Biology subjects

Koonin, E.

Publications and source records attributed to Koonin, E..

4 recordsLinked to original sources

bioRxiv2026

Evolutionary implications of phenotype switching for growth and survival of tumors in stochastic environments.

Tumors evolve under constantly changing microenvironmental conditions, and a key major mechanism by which cancer cells adapt to fluctuating environments is stochastic phenotypic switch via epithelial-mesenchymal plasticity (EMP). Here we demonstrate the existence of EMP in human breast epithelial cell lines and assess the fitness of E and M cells in environments that fluctuate between favorable and harsh conditions. We then develop a theoretical framework for analysis of tumor evolution with E-M stochastic phenotypic switch that integrates the behaviors of E and M cells. We characterize the outcomes of tumor evolution via three characteristic times describing i) tumor growth, ii) phenotypic adaptation and iii) fluctuations of the environment. We identify a tradeoff between tumor growth and survival, with different phenotype switching rates maximizing each of these objectives. An anticancer therapeutic strategy is proposed based on tumor survival analysis, revealing that blocking mesenchymal to epithelial transition, rather than epithelial to mesenchymal transition, is critical under fluctuating conditions. Thus, this study elucidates fundamental evolutionary mechanisms of tumor phenotypic adaptation in fluctuating environments with potentially important clinical implications.

evolutionary biology↗

bioRxiv2025

Evolution of gene order in prokaryotes is driven primarily by gene gain and loss

Evolution of bacterial and archaeal genomes is highly dynamic including extensive gene gain via horizontal gene transfer and gene loss as well as different types of genome rearrangements, such as inversions and translocations, so that gene order is not highly conserved even among closely related organisms. We sought to quantify the contributions of different genome dynamics processes to the evolution of the gene order relying on the recently developed "jump" model of gene translocation. The jump model has been completely solved analytically and provides the exact distribution of syntenic gene block lengths (SBL) in compared genomes based on gene translocations alone. Comparing the SBL distribution predicted by the jump model with the distributions empirically observed for multiple groups of closely related bacterial and archaeal genomes, we obtained robust estimates of the genome rearrangement to gene flux (gain and loss) ratio. In most groups of bacteria and archaea, this ratio was found to be on the order of 0.1 indicating that the loss of synteny in the evolution of bacteria and archaea is driven primarily by gene gain and loss rather than by gene translocation. SignificanceEvolution of bacterial and archaeal genomes is a highly dynamic process that includes extensive gene gain via horizontal gene transfer and gene loss as well as different types of genome rearrangements, so that gene order is not highly conserved even among closely related organisms. We developed a theoretical framework to quantify the contributions of different genome dynamics processes to the evolution of the gene order and found that in most groups of bacteria and archaea, the genome rearrangement to gene flux (combined gain and loss) is on the order of 0.1. Thus, the loss of genomic synteny in the evolution of bacteria and archaea appears to be driven primarily by gene gain and loss rather than by gene translocation.

evolutionary biology↗

bioRxiv2017

The CRISPR Spacer Space Is Dominated By Sequences From The Species-Specific Mobilome

The CRISPR-Cas is the prokaryotic adaptive immunity system that stores memory of past encounters with foreign DNA in spacers that are inserted between direct repeats in CRISPR arrays 1,2. Only for a small fraction of the spacers, homologous sequences, termed protospacers, are detectable in viral, plasmid or microbial genomes 3,4. The rest of the spacers remain the CRISPR \"dark matter\". We performed a comprehensive analysis of the spacers from all CRISPR-cas loci identified in bacterial and archaeal genomes, and found that, depending on the CRISPR-Cas subtype and the prokaryotic phylum, protospacers were detectable for 1 to about 19% of the spacers ([~]7% global average). Among the detected protospacers, the majority, typically, 80 to 90%, originate from viral genomes, and among the rest, the most common source are genes integrated in microbial chromosomes but involved in plasmid conjugation or replication. Thus, almost all spacers with identifiable protospacers target mobile genetic elements (MGE). The GC-content, as well as dinucleotide and tetranucleotide compositions, of microbial genomes, their spacer complements, and the cognate viral genomes show a nearly perfect correlation and are almost identical. Given the near absence of self-targeting spacers, these findings are best compatible with the possibility that the spacers, including the dark matter, are derived almost completely from the species-specific microbial mobilomes.

microbiology↗

bioRxiv2017

Estimation Of Universal And Taxon-Specific Parameters Of Prokaryotic Genome Evolution

Our recent study on mathematical modeling of microbial genome evolution indicated that, on average, genomes of bacteria and archaea evolve in the regime of mutation-selection balance defined by positive selection coefficients associated with gene acquisition that is counter-acted by the intrinsic deletion bias. This analysis was based on the strong assumption that parameters of genome evolution are universal across the diversity of bacteria and archaea, and yielded extremely low values of the selection coefficient. Here we further refine the modeling approach by taking into account evolutionary factors specific for individual groups of microbes using two independent fitting strategies, an ad hoc hard fitting scheme and an hierarchical Bayesian model. The resulting estimate of the mean selection coefficient of s[~]10-10 associated with the gain of one gene implies that, on average, acquisition of a gene is beneficial, and that microbial genomes typically evolve under a weak selection regime that might transition to strong selection in highly abundant organisms with large effective population sizes. The apparent selective pressure towards larger genomes is balanced by the deletion bias, which is estimated to be consistently greater than unity for all analyzed groups of microbes. The estimated values of s are more realistic than the lower values obtained previously, indicating that global and group-specific evolutionary factors synergistically affect microbial genome evolution that seems to be driven primarily by adaptation to existence in diverse niches.

evolutionary biology↗