Biology subjects

Hamrick, G. S.

Publications and source records attributed to Hamrick, G. S..

7 recordsLinked to original sources

bioRxiv2026

Gene circuit-driven amplified selection enables evolution of fast-growing Escherichia coli

The laboratory Escherichia coli K-12 strain has doubled no faster than [~]20 minutes for decades. This plateau could reflect a biophysical limit or simply the way batch culture selects on growth rate. Here we show it can be broken through amplified selection with a Red Queen gene circuit, which takes advantage of growth rate heterogeneity in monoclonal populations to selectively suppress slow-growing cells and creates a tunable mapping from intrinsic growth rate to survival. After 70 days ([~]1,000 generations) of amplified selection in MG1655+FHr and subsequent removal of the circuit, a top evolved clone (RQ70) reached a maximum specific growth rate of 2.61 h-{superscript 1} in shake-flask culture. This corresponds to a doubling time of 15.9 minutes, to our knowledge the shortest reported for E. coli K-12, against 18.1 minutes for evolved controls and 20.3 minutes for the ancestor. The gain came at the cost of a [~]3-fold increase in lag time, indicating that the 20-minute plateau is a multi-trait optimum under conventional batch selection rather than an absolute constraint. We argue that synthetic gene circuits can therefore reshape the evolutionary process itself, pushing performance beyond apparent physiological limits.

synthetic biology↗

bioRxiv2026

Microscale spatial fragmentation promotes bacterial survival under antibiotics

Most bacteria inhabit fragmented microscale environments rather than well-mixed systems in which antibiotic efficacy is typically defined. Here, we show that microscale spatial fragmentation alone can deterministically promote bacterial survival under antibiotic exposure. A coarse-grained theoretical model predicts that, at fixed bulk cell density and antibiotic concentration, fragmentation generates refuges through two coupled mechanisms: slower growth, which reduces susceptibility to growth-dependent antibiotics, and a finite antibiotic-per-cell constraint that lowers the effective intracellular antibiotic concentration. Using a microdroplet platform spanning five orders of magnitude in volume, we experimentally confirm these predictions for {beta}-lactams; we further demonstrate that the same fragmentation-mediated protection extends to antibiotics with distinct modes of action. Spatial fragmentation thus creates robust, non-genetic antibiotic refuges governed by physical constraints rather than resistance or collective protection, with implications for bacterial persistence in natural and clinical environments and for antibiotic design.

microbiology↗

bioRxiv2025

A foundation model for microbial growth dynamics

Microbial growth dynamics contain rich information about microbial populations, which support applications from antibiotic testing to microbiome engineering. However, the high dimensionality of growth data and the scarcity of large, task-specific datasets have limited generalizable modeling analysis across systems. Here, we develop a foundation model for microbial growth dynamics. It is a large-scale, self-supervised representation model trained on [~]370,000 experimental and simulated growth curves spanning diverse microbial species, environmental conditions, and community contexts. The model learns lower-dimensional latent embeddings that capture essential dynamical features of raw growth data and enable accurate reconstruction of these data. The concise representations enhance predictive performance in diverse downstream applications. Using these embedding, we achieve few-shot learning for antibiotic classification and concentration prediction, accurate forecasting of simulated and experimental communities, and inference of total abundance from relative-abundance data. By extracting transferable representations from heterogeneous datasets, our model provides a general framework for analyzing and predicting microbial community dynamics from limited measurements.

synthetic biology↗

bioRxiv2025

Emergence of population-level feedback control by transposon-plasmid coevolution

The origins of adaptive functions remain poorly understood, despite considerable interest1-5. Here, we report the de novo evolution of population-level feedback control in clonal Escherichia coli strains containing high-copy plasmids, enabling these strains to express green fluorescent protein (GFP) in response to tetracycline. Selection maintains tetA+ and tetA- plasmids within single cells, due to negative feedback from the toxic effects of a tetA-gfp tetracycline resistance transposon. At high plasmid copy numbers, the intracellular equilibrium of tetA+ and tetA- plasmids robustly responds to tetracycline through rapid evolutionary dynamics6-8. Theory predicts that the GFP response to tetracycline is determined by the covariance between GFP expression and bacterial fitness. Our findings show that small mutational changes can result in large qualitative changes to population-level behavior. Here, the evolution of polymorphic intracellular populations of mobile genetic elements allows host populations to dynamically respond to antibiotic in the environment.

systems biology↗

bioRxiv2025

Linear scaling reveals low-dimensional structure in observable microbial dynamics

Microbial communities often exhibit apparently complex dynamics driven by myriad interactions among community members and with their environments. Yet, practical modeling and control are often based on limited number of observables, raising a fundamental question: to what extent are these observed dynamics predictable given unobserved background complexity? Here, we report an emergent simplicity that the temporal dynamics of observable microbial populations can be captured by low- dimensional representations. Using variational autoencoders (VAEs), we define a critical latent dimension (Ec) that quantifies the minimal number of variables required to represent observable microbial dynamics. We find that Ec scales linearly with the number of observables, despite the complexity of unobserved background dynamics. This principle holds across simulations of ecological, spatial, and gene-transfer models, experiments with engineered and environment-derived communities, and human microbiomes. Our findings establish a scaling law for microbial community dynamics and demonstrate observable dynamics alone contain sufficient information for prediction and control, even without full knowledge of the community.

systems biology↗

bioRxiv2023

Programming dynamic division of labor using horizontal gene transfer

The metabolic engineering of microbes has broad applications, including in biomanufacturing, bioprocessing, and environmental remediation. The introduction of a complex, multi-step pathway often imposes a substantial metabolic burden on the host cell, restraining the accumulation of productive biomass and limiting pathway efficiency. One strategy to alleviate metabolic burden is division of labor (DOL), in which different subpopulations carry out different parts of the pathway and work together to convert a substrate into a final product. However, the maintenance of different engineered subpopulations is challenging due to competition and convoluted inter-strain population dynamics. Through modeling, we show that dynamic division of labor (DDOL) mediated by horizontal gene transfer (HGT) can overcome these limitations and enable the robust maintenance of burdensome, multi-step pathways. We also use plasmid genomics to uncover evidence that DDOL is a strategy utilized by natural microbial communities. Our work suggests that bioengineers can harness HGT to stabilize synthetic metabolic pathways in microbial communities, enabling the development of robust engineered systems for deployment in a variety of contexts.

synthetic biology↗

bioRxiv2021

Engineered chimeras unveil swappable modular features of fatty acid and polyketide synthase acyl carrier proteins

The strategic redesign of microbial biosynthetic pathways is a compelling route to access molecules of diverse structure and function in a potentially environmentally sustainable fashion. The promise of this approach hinges on an improved understanding of acyl carrier proteins (ACPs), which serve as central hubs in biosynthetic pathways. These small, flexible proteins mediate the transport of molecular building blocks and intermediates to enzymatic partners that extend and tailor the growing natural products. Past combinatorial biosynthesis efforts have failed due to incompatible ACP-enzyme pairings. Herein we report the design of chimeric ACPs with features of the actinorhodin polyketide synthase ACP (ACT) and of the E. coli fatty acid synthase (FAS) ACP (AcpP). We evaluate the ability of the chimeric ACPs to interact with the E. coli FAS ketosynthase FabF, which represents an interaction essential to building the carbon backbone of the synthase molecular output. Given that AcpP interacts with FabF but ACT does not, we sought to exchange modular features of ACT with AcpP to confer functionality with FabF. The interactions of chimeric ACPs with FabF were interrogated using sedimentation velocity experiments, surface plasmon resonance analyses, mechanism-based crosslinking assays, and molecular dynamics simulations. Results suggest that the residues guiding AcpP-FabF compatibility and ACT-FabF incompatibility may reside in the loop I, -helix II region. These findings can inform the development of strategic secondary element swaps that expand the enzyme compatibility of ACPs across systems and therefore represent a critical step towards the strategic engineering of unnatural natural products.

biochemistry↗