Biology subjects

Kussell, E.

Publications and source records attributed to Kussell, E..

9 recordsLinked to original sources

bioRxiv2026

Rapid enhancement of antibiotic resistance and divergent remodeling of gene expression in single cells of bacteria

Exposing bacterial cell populations to antibiotics often results in the emergence of descendants with enhanced resistance. Phenotypic heterogeneity and global physiological responses are thought to contribute to resistance evolution. However, identifying the specific stages of drug exposure where phenotypic heterogeneity and physiological responses play critical roles remains elusive. Using long-term single-cell lineage tracking of an Escherichia coli resistance model, here we reveal that resistance-enhanced cells emerge rapidly within a few generations in a clonal bacterial cell population under chloramphenicol (Cp) exposure and stably transmit the enhanced resistance for hundreds of generations in the presence of Cp. High expression of a resistance protein was advantageous during the initial period of drug exposure, but conferred only a marginal fitness advantage during the period of resistance enhancement. Transcriptomic profiles of resistance-enhanced cell populations were lineage-specific, suggesting that multiple gene expression states can support enhanced resistance. Altogether, these results suggest that an interplay between initial phenotypic heterogeneity and divergent remodeling of gene expression drives the rapid acquisition of enhanced antibiotic resistance.

microbiology↗

bioRxiv2025

Gene regulation, phenotypic memory, and selection in fluctuating environments

Gene regulatory networks coordinate how microorganisms respond to environmental changes, and their proper functioning is critical for microbial survival and adaptation [1, 2]. While evolution of gene regulation has been extensively studied by comparative functional genomics [3, 4], the role of fluctuating environments in selecting for, shaping, and maintaining gene regulatory networks has not been elucidated. Laboratory evolution experiments find that under metabolic fluctuations, regulation of metabolic genes is often lost, leading to their constitutive expression [5-8]. To identify general properties of fluctuating environments that tune expression levels and select for gene regulation, we quantify the impact of regulation on fitness in strains with perturbed gene expression dynamics under metabolic fluctuations. We reveal that expression levels can be shaped by selection to enhance phenotypic memory of past environmental states, reducing the impact of gene induction lags on long-term population growth. By quantifying growth dynamics in a wide range of metabolic fluctuations, we identify catabolite symport flux as a key determinant of selection for gene regulation. By independently perturbing the ability to sense the environment and the control of expression levels, we discover sign epistasis between sensing and control in a gene regulatory network, and identify its molecular underpinnings. Due to this epistatic interaction, maintenance of sensing enhances the ability of evolution to tune gene expression levels in a fluctuating environment. Our work establishes a new basis for understanding how gene regulatory networks evolve in fluctuating environments.

microbiology↗

bioRxiv2025

Transposon-plasmid nesting enables fast response to fluctuating environments

Mobile genetic elements (MGEs) play a critical role in shaping the response and evolution of microbial populations and communities. Despite distinct maintenance mechanisms, different types of MGEs can form nested structures. Using bioinformatics analysis of 14,338 plasmids in the NCBI RefSeq database, we found transposons to be widespread and significantly enriched on plasmids relative to chromosomes, highlighting the prevalence of transposon-plasmid nesting. We hypothesized that this nested structure provides unique adaptive advantages by combining transposition-driven genetic mobility with plasmid-mediated copy number amplification. Using engineered transposon systems, we demonstrated that nesting enables rapid and tunable responses of transposon-encoded genes in fluctuating environments. Specifically, transposition maintains a reservoir of the encoded genes, while plasmid copy number fluctuations further amplify the dynamic range of gene dosage, thus enhancing the response speed and stability of transposon-encoded traits. Our findings demonstrate an adaptive benefit of transposon-plasmid nesting and provide insights into their ecological persistence and evolutionary success.

systems biology↗

bioRxiv2022

Correlated substitutions reveal SARS-like coronaviruses recombine frequently with a diverse set of structured gene pools

Quantifying SARS-like coronavirus (SL-CoV) evolution is critical to understanding the origins of SARS-CoV-2 and the molecular processes that could underlie future epidemic viruses. While genomic evidence implicates recombination as a factor in the emergence of SARS-CoV-2, few studies have quantified recombination rates among SL-CoVs. Here, we infer recombination rates of SL-CoVs from correlated substitutions in sequencing data using a coalescent model with recombination. Our computationally-efficient, non-phylogenetic method infers recombination parameters of both sampled sequences and the unsampled gene pools with which they recombine. We apply this approach to infer recombination parameters for a range of positive-sense RNA viruses. We then analyze a set of 191 SL-CoV sequences (including SARS-CoV-2) and find that ORF1ab and S genes frequently undergo recombination. We identify which SL-CoV sequence clusters have recombined with shared gene pools, and show that these pools have distinct structures and high recombination rates, with multiple recombination events occurring per synonymous substitution. We find that individual genes have recombined with different viral reservoirs. By decoupling contributions from mutation and recombination, we recover the phylogeny of non-recombined portions for many of these SL-CoVs, including the position of SARS-CoV-2 in this clonal phylogeny. Lastly, by analyzing 444,145 SARS-CoV-2 whole genome sequences, we show current diversity levels are insufficient to infer the within-population recombination rate of the virus since the pandemic began. Our work offers new methods for inferring recombination rates in RNA viruses with implications for understanding recombination in SARS-CoV-2 evolution and the structure of clonal relationships and gene pools shaping its origins. Significance StatementQuantifying the population genetics of SARS-like coronavirus (SL-CoV) evolution is vital to deciphering the origins of SARS-CoV-2 and pinpointing viruses with epidemic potential. While some Bayesian approaches can quantify recombination for these pathogens, the required simulations of recombination networks do not scale well with the massive amounts of sequences available in the genomics era. Our approach circumvents this by measuring correlated substitutions in sequences and fitting these data to a coalescent model with recombination. This allows us to analyze hundreds of thousands of sample sequences, and infer recombination rates for unsampled viral reservoirs. Our results provide insights into both the clonal relationships of sampled SL-CoV sequence clusters and the evolutionary dynamics of the gene pools with which they recombine.

evolutionary biology↗

bioRxiv2021

Actively growing cells are the predominant persisters in exponential phase of Escherichia coli

Bacterial persistence is a phenomenon in which a small fraction of isogenic bacterial cells survives a lethal dose of antibiotics. Although the refractoriness of persistent cell populations has classically been attributed to growth-inactive cells generated before drug exposure, evidence is accumulating that actively growing cell fractions can also generate persister cells. However, single-cell characterization of persister cell history remains limited due to the extremely low frequencies of persisters. Here, we visualize the responses of over one million individual cells of wildtype Escherichia coli to lethal doses of antibiotics, sampling cells from different growth phases and culture media into a microfluidic device. We show that when cells sampled from exponentially growing populations were treated with ampicillin or ciprofloxacin, most persisters were growing before antibiotic treatment. Growing persisters exhibited heterogeneous survival dynamics, including continuous growth and fission with L-form-like morphologies, responsive growth arrest, or post-exposure filamentation. Incubating cells under stationary phase conditions increased both the frequency and the probability of survival of non-growing cells to ampicillin. Under ciprofloxacin, however, all persisters identified were growing before the antibiotic treatment, including samples from post-stationary phase culture. These results reveal diverse persister cell dynamics that depend on antibiotic types and pre-exposure history.

microbiology↗

bioRxiv2021

Core genes can have higher recombination rates than accessory genes within global microbial populations

Recombination is essential to microbial evolution1-4, and is involved in the spread of antibiotic resistance, antigenic variation, and adaptation to the host niche5-8. Yet quantifying the impact of homologous recombination on different gene classes, which is critical to understanding how selection acts on variation to shape species diversity and genome structure, remains challenging. This is largely due to the dynamic nature of bacterial genomes, whose high intraspecies genome content diversity9 and complex phylogenetic relationships10-12 present difficulties for inferring rates of recombination, particularly for rare genes. In this work, we apply a computationally efficient, non-phylogenetic approach13,14 to measure homologous recombination rates in the core and accessory genome (genes present in all strains and only a subset of strains, respectively) using >100,000 whole genome sequences from 12 microbial species. Our analysis suggests that even well-resolved sequence clusters sampled from global populations interact with overlapping gene pools, which has implications for the role of population structure in genome evolution. We show that in a majority of species, core genes have shorter coalescence times and higher recombination rates than accessory genes, and that gene frequency is often positively correlated with increased recombination. Our results provide a new line of population genomic evidence supporting the hypothesis that core genes are under strong, purifying selection15-17, and indicate that homologous recombination may play a key role in increasing the efficiency of selection in those parts of the genome most conserved within each species.

microbiology↗

bioRxiv2021

A unified framework for measuring selection on cellular lineages and traits

Intracellular states probed by gene expression profiles and metabolic activities are intrinsically noisy, causing phenotypic variations among cellular lineages. Understanding the adaptive and evolutionary roles of such variations requires clarifying their linkage to population growth rates. Extending a cell lineage statistics framework, here we show that a populations growth rate can be expanded by fitness cumulants of any cell lineage trait. The expansion enables quantifying the contribution of each fitness cumulant, such as variance and skewness, to population growth. We introduce a function that contains all the essential information of cell lineage statistics, including mean lineage fitness and selection strength. We reveal a relation between fitness heterogeneity and population growth rate response to perturbation. We apply the framework to experimental cell lineage data from bacteria to mammalian cells, revealing that third or higher-order cumulants contributions are negligible under constant growth conditions but could be significant in regrowing processes from growth-arrested conditions. Furthermore, we identify cellular populations in which selection leads to an increase of fitness variance among lineages. The framework assumes no particular growth models or environmental conditions, and is thus applicable to various biological phenomena for which phenotypic heterogeneity and cellular proliferation are important.

systems biology↗

bioRxiv2020

Origin of exponential growth in nonlinear reaction networks

Exponentially growing systems are prevalent in nature, spanning all scales from biochemical reaction networks in single cells to food webs of ecosystems. How exponential growth emerges in nonlinear systems is mathematically unclear. Here, we describe a general theoretical framework that reveals underlying principles of long-term growth: scalability of flux functions and ergodicity of the rescaled systems. Our theory shows that nonlinear fluxes can generate not only balanced growth, but also oscillatory or chaotic growth modalities, explaining non-equilibrium dynamics observed in cell cycles and ecosystems. Our mathematical framework is broadly useful in predicting long-term growth rates from natural and synthetic networks, analyzing the effects of system noise and perturbations, validating empirical and phenomenological laws on growth rate, and studying autocatalysis and network evolution. SignificanceNatural systems (e.g., cells, ecosystems) generally consist of reaction networks (e.g., metabolic networks, food webs) with nonlinear flux functions (e.g., Michaelis-Menten kinetics, density-dependent selection). Despite their complex nonlinearities, these systems often exhibit simple exponential growth in the long term. How exponential growth emerges from nonlinear networks remains elusive. Our work demonstrates mathematically how two principles, multivariate scalability of flux functions and ergodicity of the rescaled system, guarantee a well-defined rate of growth. By connecting ergodic theory, a powerful branch of mathematics, to the study of growth in biology, our theoretical framework can recapitulate various growth modalities (from balanced growth to periodic, quasi-periodic or even chaotic behaviors), greatly expanding the types of growing systems that can be studied.

systems biology↗

bioRxiv2020

Ecological memory preserves phage resistance mechanisms in bacteria

Defense mechanisms against pathogens are prevalent in nature, and their maintenance is critical for long-term survival of a species. Such mechanisms, which include CRISPR-mediated immunity in bacteria and the R genes in plants, carry substantial costs to organisms and can be rapidly lost when pathogens are eliminated. How a species preserves its molecular defenses despite their costs, in the face of variable pathogen levels, and across an ecology of localized patches remains a major unsolved problem in epidemiology and evolutionary biology. Using techniques of game theory and non-linear dynamical systems, we show that by maintaining a non-zero failure rate of immunity, hosts sustain sufficient levels of pathogen across an ecology to select against loss of the defense. This resistance switching strategy is evolutionarily stable, and provides a powerful evolutionary mechanism that maintains host-pathogen interactions and enables co-evolutionary dynamics in a wide range of systems.

evolutionary biology↗