Biology subjects

Regoes, R.

Publications and source records attributed to Regoes, R..

4 recordsLinked to original sources

bioRxiv2026

Substantial Deceleration of Adaptation of HIV-1 Within 1,500 Generations in an Experimental Evolution: A Genomic Perspective

Numerous experimental evolution studies have suggested that adaptation rate of microbial populations evolving in stable environments decline over time. Despite the generality of this phenomenon across different domains of life, the timing and magnitude of decline in adaptation can vary greatly based on the idiosyncrasies of the biological system. To investigate the characteristics of adaptation deceleration in a fast-evolving virus, we propagated HIV-1 in two human T-cell lines (MT-2 and MT-4) for approximately 4.8 years and tracked its genome evolution through next-generation sequencing. The curated sequencing data covering the whole-genome can be accessed and explored via LTEEviz, an interactive web application. Time-resolved sequencing data uncovered that despite constant fixation rate of 0.085 (MT-2) and 0.042 (MT-4) mutations per generation, the fixation kinetics of adaptive mutations changed considerably over time. The rate of fixation of adaptive parallel mutations decreased by 44% per 300 generations, while their conferred fitness gain decreased by 27% (MT-2) and 18% (MT-4) per every added adaptive mutation in their genetic background. The early and substantial deceleration of adaptation in our HIV-1 populations can, at least in part, be explained by diminishing gains of adaptive mutations. Furthermore, we identified genomic patterns consistent with a hard selective sweep that occurred in one population later in the experiment. Together, our results confirm that HIV-1 genomic evolution is characterized by a swift and substantial deceleration of adaptation, while also revealing that episodes of positive selection can occur beyond the initial adaptive phase.

evolutionary biology↗

bioRxiv2025

High-Throughput Quantification of Population Dynamics using Luminescence

The dynamics of bacterial population decline at antibiotic concentrations above the minimum inhibitory concentration (MIC) remain poorly characterized. This is because measuring colony-forming units (CFU), the standard assay to quantify inhibition, is slow, labour-intensive, costly, and can be unreliable at high drug concentrations. Luminescence assays are widely used to quantify population dynamics at subinhibitory concentrations, yet their limitations and reliability at super-MIC concentrations remain underexplored. To fill this gap, we compared luminescence- and CFU-based rates across 20 antimicrobials. In our experiments luminescence- and CFU-based rates did not differ significantly for half of them. For the other half, CFU-based estimates of rates of decline were consistently higher. The estimates differed for two main reasons: First, because light intensity tracks biomass more closely than population size, luminescence declined more slowly than the population when bacteria filamented. Second, CFU-based estimates indicated a steeper decline when antimicrobial treatment reduced the number of colonies formed per plated bacterium. This effect can result from changes in clustering behaviour, physiological changes that impair culturability, or antimicrobial carry-over. Thus, the suitability of luminescence to quantify bacterial decline depends on the physiological effects of the antimicrobial used (e.g. filamentation) and whether the quantity of interest is cell number or biomass. Within these limitations, luminescence can serve as an efficient, high-throughput alternative for quantifying bacterial dynamics at super-MIC concentrations.

microbiology↗

bioRxiv2021

Diversity of vaccination-induced immune responses can prevent the spread of vaccine escape mutants

Pathogens that are resistant against drug treatment are widely observed. In contrast, pathogens that escape the immune response elicited upon vaccination are rare. Previous studies showed that the prophylactic character of vaccines, the multiplicity of epitopes to which the immune system responds within a host, and their diversity between hosts delay the evolution and emergence of escape mutants in a vaccinated population. By extending previous mathematical models, we find that, depending on the cost of the escape mutations, there even exist critical levels of immune response diversity that completely prevent vaccine escape. Furthermore, to quantify the potential for vaccine escape below these critical levels, we propose a concept of escape depth which measures the fraction of escape mutants that can spread in a vaccinated population. Determining this escape depth for a vaccine could help to predict its sustainability in the face of pathogen evolution.

evolutionary biology↗

bioRxiv2017

Predicting Drug Resistance Evolution: Antimicrobial Peptides Vs. Antibiotics

Antibiotic resistance constitutes one of the most pressing public health concerns. Antimicrobial peptides of multicellular organisms are considered part of a solution to this problem, and AMPs produced by bacteria such as colistin are last resort drugs. Importantly, antimicrobial peptides differ from many antibiotics in their pharmacodynamic characteristics. Here we implement these differences within a theoretical framework to predict the evolution of resistance against antimicrobial peptides and compare it to antibiotic resistance. Our analysis of resistance evolution finds that pharmacodynamic differences all combine to produce a much lower probability that resistance will evolve against antimicrobial peptides. The finding can be generalized to all drugs with pharmacodynamics similar to AMPs. Pharmacodynamic concepts are familiar to most practitioners of medical microbiology, and data can be easily obtained for any drug or drug combination. Our theoretical and conceptual framework is therefore widely applicable and can help avoid resistance evolution if implemented in antibiotic stewardship schemes or the rational choice of new drug candidates.

evolutionary biology↗