Biology subjects

Meyer, F.

Publications and source records attributed to Meyer, F..

At least 19 recordsLinked to original sources

bioRxiv2026

Deciphering efficient metabolic pathways in an anaerobic gut fungus coupled with a syntrophic methanogen

Anaerobic gut fungi (AGF) are an integral part of the herbivore gut microbiome, primary decomposers of lignocellulose, and play a crucial role in establishing foundational links of syntrophic associations. The syntrophy with methanogens appears beneficial for mitigating feedback inhibition and results in the augmentation of AGF activity. However, the thermodynamic advantages of the presence of methanogens to AGF remain poorly understood. This study explores the preferred pathways adopted by Cyllamyces sp. and Methanobrevibacter olleyae, using 13C-glucose as a substrate and spiked with malate and pyruvate in different experimental set-ups. The results indicated reduced biomass formation by Cyllamyces sp. in monoxenic culture with Methanobrevibacter olleyae compared to axenic AGF culture supplemented with glucose. Additionally, metabolic analyses revealed the pyruvate:ferredoxin oxidoreductase (PFO) as a key contributor to pyruvate metabolism. Malate supplementation notably enhanced the growth of Cyllamyces sp. and M. olleyae, whereas pyruvate supplementation enhanced the growth of Cyllamyces sp. only in axenic culture. This investigation provides insights into the preferred metabolic pathways operating in the hydrogenosomes of axenic anaerobic gut fungi (AGF) cultures and monoxenic AGF-methanogen co-cultures.

microbiology↗

bioRxiv2026

Cognitive Fitness in Ageing (COFITAGE): A Multimodal and Longitudinal Neuroimaging Dataset

Purpose: Brain aging involves interrelated changes in molecular processes, neuroinflammatory mechanisms, brain macro- and microstructure, sleep physiology, and cognition. The 50 to 70 years age range represents a critical transition period, in which these subtle alterations may precede measurable cognitive decline and the onset of clinical neurodegenerative disease. To allow systematic investigation of these early alterations and the subsequent progression in brain aging, we provide an open-access data resource from a multidisciplinary longitudinal study integrating neuroimaging, genetics, sleep, and neuropsychological phenotyping with assessments at baseline and at 2-year follow-up. Acquisition and Validation Methods: The baseline cohort comprises 101 community-dwelling participants (50-69 years old) who underwent magnetic resonance imaging (MRI) using a 3T protocol that included high-resolution structural imaging (T1- and T2-weighted), quantitative multi-parametric acquisitions with B1 mapping, and multi-shell diffusion-weighted imaging. Moreover, positron emission tomography (PET) imaging was performed using [18F]Flutemetamol or [18F]Florbetapir (amyloid-beta tracers) in all participants, with a subset also undergoing [18F]THK-5351 PET (tau-related/neuroinflammation). The dataset was complemented by extensive phenotypic data, including sleep and neuropsychological assessments, and by genotype data through genetic analysis. 66 participants underwent a 2-year cognitive follow-up, enabling longitudinal analyses of cognitive trajectories. Data acquisition and curation were performed using standardized procedures, with systematic quality control to support reliable cross-sectional and longitudinal analyses. Data Format and Usage Notes: All data are distributed in a BIDS-compliant format, and released in open-access (EBRAINS). Potential Applications: This dataset supports multimodal analyses, allowing the identification of interpretable patterns characterizing brain aging from multiple perspectives. It enables the comparison of different models to derive (semi)quantitative MRI parameters, the discovery of imaging biomarkers associated with early cognitive decline, and the monitoring or prediction of brain aging progression. In addition, it offers focused coverage of adults aged 50-70 years, which is often underrepresented in existing healthy subjects public datasets.

neuroscience↗

bioRxiv2026

ThermoFusion: A Multimodal Deep Learning Framework for Generalizable Prediction of Enzyme Thermostability

Protein thermostability is a critical property for both industrial and biomedical enzyme applications, yet experimental evaluation of mutation-induced stability changes remains laborious and costly. Here, we present ThermoFusion, a hybrid deep learning framework that integrates 3D protein structure embeddings from ThermoMPNN with sequence-based embeddings from the pretrained protein language model ESM2 to predict the effects of single-point mutations on protein stability ({Delta}{Delta}G). ThermoFusion exhibits robust generalization, maintaining high predictive accuracy across out of distribution sequences with low identity to the training set - a scenario where many other machine learning models, including ThermoMPNN and state-of-the-art tools, perform poorly due to reliance on memorization. Benchmarking on a curated enzyme dataset comprising of 105 enzymes and 3144 mutations shows that ThermoFusion reliably identifies stabilizing mutations while accurately predicting stability for enzymes beyond its training set. These results establish ThermoFusion as a powerful tool for rational enzyme design beyond its training set.

bioinformatics↗

bioRxiv2026

DLC1 loss drives multicellular streaming invasion by enforcing spatially coordinated Rho and β1 integrin signaling

Efficient cancer cell invasion requires coordinated control of actomyosin contractility, extracellular matrix (ECM) engagement and remodeling, yet how these processes are integrated in complex, three-dimensional (3D) environments remains unclear. Here, we identify the tumor suppressor and RhoGAP protein DLC1 as molecular brake on multicellular streaming invasion in collagen-rich ECM. Using CRISPRoff-engineered breast cancer spheroids, DLC1 reconstitution models and patient-derived organoids embedded in collagen gels, we show that DLC1 downregulation promotes an efficient multicellular streaming phenotype. This invasion program requires matrix metalloproteinase activity, {beta}1 integrin engagement and Rho-ROCK-dependent actomyosin contractility. Mechanistically, DLC1 downregulation stabilized the rear-polarization of RhoA activity and increased {beta}1 integrin abundance, plasma membrane localization and activation. Separation-of-function mutants revealed that DLC1 restrains invasion through a dual mechanism: its RhoGAP activity limited actomyosin-driven streaming, whereas its LD-like talin-binding motif controlled {beta}1 integrin enrichment at the plasma membrane. Together, our findings provide a molecular basis for the prominent role of DLC1 as a metastasis suppressor.

Cancer Biology↗

bioRxiv2026

Differential Gene Expression in the Tropical House Cricket and Its Iridovirus in Healthy versus Diseased Specimens

The tropical house cricket, Gryllodes sigillatus, is a mass-produced insect that is used as a protein source for pets and livestock. However, intensive mass-rearing conditions, coupled with high genetic relatedness, create an ideal environment for the spread of pathogenic microbes that severely impact production. Cricket iridovirus (CrIV) is a pathogen that impedes cricket growth and causes significant losses for cricket farmers. Interestingly, recent studies have shown that CrIV is often present asymptomatically, yet the molecular basis of the emergence of disease symptoms remains unknown. To address this, we sampled healthy and diseased crickets and examined differences in cricket and CrIV gene expression via RNAseq. Using differential gene expression analysis and functional enrichment analysis, we found significant differences in host and viral gene expression between healthy and diseased crickets, including genes involved in immunity. Interestingly, while we observed high CrIV gene expression across the entire CrIV genome in sick populations, healthy asymptomatic populations showed elevated expression at a single viral locus. Our results shed light not only on the cricket immune response to CrIV infection but also identify a viral gene that is highly expressed during covert infections, suggesting its potential role in suppressing the hosts immune response. These findings enhance our understanding of how CrIV interacts with our cricket host, providing essential insights for developing targeted strategies to manage CrIV outbreaks in cricket mass-rearing facilities.

bioinformatics↗

bioRxiv2026

A Perfect Soldier: the black soldier fly as a microbial-mediated physiological resilience model .

Understanding the complex interplay between a host, its diet, and its microbiome is crucial for comprehending an organisms health and adaptability. Diet impacts both the host and microbiome, which then influence each other. We used black soldier fly larvae (Hermetia illucens) as a model to investigate this tripartite interaction due to its resilience and bioconversion capabilities. We analyzed life-history traits and metatranscriptomics in larvae fed three diets: carbohydrate-rich, protein-rich, and balanced. Our results showed that dietary macronutrients correlated with shifts in the microbial community and gene expression. The carbohydrate-rich diet, in particular, led to increased microbial diversity and carbohydrate metabolism transcripts. However, this diet also negatively affected larval weight and development, suggesting potential host control over the microbiome. Overall, black soldier fly performance was highest on the balanced diet. This study highlights the black soldier flys resilience and its value as a model for exploring host-diet-microbe interactions. Significance StatementUnderstanding the intricate interplay between an organism, its diet, and its microbiome is fundamental to health and adaptability. This complex tripartite relationship, where dietary macronutrients influence microbial communities and their gene expression, while the host maintains control, is crucial for addressing global challenges from sustainable food systems to personalized medicine. Using the black soldier fly as a resilience model, our metatranscriptomic study reveals how specific dietary shifts impact both host and microbial gene expression, providing mechanistic insights into nutrient utilization and adaptability with broad implications for diverse biological systems, including animals and humans.

systems biology↗

bioRxiv2025

PKD3 localizes to late endosomes to maintain Rab7-dependent endolysosomalhomeostasis

Protein kinase D3 (PKD3) is an important regulator of triple-negative breast cancer (TNBC) progression by promoting invasion, proliferation, and stem cell maintenance. However, the mechanism underlying these cellular functions has remained unclear. Here, we report that endogenous PKD3 localizes to Rab7/Lamp1-positive vesicles in MDA-MB-231 cells cultured on stiff matrices. Notably, upon PKD3 depletion the size of Rab7-positive vesicles is smaller. This correlates with impaired endosomal acidification, which is associated with dysregulated Wnt signaling and a decline in stemness. Our data thus unveil a previously unrecognized role of PKD3 in regulating endolysosomal dynamics that contributes to the maintenance of the cancer stem cell population.

cell biology↗

bioRxiv2024

GEMS: A Generalizable GNN Framework For Protein-Ligand Binding Affinity Prediction Through Robust Data Filtering and Language Model Integration

The field of computational drug design requires accurate scoring functions to predict binding affinities for protein-ligand interactions. However, train-test data leakage between the PDBbind database and the CASF benchmark datasets has significantly inflated the performance metrics of currently available deep-learning-based binding affinity prediction models, leading to overestimation of their generalization capabilities. We address this issue by proposing PDBbind CleanSplit, a training dataset curated by a novel structure-based filtering algorithm that eliminates train-test data leakage as well as redundancies within the training set. Retraining current top-performing models on CleanSplit caused their benchmark performance to drop significantly, indicating that the performance of existing models is largely driven by data leakage. In contrast, our graph neural network model for efficient molecular scoring (GEMS) maintains high benchmark performance when trained on CleanSplit. Leveraging a sparse graph modeling of protein-ligand interactions and transfer learning from language models, GEMS is able to generalize to strictly independent test datasets.

bioinformatics↗

bioRxiv2024

RiboSnake - a user-friendly, robust, reproducible, multipurpose and documentation-extensive pipeline for 16S rRNA gene microbiome analysis

BackgroundNext-generation sequencing for assaying microbial communities has become a standard technique in recent years. However, the initial investment required into in-silico analytics is still quite significant, especially for facilities not focused on bioinformatics. With the rapid decline in costs and growing adoption of sequencing-based methods in a number of fields, validated, fully automated, reproducible and yet flexible pipelines will play a greater role in various scientific fields in the future. ResultsWe present RiboSnake, a validated, automated, reproducible QIIME2-based analysis pipeline implemented in Snakemake for the computational analysis of 16S rRNA gene amplicon sequencing data. The pipeline comes with pre-packaged validated parameter sets, optimized for different sample types. The sets range from complex environmental samples to patient data. The configuration packages can be easily adapted and shared, requiring minimal user input. ConclusionRiboSnake is a new alternative for researchers employing 16S rRNA gene amplicon sequencing and looking for a customizable and yet user-friendly pipeline for microbiome analysis with in-vitro validated settings. The complete analysis generated with a fully automated pipeline based on validated parameter sets for different sample types is a significant improvement to existing methods. The workflow repository can be found on GitHub (https://github.com/IKIM-Essen/RiboSnake).

bioinformatics↗

bioRxiv2024

A roadmap for fair reuse of public microbiome data

Science benefits from rapid, open data sharing but samples for sequencing data are expensive for data creators to acquire and process. Current guidelines for data reuse were established two decades ago, when databases were several million times smaller, necessitating an update. This article presents a roadmap to establish best practices for sequence data reuse, developed in consultation with a data consortium of 167 microbiome scientists. It introduces a Data Reuse Information tag (DRI) for public sequencing data, which will be associated with at least one Open Researcher and Contributor ID (ORCID) account. The machine-readable DRI tag indicates that the data creators prefer to be contacted prior to data reuse, and simultaneously provides data consumers with a mechanism to get in touch with the data creators. Ideally, the DRI will facilitate and foster collaborations, and serve as a guideline that can be expanded to other data types.

microbiology↗

bioRxiv2024

Detection of known and novel virus sequences in the black solider fly and expression of host antiviral pathways

Mass rearing of animals in close quarters can be highly conducive to microbe transmission, including pathogens. This has been shown multiple times in the case of important industrial insects such as crickets, silkworms, and honeybees. One industrial insect of increasing importance is the black soldier fly (Diptera: Hermetia illucens), as it can convert organic waste into high quality protein and fatty acids. Along with this, they take up far less space than traditional protein sources, as millions of black soldier flies can be reared in a relatively small facility. Because of this, there is a growing interest in the pathogens that could impact black soldier fly rearing efforts. So far, only three black soldier fly-associated viruses have been identified. We used metatranscriptomic sequencing to survey black soldier fly guts, frass, and diet for viruses. We detected sequences from two novel viruses. One, which we name Hermetia illucens sigma-like virus 1, is phylogenetically related to viruses of the genus Sigmavirus, which have been highly studied in Drosophila. The other novel virus, which we name Hermetia illucens toti-like virus 2, is the second toti-like virus to be described in the black soldier fly. We also detected two black soldier fly-associated viruses previously identified by our group: BSF nairo-like virus, and BSF uncharacterized bunya-like virus. Consistent with our previous study, these two viruses are found primarily in frass samples and occur together more often than expected at random. When analyzing host transcription, we found significant differences in gene expression for eight candidate antiviral genes in black soldier fly when comparing samples with and without viral sequences. Our results suggest that black soldier fly-virus interactions are ongoing, and they could be of interest to black soldier fly producers.

bioinformatics↗

bioRxiv2024

Assessing computational predictions of antimicrobial resistance phenotypes from microbial genomes

The advent of rapid whole-genome sequencing has created new opportunities for computational prediction of antimicrobial resistance (AMR) phenotypes from genomic data. Both rule-based and machine learning (ML) approaches have been explored for this task, but systematic benchmarking is still needed. Here, we evaluated four state-of-the-art ML methods (Kover, PhenotypeSeeker, Seq2Geno2Pheno, and Aytan-Aktug), an ML baseline, and the rule-based ResFinder by training and testing each of them across 78 species-antibiotic datasets, using a rigorous benchmarking workflow that integrates three evaluation approaches, each paired with three distinct sample splitting methods. Our analysis revealed considerable variation in the performance across techniques and datasets. Whereas ML methods generally excelled for closely related strains, ResFinder excelled for handling divergent genomes. Overall, Kover most frequently ranked top among the ML approaches, followed by PhenotypeSeeker and Seq2Geno2Pheno. AMR phenotypes for antibiotic classes such as macrolides and sulfonamides were predicted with the highest accuracies. The quality of predictions varied substantially across species-antibiotic combinations, particularly for beta-lactams; across species, resistance phenotyping of the beta-lactams compound, aztreonam, amox-clav, cefoxitin, ceftazidime, and piperacillin/tazobactam, alongside tetracyclines demonstrated more variable performance than the other benchmarked antibiotics. By organism, C. jejuni and E. faecium phenotypes were more robustly predicted than those of Escherichia coli, Staphylococcus aureus, Salmonella enterica, Neisseria gonorrhoeae, Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, Streptococcus pneumoniae, and Mycobacterium tuberculosis. In addition, our study provides software recommendations for each species-antibiotic combination. It furthermore highlights the need for optimization for robust clinical applications, particularly for strains that diverge substantially from those used for training.

bioinformatics↗

bioRxiv2023

Do bed bugs transmit human viruses, or do humans transmit bed bug viruses? A worldwide survey of the bed bug RNA virosphere

Bed bugs (Hemiptera: Cimicidae) are a globally distributed hematophagous pest that routinely feed on humans. Unlike many blood-sucking arthropods, they have never been linked to disease transmission in a natural setting, and despite interest in their role as disease vectors, little is known about the viruses that bed bugs naturally harbor. Here, we present a global-scale survey of the bed bug RNA virosphere. We sequenced the metatranscriptomes of 22 individual bed bugs (Cimex lectularius and Cimex hemipterus) from 8 locations around the world. We detected sequences from two known bed bug viruses (Shuangao bedbug virus 1 and Shuangao bedbug virus 2) which extends their geographical range and the host range of Shuangao bedbug virus 1 to Cimex lectularius. We identified three novel bed bug virus sequences from a tenui-like virus (Bunyavirales), a toti-like virus (Ghabrivirales), and a luteo-like virus (Tolivirales). Interestingly, some of the bed bug viruses branch near to insect-transmitted plant-infecting viruses, opening questions regarding the evolution of plant virus infection. When we analyzed the putative viral sequences by their hosts collection location, we found unexpected patterns of geographical diversity that may reflect humans role in bed bug dispersal. Additionally, we investigated the effect that Wolbachia, the primary bed bug endosymbiont, may have on viral abundance and found that Wolbachia infection neither promotes nor inhibits viral infection. Finally, our results provide no evidence that bed bugs transmit any known human pathogenic viruses.

bioinformatics↗

bioRxiv2023

Bioinformatic Surveillance Leads to Discovery of Two Novel Putative Bunyaviruses Associated with Black Soldier Fly

The black soldier fly (Hermetia illucens, BSF) has emerged as an industrial insect of high promise because of its ability to convert organic waste into nutritious feedstock, making it an environmentally sustainable alternative protein source. As global interest rises, rearing efforts are also upscaled, which is highly conducive to pathogen transmission. Viral epidemics have stifled mass-rearing efforts of other insects of economic importance, such as crickets, silkworms, and honeybees, but little is known about the viruses that associate with BSF. Although it is thought that BSF are unusually resistant to pathogens because of their expansive antimicrobial gene repertoire, surveillance techniques could be useful to identify emerging pathogens and common BSF microbes. In this study, we used high-throughput sequencing data to survey BSF larvae and frass samples, and we identified two novel bunyavirus-like sequences. Our phylogenetic analyses grouped one in the family Nairoviridae, and the other with two unclassified bunyaviruses. We describe these putative novel viruses as BSF Nairovirus-like 1 and BSF uncharacterized bunyavirus-like 1. We identified candidate segments for the full BSF Nairovirus-like 1 genome using a technique based on transcript co-occurrence, and only a partial genome for BSF uncharacterized bunyavirus-like 1. These results emphasize the value of routine BSF colony surveillance and add to the number of viruses associated with BSF.

bioinformatics↗

bioRxiv2022

The GEF-GAP pair Solo and DLC3 balances Rho activity during endocytic transport

The control of intracellular membrane trafficking by Rho GTPases is central to cellular homeostasis. How defined pairs of guanine nucleotide exchange factors (GEFs) and GTPase-activating proteins (GAPs) come together to locally balance GTPase activation cycles in this process is nevertheless largely unclear. By performing a microscopy-based RNAi screen we here identify the RhoGEF protein Solo as a counterpart of DLC3, a RhoGAP protein with established roles in membrane trafficking. Biochemical, imaging and optogenetics assays further uncover Solo as a novel regulator of endosomal RhoB. Remarkably, we find that the interplay between Solo and DLC3 controls not only the activity but also total protein levels of RhoB. Together, the results of our study uncover the first functionally connected RhoGAP-RhoGEF pair at endomembranes and place the Solo-DLC3 axis at the core of endocytic trafficking.

cell biology↗

bioRxiv2021

Critical Assessment of Metagenome Interpretation - the second round of challenges

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the community-driven initiative for the Critical Assessment of Metagenome Interpretation (CAMI). In its second challenge, CAMI engaged the community to assess their methods on realistic and complex metagenomic datasets with long and short reads, created from [~]1,700 novel and known microbial genomes, as well as [~]600 novel plasmids and viruses. Altogether 5,002 results by 76 program versions were analyzed, representing a 22x increase in results. Substantial improvements were seen in metagenome assembly, some due to using long-read data. The presence of related strains still was challenging for assembly and genome binning, as was assembly quality for the latter. Taxon profilers demonstrated a marked maturation, with taxon profilers and binners excelling at higher bacterial taxonomic ranks, but underperforming for viruses and archaea. Assessment of clinical pathogen detection techniques revealed a need to improve reproducibility. Analysis of program runtimes and memory usage identified highly efficient programs, including some top performers with other metrics. The CAMI II results identify current challenges, but also guide researchers in selecting methods for specific analyses.

bioinformatics↗

bioRxiv2020

Tutorial: Assessing metagenomics software with the CAMI benchmarking toolkit

Computational methods are key in microbiome research, and obtaining a quantitative and unbiased performance estimate is important for method developers and applied researchers. For meaningful comparisons between methods, to identify best practices, common use cases, and to reduce overhead in benchmarking, it is necessary to have standardized data sets, procedures, and metrics for evaluation. In this tutorial, we describe emerging standards in computational metaomics benchmarking derived and agreed upon by a larger community of researchers. Specifically, we outline recent efforts by the Critical Assessment of Metagenome Interpretation (CAMI) initiative, which supplies method developers and applied researchers with exhaustive quantitative data about software performance in realistic scenarios and organizes community-driven benchmarking challenges. We explain the most relevant evaluation metrics to assess metagenome assembly, binning, and profiling results, and provide step-by-step instructions on how to generate them. The instructions use simulated mouse gut metagenome data released in preparation for the second round of CAMI challenges and showcase the use of a repository of tool results for CAMI data sets. This tutorial will serve as a reference to the community and facilitate informative and reproducible benchmarking in microbiome research.

bioinformatics↗

bioRxiv2020

Time-course Profiling of Bovine Herpesvirus Type 1 and Host Cell Transcriptomes using Multiplatform Sequencing

Long-read sequencing (LRS) has become a standard approach for transcriptome analysis in recent years. This technology is also used for the identification and annotation of genes of various organisms, including viruses. Bovine herpesvirus type 1 (BoHV-1) is an important pathogen of cattle worldwide. However, the transcriptome of this virus is still largely unannotated. This study reports the profiling of the dynamic lytic transcriptome of BoHV-1 using two long-read sequencing (LRS) techniques, the Oxford Nanopore Technology (ONT) MinION, and the Illumina LoopSeq synthetic LRS methods, using multiple library preparation protocols. In this work, we annotated viral mRNAs and non-coding transcripts, and a large number of transcript isoforms, including transcription start and end sites, as well as splice variants of BoHV-1. Very long polycistronic and complex viral transcripts were also detected. Our analysis demonstrated an extremely complex pattern of transcriptional overlaps formed by transcriptional read-throughs or overlapping the 5-untranslated regions of divergently-oriented transcripts. The impact of the viral infection on the host cell transcriptome was also assessed. Our results demonstrate that genes associated with antiviral response as well as viral transcription and translation are upregulated.

genomics↗