Biology subjects

Mayne, J.

Publications and source records attributed to Mayne, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Dissecting functional dynamics of fecal-derived in vitro stable microbial communities with metaproteomics

Fecal-derived in vitro microbial communities represent promising models for investigating gut microbiome function and facilitating translational applications. However, the factors governing community establishment and the underlying mechanisms remain incompletely understood. We employed large-scale quantitative metaproteomics to investigate the functional and community dynamics of human fecal microbiomes cultured in three media over 25 serial passages. Our results demonstrated that both culture medium and donor-specific microbiome characteristics significantly influence community establishment. Taxon-specific functional analyses revealed nutrient availability in the medium and the microbial stress responses as key determinants of in vitro community establishment. Notably, the metabolism of mucin glycans in RapidAIM medium contributed to the maintenance of Bacteroidaceae species that were poorly supported in other media, resulting in an in vitro community that most closely resembled the uncultured fecal inoculum. Overall, these findings provide mechanistic insights into in vitro gut microbial community establishment, supporting further optimization and application of fecal-derived in vitro microbiome models.

microbiology↗

bioRxiv2026

Donor Age and Oligosaccharide Structure Jointly Shape the Gut Microbiome Function

Non-digestible oligosaccharides are widely used as prebiotics, yet structurally related glycans can elicit distinct gut microbiome responses. Here, we combined controlled ex vivo fermentation, deep DIA metaproteomics, and targeted metabolomics to determine how oligosaccharide structure and donor age shape microbiome function. Stool microbiomes from 18 healthy donors across three age groups were cultured with seven structurally related oligosaccharides from two glycan families, fructo-oligosaccharides (FOS) and galactosyl-sucrose derivatives (GSD). We found that oligosaccharide structure organized a functional response landscape rather than simply separating substrates into broad prebiotic classes. Structurally related glycans produced more similar response profiles overall, yet closely related FOS substrates remained functionally distinguishable, indicating that subtle structural differences were resolved by the microbiome as graded functional changes. These structure-responsive functions were further associated with producer-level reorganization relative to baseline, while targeted enzyme-level analyses indicated that substrate-specific CAZyme responses could also reflect altered functional investment within shared producer backgrounds. Despite these substrate-specific entry processes, network analysis revealed convergence onto shared downstream physiological states enriched for translation, amino-acid biosynthesis, secretion/export, and chemotaxis-related pathways. Across treatments, major short-chain fatty acids increased while mucin glycan degradation-associated markers decreased, suggesting coordinated shifts toward saccharolytic metabolism and reduced host-glycan foraging. Tryptophan-associated metabolism was also consistently linked to primary fructan processing, accompanied by higher extracellular tryptophan availability. Donor age modified selected microbial functional axes and enzyme-metabolite coupling relationships rather than the overall direction of core fermentation outputs. In particular, oligosaccharides attenuated an Methanobrevibacter smithii (M. smithii) and M00567 methanogenesis-related signature in microbiomes from older adults and altered age-dependent relationships between butyrate-pathway enzymes and extracellular butyrate levels. Together, these findings show that oligosaccharide structure determines how gut microbial communities organize carbohydrate processing and downstream functional states, while donor age reshapes the taxonomic and metabolic context of these responses. This work provides a mechanistic framework for structure-aware and age-aware precision prebiotic design.

microbiology↗

bioRxiv2026

Wheat mutants lacking Starch Synthase 1 have altered starch composition and cell wall content

Starch Synthase 1 (SS1) participates in the synthesis of amylopectin. To determine its role in hexaploid bread wheat, we selected and combined TILLING mutations for each homoeologue to create two independent SS1-deficient lines. The lines, which have different combinations of ss1 mutations, both lacked SS1 protein. Both lines exhibited mild but significant changes to starch phenotype, including fewer short amylopectin chains, a slight increase in B-type starch granules and a modest increase in amylose content. Lack of SS1 also led to changes in the thermal properties of starch measured by differential scanning calorimetry including reduced enthalpy, and increased gelatinization temperature. Despite the changes to starch properties, the starch contents of the mutant lines compared to wild types were within the normal range, as were grain weight and protein content. However, the concentration of total- and water-extractable arabinoxylan, and MLG, were increased in white flour compared to wild-type controls. HighlightLack of SS1 led to changes in starch molecular structure and thermal behavior. Starch content and grain weight were normal but cell wall polysaccharides in white flour were increased.

plant biology↗

bioRxiv2025

Billion-Scale Deciphering of Human Gene Regulatory Grammar

Predicting how DNA sequence specifies gene expression remains a core challenge across regulatory genomics. Most predictive assays and models depend on native genomic DNA, constraining the full biochemical engineering space for assessing and designing new sequences. Here, we address this gap with a scalable experimental-computational platform that rapidly generates million-scale sequence-to-expression datasets that directly link degenerate sequences to their function in human cells. We built degenerate libraries of 200-bp promoter cassettes and performed pooled stable integration of up to 1012 unique constructs, enabling the curation of million-scale sequence-to-expression datasets by fluorescently sorting billions of human cells. Biophysical modeling of transcription-factor occupancy on the data using position weight matrices reveals a broad spectrum of correlations between factor abundance and expression levels, with some co-abundances reaching Pearsons r {approx} 0.99, consistent with cooperative and probabilistic regulation. Leveraging the dataset, we trained sequence-to-expression deep learning models that predict held-out expression with Pearson r {approx} 0.4, converge on shared sequence determinants, and agree strongly with each other (Pearsons r = 0.93), indicating reproducible sequence-expression relationships. Finally, with minimal retraining the models generalize to an independently generated dataset collected under distinct sorting conditions, transferring sequence rules across contexts. Our platform enables repeated, rapid studies and supports deeper mechanistic insight while providing baseline models for forward design of human regulatory elements, advancing prediction beyond genomic-DNA-anchored methods.

synthetic biology↗

bioRxiv2025

Microbiome-Dependent Functional Responses to Structurally Distinct Oligosaccharides Revealed by Metaproteomics

Dietary oligosaccharides are prebiotics that fuel gut microbes, but individual microbiomes may respond differently depending on oligosaccharide structures as well as microbiome composition and function. The extent to which specific gut microbial communities exhibit personalized functional responses to distinct oligosaccharides remains underexplored. We applied a standardized ex vivo microbiome culture, called RapidAIM, coupled with metaproteomics to examine how six structurally diverse oligosaccharides affect the gut microbiota functional response. Our study shows that while human gut microbiomes share some commonalities in utilizing oligosaccharides (e.g. prioritizing dietary fibers over mucin), the fine-scale metabolic and taxonomic responses are highly individualized. Such findings underscore the importance of considering personal microbiome profiles when predicting the outcome of prebiotic interventions. In a broader context, our metaproteomic approach provides a framework for identifying optimal prebiotic choices tailored to individual microbiomes. Ultimately, understanding these personalized responses could inform precision nutrition strategies.

microbiology↗

bioRxiv2025

Systematic Metaproteomics Mapping Reveals Functional and Ecological Landscapes of Human Gut Microbiota Responses to Therapeutic Drugs

Therapeutic compounds exert impacts on gut microbiota; however, how they affect the community functional ecology, especially as reflected at the protein level, remains largely unexplored. In this study, we systematically map metaproteomic responses of ex vivo human gut microbiota to 312 compounds, generating 4.6 million microbial protein responses, available as an interactive resource (https://shiny.imetalab.ca/MPR_Viz/). Protein-level analyses identify significant metaproteomic shifts induced by 47 compounds, with neuropharmaceuticals as the sole drug class significantly enriched among these hits. Further analyses on the community level reveal a tri-stability pattern in microbial composition and the emergence of three distinct functional states, based on a functional beta-diversity metric. Notably, neuropharmaceuticals cause particularly strong effects on the microbiomes, lowering the proteome-level functional redundancy and raising the level of antimicrobial resistance proteins, ultimately pushing the microbiome into an alternative functional state. Preliminary validation suggests that enhancing functional redundancy may contribute to maintaining microbiota resilience against neuropharmaceutical-induced antimicrobial resistance. Overall, this work establishes a comprehensive view of how drugs influence gut microbiome function and ecology at the protein level, proposes a landscape-based framework for interpreting community resilience, and highlights the need to consider protein-level and ecological responses in the evaluation of therapeutic interventions.

microbiology↗

bioRxiv2024

MetaLab Platform Enables Comprehensive DDA and DIA Metaproteomics Analysis

Metaproteomics studies the collective protein composition of complex microbial communities, providing insights into microbial roles in various environments. Despite its importance, metaproteomic data analysis is challenging due to the datas large and heterogeneous nature. While Data-Independent Acquisition (DIA) mode enhances proteomics sensitivity, it traditionally requires Data-Dependent Acquisition (DDA) results to build the library for peptide identification. This paper introduces an updated version of MetaLab, a software solution that streamlines metaproteomic analysis by supporting both DDA and DIA modes across various mass spectrometry (MS) platforms, including Orbitrap and timsTOF. MetaLabs key feature is its ability to perform DIA analysis without DDA results, allowing more experimental flexibility. It incorporates a deep learning strategy to train a neural network model, enhancing the accuracy and coverage of DIA results. Evaluations using diverse datasets demonstrate MetaLabs robust performance in accuracy and sensitivity. Benchmarks from large-scale human gut microbiome studies show that MetaLab increases peptide identification by 2.7 times compared to conventional methods. MetaLab is a versatile tool that facilitates comprehensive and flexible metaproteomic data analysis, aiding researchers in exploring microbial communities functionality and dynamics.

bioinformatics↗

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

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

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↗

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

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

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↗