Biology subjects

Levy Karin, E.

Publications and source records attributed to Levy Karin, E..

8 recordsLinked to original sources

bioRxiv2026

BFVD v3-UniProt-complete, improved viral protein structure predictions

The Big Fantastic Virus Database (BFVD) v3 is the most comprehensive resource for ColabFold-AlphaFold2-predicted viral protein structures. It holds 5,776,417 structures of nearly all viral sequences in UniProt 2025_03, a 16.4-fold increase compared to the representative-only catalogs of BFVD v1 and v2. Structure prediction quality has also improved, with high-confidence predictions accounting for 75.3% of BFVD v3 entries. This is due to Logan's enormous sequence assembly, now mined for the entire BFVD v3 instead of only for shallow alignments, alongside continued prediction quality improvements. BFVD v3 covers 72.7% of ICTV's virus species, 1.54-fold more than BFVD v2. With this version, the fraction of fully covered viral reference proteomes increases from 1.5% to 72.6%. BFVD v3 thus brings us closer to a structural catalog of the known virosphere and is freely available at bfvd.steineggerlab.workers.dev and bfvd.foldseek.com.

bioinformatics↗

bioRxiv2024

BFVD - a large repository of predicted viral protein structures

The AlphaFold Protein Structure Database (AFDB) is the largest repository of accurately predicted structures with taxonomic labels. Despite providing predictions for over 214 million UniProt entries, the AFDB does not cover viral sequences, severely limiting their study. To bridge this gap, we created the Big Fantastic Virus Database (BFVD), a repository of 351,242 protein structures predicted by applying ColabFold to the viral sequence representatives of the UniRef30 clusters. BFVD holds a unique repertoire of protein structures as over 63% of its entries show no or low structural similarity to existing repositories. We demonstrate how BFVD substantially enhances the fraction of annotated bacteriophage proteins compared to sequence-based annotation using Bakta. In that, BFVD is on par with the AFDB, while holding nearly three orders of magnitude fewer structures. BFVD is an important virus-specific expansion to protein structure repositories, offering new opportunities to advance viral research. BFVD is freely available at https://bfvd.steineggerlab.workers.dev/

bioinformatics↗

bioRxiv2023

Petascale Homology Search for Structure Prediction

The recent CASP15 competition highlighted the critical role of multiple sequence alignments (MSAs) in protein structure prediction, as demonstrated by the success of the top AlphaFold2-based prediction methods. To push the boundaries of MSA utilization, we conducted a petabase-scale search of the Sequence Read Archive (SRA), resulting in gigabytes of aligned homologs for CASP15 targets. These were merged with default MSAs produced by ColabFold-search and provided to ColabFold-predict. By using SRA data, we achieved highly accurate predictions (GDT_TS > 70) for 66% of the non-easy targets, whereas using ColabFold-search default MSAs scored highly in only 52%. Next, we tested the effect of deep homology search and ColabFolds advanced features, such as more recycles, on prediction accuracy. While SRA homologs were most significant for improving ColabFolds CASP15 ranking from 11th to 3rd place, other strategies contributed too. We analyze these in the context of existing strategies to improve prediction.

bioinformatics↗

bioRxiv2023

Identification of selective sweeps in bacteria

Selective sweeps occur when a beneficial mutation spreads rapidly throughout the population due to natural selection. Searching for selective sweeps has proved to be one of the most fruitful ways to detect the footprints selection leaves on the genome. With a plethora of detection tools, the study of selective sweeps in eukaryotic systems is a well-established field of research. However, the search for fragment-specific selective sweeps among bacterial strains received little to no attention so far. In our work, we demonstrate that inter-strains locus-specific selective sweeps can be detected in bacteria. We introduce the SINCOPA algorithm, the first phylogeny-based method for soft and incomplete selective sweeps detection. We use SINCOPA to explore inter-strains locus-specific selective sweeps in a dataset containing more than 500 microbial genomes. We observe strong evidence in several loci for locus-specific selective sweeps including genes involved in biofilm formation and others that are related to coping with various unfavorable environmental conditions. SINCOPA is freely accessible as a user-friendly web server application at https://sincopa.tau.ac.il/.

bioinformatics↗

bioRxiv2020

Fast and sensitive taxonomic assignment to metagenomic contigs

MMseqs2 taxonomy is a new tool to assign taxonomic labels to metagenomic contigs. It extracts all possible protein fragments from each contig, quickly retains those that can contribute to taxonomic annotation, assigns them with robust labels and determines the contigs taxonomic identity by weighted voting. Its fragment extraction step is suitable for the analysis of all domains of life. MMseqs2 taxonomy is 2-18x faster than state-of-the-art tools and also contains new modules for creating and manipulating taxonomic reference databases as well as reporting and visualizing taxonomic assignments. AvailabilityMMseqs2 taxonomy is part of the MMseqs2 free open-source software package available for Linux, macOS and Windows at https://mmseqs.com. Contacteli.levy.karin@gmail.com

bioinformatics↗

bioRxiv2020

SpacePHARER: Sensitive identification of phages from CRISPR spacers in prokaryotic hosts

SpacePHARER (CRISPR Spacer Phage-Host Pair Finder) is a sensitive and fast tool for de novo prediction of phage-host relationships via identifying phage genomes that match CRISPR spacers in genomic or metagenomic data. SpacePHARER gains sensitivity by comparing spacers and phages at the protein level, optimizing its scores for matching very short sequences, and combining evidence from multiple matches, while controlling for false positives. We demonstrate SpacePHARER by searching a comprehensive spacer list against all complete phage genomes.

bioinformatics↗

bioRxiv2020

A codon model for associating phenotypic traits with altered selective patterns of sequence evolution

Changes in complex phenotypes, such as pathogenicity levels, trophic lifestyle, and habitat shifts are brought on by multiple genomic changes: sub- and neofunctionalization, loss of function, and levels of gene expression. Thus, detecting the signature of selection in coding sequences and associating it with shifts in phenotypic state can unveil the genes underlying complex traits. Phylogenetic branch-site codon models are routinely applied to detect changes in selective patterns along specific branches of the phylogeny. These methods rely on a pre-specified partition of the phylogeny to branch categories, thus treating the course of trait evolution as fully resolved and assuming that transitions in phenotypic states have occurred only at speciation events. Here we present TraitRELAX, a new phylogenetic model that alleviates these strong assumptions by explicitly accounting for the uncertainty in the evolution of both trait and coding sequences. This joint statistical framework enables the detection of changes in selection intensity upon repeated trait transitions. We evaluated the performance of TraitRELAX using simulations and then applied it to two case studies. Using TraitRELAX, we found an intensification of selection in the SEMG2 gene in polygynandrous species of primates compared to species of other mating forms, as well as changes in the intensity of purifying selection operating on sixteen bacterial genes upon transitioning from free-living to an endosymbiotic lifestyle.

evolutionary biology↗

bioRxiv2019

MetaEuk - sensitive, high-throughput gene discovery and annotation for large-scale eukaryotic metagenomics

BackgroundMetagenomics is revolutionizing the study of microorganisms and their involvement in biological, biomedical, and geochemical processes, allowing us to investigate by direct sequencing a tremendous diversity of organisms without the need for prior cultivation. Unicellular eukaryotes play essential roles in most microbial communities as chief predators, decomposers, phototrophs, bacterial hosts, symbionts and parasites to plants and animals. Investigating their roles is therefore of great interest to ecology, biotechnology, human health, and evolution. However, the generally lower sequencing coverage, their more complex gene and genome architectures, and a lack of eukaryote-specific experimental and computational procedures have kept them on the sidelines of metagenomics. ResultsMetaEuk is a toolkit for high-throughput, reference-based discovery and annotation of protein-coding genes in eukaryotic metagenomic contigs. It performs fast searches with 6-frame-translated fragments covering all possible exons and optimally combines matches into multi-exon proteins. We used a benchmark of seven diverse, annotated genomes to show that MetaEuk is highly sensitive even under conditions of low sequence similarity to the reference database. To demonstrate MetaEuks power to discover novel eukaryotic proteins in large-scale metagenomic data, we assembled contigs from 912 samples of the Tara Oceans project. MetaEuk predicted >12,000,000 protein-coding genes in eight days on ten 16-core servers. Most of the discovered proteins are highly diverged from known proteins and originate from very sparsely sampled eukaryotic supergroups. ConclusionThe open-source (GPLv3) MetaEuk software (https://github.com/soedinglab/metaeuk) enables large-scale eukaryotic metagenomics through reference-based, sensitive taxonomic and functional annotation.

bioinformatics↗