Andrea Giometto

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 during evolution. How size homeostasis evolves to support such diversity without impairing cellular function remains unclear. To address this question, we used experimental evolution to progressively select for smaller Saccharomyces cerevisiae cells. Over 1,500 generations, we achieved a fourfold 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 identified mutations in the G1 cyclin Cln3 and the Target of Rapamycin (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 sixfold 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.

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, and bioengineering, as well as experimental studies of microbial ecology, evolution, and host-microbe interactions. IMPORTANCE: Arsenic 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.

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.

A biohybrid coating for crack detection: when the substrate is damaged, the coating cracks, causing spores to germinate and fluoresce.

Early detection of fatigue cracking is crucial to extend the life‐cycle of materials and structures. To reduce the risk of fatigue, parts are often over‐engineered or retired early, leading to material waste. Current methods for crack detection, including strain sensors or ultrasonic testing, can be costly, require regular maintenance, and do not respond to cracks directly via a repair mechanism. People are leveraging biology to create materials that can sense and respond. Engineered living materials have been primarily limited to porous matrices and hydrogels, which facilitate viability of organisms. We present an engineered living coating that can be applied to conventional structural materials to detect cracks. The coating integrates bacterial spores into a tailored synthetic matrix. This biohybrid coating approach unlocks potential, beyond crack detection, for crack mitigation through leveraging the biological component. This study: 1) describes the design of a spore‐polymer coating for in situ crack detection for structural materials and 2) demonstrates detection for different loading mechanisms, geometries, and materials. This work demonstrates how living materials can be used to enhance conventional materials and creates a valuable approach for crack detection. Our coating will reduce waste, increase product lifespan, and improve safety by preventing failure due to cracks.

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 nonantagonistic 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—periods of rapid growth punctuated by episodic mortality events—caused by temporal environmental fluctuations can favor nonantagonistic 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 mathematical investigation reveals that optimal toxin regulation is much more beneficial to killers in stochastic, rather than deterministic, boom-and-bust environments. Overall, our findings show how both antagonistic and nonantagonistic microbes can thrive under varying environmental conditions.

Segatella is a prevalent genus within individuals’ gut microbiomes worldwide, especially in non-Western populations. Although metagenomic assembly and genome isolation have shed light on its genetic diversity, the lack of available isolates from this genus 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 Segatella. 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 Segatella isolates either evokes strong or muted transcriptional responses in human intestinal epithelial cells. Our study exposes large phenotypic differences within related Segatella isolates, extending this to host-microbe interactions.

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. IMPORTANCE: Arsenic 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.

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.

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.