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Methylobacterium is a group of methylotrophic microbes associated with soil, fresh water, and particularly the phyllosphere, the aerial part of plants that has been well-studied in terms of physiology but whose evolutionary history and taxonomy are unclear. Recent work has suggested that Methylobacterium is much more diverse than thought previously, questioning its status as an ecologically and phylogenetically coherent taxonomic genus. However, taxonomic and evolutionary studies of Methylobacterium have mostly been restricted to model species, often isolated from habitats other than the phyllosphere, and have yet to utilize comprehensive phylogenomic methods to examine gene trees, gene content, or synteny. By analyzing 189 Methylobacterium genomes from a wide range of habitats, including the phyllosphere, we inferred a robust phylogenetic tree while explicitly accounting for the impact of horizontal gene transfers. We showed that Methylobacterium contains four evolutionary distinct groups of bacteria (namely A, B, C, D), characterized by different genome size, GC content, gene content and genome architecture, revealing the dynamic nature of Methylobacterium genomes. In addition of recovering 59 described species, we identified 45 candidate species, mostly phyllosphere-associated, stressing the significance of plants as a reservoir of Methylobacterium diversity. We inferred an ancient transition from a free-living lifestyle to association with plant roots in Methylobacteriaceae ancestor, followed by phyllosphere association of three of the major groups (A, B, D), which early branching in Methylobacterium history was heavily obscured by HGT. Together, our work lays the foundations for a thorough redefinition of Methylobacterium taxonomy, beginning with the abandon of Methylorubrum.

Methylothon is an inquiry-based high school learning module in microbial ecology, molecular biology, and bioinformatics that centers around pink-pigmented plant-associated methylotrophic bacteria. Here we present an overview of the module’s learning goals, describe course resources (available for public use on http://methylothon.com), and relate lessons learned from adapting Methylothon for remote learning during the pandemic in spring of 2021. The original in-person version of the module allows students to isolate their own strains of methylotrophic bacteria from plants they sample from the environment, to identify these using PCR, sequencing, and phylogenetic analysis, and to contribute their strains to original research in a university lab. The adapted version strengthens the focus on bioinformatics and increases its flexibility and accessibility by making the lab portion optional and adopting free web-based tools. Student feedback and graded assignments from Spring 2021 revealed that the lesson was especially effective at introducing the concepts of BLAST and phylogenetic trees, and that students valued and felt inspired by the opportunity to conduct hands-on work and to participate in community science.

A population under selection to improve one trait may evolve a sub-optimal state for another trait due to tradeoffs and other evolutionary constraints. How this evolution affects the capacity of a population to adapt when conditions change to favor the second trait is an open question. We investigated this question using isolates from a lineage spanning 60,000 generations of the Long-Term Evolution Experiment (LTEE) with Escherichia coli, where cells have access to a shared pool of resources, and have evolved increased competitive ability and a concomitant reduction in numerical yield. Using media-in oil emulsions we shifted the focus of selection to numerical yield, where cells grew in isolated patches with private resources. We found that the time spent evolving under shared resources did not affect the ability to re-evolve toward higher numerical yield. The evolution of numerical yield commonly occurred through mutations in the phosphoenolpyruvate phosphotransferase system. These mutants exhibit slower uptake of glucose, making them poorer competitors for public resources, and produce smaller cells that release less carbon as overflow metabolites. Our results demonstrate that mutations that were not part of adaptation under one selective regime may enable access to ancestral phenotypes when selection changes to favor evolutionary reversion.

Methylobacterium is a prevalent bacterial genus of the phyllosphere. Despite its ubiquity, little is known about the extent to which its diversity reflects neutral processes like migration and drift, versus environmental filtering of life history strategies and adaptations. In two temperate forests, we investigated how phylogenetic diversity within Methylobacterium was structured by biogeography, seasonality, and growth strategies. Using deep, culture-independent barcoded marker gene sequencing coupled with culture-based approaches, we uncovered a considerable diversity of Methylobacterium in the phyllosphere. We cultured different subsets of Methylobacterium lineages depending upon the temperature of isolation and growth (20 °C or 30 °C), suggesting long-term adaptation to temperature. To a lesser extent than temperature adaptation, Methylobacterium diversity was also structured across large (>100km; between forests) and small geographical scales (Methylobacterium is phylogenetically structured into lineages with distinct growth strategies, which helps explain their differential abundance across regions, host tree species, and time. This works paves the way for further investigation of adaptive strategies and traits within a ubiquitous phyllosphere genus.ImportanceMethylobacterium is a bacterial group tied to plants. Despite its ubiquity and importance to their hosts, little is known about the processes driving Methylobacterium community dynamics. By combining traditional culture-dependent and independent (metabarcoding) approaches, we monitored Methylobacterium diversity in two temperate forests over a growing season. On the surface of tree leaves, we discovered remarkably diverse and dynamic Methylobacterium communities over short temporal (from June to October) and spatial scales (within 1.2 km). Because we cultured different subsets of Methylobacterium diversity depending on the temperature of incubation, we suspected that these dynamics partly reflected climatic adaptation. By culturing strains in lab conditions mimicking seasonal variations, we found that diversity and environmental variations were indeed good predictors of Methylobacterium growth performances. Our findings suggest that Methylobacterium community dynamics at the surface of tree leaves results from the succession of strains with contrasted growth strategies in response to environmental variations.

Understanding the evolution of novel physiological traits is highly relevant for expanding the characterization and manipulation of biological systems. Acquisition of new traits can be achieved through horizontal gene transfer (HGT). Here, we investigate drivers that promote or deter the maintenance of HGT-driven degeneracy, occurring when processes accomplish identical functions through nonidentical components. Subsequent evolution can optimize newly acquired functions; for example, beneficial alleles identified in an engineered Methylorubrum extorquens strain allowed it to utilize a “Foreign” formaldehyde oxidation pathway substituted for its Native pathway for methylotrophic growth. We examined the fitness consequences of interactions between these alleles when they were combined with the Native pathway or both (Dual) pathways. Unlike the Foreign pathway context where they evolved, these alleles were often neutral or deleterious when moved into these alternative genetic backgrounds. However, there were instances where combinations of multiple alleles resulted in higher fitness outcomes than individual allelic substitutions could provide. Importantly, the genetic context accompanying these allelic substitutions significantly altered the fitness landscape, shifting local fitness peaks and restricting the set of accessible evolutionary trajectories. These findings highlight how genetic context can negatively impact the probability of maintaining native and HGT-introduced functions together, making it difficult for degeneracy to evolve. However, in cases where the cost of maintaining degeneracy was mitigated by adding evolved alleles impacting the function of these pathways, we observed rare opportunities for pathway coevolution to occur. Together, our results highlight the importance of genetic context and resulting epistasis in retaining or losing HGT-acquired degenerate functions.

For bacteria to thrive they must be well-adapted to their environmental niche, which may involve specialized metabolism, timely adaptation to shifting environments, and/or the ability to mitigate numerous stressors. These attributes are highly dependent on cellular machinery that can sense both the external and intracellular environment. Methylorubrum extorquens is an extensively studied facultative methylotroph, an organism that can use single-carbon compounds as their sole source of carbon and energy. In methylotrophic metabolism, carbon flows through formaldehyde as a central metabolite; thus, formaldehyde is both an obligate metabolite and a metabolic stressor. Via the one-carbon dissimilation pathway, free formaldehyde is rapidly incorporated by formaldehyde activating enzyme (Fae), which is constitutively expressed at high levels. In the presence of elevated formaldehyde levels, a recently identified formaldehyde-sensing protein, EfgA, induces growth arrest. Herein, we describe TtmR, a formaldehyde-responsive transcription factor that, like EfgA, modulates formaldehyde resistance. TtmR is a member of the MarR family of transcription factors and impacts the expression of 75 genes distributed throughout the genome, many of which are transcription factors and/or involved in stress response, including efgA. Notably, when M. extorquens is adapting its metabolic network during the transition to methylotrophy, efgA and ttmR mutants experience an imbalance in formaldehyde production and a notable growth delay. Although methylotrophy necessitates that M. extorquens maintain a relatively high level of formaldehyde tolerance, this work reveals a tradeoff between formaldehyde resistance and the efficient transition to methylotrophic growth and suggests that TtmR and EfgA play a pivotal role in maintaining this balance.ImportanceAll organisms produce formaldehyde as a byproduct of enzymatic reactions and as a degradation product of metabolites. The ubiquity of formaldehyde in cellular biology suggests all organisms have evolved mechanisms of mitigating formaldehyde toxicity. However, formaldehyde-sensing is poorly described and prevention of formaldehyde-induced damage is primarily understood in the context of detoxification. Here we use an organism that is regularly exposed to elevated intracellular formaldehyde concentrations through high-flux one-carbon utilization pathways to gain insight into the role of formaldehyde-responsive proteins that modulate formaldehyde resistance. Using a combination of genetic and transcriptomic analyses, we identify dozens of genes putatively involved in formaldehyde resistance, determined the relationship between two different formaldehyde response systems and identified an inherent tradeoff between formaldehyde resistance and optimal transition to methylotrophic metabolism.

For bacteria to thrive, they must be well adapted to their environmental niche, which may involve specialized metabolism, timely adaptation to shifting environments, and/or the ability to mitigate numerous stressors. These attributes are highly dependent on cellular machinery that can sense both the external and intracellular environment. Methylorubrum extorquens is an extensively studied facultative methylotroph, an organism that can use single-carbon compounds as its sole source of carbon and energy. In methylotrophic metabolism, carbon flows through formaldehyde as a central metabolite; thus, formaldehyde is both an obligate metabolite and a metabolic stressor. Via the one-carbon dissimilation pathway, free formaldehyde is rapidly incorporated by formaldehyde activating enzyme (Fae), which is constitutively expressed at high levels. In the presence of elevated formaldehyde levels, a recently identified formaldehyde-sensing protein, EfgA, induces growth arrest. Here, we describe TtmR, a formaldehyde-responsive transcription factor that, like EfgA, modulates formaldehyde resistance. TtmR is a member of the MarR family of transcription factors and impacts the expression of 75 genes distributed throughout the genome, of which many encode transcription factors and/or are involved in stress response, including efgA. Notably, when M. extorquens is adapting its metabolic network during the transition to methylotrophy, efgA and ttmR mutants experience an imbalance in formaldehyde production and a notable growth delay. Although methylotrophy necessitates that M. extorquens maintains a relatively high level of formaldehyde tolerance, this work reveals a trade-off between formaldehyde resistance and the efficient transition to methylotrophic growth and suggests that TtmR and EfgA play a pivotal role in maintaining this balance. IMPORTANCE All organisms produce formaldehyde as a by-product of enzymatic reactions and as a degradation product of metabolites. The ubiquity of formaldehyde in cellular biology suggests that all organisms have evolved mechanisms of mitigating formaldehyde toxicity. However, formaldehyde sensing is poorly described, and the prevention of formaldehyde-induced damage is understood primarily in the context of detoxification. Here, we used an organism that is regularly exposed to elevated intracellular formaldehyde concentrations through high-flux one-carbon utilization pathways to gain insight into the role of formaldehyde-responsive proteins that modulate formaldehyde resistance. Using a combination of genetic and transcriptomic analyses, we identified dozens of genes putatively involved in formaldehyde resistance, determined the relationship between two different formaldehyde response systems, and identified an inherent trade-off between formaldehyde resistance and optimal transition to methylotrophic metabolism.

The recalcitrance of complex organic polymers such as lignocellulose is one of the major obstacles to sustainable energy production from plant biomass, and the generation of toxic intermediates can negatively impact the efficiency of microbial lignocellulose degradation. Here, we describe the development of a model microbial consortium for studying lignocellulose degradation, with the specific goal of mitigating the production of the toxin formaldehyde during the breakdown of methoxylated aromatic compounds. Included are Pseudomonas putida, a lignin degrader, Cellulomonas fimi, a cellulose degrader, and sometimes Yarrowia lipolytica, an oleaginous yeast. Unique to our system is the inclusion of Methylorubrum extorquens, a methylotroph capable of using formaldehyde for growth. We developed a defined minimal “Model Lignocellulose” growth medium for reproducible coculture experiments. We demonstrated that the formaldehyde produced by P. putida growing on vanillic acid can exceed the minimum inhibitory concentration for C. fimi, and, furthermore, that the presence of M. extorquens lowers those concentrations. We also uncovered unexpected ecological dynamics, including resource competition, and interspecies differences in growth requirements and toxin sensitivities. Finally, we introduced the possibility for a mutualistic interaction between C. fimi and M. extorquens through metabolite exchange. This study lays the foundation to enable future work incorporating metabolomic analysis and modeling, genetic engineering, and laboratory evolution, on a model system that is appropriate both for fundamental eco-evolutionary studies and for the optimization of efficiency and yield in microbially-mediated biomass transformation.

Fitness landscapes are often invoked to interpret the effects of allele substitutions and their interactions; however, evolution also includes larger changes like gene loss and acquisition. Previous work with the methylotrophic bacterium Methylorubrum extorquens AM1 identified strongly beneficial mutations in a strain evolved to utilize a novel, Foreign pathway in place of its native central metabolic pathway for growth on methanol. These mutations were consistently beneficial, regardless of the order in which they arose. Here we extend this analysis to consider loss or acquisition of metabolic pathways by examining strains relying upon either the Native pathway, or both (‘Dual’) pathways present. Unlike in the Foreign pathway context in which they evolved, these alleles were often deleterious in these alternative genetic backgrounds, following patterns that were strongly contingent on the specific pathways and other evolved alleles present. Landscapes for these alternative pathway backgrounds altered which genotypes correspond to local fitness peaks and would restrict the set of accessible evolutionary trajectories. These epistatic interactions negatively impact the probability of maintaining multiple degenerate pathways, making it more difficult for these pathways to coevolve. Together, our results highlight the uncertainty of retaining novel functions acquired via horizontal gene transfer (HGT), and that the potential for cells to either adopt novel functions or to maintain degenerate pathways together in a genome is heavily dependent upon the underlying epistatic interactions between them.Author SummaryThe evolution of physiology in microbes has important impacts ranging from global cycling of elements to the emergence and spread of pathogens and their resistance to antibiotics. While genetic interactions between mutations in evolving lineages of microbes have been investigated, these have not included the acquisition of novel genes on elements like plasmids, and thus how these elements interact with existing alleles. The dynamics of novel gene retention are of interest from both positive (e.g., biotechnology) and negative (e.g., antimicrobial resistance) practical impacts. We find that the patterns of interactions between evolved alleles appear substantially different, and generally much less positive, when moved into novel genetic backgrounds. Additionally, these preexisting alleles were found to have strong impacts on the ability of genotypes to maintain – and in rare cases coevolve with – novel genes and pathways. These results show that even though they evolved separately, the particular alleles in a genetic background, and importantly the physiological impacts they confer, weigh heavily on whether genes for novel metabolic processes are maintained.

Normal cellular processes give rise to toxic metabolites that cells must mitigate. Formaldehyde is a universal stressor and potent metabolic toxin that is generated in organisms from bacteria to humans. Methylotrophic bacteria such asMethylorubrum extorquensface an acute challenge due to their production of formaldehyde as an obligate central intermediate of single-carbon metabolism. Mechanisms to sense and respond to formaldehyde were speculated to exist in methylotrophs for decades but had never been discovered. Here we identify a member of the DUF336 domain family, namedefgAfor enhanced formaldehyde growth, that plays an important role in endogenous formaldehyde stress response inM. extorquensPA1 and is found almost exclusively in methylotrophic taxa. Our experimental analyses reveal that EfgA is a formaldehyde sensor that inhibits translation in response to elevated levels of formaldehyde. Heterologous expression of EfgA inEscherichia coliincreases formaldehyde resistance, indicating that its interaction partners are widespread and conserved and may include translational machinery. EfgA represents the first example of a formaldehyde stress response system that does not involve enzymatic detoxification. Thus, EfgA comprises a unique stress response mechanism in bacteria, whereby a single protein directly senses elevated levels of a toxic intracellular metabolite and modulates translational activity.

Significance Organisms frequently exchange costly resources with other species. Theory suggests that this paradoxical cooperation between species might have its origins in waste consumption. When a species benefits from the waste of another, the recipient can evolve to aid the waste producer. The waste producer could then be selected to provide costly resources in return. We previously demonstrated the first step of this theorized process: Salmonella enterica evolved to secrete a costly amino acid to increase access to a byproduct generated by Escherichia coli. Here, we provide demonstration of a waste producer switching to costly cooperation. E. coli repeatedly evolved novel secretion of sugar to feed S. enterica. The results validate long-standing theory about the evolutionary origins of costly mutualism., Mutualisms are essential for life, yet it is unclear how they arise. A two-stage process has been proposed for the evolution of mutualisms that involve exchanges of two costly resources. First, costly provisioning by one species may be selected for if that species gains a benefit from costless byproducts generated by a second species, and cooperators get disproportionate access to byproducts. Selection could then drive the second species to provide costly resources in return. Previously, a synthetic consortium evolved the first stage of this scenario: Salmonella enterica evolved costly production of methionine in exchange for costless carbon byproducts generated by an auxotrophic Escherichia coli. Growth on agar plates localized the benefits of cooperation around methionine-secreting S. enterica. Here, we report that further evolution of these partners on plates led to hypercooperative E. coli that secrete the sugar galactose. Sugar secretion arose repeatedly across replicate communities and is costly to E. coli producers, but enhances the growth of S. enterica. The tradeoff between individual costs and group benefits led to maintenance of both cooperative and efficient E. coli genotypes in this spatially structured environment. This study provides an experimental example of de novo, bidirectional costly mutualism evolving from byproduct consumption. The results validate the plausibility of costly cooperation emerging from initially costless exchange, a scenario widely used to explain the origin of the mutualistic species interactions that are central to life on Earth.

Normal cellular processes give rise to toxic metabolites that cells must mitigate. Formaldehyde is a universal stressor and potent metabolic toxin that is generated in organisms from bacteria to humans. Methylotrophic bacteria such as Methylorubrum extorquens face an acute challenge due to their production of formaldehyde as an obligate central intermediate of single-carbon metabolism. Mechanisms to sense and respond to formaldehyde were speculated to exist in methylotrophs for decades but had never been discovered. Here, we identify a member of the DUF336 domain family, named efgA for enhanced formaldehyde growth, that plays an important role in endogenous formaldehyde stress response in M. extorquens PA1 and is found almost exclusively in methylotrophic taxa. Our experimental analyses reveal that EfgA is a formaldehyde sensor that rapidly arrests growth in response to elevated levels of formaldehyde. Heterologous expression of EfgA in Escherichia coli increases formaldehyde resistance, indicating that its interaction partners are widespread and conserved. EfgA represents the first example of a formaldehyde stress response system that does not involve enzymatic detoxification. Thus, EfgA comprises a unique stress response mechanism in bacteria, whereby a single protein directly senses elevated levels of a toxic intracellular metabolite and safeguards cells from potential damage., The known formaldehyde stress response systems involve enzymatic detoxification. Here, the authors show that the formaldehyde sensor efgA plays an important role in the endogenous formaldehyde stress response in Methylorubrum extorquens, halting cell growth in response to elevated levels of formaldehyde, and is found almost exclusively in methylotrophic taxa.

Pink-pigmented facultative methylotrophs have long been studied for their ability to grow on reduced single-carbon (C1) compounds. The C1 groups that support methylotrophic growth may come from a variety of sources. Here, we describe a group of Methylobacterium strains that can engage in methoxydotrophy: they can metabolize the methoxy groups from several aromatic compounds that are commonly the product of lignin depolymerization. In addition, these organisms can utilize the full aromatic ring as a growth substrate, a phenotype that has rarely been described in Methylobacterium. We demonstrated growth on p-hydroxybenzoate, protocatechuate, vanillate, and ferulate in laboratory culture conditions. We also used comparative genomics to explore the evolutionary history of this trait, finding that the capacity for aromatic catabolism is likely ancestral to two clades of Methylobacterium, but has also been acquired horizontally by closely related organisms. In addition, we surveyed the published metagenome data to find that the most abundant group of aromatic-degrading Methylobacterium in the environment is likely the group related to M. nodulans, and they are especially common in soil and root environments. The demethoxylation of lignin-derived aromatic monomers in aerobic environments releases formaldehyde, a metabolite that is a potent cellular toxin but that is also a growth substrate for methylotrophs. We found that, whereas some known lignin-degrading organisms excrete formaldehyde as a byproduct during growth on vanillate, Methylobacterium do not. This observation is especially relevant to our understanding of the ecology and the bioengineering of lignin degradation.

Experimental evolution has become an increasingly common approach for studying evolutionary phenomena, as well as uncovering physiological connections in a manner complementary to traditional genetics. Here I describe the development of Methylobacterium as a model system for using experimental evolution to study questions at the intersection of metabolism and evolution. Each experiment was initiated to address a particular question inspired by patterns in natural methylotrophs, such as tradeoffs between single-carbon and multi-carbon growth, or the challenges involved in incorporating novel metabolic pathways or genes with poor codon usage that are acquired via horizontal gene transfer. What I could not have appreciated initially, however, was just how many fortuitous surprise findings would emerge. These have ranged from the repeatability of evolution, complex dynamics within populations, epistasis between beneficial mutations, and even the ability to use simple mathematical models to generate testable, quantitative hypotheses about the fitness landscape.

While microbiologists often make the simplifying assumption that genotype determines phenotype in a given environment, it is becoming increasingly apparent that phenotypic heterogeneity (in which one genotype generates multiple phenotypes simultaneously even in a uniform environment) is common in many microbial populations. The importance of phenotypic heterogeneity has been demonstrated in a number of model systems involving binary phenotypic states (e.g., growth/non-growth); however, less is known about systems involving phenotype distributions that are continuous across an environmental gradient, and how those distributions change when the environment changes. Here, we describe a novel instance of phenotypic diversity in tolerance to a metabolic toxin within wild-type populations of Methylobacterium extorquens, a ubiquitous phyllosphere methylotroph capable of growing on the methanol periodically released from plant leaves. The first intermediate in methanol metabolism is formaldehyde, a potent cellular toxin that is lethal in high concentrations. We have found that at moderate concentrations, formaldehyde tolerance in M. extorquens is heterogeneous, with a cell’s minimum tolerance level ranging between 0 mM and 8 mM. Tolerant cells have a distinct gene expression profile from non-tolerant cells. This form of heterogeneity is continuous in terms of threshold (the formaldehyde concentration where growth ceases), yet binary in outcome (at a given formaldehyde concentration, cells either grow normally or die, with no intermediate phenotype), and it is not associated with any detectable genetic mutations. Moreover, tolerance distributions within the population are dynamic, changing over time in response to growth conditions. We characterized this phenomenon using bulk liquid culture experiments, colony growth tracking, flow cytometry, single-cell time-lapse microscopy, transcriptomics, and genome resequencing. Finally, we used mathematical modeling to better understand the processes by which cells change phenotype, and found evidence for both stochastic, bidirectional phenotypic diversification and responsive, directed phenotypic shifts, depending on the growth substrate and the presence of toxin. Author Summary Scientists tend to appreciate microbes for their simplicity and predictability: a population of genetically identical cells inhabiting a uniform environment is expected to behave in a uniform way. However, counter-examples to this assumption are frequently being discovered, forcing a re-examination of the relationship between genotype and phenotype. In most such examples, bacterial cells are found to split into two discrete populations, for instance growing and non-growing. Here, we report the discovery of a novel example of microbial phenotypic heterogeneity in which cells are distributed along a gradient of phenotypes, ranging from low to high tolerance of a toxic chemical. Furthermore, we demonstrate that the distribution of phenotypes changes in different growth conditions, and we use mathematical modeling to show that cells may change their phenotype either randomly or in a particular direction in response to the environment. Our work expands our understanding of how a bacterial cell’s genome, family history, and environment all contribute to its behavior, with implications for the diverse situations in which we care to understand the growth of any single-celled populations.

Mutualism is ubiquitous in nature and plays an integral role in most communities. To predict the eco-evolutionary dynamics of mutualism it is critical to extend classic pair-wise analysis to include additional species. We investigated the effect of adding a third species to a pair-wise mutualism in a spatially structured environment. We tested the hypotheses that selection for costly excretions in a focal population (i) decreases when an exploiter is added (ii) increases when a third mutualist is added relative to the pair-wise scenario. We assayed the selection acting on Salmonella enterica when it exchanges methionine for carbon in an obligate mutualism with an auxotrophic Escherichia coli. A third bacterium, Methylobacterium extorquens, was then added and acted either as an exploiter of the carbon or third obligate mutualist depending on the nitrogen source. In the tripartite mutualism M. extorquens provided nitrogen to the other species. Contrary to our expectations, adding an exploiter increased selection for methionine excretion in S. enterica. Conversely, selection for cooperation was lower in the tripartite mutualism relative to the pair-wise system. Genome-scale metabolic models helped identify the mechanisms underlying these changes in selection. Our results highlight the utility of connecting metabolic mechanisms and eco-evolutionary dynamics.

Microorganisms often encode multiple non-orthologous metabolic modules that catalyze the same reaction. However, little experimental evidence actually demonstrates a selective basis for metabolic degeneracy. Many methylotrophs-microorganisms that grow on reduced single-carbon compounds-like Methylobacterium extorquens AM1 encode two routes for methylamine oxidation: the periplasmic methylamine dehydrogenase (MaDH) and the cytoplasmic N-methylglutamate (NMG) pathway. In Methylobacterium extorquens AM1, MaDH is essential for methylamine growth, but the NMG pathway has no known physiological role. Here, we use experimental evolution of two isolates lacking (or incapable of using) MaDH to uncover the physiological challenges that need to be overcome in order to use the NMG pathway for growth on methylamine as a carbon and energy source. Physiological characterization of the evolved isolates revealed regulatory rewiring to increase expression of the NMG pathway and novel mechanisms to mitigate cytoplasmic ammonia buildup. These adaptations led us to infer and validate environmental conditions under which the NMG pathway is advantageous compared to MaDH. The highly expressed MaDH enables rapid growth on high concentrations of methylamine as the primary carbon and energy substrate, whereas the energetically expensive NMG pathway plays a pivotal role during growth with methylamine as the sole nitrogen source, which we demonstrate is especially true under limiting concentrations (1 mM). Tradeoffs between cellular localization and ammonium toxicity lead to selection for this apparent degeneracy as it is beneficial to facultative methylotrophs that have to switch between using methylamine as a carbon and energy source or just a nitrogen source.

While microbiologists often make the simplifying assumption that genotype determines phenotype in a given environment, it is becoming increasingly apparent that phenotypic heterogeneity (in which one genotype generates multiple phenotypes simultaneously even in a uniform environment) is common in many microbial populations. The importance of phenotypic heterogeneity has been demonstrated in a number of model systems involving binary phenotypic states (e.g., growth/non-growth); however, less is known about systems involving phenotype distributions that are continuous across an environmental gradient, and how those distributions change when the environment changes. Here, we describe a novel instance of phenotypic diversity in tolerance to a metabolic toxin within wild-type populations of Methylobacterium extorquens, a ubiquitous phyllosphere methylotroph capable of growing on the methanol periodically released from plant leaves. The first intermediate in methanol metabolism is formaldehyde, a potent cellular toxin that is lethal in high concentrations. We have found that at moderate concentrations, formaldehyde tolerance in M. extorquens is heterogeneous, with a cell's minimum tolerance level ranging between 0 mM and 8 mM. Tolerant cells have a distinct gene expression profile from non-tolerant cells. This form of heterogeneity is continuous in terms of threshold (the formaldehyde concentration where growth ceases), yet binary in outcome (at a given formaldehyde concentration, cells either grow normally or die, with no intermediate phenotype), and it is not associated with any detectable genetic mutations. Moreover, tolerance distributions within the population are dynamic, changing over time in response to growth conditions. We characterized this phenomenon using bulk liquid culture experiments, colony growth tracking, flow cytometry, single-cell time-lapse microscopy, transcriptomics, and genome resequencing. Finally, we used mathematical modeling to better understand the processes by which cells change phenotype, and found evidence for both stochastic, bidirectional phenotypic diversification and responsive, directed phenotypic shifts, depending on the growth substrate and the presence of toxin., Author summary Scientists tend to appreciate microbes for their simplicity and predictability: a population of genetically identical cells inhabiting a uniform environment is expected to behave in a uniform way. However, counter-examples to this assumption are frequently being discovered, forcing a re-examination of the relationship between genotype and phenotype. In most such examples, bacterial cells are found to split into two discrete populations, for instance growing and non-growing. Here, we report the discovery of a novel example of microbial phenotypic heterogeneity in which cells are distributed along a gradient of phenotypes, ranging from low to high tolerance of a toxic chemical. Furthermore, we demonstrate that the distribution of phenotypes changes in different growth conditions, and we use mathematical modeling to show that cells may change their phenotype either randomly or in a particular direction in response to the environment. Our work expands our understanding of how a bacterial cell's genome, family history, and environment all contribute to its behavior, with implications for the diverse situations in which we care to understand the growth of any single-celled populations.

Microbes in the same community but with distinct niches can have unique long stretches of perfect sequence identity due to recent genetic exchange. Arevalo et al. (2019) use this as a starting point for defining ecologically-relevant populations within a community and to identify the genes that appear to be driving divergence between populations.

Bioengineering holds great promise to provide fast and efficient biocatalysts for methanol-based biotechnology, but necessitates proven methods to optimize physiology in engineered strains. Here, we highlight experimental evolution as an effective means for optimizing an engineered Methylobacterium extorquens AM1. Replacement of the native formaldehyde oxidation pathway with a functional analog substantially decreased growth in an engineered Methylobacterium, but growth rapidly recovered after six hundred generations of evolution on methanol. We used whole-genome sequencing to identify the basis of adaptation in eight replicate evolved strains, and examined genomic changes in light of other growth and physiological data. We observed great variety in the numbers and types of mutations that occurred, including instances of parallel mutations at targets that may have been “rationalized” by the bioengineer, plus other “illogical” mutations that demonstrate the ability of evolution to expose unforeseen optimization solutions. Notably, we investigated mutations to RNA polymerase, which provided a massive growth benefit but are linked to highly aberrant transcriptional profiles. Overall, we highlight the power of experimental evolution to present genetic and physiological solutions for strain optimization, particularly in systems where the challenges of engineering are too many or too difficult to overcome via traditional engineering methods.

Natural environments are filled with multiple, often competing, signals. In contrast, biological systems are often studied in "well-controlled" environments where only a single input is varied, potentially missing important interactions between signals. Catabolite repression of galactose by glucose is one of the best-studied eukaryotic signal integration systems. In this system, it is believed that galactose metabolic (GAL) genes are induced only when glucose levels drop below a threshold. In contrast, we show that GAL gene induction occurs at a constant external galactose:glucose ratio across a wide range of sugar concentrations. We systematically perturbed the components of the canonical galactose/glucose signaling pathways and found that these components do not account for ratio sensing. Instead we provide evidence that ratio sensing occurs upstream of the canonical signaling pathway and results from the competitive binding of the two sugars to hexose transporters. We show that a mutant that behaves as the classical model expects (i.e., cannot use galactose above a glucose threshold) has a fitness disadvantage compared with wild type. A number of common biological signaling motifs can give rise to ratio sensing, typically through negative interactions between opposing signaling molecules. We therefore suspect that this previously unidentified nutrient sensing paradigm may be common and overlooked in biology.

Bacteria increase their metabolic capacity via the acquisition of genetic material or by the mutation of genes already present in the genome. Here, we explore the mechanisms and trade-offs involved when Shewanella oneidensis , a bacterium that typically consumes small organic and amino acids, rapidly evolves to expand its metabolic capacity to catabolize glucose after a short period of adaptation to a glucose-rich environment. Using whole-genome sequencing and genetic approaches, we discovered that deletions in a region including the transcriptional repressor ( nagR ) that regulates the expression of genes associated with catabolism of N -acetylglucosamine are the common basis for evolved glucose metabolism across populations. The loss of nagR results in the constitutive expression of genes for an N -acetylglucosamine permease ( nagP ) and kinase ( nagK ). We demonstrate that promiscuous activities of both NagP and NagK toward glucose allow for the transport and phosphorylation of glucose to glucose-6-phosphate, the initial events of glycolysis otherwise thought to be absent in S. oneidensis . 13 C-based metabolic flux analysis uncovered that subsequent utilization was mediated by the Entner-Doudoroff pathway. This is an example whereby gene loss and preexisting enzymatic promiscuity, and not gain-of-function mutations, were the drivers of increased metabolic capacity. However, we observed a significant decrease in the growth rate on lactate after adaptation to glucose catabolism, suggesting that trade-offs may explain why glycolytic function may not be readily observed in S. oneidensis in natural environments despite it being readily accessible through just a single mutational event. IMPORTANCE Gains in metabolic capacity are frequently associated with the acquisition of novel genetic material via natural or engineered horizontal gene transfer events. Here, we explored how a bacterium that typically consumes small organic acids and amino acids expands its metabolic capacity to include glucose via a loss of genetic material, a process frequently associated with a deterioration of metabolic function. Our findings highlight how the natural promiscuity of transporters and enzymes can be a key driver in expanding metabolic diversity and that many bacteria may possess a latent metabolic capacity accessible through one or a few mutations that remove regulatory functions. Our discovery of trade-offs between growth on lactate and on glucose suggests why this easily gained trait is not observed in nature.

The human population is growing and, globally, we must meet the challenge of increased protein needs required to feed this population. Single cell proteins (SCP), when coupled to aquaculture production, offer a means to ensure future protein needs can be met without direct competition with food for people. To demonstrate a given type of SCP has potential as a protein source for use in aquaculture feed, a number of steps need to be validated including demonstrating that the SCP is accepted by the species in question, leads to equivalent survival and growth, does not result in illness or other maladies, is palatable to the consumer, is cost effective to produce and can easily be incorporated into diets using existing technology. Here we examine white shrimp (Litopenaeus vannamei) growth and consumer taste preference, smallmouth grunt (Haemulon chrysargyreum) growth, survival, health and gut microbiota, and Atlantic salmon (Salmo salar) digestibility when fed diets that substitute the bacteriumMethylobacterium extorquensat a level of 30% (grunts), 100% (shrimp), or 55% (salmon) of the fishmeal in a compound feed.In each of these tests, animals performed equivalently when fed diets containingM. extorquensas when fed a standard aquaculture diet. This transdisciplinary approach is a first validation of this bacterium as a potential SCP protein substitute in aquafeeds. Given the ease to produce this SCP through an aerobic fermentation process, the broad applicability for use in aquaculture indicates the promise ofM. extorquensin leading toward greater food security in the future.

Vibrio natriegenshas recently emerged as an alternative toEscherichia colifor molecular biology and biotechnology, but low-efficiency genetic tools hamper its development. Here, we uncover how to induce natural competence inV. natriegensand describe methods for multiplex genome editing by natural transformation (MuGENT). MuGENT promotes integration of multiple genome edits at high-efficiency on unprecedented timescales. Also, this method allows for generating highly complex mutant populations, which can be exploited for metabolic engineering efforts. As a proof-of-concept, we attempted to enhance production of the value added chemical poly-β-hydroxybutyrate (PHB) inV. natriegensby targeting the expression of nine genes involved in PHB biosynthesis via MuGENT. Within 1 week, we isolated edited strains that produced ~100 times more PHB than the parent isolate and ~3.3 times more than a rationally designed strain. Thus, the methods described here should extend the utility of this species for diverse academic and industrial applications.

SummaryThe interspecies exchange of metabolites plays a key role in the spatiotemporal dynamics of microbial communities. This raises the question of whether ecosystem-level behavior of structured communities can be predicted using genome-scale metabolic models for multiple organisms. We developed a modeling framework that integrates dynamic flux balance analysis with diffusion on a lattice and applied it to engineered communities. First, we predicted and experimentally confirmed the species ratio to which a two-species mutualistic consortium converges and the equilibrium composition of a newly engineered three-member community. We next identified a specific spatial arrangement of colonies, which gives rise to what we term the “eclipse dilemma”: does a competitor placed between a colony and its cross-feeding partner benefit or hurt growth of the original colony? Our experimentally validated finding that the net outcome is beneficial highlights the complex nature of metabolic interactions in microbial communities while at the same time demonstrating their predictability.Video Abstract

Adaptation of one set of traits is often accompanied by attenuation of traits important in other selective environments, leading to fitness trade-offs. The mechanisms that either promote or prevent the emergence of trade-offs remain largely unknown, and are difficult to discern in most systems. Here, we investigate the basis of trade-offs that emerged during experimental evolution of Methylobacterium extorquens AM1 to distinct growth substrates. After 1500 generations of adaptation to a multi-carbon substrate, succinate (S), many lineages had lost the ability to use one-carbon compounds such as methanol (M), generating a mixture of M(+) and M(-) evolved phenotypes. We show that trade-offs in M(-) strains consistently arise via antagonistic pleiotropy through recurrent selection for loss-of-function mutations to ftfL (formate-tetrahydrofolate ligase), which improved growth on S while simultaneously eliminating growth on M. But if loss of FtfL was beneficial, why were M trade-offs not found in all populations? We discovered that eliminating FtfL was not universally beneficial on S, as it was neutral or even deleterious in certain evolved lineages that remained M(+) . This suggests that sign epistasis with earlier arising mutations prevented the emergence of mutations that drove trade-offs through antagonistic pleiotropy, limiting the evolution of metabolic specialists in some populations.

Biased codon usage in protein-coding genes is pervasive, whereby amino acids are largely encoded by a specific subset of possible codons. Within individual genes, codon bias is stronger at evolutionarily conserved residues, favoring codons recognized by abundant tRNAs. Although this observation suggests an overall pattern of selection for translation speed and/or accuracy, other work indicates that transcript structure or binding motifs drive codon usage. However, our understanding of codon bias evolution is constrained by limited experimental data on the fitness effects of altering codons in functional genes. To bridge this gap, we generated synonymous variants of a key enzyme-coding gene in Methylobacterium extorquens. We found that mutant gene expression, enzyme production, enzyme activity, and fitness were all significantly lower than wild-type. Surprisingly, encoding the gene using only rare codons decreased fitness by 40%, whereas an allele coded entirely by frequent codons decreased fitness by more than 90%. Increasing gene expression restored mutant fitness to varying degrees, demonstrating that the fitness disadvantage of synonymous mutants arose from a lack of beneficial protein rather than costs of protein production. Protein production was negatively correlated with the frequency of motifs with high affinity for the anti-Shine-Dalgarno sequence, suggesting ribosome pausing as the dominant cause of low mutant fitness. Together, our data support the idea that, although a particular set of codons are favored on average across a genome, in an individual gene selection can either act for or against codons depending on their local context.

Modern systems biology requires extensive, carefully curated measurements of cellular components in response to different environmental conditions. While high-throughput methods have made transcriptomics and proteomics datasets widely accessible and relatively economical to generate, systematic measurements of both mRNA and protein abundances under a wide range of different conditions are still relatively rare. Here we present a detailed, genome-wide transcriptomics and proteomics dataset of E. coli grown under 34 different conditions. Additionally, we provide measurements of doubling times and in-vivo metabolic fluxes through the central carbon metabolism. We manipulate concentrations of sodium and magnesium in the growth media, and we consider four different carbon sources glucose, gluconate, lactate, and glycerol. Moreover, samples are taken both in exponential and stationary phase, and we include two extensive time-courses, with multiple samples taken between 3 hours and 2 weeks. We find that exponential-phase samples systematically differ from stationary-phase samples, in particular at the level of mRNA. Regulatory responses to different carbon sources or salt stresses are more moderate, but we find numerous differentially expressed genes for growth on gluconate and under salt and magnesium stress. Our data set provides a rich resource for future computational modeling of E. coli gene regulation, transcription, and translation.

Contrary to previous understanding, recent evidence indicates that synonymous codon changes may sometimes face strong selection. However, it remains difficult to generalize the nature, strength, and mechanism(s) of such selection. Previously, we showed that synonymous variants of a key enzyme-coding gene (fae) of Methylobacterium extorquens AM1 decreased enzyme production and reduced fitness dramatically. We now show that during laboratory evolution, these variants rapidly regained fitness via parallel yet variant-specific, highly beneficial point mutations in the N-terminal region of fae These mutations (including four synonymous mutations) had weak but consistently positive impacts on transcript levels, enzyme production, or enzyme activity. However, none of the proposed mechanisms (including internal ribosome pause sites or mRNA structure) predicted the fitness impact of evolved or additional, engineered point mutations. This study shows that synonymous mutations can be fixed through strong positive selection, but the mechanism for their benefit varies depending on the local sequence context.

Epistasis between mutations in two genes is thought to reflect an interdependence of their functions. While sometimes epistasis is predictable using mechanistic models, its roots seem, in general, hidden in the complex architecture of biological networks. Here, we ask how epistasis can be quantified based on the mathematical dependence of a system-level trait (e.g. fitness) on lower-level traits (e.g. molecular or cellular properties). We first focus on a model in which fitness is the difference between a benefit and a cost trait, both pleiotropically affected by mutations. We show that despite its simplicity, this model can be used to analytically predict certain properties of the ensuing distribution of epistasis, such as a global negative bias, resulting in antagonism between beneficial mutations, and synergism between deleterious ones. We next extend these ideas to derive a general expression for epistasis given an arbitrary functional dependence of fitness on other traits. This expression demonstrates how epistasis relative to fitness can emerge despite the absence of epistasis relative to lower level traits, leading to a formalization of the concept of independence between biological processes. Our results suggest that epistasis may be largely shaped by the pervasiveness of pleiotropic effects and modular organization in biological networks.

Bioprinting experiments have emerged as an approach for studying complex cellular interactions in the context of spatial structure, ranging from intracellular networks to interspecies interactions in communities. Despite the progress made in developing and optimizing computational modeling parameters to recapitulate these interactions in silico, experimental verification of model predictions in vitro is often elusive, due to the limits of common laboratory culturing methods, especially at the micro- and nanoscale. In this work, micro-scale bioprinting was used to evaluate the spatiotemporal effects of metabolite sharing between partners in an artificial syntrophic consortium consisting of Salmonella enterica serovar Typhimurium and Escherichia coli. Micro-colonies of these bacteria were patterned at increasing spatial separation distances, in the presence of competitor or cooperator strains. Growth of the consortium members was evaluated and compared to predictions generated by a bacterial growth modeling platform known as Computation of Microbial Ecosystems in Time and Space (COMETS). In close agreement with simulation, experimental metabolite sharing between micro-colonies exhibited strong distance-dependency. When bioprinted micro-colonies were confronted with one-way or two-way diffusion barriers, such as the intervention of cooperative or competitive bacteria, experimental results showed that spatial positioning of the barriers critically influences metabolite sharing between consortium members. These results were generally predicted by simulation in COMETS. Our results demonstrate the utility of micro-scale bioprinting to experimentally test which aspects of predictive microbial growth models hold at this spatial scale, and for a range of synthetic biology applications.

Trade-offs have been put forward as essential to the generation and maintenance of diversity. However, variation in trade-offs is often determined at the molecular level, outside the scope of conventional ecological inquiry. In this study, we propose that understanding the intracellular basis for trade-offs in microbial systems can aid in predicting and interpreting patterns of diversity. First, we show how laboratory experiments and mathematical models have unveiled the hidden intracellular mechanisms underlying trade-offs key to microbial diversity: (i) metabolic and regulatory trade-offs in bacteria and yeast; (ii) life-history trade-offs in bacterial viruses. Next, we examine recent studies of marine microbes that have taken steps toward reconciling the molecular and the ecological views of trade-offs, despite the challenges in doing so in natural settings. Finally, we suggest avenues for research where mathematical modelling, experiments and studies of natural microbial communities provide a unique opportunity to integrate studies of diversity across multiple scales.

This project has developed and combined mathematical models, multi-species consortia, and spatially structured environments as an approach for studying metabolic exchange in communities like the ones between fermenters and metal reducers. We have developed novel, broadly-applicable tools for following community dynamics, come to a better understanding of both sugar and lactate-utilization in S. oneidensis, the interactions between carbon and mineral availability, and have a methodology for cell printing to match with spatiotemporal models of consortia metabolism.

How do bacteria regulate their cellular physiology in response to starvation? Here, we present a detailed characterization of Escherichia coli growth and starvation over a time-course lasting two weeks. We have measured multiple cellular components, including RNA and proteins at deep genomic coverage, as well as lipid modifications and flux through central metabolism. Our study focuses on the physiological response of E. coli in stationary phase as a result of being starved for glucose, not on the genetic adaptation of E. coli to utilize alternative nutrients. In our analysis, we have taken advantage of the temporal correlations within and among RNA and protein abundances to identify systematic trends in gene regulation. Specifically, we have developed a general computational strategy for classifying expression-profile time courses into distinct categories in an unbiased manner. We have also developed, from dynamic models of gene expression, a framework to characterize protein degradation patterns based on the observed temporal relationships between mRNA and protein abundances. By comparing and contrasting our transcriptomic and proteomic data, we have identified several broad physiological trends in the E. coli starvation response. Strikingly, mRNAs are widely down-regulated in response to glucose starvation, presumably as a strategy for reducing new protein synthesis. By contrast, protein abundances display more varied responses. The abundances of many proteins involved in energy-intensive processes mirror the corresponding mRNA profiles while proteins involved in nutrient metabolism remain abundant even though their corresponding mRNAs are down-regulated., Author Summary Bacteria frequently experience starvation conditions in their natural environments. Yet how they modify their physiology in response to these conditions remains poorly understood. Here, we performed a detailed, two-week starvation experiment in E. coli. We exhaustively monitored changes in cellular components, such as RNA and protein abundances, over time. We subsequently compared and contrasted these measurements using novel computational approaches we developed specifically for analyzing gene-expression time-course data. Using these approaches, we could identify systematic trends in the E. coli starvation response. In particular, we found that cells systematically limit mRNA and protein production, degrade proteins involved in energy-intensive processes, and maintain or increase the amount of proteins involved in energy production. Thus, the bacteria assume a cellular state in which their ongoing energy use is limited while they are poised to take advantage of any nutrients that may become available.