Optimization of lag phase shapes the evolution of a bacterial enzyme

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

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

Understanding cellular growth strategies via optimal control

Evolutionary prediction and control are increasingly interesting research topics that are expanding to new areas of application. Unravelling and anticipating successful adaptations to different selection pressures becomes crucial when steering rapidly evolving cancer or microbial populations towards a chosen target. Here we introduce and apply a rich theoretical framework of optimal control to understand adaptive use of traits, which in turn allows eco-evolutionarily informed population control. Using adaptive metabolism and microbial experimental evolution as a case study, we show how demographic stochasticity alone can lead to lag time evolution, which appears as an emergent property in our model. We further show that the cycle length used in serial transfer experiments has practical importance as it may cause unintentional selection for specific growth strategies and lag times. Finally, we show how frequency-dependent selection can be incorporated to the state-dependent optimal control framework allowing the modelling of complex eco-evolutionary dynamics. Our study demonstrates the utility of optimal control theory in elucidating organismal adaptations and the intrinsic decision making of cellular communities with high adaptive potential.

Decreased thermal niche breadth as a trade-off of antibiotic resistance

Evolutionary theory predicts that adaptations, including antibiotic resistance, should come with associated fitness costs; yet, many resistance mutations seemingly contradict this prediction by inducing no growth rate deficit. However, most growth assays comparing sensitive and resistant strains have been performed under a narrow range of environmental conditions, which do not reflect the variety of contexts that a pathogenic bacterium might encounter when causing infection. We hypothesized that reduced niche breadth, defined as diminished growth across a diversity of environments, can be a cost of antibiotic resistance. Specifically, we test whether chloramphenicol-resistant Escherichia coli incur disproportionate growth deficits in novel thermal conditions. Here we show that chloramphenicol-resistant bacteria have greater fitness costs at novel temperatures than their antibiotic-sensitive ancestors. In several cases, we observed no resistance cost in growth rate at the historic temperature but saw diminished growth at warmer and colder temperatures. These results were consistent across various genetic mechanisms of resistance. Thus, we propose that decreased thermal niche breadth is an under-documented fitness cost of antibiotic resistance. Furthermore, these results demonstrate that the cost of antibiotic resistance shifts rapidly as the environment changes; these context-dependent resistance costs should select for the rapid gain and loss of resistance as an evolutionary strategy.

Genetic mutations in adaptive evolution of growth-independent vancomycin-tolerant Staphylococcus aureus

BACKGROUND

Antibiotic tolerance allows bacteria to overcome antibiotic treatment transiently and potentially accelerates the emergence of resistance. However, our understanding of antibiotic tolerance at the genetic level during adaptive evolution of Staphylococcus aureus remains incomplete. We sought to identify the mutated genes and verify the role of these genes in the formation of vancomycin tolerance in S. aureus.

METHODS

Vancomycin-susceptible S. aureus strain Newman was used to induce vancomycin-tolerant isolates in vitro by cyclic exposure under a high concentration of vancomycin (20× MIC). WGS and Sanger sequencing were performed to identify the genetic mutations. The function of mutated genes in vancomycin-tolerant isolates were verified by gene complementation. Other phenotypes of vancomycin-tolerant isolates were also determined, including mutation frequency, autolysis, lysostaphin susceptibility, cell wall thickness and cross-tolerance.

RESULTS

A series of vancomycin-tolerant S. aureus (VTSA) strains were isolated and 18 mutated genes were identified by WGS. Among these genes, pbp4, htrA, stp1, pth and NWMN_1068 were confirmed to play roles in VTSA formation. Mutation of mutL promoted the emergence of VTSA. All VTSA showed no changes in growth phenotype. Instead, they exhibited reduced autolysis, decreased lysostaphin susceptibility and thickened cell walls. In addition, all VTSA strains were cross-tolerant to antibiotics targeting cell wall synthesis but not to quinolones and lipopeptides.

CONCLUSIONS

Our results demonstrate that genetic mutations are responsible for emergence of phenotypic tolerance and formation of vancomycin tolerance may lie in cell wall changes in S. aureus.

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.

Metabolic response to point mutations reveals principles of modulation of in vivo enzyme activity and phenotype

The relationship between sequence variation and phenotype is poorly understood. Here, we use metabolomic analysis to elucidate the molecular mechanism underlying the filamentous phenotype of E. coli strains that carry destabilizing mutations in dihydrofolate reductase (DHFR). We find that partial loss of DHFR activity causes reversible filamentation despite SOS response indicative of DNA damage, in contrast to thymineless death (TLD) achieved by complete inhibition of DHFR activity by high concentrations of antibiotic trimethoprim. This phenotype is triggered by a disproportionate drop in intracellular dTTP, which could not be explained by drop in dTMP based on the Michaelis-Menten-like in vitro activity curve of thymidylate kinase (Tmk), a downstream enzyme that phosphorylates dTMP to dTDP. Instead, we show that a highly cooperative (Hill coefficient 2.5) in vivo activity of Tmk is the cause of suboptimal dTTP levels. dTMP supplementation rescues filamentation and restores in vivo Tmk kinetics to Michaelis-Menten. Overall, this study highlights the important role of cellular environment in sculpting enzymatic kinetics with system-level implications for bacterial phenotype.

Avoidance of protein unfolding constrains protein stability in long-term evolution

Every amino acid residue can influence a protein's overall stability, making stability highly susceptible to change throughout evolution. We consider the distribution of protein stabilities evolutionarily permittable under two previously reported protein fitness functions: flux dynamics and misfolding avoidance. We develop an evolutionary dynamics theory and find that it agrees better with an extensive protein stability data set for dihydrofolate reductase orthologs under the misfolding avoidance fitness function rather than the flux dynamics fitness function. Further investigation with ribonuclease H data demonstrates that not any misfolded state is avoided; rather, it is only the unfolded state. At the end, we discuss how our work pertains to the universal protein abundance-evolutionary rate correlation seen across organisms' proteomes. We derive a closed-form expression relating protein abundance to evolutionary rate that captures Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens experimental trends without fitted parameters.

Pervasive cooperative mutational effects on multiple catalytic enzyme traits emerge via long-range conformational dynamics

Multidimensional fitness landscapes provide insights into the molecular basis of laboratory and natural evolution. To date, such efforts usually focus on limited protein families and a single enzyme trait, with little concern about the relationship between protein epistasis and conformational dynamics. Here, we report a multiparametric fitness landscape for a cytochrome P450 monooxygenase that was engineered for the regio- and stereoselective hydroxylation of a steroid. We develop a computational program to automatically quantify non-additive effects among all possible mutational pathways, finding pervasive cooperative signs and magnitude epistasis on multiple catalytic traits. By using quantum mechanics and molecular dynamics simulations, we show that these effects are modulated by long-range interactions in loops, helices and β-strands that gate the substrate access channel allowing for optimal catalysis. Our work highlights the importance of conformational dynamics on epistasis in an enzyme involved in secondary metabolism and offers insights for engineering P450s.

Connecting conformational dynamics and epistasis has so far been limited to a few proteins and a single fitness trait. Here, the authors provide evidence of positive epistasis on multiple catalytic traits in the evolution and dynamics of engineered cytochrome P450 monooxygenase, offering insights for in silico protein design.

Community lifespan, niche expansion and the evolution of interspecific cooperation

Microbes live in dense and diverse communities where they deploy many traits that promote the growth and survival of neighbouring species, all the while also competing for shared resources. Because microbial communities are highly dynamic, the costs and benefits of species interactions change over the growth cycle of a community. How mutualistic interactions evolve under such demographic and ecological conditions is still poorly understood. Here, we develop an eco-evolutionary model to explore how different forms of helping with distinct fitness effects (rate-enhancing and yield-enhancing) affect the multiple phases of community growth, and its consequences for the evolution of mutualisms. We specifically focus on a form of yield-enhancing trait in which cooperation augments the common pool of resources, termed niche expansion. We show that although mutualisms in which cooperation increases partners growth rate are generally favoured at early stages of community growth, niche expansion can evolve at later stages where densities are high. Further, we find that niche expansion can promote the evolution of reproductive restraint, in which a focal species adaptively reduces its own growth rate to increase the density of partner species. Our findings suggest that yield-enhancing mutualisms are more prevalent in stable habitats with a constant supply of resources, and where populations typically live at high densities. In general, our findings highlight the need to integrate different components of population growth in the analysis of mutualisms to understand the composition and function of microbial communities.

Taxon-specific microbial growth and mortality patterns reveal distinct temporal population responses to rewetting in a California grassland soil

Microbial activity increases after rewetting dry soil, resulting in a pulse of carbon mineralization and nutrient availability. The biogeochemical responses to wet-up are reasonably well understood and known to be microbially mediated. Yet, the population level dynamics, and the resulting changes in microbial community patterns, are not well understood as ecological phenomena. Here, we used sequencing of 16S rRNA genes coupled with heavy water (H218O) DNA quantitative stable isotope probing to estimate population-specific rates of growth and mortality in response to a simulated wet-up event in a California annual grassland soil. Bacterial growth and mortality responded rapidly to wet-up, within 3 h, and continued throughout the 168 h incubation, with patterns of sequential growth observed at the phylum level. Of the 37 phyla detected in the prewet community, growth was found in 18 phyla while mortality was measured in 26 phyla. Rapid growth and mortality rates were measurable within 3 h of wet-up but had contrasting characteristics; growth at 3 h was dominated by select taxa within the Proteobacteria and Firmicutes, whereas mortality was taxonomically widespread. Furthermore, across the community, mortality exhibited density-independence, consistent with the indiscriminate shock resulting from dry-down and wet-up, whereas growth was density-dependent, consistent with control by competition or predation. Total aggregated growth across the community was highly correlated with total soil CO2 production. Together, these results illustrate how previously "invisible" population responses can translate quantitatively to emergent observations of ecosystem-scale biogeochemistry.

Evolution of Microbial Growth Traits Under Serial Dilution

Selection of mutants in a microbial population depends on multiple cellular traits. In serial-dilution evolution experiments, three key traits are the lag time when transitioning from starvation to growth, the exponential growth rate, and the yield (number of cells per unit resource). Here, we investigate how these traits evolve in laboratory evolution experiments using a minimal model of population dynamics, where the only interaction between cells is competition for a single limiting resource. We find that the fixation probability of a beneficial mutation depends on a linear combination of its growth rate and lag time relative to its immediate ancestor, even under clonal interference. The relative selective pressure on growth rate and lag time is set by the dilution factor; a larger dilution factor favors the adaptation of growth rate over the adaptation of lag time. The model shows that yield, however, is under no direct selection. We also show how the adaptation speeds of growth and lag depend on experimental parameters and the underlying supply of mutations. Finally, we investigate the evolution of covariation between these traits across populations, which reveals that the population growth rate and lag time can evolve a nonzero correlation even if mutations have uncorrelated effects on the two traits. Altogether these results provide useful guidance to future experiments on microbial evolution.

Molecular function limits divergent protein evolution on planetary timescales

Functional conservation is known to constrain protein evolution. Nevertheless, the long-term divergence patterns of proteins maintaining the same molecular function and the possible limits of this divergence have not been explored in detail. We investigate these fundamental questions by characterizing the divergence between ancient protein orthologs with conserved molecular function. Our results demonstrate that the decline of sequence and structural similarities between such orthologs significantly slows down after ~1-2 billion years of independent evolution. As a result, the sequence and structural similarities between ancient orthologs have not substantially decreased for the past billion years. The effective divergence limit (>25% sequence identity) is not primarily due to protein sites universally conserved in all linages. Instead, less than four amino acid types are accepted, on average, per site across orthologous protein sequences. Our analysis also reveals different divergence patterns for protein sites with experimentally determined small and large fitness effects of mutations.

Editorial note

This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Weak Chemical Interactions That Drive Protein Evolution: Crowding, Sticking, and Quinary Structure in Folding and Function

In recent years, better instrumentation and greater computing power have enabled the imaging of elusive biomolecule dynamics in cells, driving many advances in understanding the chemical organization of biological systems. The focus of this Review is on interactions in the cell that affect both biomolecular stability and function and modulate them. The same protein or nucleic acid can behave differently depending on the time in the cell cycle, the location in a specific compartment, or the stresses acting on the cell. We describe in detail the crowding, sticking, and quinary structure in the cell and the current methods to quantify them both in vitro and in vivo. Finally, we discuss protein evolution in the cell in light of current biophysical evidence. We describe the factors that drive protein evolution and shape protein interaction networks. These interactions can significantly affect the free energy, ΔG, of marginally stable and low-population proteins and, due to epistasis, direct the evolutionary pathways in an organism. We finally conclude by providing an outlook on experiments to come and the possibility of collaborative evolutionary biology and biophysical efforts.

Time Series Genome-Centric Analysis Unveils Bacterial Response to Operational Disturbance in Activated Sludge

Understanding ecosystem response to disturbances and identifying the most critical traits for the maintenance of ecosystem functioning are important goals for microbial community ecology. In this study, we used 16S rRNA amplicon sequencing and metagenomics to investigate the assembly of bacterial populations in a full-scale municipal activated sludge wastewater treatment plant over a period of 3 years, including a 9-month period of disturbance characterized by short-term plant shutdowns. Following the reconstruction of 173 metagenome-assembled genomes, we assessed the functional potential, the number of rRNA gene operons, and the in situ growth rate of microorganisms present throughout the time series. Operational disturbances caused a significant decrease in bacteria with a single copy of the rRNA (rrn) operon. Despite moderate differences in resource availability, replication rates were distributed uniformly throughout time, with no differences between disturbed and stable periods. We suggest that the length of the growth lag phase, rather than the growth rate, is the primary driver of selection under disturbed conditions. Thus, the system could maintain its function in the face of disturbance by recruiting bacteria with the capacity to rapidly resume growth under unsteady operating conditions.IMPORTANCE Disturbance is a key determinant of community assembly and dynamics in natural and engineered ecosystems. Microbiome response to disturbance is thought to be influenced by bacterial growth traits and life history strategies. In this time series observational study, the response to disturbance of microbial communities in a full-scale activated sludge wastewater treatment plant was assessed by computing specific cellular traits of genomes retrieved from metagenomes. It was found that the genomes observed in disturbed periods have more copies of the rRNA operon than genomes observed in stable periods, whereas the in situ mean relative growth rates of bacteria present during stable and disturbed periods were indistinguishable. From these intriguing observations, we infer that the length of the lag phase might be a growth trait that affects the microbial response to disturbance. Further exploration of this hypothesis could contribute to better understanding of the adaptive response of microbiomes to unsteady environmental conditions.

Substrate inhibition imposes fitness penalty at high protein stability

Proteins are only moderately stable. It has long been debated whether this narrow range of stabilities is solely a result of neutral drift toward lower stability or purifying selection against excess stability-for which no experimental evidence was found so far-is also at work. Here, we show that mutations outside the active site in the essential Escherichia coli enzyme adenylate kinase (Adk) result in a stability-dependent increase in substrate inhibition by AMP, thereby impairing overall enzyme activity at high stability. Such inhibition caused substantial fitness defects not only in the presence of excess substrate but also under physiological conditions. In the latter case, substrate inhibition caused differential accumulation of AMP in the stationary phase for the inhibition-prone mutants. Furthermore, we show that changes in flux through Adk could accurately describe the variation in fitness effects. Taken together, these data suggest that selection against substrate inhibition and hence excess stability may be an important factor determining stability observed for modern-day Adk.

Niche-specific metabolic adaptation in biotrophic and necrotrophic oomycetes is manifested in differential use of nutrients, variation in gene content, and enzyme evolution

The use of host nutrients to support pathogen growth is central to disease. We addressed the relationship between metabolism and trophic behavior by comparing metabolic gene expression during potato tuber colonization by two oomycetes, the hemibiotroph Phytophthora infestans and the necrotroph Pythium ultimum. Genes for several pathways including amino acid, nucleotide, and cofactor biosynthesis were expressed more by Ph. infestans during its biotrophic stage compared to Py. ultimum. In contrast, Py. ultimum had higher expression of genes for metabolizing compounds that are normally sequestered within plant cells but released to the pathogen upon plant cell lysis, such as starch and triacylglycerides. The transcription pattern of metabolic genes in Ph. infestans during late infection became more like that of Py. ultimum, consistent with the former's transition to necrotrophy. Interspecific variation in metabolic gene content was limited but included the presence of γ-amylase only in Py. ultimum. The pathogens were also found to employ strikingly distinct strategies for using nitrate. Measurements of mRNA, ¹⁵N labeling studies, enzyme assays, and immunoblotting indicated that the assimilation pathway in Ph. infestans was nitrate-insensitive but induced during amino acid and ammonium starvation. In contrast, the pathway was nitrate-induced but not amino acid-repressed in Py. ultimum. The lack of amino acid repression in Py. ultimum appears due to the absence of a transcription factor common to fungi and Phytophthora that acts as a nitrogen metabolite repressor. Evidence for functional diversification in nitrate reductase protein was also observed. Its temperature optimum was adapted to each organism's growth range, and its K_m was much lower in Py. ultimum. In summary, we observed divergence in patterns of gene expression, gene content, and enzyme function which contribute to the fitness of each species in its niche.

A key feature of disease is the pathogen's consumption of host metabolites to support its growth and multiplication. Understanding how host nutrients are used by pathogens may lead to strategies for limiting disease, for example by developing inhibitors of metabolic pathways needed for pathogen growth. Feeding strategies of plant pathogens range between two extremes: necrotrophs kill host cells and consume the released nutrients, while biotrophs do not injure host cells but instead acquire nutrients from extracellular spaces in the plant. In this study, a comparison was made between the metabolism of Phytophthora infestans (the infamous Irish Famine pathogen) and Pythium ultimum during potato tuber colonization. These microbes have close evolutionary histories, but while Py. ultimum is a necrotroph, Ph. infestans is a biotroph for most of the disease cycle. It was discovered that distinct patterns of metabolic gene expression, gene content, and enzyme behavior underlie these lifestyles. For example, genes for utilizing compounds that are normally stored within plant cells were expressed more by Py. ultimum, while Ph. infestans appeared to synthesize more biosubstances from precursors. Several differences in carbon and nitrogen metabolism were linked to variation in enzyme content and gene expression regulators in the two species.

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.

Trade-offs between microbial growth phases lead to frequency-dependent and non-transitive selection

Mutations in a microbial population can increase the frequency of a genotype not only by increasing its exponential growth rate, but also by decreasing its lag time or adjusting the yield (resource efficiency). The contribution of multiple life-history traits to selection is a critical question for evolutionary biology as we seek to predict the evolutionary fates of mutations. Here we use a model of microbial growth to show that there are two distinct components of selection corresponding to the growth and lag phases, while the yield modulates their relative importance. The model predicts rich population dynamics when there are trade-offs between phases: multiple strains can coexist or exhibit bistability due to frequency-dependent selection, and strains can engage in rock-paper-scissors interactions due to non-transitive selection. We characterize the environmental conditions and patterns of traits necessary to realize these phenomena, which we show to be readily accessible to experiments. Our results provide a theoretical framework for analysing high-throughput measurements of microbial growth traits, especially interpreting the pleiotropy and correlations between traits across mutants. This work also highlights the need for more comprehensive measurements of selection in simple microbial systems, where the concept of an ordinary fitness landscape breaks down.

Stochastic protein multimerization, activity, and fitness

Many proteins assemble into homomultimeric structures, with a number of subunits that can vary substantially among phylogenetic lineages. As protein-protein interactions require productive encounters among subunits, such variation might partially be explained by variation in cellular protein abundance. Protein abundance in turn depends on the intrinsic rates of production and decay of mRNA and protein molecules, as well as rates of cell growth and division. Using a stochastic framework for prediction of the multimeric state of a protein as a function of these processes and the free energy associated with interface-interface binding, we demonstrate agreement with a wide class of proteins using E. coli proteome data. As such, this platform, which links protein quaternary structure with biochemical rates governing gene expression, protein association and dissociation, and cell growth and division, can be extended to evolutionary models for the emergence and diversification of multimers. While it is tempting to think of multimerization as adaptive, the diversity of multimeric states raises the question of its functional role and impact on fitness. As a force driving selection, we consider the possible increase in enzymatic activity of proteins arising strictly as a consequence of interface-interface binding-namely, enhanced stability to degradation, substrate binding affinity, or catalytic rate of multimers with respect to monomers without invoking further conformational changes, as in allostery. For fixed cost of protein production, we find a benefit conferred by multimers that is dependent on context and can therefore become different in diverging lineages.

Deep scanning lysine metabolism in Escherichia coli

Our limited ability to predict genotype-phenotype relationships has called for strategies that allow testing of thousands of hypotheses in parallel. Deep scanning mutagenesis has been successfully implemented to map genotype-phenotype relationships at a single-protein scale, allowing scientists to elucidate properties that are difficult to predict. However, most phenotypes are dictated by several proteins that are interconnected through complex and robust regulatory and metabolic networks. These sophisticated networks hinder our understanding of the phenotype of interest and limit our capabilities to rewire cellular functions. Here, we leveraged CRISPR-EnAbled Trackable genome Engineering to attempt a parallel and high-resolution interrogation of complex networks, deep scanning multiple proteins associated with lysine metabolism in Escherichia coli We designed over 16,000 mutations to perturb this pathway and mapped their contribution toward resistance to an amino acid analog. By doing so, we identified different routes that can alter pathway function and flux, uncovering mechanisms that would be difficult to rationally design. This approach sets a framework for forward investigation of complex multigenic phenotypes.

Growth tradeoffs produce complex microbial communities on a single limiting resource

The relationship between the dynamics of a community and its constituent pairwise interactions is a fundamental problem in ecology. Higher-order ecological effects beyond pairwise interactions may be key to complex ecosystems, but mechanisms to produce these effects remain poorly understood. Here we model microbial growth and competition to show that higher-order effects can arise from variation in multiple microbial growth traits, such as lag times and growth rates, on a single limiting resource with no other interactions. These effects produce a range of ecological phenomena: an unlimited number of strains can exhibit multistability and neutral coexistence, potentially with a single keystone strain; strains that coexist in pairs do not coexist all together; and a strain that wins all pairwise competitions can go extinct in a mixed competition. Since variation in multiple growth traits is ubiquitous in microbial populations, our results indicate these higher-order effects may also be widespread, especially in laboratory ecology and evolution experiments.

Higher-order interactions occur when one species mediates the interaction between two others. Here, the authors model microbial growth and competition to show that higher-order interactions can arise from tradeoffs in growth traits, leading to neutral coexistence and other complex dynamics.

Accessibility of the Shine-Dalgarno Sequence Dictates N-Terminal Codon Bias in E. coli

Despite considerable efforts, no physical mechanism has been shown to explain N-terminal codon bias in prokaryotic genomes. Using a systematic study of synonymous substitutions in two endogenous E. coli genes, we show that interactions between the coding region and the upstream Shine-Dalgarno (SD) sequence modulate the efficiency of translation initiation, affecting both intracellular mRNA and protein levels due to the inherent coupling of transcription and translation in E. coli. We further demonstrate that far-downstream mutations can also modulate mRNA levels by occluding the SD sequence through the formation of non-equilibrium secondary structures. By contrast, a non-endogenous RNA polymerase that decouples transcription and translation largely alleviates the effects of synonymous substitutions on mRNA levels. Finally, a complementary statistical analysis of the E. coli genome specifically implicates avoidance of intra-molecular base pairing with the SD sequence. Our results provide general physical insights into the coding-level features that optimize protein expression in prokaryotes.

Growth and Extended Survival of Escherichia coli O157:H7 in Soil Organic Matter

Enterohaemorrhagic Escherichia coli, such as serotype O157:H7, are a leading cause of food-associated outbreaks. While the primary reservoir is associated with cattle, plant foods have been associated as sources of human infection. E. coli is able to grow in the tissue of food plants such as spinach. While fecal contamination is the primary suspect, soil has been underestimated as a potential reservoir. Persistence of bacterial populations in open systems is the product of growth, death, predation, and competition. Here we report that E. coli O157:H7 can grow using the soluble compounds in soil, and characterize the effect of soil growth on the stationary phase proteome. E. coli 933D (stxII⁻) was cultured in Soil Extracted Soluble Organic Matter (SESOM) and the culturable count determined for 24d. The proteomes of exponential and stationary phase populations were characterized by 2D gel electrophoresis and protein spots were identified by MALDI-TOF mass spectrometry. While LB controls displayed a death phase, SESOM grown population remained culturable for 24d, indicating an altered physiological state with superior longevity. This was not due to decreased cell density on entry to stationary phase as 24 h SESOM populations concentrated 10-fold retained their longevity. Principal component analysis showed that stationary phase proteomes from SESOM and LB were different. Differences included proteins involved in stress response, motility, membrane and wall composition, nutrient uptake, translation and protein turnover, and anabolic and catabolic pathways, indicating an altered physiological state of soil-grown cells entering stationary phase. The results suggest that E. coli may be a soil commensal that, in absence of predation and competition, maintains stable populations in soil.

Effect of cryopreservation and lyophilization on viability and growth of strict anaerobic human gut microbes

Strict anaerobic gut microbes have been suggested as ‘next‐generation probiotics’ for treating several intestinal disorders. The development of preservation techniques is of major importance for therapeutic application. This study investigated cryopreservation (−80°C) and lyophilization survival and storage stability (4°C for 3 months) of the strict anaerobic gut microbes Bacteroides thetaiotaomicron, Faecalibacterium prausnitzii, Roseburia intestinalis, Anaerostipes caccae, Eubacterium hallii and Blautia obeum. To improve preservation survival, protectants sucrose and inulin (both 5% w/v) were added for lyophilization and were also combined with glycerol (15% v/v) for cryopreservation. Bacterial fitness, evaluated by maximum growth rate and lag phase, viability and membrane integrity were determined using a standardized growth assay and by flow cytometry as markers for preservation resistance. Lyophilization was more detrimental to viability and fitness than cryopreservation, but led to better storage stability. Adding sucrose and inulin enhanced viability and the proportion of intact cells during lyophilization of all strains. Viability of protectant‐free B. thetaiotaomicron, A. caccae and F. prausnitzii was above 50% after cryopreservation and storage and increased to above 80% if protectants were present. The addition of glycerol, sucrose and inulin strongly enhanced the viability of B. obeum, E. hallii and R. intestinalis from 0.03–2% in protectant‐free cultures to 11–37%. This is the first study that quantitatively compared the effect of cryopreservation and lyophilization and the addition of selected protectants on viability and fitness of six strict anaerobic gut microbes. Our results suggest that efficiency of protectants is process‐ and species‐specific.

Gene Dosage Experiments in Enterobacteriaceae Using Arabinose-regulated Promoters

This protocol is used to assay the effect of protein over-expression on fitness of E. coli. It is based on a plasmid expression of a protein of interest from an arabinose-regulated pBAD promoter followed by the measurement of the intracellular protein abundance by Western blot along with the measurement of growth parameters of E. coli cell expressing this protein.