Nutrient-Dependent Trade-Offs between Ribosomes and Division Protein Synthesis Control Bacterial Cell Size and Growth

Impacts of ribosomal RNA sequence variation on gene expression and phenotype

Since the framing of the Central Dogma, it has been speculated that physically distinct ribosomes within cells may influence gene expression and cellular physiology. While heterogeneity in ribosome composition has been reported in bacteria, protozoans, fungi, zebrafish, mice and humans, its functional implications remain actively debated. Here, we review recent evidence demonstrating that expression of conserved variant ribosomal DNA (rDNA) alleles in bacteria, mice and humans renders their actively translating ribosome pool intrinsically heterogeneous at the level of ribosomal RNA (rRNA). In this context, we discuss reports that nutrient limitation-induced stress in Escherichia coli leads to changes in variant rRNA allele expression, programmatically altering transcription and cellular phenotype. We highlight that cells expressing ribosomes from distinct operons exhibit distinct drug sensitivities, which can be recapitulated in vitro and potentially rationalized by subtle perturbations in ribosome structure or in their dynamic properties. Finally, we discuss evidence that differential expression of variant rDNA alleles results in different populations of ribosome subtypes within mammalian tissues. These findings motivate further research into the impacts of rRNA heterogeneities on ribosomal function and predict that strategies targeting distinct ribosome subtypes may hold therapeutic potential.This article is part of the discussion meeting issue 'Ribosome diversity and its impact on protein synthesis, development and disease'.

Antibiotics change the population growth rate heterogeneity and morphology of bacteria

A better understanding of the system-level effects of antibiotics on bacterial cells is essential to address the growing challenge of antibiotic resistance. Utilising Multipad Agarose Plate (MAP) platforms, we monitor the growth rate and cell morphology of three clinically relevant species (E.coli, S.aureus and P.aeruginosa) following exposure to 14 antibiotics across 11 concentrations (31 microbe-antibiotic combinations in total). Our results reveal a consistent increase in population growth rate heterogeneity (PGRH) as drug concentrations approach the minimum inhibitory concentration (MIC). Strikingly, the magnitude of this heterogeneity correlates with the functional distance between the ribosome and the specific cellular processes targeted by the antibiotics. Among the seven antibiotic classes studied, protein synthesis inhibitors and disruptors cause the lowest PGRH, while heterogeneity progressively increases with RNA synthesis inhibitors, DNA replication inhibitors, cell membrane disruptors and cell wall synthesis inhibitors. Because the ribosome is central to growth rate control, we hypothesize that heterogeneity might arise at the system level as a result of the propagation of damage to protein synthesis. Low heterogeneity is desirable from a clinical perspective, as high heterogeneity is often associated with persistence and treatment survival. Additionally, we observed a strong correlation between morphological alterations and growth inhibition across all antibiotics and species tested. This led to the development of a novel morphological parameter, MOR50, which enables rapid estimation of MIC for antibiotic susceptibility testing (AST) with a single snapshot after just 2.5 hours of incubation. In addition to introducing a novel, resource-efficient and rapid AST method, our findings shed new light on the system-level effects of antibiotic perturbations on bacteria, which might inform treatment design.

Impact of fleQ Deficiency on Resource Allocation and Heterologous Gene Expression in Pseudomonas putida Across Various Growth Media

Pseudomonas putida is widely used in industrial applications, including the recombinant proteins production, because of its natural advantageous properties. In this study, the gene encoding FleQ, the primary regulator of flagellar synthesis, was deleted to construct a new non-motile P. putida KT2440-derived strain (ΔfleQ). The non-motile cells showed reduced biofilm formation and enhanced expression of a heterologous gene in nutrient-rich media compared with the wild-type (WT) strain, attributed to the reallocation of cellular resources from flagellar synthesis and cellular motility. Additionally, the ΔfleQ strain exhibited enhanced tolerance to chloramphenicol, indicating higher ribosome production, confirmed by a higher RNA/protein ratio relative to the WT. While the WT strain showed decreased growth and a three-fold increase in reporter gene activity in minimal media, the ΔfleQ strain maintained consistent reporter gene expression and exhibited a relatively higher growth rate. This suggests that the FleQ is involved in modulating proteome allocation based on nutrient quality. The removal of FleQ allows for more flexible resource allocation, creating a chassis strain with nutrient quality-independent gene expression capacity, which could be valuable in industrial applications where consistent output is essential.

Eukaryotic cell size regulation and its implications for cellular function and dysfunction

Depending on cell type, environmental inputs, and disease, the cells in the human body can have widely different sizes. In recent years, it has become clear that cell size is a major regulator of cell function. However, we are only beginning to understand how the optimization of cell function determines a given cell's optimal size. Here, we review currently known size control strategies of eukaryotic cells and the intricate link of cell size to intracellular biomolecular scaling, organelle homeostasis, and cell cycle progression. We detail the cell size-dependent regulation of early development and the impact of cell size on cell differentiation. Given the importance of cell size for normal cellular physiology, cell size control must account for changing environmental conditions. We describe how cells sense environmental stimuli, such as nutrient availability, and accordingly adapt their size by regulating cell growth and cell cycle progression. Moreover, we discuss the correlation of pathological states with misregulation of cell size and how for a long time this was considered a downstream consequence of cellular dysfunction. We review newer studies that reveal a reversed causality, with misregulated cell size leading to pathophysiological phenotypes such as senescence and aging. In summary, we highlight the important roles of cell size in cellular function and dysfunction, which could have major implications for both diagnostics and treatment in the clinic.

Deciphering the Relationship between Cell Growth and Cell Cycle in Individual Escherichia coli Cells by Flow Cytometry

Accurate coordination of chromosome replication and cell division is essential for cellular processes, yet the regulatory mechanisms governing the bacterial cell cycle remain contentious. The lack of quantitative data connecting key cell cycle players at the single-cell level across large samples hinders consensus. Employing high-throughput flow cytometry, we quantitatively correlated the expression levels of key cell cycle proteins (FtsZ, MreB, and DnaA) with DNA content in individual bacteria. Our findings reveal distinct correlations depending on the chromosome number (CN), specifically whether CN ≤2 or ≥4, unveiling a mixed regulatory scenario in populations where CN of 2 or 4 coexist. We observed function-dependent regulations for these key proteins across nonoverlapping division cycles and various nutrient conditions. Notably, a logarithmic relationship between total protein content and replication origin number across nutrient conditions suggests a unified mechanism governing cell cycle progression, confirming the applicability of Schaechter's growth law to cells with CN ≥4. For the first time, we established a proportional relationship between the synthesis rates of key cell cycle proteins and chromosome dynamics in cells with CN ≥4. Drug experiments highlighted CN 2 and 4 as pivotal turning points influencing cellular resource allocation. This high-throughput, single-cell analysis provides interconnected quantitative insights into key molecular events, facilitating a predictive understanding of the relationship between cell growth and cell cycle.

Gene expression tradeoffs determine bacterial survival and adaptation to antibiotic stress

To optimize their fitness, cells face the crucial task of efficiently responding to various stresses. This necessitates striking a balance between conserving resources for survival and allocating resources for growth and division. The fundamental principles governing these tradeoffs is an outstanding challenge in the physics of living systems. In this study, we introduce a coarse-grained theoretical framework for bacterial physiology that establishes a connection between the physiological state of cells and their survival outcomes in dynamic environments, particularly in the context of antibiotic exposure. Predicting bacterial survival responses to varying antibiotic doses proves challenging due to the profound influence of the physiological state on critical parameters, such as the Minimum Inhibitory Concentration (MIC) and killing rates, even within an isogenic cell population. Our proposed theoretical model bridges the gap by linking extracellular antibiotic concentration and nutrient quality to intracellular damage accumulation and gene expression. This framework allows us to predict and explain the control of cellular growth rate, death rate, MIC and survival fraction in a wide range of time-varying environments. Surprisingly, our model reveals that cell death is rarely due to antibiotic levels being above the maximum physiological limit, but instead survival is limited by the inability to alter gene expression sufficiently quickly to transition to a less susceptible physiological state. Moreover, bacteria tend to overexpress stress response genes at the expense of reduced growth, conferring greater protection against further antibiotic exposure. This strategy is in contrast to those employed in different nutrient environments, in which bacteria allocate resources to maximize growth rate. This highlights an important tradeoff between the cellular capacity for growth and the ability to survive antibiotic exposure.

Energy allocation theory for bacterial growth control in and out of steady state

Efficient allocation of energy resources to key physiological functions allows living organisms to grow and thrive in diverse environments and adapt to a wide range of perturbations. To quantitatively understand how unicellular organisms utilize their energy resources in response to changes in growth environment, we introduce a theory of dynamic energy allocation which describes cellular growth dynamics based on partitioning of metabolizable energy into key physiological functions: growth, division, cell shape regulation, energy storage and loss through dissipation. By optimizing the energy flux for growth, we develop the equations governing the time evolution of cell morphology and growth rate in diverse environments. The resulting model accurately captures experimentally observed dependencies of bacterial cell size on growth rate, superlinear scaling of metabolic rate with cell size, and predicts nutrient-dependent trade-offs between energy expended for growth, division, and shape maintenance. By calibrating model parameters with available experimental data for the model organism E. coli, our model is capable of describing bacterial growth control in dynamic conditions, particularly during nutrient shifts and osmotic shocks. The model captures these perturbations with minimal added complexity and our unified approach predicts the driving factors behind a wide range of observed morphological and growth phenomena.

Pairing metagenomics and metaproteomics to characterize ecological niches and metabolic essentiality of gut microbiomes

The genome of a microorganism encodes its potential functions that can be implemented through expressed proteins. It remains elusive how a protein's selective expression depends on its metabolic essentiality to microbial growth or its ability to claim resources as ecological niches. To reveal a protein's metabolic or ecological role, we developed a computational pipeline, which pairs metagenomics and metaproteomics data to quantify each protein's gene-level and protein-level functional redundancy simultaneously. We first illustrated the idea behind the pipeline using simulated data of a consumer-resource model. We then validated it using real data from human and mouse gut microbiome samples. In particular, we analyzed ABC-type transporters and ribosomal proteins, confirming that the metabolic and ecological roles predicted by our pipeline agree well with prior knowledge. Finally, we performed in vitro cultures of a human gut microbiome sample and investigated how oversupplying various sugars involved in ecological niches influences the community structure and protein abundance. The presented results demonstrate the performance of our pipeline in identifying proteins' metabolic and ecological roles, as well as its potential to help us design nutrient interventions to modulate the human microbiome.

Gene Expression Tradeoffs Determine Bacterial Survival and Adaptation to Antibiotic Stress

To optimize their fitness, cells face the crucial task of efficiently responding to various stresses. This necessitates striking a balance between conserving resources for survival and allocating resources for growth and division. The fundamental principles governing these tradeoffs is an outstanding challenge in the physics of living systems. In this study, we introduce a coarse-grained theoretical framework for bacterial physiology that establishes a connection between the physiological state of cells and their survival outcomes in dynamic environments, particularly in the context of antibiotic exposure. Predicting bacterial survival responses to varying antibiotic doses proves challenging due to the profound influence of the physiological state on critical parameters, such as the minimum inhibitory concentration (MIC) and killing rates, even within an isogenic cell population. Our proposed theoretical model bridges the gap by linking extracellular antibiotic concentration and nutrient quality to intracellular damage accumulation and gene expression. This framework allows us to predict and explain the control of cellular growth rate, death rate, MIC, and survival fraction in a wide range of time-varying environments. Surprisingly, our model reveals that cell death is rarely due to antibiotic levels being above the maximum physiological limit, but instead survival is limited by the inability to alter gene expression sufficiently quickly to transition to a less susceptible physiological state. Moreover, bacteria tend to overexpress stress response genes at the expense of reduced growth, conferring greater protection against further antibiotic exposure. This strategy is in contrast to those employed in different nutrient environments, in which bacteria allocate resources to maximize growth rate. This highlights an important tradeoff between the cellular capacity for growth and the ability to survive antibiotic exposure.

Implications of differential size-scaling of cell-cycle regulators on cell size homeostasis

Accurate timing of division and size homeostasis is crucial for cells. A potential mechanism for cells to decide the timing of division is the differential scaling of regulatory protein copy numbers with cell size. However, it remains unclear whether such a mechanism can lead to robust growth and division, and how the scaling behaviors of regulatory proteins influence the cell size distribution. Here we study a mathematical model combining gene expression and cell growth, in which the cell-cycle activators scale superlinearly with cell size while the inhibitors scale sublinearly. The cell divides once the ratio of their concentrations reaches a threshold value. We find that the cell can robustly grow and divide within a finite range of the threshold value with the cell size proportional to the ploidy. In a stochastic version of the model, the cell size at division is uncorrelated with that at birth. Also, the more differential the cell-size scaling of the cell-cycle regulators is, the narrower the cell-size distribution is. Intriguingly, our model with multiple regulators rationalizes the observation that after the deletion of a single regulator, the coefficient of variation of cell size remains roughly the same though the average cell size changes significantly. Our work reveals that the differential scaling of cell-cycle regulators provides a robust mechanism of cell size control.

Dynamic proteome trade-offs regulate bacterial cell size and growth in fluctuating nutrient environments

Bacteria dynamically regulate cell size and growth to thrive in changing environments. While previous studies have characterized bacterial growth physiology at steady-state, a quantitative understanding of bacterial physiology in time-varying environments is lacking. Here we develop a quantitative theory connecting bacterial growth and division rates to proteome allocation in time-varying nutrient environments. In such environments, cell size and growth are regulated by trade-offs between prioritization of biomass accumulation or division, resulting in decoupling of single-cell growth rate from population growth rate. Specifically, bacteria transiently prioritize biomass accumulation over production of division machinery during nutrient upshifts, while prioritizing division over growth during downshifts. When subjected to pulsatile nutrient concentration, we find that bacteria exhibit a transient memory of previous metabolic states due to the slow dynamics of proteome reallocation. This allows for faster adaptation to previously seen environments and results in division control which is dependent on the time-profile of fluctuations.

Bacterial Subcellular Architecture, Structural Epistasis, and Antibiotic Resistance

Epistasis refers to the way in which genetic interactions between some genetic loci affect phenotypes and fitness. In this study, we propose the concept of "structural epistasis" to emphasize the role of the variable physical interactions between molecules located in particular spaces inside the bacterial cell in the emergence of novel phenotypes. The architecture of the bacterial cell (typically Gram-negative), which consists of concentrical layers of membranes, particles, and molecules with differing configurations and densities (from the outer membrane to the nucleoid) determines and is in turn determined by the cell shape and size, depending on the growth phases, exposure to toxic conditions, stress responses, and the bacterial environment. Antibiotics change the bacterial cell's internal molecular topology, producing unexpected interactions among molecules. In contrast, changes in shape and size may alter antibiotic action. The mechanisms of antibiotic resistance (and their vectors, as mobile genetic elements) also influence molecular connectivity in the bacterial cell and can produce unexpected phenotypes, influencing the action of other antimicrobial agents.

Untargeted proteomic differences between clinical strains of methicillin-sensitive and methicillin-resistant Staphylococcusaureus

Staphylococcus aureus is a common disease-causing bacterium that has developed resistances to a wide variety of antibiotics. This increasing antibiotic resistance has made management of these infections difficult. A better understanding of the general differences among clinical S. aureus strains beyond the well characterized resistance mechanisms may help in identifying new anti-microbial targets. This study aimed to identify and compare the general differences in protein profiles among clinical strains of S. aureus sensitive and resistant to methicillin. The proteomic profiles of five methicillin sensitive (MSSA) and five methicillin resistant (MRSA) S. aureus strains were analyzed by ultra-performance liquid chromatography-mass spectrometry. Protein identification was done using Progenesis QI for Proteomics and the UniProt S. aureus database. Proteins that play roles in virulence, metabolism, and protein synthesis were found to be present at different abundances between MSSA and MRSA (Data available via ProteomeXchange with identifier PXD021629). This study shows differences in protein profiles between antibiotic sensitive and antibiotic resistant clinical strains of S. aureus that may affect the resistance mechanism. Further research on these differences may identify new drug targets against methicillin resistant S. aureus strains.

Super-exponential growth and stochastic size dynamics in rod-like bacteria

Proliferating bacterial cells exhibit stochastic growth and size dynamics, but the regulation of noise in bacterial growth and morphogenesis remains poorly understood. A quantitative understanding of morphogenetic noise control, and how it changes under different growth conditions, would provide better insights into cell-to-cell variability and intergenerational fluctuations in cell physiology. Using multigenerational growth and width data of single Escherichia coli and Caulobacter crescentus cells, we deduce the equations governing growth and size dynamics of rod-like bacterial cells. Interestingly, we find that both E. coli and C. crescentus cells deviate from exponential growth within the cell cycle. In particular, the exponential growth rate increases during the cell cycle irrespective of nutrient or temperature conditions. We propose a mechanistic model that explains the emergence of super-exponential growth from autocatalytic production of ribosomes coupled to the rate of cell elongation and surface area synthesis. Using this new model and statistical inference on large datasets, we construct the Langevin equations governing cell growth and size dynamics of E. coli cells in different nutrient conditions. The single-cell level model predicts how noise in intragenerational and intergenerational processes regulate variability in cell morphology and generation times, revealing quantitative strategies for cellular resource allocation and morphogenetic noise control in different growth conditions.

Characterization of proteome-size scaling by integrative omics reveals mechanisms of proliferation control in cancer

Almost all living cells maintain size uniformity through successive divisions. Proteins that over and underscale with size can act as rheostats, which regulate cell cycle progression. Using a multiomic strategy, we leveraged the heterogeneity of melanoma cell lines to identify peptides, transcripts, and phosphorylation events that differentially scale with cell size. Subscaling proteins are enriched in regulators of the DNA damage response and cell cycle progression, whereas super-scaling proteins included regulators of the cytoskeleton, extracellular matrix, and inflammatory response. Mathematical modeling suggested that decoupling growth and proliferative signaling may facilitate cell cycle entry over senescence in large cells when mitogenic signaling is decreased. Regression analysis reveals that up-regulation of TP53 or CDKN1A/p21CIP1 is characteristic of proliferative cancer cells with senescent-like sizes/proteomes. This study provides one of the first demonstrations of size-scaling phenomena in cancer and how morphology influences the chemistry of the cell.

Cellular resource allocation strategies for cell size and shape control in bacteria

Bacteria are highly adaptive microorganisms that thrive in a wide range of growth conditions via changes in cell morphologies and macromolecular composition. How bacterial morphologies are regulated in diverse environmental conditions is a long-standing question. Regulation of cell size and shape implies control mechanisms that couple the growth and division of bacteria to their cellular environment and macromolecular composition. In the past decade, simple quantitative laws have emerged that connect cell growth to proteomic composition and the nutrient availability. However, the relationships between cell size, shape, and growth physiology remain challenging to disentangle and unifying models are lacking. In this review, we focus on regulatory models of cell size control that reveal the connections between bacterial cell morphology and growth physiology. In particular, we discuss how changes in nutrient conditions and translational perturbations regulate the cell size, growth rate, and proteome composition. Integrating quantitative models with experimental data, we identify the physiological principles of bacterial size regulation, and discuss the optimization strategies of cellular resource allocation for size control.

Effects of antibiotics on bacterial cell morphology and their physiological origins

Characterizing the physiological response of bacterial cells to antibiotic treatment is crucial for the design of antibacterial therapies and for understanding the mechanisms of antibiotic resistance. While the effects of antibiotics are commonly characterized by their minimum inhibitory concentrations or the minimum bactericidal concentrations, the effects of antibiotics on cell morphology and physiology are less well characterized. Recent technological advances in single-cell studies of bacterial physiology have revealed how different antibiotic drugs affect the physiological state of the cell, including growth rate, cell size and shape, and macromolecular composition. Here, we review recent quantitative studies on bacterial physiology that characterize the effects of antibiotics on bacterial cell morphology and physiological parameters. In particular, we present quantitative data on how different antibiotic targets modulate cellular shape metrics including surface area, volume, surface-to-volume ratio, and the aspect ratio. Using recently developed quantitative models, we relate cell shape changes to alterations in the physiological state of the cell, characterized by changes in the rates of cell growth, protein synthesis and proteome composition. Our analysis suggests that antibiotics induce distinct morphological changes depending on their cellular targets, which may have important implications for the regulation of cellular fitness under stress.

A deep-sea sulfate-reducing bacterium generates zero-valent sulfur via metabolizing thiosulfate

Zero-valent sulfur (ZVS) is a crucial intermediate in the sulfur geobiochemical circulation and is widespread in deep-sea cold seeps. Sulfur-oxidizing bacteria are thought to be the major contributors to the formation of ZVS. However, ZVS production mediated by sulfate-reducing bacteria (SRB) has rarely been reported. In this study, we isolated and cultured a typical SRB designated Oceanidesulfovibrio marinus CS1 from deep-sea cold seep sediment in the South China Sea. We show that O. marinus CS1 forms ZVS in the medium supplemented with thiosulfate. Proteomic and protein activity assays revealed that thiosulfate reductase (PhsA) and the sulfide:quinone oxidoreductase (SQR) played key roles in driving ZVS formation in O. marinus CS1. During this process, thiosulfate firstly was reduced by PhsA to form sulfide, then sulfide was oxidized by SQR to produce ZVS. The expressions of PhsA and SQR were significantly upregulated when O. marinus CS1 was cultured in a deep-sea cold seep, strongly indicating that strain CS1 might form ZVS in the deep-sea environment. Notably, homologs of phsA and sqr were widely identified from microbes living in sediments of deep-sea cold seep in the South China Sea by the metagenomic analysis. We thus propose that SRB containing phsA and sqr genes potentially contribute to the formation of ZVS in deep-sea cold seep environments.

Filamentous morphology of bacterial pathogens: regulatory factors and control strategies

Several studies have demonstrated that when exposed to physical, chemical, and biological stresses in the environment, many bacteria (Gram-positive and Gram-negative) change their morphology from a normal cell to a filamentous shape. The formation of filamentous morphology is one of the survival strategies against environmental stress and protection against phagocytosis or protist predators. Numerous pathogenic bacteria have shown filamentous morphologies when examined in vivo or in vitro. During infection, certain pathogenic bacteria adopt a filamentous shape inside the cell to avoid phagocytosis by immune cells. Filamentous morphology has also been seen in biofilms formed on biotic or abiotic surfaces by certain bacteria. As a result, in addition to protecting against phagocytosis by immune cells or predators, the filamentous shape aids in biofilm adhesion or colonization to biotic or abiotic surfaces. Furthermore, these filamentous morphologies of bacterial pathogens lead to antimicrobial drug resistance. Clinically, filamentous morphology has become one of the most serious challenges in treating bacterial infection. The current review went into great detail about the various factors involved in the change of filamentous morphology and the underlying mechanisms. In addition, the review discussed a control strategy for suppressing filamentous morphology in order to combat bacterial infections. Understanding the mechanism underlying the filamentous morphology induced by various environmental conditions will aid in drug development and lessen the virulence of bacterial pathogens. KEY POINTS: • The bacterial filamentation morphology is one of the survival mechanisms against several environmental stress conditions and protection from phagocytosis by host cells and protist predators. • The filamentous morphologies in bacterial pathogens contribute to enhanced biofilm formation, which develops resistance properties against antimicrobial drugs. • Filamentous morphology has become one of the major hurdles in treating bacterial infection, hence controlling strategies employed for inhibiting the filamentation morphology from combating bacterial infections.

An expanded whole-cell model of E. coli links cellular physiology with mechanisms of growth rate control

Growth and environmental responses are essential for living organisms to survive and adapt to constantly changing environments. In order to simulate new conditions and capture dynamic responses to environmental shifts in a developing whole-cell model of E. coli, we incorporated additional regulation, including dynamics of the global regulator guanosine tetraphosphate (ppGpp), along with dynamics of amino acid biosynthesis and translation. With the model, we show that under perturbed ppGpp conditions, small molecule feedback inhibition pathways, in addition to regulation of expression, play a role in ppGpp regulation of growth. We also found that simulations with dysregulated amino acid synthesis pathways provide average amino acid concentration predictions that are comparable to experimental results but on the single-cell level, concentrations unexpectedly show regular fluctuations. Additionally, during both an upshift and downshift in nutrient availability, the simulated cell responds similarly with a transient increase in the mRNA:rRNA ratio. This additional simulation functionality should support a variety of new applications and expansions of the E. coli Whole-Cell Modeling Project.

Antibiotic Resistance via Bacterial Cell Shape-Shifting

Bacteria have evolved to develop multiple strategies for antibiotic resistance by effectively reducing intracellular antibiotic concentrations or antibiotic binding affinities, but the role of cell morphology in antibiotic resistance remains poorly understood. By analyzing cell morphological data for different bacterial species under antibiotic stress, we find that bacteria increase or decrease the cell surface-to-volume ratio depending on the antibiotic target. Using quantitative modeling, we show that by reducing the surface-to-volume ratio, bacteria can effectively reduce the intracellular antibiotic concentration by decreasing antibiotic influx. The model further predicts that bacteria can increase the surface-to-volume ratio to induce the dilution of membrane-targeting antibiotics, in agreement with experimental data. Using a whole-cell model for the regulation of cell shape and growth by antibiotics, we predict shape transformations that bacteria can utilize to increase their fitness in the presence of antibiotics. We conclude by discussing additional pathways for antibiotic resistance that may act in synergy with shape-induced resistance.

The role of sigma factor competition in bacterial adaptation under prolonged starvation

The study of adaptive microbial evolution in the laboratory can illuminate the genetic mechanisms of gaining fitness under a pre-defined set of selection factors. Laboratory evolution of bacteria under long-term starvation has gained importance in recent years because of its ability to uncover adaptive strategies that overcome prolonged nutrient limitation, a condition often encountered by natural microbes. In this evolutionary paradigm, bacteria are maintained in an energy-restricted environment in a growth phase called long-term stationary phase (LTSP). This phase is characterized by a stable, viable population size and highly dynamic genetic changes. Multiple independent iterations of LTSP evolution experiments have given rise to mutants that are slow-growing compared to the ancestor. Although the antagonistic regulation between rapid growth and the stress response is well-known in bacteria (especially Escherichia coli), the growth deficit of many LTSP-adapted mutants has not been explored in detail. In this review, I pinpoint the trade-off between growth and stress response as a dominant driver of evolutionary strategies under prolonged starvation. Focusing on mainly E. coli-based research, I discuss the various affectors and regulators of the competition between sigma factors to occupy their targets on the genome, and assess its effect on growth advantage in stationary phase (GASP). Finally, I comment on some crucial issues that hinder the progress of the field, including identification of novel metabolites in nutrient-depleted media, and the importance of using multidisciplinary research to resolve them.

Quantitative Examination of Five Stochastic Cell-Cycle and Cell-Size Control Models for Escherichia coli and Bacillus subtilis

We examine five quantitative models of the cell-cycle and cell-size control in Escherichia coli and Bacillus subtilis that have been proposed over the last decade to explain single-cell experimental data generated with high-throughput methods. After presenting the statistical properties of these models, we test their predictions against experimental data. Based on simple calculations of the defining correlations in each model, we first dismiss the stochastic Helmstetter-Cooper model and the Initiation Adder model, and show that both the Replication Double Adder (RDA) and the Independent Double Adder (IDA) model are more consistent with the data than the other models. We then apply a recently proposed statistical analysis method and obtain that the IDA model is the most likely model of the cell cycle. By showing that the RDA model is fundamentally inconsistent with size convergence by the adder principle, we conclude that the IDA model is most consistent with the data and the biology of bacterial cell-cycle and cell-size control. Mechanistically, the Independent Adder Model is equivalent to two biological principles: (i) balanced biosynthesis of the cell-cycle proteins, and (ii) their accumulation to a respective threshold number to trigger initiation and division.

A stochastic model of homeostasis: The roles of noise and nuclear positioning in deciding cell fate

We study a population-based cellular model that starts from a single stem cell that divides stochastically to give rise to either daughter stem cells or differentiated daughter cells. There are three main components in the model: nucleus position, the underlying gene-regulatory network, and stochastic segregation of transcription factors in the daughter cells. The proportion of self-renewal and differentiated cell lines as a function of the nucleus position which in turn decides the plane of cleavage is studied. Both nuclear position and noise play an important role in determining the stem cell genealogies. We have observed both long and short genealogies in model simulation, and these compare well with experimental results from neuroblast and B-cell division. Symmetric divisions are observed in apical nuclei, while asymmetric division occurs when the nucleus is toward the base. In this model, the number of clones decreases over time, although the average clone size increases.

Two different cell-cycle processes determine the timing of cell division in Escherichia coli

Cells must control the cell cycle to ensure that key processes are brought to completion. In Escherichia coli, it is controversial whether cell division is tied to chromosome replication or to a replication-independent inter-division process. A recent model suggests instead that both processes may limit cell division with comparable odds in single cells. Here, we tested this possibility experimentally by monitoring single-cell division and replication over multiple generations at slow growth. We then perturbed cell width, causing an increase of the time between replication termination and division. As a consequence, replication became decreasingly limiting for cell division, while correlations between birth and division and between subsequent replication-initiation events were maintained. Our experiments support the hypothesis that both chromosome replication and a replication-independent inter-division process can limit cell division: the two processes have balanced contributions in non-perturbed cells, while our width perturbations increase the odds of the replication-independent process being limiting.

Directed evolution of rRNA improves translation kinetics and recombinant protein yield

In bacteria, ribosome kinetics are considered rate-limiting for protein synthesis and cell growth. Enhanced ribosome kinetics may augment bacterial growth and biomanufacturing through improvements to overall protein yield, but whether this can be achieved by ribosome-specific modifications remains unknown. Here, we evolve 16S ribosomal RNAs (rRNAs) from Escherichia coli, Pseudomonas aeruginosa, and Vibrio cholerae towards enhanced protein synthesis rates. We find that rRNA sequence origin significantly impacted evolutionary trajectory and generated rRNA mutants with augmented protein synthesis rates in both natural and engineered contexts, including the incorporation of noncanonical amino acids. Moreover, discovered consensus mutations can be ported onto phylogenetically divergent rRNAs, imparting improved translational activities. Finally, we show that increased translation rates in vivo coincide with only moderately reduced translational fidelity, but do not enhance bacterial population growth. Together, these findings provide a versatile platform for development of unnatural ribosomal functions in vivo.

Fundamental limits on the rate of bacterial growth and their influence on proteomic composition

Despite abundant measurements of bacterial growth rate, cell size, and protein content, we lack a rigorous understanding of what sets the scale of these quantities and when protein abundances should (or should not) depend on growth rate. Here, we estimate the basic requirements and physical constraints on steady-state growth by considering key processes in cellular physiology across a collection of Escherichia coli proteomic data covering ≈4,000 proteins and 36 growth rates. Our analysis suggests that cells are predominantly tuned for the task of cell doubling across a continuum of growth rates; specific processes do not limit growth rate or dictate cell size. We present a model of proteomic regulation as a function of nutrient supply that reconciles observed interdependences between protein synthesis, cell size, and growth rate and propose that a theoretical inability to parallelize ribosomal synthesis places a firm limit on the achievable growth rate. A record of this paper's transparent peer review process is included in the supplemental information.

Kinetic, metabolic, and statistical analytics: addressing metabolic transport limitations among organelles and microbial communities

Microbial organisms engage in a variety of metabolic interactions. A crucial part of these interactions is the exchange of molecules between different organelles, cells, and the environment. The main forces mediating this metabolic exchange are transporters. This transport can be difficult to measure experimentally because several transport mechanisms remain opaque. However, theoretical calculations about the inputs and outputs of cells via metabolic exchanges have enabled the successful inference of the workings of intra-organismal and inter-organismal systems. Kinetic, metabolic, and statistical modeling approaches in combination with omics data are enhancing our knowledge and understanding about metabolic exchange and mass resource allocation. This model-driven analytics approach can guide effective experimental design and yield new insights into biological function and control.

Threshold accumulation of a constitutive protein explains E. coli cell-division behavior in nutrient upshifts

Despite a boost of recent progress in dynamic single-cell measurements and analyses in Escherichia coli, we still lack a mechanistic understanding of the determinants of the decision to divide. Specifically, the debate is open regarding the processes linking growth and chromosome replication to division and on the molecular origin of the observed "adder correlations," whereby cells divide, adding roughly a constant volume independent of their initial volume. In order to gain insight into these questions, we interrogate dynamic size-growth behavior of single cells across nutrient upshifts with a high-precision microfluidic device. We find that the division rate changes quickly after nutrients change, much before growth rate goes to a steady state, and in a way that adder correlations are robustly conserved. Comparison of these data to simple mathematical models falsifies proposed mechanisms, where replication-segregation or septum completions are the limiting step for cell division. Instead, we show that the accumulation of a putative constitutively expressed "P-sector divisor" protein explains the behavior during the shift.

Bacterial cell shape control by nutrient-dependent synthesis of cell division inhibitors

By analyzing cell size and shapes of the bacterium Bacillus subtilis under nutrient perturbations, protein depletion, and antibiotic treatments, we find that cell geometry is extremely robust, reflected in a well-conserved scaling relation between surface area (S) and volume (V), S∼V^γ, with γ=0.85. We develop a molecular model supported by single-cell simulations to predict that the surface-to-volume scaling exponent γ is regulated by nutrient-dependent production of metabolic enzymes that act as cell division inhibitors in bacteria. Using theory that is supported by experimental data, we predict the modes of cell shape transformations in different bacterial species and propose a mechanism of cell shape adaptation to different nutrient perturbations. For organisms with high surface-to-volume scaling exponent γ, such as B. subtilis, cell width is not sensitive to growth-rate changes, whereas organisms with low γ, such as Acinetobacter baumannii, cell shape adapts readily to growth-rate changes.

Cell Size Is Coordinated with Cell Cycle by Regulating Initiator Protein DnaA in E. coli

Sixty years ago, bacterial cell size was found to be an exponential function of growth rate. Fifty years ago, a more general relationship was proposed, in which cell mass was equal to the initiation mass multiplied by 2 to the power of the ratio of the total time of C and D periods to the doubling time. This relationship has recently been experimentally confirmed by perturbing doubling time, C period, D period, or initiation mass. However, the underlying molecular mechanism remains unclear. Here, we developed a theoretical model for initiator protein DnaA mediating DNA replication initiation in Escherichia coli. We introduced an initiation probability function for competitive binding of DnaA-ATP and DnaA-ADP at oriC. We established a kinetic description of regulatory processes (e.g., expression regulation, titration, inactivation, and reactivation) of DnaA. Cell size as a spatial constraint also participates in the regulation of DnaA. By simulating DnaA kinetics, we obtained a regular DnaA oscillation coordinated with cell cycle and a converged cell size that matches replication initiation frequency to the growth rate. The relationship between the simulated cell size and growth rate, C period, D period, or initiation mass reproduces experimental results. The model also predicts how DnaA number and initiation mass vary with perturbation parameters, comparable with experimental data. The results suggest that 1) when growth rate, C period, or D period changes, the regulation of DnaA determines the invariance of initiation mass; 2) ppGpp inhibition of replication initiation may be important for the growth rate independence of initiation mass because three possible mechanisms therein produce different DnaA dynamics, which is experimentally verifiable; and 3) perturbation of some DnaA regulatory process causes a changing initiation mass or even an abnormal cell cycle. This study may provide clues for concerted control of cell size and cell cycle in synthetic biology.