The Landscape and Perspectives of the Human Gut Metaproteomics

The human gut microbiome is closely associated with human health and diseases. Metaproteomics has emerged as a valuable tool for studying the functionality of the gut microbiome by analyzing the entire proteins present in microbial communities. Recent advancements in liquid chromatography and tandem mass spectrometry (LC-MS/MS) techniques have expanded the detection range of metaproteomics. However, the overall coverage of the proteome in metaproteomics is still limited. While metagenomics studies have revealed substantial microbial diversity and functional potential of the human gut microbiome, few studies have summarized and studied the human gut microbiome landscape revealed with metaproteomics. In this paper, we present the current landscape of human gut metaproteomics studies by re-analyzing the identification results from fifteen published studies. We quantified the limited proteome coverage in metaproteomics and revealed a high proportion of annotation coverage of metaproteomics-identified proteins. We conducted a preliminary comparison between the metaproteomics view and the metagenomics view of the human gut microbiome, identifying key areas of consistency and divergence. Based on the current landscape of human gut metaproteomics, we discuss the feasibility of using metaproteomics to study functionally unknown proteins and propose a whole workflow peptide-centric analysis. Additionally, we suggest enhancing metaproteomics analysis by refining taxonomic classification and calculating confidence scores, as well as developing tools for analyzing the interaction between taxonomy and function.

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.

Staufen1 controls mitochondrial metabolism via HIF2α in embryonal rhabdomyosarcoma and promotes tumorigenesis

Elevated mitochondrial metabolism promotes tumorigenesis of Embryonal Rhabdomyosarcomas (ERMS). Accordingly, targeting oxidative phosphorylation (OXPHOS) could represent a therapeutic strategy for ERMS. We previously demonstrated that genetic reduction of Staufen1 (STAU1) levels results in the inhibition of ERMS tumorigenicity. Here, we examined STAU1-mediated mechanisms in ERMS and focused on its potential involvement in regulating OXPHOS. We report the novel and differential role of STAU1 in mitochondrial metabolism in cancerous versus non-malignant skeletal muscle cells (NMSkMCs). Specifically, our data show that STAU1 depletion reduces OXPHOS and inhibits proliferation of ERMS cells. Our findings further reveal the binding of STAU1 to several OXPHOS mRNAs which affects their stability. Indeed, STAU1 depletion reduced the stability of OXPHOS mRNAs, causing inhibition of mitochondrial metabolism. In parallel, STAU1 depletion impacted negatively the HIF2α pathway which further modulates mitochondrial metabolism. Exogenous expression of HIF2α in STAU1-depleted cells reversed the mitochondrial inhibition and induced cell proliferation. However, opposite effects were observed in NMSkMCs. Altogether, these findings revealed the impact of STAU1 in the regulation of mitochondrial OXPHOS in cancer cells as well as its differential role in NMSkMCs. Overall, our results highlight the therapeutic potential of targeting STAU1 as a novel approach for inhibiting mitochondrial metabolism in ERMS.

The LDL receptor is regulated by membrane cholesterol as revealed by fluorescence fluctuation analysis

Membrane cholesterol-rich domains have been shown to be important for regulating a range of membrane protein activities. Low-density lipoprotein receptor (LDLR)-mediated internalization of cholesterol-rich LDL particles is tightly regulated by feedback mechanisms involving intracellular sterol sensors. Since LDLR plays a role in maintaining cellular cholesterol homeostasis, we explore the role that membrane domains may have in regulating LDLR activity. We expressed a fluorescent LDLR-mEGFP construct in HEK293T cells and imaged the unligated receptor or bound to an LDL/DiI fluorescent ligand using total internal reflection fluorescence microscopy. We studied the receptor's spatiotemporal dynamics using fluorescence fluctuation analysis methods. Image cross correlation spectroscopy reveals a lower LDL-to-LDLR binding fraction when membrane cholesterol concentrations are augmented using cholesterol esterase, and a higher binding fraction when the cells are treated with methyl-β-cyclodextrin) to lower membrane cholesterol. This suggests that LDLR's ability to metabolize LDL particles is negatively correlated to membrane cholesterol concentrations. We then tested if a change in activity is accompanied by a change in membrane localization. Image mean-square displacement analysis reveals that unligated LDLR-mEGFP and ligated LDLR-mEGFP/LDL-DiI constructs are transiently confined on the cell membrane, and the size of their confinement domains increases with augmented cholesterol concentrations. Receptor diffusion within the domains and their domain-escape probabilities decrease upon treatment with methyl-β-cyclodextrin, consistent with a change in receptor populations to more confined domains, likely clathrin-coated pits. We propose a feedback model to account for regulation of LDLR within the cell membrane: when membrane cholesterol concentrations are high, LDLR is sequestered in cholesterol-rich domains. These LDLR populations are attenuated in their efficacy to bind and internalize LDL. However, when membrane cholesterol levels drop, LDL has a higher binding affinity to its receptor and the LDLR transits to nascent clathrin-coated domains, where it diffuses at a slower rate while awaiting internalization.

MetaPep: A core peptide database for faster human gut metaproteomics database searches

Metaproteomics has increasingly been applied to study functional changes in the human gut microbiome. Peptide identification is an important step in metaproteomics research, with sequence database search (SDS) and spectral library search (SLS) as the two main methods to identify peptides. However, the large search space in metaproteomics studies causes significant challenges for both identification methods. Moreover, with the development of mass spectrometry, it is now feasible to perform metaproteomic projects involving 100-1000 individual microbiomes. These large-scale projects create a conundrum for searching large databases. In this study, we constructed MetaPep, a core peptide database (including both collections of peptide sequences and tandem MS spectra) greatly accelerating the peptide identifications. Raw files from fifteen metaproteomics projects were re-analyzed and the identified peptide-spectrum matches (PSMs) were used to construct the MetaPep database. The constructed MetaPep database achieved rapid and accurate identification of peptides for human gut metaproteomics. MetaPep has a large collection of peptides and spectra that have been identified in published human gut metaproteomics datasets. MetaPep database can be used as an important resource in the current stage of human gut metaproteomics research. This study showed the possibility of applying a core peptide database as a generic metaproteomics workflow. MetaPep could also be an important resource for future human gut metaproteomics research, such as DIA (data-independent acquisition) analysis.

The Influence of Protein Secretomes of Enterococcus durans on ex vivo Human Gut Microbiome

The gut microbiome plays a critical role to all animals and humans health. Methods based on ex vivo cultures are time and cost-effective solutions for rapid evaluation of probiotic effects on microbiomes. In this study, we assessed whether the protein secretome from the potential probiotic Enterococcus durans LAB18S grown on fructoligosaccharides (FOS) and galactoligosaccharides (GOS) had specific effects on ex vivo cultured intestinal microbiome obtained from a healthy individual. Metaproteomics was used to evaluate changes in microbial communities of the human intestinal microbiome. Hierarchical clustering analysis revealed 654 differentially abundant proteins from the metaproteome samples, showing that gut microbial protein expression varied on the presence of different E. durans secretomes. Increased amount of Bacteroidetes phylum was observed in treatments with secretomes from E. durans cultures on FOS, GOS and albumin, resulting in a decrease of the Firmicutes to Bacteroidetes (F/B) ratio. The most functionally abundant bacterial taxa were Roseburia, Bacteroides, Alistipes and Faecalibacterium. The results suggest that the secretome of E. durans may have favorable effects on the intestinal microbial composition, stimulating growth and different protein expression of beneficial bacteria. These findings suggest that proteins secreted by E. durans growing on FOS and GOS have different effects on the modulation of gut microbiota functional activities during cultivation.

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.

Early postnatal defects in neurogenesis in the 3xTg mouse model of Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder leading to dementia. The hippocampus, which is one of the sites where neural stem cells reside and new neurons are born, exhibits the most significant neuronal loss in AD. A decline in adult neurogenesis has been described in several animal models of AD. However, the age at which this defect first appears remains unknown. To determine at which stage, from birth to adulthood, the neurogenic deficits are found in AD, we used the triple transgenic mouse model of AD (3xTg). We show that defects in neurogenesis are present as early as postnatal stages, well before the onset of any neuropathology or behavioral deficits. We also show that 3xTg mice have significantly fewer neural stem/progenitor cells, with reduced proliferation and decreased numbers of newborn neurons at postnatal stages, consistent with reduced volumes of hippocampal structures. To determine whether there are early changes in the molecular signatures of neural stem/progenitor cells, we perform bulk RNA-seq on cells sorted directly from the hippocampus. We show significant changes in the gene expression profiles at one month of age, including genes of the Notch and Wnt pathways. These findings reveal impairments in neurogenesis very early in the 3xTg AD model, which provides new opportunities for early diagnosis and therapeutic interventions to prevent neurodegeneration in AD.

An emerging field: Post-translational modification in microbiome

Post-translational modifications (PTMs) play an essential role in most biological processes. PTMs on human proteins have been extensively studied. Studies on bacterial PTMs are emerging, which demonstrate that bacterial PTMs are different from human PTMs in their types, mechanisms and functions. Few PTM studies have been done on the microbiome. Here, we reviewed several studied PTMs in bacteria including phosphorylation, acetylation, succinylation, glycosylation, and proteases. We discussed the enzymes responsible for each PTM and their functions. We also summarized the current methods used to study microbiome PTMs and the observations demonstrating the roles of PTM in the microbe-microbe interactions within the microbiome and their interactions with the environment or host. Although new methods and tools for PTM studies are still needed, the existing technologies have made great progress enabling a deeper understanding of the functional regulation of the microbiome. Large-scale application of these microbiome-wide PTM studies will provide a better understanding of the microbiome and its roles in the development of human diseases.

Butyrate's role in human health and the current progress towards its clinical application to treat gastrointestinal disease

Butyrate is a key energy source for colonocytes and is produced by the gut microbiota through fermentation of dietary fiber. Butyrate is a histone deacetylase inhibitor and also signals through three G-protein coupled receptors. It is clear that butyrate has an important role in gastrointestinal health and that butyrate levels can impact both host and microbial functions that are intimately coupled with each other. Maintaining optimal butyrate levels improves gastrointestinal health in animal models by supporting colonocyte function, decreasing inflammation, maintaining the gut barrier, and promoting a healthy microbiome. Butyrate has also shown protective actions in the context of intestinal diseases such as inflammatory bowel disease, graft-versus-host disease of the gastrointestinal tract, and colon cancer, whereas lower levels of butyrate and/or the microbes which are responsible for producing this metabolite are associated with disease and poorer health outcomes. However, clinical efforts to increase butyrate levels in humans and reverse these negative outcomes have generated mixed results. This article discusses our current understanding of the molecular mechanisms of butyrate action with a focus on the gastrointestinal system, the links between host and microbial factors, and the efforts that are currently underway to apply the knowledge gained from the bench to bedside.

Microbiota-directed biotherapeutics: considerations for quality and functional assessment

Mounting evidence points to causative or correlative roles of gut microbiome in the development of a myriad of diseases ranging from gastrointestinal diseases, metabolic diseases to neurological disorders and cancers. Consequently, efforts have been made to develop and apply therapeutics targeting the human microbiome, in particular the gut microbiota, for treating diseases and maintaining wellness. Here we summarize the current development of gut microbiota-directed therapeutics with a focus on novel biotherapeutics, elaborate the need of advanced -omics approaches for evaluating the microbiota-type biotherapeutics, and discuss the clinical and regulatory challenges. We also discuss the development and potential application of ex vivo microbiome assays and in vitro intestinal cellular models in this context. Altogether, this review aims to provide a broad view of promises and challenges of the emerging field of microbiome-directed human healthcare.

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.

The Functional Characteristics of Goat Cheese Microbiota from a One-Health Perspective

Goat cheese is an important element of the Mediterranean diet, appreciated for its health-promoting features and unique taste. A pivotal role in the development of these characteristics is attributed to the microbiota and its continuous remodeling over space and time. Nevertheless, no thorough study of the cheese-associated microbiota using two metaomics approaches has previously been conducted. Here, we employed 16S rRNA gene sequencing and metaproteomics to explore the microbiota of a typical raw goat milk cheese at various ripening timepoints and depths of the cheese wheel. The 16S rRNA gene-sequencing and metaproteomics results described a stable microbiota ecology across the selected ripening timepoints, providing evidence for the microbiologically driven fermentation of goat milk products. The important features of the microbiota harbored on the surface and in the core of the cheese mass were highlighted in both compositional and functional terms. We observed the rind microbiota struggling to maintain the biosafety of the cheese through competition mechanisms and/or by preventing the colonization of the cheese by pathobionts of animal or environmental origin. The core microbiota was focused on other biochemical processes, supporting its role in the development of both the health benefits and the pleasant gustatory nuances of goat cheese.

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.

A234 IN VITRO GUT MICROBIOME AND METABOLITE RESPONSES TO RESISTANT STARCH ARE INDIVIDUALIZED

Background

Gut microbes degrade and ferment resistant starch (RS) into metabolites that help maintain gut homeostasis. Clinical trials have evaluated RS for various health conditions, but individuals respond to RS with profound variability. The reason for this variability is unclear.

Aims

Using in vitro culturing methods and multi-omic analyses, we hypothesize that individuals will elicit variable responses to RS with respect to overall fermentation, bacterial composition, short chain acid production, and metabolite flux.

Methods

As part of an ongoing clinical trial, we have selected 4 pediatric patients with inflammatory bowel disease to better understand microbiome-RS interactions. We cultured stools anaerobically using a high-throughput platform (“RapidAIM”) with 9 different pre-digested RS. After 18-hour incubations, media supernatants were used to measure pH and perform targeted and semi-targeted metabolomic analyses with a panel of 116 compounds. Bacterial pellets were isolated for 16S rRNA gene sequencing analyses to evaluate changes in microbiome compositions. Data were analyzed with generalized linear mixed models, principal component analysis (PCA), random forest (RF) classification with feature selection, and network construction with graphical lasso.

Results

Changes in several microbiome parameters were different across individuals, including the magnitude of pH changes, metabolite signatures, and relative abundances of important bacterial taxa. Bacterial species known to degrade RS were more abundant in individuals showing stronger RS fermentation. Inter-individual discrimination was accomplished with PCA and RF, from which we could identify metabolite signatures. The robustness of microbiome networks corresponded to RS fermentation and butyrate production.

Conclusions

We report a novel perspective on how individuals respond to RS’ differently. Butyrate remains an important hub of the microbiome architecture with respect to RS fermentation. Future work will interrogate the roles of individualized metabolomic responses on host physiology. In vivo responses to RS are being evaluated in an ongoing clinical trial.

Funding Agencies

CCC, CIHRGenome Ontario, Genome Canada

Structural analysis of Atopobium parvulum SufS cysteine desulfurase linked to Crohn's disease

Crohn's Disease (CD) is characterized by the chronic inflammation of the gastrointestinal tract. A dysbiotic microbiome and a defective immune system are linked to CD, where hydrogen sulfide (H₂ S) microbial producers positively correlate with the severity of the disease. Atopobium parvulum is a key H₂ S producer from the microbiome of CD patients. In this study, the biochemical characterization of two Atopobium parvulum cysteine desulfurases, ApSufS and ApCsdB, show that the enzymes are allosterically regulated. Structural analyses reveal that ApSufS forms a dimer with conserved characteristics observed in type II cysteine desulfurases. Four residues surrounding the active site are essential to catalyze cysteine desulfurylation, and a segment of short-chain residues grant access for substrate binding. A better understanding of ApSufS will help future avenues for CD treatment.

Proteogenomic characterization identifies clinically relevant subgroups of intrahepatic cholangiocarcinoma

We performed proteogenomic characterization of intrahepatic cholangiocarcinoma (iCCA) using paired tumor and adjacent liver tissues from 262 patients. Integrated proteogenomic analyses prioritized genetic aberrations and revealed hallmarks of iCCA pathogenesis. Aflatoxin signature was associated with tumor initiation, proliferation, and immune suppression. Mutation-associated signaling profiles revealed that TP53 and KRAS co-mutations may contribute to iCCA metastasis via the integrin-FAK-SRC pathway. FGFR2 fusions activated the Rho GTPase pathway and could be a potential source of neoantigens. Proteomic profiling identified four patient subgroups (S1-S4) with subgroup-specific biomarkers. These proteomic subgroups had distinct features in prognosis, genetic alterations, microenvironment dysregulation, tumor microbiota composition, and potential therapeutics. SLC16A3 and HKDC1 were further identified as potential prognostic biomarkers associated with metabolic reprogramming of iCCA cells. This study provides a valuable resource for researchers and clinicians to further identify molecular pathogenesis and therapeutic opportunities in iCCA.

Novel Bioinformatics Strategies Driving Dynamic Metaproteomic Studies

Constant improvements in mass spectrometry technologies and laboratory workflows have enabled the proteomics investigation of biological samples of growing complexity. Microbiomes represent such complex samples for which metaproteomics analyses are becoming increasingly popular. Metaproteomics experimental procedures create large amounts of data from which biologically relevant signal must be efficiently extracted to draw meaningful conclusions. Such a data processing requires appropriate bioinformatics tools specifically developed for, or capable of handling metaproteomics data. In this chapter, we outline current and novel tools that can perform the most commonly used steps in the analysis of cutting-edge metaproteomics data, such as peptide and protein identification and quantification, as well as data normalization, imputation, mining, and visualization. We also provide details about the experimental setups in which these tools should be used.

A simultaneous identification and quantification strategy for determination of sulfhydryl-containing metabolites in normal- and high-fat diet hamsters using stable isotope labeling combined with LC-MS

Sulfur-containing metabolites are related to several physiologic disorders and metabolic diseases. In this study, a simultaneous identification and quantification strategy in one batch for determination of sulfhydryl-containing metabolites was developed using stable isotope labeling combined with liquid chromatography-tandem mass spectrometry (SIL-LC-MS). In the proposed method, a pair of isotope labeling reagents, D₀/D₅-N-ethylmaleimide (D₀/D₅-NEM), was used to derivatize sulfhydryl-containing metabolites in blood and plasma of normal- and high-fat-diet (NFD and HFD) hamsters for reduced (-SH) and total (-SH, -S-S-, S-glutathionylated proteins) analysis. Quality control (QC) samples and test samples were prepared for LC-MS analysis. First, both QC samples and stable isotope labeled internal standards were used to monitor the status of the instrument and ensure the reliability of the analysis. Subsequently, an inhouse database containing 45 sulfhydryl-containing metabolites was established by MS¹ based on QC samples. Then, qualitatively differential sulfhydryl-containing metabolites were found by MS² between the NFD and HFD hamsters of the test samples, including 3 in reduced and 8 in total analysis of blood samples, and 2 in reduced and 2 in total analysis of plasma samples. Next, in quantitative analysis, satisfied linearities for 6 sulfhydryl-containing metabolites were obtained with the correlation coefficient (R²) > 0.99 and absolute quantification was carried out. The results showed that glutathione and cysteine have different concentrations in blood and plasma of hamsters. Finally, the correlation of sulfhydryl-containing metabolites with blood lipid and oxidative stress levels was determined, which provided insight into the hyperlipidemia-related oxidative stress. Taken together, the developed method of simultaneous identification with the inhouse database and MS² and quantification with standards in one batch provides a promising strategy for the analysis of sulfhydryl-containing metabolites in biological samples, which may promote the in-depth investigation on sulfhydryl-containing metabolites and related diseases.

Elevated colonic microbiota-associated paucimannosidic and truncated N-glycans in pediatric ulcerative colitis

Pediatric ulcerative colitis (UC) is a distinct type of inflammatory bowel disease with severe disease activity and rapid progression, which can lead to detrimental life-long consequences. The pathogenesis of pediatric UC remains unclear, although dysbiosis of the gut microbiota has been considered an important factor. In this study, we collected intestinal mucosal-luminal interface microbiota samples from a cohort of treatment-naïve pediatric UC or control patients and used two different mass spectrometry-based glycomic approaches to examine the N-glycans that were associated with the microbiota. We observed abundant small N-glycans that were associated with the microbiota and found that the pediatric UC microbiota samples contained significantly higher levels of these atypical N-glycans compared to those of controls. Four paucimannosidic or other truncated N-glycans were identified to successfully segregate UC from control patients with an area under the ROC curve of ≥0.9. This study indicates that the aberrant metabolism of glycans in the intestinal by gut microbiota may be involved in the pathogenesis of UC and intestinal N-glycans, including small glycans, can act as novel biomarker candidates for pediatric UC. SIGNIFICANCE: There is no cure for pediatric ulcerative colitis (UC) due to its unclear pathogenesis and the diagnosis of UC in children still largely depends on invasive colonoscopic examination. Recent evidence suggests that the dysbiosis of intestinal microbiota is associated with the onset and development of UC, however how the microbiota interact with the host remains unclear. This study used two different mass spectrometry-based glycomic approaches to quantitatively examine N-glycans that are associated with colonic mucosal-luminal interface microbiota of pediatric UC or control patients. To the best of our knowledge, this is the first comprehensive glycomic study of intestinal microbiota samples in UC, which demonstrated that intestinal microbiota was associated with abundant atypical small N-glycans with elevated levels in UC than controls. This study also identified four intestinal paucimannosidic or other truncated N-glycans as promising biomarker candidates for pediatric UC. These findings shed light on the mechanism study of host-microbiome interactions in UC and indicate that atypical glycans present in the gut can be a source for UC biomarker discovery.

Associations between Cellular Energy and Pediatric Inflammatory Bowel Disease Patient Response to Treatment

Inflammatory bowel diseases (IBDs), including Crohn's disease (CD) and ulcerative colitis, are chronic diseases of the gastrointestinal tract, with an unknown etiology, that affect over 6.8 million people worldwide. To characterize disease pathogenesis, proteomic and bioinformatic analyses were performed on colon biopsies collected during diagnostic endoscopy from 119 treatment-naïve pediatric patients, including from 78 IBD patients and 41 non-IBD patients who served as controls. Due to the presence of noninflamed and/or inflamed regions in IBD patients, up to two biopsies were obtained from IBD patients as compared to a single noninflamed biopsy from non-IBD pediatric control patients. Additional biopsies were obtained and analyzed from 33 of the IBD patients after IBD-directed therapeutic intervention for comparison of pre- and post-treatment proteomes. SuperSILAC was utilized to perform quantitative analysis of homogenized tissues, which were processed by filter-aided sample preparation. Hierarchical clustering and principal component analyses revealed proteomic patterns that distinguished inflamed from noninflamed tissues independent of therapy. Gene ontology revealed that proteins downregulated in inflammation are associated with metabolism, whereas upregulated proteins contribute to protein processing. A comparison of pre- and post-treatment proteomes from CD patients identified over 100 proteins that are significantly different between patients who responded and those who did not respond to therapy, including creatine kinase B and basigin.

Catching a resurgence: Increase in SARS-CoV-2 viral RNA identified in wastewater 48 h before COVID-19 clinical tests and 96 h before hospitalizations

Curtailing the Spring 2020 COVID-19 surge required sweeping and stringent interventions by governments across the world. Wastewater-based COVID-19 epidemiology programs have been initiated in many countries to provide public health agencies with a complementary disease tracking metric and non-discriminating surveillance tool. However, their efficacy in prospectively capturing resurgences following a period of low prevalence is unclear. In this study, the SARS-CoV-2 viral signal was measured in primary clarified sludge harvested every two days at the City of Ottawa's water resource recovery facility during the summer of 2020, when clinical testing recorded daily percent positivity below 1%. In late July, increases of >400% in normalized SARS-CoV-2 RNA signal in wastewater were identified 48 h prior to reported >300% increases in positive cases that were retrospectively attributed to community-acquired infections. During this resurgence period, SARS-CoV-2 RNA signal in wastewater preceded the reported >160% increase in community hospitalizations by approximately 96 h. This study supports wastewater-based COVID-19 surveillance of populations in augmenting the efficacy of diagnostic testing, which can suffer from sampling biases or timely reporting as in the case of hospitalization census.

Catching a resurgence: Increase in SARS-CoV-2 viral RNA identified in wastewater 48 h before COVID-19 clinical tests and 96 h before hospitalizations

Curtailing the Spring 2020 COVID-19 surge required sweeping and stringent interventions by governments across the world. Wastewater-based COVID-19 epidemiology programs have been initiated in many countries to provide public health agencies with a complementary disease tracking metric and non-discriminating surveillance tool. However, their efficacy in prospectively capturing resurgences following a period of low prevalence is unclear. In this study, the SARS-CoV-2 viral signal was measured in primary clarified sludge harvested every two days at the City of Ottawa's water resource recovery facility during the summer of 2020, when clinical testing recorded daily percent positivity below 1%. In late July, increases of >400% in normalized SARS-CoV-2 RNA signal in wastewater were identified 48 h prior to reported >300% increases in positive cases that were retrospectively attributed to community-acquired infections. During this resurgence period, SARS-CoV-2 RNA signal in wastewater preceded the reported >160% increase in community hospitalizations by approximately 96 h. This study supports wastewater-based COVID-19 surveillance of populations in augmenting the efficacy of diagnostic testing, which can suffer from sampling biases or timely reporting as in the case of hospitalization census.

Exploring the Microbiome-Wide Lysine Acetylation, Succinylation, and Propionylation in Human Gut Microbiota

Lysine acylations are important post-translational modifications that are present in both eukaryotes and prokaryotes and regulate diverse cellular functions. Our knowledge of the microbiome lysine acylation remains limited due to the lack of efficient analytical and bioinformatics methods for complex microbial communities. Here, we show that the serial enrichment using motif antibodies successfully captures peptides containing lysine acetylation, propionylation, and succinylation from human gut microbiome samples. A new bioinformatic workflow consisting of an unrestricted database search confidently identified >60,000 acetylated, and ∼20,000 propionylated and succinylated gut microbial peptides. The characterization of these identified modification-specific metaproteomes, i.e., meta-PTMomes, demonstrates that lysine acylations are differentially distributed in microbial species with different metabolic capabilities. This study provides an analytical framework for the study of lysine acylations in the microbiome, which enables functional microbiome studies at the post-translational level.

Identification of novel lipid droplet factors that regulate lipophagy and cholesterol efflux in macrophage foam cells

Macrophage autophagy is a highly anti-atherogenic process that promotes the catabolism of cytosolic lipid droplets (LDs) to maintain cellular lipid homeostasis. Selective autophagy relies on tags such as ubiquitin and a set of selectivity factors including selective autophagy receptors (SARs) to label specific cargo for degradation. Originally described in yeast cells, "lipophagy" refers to the degradation of LDs by autophagy. Yet, how LDs are targeted for autophagy is poorly defined. Here, we employed mass spectrometry to identify lipophagy factors within the macrophage foam cell LD proteome. In addition to structural proteins (e.g., PLIN2), metabolic enzymes (e.g., ACSL) and neutral lipases (e.g., PNPLA2), we found the association of proteins related to the ubiquitination machinery (e.g., AUP1) and autophagy (e.g., HMGB, YWHA/14-3-3 proteins). The functional role of candidate lipophagy factors (a total of 91) was tested using a custom siRNA array combined with high-content cholesterol efflux assays. We observed that knocking down several of these genes, including Hmgb1, Hmgb2, Hspa5, and Scarb2, significantly reduced cholesterol efflux, and SARs SQSTM1/p62, NBR1 and OPTN localized to LDs, suggesting a role for these in lipophagy. Using yeast lipophagy assays, we established a genetic requirement for several candidate lipophagy factors in lipophagy, including HSPA5, UBE2G2 and AUP1. Our study is the first to systematically identify several LD-associated proteins of the lipophagy machinery, a finding with important biological and therapeutic implications. Targeting these to selectively enhance lipophagy to promote cholesterol efflux in foam cells may represent a novel strategy to treat atherosclerosis.Abbreviations:ADGRL3: adhesion G protein-coupled receptor L3; agLDL: aggregated low density lipoprotein; AMPK: AMP-activated protein kinase; APOA1: apolipoprotein A1; ATG: autophagy related; AUP1: AUP1 lipid droplet regulating VLDL assembly factor; BMDM: bone-marrow derived macrophages; BNIP3L: BCL2/adenovirus E1B interacting protein 3-like; BSA: bovine serum albumin; CALCOCO2: calcium binding and coiled-coil domain 2; CIRBP: cold inducible RNA binding protein; COLGALT1: collagen beta(1-O)galactosyltransferase 1; CORO1A: coronin 1A; DMA: deletion mutant array; Faa4: long chain fatty acyl-CoA synthetase; FBS: fetal bovine serum; FUS: fused in sarcoma; HMGB1: high mobility group box 1; HMGB2: high mobility group box 2: HSP90AA1: heat shock protein 90: alpha (cytosolic): class A member 1; HSPA5: heat shock protein family A (Hsp70) member 5; HSPA8: heat shock protein 8; HSPB1: heat shock protein 1; HSPH1: heat shock 105kDa/110kDa protein 1; LDAH: lipid droplet associated hydrolase; LIPA: lysosomal acid lipase A; LIR: LC3-interacting region; MACROH2A1: macroH2A.1 histone; MAP1LC3: microtubule-associated protein 1 light chain 3; MCOLN1: mucolipin 1; NBR1: NBR1, autophagy cargo receptor; NPC2: NPC intracellular cholesterol transporter 2; OPTN: optineurin; P/S: penicillin-streptomycin; PLIN2: perilipin 2; PLIN3: perilipin 3; PNPLA2: patatin like phospholipase domain containing 2; RAB: RAB, member RAS oncogene family; RBBP7, retinoblastoma binding protein 7, chromatin remodeling factor; SAR: selective autophagy receptor; SCARB2: scavenger receptor class B, member 2; SGA: synthetic genetic array; SQSTM1: sequestosome 1; TAX1BP1: Tax1 (human T cell leukemia virus type I) binding protein 1; TFEB: transcription factor EB; TOLLIP: toll interacting protein; UBE2G2: ubiquitin conjugating enzyme E2 G2; UVRAG: UV radiation resistance associated gene; VDAC2: voltage dependent anion channel 2; VIM: vimentin.

Quantitative analysis of SARS-CoV-2 RNA from wastewater solids in communities with low COVID-19 incidence and prevalence

In the absence of an effective vaccine to prevent COVID-19 it is important to be able to track community infections to inform public health interventions aimed at reducing the spread and therefore reduce pressures on health-care, improve health outcomes and reduce economic uncertainty. Wastewater surveillance has rapidly emerged as a potential tool to effectively monitor community infections through measuring trends of RNA signal in wastewater systems. In this study SARS-CoV-2 viral RNA N1 and N2 gene regions are quantified in solids collected from influent post grit solids (PGS) and primary clarified sludge (PCS) in two water resource recovery facilities (WRRF) serving Canada's national capital region, i.e., the City of Ottawa, ON (pop. ≈ 1.1M) and the City of Gatineau, QC (pop. ≈ 280K). PCS samples show signal inhibition using RT-ddPCR compared to RT-qPCR, with PGS samples showing similar quantifiable concentrations of RNA using both assays. RT-qPCR shows higher frequency of detection of N1 and N2 gene regions in PCS (92.7, 90.6%, n = 6) as compared to PGS samples (79.2, 82.3%, n = 5). Sampling of PCS may therefore be an effective approach for SARS-CoV-2 viral quantification, especially during periods of declining and low COVID-19 incidence in the community. The pepper mild mottle virus (PMMoV) is determined to have a less variable RNA signal in PCS over a three month period for two WRRFs, regardless of environmental conditions, compared to Bacteroides 16S rRNA or human 18S rRNA, making PMMoV a potentially useful biomarker for normalization of SARS-CoV-2 signal. PMMoV-normalized PCS RNA signal from WRRFs of two cities correlated with the regional public health epidemiological metrics, identifying PCS normalized to a fecal indicator (PMMoV) as a potentially effective tool for monitoring trends during decreasing and low-incidence of infection of SARS-Cov-2 in communities.

Quantitative analysis of SARS-CoV-2 RNA from wastewater solids in communities with low COVID-19 incidence and prevalence

In the absence of an effective vaccine to prevent COVID-19 it is important to be able to track community infections to inform public health interventions aimed at reducing the spread and therefore reduce pressures on health-care, improve health outcomes and reduce economic uncertainty. Wastewater surveillance has rapidly emerged as a potential tool to effectively monitor community infections through measuring trends of RNA signal in wastewater systems. In this study SARS-CoV-2 viral RNA N1 and N2 gene regions are quantified in solids collected from influent post grit solids (PGS) and primary clarified sludge (PCS) in two water resource recovery facilities (WRRF) serving Canada's national capital region, i.e., the City of Ottawa, ON (pop. ≈ 1.1M) and the City of Gatineau, QC (pop. ≈ 280K). PCS samples show signal inhibition using RT-ddPCR compared to RT-qPCR, with PGS samples showing similar quantifiable concentrations of RNA using both assays. RT-qPCR shows higher frequency of detection of N1 and N2 gene regions in PCS (92.7, 90.6%, n = 6) as compared to PGS samples (79.2, 82.3%, n = 5). Sampling of PCS may therefore be an effective approach for SARS-CoV-2 viral quantification, especially during periods of declining and low COVID-19 incidence in the community. The pepper mild mottle virus (PMMoV) is determined to have a less variable RNA signal in PCS over a three month period for two WRRFs, regardless of environmental conditions, compared to Bacteroides 16S rRNA or human 18S rRNA, making PMMoV a potentially useful biomarker for normalization of SARS-CoV-2 signal. PMMoV-normalized PCS RNA signal from WRRFs of two cities correlated with the regional public health epidemiological metrics, identifying PCS normalized to a fecal indicator (PMMoV) as a potentially effective tool for monitoring trends during decreasing and low-incidence of infection of SARS-Cov-2 in communities.

Studying the Temporal Dynamics of the Gut Microbiota Using Metabolic Stable Isotope Labeling and Metaproteomics

The gut microbiome and its metabolic processes are dynamic systems. Surprisingly, our understanding of gut microbiome dynamics is limited. Here, we report a metaproteomic workflow that involves protein stable isotope probing (protein-SIP) and identification/quantification of partially labeled peptides. We also developed a package, which we call MetaProfiler, that corrects for false identifications and performs phylogenetic and time series analysis for the study of microbiome dynamics. From the stool sample of five mice that were fed with ¹⁵N hydrolysate from Ralstonia eutropha, we identified 12 326 nonredundant unlabeled peptides, of which 8256 of their heavy counterparts were quantified. These peptides revealed incorporation profiles over time that were different between and within taxa, as well as between and within clusters of orthologous groups (COGs). Our study helps unravel the complex dynamics of protein synthesis and bacterial dynamics in the mouse microbiome. MetaProfiler and the bioinformatic pipeline are available at https://github.com/northomics/MetaProfiler.git.

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.

Berberine and its structural analogs have differing effects on functional profiles of individual gut microbiomes

The understanding of the effects of compounds on the gut microbiome is limited. In particular, it is unclear whether structurally similar compounds would have similar or distinct effects on the gut microbiome. Here, we selected berberine (BBR), an isoquinoline quaternary alkaloid, and 16 structural analogs and evaluated their effects on seven individual gut microbiomes cultured in vitro. The responses of the individual microbiomes were evaluated by metaproteomic profiles and by assessing butyrate production. We show that both interindividual differences and compound treatments significantly contributed to the variance of metaproteomic profiles. BBR and eight analogs led to changes in proteins involved in microbial defense and stress responses and enrichment of proteins from Verrucomicrobia, Proteobacteria, and Bacteroidetes phyla. It also led to a decrease in proteins from the Firmicutes phylum and its Clostridiales order which correlated to decrease proteins involved in the butyrate production pathway and butyrate concentration. Three of the compounds, sanguinarine, chelerythrine, and ethoxysanguinarine, activated bacterial protective mechanisms, enriched Proteobacteria, increased opacity proteins, and markedly reduced butyrate production. Dihydroberberine had a similar function to BBR in enriching the Akkermansia genus. In addition, it showed less overall adverse impacts on the functionality of the gut microbiome, including a better maintenance of the butyrate level. Our study shows that ex vivo microbiome assay can assess differential regulating effects of compounds with subtle differences and reveals that compound analogs can have distinct effects on the microbiome.

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.

MealTime-MS: A Machine Learning-Guided Real-Time Mass Spectrometry Analysis for Protein Identification and Efficient Dynamic Exclusion

Mass spectrometry-based proteomics technologies are prime methods for the high-throughput identification of proteins in complex biological samples. Nevertheless, there are still technical limitations that hinder the ability of mass spectrometry to identify low abundance proteins in complex samples. Characterizing such proteins is essential to provide a comprehensive understanding of the biological processes taking place in cells and tissues. Still today, most mass spectrometry-based proteomics approaches use a data-dependent acquisition strategy, which favors the collection of mass spectra from proteins of higher abundance. Since the computational identification of proteins from proteomics data is typically performed after mass spectrometry analysis, large numbers of mass spectra are typically redundantly acquired from the same abundant proteins, and little to no mass spectra are acquired for proteins of lower abundance. We therefore propose a novel supervised learning algorithm, MealTime-MS, that identifies proteins in real-time as mass spectrometry data are acquired and prevents further data collection from confidently identified proteins to ultimately free mass spectrometry resources to improve the identification sensitivity of low abundance proteins. We use real-time simulations of a previously performed mass spectrometry analysis of a HEK293 cell lysate to show that our approach can identify 92.1% of the proteins detected in the experiment using 66.2% of the MS2 spectra. We also demonstrate that our approach outperforms a previously proposed method, is sufficiently fast for real-time mass spectrometry analysis, and is flexible. Finally, MealTime-MS' efficient usage of mass spectrometry resources will provide a more comprehensive characterization of proteomes in complex samples.

Metaproteomics Reveals Growth Phase-Dependent Responses of an In Vitro Gut Microbiota to Metformin

Metaproteomics has been used in combination with in vitro gut microbiota models to study drug-microbiome interactions. However, it remains unexplored whether the metaproteomics profile of in vitro gut microbiota responds differently to a same stimulus added at different growth phases. In this study, we cultured a human gut microbiota in 96-deep well plates using a previously validated model. Metformin was added during the lag, log, and stationary phases. Microbiome samples, collected at different time points, were analyzed by optical density and function by metaproteomic. The in vitro gut microbiota growth curves, taxonomy, and functional responses were different depending whether metformin was added during the lag, log, or stationary phases. The addition of drugs at the log phase may lead to the greatest decline of bacterial growth. Metaproteomic analysis suggests that the strength of the metformin effect on the gut microbiome functional profile may be ranked as lag phase > log phase > stationary phase. Metformin added at the lag phase may result in a significantly reduced level of the Clostridiales order and an increased level of the Bacteroides genus, which is different from stimulations during the rest of the growth phases. Metformin may also result in alterations of several pathways, including energy production and conversion, lipid transport and metabolism, translation, ribosomal structure, and biogenesis. Our results indicate that the timing for drug stimulation should be considered when studying drug-microbiome interactions in vitro.

Comparative proteomic analysis reveals metabolic variability of probiotic Enterococcus durans during aerobic and anaerobic cultivation

The variation in the bioavailability of oxygen constitutes the environmental conditions found by bacteria in their passage through the host gastro-intestinal tract. Given the importance of oxygen in the defense mechanism of bacteria, it is important to understand how bacteria respond to this stress at a metabolic level. The probiotic strain Enterococcus durans LAB18S was cultivated under aerobic and anaerobic conditions using prebiotic oligosaccharides as carbon source. The whole cell proteome and secretome were analyzed through label-free quantitative proteomics approach. The results showed that the LAB18S isolate when grown with fructo-oligosacchrides (FOS) showed a higher number of differentially expressed proteins compared to samples with galacto-oligosaccharides (GOS) or glucose. Clinically important enzymes for the treatment of cancer, L-asparaginase and arginine deiminase, were overexpressed when the isolate was cultured in FOS. In addition, the absence of oxygen induced the strain to produce proteins related to cell multiplication, cell wall integrity and resistance, and H₂O₂ detoxification. This study showed that E. durans LAB18S growing on FOS was stimulated to produce clinically important biomolecules, including proteins that have been investigated as potential antineoplastic agents. Significance: The probiotic strain E. durans LAB18S produce clinically relevant enzymes for the treatment of cancer when cultivated in symbiosis with fructo-oligosacchrides (FOS). In addition, proteins associated with cellular multiplication, cell wall integrity and resistance, and H₂O₂ detoxification were induced under anaerobic growth. These characteristics could be relevant to support maintenance of intestinal health.

pepFunk: a tool for peptide-centric functional analysis of metaproteomic human gut microbiome studies

Motivation

Enzymatic digestion of proteins before mass spectrometry analysis is a key process in metaproteomic workflows. Canonical metaproteomic data processing pipelines typically involve matching spectra produced by the mass spectrometer to a theoretical spectra database, followed by matching the identified peptides back to parent-proteins. However, the nature of enzymatic digestion produces peptides that can be found in multiple proteins due to conservation or chance, presenting difficulties with protein and functional assignment.

Results

To combat this challenge, we developed pepFunk, a peptide-centric metaproteomic workflow focused on the analysis of human gut microbiome samples. Our workflow includes a curated peptide database annotated with Kyoto Encyclopedia of Genes and Genomes (KEGG) terms and a gene set variation analysis-inspired pathway enrichment adapted for peptide-level data. Analysis using our peptide-centric workflow is fast and highly correlated to a protein-centric analysis, and can identify more enriched KEGG pathways than analysis using protein-level data. Our workflow is open source and available as a web application or source code to be run locally.

Availability and implementation

pepFunk is available online as a web application at https://shiny.imetalab.ca/pepFunk/ with open-source code available from https://github.com/northomics/pepFunk.

Contact

dfigeys@uottawa.ca

Supplementary information

Supplementary data are available at Bioinformatics online.

RapidAIM: a culture- and metaproteomics-based Rapid Assay of Individual Microbiome responses to drugs

BACKGROUND

Human-targeted drugs may exert off-target effects or can be repurposed to modulate the gut microbiota. However, our understanding of such effects is limited due to a lack of rapid and scalable assay to comprehensively assess microbiome responses to drugs. Drugs and other compounds can drastically change the overall abundance, taxonomic composition, and functions of a gut microbiome.

RESULTS

Here, we developed an approach to screen compounds against individual microbiomes in vitro, using metaproteomics to both measure absolute bacterial abundances and to functionally profile the microbiome. Our approach was evaluated by testing 43 compounds (including 4 antibiotics) against 5 individual microbiomes. The method generated technically highly reproducible readouts, including changes of overall microbiome abundance, microbiome composition, and functional pathways. Results show that besides the antibiotics, the compounds berberine and ibuprofen inhibited the accumulation of biomass during in vitro growth of the microbiota. By comparing genus and species level-biomass contributions, selective antibacterial-like activities were found with 35 of the 39 non-antibiotic compounds. Seven of the compounds led to a global alteration of the metaproteome, with apparent compound-specific patterns of functional responses. The taxonomic distributions of altered proteins varied among drugs, i.e., different drugs affect functions of different members of the microbiome. We also showed that bacterial function can shift in response to drugs without a change in the abundance of the bacteria.

CONCLUSIONS

Current drug-microbiome interaction studies largely focus on relative microbiome composition and microbial drug metabolism. In contrast, our workflow enables multiple insights into microbiome absolute abundance and functional responses to drugs. The workflow is robust, reproducible, and quantitative and is scalable for personalized high-throughput drug screening applications.

Differential Lysis Approach Enables Selective Extraction of Taxon-Specific Proteins for Gut Metaproteomics

Changes in microbiome composition and function have been linked to human health and diseases. Metaproteomics provides invaluable functional information on the state of a microbiome. However, lower-abundance bacteria in complex microbiomes are difficult to observe by metaproteomics. In this study, stepwise differential lysis protocols were developed for human stool microbiomes to separate different microbial species and to increase the depth of metaproteomic measurements. We achieved differential lysis of Gram-positive (G⁺) and Gram-negative (G^-) bacteria, selective enrichment of specific bacteria, and functional enrichment by our stepwise differential lysis protocols. Therefore, differential lysis can serve as a fractionation method to reduce sample complexity and selectively extract proteins from specific taxa for deep metaproteomic studies.

Aging Disrupts the Circadian Patterns of Protein Expression in the Murine Hippocampus

Aging is associated with cognitive decline and dysregulation of the circadian system, which modulates hippocampal-dependent memory as well as biological processes underlying hippocampal function. While circadian dysfunction and memory impairment are common features of aging and several neurodegenerative brain disorders, how aging impacts the circadian expression patterns of proteins involved in processes that underlie hippocampal-dependent memory is not well understood. In this study, we profiled the hippocampal proteomes of young and middle-aged mice across two circadian cycles using quantitative mass spectrometry in order to explore aging-associated changes in the temporal orchestration of biological pathways. Of the ∼1,420 proteins that were accurately quantified, 15% (214 proteins) displayed circadian rhythms in abundance in the hippocampus of young mice, while only 1.6% (23 proteins) were rhythmic in middle-aged mice. Remarkably, aging disrupted the circadian regulation of proteins involved in cellular functions critical for hippocampal function and memory, including dozens of proteins participating in pathways of energy metabolism, neurotransmission, and synaptic plasticity. These included processes such as glycolysis, the tricarboxylic acid cycle, synaptic vesicle cycling, long-term potentiation, and cytoskeletal organization. Moreover, aging altered the daily expression rhythms of proteins implicated in hallmarks of aging and the pathogenesis of several age-related neurodegenerative brain disorders affecting the hippocampus. Notably, we identified age-related alterations in the rhythmicity of proteins involved in mitochondrial dysfunction and loss of proteostasis, as well as proteins involved in the pathogenesis of disorders such as Alzheimer’s disease and Parkinson’s disease. These insights into aging-induced changes in the hippocampal proteome provide a framework for understanding how the age-dependent circadian decline may contribute to cognitive impairment and the development of neurodegenerative diseases during aging.

A non-canonical monovalent zinc finger stabilizes the integration of Cfp1 into the H3K4 methyltransferase complex COMPASS

COMPlex ASsociating with SET1 (COMPASS) is a histone H3 Lys-4 methyltransferase that typically marks the promoter region of actively transcribed genes. COMPASS is a multi-subunit complex in which the catalytic unit, SET1, is required for H3K4 methylation. An important subunit known to regulate SET1 methyltransferase activity is the CxxC zinc finger protein 1 (Cfp1). Cfp1 binds to COMPASS and is critical to maintain high level of H3K4me3 in cells but the mechanisms underlying its stimulatory activity is poorly understood. In this study, we show that Cfp1 only modestly activates COMPASS methyltransferase activity in vitro. Binding of Cfp1 to COMPASS is in part mediated by a new type of monovalent zinc finger (ZnF). This ZnF interacts with the COMPASS's subunits RbBP5 and disruption of this interaction blunts its methyltransferase activity in cells and in vivo. Collectively, our studies reveal that a novel form of ZnF on Cfp1 enables its integration into COMPASS and contributes to epigenetic signaling.

Advancing functional and translational microbiome research using meta-omics approaches

The gut microbiome has emerged as an important factor affecting human health and disease. The recent development of -omics approaches, including phylogenetic marker-based microbiome profiling, shotgun metagenomics, metatranscriptomics, metaproteomics, and metabolomics, has enabled efficient characterization of microbial communities. These techniques can provide strain-level taxonomic resolution of the taxa present in microbiomes, assess the potential functions encoded by the microbial community and quantify the metabolic activities occurring within a complex microbiome. The application of these meta-omics approaches to clinical samples has identified microbial species, metabolic pathways, and metabolites that are associated with the development and treatment of human diseases. These findings have further facilitated microbiome-targeted drug discovery and efforts to improve human health management. Recent in vitro and in vivo investigations have uncovered the presence of extensive drug-microbiome interactions. These interactions have also been shown to be important contributors to the disparate patient responses to treatment that are often observed during disease therapy. Therefore, developing techniques or frameworks that enable rapid screening, detailed evaluation, and accurate prediction of drug/host-microbiome interactions is critically important in the modern era of microbiome research and precision medicine. Here we review the current status of meta-omics techniques, including integrative multi-omics approaches, for characterizing the microbiome's functionality in the context of health and disease. We also summarize and discuss new frameworks for applying meta-omics approaches and microbiome assays to study drug-microbiome interactions. Lastly, we discuss and exemplify strategies for implementing microbiome-based precision medicines using these meta-omics approaches and high throughput microbiome assays.

iMetaLab 1.0: a web platform for metaproteomics data analysis

Summary

The human gut microbiota, a complex, dynamic and biodiverse community, has been increasingly shown to influence many aspects of health and disease. Metaproteomic analysis has proven to be a powerful approach to study the functionality of the microbiota. However, the processing and analyses of metaproteomic mass spectrometry data remains a daunting task in metaproteomics data analysis. We developed iMetaLab, a web based platform to provide a user-friendly and comprehensive data analysis pipeline with a focus on lowering the technical barrier for metaproteomics data analysis.

Availability and implementation

iMetaLab is freely available through at http://imetalab.ca.

Supplementary information

Supplementary data are available at Bioinformatics online.

An in vitro model maintaining taxon-specific functional activities of the gut microbiome

In vitro gut microbiome models could provide timely and cost-efficient solutions to study microbiome responses to drugs. For this purpose, in vitro models that maintain the functional and compositional profiles of in vivo gut microbiomes would be extremely valuable. Here, we present a 96-deep well plate-based culturing model (MiPro) that maintains the functional and compositional profiles of individual gut microbiomes, as assessed by metaproteomics, while allowing a four-fold increase in viable bacteria counts. Comparison of taxon-specific functions between pre- and post-culture microbiomes shows a Pearson's correlation coefficient r of 0.83 ± 0.03. In addition, we show a high degree of correlation between gut microbiome responses to metformin in the MiPro model and those in mice fed a high-fat diet. We propose MiPro as an in vitro gut microbiome model for scalable investigation of drug-microbiome interactions such as during high-throughput drug screening.

Exploring the effects of operational mode and microbial interactions on bacterial community assembly in a one-stage partial-nitritation anammox reactor using integrated multi-omics

BACKGROUND

The metabolic capacities of anammox bacteria and associated microbial community interactions in partial-nitritation anammox (PNA) reactors have received considerable attention for their crucial roles in energy-efficient nitrogen removal from wastewater. However, a comprehensive understanding of how abiotic and biotic factors shape bacterial community assembly in PNA reactors is not well reported.

RESULTS

Here, we used integrated multi-omics (i.e., high-throughput 16S rRNA gene, metagenomic, metatranscriptomic, and metaproteomic sequencing) to reveal how abiotic and biotic factors shape the bacterial community assembly in a lab-scale one-stage PNA reactor treating synthetic wastewater. Analysis results of amplicon sequences (16S rRNA gene) from a time-series revealed distinct relative abundance patterns of the key autotrophic bacteria, i.e., anammox bacteria and ammonia-oxidizing bacteria (AOB), and the associated heterotrophic populations in the seed sludge and the sludge at the new stable state after deterioration. Using shotgun metagenomic sequences of anammox sludge, we recovered 58 metagenome-assembled genomes (MAGs), including 3 MAGs of anammox bacteria and 3 MAGs of AOB. The integrated metagenomic, metatranscriptomic, and metaproteomic data revealed that nitrogen metabolism is the most active process in the studied PNA reactor. The abundant heterotrophs contribute to the reduction of nitrate to nitrite/ammonium for autotrophic bacteria (anammox bacteria and AOB). Genomic and transcriptomic data revealed that the preference for electron donors of the dominant heterotrophs in different bacterial assemblages (seed and new stable state) varied along with the shift in anammox bacteria that have different metabolic features in terms of EPS composition. Notably, the most abundant heterotrophic bacteria in the reactor were more auxotrophic than the less abundant heterotrophs, regarding the syntheses of amino acids and vitamins. In addition, one of the abundant bacteria observed in the bacterial community exhibited highly transcribed secretion systems (type VI).

CONCLUSIONS

These findings provide the first insight that the bacterial communities in the PNA reactor are defined by not only abiotic factors (operating mode) but also metabolic interactions, such as nitrogen metabolism, exchange of electron donors, and auxotrophies.

Metaproteomic and Metabolomic Approaches for Characterizing the Gut Microbiome

The gut microbiome has been shown to play a significant role in human healthy and diseased states. The dynamic signaling that occurs between the host and microbiome is critical for the maintenance of host homeostasis. Analyzing the human microbiome with metaproteomics, metabolomics, and integrative multi-omics analyses can provide significant information on markers for healthy and diseased states, allowing for the eventual creation of microbiome-targeted treatments for diseases associated with dysbiosis. Metaproteomics enables functional activity information to be gained from the microbiome samples, while metabolomics provides insight into the overall metabolic states affecting/representing the host-microbiome interactions. Combining these functional -omic platforms together with microbiome composition profiling allows for a holistic overview on the functional and metabolic state of the microbiome and its influence on human health. Here the benefits of metaproteomics, metabolomics, and the integrative multi-omic approaches to investigating the gut microbiome in the context of human health and diseases are reviewed.