Biology subjects

Heyer, R.

Publications and source records attributed to Heyer, R..

11 recordsLinked to original sources

bioRxiv2026

Curating MitoCore: A Standardized Small-Scale Human Metabolic Model as Platform for Proteomics Integration and Disease Modeling

MotivationCentral human metabolism powers cellular processes, yet its dysregulation in disease remains poorly understood. While comprehensive genome-scale metabolic models like Human-GEM are available, their size limits interpretability and computational efficiency. Conversely, the smaller MitoCore model is more manageable but lacks the standardized annotations and curated gene-protein-reaction (GPR) associations necessary for omics integration like protein-constrained modeling. Improving MitoCores annotation quality is therefore essential for its use in integrative workflows. ResultsWe systematically updated MitoCore to enhance compatibility with the protein-constrained modeling framework sMO-MENT. By restructuring legacy annotations and integrating data from Human-GEM and MitoMammal, we increased EC-codes from 354 to 593 and UniProt-annotated genes from 0 to 592. MitoCore captures central metabolic processes, confirmed by mapping its reactions to 51 of 106 metabolic KEGG modules. Integration of thrombocyte proteomics and experimental ATP data for original and curated models showed an increase in mapped proteins (228 to 294) and reactions with kcat values (295 to 310), adding 33 protein-constrained reactions. Consequently, prediction errors for exchange fluxes and ATP production decreased by 19% and 89%, respectively, with 100% of ATP predictions falling within the 95% confidence interval (compared to 16% for the original model). Finally, we implemented a continuous integration/continuous deployment pipeline for automated updates from future Human-GEM releases. These improvements provide a computationally efficient, well-annotated model for studying central metabolism across human cell types. Availability and ImplementationAll source code for reproducing results from this paper is available at https://doi.org/10.5281/zenodo.20813825.

Systems Biology↗

bioRxiv2025

A metaproteomics-based meta study of samples from patients with inflammatory bowel disease identifies potential markers for diagnosis and therapy monitoring

Inflammatory bowel disease (IBD) is a chronic intestinal disorder involving recurring inflammation and pronounced microbial dysbiosis. Comprehensive studies with large patient cohorts are required to Identify meaningful biomarker candidates for diagnosing and monitoring IBD. In this large-scale meta-study of over 600 samples based on fecal metaproteomics, our goal was to validate known biomarkers and discover new candidates. We performed bioinformatic reanalysis using the Mascot search engine and MMUPHin for batch effect correction as well as knowledge graph-enhanced data analysis. We identified 59 protein groups that varied primarily due to disease, rather than laboratory conditions. These included Alpha-1-acid glycoprotein, which was not reported in the original studies. Of these groups, 53 were differentially abundant in at least one of the two validation datasets. Additionally, 23 of the successfully validated protein groups, primarily from human neutrophil vesicles, were found to be significantly associated with remission during treatment in an independent dataset. This finding suggests their potential for disease monitoring. Validation in other disease contexts, such as non-alcoholic steatohepatitis, diabetes, and colorectal cancer, revealed the necessity of biomarker panels, because individual biomarkers could only distinguish IBD from specific conditions. Our results demonstrate the effectiveness of metaproteomics meta-analyses in discovering and validating biomarker panels and assessing their specificity for IBD. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/684320v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@18a6617org.highwire.dtl.DTLVardef@1349adaorg.highwire.dtl.DTLVardef@a27044org.highwire.dtl.DTLVardef@78aabe_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

A structured evaluation and benchmarking of Boolean logical modelling tools

Biomolecules form complex interaction systems at different biological levels. The dynamics behind the interactions of biomolecules result in cellular phenotypes and responses. Two typical biological interaction systems are signal transduction and gene regulatory networks. Boolean models characterise these systems components with binary state variables and their interactions with rules governing their influence on each other, without requiring kinetic and abundance information about these components. Tools are available to define, analyse, and manage these models, but there is a lack of an overview and evaluation of such tools quality and functionality. This work aims to facilitate the selection of software tools for Boolean modelling of signal transduction and gene regulatory networks by developing benchmark and evaluation criteria and applying them to the available tools. Twenty Boolean modelling tools were identified, which were assessed on their compliance to ten FAIR4RS (Findability, Accessibility, Interoperability, and Reusability for Research Software) aspects. Additionally, usability was assessed using a set of 25 developed sub-criteria. Furthermore, the functionalities were analysed, validated and the tools abilities to simulate and analyse Boolean models of different sizes were benchmarked. The evaluation demonstrated that, whilst the results produced by the 20 tools were completely consistent, their analytical functionalities and capabilities to simulate larger models varied widely. Size constraints for tools functionalities ranged between 25 and more than 10,000 nodes. Each tool only covered part of the available functionalities, and many exhibited deficiencies in FAIR4RS compliance and usability. Based on our analysis, we see great potential for researchers to improve the usability of their tools along the FAIR4RS aspects in the future, with average tools in our evaluation not yet addressing 40% of the aspects (20% for the best-performing one). The aim is to present a useful overview of usability and functionality of Boolean modelling tools and to show how they can be improved throughout the entire community. Author summaryOur study provides a set of criteria and a benchmarking toolkit for evaluating FAIR4RS and usability aspects as well as functionalities of Boolean modelling tools. We establish an overview of a wide range of Boolean modelling tools for signal transduction and gene regulatory network modelling, which is intended to make it easier for users to choose software according to their needs. This work empowers developers by offering crucial assets: a standardised evaluation criteria set for comparing their tools functionalities, usability, and FAIR4RS compliance throughout the community. Our models and benchmarking assets further enable developers to precisely determine and improve their softwares model size limitations.

systems biology↗

bioRxiv2025

Critical Assessment of MetaProteome Investigation 2 (CAMPI-2): Multi-laboratory assessment of sample processing methods to stabilize fecal microbiome for functional analysis

BackgroundFecal samples are widely used as a proxy for studying gut microbiome composition in both human and animal research. Fecal metaproteomics provides valuable insights by tracking changes in the relative abundance of microbial taxa and their protein functions. To ensure reliable results, it is crucial to minimize alterations in the metaproteome occurring from sample collection to protein extraction. Therefore, employing effective stabilization methods is essential to preserve the integrity of the fecal metaproteome from sample collection to laboratory analysis, particularly over long distances or when rapid freezing options are not readily available. In line with these needs, the second edition of the Critical Assessment of MetaProteome Investigation (CAMPI-2) was specifically focused on testing sample stabilization protocols to be applied before metaproteomic analysis. ResultsThis collaborative multicenter study assessed the ability of five different stabilization methods, based on two commercial devices and three specific reagents (acetone, lithium dodecyl sulfate, and an RNAlater-like buffer), respectively, to stabilize the fecal metaproteome during room-temperature storage (14 days) and shipment to mass spectrometry facilities. The five methods were tested simultaneously by eight different laboratories across Europe, using aliquots from the same fecal sample. After protein extraction and digestion, duplicate aliquots of the resulting peptides were analyzed independently by two mass spectrometry facilities at distinct international locations. Analysis of the mass spectrometric data using two different search engines revealed that the fecal metaproteome profile differed considerably depending on the stabilization method used in terms of richness, alpha and beta diversity, reproducibility, and quantitative distribution of main taxa and functions. Although each method showed unique strengths and weaknesses, a commercial swab-based device stood out for its remarkable reproducibility and ranked highest for most of the metrics measured. ConclusionsCAMPI-2 allowed a robust evaluation of five different methods for preserving fecal metaproteome samples. The present investigation provides useful data for the design of metaproteomics and multi-omics studies where fecal sampling cannot be immediately followed by long-term storage at -80{degrees}C. Further optimization of the tested protocols is necessary to improve stabilization efficiency and control bias in the taxonomic and functional profile of the gut microbiome.

microbiology↗

bioRxiv2024

Creating microbiome-model harmony between metaproteomics data and the ADM1da for a two-step anaerobic digester

The effective operation, planning, and optimization of renewable energy production in anaerobic digestion (AD) plants relies on advanced process models, such as the Anaerobic Digestion Model No. 1 (ADM1). This study applies an ADM1-based model (ADM1da) to simulate a two-step digester in an industrial setting. The data demonstrate that 2.6% of the methane is lost as a result of open hydrolysis. Conversely, the incorporation of a hydrolysis fermenter enhances methane production by an average of 2.5%. Although ADM1-like models are widely recognized for accurately representing anaerobic digestion processes, mechanistic insights into the microbiome involved have been limited by the absence of tools to analyze microbial composition and functionality at the time these models were developed. To overcome this limitation, we utilized a metaproteomics approach to assess the abundance and biomass-correlated activity of microbial groups as defined by the model, aiming to bridge the gap between microbial ecology and bioprocess engineering in AD systems. We also developed and evaluated a series of rules for associating particular microbial species with functional groups of the model. Our analysis demonstrates that while the model supports the presence of a stable microbiome composition in the main fermenter, it is difficult to capture the dynamic behavior observed in the hydrolysis fermenter. Furthermore, the actual AD microbiome displays a greater versatility than the model assumes, with microorganisms performing multiple functions rather than being restricted to single roles. In conclusion, this study identifies options for improving AD models and integrating comprehensive biological knowledge to further optimize the performance of anaerobic digesters. HighlightsO_LISimulations revealed 2.6 % methane volume loss attributed to open hydrolysis C_LIO_LIImplementation of a two-step process increased methane production by 2.5% C_LIO_LIIdentification of rules to map metaproteomics data to ADM1da C_LIO_LISimulations of ADM1da depict the dynamic in the main but not in the hydrolysis fermenter C_LIO_LIMicrobial species perform multiple functions not just one as assumed in the ADM1da C_LI

bioengineering↗

bioRxiv2024

Tracing active bugs in microbial communities by BONCAT and click chemistry-based enrichment of newly synthesised proteins

A comprehensive understanding of microbial community dynamics is fundamental to the advancement of environmental microbiology, human health, and biotechnology. Metaproteomics, i.e. the analysis of all proteins in a microbial community, provides insights into these complex systems. Microbial adaptation and activity depend to an important extent on newly synthesized proteins (nP), however, the distinction between nP and bulk proteins is challenging. The application of bioorthogonal non-canonical amino acid tagging (BONCAT) with click chemistry has demonstrated efficacy in the enrichment of nP in pure cultures. However, the transfer of this technique to microbial communities has proven challenging and has therefore not been used on microbial communities before. To address this, a new workflow with efficient and specific nP enrichment was developed using a laboratory-scale mixture of labelled E. coli and unlabelled yeast. This workflow was successfully applied to an anaerobic microbial community with initially low BONCAT efficiency. A substrate shift from glucose to ethanol selectively enriched nP with minimal background. The identification of bifunctional alcohol dehydrogenase and a syntrophic interaction between an ethanol-utilizing bacterium and two methanogens (hydrogenotrophic and acetoclastic) demonstrates the potential of metaproteomics targeting nP to trace microbial activity in complex microbial communities.

microbiology↗

bioRxiv2024

Detection, isolation and characterisation of phage-host complexes using BONCAT and click chemistry

Phages are viruses that infect prokaryotes and can shape microbial communities by lysis, thus offering applications in various fields. However, challenges exist in sampling, isolation, and predicting host specificity of phages. A new workflow using biorthogonal non-canonical amino acid tagging (BONCAT) and click chemistry (CC) allows combined analysis of phages and their hosts. Replication of phage {lambda} in Escherichia coli was selected as a model for workflow development. Specific labelling of phage {lambda} proteins with the non-canonical amino acid 4-azido-L-homoalanine (AHA) during infection of E. coli was confirmed by LC-MS/MS. Subsequent tagging of AHA with fluorescent dyes via CC allowed the visualization of phages adsorbed to the cell surface by fluorescence microscopy. Flow cytometry enabled the automated detection of these fluorescent phage-host complexes. AHA-labeled phages were tagged with biotin for purification by affinity chromatography. The biotinylated phages could be purified and were infectious despite biotinylation after purification. Applying this assay approach to environmental samples would enable host screening without cultivation. A flexible and powerful workflow was established to detect and enrich phages and their hosts. In the future, fluorescence-activated cell sorting or biotin purification could be used to isolate phage-host complexes in microbial communities.

microbiology↗

bioRxiv2021

MPA_Pathway_Tool: User-friendly, automatic assignment of microbial community data on metabolic pathways

MotivationTaxonomic and functional characterization of microbial communities from diverse environments such as the human gut or biogas plants by multi-omics methods plays an ever more important role. Researchers assign all identified genes, transcripts, or proteins to biological pathways to better understand the function of single species and microbial communities. However, due to the versatility of microbial metabolism and a still increasing number of new biological pathways, linkage to standard pathway maps such as the KEGG (Kyoto Encyclopedia of Genes and Genomes) central carbon metabolism is often problematic. ResultsWe successfully implemented and validated a new user-friendly, stand-alone web application, the MPA_Pathway_Tool. It consists of two parts, called Pathway-Creator and Pathway-Calculator. The Pathway-Creator enables an easy setup of user-defined pathways with specific taxonomic constraints. The Pathway-Calculator automatically maps microbial community data from multiple measurements on selected pathways and visualizes the results. Availability and ImplementationThe MPA_Pathway_Tool is implemented in Java and ReactJS. It is freely available on http://mpa-pathwaymapper.ovgu.de/. Further documentation and the complete source code are available on GitHub (https://github.com/danielwalke/MPA_Pathway_Tool). Contactdaniel.walke@ovgu.de, mailto:heyer@mpi-magdeburg.mpg.de heyer@mpi-magdeburg.mpg.de Supplementary InformationAdditional files and images are available at MDPI online. Highlightsuser-friendly generation of pathways, re-using of existent metabolic pathways, automated mapping of data

bioinformatics↗

bioRxiv2021

Triangulation of microbial fingerprinting in anaerobic digestion reveals consistent fingerprinting profiles

The anaerobic digestion microbiome has been puzzling us since the dawn of molecular methods for mixed microbial community analysis. Monitoring of the anaerobic digestion microbiome can either take place via a non-targeted holistic evaluation of the microbial community through fingerprinting or by targeted monitoring of selected taxa. Here, we compared four different microbial community fingerprinting methods, i.e., amplicon sequencing, metaproteomics, metabolomics and cytomics, in their ability to characterise the full-scale anaerobic digestion microbiome. Cytometric fingerprinting through cytomics reflects a, for anaerobic digestion, novel, single cell-based approach of direct microbial community fingerprinting by flow cytometry. Three different digester types, i.e., sludge digesters, digesters treating agro-industrial waste and dry anaerobic digesters, each reflected different operational parameters. The -diversity analysis yielded inconsistent results, especially for richness, across the different methods. In contrast, {beta}-diversity analysis resulted in comparable profiles, even when translated into phyla or functions, with clear separation of the three digester types. In-depth analysis of each methods features i.e., operational taxonomic units, metaproteins, metabolites, and cytometric traits, yielded certain similar features, yet, also some clear differences between the different methods, which was related to the complexity of the anaerobic digestion process. In conclusion, cytometric fingerprinting through flow cytometry is a reliable, fast method for holistic monitoring of the anaerobic digestion microbiome, and the complementary identification of key features through other methods could give rise to a direct interpretation of anaerobic digestion process performance.

bioengineering↗

bioRxiv2021

Integrated cycles for urban biomass as a strategy to promote a CO2-neutral society - A feasibility study

Progressive global warming is one of the biggest challenges civilization is facing today. The establishment of a carbon dioxide (CO2)-neutral society based on sustainable value creation cycles is required to stop this development. The Integrated Cycles for Urban Biomass (ICU) concept is a new concept towards a CO2-neutral society. The integration of closed biomass cycles into residential buildings enable efficient resource utilization and avoid transport of biowaste. In this scenario, biowaste is degraded on-site into biogas that is converted into heat and electricity. The liquid fermentation residues are upgraded by nitrification processes (e.g., by a soiling(R)-process, EP3684909A1) to refined fertilizer, which can be used subsequently in house-internal gardens to produce fresh food for residents. Whereas this scenario sounds promising, comprehensive evaluations of produced amounts of biogas and food, saved CO2 and costs as well as social-cultural aspects are lacking. To assess these points, a feasibility study was performed, which estimated the material and energy flows based on simulations of the biogas process and food production. The calculations show that a residential complex with 100 persons can generate 21 % of the annual power (electrical and heat) consumption from the accumulated biowaste. The nitrogen (N) in the liquid fermentation residues enables the production of up to 6.3 t of fresh mass of lettuce per year in a 70 m2 professional hydroponic production area. The amount of produced lettuce corresponds to the amount of calories required to feed four persons for one year. Additionally, due to the reduction of biowaste transport and the in-house food and fertilizer production, 6 468 kg CO2-equivalent (CO2-eq) per year are saved compared to a conventional building. While the ICU concept is technically feasible, its costs are still 1.5 times higher than the revenues. However, the model predictions show that the ICU concept becomes economically feasible in case food prices further increase and ICU is implemented at larger scale, e.g.; at the district level. Finally, this study demonstrates that the ICU implementation can be a worthwile contribution towards a sustainable CO2-neutral society and enable to decrease the demand for agricultural land.

bioengineering↗

bioRxiv2021

Critical Assessment of Metaproteome Investigation (CAMPI): a Multi-Lab Comparison of Established Workflows

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carried out the first community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluated the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observed that variability at the peptide level was predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappeared at the protein group level. While differences were observed for predicted community composition, similar functional profiles were obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

microbiology↗