High-throughput genetics enables identification of nutrient utilization and accessory energy metabolism genes in a model methanogen.

Archaea are widespread in the environment and play fundamental roles in diverse ecosystems; however, characterization of their unique biology requires advanced tools. This is particularly challenging when characterizing gene function. Here, we generate randomly barcoded transposon libraries in the model methanogenic archaeon Methanococcus maripaludis and use high-throughput growth methods to conduct fitness assays (RB-TnSeq) across over 100 unique growth conditions. Using our approach, we identified new genes involved in nutrient utilization and response to oxidative stress. We identified novel genes for the usage of diverse nitrogen sources in M. maripaludis including a putative regulator of alanine deamination and molybdate transporters important for nitrogen fixation. Furthermore, leveraging the fitness data, we inferred that M. maripaludis can utilize additional nitrogen sources including ʟ-glutamine, ᴅ-glucuronamide, and adenosine. Under autotrophic growth conditions, we identified a gene encoding a domain of unknown function (DUF166) that is important for fitness and hypothesize that it has an accessory role in carbon dioxide assimilation. Finally, comparing fitness costs of oxygen versus sulfite stress, we identified a previously uncharacterized class of dissimilatory sulfite reductase-like proteins (Dsr-LP; group IIId) that is important during growth in the presence of sulfite. When overexpressed, Dsr-LP conferred sulfite resistance and enabled use of sulfite as the sole sulfur source. The high-throughput approach employed here allowed for generation of a large-scale data set that can be used as a resource to further understand gene function and metabolism in the archaeal domain.IMPORTANCEArchaea are widespread in the environment, yet basic aspects of their biology remain underexplored. To address this, we apply randomly barcoded transposon libraries (RB-TnSeq) to the model archaeon Methanococcus maripaludis. RB-TnSeq coupled with high-throughput growth assays across over 100 unique conditions identified roles for previously uncharacterized genes, including several encoding proteins with domains of unknown function (DUFs). We also expand on our understanding of carbon and nitrogen metabolism and characterize a group IIId dissimilatory sulfite reductase-like protein as a functional sulfite reductase. This data set encompasses a wide range of additional conditions including stress, nitrogen fixation, amino acid supplementation, and autotrophy, thus providing an extensive data set for the archaeal community to mine for characterizing additional genes of unknown function.

Iron Supplementation Eliminates Antagonistic Interactions Between Root-Associated Bacteria.

The rhizosphere microbiome (rhizobiome) plays a critical role in plant health and development. However, the processes by which the constituent microbes interact to form and maintain a community are not well understood. To investigate these molecular processes, we examined pairwise interactions between 11 different microbial isolates under select nutrient-rich and nutrient-limited conditions. We observed that when grown with media supplemented with 56 mM glucose, two microbial isolates were able to inhibit the growth of six other microbes. The interaction between microbes persisted even after the antagonistic microbe was removed, upon exposure to spent media. To probe the genetic basis for these antagonistic interactions, we used a barcoded transposon library in a proxy bacterium, Pseudomonas putida, to identify genes which showed enhanced sensitivity to the antagonistic factor(s) secreted by Acinetobacter sp. 02. Iron metabolism-related gene clusters in P. putida were implicated by this systems-level analysis. The supplementation of iron prevented the antagonistic interaction in the original microbial pair, supporting the hypothesis that iron limitation drives antagonistic microbial interactions between rhizobionts. We conclude that rhizobiome community composition is influenced by competition for limiting nutrients, with implications for growth and development of the plant.

System-Wide Adaptations of Desulfovibrio alaskensis G20 to Phosphate-Limited Conditions.

The prevalence of lipids devoid of phosphorus suggests that the availability of phosphorus limits microbial growth and activity in many anoxic, stratified environments. To better understand the response of anaerobic bacteria to phosphate limitation and starvation, this study combines microscopic and lipid analyses with the measurements of fitness of pooled barcoded transposon mutants of the model sulfate reducing bacterium Desulfovibrio alaskensis G20. Phosphate-limited G20 has lower growth rates and replaces more than 90% of its membrane phospholipids by a mixture of monoglycosyl diacylglycerol (MGDG), glycuronic acid diacylglycerol (GADG) and ornithine lipids, lacks polyphosphate granules, and synthesizes other cellular inclusions. Analyses of pooled and individual mutants reveal the importance of the high-affinity phosphate transport system (the Pst system), PhoR, and glycolipid and ornithine lipid synthases during phosphate limitation. The phosphate-dependent synthesis of MGDG in G20 and the widespread occurrence of the MGDG/GADG synthase among sulfate reducing ∂-Proteobacteria implicate these microbes in the production of abundant MGDG in anaerobic environments where the concentrations of phosphate are lower than 10 µM. Numerous predicted changes in the composition of the cell envelope and systems involved in transport, maintenance of cytoplasmic redox potential, central metabolism and regulatory pathways also suggest an impact of phosphate limitation on the susceptibility of sulfate reducing bacteria to other anthropogenic or environmental stresses.

Exometabolomics Assisted Design and Validation of Synthetic Obligate Mutualism.

Synthetic microbial ecology has the potential to enhance the productivity and resiliency of biotechnology processes compared to approaches using single isolates. Engineering microbial consortia is challenging; however, one approach that has attracted significant attention is the creation of synthetic obligate mutualism using auxotrophic mutants that depend on each other for exchange or cross-feeding of metabolites. Here, we describe the integration of mutant library fitness profiling with mass spectrometry based exometabolomics as a method for constructing synthetic mutualism based on cross-feeding. Two industrially important species lacking known ecological interactions, Zymomonas mobilis and Escherichia coli, were selected as the test species. Amino acid exometabolites identified in the spent medium of Z. mobilis were used to select three corresponding E. coli auxotrophs (proA, pheA and IlvA), as potential E. coli counterparts for the coculture. A pooled mutant fitness assay with a Z. mobilis transposon mutant library was used to identify mutants with improved growth in the presence of E. coli. An auxotroph mutant in a gene (ZMO0748) with sequence similarity to cysteine synthase A (cysK), was selected as the Z. mobilis counterpart for the coculture. Exometabolomic analysis of spent E. coli medium identified glutathione related metabolites as potentially available for rescue of the Z. mobilis cysteine synthase mutant. Three sets of cocultures between the Z. mobilis auxotroph and each of the three E. coli auxotrophs were monitored by optical density for growth and analyzed by flow cytometry to confirm high cell counts for each species. Taken together, our methods provide a technological framework for creating synthetic mutualisms combining existing screening based methods and exometabolomics for both the selection of obligate mutualism partners and elucidation of metabolites involved in auxotroph rescue.

Interactive XCMS Online: simplifying advanced metabolomic data processing and subsequent statistical analyses.

XCMS Online (xcmsonline.scripps.edu) is a cloud-based informatic platform designed to process and visualize mass-spectrometry-based, untargeted metabolomic data. Initially, the platform was developed for two-group comparisons to match the independent, "control" versus "disease" experimental design. Here, we introduce an enhanced XCMS Online interface that enables users to perform dependent (paired) two-group comparisons, meta-analysis, and multigroup comparisons, with comprehensive statistical output and interactive visualization tools. Newly incorporated statistical tests cover a wide array of univariate analyses. Multigroup comparison allows for the identification of differentially expressed metabolite features across multiple classes of data while higher order meta-analysis facilitates the identification of shared metabolic patterns across multiple two-group comparisons. Given the complexity of these data sets, we have developed an interactive platform where users can monitor the statistical output of univariate (cloud plots) and multivariate (PCA plots) data analysis in real time by adjusting the threshold and range of various parameters. On the interactive cloud plot, metabolite features can be filtered out by their significance level (p-value), fold change, mass-to-charge ratio, retention time, and intensity. The variation pattern of each feature can be visualized on both extracted-ion chromatograms and box plots. The interactive principal component analysis includes scores, loadings, and scree plots that can be adjusted depending on scaling criteria. The utility of XCMS functionalities is demonstrated through the metabolomic analysis of bacterial stress response and the comparison of lymphoblastic leukemia cell lines.

Control of methionine metabolism by the SahR transcriptional regulator in Proteobacteria.

Sulphur is an essential element in the metabolism. The sulphur-containing amino acid methionine is a metabolic precursor for S-adenosylmethionine (SAM), which serves as a coenzyme for ubiquitous methyltrtansferases. Recycling of organic sulphur compounds, e.g. via the SAM cycle, is an important metabolic process that needs to be tightly regulated. Knowledge about transcriptional regulation of these processes is still limited for many free-living bacteria. We identified a novel transcription factor SahR from the ArsR family that controls the SAM cycle genes in diverse microorganisms from soil and aquatic ecosystems. By using comparative genomics, we predicted SahR-binding DNA motifs and reconstructed SahR regulons in the genomes of 62 Proteobacteria. The conserved core of SahR regulons includes all enzymes required for the SAM cycle: the SAH hydrolase AhcY, the methionine biosynthesis enzymes MetE/MetH and MetF, and the SAM synthetase MetK. By using a combination of experimental techniques, we validated the SahR regulon in the sulphate-reducing Deltaproteobacterium Desulfovibrio alaskensis. SahR functions as a negative regulator that responds to the S-adenosylhomocysteine (SAH). The elevated SAH level in the cell dissociates SahR from its DNA operators and induces the expression of SAM cycle genes. The effector-sensing domain in SahR is related to SAM-dependent methylases that are able to tightly bind SAH. SahR represents a novel type of transcriptional regulators for the control of sulphur amino acid metabolism.