Biology subjects

Barylski, J.

Publications and source records attributed to Barylski, J..

6 recordsLinked to original sources

bioRxiv2026

First community challenge for automated virus taxonomy

The rapid rate of virus discovery renders manual curation by taxonomy experts increasingly impractical, creating a need for reliable software that can reproducibly assign viral contigs to taxa at all fifteen ranks of the virus taxonomy. We led an open community challenge for the computational taxonomic classification of viruses and assembled a dataset of virus sequences combining expert-curated and metagenomic sequences. Seventeen teams contributed a total of thirty-four automated, fully reproducible classification pipelines. Most tools correctly assigned viruses belonging to established species, genera, or families, but viruses that are unclassified at those lower ranks remain challenging. This study provides datasets, open-source software, novel approaches, and recommendations to benchmark computational taxonomic classification of viruses, and support organizing the many viruses discovered in big omics data.

microbiology↗

bioRxiv2024

Ultrafast and accurate sequence alignment and clustering of viral genomes

Viromics produces millions of viral genomes and fragments annually, overwhelming traditional sequence comparison methods. We introduce Vclust, a novel approach that determines average nucleotide identity by Lempel-Ziv parsing and clusters viral genomes with thresholds endorsed by authoritative viral genomics and taxonomy consortia. Vclust demonstrates superior accuracy and efficiency compared to existing tools, clustering millions of virus genomes in a few hours on a mid-range workstation.

bioinformatics↗

bioRxiv2023

Ultra-conserved bacteriophage genome sequence identified in 1300-year-old human paleofaeces

Bacteriophages are widely recognised as rapidly evolving biological entities. However, we discovered an ancient genome nearly identical to present-day Mushuvirus mushu, a phage that infects commensal microorganisms in the human gut ecosystem. The DNA damage patterns of this genome have confirmed its ancient origin, and, despite 1300 years of evolution, the ancient Mushuvirus genome shares 97.7% nucleotide identity with its modern counterpart, indicating a long-term relationship between the prophage and its host. We also reconstructed and authenticated 297 other phage genomes from the last 5300 years, including those belonging to unknown families. Our findings demonstrate the feasibility of reconstructing ancient phage genomes, expanding the known virosphere, and offering new insights into phage-bacteria interactions that cover several millennia.

microbiology↗

bioRxiv2021

Taxonomy-aware, sequence similarity ranking reliably predicts phage-host relationships

BackgroundSimilar regions in virus and host genomes provide strong evidence for phage-host interaction, and BLAST is one of the leading tools to predict prokaryotic hosts from phage sequences. However, BLAST-based host prediction has three major limitations: (i) top-scoring sequences do not always point to the actual host, (ii) mosaic phage genomes may match to many, typically related, bacteria, and (iii) phage and host sequences may diverge beyond the point where their relationship can be detected by a BLAST alignment. ResultsWe created an extension to BLAST, named Phirbo, that improves host prediction quality beyond what is obtainable from standard BLAST searches. The tool harnesses information concerning sequence similarity and bacteria relatedness to predict phage-host interactions. Phirbo was evaluated on three benchmark sets of known phage-host pairs, and it improved precision and recall by 11-40 percentage points over currently available, state-of-the-art, alignment-based, alignment-free, and machine learning host prediction tools. Moreover, the discriminatory power of Phirbo for the recognition of phage-host relationships surpassed the results of other tools by at least 10 percentage points (Area Under the Curve = 0.95), yielding a mean host prediction accuracy of 57% and 68% at the genus and family levels respectively, and drops by 12 percentage points when using only a fraction of phage genome sequences (3 kb). Finally, we provide insights into a repertoire of protein and ncRNA genes that are shared between phages and hosts and may be prone to horizontal transfer during infection. ConclusionsOur results suggest that Phirbo is a simple and effective tool for predicting phage host relationships.

bioinformatics↗

bioRxiv2020

RaFAH: A superior method for virus-host prediction

Viruses of prokaryotes are extremely abundant and diverse. Culture-independent approaches have recently shed light on the biodiversity these biological entities1,2. One fundamental question when trying to understand their ecological roles is: which host do they infect? To tackle this issue we developed a machine-learning approach named Random Forest Assignment of Hosts (RaFAH), based on the analysis of nearly 200,000 viral genomes. RaFAH outperformed other methods for virus-host prediction (F1-score = 0.97 at the level of phylum). RaFAH was applied to diverse datasets encompassing genomes of uncultured viruses derived from eight different biomes of medical, biotechnological, and environmental relevance, and was capable of accurately describing these viromes. This led to the discovery of 537 genomic sequences of archaeal viruses. These viruses represent previously unknown lineages and their genomes encode novel auxiliary metabolic genes, which shed light on how these viruses interfere with the host molecular machinery. RaFAH is available at https://sourceforge.net/projects/rafah/.

bioinformatics↗

bioRxiv2017

Genomic, proteomic, and phylogenetic analysis of spounaviruses indicates paraphyly of the order Caudovirales

It is almost a cliche that tailed bacteriophages of the order Caudovirales are the most abundant and diverse viruses in the world. Yet, their taxonomy still consists of a single order with just three families: Myoviridae, Siphoviridae, and Podoviridae. Thousands of newly discovered phage genomes have recently challenged this morphology-based classification, revealing that tailed bacteriophages are genomically even more diverse than once thought. Here, we evaluate a range of methods for bacteriophage taxonomy by using a particularly challenging group as an example, the Bacillus phage SPO1-related viruses of the myovirid subfamily Spounavirinae. Exhaustive phylogenetic and phylogenomic analyses indicate that the spounavirins are consistent with the taxonomic rank of family and should be divided into at least five subfamilies. This work is a case study for virus genomic taxonomy and the first step in an impending massive reorganization of the tailed bacteriophage taxonomy.

microbiology↗