Metabolic Genes Research Articles

A new selective force driving metabolic gene clustering.

The formation of clusters of functionally related genes in microbial genomes has puzzled microbiologists since their discovery. Here, we suggest that replication, and the copy number variations due to the replisome passage, might play a role in the process through a perturbation in metabolite homeostasis. We provide theoretical support to this hypothesis, and we found that both simulations and genomic analysis support our hypothesis.

Gene-echocardiography: unmasking the covert role of fatty acid metabolism gene mutations in adult cardiomyopathy

Abstract Background Although the role of fatty acid metabolic deficiencies in cardiomyopathy is established, the precise identity of causative genes and their respective phenotypes in adult cardiomyopathy remains unclear. Methods We implemented a combination of echocardiography and whole exome sequencing in clinically diagnosed cardiomyopathy patients to uncover this relationship. This involved recording cardiac phenotypes, identifying genes associated with disrupted fatty acid metabolism, and subsequently followed up with these patients. Results Out of 802 cardiomyopathy patients, 27 exhibited mutations in genes tied to fatty acid metabolism. Specifically, 16 patients demonstrated a hypertrophic cardiomyopathy (HCM) phenotype, and 11 showed a dilated cardiomyopathy (DCM) phenotype. The implicated genes were SLC22A5 (n=7), ACADVL (n=6), ACADS (n=4), ACADM (n=3), SLC25A20 (n=3), ACADL (n=2), HADH (n=1), and AGK (n=1), with a higher prevalence in males. Among these, the SLC22A5 mutation was predominant and correlated with HCM phenotype. Notably, compound mutations were frequently observed (16/27), leading to earlier disease onset and diminished aortic sinus dimension. Further investigation showed that smaller aortic sinus dimensions resulted from abnormal left ventricular myocardial work. HCM phenotype mutation carriers showed more consistent left ventricular hypertrophy and a higher probability of right ventricular hypertrophy, while DCM phenotype mutation carriers exhibited impaired contractile function across all left ventricle segments. After a 24-month follow-up, the DCM phenotype group demonstrated higher cardiovascular risk, including two fatalities. Conclusion Our investigation highlights the significant prevalence of mutations related to abnormal fatty acid metabolism in adult cardiomyopathy patients, underscoring the utility of a gene-echocardiography approach for diagnosis.

Differential cellular communication in tumor immune microenvironment during early and advanced stages of lung adenocarcinoma.

Heterogeneous behavior of each cell type and their cross-talks in tumor immune microenvironment (TIME) refers to tumor immunological heterogeneity that emerges during tumor progression and represents formidable challenges for effective anti-tumor immune response and promotes drug resistance. To comprehensively elucidate the heterogeneous behavior of individual cell types and their interactions across different stages of tumor development at system level, a computational framework was devised that integrates cell specific data from single-cell RNASeq into networks illustrating interactions among signaling and metabolic response genes within and between cells in TIME. This study identified stage specific novel markers which remodel the cross-talks, thereby facilitating immune stimulation. Particularly, multicellular knockout of metabolic gene APOE (Apolipoprotein E in mast cell, myeloid cell and fibroblast) combined with signaling gene CAV1 (Caveolin1 in endothelial and epithelial cells) resulted in the activation of T-cell mediated signaling pathways. Additionally, this knockout also initiated intervention of cytotoxic gene regulations during tumor immune cell interactions at the early stage of Lung Adenocarcinoma (LUAD). Furthermore, a unique interaction motif from multiple cells emerged significant in regulating the overall immune response at the advanced stage of LUAD. Most significantly, FCER1G (Fc Fragment of IgE Receptor Ig) was identified as the common regulator in activating the anti-tumor immune response at both stages. Predicted markers exhibited significant association with patient overall survival in patient specific dataset. This study uncovers the significance of signaling and metabolic interplay within TIME and discovers important targets to enhance anti-tumor immune response at each stage of tumor development.

Identification and Functional Analysis of Key Genes Regulating Organic Acid Metabolism in Jujube Fruit

Organic acids are crucial indicators of fruit flavor quality, but the metabolic characteristics and regulatory genes of organic acids during jujube fruit development remain largely unexplored. In this study, the cultivar ‘Heigeda’ with a high organic acid content was used as the experimental material. The organic acid content was quantified, and key candidate genes were identified through transcriptome analysis. The results indicated that malic acid and citric acid were the main organic acid content in jujube fruit and increased gradually with fruit development. Transcriptome analysis identified nine genes associated with malic acid and seven with citric acid, with four genes co-regulating malic acid and citric acid. Functional assays by transient overexpression and silencing of these four genes in the jujube fruits revealed that overexpression significantly upregulated the malic and citric acid content. However, only the silencing of aconitase1 (ZjACO1) and aconitase3 (ZjACO3) significantly downregulated the content of malic and citric acids. Therefore, aconitase1 (ZjACO1) and aconitase3 (ZjACO3) are considered the key genes that regulate the metabolism of citric acid and malic acid in jujube fruits. Our study can enrich the regulation mechanism of the organic acid metabolism of jujube fruit and provide theoretical support for the efficient cultivation of jujube fruit.

Transcriptional and physiological plasticity of the green peach aphid (Hemiptera: Aphididae) to cabbage and pepper plants.

Defensive metabolites and nutrient restriction of host plants are 2 major obstacles to the colonization of insect herbivores. The green peach aphid (GPA) Myzus persicae (Sulzer) broadly colonizes plants with diverse nutritional and defensive traits. However, how GPA adapts to nutritional and defensive traits within different plants remains largely unknown. To elucidate this, we first investigated the performances and transcriptomes of GPA feeding on cabbage Brassica oleracea and pepper Capsicum annuum. The green peach aphid had lower weight and fecundity when feeding on cabbage than on pepper. The transcriptomic analysis found 824 differentially expressed genes (DEGs), and 13 of the top 20 Kyoto Encyclopedia of Genes and Genomes pathways are related to nutrient metabolism, energy metabolism, and detoxification. Specifically, we found 160 DEGs associated with the metabolism of protein and amino acids, sugar and lipids, and xenobiotic substances, 86 upregulated in cabbage-fed GPA. Fourteen cathepsin B genes were strongly upregulated in cabbage-fed GPA, and were enriched in lysosome pathway and 2 dominated gene ontology terms peptidase activity and proteolysis. In addition, cabbage-fed GPA upregulated sugar and lipid digestion, while downregulated lipid biosynthesis processes. Furthermore, 55 metabolic detoxification enzyme genes were differentially expressed between GPA on 2hosts, and detoxification enzyme activities of GPA indeed changed accordingly to the host. Then, we found that cabbage has lower amino acids nutrition quality for GPA compared to pepper. Our results suggested that adjustment of nitrogen nutrient metabolism, sugar and lipid metabolism, and metabolic detoxification in a host-specific manner play crucial roles in the adaptations of GPA to different host plants.

A Convenient Route to Large-Scale Chemical Synthesis of p-Hydroxyphenylacetaldehyde Oxime and Its p-β-d-Glucopyranoside: Key Intermediates and Products in Plant Specialized Metabolism.

Oximes are unrecognized chameleons in general and specialized plant metabolism. E- and Z-p-hydroxyphenylacetaldehyde oxime are key intermediates in the biosynthesis of the cyanogenic glucoside dhurrin produced in sorghum. Nevertheless, none of the geometrical oxime isomers accumulate in the plant. Herein, we report a convenient route to the chemical synthesis of E- and Z-p-hydroxyphenylacetaldehyde oxime and its biologically produced p-β-d-glucopyranoside using p-hydroxyphenylacetic acid as a starting material. This starting material is also available in radiolabeled forms. All reaction steps proceeded with excellent yield under mild conditions, operational facility, and scalability.

Versatile MXenzymes Scavenging ROS for Promotion of Seed Germination under Salt Stress.

Salinization is recognized as a global problem, restricting agricultural production and sustainability. Targeting the salinity-induced oxidative stress, antioxidant treatment represents a protective strategy to improve plant salt tolerance. Herein, we report a V4C3 MXene nanozyme (MXenzyme), which exhibits good biocompatibility and excellent reactive oxygen species scavenging activity to ameliorate the salt stress-induced inhibition of seed germination. V4C3 MXenzyme treatment can significantly relieve salinity-induced oxidative stress and restore the antioxidant system in pea seeds, thus improving the phenotypic traits during germination. The molecular mechanism by which antioxidant V4C3 MXenzymes augment salt tolerances is revealed through transcriptomics and metabolomics. V4C3 MXenzymes significantly regulate the gene expression of antioxidant enzymes and molecule biosynthesis that correlate closely with hormone signal transduction genes and energy metabolism genes. With correlation and the combined analysis, redox homeostasis targeted by antioxidant V4C3 MXenzymes plays a critical role in promoting plant growth under salt stress.

Chronic exposure to polycyclic aromatic hydrocarbons alters skin virome composition and virus-host interactions.

Exposure to polycyclic aromatic hydrocarbons (PAHs) in polluted air influences the composition of the skin microbiome, which in turn is associated with altered skin phenotypes. However, the interactions between PAH exposure and viromes are unclear. This study aims to elucidate how PAH exposure affects the composition and function of skin viruses, their role in shaping the metabolism of bacterial hosts, and the subsequent effects on skin phenotype. We analyzed metagenomes from cheek skin swabs collected from 124 Chinese women in our previous study and found that the viruses associated with the two microbiome cutotypes had distinct diversities, compositions, functions, and lifestyles following PAH exposure. Moreover, exposure to high concentrations of PAHs substantially increased interactions between viruses and certain biodegrading bacteria. Under high-PAH exposure, the viruses were enriched in xenobiotic degradation functions, and there was evidence suggesting that the insertion of bacteriophage-encoded auxiliary metabolic genes into hosts aids biodegradation. Under low-PAH exposure conditions, the interactions followed the "Piggyback-the-Winner" model, with Cutibacterium acnes being "winners," whereas under high-PAH exposure, they followed the "Piggyback-the-Persistent" model, with biodegradation bacteria being "persistent." These findings highlight the impact of air pollutants on skin bacteria and viruses, their interactions, and their modulation of skin health. Understanding these intricate relationships could provide insights for developing targeted strategies to maintain skin health in polluted environments, emphasizing the importance of mitigating pollutant exposure and harnessing the potential of viruses to help counteract the adverse effects.

Apolipoprotein E Induces Lipid Accumulation Through Dgat2 That Is Prevented with Time-Restricted Feeding in Drosophila

Background: Apolipoprotein E (ApoE) is the leading genetic risk factor for late-onset Alzheimer’s disease (AD), which is the leading cause of dementia worldwide. Most people have two ApoE-ε3 (ApoE3) alleles, while ApoE-ε2 (ApoE2) is protective from AD, and ApoE-ε4 (ApoE4) confers AD risk. How these alleles modulate AD risk is not clearly defined, and ApoE’s role in lipid metabolism is also not fully known. Lipid droplets increase in AD. However, how ApoE contributes to lipid accumulation in the brain remains unknown. Methods: Here, we use Drosophila to study the effects of ApoE alleles on lipid accumulation in the brain and muscle in a cell-autonomous and non-cell-autonomous manner. Results: We report that pan-neuronal expression of each ApoE allele induces lipid accumulation specifically in the brain, but not in the muscle. However, this was not the case when expressed with muscle-specific drivers. ApoE2- and ApoE3-induced lipid accumulation is dependent on the expression of Dgat2, a key regulator of triacylglycerol production, while ApoE4 still induces lipid accumulation even with knock-down of Dgat2. Additionally, we find that implementation of time-restricted feeding (TRF), a dietary intervention in which food access only occurs in the active period (day), prevents ApoE-induced lipid accumulation in the brain of flies and modulates lipid metabolism genes. Conclusions: Altogether, our results demonstrate that ApoE induces lipid accumulation in the brain, that ApoE4 is unique in causing lipid accumulation independent of Dgat2, and that TRF prevents ApoE-induced lipid accumulation. These results support the idea that lipid metabolism is critical in AD, and that TRF could be a promising therapeutic approach to prevent ApoE-associated dysfunction in lipid metabolism.

A benchmark of RNA-seq data normalization methods for transcriptome mapping on human genome-scale metabolic networks

Genome-scale metabolic models (GEMs) cover the entire list of metabolic genes in an organism and associated reactions, in a tissue/condition non-specific manner. RNA-seq provides crucial information to make the GEMs condition-specific. Integrative Metabolic Analysis Tool (iMAT) and Integrative Network Inference for Tissues (INIT) are the two most popular algorithms to create condition-specific GEMs from human transcriptome data. The normalization method of choice for raw RNA-seq count data affects the model content produced by these algorithms and their predictive accuracy. However, a benchmark of the RNA-seq normalization methods on the performance of iMAT and INIT algorithms is missing in the literature. Another important phenomenon is covariates such as age and gender in a dataset, and they can affect the predictivity of analysis. In this study, we aimed to compare five different RNA-seq data normalization methods (TPM, FPKM, TMM, GeTMM, and RLE) and covariate adjusted versions of the normalized data by mapping them on a human GEM using the iMAT and INIT algorithms to generate personalized metabolic models. We used RNA-seq data for Alzheimer’s disease (AD) and lung adenocarcinoma (LUAD) patients. The results demonstrated that RNA-seq data normalized by the RLE, TMM, or GeTMM methods enabled the production of condition-specific metabolic models with considerably low variability in terms of the number of active reactions compared to the within-sample normalization methods (FPKM, TPM). Using these models, we could more accurately capture the disease-associated genes (average accuracy of ~0.80 for AD and ~0.67 for LUAD) for the RLE, TMM, and GeTMM normalization methods. An increase in the accuracies was observed for all the methods when covariate adjustment was applied. We found a similar accuracy trend when we compared the metabolites of perturbed reactions to metabolome data for AD. Together, our benchmark study shows that the between-sample RNA-seq normalization methods reduce false positive predictions at the expense of missing some true positive genes when mapped on GEMs.

Surface microlayer-mediated virome dissemination in the Central Arctic

BackgroundAquatic viruses act as key players in shaping microbial communities. In polar environments, they face significant challenges such as limited host availability and harsh conditions. However, due to the restricted accessibility of these ecosystems, our understanding of viral diversity, abundance, adaptations, and host interactions remains limited.ResultsTo fill this knowledge gap, we studied viruses from atmosphere-close aquatic ecosystems in the Central Arctic and Northern Greenland. Aquatic samples for virus-host analysis were collected from ~60 cm depth and the submillimeter surface microlayer (SML) during the Synoptic Arctic Survey 2021 on icebreaker Oden in the Arctic summer. Water was sampled from a melt pond and open water before undergoing size-fractioned filtration, followed by genome-resolved metagenomic and cultivation investigations. The prokaryotic diversity in the melt pond was considerably lower compared to that of open water. The melt pond was dominated by a Flavobacterium sp. and Aquiluna sp., the latter having a relatively small genome size of 1.2 Mb and the metabolic potential to generate ATP using the phosphate acetyltransferase-acetate kinase pathway. Viral diversity on the host fraction (0.2–5 µm) of the melt pond was strikingly limited compared to that of open water. From the 1154 viral operational taxonomic units (vOTUs), of which two-thirds were predicted bacteriophages, 17.2% encoded for auxiliary metabolic genes (AMGs) with metabolic functions. Some AMGs like glycerol-3-phosphate cytidylyltransferase and ice-binding like proteins might serve to provide cryoprotection for the host. Prophages were often associated with SML genomes, and two active prophages of new viral genera from the Arctic SML strain Leeuwenhoekiella aequorea Arc30 were induced. We found evidence that vOTU abundance in the SML compared to that of ~60 cm depth was more positively correlated with the distribution of a vOTU across five different Arctic stations.ConclusionsThe results indicate that viruses employ elaborate strategies to endure in extreme, host-limited environments. Moreover, our observations suggest that the immediate air-sea interface serves as a platform for viral distribution in the Central Arctic.Dvb_jZZ1H7pg55rxrDSVb2Video

The transcription factor TaFDL2-1A functions in auxin metabolism mediated by abscisic acid to regulate shoot growth in wheat.

Genetic strategies can be effective in improving wheat (Triticum aestivum L.) drought stress tolerance, but accumulating evidence suggests that overexpressing drought-resistance genes, especially genes related to the abscisic acid (ABA) signaling pathway, can retard plant growth. We previously characterized the positive roles of the wheat bZIP transcription factor TaFD-Like2-1A (TaFDL2-1A) in drought stress tolerance and ABA biosynthesis and response, whereas a dwarfing shoot exhibited under normal conditions. This study determined the underlying mechanisms that allow TaFDL2-1A to affect shoot growth. Overexpressing TaFDL2-1A decreased cell length, cell width, leaf size, shoot length, and biomass in wheat. The results of RNA-seq showed that multiple differently expressed transcripts are enriched in the auxin signaling pathway. Further analysis indicated higher expression levels of Gretchen Hagen3 (GH3) genes and lower indole-3-acetic acid (IAA) concentrations in the TaFDL2-1A overexpression lines. Exogenous IAA treatment restored the phenotypes of the TaFDL2-1A overexpression lines to wild-type levels. Transcriptional regulation analysis suggested that TaFDL2-1A enhances the expression of auxin metabolism genes, such as TaGH3.2-3A, TaGH3.2-3B, TaGH3.8-2A, and TaGH3.8-2D, by directly binding to ACGT core cis-elements. Furthermore, tafdl2 knock-out plants had lower expression levels of these GH3 genes and higher IAA levels than Fielder wheat. These GH3 gene expression and IAA levels were induced and reduced in Fielder wheat and tafdl2 knock-out plants treated with exogenous ABA. Our findings elucidate mechanisms underlying the functional redundancy of TaFDL2-1A in the crosstalk between ABA and IAA to affect shoot growth and provide insights into the balance between drought resistance and yield in wheat.

Use of transcriptomics and genomics to assess the effect of disinfectant exposure on the survival and resistance of Escherichia coli O157:H7, a human pathogen.

Disinfectants are essential for biosecurity, preventing the persistence and spread of zoonotic pathogens on farms and subsequent human infections. In this study, transcriptomics and genomics were utilised to assess the effect of disinfectant exposure on pathogenic Escherichia coli. The exposure of E. coli O157:H7 to sub-optimal concentrations of commonly used farm disinfectants elicited changes in both the transcriptome and genome. The transcriptomics identified upregulation of >300 genes and downregulation of >100 genes with functions, which included stress response, metabolism, transcription, transportation, membrane-associated and virulence genes. The phage shock protein (psp) operon was highly upregulated in response to a quaternary ammonium compound (QAC)-containing disinfectant, which has not previously been associated with a response to chemical stress. Disinfectant-adapted isolates generated by exposure to sub-lethal disinfectants levels demonstrated resistance to several common antibiotics and decreased sensitivity to biocides. Whole genome sequencing of the mutant strains indicated that they had acquired mutations in the genes associated with the upregulation of the multiple antibiotic resistance (MAR) efflux system (lon protease and marR) and topoisomerase genes (gyrA and gyrB). The disinfectant-adapted isolates also exhibited increased expression of transcription, respiration and several pH stress response genes localised in the "acid fitness island." This study demonstrated that sub-optimal disinfectant concentrations allow E. coli O157:H7 to adapt and survive disinfection and develop antibiotic resistance. These changes could have implications for disease treatment and elimination on farms. Although E. coli O157:H7 and farm disinfectants were the focus of this study, we believe these findings are also applicable to other settings, including hospitals.

Activation of estrogen-related receptor γ by calcium and cadmium.

Estrogen-related receptor γ (ERRγ) is a metabolic regulator with no identified physiological ligands. This study investigates whether calcium is an ERRγ ligand that mediates the effects of glucagon and whether cadmium, which mimics the effects of calcium, disrupts metabolism through ERRγ. HepG2, MCF-7, and HEK293T transfected with ERRγ were treated with glucagon, calcium, cadmium, ERRγ agonist, or ERRγ inhibitor. Cells were then collected for in vitro assays including real-time qPCR, Western blot, ChIP, immunofluorescence, mutational analysis, or gene set enrichment analysis. Molecular dynamics simulations were performed to study mutation sites. In HepG2 cells, treatment with glucagon, calcium, or cadmium re-localized ERRγ to the cell nucleus, recruited ERRγ to estrogen-related response elements, induced the expression of ERRγ-regulated genes, and increased extracellular glucose that was blocked by an ERRγ antagonist. In MCF-7 cells and HEK293T cells transfected with ERRγ, similar treatments induced the expression of metabolic genes. Mutational analysis identified S303, T429, and E452 in the ligand-binding domain as potential interaction sites. Molecular dynamics simulations showed that calcium induced changes in ERRγ similar to ERRγ agonist. The results suggest that calcium is a potential ligand of ERRγ that mediates the effects of glucagon and cadmium disrupts metabolism through ERRγ.

Dynamic Hydration and Viscosity Control of Konjac Glucomannan Enhance Long-Term Antiobesity Effects by Reducing Food Intake in High-Fat-Diet-Fed Mice.

The purpose of this study was to investigate the necessity and importance of dynamic hydration rate and ultimate viscosity control of konjac glucomannan (KGM) for long-term antiobesity effects in C57BL/6J mice on high-fat (HF) diets. KGM supplementation effectively attenuated HF-diet-induced increases in body and tissue weights. The hydration rate and viscosity changes of KGM in the digestive tract were found to have marked impacts on antiobesity effects. KGM with medium hydration and viscosity slowed gastric emptying and intestinal transit, leading to prolonged presence in the lower ileum, increased satiety-related hormones (GLP-1 and PYY), and an 18.27% reduction in daily food intake over 10 weeks (p < 0.05). This resulted in the greatest reduction in weight gain among HF-fed mice. In contrast, KGM with faster hydration and higher viscosity provided only short-term satiety due to rapid dilution. Furthermore, KGM improved metabolic health and altered glycolipid metabolism gene transcription while enriching beneficial gut bacteria; however, no significant differences were observed among the KGM groups in these effects. These findings highlight that synchronizing KGM's hydration rate and viscosity with digestive processes is crucial for regulating satiety and achieving long-term weight loss.

Single-cell omics and machine learning integration to develop a polyamine metabolism-based risk score model in breast cancer patients

BackgroundBreast cancer remains the leading malignant neoplasm among women globally, posing significant challenges in terms of treatment and prognostic evaluation. The metabolic pathway of polyamines is crucial in breast cancer progression, with a strong association to the increased capabilities of tumor cells for proliferation, invasion, and metastasis.MethodsWe used a multi-omics approach combining bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) to study polyamine metabolism. Data from The Cancer Genome Atlas, Gene Expression Omnibus, and Genotype-Tissue Expression identified 286 differentially expressed genes linked to polyamine pathways in breast cancer. These genes were analyzed using univariate COX and machine learning algorithms to develop a prognostic scoring algorithm. Single-cell RNA sequencing validated the model by examining gene expression heterogeneity at the cellular level.ResultsOur single-cell analyses revealed distinct subpopulations with different expressions of genes related to polyamine metabolism, highlighting the heterogeneity of the tumor microenvironment. The SuperPC model (a constructed risk score) demonstrated high accuracy when predicting patient outcomes. The immune profiling and functional enrichment analyses revealed that the genes identified play a crucial role in cell cycle control and immune modulation. Single-cell validation confirmed that polyamine metabolism genes were present in specific cell clusters. This highlights their potential as therapeutic targets.ConclusionsThis study integrates single cell omics with machine-learning to develop a robust scoring model for breast cancer based on polyamine metabolic pathways. Our findings offer new insights into tumor heterogeneity, and a novel framework to personalize prognosis. Single-cell technologies are being used in this context to enhance our understanding of the complex molecular terrain of breast cancer and support more effective clinical management.

Early-Stage Infection-Specific Heterobasidion annosum (Fr.) Bref. Transcripts in H. annosum-Pinus sylvestris L. Pathosystem.

Transcriptomes from stem-inoculated Scots pine saplings were analyzed to identify unique and enriched H. annosum transcripts in the early stages of infection. Comparing different time points since inoculation identified 131 differentially expressed H. annosum genes with p-values of ≤0.01. Our research supports the results of previous studies on the Norway spruce-Heterobasidion annosum s.l. pathosystem, indicating the role of carbohydrate and lignin degradation genes in pathogenesis at different time points post-inoculation and the role of lipid metabolism genes (including but not limited to the delta-12 fatty acid desaturase gene previously reported to be an important factor). The results of this study indicate that the malic enzyme could be a potential gene of interest in the context of H. annosum virulence. During this study, difficulties related to incomplete reference material of the host plant species and a low proportion of H. annosum transcripts in the RNA pool were encountered. In addition, H. annosum transcripts are currently not well annotated. Improvements in sequencing technologies (including sequencing depth) or bioinformatics focusing on small subpopulations of RNA would be welcome.

Metagenomic time series reveals a Western English Channel viral community dominated by members with strong seasonal signals.

Marine viruses are key players of ocean biogeochemistry, profoundly influencing microbial community ecology and evolution. Despite their importance, few studies have explored continuous inter-seasonal viral metagenomic time series in marine environments. Viral dynamics are complex, influenced by multiple factors such as host population dynamics and environmental conditions. To disentangle the complexity of viral communities, we developed an unsupervised machine learning framework to classify viral contigs into "chronotypes" based on temporal abundance patterns. Analysing an inter-seasonal monthly time series of surface viral metagenomes from the Western English Channel, we identified chronotypes and compared their functional and evolutionary profiles. Results revealed a consistent annual cycle with steep compositional changes from winter to summer and steadier transitions from summer to winter. Seasonal chronotypes were enriched in potential auxiliary metabolic genes of the ferrochelatases and 2OG-Fe(II) oxygenase orthologous groups compared to non-seasonal types. Chronotypes clustered into four groups based on their correlation profiles with environmental parameters, primarily driven by temperature and nutrients. Viral contigs exhibited a rapid turnover of polymorphisms, akin to Red Queen dynamics. However, within seasonal chronotypes, some sequences exhibited annual polymorphism recurrence, suggesting that a fraction of the seasonal viral populations evolve more slowly. Classification into chronotypes revealed viral genomic signatures linked to temporal patterns, likely reflecting metabolic adaptations to environmental fluctuations and host dynamics. This novel framework enables the identification of long-term trends in viral composition, environmental influences on genomic structure, and potential viral interactions.

Effects of three elicitors on primary metabolism six days after treatment in healthy &lt;i&gt;Vitis vinifera&lt;/i&gt; leaves and eight days after treatment in healthy and downy mildew-inoculated leaves

Elicitors can be used to reduce the application of conventional pesticides against grapevine diseases; however, they may disrupt plant primary metabolism. The long-term effects (more than 6 days after treatment) of applying plant defence stimulators (PDS) to protect grapevine from Plasmopara viticola were investigated. We studied the effect of three PDS (acibenzolar-S-methyl/ASM, potassium phosphonate/PHOS, methyl jasmonate/MeJA) and one surfactant (Triton) on gene expression and metabolite production in leaves of Vitis vinifera cv. Cabernet-Sauvignon before or after their inoculation with P. viticola. The molecular and biochemical results show the impact of these PDS on grapevine metabolism more than 6 days after treatment, and after inoculation. High-throughput q-RT-PCR revealed that sixty of the primary metabolism genes (ion homeostasis and hormones pathways) were modulated by all treatments, some modulations being specific to a given PDS. Meanwhile, 1H NMR studies revealed variations in metabolite abundances (amines, amino acids, organic acids, polyphenols and sugars), with some being common to all treatments (organic acid increase) and others specific to a single one. By combining two methodological approaches, it was possible to determine the specific effects of each PDS on Vitis. All PDS-induced resistance involved modulation of the primary metabolism. This innovative approach can be extended to vineyard studies in order to help better understand the variability of PDS effects in natura.

Metabolic engineering of Corynebacterium crenatum for enhanced L-tyrosine production from mannitol and glucose

BackgroundL-Tyrosine (L-Tyr) is a significant aromatic amino acid that is experiencing an increasing demand in the market due to its distinctive characteristics. Traditional production methods exhibit various limitations, prompting researchers to place greater emphasis on microbial synthesis as an alternative approach.ResultsHere, we developed a metabolic engineering-based method for efficient production of L-Tyr from Corynebacterium crenatum, including the elimination of competing pathways, the overexpression of aroB, aroD, and aroE, and the introduction of the mutated E. coli tyrAfbr gene for elevating L-Tyr generation. Moreover, the mtlR gene was knocked out, and the mtlD and pfkB genes were overexpressed, allowing C. crenatum to produce L-Tyr from mannitol. The L-Tyr production achieved 6.42 g/L at a glucose-to-mannitol ratio of 3:1 in a shake flask, which was 16.9% higher than that of glucose alone. Notably, the L-Tyr production of the fed-batch fermentation was elevated to 34.6 g/L, exhibiting the highest titers among those of C. glutamicum previously reported.ConclusionThe importance of this research is underscored by its pioneering application of mannitol as a carbon source for the biosynthesis of L-Tyr, as well as its examination of the influence of mannitol-associated genes in microbial metabolism. A promising platform is provided for the production of target compounds that does not compete with human food source.