Microbial phenotypic heterogeneity in response to a metabolic toxin: Continuous, dynamically shifting distribution of formaldehyde tolerance in Methylobacterium extorquens populations

Microbial life in slow and stopped lanes

Microbes in nature often lack nutrients and face extreme or widely fluctuating temperatures, unlike microbes in growth-optimized settings in laboratories that much of the literature examines. Slowed or suspended lives are the norm for microbes. Studying them is important for understanding the consequences of climate change and for addressing fundamental questions about life: are there limits to how slowly a cell's life can progress, and how long cells can remain viable without self-replicating? Recent studies began addressing these questions with single-cell-level measurements and mathematical models. Emerging principles that govern slowed or suspended lives of cells - including lives of dormant spores and microbes at extreme temperatures - are re-defining discrete cellular states as continuums and revealing intracellular dynamics at new timescales. Nearly inactive, lifeless-appearing microbes are transforming our understanding of life.

Bacterial toxin-antitoxin systems: Novel insights on toxin activation across populations and experimental shortcomings

The alarming rise in hard-to-treat bacterial infections is of great concern to human health. Thus, the identification of molecular mechanisms that enable the survival and growth of pathogens is of utmost urgency for the development of more efficient antimicrobial therapies. In challenging environments, such as presence of antibiotics, or during host infection, metabolic adjustments are essential for microorganism survival and competitiveness. Toxin-antitoxin systems (TASs) consisting of a toxin with metabolic modulating activity and a cognate antitoxin that antagonizes that toxin are important elements in the arsenal of bacterial stress defense. However, the exact physiological function of TA systems is highly debatable and with the exception of stabilization of mobile genetic elements and phage inhibition, other proposed biological functions lack a broad consensus. This review aims at gaining new insights into the physiological effects of TASs in bacteria and exploring the experimental shortcomings that lead to discrepant results in TAS research. Distinct control mechanisms ensure that only subsets of cells within isogenic cultures transiently develop moderate levels of toxin activity. As a result, TASs cause phenotypic growth heterogeneity rather than cell stasis in the entire population. It is this feature that allows bacteria to thrive in diverse environments through the creation of subpopulations with different metabolic rates and stress tolerance programs.

Comparative Genomic Analysis of a Methylorubrum rhodesianum MB200 Isolated from Biogas Digesters Provided New Insights into the Carbon Metabolism of Methylotrophic Bacteria

Methylotrophic bacteria are widely distributed in nature and can be applied in bioconversion because of their ability to use one-carbon source. The aim of this study was to investigate the mechanism underlying utilization of high methanol content and other carbon sources by Methylorubrum rhodesianum strain MB200 via comparative genomics and analysis of carbon metabolism pathway. The genomic analysis revealed that the strain MB200 had a genome size of 5.7 Mb and two plasmids. Its genome was presented and compared with that of the 25 fully sequenced strains of Methylobacterium genus. Comparative genomics revealed that the Methylorubrum strains had closer collinearity, more shared orthogroups, and more conservative MDH cluster. The transcriptome analysis of the strain MB200 in the presence of various carbon sources revealed that a battery of genes was involved in the methanol metabolism. These genes are involved in the following functions: carbon fixation, electron transfer chain, ATP energy release, and resistance to oxidation. Particularly, the central carbon metabolism pathway of the strain MB200 was reconstructed to reflect the possible reality of the carbon metabolism, including ethanol metabolism. Partial propionate metabolism involved in ethyl malonyl-CoA (EMC) pathway might help to relieve the restriction of the serine cycle. In addition, the glycine cleavage system (GCS) was observed to participate in the central carbon metabolism pathway. The study revealed the coordination of several metabolic pathways, where various carbon sources could induce associated metabolic pathways. To the best of our knowledge, this is the first study providing a more comprehensive understanding of the central carbon metabolism in Methylorubrum. This study provided a reference for potential synthetic and industrial applications of this genus and its use as chassis cells.

A lineage tree-based hidden Markov model quantifies cellular heterogeneity and plasticity

Individual cells can assume a variety of molecular and phenotypic states and recent studies indicate that cells can rapidly adapt in response to therapeutic stress. Such phenotypic plasticity may confer resistance, but also presents opportunities to identify molecular programs that could be targeted for therapeutic benefit. Approaches to quantify tumor-drug responses typically focus on snapshot, population-level measurements. While informative, these methods lack lineage and temporal information, which are particularly critical for understanding dynamic processes such as cell state switching. As new technologies have become available to measure lineage relationships, modeling approaches will be needed to identify the forms of cell-to-cell heterogeneity present in these data. Here we apply a lineage tree-based adaptation of a hidden Markov model that employs single cell lineages as input to learn the characteristic patterns of phenotypic heterogeneity and state transitions. In benchmarking studies, we demonstrated that the model successfully classifies cells within experimentally-tractable dataset sizes. As an application, we analyzed experimental measurements in cancer and non-cancer cell populations under various treatments. We find evidence of multiple phenotypically distinct states, with considerable heterogeneity and unique drug responses. In total, this framework allows for the flexible modeling of single cell heterogeneity across lineages to quantify, understand, and control cell state switching.

Collective behavior and nongenetic inheritance allow bacterial populations to adapt to changing environments

Collective behaviors require coordination among a group of individuals. As a result, individuals that are too phenotypically different from the rest of the group can be left out, reducing heterogeneity, but increasing coordination. If individuals also reproduce, the offspring can have different phenotypes from their parent(s). This raises the question of how these two opposing processes-loss of diversity by collective behaviors and generation of it through growth and inheritance-dynamically shape the phenotypic composition of an isogenic population. We examine this question theoretically using collective migration of chemotactic bacteria as a model system, where cells of different swimming phenotypes are better suited to navigate in different environments. We find that the differential loss of phenotypes caused by collective migration is environment-dependent. With cell growth, this differential loss enables migrating populations to dynamically adapt their phenotype compositions to the environment, enhancing migration through multiple environments. Which phenotypes are produced upon cell division depends on the level of nongenetic inheritance, and higher inheritance leads to larger composition adaptation and faster migration at steady state. However, this comes at the cost of slower responses to new environments. Due to this trade-off, there is an optimal level of inheritance that maximizes migration speed through changing environments, which enables a diverse population to outperform a nondiverse one. Growing populations might generally leverage the selection-like effects provided by collective behaviors to dynamically shape their own phenotype compositions, without mutations.

Approaches to Formaldehyde Measurement: From Liquid Biological Samples to Cells and Organisms

Formaldehyde (FA) is the simplest aldehyde present both in the environment and in living organisms. FA is an extremely reactive compound capable of protein crosslinking and DNA damage. For a long time, FA was considered a "biochemical waste" and a by-product of normal cellular metabolism, but in recent decades the picture has changed. As a result, the need arose for novel instruments and approaches to monitor and measure not only environmental FA in water, cosmetics, and household products, but also in food, beverages and biological samples including cells and even organisms. Despite numerous protocols being developed for in vitro and in cellulo FA assessment, many of them have remained at the "proof-of-concept" stage. We analyze the suitability of different methods developed for non-biological objects, and present an overview of the recently developed approaches, including chemically-synthesized probes and genetically encoded FA-sensors for in cellulo and in vivo FA monitoring. We also discuss the prospects of classical methods such as chromatography and spectrophotometry, and how they have been adapted in response to the demand for precise, selective and highly sensitive evaluation of FA concentration fluctuations in biological samples. The main objectives of this review is to summarize data on the main approaches for FA content measurement in liquid biological samples, pointing out the advantages and disadvantages of each method; to report the progress in development of novel molecules suitable for application in living systems; and, finally, to discuss genetically encoded FA-sensors based on existing natural biological FA-responsive elements.

Nutrient Gradients Mediate Complex Colony-Level Antibiotic Responses in Structured Microbial Populations

Antibiotic treatments often fail to eliminate bacterial populations due to heterogeneity in how individual cells respond to the drug. In structured bacterial populations such as biofilms, bacterial metabolism and environmental transport processes lead to an emergent phenotypic structure and self-generated nutrient gradients toward the interior of the colony, which can affect cell growth, gene expression and susceptibility to the drug. Even in single cells, survival depends on a dynamic interplay between the drug's action and the expression of resistance genes. How expression of resistance is coordinated across populations in the presence of such spatiotemporal environmental coupling remains elusive. Using a custom microfluidic device, we observe the response of spatially extended microcolonies of tetracycline-resistant E. coli to precisely defined dynamic drug regimens. We find an intricate interplay between drug-induced changes in cell growth and growth-dependent expression of resistance genes, resulting in the redistribution of metabolites and the reorganization of growth patterns. This dynamic environmental feedback affects the regulation of drug resistance differently across the colony, generating dynamic phenotypic structures that maintain colony growth during exposure to high drug concentrations and increase population-level resistance to subsequent exposures. A mathematical model linking metabolism and the regulation of gene expression is able to capture the main features of spatiotemporal colony dynamics. Uncovering the fundamental principles that govern collective mechanisms of antibiotic resistance in spatially extended populations will allow the design of optimal drug regimens to counteract them.

Unravelling Formaldehyde Metabolism in Bacteria: Road towards Synthetic Methylotrophy

Formaldehyde metabolism is prevalent in all organisms, where the accumulation of formaldehyde can be prevented through the activity of dissimilation pathways. Furthermore, formaldehyde assimilatory pathways play a fundamental role in many methylotrophs, which are microorganisms able to build biomass and obtain energy from single- and multicarbon compounds with no carbon–carbon bonds. Here, we describe how formaldehyde is formed in the environment, the mechanisms of its toxicity to the cells, and the cell’s strategies to circumvent it. While their importance is unquestionable for cell survival in formaldehyde rich environments, we present examples of how the modification of native formaldehyde dissimilation pathways in nonmethylotrophic bacteria can be applied to redirect carbon flux toward heterologous, synthetic formaldehyde assimilation pathways introduced into their metabolism. Attempts to engineer methylotrophy into nonmethylotrophic hosts have gained interest in the past decade, with only limited successes leading to the creation of autonomous synthetic methylotrophy. Here, we discuss how native formaldehyde assimilation pathways can additionally be employed as a premise to achieving synthetic methylotrophy. Lastly, we discuss how emerging knowledge on regulation of formaldehyde metabolism can contribute to creating synthetic regulatory circuits applied in metabolic engineering strategies.

Establishment of a simple method to evaluate mixing times in a plastic bag photobioreactor using image processing based on freeware tools

Objective

Accurate determination of the mixing time in bioreactors is essential for the optimization of the productivity of bioprocesses. The aim of this work was to develop a simple optical method to determine the mixing time in a photobioreactor. The image processing method should be based on freeware tools, should not require programming skills, and thus could be used in education within high schools and in early stages of undergraduate programs.

Results

An optical method has been established to analyze images from recorded videos of mixing experiments. The steps are: 1. Extraction of a sequence of images from the video file; 2. Cropping of the pictures; 3. Background removal; and 4. Image analysis and mixing time evaluation based on quantification of pixel-to-pixel heterogeneity within a given area of interest. The novel method was generally able to track the dependency between aeration rate and mixing time within the investigated photobioreactor. In direct comparison, a pearson correlation coefficient of rho = 0.99 was obtained. Gas flow rates between 10 L h⁻¹, and 300 L h⁻¹ resulted from mixing times of between 48 and 14 s, respectively. This technique is applicable without programming skills and can be used in education with inexperienced user groups.

EfgA is a conserved formaldehyde sensor that leads to bacterial growth arrest in response to elevated formaldehyde

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.

Formaldehyde-responsive proteins, TtmR and EfgA, reveal a tradeoff between formaldehyde resistance and efficient transition to methylotrophy in Methylorubrum extorquens

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.Importance: All 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.

Global Transcriptional Response of Methylorubrum extorquens to Formaldehyde Stress Expands the Role of EfgA and Is Distinct from Antibiotic Translational Inhibition

The potency and indiscriminate nature of formaldehyde reactivity upon biological molecules make it a universal stressor. However, some organisms such as Methylorubrum extorquens possess means to rapidly and effectively mitigate formaldehyde-induced damage. EfgA is a recently identified formaldehyde sensor predicted to halt translation in response to elevated formaldehyde as a means to protect cells. Herein, we investigate growth and changes in gene expression to understand how M. extorquens responds to formaldehyde with and without the EfgA-formaldehyde-mediated translational response, and how this mechanism compares to antibiotic-mediated translation inhibition. These distinct mechanisms of translation inhibition have notable differences: they each involve different specific players and in addition, formaldehyde also acts as a general, multi-target stressor and a potential carbon source. We present findings demonstrating that in addition to its characterized impact on translation, functional EfgA allows for a rapid and robust transcriptional response to formaldehyde and that removal of EfgA leads to heightened proteotoxic and genotoxic stress in the presence of increased formaldehyde levels. We also found that many downstream consequences of translation inhibition were shared by EfgA-formaldehyde- and kanamycin-mediated translation inhibition. Our work uncovered additional layers of regulatory control enacted by functional EfgA upon experiencing formaldehyde stress, and further demonstrated the importance this protein plays at both transcriptional and translational levels in this model methylotroph.

Cross-Feeding of a Toxic Metabolite in a Synthetic Lignocellulose-Degrading Microbial Community

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.

Microbial metabolic noise

From the time a cell was first placed under the microscope, it became apparent that identifying two clonal cells that "look" identical is extremely challenging. Since then, cell-to-cell differences in shape, size, and protein content have been carefully examined, informing us of the ultimate limits that hinder two cells from occupying an identical phenotypic state. Here, we present recent experimental and computational evidence that similar limits emerge also in cellular metabolism. These limits pertain to stochastic metabolic dynamics and, thus, cell-to-cell metabolic variability, including the resulting adapting benefits. We review these phenomena with a focus on microbial metabolism and conclude with a brief outlook on the potential relationship between metabolic noise and adaptive evolution. This article is categorized under: Metabolic Diseases > Computational Models Metabolic Diseases > Biomedical Engineering.