Biology subjects

Yurkov, A.

Publications and source records attributed to Yurkov, A..

3 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↗

bioRxiv2023

Lifestyle transitions in basidiomycetous fungi are reflected by tRNA composition and translation efficiency of metabolic genes

Fungi are ubiquitous and inhabit every known terrestrial habitat. Pathogenic fungi are highly diverse, and recent years have seen an uprise in the emergence of new pathogens on crops, animals and humans. The order Trichosporonales (Tremellomycetes, Agaricomycotina, Basidiomycota) harbours saprobic and a few opportunistic human pathogenic species. These emerging pathogens cause superficial skin irritations, as well as invasive life-threatening infections. Yet, little is known about their evolution, ecology, virulence mechanisms and transition to pathogenic lifestyles. In this study we aimed to determine genomic signatures associated with lifestyle transitions, virulence and host/substrate specialization among 30 Trichosporonales species from a total of 41 genome sequences. We used comparative analyses of genome content, including gene functional categories, repetitive element content and tRNA composition among saprotrophic and reported opportunistic human pathogens. A genome-scale phylogenetic reconstruction revealed that even though the different genera are monophyletic, opportunistic pathogenic species are present in distantly-related clades. Statistical analyses showed that differences in genome structure among species did not correlate with predicted lifestyles. Intriguingly, we found that tRNA content varied widely across species (from 51 to 1455 manually curated tRNA genes). The expansion was independent from the phylogenetic structure. Opportunistic pathogenic species showed an overall increased efficiency in the translation of genes associated with host colonization (i.e. lipid metabolism), while exclusively saprotrophic species showed an increase translation efficiency for genes associated with a saprotrophic lifestyle (i.e. carbohydrate metabolism). This pattern was consistent among distantly-related saprotrophic and pathogenic Cryptococcus species (order Tremellales). In conclusion, our analyses link genomic information with ecology and fungal lifestyles across an entire order. We find evidence for an evolutionary scenario where distinct habitats select for an optimized translation of genes involved in successful proliferation in the respective habitat. We predict that lifestyles are not strictly defined by gene repertoires, but also by expression profiles in fungal pathogens.

genomics↗

bioRxiv2018

Long-read DNA metabarcoding of ribosomal rRNA in the analysis of fungi from aquatic environments

DNA metabarcoding is now widely used to study prokaryotic and eukaryotic microbial diversity. Technological constraints have limited most studies to marker lengths of ca. 300-600 bp. Longer sequencing reads of several 5 thousand bp are now possible with third-generation sequencing. The increased marker lengths provide greater taxonomic resolution and enable the use of phylogenetic methods of classifcation, but longer reads may be subject to higher rates of sequencing error and chimera formation. In addition, most well-established bioinformatics tools for DNA metabarcoding were originally 10 designed for short reads and are therefore not suitable. Here we used Pacifc Biosciences circular consensus sequencing (CCS) to DNA-metabarcode environmental samples using a ca. 4,500 bp marker that included most of the eukaryote ribosomal SSU and LSU rRNA genes and the ITS spacer region. We developed a long-read analysis pipeline that reduced error rates to levels 15 comparable to short-read platforms. Validation using fungal isolates and a mock community indicated that our pipeline detected 98% of chimeras de novo i.e., even in the absence of reference sequences. We recovered 947 OTUs from water and sediment samples in a natural lake, 848 of which could be classifed to phylum, 486 to family, 397 to genus and 330 to species. By 20 allowing for the simultaneous use of three global databases (Unite, SILVA, RDP LSU), long-read DNA metabarcoding provided better taxonomic resolution than any single marker. We foresee the use of long reads enabling the cross-validation of reference sequences and the synthesis of ribosomal rRNA gene databases. The universal nature of the rRNA operon and our recovery of >100 25 non-fungal OTUs indicate that long-read DNA metabarcoding holds promise for the study of eukaryotic diversity more broadly.

ecology↗