Biology subjects

Ansmann, G.

Publications and source records attributed to Ansmann, G..

4 recordsLinked to original sources

bioRxiv2025

Function-specific epistasis shapes evolutionary trajectories towards antibiotic resistance

Pre-existing mutations can influence subsequent evolution by constraining or opening evolutionary pathways through epistatic interactions. In some cases, global epistasis allows evolutionary pathways to be predicted from the fitness of the genetic background alone. In other cases, idiosyncratic epistasis makes evolution less predictable. Here, we show that the evolution of antibiotic resistance is highly repeatable, following a common path across most genetic backgrounds. However, a minority of genetic backgrounds exhibit evolutionary trajectories that significantly deviate from this common path. Rather than being predictable from global epistasis, these deviations are modulated by function-specific epistasis: perturbations to specific cellular functions lead to novel evolutionary trajectories towards resistance. Using tightly controlled robotic evolution experiments, we quantitatively analyzed resistance trajectories for three clinically relevant antibiotics across multiple genetic backgrounds, including hundreds of Escherichia coli gene-deletion strains and several clinical isolates from urinary-tract infections. We show that disrupting distinct sets of cellular functions alters evolutionary trajectories for specific drugs and across different drugs, and we identify genetic changes defining these alternative trajectories. Importantly, this function-specific epistasis often slows down resistance evolution. Some of these effects can also be induced by small-molecule inhibitors of the identified targets, suggesting that function-specific epistasis can be exploited to improve drug treatments.

evolutionary biology↗

bioRxiv2025

Ultrasensitive fitness costs arise from membrane proteome displacement under protein overexpression

Protein overexpression is crucial in many diseases and can lead to antibiotic resistance by increasing the expression of drug targets or resistance genes, such as membrane-localized efflux pumps. Using a high-throughput colony-imaging technique, we performed a quantitative genome-wide study of protein overexpression in Escherichia coli. Our results show that most membrane proteins impose steep overexpression costs, leading to an abrupt growth collapse beyond a critical expression threshold. By manipulating synthetic membrane proteins to target different translocation pathways, we ruled out saturation of these pathways as the cause of these fitness costs. Instead, we found that the growth collapse is driven by the displacement of endogenous membrane proteins, which we show directly using single-cell time-lapse imaging with fluorescently tagged membrane proteins in a microfluidic device. Displacement of as little as 10% of the membrane proteome trapped most bacteria in a non-growing state. Our findings enhance the quantitative understanding of expression costs, with implications for antibiotic resistance and the biotechnological production of membrane proteins.

systems biology↗

bioRxiv2024

Trace elements increase reproducibility of microbial growth

Trace elements are often omitted from chemically defined growth media. From established properties of trace elements, we deduce that this omission makes experiments unnecessarily sensitive to unavoidable contamination with trace elements. We confirm this experimentally by growing eleven bacterial strains in high replicate with and without supplementing trace elements, keeping all other conditions as fixed as possible to isolate the effect of trace elements. We find that supplementing trace elements considerably reduces variability of growth even in this benign scenario, and we argue that typical experimental setups exacerbate this. We discuss implications for the design and use of trace-element supplements, and in particular argue that their use should be standard practice, as they can reduce variability of almost all experiments using chemically defined media, taking a step towards greater precision and replicability in microbiology.

microbiology↗

bioRxiv2019

Axiomatic Ecology: Rules for Building Consistent Ecosystem Models

Many ecological studies employ general models that can feature an arbitrary number of populations. A critical requirement imposed on such models is clone consistency: If the individuals from two populations are indistinguishable, joining these populations into one shall not affect the outcome of the model. Otherwise a model produces different outcomes for the same scenario. Using functional analysis, we comprehensively characterize all clone-consistent models: We prove that they are necessarily composed from basic building blocks, namely linear combinations of parameters and abundances. These strong constraints enable a straightforward validation of model consistency or reveal implicit assumptions required to achieve it. We show that such implicit assumptions can considerably limit the applicability of models and the generality of results obtained with them. Moreover, our insights facilitate building new clone-consistent models, which we illustrate for a data-driven model of microbial communities. Finally, our insights point to new relevant forms of general models for theoretical ecology. Our framework thus provides a systematic way of comprehending ecological models, which can guide a wide range of studies.

ecology↗