Biology subjects

Giometto, A.

Publications and source records attributed to Giometto, A..

7 recordsLinked to original sources

bioRxiv2025

Experimental evolution of cellular miniaturization reveals a mechanism for cell size evolution

Cell volume, a key determinant of physiology, is maintained by cell size homeostasis. Large deviations from typical size are often harmful, yet cell sizes have diverged drastically in evolution. How size homeostasis evolves to support such diversity without impairing cellular function remains unclear. To address this question, we used experimental evolution to select progressively smaller Saccharomyces cerevisiae cells. Over 1,500 generations, we achieved a four-fold modal volume reduction compared to wild type. Despite this reduction, evolved populations maintained robust size homeostasis and relatively high fitness, revealing that substantial decreases in cell volume can occur without severe growth defects. Whole-genome sequencing and genetic perturbations identify mutations in the G1 cyclin Cln3 and the TOR pathway effector Sch9 as major contributors to cell size reduction, with the Greatwall kinase Rim15 signaling cascade further modulating this phenotype. Manipulating these pathways produced a six-fold range in cell size without changes in ploidy, with engineered mutations recapitulating the volumes of evolved lines and loss-of-function mutations yielding enlarged cells. Our results demonstrate the evolutionary plasticity of cell size homeostasis and reveal a putative mechanism for eukaryotic cell size evolution.

cell biology↗

bioRxiv2024

Tunable Low-Rate Genomic Recombination with Cre-lox in E. coli: A Versatile Tool for Synthetic Biology and Environmental Sensing

The ability to induce heritable genomic changes in response to environmental cues is valuable for environmental biosensing, for experimentally probing microbial ecology and evolution, and for synthetic biology applications. Site-specific recombinases provide a route to genetic memory via targeted DNA modifications, but their high specificity and efficiency are offset by leaky expression and limited tunability in prokaryotes. We developed a tightly regulated, titratable Cre recombinase system for Escherichia coli that achieves low recombination rates and minimal basal activity. Implemented on both plasmids and the chromosome, the latter showed superior retention of genetic memory across generations. These features make the system broadly useful for environmental biosensing and other applications. To demonstrate applicability to environmental biosensing, we developed a whole-cell recombination-based biosensor for arsenite, a toxic and ubiquitous pollutant that is primarily mobilized in anoxic environments such as flooded soils, sediments, and aquifers. However, existing arsenite whole-cell biosensors face limitations in sensitivity and workflow in anaerobic settings. Our biosensor reliably recorded anoxic arsenite exposure as a stable genetic memory for delayed fluorescence readout in aerobic conditions, with detection sensitivity comparable to conventional wet chemical methods. By decoupling exposure from measurement, this approach offers a foundation for arsenite biosensing under field-relevant conditions, including redox variability and other physicochemical gradients, without the constraints of anoxic measurement. More broadly, the ability to induce low-rate, heritable genetic changes expands the genetic toolkit for environmentally responsive systems, with applications in environmental monitoring, bioproduction, bioengineering, as well as experimental studies of microbial ecology, evolution, and host-microbe interactions. IMPORTANCEArsenic is a toxic and globally prevalent pollutant, mobilized primarily under anoxic conditions where detection is challenging. Whole-cell biosensors offer a promising route for monitoring bioavailable arsenic in situ, but their development has largely focused on aerobic conditions, with anoxic assays limited by sensitivity and workflow constraints. Genetic tools that enable heritable, low-frequency genomic changes in bacteria can expand biosensor capabilities by recording transient exposures and supporting applications in environmental monitoring, synthetic biology, and quantitative microbial population dynamics research. Here, we developed a tightly regulated, chemically inducible Cre-lox system in Escherichia coli that enables recombination at low, tunable rates. We demonstrate its utility by constructing an arsenite biosensor that reliably detects low concentrations and records exposures under both aerobic and anoxic conditions. This approach is broadly applicable for biosensors designed for field deployment and for experiments investigating microbial ecology and evolution, where controllable genetic diversification may be desirable.

synthetic biology↗

bioRxiv2024

Overcoming toxicity: why boom-and-bust cycles are good for non-antagonistic microbes

Antagonistic interactions are critical determinants of microbial community stability and composition, offering host benefits such as pathogen protection and providing avenues for antimicrobial control. While the ability to eliminate competitors confers an advantage to antagonistic microbes, it often incurs a fitness cost. Consequently, many microbes only produce toxins or engage in antagonistic behavior in response to specific cues like quorum sensing molecules or environmental stress. In laboratory settings, antagonistic microbes typically dominate over sensitive ones, raising the question of why both antagonistic and non-antagonistic microbes are found in natural environments and host microbiomes. Here, using both theoretical models and experiments with killer strains of Saccharomyces cerevisiae, we show that boom-and-bust dynamics caused by temporal environmental fluctuations can favor non-antagonistic microbes that do not incur the growth rate cost of toxin production. Additionally, using control theory, we derive bounds on the competitive performance and identify optimal regulatory toxin-production strategies in various boom- and-bust environments where population dilutions occur either deterministically or stochastically over time. Our findings offer a new perspective on how both antagonistic and non-antagonistic microbes can thrive under varying environmental conditions.

microbiology↗

bioRxiv2024

Segatella copri strains adopt distinct roles within a single individual's gut

Segatella copri is a dominant member of individuals gut microbiomes worldwide, especially in non-Western populations. Although metagenomic assembly and genome isolation have shed light on the genetic diversity of S. copri, the lack of available isolates from this clade has resulted in a limited understanding of how members genetic diversity translates into phenotypic diversity. Within the confines of a single gut microbiome, we have isolated 63 strains from diverse lineages of S. copri. We performed comparative analyses that exposed differences in cellular morphologies, preferences in polysaccharide utilization, yield of short-chain fatty acids, and antibiotic resistance across isolates. We further show that exposure to S. copri lineages either evokes strong or muted transcriptional responses in human intestinal epithelial cells. Our study exposes large phenotypic differences within related S. copri isolates, extending this to host-microbe interactions.

microbiology↗

bioRxiv2020

Antagonism between killer yeast strains as an experimental model for biological nucleation dynamics

Antagonistic interactions are widespread in the microbial world and affect microbial evolutionary dynamics. Natural microbial communities often display spatial structure, which affects biological interactions, but much of what we know about microbial warfare comes from laboratory studies of well-mixed communities. To overcome this limitation, we manipulated two killer strains of the budding yeast Saccharomyces cerevisiae, expressing different toxins, to independently control the rate at which they released their toxins. We developed mathematical models that predict the experimental dynamics of competition between toxin-producing strains in both well-mixed and spatially structured populations. In both situations, we experimentally verified theorys prediction that a stronger antagonist can invade a weaker one only if the initial invading population exceeds a critical frequency or size. Finally, we found that toxin-resistant cells and weaker killers arose in spatially structured competitions between toxin-producing strains, suggesting that adaptive evolution can affect the outcome of microbial antagonism in spatial settings.

evolutionary biology↗

bioRxiv2020

Proteome allocation influences population dynamics in microbial communities

Microbial communities are ubiquitous and play crucial roles in many natural processes. Despite their importance for the environment, industry and human health, there are still many aspects of microbial community dynamics that we do not understand quantitatively. Recent experiments have shown that the metabolism of species in a community is intertwined with its composition, suggesting that properties at the intracellular level such as the allocation of cellular proteomic resources must be taken into account when describing microbial communities with a population dynamics approach. In this work we reconsider one of the theoretical frameworks most commonly used to model population dynamics in competitive ecosystems, MacArthurs consumer-resource model, in light of experimental evidence showing how pro-teome allocation affects microbial growth. This new framework allows us to describe community dynamics at an intermediate level of complexity between classical consumer-resource models and biochemical models of microbial metabolism, accounting for temporally-varying proteome allocation subject to constraints on growth and protein synthesis in the presence of multiple resources, while preserving analytical insight into the dynamics of the system. We first show experimentally that proteome allocation needs to be accounted for to properly understand the dynamics of even the simplest microbial community, i.e. two bacterial strains competing for one common resource. We then study the model analytically and numerically to determine the conditions that allow multiple species to coexist in systems with arbitrary numbers of species and resources.

biophysics↗

bioRxiv2018

Physical interactions reduce the power of natural selection in growing yeast colonies

Microbial populations often assemble in dense populations in which proliferating individuals exert mechanical forces on the nearby cells. Here, we use yeast strains whose doubling times depend differently on temperature to show that physical interactions among cells affect the competition between different genotypes in growing yeast colonies. Our experiments demonstrate that these physical interactions have two related effects: they cause the prolonged survival of slower-growing strains at the actively-growing frontier of the colony and cause faster-growing strains to increase their frequency more slowly than expected in the absence of physical interactions. These effects also promote the survival of slower-growing strains and the maintenance of genetic diversity in colonies grown in time-varying environments. A continuum model inspired by overdamped hydrodynamics reproduces the experiments and predicts that the strength of natural selection depends on the width of the actively-growing layer at the colony frontier. We verify these predictions experimentally. The reduced power of natural selection observed here may favor the maintenance of drug-resistant cells in microbial populations and could explain the apparent neutrality of inter-clone competition within tumors.\n\nSignificance StatementMicrobes often live in dense populations such as colonies and biofilms. We show that the success and extinction of yeast strains within a growing colony are determined by a combination of their relative fitness and the forces exerted by proliferating cells on their neighbors. These physical interactions prolong the survival of less-fit strains at the growing frontier of the colony and slow down the colonys takeover by fitter strains. This reduction in the power of natural selection favors the maintenance of genetic diversity in environments in which the strains relative growth rates vary with time. Growth-induced physical interactions may thus favor the maintenance of drug-resistant cells, which are typically less-fit than non-resistant cells, within dense microbial populations.

biophysics↗