Bet-hedging during bacterial diauxic shift

DmdA-independent lag phase shortening in Phaeobacter inhibens bacteria under stress conditions

Bacteria can shorten their lag phase by using methyl groups from compounds like dimethylsulfoniopropionate (DMSP), which are incorporated into cellular components via the methionine cycle. However, the role of specific methionine synthases in this process is not fully understood. Using transcriptomics, genetics, and biochemical assays, we investigated methionine synthases involved in lag phase shortening in Phaeobacter inhibens. We focused on a cobalamin-dependent methionine synthase (MetH)-like complex encoded by three genes: a betaine-homocysteine S-methyltransferase (bmt), a cobalamin-binding protein (cbp), and an intermediate methyl carrier (PGA1_c16040). Expression profiling revealed transcriptional decoupling among these genes. Deleting bmt disrupted lag phase shortening in response to DMSP. Functional assays showed that Bmt can directly produce methionine from DMSP and betaine, independent of tetrahydrofolate (THF) or cobalamin. Interestingly, under stress conditions, lag phase shortening occurred even in the absence of dimethylsulfoniopropionate demethylase DmdA, the primary DMSP demethylase. Under osmotic and oxidative stress, bmt expression increased significantly in response to both DMSP and betaine, suggesting an alternative methylation route. This highlights the role of Bmt as both demethylase and a methionine synthase under stress, offering a cost-effective strategy for methyl group assimilation. Our findings reveal a novel stress-responsive pathway for methionine synthesis and demonstrate the role of Bmt in promoting bacterial adaptation by accelerating the lag phase.

Combination therapy delays antimicrobial resistance after adaptive laboratory evolution of Staphylococcus aureus

Antibiotic resistance, driven by misuse and overuse of antibiotics, is one of the greatest threats against human health. The antimicrobial pressure during prolonged antibiotic treatment of chronic bacterial infections selects for resistance. While antibiotic combinations may reduce resistance emergence, antibiotic-tolerant persister cells can serve as a reservoir for resistance development. Therefore, targeting these cells with anti-persister drugs might provide a novel strategy for resistance prevention. In this study, we conducted 42 days of adaptive laboratory evolution using Staphylococcus aureus exposed to rifampicin, ciprofloxacin, daptomycin, and vancomycin, alone or in combination with the anti-persister drug mitomycin C. We monitored antibiotic susceptibility daily and assessed phenotypic changes in growth and biofilm formation in evolved strains. Whole-genome sequencing revealed mutations linked to antibiotic resistance and phenotypic shifts. Rifampicin resistance developed within a few days, while ciprofloxacin and daptomycin emerged in approximately 3 weeks. Treatments with vancomycin or mitomycin C resulted in minimal changes in susceptibility. While combination therapy delayed resistance, it did not fully prevent it. Notably, the combination of rifampicin with mitomycin C maintained rifampicin susceptibility throughout the long-term evolution experiment. Sub-inhibitory antibiotic treatments selected for both previously characterized and novel mutations, including unprecedented alterations in the nucleotide excision repair system and azoreductase following mitomycin C exposure. The delayed resistance development observed with combination therapy, particularly mitomycin C's ability to suppress rifampicin resistance, suggests potential therapeutic applications. Future studies should evaluate the clinical efficacy of anti-persister drugs in preventing resistance across different bacterial pathogens and infection models.

Growth Rate Prediction, Performance, and Biochemical Enhancement of Black Soldier Fly (Hermetia illucens) Fed with Marine By-Products and Co-Products: A Potential Value-Added Resource for Marine Aquafeeds

Aquafeed production is a fast-growing industry, seeking novel, cost-efficient raw materials to diversify traditional ingredients like fish meal and oil. Insects, particularly BSF larvae, convert by-products and waste into value-added biomass. In this study, by-products and co-products from two major fish-transforming industries in the Iberian Peninsula, i.e., tuna heads (THs) and codfish frames (CFs), hydrolysates of THs and CFs, and TH oils, were supplied to BSF larvae to improve their profile in n-3 fatty acids (FAs), namely EPA and DHA, and their protein/amino acid content. By testing the replacement levels of a control diet with by-products and co-products, we evaluated the amount of n-3 FA that could be added to BSF larval tissues. The results showed that high levels of a hydrolysed diet negatively impacted larval survival. In addition, parameters such as the moisture, protein content, and viscosity of the substrate affected bioconversion rates. Nevertheless, BSF fed with these diets contained high levels of lysine (5.8-8.4%, dry weight (DW)), methionine (1.5-2.4%, DW), and n-3 FA (14.4% DW: EPA 6.7% and DHA 7.1%). These findings suggest that BSF can effectively convert fish by-products into a nutrient-rich biomass for aquafeeds, supporting the diversification of raw material sources and promoting a circular bioeconomy.

Single-cell data reveal heterogeneity of investment in ribosomes across a bacterial population

Ribosomes are responsible for the synthesis of proteins, the major component of cellular biomass. Classical experiments have established a linear relationship between the fraction of resources invested in ribosomal proteins and the rate of balanced growth of a microbial population. Very little is known, however, about how the investment in ribosomes varies over individual cells in a population. We therefore extended the study of ribosomal resource allocation from populations to single cells, using a combination of time-lapse fluorescence microscopy and statistical inference. We found a large variability of ribosome concentrations and growth rates in conditions of balanced growth of the model bacterium Escherichia coli in a given medium, which cannot be accounted for by the population-level growth law. A large variability in the allocation of resources to ribosomes was also found during the transition of the bacteria from a poor to a rich growth medium. While some cells immediately adapt their ribosome synthesis rate to the new environment, others do so only gradually. Our results thus reveal a range of strategies for investing resources in the molecular machines at the heart of cellular self-replication. This raises the fundamental question whether the observed variability is an intrinsic consequence of the stochastic nature of the underlying biochemical processes or whether it improves the fitness of Escherichia coli in its natural environment.

Experimental evolution under different nutritional conditions changes the genomic architecture and virulence of Acinetobacter baumannii

This study uncovers the molecular processes governing the adaptive evolution of multidrug-resistant (MDR) pathogens without antibiotic pressure. Genomic analysis of MDR Acinetobacter baumannii cells cultured for 8000 generations under starvation conditions (EAB1) or nutrient-rich conditions (EAB2) revealed significant genomic changes, primarily by insertion sequence (IS)-mediated insertions and deletions. Only two Acinetobacter-specific prophage-related deletions and translocations were observed in the EAB1 strain. Both evolved strains exhibited higher virulence in mouse infection studies, each with different modes of action. The EAB1 strain displayed a heightened ability to cross the epithelial barrier of human lung tissue, evade the immune system, and spread to lung tissues, ultimately resulting in cellular mortality. In contrast, the EAB2 strain strongly attached to epithelial cells, leading to increased synthesis of proinflammatory cytokines and chemokines. The genomic alterations and increased virulence observed in evolved strains during short-term evolution underscore the need for caution when handling these pathogens, as these risks persist even without antibiotic exposure.

Calorie Restriction Decreases Competitive Fitness in Saccharomyces cerevisiae Following Heat Stress

Experiments exposing Saccharomyces cerevisiae to glucose limitation (calorie restriction) are widely used to determine impacts on cell health as a model for aging. Using growth on plates and in liquid culture, we demonstrated that calorie restriction reduces fitness in subsequent nutrient-limited environments. Yeast grown in a calorie-restricted environment took longer to emerge from the lag phase, had an extended doubling time and had a lower percentage of culturability. Cells grown under moderate calorie restriction were able to withstand a gradual heat stress in a similar manner to cells grown without calorie restriction but fared less well with a sudden heat shock. Yeast grown under extreme calorie restriction were less fit when exposed to gradual heating or heat shock. Using RNAseq analysis, we provide novel insight into the mechanisms underlying this response, showing that in the absence of calorie restriction, genes whose products are involved in energy metabolism (glycolysis/gluconeogenesis and the citrate cycle) are predominantly overexpressed when yeasts were exposed to gradual heating, whereas this was not the case when they were exposed to shock. We show that both the culture history and the current environment must be considered when assaying physiological responses, and this has wider implications when developing strategies for the propagation, preservation or destruction of microbial cells.

Fragmented micro-growth habitats present opportunities for alternative competitive outcomes

Bacteria in nature often thrive in fragmented environments, like soil pores, plant roots or plant leaves, leading to smaller isolated habitats, shared with fewer species. This spatial fragmentation can significantly influence bacterial interactions, affecting overall community diversity. To investigate this, we contrast paired bacterial growth in tiny picoliter droplets (1-3 cells per 35 pL up to 3-8 cells per species in 268 pL) with larger, uniform liquid cultures (about 2 million cells per 140 µl). We test four interaction scenarios using different bacterial strains: substrate competition, substrate independence, growth inhibition, and cell killing. In fragmented environments, interaction outcomes are more variable and sometimes even reverse compared to larger uniform cultures. Both experiments and simulations show that these differences stem mostly from variation in initial cell population growth phenotypes and their sizes. These effects are most significant with the smallest starting cell populations and lessen as population size increases. Simulations suggest that slower-growing species might survive competition by increasing growth variability. Our findings reveal how microhabitat fragmentation promotes diverse bacterial interaction outcomes, contributing to greater species diversity under competitive conditions.

Quantum modeling simulates nutrient effect of bioplastic polyhydroxyalkanoate (PHA) production in Pseudomonas putida

Polyhydroxyalkanoates (PHAs) could be used to make sustainable, biodegradable plastics. However, the precise and accurate mechanistic modeling of PHA biosynthesis, especially medium-chain-length PHA (mcl-PHA), for yield improvement remains a challenge to biology. PHA biosynthesis is typically triggered by nitrogen limitation and tends to peak at an optimal carbon-to-nitrogen (C/N) ratio. Specifically, simulation of the underlying dynamic regulation mechanisms for PHA bioprocess is a bottleneck owing to surfeit model complexity and current modeling philosophies for uncertainty. To address this issue, we proposed a quantum-like decision-making model to encode gene expression and regulation events as hidden layers by the general transformation of a density matrix, which uses the interference of probability amplitudes to provide an empirical-level description for PHA biosynthesis. We implemented our framework modeling the biosynthesis of mcl-PHA in Pseudomonas putida with respect to external C/N ratios, showing its optimization production at maximum PHA production of 13.81% cell dry mass (CDM) at the C/N ratio of 40:1. The results also suggest the degree of P. putida's preference in channeling carbon towards PHA production as part of the bacterium's adaptative behavior to nutrient stress using quantum formalism. Generic parameters (kD, kN and theta θ) obtained based on such quantum formulation, representing P. putida's PHA biosynthesis with respect to external C/N ratios, was discussed. This work offers a new perspective on the use of quantum theory for PHA production, demonstrating its application potential for other bioprocesses.

Phenotypic heterogeneity follows a growth-viability tradeoff in response to amino acid identity

In their natural environments, microorganisms mainly operate at suboptimal growth conditions with fluctuations in nutrient abundance. The resulting cellular adaptation is subject to conflicting tasks: growth or survival maximisation. Here, we study this adaptation by systematically measuring the impact of a nitrogen downshift to 24 nitrogen sources on cellular metabolism at the single-cell level. Saccharomyces lineages grown in rich media and exposed to a nitrogen downshift gradually differentiate to form two subpopulations of different cell sizes where one favours growth while the other favours viability with an extended chronological lifespan. This differentiation is asymmetrical with daughter cells representing the new differentiated state with increased viability. We characterise the metabolic response of the subpopulations using RNA sequencing, metabolic biosensors and a transcription factor-tagged GFP library coupled to high-throughput microscopy, imaging more than 800,000 cells. We find that the subpopulation with increased viability is associated with a dormant quiescent state displaying differences in MAPK signalling. Depending on the identity of the nitrogen source present, differentiation into the quiescent state can be actively maintained, attenuated, or aborted. These results establish amino acids as important signalling molecules for the formation of genetically identical subpopulations, involved in chronological lifespan and growth rate determination.

Single-cell RNA sequencing reveals plasmid constrains bacterial population heterogeneity and identifies a non-conjugating subpopulation

Transcriptional heterogeneity in isogenic bacterial populations can play various roles in bacterial evolution, but its detection remains technically challenging. Here, we use microbial split-pool ligation transcriptomics to study the relationship between bacterial subpopulation formation and plasmid-host interactions at the single-cell level. We find that single-cell transcript abundances are influenced by bacterial growth state and plasmid carriage. Moreover, plasmid carriage constrains the formation of bacterial subpopulations. Plasmid genes, including those with core functions such as replication and maintenance, exhibit transcriptional heterogeneity associated with cell activity. Notably, we identify a cell subpopulation that does not transcribe conjugal plasmid transfer genes, which may help reduce plasmid burden on a subset of cells. Our study advances the understanding of plasmid-mediated subpopulation dynamics and provides insights into the plasmid-bacteria interplay.

Unveiling the regulatory network controlling natural transformation in lactococci

Lactococcus lactis is a lactic acid bacterium of major importance for food fermentation and biotechnological applications. The ability to manipulate its genome quickly and easily through competence for DNA transformation would accelerate its general use as a platform for a variety of applications. Natural transformation in this species requires the activation of the master regulator ComX. However, the growth conditions that lead to spontaneous transformation, as well as the regulators that control ComX production, are unknown. Here, we identified the carbon source, nitrogen supply, and pH as key factors controlling competence development in this species. Notably, we showed that these conditions are sensed by three global regulators (i.e., CcpA, CodY, and CovR), which repress comX transcription directly. Furthermore, our systematic inactivation of known signaling systems suggests that classical pheromone-sensing regulators are not involved. Finally, we revealed that the ComX-degrading MecA-ClpCP machinery plays a predominant role based on the identification of a single amino-acid substitution in the adaptor protein MecA of a highly transformable strain. Contrasting with closely-related streptococci, the master competence regulator in L. lactis is regulated both proximally by general sensors and distantly by the Clp degradation machinery. This study not only highlights the diversity of regulatory networks for competence control in Gram-positive bacteria, but it also paves the way for the use of natural transformation as a tool to manipulate this biotechnologically important bacterium.

Shaping of microbial phenotypes by trade-offs

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

Serial adaptive laboratory evolution enhances mixed carbon metabolic capacity of Escherichia coli

Microbes have inherent capacities for utilizing various carbon sources, however they often exhibit sub-par fitness due to low metabolic efficiency. To test whether a bacterial strain can optimally utilize multiple carbon sources, Escherichia coli was serially evolved in L-lactate and glycerol. This yielded two end-point strains that evolved first in L-lactate then in glycerol, and vice versa. The end-point strains displayed a universal growth advantage on single and a mixture of adaptive carbon sources, enabled by a concerted action of carbon source-specialists and generalist mutants. The combination of just four variants of glpK, ppsA, ydcI, and rph-pyrE, accounted for more than 80% of end-point strain fitness. In addition, machine learning analysis revealed a coordinated activity of transcriptional regulators imparting condition-specific regulation of gene expression. The effectiveness of the serial adaptive laboratory evolution (ALE) scheme in bioproduction applications was assessed under single and mixed-carbon culture conditions, in which serial ALE strain exhibited superior productivity of acetoin compared to ancestral strains. Together, systems-level analysis elucidated the molecular basis of serial evolution, which hold potential utility in bioproduction applications.

Biodiversity is enhanced by sequential resource utilization and environmental fluctuations via emergent temporal niches

How natural communities maintain their remarkable biodiversity and which species survive in complex communities are central questions in ecology. Resource competition models successfully explain many phenomena but typically predict only as many species as resources can coexist. Here, we demonstrate that sequential resource utilization, or diauxie, with periodic growth cycles can support many more species than resources. We explore how communities modify their own environments by sequentially depleting resources to form sequences of temporal niches, or intermediately depleted environments. Biodiversity is enhanced when community-driven or environmental fluctuations modulate the resource depletion order and produce different temporal niches on each growth cycle. Community-driven fluctuations under constant environmental conditions are rare, but exploring them illuminates the temporal niche structure that emerges from sequential resource utilization. With environmental fluctuations, we find most communities have more stably coexisting species than resources with survivors accurately predicted by the same temporal niche structure and each following a distinct optimal strategy. Our results thus present a new niche-based approach to understanding highly diverse fluctuating communities.

Bet hedging in a unicellular microalga

Understanding how organisms have adapted to persist in unpredictable environments is a fundamental goal in biology. Bet hedging, an evolutionary adaptation observed from microbes to humans, facilitates reproduction and population persistence in randomly fluctuating environments. Despite its prevalence, empirical evidence in microalgae, crucial primary producers and carbon sinks, is lacking. Here, we report a bet-hedging strategy in the unicellular microalga Haematococcus pluvialis. We show that isogenic populations reversibly diversify into heterophenotypic mobile and non-mobile cells independently of environmental conditions, likely driven by stochastic gene expression. Mobile cells grow faster but are stress-sensitive, while non-mobile cells prioritise stress resistance over growth. This is due to shifts from growth-promoting activities (cell division, photosynthesis) to resilience-promoting processes (thickened cell wall, cell enlargement, aggregation, accumulation of antioxidant and energy-storing compounds). Our results provide empirical evidence for bet hedging in a microalga, indicating the potential for adaptation to current and future environmental conditions and consequently conservation of ecosystem functions.

A fast method to distinguish between fermentative and respiratory metabolisms in single yeast cells

Saccharomyces cerevisiae adjusts its metabolism based on nutrient availability, typically transitioning from glucose fermentation to ethanol respiration as glucose becomes limiting. However, our understanding of the regulation of metabolism is largely based on population averages, whereas nutrient transitions may cause heterogeneous responses. Here we introduce iCRAFT, a method that couples the ATP Förster resonance energy transfer (FRET)-based biosensor yAT1.03 with Antimycin A to differentiate fermentative and respiratory metabolisms in individual yeast cells. Upon Antimycin A addition, respiratory cells experienced a sharp decrease of the normalized FRET ratio, while respiro-fermentative cells showed no response. Next, we tracked changes in metabolism during the diauxic shift of a glucose pre-grown culture. Following glucose exhaustion, the entire cell population experienced a progressive rise in cytosolic ATP produced via respiration, suggesting a gradual increase in respiratory capacity. Overall, iCRAFT is a robust tool to distinguish fermentation from respiration, offering a new single-cell opportunity to study yeast metabolism.

The hierarchy of sugar catabolization in Lactococcus cremoris

IMPORTANCE

The availability of nutrients to microorganisms varies considerably between different environments, and changes can occur rapidly. As a general rule, a fast growth rate-typically growth on glucose-is associated with the repression of other carbohydrate utilization genes, but it is not clear to what extent catabolite repression is exerted by other sugars. We investigated the hierarchy of sugar utilization after substrate transitions in Lactococcus cremoris. For this, we determined the proteome and carbohydrate utilization capacity after growth on different sugars. The results show that the preparedness of cells for the utilization of "slower" sugars is not strictly determined by the growth rate. The data point to individual proteins relevant for various sugar transitions and suggest that the evolutionary history of the organism might be responsible for deviations from a strictly growth rate-related sugar catabolization hierarchy.

RNA recording in single bacterial cells using reprogrammed tracrRNAs

Capturing an individual cell's transcriptional history is a challenge exacerbated by the functional heterogeneity of cellular communities. Here, we leverage reprogrammed tracrRNAs (Rptrs) to record selected cellular transcripts as stored DNA edits in single living bacterial cells. Rptrs are designed to base pair with sensed transcripts, converting them into guide RNAs. The guide RNAs then direct a Cas9 base editor to target an introduced DNA target. The extent of base editing can then be read in the future by sequencing. We use this approach, called TIGER (transcribed RNAs inferred by genetically encoded records), to record heterologous and endogenous transcripts in individual bacterial cells. TIGER can quantify relative expression, distinguish single-nucleotide differences, record multiple transcripts simultaneously and read out single-cell phenomena. We further apply TIGER to record metabolic bet hedging and antibiotic resistance mobilization in Escherichia coli as well as host cell invasion by Salmonella. Through RNA recording, TIGER connects current cellular states with past transcriptional states to decipher complex cellular responses in single cells.

Microbiota and epigenetics: Health impact

Epigenetic changes associated with disease development and progressions are of increasing importance because of their potential diagnostic and therapeutic applications. Several epigenetic changes associated with chronic metabolic disorders have been studied in various diseases. Epigenetic changes are mostly modulated by environmental factors, including the human microbiota living in different parts of our bodies. The microbial structural components and the microbially derived metabolites directly interact with host cells, thereby maintaining homeostasis. Microbiome dysbiosis, on the other hand, is known to produce elevated levels of disease-linked metabolites, which may directly affect a host metabolic pathway or induce epigenetic changes that can lead to disease development. Despite their important role in host physiology and signal transduction, there has been little research into the mechanics and pathways associated with epigenetic modifications. This chapter focuses on the relationship between microbes and their epigenetic effects in diseased pathology, as well as on the regulation and metabolism of the dietary options available to the microbes. Furthermore, this chapter also provides a prospective link between these two important phenomena, termed "Microbiome and Epigenetics."

Evolutionary explanations for heterogeneous behavior in clonal bacterial populations

Cellular heterogeneity in clonal bacterial populations is widespread. Division of labor and bet hedging are common adaptive explanations for the function of such heterogeneity. We suggest group-level phenotypes via shareable molecules and variation in cellular vigor as two alternative evolutionary explanations for bacterial cellular heterogeneity.

The Ability of Streptococcus thermophilus BT01 to Modulate Urease Activity in Healthy Subjects' Fecal Samples Depends on the Biomass Production Process

SCOPE

This study evaluates how manufacturing conditions of probiotic biomass production, using two different cryoprotectants, Cryo-A and Cryo-B, can affect Streptococcus thermophilus BT01 in vivo gastrointestinal tract survival and its ability to modulate the level of urease activity in fecal samples of healthy subjects.

METHODS AND RESULTS

A randomized controlled cross-over study is carried out on 20 adult healthy subjects to evaluate total and viable loads, persistence of S. thermophilus BT01, and urease activity in fecal samples. Strain-specific quantification by using developed culture-based method and molecular qPCR tool allows to quantify viable S. thermophilus BT01 strain in 90% of the subjects. The quantification of both total DNA and recovered viable S. thermophilus BT01 in fecal samples does not reveal significant differences between Cryo-A or Cryo-B treated biomass. However, the administration of S. thermophilus BT01 produced with Cryo-A results in a decreased urease activity in fecal samples compared to Cryo-B protected cells.

CONCLUSION

This study i) highlights how the manufacturing conditions can play a role in influencing the probiotic functionality in vivo and ii) represents the first evidence that links S. thermophilus to a specific probiotic mechanism, the reduction of urease activity in fecal samples.

Changes in interactions over ecological time scales influence single-cell growth dynamics in a metabolically coupled marine microbial community

Microbial communities thrive in almost all habitats on earth. Within these communities, cells interact through the release and uptake of metabolites. These interactions can have synergistic or antagonistic effects on individual community members. The collective metabolic activity of microbial communities leads to changes in their local environment. As the environment changes over time, the nature of the interactions between cells can change. We currently lack understanding of how such dynamic feedbacks affect the growth dynamics of individual microbes and of the community as a whole. Here we study how interactions mediated by the exchange of metabolites through the environment change over time within a simple marine microbial community. We used a microfluidic-based approach that allows us to disentangle the effect cells have on their environment from how they respond to their environment. We found that the interactions between two species-a degrader of chitin and a cross-feeder that consumes metabolic by-products-changes dynamically over time as cells modify their environment. Cells initially interact positively and then start to compete at later stages of growth. Our results demonstrate that interactions between microorganisms are not static and depend on the state of the environment, emphasizing the importance of disentangling how modifications of the environment affects species interactions. This experimental approach can shed new light on how interspecies interactions scale up to community level processes in natural environments.

Using click chemistry to study microbial ecology and evolution

Technological advances have largely driven the revolution in our understanding of the structure and function of microbial communities. Culturing, long the primary tool to probe microbial life, was supplanted by sequencing and other -omics approaches, which allowed detailed quantitative insights into species composition, metabolic potential, transcriptional activity, secretory responses and more. Although the ability to characterize "who's there" has never been easier or cheaper, it remains technically challenging and expensive to understand what the diverse species and strains that comprise microbial communities are doing in situ, and how these behaviors change through time. Our aim in this brief review is to introduce a developing toolkit based on click chemistry that can accelerate and reduce the expense of functional analyses of the ecology and evolution of microbial communities. After first outlining the history of technological development in this field, we will discuss key applications to date using diverse labels, including BONCAT, and then end with a selective (biased) view of areas where click-chemistry and BONCAT-based approaches stand to have a significant impact on our understanding of microbial communities.

Application of an Escherichia coli triple reporter strain for at-line monitoring of single-cell physiology during L-phenylalanine production

Biotechnological production processes are sustainable approaches for the production of biobased components such as amino acids for food and feed industry. Scale-up from ideal lab-scale bioreactors to large-scale processes is often accompanied by loss in productivity. This may be related to population heterogeneities of cells originating from isogenic cultures that arise due to dynamic non-ideal conditions in the bioreactor. To better understand this phenomenon, deeper insights into single-cell physiologies in bioprocesses are mandatory before scale-up. Here, a triple reporter strain (3RP) was developed by chromosomally integrating the fluorescent proteins mEmerald, CyOFP1, and mTagBFP2 into the L-phenylalanine producing Escherichia coli strain FUS4 (pF81kan) to allow monitoring of growth, oxygen availability, and general stress response of the single cells. Functionality of the 3RP was confirmed in well-mixed lab-scale fed-batch processes with glycerol as carbon source in comparison to the strain without fluorescent proteins, leading to no difference in process performance. Fluorescence levels could successfully reflect the course of related process state variables, revealed population heterogeneities during the transition between different process phases and potentially subpopulations that exhibit superior process performance. Furthermore, indications were found for noise in gene expression as regulation strategy against environmental perturbation.

Public good-driven release of heterogeneous resources leads to genotypic diversification of an isogenic yeast population

Understanding the basis of biological diversity remains a central problem in evolutionary biology. Using microbial systems, adaptive diversification has been studied in (a) spatially heterogeneous environments, (b) temporally segregated resources, and (c) resource specialization in a homogeneous environment. However, it is not well understood how adaptive diversification can take place in a homogeneous environment containing a single resource. Starting from an isogenic population of yeast Saccharomyces cerevisiae, we report rapid adaptive diversification, when propagated in an environment containing melibiose as the carbon source. The diversification is driven due to a public good enzyme α-galactosidase, which hydrolyzes melibiose into glucose and galactose. The diversification is driven by mutations at a single locus, in the GAL3 gene in the S. cerevisiae GAL/MEL regulon. We show that metabolic co-operation involving public resources could be an important mode of generating biological diversity. Our study demonstrates sympatric diversification of yeast starting from an isogenic population and provides detailed mechanistic insights into the factors and conditions responsible for generating and maintaining the population diversity.

Ecological memory of prior nutrient exposure in the human gut microbiome

Many ecosystems have been shown to retain a memory of past conditions, which in turn affects how they respond to future stimuli. In microbial ecosystems, community disturbance has been associated with lasting impacts on microbiome structure. However, whether microbial communities alter their response to repeated stimulus remains incompletely understood. Using the human gut microbiome as a model, we show that bacterial communities retain an "ecological memory" of past carbohydrate exposures. Memory of the prebiotic inulin was encoded within a day of supplementation among a cohort of human study participants. Using in vitro gut microbial models, we demonstrated that the strength of ecological memory scales with nutrient dose and persists for days. We found evidence that memory is seeded by transcriptional changes among primary degraders of inulin within hours of nutrient exposure, and that subsequent changes in the activity and abundance of these taxa are sufficient to enhance overall community nutrient metabolism. We also observed that ecological memory of one carbohydrate species impacts microbiome response to other carbohydrates, and that an individual's habitual exposure to dietary fiber was associated with their gut microbiome's efficiency at digesting inulin. Together, these findings suggest that the human gut microbiome's metabolic potential reflects dietary exposures over preceding days and changes within hours of exposure to a novel nutrient. The dynamics of this ecological memory also highlight the potential for intra-individual microbiome variation to affect the design and interpretation of interventions involving the gut microbiome.

Erythro-PmBs: A Selective Polymyxin B Delivery System Using Antibody-Conjugated Hybrid Erythrocyte Liposomes

As a result of the growing worldwide antibiotic resistance crisis, many currently existing antibiotics have become ineffective due to bacteria developing resistive mechanisms. There are a limited number of potent antibiotics that are successful at suppressing microbial growth, such as polymyxin B (PmB); however, these are often deemed as a last resort due to their toxicity. We present a novel PmB delivery system constructed by conjugating hybrid erythrocyte liposomes with antibacterial antibodies to combine a high loading efficiency with guided delivery. The retention of PmB is enhanced by incorporating negatively charged lipids into the red blood cells' cytoplasmic membrane (RBC_cm). Anti-Escherichia coli antibodies are attached to these hybrid erythrocyte liposomes by the inclusion of DSPE-PEG maleimide linkers. We show that these erythro-PmBs have a loading efficiency of ∼90% and are effective in delivering PmB to E. coli, with values for the minimum inhibitory concentration (MIC) being comparable to those of free PmB. The MIC values for Klebsiella aerogenes, however, significantly increased well beyond the resistant breakpoint, indicating that the inclusion of the anti-E. coli antibodies enables the erythro-PmBs to selectively deliver antibiotics to specific targets.

Better under stress: Improving bacterial cellulose production by Komagataeibacter xylinus K2G30 (UMCC 2756) using adaptive laboratory evolution

Among naturally produced polymers, bacterial cellulose is receiving enormous attention due to remarkable properties, making it suitable for a wide range of industrial applications. However, the low yield, the instability of microbial strains and the limited knowledge of the mechanisms regulating the metabolism of producer strains, limit the large-scale production of bacterial cellulose. In this study, Komagataeibacter xylinus K2G30 was adapted in mannitol based medium, a carbon source that is also available in agri-food wastes. K. xylinus K2G30 was continuously cultured by replacing glucose with mannitol (2% w/v) for 210 days. After a starting lag-phase, in which no changes were observed in the utilization of mannitol and in bacterial cellulose production (cycles 1-25), a constant improvement of the phenotypic performances was observed from cycle 26 to cycle 30, accompanied by an increase in mannitol consumption. At cycle 30, the end-point of the experiment, bacterial cellulose yield increased by 38% in comparision compared to cycle 1. Furthermore, considering the mannitol metabolic pathway, D-fructose is an intermediate in the bioconversion of mannitol to glucose. Based on this consideration, K. xylinus K2G30 was tested in fructose-based medium, obtaining the same trend of bacterial cellulose production observed in mannitol medium. The adaptive laboratory evolution approach used in this study was suitable for the phenotypic improvement of K. xylinus K2G30 in bacterial cellulose production. Metabolic versatility of the strain was confirmed by the increase in bacterial cellulose production from D-fructose-based medium. Moreover, the adaptation on mannitol did not occur at the expense of glucose, confirming the versatility of K2G30 in producing bacterial cellulose from different carbon sources. Results of this study contribute to the knowledge for designing new strategies, as an alternative to the genetic engineering approach, for bacterial cellulose production.

Stability criteria for the consumption and exchange of essential resources

Models of consumer effects on a shared resource environment have helped clarify how the interplay of consumer traits and resource supply impact stable coexistence. Recent models generalize this picture to include the exchange of resources alongside resource competition. These models exemplify the fact that although consumers shape the resource environment, the outcome of consumer interactions is context-dependent: such models can have either stable or unstable equilibria, depending on the resource supply. However, these recent models focus on a simplified version of microbial metabolism where the depletion of resources always leads to consumer growth. Here, we model an arbitrarily large system of consumers governed by Liebig’s law, where species require and deplete multiple resources, but each consumer’s growth rate is only limited by a single one of these resources. Resources that are taken up but not incorporated into new biomass are leaked back into the environment, possibly transformed by intracellular reactions, thereby tying the mismatch between depletion and growth to cross-feeding. For this set of dynamics, we show that feasible equilibria can be either stable or unstable, again depending on the resource environment. We identify special consumption and production networks which protect the community from instability when resources are scarce. Using simulations, we demonstrate that the qualitative stability patterns derived analytically apply to a broader class of network structures and resource inflow profiles, including cases where multiple species coexist on only one externally supplied resource. Our stability criteria bear some resemblance to classic stability results for pairwise interactions, but also demonstrate how environmental context can shape coexistence patterns when resource limitation and exchange are modeled directly.

A Microfluidic Platform for Tracking Individual Cell Dynamics during an Unperturbed Nutrients Exhaustion

Microorganisms have evolved adaptive strategies to respond to the autonomous degradation of their environment. Indeed, a growing culture progressively exhausts nutrients from its media and modifies its composition. Yet, how single cells react to these modifications remains difficult to study since it requires population-scale growth experiments to allow cell proliferation to have a collective impact on the environment, while monitoring the same individuals exposed to this environment for days. For this purpose, we have previously described an integrated microfluidic pipeline, based on continuous separation of the cells from the media and subsequent perfusion of the filtered media in an observation chamber containing isolated single cells. Here, we provide a detailed protocol to implement this methodology, including the setting up of the microfluidic system and the processing of timelapse images.

Single-cell stable isotope probing in microbial ecology

Environmental and host-associated microbiomes are typically diverse assemblages of organisms performing myriad activities and engaging in a network of interactions that play out in spatially structured contexts. As the sum of these activities and interactions give rise to overall microbiome function, with important consequences for environmental processes and human health, elucidating specific microbial activities within complex communities is a pressing challenge. Single-cell stable isotope probing (SC-SIP) encompasses multiple techniques that typically utilize Raman microspectroscopy or nanoscale secondary ion mass spectrometry (NanoSIMS) to enable spatially resolved tracking of isotope tracers in cells, cellular components, and metabolites. SC-SIP techniques are uniquely suited for illuminating single-cell activities in microbial communities and for testing hypotheses about cellular functions generated for example from meta-omics datasets. Here, we illustrate the insights enabled by SC-SIP techniques by reviewing selected applications in microbiology and offer a perspective on their potential for future research.

Digital models in biotechnology: Towards multi-scale integration and implementation

Industrial biotechnology encompasses a large area of multi-scale and multi-disciplinary research activities. With the recent megatrend of digitalization sweeping across all industries, there is an increased focus in the biotechnology industry on developing, integrating and applying digital models to improve all aspects of industrial biotechnology. Given the rapid development of this field, we systematically classify the state-of-art modelling concepts applied at different scales in industrial biotechnology and critically discuss their current usage, advantages and limitations. Further, we critically analyzed current strategies to couple cell models with computational fluid dynamics to study the performance of industrial microorganisms in large-scale bioprocesses, which is of crucial importance for the bio-based production industries. One of the most challenging aspects in this context is gathering intracellular data under industrially relevant conditions. Towards comprehensive models, we discuss how different scale-down concepts combined with appropriate analytical tools can capture intracellular states of single cells. We finally illustrated how the efforts could be used to develop digitals models suitable for both cell factory design and process optimization at industrial scales in the future.

Using fluorescent promoter-reporters to study sugar utilization control in Bifidobacterium longum NCC 2705

Bifidobacteria are amongst the first bacteria to colonize the human gastro-intestinal system and have been proposed to play a crucial role in the development of the infant gut since their absence is correlated to the development of diseases later in life. Bifidobacteria have the capacity to metabolize a diverse range of (complex) carbohydrates, reflecting their adaptation to the lower gastro-intestinal tract. Detailed understanding of carbohydrate metabolism regulation in this genus is of prime importance and availability of additional genetic tools easing such studies would be beneficial. To develop a fluorescent protein-based reporter system that can be used in B. longum NCC 2705, we first selected the most promising fluorescent protein out of the seven we tested (i.e., mCherry). This reporter protein was then used to study the carbohydrate mediated activation of P_Bl1518 and P_Bl1694, two promoters respectively predicted to be controlled by the transcriptional factors AraQ and AraU, previously suggested to regulate arabinose utilization and proposed to also act as global transcriptional regulators in bifidobacteria. We confirmed that in B. longum NCC 2705 the AraQ controlled promoter (P_Bl1518) is induced strongly by arabinose and established that the AraU controlled promoter (P_Bl1694) was mostly induced by the hexoses galactose and fructose. Combining the mCherry reporter system with flow cytometry, we established that NCC 2705 is able to co-metabolize arabinose and glucose while galactose was only consumed after glucose exhaustion, thus illustrating the complexity of different carbohydrate consumption patterns and their specific regulation in this strain.

Diauxic lags explain unexpected coexistence in multi-resource environments

How the coexistence of species is affected by the presence of multiple resources is a major question in microbial ecology. We experimentally demonstrate that differences in diauxic lags, which occur as species deplete their own environments and adapt their metabolisms, allow slow-growing microbes to stably coexist with faster-growing species in multi-resource environments despite being excluded in single-resource environments. In our focal example, an Acinetobacter species (Aci2) competitively excludes Pseudomonas aurantiaca (Pa) on alanine and on glutamate. However, they coexist on the combination of both resources. Experiments reveal that Aci2 grows faster but Pa has shorter diauxic lags. We establish a tradeoff between Aci2's fast growth and Pa's short lags as their mechanism for coexistence. We model this tradeoff to accurately predict how environmental changes affect community composition. We extend our work by surveying a large set of competitions and observe coexistence nearly four times as frequently when the slow-grower is the fast-switcher. Our work illustrates a simple mechanism, based entirely on supplied-resource growth dynamics, for the emergence of multi-resource coexistence.

Diversity of bet-hedging strategies in microbial communities-Recent cases and insights

Microbial communities are continuously exposed to unpredictable changes in their environment. To thrive in such dynamic habitats, microorganisms have developed the ability to readily switch phenotypes, resulting in a number of differently adapted subpopulations expressing various traits. In evolutionary biology, a particular case of phenotypic heterogeneity that evolved in an unpredictably changing environment has been defined as bet‐hedging. Bet‐hedging is a risk‐spreading strategy where isogenic populations stochastically (randomly) diversify their phenotypes, often resulting in maladapted individuals that suffer lower reproductive success. This fitness trade‐off in a specific environment may have a selective advantage upon the sudden environmental shift. Thus, a bet‐hedging strategy allows populations to persist in very dynamic habitats, but with a particular fitness cost. In recent years, numerous examples of phenotypic heterogeneity in different microorganisms have been observed, some suggesting bet‐hedging. Here, we highlight the latest reports concerning bet‐hedging phenomena in various microorganisms to show how versatile this strategy is within the microbial realms.

This article is categorized under:

Infectious Diseases > Molecular and Cellular Physiology

Global pleiotropic effects in adaptively evolved Escherichia coli lacking CRP reveal molecular mechanisms that define the growth physiology

Evolution facilitates emergence of fitter phenotypes by efficient allocation of cellular resources in conjunction with beneficial mutations. However, system-wide pleiotropic effects that redress the perturbations to the apex node of the transcriptional regulatory networks remain unclear. Here, we elucidate that absence of global transcriptional regulator CRP in Escherichia coli results in alterations in key metabolic pathways under glucose respiratory conditions, favouring stress- or hedging-related functions over growth-enhancing functions. Further, we disentangle the growth-mediated effects from the CRP regulation-specific effects on these metabolic pathways. We quantitatively illustrate that the loss of CRP perturbs proteome efficiency, as evident from metabolic as well as ribosomal proteome fractions, that corroborated with intracellular metabolite profiles. To address how E. coli copes with such systemic defect, we evolved Δcrp mutant in the presence of glucose. Besides acquiring mutations in the promoter of glucose transporter ptsG, the evolved populations recovered the metabolic pathways to their pre-perturbed state coupled with metabolite re-adjustments, which altogether enabled increased growth. By contrast to Δcrp mutant, the evolved strains remodelled their proteome efficiency towards biomass synthesis, albeit at the expense of carbon efficiency. Overall, we comprehensively illustrate the genetic and metabolic basis of pleiotropic effects, fundamental for understanding the growth physiology.

Robustness: linking strain design to viable bioprocesses

Microbial cell factories are becoming increasingly popular for the sustainable production of various chemicals. Metabolic engineering has led to the design of advanced cell factories; however, their long-term yield, titer, and productivity falter when scaled up and subjected to industrial conditions. This limitation arises from a lack of robustness - the ability to maintain a constant phenotype despite the perturbations of such processes. This review describes predictable and stochastic industrial perturbations as well as state-of-the-art technologies to counter process variability. Moreover, we distinguish robustness from tolerance and discuss the potential of single-cell studies for improving system robustness. Finally, we highlight ways of achieving consistent and comparable quantification of robustness that can guide the selection of strains for industrial bioprocesses.

Suboptimal resource allocation in changing environments constrains response and growth in bacteria

To respond to fluctuating conditions, microbes typically need to synthesize novel proteins. As this synthesis relies on sufficient biosynthetic precursors, microbes must devise effective response strategies to manage depleting precursors. To better understand these strategies, we investigate the active response of Escherichia coli to changes in nutrient conditions, connecting transient gene expression to growth phenotypes. By synthetically modifying gene expression during changing conditions, we show how the competition by genes for the limited protein synthesis capacity constrains cellular response. Despite this constraint cells substantially express genes that are not required, trapping them in states where precursor levels are low and the genes needed to replenish the precursors are outcompeted. Contrary to common modeling assumptions, our findings highlight that cells do not optimize growth under changing environments but rather exhibit hardwired response strategies that may have evolved to promote fitness in their native environment. The constraint and the suboptimality of the cellular response uncovered provide a conceptual framework relevant for many research applications, from the prediction of evolution to the improvement of gene circuits in biotechnology.

Monitoring single-cell dynamics of entry into quiescence during an unperturbed life cycle

The life cycle of microorganisms is associated with dynamic metabolic transitions and complex cellular responses. In yeast, how metabolic signals control the progressive choreography of structural reorganizations observed in quiescent cells during a natural life cycle remains unclear. We have developed an integrated microfluidic device to address this question, enabling continuous single-cell tracking in a batch culture experiencing unperturbed nutrient exhaustion to unravel the coordination between metabolic and structural transitions within cells. Our technique reveals an abrupt fate divergence in the population, whereby a fraction of cells is unable to transition to respiratory metabolism and undergoes a reversible entry into a quiescence-like state leading to premature cell death. Further observations reveal that nonmonotonous internal pH fluctuations in respiration-competent cells orchestrate the successive waves of protein superassemblies formation that accompany the entry into a bona fide quiescent state. This ultimately leads to an abrupt cytosolic glass transition that occurs stochastically long after proliferation cessation. This new experimental framework provides a unique way to track single-cell fate dynamics over a long timescale in a population of cells that continuously modify their ecological niche.

Role of xylose from acidic hydrolysates of agave bagasse during biohydrogen production

This study compares the H₂ production from glucose, xylose, and acidic hydrolysates of Agave tequilana bagasse as substrates. The fermentation was performed in a granular sludge reactor operated in two phases: (1) model substrates (glucose and xylose) and (2) acidic hydrolysates at 35 °C, pH 4.5 and a hydraulic retention time of 5.5 h with glucose (10 g L^-1) and xylose (12 g L^-1). A sequencing batch reactor was used to acclimate the biomass between the glucose and xylose continuous fermentation (with a mixture of xylose-glucose) and acidic hydrolysates. During the discontinuous acclimating step, the xylose/glucose ratio increment negatively affected the H₂ productivity. Although the continuous H₂ production with xylose was negligible, the co-fermentation with glucose (88-12%) allowed H₂ productivity of 2,889 ± 502 mL H₂ L^-1d^-1. An acidic hydrolysate concentration of 3.3 g_carbohydrate L^-1 showed a three-fold higher H₂ productivity than with a concentration of 10 g L^-1. The results indicated that xylose, as the only substrate, was challenging to metabolize by the inoculum, and its mixture with glucose improved the H₂ productivity. Therefore, the low H₂ productivity with hydrolysates could be related to the presence of xylose.

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.

Dual Regulation of Cytoplasm and Peroxisomes for Improved Α-Farnesene Production in Recombinant Pichia pastoris

Microbial production of α-farnesene from renewable raw materials is a feasible alternative to traditional petroleum craft. Recently, the research on improving α-farnesene production in Pichia pastoris mainly focused on cytoplasmic engineering, while comprehensive engineering of multiple subcellular compartments is rarely reported. Here, we first sought to confirm that the isopentenol utilization pathway (IUP) could act as a two-step shortcut for IPP synthesis in P. pastoris peroxisomes. In addition, we proposed dual regulation of cytoplasm and peroxisomes to boost α-farnesene synthesis in P. pastoris X33, thus the resultant strain produced 2.18 ± 0.04 g/L, which was 1.3 times and 2.1 times than that of the strain only with peroxisomal or cytoplasmic engineering, respectively. The α-farnesene production achieved 2.56 ± 0.04 g/L in shake flasks after carbon source cofeeding, which was the highest reported production in worldwide literatures to the best of my knowledge. Therefore, we propose these strategies as efficient approaches to enhancing α-farnesene production in P. pastoris, which might bring new ideas for the biosynthesis of high-value compounds.

Reducing phenotypic instabilities of a microbial population during continuous cultivation based on cell switching dynamics

Predicting the fate of individual cells among a microbial population (i.e., growth and gene expression) remains a challenge, especially when this population is exposed to very dynamic environmental conditions, such as those encountered during continuous cultivation. Indeed, the dynamic nature of a continuous cultivation process implies the potential diversification of the microbial population resulting in genotypic and phenotypic heterogeneity. The present work focused on the induction of the arabinose operon in Escherichia coli as a model system to study this diversification process in continuous cultivations. As a preliminary step, the green fluorescent protein (GFP) level triggered by an arabinose-inducible ParaBAD promoter was tracked by flow cytometry in chemostat cultivations with glucose-arabinose co-feeding. For a wide range of glucose-arabinose co-feeding concentrations in the chemostats, the simultaneous occurrence of GFP positive and negative subpopulation was observed. In the second set of experiments, continuous cultivation was performed by adding glucose continuously and arabinose based on the capability of individual cells to switch from low GFP to high GFP expression states, performed with a technology setup called segregostat. In the segregostat cultivation mode, on-line flow cytometry analysis was used for adjusting the arabinose/glucose transitions based on the phenotypic switching profiles of the microbial population. This strategy allowed finding an appropriate arabinose pulsing frequency, leading to prolonged maintenance of the induction level with a limited increase in the phenotypic diversity for more than 60 generations. The results suggest that the steady forcing of individual cells into a given phenotypic trajectory may not be the best strategy for controlling cell populations. Instead, allowing individual cells to switch periodically around a predefined threshold seems to be a more robust strategy leading to oscillations, but within a predictable cell population behavior range.

Generation of Genetic Tools for Gauging Multiple-Gene Expression at the Single-Cell Level

Key microbial processes in many bacterial species are heterogeneously expressed in single cells of bacterial populations. However, the paucity of adequate molecular tools for live, real-time monitoring of multiple-gene expression at the single-cell level has limited the understanding of phenotypic heterogeneity. To investigate phenotypic heterogeneity in the ubiquitous opportunistic pathogen Pseudomonas aeruginosa, a genetic tool that allows gauging multiple-gene expression at the single-cell level has been generated. This tool, named pRGC, consists of a promoter-probe vector for transcriptional fusions that carries three reporter genes coding for the fluorescent proteins mCherry, green fluorescent protein (GFP), and cyan fluorescent protein (CFP). The pRGC vector has been characterized and validated via single-cell gene expression analysis of both constitutive and iron-regulated promoters, showing clear discrimination of the three fluorescence signals in single cells of a P. aeruginosa population without the need for image processing for spectral cross talk correction. In addition, two pRGC variants have been generated for either (i) integration of the reporter gene cassette into a single neutral site of P. aeruginosa chromosome that is suitable for long-term experiments in the absence of antibiotic selection or (ii) replication in bacterial genera other than Pseudomonas The easy-to-use genetic tools generated in this study will allow rapid and cost-effective investigation of multiple-gene expression in populations of environmental and pathogenic bacteria, hopefully advancing the understanding of microbial phenotypic heterogeneity.IMPORTANCE Within a bacterial population, single cells can differently express some genes, even though they are genetically identical and experience the same chemical and physical stimuli. This phenomenon, known as phenotypic heterogeneity, is mainly driven by gene expression noise and results in the emergence of bacterial subpopulations with distinct phenotypes. The analysis of gene expression at the single-cell level has shown that phenotypic heterogeneity is associated with key bacterial processes, including competence, sporulation, and persistence. In this study, new genetic tools have been generated that allow easy cloning of up to three promoters upstream of distinct fluorescent genes, making it possible to gauge multiple-gene expression at the single-cell level by fluorescence microscopy without the need for advanced image-processing procedures. A proof of concept has been provided by investigating iron uptake and iron storage gene expression in response to iron availability in P. aeruginosa.

Global Transcriptional Regulators Fine-Tune the Translational and Metabolic Efficiency for Optimal Growth of Escherichia coli

Global transcriptional regulators coordinate complex genetic interactions that bestow better adaptability for an organism against external and internal perturbations. These transcriptional regulators are known to control an enormous array of genes with diverse functionalities. However, regulator-driven molecular mechanisms that underpin precisely tuned translational and metabolic processes conducive for rapid exponential growth remain obscure. Here, we comprehensively reveal the fundamental role of global transcriptional regulators FNR, ArcA, and IHF in sustaining translational and metabolic efficiency under glucose fermentative conditions in Escherichia coli By integrating high-throughput gene expression profiles and absolute intracellular metabolite concentrations, we illustrate that these regulators are crucial in maintaining nitrogen homeostasis, govern expression of otherwise unnecessary or hedging genes, and exert tight control on metabolic bottleneck steps. Furthermore, we characterize changes in expression and activity profiles of other coregulators associated with these dysregulated metabolic pathways, determining the regulatory interactions within the transcriptional regulatory network. Such systematic findings emphasize their importance in optimizing the proteome allocation toward metabolic enzymes as well as ribosomes, facilitating condition-specific phenotypic outcomes. Consequentially, we reveal that disruption of this inherent trade-off between ribosome and metabolic proteome economy due to the loss of regulators resulted in lowered growth rates. Moreover, our findings reinforce that the accumulations of intracellular metabolites in the event of proteome repartitions negatively affects the glucose uptake. Overall, by extending the three-partition proteome allocation theory concordant with multi-omics measurements, we elucidate the physiological consequences of loss of global regulators on central carbon metabolism restraining the organism to attain maximal biomass synthesis.IMPORTANCE Cellular proteome allocation in response to environmental or internal perturbations governs their eventual phenotypic outcome. This entails striking an effective balance between amino acid biosynthesis by metabolic proteins and its consumption by ribosomes. However, the global transcriptional regulator-driven molecular mechanisms that underpin their coordination remains unexplored. Here, we emphasize that global transcriptional regulators, known to control expression of a myriad of genes, are fundamental for precisely tuning the translational and metabolic efficiencies that define the growth optimality. Towards this, we systematically characterized the single deletion effect of FNR, ArcA, and IHF regulators of Escherichia coli on exponential growth under anaerobic glucose fermentative conditions. Their absence disrupts the stringency of proteome allocation, which manifests as impairment in key metabolic processes and an accumulation of intracellular metabolites. Furthermore, by incorporating an extension to the empirical growth laws, we quantitatively demonstrate the general design principles underlying the existence of these regulators in E. coli.

Lifestyle, metabolism and environmental adaptation in Lactococcus lactis

Lactococcus lactis serves as a paradigm organism for the lactic acid bacteria (LAB). Extensive research into the molecular biology, metabolism and physiology of several model strains of this species has been fundamental for our understanding of the LAB. Genomic studies have provided new insights into the species L. lactis, including the resolution of the genetic basis of its subspecies division, as well as the control mechanisms involved in the fine-tuning of growth rate and energy metabolism. In addition, it has enabled novel approaches to study lactococcal lifestyle adaptations to the dairy application environment, including its adjustment to near-zero growth rates that are particularly relevant in the context of cheese ripening. This review highlights various insights in these areas and exemplifies the strength of combining experimental evolution with functional genomics and bacterial physiology research to expand our fundamental understanding of the L. lactis lifestyle under different environmental conditions.

Proteomic analysis of secretomes from Bacillus sp. AR03: characterization of enzymatic cocktails active on complex carbohydrates for xylooligosaccharides production

Bacillus sp. AR03 have been described as an important producer of carbohydrate-active enzymes (CAZymes) when growing in a peptone-based medium supplemented with simple sugars and/or carboxymethyl cellulose (CMC) as carbon sources. This work aimed to identify the extracellular enzymatic cocktails through shotgun proteomics. The proteomic analysis showed that enzymes involved in cellulose and xylan degradation were among the most abundant proteins. These enzymes included an endo-glucanase GH5_2 and a glucuronoxylanase GH30_8, which were found in all conditions. In addition, several proteins were differentially expressed in the three evaluated culture media, indicating microbial metabolic changes due to the different supplied carbon sources, particularly, in the presence of CMC. Finally, the capability of the crude enzymatic cocktails from culture media to degrade birchwood xylan was assessed, which produced mostly xylooligosaccharides containing among 3-5 xylose units. Consequently, this work shows the potential of the extracellular enzymes from Bacillus sp. AR03 for producing emergent prebiotics.

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.

Phenotypic Heterogeneity in Tumor Progression, and Its Possible Role in the Onset of Cancer

Heterogeneity among isogenic cells/individuals has been known for at least 150 years. Even Mendel, working on pea plants, realized that not all tall plants were identical. However, Mendel was more interested in the discontinuous variation between genetically distinct individuals. The concept of environment dictating distinct phenotypes among isogenic individuals has since been shown to impact the evolution of populations in numerous examples at different scales of life. In this review, we discuss how phenotypic heterogeneity and its evolutionary implications exist at all levels of life, from viruses to mammals. In particular, we discuss how a particular disease condition (cancer) is impacted by heterogeneity among isogenic cells, and propose a potential role that phenotypic heterogeneity might play toward the onset of the disease.