Single-cell and population lag times as a function of cell age

Universal Transitions between Growth and Dormancy via Intermediate Complex Formation

A simple cell model consisting of a catalytic reaction network with intermediate complex formation is numerically studied. As nutrients are depleted, the transition from the exponential growth phase to the growth-arrested dormant phase occurs along with hysteresis and a lag time for growth recovery. This transition is caused by the accumulation of intermediate complexes, leading to the jamming of reactions and the diversification of components. These properties are generic in random reaction networks, as supported by dynamical systems analyses of corresponding mean-field models.

The proteome of bacterial membrane vesicles in Escherichia coli-a time course comparison study in two different media

Introduction

Bacteria inhabit the in- and outside of the human body, such as skin, gut or the oral cavity where they play an innoxious, beneficial or even pathogenic role. It is well known that bacteria can secrete membrane vesicles (MVs) like eukaryotic cells with extracellular vesicles (EVs). Several studies indicate that bacterial membrane vesicles (bMVs) play a crucial role in microbiome-host interactions. However, the composition of such bMVs and their functionality under different culture conditions are still largely unknown.

Methods

To gain a better insight into bMVs, we investigated the composition and functionality of E. coli (DSM 105380) bMVs from the culture media Lysogeny broth (LB) and RPMI 1640 throughout the different phases of growth (lag-, log- and stationary-phase). bMVs from three time points (8 h, 54 h, and 168 h) and two media (LB and RPMI 1640) were isolated by ultracentrifugation and analyzed using nanoparticle tracking analysis (NTA), cryogenic electron microscopy (Cryo-EM), conventional transmission electron microscopy (TEM) and mass spectrometry-based proteomics (LC-MS/MS). Furthermore, we examined pro-inflammatory cytokines IL-1β and IL-8 in the human monocyte cell line THP-1 upon bMV treatment.

Results

Particle numbers increased with inoculation periods. The bMV morphologies in Cryo-EM/TEM were similar at each time point and condition. Using proteomics, we identified 140 proteins, such as the common bMV markers OmpA and GroEL, present in bMVs isolated from both media and at all time points. Additionally, we were able to detect growth-condition-specific proteins. Treatment of THP-1 cells with bMVs of all six groups lead to significantly high IL-1β and IL-8 expressions.

Conclusion

Our study showed that the choice of medium and the duration of culturing significantly influence both E. coli bMV numbers and protein composition. Our TEM/Cryo-EM results demonstrated the presence of intact E. coli bMVs. Common E. coli proteins, including OmpA, GroEL, and ribosome proteins, can consistently be identified across all six tested growth conditions. Furthermore, our functional assays imply that bMVs isolated from the six groups retain their function and result in comparable cytokine induction.

Distinct Survival, Growth Lag, and rRNA Degradation Kinetics during Long-Term Starvation for Carbon or Phosphate

The stationary phase is the general term for the state a bacterial culture reaches when no further increase in cell mass occurs due to exhaustion of nutrients in the growth medium. Depending on the type of nutrient that is first depleted, the metabolic state of the stationary phase cells may vary greatly, and the subsistence strategies that best support cell survival may differ. As ribosomes play a central role in bacterial growth and energy expenditure, ribosome preservation is a key element of such strategies. To investigate the degree of ribosome preservation during long-term starvation, we compared the dynamics of rRNA levels of carbon-starved and phosphorus-starved Escherichia coli cultures for up to 28 days. The starved cultures' contents of full-length 16S and 23S rRNA decreased as the starvation proceeded in both cases, and phosphorus starvation resulted in much more rapid rRNA degradation than carbon starvation. Bacterial survival and regrowth kinetics were also quantified. Upon replenishment of the nutrient in question, carbon-starved cells resumed growth faster than cells starved for phosphate for the equivalent amount of time, and for both conditions, the lag time increased with the starvation time. While these results are in accordance with the hypothesis that cells with a larger ribosome pool recover more readily upon replenishment of nutrients, we also observed that the lag time kept increasing with increasing starvation time, also when the amount of rRNA per viable cell remained constant, highlighting that lag time is not a simple function of ribosome content under long-term starvation conditions. IMPORTANCE The exponential growth of bacterial populations is punctuated by long or short periods of starvation lasting from the point of nutrient exhaustion until nutrients are replenished. To understand the consequences of long-term starvation for Escherichia coli cells, we performed month-long carbon and phosphorus starvation experiments and measured three key phenotypes of the cultures, namely, the survival of the cells, the time needed for them to resume growth after nutrient replenishment, and the levels of intact rRNA preserved in the cultures. The starved cultures' concentration of rRNA dropped with starvation time, as did cell survival, while the lag time needed for regrowth increased. While all three phenotypes were more severely affected during starvation for phosphorus than for carbon, our results demonstrate that neither survival nor lag time is correlated with ribosome content in a straightforward manner.

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.

Microbial population dynamics and evolutionary outcomes under extreme energy limitation

Microorganisms commonly inhabit energy-limited ecosystems where cellular maintenance and reproduction is highly constrained. To gain insight into how individuals persist under such conditions, we derived demographic parameters from a collection of 21 heterotrophic bacterial taxa by censusing 100 populations in an effectively closed system for 1,000 d. All but one taxon survived prolonged resource scarcity, yielding estimated times to extinction ranging over four orders of magnitude from 100 to 105 y. Our findings corroborate reports of long-lived bacteria recovered from ancient environmental samples, while providing insight into mechanisms of persistence. As death rates declined over time, lifespan was extended through the scavenging of dead cells. Although reproduction was suppressed in the absence of exogenous resources, populations continued to evolve. Hundreds of mutations were acquired, contributing to genome-wide signatures of purifying selection as well as molecular signals of adaptation. Consistent ecological and evolutionary dynamics indicate that distantly related bacteria respond to energy limitation in a similar and predictable manner, which likely contributes to the stability and robustness of microbial life.

Application of growth rate from kinetic model to calculate stochastic growth of a bacteria population at low contamination level

Traditional predictive microbiology is not suited for cell growth predictions for low-level contamination, where individual cell heterogeneity becomes apparent. Accordingly, we simulated a stochastic birth process of bacteria population using kinetic parameters. We predicted the variation in behavior of Salmonella enterica serovar Typhimurium cells at low inoculum density. The modeled cells were grown in tryptic soy broth at 25 °C. Kinetic growth parameters were first determined empirically for an initial cell number of 10⁴ cells. Monte Carlo simulation based on the growth kinetics and Poisson distribution for different initial cell numbers predicted the results of 50 replicate growth experiments with the initial cell number of 1, 10, and 64 cells. Indeed, measured behavior of 85% cells fell within the 95% prediction area of the simulation. The calculations link the kinetic and stochastic birth process with Poisson distribution. The developed model can be used to calculate the probability distribution of population size for exposure assessment and for the evaluation of a probability that a pathogen would exceed critical contamination level during food storage.

The Conjugation Window in an Escherichia coli K-12 Strain with an IncFII Plasmid

Many studies have examined the role that conjugation plays in disseminating antibiotic resistance genes in bacteria. However, relatively little research has quantitively examined and modeled the dynamics of conjugation under growing and nongrowing conditions beyond a couple of hours. We therefore examined growing and nongrowing cultures of Escherichia coli over a 24-h period to understand the dynamics of bacterial conjugation in the presence and absence of antibiotics with pUUH239.2, an IncFII plasmid containing multiantibiotic- and metal-resistant genes. Our data indicate that conjugation occurs after E. coli cells divide and before they have transitioned to a nongrowing phase. The result is that there is only a small window of opportunity for E. coli to conjugate with pUUH239.2 under both growing and nongrowing conditions. Only a very small percentage of the donor cells likely are capable of even undergoing conjugation, and not all transconjugants can become donor cells due to molecular regulatory controls and not being in the correct growth phase. Once a growing culture enters stationary phase, the number of capable donor cells decreases rapidly and conjugation slows to produce a plateau. Published models did not provide accurate descriptions of conjugation under nongrowing conditions. We present here a modified modeling approach that accurately describes observed conjugation behavior under growing and nongrowing conditions.IMPORTANCE There has been growing interest in horizontal gene transfer of antibiotic resistance plasmids as the antibiotic resistance crisis has worsened over the years. Most studies examining conjugation of bacterial plasmids focus on growing cultures of bacteria for short periods, but in the environment, most bacteria grow episodically and at much lower rates than in the laboratory. We examined conjugation of an IncFII antibiotic resistance plasmid in E. coli under growing and nongrowing conditions to understand the dynamics of conjugation under which the plasmid is transferred. We found that conjugation occurs in a narrow time frame when E. coli is transitioning from a growing to nongrowing phase and that the conjugation plateau develops because of a lack of capable donor cells in growing cultures. From an environmental aspect, our results suggest that episodic growth in nutrient-depleted environments could result in more conjugation than sustained growth in a nutrient rich environment.

Modeling the Effects of the Preculture Temperature on the Lag Phase of Listeria monocytogenes at 25°C

In predictive microbiology, the study of the microbial lag phase, i.e., the time needed for bacteria to adapt to a new environment before multiplying, has received a great deal of attention in the research literature. The microbial lag phase is more difficult to estimate than the specific growth rate because the lag phase is impacted by the previous and actual growth environments. In this study, the growth of Listeria monocytogenes preincubated at 0, 5, 10, and 15°C and subsequently grown at 25°C was investigated at the single-cell and population levels. The population lag phase of L. monocytogenes was obtained by fitting the Baranyi model, and the single-cell lag time was estimated by the time to detection method. The lag phase at the single-cell and population levels of L. monocytogenes presented a downward trend as the preculture temperature ranged from 0 to 15°C. The population lag phase of L. monocytogenes was lower than the single-cell lag time at the same preculture temperature. In addition, except for the zero-lag distribution at a preculture temperature of 15°C, all the single-cell lag time distributions of L. monocytogenes followed a Weibull distribution under all preculture temperatures. The preculture temperature had a significant impact on the rapid variation in the single-cell lag time distribution. Thus, the influence of preculture temperature on the lag phase needs to be quantitatively analyzed for better assessment of microbiological risk.

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.

Quantitative high-throughput population dynamics in continuous-culture by automated microscopy

We present a high-throughput method to measure abundance dynamics in microbial communities sustained in continuous-culture. Our method uses custom epi-fluorescence microscopes to automatically image single cells drawn from a continuously-cultured population while precisely controlling culture conditions. For clonal populations of Escherichia coli our instrument reveals history-dependent resilience and growth rate dependent aggregation.

Growth resumption from stationary phase reveals memory in Escherichia coli cultures

Frequent changes in nutrient availability often result in repeated cycles of bacterial growth and dormancy. The timing of growth resumption can differ among isogenic cells and delayed growth resumption can lead to antibiotic tolerant persisters. Here we describe a correlation between the timing of entry into stationary phase and resuming growth in the next period of cell proliferation. E. coli cells can follow a last in first out rule: the last ones to shut down their metabolism in the beginning of stationary phase are the first to recover in response to nutrients. This memory effect can last for several days in stationary phase and is not influenced by environmental changes. We observe that the speed and heterogeneity of growth resumption depends on the carbon source. A good carbon source (glucose) can promote rapid growth resumption even at low concentrations, and is seen to act more like a signal than a growth substrate. Heterogeneous growth resumption can protect the population from adverse effect of stress, investigated here using heat-shock, because the stress-resilient dormant cells are always present.

Survival guide: Escherichia coli in the stationary phase

This review centers on the stationary phase of bacterial culture. The basic processes specific to the stationary phase, as well as the regulatory mechanisms that allow the bacteria to survive in conditions of stress, are described.

ScanLag: high-throughput quantification of colony growth and lag time

Growth dynamics are fundamental characteristics of microorganisms. Quantifying growth precisely is an important goal in microbiology. Growth dynamics are affected both by the doubling time of the microorganism and by any delay in growth upon transfer from one condition to another, the lag. The ScanLag method enables the characterization of these two independent properties at the level of colonies originating each from a single cell, generating a two-dimensional distribution of the lag time and of the growth time. In ScanLag, measurement of the time it takes for colonies on conventional nutrient agar plates to be detected is automated on an array of commercial scanners controlled by an in house application. Petri dishes are placed on the scanners, and the application acquires images periodically. Automated analysis of colony growth is then done by an application that returns the appearance time and growth rate of each colony. Other parameters, such as the shape, texture and color of the colony, can be extracted for multidimensional mapping of sub-populations of cells. Finally, the method enables the retrieval of rare variants with specific growth phenotypes for further characterization. The technique could be applied in bacteriology for the identification of long lag that can cause persistence to antibiotics, as well as a general low cost technique for phenotypic screens.

Global gene expression analysis of long-term stationary phase effects in E. coli K12 MG1655

Global gene expression was monitored in long-term stationary phase (LSP) cells of E. coli K12 MG1655 and compared with stationary phase (SP) cells that were sub-cultured without prolonged delay to get an insight into the survival strategies of LSP cells. The experiments were carried out using both LB medium and LB supplemented with 10% of glycerol. In both the media the LSP cells showed decreased growth rate compared to SP cells. DNA microarray analysis of LSP cells in both the media resulted in the up- and down-regulation of several genes in LSP cells compared to their respective SP cells in the corresponding media. In LSP cells grown in LB 204 genes whereas cells grown in LB plus glycerol 321 genes were differentially regulated compared to the SP cells. Comparison of these differentially regulated genes indicated that irrespective of the medium used for growth in LSP cells expression of 95 genes (22 genes up-regulated and 73 down-regulated) were differentially regulated. These 95 genes could be associated with LSP status of the cells and are likely to influence survival and growth characteristics of LSP cells. This is indeed so since the up- and down-regulated genes include genes that protect E. coli LSP cells from stationary phase stress and genes that would help to recover from stress when transferred into fresh medium. The growth phenotype in LSP cells could be attributed to up-regulation of genes coding for insertion sequences that confer beneficial effects during starvation, genes coding for putative transposases and simultaneous down-regulation of genes coding for ribosomal protein synthesis, transport-related genes, non-coding RNA genes and metabolic genes. As yet we still do not know the role of several unknown genes and genes coding for hypothetical proteins which are either up- or down-regulated in LSP cells compared to SP cells.

Promoter activity dynamics in the lag phase of Escherichia coli

Background

Lag phase is a period of time with no growth that occurs when stationary phase bacteria are transferred to a fresh medium. Bacteria in lag phase seem inert: their biomass does not increase. The low number of cells and low metabolic activity make it difficult to study this phase. As a consequence, it has not been studied as thoroughly as other bacterial growth phases. However, lag phase has important implications for bacterial infections and food safety. We asked which, if any, genes are expressed in the lag phase of Escherichia coli, and what is their dynamic expression pattern.

Results

We developed an assay based on imaging flow cytometry of fluorescent reporter cells that overcomes the challenges inherent in studying lag phase. We distinguish between lag1 phase- in which there is no biomass growth, and lag2 phase- in which there is biomass growth but no cell division. We find that in lag1 phase, most promoters are not active, except for the enzymes that utilize the specific carbon source in the medium. These genes show promoter activities that increase exponentially with time, despite the fact that the cells do not measurably increase in size. An oxidative stress promoter, katG, is also active. When cells enter lag2 and begin to grow in size, they switch to a full growth program of promoter activity including ribosomal and metabolic genes.

Conclusions

The observed exponential increase in enzymes for the specific carbon source followed by an abrupt switch to production of general growth genes is a solution of an optimal control model, known as bang-bang control. The present approach contributes to the understanding of lag phase, the least studied of bacterial growth phases.

Stochasticity in colonial growth dynamics of individual bacterial cells

Conventional bacterial growth studies rely on large bacterial populations without considering the individual cells. Individual cells, however, can exhibit marked behavioral heterogeneity. Here, we present experimental observations on the colonial growth of 220 individual cells of Salmonella enterica serotype Typhimurium using time-lapse microscopy videos. We found a highly heterogeneous behavior. Some cells did not grow, showing filamentation or lysis before division. Cells that were able to grow and form microcolonies showed highly diverse growth dynamics. The quality of the videos allowed for counting the cells over time and estimating the kinetic parameters lag time (λ) and maximum specific growth rate (μmax) for each microcolony originating from a single cell. To interpret the observations, the variability of the kinetic parameters was characterized using appropriate probability distributions and introduced to a stochastic model that allows for taking into account heterogeneity using Monte Carlo simulation. The model provides stochastic growth curves demonstrating that growth of single cells or small microbial populations is a pool of events each one of which has its own probability to occur. Simulations of the model illustrated how the apparent variability in population growth gradually decreases with increasing initial population size (N(0)). For bacterial populations with N(0) of >100 cells, the variability is almost eliminated and the system seems to behave deterministically, even though the underlying law is stochastic. We also used the model to demonstrate the effect of the presence and extent of a nongrowing population fraction on the stochastic growth of bacterial populations.

Assessing chronological aging in bacteria

Bacteria, which are often considered as avid reproductive organisms under constant selective pressure to utilize available nutrients to proliferate, might seem an inappropriate model to study aging. However, environmental conditions are rarely supporting the exponential growth that is most often studied in laboratories. In the wild, Escherichia coli inhabits environments of relative nutritional paucity. Not surprisingly, under such circumstances, members of an E. coli population age and progressively lose the ability to reproduce, even when environmental conditions provide such an opportunity. Here, we review the methods to study chronological aging in bacteria and some of the mechanisms that may contribute to their age-dependent loss of viability.

Age of inoculum strongly influences persister frequency and can mask effects of mutations implicated in altered persistence

The majority of cells transferred from stationary-phase culture into fresh medium resume growth quickly, while a few remain in a nongrowing state for longer. These temporarily nonproliferating bacteria are tolerant of several bactericidal antibiotics and constitute a main source of persisters. Several genes have been shown to influence the frequency of persisters in Escherichia coli, although the exact mechanism underlying persister formation is unknown. This study demonstrates that the frequency of persisters is highly dependent on the age of the inoculum and the medium in which it has been grown. The hipA7 mutant had 1,000 times more persisters than the wild type when inocula were sampled from younger stationary-phase cultures. When started after a long stationary phase, the two displayed equal and elevated persister frequencies. The lower persister frequencies of glpD, dnaJ, and surA knockout strains were increased to the level of the wild type when inocula aged. The mqsR and phoU deletions showed decreased persister levels only when the inocula were from aged cultures, while sucB and ygfA deletions had decreased persister levels irrespective of the age of the inocula. A dependency on culture conditions underlines the notion that during screening for mutants with altered persister frequencies, the exact experimental details are of great importance. Unlike ampicillin and norfloxacin, which always leave a fraction of bacteria alive, amikacin killed all cells in the growth resumption experiment. It was concluded that the frequency of persisters depends on the conditions of inoculum cultivation, particularly its age, and the choice of antibiotic.

The role of physiological heterogeneity in microbial population behavior

As the ability to analyze individual cells in microbial populations expands, it is becoming apparent that isogenic microbial populations contain substantial cell-to-cell differences in physiological parameters such as growth rate, resistance to stress and regulatory circuit output. Subpopulations exist that are manyfold different in these parameters from the population average, and these differences arise by stochastic processes. Such differences can dramatically affect the response of cells to perturbations, especially stress, which in turn dictates overall population response. Defining the role of cell-to-cell heterogeneity in population behavior is important for understanding population-based research problems, including those involving infecting populations, normal flora and bacterial populations in water and soils. Emerging technological breakthroughs are poised to transform single-cell analysis and are critical for the next phase of insights into physiological heterogeneity in the near future. These include technologies for multiparameter analysis of live cells, with downstream processing and analysis.

Automated imaging with ScanLag reveals previously undetectable bacterial growth phenotypes

We developed an automated system, ScanLag, that measures in parallel the delay in growth (lag time) and growth rate of thousands of cells. Using ScanLag, we detected small subpopulations of bacteria with dramatically increased lag time upon starvation. By screening a library of Escherichia coli deletion mutants, we achieved two-dimensional mapping of growth characteristics, which showed that ScanLag enables multidimensional screens for quantitative characterization and identification of rare phenotypic variants.

Exploring the lag phase and growth initiation of a yeast culture by means of an individual-based model

The performance of fermentation processes is greatly influenced by the size and quality of inocula. The characterization of the replicative age is decided by the number of birth scars each yeast exhibits on its cellular membrane. Yeast ageing and inoculum size are factors that affect industrial fermentation, particularly those processes in which the yeast cells are reused such as the production of beer. This process reuses yeast cropped at the end of one fermentation in the following one, in a process called "serial repitching". The aim of this study was to explore the effects of inoculum size and ageing on the first stages of the dynamics of yeast population growth. However, only Individual-based Models (IbMs) allow the study of small, well-characterized, microbial inocula. We used INDISIM-YEAST, based on the generic IbM simulator INDISIM, to carry out these studies. Several simulations were performed to analyze the effect of the inoculum size and genealogical age of the cells that made it up on the lag phase, first division time and specific growth rate. The shortest lag phase and time to the first division were obtained with largest inocula and with the youngest inoculated parent cells.

Modeling the lag period and exponential growth of Listeria monocytogenes under conditions of fluctuating temperature and water activity values

The dynamic model for the growth of a bacterial population described by Baranyi and Roberts (J. Baranyi and T. A. Roberts, Int. J. Food Microbiol. 23:277-294, 1994) was applied to model the lag period and exponential growth of Listeria monocytogenes under conditions of fluctuating temperature and water activity (a(w)) values. To model the duration of the lag phase, the dependence of the parameter h(0), which quantifies the amount of work done during the lag period, on the previous and current environmental conditions was determined experimentally. This parameter depended not only on the magnitude of the change between the previous and current environmental conditions but also on the current growth conditions. In an exponentially growing population, any change in the environment requiring a certain amount of work to adapt to the new conditions initiated a lag period that lasted until that work was finished. Observations for several scenarios in which exponential growth was halted by a sudden change in the temperature and/or a(w) were in good agreement with predictions. When a population already in a lag period was subjected to environmental fluctuations, the system was reset with a new lag phase. The work to be done during the new lag phase was estimated to be the workload due to the environmental change plus the unfinished workload from the uncompleted previous lag phase.

Stationary phase in gram-negative bacteria

Conditions that sustain constant bacterial growth are seldom found in nature. Oligotrophic environments and competition among microorganisms force bacteria to be able to adapt quickly to rough and changing situations. A particular lifestyle composed of continuous cycles of growth and starvation is commonly referred to as feast and famine. Bacteria have developed many different mechanisms to survive in nutrient-depleted and harsh environments, varying from producing a more resistant vegetative cell to complex developmental programmes. As a consequence of prolonged starvation, certain bacterial species enter a dynamic nonproliferative state in which continuous cycles of growth and death occur until 'better times' come (restoration of favourable growth conditions). In the laboratory, microbiologists approach famine situations using batch culture conditions. The entrance to the stationary phase is a very regulated process governed by the alternative sigma factor RpoS. Induction of RpoS changes the gene expression pattern, aiming to produce a more resistant cell. The study of stationary phase revealed very interesting phenomena such as the growth advantage in stationary phase phenotype. This review focuses on some of the interesting responses of gram-negative bacteria when they enter the fascinating world of stationary phase.

Network analysis of the transcriptional pattern of young and old cells of Escherichia coli during lag phase

Background

The aging process of bacteria in stationary phase is halted if cells are subcultured and enter lag phase and it is then followed by cellular division. Network science has been applied to analyse the transcriptional response, during lag phase, of bacterial cells starved previously in stationary phase for 1 day (young cells) and 16 days (old cells).

Results

A genome scale network was constructed for E. coli K-12 by connecting genes with operons, transcription and sigma factors, metabolic pathways and cell functional categories. Most of the transcriptional changes were detected immediately upon entering lag phase and were maintained throughout this period. The lag period was longer for older cells and the analysis of the transcriptome revealed different intracellular activity in young and old cells. The number of genes differentially expressed was smaller in old cells (186) than in young cells (467). Relatively, few genes (62) were up- or down-regulated in both cultures. Transcription of genes related to osmotolerance, acid resistance, oxidative stress and adaptation to other stresses was down-regulated in both young and old cells. Regarding carbohydrate metabolism, genes related to the citrate cycle were up-regulated in young cells while old cells up-regulated the Entner Doudoroff and gluconate pathways and down-regulated the pentose phosphate pathway. In both old and young cells, anaerobic respiration and fermentation pathways were down-regulated, but only young cells up-regulated aerobic respiration while there was no evidence of aerobic respiration in old cells.

Numerous genes related to DNA maintenance and replication, translation, ribosomal biosynthesis and RNA processing as well as biosynthesis of the cell envelope and flagellum and several components of the chemotaxis signal transduction complex were up-regulated only in young cells. The genes for several transport proteins for iron compounds were up-regulated in both young and old cells. Numerous genes encoding transporters for carbohydrates and organic alcohols and acids were down-regulated in old cells only.

Conclusion

Network analysis revealed very different transcriptional activities during the lag period in old and young cells. Rejuvenation seems to take place during exponential growth by replicative dilution of old cellular components.

Analysis of the variability in the number of viable bacteria after mild heat treatment of food

Variability in the numbers of bacteria remaining in saline solution and whole milk following mild heat treatment has been studied with Listeria innocua, Enterococcus faecalis, Salmonella enterica serovar Enteritidis, and Pseudomonas fluorescens. As expected, the most heat-resistant bacterium was E. faecalis, while P. fluorescens was the least heat resistant, and all bacteria showed greater thermal resistance in whole milk than in saline solution. Despite the differences in the inactivation kinetics of these bacteria in different media, the variability in the final number of bacteria was affected neither by the species nor by the heating substrate, but it did depend on the intensity of the heat treatment. The more severe the heat treatment was, the lower the average number of surviving bacteria but the greater the variability. Our results indicated that the inactivation times for the cells within a population are not identically distributed random variables and that, therefore, the population includes subpopulations of cells with different distributions for the heat resistance parameters. A linear relationship between the variability of the log of the final bacterial concentration and the logarithmic reduction in the size of the bacterial population was found.

Equalizing growth in high-throughput small scale cultivations via precultures operated in fed-batch mode

An often underestimated problem when working with different clones in microtiter plates and shake flask screenings is the non-parallel and non-equal growth of batch cultures. These growth differences are caused by variances of individual clones regarding initial biomass concentration, lag-phase or specific growth rate. Problems arising from unequal growth kinetics are different induction points in expression studies or uneven cultivation periods at the time of harvest. Screening for the best producing clones of a library under comparable conditions is thus often impractical or even impossible. A new approach to circumvent the problem of unequal growth kinetics of main cultures is the application of fed-batch mode in precultures in microtiter plates and shake flasks. Fed-batch operation in precultures is realized through a slow-release system for glucose. After differently growing cultures turn to glucose-limited growth, they all consume the same amount of glucose due to the fixed feed profile of glucose provided by the slow-release system. This leads to equalized growth. Inherent advantages of this method are that it is easy to use and requires no additional equipment like pumps. This new technique for growth equalization in high-throughput cultivations is simulated and verified experimentally. The growth of distinctly inoculated precultures in microtiter plates and shake flasks could be equalized for different microorganisms such as Escherichia coli and Hansenula polymorpha.

Effect of capric, lauric and alpha-linolenic acids on the division time distributions of single cells of Staphylococcus aureus

The effect of non-inhibitory concentrations of capric, lauric and alpha-linolenic acids (C10:0, C12:0 and C18:3 respectively) on the division time distribution of single cells of Staphylococcus aureus was evaluated at pH 7 and pH 5. The effect of the initial cell concentration on the lag time of growing cell populations was also assessed. The statistical properties of the division times (defined as the time interval from birth to next binary fission for a single cell) were studied using the method of Elfwing et al. [Elfwing, A., Le Marc, Y., Baranyi, J., Ballagi, A., 2004. Observing the growth and division of large number of individual bacteria using image analysis. Applied and Environmental Microbiology 70, 675-678]. The division times were significantly longer in the presence of free fatty acids than in the control. Shorter division intervals were detected at pH 7 than at pH 5 in the control experiment and in the presence of C10:0. However, both C12:0 and C18:3 slowed down the growth, regardless of the pH. The observed division time distributions were used to simulate growth curves from different inoculum sizes using the stochastic birth process described by Pin and Baranyi [Pin, C., Baranyi, J., 2006. Kinetics of single cells: observation and modelling of a stochastic process. Applied and Environmental Microbiology 72, 2163-2169]. The output of the simulation results were compared with observed data. The lag times fitted to simulated growth curves were in good agreement with those fitted to growth curves measured by plate counts. The averaged out effect of the population masked the effect of the free fatty acids and pH on the division times of single cells.