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Background: Two variants of Methylobacterium extorquens AM1 demonstrated a trade-off between growth rate and biomass yield. In addition, growth rate and biomass yield were also affected by supplementation of growth medium with different amounts of cobalt. The metabolism changes relating to these growth phenomena as well as the trade-off were investigated in this study. 13C metabolic flux analysis was used to generate a detailed central carbon metabolic flux map with both absolute and normalized flux values. Results: The major differences between the two variants occurred at the formate node as well as within C3-C4 inter-conversion pathways. Higher relative fluxes through formyltetrahydrofolate ligase, phosphoenolpyruvate carboxylase, and malic enzyme led to higher biomass yield, while higher relative fluxes through pyruvate kinase and pyruvate dehydrogenase led to higher growth rate. These results were then tested by phenotypic studies on three mutants (null pyk, null pck mutant and null dme mutant) in both variants, which agreed with the model prediction. Conclusions: In this study, 13C metabolic flux analysis for two strain variants of M. extorquens AM1 successfully identified metabolic pathways contributing to the trade-off between cell growth and biomass yield. Phenotypic analysis of mutants deficient in corresponding genes supported the conclusion that C3-C4 inter-conversion strategies were the major response to the trade-off. [ABSTRACT FROM AUTHOR]

Background: The toxicity of alcohols is one of the major roadblocks of biological fermentation for biofuels production. Methylobacterium extorquens AM1, a facultative methylotrophic a-proteobacterium, has been engineered to generate 1-butanol from cheap carbon feedstocks through a synthetic metabolic pathway. However, M. extorquens AM1 is vulnerable to solvent stress, which impedes further development for 1-butanol production. Only a few studies have reported the general stress response of M. extorquens AM1 to solvent stress. Therefore, it is highly desirable to obtain a strain with ameliorated 1-butanol tolerance and elucidate the molecular mechanism of 1-butnaol tolerance in M. extorquens AM1 for future strain improvement. Results: In this work, adaptive laboratory evolution was used as a tool to isolate mutants with 1-butanol tolerance up to 0.5 %. The evolved strains, BHBT3 and BHBT5, demonstrated increased growth rates and higher survival rates with the existence of 1-butanol. Whole genome sequencing revealed a SNP mutation at kefB in BHBT5, which was confirmed to be responsible for increasing 1-butanol tolerance through an allelic exchange experiment. Global metabolomic analysis further discovered that the pools of multiple key metabolites, including fatty acids, amino acids, and disaccharides, were increased in BHBT5 in response to 1-butanol stress. Additionally, the carotenoid synthesis pathway was significantly down-regulated in BHBT5. Conclusions: We successfully screened mutants resistant to 1-butanol and provided insights into the molecular mechanism of 1-butanol tolerance in M. extorquens AM1. This research will be useful for uncovering the mechanism of cellular response of M. extorquens AM1 to solvent stress, and will provide the genetic blueprint for the rational design of a strain of M. extorquens AM1 with increased 1-butanol tolerance in the future. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Mass-Suite (MSS) is a Python-based, open-source software package designed to analyze high-resolution mass spectrometry (HRMS)-based non-targeted analysis (NTA) data, particularly for water quality assessment and other environmental applications. MSS provides flexible, user-defined workflows for HRMS data processing and analysis, including both basic functions (e.g., feature extraction, data reduction, feature annotation, data visualization, and statistical analyses) and advanced exploratory data mining and predictive modeling capabilities that are not provided by currently available open-source software (e.g., unsupervised clustering analyses, a machine learning-based source tracking and apportionment tool). As a key advance, most core MSS functions are supported by machine learning algorithms (e.g., clustering algorithms and predictive modeling algorithms) to facilitate function accuracy and/or efficiency. MSS reliability was validated with mixed chemical standards of known composition, with 99.5% feature extraction accuracy and ~ 52% overlap of extracted features relative to other open-source software tools. Example user cases of laboratory data evaluation are provided to illustrate MSS functionalities and demonstrate reliability. MSS expands available HRMS data analysis workflows for water quality evaluation and environmental forensics, and is readily integrated with existing capabilities. As an open-source package, we anticipate further development of improved data analysis capabilities in collaboration with interested users., (© 2023. The Author(s).)

Background: Two variants of Methylobacterium extorquens AM1 demonstrated a trade-off between growth rate and biomass yield. In addition, growth rate and biomass yield were also affected by supplementation of growth medium with different amounts of cobalt. The metabolism changes relating to these growth phenomena as well as the trade-off were investigated in this study. (13)C metabolic flux analysis was used to generate a detailed central carbon metabolic flux map with both absolute and normalized flux values., Results: The major differences between the two variants occurred at the formate node as well as within C3-C4 inter-conversion pathways. Higher relative fluxes through formyltetrahydrofolate ligase, phosphoenolpyruvate carboxylase, and malic enzyme led to higher biomass yield, while higher relative fluxes through pyruvate kinase and pyruvate dehydrogenase led to higher growth rate. These results were then tested by phenotypic studies on three mutants (null pyk, null pck mutant and null dme mutant) in both variants, which agreed with the model prediction., Conclusions: In this study, (13)C metabolic flux analysis for two strain variants of M. extorquens AM1 successfully identified metabolic pathways contributing to the trade-off between cell growth and biomass yield. Phenotypic analysis of mutants deficient in corresponding genes supported the conclusion that C3-C4 inter-conversion strategies were the major response to the trade-off.

Background: The toxicity of alcohols is one of the major roadblocks of biological fermentation for biofuels production. Methylobacterium extorquens AM1, a facultative methylotrophic α-proteobacterium, has been engineered to generate 1-butanol from cheap carbon feedstocks through a synthetic metabolic pathway. However, M. extorquens AM1 is vulnerable to solvent stress, which impedes further development for 1-butanol production. Only a few studies have reported the general stress response of M. extorquens AM1 to solvent stress. Therefore, it is highly desirable to obtain a strain with ameliorated 1-butanol tolerance and elucidate the molecular mechanism of 1-butnaol tolerance in M. extorquens AM1 for future strain improvement., Results: In this work, adaptive laboratory evolution was used as a tool to isolate mutants with 1-butanol tolerance up to 0.5 %. The evolved strains, BHBT3 and BHBT5, demonstrated increased growth rates and higher survival rates with the existence of 1-butanol. Whole genome sequencing revealed a SNP mutation at kefB in BHBT5, which was confirmed to be responsible for increasing 1-butanol tolerance through an allelic exchange experiment. Global metabolomic analysis further discovered that the pools of multiple key metabolites, including fatty acids, amino acids, and disaccharides, were increased in BHBT5 in response to 1-butanol stress. Additionally, the carotenoid synthesis pathway was significantly down-regulated in BHBT5., Conclusions: We successfully screened mutants resistant to 1-butanol and provided insights into the molecular mechanism of 1-butanol tolerance in M. extorquens AM1. This research will be useful for uncovering the mechanism of cellular response of M. extorquens AM1 to solvent stress, and will provide the genetic blueprint for the rational design of a strain of M. extorquens AM1 with increased 1-butanol tolerance in the future.

Background: Molecular dynamics (MD) simulations offer the ability to observe the dynamics and interactions of both whole macromolecules and individual atoms as a function of time. Taken in context with experimental data, atomic interactions from simulation provide insight into the mechanics of protein folding, dynamics, and function. The calculation of atomic interactions or contacts from an MD trajectory is computationally demanding and the work required grows exponentially with the size of the simulation system. We describe the implementation of a spatial indexing algorithm in our multi-terabyte MD simulation database that significantly reduces the run-time required for discovery of contacts. The approach is applied to the Dynameomics project data. Spatial indexing, also known as spatial hashing, is a method that divides the simulation space into regular sized bins and attributes an index to each bin. Since, the calculation of contacts is widely employed in the simulation field, we also use this as the basis for testing compression of data tables. We investigate the effects of compression of the trajectory coordinate tables with different options of data and index compression within MS SQL SERVER 2008., Results: Our implementation of spatial indexing speeds up the calculation of contacts over a 1 nanosecond (ns) simulation window by between 14% and 90% (i.e., 1.2 and 10.3 times faster). For a 'full' simulation trajectory (51 ns) spatial indexing reduces the calculation run-time between 31 and 81% (between 1.4 and 5.3 times faster). Compression resulted in reduced table sizes but resulted in no significant difference in the total execution time for neighbour discovery. The greatest compression (~36%) was achieved using page level compression on both the data and indexes., Conclusions: The spatial indexing scheme significantly decreases the time taken to calculate atomic contacts and could be applied to other multidimensional neighbor discovery problems. The speed up enables on-the-fly calculation and visualization of contacts and rapid cross simulation analysis for knowledge discovery. Using page compression for the atomic coordinate tables and indexes saves ~36% of disk space without any significant decrease in calculation time and should be considered for other non-transactional databases in MS SQL SERVER 2008.