Identification of metabolic biomarkers in idiopathic pulmonary arterial hypertension using targeted metabolomics and bioinformatics analysis.

Pulmonary arterial hypertension (PAH) is a life-threatening disease with a poor prognosis, and metabolic abnormalities play a critical role in its development. This study used metabolomics, machine learning algorithms and bioinformatics to screen for potential metabolic biomarkers associated with the diagnosis of PAH. In this study, plasma samples were collected from 17 patients diagnosed with idiopathic pulmonary arterial hypertension (IPAH) and 20 healthy controls. Plasma metabolomic profiling was performed by high-performance liquid chromatography-mass spectrometry. Gene profiles of PAH patients were obtained from the GEO database. Key differentially expressed metabolites (DEMs) and metabolism-related genes were subsequently identified using machine learning algorithms. Twenty differential plasma metabolites associated with IPAH were identified (VIP score > 1 and p < 0 0.05), and enrichment analysis revealed the arginine biosynthesis pathway as the most altered pathway. Using machine learning models, including least absolute shrinkage and selection operator (LASSO), random forest (RF) and support vector machine (SVM), we extracted key metabolites that correlated with clinical phenotypes. Our results suggested that five metabolites, kynurenine, homoserine, tryptophan, AMP, and spermine, are potential biomarkers for IPAH. Bioinformatics analysis also identified 3 metabolism-related genes, MAPK6, SLC7A11 and CDC42BPA, that are strongly correlated with pulmonary hypertension, demonstrating strong predictive power and clinical relevance. Our findings revealed some key genes associated with metabolism in PH, and provided crucial information about complex metabolic reprogramming signals and may lead to the identification of useful metabolic biomarkers for the diagnosis of PAH.

Unraveling Cecal Alterations in Clostridioides difficile Colonized Mice through Comprehensive Metabolic Profiling.

The disruption of gut microbiota caused by antibiotics favors the intestinal colonization of Clostridioides difficile - a Gram-positive, spore-forming anaerobic bacterium that causes potentially fatal gastrointestinal infections. In an endeavor to elucidate the complexities of the gut-brain axis in the context of Clostridium difficile infection (CDI), a murine model has been used to investigate the potential effects of antibiotic administration and subsequent colonization by C. difficile, as well as the impact of three different 10-day treatments (metronidazole, probiotics, and fecal microbiota transplantation), on the cecal metabolome for the first time. This follows our previous research which highlighted the metabolic effect of CDI and these treatments in the brain and employs the same four different metabolomics-based methods (targeted GC-MS/MS, targeted HILIC-MS/MS, untargeted RP-LC-HRMS/MS and untargeted GC-MS). A total of 286 unique metabolites have been identified in the mouse cecal profiles and statistical analysis revealed that CDI, as well as the subsequent treatments, significantly alters cecal metabolites and lipids implicated in various biochemical pathways centered around amino acid metabolism, glycerophospholipid metabolism, and central carbon metabolism. To our knowledge, this study represents the first exploration of the effects of C. difficile-induced colitis and potential treatments on the cecal tissue metabolome.

Recent progress of methods for cuproptosis detection.

Varying from other identified cell death pathways, cuproptosis is a new type of regulated cell death characterized by excess Cu ions, abnormal aggregation of lipoylated proteins in TCA cycle, loss of Fe-S cluster proteins, upregulation of HSP70, leading to proteotoxic and oxidative stress. Cuproptosis is highly concerned by scientific community and as the field of cuproptosis further develops, remarkable progress has been made in the verification and mechanism of cuproptosis, and methods used to detect cuproptosis have been continuously improved. According to the characteristic changes of cuproptosis, techniques based on cell death verification, Cu content, morphology, molecular biology of protein levels of cuproptosis-related molecules and biochemical pathways of cuproptosis-related enzyme activity and metabolites of oxidative stress, lipoic acid, TCA cycle, Fe-S cluster proteins, oxidative phosphorylation, cell respiration intensity have been subject to cuproptosis verification and research. In order to further deepen the understanding of detecting cuproptosis, the principle and application of common cuproptosis detection methods are reviewed and categorized in cellular phenomena and molecular mechanism in terms of cell death, Cu content, morphology, molecular biology, biochemical pathways with a flow chart. All the indicating results have been displayed in response to the markers of cuproptosis, their advantages and limitations are summaried, and comparison of cuproptosis and ferroptosis detection is performed in this study. Our collection of methods for cuproptosis detection will provide a great basis for cuproptosis verification and research in the future.

Tuning and modeling cheese flavor.

Flavor is a major sensory attribute affecting consumers' preference for cheese products. Differences in cheesemaking change the cheese microenvironment, thereby affecting cheese flavor profiles. A framework for tuning cheese flavor is proposed in this study, which depicts the full picture of flavor development and modulation, from manufacturing and ripening factors through the main biochemical pathways to flavor compounds and flavor notes. Taking semi-hard and hard cheeses as examples, this review describes how cheese flavor profiles are affected by milk type and applied treatment, fat and salt content, microbiota composition and microbial interactions, ripening time, temperature, and environmental humidity, together with packaging method and material. Moreover, these factors are linked to flavor profiles through their effects on proteolysis, the further catabolism of amino acids, and lipolysis. Acids, alcohols, ketones, esters, aldehydes, lactones, and sulfur compounds are key volatiles, which elicit fruity, sweet, rancid, green, creamy, pungent, alcoholic, nutty, fatty, and sweaty flavor notes, contributing to the overall flavor profiles. Additionally, this review demonstrates how data-driven modeling techniques can link these influencing factors to resulting flavor profiles. This is done by providing a comprehensive review on the (i) identification of key factors and flavor compounds, (ii) discrimination of cheeses, and (iii) prediction of flavor notes. Overall, this review provides knowledge tools for cheese flavor modulation and sheds light on using data-driven modeling techniques to aid cheese flavor analysis and flavor prediction.

Integrated transcriptomic and proteomic analysis of exogenous abscisic acid regulation on tuberous root development in Pseudostellaria heterophylla.

Abscisic acid (ABA) significantly regulates plant growth and development, promoting tuberous root formation in various plants. However, the molecular mechanisms of ABA in the tuberous root development of Pseudostellaria heterophylla are not yet fully understood. This study utilized Illumina sequencing and de novo assembly strategies to obtain a reference transcriptome associated with ABA treatment. Subsequently, integrated transcriptomic and proteomic analyses were used to determine gene expression profiles in P. heterophylla tuberous roots. ABA treatment significantly increases the diameter and shortens the length of tuberous roots. Clustering analysis identified 2,256 differentially expressed genes and 679 differentially abundant proteins regulated by ABA. Gene co-expression and protein interaction networks revealed ABA positively induced 30 vital regulators. Furthermore, we identified and assigned putative functions to transcription factors (PhMYB10, PhbZIP2, PhbZIP, PhSBP) that mediate ABA signaling involved in the regulation of tuberous root development, including those related to cell wall metabolism, cell division, starch synthesis, hormone metabolism. Our findings provide valuable insights into the complex signaling networks of tuberous root development modulated by ABA. It provided potential targets for genetic manipulation to improve the yield and quality of P. heterophylla, which could significantly impact its cultivation and medicinal value.

Revealing the effects of amino acid, organic acid, and phytohormones on the germination of tomato seeds under salinity stress.

Salinity accumulation poses a threat to the production and productivity of economically important crops such as tomatoes (Solanum lycopersicum L.). Currently, salt tolerance breeding programs have been limited by insufficient genetic and physiological knowledge of tolerance-related traits and a lack of an efficient selection domain. For that purpose, we aimed to determine the ability of tomato cultivars to tolerate salt based on seed traits by multiple biochemical pathways. First, we tested three tomato cultivars according to their response to different sodium chloride (NaCl) concentrations (0, 6.3, 9.8, 13.0, and 15.8 dS m-1) and then we analysed their amino acids, organic acids, and phytohormones. Considering the results of germination traits, it is possible to conclude that cultivar H-2274 was more tolerant to salt stress than others. As a result, multivariate discriminant analysis including principal component analysis and two-way hierarchical clustering analyses were constructed and demonstrated that tomato cultivars were separated from each other by the amino acid, organic acid, and phytohormone contents. Considering germination traits of tomato seeds, cv. 'H-2274' was more tolerant to salinity than others depending on high proline (29 pmol µl-1) and citric acid (568 ng µl-1) assays. Biochemical variability offers a valuable tool for investigating salt tolerance mechanisms in tomatoes, and it will be appreciated to find high-tolerant tomato cultivar(s) to saline conditions. Also, the findings of this study have significant potential for practical applications in agriculture, particularly in developing salt-tolerant tomato cultivars to enhance productivity in saline environments and address socio-economic challenges.

Bacterial microcompartments as a next-generation metabolic engineering tool: utilizing nature's solution for confining challenging catabolic pathways.

Advancements in synthetic biology have facilitated the incorporation of heterologous metabolic pathways into various bacterial chassis, leading to the synthesis of targeted bioproducts. However, total output from heterologous production pathways can suffer from low flux, enzyme promiscuity, formation of toxic intermediates, or intermediate loss to competing reactions, which ultimately hinder their full potential. The self-assembling, easy-to-modify, protein-based bacterial microcompartments (BMCs) offer a sophisticated way to overcome these obstacles by acting as an autonomous catalytic module decoupled from the cell's regulatory and metabolic networks. More than a decade of fundamental research on various types of BMCs, particularly structural studies of shells and their self-assembly, the recruitment of enzymes to BMC shell scaffolds, and the involvement of ancillary proteins such as transporters, regulators, and activating enzymes in the integration of BMCs into the cell's metabolism, has significantly moved the field forward. These advances have enabled bioengineers to design synthetic multi-enzyme BMCs to promote ethanol or hydrogen production, increase cellular polyphosphate levels, and convert glycerol to propanediol or formate to pyruvate. These pioneering efforts demonstrate the enormous potential of synthetic BMCs to encapsulate non-native multi-enzyme biochemical pathways for the synthesis of high-value products.

Metabolomic profiling of Prader-Willi syndrome compared with essential obesity.

Introduction: Prader-Willi syndrome (PWS) is a rare disease, which shows a peculiar clinical phenotype, including obesity, which is different from essential obesity (EOB). Metabolomics might represent a valuable tool to reveal the biochemical mechanisms/pathways underlying clinical differences between PWS and EOB. The aim of the present (case-control, retrospective) study was to determine the metabolomic profile that characterizes PWS compared to EOB. Methods: A validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) targeted metabolomic approach was used to measure a total of 188 endogenous metabolites in plasma samples of 32 patients with PWS (F/M = 23/9; age: 31.6 ± 9.2 years; body mass index [BMI]: 42.1 ± 7.0 kg/m2), compared to a sex-, age- and BMI-matched group of patients with EOB (F/M = 23/9; age: 31.4 ± 6.9 years; BMI: 43.5 ± 3.5 kg/m2). Results: Body composition in PWS was different when compared to EOB, with increased fat mass and decreased fat-free mass. Glycemia and HDL cholesterol were higher in patients with PWS than in those with EOB, while insulinemia was lower, as well as heart rate. Resting energy expenditure was lower in the group with PWS than in the one with EOB, a difference that was missed after fat-free mass correction. Carrying out a series of Tobit multivariable linear regressions, adjusted for sex, diastolic blood pressure, and C reactive protein, a total of 28 metabolites was found to be associated with PWS (vs. non-PWS, i.e., EOB), including 9 phosphatidylcholines (PCs) ae, 5 PCs aa, all PCs aa, 7 lysoPCs a, all lysoPCs, 4 acetylcarnitines, and 1 sphingomyelin, all of which were higher in PWS than EOB. Conclusions: PWS exhibits a specific metabolomic profile when compared to EOB, suggesting a different regulation of some biochemical pathways, fundamentally related to lipid metabolism.

Key Proteomics Tools for Fundamental and Applied Microalgal Research.

Microscopic, photosynthetic prokaryotes and eukaryotes, collectively referred to as microalgae, are widely studied to improve our understanding of key metabolic pathways (e.g., photosynthesis) and for the development of biotechnological applications. Omics technologies, which are now common tools in biological research, have been shown to be critical in microalgal research. In the past decade, significant technological advancements have allowed omics technologies to become more affordable and efficient, with huge datasets being generated. In particular, where studies focused on a single or few proteins decades ago, it is now possible to study the whole proteome of a microalgae. The development of mass spectrometry-based methods has provided this leap forward with the high-throughput identification and quantification of proteins. This review specifically provides an overview of the use of proteomics in fundamental (e.g., photosynthesis) and applied (e.g., lipid production for biofuel) microalgal research, and presents future research directions in this field.

Isotopically nonstationary metabolic flux analysis of plants: recent progress and future opportunities.

Metabolic flux analysis (MFA) is a valuable tool for quantifying cellular phenotypes and to guide plant metabolic engineering. By introducing stable isotopic tracers and employing mathematical models, MFA can quantify the rates of metabolic reactions through biochemical pathways. Recent applications of isotopically nonstationary MFA (INST-MFA) to plants have elucidated nonintuitive metabolism in leaves under optimal and stress conditions, described coupled fluxes for fast-growing algae, and produced a synergistic multi-organ flux map that is a first in MFA for any biological system. These insights could not be elucidated through other approaches and show the potential of INST-MFA to correct an oversimplified understanding of plant metabolism.

Fatty acid composition and metabolic pathways in Arbacia dufresnii (Arbaciidae: Arbacioida) gametes: implications of shrimp byproducts in aquaculture feeds / Composición de ácidos grasos y vías metabólicas en los gametos de Arbacia dufresnii (Arbaciidae: Arbacioida) implicaciones de los subproductos de langostinos en los alimentos de acuicultura

Abstract Introduction: Care towards nutrition is essential for the quality of a sustainable aquaculture product. Since the balance in food affects the growth and production of gametes. The circular economy is made possible through the use of discarded materials. Objective: The aim of this research was to study the fatty acid composition and metabolic pathways in the gametes of Arbacia dufresnii, with a focus on the implications of incorporating shrimp byproducts into aquaculture feeds. Methods: Four different treatments were designed to maintain optimal nutritional quality, particularly in lipids and proteins, based on previous studies. The fatty acid profiles of the feeds and gametes were analyzed by using gas-chromatography, and statistical analyses were conducted to determine significant differences. Results: Significant differences were observed in the abundance (%) of omega-3 (ω-3) and omega-6 (ω-6) fatty acids. The (ω-3) metabolic pathway was more pronounced in the gametes of wild animals and those fed with the experimental feeds. In contrast, the (ω-6) metabolic pathway was less relevant in these groups. The (ω-3) /(ω-6) ratio was highest in the gametes of wild animals. Feeds enriched in fatty acids enhanced their bioaccumulation in the gametes reaching higher concentrations than wild animals. The availability of fatty acids in foods allowed their bioaccumulation in gametes, with concentrations equal to or higher than those observed in animals in their natural environment for certain fatty acids. Conclusions: Incorporating shrimp byproducts in aquaculture feeds demonstrated a promising strategy for resource utilization and organic input generation. The fatty acid composition in the gametes of A. dufresnii was influenced by the diet, highlighting the potential of balanced feeds to enhance the bioaccumulation of essential fatty acids. These findings provide valuable insights for the development of sustainable aquaculture practices and the production of nutritionally enriched seafood products.

Resumen Introducción: El cuidado hacia la nutrición es fundamental para la calidad de un producto acuícola sostenible. Ya que el balance en los alimentos afecta el crecimiento y producción de los gametos. A partir del aprovechamiento de materias de descarte se posibilita la economía circular. Objetivo: El objetivo de este estudio fue investigar la composición de ácidos grasos y las vías metabólicas en los gametos de Arbacia dufresnii, centrándose en las implicaciones de la incorporación de subproductos de camarones en los alimentos de acuicultura. Métodos: Se diseñaron cuatro tratamientos diferentes para mantener una calidad nutricional óptima, especialmente en lípidos y proteínas, basándose en estudios previos. Se analizaron los perfiles de ácidos grasos de los alimentos y los gametos mediante cromatografía de gases, y se realizaron análisis estadísticos para determinar diferencias significativas. Resultados: Se observaron diferencias significativas en la abundancia (%) de ácidos grasos omega-3 (ω-3) y omega-6 (ω-6). La vía metabólica de (ω-3) fue más pronunciada en los gametos de los animales en su entorno natural y aquellos alimentados con los piensos experimentales. Por el contrario, la vía metabólica de (ω-6) tuvo menos relevancia en estos grupos. La relación (ω-3) /(ω-6) fue más alta en los gametos de los animales en su entorno natural. La disponibilidad de ácidos grasos en los alimentos permitió su bioacumulación en los gametos, con concentraciones iguales o superiores a las observadas en los animales en su entorno natural para ciertos ácidos grasos. Conclusiones: La incorporación de subproductos de camarones en los alimentos de acuicultura demostró ser una estrategia prometedora para la utilización de recursos y la generación de insumos orgánicos. La composición de ácidos grasos en los gametos de A. dufresnii fue influenciada por la dieta, destacando el potencial de los alimentos balanceados para mejorar la bioacumulación de ácidos grasos esenciales. Estos hallazgos brindan información valiosa para el desarrollo de prácticas sostenibles en acuicultura y la producción de productos marinos enriquecidos nutricionalmente.

Spatial transcriptomic patterns underlying amyloid-ß and tau pathology are associated with cognitive dysfunction in Alzheimer's disease.

Amyloid-ß (Aß) and tau proteins accumulate within distinct neuronal systems in Alzheimer's disease (AD). Although it is not clear why certain brain regions are more vulnerable to Aß and tau pathologies than others, gene expression may play a role. We study the association between brain-wide gene expression profiles and regional vulnerability to Aß (gene-to-Aß associations) and tau (gene-to-tau associations) pathologies by leveraging two large independent AD cohorts. We identify AD susceptibility genes and gene modules in a gene co-expression network with expression profiles specifically related to regional vulnerability to Aß and tau pathologies in AD. In addition, we identify distinct biochemical pathways associated with the gene-to-Aß and the gene-to-tau associations. These findings may explain the discordance between regional Aß and tau pathologies. Finally, we propose an analytic framework, linking the identified gene-to-pathology associations to cognitive dysfunction in AD at the individual level, suggesting potential clinical implication of the gene-to-pathology associations.

Relationship between Biochemical Pathways and Non-Coding RNAs Involved in the Progression of Diabetic Retinopathy.

Diabetic retinopathy (DR) is a progressive blinding disease, which affects the vision and quality of life of patients, and it severely impacts the society. This complication, caused by abnormal glucose metabolism, leads to structural, functional, molecular, and biochemical abnormalities in the retina. Oxidative stress and inflammation also play pivotal roles in the pathogenic process of DR, leading to mitochondrial damage and a decrease in mitochondrial function. DR causes retinal degeneration in glial and neural cells, while the disappearance of pericytes in retinal blood vessels leads to alterations in vascular regulation and stability. Clinical changes include dilatation and blood flow changes in response to the decrease in retinal perfusion in retinal blood vessels, leading to vascular leakage, neovascularization, and neurodegeneration. The loss of vascular cells in the retina results in capillary occlusion and ischemia. Thus, DR is a highly complex disease with various biological factors, which contribute to its pathogenesis. The interplay between biochemical pathways and non-coding RNAs (ncRNAs) is essential for understanding the development and progression of DR. Abnormal expression of ncRNAs has been confirmed to promote the development of DR, suggesting that ncRNAs such as miRNAs, lncRNAs, and circRNAs have potential as diagnostic biomarkers and theranostic targets in DR. This review provides an overview of the interactions between abnormal biochemical pathways and dysregulated expression of ncRNAs under the influence of hyperglycemic environment in DR.

Breast cancer and its therapeutic targets: A comprehensive review.

Breast cancer is a common and deadly disease, so there is a constant need for research to find efficient targets and therapeutic approaches. Breast cancer can be classified on a molecular and histological base. Breast cancer can be divided into ER (estrogen receptor)-positive and ER-negative, HER2 (human epidermal growth factor receptor2)-positive and HER2-negative subtypes based on the presence of specific biomarkers. Targeting hormone receptors, such as the HER2, progesterone receptor (PR), and ER, is very significant and plays a vital role in the onset and progression of breast cancer. Endocrine treatments and HER2-targeted drugs are examples of targeted therapies now being used against these receptors. Emerging immune-based medicines with promising outcomes in the treatment of breast cancer include immune checkpoint inhibitors, cancer vaccines, and adoptive T-cell therapy. It is also explored how immune cells and the tumor microenvironment affect breast cancer development and treatment response. The major biochemical pathways, signaling cascades, and DNA repair mechanisms that are involved in the development and progression of breast cancer, include the PI3K/AKT/mTOR system, the MAPK pathway, and others. These pathways are intended to be inhibited by a variety of targeted drugs, which are then delivered with the goal of restoring normal cellular function. This review aims to shed light on types of breast cancer with the summarization of different therapeutic approaches which can target different pathways for tailored medicines and better patient outcomes.

Impact of sampling location and aging on the Longissimus thoracis et lumborum muscle proteome of dry-aged beef.

This study aimed to explore the differences in the proteome and molecular pathways between two sampling locations (external, internal) of bovine Longissimus thoracis et lumborum (LTL) muscles at 0, 21, and 28 days of dry-aging (i.e. 3, 24, and 31 days post-mortem). It further assessed the impact of post-mortem aging on the meat proteome changes and the biological processes at interplay. Proteins related to defence response to bacterium and regulation of viral entry into host cell were identified to be more abundant on the external location before dry-aging, which may be associated to the oxidative conditions and microbial activity to which post-mortem muscle is exposed during dressing, chilling, and/or quartering of the carcasses. This highlights the relevance of sampling from interior tissues when searching for meat quality biomarkers. As dry-aging progressed, the meat proteome and related biological processes changed differently between sampling locations; proteins related to cell-cell adhesion and ATP metabolic processes pathways were revealed in the external location at 21 and 28 days, respectively. On the other hand, the impact of aging on the proteome of the interior meat samples, evidenced that muscle contraction and structure together with energy metabolism were the major pathways driving dry-aging. Additionally, aging impacted other pathways in the interior tissues, such as regulation of calcium import, neutrophil activation, and regeneration. Overall, the differences in the proteome allowed discriminating the three dry-aging times, regardless of the sampling location. Several proteins were proposed for validation as robust biomarkers to monitor the aging process (tenderization) of dry-aged beef: TTN, GRM4, EEF1A1, LDB3, CILP2, TNNT3, GAPDH, SERPINI1, and OMD.

Understanding Snail Mucus Biosynthesis and Shell Biomineralisation through Genomic Data Mining of the Reconstructed Carbohydrate and Glycan Metabolic Pathways of the Giant African Snail (Achatina fulica).

The giant African snail (Order Stylommatophora: Family Achatinidae), Achatina fulica (Bowdich, 1822), is the most significant and invasive land snail pest. The ecological adaptability of this snail involves high growth rate, reproductive capacity, and shell and mucus production, driven by several biochemical processes and metabolism. The available genomic information for A. fulica provides excellent opportunities to hinder the underlying processes of adaptation, mainly carbohydrate and glycan metabolic pathways toward the shell and mucus formation. The authors analysed the 1.78 Gb draft genomic contigs of A. fulica to identify enzyme-coding genes and reconstruct biochemical pathways related to the carbohydrate and glycan metabolism using a designed bioinformatic workflow. Three hundred and seventy-seven enzymes involved in the carbohydrate and glycan metabolic pathways were identified based on the KEGG pathway reference in combination with protein sequence comparison, structural analysis, and manual curation. Fourteen complete pathways of carbohydrate metabolism and seven complete pathways of glycan metabolism supported the nutrient acquisition and production of the mucus proteoglycans. Increased copy numbers of amylases, cellulases, and chitinases highlighted the snail advantage in food consumption and fast growth rate. The ascorbate biosynthesis pathway identified from the carbohydrate metabolic pathways of A. fulica was involved in the shell biomineralisation process in association with the collagen protein network, carbonic anhydrases, tyrosinases, and several ion transporters. Thus, our bioinformatic workflow was able to reconstruct carbohydrate metabolism, mucus biosynthesis, and shell biomineralisation pathways from the A. fulica genome and transcriptome data. These findings could reveal several evolutionary advantages of the A. fulica snail, and will benefit the discovery of valuable enzymes for industrial and medical applications.

Impact of renal tubular Cpt1a overexpression on the kidney metabolome in the folic acid-induced fibrosis mouse model.

Background: Chronic kidney disease (CKD) is characterized by the progressive and irreversible deterioration of kidney function and structure with the appearance of renal fibrosis. A significant decrease in mitochondrial metabolism, specifically a reduction in fatty acid oxidation (FAO) in tubular cells, is observed in tubulointerstitial fibrosis, whereas FAO enhancement provides protection. Untargeted metabolomics offers the potential to provide a comprehensive analysis of the renal metabolome in the context of kidney injury. Methodology: Renal tissue from a carnitine palmitoyl transferase 1a (Cpt1a) overexpressing mouse model, which displays enhanced FAO in the renal tubule, subjected to folic acid nephropathy (FAN) was studied through a multiplatform untargeted metabolomics approach based on LC-MS, CE-MS and GC-MS analysis to achieve the highest coverage of the metabolome and lipidome affected by fibrosis. The expression of genes related to the biochemical routes showing significant changes was also evaluated. Results: By combining different tools for signal processing, statistical analysis and feature annotation, we were able to identify variations in 194 metabolites and lipids involved in many metabolic routes: TCA cycle, polyamines, one-carbon metabolism, amino acid metabolism, purine metabolism, FAO, glycerolipids and glycerophospholipids synthesis and degradation, glycosphingolipids interconversion, and sterol metabolism. We found several metabolites strongly altered by FAN, with no reversion induced by Cpt1a overexpression (v.g. citric acid), whereas other metabolites were influenced by CPT1A-induced FAO (v.g. glycine-betaine). Conclusion: It was implemented a successful multiplatform metabolomics approach for renal tissue analysis. Profound metabolic changes accompany CKD-associated fibrosis, some associated with tubular FAO failure. These results highlight the importance of addressing the crosstalk between metabolism and fibrosis when undertaking studies attempting to elucidate the mechanism of CKD progression.

Microbial biochemical pathways of arsenic biotransformation and their application for bioremediation.

Arsenic is a ubiquitous toxic metalloid, the concentration of which is beyond WHO safe drinking water standards in many areas of the world, owing to many natural and anthropogenic activities. Long-term exposure to arsenic proves lethal for plants, humans, animals, and even microbial communities in the environment. Various sustainable strategies have been developed to mitigate the harmful effects of arsenic which include several chemical and physical methods, however, bioremediation has proved to be an eco-friendly and inexpensive technique with promising results. Many microbes and plant species are known for arsenic biotransformation and detoxification. Arsenic bioremediation involves different pathways such as uptake, accumulation, reduction, oxidation, methylation, and demethylation. Each of these pathways has a certain set of genes and proteins to carry out the mechanism of arsenic biotransformation. Based on these mechanisms, various studies have been conducted for arsenic detoxification and removal. Genes specific for these pathways have also been cloned in several microorganisms to enhance arsenic bioremediation. This review discusses different biochemical pathways and the associated genes which play important roles in arsenic redox reactions, resistance, methylation/demethylation, and accumulation. Based on these mechanisms, new methods can be developed for effective arsenic bioremediation.

Towards the discovery of goat meat quality biomarkers using label-free proteomics.

This study aimed to identify for the first time protein biomarkers of meat quality traits from Longissimus thoracis (LT) muscle of goats (Capra hircus). Male goats of similar age and weight reared under extensive rearing conditions were used to relate the LT muscle proteome with multiple meat quality traits. The early post-mortem muscle proteome analyzed using label-free proteomics was compared among three texture clusters built using hierarchical clustering analysis. Twenty-five proteins were differentially abundant and their mining using bioinformatics revealed three major biological pathways to be involved: 10 muscle structure proteins (MYL1, MYL4, MYLPF, MYL6B, MYH1, MYH2, ACTA1, ACTBL2, FHL1 and MYOZ1); 6 energy metabolism proteins (ALDOA, PGAM2, ATP5F1A, GAPDH, PGM1 and ATP5IF1), and two heat shock proteins: HSPB1 (small) and HSPA8 (large). Seven other miscellaneous proteins belonging to pathways such as regulation, proteolysis, apoptosis, transport and binding, tRNA processing or calmodulin-binding were further identified to play a role in the variability of goat meat quality. The differentially abundant proteins were correlated with the goat meat quality traits in addition to multivariate regression models built to propose the first regression equations of each quality trait. This study is the first to highlight in a multi-trait quality comparison the early post-mortem changes in the goat LT muscle proteome. It also evidenced the mechanisms underpinning the development of several quality traits of interest in goat meat production along the major biochemical pathways at interplay. SIGNIFICANCE: The discovery of protein biomarkers in the field of meat research is an emerging topic. In the case of goat meat quality, very few studies using proteomics have been conducted with the aim of proposing biomarkers. Therefore, this study is the first to quest for biomarkers of goat meat quality using label-free shotgun proteomics with a focus on multiple quality traits. We identified the molecular signatures underlying goat meat texture variation, which were found to belong to muscle structure and related proteins, energy metabolism and heat shock proteins along with other proteins involved in regulation, proteolysis, apoptosis, transport and binding, tRNA processing or calmodulin-binding. We further evaluated the potential of the candidate biomarkers to explain meat quality using the differentially abundant proteins by means of correlation and regression analyses. The results allowed the explanation of the variation in multiple traits such as pH, color, water-holding capacity, drip and cook losses traits and texture.