic, sulphur-oxidizing symbionts that dominated the microbial consortium of all O. algarvensis individuals. In contrast, fidelity was only intermediate to absent in the sulphate-reducing and spirochaetal symbionts with lower abundance. These differences in fidelity are likely driven by both selective and stochastic forces acting on the consistency with which symbionts are vertically transmitted. CONCLUSIONS: We hypothesize that variable degrees of fidelity are advantageous for O. algarvensis by allowing the faithful transmission of their nutritionally most important symbionts and flexibility in the acquisition of other symbionts that promote ecological plasticity in the acquisition of environmental resources. Video Abstract.

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

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.

Elucidating Plant-Microbe-Environment Interactions Through Omics-Enabled Metabolic Modelling Using Synthetic Communities.

With a growing world population and increasing frequency of climate disturbance events, we are in dire need of methods to improve plant productivity, resilience, and resistance to both abiotic and biotic stressors, both for agriculture and conservation efforts. Microorganisms play an essential role in supporting plant growth, environmental response, and susceptibility to disease. However, understanding the specific mechanisms by which microbes interact with each other and with plants to influence plant phenotypes is a major challenge due to the complexity of natural communities, simultaneous competition and cooperation effects, signalling interactions, and environmental impacts. Synthetic communities are a major asset in reducing the complexity of these systems by simplifying to dominant components and isolating specific variables for controlled experiments, yet there still remains a large gap in our understanding of plant microbiome interactions. This perspectives article presents a brief review discussing ways in which metabolic modelling can be used in combination with synthetic communities to continue progress toward understanding the complexity of plant-microbe-environment interactions. We highlight the utility of metabolic models as applied to a community setting, identify different applications for both flux balance and elementary flux mode simulation approaches, emphasize the importance of ecological theory in guiding data interpretation, and provide ideas for how the integration of metabolic modelling techniques with big data may bridge the gap between simplified synthetic communities and the complexity of natural plant-microbe systems.

Considerations for constructing a protein sequence database for metaproteomics.

Mass spectrometry-based metaproteomics has emerged as a prominent technique for interrogating the functions of specific organisms in microbial communities, in addition to total community function. Identifying proteins by mass spectrometry requires matching mass spectra of fragmented peptide ions to a database of protein sequences corresponding to the proteins in the sample. This sequence database determines which protein sequences can be identified from the measurement, and as such the taxonomic and functional information that can be inferred from a metaproteomics measurement. Thus, the construction of the protein sequence database directly impacts the outcome of any metaproteomics study. Several factors, such as source of sequence information and database curation, need to be considered during database construction to maximize accurate protein identifications traceable to the species of origin. In this review, we provide an overview of existing strategies for database construction and the relevant studies that have sought to test and validate these strategies. Based on this review of the literature and our experience we provide a decision tree and best practices for choosing and implementing database construction strategies.

Evaluation of Sample Preservation and Storage Methods for Metaproteomics Analysis of Intestinal Microbiomes.

A critical step in studies of the intestinal microbiome using meta-omics approaches is the preservation of samples before analysis. Preservation is essential for approaches that measure gene expression, such as metaproteomics, which is used to identify and quantify proteins in microbiomes. Intestinal microbiome samples are typically stored by flash-freezing and storage at -80°C, but some experimental setups do not allow for immediate freezing of samples. In this study, we evaluated methods to preserve fecal microbiome samples for metaproteomics analyses when flash-freezing is not possible. We collected fecal samples from C57BL/6 mice and stored them for 1 and 4 weeks using the following methods: flash-freezing in liquid nitrogen, immersion in RNAlater, immersion in 95% ethanol, immersion in a RNAlater-like buffer, and combinations of these methods. After storage, we extracted protein and prepared peptides for liquid chromatography with tandem mass spectrometry (LC-MS/MS) analysis to identify and quantify peptides and proteins. All samples produced highly similar metaproteomes, except for ethanol-preserved samples that were distinct from all other samples in terms of protein identifications and protein abundance profiles. Flash-freezing and RNAlater (or RNAlater-like treatments) produced metaproteomes that differed only slightly, with less than 0.7% of identified proteins differing in abundance. In contrast, ethanol preservation resulted in an average of 9.5% of the identified proteins differing in abundance between ethanol and the other treatments. Our results suggest that preservation at room temperature in RNAlater or an RNAlater-like solution performs as well as freezing for the preservation of intestinal microbiome samples before metaproteomics analyses. IMPORTANCE Metaproteomics is a powerful tool to study the intestinal microbiome. By identifying and quantifying a large number of microbial, dietary, and host proteins in microbiome samples, metaproteomics provides direct evidence of the activities and functions of microbial community members. A critical step for metaproteomics workflows is preserving samples before analysis because protein profiles are susceptible to fast changes in response to changes in environmental conditions (air exposure, temperature changes, etc.). This study evaluated the effects of different preservation treatments on the metaproteomes of intestinal microbiome samples. In contrast to prior work on preservation of fecal samples for metaproteomics analyses, we ensured that all steps of sample preservation were identical so that all differences could be attributed to the preservation method.

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

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.