Biology subjects

Ning, Z.

Publications and source records attributed to Ning, Z..

At least 19 recordsLinked to original sources

bioRxiv2026

A spatial and single-cell transcriptomic atlas of the embryonic synovial joint and its explant model

Synovial joint formation requires the coordinated differentiation of multiple cell types while balancing opposing migratory cues that recruit joint progenitors and exclude other populations. More specifically, a subset of limb bud mesenchyme is recruited into the interzone while neighboring chondrocytes and endothelial cells are excluded. Existing single-cell references sample this process sparsely, without position, or without the surrounding mesenchyme. Here, we present an atlas of the mouse hindlimb from E11.5 to E15.5 that pairs 228,703 single-cell transcriptomes with 47 spatial transcriptomic sections, annotates 56 cell types by their location, and extends the same profiling to limb explant culture. Explants preserve the lineages and axial patterning of the limb for three days, with delayed chondrocyte hypertrophy. Using the atlas, we found that Sema3c is co-expressed with Sox9 and Gdf5 during condensation and is required for chondrogenesis and joint formation in culture; that interzone cells carry a chondrogenic signature early and a tenogenic signature late; and that a core interzone signature includes eleven previously unreported markers, one of which, Igfbp5, is required for knee formation in explants.

developmental biology↗

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

Dissociating the intensity and phase origins of sleepiness through a threshold-distance model of sleep-wake dynamics

Sleepiness is a leading proximate cause of drowsy-driving fatalities, medical errors and industrial accidents, yet it has resisted mechanistic prediction; although it arises from well-characterized sleep-wake physiology, it is experienced as a subjective state and has lacked a quantitative link to the underlying dynamics. We previously showed that subjective sleepiness maps linearly, with a protocol-invariant form, onto the signed distance H - H+ between the homeostatic pressure H and the circadian-modulated sleep-onset threshold H+. This single quantity predicts sleepiness accurately but is mechanistically ambiguous: the same value can arise either because H sits far from the boundary or because the threshold H+(t) has shifted with circadian phase, and these two origins call for entirely different interpretations and interventions. Here we resolve this ambiguity by decomposing H - H+ into two mechanistically separable axes-intensity and phase. The intensity axis is the time-averaged margin [<] H - H+[>], set by how far, on average, H sits from the sleep boundary: slowed homeostatic accumulation accounts for the paradoxically blunted sleepiness of older adults, and pharmacological suppression of H accounts for the dose-dependent alerting effect of caffeine. The phase axis is set by the circadian modulation of H+(t): under a forced-desynchrony protocol, in which the pacemaker free-runs and the homeostatic and circadian processes are experimentally decoupled, sleepiness tracks the circadian profile of H+(t) across all phases while the intensity mapping itself remains unchanged-a clean dissociation of the two axes. By resolving felt sleepiness into these two physiological degrees of freedom, this framework renders previously isolated phenomena-aging, caffeine and circadian misalignment-commensurable within a single theory and provides a physiologically interpretable basis for prospective fatigue-risk prediction. Author summaryWhy people feel sleepy after sleep loss, or at particular times of day, remains difficult to predict from physiology alone. Sleep and wake are shaped by two interacting processes: a daily circadian rhythm and a homeostatic pressure that builds during wakefulness. In earlier work, we linked subjective sleepiness ratings to a simple geometric quantity-how close sleep pressure sits to a circadian sleep-onset boundary. That link is useful, but ambiguous: the same distance can arise either because pressure itself has changed, or because the boundary has moved with circadian phase. Here we use a computational model of the sleep-wake switch, extended to include the wake-stabilizing orexin system, to separate these contributions into an intensity axis and a phase axis. We find that aging and caffeine mainly alter how large the average distance to the boundary becomes, whereas forced desynchrony mainly alters how that distance varies across circadian phase. This dissociation offers a compact way to interpret several otherwise separate observations within one quantitative picture, and a step toward more physiologically grounded fatigue-risk assessment.

neuroscience↗

bioRxiv2026

Circadian-Modulated Thresholds for Sleep Patterns in Aging and Narcolepsy

In the two-process model of sleep-wake regulation, circadian-modulated thresholds time every sleep onset and awakening, yet they remain free parameters rather than quantities derived from neuronal dynamics. This limitation leaves the framework unable to predict how sleep patterns change when neuromodulatory drive is altered, as in aging and narcolepsy. Here we close that gap by deriving closed-form, circadian-modulated threshold expressions from the Phillips-Robinson model with explicit orexinergic excitation of the wake-promoting population. Within this single threshold geometry, aging and narcolepsy appear as opposite deformations along the orexinergic axis: age-related hyperexcitability of orexin neurons elevates the sleep-onset boundary and creates a fragility regime in which minor nocturnal disturbances trigger premature awakenings, whereas orexin loss depresses the same boundary toward the wake-onset threshold and produces the rapid state fragmentation of narcolepsy. Concurrently, reduced circadian amplitude compresses the inter-threshold corridor, advancing sleep onset and shortening sleep duration. These results convert the classical two-process thresholds from descriptive conveniences into mechanistic organizers of sleep-wake dynamics across healthy aging and orexin deficiency. Author summaryThe classical two-process model of sleep relies on a pair of switching thresholds that have been imposed by hand rather than derived from the neurons that actually stabilize sleep and wakefulness. Here we remove this limitation: starting from a biophysical mean-field model of the sleep- and wake-promoting populations, and adding the orexin system that stabilizes arousal, we derive the sleep-onset and awakening thresholds analytically from the bifurcation geometry of the underlying dynamical system. These closed-form thresholds depend explicitly on circadian phase, homeostatic state, and orexinergic tone, revealing that aging and narcolepsy are opposite deformations of a single threshold corridor along one orexinergic axis. In aging, orexin hyperexcitability raises the sleep-onset barrier past a sharp "arousal fragility boundary," beyond which a minor disturbance triggers irreversible awakening; in narcolepsy, orexin loss collapses the same barrier and fragments sleep while paradoxically preserving total sleep time. We further find, contrary to common assumption, that orexin sustains wakefulness chiefly by raising the barrier to falling asleep rather than by resisting awakening. This work turns phenomenological sleep thresholds into physics-derived organizers of behavior, providing a mechanistic bridge from neuronal circuitry to whole-organism sleep dynamics.

neuroscience↗

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

MetaUmbra: Statistically Controlled Genome-Level Presence Inference from Metaproteomic Peptides

Taxonomic interpretation of metaproteomic peptides remains difficult because many peptide sequences are present in proteins from different organisms, reducing taxonomic specificity. Current peptide-centric workflows can report taxonomic summaries or taxon level confidence scores, but they do not provide formal statistical evidence that a taxon is present in the microbiome. Here we present MetaUmbra, a tool that derives genome-level statistical significance values from identified peptides. MetaUmbra builds theoretical peptide lists by in silico digestion of the taxon specific proteins and matches observed peptides against these references. It then combines a conservative significance estimate from unique peptides with a Monte Carlo based p-value for shared peptide evidence estimated under an empirical null model. In the defined community benchmark SIHUMIx, MetaUmbra identified the expected genomes without introducing false-positive genomes after embedding the SIHUMIx genomes in a large gut reference background. In the single strain benchmark Mix24X, all expected genomes were identified with the best statistical significances even after near neighbor and full background expansion. In a hamster gut genome panel, MetaUmbra further preserved an interpretable ranking of candidate genomes in a dense real-data setting. Together, these results show that MetaUmbra can statistically identify the presence of specific microbes in a complex microbiome while maintaining low false-positive calls. MetaUmbra therefore provides a practical framework for converting peptide evidence into genome-level statistical inference in metaproteomics.

bioinformatics↗

bioRxiv2026

MetaTree: an interactive web platform for hierarchical data visualization and multi-group comparison

BackgroundHierarchical quantitative profiles are widely used in microbiome studies and other domains. However, comparing multiple samples and experimental groups while preserving hierarchical structure remains challenging. Many existing workflows require extensive manual figure assembly or do not support aligned comparisons across conditions on a shared hierarchy. ResultsWe developed MetaTree, an open-source platform that runs in a web browser for interactive visualization and comparative analysis of hierarchical quantitative data. MetaTree anchors samples, groups, and contrasts between groups to a shared reference hierarchy, preserving one-to-one node correspondence so that the same clade is compared in the same position across views. In addition to visualization, MetaTree integrates statistical testing for comparisons between two groups with false discovery rate (FDR) control, enabling users to identify clades with consistent differences between conditions and interpret them in hierarchical context. MetaTree also provides user configurable controls for visual encoding, filtering thresholds, label density, and layout, allowing figures to be adapted to different datasets and reporting needs. The interface remains usable for large hierarchies through interactive navigation, adaptive label handling, and branch collapsing. ConclusionsMetaTree is an installation-free web platform (https://byemaxx.github.io/MetaTree) for topology-consistent visualization and comparison of hierarchical profiles, supporting coordinated multi-panel exploration and automated comparison matrices to enable rapid generation of publication-ready figures for microbiome and other hierarchical datasets.

bioinformatics↗

bioRxiv2025

Modeling Post-Gastrula Development via Bidirectional Pluripotent Stem Cells

The absence of stem cells capable of efficiently generating both trophoblast and epiblast lineages has hindered precise recapitulation of embryonic development. Through high-content chemical screening, we established an AL medium to generate mouse and human bidirectional pluripotent stem cells (BPSCs) characterized by concurrent OCT4/CDX2 expression. Mouse BPSCs demonstrated high plastic differentiation into trophoblast, epiblast and primitive endoderm lineages in vitro within 48 hours without exogenous induction factors and efficiently contributed to the embryo and extraembryonic tissues in vivo. Mechanistically, hyperactivation of the Wnt signaling pathway breaks the early lineage differentiation barrier by initiating a Lef1-dependent bypass. Remarkably, BPSCs can efficiently generated E8.5 embryoids that completed gastrulation and displayed advanced features such as brain development, a closed neural tube, a beating heart, somite formation, and primordial germ cells. These findings highlight BPSCs as a powerful tool for investigating early lineage specification and post-gastrulation embryonic development, with potential applications across multiple species.

developmental 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

Peptide abundance correlations in metaproteomics enhance taxonomic and functional analysis of the human gut microbiome

Mass spectrometry (MS)-based proteomics is widely used for quantitative protein profiling and has become a powerful tool for studying protein interactions. However, most current research focuses on single-species proteomics to study protein interactions. Protein interactions within more complex microbiomes, composed of 100s of bacterial species, remain largely unexplored. The human gut microbiome, closely linked to human health and disease, has become a key area of study using metaproteomics. Yet, due to the complexity of the microbiome, the interactions between gut microbes and their host remain largely unknown. In this study, we analyzed peptide abundance correlations within a metaproteomics dataset derived from in vitro cultured human gut microbiomes subjected to various drug treatments. Our analysis revealed that peptides from the same protein or taxon exhibited correlated abundance changes. By using t-SNE for visualization, we generated a peptide correlation map in which peptides from the same taxon formed distinct clusters. Furthermore, peptide abundance correlations enabled genome-level taxonomic assignments for a greater number of peptides. In single-species subsets of the dataset, peptide correlation networks constructed using taxon-based normalized peptide abundance (TNPA) linked peptides from functionally related proteins. These networks also provided insights into the potential functions of previously uncharacterized proteins. Altogether, our study demonstrates that analyzing peptide abundance correlations enhances both taxonomic and functional analyses in human gut metaproteomics research.

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

Metaproteomics reveals age-specific alterations of gut microbiome in hamsters with SARS-CoV-2 infection

The gut microbiomes pivotal role in health and disease is well-established. SARS-CoV-2 infection often causes gastrointestinal symptoms and is associated with changes of the microbiome in both human and animal studies. While hamsters serve as important animal models for coronavirus research, there exists a notable void in the functional characterization of their microbiomes with metaproteomics. In this study, we present a workflow for analyzing the hamster gut microbiome, including a metagenomics-derived hamster gut microbial protein database and a data-independent acquisition metaproteomics method. Using this workflow, we identified 32419 protein groups from the fecal microbiomes of young and old hamsters infected with SARS-CoV-2. We showed age-specific changes in the expressions of microbiome functions and host proteins associated with microbiomes, providing further functional insight into the dysbiosis and aberrant cross-talks between the microbiome and host in SARS-CoV-2 infection. Altogether this study established and demonstrated the capability of metaproteomics for the study of hamster microbiomes.

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↗

bioRxiv2024

PhyloFunc: Phylogeny-informed Functional Distance as a New Ecological Metric for Metaproteomic Data Analysis

BackgroundBeta-diversity is a fundamental ecological metric for exploring dissimilarities between microbial communities. On the functional dimension, metaproteomics data can be used to quantify beta-diversity to understand how microbial community functional profiles vary under different environmental conditions. Conventional approaches to metaproteomic functional beta-diversity often treat protein functions as independent features, ignoring the evolutionary relationships among microbial taxa from which different proteins originate. A more informative functional distance metric that incorporates evolutionary relatedness is needed to better understand microbiome functional dissimilarities. ResultsHere, we introduce PhyloFunc, a novel functional beta-diversity metric that incorporates microbiome phylogeny to inform on metaproteomic functional distance. Leveraging the phylogenetic framework of weighted UniFrac distance, PhyloFunc innovatively utilizes branch lengths to weigh between-sample functional distances for each taxon, rather than differences in taxonomic abundance as in weighted UniFrac. Proof-of-concept using a simulated toy dataset and a real dataset from mouse inoculated with a synthetic gut microbiome and fed different diets show that PhyloFunc successfully captured functional compensatory effects between phylogenetically related taxa. We further tested a third dataset of complex human gut microbiomes treated with five different drugs to compare PhyloFuncs performance with other traditional distance methods. PCoA and machine learning-based classification algorithms revealed higher sensitivity of PhyloFunc in microbiome responses to paracetamol. We provide PhyloFunc as an open-source Python package (available at https://pydigger.com/pypi/PhyloFunc), enabling efficient calculation of functional beta-diversity distances between a pair of samples or the generation of a distance matrix for all samples within a dataset. ConclusionsUnlike traditional approaches that consider metaproteomics features as independent and unrelated, PhyloFunc acknowledges the role of phylogenetic context in shaping the functional landscape in metaproteomes. In particular, we report that PhyloFunc accounts for the functional compensatory effect of taxonomically related species. Its effectiveness, ecological relevance, and enhanced sensitivity in distinguishing group variations are demonstrated through the specific applications presented in this study.

bioinformatics↗

bioRxiv2024

MetaX: A peptide centric metaproteomic data analysis platform using Operational Taxa-Functions (OTF)

Metaproteomics analyzes the functional dynamics of microbial communities by identifying peptides and mapping them to the most likely proteins and taxa. The challenge in this field lies in seamlessly integrating taxonomic and functional annotations to accurately represent the contributions of individual microbial taxa to functional diversity. We introduce MetaX, a comprehensive tool for analyzing taxa-function relationships in metaproteomics by mapping peptides to their lowest common ancestors and assigning functions based on proportional thresholds, ensuring accurate peptide-level mappings. Importantly, MetaX introduces the Operational Taxa-Functions (OTF), a new conceptual unit for exploring microbial roles and interactions within ecosystems. Additionally, MetaX extends traditional taxonomic classification by adding a genome level below the species level, enhancing the accuracy of function attribution to specific genomes. We demonstrated MetaX by reanalyzing metaproteomic data from gut microbiomes exposed to various sweeteners, achieving results similar to traditional protein analysis. Furthermore, using the peptide-centric approach and OTF, we observed that Parabacteroides distasonis significantly responds to certain sweeteners, highlighting its role in modifying specific metabolic functions. With its intuitive, user-friendly interface, MetaX facilitates detailed study of the complex interactions between microbial taxa and their functions in metaproteomics. It enhances our understanding of microbial roles in ecosystems and health.

bioinformatics↗

bioRxiv2024

MetaDIA: A Novel Database Reduction Strategy for DIA Human Gut Metaproteomics

BackgroundMicrobiomes, especially within the gut, are complex and may comprise hundreds of species. The identification of peptides in metaproteomics presents a significant challenge, as it involves matching peptides to mass spectra within an enormous search space for complex and unknown samples. This poses difficulties for both the accuracy and the speed of identification. Specifically, analysis of data-independent acquisition (DIA) datasets has relied on libraries constructed from prior data-dependent acquisition (DDA) results. This approach requires running the samples in DDA mode to construct a library from the identified results, which can then be used for the DIA data. However, this method is resource-intensive, consumes samples, and limits identification to peptides previously identified by DDA. These limitations restrict the application of DIA in metaproteomics research. ResultsWe introduced a novel strategy to reduce the search space by utilizing species abundance and functional abundance information from the microbiome to score each peptide and prioritize those most likely to be detected. Employing this strategy, we have developed and optimized a workflow called MetaDIA for analysis of microbiome DIA data, which operates independently of DDA assistance. Our method demonstrated strong consistency with the traditional DDA-based library approach at both protein and functional levels. ConclusionOur approach successfully created a smaller, yet sufficient database for DIA data search requirements in metaproteomics, showing high consistency with results from the conventional DDA-based library. We believe this method can facilitate the application of DIA in metaproteomics.

bioinformatics↗

bioRxiv2024

Assessing fecal metaproteomics workflow and small protein recovery using DDA and DIA PASEF mass spectrometry

AimThis study aims to evaluate the impact of experimental workflow on fecal metaproteomic observations, including the recovery of small and antimicrobial proteins often overlooked in metaproteomic studies. The overarching goal is to provide guidance for optimized metaproteomic experimental design, considering the emerging significance of the gut microbiome in human health, disease, and therapeutic interventions. MethodsMouse feces were utilized as the experimental model. Fecal sample pre-processing methods (differential centrifugation and non-differential centrifugation), protein digestion techniques (in-solution and filter-aided), data acquisition modes (data-dependent and data-independent, or DDA and DIA) when combined with parallel accumulation-serial fragmentation (PASEF), and different bioinformatic workflows were assessed. ResultsWe showed that, in DIA-PASEF metaproteomics, the library-free search using protein sequence database generated from DDA-PASEF data achieved better identifications than using the generated spectral library. Compared to DDA, DIA-PASEF identified more microbial peptides, quantified more proteins with less missing values, and recovered more small antimicrobial proteins. We didnt observe obvious impacts of protein digestion methods on both taxonomic and functional profiles. However, differential centrifugation decreased the recovery of small and antimicrobial proteins, biased the taxonomic observation with a marked over-estimation of Muribaculum species, and altered the measured functional compositions of metaproteome. ConclusionThis study underscores the critical impact of experimental choices on metaproteomic outcomes and sheds light on the potential biases introduced at different stages of the workflow. The comprehensive methodological comparisons serve as a valuable guide for researchers aiming to enhance the accuracy and completeness of metaproteomic analyses.

microbiology↗

bioRxiv2024

Multilevel proteomic profiling of colorectal adenocarcinoma cell differentiation to characterize an intestinal epithelial model

Emergent advancements on the intestinal microbiome for human health and disease treatment necessitates well-defined intestinal cellular models to study and rapidly assess host, microbiome, and drug interactions. This study characterized molecular alterations during Caco-2 cell differentiation, an epithelial intestinal model, using quantitative multi-omic approaches. We demonstrated that both spontaneous and medium-induced cellular differentiations displayed similar protein and pathway changes, including the down-regulation of proteins related to translation and proliferation, and up-regulation of proteins related to cell adhesion, molecule binding and metabolic pathways. Acetyl-proteomics revealed decreased histone acetylation and increased acetylation in proteins associated with mitochondria functions in differentiated cells. Butyrate-containing differentiation medium accelerates differentiation, with earlier up-regulation of proteins related to differentiation and host-microbiome interactions. These results emphasize the controlled progression of Caco-2 differentiation toward a specialized intestinal epithelial-like cell. This further enhances their characterization, establishing their suitability for facilitating the effective evaluation of risk and quality in microbiome-directed therapeutics.

systems biology↗