Biology subjects

Glass, D. S.

Publications and source records attributed to Glass, D. S..

8 recordsLinked to original sources

bioRxiv2025

Dynamic growth trajectories distinguish bacteriostatic and bactericidal antibiotics at subinhibitory concentrations

Subinhibitory antibiotic exposures are common in clinical and environmental contexts, yet their effects on bacterial growth dynamics remain incompletely understood. We studied the temporal response of Escherichia coli to a panel of bactericidal ("cidal") and bacteriostatic ("static") antibiotics at sub-minimum inhibitory concentrations (sub-MIC). We uncover a sharp dynamical distinction between the two classes. Bacteriostatic antibiotics reduce the initial growth rate in a dose-dependent manner, similar to a nutrient starvation response. In contrast, bactericidal antibiotics do not alter initial growth rates - cells continue to grow as fast as untreated cells - until an abrupt slowdown in growth rate. The onset of slowdown occurs earlier with increasing dose, suggesting a damage accumulation mechanism leading to a lethal threshold. Cidals also show a steeper dose-response curve. We propose that bacteria respond to cidal antibiotics with a "grow-fast-then-crash" strategy that is adaptive for transient lethal threats, whereas static antibiotics trigger stress adaptation and slower growth. While clinical outcomes of statics and cidals may be similar at full inhibitory doses, these sub-MIC dynamical signatures could influence resistance evolution and treatment outcomes in biofilms or partially resistant strains. Our findings offer a dynamic framework for antibiotic classification and raise new questions about how bacteria respond to sublethal antibiotic stress.

systems biology↗

bioRxiv2024

Unifying regulatory motifs in endocrine circuits

In this study we identify unifying design principles in human endocrine systems. We find that 43 hormone systems, controlling diverse physiological functions, fall into 5 classes of circuits with shared structure - thus only a small number of the possible circuits actually occur. Each class uses a different regulatory logic to perform specific dynamical functions, such as homeostasis, acute input-output response or adjustable set points. The circuits employ interactions on two timescales: hormone secretion on the scale of minutes-hours and growth and shrinkage of endocrine gland mass on the scale of months, which impacts the amount of hormone the glands secrete. This two-timescale principle recurs in several classes of circuits, including the most complex class, which has an intermediate gland, the pituitary. We analyze the pituitary circuit in detail and find tradeoffs between endocrine amplification, buffering of hypersecreting tumors, and rapid response times. These unifying principles of regulation build a foundation for systems endocrinology.

systems biology↗

bioRxiv2024

Preventing plasmid multimer formation in commonly used synthetic biology plasmids

Plasmids are an essential tool for basic research and biotechnology applications. To optimize plasmid-based circuits, it is crucial to control plasmid integrity, including the formation of plasmid multimers. Multimers are tandem repeats of entire plasmids formed during replication by failed dimer resolution. Multimers can affect the behavior of synthetic circuits, especially ones that include DNA-editing enzymes. However, occurrence of multimers is not commonly assayed. Here we survey four commonly used plasmid backbones for occurrence of multimers in cloning (JM109) and wild-type (MG1655) strains. We find that multimers occur appreciably only in MG1655, with the fraction of plasmids existing as multimers increasing with both plasmid copy number and culture passaging. In contrast, introduction of multimers into JM109 can produce strains containing only multimers. We present an MG1655{Delta} recA single-locus knockout that avoids multimer production. These results can aid synthetic biologists in improving design and reliability of plasmid-based circuits.

synthetic biology↗

bioRxiv2023

Unifying design principles of endocrine gland mass and its regulatory circuits

Hormones are regulatory molecules that impact physiological functions. Much is known about individual hormones, but general rules that connect the regulatory logic of different hormone systems are limited. In this study, we analyzed a range of human hormone systems using a mathematical approach to integrate knowledge on endocrine cells, target tissues and regulation, to uncover unifying principles and regulatory circuits. We find that the number of cells in an endocrine gland is proportional to the number of cells in its target tissues, as one single endocrine cell serves approximately 2000 target cells. We identified five classes of regulatory circuits, each has specific regulatory functions such as homeostasis or allostasis. The most complex class includes an intermediate gland, the pituitary, which can otherwise be considered redundant and exposes to fragilities. We suggest a tradeoff: with the price of fragilities comes advantages -amplification, buffering of hypersecreting tumors, and faster response times. By elucidating these unifying principles and circuits, this study deepens our understanding of the control of endocrine processes and builds the foundation for systems endocrinology.

physiology↗

bioRxiv2023

Robust differentiation in a synthetic stem-cell circuit

Differentiation is a process fundamental to multicellularity. In its simplest form, differentiation converts self-renewing stem cells into non-proliferative cells with specified function. This process is inherently susceptible to mutant takeover -- mutant stem cells that never differentiate produce excess proliferative daughter cells, driving cancer-like expansion and decreasing the availability of differentiated cells to the organism. It has been proposed that coupling differentiation to an essential trait can select against these mutants by producing a biphasic fitness curve. This would provide mutant stem cells that do not differentiate with a selective disadvantage. However, this theory has yet to be tested experimentally. Here we use "fitness landscape engineering" to design and construct a synthetic biological model of stem cell differentiation in Escherichia coli with biphasic fitness. We find that this circuit is robust to mutations as predicted. Surprisingly, its optimal differentiation rate is robust to a wide range of environmental pressures. This environmental robustness is driven by transit-amplifying cells that differentiate and proliferate irrespective of environment. These results provide new interpretations for natural differentiation mechanisms and suggest strategies for engineering robust, complex multicellular consortia.

synthetic biology↗

bioRxiv2022

Tradeoffs in bacterial physiology determine the efficiency of antibiotic killing

Antibiotics can kill or stop the growth of bacteria, and their effectiveness depends on many factors. It is important to understand the relation between bacterial physiology, the environment and antibiotic action. While many of the mechanistic details of antibiotic action are known, the connection between death rate and bacterial physiology is poorly understood. Death rate in antibiotics has often been shown to rise linearly with growth rate; however, it remains unclear how environmental factors, in concert with whole-cell physiological properties, affect bactericidal activity. To address this, we developed a high-throughput assay to precisely measure antibiotic-mediated bacterial death. We found that death rate is linear in growth rate, but the slope depends on environmental conditions. Specifically, stressors lower the death rate compared to a non-stressed environment with the same growth rate. To understand the role of stress, we developed a mathematical model of bacterial death based on resource allocation that takes into account a newly defined stress-response sector; we identify this sector using RNA-seq. Our model accurately predicts the death rate and minimal inhibitory concentration of antibiotics across a wide range of conditions, including a previously unknown increase in the stress response and protection from death at very low levels of cAMP. The present death-growth model suggests conditions that may improve antibiotic efficacy.

systems biology↗

bioRxiv2020

Nonlinear delay differential equations and their application to modeling biological network motifs

Biological regulatory systems, such as transcription factor or kinase networks, nervous systems and ecological webs, consist of complex dynamical interactions among many components. "Network motif" models focus on small sub-networks to provide quantitative insight into overall behavior. However, conventional network motif models often ignore time delays either inherent to biological processes or associated with multi-step interactions. Here we systematically examine explicit-delay versions of the most common network motifs via delay differential equations (DDEs), both analytically and numerically. We find many broadly applicable results, such as the reduction in number of parameters compared to canonical descriptions via ordinary differential equations (ODE), criteria for when delays may be ignored, a complete phase space for autoregulation, explicit dependence of feedforward loops on a difference of delays, a unified framework for Hill-function logic, and conditions for oscillations and chaos. We emphasize relevance to biological function throughout our analysis, summarize key points in non-mathematical form, and conclude that explicit-delay modeling simplifies the phenomenological understanding of many biological networks and may aid in discovering new functional motifs.

systems biology↗

bioRxiv2017

A genetically encoded adhesin toolbox for programming multicellular morphologies and patterns

Synthetic multicellular systems hold promise for understanding natural development of biofilms and higher organisms1,2, as well as for engineering complex multi-component metabolic pathways2,3 and materials4. However, such efforts will require tools to adhere cells into defined morphologies and patterns, and these tools are currently lacking1,5,6. Here we report the first 100% genetically encoded synthetic platform for modular cell-cell adhesion in Escherichia coli, which provides control over multicellular self-assembly. Adhesive selectivity is provided by a library of outer membrane-displayed nanobody7,8 and antigen peptides with orthogonal intra-library specificities, while affinity is controlled by intrinsic adhesin affinity, competitive inhibition, and inducible expression. We demonstrate the resulting capabilities for rational design of well-defined morphologies and patterns through homophilic and heterophilic interactions, lattice-like self-assembly, phase separation, differential adhesion, and sequential layering. This adhesion toolbox, compatible with synthetic biology standards9, will enable construction of high-level multicellular designs and shed light on the evolutionary transition to multicellularity6,10.

synthetic biology↗