Biology subjects

Meyer, W.

Publications and source records attributed to Meyer, W..

7 recordsLinked to original sources

bioRxiv2026

The StrainDiscoveryDatabase: an open framework for standardized microbial strain data

The vast amount of existing data on microbial strains holds immense potential to revolutionize bioindustry through the application of Artificial Intelligence (AI). However, the training of robust predictive AI models requires large-scale, unified, and non-redundant microbial datasets, which is currently severely hindered by the deep fragmentation of the data and the existence of synonymous strain identifiers in different culture collections. To overcome these infrastructural bottlenecks, we have established the StrainDiscoveryDatabase (SDD), a comprehensive, machine-readable dataset encompassing over 6.2 million harmonized data points for 256,889 microbial strains. The SDD does not rely on its own data repository, but rather on existing data that is retrieved on the fly from highly curated databases. Through an automated pipeline phenotypic, genotypic, and contextual data are systematically retrieved via the Application Programming Interfaces (APIs) of the Bacterial Diversity database (BacDive), the Microbial Resource Research Infrastructure Information System (MIRRI-IS) and the catalogue of the DSMZ. In order to reliably resolve synonymous strain identifiers, the StrainInfo database and its identification tools are employed, enabling the accurate deduplication and unification of records from disparate sources. The resulting aggregated, globally unique dataset is provided in a highly standardized JSON format in strict adherence to the FAIR data principles. By bridging isolated database silos and linking distributed knowledge to discrete biological entities, the SDD provides a high-quality, foundational resource designed to accelerate trait-based strain discovery, large-scale comparative analysis, and machine learning applications, thereby supporting the translation of the extensive existing knowledge on microbial traits to bioindustrial applications.

microbiology↗

bioRxiv2025

Diet-Related Molecular Evolution Differs between Vertivores, Invertivores, and Combined Carnivores

Mammals have repeatedly evolved specialized diets, including a variety of predatory diets targeting different prey animals. Prior research has found differences in positive selection, gene family evolution and gene functional loss linked with diet, but has focused primarily on trophic level classifications of herbivory, carnivory, and omnivory. Here we divide "carnivores" into vertivores and invertivores, due to the differences in nutrient composition of those food sources. We find significant differences in evolutionary conservation of multiple genes and GO categories between vertivores and invertivores. Conservation relative to herbivores differs among vertivores, invertivores, and the combination of all carnivores. Lineages with predatory diets have increased conservation in lipid and amino acid metabolism relative to herbivores. Notably, we find that results in the combined carnivore-herbivore comparison are much more similar to those of the invertivore-herbivore comparison than the vertivore-herbivore comparison, which suggests that prior studies on carnivory may have been detecting signatures of selection related to invertivory.

genetics↗

bioRxiv2025

CRISPR screening reveals genetic regulators associated with the evolution of eye degeneration

Determining the genetic factors contributing to trait evolution is critical for understanding how and why traits evolve; however, establishing which genes underlie the evolution of complex traits remains challenging. The freshwater fish Astyanax mexicanus, a species that includes blind, cave-dwelling and eyed, surface-dwelling fish, is a powerful model for evolutionary genetics. While genetic mapping studies in this species previously identified genomic regions associated with cave-derived traits, few causative genes and genetic changes have been identified. Here, we develop methods to identify and rapidly functionally assess candidate genes in A. mexicanus, focusing on a defining trait of cave animals, eye loss. Candidate genes were identified based on whether they fell within an eye-related quantitative trait locus, were differentially expressed between surface and cave eyes, and showed evidence of positive selection in cavefish. Single-nucleus RNA-sequencing revealed that these candidate genes were expressed in multiple cell types during development, including those in different tissues of the eye. CRISPR-Cas9-based mutagenesis demonstrated that disruption of nine of these candidate genes in surface fish resulted in altered eye size. Perturbation of one of these genes, fibulin-7 (fbln7), revealed changes in eye size across multiple stages of eye development. Together, this work identified multiple genes associated with the evolution of eye degeneration in A. mexicanus. Further, this study represents a roadmap for rapid identification and functional assessment of candidate genes implicated in the evolution of traits in cavefish that can be applied to other evolutionary genetic models.

genetics↗

bioRxiv2021

Inferring species compositions of complex fungal communities from long- and short-read sequence data

BackgroundThe kingdom fungi is crucial for life on earth and is highly diverse. Yet fungi are challenging to characterize. They can be difficult to culture and may be morphologically indistinct in culture. They can have complex genomes of over 1 Gb in size and are still underrepresented in whole genome sequence databases. Overall their description and analysis lags far behind other microbes such as bacteria. At the same time, classification of species via high throughput sequencing without prior purification is increasingly becoming the norm for pathogen detection, microbiome studies, and environmental monitoring. However, standardized procedures for characterizing unknown fungi from complex sequencing data have not yet been established. ResultsWe compared different metagenomics sequencing and analysis strategies for the identification of fungal species. Using two fungal mock communities of 44 phylogenetically diverse species, we compared species classification and community composition analysis pipelines using shotgun metagenomics and amplicon sequencing data generated from both short and long read sequencing technologies. We show that regardless of the sequencing methodology used, the highest accuracy of species identification was achieved by sequence alignment against a fungi-specific database. During the assessment of classification algorithms, we found that applying cut-offs to the query coverage of each read or contig significantly improved the classification accuracy and community composition analysis without significant data loss. ConclusionOverall, our study expands the toolkit for identifying fungi by improving sequence-based fungal classification, and provides a practical guide for the design of metagenomics analyses.

bioinformatics↗

bioRxiv2019

CCMetagen: comprehensive and accurate identification of eukaryotes and prokaryotes in metagenomic data

High-throughput sequencing of DNA and RNA from environmental and host-associated samples (metagenomics and metatranscriptomics) is a powerful tool to assess which organisms are present in a sample. Taxonomic identification software usually align individual short sequence reads to a reference database, sometimes containing taxa with complete genomes only. This is a challenging task given that different species can share identical sequence regions and complete genome sequences are only available for a fraction of organisms. A recently developed approach to map sequence reads to reference databases involves weighing all high scoring read-mappings to the data base as a whole to produce better-informed alignments. We used this novel concept in read mapping to develop a highly accurate metagenomic classification pipeline named CCMetagen. Using simulated fungal and bacterial metagenomes, we demonstrate that CCMetagen substantially outperforms other commonly used metagenome classifiers, attaining a 3 - 1580 fold increase in precision and a 2 - 922 fold increase in F1 scores for species-level classifications when compared to Kraken2, Centrifuge and KrakenUniq. CCMetagen is sufficiently fast and memory efficient to use the entire NCBI nucleotide collection (nt) as reference, enabling the assessment of species with incomplete genome sequence data from all biological kingdoms. Our pipeline efficiently produced a comprehensive overview of the microbiome of two biological data sets, including both eukaryotes and prokaryotes. CCMetagen is user-friendly and the results can be easily integrated into microbial community analysis software for streamlined and automated microbiome studies.

bioinformatics↗

bioRxiv2019

Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities

High-throughput sequencing (HTS) enables the generation of large amounts of genome sequence data at a reasonable cost. Organisms in mixed microbial communities can now be sequenced and identified in a culture-independent way, usually using amplicon sequencing of a DNA barcode. Bulk RNA-seq (metatranscriptomics) has several advantages over DNA-based amplicon sequencing: it is less susceptible to amplification biases, it captures only living organisms, and it enables a larger set of genes to be used for taxonomic identification. Using a defined mock community comprised of 17 fungal isolates, we evaluated whether metatranscriptomics can accurately identify fungal species and subspecies in mixed communities. Overall, 72.9% of the RNA transcripts were classified, from which the vast majority (99.5%) were correctly identified at the species-level. Of the 15 species sequenced, 13 were retrieved and identified correctly. We also detected strain-level variation within the Cryptococcus species complexes: 99.3% of transcripts assigned to Cryptococcus were classified as one of the four strains used in the mock community. Laboratory contaminants and/or misclassifications were diverse but represented only 0.44% of the transcripts. Hence, these results show that it is possible to obtain accurate species- and strain-level fungal identification from metatranscriptome data as long as taxa identified at low abundance are discarded to avoid false-positives derived from contamination or misclassifications. This study therefore establishes a base-line for the application of metatranscriptomics in clinical mycology and ecological studies.

molecular biology↗

bioRxiv2017

Population Genomics Of Cryptococcus neoformans var. grubii Reveals New Biogeographic Relationships And Finely Maps Hybridization

Cryptococcus neoformans var. grubii is the causative agent of cryptococcal meningitis, a significant source of mortality in immunocompromised individuals, typically HIV/AIDS patients from developing countries. Despite the worldwide emergence of this ubiquitous infection, little is known about the global molecular epidemiology of this fungal pathogen. Here we sequence the genomes of 188 diverse isolates and characterized the major subdivisions, their relative diversity and the level of genetic exchange between them. While most isolates of C. neoformans var. grubii belong to one of three major lineages (VNI, VNII, and VNB), some haploid isolates show hybrid ancestry including some that appear to have recently interbred, based on the detection of large blocks of each ancestry across each chromosome. Many isolates display evidence of aneuploidy, which was detected for all chromosomes. In diploid isolates of C. neoformans var. grubii (serotype A/A) and of hybrids with C. neoformans var. neoformans (serotype A/D) such aneuploidies have resulted in loss of heterozygosity, where a chromosomal region is represented by the genotype of only one parental isolate. Phylogenetic and population genomic analyses of isolates from Brazil revealed that the previously African VNB lineage occurs naturally in the South American environment. This suggests migration of the VNB lineage between Africa and South America prior to its diversification, supported by finding ancestral recombination events between isolates from different lineages and regions. The results provide evidence of substantial population structure, with all lineages showing multi-continental distributions demonstrating the highly dispersive nature of this pathogen.\n\nAuthor SummaryCryptococcus neoformans var. grubii is a human fungal pathogen of immunocompromised individuals that has global clinical impact, causing half a million deaths per year. Substantial genetic substructure exists for this pathogen, with two lineages found globally (VNI, VNII) whereas a third has appeared confined to sub-Saharan Africa (VNB). Here, we utilized genome sequencing of a large set of global isolates to examine the genetic diversity, hybridization, and biogeography of these lineages. We found that while the three major lineages are well separated, recombination between the lineages has occurred, notably resulting in hybrid isolates with segmented ancestry across the genome. In addition, we showed that isolates from South America are placed within the VNB lineage, formerly thought to be confined to Africa, and that there is phylogenetic separation between these geographies that substantially expands the diversity of these lineages. Our findings provide a new framework for further studies of the dynamics of natural populations of C. neoformans var. grubii.

genomics↗