RapidAIM 2.0: a high-throughput assay to study functional response of human gut microbiome to xenobiotics.

Aim: Our gut microbiome has its own functionalities which can be modulated by various xenobiotic and biotic components. The development and application of a high-throughput functional screening approach of individual gut microbiomes accelerates drug discovery and our understanding of microbiome-drug interactions. We previously developed the rapid assay of individual microbiome (RapidAIM), which combined an optimized culturing model with metaproteomics to study gut microbiome responses to xenobiotics. In this study, we aim to incorporate automation and multiplexing techniques into RapidAIM to develop a high-throughput protocol. Methods: To develop a 2.0 version of RapidAIM, we automated the protein analysis protocol, and introduced a tandem mass tag (TMT) multiplexing technique. To demonstrate the typical outcome of the protocol, we used RapidAIM 2.0 to evaluate the effect of prebiotic kestose on ex vivo individual human gut microbiomes biobanked with five different workflows. Results: We describe the protocol of RapidAIM 2.0 with extensive details on stool sample collection, biobanking, in vitro culturing and stimulation, sample processing, metaproteomics measurement, and data analysis. The analysis depth of 5,014 ± 142 protein groups per multiplexed sample was achieved. A test on five biobanking methods using RapidAIM 2.0 showed the minimal effect of sample processing on live microbiota functional responses to kestose. Conclusions: Depth and reproducibility of RapidAIM 2.0 are comparable to previous manual label-free metaproteomic analyses. In the meantime, the protocol realizes culturing and sample preparation of 320 samples in six days, opening the door to extensively understanding the effects of xenobiotic and biotic factors on our internal ecology.

Self-Assembled MXene@Fluorographene Hybrid for High Dielectric Constant and Low Loss Ferroelectric Polymer Composite Films.

Modern electrical applications urgently need flexible polymer films with a high dielectric constant (εr) and low loss. Recently, the MXene-filled percolative composite has emerged as a potential material choice because of the promised high εr. Nevertheless, the typically accompanied high dielectric loss hinders its applications. Herein, a facile and effective surface modification strategy of cladding Ti3C2Tx MXene (T = F or O; FMX) with fluorographene (FG) via self-assembly is proposed. The obtained FMX@FG hybrid yields high εr (up to 108 @1 kHz) and low loss (loss tangent tan δ = 1.16 @ 1 kHz) in a ferroelectric polymer composite at a low loading level (the equivalent of 1.5 wt % FMX), which is superior to its counterparts in our work (e.g., FMX: εr = 104, tan δ = 10.71) and other studies. It is found that the FG layer outside FMX plays a critical role in both the high dielectric constant and low loss from experimental characterizations and finite element simulations. For one thing, FG with a high F/C ratio would induce a favorable structure of high ß-phase crystallinity, extensive microcapacitor networks, and abundant interfacial dipoles in polymer composites that account for the high εr. For another, FG, as a highly insulating layer, can inhibit the formation of conductive networks and inter-FMX electron tunneling, which is responsible for conduction loss. The results demonstrate the potential of a self-assembled FMX@FG hybrid for high εr and low loss polymer composite films and offer a new strategy for designing advanced polymer composite dielectrics.

Pairing metagenomics and metaproteomics to characterize ecological niches and metabolic essentiality of gut microbiomes.

The genome of a microorganism encodes its potential functions that can be implemented through expressed proteins. It remains elusive how a protein's selective expression depends on its metabolic essentiality to microbial growth or its ability to claim resources as ecological niches. To reveal a protein's metabolic or ecological role, we developed a computational pipeline, which pairs metagenomics and metaproteomics data to quantify each protein's gene-level and protein-level functional redundancy simultaneously. We first illustrated the idea behind the pipeline using simulated data of a consumer-resource model. We then validated it using real data from human and mouse gut microbiome samples. In particular, we analyzed ABC-type transporters and ribosomal proteins, confirming that the metabolic and ecological roles predicted by our pipeline agree well with prior knowledge. Finally, we performed in vitro cultures of a human gut microbiome sample and investigated how oversupplying various sugars involved in ecological niches influences the community structure and protein abundance. The presented results demonstrate the performance of our pipeline in identifying proteins' metabolic and ecological roles, as well as its potential to help us design nutrient interventions to modulate the human microbiome.

All-natural 2D nanofluidics as highly-efficient osmotic energy generators.

Two-dimensional nanofluidics based on naturally abundant clay are good candidates for harvesting osmotic energy between the sea and river from the perspective of commercialization and environmental sustainability. However, clay-based nanofluidics outputting long-term considerable osmotic power remains extremely challenging to achieve due to the lack of surface charge and mechanical strength. Here, a two-dimensional all-natural nanofluidic (2D-NNF) is developed as a robust and highly efficient osmotic energy generator based on an interlocking configuration of stacked montmorillonite nanosheets (from natural clay) and their intercalated cellulose nanofibers (from natural wood). The generated nano-confined interlamellar channels with abundant surface and space negative charges facilitate selective and fast hopping transport of cations in the 2D-NNF. This contributes to an osmotic power output of ~8.61 W m-2 by mixing artificial seawater and river water, higher than other reported state-of-the-art 2D nanofluidics. According to detailed life cycle assessments (LCA), the 2D-NNF demonstrates great advantages in resource consumption (1/14), greenhouse gas emissions (1/9), and production costs (1/13) compared with the mainstream 2D nanofluidics, promising good sustainability for large-scale and highly-efficient osmotic power generation.

Molecular characterization of hybrid virulence plasmids in ST11-KL64 KPC-2-producing multidrug-resistant hypervirulent Klebsiella pneumoniae from China.

Introduction: Carbapenem-resistant hypervirulent Klebsiella pneumoniae (CR-HvKP) strains combining virulence and multidrug resistance (MDR) features pose a great public health concern. The aim of this study is to explore the evolutionary characteristics of virulence in CR-HvKP by investigating the genetic features of resistance and virulence hybrid plasmids. Methods: The resistance and virulence phenotypes were determined by using antimicrobial susceptibility testing and the mouse bacteremia infection model, respectively. Plasmid profiles were investigated by S1 nuclease pulsed-field gel electrophoresis (S1-PFGE) and Southern blotting, conjugation assay, and whole genome sequencing (WGS). Bioinformatics tools were used to uncover the genetic features of the resistance and virulence hybrid plasmids. Results: Two ST11-KL64 CRKP clinical isolates (KP18-3-8 and KP18-2079), which exhibited enhanced virulence compared with the classic CRKP, were detected positive for blaKPC-2 and rmpA2. The virulence level of the hypermucoviscous strain KP18-3-8 was higher than that of KP18-2079. S1-PFGE, Southern hybridization and WGS analysis identified two novel hybrid virulence plasmids in KP18-3-8 (pKP1838-KPC-vir, 228,158 bp) and KP18-2079 (pKP1838-KPC-vir, 182,326 bp), respectively. The IncHI1B/repB-type plasmid pKP1838-KPC-vir co-harboring blaKPC-2 and virulence genes (rmpA2, iucABCD and iutA) but lacking type IV secretion system could transfer into non-hypervirulent ST11 K. pneumoniae with the assistance of a helper plasmid in conjugation. The IncFII/IncR-type virulence plasmid pKP18-2079-vir may have been generated as a result of recombination between a typical pLVPK-like virulence plasmid and an MDR plasmid. Conclusion: Our studies further highlight co-evolution of the virulence and resistance plasmids in ST11-CRKP isolates. Close surveillance of such hybrid virulence plasmids in clinical K. pneumoniae should be performed.

Introducing π-HelixNovo for practical large-scale de novo peptide sequencing.

De novo peptide sequencing is a promising approach for novel peptide discovery, highlighting the performance improvements for the state-of-the-art models. The quality of mass spectra often varies due to unexpected missing of certain ions, presenting a significant challenge in de novo peptide sequencing. Here, we use a novel concept of complementary spectra to enhance ion information of the experimental spectrum and demonstrate it through conceptual and practical analyses. Afterward, we design suitable encoders to encode the experimental spectrum and the corresponding complementary spectrum and propose a de novo sequencing model $\pi$-HelixNovo based on the Transformer architecture. We first demonstrated that $\pi$-HelixNovo outperforms other state-of-the-art models using a series of comparative experiments. Then, we utilized $\pi$-HelixNovo to de novo gut metaproteome peptides for the first time. The results show $\pi$-HelixNovo increases the identification coverage and accuracy of gut metaproteome and enhances the taxonomic resolution of gut metaproteome. We finally trained a powerful $\pi$-HelixNovo utilizing a larger training dataset, and as expected, $\pi$-HelixNovo achieves unprecedented performance, even for peptide-spectrum matches with never-before-seen peptide sequences. We also use the powerful $\pi$-HelixNovo to identify antibody peptides and multi-enzyme cleavage peptides, and $\pi$-HelixNovo is highly robust in these applications. Our results demonstrate the effectivity of the complementary spectrum and take a significant step forward in de novo peptide sequencing.

Revealing proteome-level functional redundancy in the human gut microbiome using ultra-deep metaproteomics.

Functional redundancy is a key ecosystem property representing the fact that different taxa contribute to an ecosystem in similar ways through the expression of redundant functions. The redundancy of potential functions (or genome-level functional redundancy [Formula: see text]) of human microbiomes has been recently quantified using metagenomics data. Yet, the redundancy of expressed functions in the human microbiome has never been quantitatively explored. Here, we present an approach to quantify the proteome-level functional redundancy [Formula: see text] in the human gut microbiome using metaproteomics. Ultra-deep metaproteomics reveals high proteome-level functional redundancy and high nestedness in the human gut proteomic content networks (i.e., the bipartite graphs connecting taxa to functions). We find that the nested topology of proteomic content networks and relatively small functional distances between proteomes of certain pairs of taxa together contribute to high [Formula: see text] in the human gut microbiome. As a metric comprehensively incorporating the factors of presence/absence of each function, protein abundances of each function and biomass of each taxon, [Formula: see text] outcompetes diversity indices in detecting significant microbiome responses to environmental factors, including individuality, biogeography, xenobiotics, and disease. We show that gut inflammation and exposure to specific xenobiotics can significantly diminish the [Formula: see text] with no significant change in taxonomic diversity.

Positive mood-related gut microbiota in a long-term closed environment: a multiomics study based on the "Lunar Palace 365" experiment.

BACKGROUND: Psychological health risk is one of the most severe and complex risks in manned deep-space exploration and long-term closed environments. Recently, with the in-depth research of the microbiota-gut-brain axis, gut microbiota has been considered a new approach to maintain and improve psychological health. However, the correlation between gut microbiota and psychological changes inside long-term closed environments is still poorly understood. Herein, we used the "Lunar Palace 365" mission, a 1-year-long isolation study in the Lunar Palace 1 (a closed manned Bioregenerative Life Support System facility with excellent performance), to investigate the correlation between gut microbiota and psychological changes, in order to find some new potential psychobiotics to maintain and improve the psychological health of crew members. RESULTS: We report some altered gut microbiota that were associated with psychological changes in the long-term closed environment. Four potential psychobiotics (Bacteroides uniformis, Roseburia inulinivorans, Eubacterium rectale, and Faecalibacterium prausnitzii) were identified. On the basis of metagenomic, metaproteomic, and metabolomic analyses, the four potential psychobiotics improved mood mainly through three pathways related to nervous system functions: first, by fermenting dietary fibers, they may produce short-chain fatty acids, such as butyric and propionic acids; second, they may regulate amino acid metabolism pathways of aspartic acid, glutamic acid, tryptophan, etc. (e.g., converting glutamic acid to gamma-aminobutyric acid; converting tryptophan to serotonin, kynurenic acid, or tryptamine); and third, they may regulate other pathways, such as taurine and cortisol metabolism. Furthermore, the results of animal experiments confirmed the positive regulatory effect and mechanism of these potential psychobiotics on mood. CONCLUSIONS: These observations reveal that gut microbiota contributed to a robust effect on the maintenance and improvement of mental health in a long-term closed environment. Our findings represent a key step towards a better understanding the role of the gut microbiome in mammalian mental health during space flight and provide a basis for future efforts to develop microbiota-based countermeasures that mitigate risks to crew mental health during future long-term human space expeditions on the moon or Mars. This study also provides an essential reference for future applications of psychobiotics to neuropsychiatric treatments. Video Abstract.

MetaLab-MAG: A Metaproteomic Data Analysis Platform for Genome-Level Characterization of Microbiomes from the Metagenome-Assembled Genomes Database.

The studies of microbial communities have drawn increased attention in various research fields such as agriculture, environment, and human health. Recently, metaproteomics has become a powerful tool to interpret the roles of the community members by investigating the expressed proteins of the microbes. However, analyzing the metaproteomic data sets at genome resolution is still challenging because of the lack of efficient bioinformatics tools. Here we develop MetaLab-MAG, a specially designed tool for the characterization of microbiomes from metagenome-assembled genomes databases. MetaLab-MAG was evaluated by analyzing various human gut microbiota data sets and performed comparably or better than searching the gene catalog protein database directly. MetaLab-MAG can quantify the genome-level microbiota compositions and supports both label-free and isobaric labeling-based quantification strategies. MetaLab-MAG removes the obstacles of metaproteomic data analysis and provides the researchers with in-depth and comprehensive information from the microbiomes.

An economic and robust TMT labeling approach for high throughput proteomic and metaproteomic analysis.

Multiplexed quantitative proteomics using tandem mass tag (TMT) is increasingly used in -omic study of complex samples. While TMT-based proteomics has the advantages of the higher quantitative accuracy, fewer missing values, and reduced instrument analysis time, it is limited by the additional reagent cost. In addition, current TMT labeling workflows involve repeated small volume pipetting of reagents in volatile solvents, which may increase the sample-to-sample variations and is not readily suitable for high throughput applications. In this study, we demonstrated that the TMT labeling procedures could be streamlined by using pre-aliquoted dry TMT reagents in a 96 well plate or 12-tube strip. As little as 50 µg dry TMT per channel was used to label 6-12 µg peptides, yielding high TMT labeling efficiency (∼99%) in both microbiome and mammalian cell line samples. We applied this workflow to analyze 97 samples in a study to evaluate whether ice recrystallization inhibitors improve the cultivability and activity of frozen microbiota. The results demonstrated tight sample clustering corresponding to groups and consistent microbiome responses to prebiotic treatments. This study supports the use of TMT reagents that are pre-aliquoted, dried, and stored for robust quantitative proteomics and metaproteomics in high throughput applications.

Cuboid-like phosphorus-doped metal-organic framework-derived CoSe2 on carbon cloth as an advanced bifunctional oxygen electrocatalyst for rechargeable zinc-air batteries.

Zinc-air batteries (ZABs) are regarded as attractive devices for electrochemical energy storage and conversion due to their outstanding electrochemical performance, low price, and high safety. However, it remains a challenge to design a stable and efficient bifunctional oxygen catalyst that can accelerate the reaction kinetics and improve the performance of ZABs. Herein, a phosphorus-doped transition metal selenide/carbon composite catalyst derived from metal-organic frameworks (P-CoSe2/C@CC) is constructed by a self-supporting carbon cloth structure through a simple solvothermal process with subsequent selenization and phosphatization. The P-CoSe2/C@CC exhibits a low overpotential of 303.1 mV at 10 mA cm-2 toward the oxygen evolution reaction and an obvious reduction peak for the oxygen reduction reaction. The abovementioned electrochemical performances for the P-CoSe2/C@CC are attributed to the specific architecture, the super-hydrophilic surface, and the P-doping effect. Remarkably, the homemade zinc-air battery based on our P-CoSe2/C@CC catalyst shows an expected peak power density of 124.4 mW cm-2 along with excellent cycling stability, confirming its great potential application in ZABs for advanced bifunctional electrocatalysis.

Assessing the Dark Field of Metaproteome.

The human gut microbiome is a complex system composed of hundreds of species, and metaproteomics can be used to explore their expressed functions. However, many lower abundance species are not detected by current metaproteomic techniques and represent the dark field of metaproteomics. We do not know the minimal abundance of a bacterium in a microbiome(depth) that can be detected by shotgun metaproteomics. In this study, we spiked 15N-labeled E. coli peptides at different percentages into peptides mixture derived from the human gut microbiome to evaluate the depth that can be achieved by shotgun metaproteomics. We observed that the number of identified peptides and peptide intensity from 15N-labeled E. coli were linearly correlated with the spike-in levels even when 15N-labeled E. coli was down to 0.5% of the biomass. Below that level, it was not detected. Interestingly, the match-between-run strategy significantly increased the number of quantified peptides even when 15N-labeled E. coli peptides were at low abundance. This is indicative that in metaproteomics of complex gut microbiomes many peptides from low abundant species are likely observable in MS1 but are not selected for MS2 by standard shotgun strategies.

MetaProClust-MS1: an MS1 Profiling Approach for Large-Scale Microbiome Screening.

Metaproteomics is used to explore the functional dynamics of microbial communities. However, acquiring metaproteomic data by tandem mass spectrometry (MS/MS) is time-consuming and resource-intensive, and there is a demand for computational methods that can be used to reduce these resource requirements. We present MetaProClust-MS1, a computational framework for microbiome feature screening developed to prioritize samples for follow-up MS/MS. In this proof-of-concept study, we tested and compared MetaProClust-MS1 results on gut microbiome data, from fecal samples, acquired using short 15-min MS1-only chromatographic gradients and MS1 spectra from longer 60-min gradients to MS/MS-acquired data. We found that MetaProClust-MS1 identified robust gut microbiome responses caused by xenobiotics with significantly correlated cluster topologies of comparable data sets. We also used MetaProClust-MS1 to reanalyze data from both a clinical MS/MS diagnostic study of pediatric patients with inflammatory bowel disease and an experiment evaluating the therapeutic effects of a small molecule on the brain tissue of Alzheimer's disease mouse models. MetaProClust-MS1 clusters could distinguish between inflammatory bowel disease diagnoses (ulcerative colitis and Crohn's disease) using samples from mucosal luminal interface samples and identified hippocampal proteome shifts of Alzheimer's disease mouse models after small-molecule treatment. Therefore, we demonstrate that MetaProClust-MS1 can screen both microbiomes and single-species proteomes using only MS1 profiles, and our results suggest that this approach may be generalizable to any proteomics experiment. MetaProClust-MS1 may be especially useful for large-scale metaproteomic screening for the prioritization of samples for further metaproteomic characterization, using MS/MS, for instance, in addition to being a promising novel approach for clinical diagnostic screening. IMPORTANCE Growing evidence suggests that human gut microbiome composition and function are highly associated with health and disease. As such, high-throughput metaproteomic studies are becoming more common in gut microbiome research. However, using a conventional long liquid chromatography (LC)-MS/MS gradient metaproteomics approach as an initial screen in large-scale microbiome experiments can be slow and expensive. To combat this challenge, we introduce MetaProClust-MS1, a computational framework for microbiome screening using MS1-only profiles. In this proof-of-concept study, we show that MetaProClust-MS1 identifies clusters of gut microbiome treatments using MS1-only profiles similar to those identified using MS/MS. Our approach allows researchers to prioritize samples and treatments of interest for further metaproteomic analyses and may be generally applicable to any proteomic analysis. In particular, this approach may be especially useful for large-scale metaproteomic screening or in clinical settings where rapid diagnostic evidence is required.

Comprehensive Assessment of Functional Effects of Commonly Used Sugar Substitute Sweeteners on Ex Vivo Human Gut Microbiome.

The composition and function of the human gut microbiome are often associated with health and disease status. Sugar substitute sweeteners are widely used food additives, although many studies using animal models have linked sweetener consumption to gut microbial changes and health issues. Whether sugar substitute sweeteners directly change the human gut microbiome functionality remains largely unknown. In this study, we systematically investigated the responses of five human gut microbiomes to 21 common sugar substitute sweeteners, using an approach combining high-throughput in vitro microbiome culturing and metaproteomic analyses to quantify functional changes in different taxa. Hierarchical clustering based on metaproteomic responses of individual microbiomes resulted in two clusters. The noncaloric artificial sweetener (NAS) cluster was composed of NASs and two sugar alcohols with shorter carbon backbones (4 or 5 carbon atoms), and the carbohydrate (CHO) cluster was composed of the remaining sugar alcohols. The metaproteomic functional responses of the CHO cluster were clustered with those of the prebiotics fructooligosaccharides and kestose. The sugar substitute sweeteners in the CHO cluster showed the ability to modulate the metabolism of Clostridia. This study provides a comprehensive evaluation of the direct effects of commonly used sugar substitute sweeteners on the functions of the human gut microbiome using a functional metaproteomic approach, improving our understanding of the roles of sugar substitute sweeteners on microbiome-associated human health and disease issues. IMPORTANCE The human gut microbiome is closely related to human health. Sugar substitute sweeteners as commonly used food additives are increasingly consumed and have potential impacts on microbiome functionality. Although many studies have evaluated the effects of a few sweeteners on gut microbiomes using animal models, the direct effect of sugar substitute sweeteners on the human gut microbiome remains largely unknown. Our results revealed that the sweetener-induced metaproteomic responses of individual microbiomes had two major patterns, which were associated with the chemical properties of the sweeteners. This study provided a comprehensive evaluation of the effects of commonly used sugar substitute sweeteners on the human gut microbiome.

Evaluating live microbiota biobanking using an ex vivo microbiome assay and metaproteomics.

Biobanking of live microbiota is becoming indispensable for mechanistic and clinical investigations of drug-microbiome interactions and fecal microbiota transplantation. However, there is a lack of methods to rapidly and systematically evaluate whether the biobanked microbiota maintains their cultivability and functional activity. In this study, we use a rapid ex vivo microbiome assay and metaproteomics to evaluate the cultivability and the functional responses of biobanked microbiota to treatment with a prebiotic (fructo-oligosaccharide, FOS). Our results indicate that the microbiota cultivability and their functional responses to FOS treatment were well maintained by freezing in a deoxygenated glycerol buffer at -80°C for 12 months. We also demonstrate that the fecal microbiota is functionally stable for 48 hours on ice in a deoxygenated glycerol buffer, allowing off-site fecal sample collection and shipping to laboratory for live microbiota biobanking. This study provides a method for rapid evaluation of the cultivability of biobanked live microbiota. Our results show minimal detrimental influences of long-term freezing in deoxygenated glycerol buffer on the cultivability of fecal microbiota.

Fabrication of Vertical-Standing Co-MOF Nanoarrays with 2D Parallelogram-like Morphology for Aqueous Asymmetric Electrochemical Capacitors.

Metal organic frameworks (MOFs) have been considered as one of the most promising electrode materials for electrochemical capacitors due to their large specific surface area and abundant pore structure. Herein, we report a Co-MOF electrode with a vertical-standing 2D parallelogram-like nanoarray structure on a Ni foam substrate via a one-step solvothermal method. The as-prepared Co-MOF on a Ni foam electrode delivered a high area-specific capacitance of 582.0 mC cm-2 at a current density of 2 mA cm-2 and a good performance rate of 350.0 mC cm-2 at 50 mA cm-2. Moreover, an asymmetric electrochemical capacitor (AEC) device (Co-MOF on Ni foam//AC) was assembled by using the as-prepared Co-MOF on a Ni foam as the cathode and a active carbon-coated Ni foam as the anode to achieve a maximum energy density of 0.082 mW cm-2 at a power density of 0.8 mW cm-2, which still maintained 0.065 mW cm-2 at a high power density of 11.94 mW cm-2. Meanwhile, our assembled device exhibited an excellent cycling stability with a capacitance retention of nearly 100% after 1000 cycles. Therefore, this work provides a simple method to prepare MOF-based material for the application of energy storage and conversion.

A functional ecological network based on metaproteomics responses of individual gut microbiomes to resistant starches.

Resistant starches (RS) are dietary compounds processed by the gut microbiota into metabolites, such as butyrate, that are beneficial to the host. The production of butyrate by the microbiome appears to be affected by the plant source and type of RS as well as the individual's microbiota. In this study, we used in vitro culture and metaproteomic methods to explore individual microbiome's functional responses to RS2 (enzymatically-resistant starch), RS3 (retrograded starch) and RS4 (chemically-modified starch). Results showed that RS2 and RS3 significantly altered the protein expressions in the individual gut microbiomes, while RS4 did not result in significant protein changes. Significantly elevated protein groups were enriched in carbohydrate metabolism and transport functions of families Eubacteriaceae, Lachnospiraceae and Ruminococcaceae. In addition, Bifidobacteriaceae was significantly increased in response to RS3. We also observed taxon-specific enrichments of starch metabolism and pentose phosphate pathways corresponding to this family. Functions related to starch utilization, ABC transporters and pyruvate metabolism pathways were consistently increased in the individual microbiomes in response to RS2 and RS3. Given that these taxon-specific responses depended on the type of carbohydrate sources, we constructed a functional ecological network to gain a system-level insight of functional organization. Our results suggest that while some microbes tend to be functionally independent, there are subsets of microbes that are functionally co-regulated by environmental changes, potentially by alterations of trophic interactions.

Proteomics and Metaproteomics Add Functional, Taxonomic and Biomass Dimensions to Modeling the Ecosystem at the Mucosal-luminal Interface.

Recent efforts in gut microbiome studies have highlighted the importance of explicitly describing the ecological processes beyond correlative analysis. However, we are still at the early stage of understanding the organizational principles of the gut ecosystem, partially because of the limited information provided by currently used analytical tools in ecological modeling practices. Proteomics and metaproteomics can provide a number of insights for ecological studies, including biomass, matter and energy flow, and functional diversity. In this Mini Review, we discuss proteomics and metaproteomics-based experimental strategies that can contribute to studying the ecology, in particular at the mucosal-luminal interface (MLI) where the direct host-microbiome interaction happens. These strategies include isolation protocols for different MLI components, enrichment methods to obtain designated array of proteins, probing for specific pathways, and isotopic labeling for tracking nutrient flow. Integration of these technologies can generate spatiotemporal and site-specific biological information that supports mathematical modeling of the ecosystem at the MLI.

MetaLab 2.0 Enables Accurate Post-Translational Modifications Profiling in Metaproteomics.

Studying the structure and function of microbiomes is an emerging research field. Metaproteomic approaches focusing on the characterization of expressed proteins and post-translational modifications (PTMs) provide a deeper understanding of microbial communities. Previous research has highlighted the value of examining microbiome-wide protein expression in studying the roles of the microbiome in human diseases. Nevertheless, the regulation of protein functions in complex microbiomes remains underexplored. This is mainly due to the lack of efficient bioinformatics tools to identify and quantify PTMs in the microbiome. We have developed comprehensive software termed MetaLab for the data analysis of metaproteomic data sets. Here, we build an open search workflow within MetaLab for unbiased identification and quantification of unmodified peptides as well as peptides with various PTMs from microbiome samples. This bioinformatics platform provides information about proteins, PTMs, taxa, functions, and pathways of microbial communities. The performance of the workflow was evaluated using conventional proteomics, metaproteomics from mouse and human gut microbiomes, and modification-specific enriched data sets. Superior accuracy and sensitivity were obtained simultaneously by using our method compared with the traditional closed search strategy.