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Engineering microorganisms into biological factories that convert renewable feedstocks into valuable materials is a major goal of synthetic biology; however, for many nonmodel organisms, we do not yet have the genetic tools, such as suites of strong promoters, necessary to effectively engineer them. In this work, we developed a computational framework that can leverage standard RNA-seq data sets to identify sets of constitutive, strongly expressed genes and predict strong promoter signals within their upstream regions. The framework was applied to a diverse collection of RNA-seq data measured for the methanotroph Methylotuvimicrobium buryatense 5GB1 and identified 25 genes that were constitutively, strongly expressed across 12 experimental conditions. For each gene, the framework predicted short (27-30 nucleotide) sequences as candidate promoters and derived -35 and -10 consensus promoter motifs (TTGACA and TATAAT, respectively) for strong expression in M. buryatense . This consensus closely matches the canonical E. coli sigma-70 motif and was found to be enriched in promoter regions of the genome. A subset of promoter predictions was experimentally validated in a XylE reporter assay, including the consensus promoter, which showed high expression. The pmoC , pqqA , and ssrA promoter predictions were additionally screened in an experiment that scrambled the -35 and -10 signal sequences, confirming that transcription initiation was disrupted when these specific regions of the predicted sequence were altered. These results indicate that the computational framework can make biologically meaningful promoter predictions and identify key pieces of regulatory systems that can serve as foundational tools for engineering diverse microorganisms for biomolecule production.

Methylomicrobium buryatense 5GB1 is an obligate methylotroph which grows on methane or methanol with similar growth rates. It has long been assumed that the core metabolic pathways must be similar on the two substrates, but recent studies of methane metabolism in this bacterium suggest that growth on methanol might have significant differences from growth on methane. In this study, both a targeted metabolomics approach and a 13 C tracer approach were taken to understand core carbon metabolism in M. buryatense 5GB1 during growth on methanol and to determine whether such differences occur. Our results suggest a systematic shift of active core metabolism in which increased flux occurred through both the Entner-Doudoroff (ED) pathway and the partial serine cycle, while the tricarboxylic acid (TCA) cycle was incomplete, in contrast to growth on methane. Using the experimental results as constraints, we applied flux balance analysis to determine the metabolic flux phenotype of M. buryatense 5GB1 growing on methanol, and the results are consistent with predictions based on ATP and NADH changes. Transcriptomics analysis suggested that the changes in fluxes and metabolite levels represented results of posttranscriptional regulation. The combination of flux balance analysis of the genome-scale model and the flux ratio from 13 C data changed the solution space for a better prediction of cell behavior and demonstrated the significant differences in physiology between growth on methane and growth on methanol. IMPORTANCE One-carbon compounds such as methane and methanol are of increasing interest as sustainable substrates for biological production of fuels and industrial chemicals. The bacteria that carry out these conversions have been studied for many decades, but gaps exist in our knowledge of their metabolic pathways. One such gap is the difference between growth on methane and growth on methanol. Understanding such metabolism is important, since each has advantages and disadvantages as a feedstock for production of chemicals and fuels. The significance of our research is in the demonstration that the metabolic network is substantially altered in each case and in the delineation of these changes. The resulting new insights into the core metabolism of this bacterium now provide an improved basis for future strain design., (Copyright © 2019 Fu et al.)

Aerobic methanotrophic bacteria use methane as their sole source of carbon and energy and serve as a major sink for the potent greenhouse gas methane in freshwater ecosystems. Dissecting the molecular details of how these organisms interact in the environment may increase our understanding of how they perform this important ecological role. Many bacterial species use quorum sensing (QS) systems to regulate gene expression in a cell density-dependent manner. We have identified a QS system in the genome of Methylobacter tundripaludum , a dominant methane oxidizer in methane enrichments of sediment from Lake Washington (Seattle, WA). We determined that M. tundripaludum produces primarily N -3-hydroxydecanoyl-l-homoserine lactone (3-OH-C 10 -HSL) and that its production is governed by a positive feedback loop. We then further characterized this system by determining which genes are regulated by QS in this methane oxidizer using transcriptome sequencing (RNA-seq) and discovered that this system regulates the expression of a putative nonribosomal peptide synthetase biosynthetic gene cluster. Finally, we detected an extracellular factor that is produced by M. tundripaludum in a QS-dependent manner. These results identify and characterize a mode of cellular communication in an aerobic methane-oxidizing bacterium. IMPORTANCE Aerobic methanotrophs are critical for sequestering carbon from the potent greenhouse gas methane in the environment, yet the mechanistic details of chemical interactions in methane-oxidizing bacterial communities are not well understood. Understanding these interactions is important in order to maintain, and potentially optimize, the functional potential of the bacteria that perform this vital ecosystem function. In this work, we identify a quorum sensing system in the aerobic methanotroph Methylobacter tundripaludum and use both chemical and genetic methods to characterize this system at the molecular level., (Copyright © 2017 American Society for Microbiology.)

Background: Methane-utilizing bacteria (methanotrophs) are capable of growth on methane and are attractive systems for bio-catalysis. However, the application of natural methanotrophic strains to large-scale production of value-added chemicals/biofuels requires a number of physiological and genetic alterations. An accurate metabolic model coupled with flux balance analysis can provide a solid interpretative framework for experimental data analyses and integration., Results: A stoichiometric flux balance model of Methylomicrobium buryatense strain 5G(B1) was constructed and used for evaluating metabolic engineering strategies for biofuels and chemical production with a methanotrophic bacterium as the catalytic platform. The initial metabolic reconstruction was based on whole-genome predictions. Each metabolic step was manually verified, gapfilled, and modified in accordance with genome-wide expression data. The final model incorporates a total of 841 reactions (in 167 metabolic pathways). Of these, up to 400 reactions were recruited to produce 118 intracellular metabolites. The flux balance simulations suggest that only the transfer of electrons from methanol oxidation to methane oxidation steps can support measured growth and methane/oxygen consumption parameters, while the scenario employing NADH as a possible source of electrons for particulate methane monooxygenase cannot. Direct coupling between methane oxidation and methanol oxidation accounts for most of the membrane-associated methane monooxygenase activity. However the best fit to experimental results is achieved only after assuming that the efficiency of direct coupling depends on growth conditions and additional NADH input (about 0.1-0.2 mol of incremental NADH per one mol of methane oxidized). The additional input is proposed to cover loss of electrons through inefficiency and to sustain methane oxidation at perturbations or support uphill electron transfer. Finally, the model was used for testing the carbon conversion efficiency of different pathways for C1-utilization, including different variants of the ribulose monophosphate pathway and the serine cycle., Conclusion: We demonstrate that the metabolic model can provide an effective tool for predicting metabolic parameters for different nutrients and genetic perturbations, and as such, should be valuable for metabolic engineering of the central metabolism of M. buryatense strains.

We report observations on the dynamics of bacterial communities in response to methane stimulus in laboratory microcosm incubations prepared with lake sediment samples. We first measured taxonomic compositions of long-term enrichment cultures and determined that, although dominated by Methylococcaceae types, these cultures also contained accompanying types belonging to a limited number of bacterial taxa, methylotrophs and non-methylotrophs. We then followed the short-term community dynamics, in two oxygen tension regimens (150 μM and 15 μM), observing rapid loss of species diversity. In all microcosms, a single type of Methylobacter represented the major methane-oxidizing partner. The accompanying members of the communities revealed different trajectories in response to different oxygen tensions, with Methylotenera species being the early responders to methane stimulus under both conditions. The communities in both conditions were convergent in terms of their assemblage, suggesting selection for specific taxa. Our results support prior observations from metagenomics on distribution of carbon from methane among diverse bacterial populations and further suggest that communities are likely responsible for methane cycling, rather than a single type of microbe.

Aerobic methanotrophs oxidize methane at ambient temperatures and pressures and are therefore attractive systems for methane-based bioconversions. In this work, we developed and validated genetic tools for Methylomicrobium buryatense, a haloalkaliphilic gammaproteobacterial (type I) methanotroph. M. buryatense was isolated directly on natural gas and grows robustly in pure culture with a 3-h doubling time, enabling rapid genetic manipulation compared to many other methanotrophic species. As a proof of concept, we used a sucrose counterselection system to eliminate glycogen production in M. buryatense by constructing unmarked deletions in two redundant glycogen synthase genes. We also selected for a more genetically tractable variant strain that can be conjugated with small incompatibility group P (IncP)-based broad-host-range vectors and determined that this capability is due to loss of the native plasmid. These tools make M. buryatense a promising model system for studying aerobic methanotroph physiology and enable metabolic engineering in this bacterium for industrial biocatalysis of methane., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

Biotechnologies for effective conversion of atmospheric greenhouse gases (CO(2) and CH(4)) into valuable compounds, such as chemical and petrochemical feedstocks or alternative fuels, offer promising new strategies for stabilization of global warming. A novel approach in this field involves the use of methanotrophic bacteria as catalysts for CH(4) conversion. In recent years, extremophilic methanotrophic species related to the genus Methylomicrobium have become favorable systems for bioprocess engineering, due to their high growth rates and tolerance of a wide range of environmental conditions and perturbations. While the cultures hold the potential of producing a broader range of chemicals from methane, the biotechnologies are still limited by the lack of reliable genetic approaches for system-level studies and strain engineering. In this chapter, we describe a set of molecular tools for genetic investigation and alteration of the Methylomicrobium spp., (Copyright © 2011 Elsevier Inc. All rights reserved.)