Biology subjects

Figeys, D.

Publications and source records attributed to Figeys, D..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

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

Our gut microbiome functions like an organ, having its own set of functions and roles which can be modulated by various types of xenobiotic and biotic components. High-throughput screening approaches that are established based on in vitro or ex vivo cell, tissue or organ models greatly accelerate drug discovery and our understanding of biological and pathological processes within these systems. There was a lack of a high-throughput compatible functional screening approach of the gut microbiome until we recently developed the RapidAIM (Rapid Assay of Individual Microbiome). RapidAIM combines an optimized culturing model, which maintains the taxonomic and functional profiles of the human gut microbiome in vitro, and a high-throughput metaproteomics workflow to gain deep functional insights into microbiome responses. This protocol describes the most recently optimized 2.0 version of RapidAIM, consisting of extensive details on stool sample collection, biobanking, in vitro culturing and stimulation, microbiome sample processing, and metaproteomics measurement and data analysis. To demonstrate the typical outcome of the protocol, we show an example of using RapidAIM 2.0 to evaluate the effect of prebiotic kestose on ex vivo individual human gut microbiomes biobanked with five different workflows; we also show that kestose had consistent functional effects across individuals and can be used as positive control in the assay.

microbiology↗

bioRxiv2022

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 increased cost due to the use of labeling reagents. In addition, current TMT labeling workflows involve repeated small volume pipetting of reagents in volatile organic 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 g dry TMT per channel effectively labels 6-12 g peptides, yielding efficient TMT labeling efficiency ([~]99%) in both microbiome and mammalian cell line samples. This streamlined workflow decreases reagent loss and reduces inter-sample variations. 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 streamlined and robust quantitative proteomics and metaproteomics in high throughput applications.

systems biology↗

bioRxiv2022

Alterations in neural stem cell quiescence and activation in the 3xTG-AD model of Alzheimers Disease

Alzheimers Disease (AD) is the most common form of dementia with progressive cognitive deficits and mood disorders (Knopman et al., 2021). Recent studies have associated AD pathology with the impairment of adult neurogenesis, as indicated by impaired neural stem cell (NSCs) homeostasis (Bond et al., 2015). Recent work has further associated AD progression with a decline in the number and maturation of adult-born neurons in the SGZ, distinct from typical age-related decline (Moreno-Jimenez et al., 2019). In 3xTG-AD mice, a well-established mouse model of AD, our and other groups have demonstrated impairments to NSC pool and neural progenitor proliferation, as well as adult-born neurons, before the onset of A{beta} plaques and NFTs (Hamilton et al., 2010, 2015; Rodriguez et al., 2008, 2009). However, the regulatory mechanisms underlying the functional impairment of adult NSCs remain to be resolved. Here, we employ single-cell RNA-Seq to establish population-specific defects in the 3xTG-AD mouse model during adult SGZ neurogenesis. Relative to control mice, we observe a dramatic AD-induced decrease in the primed and activated NSC population, which results in a progressive loss of cells committed to neurogenesis. Transcriptome measurements suggest that 3xTG-AD NSCs and their progeny represent enhanced ribosomal and mitochondrial biogenesis, and disturbed Notch signaling pathway. RNA velocity analysis reveals reduced NSC activation as evidenced by a large fraction of Ascl1-postive cells, instead of entering cell cycle, returning to the primed and quiescent state. This is further supported by reduced numbers of Lpar1-expressing cells, a marker of neural progenitor cells, in the SGZ. Our work explores, at a stage-specific resolution, changes in the regulatory networks guiding adult neurogenesis, and identifies niche disturbances in the regulation of NSC quiescence and activation. These NSC deficits underlying impaired neurogenesis identified in AD mice, may be key contributors underlying the compromised hippocampal function in AD.

neuroscience↗

bioRxiv2022

Comprehensive assessment of functional effects of commonly used sweeteners on ex vivo human gut microbiome

The gut microbiome composition and function are associated with health and diseases. Sweeteners are widely used food additives, although many studies using animal models have linked sweetener consumption to gut microbial changes and health issues. Whether 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 sweeteners, using an approach combining high-throughput ex vivo microbiome culturing and metaproteomics to quantify functional changes in different taxa. Hierarchical clustering based on metaproteomic responses of individual microbiomes resulted in two clusters. The first cluster was composed of non-caloric artificial sweeteners (NAS) and two sugar alcohols with shorter carbon backbones (4-5 carbon atoms), and the second cluster was composed of sugar alcohols with longer carbon backbones. The metaproteomic functional responses of the second cluster were similar to the prebiotic fructooligosaccharides and kestose, indicating that these sugar alcohol-type sweeteners have potential prebiotic functions. This study provides a comprehensive evaluation of the direct effects of commonly used sweeteners on the functions of the human gut microbiome using a functional metaproteomics approach, improving our understanding of the roles of sweeteners on microbiome-associated human health and disease issues.

microbiology↗

bioRxiv2021

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{degrees}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.

microbiology↗

bioRxiv2021

Revealing Protein-Level Functional Redundancy in the Human Gut Microbiome using Ultra-deep Metaproteomics

Functional redundancy is a key property of ecosystems and represents the fact that phylogenetically unrelated taxa can play similar functional roles within an ecosystem. The redundancy of potential functions of human microbiome has been recently quantified using metagenomics data. Yet, the redundancy of functions which are actually expressed within the human microbiome remains largely unexplored. Here, we quantify the protein-level functional redundancy in the human gut microbiome using metaproteomics and network approaches. In particular, our ultra-deep metaproteomics approach revealed high protein-level functional redundancy and high nestedness in proteomic content networks - bipartite graphs that connect taxa with their expressed functions. We further examined multiple metaproteomics datasets and showed that various environmental factors, including individuality, biogeography, xenobiotics, and disease, significantly altered the protein-level functional redundancy. Finally, by projecting the bipartite proteomic content networks into unipartite weighted genus networks, functional hub genera across individual microbiomes were discovered, suggesting that there may be a universal principle of functional organization in microbiome assembly. HighlightsO_LIUltra-deep metaproteomics reveals high protein-level functional redundancy in the human gut microbiome C_LIO_LIWithin-sample proteomic content networks display universal topology C_LIO_LIVarious environmental factors influence the redundancy of expressed functions C_LIO_LIFunctional hub genera are present across different datasets C_LI

systems biology↗

bioRxiv2021

Examining the effects of an anti-Salmonella bacteriophage preparation, BAFASAL, on ex vivo human gut microbiome composition and function using a multi-omics approach

Salmonella infections (salmonellosis) pose serious health risks to humans, usually via contamination in our food chain. This foodborne pathogen causes major food losses and human illnesses that result in significant economic impacts. Pathogens such as Salmonella have traditionally been kept at bay through the use of antibiotics, but antibiotic overuse within the food industry has led to the development of numerous multidrug-resistant bacterial strains. Thus, governments are now restricting antibiotic use, forcing the industry to search for alternatives to secure safe food chains. Bacteriophages, viruses that infect and kill bacteria, are currently being investigated and used as replacement treatments and prophylactics due to their specificity and efficacy. They are generally regarded as safe alternatives to antibiotics as they are natural components of the ecosystem. One example is BAFASEL, a commercial bacteriophage mixture that specifically targets Salmonella and is currently approved for use in poultry farming. However, when specifically used in the industry they can also make their way into humans through our food chain or exposure as is the case for antibiotics. In particular, agricultural workers could be repeatedly exposed to bacteriophages supplemented in animal feeds. To the best of our knowledge, no studies have investigated the effects of such exposure to bacteriophages on the human gut microbiome. In this study, we used a novel in vitro assay called RapidAIM to investigate BAFASALs potential impact on five individual human gut microbiomes. Multi-omics analyses, including 16S rRNA gene sequencing and metaproteomic, revealed that ex vivo human gut microbiota composition and function were unaffected by BAFASAL treatment providing an additional measure for its safety. Due to the critical role of the gut microbiome in human health and the known role of bacteriophages in regulation of microbiome composition and function, we suggest assaying the impact of bacteriophage-cocktails on the human gut microbiome as a part of their safety assessment. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

microbiology↗

bioRxiv2021

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 used mass spectrometry-based glycomic approaches to examine the N-glycans that were associated with the intestinal mucosal-luminal interface microbiota cells of treatment-naive pediatric UC or control patients. We observed abundant paucimannosidic and other truncated 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. This study indicates that intestinal N-glycans may be used as novel UC biomarker candidates and the aberrant metabolism of glycans by gut microbiota may be involved in the pathogenesis of UC in children.

systems biology↗

bioRxiv2021

Retention Time Standardization and Registration (RTStaR): An algorithm that matches corresponding and identifies unique species in nanoliquid chromatography-nanoelectrospray ionization-mass spectrometry lipidomic datasets

Bioinformatic tools capable of registering, rapidly and reproducibly, large numbers of nanoliquid chromatography-nanoelectrospray ionization-tandem mass spectrometry (nLC-nESI-MS/MS) lipidomic datasets are lacking. We provide here a freely available Retention Time Standardization and Registration (RTStaR) algorithm that aligns nLC-nESI-MS/MS spectra within a single dataset and compares these aligned retention times across multiple datasets. This two-step calibration matches corresponding and identifies unique lipid species in different lipidomes from different matrices and organisms. RTStaR was developed using a population-based study of 1001 human serum samples composed of 71 distinct glycerophosphocholine metabolites comprising a total of 68,572 analytes. Platform and matrix independence were validated using different MS instruments, nLC methodologies, and mammalian lipidomes. The complete algorithm is packaged in two modular ExcelTM workbook templates for easy implementation. RTStaR is freely available from the India Taylor Lipidomics Research Platform http://www.neurolipidomics.ca/rtstar/rtstar.html. Technical support is provided through ldomic@uottawa.ca

bioinformatics↗

bioRxiv2021

MetaProClust-MS1: A tool for clustering metaproteomes using rapid MS1 profiling

Metaproteomics is used to explore the composition, dynamics and function of microbial communities. How-ever, acquiring data by tandem mass spectrometry is time consuming and resource intensive. To mediate this challenge, we present MetaProClust-MS1, a computational framework for microbiome screening developed to reduce the time required for data acquisition by mass spectrometry. In this proof-of-concept study, we tested MetaProClust-MS1 on data acquired using short 15 minute MS1-only mass spectrometry gradients and compared the results to those produced using data acquired by a traditional tandem mass spectrometry approach. MetaProClust-MS1 identified robust microbiome shifts caused by xenobiotics in both datasets. Cluster topologies were also significantly correlated. We demonstrate that MetaProClust-MS1 is able to rapidly screen microbiomes using only short MS1 profiles. This approach can be used to prioritize samples for deep metaproteomic analysis and will be especially useful in large-scale metaproteomic screens or in clinical settings where rapid results are required.

bioinformatics↗

bioRxiv2020

Exploring the microbiome-wide lysine acetylation, succinylation and propionylation in human gut microbiota

BackgroundLysine acylations are important post-translational modifications that are present in both eukaryotes and prokaryotes, regulating 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. ResultsWe show that 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 unrestricted database search confidently identified >60,000 acetylated, and ~20,000 propionylated and succinylated gut microbial peptides. 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. ConclusionThis study provides an analytical framework, consisting of a serial immunoaffinity enrichment and an open database search strategy, for the study of lysine acylations in microbiome, which enables functional microbiome studies at the post-translational level.

microbiology↗

bioRxiv2020

MealTime-MS: A Machine Learning-Guided Real-Time Mass SpectrometryAnalysis for Protein Identification and Efficient DynamicExclusion

Mass spectrometry-based proteomics technologies are the 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 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.

bioinformatics↗

bioRxiv2020

Studying the dynamics of the gut microbiota using metabolically stable isotopic labeling and metaproteomics.

BackgroundThe 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 and 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 gut microbiome functional dynamics. ResultsFrom the stool sample of five mice that were fed with 15N hydrolysate from Ralstonia eutropha, we identified 15,297 non-redundant unlabeled peptides of which 10,839 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). ConclusionsOur study helps unravel the complex dynamics of protein synthesis and bacterial dynamics in the mouse microbiome. AvailabilityMetaProfiler and the bioinformatic pipeline are available at https://github.com/psmyth94/MetaProfiler.git.

microbiology↗

bioRxiv2020

Metaproteomic responses of in vitro gut microbiomes to resistant starches: the role of resistant starch type and inter-individual variations

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 individuals microbiota. In this study, we used in vitro culture and metaproteomic methods to explore the consistency and variations in individual microbiomes functional responses to three types of RS - RS2(Hi Maize 260), RS3(Novelose 330) and RS4(Fibersym RW). Results showed that RS2 and RS3 significantly altered the levels of protein expression 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; in contrast, the downstream butyrate producing pathway response varied. Our study confirm that different types of RS have markedly variable functional effects on the human gut microbiome, and also found considerable inter-individual differences in microbiome pathway responses.

microbiology↗

bioRxiv2020

Growth phase-dependent responses of an in vitro gut microbiome to metformin

In vitro gut microbiota models are often used to study drug-microbiome interaction. Similar to culturing individual microbial strains, the biomass accumulation of in vitro gut microbiota follows a logistic growth curve. Current studies on in vitro gut microbiome responses introduce drug stimulation during different growth stages, e.g. lag phase or stationary phase. However, in vitro gut microbiota in different growth phases may respond differently to same stimuli. Therefore, in this study, we used a 96-deep well plate-based culturing model (MiPro) to culture the human gut microbiota. Metformin, as the stimulus, was added at the lag, log and stationary phases of growth. Microbiome samples were collected at different time points for optical density and metaproteomic functional analysis. Results show that in vitro gut microbiota responded differently to metformin added during different growth phases, in terms of the growth curve, alterations of taxonomic and functional compositions. The addition of drugs at log phase leads to the greatest decline of bacterial growth. Metaproteomic analysis suggested that the strength of the metformin effect on the gut microbiome functional profile was ranked as lag phase > log phase > stationary phase. Our results showed that metformin added at lag phase resulted in a significantly reduced abundance of the Clostridiales order as well as an increased abundance of the Bacteroides genus, which was different from stimulation during the rest of the growth phase. Metformin also resulted 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.

microbiology↗

bioRxiv2019

pepFunk, a tool for peptide-centric functional analysis in metaproteomic human gut microbiome studies

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. To combat this challenge, we developed a peptide-centric metaproteomic workflow focused on the analysis of human gut microbiome samples. Our workflow includes a curated peptide database annotated with KEGG terms and a pathway enrichment analysis adapted for peptide level data. Analysis using our peptide-centric workflow is fast and identifies more enriched KEGG pathways than protein-centric analysis. Our workflow is open source and available as a web application or source code to be run locally.

bioinformatics↗

bioRxiv2019

A Chemoenzymatic Method for Glycoproteomic N-glycan Type Quantitation

Glycosylation is one of the most important post-translational modifications in biological systems. Current glycoproteome methods mainly focus on qualitative identification of glycosylation sites or intact glycopeptides. However, the systematic quantitation of glycoproteins has remained largely unexplored. Here, we developed a chemoenzymatic method to quantitatively investigate N-glycoproteome based on the N-glycan types. Taking advantage of the specificity of different endoglycosidases and isotope dimethyl labeling, six N-glycan types of structures linked on each glycopeptide, including high-mannose/hybrid, bi-antennary and tri-antennary with/without core fucose, were quantified. As a proof of principle, the glycoproteomic N-glycan type quantitative (glyco-TQ) method was first used to determine the N-glycan type composition of immunoglobulin G1 (IgG1) Fc fragment. Then we applied the method to analyze the glycan type profile of proteins in the breast cancer cell line MCF7, and quantitatively revealed the N-glycan type micro-heterogeneity at both the glycopeptide and glycoprotein levels. The novel quantitative strategy to evaluate the relative intensity of the six states of N-glycan type glycosylation on each site provides a new avenue to investigate function of glycoproteins in broad areas, such as cancer biomarker research, pharmaceuticals characterization and anti-glycan vaccine development.

systems biology↗

bioRxiv2019

Deep characterization of the protein lysine acetylation in human gut microbiome and its alterations in patients with Crohn’s disease

Metagenomic and metaproteomic approaches have been used to study the composition and functions of the microbiota. However, no studies have examined post-translational modifications (PTM) on human microbiome proteins at the metaproteome level, and it remains unknown whether the microbial PTM is altered or not in patient microbiome. Herein we used anti-acetyl-lysine (Kac) antibody enrichment strategy and mass spectrometry to characterize the protein lysine acetylation in human microbiome, which successfully identified 35,200 Kac peptides corresponding to 31,821 Kac sites from the microbial or host proteins in human gut microbiome samples. The gut microbial proteins exhibited Kac motifs that were distinct from those of human proteins. Functional analysis showed that microbial Kac proteins were significantly enriched in energy production and abundant in enzymes related to transferases and oxidoreductases. Applying to the analysis of pediatric Crohns disease (CD) patient microbiome identified 52 host and 136 microbial protein Kac sites that were differentially abundant in CD versus controls. Interestingly, most of the decreased Kac sites in CD were derived from Firmicutes and most of the increased sites were derived from Bacteroidetes. Forty-six out of the 52 differentially abundant human protein Kac sites were increased in CD patients, including those on calprotectin, lactotransferrin and immunoglobulins. Taken together, this study provides an efficient approach to study the lysine acetylation in microbiome and revealed taxon-specific alterations in the lysine acetylome as well as changes in host protein acetylation levels in intestinal samples during the on-set of disease in CD patients.

systems biology↗