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At least 19 recordsLinked to original sources

PubMed2026

A streamlined workflow for high throughput metaproteomic analysis of the rumen microbiome.

Metaproteomics can provide direct functional insights into complex microbial communities, yet its application in rumen research remains limited due to labor-intensive and low-throughput sample preparation workflows before the MS analysis. This work aimed to develop and characterize a streamlined, high throughput metaproteomic workflow optimized for rumen samples. Key steps, including microbial cell extraction, cell lysis, protein digestion, and LC-MS/MS acquisition, were systematically assessed and optimized to reduce hands-on time while maintaining deep proteome coverage. The optimized workflow integrates a minimized cell extraction protocol using 0.5 g starting material and in-solution tryptic digestion. Application of the final workflow to 72 samples from in vitro fermentation revealed that biological variability between inocula dominated technical variability, which remained moderate (median CV of 21-24% across batches). Overall, the optimized workflow supports robust taxonomic and functional characterization of the rumen microbiome with improved scalability. These advances provide a foundation for applying metaproteomics to larger experimental designs, including nutritional trials and cohort studies, thereby enabling broader functional interrogation of rumen microbial ecosystems. SIGNIFICANCE: This study addresses current limitations in the application of metaproteomics to rumen microbiome research by developing a streamlined and scalable sample preparation workflow. By optimizing key steps and reducing sample input while maintaining reproducibility and proteome coverage, this work enables more efficient processing of larger sample sets. These advances support the broader use of metaproteomics in rumen studies and facilitate functional investigations relevant to animal nutrition and sustainable livestock production.

Animals↗

PubMed2025

Functional metaproteomics for enzyme discovery.

Discovery of microbial biocatalysts traditionally relied on activity screening of isolated bacterial strains. However, since most microorganisms cannot be cultivated in the lab, such an approach leaves the majority of the microbial enzyme diversity untapped. Metagenomic approaches, in which the DNA from a microbial community is directly isolated and then used either for the creation of an expression library or for sequencing and metagenome annotation have alleviated this shortcoming to an extent, but have their own limitations: the generation of large expression libraries is time-consuming and their screening is costly, while metagenome annotation can infer biocatalytic function only from prior knowledge. We have thus developed a functional metaproteomic approach, which combines the immediacy of traditional activity screening with the comprehensiveness of a meta-omics approach. Briefly, the whole metaproteome of an environmental sample is separated on a 2-D gel, biocatalytically active proteins are visualized in-gel through zymography, and those candidate biocatalysts are then identified through mass spectrometry, searching against a metagenome-derived database obtained from the very same environmental sample. Here we explain the process in detail, with a focus on esterases, and give guidelines on how to develop a functional metaproteomic workflow for enzyme discovery.

Proteomics↗

PubMed2026

Pilot metaproteomic profiling reveals bacterial diversity and potential medical and veterinary relevance of tick microbiomes in northern Algeria.

Ticks are major ectoparasites and vectors of pathogens affecting humans, livestock, and wildlife. They harbor diverse microbial communities that may influence tick biology and interactions with microorganisms; however, functional information on tick-associated microbiomes remains limited, particularly in North Africa. In this pilot study, we applied a metaproteomic approach based on high-resolution tandem mass spectrometry to characterize bacterial communities associated with three tick species collected in Algeria: Rhipicephalus sanguineus sensu lato, Hyalomma aegyptium, and Hyalomma dromedarii. Peptide spectra were assigned to taxa using a two-step database search strategy based on NCBInr, and bacterial composition and relative abundance were compared across tick species and sampling locations. A total of 40 bacterial genera belonging to 32 families and four phyla were identified. Microbiome composition differed significantly between tick genera and collection locations, suggesting an influence of species-specific and geographical factors on microbial community structure. Dominant genera included Streptomyces, Bacillus, Clostridium, Escherichia, Flavobacterium, Paenibacillus, and Providencia. Peptides related to Coxiella spp. were frequently detected, consistent with previous reports of Coxiella-like endosymbionts in ticks. This pilot study provides a first metaproteomic characterization of tick-associated communities in Algeria. The results reveal species- and location-associated differences in microbial composition and highlight the potential of metaproteomics for exploring tick-associated microbiomes in North Africa.

Animals↗

PubMed2024

metaExpertPro: A Computational Workflow for Metaproteomics Spectral Library Construction and Data-Independent Acquisition Mass Spectrometry Data Analysis.

Analysis of large-scale data-independent acquisition mass spectrometry metaproteomics data remains a computational challenge. Here, we present a computational pipeline called metaExpertPro for metaproteomics data analysis. This pipeline encompasses spectral library generation using data-dependent acquisition MS, protein identification and quantification using data-independent acquisition mass spectrometry, functional and taxonomic annotation, as well as quantitative matrix generation for both microbiota and hosts. By integrating FragPipe and DIA-NN, metaExpertPro offers compatibility with both Orbitrap and timsTOF MS instruments. To evaluate the depth and accuracy of identification and quantification, we conducted extensive assessments using human fecal samples and benchmark tests. Performance tests conducted on human fecal samples indicated that metaExpertPro quantified an average of 45,000 peptides in a 60-min diaPASEF injection. Notably, metaExpertPro outperformed three existing software tools by characterizing a higher number of peptides and proteins. Importantly, metaExpertPro maintained a low factual false discovery rate of approximately 5% for protein groups across four benchmark tests. Applying a filter of five peptides per genus, metaExpertPro achieved relatively high accuracy (F-score = 0.67-0.90) in genus diversity and showed a high correlation (rSpearman = 0.73-0.82) between the measured and true genus relative abundance in benchmark tests. Additionally, the quantitative results at the protein, taxonomy, and function levels exhibited high reproducibility and consistency across the commonly adopted public human gut microbial protein databases IGC and UHGP. In a metaproteomic analysis of dyslipidemia patients, metaExpertPro revealed characteristic alterations in microbial functions and potential interactions between the microbiota and the host.

Proteomics↗

PubMed2026

The need for standardization and improved open (meta)data practices in metaproteomics.

Metaproteomics enables functional insight into microbial communities by identifying and quantifying proteins in complex samples. Yet, heterogeneous analytical workflows and the lack of standardization across experimental and bioinformatics stages hinder reproducibility and comparability, limiting integration with other omics data. We here present a community-developed reporting checklist tailored to the specific needs of metaproteomics. We also outline current efforts to enable structured and interoperable metadata capture, drawing on standards from proteomics and microbiome research wherever possible. By promoting transparent reporting and advancing metadata practices, our recommendations aim to align metaproteomics more closely with FAIR principles and support reproducible and interoperable research practices. Video Abstract.

Proteomics↗

PubMed2025

Metaproteomic Analysis to Assess the Impact of Storage Media on Human Gut Microbiome in Fecal Samples.

The human gut microbiome is a diverse community of microorganisms residing in the gastrointestinal tract. The storage condition of fecal samples may impact the taxonomic and protein compositions of microbiomes in these samples. Here, we performed a mass spectrometry-based metaproteomic study to assess the impact of storage media on human gut microbiome in fecal samples. We evaluated FDA-authorized OMNIgene·GUT (OG), phosphate-buffered saline (PBS), and RNALater (RNAL) buffers and identified 38,185 microbial peptides corresponding to 7348 microbial proteins, which matched 16 phyla, 20 classes, 50 orders, 104 families, 332 genera, and 453 species. We found a high similarity among the fecal microbiomes preserved in OG, PBS, and RNAL in terms of the identification of proteins, taxa, and functional annotations. Both alpha and beta diversity suggested the high similarity among samples stored in the three media. Nonetheless, we also found some notable differences among buffers regarding the abundances of a few taxon groups. A partial human proteome (over 400 proteins) was identified in the fecal samples, with most of these proteins associated with the membrane and extracellular regions. The findings indicate the similarity among microbiomes in the fecal samples stored in OG, PBS, and RNAL regarding proteome profile, taxa, and functional capacity. SUMMARY: This study thoroughly analyzed and compared the metaproteomes of fecal samples preserved at -80°C in PBS, RNALater, and OMNIgene·GUT Dx buffers, offering novel insights into the effectiveness of these buffers in maintaining the stability and composition of the human gut microbiome. We found a high similarity in the identification and quantification of proteins, taxa, and functional annotations across the three buffers, with notable quantitative differences highlighting subtle yet important variations in preservation efficacy. The unique datasets and findings could offer valuable revelations into the impact of fecal sample preservation on translational and clinical analyses of the human gut microbiome.

Humans↗

PubMed2026

Metaproteomic profiling reveals viral proteins and associated host proteomic alterations in glioblastoma.

Glioblastoma (GB) is a WHO grade 4 brain cancer with dismal prognosis, yet its aetiology remains poorly defined. Although viral involvement has been proposed, findings across studies remain inconsistent, reflecting inherent limitations of individual technologies and cohort size. Here we applied metaproteomic profiling to a publicly available GB proteome dataset (12 control, 21 adjacent, 159 tumour) and an independent cohort of 81 samples (37 control, 44 tumour) to detect viral proteins in tumour and controls tissues. Across cohorts, we detected viral proteins from diverse species, with human herpesviruses (HHV-1, 2, and 8) more frequently detected in GB tumours compared with control tissues. Analysis of the host tumour proteome revealed differential abundance of proteins related to transcriptional regulation, RNA processing, protein translation, immune responses, and mitochondrial-associated metabolism. Correlation analysis identified associations between viral and human proteins, with several linked to biological processes previously implicated in DNA virus-host interactions. Further stratification of tumour by HHV-1 status showed consistent alterations in proteins associated with mitochondrial-associated metabolism, protein turnover, and cell adhesion/signalling.In summary, this study demonstrates the feasibility of metaproteomics for detecting viral components in archival GB tissues. Using this approach, we observed differences in viral protein landscape across cohorts and identified associations between viral presence and host proteomic features, providing a protein-level framework for future studies of virus-host interactions in GB.

Humans↗

PubMed2026

Integrated metagenomic and metaproteomic insights into current-carrying-coil magnetic field enhanced synergistic methanogenic system and antibiotic resistance gene reduction in cow manure anaerobic digestion.

Anaerobic digestion (AD) is a sustainable strategy for valorizing cow manure (CM). However, the high ammonia (NH3) concentration and low biodegradability of CM limit hydrolysis and methane production. This study investigated the application of a current-carrying-coil-based magnetic field (CCC-MF) to AD of CM. The CCC-MF digesters showed higher soluble chemical oxygen demand and attained 16.59 % higher ammonium nitrogen reduction, contributing to a 37.50 % higher average methane yield than the control. Further, CCC-MF digesters showed higher enzyme activities (alkaline protease + 30 %, acetate kinase + 22 % and hydrazine dehydrogenase + 26 %) and increased microbial metabolic indices (dehydrogenase activity + 17 % and electron transport system activity + 10 %) than the control. Metagenomics analysis revealed that abundances of the bacterial genera Mesotoga, Aminobacterium, Xiashengella, unclassified Candidatus Cloacimonadota, Advenella, Pseudomonas, and Comamonas increased, whereas the acetoclastic methanogen Methanothrix decreased by 2.58 %, accompanied by 2.07- and 1.64-fold increases in hydrogenotrophic methanogens Methanospirillum and Methanobacterium, respectively, in CCC-MF digesters. The abundance of nitrogen dissimilation and assimilation genes NirK, NorB, NarB, NapA, nmo, and GLT1 were enhanced by 1.14, 1.04, 2.30, 1.32, 1.17, and 1.29-fold in CCC-MF digesters compared to the control. Moreover, metaproteomics revealed higher up-regulated differentially expressed proteins in NH3 reduction-related amino acid metabolism pathways in CCC-MF digester compared to control. Additionally, reduced abundances of bacitracin, polymyxin, sulfonamide, and multidrug antibiotic resistance (MAR) gene types were observed in the CCC-MF digesters. The findings suggest that applying CCC-MF may be associated with higher methane production and ammonium reduction, potentially linked to a more favorable synergistic methanogenic system and nitrogen transformation pathways.

Manure↗

PubMed2025

Large Quantities of Bacterial DNA and Protein in Common Dietary Protein Source Used in Microbiome Studies.

Diet has been shown to greatly impact the intestinal microbiota. To understand the role of individual dietary components, defined diets with purified components are frequently used in diet-microbiota studies. Defined diets frequently use purified casein as the protein source. Previous work indicated that casein contains microbial DNA potentially impacting results of microbiome studies. Other diet-based microbially derived molecules that may impact microbiome measurements, such as proteins detected by metaproteomics, have not been determined for casein. Additionally, other protein sources used in microbiome studies have not been characterized for their microbial content. We used metagenomics and metaproteomics to identify and quantify microbial DNA and protein in a casein-based defined diet to better understand potential impacts on metagenomic and metaproteomic microbiome studies. We further tested six additional defined diets with purified protein sources with an integrated metagenomic-metaproteomic approach and found that contaminating microbial protein is unique to casein within the tested set as microbial protein was not identified in diets with other protein sources. We also illustrate the contribution of diet-derived microbial protein in diet-microbiota studies by metaproteomic analysis of stool samples from germ-free mice (GF) and mice with a conventional microbiota (CV) following consumption of diets with casein and non-casein protein. This study highlights a potentially confounding factor in diet-microbiota studies that must be considered through evaluation of the diet itself within a given study.

Animals↗

PubMed2025

Consumption of traditional Sardinian fermented milk promotes changes in the rat gut microbiota composition and functions.

BACKGROUND: Fermented milk products are part of the staple diet for many Mediterranean populations. Most of these traditional foods are enriched with lactobacilli and other lactic acid bacteria, as well as with metabolites resulting from lactose fermentation. Currently, there is very little scientific knowledge on how dietary supplementation with fermented milk affects the composition of the gut microbiota and its metabolic activities. RESULTS: We integrated 16 S rRNA gene-based taxonomic profiling with metaproteomics-based functional analysis to investigate gut microbiota changes in rats exposed to an 8-week dietary supplementation with casu axedu, a traditional fermented milk produced within rural communities in Sardinia (Italy). Several microbial taxa showed a significantly increased abundance at the end of the dietary treatment, including Phascolarctobacterium, Prevotella, Blautia glucerasea, and Lactococcus lactis, while Bacteroides dorei and Helicobacter rodentium were decreased compared to the control rats. Metaproteomic analysis highlighted a striking reshaping of the Prevotella proteome in agreement with its blooming in casu axedu-fed animals, suggesting an increase of the glycolytic activity through the Embden-Meyerhof-Parnas pathway over the Entner-Doudoroff pathway. Moreover, an increased production of enzymes involved in succinate biosynthesis was observed, which in turn significantly boosted the abundance of Phascolarctobacterium and its production of propionate. Fermented milk consumption also promoted microbial synthesis of branched chain essential amino acids L-valine and L-leucine. Finally, metaproteomic data indicated a reduction of bacterial virulence factors and host inflammatory markers, suggesting that the consumption of casu axedu can have beneficial effects on the gut mucosa health. CONCLUSIONS: Our integrated multi-omics approach reveals that dietary supplementation with the traditional Sardinian fermented milk, casu axedu, induces significant shifts in the rat gut microbiota composition and function, characterized by the enrichment of beneficial taxa and metabolic pathways associated with improved gut health and reduced inflammation.

Animals↗

PubMed2026

MegaPX: fast and space-efficient peptide assignment method using IBF-based multi-indexing.

MOTIVATION: A central problem for metaproteomic analysis is the often-unknown taxonomic composition of the analyzed microbiomes. Using a database search, the standard approach requires prior knowledge of which proteins and taxa to include in the protein reference database or to use tailored metagenome-derived databases, which are expensive and error-prone in their generation. A possible strategy to circumvent this database search issue is de novo sequencing, where peptide sequences are directly identified from mass spectra. However, these sequences must still be mapped back to potentially extensive databases. Here, alignment-based approaches enable robust and precise results, with the potential drawback of high memory usage and long run times. RESULTS: We present MegaPX, a software for rapidly classifying de novo peptide sequences against large protein databases. MegaPX implemented as a C++-based tool, uses an alignment-free, k-mer approach as a taxonomic classification method with the possibility of generating mutated reference databases for error-tolerant searching. It uses various algorithms, including interleaved Bloom filters, to efficiently compute approximate membership queries, ensuring fast processing times while querying and indexing large databases in a multi-indexing fashion. We demonstrate the potential of MegaPX by analyzing different samples, including metaproteomics, against extensive reference databases, highlighting its use as a fast screening tool.

Software↗

PubMed2026

Unveiling microbial risks in Chinese household dust: a comprehensive analysis from absolute abundance to virulence unit.

BACKGROUND: People spend the majority of their lives indoors, yet the risk and virulence potential of household microbiota remain largely unexplored, particularly in developing countries. RESULTS: Here, we conducted a nationwide survey on both dust samples and health information across 118 Chinese households. The microbiota composition and its functional units were analyzed using absolute 16S rRNA/ITS sequencing, metagenomics, and metaproteomics. Cross-domain network analysis of the core microbial communities revealed robust co-occurrence patterns in household dust. The mean absolute abundance of potentially pathogenic bacteria and fungi in households was 2.39 × 105 and 2.83 × 106 DNA copies/g dust. The potentially pathogenic community was primarily influenced by latitude, relative humidity, and average temperature. Although total absolute abundance was substantially lower in urban areas, the relative abundance of potentially pathogenic bacteria was markedly higher compared to rural environments. While urban-rural differences existed, the underlying statistical drivers were the environmental variables. The absolute abundance of potential pathogens was significantly associated with the prevalence of rhinitis, wheeze, and dermatitis in 266 participants. Children were identified as the highest-risk group from inhalation exposure of average daily dose. A total of 170 bacterial, 223 fungal virulence factors (VFs), and 370 antibiotic resistance genes (ARGs) were detected in dust and dust extracellular vesicle (EV)-associated DNA. EV-associated cargoes contributed 47.13% to the bacterial VF profiles, 11.90% to fungal VF profiles, and 44.45% to ARG profiles. Metaproteomic analysis confirmed the presence of VF profiles in dust EVs, which was further verified by curated proteomics data from 35 household pathogens. CONCLUSIONS: This study provides a comprehensive, quantitative framework linking indoor microbial exposure to health risks, highlighting EVs as a non-negligible, novel, extracellular mechanistic pathway for health impact in household environments. Video Abstract.

Child↗

PubMed2026

Symbiosis reshapes metabolism of sulfate-reducing bacteria in gutless marine worms.

Sulfate-reducing bacteria (SRB) are widespread in marine and terrestrial environments, where they often form syntrophic associations with bacteria, archaea, and eukaryotes. Among the most intimate of these are multipartite symbioses in gutless marine oligochaete worms, which host SRB and sulfur-oxidizing endosymbionts that engage in a syntrophic exchange of sulfur compounds. Despite decades of research on free-living SRB, the metabolic traits that enable SRB to persist in symbiosis, and how these differ across hosts and environments, remain poorly understood. We show that a globally distributed clade of symbiotic SRB, which we named Candidatus Desulfoconcordia, has a conserved core metabolism that diverges from free-living relatives. Using comparative genomics and metaproteomics, we reveal that these endosymbionts retain key traits of SRB such as sulfate reduction, complete oxidation of acetate to CO2, amino acid degradation for nitrogen acquisition, and transport of essential nutrients. However, they exhibit a more oxygen-tolerant metabolism and lack typical nutrient-scavenging mechanisms of free-living SRB. One trait, the glyoxylate bypass, was consistently expressed in situ and may serve both in reactive oxygen species defence and in biomass generation. The expression of oxygen-tolerant pathways, coupled with the loss of nutrient-scavenging functions, indicate specialization to a host-associated, redox-fluctuating environment distinct from that of free-living SRB. The symbiont genomes are also larger than those of free-living relatives, contrasting with genome reduction in many endosymbionts and reinforcing the importance of metabolic versatility. Our findings provide a framework for understanding how metabolic flexibility enables SRB to persist in long-term multipartite symbioses across diverse marine ecosystems.

Symbiosis↗

PubMed2026

From Variability to Consensus: Rescoring Harmonizes Peptide Identification across Diverse Search Engines and Data Sets.

Peptide-spectrum match (PSM) rescoring has become standard in proteomics workflows, improving peptide identification accuracy across diverse search engines. Despite the availability of multiple rescoring strategies, systematic comparisons spanning several search engines, data sets, and database configurations remain limited. Here, we benchmarked seven publicly available search engines, evaluating standard target-decoy-based false discovery rate (FDR) estimation alongside Percolator, MS2Rescore, and Oktoberfest across four data sets acquired on different mass spectrometry platforms in data-dependent mode and searched against protein databases of varying size and composition. Rescoring substantially increased identification consensus and reduced variability between search engines, with prediction-based approaches yielding the largest gains. While database size had limited impact for human data sets, it significantly affected identification rates on a metaproteomic data set. Entrapment-based evaluation indicated generally adequate FDR control across methods, although prediction-based rescoring exhibited a higher tendency toward FDR underestimation in specific configurations. Overall, advanced rescoring strategies harmonize peptide identification outcomes across search engines, thereby enhancing robustness and comparability in proteomics analyses. However, careful feature selection and appropriate database choice remain essential to ensure reliable FDR control and optimal performance across diverse experimental settings.

Search Engine↗

PubMed2026

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.

Fermented Foods↗

PubMed2026

Lithosyntrophy: Obligate syntrophy in a phosphite-oxidizing, methanogenic culture.

The anaerobic conversion of organic matter to methane and carbon dioxide typically relies on obligate syntrophic interactions between bacteria and methanogenic archaea, where interspecies electron transfer enables thermodynamically constrained reactions to proceed near equilibrium. Syntrophs often couple the oxidation of fermentation products such as fatty acids and alcohols to the reduction of protons to form hydrogen (H2). These reactions can only proceed if low H2 concentrations are maintained by H2-consuming syntrophic partners. Here, we describe "lithosyntrophy," a mode of syntrophic interaction in which electrons that drive hydrogenotrophic methanogenesis originate from an inorganic compound rather than from the canonical organic substrates. Candidatus Phosphitivorax anaerolimi Phox-21 oxidizes phosphite (HPO32-, oxidation state +3) to phosphate coupled to hydrogenogenesis in an obligate energetic dependency on a hydrogenotrophic methanogen, Methanoculleus sp. Physiology experiments, thermodynamic calculations, genomic annotation, and metaproteomics analysis collectively revealed a mechanism for syntrophic phosphite oxidation in Phox-21. In this pathway, electrons derived from phosphite drive H2 production via an electron-confurcating hydrogenase. Unlike previously characterized acetogenic phosphite oxidizers, Phox-21 is a mixotroph that assimilates acetate to form biomass. Lithosyntrophic phosphite oxidizers may play important roles both in transferring reducing equivalents as well as biologically available phosphorus to other members of their surrounding microbial communities, establishing a previously unrecognized metabolic and biogeochemical link between the phosphorus and carbon redox cycles in anoxic ecosystems.

Oxidation-Reduction↗

PubMed2026

Foundation model enables interpretable open and error-tolerant searching for mass spectrometry-based proteomics.

MOTIVATION: Mass spectrometry-based proteomics allows studying all proteins of a sample on a molecular level. However, mass spectra are noisy and contain complex patterns, making them inherently challenging to analyze with algorithmic approaches. In terms of the protein sequence landscape, most recent bottom-up MS-based proteomics studies consider either a diverse pool of post-translational modifications, employ large databases-as in metaproteomics or proteogenomics, study multiple isoforms of proteins, include unspecific cleavage sites or even combinations thereof. All this makes peptide and protein identifications challenging. RESULTS: Here, we present a foundation model, called yHydra, that jointly embeds spectra and peptides. This allows us to implement various downstream tasks and search modes in Euclidean space. We implement an open search which allows querying multiple ten-thousands of spectra against millions of peptides. Furthermore, we implement an error-tolerant search for identifying additional proteoforms that are not included in off-the-shelf reference proteomes. Our foundation model provides meaningful embeddings, as we interpret learned peptide embeddings in comparison to the peptide's physico-chemical properties. Hydra's open search, assigns delta masses to each identification which allows to unrestrictedly characterize post-translational modifications. The error-tolerant mode of yHydra can be used as post-processing to existing search engines or as a standalone. yHydra is evaluated on several real life data sets for the identification of modified peptide sequences and shows up to 25% increase in peptide identification at constant false discovery rate compared to the current state-of-the-art. AVAILABILITY AND IMPLEMENTATION: Code is available on Gitlab: https://gitlab.com/dacs-hpi/yHydra, and https://gitlab.com/dacs-hpi/yHydra_train.

Proteomics↗

PubMed2025

Bone Adhered Sediments as a Source of Target and Environmental DNA and Proteins.

In recent years, sediments from cave environments have provided invaluable insights into ancient hominids, as well as past fauna and flora. Unfortunately, however, sediments are not always collected during excavation. In this study, we analyzed an overlooked but abundant resource in archaeological collections - sediments adhered to bone. We performed metagenomics and metaproteomics analysis on sediment from several human skeletal elements, originating from Neolithic to Medieval sites in England. We were able to reconstruct a partial human genome, the genetic profile of which matches that recovered from the original skeletal element. Additionally, aDNA sequences matching the genomes of endogenous gut microbiome bacteria were identified. We also found the presence of genetic sequences corresponding to animals and plants. In particular, we managed to retrieve the partial genome and proteome of a Black Rat (Rattus rattus), sharing close genetic affinities to other medieval Rattus rattus. Our results demonstrate that material that is usually ignored or discarded, can be used to reveal information about the individual and the environmental conditions at the time of their death.

Animals↗