Biology subjects

Kondrashov, F.

Publications and source records attributed to Kondrashov, F..

4 recordsLinked to original sources

bioRxiv2022

Distinct features in fish Bouncer proteins determine sperm-egg compatibility

All sexually reproducing organisms depend on fertilization to survive as species. Despite the importance of fertilization, the mechanisms that drive sperm-egg compatibility are poorly understood. In fish, the egg protein Bouncer is necessary for fertilization and is species-specific between medaka and zebrafish. Here, we investigate whether Bouncer is generally species-specific in fish and identify features mediating its medaka/zebrafish specificity. In vitro fertilization experiments using zebrafish and medaka show that Bouncer is not a general specificity factor. Instead, its homologs exhibit wide compatibility with sperm, in line with the pervasive purifying selection that dominates Bouncers evolution. We further uncover specific features of Bouncer-- distinct amino acid residues and N-glycosylation patterns--that differentially influence the function of medaka and zebrafish Bouncer homologs and contribute to medaka/zebrafish specificity. This work reveals important themes central to understanding Bouncers function in sperm binding and clarifying the molecular requirements for Bouncers sperm interaction partner.

developmental biology↗

bioRxiv2021

Heterogeneity of the GFP fitness landscape and data-driven protein design

Studies of protein fitness landscapes reveal biophysical constraints guiding protein evolution and empower prediction of functional proteins. However, generalisation of these findings is limited due to scarceness of systematic data on fitness landscapes of proteins with a defined evolutionary relationship. We characterized the fitness peaks of four orthologous fluorescent proteins with a broad range of sequence divergence. While two of the four studied fitness peaks were sharp, the other two were considerably flatter, being almost entirely free of epistatic interactions. Counterintuitively, mutationally robust proteins, characterized by a flat fitness peak, were not optimal templates for machine-learning-driven protein design - instead, predictions were more accurate for fragile proteins with epistatic landscapes. Our work paves insights for practical application of fitness landscape heterogeneity in protein engineering.

synthetic biology↗

bioRxiv2021

Chromosome-encoded IpaH ubiquitin ligases indicate non-human pathogenic Escherichia

Until recently, Shigella and enteroinvasive Escherichia coli were thought to be primate-restricted pathogens. The base of their pathogenicity is the type 3 secretion system (T3SS) encoded by the pINV virulence plasmid, which facilitates host cell invasion and subsequent proliferation. A large family of T3SS effectors, E3 ubiquitin-ligases encoded by the ipaH genes, have a key role in the Shigella pathogenicity through the modulation of cellular ubiquitination that degrades host proteins. However, recent genomic studies identified ipaH genes in the genomes of Escherichia marmotae, a potential marmot pathogen, and an E. coli extracted from fecal samples of bovine calves, suggesting that non-human hosts may also be infected by these strains, potentially pathogenic to humans. We performed a comparative genomic study of the functional repertoires in the ipaH gene family in Shigella and enteroinvasive Escherichia from human and predicted non-human hosts. We found that fewer than half of Shigella genomes had a complete set of ipaH genes, with frequent gene losses and duplications that were not consistent with the species tree and nomenclature. Non-human host IpaH proteins had a diverse set of substrate-binding domains and, in contrast to the Shigella proteins, two different types of the NEL C-terminal domain. Only the ipaH9.8 gene was found in Escherichia derived from both human and non-human hosts. These results provide a framework for understanding of ipaH-mediated host-pathogens interactions and suggest a need for a genomic study of fecal samples from diseased animals.

microbiology↗

bioRxiv2018

Fast and accurate large multiple sequence alignments using root-to-leave regressive computation

Inferences derived from large multiple alignments of biological sequences are critical to many areas of biology, including evolution, genomics, biochemistry, and structural biology. However, the complexity of the alignment problem imposes the use of approximate solutions. The most common is the progressive algorithm, which starts by aligning the most similar sequences, incorporating the remaining ones following the order imposed by a guide-tree. We developed and validated on protein sequences a regressive algorithm that works the other way around, aligning first the most dissimilar sequences. Our algorithm produces more accurate alignments than non-regressive methods, especially on datasets larger than 10,000 sequences. By design, it can run any existing alignment method in linear time thus allowing the scale-up required for extremely large genomic analyses.\n\nOne Sentence SummaryInitiating alignments with the most dissimilar sequences allows slow and accurate methods to be used on large datasets

bioinformatics↗