Biology subjects

Kleiner, M.

Publications and source records attributed to Kleiner, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Wild Luteibacter populations exhibit climate-associated divergence and distinct genomic strategies for osmotic stress tolerance

Soil bacteria play a crucial role in supporting ecosystem health, yet little is known about how wild populations adapt to abiotic stressors, like limited water availability. We used 186 Luteibacter isolates from maize roots grown in never-irrigated prairie soils collected from a steep precipitation gradient in Kansas, US to test whether climate history is associated with osmotic stress tolerance and genomic differentiation. In vitro, strains from semi-arid sites were more tolerant to osmotic-stress treatment than those from humid sites. Comparative genomics of a subset of 96 isolates identified four strongly biogeographically structured lineages and extensive accessory-genome diversity. Semi-arid climate-associated strains were enriched for genes involved in osmotic homeostasis, oxidative stress protection, motility, and type IV secretion. Humid climate-associated strains were enriched in environmental sensing, metabolic versatility, biofilm formation, iron acquisition, type VI secretion, and resource competition. GWAS identified 22 candidate genes associated with osmotic-stress tolerance, including those related to type IV pili, biofilm production, DNA repair, and phage. No candidates were shared between semi-arid and humid strains, suggesting distinct genetic mechanisms of osmotic tolerance. Predicted prophage composition was also geographically structured, although total prophage gene content did not predict osmotic-stress tolerance. Together, these results show that adaptation to long-term differences in water availability likely involves coordinated shifts in stress physiology, genome content, and ecological interactions in wild bacterial populations, providing insight into predicting microbial responses to changing climates.

microbiology↗

bioRxiv2026

Bloom-forming bacteria heavily invest in anti-phage defense

Bacterial blooms are characterized by unusually high cell densities and exceptionally low diversity and can profoundly alter ecosystem function and services. Bacteriophages have long been considered an important cause of mortality in blooms, acting as a mechanism for control. Here, we characterize the viral ecology of a long-lasting estuarine bloom of green sulfur bacteria (Chlorobiota). We combined direct cell and viral counts with metagenomic and metaproteomic data to characterize host and phage activity at different time points. The abundance of virus-like particles (VLPs) decreased at high cell densities, suggesting reduced lytic infection rates. The dominant organism, GSB-TRL01 (genus Prosthecochloris), apparently contained a large conjugative plasmid encoding five different anti-phage defense systems. The organism's genome encoded 13 additional defense systems. Compared to the average of five defense systems per microbial genome, this enrichment suggests robust anti-phage defense capabilities. Proteins from ten different defense systems on GSB-TRL01's genome and four systems from the conjugative plasmid were expressed in the proteome. This suggests that GSB-TRL01 invests heavily in anti-phage defense, leading to reduced lysis at high cell densities and allowing blooms to persist for weeks to months. To determine whether this ability is widespread among bloom forming organisms, we compared genomes of putative bloomers to those of non-blooming organisms. We found that bloomer genomes were significantly enriched with anti-phage defense systems. This challenges traditional paradigms of phage ecology in bloom-forming systems and suggests that microbes adapted to high-density growth may have evolved mechanisms to reduce their susceptibility to phage attack.

microbiology↗

bioRxiv2026

Anoxygenic phototrophic Chlorobi use broad metabolic and resource acquisition strategies to support stable near-clonal blooms

Anoxygenic phototrophic green sulfur bacteria (GSB; Chlorobiia) are important primary producers in anoxic and sulfidic environments, whose significance in aquatic ecosystems will expand with coastal deoxygenation. Here, we employed a uniquely comprehensive analytical approach to investigate the formation, maintenance, and collapse of a GSB bloom. We combined multi-omics -- V4V5 and synthetic long read 16S rRNA amplicon sequencing, metagenomics, and metaproteomics -- with total and GSB-specific cell counts, biogeochemical measurements, and isotopic analysis. The GSB bloom exceeded 109 cells ml-1, among the highest environmental cell densities reported to date, with up to 96 % of the bloom consisting of a single strain-level Prosthecochloris lineage (GSB-TRL01). Extreme sulfide concentrations (> 17 mM) coincided with peaking cell density and a shift in isotopic composition. Bloom persistence is supported by tightly coupled sulfur cycling, high rates of nitrogen fixation, mechanisms to tolerate oxidative stress and maintain redox balance, and nutrient acquisition through outer membrane transport systems. A shift in sulfur oxidizing enzymes towards enzymes with higher sulfide affinity proceeded bloom demise. Prosthecochloris GSB-TRL01 differs from closely related lineages in several outer membrane transport systems, including porins to transport phosphate and tonB-dependent transporters. Collectively, these findings identify physiological and metabolic strategies that may enable near-clonal Prosthecochloris populations to attain extraordinary biomass while coupling the sulfur, carbon, and nitrogen cycles in coastal euxinic environments.

microbiology↗

bioRxiv2026

Conserved inhibitory mechanisms of root-associated bacteria towardsArabidopsis thaliana and Chlamydomonas reinhardtii

Soil bacteria colonize plants without causing visible disease, yet many suppress host growth. The prevalence and evolutionary reach of this cryptic inhibition are unknown, because phenotyping hundreds of isolates in plants is prohibitively slow. Here we use the unicellular algae Chlamydomonas reinhardtii as a scalable proxy for the green lineage. We screened 148 plant-associated bacteria on Chlamydomonas lawns. Seven of eight Chlamydomonas inhibitors also inhibited the vascular model plant Arabidopsis thaliana. In one of these dual inhibitors, Burkholderia sola MF6, transposon screening and proteomics implicated type VI secretion and tight-adherence pili, and over half the non-inhibitory mutants also failed against Arabidopsis. In the algae, infection triggers rapid deflagellation, then non-lytic regulated cell death. The algal zinc/iron transporter ZIP3 promotes inhibition, whereas the cathepsin X protease CEP12 restrains it, and ZIP3 is epistatic to CEP12. Cryptic inhibition is thus ancient and widespread, and a unicellular algae uncovers it at scale.

plant biology↗

bioRxiv2026

Diet-derived peptides mediate the effects of dietary protein source on gastrointestinal health

Plant-based diets support gastrointestinal (GI) health while animal-based diets can disrupt gut homeostasis. Although multiple aspects of these diet types are believed to confer their respective effects, the role of their protein component is less well understood. Here, we conducted a randomized crossover-controlled feeding trial wherein healthy subjects consumed 70% of their daily protein intake in the form of pea protein (PP) or egg white protein (EWP) isolate (NCT05619939). Individuals who consumed EWP reported increased GI symptoms and exhibited elevated intestinal permeability. In contrast, these endpoints did not change following PP consumption. Fecal analysis showed increased diet-derived peptides only following EWP consumption, which was associated with resistance of EWP isolate to degradation by digestive enzymes in vitro. Metagenomic, metaproteomic and metabolomic analyses of stool after the EWP-based diet showed reduced abundance of multiple gut-protective bacterial species and increased bacterial amino acid utilization compared to samples following the PP-based diet. Dietary peptides in the gut luminal content of EWP-fed subjects reduced metabolic function of intestinal epithelial cell in culture. Providing an amino acid-based diet mimicking EWP composition to mice prevented colonic accumulation of diet-derived proteins and GI dysfunction associated with EWP diet consumption. Collectively, these findings demonstrate that dietary protein source is a key mediator of GI function, revealing a modifiable lifestyle factor that impacts human health.

physiology↗

bioRxiv2026

TriMic: a Triticum aestivum microbial culture collection and synthetic community for dissecting wheat-microbe interactions

Understanding the molecular mechanisms underlying plant-microbe interactions is essential for developing innovative microbe-based agrotechnologies. However, deciphering these mechanisms within the complexity of natural microbial communities remains challenging. Such challenges can be addressed by employing synthetic microbial communities (SynComs) derived from well characterized microbial culture collections. Despite their importance, plant-associated microbial collections from major agricultural crops remain scarce. To bridge this gap, we established TriMic, a taxonomically and functionally representative culture collection of wheat root-associated bacteria. Complementing this collection, we include high quality genome sequences and an overview of genes involved in plant colonization, nutrient cycling, and plant growth promotion. Furthermore, we expanded this experimental toolkit by designing a reduced complexity SynCom that enables controlled dissection of plant-microbe interactions. Together, these resources lay the groundwork for mechanistic studies of plant-microbe interactions to accelerate biostimulant development aimed at enhancing agricultural productivity and sustainability. The TriMic collection and whole genomes are publicly available at the DSMZ (https://www.dsmz.de/collection/catalogue/microorganisms/microbiota/trimic) and NCBI. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=166 SRC="FIGDIR/small/740170v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@91bda0org.highwire.dtl.DTLVardef@386c49org.highwire.dtl.DTLVardef@4d455aorg.highwire.dtl.DTLVardef@1043ccb_HPS_FORMAT_FIGEXP M_FIG C_FIG Overview of the workflow for development of the wheat root bacterial collection and SynCom. (a) Bacterial isolates were recovered from roots of wheat grown in natural soil using two strategies after a root slurry was prepared: directly plating or host-mediated, which involved producing a secondary root slurry from wheat roots inoculated with the original root slurry (Ben Niu et al. 2017). Both root slurries were diluted and then plated onto four different types of media (1/10 R2A, 1/20 R2A, 1/100 R2A, and VxylG). Colonies were picked based on morphology and time of appearance. (b) Non-redundant strains of 88 purified isolates were made publicly available at the German Collection of Microorganisms and Cell cultures GmbH (DSMZ). (c) A 15-species synthetic community (SynCom) was developed after evaluating community dynamics in wheat roots inoculated with a 27-member consortium selected across genera in the collection. (d) Isolate genomes were sequenced using either short-read or hybrid assemblies with long-reads. Following functional annotation, genomes were screened for traits associated with plant-microbe interactions and secondary metabolite production.

microbiology↗

bioRxiv2026

Perturbations shift the composition of bacterial DNA carried by virus-like particles in the murine gut microbiome

Horizontal gene transfer (HGT) is a driving force in microbial evolution that allows community members to rapidly evolve to cope with environmental stressors and competition. Despite the importance of HGT for the generation of genetic diversity, little is known about the specific mechanisms or dynamics of transfer in complex communities. Transductomics is a sequencing based technique which identifies potential HGT by bacteriophages (transduction) through sequencing of the transductome - the DNA carried by bacteriophages and other virus-like particles in a sample. We analyzed the murine gut transductome before and after perturbations with antibiotics and Clostridioides difficile infection (CDI). We found that several bacterial families - the Oscillospiraceae, Butyricoccaceae, and Turicibactericeae - disproportionally contributed to the transductome. Some families, like the Butyricicoccaceae, were frequent transducers in both the baseline and perturbed murine gut microbiome while other taxa displayed condition-specific transduction indicating that there may be specific transducing subpopulations or regulatory mechanisms controlling transduction frequency. Additionally, we found a diversity of highly abundant and enriched mobile genetic elements (MGEs) in the transductome including plasmids, integrative conjugative elements, phage satellites and transposons. The detection of MGEs containing conjugative elements suggest that some MGEs may spread through both transduction and conjugation. Overall, our work reveals a complex network of gene exchange occurring through transduction in the gut microbiome.

microbiology↗

bioRxiv2026

High throughput chromatographic ultra-purification of virus-like particles for downstream viromics

Virus-like particles (VLPs) are an abundant component of microbiomes with critical ecological roles such as population control through viral predation and horizontal gene transfer. Studying the collection of viruses in microbiomes (the virome) through metagenomics has provided important insights into the composition and functions of VLPs in different environments. However, the current gold-standard method for VLP purification, CsCl density gradient ultracentrifugation (CsCl), is low throughput, time consuming and suffers from biases which limits the ability to study viromes in larger sample sets and can interfere with data interpretation. Here we present an anion exchange (AEX) chromatography-based approach for the purification of VLPs from microbiome samples that allows for significant increases in throughput and reproducibility while achieving VLP purity levels similar to or higher than CsCl. We used microbiome samples of known composition to first establish and evaluate the AEX approaches and compare them to CsCl. We implemented the AEX approach both for fast performance liquid chromatography (FPLC) and in multi-well plates. We compared the VLPs purified with CsCl and AEX using shotgun metagenomic sequencing and found that AEX performs similarly to or better than CsCl for purification of VLPs. AEX purified VLP-fractions captured significantly more viral DNA compared to CsCl. We also found that both AEX and CsCl were capable of capturing viruses present at extremely low relative abundances (<0.001%). Additionally, we found that DNase digestion and CsCl may bias against filamentous phage morphologies. Finally, we purified VLPs from conventional murine feces using AEX and CsCl. AEX purified murine fecal VLPs had a much higher viral DNA content (85%) than CsCl (41%). While there were some differences in viral contigs assembled from AEX and CsCl VLP metagenomes, these method unique viral contigs made up only small proportions (<8%) of the relative abundance in the VLP metagenomes. AEX, particularly in the multi-well format, enables the ultrapurification of VLPs from tens to hundreds of samples in a single day thus facilitating virome studies with the large sample numbers needed for translational and clinical research.

microbiology↗

bioRxiv2026

Spatial localisation of touch on a robotic limb in the absence of direct haptic feedback

Artificial limbs typically lack somatosensory receptors, limiting users access to haptic feedback about movement outcomes. However, indirect tactile signals generated during object interaction are transmitted to the body-limb interface and may serve as a haptic feedback source. This study investigates whether such indirect tactile signals convey distinct information that can support localisation of touch on an artificial body part. Using an additional robotic thumb (The Third Thumb, Dani Clode Design), we measured tactile signals at the interface between the Third Thumb and the hand following stimulation from four vibration motors positioned along the Thumb. We then assessed whether participants could discriminate these signals and integrate them with different Thumb postures to spatially localise touch. Measurements showed that each stimulation site produced distinct tactile signatures at the interface. Behaviourally, participants localised touch at above-chance levels. Representational similarity analyses further revealed that performance was best explained by the spatial positions of stimuli, rather than by limb-based coordinates or indirect signal patterns alone, indicating flexible mapping of indirect touch signals onto the Third Thumb posture. Together, these findings demonstrate that indirect tactile signals transmitted through an artificial limb can be discriminated and flexibly remapped to support spatial localisation of touch.

neuroscience↗

bioRxiv2026

Identification of cytoplasmic incompatibility effectors of the reproductive manipulator Cardinium hertigii

Cytoplasmic incompatibility (CI), a widespread symbiont-induced reproductive manipulation phenotype in arthropods, selectively kills embryonic offspring produced when infected males mate with uninfected females. Most knowledge on CI comes from studying the Pseudomonadota symbiont Wolbachia and their CI effector (cif) genes, and little is known about CI mechanisms of symbionts without cif genes. We identify two putative CI effectors of Cardinium hertigii cEper1, a Bacteroidota symbiont of the parasitoid wasp Encarsia suzannae, using a combined proteomics and heterologous expression approach. We show that these genes, CAHE_0406 and CAHE_p0043, have no homology to known cif genes, yet impair yeast growth similar to known cifs and that CAHE_p0043 localizes to diffuse and fragmented yeast nuclei. These results suggest that CAHE_0406 and/or CAHE_p0043 could play a role in cEper1-induced CI, expanding our current understanding of the diversity of proteins involved in cytoplasmic incompatibility across symbiont lineages.

microbiology↗

bioRxiv2026

Genome-scale community metabolic modeling of maize root-associated microbiota shows that root exudates stimulate diverse metabolic interactions

Microbes play a vital role in plant development, health, and resilience, yet relatively little is known about the specific metabolic mechanisms driving interactions in these host-associated communities. Systems biology models enable a computational approach to understanding metabolic interactions, which can be difficult to pinpoint experimentally; however, these methods cannot yet accommodate the large number of species in natural communities. Synthetic communities (SynComs) provide a more tractable alternative to explore targeted interactions. Here, we investigated metabolite exchange in a seven-member maize root-associated SynCom, specifically accounting for plant host context by designing a customized exudate medium. We constructed metabolic models for each bacterial species and curated them with in vitro phenotyping data to reflect experimentally based carbon uptake potential. Flux balance analysis of individual species demonstrated that integrating phenotype data and changing medium type had substantial impacts on predicted growth rates, which in turn shaped potential interspecies interactions. In silico community growth optimization of the seven-member community model showed that the exudate medium supported a more diverse community composition compared to minimal medium, with predictions of community member abundance closely aligned to literature-derived experimental results. Predicted metabolite exchange in the root exudate environment showed Enterobacter ludwigii as a community hub, and cross-feeding of indole suggested a potential effect of bacterial community interactions on the plant host. Our in silico findings indicate the host plays an important role in structuring microbial interactions and cross-feeding at the metabolic level, underscoring the importance of considering environmental context from both theoretical and experimental perspectives. IMPORTANCETrue understanding of a system is marked by the ability to predict its behavior. The complexity of natural host-microbe systems represents a frontier of knowledge that scientists are working to understand, and elucidating principles of interactions within multi-partite microbial communities remains a challenge in microbial ecology. Synthetic communities provide a tractable starting point for investigating interaction mechanisms, and computational approaches complement laboratory experiments by systematically evaluating multiple possibilities for metabolic pathway processing, thereby allowing us to comprehensively study the interconnected metabolic networks of host-associated microbiota. The model we developed for the seven-member maize root-associated bacterial community presents a step toward predicting plant-microbe behavior, providing hypotheses for future experimental testing and serving as a template for expanding model complexity to more members and other systems.

systems biology↗

bioRxiv2026

Metagenomics-enabled proteomics reveals how AMF and PSB co-inoculation reshapes tomato rhizosphere dynamics across growth stages

Urban agriculture increasingly relies on compost-based substrates for sustainable production, yet we lack a clear characterization of how these systems respond to biological amendments aimed at introducing beneficial microbiota. Here we investigated how developmental stage and co-inoculation with arbuscular mycorrhizal fungi (AMF) and phosphate-solubilizing bacteria (PSB) reshape rhizosphere microbial function in Solanum lycopersicum grown in compost-based urban farm substrate. Using plant physiology assays, 16S rRNA amplicon sequencing, and metagenome-informed metaproteomics, we characterized tomato physiological responses and rhizosphere microbial activity during flowering and fruiting across control, single AMF, single PSB, and AMF and PSB co-inoculation treatments. Co-inoculation synergistically enriched beneficial taxa, improved fruit nutrient accumulation, elevated nutrient transporter and quorum sensing protein production, and drove stress-driven dormancy in competitively excluded taxa, with responses varying between developmental stages. Our findings establish metagenome-informed metaproteomics as essential for resolving stage-specific rhizosphere microbiome functional responses to tomato development and AMF and PSB co-inoculation.

bioinformatics↗

bioRxiv2026

Area under the curve quantification outperforms spectral counting in metaproteomics, but matching between runs is detrimental

Metaproteomics enables the functional characterization of complex microbial communities by detecting and quantifying thousands of proteins. Accurate quantification is essential for deriving meaningful biological inferences from metaproteomes. In mass spectrometry-driven metaproteomics, protein quantification is performed using either MS1-based area under the curve (AUC) or MS2-based peptide spectral counts (SpC). Systematic benchmarking of AUC vs. SpC quantification for metaproteomics, however, is lacking. Additionally, the impact of matching identifications between runs (MBR) on AUC quantification accuracy has not been evaluated. Here, we tested whether AUC or SpC is better suited for quantification in metaproteomics using data-dependent acquisition mass spectrometry data and investigated the impact of MBR on AUC using defined metaproteomics samples with known composition as ground truth. We found that MBR incorrectly transferred peptide and protein identifications and led to a substantial number of falsely identified proteins in samples of known composition. Additionally, when comparing MBR-free AUC data to SpC, AUC data had a wider dynamic range, higher quantitative accuracy, and higher sensitivity for detecting abundance differences. Based on these findings, we recommend MBR-free AUC quantification for metaproteomics analysis, while SpC-based identifications can be used to increase the number of identified proteins to obtain a more comprehensive view of expressed functions. Significance of the studyAlthough accurate quantification of proteins is crucial for characterizing microbial functions in microbiomes, quantification strategies in metaproteomics are mostly selected based on convention rather than evidence. With this study, we provide an evidence-based framework for the informed selection of quantification strategies in metaproteomics. We highlight the strengths and limitations of the tested approaches with respect to dynamic range, quantitative accuracy, and proteome coverage. Based on our results, we recommend using AUC data without MBR for quantitative metaproteomics.

molecular biology↗

bioRxiv2026

TrIdent - An R package to automate transductomics analysis of virus-like particle mediated DNA mobilization

BackgroundTransduction is a form of horizontal gene transfer in which bacterial DNA is packaged and transferred by virus-like particles (VLPs). Transductomics is a sequencing-based method used to detect DNA carried by VLPs. During transductomics analysis, reads from a samples ultra-purified VLPs are mapped to metagenomic contigs assembled from the same samples whole-community. The read mapping produces coverage patterns that require a time-consuming manual inspection and classification process which makes the methods use unfeasible for datasets with many samples. ResultsWe developed a novel algorithm, TrIdent (Transduction Identification), that uses pattern-matching to automate the transductomics data analysis and that is available as an R package (https://jlmaier12.github.io/TrIdent/). There is no software equivalent to TrIdent so we compared TrIdents classifications of transductomics datasets to classifications made by human classifiers. TrIdents classifications were generally comparable to the manual classifications on a previously generated, manually classified transductomics dataset. When applied to newly generated transductomics data from the murine microbiota, TrIdent agreed with two independent human classifiers as much as the two independent human classifications agreed with each other. TrIdent classified transductomics datasets in a fraction of the time needed by human classifiers, and the classifications produced by TrIdent are fully reproducible. We used TrIdent to explore three murine gut transductomes and found that bacterial DNA associated with the Oscillospiraceae and Turicibacteraceae families was highly enriched in the DNA packaged by VLPs as compared to the whole community metagenomes. ConclusionsThe TrIdent software is a more accessible, more efficient, and more reproducible alternative to the manual inspection of read coverage patterns previously required for transductomics data analysis. To demonstrate the application of TrIdent, we analyzed transductomics datasets from murine fecal pellets and showed that specific low abundance bacterial families appear to be heavily involved in transduction.

genomics↗

bioRxiv2026

ZeaMiC: a Publicly Available Culture Collection of Maize Root-Associated Bacteria

Plant-associated microbiota are composed of hundreds of microbial species. For many of them, little is known about their individual functions and even less is known about their emergent community-level traits. While culture-independent methods provide valuable insights into the composition, diversity, and functional potential of plant-associated microbiota, culture-dependent methods are essential for reductionist lines of inquiry into the roles of individual species and their interactions within a community. Here, we present ZeaMiC, a publicly available culture collection of root-associated bacteria from Zea mays (maize). This resource comprises 88 isolates obtained from diverse soils and several maize genotypes, with live cultures available through DSMZ (German Collection of Microorganisms and Cell Cultures) both as single stocks and as cost-effective bundles (https://www.dsmz.de/collection/catalogue/microorganisms/microbiota/zeamic). To maximize relevance, isolates were selected to be representative of maize root-associated microbiomes in the Corn Belt of the United States, based on abundance-occupancy patterns from previously published root microbiome data, phylogenetic diversity, and literature-based evidence of functional importance. Whole-genome sequencing and annotation revealed genes associated with root colonization, plant growth promotion, and nutrient cycling, including functions such as chemotaxis, biofilm formation, secretion systems, hormone modulation, and phosphate solubilization. This collection serves as a community resource for future mechanistic studies of plant-microbe and microbe-microbe interactions, filling the gap in our understanding of the ecological interactions in plant microbiomes.

microbiology↗

bioRxiv2025

Evaluation of statistical approaches for differential metaproteomics

BackgroundMetaproteomics characterizes and compares molecular phenotypes of organisms in communities by comprehensively analyzing their protein expression profiles using statistical methods. However, not all statistical methods are suitable for determining differentially abundant protein groups in metaproteomic analyses. Statistical challenges in metaproteomics include: data sparsity, non-normality, compositionality, and large between-sample variability. These challenges can potentially be addressed with several data processing steps, including imputation, normalization, transformation, and selection of the appropriate statistical tests. The potential combinations of different processing methods create a complex matrix of analysis options and it is currently unclear how these combinations impact the results of statistical tests on metaproteomic data. ResultsTo determine what data processing methods and statistical tests are best for identifying differentially abundant proteins in metaproteomics datasets, we generated a set of thirteen metaproteomic samples with known compositions, known differences, and differing levels of complexity. These defined metaproteomes address the general challenges outlined above, using various scenarios in metaproteomic data analyses. We compared over 110 different statistical analysis combination options, including regression-based tools, general statistics inference, and machine learning techniques. We found that several combinations within the frameworks of limma, edgeR, MaAslin2, custom linear and Bayesian linear models, and random forests all offer suitable evaluation options. ConclusionsWe highlight key recommendations for differential expression analysis in metaproteomics. Our work enables improved assessment of statistical methods for metaproteomics by establishing a framework for testing statistical approaches, including comprehensive raw mass spectrometry data and reproducible benchmarking code.

molecular biology↗

bioRxiv2025

Assessing the diversity and functional profile of the microbial proteome in fermented foods

Fermented foods are staples in diets worldwide and are known for their health benefits. Microorganisms are the key to fermented food production as they convert raw substrates into digestible, nutritious, and health-promoting products. While microbes are essential for fermented food production, their contribution to the dietary protein profile of the final food product in terms of microbial biomass is largely unknown. We analyzed proteins from 17 fermented foods using metaproteomics to identify and quantify microbial and food-derived proteins. We found that microbial proteins contribute up to 11% of the total protein content in fermented foods and comprise as much as 60% of the total number of identified proteins. These microbial proteins included many for central functions in microbial cells, such as glycolysis enzymes, translation machinery, and chaperones, as well as proteins for specialized functions that are important for the ecological niches in food fermentation, such as carbohydrate degrading enzymes and proteases. Some of these microbial proteins, such as proteases, could impact gut physiology. These findings highlight the substantial contribution of microbial proteins to the nutritional and functional profile of fermented foods, which may have important implications for interactions with the gut microbiota and health outcomes.

microbiology↗

bioRxiv2025

Evaluation of Parallel Accumulation-Serial Fragmentation methods for metaproteomics using a model microbiome

Mass spectrometry-based metaproteomics allows for the identification and quantification of thousands of proteins from clinical and environmental samples and is rapidly gaining importance in microbiome sciences. Metaproteomics researchers can measure taxonomic and functional abundances of microbiomes, shedding light on mechanistic details of microbiome interactions with their environment. However, metaproteomic analysis suffers from limited depth of coverage due to the presence of millions of peptides at lower abundance levels. Recent advances in data-independent acquisition mass spectrometry coupled with Parallel Accumulation-Serial Fragmentation (PASEF) technology offer improved depth of coverage. PASEF technology enables simultaneous accumulation of ions from multiple co-eluting peptides by combining ion mobility separation with dynamic quadrupole isolation, allowing efficient and selective fragmentation in a single scan. This boosts ion sampling efficiency and resolves overlapping signals with high sensitivity. In this study, we assessed proteome coverage, quantitative precision, and accuracy of Data-dependent acquisition (DDA) and Data-independent acquisition (DIA) methods coupled with the PASEF method. For this, we used a ground-truth mock community containing 28 species (30 strains) from all three domains of life and bacteriophages with a 400-fold dynamic range of organism abundance. Our results showed that diaPASEF demonstrated superior performance, identifying 168% more peptide precursors, 155% more peptides, and 66% more protein groups compared to ddaPASEF. Quantitative measurements showed improved precision with diaPASEF, with 26 out of 28 organisms exhibiting coefficient of variation values below 20%, compared to 24 organisms with ddaPASEF. Both ddaPASEF and diaPASEF methods accurately quantified the 22 most abundant organisms, while measurements of low-abundance bacteriophages showed significant deviation from expected values. Our findings demonstrate that diaPASEF provides enhanced depth of coverage and quantitative reliability for metaproteomics analysis, particularly beneficial for clinical and environmental microbiome studies where deeper functional characterization is essential. This study provides valuable benchmark data to facilitate the development of advanced bioinformatic methods for quantitative metaproteomics.

biochemistry↗