Genetic causality and metabolite pathway identifying the relationship of blood metabolites and psoriasis.

BACKGROUND: Psoriasis is a chronic inflammatory disease that causes significant disability. However, little is known about the underlying metabolic mechanisms of psoriasis. Our study aims to investigate the causality of 975 blood metabolites with the risk of psoriasis. MATERIALS AND METHODS: We mainly applied genetic analysis to explore the possible associations between 975 blood metabolites and psoriasis. The inverse variance weighted (IVW) method was used as the primary analysis to assess the possible association of blood metabolites with psoriasis. Moreover, generalized summary-data-based Mendelian randomization (GSMR) was used as a supplementary analysis. In addition, linkage disequilibrium score regression (LDSC) was used to investigate their genetic correction further. Metabolic pathway analysis of the most suggested metabolites was also performed using MetaboAnalyst 5.0. RESULTS: In our primary analysis, 17 metabolites, including unsaturated fatty acids, phospholipids, and triglycerides traits, were selected as potential factors in psoriasis, with odd ratios (OR) ranging from 0.986 to 1.01. The GSMR method confirmed the above results (ß = 0.001, p < 0.05). LDSC analysis mainly suggested the genetic correlation of psoriasis with genetic correlations (rg) from 0.088 to 0.155. Based on the selected metabolites, metabolic pathway analysis suggested seven metabolic pathways including ketone body that may be prominent pathways for metabolites in psoriasis. CONCLUSION: Our study supports the causal role of unsaturated fatty acid properties and lipid traits with psoriasis. These properties may be regulated by the ketone body metabolic pathway.

Causal impact of human blood metabolites and metabolic pathways on serum uric acid and gout: a mendelian randomization study.

Objective: Hyperuricaemia and gout are common metabolic disorders. However, the causal relationships between blood metabolites and serum urate levels, as well as gout, remain unclear. A systematic evaluation of the causal connections between blood metabolites, hyperuricemia, and gout could enhance early screening and prevention of hyperuricemia and gout in clinical settings, providing novel insights and approaches for clinical treatment. Methods: In this study, we employed a bidirectional two-sample Mendelian randomization analysis utilizing data from a genome-wide association study involving 7,286 participants, encompassing 486 blood metabolites. Serum urate and gout data were sourced from the Chronic Kidney Disease Genetics consortium, including 288,649 participants for serum urate and 9,819 African American and 753,994 European individuals for gout. Initially, LDSC methodology was applied to identify blood metabolites with a genetic relationship to serum urate and gout. Subsequently, inverse-variance weighting was employed as the primary analysis method, with a series of sensitivity and pleiotropy analyses conducted to assess the robustness of the results. Results: Following LDSC, 133 blood metabolites exhibited a potential genetic relationship with serum urate and gout. In the primary Mendelian randomization analysis using inverse-variance weighting, 19 blood metabolites were recognized as potentially influencing serum urate levels and gout. Subsequently, the IVW p-values of potential metabolites were corrected using the false discovery rate method. We find leucine (IVW P FDR = 0.00004), N-acetylornithine (IVW P FDR = 0.0295), N1-methyl-3-pyridone-4-carboxamide (IVW P FDR = 0.0295), and succinyl carnitine (IVW P FDR = 0.00004) were identified as significant risk factors for elevated serum urate levels. Additionally, 1-oleoylglycerol (IVW P FDR = 0.0007) may lead to a substantial increase in the risk of gout. Succinyl carnitine exhibited acceptable weak heterogeneity, and the results for other blood metabolites remained robust after sensitivity, heterogeneity, and pleiotropy testing. We conducted an enrichment analysis on potential blood metabolites, followed by a metabolic pathway analysis revealing four pathways associated with serum urate levels. Conclusion: The identified causal relationships between these metabolites and serum urate and gout offer a novel perspective, providing new mechanistic insights into serum urate levels and gout.

PEMPS: a phylogenetic software tool to model the evolution of metabolic pathways.

BACKGROUND: Metabolic pathways support the enzyme flux that converts input chemicals into energy and cellular building blocks. With a constant rate of input, steady-state flux is achieved when metabolite concentrations and reaction rates remain constant over time. Individual genes undergo mutation, while selection acts on higher level functions of the pathway, such as steady-state flux where applicable. Modeling the evolution of metabolic pathways through mechanistic sets of ordinary differential equations is a piece of the genotype-phenotype map model for interpreting genetic variation and inter-specific differences. Such models can generate distinct compensatory changes and adaptive changes from directional selection, indicating single nucleotide polymorphisms and fixed differences that could affect phenotype. If used for inference, this would ultimately enable detection of selection on metabolic pathways as well as inference of ancestral states for metabolic pathway function. RESULTS: A software tool for simulating the evolution of metabolic pathways based upon underlying biochemistry, phylogenetics, and evolutionary considerations is presented. The Python program, Phylogenetic Evolution of Metabolic Pathway Simulator (PEMPS), implements a mutation-selection framework to simulate the evolution of the pathway over a phylogeny by interfacing with COPASI to calculate the steady-state flux of the metabolic network, introducing mutations as alterations in parameter values according to a model, and calculating a fitness score and corresponding probability of fixation based on the change in steady-state flux value(s). Results from simulations are consistent with a priori expectations of fixation probabilities and systematic change in model parameters. CONCLUSIONS: The PEMPS program simulates the evolution of a metabolic pathway with a mutation-selection modeling framework based on criteria like steady-state flux that is designed to work with SBML-formatted kinetic models, and Newick-formatted phylogenetic trees. The Python software is run on the Linux command line and is available at https://github.com/nmccloskey/PEMPS .

Bioprobe-RNA-seq-microRaman system for deep tracking of the live single-cell metabolic pathway chemometrics.

The integration between RNA-sequencing and micro-spectroscopic techniques has recently profiled the advanced transcriptomic discoveries on the cellular level. In the current study, by combining the sensation approach (including bio-molecules structural evaluation, high throughput next-generation sequencing (HT-NGS), and confocal Raman microscopy) the functionality on the single live cancer cells' ferroptosis and apoptosis signaling pathways is visualized. Our study reveals a hydrophobic tunnel by phycocyanin-isoprene molecule (PC-SIM) electrostatic charge within hepatoma cells (HepG2) that activates the ferritin light chain (FTL) and caspase-8 associate protein (CASP8AP2) ferroptosis responsible genes. Moreover, this research proves that PC-vanillin (VAN) stimulation induces the actin-binding factor profilin-1 (PFN1), subsequently in situ tracking its expression at 1139.75 cm-1 microRaman wavenumber. While PC-thymol (THY) induces the lysophospholipase-2 (LYPLA2) (p-value = 0.009) and acetylneuraminate-9-O-acetyltransferase (CASD1) (p-value = 0.022) at 1143.19 cm-1. Our findings establish a new concept to promote the cross-disciplinary use of instant cellular-based detection technology for intermediary evaluating the signaling cellular transcriptome.

Living in mangroves: a syntrophic scenario unveiling a resourceful microbiome.

BACKGROUND: Mangroves are complex and dynamic coastal ecosystems under frequent fluctuations in physicochemical conditions related to the tidal regime. The frequent variation in organic matter concentration, nutrients, and oxygen availability, among other factors, drives the microbial community composition, favoring syntrophic populations harboring a rich and diverse, stress-driven metabolism. Mangroves are known for their carbon sequestration capability, and their complex and integrated metabolic activity is essential to global biogeochemical cycling. Here, we present a metabolic reconstruction based on the genomic functional capability and flux profile between sympatric MAGs co-assembled from a tropical restored mangrove. RESULTS: Eleven MAGs were assigned to six Bacteria phyla, all distantly related to the available reference genomes. The metabolic reconstruction showed several potential coupling points and shortcuts between complementary routes and predicted syntrophic interactions. Two metabolic scenarios were drawn: a heterotrophic scenario with plenty of carbon sources and an autotrophic scenario with limited carbon sources or under inhibitory conditions. The sulfur cycle was dominant over methane and the major pathways identified were acetate oxidation coupled to sulfate reduction, heterotrophic acetogenesis coupled to carbohydrate catabolism, ethanol production and carbon fixation. Interestingly, several gene sets and metabolic routes similar to those described for wastewater and organic effluent treatment processes were identified. CONCLUSION: The mangrove microbial community metabolic reconstruction reflected the flexibility required to survive in fluctuating environments as the microhabitats created by the tidal regime in mangrove sediments. The metabolic components related to wastewater and organic effluent treatment processes identified strongly suggest that mangrove microbial communities could represent a resourceful microbial model for biotechnological applications that occur naturally in the environment.

Application of Graph Models to the Identification of Transcriptomic Oncometabolic Pathways in Human Hepatocellular Carcinoma.

Whole-tissue transcriptomic analyses have been helpful to characterize molecular subtypes of hepatocellular carcinoma (HCC). Metabolic subtypes of human HCC have been defined, yet whether these different metabolic classes are clinically relevant or derive in actionable cancer vulnerabilities is still an unanswered question. Publicly available gene sets or gene signatures have been used to infer functional changes through gene set enrichment methods. However, metabolism-related gene signatures are poorly co-expressed when applied to a biological context. Here, we apply a simple method to infer highly consistent signatures using graph-based statistics. Using the Cancer Genome Atlas Liver Hepatocellular cohort (LIHC), we describe the main metabolic clusters and their relationship with commonly used molecular classes, and with the presence of TP53 or CTNNB1 driver mutations. We find similar results in our validation cohort, the LIRI-JP cohort. We describe how previously described metabolic subtypes could not have therapeutic relevance due to their overall downregulation when compared to non-tumoral liver, and identify N-glycan, mevalonate and sphingolipid biosynthetic pathways as the hallmark of the oncogenic shift of the use of acetyl-coenzyme A in HCC metabolism. Finally, using DepMap data, we demonstrate metabolic vulnerabilities in HCC cell lines.

Inactivation of Pseudomonas putida KT2440 pyruvate dehydrogenase relieves catabolite repression and improves the usefulness of this strain for degrading aromatic compounds.

Pyruvate dehydrogenase (PDH) catalyses the irreversible decarboxylation of pyruvate to acetyl-CoA, which feeds the tricarboxylic acid cycle. We investigated how the loss of PDH affects metabolism in Pseudomonas putida. PDH inactivation resulted in a strain unable to utilize compounds whose assimilation converges at pyruvate, including sugars and several amino acids, whereas compounds that generate acetyl-CoA supported growth. PDH inactivation also resulted in the loss of carbon catabolite repression (CCR), which inhibits the assimilation of non-preferred compounds in the presence of other preferred compounds. Pseudomonas putida can degrade many aromatic compounds, most of which produce acetyl-CoA, making it useful for biotransformation and bioremediation. However, the genes involved in these metabolic pathways are often inhibited by CCR when glucose or amino acids are also present. Our results demonstrate that the PDH-null strain can efficiently degrade aromatic compounds even in the presence of other preferred substrates, which the wild-type strain does inefficiently, or not at all. As the loss of PDH limits the assimilation of many sugars and amino acids and relieves the CCR, the PDH-null strain could be useful in biotransformation or bioremediation processes that require growth with mixtures of preferred substrates and aromatic compounds.

Heat-stress-responsive HvHSFA2e gene regulates the heat and drought tolerance in barley through modulation of phytohormone and secondary metabolic pathways.

KEY MESSAGE: The heat stress transcription factor HSFA2e regulates both temperature and drought response via hormonal and secondary metabolism alterations. High temperature and drought are the primary yield-limiting environmental constraints for staple food crops. Heat shock transcription factors (HSF) terminally regulate the plant abiotic stress responses to maintain growth and development under extreme environmental conditions. HSF genes of subclass A2 predominantly express under heat stress (HS) and activate the transcriptional cascade of defense-related genes. In this study, a highly heat-inducible HSF, HvHSFA2e was constitutively expressed in barley (Hordeum vulgare L.) to investigate its role in abiotic stress response and plant development. Transgenic barley plants displayed enhanced heat and drought tolerance in terms of increased chlorophyll content, improved membrane stability, reduced lipid peroxidation, and less accumulation of ROS in comparison to wild-type (WT) plants. Transcriptome analysis revealed that HvHSFA2e positively regulates the expression of abiotic stress-related genes encoding HSFs, HSPs, and enzymatic antioxidants, contributing to improved stress tolerance in transgenic plants. The major genes of ABA biosynthesis pathway, flavonoid, and terpene metabolism were also upregulated in transgenics. Our findings show that HvHSFA2e-mediated upregulation of heat-responsive genes, modulation in ABA and flavonoid biosynthesis pathways enhance drought and heat stress tolerance.

A long-term growth stable Halomonas sp. deleted with multiple transposases guided by its metabolic network model Halo-ecGEM.

Microbial instability is a common problem during bio-production based on microbial hosts. Halomonas bluephagenesis has been developed as a chassis for next generation industrial biotechnology (NGIB) under open and unsterile conditions. However, the hidden genomic information and peculiar metabolism have significantly hampered its deep exploitation for cell-factory engineering. Based on the freshly completed genome sequence of H. bluephagenesis TD01, which reveals 1889 biological process-associated genes grouped into 84 GO-slim terms. An enzyme constrained genome-scale metabolic model Halo-ecGEM was constructed, which showed strong ability to simulate fed-batch fermentations. A visible salt-stress responsive landscape was achieved by combining GO-slim term enrichment and CVT-based omics profiling, demonstrating that cells deploy most of the protein resources by force to support the essential activity of translation and protein metabolism when exposed to salt stress. Under the guidance of Halo-ecGEM, eight transposases were deleted, leading to a significantly enhanced stability for its growth and bioproduction of various polyhydroxyalkanoates (PHA) including 3-hydroxybutyrate (3HB) homopolymer PHB, 3HB and 3-hydroxyvalerate (3HV) copolymer PHBV, as well as 3HB and 4-hydroxyvalerate (4HB) copolymer P34HB. This study sheds new light on the metabolic characteristics and stress-response landscape of H. bluephagenesis, achieving for the first time to construct a long-term growth stable chassis for industrial applications. For the first time, it was demonstrated that genome encoded transposons are the reason for microbial instability during growth in flasks and fermentors.

Cordyceps militaris: A novel mushroom platform for metabolic engineering.

Cordyceps militaris, widely recognized as a medicinal and edible mushroom in East Asia, contains a variety of bioactive compounds, including cordycepin (COR), pentostatin (PTN) and other high-value compounds. This review explores the potential of developing C. militaris as a cell factory for the production of high-value chemicals and nutrients. This review comprehensively summarizes the fermentation advantages, metabolic networks, expression elements, and genome editing tools specific to C. militaris and discusses the challenges and barriers to further research on C. militaris across various fields, including computational biology, existing DNA elements, and genome editing approaches. This review aims to describe specific and promising opportunities for the in-depth study and development of C. militaris as a new chassis cell. Additionally, to increase the practicability of this review, examples of the construction of cell factories are provided, and promising strategies for synthetic biology development are illustrated.

Logistic PCA explains differences between genome-scale metabolic models in terms of metabolic pathways.

Genome-scale metabolic models (GSMMs) offer a holistic view of biochemical reaction networks, enabling in-depth analyses of metabolism across species and tissues in multiple conditions. However, comparing GSMMs Against each other poses challenges as current dimensionality reduction algorithms or clustering methods lack mechanistic interpretability, and often rely on subjective assumptions. Here, we propose a new approach utilizing logisitic principal component analysis (LPCA) that efficiently clusters GSMMs while singling out mechanistic differences in terms of reactions and pathways that drive the categorization. We applied LPCA to multiple diverse datasets, including GSMMs of 222 Escherichia-strains, 343 budding yeasts (Saccharomycotina), 80 human tissues, and 2943 Firmicutes strains. Our findings demonstrate LPCA's effectiveness in preserving microbial phylogenetic relationships and discerning human tissue-specific metabolic profiles, exhibiting comparable performance to traditional methods like t-distributed stochastic neighborhood embedding (t-SNE) and Jaccard coefficients. Moreover, the subsystems and associated reactions identified by LPCA align with existing knowledge, underscoring its reliability in dissecting GSMMs and uncovering the underlying drivers of separation.

Metaproteomic portrait of the healthy human gut microbiota.

Gut metaproteomics can provide direct evidence of microbial functions actively expressed in the colonic environments, contributing to clarify the role of the gut microbiota in human physiology. In this study, we re-analyzed 10 fecal metaproteomics datasets of healthy individuals from different continents and countries, with the aim of identifying stable and variable gut microbial functions and defining the contribution of specific bacterial taxa to the main metabolic pathways. The "core" metaproteome included 182 microbial functions and 83 pathways that were identified in all individuals analyzed. Several enzymes involved in glucose and pyruvate metabolism, along with glutamate dehydrogenase, acetate kinase, elongation factors G and Tu and DnaK, were the proteins with the lowest abundance variability in the cohorts under study. On the contrary, proteins involved in chemotaxis, response to stress and cell adhesion were among the most variable functions. Random-effect meta-analysis of correlation trends between taxa, functions and pathways revealed key ecological and molecular associations within the gut microbiota. The contribution of specific bacterial taxa to the main biological processes was also investigated, finding that Faecalibacterium is the most stable genus and the top contributor to anti-inflammatory butyrate production in the healthy gut microbiota. Active production of other mucosal immunomodulators facilitating host tolerance was observed, including Roseburia flagellin and lipopolysaccharide biosynthetic enzymes expressed by members of Bacteroidota. Our study provides a detailed picture of the healthy human gut microbiota, contributing to unveil its functional mechanisms and its relationship with nutrition, immunity, and environmental stressors.

Metabolomic and transcriptomic analyses highlight metabolic regulatory networks of Salvia miltiorrhiza in response to replant disease.

BACKGROUND: Salvia miltiorrhiza, a well-known traditional Chinese medicine, frequently suffers from replant diseases that adversely affect its quality and yield. To elucidate S. miltiorrhiza's metabolic adaptations to replant disease, we analyzed its metabolome and transcriptome, comparing normal and replant diseased plants for the first time. RESULTS: We identified 1,269 metabolites, 257 of which were differentially accumulated metabolites, and identified 217 differentially expressed genes. Integrated transcriptomic and metabolomic analyses revealed a significant up-regulation and co-expression of metabolites and genes associated with plant hormone signal transduction and flavonoid biosynthesis pathways in replant diseases. Within plant hormone signal transduction pathway, plants afflicted with replant disease markedly accumulated indole-3-acetic acid and abscisic acid, correlating with high expression of their biosynthesis-related genes (SmAmidase, SmALDH, SmNCED, and SmAAOX3). Simultaneously, changes in hormone concentrations activated plant hormone signal transduction pathways. Moreover, under replant disease, metabolites in the local flavonoid metabolite biosynthetic pathway were significantly accumulated, consistent with the up-regulated gene (SmHTC1 and SmHTC2). The qRT-PCR analysis largely aligned with the transcriptomic results, confirming the trends in gene expression. Moreover, we identified 10 transcription factors co-expressed with differentially accumulated metabolites. CONCLUSIONS: Overall, we revealed the key genes and metabolites of S. miltiorrhiza under replant disease, establishing a robust foundation for future inquiries into the molecular responses to combat replant stress.

Comparative metabolic profiling of the mycelium and fermentation broth of Penicillium restrictum from Peucedanum praeruptorum rhizosphere.

Microorganisms in the rhizosphere, particularly arbuscular mycorrhiza, have a broad symbiotic relationship with their host plants. One of the major fungi isolated from the rhizosphere of Peucedanum praeruptorum is Penicillium restrictum. The relationship between the metabolites of P. restrictum and the root exudates of P. praeruptorum is being investigated. The accumulation of metabolites in the mycelium and fermentation broth of P. restrictum was analysed over different fermentation periods. Non-targeted metabolomics was used to compare the differences in intracellular and extracellular metabolites over six periods. There were significant differences in the content and types of mycelial metabolites during the incubation. Marmesin, an important intermediate in the biosynthesis of coumarins, was found in the highest amount on the fourth day of incubation. The differential metabolites were screened to obtain 799 intracellular and 468 extracellular differential metabolites. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed that the highly enriched extracellular metabolic pathways were alanine, aspartate and glutamate metabolism, glyoxylate and dicarboxylate metabolism, and terpenoid backbone biosynthesis. In addition, the enrichment analysis associated with intracellular and extracellular ATP-binding cassette transporter proteins revealed that some ATP-binding cassette transporters may be involved in the transportation of certain amino acids and carbohydrates. Our results provide some theoretical basis for the regulatory mechanisms between the rhizosphere and the host plant and pave the way for the heterologous production of furanocoumarin.

New insights into the dominance of mixed fermentation of Staphylococcus cohnii and Staphylococcus saprophyticus in Chinese bacon: Complete genomic and comparative genomic perspectives.

Previous studies have demonstrated that Staphylococcus cohnii WX_M8 and S. saprophyticus MY_A10 significantly enhanced the flavor of Chinese bacon in a mixed fermentation. However, due to the complexity of the processing, the contribution of the bacteria is deceptive when investigating only the phenotypic changes at the time of fermentation. In order to clarify the metabolic mechanisms of mixed fermentation, a technological characterization, whole genome and comparative genomics analysis, and metabolites were approached in this study. Results showed that differences in tolerance characteristics existed between WX_M8 and MY_A10. And the genomes of both the two strains consisted of one chromosome and four circular plasmids. Their genome sizes were 2.74 Mp and 2.62 Mp, the GC contents were 32.45% and 33.18%, and the predicted coding genes (CDS) were 2564 and 2541, respectively. Based on the annotation of gene functions and assessment of metabolic pathways in the KEGG database, WX_M8 and MY_A10 strains were found to harbor complete protein degradation and amino acid metabolic pathways, pyruvate and butanol metabolic pathways, and isoleucine metabolic pathways, and their diverse enzyme-encoding genes superimposed the metabolic functions, whereas the alcohol dehydrogenase genes, adh and frmA, achieved complementary functions in the production of esters. Comparative genomics analysis revealed a diversity of encoding genes of aminotransferases and a greater metabolism for sulfur-containing amino acids, aromatic amino acids, and branched-chain amino acids in the mixed fermentation of strains WX_M8 and MY_A10. Metabolites analysis showed that MY_A10 focused on the production of soluble peptides and free amino acids (FAAs), while WX_M8 focused on volatile organic compounds (VOCs), resulting in a significant enhancement of the flavor of Chinese bacon when the two were mixed fermented. This result may provide direction for strains WX_M8 and MY_A10 to be used as starter cultures and targeted to regulate flavor.

Multi-omics reveals new links between Fructosamine-3-Kinase (FN3K) and core metabolic pathways.

Fructosamine-3-kinases (FN3Ks) are a conserved family of repair enzymes that phosphorylate reactive sugars attached to lysine residues in peptides and proteins. Although FN3Ks are present across the Tree of Life and share detectable sequence similarity to eukaryotic protein kinases, the biological processes regulated by these kinases are largely unknown. To address this knowledge gap, we leveraged the FN3K CRISPR Knock-Out (KO) HepG2 cell line alongside an integrative multi-omics study combining transcriptomics, metabolomics, and interactomics to place these enzymes in a pathway context. The integrative analyses revealed the enrichment of pathways related to oxidative stress response, lipid biosynthesis (cholesterol and fatty acids), and carbon and co-factor metabolism. Moreover, enrichment of nicotinamide adenine dinucleotide (NAD) binding proteins and localization of human FN3K (HsFN3K) to mitochondria suggests potential links between FN3K and NAD-mediated energy metabolism and redox balance. We report specific binding of HsFN3K to NAD compounds in a metal and concentration-dependent manner and provide insight into their binding mode using modeling and experimental site-directed mutagenesis. Our studies provide a framework for targeting these understudied kinases in diabetic complications and metabolic disorders where redox balance and NAD-dependent metabolic processes are altered.

Model-driven characterization of functional diversity of Pseudomonas aeruginosa clinical isolates with broadly representative phenotypes.

Pseudomonas aeruginosa is a leading cause of infections in immunocompromised individuals and in healthcare settings. This study aims to understand the relationships between phenotypic diversity and the functional metabolic landscape of P. aeruginosa clinical isolates. To better understand the metabolic repertoire of P. aeruginosa in infection, we deeply profiled a representative set from a library of 971 clinical P. aeruginosa isolates with corresponding patient metadata and bacterial phenotypes. The genotypic clustering based on whole-genome sequencing of the isolates, multilocus sequence types, and the phenotypic clustering generated from a multi-parametric analysis were compared to each other to assess the genotype-phenotype correlation. Genome-scale metabolic network reconstructions were developed for each isolate through amendments to an existing PA14 network reconstruction. These network reconstructions show diverse metabolic functionalities and enhance the collective P. aeruginosa pangenome metabolic repertoire. Characterizing this rich set of clinical P. aeruginosa isolates allows for a deeper understanding of the genotypic and metabolic diversity of the pathogen in a clinical setting and lays a foundation for further investigation of the metabolic landscape of this pathogen and host-associated metabolic differences during infection.

Environmental and genetic regulation of Streptococcus pneumoniae galactose catabolic pathways.

Efficient utilization of nutrients is crucial for microbial survival and virulence. The same nutrient may be utilized by multiple catabolic pathways, indicating that the physical and chemical environments for induction as well as their functional roles may differ. Here, we study the tagatose and Leloir pathways for galactose catabolism of the human pathogen Streptococcus pneumoniae. We show that galactose utilization potentiates pneumococcal virulence, the induction of galactose catabolic pathways is influenced differentially by the concentration of galactose and temperature, and sialic acid downregulates galactose catabolism. Furthermore, the genetic regulation and in vivo induction of each pathway differ, and both galactose catabolic pathways can be turned off with a galactose analogue in a substrate-specific manner, indicating that galactose catabolic pathways can be potential drug targets.

Leveraging genome-scale metabolic models to understand aerobic methanotrophs.

Genome-scale metabolic models (GEMs) are valuable tools serving systems biology and metabolic engineering. However, GEMs are still an underestimated tool in informing microbial ecology. Since their first application for aerobic gammaproteobacterial methane oxidizers less than a decade ago, GEMs have substantially increased our understanding of the metabolism of methanotrophs, a microbial guild of high relevance for the natural and biotechnological mitigation of methane efflux to the atmosphere. Particularly, GEMs helped to elucidate critical metabolic and regulatory pathways of several methanotrophic strains, predicted microbial responses to environmental perturbations, and were used to model metabolic interactions in cocultures. Here, we conducted a systematic review of GEMs exploring aerobic methanotrophy, summarizing recent advances, pointing out weaknesses, and drawing out probable future uses of GEMs to improve our understanding of the ecology of methane oxidizers. We also focus on their potential to unravel causes and consequences when studying interactions of methane-oxidizing bacteria with other methanotrophs or members of microbial communities in general. This review aims to bridge the gap between applied sciences and microbial ecology research on methane oxidizers as model organisms and to provide an outlook for future studies.

Beyond methane, new frontiers in anaerobic microbial hydrocarbon utilizing pathways.

Alkanes, single carbon methane to long-chain hydrocarbons (e.g. hexadecane and tetradecane), are important carbon sources to anaerobic microbial communities. In anoxic environments, archaea are known to utilize and produce methane via the methyl-coenzyme M reductase enzyme (MCR). Recent explorations of new environments, like deep sea sediments, that have coupled metagenomics and cultivation experiments revealed divergent MCRs, also referred to as alkyl-coenzyme M reductases (ACRs) in archaea, with similar mechanisms as the C1 utilizing canonical MCR mechanism. These ACR enzymes have been shown to activate other alkanes such as ethane, propane and butane for subsequent degradation. The reversibility of canonical MCRs suggests that these non-methane-activating homologues (ACRs) might have similar reversibility, perhaps mediated by undiscovered lineages that produce alkanes under certain conditions. The discovery of these alternative alkane utilization pathways holds significant promise for a breadth of potential biotechnological applications in bioremediation, energy production and climate change mitigation.