EgMADS3 directly regulates EgLPAAT to mediate medium-chain fatty acids (MCFA) anabolism in the mesocarp of oil palm.

KEY MESSAGE: EgMADS3, a pivotal transcription factor, positively regulates MCFA accumulation via binding to the EgLPAAT promoter, advancing lipid content in mesocarp of oil palm. Lipids function as the structural components of cell membranes, which serve as permeable barriers to the external environment of cells. The medium-chain fatty acid in the stored lipids of plants is an important renewable energy. Most research on MCFA production in plant lipid synthesis is based on biochemical methods, and the importance of transcriptional regulation in MCFA synthesis and its incorporation into TAGs needs further research. Oil palm is the most productive oil crop in the world and has the highest productivity among the main oil crops. In this study, the MADS transcription factor (EgMADS3) in the mesocarp of oil palm was characterized. Through the VIGS-virus induced gene silencing, it was determined that the potential target gene of EgMADS3 was related to the biosynthesis of medium-chain fatty acid (MCFA). Transient transformation in protoplasts and qRT-PCR analysis showed that EgMADS3 positively regulated the expression of EgLPAAT. The results of the yeast one-hybrid assays and EMSA indicated the interaction between EgMADS3 and EgLPAAT promoter. Through genetic transformation and fatty acid analysis, it is concluded that EgMADS3 directly regulates the mid-chain fatty acid synthesis pathway of the potential target gene EgLPAAT, thus promotes the accumulation of MCFA and improves the total lipid content. This study is innovative in the functional analysis of the MADS family transcription factor in the metabolism of medium-chain fatty acids (MCFA) of oil palm, provides a certain research basis for improving the metabolic pathway of chain fatty acids in oil palm, and improves the synthesis of MCFA in plants. Our results will provide a reference direction for further research on improving the oil quality through biotechnology of oil palm.

Metabolic Pathway Coupled with Fermentation Process Optimization for High-Level Production of Retinol in Yarrowia lipolytica.

Retinol is a lipid-soluble form of vitamin A that is crucial for human visual and immune functions. The production of retinol through microbial fermentation has been the focus of recent exploration. However, the obtained titer remains limited and the product is often a mixture of retinal, retinol, and retinoic acid, necessitating purification. To achieve efficient biosynthesis of retinol in Yarrowia lipolytica, we improved the metabolic flux of ß-carotene to provide sufficient precursors for retinol in this study. Coupled with the optimization of the expression level of ß-carotene 15,15'-dioxygenase, de novo production of retinol was achieved. Furthermore, Tween 80 was used as an extractant and butylated hydroxytoluene as an antioxidant to extract intracellular retinol and prevent retinol oxidation, respectively. This strategy significantly increased the level of retinol production. By optimizing the enzymes converting retinal to retinol, the proportion of extracellular retinol in the produced retinoids reached 100%, totaling 1042.3 mg/L. Finally, total retinol production reached 5.4 g/L through fed-batch fermentation in a 5 L bioreactor, comprising 4.2 g/L extracellular retinol and 1.2 g/L intracellular retinol. This achievement represents the highest reported titer so far and advances the industrial production of retinol.

Melosira nummuloides Ethanol Extract Ameliorates Alcohol-Induced Liver Injury by Affecting Metabolic Pathways.

Melosira nummuloides is a microalga with a nutritionally favorable polyunsaturated fatty acid profile. In the present study, M. nummuloides ethanol extract (MNE) was administered to chronic-binge alcohol-fed mice and alcohol-treated HepG2 cells, and its hepatoprotective effects and underlying mechanisms were investigated. MNE administration reduced triglyceride (TG), total cholesterol (T-CHO), and liver injury markers, including aspartate transaminase (AST) and alanine transaminase (ALT), in the serum of chronic-binge alcohol-fed mice. However, MNE administration increased the levels of phosphorylated adenosine monophosphate-activated protein kinase (P-AMPK/AMPK) and PPARα, which was accompanied by a decrease in SREBP-1; this indicates that MNE can inhibit adipogenesis and improve fatty acid oxidation. Moreover, MNE administration upregulated the expression of antioxidant enzymes, including SOD, NAD(P)H quinone dehydrogenase 1, and GPX, and ameliorated alcohol-induced inflammation by repressing the Akt/NFκB/COX-2 pathway. Metabolomic analysis revealed that MNE treatment modulated many lipid metabolites in alcohol-treated HepG2 cells. Our study findings provide evidence for the efficacy and mechanisms of MNE in ameliorating alcohol-induced liver injury.

Targeting nucleotide metabolic pathways in colorectal cancer by integrating scRNA-seq, spatial transcriptome, and bulk RNA-seq data.

BACKGROUND: Colorectal cancer is a malignant tumor of the digestive system originating from abnormal cell proliferation in the colon or rectum, often leading to gastrointestinal symptoms and severe health issues. Nucleotide metabolism, which encompasses the synthesis of DNA and RNA, is a pivotal cellular biochemical process that significantly impacts both the progression and therapeutic strategies of colorectal cancer METHODS: For single-cell RNA sequencing (scRNA-seq), five functions were employed to calculate scores related to nucleotide metabolism. Cell developmental trajectory analysis and intercellular interaction analysis were utilized to explore the metabolic characteristics and communication patterns of different epithelial cells. These findings were further validated using spatial transcriptome RNA sequencing (stRNA-seq). A risk model was constructed using expression profile data from TCGA and GEO cohorts to optimize clinical decision-making. Key nucleotide metabolism-related genes (NMRGs) were functionally validated by further in vitro experiments. RESULTS: In both scRNA-seq and stRNA-seq, colorectal cancer (CRC) exhibited unique cellular heterogeneity, with myeloid cells and epithelial cells in tumor samples displaying higher nucleotide metabolism scores. Analysis of intercellular communication revealed enhanced signaling pathways and ligand-receptor interactions between epithelial cells with high nucleotide metabolism and fibroblasts. Spatial transcriptome sequencing confirmed elevated nucleotide metabolism states in the core region of tumor tissue. After identifying differentially expressed NMRGs in epithelial cells, a risk prognostic model based on four genes effectively predicted overall survival and immunotherapy outcomes in patients. High-risk group patients exhibited an immunosuppressive microenvironment and relatively poorer prognosis and responses to chemotherapy and immunotherapy. Finally, based on data analysis and a series of cellular functional experiments, ACOX1 and CPT2 were identified as novel therapeutic targets for CRC. CONCLUSION: In this study, a comprehensive analysis of NMRGs in CRC was conducted using a combination of single-cell sequencing, spatial transcriptome sequencing, and high-throughput data. The prognostic model constructed with NMRGs shows potential as a standalone prognostic marker for colorectal cancer patients and may significantly influence the development of personalized treatment approaches for CRC.

Logic programming-based Minimal Cut Sets reveal consortium-level therapeutic targets for chronic wound infections.

Minimal Cut Sets (MCSs) identify sets of reactions which, when removed from a metabolic network, disable certain cellular functions. The traditional search for MCSs within genome-scale metabolic models (GSMMs) targets cellular growth, identifies reaction sets resulting in a lethal phenotype if disrupted, and retrieves a list of corresponding gene, mRNA, or enzyme targets. Using the dual link between MCSs and Elementary Flux Modes (EFMs), our logic programming-based tool aspefm was able to compute MCSs of any size from GSMMs in acceptable run times. The tool demonstrated better performance when computing large-sized MCSs than the mixed-integer linear programming methods. We applied the new MCSs methodology to a medically-relevant consortium model of two cross-feeding bacteria, Staphylococcus aureus and Pseudomonas aeruginosa. aspefm constraints were used to bias the computation of MCSs toward exchanged metabolites that could complement lethal phenotypes in individual species. We found that interspecies metabolite exchanges could play an essential role in rescuing single-species growth, for instance inosine could complement lethal reaction knock-outs in the purine synthesis, glycolysis, and pentose phosphate pathways of both bacteria. Finally, MCSs were used to derive a list of promising enzyme targets for consortium-level therapeutic applications that cannot be circumvented via interspecies metabolite exchange.

Enhanced protein-metabolite correlation analysis: To investigate the association between Staphylococcus aureus mastitis and metabolic immune pathways.

Mastitis is a disease characterized by congestion, swelling, and inflammation of the mammary gland and usually caused by infection with pathogenic microorganisms. Furthermore, the development of mastitis is closely linked to the exogenous pathway of the gastrointestinal tract. However, the regulatory mechanisms governing the gut-metabolism-mammary axis remain incompletely understood. The present study revealed alterations in the gut microbiota of mastitis rats characterized by an increased abundance of the Proteobacteria phylum. Plasma analysis revealed significantly higher levels of L-isoleucine and cholic acid along with 7-ketodeoxycholic acid. Mammary tissue showed elevated levels of arachidonic acid metabolites and norlithocholic acid. Proteomic analysis showed increased levels of IFIH1, Tnfaip8l2, IRGM, and IRF5 in mastitis rats, which suggests that mastitis triggers an inflammatory response and immune stress. Follistatin (Fst) and progesterone receptor (Pgr) were significantly downregulated, raising the risk of breast cancer. Extracellular matrix (ECM) receptors and focal adhesion signaling pathways were downregulated, while blood-milk barrier integrity was disrupted. Analysis of protein-metabolic network regulation revealed that necroptosis, protein digestion and absorption, and arachidonic acid metabolism were the principal regulatory pathways involved in the development of mastitis. In short, the onset of mastitis leads to changes in the microbiota and alterations in the metabolic profiles of various biological samples, including colonic contents, plasma, and mammary tissue. Key manifestations include disturbances in bile acid metabolism, amino acid metabolism, and arachidonic acid metabolism. At the same time, the integrity of the blood-milk barrier is compromised while inflammation is promoted, thereby reducing cell adhesion in the mammary glands. These findings contribute to a more comprehensive understanding of the metabolic status of mastitis and provide new insights into its impact on the immune system.

A Practical Guide to the Representation of Protein Regulation in the Web Application ChloroKB.

ChloroKB ( http://chlorokb.fr ) is a knowledge base providing synoptic representations of the metabolism of the model plant Arabidopsis thaliana and its regulation. Initially focused on plastid metabolism, ChloroKB now accounts for the metabolism throughout the cell. ChloroKB is based on the CellDesigner formalism. CellDesigner supports graphical notation and listing of the corresponding symbols based on the Systems Biology Graphical Notation. Thus, this formalism allows biologists to represent detailed biochemical processes in a way that can be easily understood and shared, facilitating communication between researchers. In this chapter, we will focus on a specificity of ChloroKB, the representation of multilayered regulation of protein activity. Information on regulation of protein activity is indeed central to understanding the plant response to fluctuating environmental conditions. However, the intrinsic diversity of the regulatory modes and the abundance of detail may hamper comprehension of the regulatory processes described in ChloroKB. With this chapter, ChloroKB users will be guided through the representation of these sophisticated biological processes of prime importance to understanding metabolism or for applied purposes. The descriptions provided, which summarize years of work and a broad bibliography in a few pages, can help speed up the integration of regulatory processes in kinetic models of plant metabolism.

Exhaled breath and urinary volatile organic compounds (VOCs) for cancer diagnoses, and microbial-related VOC metabolic pathway analysis: a systematic review and meta-analysis.

BACKGROUND: The gradual evolution of the detection and quantification of volatile organic compounds (VOCs) has been instrumental in cancer diagnosis. The primary objective of this study was to assess the diagnostic potential of exhaled breath and urinary VOCs in cancer detection. As VOCs are indicative of tumor and human metabolism, our work also sought to investigate the metabolic pathways linked to the development of cancerous tumors. MATERIALS AND METHODS: An electronic search was performed in the PubMed database. Original studies on VOCs within exhaled breath and urine for cancer detection with a control group were included. A meta-analysis was conducted using a bivariate model to assess the sensitivity and specificity of the VOCs for cancer detection. Fagan's nomogram was designed to leverage the findings from our diagnostic analysis for the purpose of estimating the likelihood of cancer in patients. Ultimately, MetOrigin was employed to conduct an analysis of the metabolic pathways associated with VOCs in relation to both human and/or microbiota. RESULTS: The pooled sensitivity, specificity and the area under the curve for cancer screening utilizing exhaled breath and urinary VOCs were determined to be 0.89, 0.88, and 0.95, respectively. A pretest probability of 51% can be considered as the threshold for diagnosing cancers with VOCs. As the estimated pretest probability of cancer exceeds 51%, it becomes more appropriate to emphasize the 'ruling in' approach. Conversely, when the estimated pretest probability of cancer falls below 51%, it is more suitable to emphasize the 'ruling out' approach. A total of 14, 14, 6, and 7 microbiota-related VOCs were identified in relation to lung, colorectal, breast, and liver cancers, respectively. The enrichment analysis of volatile metabolites revealed a significant enrichment of butanoate metabolism in the aforementioned tumor types. CONCLUSIONS: The analysis of exhaled breath and urinary VOCs showed promise for cancer screening. In addition, the enrichment analysis of volatile metabolites revealed a significant enrichment of butanoate metabolism in four tumor types, namely lung, colorectum, breast and liver. These findings hold significant implications for the prospective clinical application of multiomics correlation in disease management and the exploration of potential therapeutic targets.

Design of a cofactor self-sufficient whole-cell biocatalyst for enzymatic asymmetric reduction via engineered metabolic pathways and multi-enzyme cascade.

NAD(P)H-dependent oxidoreductases are crucial biocatalysts for synthesizing chiral compounds. Yet, the industrial implementation of enzymatic redox reactions is often hampered by an insufficient supply of expensive nicotinamide cofactors. Here, a cofactor self-sufficient whole-cell biocatalyst was developed for the enzymatic asymmetric reduction of 2-oxo-4-[(hydroxy)(-methyl)phosphinyl] butyric acid (PPO) to L-phosphinothricin (L-PPT). The endogenous NADP+ pool was significantly enhanced by regulating Preiss-Handler pathway toward NAD(H) synthesis and, in the meantime, introducing NAD kinase to phosphorylate NAD(H) toward NADP+. The intracellular NADP(H) concentration displayed a 2.97-fold increase with the strategy compared with the wild-type strain. Furthermore, a recombinant multi-enzyme cascade biocatalytic system was constructed based on the Escherichia coli chassis. In order to balance multi-enzyme co-expression levels, the strategy of modulating rate-limiting enzyme PmGluDH by RBS strengths regulation successfully increased the catalytic efficiency of PPO conversion. Finally, the cofactor self-sufficient whole-cell biocatalyst effectively converted 300 mM PPO to L-PPT in 2 h without the need to add exogenous cofactors, resulting in a 2.3-fold increase in PPO conversion (%) from 43% to 100%, with a high space-time yield of 706.2 g L-1 d-1 and 99.9% ee. Overall, this work demonstrates a technological example for constructing a cofactor self-sufficient system for NADPH-dependent redox biocatalysis.

Photoheterotroph improved the growth and nutrient levels of Chlorella vulgaris and the related molecular mechanism.

Microalgae are rich in fatty acids, proteins, and other nutrients, which have gained the general attention of researchers all over the world. For the development of Chlorella vulgaris in food and feed industry, this study was conducted to investigate the differences in C. vulgaris' growth and nutritional components under different culture conditions (autotrophic, heterotrophic, photoheterotrophic) and the internal factors through cell counting in combination with transcriptome and nutrient analyses. The results showed that, under the photoheterotrophic condition, Chlorella's growth and the contents of lipid and protein were significantly higher than that under the heterotrophic condition, and the moisture content was lower than that under the heterotrophic condition. The saturated fatty acid content under the photoheterotrophic condition was the lowest, while the polyunsaturated fatty acid content was significantly higher than those under the other two conditions. There were 46,583 differentially expressed genes (DEGs), including 33,039 up-regulated DEGs (70.93%) and 13,544 down-regulated DEGs (29.07%), under the photoheterotrophic condition in comparison with the autotrophic condition. The fold change between the two conditions of samples of up-regulated genes was higher than that of the down-regulated genes. The KEGG enrichment showed that the up-regulated DEGs in the photoheterotrophic condition were significantly enriched in 5 pathways, including protein processing in endoplasmic reticulum pathway, photosynthesis pathway, photosynthesis-antenna protein pathway, endocytosis pathway, and phosphonate and phosphinate metabolism pathway. DEGs related to fatty acid metabolic pathways were significantly enriched in the fatty acid biosynthesis pathway and the biosynthesis of unsaturated fatty acid pathway. The qPCR analysis showed that the expression pattern of the selected genes was consistent with that of transcriptome analysis. The results of this study lay a theoretical foundation for the large-scale production of Chlorella and its application in food, feed, and biodiesel. KEY POINTS: • Nutrient levels under photoheterotrophic condition were higher than other conditions. • Six important pathways were discovered that affect changes in nutritional composition. • Explored genes encode important enzymes in the differential metabolic pathways.

Unlocking the potential of T-cell metabolism reprogramming: Advancing single-cell approaches for precision immunotherapy in tumour immunity.

As single-cell RNA sequencing enables the detailed clustering of T-cell subpopulations and facilitates the analysis of T-cell metabolic states and metabolite dynamics, it has gained prominence as the preferred tool for understanding heterogeneous cellular metabolism. Furthermore, the synergistic or inhibitory effects of various metabolic pathways within T cells in the tumour microenvironment are coordinated, and increased activity of specific metabolic pathways generally corresponds to increased functional activity, leading to diverse T-cell behaviours related to the effects of tumour immune cells, which shows the potential of tumour-specific T cells to induce persistent immune responses. A holistic understanding of how metabolic heterogeneity governs the immune function of specific T-cell subsets is key to obtaining field-level insights into immunometabolism. Therefore, exploring the mechanisms underlying the interplay between T-cell metabolism and immune functions will pave the way for precise immunotherapy approaches in the future, which will empower us to explore new methods for combating tumours with enhanced efficacy.

Construction of 5-Aminolevulinic Acid Microbial Cell Factories through Identification of Novel Synthases and Metabolic Pathway Screens and Transporters.

5-Aminolevulinic acid (5-ALA) plays a pivotal role in the biosynthesis of heme and chlorophyll and has garnered great attention for its agricultural applications. This study explores the multifaceted construction of 5-ALA microbial cell factories. Evolutionary analysis-guided screening identified a novel 5-ALA synthase from Sphingobium amiense as the best synthase. An sRNA library facilitated global gene screening that demonstrated that trpC and ilvA repression enhanced 5-ALA production by 74.3% and 102%, respectively. Subsequently, efflux of 5-ALA by the transporter Gdx increased 5-ALA biosynthesis by 25.7%. To mitigate oxidative toxicity, DNA-binding proteins from starved cells were employed, enhancing cell density and 5-ALA titer by 21.1 and 4.1%, respectively. Combining these strategies resulted in an Escherichia coli strain that produced 5-ALA to 1.51 g·L-1 in shake flask experiments and 6.19 g·L-1 through fed-batch fermentation. This study broadens the repertoire of available 5-ALA synthases and transporters and provides a new platform for optimizing 5-ALA bioproduction.

A dynamic model of growth phase of bio-conversion of methane to polyhydroxybutyrate using dynamic flux balance analysis.

Biological conversion of waste methane to biodegradable plastics is a way of reducing their production cost. This study addresses the computational modeling of the growth phase reactor of the process of polyhydroxybutyrate production. The model was used for investigating the effect of gas recycling and inlet gas retention time on the reactor performance. The model was run by the use of a genome-scale metabolic network of Methylocystis hirsuta in a dynamic flux balance analysis framework. The reactor has been modeled for two separate feeding scenarios: a pure methane feed and a biogas feed. The mass transfer coefficient parameter was predicted as a function of superficial gas velocities by the regression of data from published experiments. The results show an increase of removal efficiency by 38% and biomass concentration by 2.8 g/L with the increase of gas recycle ratio from 0 to 30 at the empty bed residence time of 60  min .

Revealing the biological significance of multiple metabolic pathways of chloramphenicol by Sphingobium sp. WTD-1.

Chloramphenicol (CAP) is an antibiotic that commonly pollutes the environment, and microorganisms primarily drive its degradation and transformation. Although several pathways for CAP degradation have been documented in different bacteria, multiple metabolic pathways in the same strain and their potential biological significance have not been revealed. In this study, Sphingobium WTD-1, which was isolated from activated sludge, can completely degrade 100 mg/L CAP within 60 h as the sole energy source. UPLC-HRMS and HPLC analyses showed that three different pathways, including acetylation, hydroxyl oxidation, and oxidation (C1-C2 bond cleavage), are responsible for the metabolism of CAP. Importantly, acetylation and C3 hydroxyl oxidation reduced the cytotoxicity of the substrate to strain WTD-1, and the C1-C2 bond fracture of CAP generated the metabolite p-nitrobenzoic acid (PNBA) to provide energy for its growth. This indicated that the synergistic action of three metabolic pathways caused WTD-1 to be adaptable and able to degrade high concentrations of CAP in the environment. This study deepens our understanding of the microbial degradation pathway of CAP and highlights the biological significance of the synergistic metabolism of antibiotic pollutants by multiple pathways in the same strain.

The hidden treasures in endophytic fungi: a comprehensive review on the diversity of fungal bioactive metabolites, usual analytical methodologies, and applications.

This review provides a comprehensive overview of the key aspects of the natural metabolite production by endophytic fungi, which has attracted significant attention due to its diverse biological activities and wide range of applications. Synthesized by various fungal species, these metabolites encompass compounds with therapeutic, agricultural, and commercial significance. We delved into strategies and advancements aimed at optimizing fungal metabolite production. Fungal cultivation, especially by Aspergillus, Penicillium, and Fusarium, plays a pivotal role in metabolite biosynthesis, and researchers have explored both submerged and solid-state cultivation processes to harness the full potential of fungal species. Nutrient optimization, pH, and temperature control are critical factors in ensuring high yields of the targeted bioactive metabolites especially for scaling up processes. Analytical methods that includes High-Performance Liquid Chromatography (HPLC), Liquid Chromatography-Mass Spectrometry (LC-MS), Gas Chromatography-Mass Spectrometry (GC-MS), Nuclear Magnetic Resonance (NMR), and Mass Spectrometry (MS), are indispensable for the identification and quantification of the compounds. Moreover, genetic engineering and metabolic pathway manipulation have emerged as powerful tools to enhance metabolite production and develop novel fungal strains with increased yields. Regulation and control mechanisms at the genetic, epigenetic, and metabolic levels are explored to fine-tune the biosynthesis of fungal metabolites. Ongoing research aims to overcome the complexity of the steps involved to ensure the efficient production and utilization of fungal metabolites.

Stable States of a Microbial Community Are Formed by Dynamic Metabolic Networks with Members Functioning to Achieve Both Robustness and Plasticity.

A more detailed understanding of the mechanisms underlying the formation of microbial communities is essential for the efficient management of microbial ecosystems. The stable states of microbial communities are commonly perceived as static and, thus, have not been extensively examined. The present study investigated stabilizing mechanisms, minority functions, and the reliability of quantitative ana-lyses, emphasizing a metabolic network perspective. A bacterial community, formed by batch transferred cultures supplied with phenol as the sole carbon and energy source and paddy soil as the inoculum, was analyzed using a principal coordinate ana-lysis (PCoA), mathematical models, and quantitative parameters defined as growth activity, community-changing activity, community-forming activity, vulnerable force, and resilience force depending on changes in the abundance of operational taxonomic units (OTUs) using 16S rRNA gene amplicon sequences. PCoA showed succession states until the 3rd transferred cultures and stable states from the 5th to 10th transferred cultures. Quantitative parameters indicated that the bacterial community was dynamic irrespective of the succession and stable states. Three activities fluctuated under stable states. Vulnerable and resilience forces were detected under the succession and stable states, respectively. Mathematical models indicated the construction of metabolic networks, suggesting the stabilizing mechanism of the community structure. Thirteen OTUs coexisted during stable states, and were recognized as core OTUs consisting of majorities, middle-class, and minorities. The abundance of the middle-class changed, whereas that of the others did not, which indicated that core OTUs maintained metabolic networks. Some extremely low abundance OTUs were consistently exchanged, suggesting a role for scavengers. These results indicate that stable states were formed by dynamic metabolic networks with members functioning to achieve robustness and plasticity.

Metabolites alterations associated with obesity: A scoping review.

INTRODUCTION: Obesity can be considered a major public health concern throughout the world. Various studies have been conducted to combat the rising number of cases of this health problem. Therefore, identifying the roots of the disease is critical in developing the desperately needed treatment approaches. However, in order to fully understand the origin of this disease, figuring out the metabolites present, and the alterations that occurred in a particular metabolism are crucial, and the information regarding the metabolites involved is limited. The aim of this study is to analyse the literature relevant to the metabolites involved in obesity conditions through a scoping review. MATERIALS AND METHODS: This review utilises three databases (SCOPUS, Science Direct, and PubMed). The search phrases used are (Metabolomic* OR Metabolite*) for metabolomic study, (3T3-L1 OR Adipocyte OR "Adipose Tissue") for experimental design, and (Obesity) for obesity condition. Each of the search keywords was separated by an "AND" term in the databases. Other terms related to obesity, such as insulin resistance, heart disease, type 2 diabetes, muscular disorders, respiratory problems, and psychological problems were omitted because they did not contribute to the total number of studies discovered. RESULTS: A total of 27 research publications were included in this scoping review. Most of the study focuses on metabolomics in obesity. Metabolites detected were found in various metabolic pathways including amino acids, carbohydrates, lipids as well as other metabolisms. Most of these metabolites discovered in obese conditions showed an alteration when compared to the level of the metabolite in normal conditions. CONCLUSION: Unfortunately, these studies had some limitations in which the metabolites detected varied between the articles and the information concerning the relationship between the technique or instrument utilised and the metabolites detected in the samples were not well described. Therefore, using the findings obtained in this study, it can help to determine the direction of the study in the future.

Tartary buckwheat rutin: Accumulation, metabolic pathways, regulation mechanisms, and biofortification strategies.

Rutin is a significant flavonoid with strong antioxidant property and various therapeutic effects. It plays a crucial role in disease prevention and human health maintenance, especially in anti-inflammatory, antidiabetic, hepatoprotective and cardiovascular effects. While many plants can synthesize and accumulate rutin, tartary buckwheat is the only food crop possessing high levels of rutin. At present, the rutin content (RC) is regarded as the key index for evaluating the nutritional quality of tartary buckwheat. Consequently, rutin has become the focus for tartary buckwheat breeders and has made considerable progress. Here, we summarize research on the rutin in tartary buckwheat in the past two decades, including its accumulation, biosynthesis and breakdown pathways, and regulatory mechanisms. Furthermore, we propose several strategies to increase the RC in tartary buckwheat seeds based on current knowledge. This review aims to provide valuable references for elevating the quality of tartary buckwheat in the future.

Using design of experiments to guide genetic optimization of engineered metabolic pathways.

Design of experiments (DoE) is a term used to describe the application of statistical approaches to interrogate the impact of many variables on the performance of a multivariate system. It is commonly used for process optimization in fields such as chemical engineering and material science. Recent advances in the ability to quantitatively control the expression of genes in biological systems open up the possibility to apply DoE for genetic optimization. In this review targeted to genetic and metabolic engineers, we introduce several approaches in DoE at a high level and describe instances wherein these were applied to interrogate or optimize engineered genetic systems. We discuss the challenges of applying DoE and propose strategies to mitigate these challenges. ONE-SENTENCE SUMMARY: This is a review of literature related to applying Design of Experiments for genetic optimization.

Transposon sequencing reveals metabolic pathways essential for Mycobacterium tuberculosis infection.

New drugs are needed to shorten and simplify treatment of tuberculosis caused by Mycobacterium tuberculosis. Metabolic pathways that M. tuberculosis requires for growth or survival during infection represent potential targets for anti-tubercular drug development. Genes and metabolic pathways essential for M. tuberculosis growth in standard laboratory culture conditions have been defined by genome-wide genetic screens. However, whether M. tuberculosis requires these essential genes during infection has not been comprehensively explored because mutant strains cannot be generated using standard methods. Here we show that M. tuberculosis requires the phenylalanine (Phe) and de novo purine and thiamine biosynthetic pathways for mammalian infection. We used a defined collection of M. tuberculosis transposon (Tn) mutants in essential genes, which we generated using a custom nutrient-rich medium, and transposon sequencing (Tn-seq) to identify multiple central metabolic pathways required for fitness in a mouse infection model. We confirmed by individual retesting and complementation that mutations in pheA (Phe biosynthesis) or purF (purine and thiamine biosynthesis) cause death of M. tuberculosis in the absence of nutrient supplementation in vitro and strong attenuation in infected mice. Our findings show that Tn-seq with defined Tn mutant pools can be used to identify M. tuberculosis genes required during mouse lung infection. Our results also demonstrate that M. tuberculosis requires Phe and purine/thiamine biosynthesis for survival in the host, implicating these metabolic pathways as prime targets for the development of new antibiotics to combat tuberculosis.