From coarse to fine: the absolute Escherichia coli proteome under diverse growth conditions

Proteome allocation is linked to transcriptional regulation through a modularized transcriptome

It has proved challenging to quantitatively relate the proteome to the transcriptome on a per-gene basis. Recent advances in data analytics have enabled a biologically meaningful modularization of the bacterial transcriptome. We thus investigate whether matched datasets of transcriptomes and proteomes from bacteria under diverse conditions can be modularized in the same way to reveal novel relationships between their compositions. We find that; (1) the modules of the proteome and the transcriptome are comprised of a similar list of gene products, (2) the modules in the proteome often represent combinations of modules from the transcriptome, (3) known transcriptional and post-translational regulation is reflected in differences between two sets of modules, allowing for knowledge-mapping when interpreting module functions, and (4) through statistical modeling, absolute proteome allocation can be inferred from the transcriptome alone. Quantitative and knowledge-based relationships can thus be found at the genome-scale between the proteome and transcriptome in bacteria.

Chicken Juice Enhances C. jejuni NCTC 11168 Biofilm Formation with Distinct Morphological Features and Altered Protein Expression

Campylobacter jejuni is the foodborne pathogen causing most gastrointestinal infections. Understanding its ability to form biofilms is crucial for devising effective control strategies in food processing environments. In this study, we investigated the growth dynamics and biofilm formation of C. jejuni NCTC 11168 in various culture media, including chicken juice (CJ), brain heart infusion (BHI), and Mueller Hinton (MH) broth. Our results demonstrated that C. jejuni exhibited a higher growth rate and enhanced biofilm formation in CJ and in 1:1 mixtures of CJ with BHI or MH broth compared to these measures in BHI or MH broth alone. Electron microscopy unveiled distinct morphological attributes of late-stage biofilm cells in CJ, including the presence of elongated spiral-shaped cells, thinner stretched structures compared to regular cells, and extended thread-like structures within the biofilms. Proteomic analysis identified significant alterations in protein expression profiles in C. jejuni biofilms, with a predominance of downregulated proteins associated with vital functions like metabolism, energy production, and amino acid and protein biosynthesis. Additionally, a significant proportion of proteins linked to biofilm formation, virulence, and iron uptake were suppressed. This shift toward a predominantly coccoid morphology echoed the reduced energy demands of these biofilm communities. Our study unlocks valuable insights into C. jejuni's biofilm in CJ, demonstrating its adaptation and survival.

Proteome profiling of Campylobacter jejuni 81-176 at 37 °C and 42 °C by label-free mass spectrometry

BACKGROUND

The main natural reservoir for Campylobacter jejuni is the avian intestinal tract. There, C. jejuni multiplies optimally at 42 °C - the avian body temperature. After infecting humans through oral intake, the bacterium encounters the lower temperature of 37 °C in the human intestinal tract. Proteome profiling by label-free mass spectrometry (DIA-MS) was performed to examine the processes which enable C. jejuni 81-176 to thrive at 37 °C in comparison to 42 °C. In total, four states were compared with each other: incubation for 12 h at 37 °C, for 24 h at 37 °C, for 12 h at 42 °C and 24 h at 42 °C.

RESULTS

It was shown that the proteomic changes not only according to the different incubation temperature but also to the length of the incubation period were evident when comparing 37 °C and 42 °C as well as 12 h and 24 h of incubation. Altogether, the expression of 957 proteins was quantifiable. 37.1 - 47.3% of the proteins analyzed showed significant differential regulation, with at least a 1.5-fold change in either direction (i.e. log2 FC ≥ 0.585 or log2 FC ≤ -0.585) and an FDR-adjusted p-value of less than 0.05. The significantly differentially expressed proteins could be arranged in 4 different clusters and 16 functional categories.

CONCLUSIONS

The C. jejuni proteome at 42 °C is better adapted to high replication rates than that at 37 °C, which was in particular indicated by the up-regulation of proteins belonging to the functional categories "replication" (e.g. Obg, ParABS, and NapL), "DNA synthesis and repair factors" (e.g. DNA-polymerase III, DnaB, and DnaE), "lipid and carbohydrate biosynthesis" (e.g. capsular biosynthesis sugar kinase, PrsA, AccA, and AccP) and "vitamin synthesis, metabolism, cofactor biosynthesis" (e.g. MobB, BioA, and ThiE). The relative up-regulation of proteins with chaperone function (GroL, DnaK, ClpB, HslU, GroS, DnaJ, DnaJ-1, and NapD) at 37 °C in comparison to 42 °C after 12 h incubation indicates a temporary lower-temperature proteomic response. Additionally the up-regulation of factors for DNA uptake (ComEA and RecA) at 37 °C compared to 42 °C indicate a higher competence for the acquisition of extraneous DNA at human body temperature.

Shaping of microbial phenotypes by trade-offs

Growth rate maximization is an important fitness strategy for microbes. However, the wide distribution of slow-growing oligotrophic microbes in ecosystems suggests that rapid growth is often not favored across ecological environments. In many circumstances, there exist trade-offs between growth and other important traits (e.g., adaptability and survival) due to physiological and proteome constraints. Investments on alternative traits could compromise growth rate and microbes need to adopt bet-hedging strategies to improve fitness in fluctuating environments. Here we review the mechanistic role of trade-offs in controlling bacterial growth and further highlight its ecological implications in driving the emergences of many important ecological phenomena such as co-existence, population heterogeneity and oligotrophic/copiotrophic lifestyles.

Proteome partitioning constraints in long-term laboratory evolution

Adaptive laboratory evolution experiments provide a controlled context in which the dynamics of selection and adaptation can be followed in real-time at the single-nucleotide level. And yet this precision introduces hundreds of degrees-of-freedom as genetic changes accrue in parallel lineages over generations. On short timescales, physiological constraints have been leveraged to provide a coarse-grained view of bacterial gene expression characterized by a small set of phenomenological parameters. Here, we ask whether this same framework, operating at a level between genotype and fitness, informs physiological changes that occur on evolutionary timescales. Using a strain adapted to growth in glucose minimal medium, we find that the proteome is substantially remodeled over 40 000 generations. The most striking change is an apparent increase in enzyme efficiency, particularly in the enzymes of lower-glycolysis. We propose that deletion of metabolic flux-sensing regulation early in the adaptation results in increased enzyme saturation and can account for the observed proteome remodeling.

Sm-like protein Rof inhibits transcription termination factor ρ by binding site obstruction and conformational insulation

Transcription termination factor ρ is a hexameric, RNA-dependent NTPase that can adopt active closed-ring and inactive open-ring conformations. The Sm-like protein Rof, a homolog of the RNA chaperone Hfq, inhibits ρ-dependent termination in vivo but recapitulation of this activity in vitro has proven difficult and the precise mode of Rof action is presently unknown. Here, our cryo-EM structures of ρ-Rof and ρ-RNA complexes show that Rof undergoes pronounced conformational changes to bind ρ at the protomer interfaces, undercutting ρ conformational dynamics associated with ring closure and occluding extended primary RNA-binding sites that are also part of interfaces between ρ and RNA polymerase. Consistently, Rof impedes ρ ring closure, ρ-RNA interactions and ρ association with transcription elongation complexes. Structure-guided mutagenesis coupled with functional assays confirms that the observed ρ-Rof interface is required for Rof-mediated inhibition of cell growth and ρ-termination in vitro. Bioinformatic analyses reveal that Rof is restricted to Pseudomonadota and that the ρ-Rof interface is conserved. Genomic contexts of rof differ between Enterobacteriaceae and Vibrionaceae, suggesting distinct modes of Rof regulation. We hypothesize that Rof and other cellular anti-terminators silence ρ under diverse, but yet to be identified, stress conditions when unrestrained transcription termination by ρ may be detrimental.

Concerted transformation of a hyper-paused transcription complex and its reinforcing protein

RfaH, a paralog of the universally conserved NusG, binds to RNA polymerases (RNAP) and ribosomes to activate expression of virulence genes. In free, autoinhibited RfaH, an α-helical KOW domain sequesters the RNAP-binding site. Upon recruitment to RNAP paused at an ops site, KOW is released and refolds into a β-barrel, which binds the ribosome. Here, we report structures of ops-paused transcription elongation complexes alone and bound to the autoinhibited and activated RfaH, which reveal swiveled, pre-translocated pause states stabilized by an ops hairpin in the non-template DNA. Autoinhibited RfaH binds and twists the ops hairpin, expanding the RNA:DNA hybrid to 11 base pairs and triggering the KOW release. Once activated, RfaH hyper-stabilizes the pause, which thus requires anti-backtracking factors for escape. Our results suggest that the entire RfaH cycle is solely determined by the ops and RfaH sequences and provide insights into mechanisms of recruitment and metamorphosis of NusG homologs across all life.

From the outer space to the inner cell: deconvoluting the complexity of Bacillus subtilis disulfide stress responses by redox state and absolute abundance quantification of extracellular, membrane, and cytosolic proteins

Understanding cellular mechanisms of stress management relies on omics data as a valuable resource. However, the lack of absolute quantitative data on protein abundances remains a significant limitation, particularly when comparing protein abundances across different cell compartments. In this study, we aimed to gain deeper insights into the proteomic responses of the Gram-positive model bacterium Bacillus subtilis to disulfide stress. We determined proteome-wide absolute abundances, focusing on different sub-cellular locations (cytosol and membrane) as well as the extracellular medium, and combined these data with redox state determination. To quantify secreted proteins in the culture medium, we developed a simple and straightforward protocol for the absolute quantification of extracellular proteins in bacteria. We concentrated extracellular proteins, which are highly diluted in the medium, using StrataClean beads along with a set of standard proteins to determine the extent of the concentration step. The resulting data set provides new insights into protein abundances in different sub-cellular compartments and the extracellular medium, along with a comprehensive proteome-wide redox state determination. Our study offers a quantitative understanding of disulfide stress management, protein production, and secretion in B. subtilis.

IMPORTANCE

Stress responses play a crucial role in bacterial survival and adaptation. The ability to quantitatively measure protein abundances and redox states in different cellular compartments and the extracellular environment is essential for understanding stress management mechanisms. In this study, we addressed the knowledge gap regarding absolute quantification of extracellular proteins and compared protein concentrations in various sub-cellular locations and in the extracellular medium under disulfide stress conditions. Our findings provide valuable insights into the protein production and secretion dynamics of B. subtilis, shedding light on its stress response strategies. Furthermore, the developed protocol for absolute quantification of extracellular proteins in bacteria presents a practical and efficient approach for future studies in the field. Overall, this research contributes to the quantitative understanding of stress management mechanisms and protein dynamics in B. subtilis, which can be used to enhance bacterial stress tolerance and protein-based biotechnological applications.

Relative impact of three growth conditions on the Escherichia coli protein acetylome

Nε-lysine acetylation is a common posttranslational modification observed in Escherichia coli. In the present study, integrative analysis of the proteome and acetylome was performed using label-free quantitative mass spectrometry to analyze the relative influence of three factors affecting growth. The results revealed differences in the proteome, mainly owing to the type of culture medium used (defined or complex). In the acetylome, 7482 unique acetylation sites were identified. Acetylation is directly related to the abundance of proteins, and the level of acetylation in each type of culture is associated with extracellular acetate concentration. Furthermore, most acetylated lysines in the exponential phase remained in the stationary phase without dynamic turnover. Interestingly, unique acetylation sites were detected in proteins whose presence or abundance was linked to the type of culture medium. Finally, the biological function of the acetylation changes was demonstrated for three central metabolic proteins (GapA, Mdh, and AceA).

Integrated control of bacterial growth and stress response by (p)ppGpp in Escherichia coli: A seesaw fashion

To thrive in nature, bacteria have to reproduce efficiently under favorable conditions and persist during stress. The global strategy that integrates the growth control and stress response remains to be explored. Here, we find that a moderate induction of (p)ppGpp reduces growth rate but significantly enhances the stress tolerance of E. coli, resulting from a global resource re-allocation from ribosome synthesis to the synthesis of stress-responsive proteins. Strikingly, the activation of stress response by (p)ppGpp is still largely retained in the absence of RpoS. In addition, (p)ppGpp induction could activate the catabolism of alanine and arginine, facilitating the adaption of bacteria to nutrient downshift. Our work demonstrates that the activation of stress response by (p)ppGpp could occur in an RpoS-independent manner and (p)ppGpp enables bacteria to integrate the control of growth and stress response in a seesaw fashion, thus acting as an important global regulator of the bacterial fitness landscape.

Reverse stable isotope labelling with Raman spectroscopy for microbial proteomics

Global proteome changes in microbes affect the survival and overall production of commercially relevant metabolites through different bioprocesses. The existing methods to monitor proteome level changes are destructive in nature. Stable isotope probing (SIP) coupled with Raman spectroscopy is a relatively new approach for proteome analysis. However, applying this approach for monitoring changes in a large culture volume is not cost-effective. In this study, for the first time we are presenting a novel method of combining reverse SIP using 13 C-glucose and Deuterium to monitor the proteome changes through Raman spectroscopy. The findings of the study revealed visible changes (blue shifts) in proteome related peaks that can be used for monitoring proteome dynamics, that is, synthesis of nascent amino acids and its turnover with time in a non-destructive, cost-effective, and label-free manner.

Synonymous edits in the Escherichia coli genome have substantial and condition-dependent effects on fitness

CRISPR-Cas-based genome editing is widely used in bacteria at scales ranging from construction of individual mutants to massively parallel libraries. This procedure relies on guide RNA-directed cleavage of the genome followed by repair with a template that introduces a desired mutation along with synonymous "immunizing" mutations to prevent re-cleavage of the genome after editing. Because the immunizing mutations do not change the protein sequence, they are often assumed to be neutral. However, synonymous mutations can change mRNA structures in ways that alter levels of the encoded proteins. We have tested the assumption that immunizing mutations are neutral by constructing a library of over 50,000 edits that consist of only synonymous mutations in Escherichia coli. Thousands of edits had substantial effects on fitness during growth of E. coli on acetate, a poor carbon source that is toxic at high concentrations. The percentage of high-impact edits varied considerably between genes and at different positions within genes. We reconstructed clones with high-impact edits and found that 69% indeed had significant effects on growth in acetate. Interestingly, fewer edits affected fitness during growth in glucose, a preferred carbon source, suggesting that changes in protein expression caused by synonymous mutations may be most important when an organism encounters challenging conditions. Finally, we showed that synonymous edits can have widespread effects; a synonymous edit at the 5' end of ptsI altered expression of hundreds of genes. Our results suggest that the synonymous immunizing edits introduced during CRISPR-Cas-based genome editing should not be assumed to be innocuous.

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.

Searching for Principles of Microbial Ecology Across Levels of Biological Organization

Microbial communities play pivotal roles in ecosystems across different scales, from global elemental cycles to household food fermentations. These complex assemblies comprise hundreds or thousands of microbial species whose abundances vary over time and space. Unraveling the principles that guide their dynamics at different levels of biological organization, from individual species, their interactions, to complex microbial communities, is a major challenge. To what extent are these different levels of organization governed by separate principles, and how can we connect these levels to develop predictive models for the dynamics and function of microbial communities? Here, we will discuss recent advances that point towards principles of microbial communities, rooted in various disciplines from physics, biochemistry, and dynamical systems. By considering the marine carbon cycle as a concrete example, we demonstrate how the integration of levels of biological organization can offer deeper insights into the impact of increasing temperatures, such as those associated with climate change, on ecosystem-scale processes. We argue that by focusing on principles that transcend specific microbiomes, we can pave the way for a comprehensive understanding of microbial community dynamics and the development of predictive models for diverse ecosystems.

Tradeoffs in bacterial physiology determine the efficiency of antibiotic killing

Antibiotic effectiveness depends on a variety of factors. While many mechanistic details of antibiotic action are known, the connection between death rate and bacterial physiology is poorly understood. A common observation is that death rate in antibiotics rises linearly with growth rate; however, it remains unclear how other factors, such as environmental conditions and whole-cell physiological properties, affect bactericidal activity. To address this, we developed a high-throughput assay to precisely measure antibiotic-mediated death. We found that death rate is linear in growth rate, but the slope depends on environmental conditions. Growth under stress lowers death rate compared to nonstressed environments with similar growth rate. To understand stress's role, we developed a mathematical model of bacterial death based on resource allocation that includes a stress-response sector; we identify this sector using RNA-seq. Our model accurately predicts the minimal inhibitory concentration (MIC) with zero free parameters across a wide range of growth conditions. The model also quantitatively predicts death and MIC when sectors are experimentally modulated using cyclic adenosine monophosphate (cAMP), including protection from death at very low cAMP levels. The present study shows that different conditions with equal growth rate can have different death rates and establishes a quantitative relation between growth, death, and MIC that suggests approaches to improve antibiotic efficacy.

Simultaneous application of enzyme and thermodynamic constraints to metabolic models using an updated Python implementation of GECKO

IMPORTANCE

The metabolism of biological cells is an intricate network of reactions that interconvert chemical compounds, gathering energy, and using that energy to grow. The static analysis of these metabolic networks can be turned into a computational model that can efficiently output the distribution of fluxes in the network. With the inclusion of enzymes in the network, we can also interpret the role and concentrations of the metabolic proteins. However, the models and the experimental data often clash, resulting in a network that cannot grow. Here, we tackle this situation with a suite of relaxation algorithms in a package called geckopy. Geckopy also integrates with other software to allow for adding thermodynamic and metabolomic constraints. In addition, to ensure that enzyme-constrained models follow the community standards, a format for the proteins is postulated. We hope that the package and algorithms presented here will be useful for the constraint-based modeling community.

Design and thermodynamic analysis of a pathway enabling anaerobic production of poly-3-hydroxybutyrate in Escherichia coli

Utilizing anaerobic metabolisms for the production of biotechnologically relevant products presents potential advantages, such as increased yields and reduced energy dissipation. However, lower energy dissipation may indicate that certain reactions are operating closer to their thermodynamic equilibrium. While stoichiometric analyses and genetic modifications are frequently employed in metabolic engineering, the use of thermodynamic tools to evaluate the feasibility of planned interventions is less documented. In this study, we propose a novel metabolic engineering strategy to achieve an efficient anaerobic production of poly-(R)-3-hydroxybutyrate (PHB) in the model organism Escherichia coli. Our approach involves re-routing of two-thirds of the glycolytic flux through non-oxidative glycolysis and coupling PHB synthesis with NADH re-oxidation. We complemented our stoichiometric analysis with various thermodynamic approaches to assess the feasibility and the bottlenecks in the proposed engineered pathway. According to our calculations, the main thermodynamic bottleneck are the reactions catalyzed by the acetoacetyl-CoA β-ketothiolase (EC 2.3.1.9) and the acetoacetyl-CoA reductase (EC 1.1.1.36). Furthermore, we calculated thermodynamically consistent sets of kinetic parameters to determine the enzyme amounts required for sustaining the conversion fluxes. In the case of the engineered conversion route, the protein pool necessary to sustain the desired fluxes could account for 20% of the whole cell dry weight.

Milligrams to kilograms: making microbes work at scale

If biomanufacturing can become a sustainable route for producing chemicals, it will provide a critical step in reducing greenhouse gas emissions to fight climate change. However, efforts to industrialize microbial synthesis of chemicals have met with varied success, due, in part, to challenges in translating laboratory successes to industrial scale. With a particular focus on Escherichia coli, this review examines the lessons learned when studying microbial physiology and metabolism under conditions that simulate large-scale bioreactors and methods to minimize cellular waste through reduction of maintenance energy, optimizing the stress response and minimizing culture heterogeneity. With general strategies to overcome these challenges, biomanufacturing process scale-up could be de-risked and the time and cost of bringing promising syntheses to market could be reduced.

The modular biochemical reaction network structure of cellular translation

Translation is an essential attribute of all living cells. At the heart of cellular operation, it is a chemical information decoding process that begins with an input string of nucleotides and ends with the synthesis of a specific output string of peptides. The translation process is interconnected with gene expression, physiological regulation, transcription, and responses to signaling molecules, among other cellular functions. Foundational efforts have uncovered a wealth of knowledge about the mechanistic functions of the components of translation and their many interactions between them, but the broader biochemical connections between translation, metabolism and polymer biosynthesis that enable translation to occur have not been comprehensively mapped. Here we present a multilayer graph of biochemical reactions describing the translation, polymer biosynthesis and metabolism networks of an Escherichia coli cell. Intriguingly, the compounds that compose these three layers are distinctly aggregated into three modes regardless of their layer categorization. Multimodal mass distributions are well-known in ecosystems, but this is the first such distribution reported at the biochemical level. The degree distributions of the translation and metabolic networks are each likely to be heavy-tailed, but the polymer biosynthesis network is not. A multimodal mass-degree distribution indicates that the translation and metabolism networks are each distinct, adaptive biochemical modules, and that the gaps between the modes reflect evolved responses to the functional use of metabolite, polypeptide and polynucleotide compounds. The chemical reaction network of cellular translation opens new avenues for exploring complex adaptive phenomena such as percolation and phase changes in biochemical contexts.

Conditionally unutilized proteins and their profound effects on growth and adaptation across microbial species

Protein synthesis is an important determinant of microbial growth and response that demands a high amount of metabolic and biosynthetic resources. Despite these costs, microbial species from different taxa and habitats massively synthesize proteins that are not utilized in the conditions they currently experience. Based on resource allocation models, recent studies have begun to reconcile the costs and benefits of these conditionally unutilized proteins (CUPs) in the context of varying environmental conditions. Such massive synthesis of CUPs is crucial to consider in different areas of modern microbiology, from the systematic investigation of cell physiology, via the prediction of evolution in laboratory and natural environments, to the rational design of strains in biotechnology applications.

Trade-offs between the instantaneous growth rate and long-term fitness: Consequences for microbial physiology and predictive computational models

Microbial systems biology has made enormous advances in relating microbial physiology to the underlying biochemistry and molecular biology. By meticulously studying model microorganisms, in particular Escherichia coli and Saccharomyces cerevisiae, increasingly comprehensive computational models predict metabolic fluxes, protein expression, and growth. The modeling rationale is that cells are constrained by a limited pool of resources that they allocate optimally to maximize fitness. As a consequence, the expression of particular proteins is at the expense of others, causing trade-offs between cellular objectives such as instantaneous growth, stress tolerance, and capacity to adapt to new environments. While current computational models are remarkably predictive for E. coli and S. cerevisiae when grown in laboratory environments, this may not hold for other growth conditions and other microorganisms. In this contribution, we therefore discuss the relationship between the instantaneous growth rate, limited resources, and long-term fitness. We discuss uses and limitations of current computational models, in particular for rapidly changing and adverse environments, and propose to classify microbial growth strategies based on Grimes's CSR framework.

A fitness trade-off between growth and survival governed by Spo0A-mediated proteome allocation constraints in Bacillus subtilis

Growth and survival are key determinants of bacterial fitness. However, how resource allocation of bacteria could reconcile these two traits to maximize fitness remains poorly understood. Here, we find that the resource allocation strategy of Bacillus subtilis does not lead to growth maximization on various carbon sources. Survival-related pathways impose strong proteome constraints on B. subtilis. Knockout of a master regulator gene, spo0A, triggers a global resource reallocation from survival-related pathways to biosynthesis pathways, further strongly stimulating the growth of B. subtilis. However, the fitness of spo0A-null strain is severely compromised because of various disadvantageous phenotypes (e.g., abolished sporulation and enhanced cell lysis). In particular, it also exhibits a strong defect in peptide utilization, being unable to efficiently recycle nutrients from the lysed cell debris to maintain long-term viability. Our work uncovers a fitness trade-off between growth and survival that governed by Spo0A-mediated proteome allocation constraints in B. subtilis, further shedding light on the fundamental design principle of bacteria.

Simulation-based Reconstructed Diffusion unveils the effect of aging on protein diffusion in Escherichia coli

We have developed Simulation-based Reconstructed Diffusion (SbRD) to determine diffusion coefficients corrected for confinement effects and for the bias introduced by two-dimensional models describing a three-dimensional motion. We validate the method on simulated diffusion data in three-dimensional cell-shaped compartments. We use SbRD, combined with a new cell detection method, to determine the diffusion coefficients of a set of native proteins in Escherichia coli. We observe slower diffusion at the cell poles than in the nucleoid region of exponentially growing cells, which is independent of the presence of polysomes. Furthermore, we show that the newly formed pole of dividing cells exhibits a faster diffusion than the old one. We hypothesize that the observed slowdown at the cell poles is caused by the accumulation of aggregated or damaged proteins, and that the effect is asymmetric due to cell aging.

Inherited chitinases enable sustained growth and rapid dispersal of bacteria from chitin particles

Many biogeochemical functions involve bacteria utilizing solid substrates. However, little is known about the coordination of bacterial growth with the kinetics of attachment to and detachment from such substrates. In this quantitative study of Vibrio sp. 1A01 growing on chitin particles, we reveal the heterogeneous nature of the exponentially growing culture comprising two co-existing subpopulations: a minority replicating on chitin particles and a non-replicating majority which was planktonic. This partition resulted from a high rate of cell detachment from particles. Despite high detachment, sustained exponential growth of cells on particles was enabled by the enrichment of extracellular chitinases excreted and left behind by detached cells. The 'inheritance' of these chitinases sustains the colonizing subpopulation despite its reduced density. This simple mechanism helps to circumvent a trade-off between growth and dispersal, allowing particle-associated marine heterotrophs to explore new habitats without compromising their fitness on the habitat they have already colonized.

Sm-like protein Rof inhibits transcription termination factor ρ by binding site obstruction and conformational insulation

Transcription termination factor ρ is a hexameric, RNA-dependent NTPase that can adopt active closed-ring and inactive open-ring conformations. The Sm-like protein Rof, a homolog of the RNA chaperone Hfq, inhibits ρ-dependent termination in vivo but recapitulation of this activity in vitro has proven difficult and the precise mode of Rof action is presently unknown. Our electron microscopic structures of ρ-Rof and ρ-RNA complexes show that Rof undergoes pronounced conformational changes to bind ρ at the protomer interfaces, undercutting ρ conformational dynamics associated with ring closure and occluding extended primary RNA-binding sites that are also part of interfaces between ρ and RNA polymerase. Consistently, Rof impedes ρ ring closure, ρ-RNA interactions, and ρ association with transcription elongation complexes. Structure-guided mutagenesis coupled with functional assays confirmed that the observed ρ-Rof interface is required for Rof-mediated inhibition of cell growth and ρ-termination in vitro. Bioinformatic analyses revealed that Rof is restricted to Pseudomonadota and that the ρ-Rof interface is conserved. Genomic contexts of rof differ between Enterobacteriaceae and Vibrionaceae, suggesting distinct modes of Rof regulation. We hypothesize that Rof and other cellular anti-terminators silence ρ under diverse, but yet to be identified, stress conditions when unrestrained transcription termination by ρ would be lethal.

Genetic effects on molecular network states explain complex traits

The complexity of many cellular and organismal traits results from the integration of genetic and environmental factors via molecular networks. Network structure and effect propagation are best understood at the level of functional modules, but so far, no concept has been established to include the global network state. Here, we show when and how genetic perturbations lead to molecular changes that are confined to small parts of a network versus when they lead to modulation of network states. Integrating multi-omics profiling of genetically heterogeneous budding and fission yeast strains with an array of cellular traits identified a central state transition of the yeast molecular network that is related to PKA and TOR (PT) signaling. Genetic variants affecting this PT state globally shifted the molecular network along a single-dimensional axis, thereby modulating processes including energy and amino acid metabolism, transcription, translation, cell cycle control, and cellular stress response. We propose that genetic effects can propagate through large parts of molecular networks because of the functional requirement to centrally coordinate the activity of fundamental cellular processes.

Unified Workflow for the Rapid and In-Depth Characterization of Bacterial Proteomes

Bacteria are the most abundant and diverse organisms among the kingdoms of life. Due to this excessive variance, finding a unified, comprehensive, and safe workflow for quantitative bacterial proteomics is challenging. In this study, we have systematically evaluated and optimized sample preparation, mass spectrometric data acquisition, and data analysis strategies in bacterial proteomics. We investigated workflow performances on six representative species with highly different physiologic properties to mimic bacterial diversity. The best sample preparation strategy was a cell lysis protocol in 100% trifluoroacetic acid followed by an in-solution digest. Peptides were separated on a 30-min linear microflow liquid chromatography gradient and analyzed in data-independent acquisition mode. Data analysis was performed with DIA-NN using a predicted spectral library. Performance was evaluated according to the number of identified proteins, quantitative precision, throughput, costs, and biological safety. With this rapid workflow, over 40% of all encoded genes were detected per bacterial species. We demonstrated the general applicability of our workflow on a set of 23 taxonomically and physiologically diverse bacterial species. We could confidently identify over 45,000 proteins in the combined dataset, of which 30,000 have not been experimentally validated before. Our work thereby provides a valuable resource for the microbial scientific community. Finally, we grew Escherichia coli and Bacillus cereus in replicates under 12 different cultivation conditions to demonstrate the high-throughput suitability of the workflow. The proteomic workflow we present in this manuscript does not require any specialized equipment or commercial software and can be easily applied by other laboratories to support and accelerate the proteomic exploration of the bacterial kingdom.

Coenzyme biosynthesis in response to precursor availability reveals incorporation of β-alanine from pantothenate in prototrophic bacteria

Coenzymes are important for all classes of enzymatic reactions and essential for cellular metabolism. Most coenzymes are synthesized from dedicated precursors, also referred to as vitamins, which prototrophic bacteria can either produce themselves from simpler substrates or take up from the environment. The extent to which prototrophs use supplied vitamins and whether externally available vitamins affect the size of intracellular coenzyme pools and control endogenous vitamin synthesis is currently largely unknown. Here, we studied coenzyme pool sizes and vitamin incorporation into coenzymes during growth on different carbon sources and vitamin supplementation regimes using metabolomics approaches. We found that the model bacterium Escherichia coli incorporated pyridoxal, niacin, and pantothenate into pyridoxal 5'-phosphate, NAD, and coenzyme A (CoA), respectively. In contrast, riboflavin was not taken up and was produced exclusively endogenously. Coenzyme pools were mostly homeostatic and not affected by externally supplied precursors. Remarkably, we found that pantothenate is not incorporated into CoA as such but is first degraded to pantoate and β-alanine and then rebuilt. This pattern was conserved in various bacterial isolates, suggesting a preference for β-alanine over pantothenate utilization in CoA synthesis. Finally, we found that the endogenous synthesis of coenzyme precursors remains active when vitamins are supplied, which is consistent with described expression data of genes for enzymes involved in coenzyme biosynthesis under these conditions. Continued production of endogenous coenzymes may ensure rapid synthesis of the mature coenzyme under changing environmental conditions, protect against coenzyme limitation, and explain vitamin availability in naturally oligotrophic environments.

Functional decomposition of metabolism allows a system-level quantification of fluxes and protein allocation towards specific metabolic functions

Quantifying the contribution of individual molecular components to complex cellular processes is a grand challenge in systems biology. Here we establish a general theoretical framework (Functional Decomposition of Metabolism, FDM) to quantify the contribution of every metabolic reaction to metabolic functions, e.g. the synthesis of biomass building blocks. FDM allowed for a detailed quantification of the energy and biosynthesis budget for growing Escherichia coli cells. Surprisingly, the ATP generated during the biosynthesis of building blocks from glucose almost balances the demand from protein synthesis, the largest energy expenditure known for growing cells. This leaves the bulk of the energy generated by fermentation and respiration unaccounted for, thus challenging the common notion that energy is a key growth-limiting resource. Moreover, FDM together with proteomics enables the quantification of enzymes contributing towards each metabolic function, allowing for a first-principle formulation of a coarse-grained model of global protein allocation based on the structure of the metabolic network.

The one-message-per-cell-cycle rule: A conserved minimum transcription level for essential genes

The inherent stochasticity of cellular processes leads to significant cell-to-cell variation in protein abundance. Although this noise has already been characterized and modeled, its broader implications and significance remain unclear. In this paper, we revisit the noise model and identify the number of messages transcribed per cell cycle as the critical determinant of noise. In yeast, we demonstrate that this quantity predicts the non-canonical scaling of noise with protein abundance, as well as quantitatively predicting its magnitude. We then hypothesize that growth robustness requires an upper ceiling on noise for the expression of essential genes, corresponding to a lower floor on the transcription level. We show that just such a floor exists: a minimum transcription level of one message per cell cycle is conserved between three model organisms: Escherichia coli, yeast, and human. Furthermore, all three organisms transcribe the same number of messages per gene, per cell cycle. This common transcriptional program reveals that robustness to noise plays a central role in determining the expression level of a large fraction of essential genes, and that this fundamental optimal strategy is conserved from E. coli to human cells.

The one-message-per-cell-cycle rule: A conserved minimum transcription level for essential genes

The inherent stochasticity of cellular processes leads to significant cell-to-cell variation in protein abundance. Although this noise has already been characterized and modeled, its broader implications and significance remain unclear. In this paper, we revisit the noise model and identify the number of messages transcribed per cell cycle as the critical determinant of noise. In yeast, we demonstrate that this quantity predicts the non-canonical scaling of noise with protein abundance, as well as quantitatively predicting its magnitude. We then hypothesize that growth robustness requires an upper ceiling on noise for the expression of essential genes, corresponding to a lower floor on the transcription level. We show that just such a floor exists: a minimum transcription level of one message per cell cycle is conserved between three model organisms: Escherichia coli, yeast, and human. Furthermore, all three organisms transcribe the same number of messages per gene, per cell cycle. This common transcriptional program reveals that robustness to noise plays a central role in determining the expression level of a large fraction of essential genes, and that this fundamental optimal strategy is conserved from E. coli to human cells.

Design and Selection of Heterodimerizing Helical Hairpins for Synthetic Biology

Synthetic biology applications would benefit from protein modules of reduced complexity that function orthogonally to cellular components. As many subcellular processes depend on peptide-protein or protein-protein interactions, de novo designed polypeptides that can bring together other proteins controllably are particularly useful. Thanks to established sequence-to-structure relationships, helical bundles provide good starting points for such designs. Typically, however, such designs are tested in vitro and function in cells is not guaranteed. Here, we describe the design, characterization, and application of de novo helical hairpins that heterodimerize to form 4-helix bundles in cells. Starting from a rationally designed homodimer, we construct a library of helical hairpins and identify complementary pairs using bimolecular fluorescence complementation in E. coli. We characterize some of the pairs using biophysics and X-ray crystallography to confirm heterodimeric 4-helix bundles. Finally, we demonstrate the function of an exemplar pair in regulating transcription in both E. coli and mammalian cells.

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.

Shaping bacterial gene expression by physiological and proteome allocation constraints

Networks of molecular regulators are often the primary objects of focus in the study of gene regulation, with the machinery of protein synthesis tacitly relegated to the background. Shifting focus to the constraints imposed by the allocation of protein synthesis flux reveals surprising ways in which the actions of molecular regulators are shaped by physiological demands. Using carbon catabolite repression as a case study, we describe how physiological constraints are sensed through metabolic fluxes and how flux-controlled regulation gives rise to simple empirical relations between protein levels and the rate of cell growth.

Spatial transcriptome uncovers rich coordination of metabolism in E. coli K12 biofilm

Microbial communities often display region-specific properties, which give rise to complex interactions and emergent behaviors that are critical to the homeostasis and stress response of the communities. However, systems-level understanding of these properties still remains elusive. In this study, we established RAINBOW-seq and profiled the transcriptome of Escherichia coli biofilm communities with high spatial resolution and high gene coverage. We uncovered three modes of community-level coordination, including cross-regional resource allocation, local cycling and feedback signaling, which were mediated by strengthened transmembrane transport and spatially specific activation of metabolism. As a consequence of such coordination, the nutrient-limited region of the community maintained an unexpectedly high level of metabolism, enabling it to express many signaling genes and functionally unknown genes with potential sociality functions. Our work provides an extended understanding of the metabolic interplay in biofilms and presents a new approach of investigating complex interactions in bacterial communities on the systems level.

Novel 15N Metabolic Labeling-Based Large-Scale Absolute Quantitative Proteomics Method for Corynebacterium glutamicum

With fast growth, synthetic biology powers us with the capability to produce high commercial value products in an efficient resource/energy-consuming manner. Comprehensive knowledge of the protein regulatory network of a bacterial host chassis, e.g., the actual amount of the given proteins, is the key to building cell factories for certain target hyperproduction. Many talent methods have been introduced for absolute quantitative proteomics. However, for most cases, a set of reference peptides with isotopic labeling (e.g., SIL, AQUA, QconCAT) or a set of reference proteins (e.g., commercial UPS2 kit) needs to be prepared. The higher cost hinders these methods for large sample research. In this work, we proposed a novel metabolic labeling-based absolute quantification approach (termed nMAQ). The reference Corynebacterium glutamicum strain is metabolically labeled with ¹⁵N, and a set of endogenous anchor proteins of the reference proteome is quantified by chemically synthesized light (¹⁴N) peptides. The prequantified reference proteome was then utilized as an internal standard (IS) and spiked into the target (¹⁴N) samples. SWATH-MS analysis is performed to obtain the absolute expression levels of the proteins from the target cells. The cost for nMAQ is estimated to be less than 10 dollars per sample. We have benchmarked the quantitative performance of the novel method. We believe this method will help with the deep understanding of the intrinsic regulatory mechanism of C. glutamicum during bioengineering and will promote the process of building cell factories for synthetic biology.

Protocol for absolute quantification of proteins in Gram-negative bacteria based on QconCAT-based labeled peptides

Mass-spectrometry-based absolute protein quantification uses labeled quantification concatamer (QconCAT) as internal standards (ISs). To calculate the amount of protein(s), the ion intensity ratio between the analyte and its cognate IS is compared in each biological sample. The present protocol describes a systematic workflow to design, produce, and purify QconCATs and to quantify soluble proteins in Pseudomonas putida KT2440. Our methodology enables the quantification of detectable peptide and serves as a versatile platform to produce ISs for different biological systems.

Tracking nitrogen allocation to proteome biosynthesis in a marine microbial community

Microbial growth in many environments is limited by nitrogen availability, yet there is limited understanding of how complex communities compete for and allocate this resource. Here we develop a broadly applicable approach to track biosynthetic incorporation of ¹⁵N-labelled nitrogen substrates into microbial community proteomes, enabling quantification of protein turnover and N allocation to specific cellular functions in individual taxa. Application to oligotrophic ocean surface water identifies taxa-specific substrate preferences and a distinct subset of protein functions undergoing active biosynthesis. The cyanobacterium Prochlorococcus is the most effective competitor for acquisition of ammonium and urea and shifts its proteomic allocation of N over the day/night cycle. Our approach reveals that infrastructure and protein-turnover functions comprise substantial biosynthetic demand for N in Prochlorococcus and a range of other microbial taxa. The direct interrogation of the proteomic underpinnings of N limitation with ¹⁵N-tracking proteomics illuminates how nutrient stress differentially influences metabolism in co-existing microbes.

Characterization of RNA-based and protein-only RNases P from bacteria encoding both enzyme types

A small group of bacteria encode two types of RNase P, the classical ribonucleoprotein (RNP) RNase P as well as the protein-only RNase P HARP (homolog of Aquifex RNase P). We characterized the dual RNase P activities of five bacteria that belong to three different phyla. All five bacterial species encode functional RNA (gene rnpB) and protein (gene rnpA) subunits of RNP RNase P, but only the HARP of the thermophile Thermodesulfatator indicus (phylum Thermodesulfobacteria) was found to have robust tRNA 5'-end maturation activity in vitro and in vivo in an Escherichia coli RNase P depletion strain. These findings suggest that both types of RNase P are able to contribute to the essential tRNA 5'-end maturation activity in T. indicus, thus resembling the predicted evolutionary transition state in the progenitor of the Aquificaceae before the loss of rnpA and rnpB genes in this family of bacteria. Remarkably, T. indicus RNase P RNA is transcribed with a P12 expansion segment that is posttranscriptionally excised in vivo, such that the major fraction of the RNA is fragmented and thereby truncated by ∼70 nt in the native T. indicus host as well as in the E. coli complementation strain. Replacing the native P12 element of T. indicus RNase P RNA with the short P12 helix of Thermotoga maritima RNase P RNA abolished fragmentation, but simultaneously impaired complementation efficiency in E. coli cells, suggesting that intracellular fragmentation and truncation of T. indicus RNase P RNA may be beneficial to RNA folding and/or enzymatic activity.

A Genome-Scale Metabolic Model of Marine Heterotroph Vibrio splendidus Strain 1A01

While Vibrio splendidus is best known as an opportunistic pathogen in oysters, Vibrio splendidus strain 1A01 was first identified as an early colonizer of synthetic chitin particles incubated in seawater. To gain a better understanding of its metabolism, a genome-scale metabolic model (GSMM) of V. splendidus 1A01 was reconstructed. GSMMs enable us to simulate all metabolic reactions in a bacterial cell using flux balance analysis. A draft model was built using an automated pipeline from BioCyc. Manual curation was then performed based on experimental data, in part by gap-filling metabolic pathways and tailoring the model's biomass reaction to V. splendidus 1A01. The challenges of building a metabolic model for a marine microorganism like V. splendidus 1A01 are described. IMPORTANCE A genome-scale metabolic model of V. splendidus 1A01 was reconstructed in this work. We offer solutions to the technical problems associated with model reconstruction for a marine bacterial strain like V. splendidus 1A01, which arise largely from the high salt concentration found in both seawater and culture media that simulate seawater.

Enzyme expression kinetics by Escherichia coli during transition from rich to minimal media depends on proteome reserves

Bacterial fitness depends on adaptability to changing environments. In rich growth medium, which is replete with amino acids, Escherichia coli primarily expresses protein synthesis machineries, which comprise ~40% of cellular proteins and are required for rapid growth. Upon transition to minimal medium, which lacks amino acids, biosynthetic enzymes are synthesized, eventually reaching ~15% of cellular proteins when growth fully resumes. We applied quantitative proteomics to analyse the timing of enzyme expression during such transitions, and established a simple positive relation between the onset time of enzyme synthesis and the fractional enzyme 'reserve' maintained by E. coli while growing in rich media. We devised and validated a coarse-grained kinetic model that quantitatively captures the enzyme recovery kinetics in different pathways, solely on the basis of proteomes immediately preceding the transition and well after its completion. Our model enables us to infer regulatory strategies underlying the 'as-needed' gene expression programme adopted by E. coli.

Stringent response ensures the timely adaptation of bacterial growth to nutrient downshift

Timely adaptation to nutrient downshift is crucial for bacteria to maintain fitness during feast and famine cycle in the natural niche. However, the molecular mechanism that ensures the timely adaption of bacterial growth to nutrient downshift remains poorly understood. Here, we quantitatively investigated the adaptation of Escherichia coli to various kinds of nutrient downshift. We found that relA deficient strain, which is devoid of stringent response, exhibits a significantly longer growth lag than wild type strain during adapting to both amino acid downshift and carbon downshift. Quantitative proteomics show that increased (p)ppGpp level promotes the growth adaption of bacteria to amino acid downshift via triggering the proteome resource re-allocation from ribosome synthesis to amino acid biosynthesis. Such type of proteome re-allocation is significantly delayed in the relA-deficient strain, which underlies its longer lag than wild type strain during amino acid downshift. During carbon downshift, a lack of stringent response in relA deficient strain leads to disruption of the transcription-translation coordination, thus compromising the transcription processivity and further the timely expression of related catabolic operons for utilizing secondary carbon sources. Our studies shed light on the fundamental strategy of bacteria to maintain fitness under nutrient-fluctuating environments.

Principles of gene regulation quantitatively connect DNA to RNA and proteins in bacteria

Protein concentrations are set by a complex interplay between gene-specific regulatory processes and systemic factors, including cell volume and shared gene expression machineries. Elucidating this interplay is crucial for discerning and designing gene regulatory systems. We quantitatively characterized gene-specific and systemic factors that affect transcription and translation genome-wide for Escherichia coli across many conditions. The results revealed two design principles that make regulation of gene expression insulated from concentrations of shared machineries: RNA polymerase activity is fine-tuned to match translational output, and translational characteristics are similar across most messenger RNAs (mRNAs). Consequently, in bacteria, protein concentration is set primarily at the promoter level. A simple mathematical formula relates promoter activities and protein concentrations across growth conditions, enabling quantitative inference of gene regulation from omics data.

Analysis of proteome adaptation reveals a key role of the bacterial envelope in starvation survival

Bacteria reorganize their physiology upon entry to stationary phase. What part of this reorganization improves starvation survival is a difficult question because the change in physiology includes a global reorganization of the proteome, envelope, and metabolism of the cell. In this work, we used several trade-offs between fast growth and long survival to statistically score over 2,000 Escherichia coli proteins for their global correlation with death rate. The combined ranking allowed us to narrow down the set of proteins that positively correlate with survival and validate the causal role of a subset of proteins. Remarkably, we found that important survival genes are related to the cell envelope, i.e., periplasm and outer membrane, because the maintenance of envelope integrity of E. coli plays a crucial role during starvation. Our results uncover a new protective feature of the outer membrane that adds to the growing evidence that the outer membrane is not only a barrier that prevents abiotic substances from reaching the cytoplasm but also essential for bacterial proliferation and survival.

Recent functional insights into the magic role of (p)ppGpp in growth control

Rapid growth and survival are two key traits that enable bacterial cells to thrive in their natural habitat. The guanosine tetraphosphate and pentaphosphate [(p)ppGpp], also known as "magic spot", is a key second messenger inside bacterial cells as well as chloroplasts of plants and green algae. (p)ppGpp not only controls various stages of central dogma processes (replication, transcription, ribosome maturation and translation) and central metabolism but also regulates various physiological processes such as pathogenesis, persistence, motility and competence. Under extreme conditions such as nutrient starvation, (p)ppGpp-mediated stringent response is crucial for the survival of bacterial cells. This mini-review highlights some of the very recent progress on the key role of (p)ppGpp in bacterial growth control in light of cellular resource allocation and cell size regulation. We also briefly discuss some recent functional insights into the role of (p)ppGpp in plants and green algae from the angle of growth and development and further discuss several important open directions for future studies.

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.

Global and gene-specific translational regulation in Escherichia coli across different conditions

How well mRNA transcript levels represent protein abundances has been a controversial issue. Particularly across different environments, correlations between mRNA and protein exhibit remarkable variability from gene to gene. Translational regulation is likely to be one of the key factors contributing to mismatches between mRNA level and protein abundance in bacteria. Here, we quantified genome-wide transcriptome and relative translation efficiency (RTE) under 12 different conditions in Escherichia coli. By quantifying the mRNA-RTE correlation both across genes and across conditions, we uncovered a diversity of gene-specific translational regulations, cooperating with transcriptional regulations, in response to carbon (C), nitrogen (N), and phosphate (P) limitations. Intriguingly, we found that many genes regulating translation are themselves subject to translational regulation, suggesting possible feedbacks. Furthermore, a random forest model suggests that codon usage partially predicts a gene's cross-condition variability in translation efficiency; such cross-condition variability tends to be an inherent quality of a gene, independent of the specific nutrient limitations. These findings broaden the understanding of translational regulation under different environments and provide novel strategies for the control of translation in synthetic biology. In addition, our data offers a resource for future multi-omics studies.

Mechanisms of chlorate toxicity and resistance in Pseudomonas aeruginosa

Pseudomonas aeruginosa is an opportunistic bacterial pathogen that often encounters hypoxic/anoxic environments within the host, which increases its tolerance to many conventional antibiotics. Toward identifying novel treatments, we explored the therapeutic potential of chlorate, a pro-drug that kills hypoxic/anoxic, antibiotic-tolerant P. aeruginosa populations. While chlorate itself is relatively nontoxic, it is enzymatically reduced to the toxic oxidizing agent, chlorite, by hypoxically induced nitrate reductase. To better assess chlorate's therapeutic potential, we investigated mechanisms of chlorate toxicity and resistance in P. aeruginosa. We used transposon mutagenesis to identify genes that alter P. aeruginosa fitness during chlorate treatment, finding that methionine sulfoxide reductases (Msr), which repair oxidized methionine residues, support survival during chlorate stress. Chlorate treatment leads to proteome-wide methionine oxidation, which is exacerbated in a ∆msrA∆msrB strain. In response to chlorate, P. aeruginosa upregulates proteins involved in a wide range of functions, including metabolism, DNA replication/repair, protein repair, transcription, and translation, and these newly synthesized proteins are particularly vulnerable to methionine oxidation. The addition of exogenous methionine partially rescues P. aeruginosa survival during chlorate treatment, suggesting that widespread methionine oxidation contributes to death. Finally, we found that mutations that decrease nitrate reductase activity are a common mechanism of chlorate resistance.