Promoter activity dynamics in the lag phase of Escherichia coli

2-Stage microfermentations

Cell based factories can be engineered to produce a wide variety of products. Advances in DNA synthesis and genome editing have greatly simplified the design and construction of these factories. It has never been easier to generate hundreds or even thousands of cell factory strain variants for evaluation. These advances have amplified the need for standardized, higher throughput means of evaluating these designs. Toward this goal, we have previously reported the development of engineered E. coli strains and associated 2-stage production processes to simplify and standardize strain engineering, evaluation and scale up. This approach relies on decoupling growth (stage 1), from production, which occurs in stationary phase (stage 2). Phosphate depletion is used as the trigger to stop growth as well as induce heterologous expression. Here, we describe in detail the development of protocols for the evaluation of engineered E. coli strains in 2-stage microfermentations. These protocols are readily adaptable to the evaluation of strains producing a wide variety of protein as well as small molecule products. Additionally, by detailing the approach to protocol development, these methods are also adaptable to additional cellular hosts, as well as other 2-stage processes with various additional triggers.

Biosensor that Detects Stress Caused by Periplasmic Proteins

Escherichia coli is often used as a factory to produce recombinant proteins. In many cases, the recombinant protein needs disulfide bonds to fold and function correctly. These proteins are genetically fused to a signal peptide so that they are secreted to the oxidizing environment of the periplasm (where the enzymes required for disulfide bond formation exist). Currently, it is difficult to determine in vivo whether a recombinant protein is efficiently secreted from the cytoplasm and folded in the periplasm or if there is a bottleneck in one of these steps because cellular capacity has been exceeded. To address this problem, we have developed a biosensor that detects cellular stress caused by (1) inefficient secretion of proteins from the cytoplasm and (2) aggregation of proteins in the periplasm. We demonstrate how the fluorescence fingerprint obtained from the biosensor can be used to identify induction conditions that do not exceed the capacity of the cell and therefore do not cause cellular stress. These induction conditions result in more effective biomass and in some cases higher titers of soluble recombinant proteins.

Reducing the Bacterial Lag Phase Through Methylated Compounds: Insights from Algal-Bacterial Interactions

The bacterial lag phase is a key period for resuming growth. Despite its significance, the lag phase remains underexplored, particularly in environmental bacteria. Here, we explore the lag phase of the model marine bacterium Phaeobacter inhibens when it transitions from starvation to growth with a microalgal partner. Utilizing transcriptomics and 13 C-labeled metabolomics, our study reveals that methylated compounds, which are abundantly produced by microalgae, shorten the bacterial lag phase. Our findings underscore the significance of methyl groups as a limiting factor during the lag phase and demonstrate that methyl groups can be harvested from algal compounds and assimilated through the methionine cycle. Furthermore, we show that methylated compounds, characteristic of photosynthetic organisms, induce variable reductions in lag times among bacteria associated with algae and plants. These findings highlight the adjustability of the bacterial lag phase and emphasize the importance of studying bacteria in an environmental context.

One-Sentence Summary

Bacteria use algal compounds as a metabolic shortcut to transition from starvation to growth.

A Second Role for the Second Messenger Cyclic-di-GMP in E. coli: Arresting Cell Growth by Altering Metabolic Flow

c-di-GMP primarily controls motile to sessile transitions in bacteria. Diguanylate cyclases (DGCs) catalyze the synthesis of c-di-GMP from two GTP molecules. Typically, bacteria encode multiple DGCs that are activated by specific environmental signals. Their catalytic activity is modulated by c-di-GMP binding to autoinhibitory sites (I-sites). YfiN is a conserved inner membrane DGC that lacks these sites. Instead, YfiN activity is directly repressed by periplasmic YfiR, which is inactivated by redox stress. In Escherichia coli, an additional envelope stress causes YfiN to relocate to the mid-cell to inhibit cell division by interacting with the division machinery. Here, we report a third activity for YfiN in E. coli, where cell growth is inhibited without YfiN relocating to the division site. This action of YfiN is only observed when the bacteria are cultured on gluconeogenic carbon sources, and is dependent on absence of the autoinhibitory sites. Restoration of I-site function relieves the growth-arrest phenotype, and disabling this function in a heterologous DGC causes acquisition of this phenotype. Arrested cells are tolerant to a wide range of antibiotics. We show that the likely cause of growth arrest is depletion of cellular GTP from run-away synthesis of c-di-GMP, explaining the dependence of growth arrest on gluconeogenic carbon sources that exhaust more GTP during production of glucose. This is the first report of c-di-GMP-mediated growth arrest by altering metabolic flow. IMPORTANCE The c-di-GMP signaling network in bacteria not only controls a variety of cellular processes such as motility, biofilms, cell development, and virulence, but does so by a dizzying array of mechanisms. The DGC YfiN singularly represents the versatility of this network in that it not only inhibits motility and promotes biofilms, but also arrests growth in Escherichia coli by relocating to the mid-cell and blocking cell division. The work described here reveals that YfiN arrests growth by yet another mechanism in E. coli, changing metabolic flow. This function of YfiN, or of DGCs without autoinhibitory I-sites, may contribute to antibiotic tolerant persisters in relevant niches such as the gut where gluconeogenic sugars are found.

Ampicillin-controlled glucose metabolism manipulates the transition from tolerance to resistance in bacteria

The mechanism(s) of how bacteria acquire tolerance and then resistance to antibiotics remains poorly understood. Here, we show that glucose abundance decreases progressively as ampicillin-sensitive strains acquire resistance to ampicillin. The mechanism involves that ampicillin initiates this event via targeting pts promoter and pyruvate dehydrogenase (PDH) to promote glucose transport and inhibit glycolysis, respectively. Thus, glucose fluxes into pentose phosphate pathway to generate reactive oxygen species (ROS) causing genetic mutations. Meanwhile, PDH activity is gradually restored due to the competitive binding of accumulated pyruvate and ampicillin, which lowers glucose level, and activates cyclic adenosine monophosphate (cAMP)/cAMP receptor protein (CRP) complex. cAMP/CRP negatively regulates glucose transport and ROS but enhances DNA repair, leading to ampicillin resistance. Glucose and Mn²⁺ delay the acquisition, providing an effective approach to control the resistance. The same effect is also determined in the intracellular pathogen Edwardsiella tarda. Thus, glucose metabolism represents a promising target to stop/delay the transition of tolerance to resistance.

Rules for body fat interventions based on an operating point mechanism

Interventions to reduce fat are important for human health. However, they can have opposing effects such as exercise that decreases fat but increases food intake, or coherent effects such as leptin resistance which raises both. Furthermore, some interventions show an overshoot in food intake, such as recovery from a diet, whereas others do not. To explain these properties we present a graphical framework called the operating point model, based on leptin control of feeding behavior. Steady-state fat and food intake is given by the intersection of two experimental curves - steady-state fat at a given food intake and ad libitum food intake at a given fat level. Depending on which curve an intervention shifts, it has opposing or coherent effects with or without overshoot, in excellent agreement with rodent data. The model also explains the quadratic relation between leptin and fat in humans. These concepts may guide the understanding of fat regulation disorders.

Observation of universal ageing dynamics in antibiotic persistence

Stress responses allow cells to adapt to changes in external conditions by activating specific pathways¹. Here we investigate the dynamics of single cells that were subjected to acute stress that is too strong for a regulated response but not lethal. We show that when the growth of bacteria is arrested by acute transient exposure to strong inhibitors, the statistics of their regrowth dynamics can be predicted by a model for the cellular network that ignores most of the details of the underlying molecular interactions. We observed that the same stress, applied either abruptly or gradually, can lead to totally different recovery dynamics. By measuring the regrowth dynamics after stress exposure on thousands of cells, we show that the model can predict the outcome of antibiotic persistence measurements. Our results may account for the ubiquitous antibiotic persistence phenotype², as well as for the difficulty in attempts to link it to specific genes³. More generally, our approach suggests that two different cellular states can be observed under stress: a regulated state, which prepares cells for fast recovery, and a disrupted cellular state due to acute stress, with slow and heterogeneous recovery dynamics. The disrupted state may be described by general properties of large random networks rather than by specific pathway activation. Better understanding of the disrupted state could shed new light on the survival and evolution of cells under stress.

An oxygen-uptake-rate-based estimator of the specific growth rate in Escherichia coli BL21 strains cultivation processes

The cell cultivation process in a bioreactor is a high-value manufacturing process that requires excessive monitoring and control compatibility. The specific cell growth rate is a crucial parameter that describes the online quality of the cultivation process. Most methods and algorithms developed for online estimations of the specific growth rate controls in batch and fed-batch microbial cultivation processes rely on biomass growth models. In this paper, we present a soft sensor – a specific growth rate estimator that does not require a particular bioprocess model. The approach for online estimation of the specific growth rate is based on an online measurement of the oxygen uptake rate. The feasibility of the estimator developed in this study was determined in two ways. First, we used numerical simulations on a virtual platform, where the cell culture processes were theoretically modeled. Next, we performed experimental validation based on laboratory-scale (7, 12, 15 L) bioreactor experiments with three different Escherichia coli BL21 cell strains.

Bacillus subtilis Colonization of Arabidopsis thaliana Roots Induces Multiple Biosynthetic Clusters for Antibiotic Production

Beneficial and probiotic bacteria play an important role in conferring immunity of their hosts to a wide range of bacterial, viral, and fungal diseases. Bacillus subtilis is a Gram-positive bacterium that protects the plant from various pathogens due to its capacity to produce an extensive repertoire of antibiotics. At the same time, the plant microbiome is a highly competitive niche, with multiple microbial species competing for space and resources, a competition that can be determined by the antagonistic potential of each microbiome member. Therefore, regulating antibiotic production in the rhizosphere is of great importance for the elimination of pathogens and establishing beneficial host-associated communities. In this work, we used B. subtilis as a model to investigate the role of plant colonization in antibiotic production. Flow cytometry and imaging flow cytometry (IFC) analysis supported the notion that Arabidopsis thaliana specifically induced the transcription of the biosynthetic clusters for the non-ribosomal peptides surfactin, bacilysin, plipastatin, and the polyketide bacillaene. IFC was more robust in quantifying the inducing effects of A. thaliana, considering the overall heterogeneity of the population. Our results highlight IFC as a useful tool to study the effect of association with a plant host on bacterial gene expression. Furthermore, the common regulation of multiple biosynthetic clusters for antibiotic production by the plant can be translated to improve the performance and competitiveness of beneficial members of the plant microbiome.

The Application of Imaging Flow Cytometry for Characterisation and Quantification of Bacterial Phenotypes

Bacteria modify their morphology in response to various factors including growth stage, nutrient availability, predation, motility and long-term survival strategies. Morphological changes may also be associated with specific physiological phenotypes such as the formation of dormant or persister cells in a “viable but non-culturable” (VBNC) state which frequently display different shapes and size compared to their active counterparts. Such dormancy phenotypes can display various degrees of tolerance to antibiotics and therefore a detailed understanding of these phenotypes is crucial for combatting chronic infections and associated diseases. Cell shape and size are therefore more than simple phenotypic characteristics; they are important physiological properties for understanding bacterial life-strategies and pathologies. However, quantitative studies on the changes to cell morphologies during bacterial growth, persister cell formation and the VBNC state are few and severely constrained by current limitations in the most used investigative techniques of flow cytometry (FC) and light or electron microscopy. In this study, we applied high-throughput Imaging Flow Cytometry (IFC) to characterise and quantify, at single-cell level and over time, the phenotypic heterogeneity and morphological changes in cultured populations of four bacterial species, Bacillus subtilis, Lactiplantibacillus plantarum, Pediococcus acidilactici and Escherichia coli. Morphologies in relation to growth stage and stress responses, cell integrity and metabolic activity were analysed. Additionally, we were able to identify and morphologically classify dormant cell phenotypes such as VBNC cells and monitor the resuscitation of persister cells in Escherichia coli following antibiotic treatment. We therefore demonstrate that IFC, with its high-throughput data collection and image capture capabilities, provides a platform by which a detailed understanding of changes in bacterial phenotypes and their physiological implications may be accurately monitored and quantified, leading to a better understanding of the role of phenotypic heterogeneity in the dynamic microbiome.

Visualization and Quantification of Genetically Adapted Microbial Cells During Preculture

As culture history is known to affect the length of the lag phase and microbial cell growth, precultures are often grown in the same medium as the main culture for physiological adaptation and to reduce a prolonged lag time in some microbial cells. To understand the adaptation process of microbial cells during transfer from Luria-Bertani medium to minimal medium, we used the growth of Escherichia coli BL21(DE3) in succinate minimal medium as a model system. We observed that only one or two sequential transfers from minimal medium to fresh minimal medium accelerated the growth rate of BL21(DE3) cells. In addition, the number of large colonies (diameter ≥0.1 cm) on succinate agar increased with the number of transfers. Genome and transcript analyses showed that the C-to-T point mutation in large colony cells converted the inactive promoter of kgtP (known to encode α-ketoglutarate permease) to the active form, allowing efficient uptake of exogenous succinate. Moreover, we visualized the occurrence of genetically adapted cells with better fitness in real time and quantified the number of those cells in the microbial population during transfer to the same medium. Fluorescence microscopy showed the occurrence and increase of adapted mutant cells, which contain intracellular KgtP-fused green fluorescent proteins, as a result of the C-to-T mutation in the promoter of a fused kgtP-sfgfp during transfer to fresh medium. Flow cytometry revealed that the proportion of mutant cells increased from 1.75% (first transfer) to 12.16% (second transfer) and finally 70.79% (third transfer), explaining the shortened lag time and accelerated growth rate of BL21(DE3) cells during adaptation to the minimal medium. This study provides new insights into the genetic heterogeneity of microbial populations that aids microbial adaptability in new environments.

Measuring and modeling energy and power consumption in living microbial cells with a synthetic ATP reporter

Background

Adenosine triphosphate (ATP) is the main energy carrier in living organisms, critical for metabolism and essential physiological processes. In humans, abnormal regulation of energy levels (ATP concentration) and power consumption (ATP consumption flux) in cells is associated with numerous diseases from cancer, to viral infection and immune dysfunction, while in microbes it influences their responses to drugs and other stresses. The measurement and modeling of ATP dynamics in cells is therefore a critical component in understanding fundamental physiology and its role in pathology. Despite the importance of ATP, our current understanding of energy dynamics and homeostasis in living cells has been limited by the lack of easy-to-use ATP sensors and the lack of models that enable accurate estimates of energy and power consumption related to these ATP dynamics. Here we describe a dynamic model and an ATP reporter that tracks ATP in E. coli over different growth phases.

Results

The reporter is made by fusing an ATP-sensing rrnB P1 promoter with a fast-folding and fast-degrading GFP. Good correlations between reporter GFP and cellular ATP were obtained in E. coli growing in both minimal and rich media and in various strains. The ATP reporter can reliably monitor bacterial ATP dynamics in response to nutrient availability. Fitting the dynamics of experimental data corresponding to cell growth, glucose, acetate, dissolved oxygen, and ATP yielded a mathematical and circuit model. This model can accurately predict cellular energy and power consumption under various conditions. We found that cellular power consumption varies significantly from approximately 0.8 and 0.2 million ATP/s for a tested strain during lag and stationary phases to 6.4 million ATP/s during exponential phase, indicating ~ 8–30-fold changes of metabolic rates among different growth phases. Bacteria turn over their cellular ATP pool a few times per second during the exponential phase and slow this rate by ~ 2–5-fold in lag and stationary phases.

Conclusion

Our rrnB P1-GFP reporter and kinetic circuit model provide a fast and simple way to monitor and predict energy and power consumption dynamics in bacterial cells, which can impact fundamental scientific studies and applied medical treatments in the future.

Conjugation dynamics depend on both the plasmid acquisition cost and the fitness cost

Plasmid conjugation is a major mechanism responsible for the spread of antibiotic resistance. Plasmid fitness costs are known to impact long-term growth dynamics of microbial populations by providing plasmid-carrying cells a relative (dis)advantage compared to plasmid-free counterparts. Separately, plasmid acquisition introduces an immediate, but transient, metabolic perturbation. However, the impact of these short-term effects on subsequent growth dynamics has not previously been established. Here, we observed that de novo transconjugants grew significantly slower and/or with overall prolonged lag times, compared to lineages that had been replicating for several generations, indicating the presence of a plasmid acquisition cost. These effects were general to diverse incompatibility groups, well-characterized and clinically captured plasmids, Gram-negative recipient strains and species, and experimental conditions. Modeling revealed that both fitness and acquisition costs modulate overall conjugation dynamics, validated with previously published data. These results suggest that the hours immediately following conjugation may play a critical role in both short- and long-term plasmid prevalence. This time frame is particularly relevant to microbiomes with high plasmid/strain diversity considered to be hot spots for conjugation.

When to wake up? The optimal waking-up strategies for starvation-induced persistence

Prolonged lag time can be induced by starvation contributing to the antibiotic tolerance of bacteria. We analyze the optimal lag time to survive and grow the iterative and stochastic application of antibiotics. A simple model shows that the optimal lag time can exhibit a discontinuous transition when the severeness of the antibiotic application, such as the probability to be exposed the antibiotic, the death rate under the exposure, and the duration of the exposure, is increased. This suggests the possibility of reducing tolerant bacteria by controlled usage of antibiotics application. When the bacterial populations are able to have two phenotypes with different lag times, the fraction of the second phenotype that has different lag time shows a continuous transition. We then present a generic framework to investigate the optimal lag time distribution for total population fitness for a given distribution of the antibiotic application duration. The obtained optimal distributions have multiple peaks for a wide range of the antibiotic application duration distributions, including the case where the latter is monotonically decreasing. The analysis supports the advantage in evolving multiple, possibly discrete phenotypes in lag time for bacterial long-term fitness.

Availability of the Molecular Switch XylR Controls Phenotypic Heterogeneity and Lag Duration during Escherichia coli Adaptation from Glucose to Xylose

The glucose-xylose metabolic transition is of growing interest as a model to explore cellular adaption since these molecules are the main substrates resulting from the deconstruction of lignocellulosic biomass. Here, we investigated the role of the XylR transcription factor in the length of the lag phases when the bacterium Escherichia coli needs to adapt from glucose- to xylose-based growth. First, a variety of lag times were observed when different strains of E. coli were switched from glucose to xylose. These lag times were shown to be controlled by XylR availability in the cells with no further effect on the growth rate on xylose. XylR titration provoked long lag times demonstrated to result from phenotypic heterogeneity during the switch from glucose to xylose, with a subpopulation unable to resume exponential growth, whereas the other subpopulation grew exponentially on xylose. A stochastic model was then constructed based on the assumption that XylR availability influences the probability of individual cells to switch to xylose growth. The model was used to understand how XylR behaves as a molecular switch determining the bistability set-up. This work shows that the length of lag phases in E. coli is controllable and reinforces the role of stochastic mechanism in cellular adaptation, paving the way for new strategies for the better use of sustainable carbon sources in bioeconomy.

Using fluorescence flow cytometry data for single-cell gene expression analysis in bacteria

Fluorescence flow cytometry is increasingly being used to quantify single-cell expression distributions in bacteria in high-throughput. However, there has been no systematic investigation into the best practices for quantitative analysis of such data, what systematic biases exist, and what accuracy and sensitivity can be obtained. We investigate these issues by measuring the same E. coli strains carrying fluorescent reporters using both flow cytometry and microscopic setups and systematically comparing the resulting single-cell expression distributions. Using these results, we develop methods for rigorous quantitative inference of single-cell expression distributions from fluorescence flow cytometry data. First, we present a Bayesian mixture model to separate debris from viable cells using all scattering signals. Second, we show that cytometry measurements of fluorescence are substantially affected by autofluorescence and shot noise, which can be mistaken for intrinsic noise in gene expression, and present methods to correct for these using calibration measurements. Finally, we show that because forward- and side-scatter signals scale non-linearly with cell size, and are also affected by a substantial shot noise component that cannot be easily calibrated unless independent measurements of cell size are available, it is not possible to accurately estimate the variability in the sizes of individual cells using flow cytometry measurements alone. To aid other researchers with quantitative analysis of flow cytometry expression data in bacteria, we distribute E-Flow, an open-source R package that implements our methods for filtering debris and for estimating true biological expression means and variances from the fluorescence signal. The package is available at https://github.com/vanNimwegenLab/E-Flow.

Escherichia coli with a Tunable Point Mutation Rate for Evolution Experiments

The mutation rate and mutations' effects on fitness are crucial to evolution. Mutation rates are under selection due to linkage between mutation rate modifiers and mutations' effects on fitness. The linkage between a higher mutation rate and more beneficial mutations selects for higher mutation rates, while the linkage between a higher mutation rate and more deleterious mutations selects for lower mutation rates. The net direction of selection on mutations rates depends on the fitness landscape, and a great deal of work has elucidated the fitness landscapes of mutations. However, tests of the effect of varying a mutation rate on evolution in a single organism in a single environment have been difficult. This has been studied using strains of antimutators and mutators, but these strains may differ in additional ways and typically do not allow for continuous variation of the mutation rate. To help investigate the effects of the mutation rate on evolution, we have genetically engineered a strain of Escherichia coli with a point mutation rate that can be smoothly varied over two orders of magnitude. We did this by engineering a strain with inducible control of the mismatch repair proteins MutH and MutL. We used this strain in an approximately 350 generation evolution experiment with controlled variation of the mutation rate. We confirmed the construct and the mutation rate were stable over this time. Sequencing evolved strains revealed a higher number of single nucleotide polymorphisms at higher mutations rates, likely due to either the beneficial effects of these mutations or their linkage to beneficial mutations.

Wide lag time distributions break a trade-off between reproduction and survival in bacteria

Many microorganisms face a fundamental trade-off between reproduction and survival: Rapid growth boosts population size but makes microorganisms sensitive to external stressors. Here, we show that starved bacteria encountering new resources can break this trade-off by evolving phenotypic heterogeneity in lag time. We quantify the distribution of single-cell lag times of populations of starved Escherichia coli and show that population growth after starvation is primarily determined by the cells with shortest lag due to the exponential nature of bacterial population dynamics. As a consequence, cells with long lag times have no substantial effect on population growth resumption. However, we observe that these cells provide tolerance to stressors such as antibiotics. This allows an isogenic population to break the trade-off between reproduction and survival. We support this argument with an evolutionary model which shows that bacteria evolve wide lag time distributions when both rapid growth resumption and survival under stressful conditions are under selection. Our results can explain the prevalence of antibiotic tolerance by lag and demonstrate that the benefits of phenotypic heterogeneity in fluctuating environments are particularly high when minorities with extreme phenotypes dominate population dynamics.

Effects of a polysaccharide-rich extract derived from Irish-sourced Laminaria digitata on the composition and metabolic activity of the human gut microbiota using an in vitro colonic model

BACKGROUND

Brown seaweeds are known to be a rich source of fiber with the presence of several non-digestible polysaccharides including laminarin, fucoidan and alginate. These individual polysaccharides have previously been shown to favorably alter the gut microbiota composition and activity albeit the effect of the collective brown seaweed fiber component on the microbiota remains to be determined.

METHODS

This study investigated the effect of a crude polysaccharide-rich extract obtained from Laminaria digitata (CE) and a depolymerized CE extract (DE) on the gut microbiota composition and metabolism using an in vitro fecal batch culture model though metagenomic compositional analysis using 16S rRNA FLX amplicon pyrosequencing and short-chain fatty acid (SCFA) analysis using GC-FID.

RESULTS

Selective culture analysis showed no significant changes in cultured lactobacilli or bifidobacteria between the CE or DE and the cellulose-negative control at any time point measured (0, 5, 10, 24, 36, 48 h). Following metagenomic analysis, the CE and DE significantly altered the relative abundance of several families including Lachnospiraceae and genera including Streptococcus, Ruminococcus and Parabacteroides of human fecal bacterial populations in comparison to cellulose after 24 h. The concentrations of acetic acid, propionic acid, butyric acid and total SCFA were significantly higher for both the CE and DE compared to cellulose after 10, 24, 36 and 48 h fermentation (p < 0.05). Furthermore, the acetate:propionate ratio was significantly reduced (p < 0.05) for both CD and DE following 24, 36 and 48 h fermentation.

CONCLUSION

The microbiota-associated metabolic and compositional changes noted provide initial indication of putative beneficial health benefits of L. digitata in vitro; however, research is needed to clarify if L. digitata-derived fiber can favorably alter the gut microbiota and confer health benefits in vivo.

A Bacterial Growth Law out of Steady State

Bacterial growth follows simple laws in constant conditions. However, bacteria in nature often face fluctuating environments. We therefore ask whether there are growth laws that apply to changing environments. We derive a law for upshifts using an optimal resource-allocation model: the post-shift growth rate equals the geometrical mean of the pre-shift growth rate and the growth rate on saturating carbon. We test this using chemostat and batch culture experiments, as well as previous data from several species. The increase in growth rate after an upshift indicates that ribosomes have spare capacity (SC). We demonstrate theoretically that SC has the cost of slow steady-state growth but is beneficial after an upshift because it prevents large overshoots in intracellular metabolites and allows rapid response to change. We also provide predictions for downshifts. The present study quantifies the optimal degree of SC, which rises the slower the growth rate, and suggests that SC can be precisely regulated.

Identifying the Growth Modulon of Corynebacterium glutamicum

The growth rate (μ) of industrially relevant microbes, such as Corynebacterium glutamicum, is a fundamental property that indicates its production capacity. Therefore, understanding the mechanism underlying the growth rate is imperative for improving productivity and performance through metabolic engineering. Despite recent progress in the understanding of global regulatory interactions, knowledge of mechanisms directing cell growth remains fragmented and incomplete. The current study investigated RNA-Seq data of three growth rate transitions, induced by different pre-culture conditions, in order to identify transcriptomic changes corresponding to increasing growth rates. These transitions took place in minimal medium and ranged from 0.02 to 0.4 h^-1 μ. This study enabled the identification of 447 genes as components of the growth modulon. Enrichment of genes within the growth modulon revealed 10 regulons exhibiting a significant effect over growth rate transition. In summary, central metabolism was observed to be regulated by a combination of metabolic and transcriptional activities orchestrating control over glycolysis, pentose phosphate pathway, and the tricarboxylic acid cycle. Additionally, major responses to changes in the growth rate were linked to iron uptake and carbon metabolism. In particular, genes encoding glycolytic enzymes and the glucose uptake system showed a positive correlation with the growth rate.

Silver nanoparticles exert concentration-dependent influences on biofilm development and architecture

Objectives

To investigate the impact of silver nanoparticles (AgNPs) on the biofilm growth and architecture.

Materials and methods

Silver nitrate was reduced by d‐maltose to prepare AgNPs in the presence of ammonia and sodium hydroxide. The physicochemical properties of AgNPs were characterized by transmission electron microscopy, ultraviolet‐visible spectroscopy and inductively coupled plasma mass spectrometry. The development of biofilm with and without AgNPs was explored by crystal violet stain. The structures of mature biofilm were visually studied by confocal laser scanning microscopy and scanning electron microscopy. Bacterial cell, polysaccharide and protein within biofilm were assessed quantitatively by colony‐counting method, phenol‐sulphuric acid method and Bradford assay, respectively.

Results

The spherical AgNPs (about 30 nm) were successfully synthesized. The effect of AgNPs on Pseudomonas aeruginosa biofilm development was concentration‐dependent. Biofilm was more resistant to AgNPs than planktonic cells. Low doses of AgNPs exposure remarkably delayed the growth cycle of biofilm, whereas high concentration (18 μg/mL) of AgNPs fully prevented biofilm development. The analysis of biofilm architecture at the mature stage demonstrated that AgNPs exposure at all concentration led to significant decrease of cell viability within treated biofilms. However, sublethal doses of AgNPs increased the production of both polysaccharide and protein compared to control, which significantly changed the biofilm structure.

Conclusions

AgNPs exert concentration‐dependent influences on biofilm development and structure, which provides new insight into the role of concentration played in the interaction between antibacterial nanoparticles and biofilm, especially, an ignored sublethal concentration associated with potential unintended consequences.

Lag Phase Is a Dynamic, Organized, Adaptive, and Evolvable Period That Prepares Bacteria for Cell Division

Lag is a temporary period of nonreplication seen in bacteria that are introduced to new media. Despite latency being described by Müller in 1895, only recently have we gained insights into the cellular processes characterizing lag phase. This review covers literature to date on the transcriptomic, proteomic, metabolomic, physiological, biochemical, and evolutionary features of prokaryotic lag. Though lag is commonly described as a preparative phase that allows bacteria to harvest nutrients and adapt to new environments, the implications of recent studies indicate that a refinement of this view is well deserved. As shown, lag is a dynamic, organized, adaptive, and evolvable process that protects bacteria from threats, promotes reproductive fitness, and is broadly relevant to the study of bacterial evolution, host-pathogen interactions, antibiotic tolerance, environmental biology, molecular microbiology, and food safety.

Synthesis and degradation of FtsZ quantitatively predict the first cell division in starved bacteria

In natural environments, microbes are typically non-dividing and gauge when nutrients permit division. Current models are phenomenological and specific to nutrient-rich, exponentially growing cells, thus cannot predict the first division under limiting nutrient availability. To assess this regime, we supplied starving Escherichia coli with glucose pulses at increasing frequencies. Real-time metabolomics and microfluidic single-cell microscopy revealed unexpected, rapid protein, and nucleic acid synthesis already from minuscule glucose pulses in non-dividing cells. Additionally, the lag time to first division shortened as pulsing frequency increased. We pinpointed division timing and dependence on nutrient frequency to the changing abundance of the division protein FtsZ. A dynamic, mechanistic model quantitatively relates lag time to FtsZ synthesis from nutrient pulses and FtsZ protease-dependent degradation. Lag time changed in model-congruent manners, when we experimentally modulated the synthesis or degradation of FtsZ. Thus, limiting abundance of FtsZ can quantitatively predict timing of the first cell division.

The importance of lag time extension in determining bacterial resistance to antibiotics

It is widely appreciated that widespread antibiotic resistance has significantly reduced the utility of today's antibiotics. Many antibiotics now fail to cure infectious diseases, although they are classified as effective bactericidal agents based on antibiotic susceptibility tests. Here, via kinetic growth assays, we evaluated the effects of 12 commonly used antibiotics on the lag phase of a range of pure environmental isolates and of sludge bacterial communities with a high diversity. We show that an extended lag phase offers bacteria survival advantages and promotes regrowth upon the removal of antibiotics. By utilizing both lag phase extension and IC50, the killing efficiency of an antibiotic on a strain or a community can be easily revealed. Interestingly, for several strains of relevance to endemic nosocomial infections (e.g. Acinetobacter sp. and Pseudomonas aeruginosa) and the diverse sludge communities, tetracycline and quinolone antibiotics are most likely to be resisted via extended lag phase. This discovery is significant from a clinical point view since underestimation of bacteria resistance can lead to the recurrence of diseases.

Modeling of starter cultures growth for improved Thai sausage fermentation and cost estimating for sausage preparation and transportation

The purpose of this study was to improve Thai fermented sausage flavor by adding starter cultures (i.e., Pediococcus pentosaceus, Pediococcus acidilactici, Weissella cibaria, Lactobacillus plantarum, Lactobacillus pentosus, and Lactobacillus sakei) as compared with naturally fermented sausage. The predictive mathematical models for growth of P. acidilactici and natural lactic acid bacteria (LAB) in Thai fermented sausage were developed to obtain specific prepared sausage quality. Furthermore, comparisons of sausage preparation and transportation cost between nonrefrigerated and refrigerated trucks were studied. The concentration of 3-methyl-butanoic acid synthesized from LAB inoculated sausage was higher than in the control sample which contributed to the flavor forming. Moreover, the proposed unstructured kinetic models of Thai fermented sausage substrates and products describing the consumption of total protein and glucose, and the production of nonprotein nitrogen responsible for flavor enhancer, lactic acid and formic acid concentration were successfully fitted with two selected experimental data sets of the in situ fermentation of Thai fermented sausage. Finally, the transportation of inoculated sausages in a nonrefrigerated truck by combining fermentation process and transportation was more cost efficient for delivering sausages in a long distance.

Sustained antibacterial activity of berberine hydrochloride loaded supramolecular organoclay networks with hydrogen-bonding junctions

The environmental risk from antibiotics is an issue of increasing concern. So, carboxymethyl β-cyclodextrin-functionalized montmorillonite nanosheets were for the first time successfully synthesized through a cheap, environmentally friendly and scalable approach and confirmed by FTIR, XRD and TGA. FE-SEM investigation showed that the resulting functional material could be further self-assembled into dense supramolecular organoclay networks (D-networks). The antibacterial properties of the D-networks loaded with natural berberine hydrochloride (BBH) were investigated toward E. coli and S. aureus by using colony growth on agar plates, bacterial growth curves based on optical densities, and confocal and fluorescence microscopy. Our studies demonstrated that the BBH loaded D-network antibacterial activity was concentration dependent and significantly exceeded that of free BBH. FE-SEM observation confirmed that E. coli and S. aureus can directly contact the D-networks and confocal and fluorescence microscopy showed that free BBH was only very poorly internalized, while the BBH released from the BBH-loaded D-network could be internalized efficiently into bacterial cells, resulting in an increment of the intracellular BBH level compared with the free BBH group. Time-dependent antibacterial activity was observed and it was found that the BBH-loaded D-network dispersion at the BBH dosage of 600 μg mL^-1 almost completely suppressed the growth of E. coli, leading to a viability loss of up to 98.45 ± 1.22%, while the BBH-loaded D-network dispersion at the BBH concentration of 250 μg mL^-1 exhibited a growth inhibition of 97.81 ± 0.83% toward S. aureus over three days. Our results suggest that supramolecular organoclay networks, in the future, may function as promising antibacterial drug carrier systems to promote BBH delivery in E. coli and S. aureus, which can reduce the environmental risk of antibiotics.

A Dynamic Model of Resource Allocation in Response to the Presence of a Synthetic Construct

Introducing synthetic constructs into bacteria often carries a burden that leads to reduced fitness and selective pressure for organisms to mutate their constructs and hence to a reduced functional lifetime. Understanding burden requires suitable methods for accurate measurement and quantification. We develop a dynamic growth model from physiologically relevant first-principles that allows parameters relevant to burden to be extracted from standard growth curves. We test several possibilities for the response of a bacterium to a new environment in terms of resource allocation. We find that burden manifests in the time taken to respond to new conditions as well as the rate of growth in exponential phase. Furthermore, we see that the presence of a synthetic construct hastens the reduction of ribosomes when approaching stationary phase, altering memory effects from previous periods of growth.

Reconstructing Dynamic Promoter Activity Profiles from Reporter Gene Data

Accurate characterization of promoter activity is important when designing expression systems for systems biology and metabolic engineering applications. Promoters that respond to changes in the environment enable the dynamic control of gene expression without the necessity of inducer compounds, for example. However, the dynamic nature of these processes poses challenges for estimating promoter activity. Most experimental approaches utilize reporter gene expression to estimate promoter activity. Typically the reporter gene encodes a fluorescent protein that is used to infer a constant promoter activity despite the fact that the observed output may be dynamic and is a number of steps away from the transcription process. In fact, some promoters that are often thought of as constitutive can show changes in activity when growth conditions change. For these reasons, we have developed a system of ordinary differential equations for estimating dynamic promoter activity for promoters that change their activity in response to the environment that is robust to noise and changes in growth rate. Our approach, inference of dynamic promoter activity (PromAct), improves on existing methods by more accurately inferring known promoter activity profiles. This method is also capable of estimating the correct scale of promoter activity and can be applied to quantitative data sets to estimate quantitative rates.

Enterococcus faecalis Hydrolyzes Dental Resin Composites and Adhesives

INTRODUCTION

After root canal treatment, the dentin-sealer interface undergoes degradation, allowing for interfacial microbial biofilm proliferation and treatment failure. Saliva and cariogenic bacteria showed esterase-like activities (ie, cholesterol esterase [CE]-like and/or pseudocholinesterase [PCE]-like) that degrade methacrylate-based resin materials and/or the restoration-tooth interface, increasing microbial interfacial proliferation. Enterococcus faecalis is a gram-positive bacterium that is commonly detected in persistent endodontic infections. The aim of this study was to measure E. faecalis esterase-like, CE-like, and PCE-like activities and to assess the ability of the bacterium to degrade methacrylate-based resin composite (RC) and total-etch (TE) and self-etch (SE) adhesives.

METHODS

CE-like and PCE-like activities from E. faecalis were measured using nitrophenyl and butyrylthiocholine substrates, respectively. The ability of E. faecalis to degrade resin composite, total-etch and self-etch adhesives was examined by quantifying the release of a universal resin degradation by-product (ie, Bis[hydroxypropoxy]-phenyl propane [BisHPPP]) using high-performance liquid chromatography.

RESULTS

E. faecalis showed CE-like (1.23 ± 0.13 U/μg dry bacteria) but no PCE-like activity. After 30 days and/or 14 days of incubation, the amount of BisHPPP released was significantly higher in the presence of bacteria versus media for TE and RC but not SE (P < .05). The amount of BisHPPP released after 30 days of incubation with bacteria was highest for TE (23.69 ± 1.72 μg/cm²) followed by RC (3.43 ± 1.20 μg/cm²) and lowest for SE (0.86 ± 0.44 μg/cm²) (P < .05).

CONCLUSIONS

E. faecalis possesses esterase-like degradative activity toward dental methacrylate resin restoration materials, which could accelerate the degradation of the dentin-methacrylate resin interface, increasing bacterial biofilm proliferation and penetration into the root canal system.

Global Inhibition with Specific Activation: How p53 and MYC Redistribute the Transcriptome in the DNA Double-Strand Break Response

In response to stresses, cells often halt normal cellular processes, yet stress-specific pathways must bypass such inhibition to generate effective responses. We investigated how cells redistribute global transcriptional activity in response to DNA damage. We show that an oscillatory increase of p53 levels in response to double-strand breaks drives a counter-oscillatory decrease of MYC levels. Using RNA sequencing (RNA-seq) of newly synthesized transcripts, we found that p53-mediated reduction of MYC suppressed general transcription, with the most highly expressed transcripts reduced to a greater extent. In contrast, upregulation of p53 targets was relatively unaffected by MYC suppression. Reducing MYC during the DNA damage response was important for cell-fate regulation, as counteracting MYC repression reduced cell-cycle arrest and elevated apoptosis. Our study shows that global inhibition with specific activation of transcriptional pathways is important for the proper response to DNA damage; this mechanism may be a general principle used in many stress responses.

Global mRNA polarization regulates translation efficiency in the intestinal epithelium

Asymmetric messenger RNA (mRNA) localization facilitates efficient translation in cells such as neurons and fibroblasts. However, the extent and importance of mRNA polarization in epithelial tissues are unclear. Here, we used single-molecule transcript imaging and subcellular transcriptomics to uncover global apical-basal intracellular polarization of mRNA in the mouse intestinal epithelium. The localization of mRNAs did not generally overlap protein localization. Instead, ribosomes were more abundant on the apical sides, and apical transcripts were consequently more efficiently translated. Refeeding of fasted mice elicited a basal-to-apical shift in polarization of mRNAs encoding ribosomal proteins, which was associated with a specific boost in their translation. This led to increased protein production, required for efficient nutrient absorption. These findings reveal a posttranscriptional regulatory mechanism involving dynamic polarization of mRNA and polarized translation.

Obtaining a Panel of Cascade Promoter-5'-UTR Complexes in Escherichia coli

A promoter is one of the most important and basic tools used to achieve diverse synthetic biology goals. Escherichia coli is one of the most commonly used model organisms in synthetic biology to produce useful target products and establish complicated regulation networks. During the fine-tuning of metabolic or regulation networks, the limited number of well-characterized inducible promoters has made implementing complicated strategies difficult. In this study, 104 native promoter-5'-UTR complexes (PUTR) from E. coli were screened and characterized based on a series of RNA-seq data. The strength of the 104 PUTRs varied from 0.007% to 4630% of that of the P_BAD promoter in the transcriptional level and from 0.1% to 137% in the translational level. To further upregulate gene expression, a series of combinatorial PUTRs and cascade PUTRs were constructed by integrating strong transcriptional promoters with strong translational 5'-UTRs. Finally, two combinatorial PUTRs (P_ssrA-UTR_rpsT and P_dnaKJ-UTR_rpsT) and two cascade PUTRs (PUTR_ssrA-PUTR_infC-rplT and PUTR_alsRBACE-PUTR_infC-rplT) were identified as having the highest activity, with expression outputs of 170%, 137%, 409%, and 203% of that of the P_BAD promoter, respectively. These engineered PUTRs are stable for the expression of different genes, such as the red fluorescence protein gene and the β-galactosidase gene. These results show that the PUTRs characterized and constructed in this study may be useful as a plug-and-play synthetic biology toolbox to achieve complicated metabolic engineering goals in fine-tuning metabolic networks to produce target products.

Antimicrobial Activity and Resistance: Influencing Factors

Rational use of antibiotic is the key approach to improve the antibiotic performance and tackling of the antimicrobial resistance. The efficacy of antimicrobials are influenced by many factors: (1) bacterial status (susceptibility and resistance, tolerance, persistence, biofilm) and inoculum size; (2) antimicrobial concentrations [mutant selection window (MSW) and sub-inhibitory concentration]; (3) host factors (serum effect and impact on gut micro-biota). Additional understandings regarding the linkage between antimicrobial usages, bacterial status and host response offers us new insights and encourage the struggle for the designing of antimicrobial treatment regimens that reaching better clinical outcome and minimizing the emergence of resistance at the same time.

Kinetic 15N-isotope effects on algal growth

Stable isotope labeling is a standard technique for tracing material transfer in molecular, ecological and biogeochemical studies. The main assumption in this approach is that the enrichment with a heavy isotope has no effect on the organism metabolism and growth, which is not consistent with current theoretical and empirical knowledge on kinetic isotope effects. Here, we demonstrate profound changes in growth dynamics of the green alga Raphidocelis subcapitata grown in 15N-enriched media. With increasing 15N concentration (0.37 to 50 at%), the lag phase increased, whereas maximal growth rate and total yield decreased; moreover, there was a negative relationship between the growth and the lag phase across the treatments. The latter suggests that a trade-off between growth rate and the ability to adapt to the high 15N environment may exist. Remarkably, the lag-phase response at 3.5 at% 15N was the shortest and deviated from the overall trend, thus providing partial support to the recently proposed Isotopic Resonance hypothesis, which predicts that certain isotopic composition is particularly favorable for living organisms. These findings confirm the occurrence of KIE in isotopically enriched algae and underline the importance of considering these effects when using stable isotope labeling in field and experimental studies.

Resuscitation of Pseudomonas aeruginosa from dormancy requires hibernation promoting factor (PA4463) for ribosome preservation

Pseudomonas aeruginosa biofilm infections are difficult to treat with antibiotic therapy in part because the biofilms contain subpopulations of dormant antibiotic-tolerant cells. The dormant cells can repopulate the biofilms following alleviation of antibiotic treatments. While dormant, the bacteria must maintain cellular integrity, including ribosome abundance, to reinitiate the de novo protein synthesis required for resuscitation. Here, we demonstrate that the P. aeruginosa gene PA4463 [hibernation promoting factor (HPF)], but not the ribosome modulation factor (PA3049), is required for ribosomal RNA preservation during prolonged nutrient starvation conditions. Single-cell-level studies using fluorescence in situ hybridization (FISH) and growth in microfluidic drops demonstrate that, in the absence of hpf, the rRNA abundances of starved cells decrease to levels that cause them to lose their ability to resuscitate from starvation, leaving intact nondividing cells. P. aeruginosa defective in the stringent response also had reduced ability to resuscitate from dormancy. However, FISH analysis of the starved stringent response mutant showed a bimodal response where the individual cells contained either abundant or low ribosome content, compared with the wild-type strain. The results indicate that ribosome maintenance is key for maintaining the ability of P. aeruginosa to resuscitate from starvation-induced dormancy and that HPF is the major factor associated with P. aeruginosa ribosome preservation.

Molecular switching involving metastable states: molecular thermal hysteresis and sensing of environmental changes by chiral helicene oligomeric foldamers

Molecular switching is a phenomenon in which the molecular structure reversibly changes in response to external stimulation. It is crucial in biology and is used in various biological sensing applications and responses. In contrast to the well-studied molecular switching involving two or more thermodynamically stable states, switching involving metastable states exhibits notable non-equilibrium thermodynamic properties. Synthetic chiral helicene oligomeric foldamers that exhibit molecular thermal hysteresis in dilute solution are examples. Molecular switching can be used for sensing environmental changes, including temperature threshold, temperature decrease/increase, rate of temperature decrease, counting the numbers 1 and 2, and concentration increase.

SuperSegger: robust image segmentation, analysis and lineage tracking of bacterial cells

Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame-to-frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB-based image processing package well-suited to quantitative analysis of high-throughput live-cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine-learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame-to-frame. Unlike existing packages, it can reliably segment microcolonies with many cells, facilitating the analysis of cell-cycle dynamics in bacteria as well as cell-contact mediated phenomena. This package has a range of built-in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter and neighbouring cells, and computing statistics on cellular fluorescence, the location and intensity of fluorescent foci. SuperSegger provides a variety of postprocessing data visualization tools for single cell and population level analysis, such as histograms, kymographs, frame mosaics, movies and consensus images. Finally, we demonstrate the power of the package by analyzing lag phase growth with single cell resolution.

Flow cytometry what you see matters: Enhanced clinical detection using image-based flow cytometry

Image-based flow cytometry combines the throughput of traditional flow cytometry with the ability to visually confirm findings and collect novel data that would not be possible otherwise. Since image-based flow cytometry borrows measurement parameters and analysis techniques from microscopy, it is possible to collect unique measures (i.e. nuclear translocation, co-localization, cellular synapse, cellular endocytosis, etc.) that would not be possible with traditional flow cytometry. The ability to collect unique outcomes has led many researchers to develop novel assays for the monitoring and detection of a variety of clinical conditions and diseases. In many cases, investigators have innovated and expanded classical assays to provide new insight regarding clinical conditions and chronic disease. Beyond human clinical applications, image-based flow cytometry has been used to monitor marine biology changes, nano-particles for solar cell production, and particle quality in pharmaceuticals. This review article summarizes work from the major scientists working in the field of image-based flow cytometry.

A General Method for Measuring Persister Levels in Escherichia coli Cultures

Genetically homogeneous bacterial cultures contain persisters, cells that are not killed by bactericidal antibiotics. These cells are suggested to be involved in the establishment of chronic infections. Persister levels depend on growth conditions. Here, we discuss the parameters that have to be considered when measuring persister levels and provide a sample protocol to do it.

Persisters-as elusive as ever

Persisters—a drug-tolerant sub-population in an isogenic bacterial culture—have been featured throughout the last decade due to their important role in recurrent bacterial infections. Numerous investigations detail the mechanisms responsible for the formation of persisters and suggest exciting strategies for their eradication. In this review, we argue that the very term “persistence” is currently used to describe a large and heterogeneous set of physiological phenomena that are functions of bacterial species, strains, growth conditions, and antibiotics used in the experiments. We caution against the oversimplification of the mechanisms of persistence and urge for a more rigorous validation of the applicability of these mechanisms in each case.

Principles of dynamical modularity in biological regulatory networks

Intractable diseases such as cancer are associated with breakdown in multiple individual functions, which conspire to create unhealthy phenotype-combinations. An important challenge is to decipher how these functions are coordinated in health and disease. We approach this by drawing on dynamical systems theory. We posit that distinct phenotype-combinations are generated by interactions among robust regulatory switches, each in control of a discrete set of phenotypic outcomes. First, we demonstrate the advantage of characterizing multi-switch regulatory systems in terms of their constituent switches by building a multiswitch cell cycle model which points to novel, testable interactions critical for early G2/M commitment to division. Second, we define quantitative measures of dynamical modularity, namely that global cell states are discrete combinations of switch-level phenotypes. Finally, we formulate three general principles that govern the way coupled switches coordinate their function.

Dynamical Allocation of Cellular Resources as an Optimal Control Problem: Novel Insights into Microbial Growth Strategies

Microbial physiology exhibits growth laws that relate the macromolecular composition of the cell to the growth rate. Recent work has shown that these empirical regularities can be derived from coarse-grained models of resource allocation. While these studies focus on steady-state growth, such conditions are rarely found in natural habitats, where microorganisms are continually challenged by environmental fluctuations. The aim of this paper is to extend the study of microbial growth strategies to dynamical environments, using a self-replicator model. We formulate dynamical growth maximization as an optimal control problem that can be solved using Pontryagin’s Maximum Principle. We compare this theoretical gold standard with different possible implementations of growth control in bacterial cells. We find that simple control strategies enabling growth-rate maximization at steady state are suboptimal for transitions from one growth regime to another, for example when shifting bacterial cells to a medium supporting a higher growth rate. A near-optimal control strategy in dynamical conditions is shown to require information on several, rather than a single physiological variable. Interestingly, this strategy has structural analogies with the regulation of ribosomal protein synthesis by ppGpp in the enterobacterium Escherichia coli. It involves sensing a mismatch between precursor and ribosome concentrations, as well as the adjustment of ribosome synthesis in a switch-like manner. Our results show how the capability of regulatory systems to integrate information about several physiological variables is critical for optimizing growth in a changing environment.

Microbial growth is the process by which cells sustain and reproduce themselves from available matter and energy. Strategies enabling microorganisms to optimize their growth rate have been extensively studied, but mostly in stable environments. Here, we build a coarse-grained model of microbial growth and use methods from optimal control theory to determine a resource allocation scheme that would lead to maximal biomass accumulation when the cells are dynamically shifted from one growth medium to another. We compare this optimal solution with several cellular implementations of growth control, based on the capacity of the cell to sense different physiological variables. We find that strategies maximizing growth in steady-state conditions perform quite differently in dynamical conditions. Moreover, the control strategy with performance close to the theoretical maximum exploits information of more than one physiological variable, suggesting that optimization of microbial growth in dynamical rather than steady environments requires broader sensory capacities. Interestingly, the ppGpp alarmone system in the enterobacterium Escherichia coli, known to play an important role in growth control, has structural similarities with the control strategy approaching the theoretical maximum. It senses a discrepancy between the concentrations of precursors and ribosomes, and adjusts ribosome synthesis in an on-off fashion. This suggests that E. coli is adapted for environments with intermittent, rapid changes in nutrient availability.

Real-time metabolome profiling of the metabolic switch between starvation and growth

Metabolic systems are often the first networks to respond to environmental changes, and the ability to monitor metabolite dynamics is key for understanding these cellular responses. Because monitoring metabolome changes is experimentally tedious and demanding, dynamic data on time scales from seconds to hours are scarce. Here we describe real-time metabolome profiling by direct injection of living bacteria, yeast or mammalian cells into a high-resolution mass spectrometer, which enables automated monitoring of about 300 compounds in 15-30-s cycles over several hours. We observed accumulation of energetically costly biomass metabolites in Escherichia coli in carbon starvation-induced stationary phase, as well as the rapid use of these metabolites upon growth resumption. By combining real-time metabolome profiling with modeling and inhibitor experiments, we obtained evidence for switch-like feedback inhibition in amino acid biosynthesis and for control of substrate availability through the preferential use of the metabolically cheaper one-step salvaging pathway over costly ten-step de novo purine biosynthesis during growth resumption.