PubMed

Int J Mol Sci. 2024 Nov 20;25(22):12446. doi: 10.3390/ijms252212446.ABSTRACTBananas (Musa spp.) are among the most important fruit and staple food crops globally, holding a significant strategic position in food security in tropical and subtropical regions. However, the industry is grappling with a significant threat from Fusarium wilt, a disease incited by Fusarium oxysporum f. sp. cubense (Foc). In this study, we explored the potential of Piriformospora indica (Pi), a mycorrhizal fungus renowned for bolstering plant resilience and nutrient assimilation, to fortify bananas against this devastating disease. Through a meticulous comparative analysis of mRNA and miRNA expression in control, Foc-inoculated, Pi-colonized, and Pi-colonized followed by Foc-inoculated plants via transcriptome and sRNAome, we uncovered a significant enrichment of differentially expressed genes (DEGs) and DE miRNAs in pathways associated with plant growth and development, glutathione metabolism, and stress response. Our findings suggest that P. indica plays a pivotal role in bolstering banana resistance to Foc. We propose that P. indica modulates the expression of key genes, such as glutathione S-transferase (GST), and transcription factors (TFs), including TCP, through miRNAs, thus augmenting the plant's defensive capabilities. This study offers novel perspectives on harnessing P. indica for the management of banana wilt disease.PMID:39596511 | DOI:10.3390/ijms252212446

Int J Mol Sci. 2024 Nov 19;25(22):12410. doi: 10.3390/ijms252212410.ABSTRACTIn neuroscience research, chiral metabolomics is an emerging field, in which D-amino acids play an important role as potential biomarkers for neurological diseases. The targeted chiral analysis of the brain metabolome, employing liquid chromatography (LC) coupled to mass spectrometry (MS), is a pivotal approach for the identification of biomarkers for neurological diseases. This review provides an overview of D-amino acids in neurological diseases and of the state-of-the-art strategies for the enantioselective analysis of chiral amino acids (AAs) in biological samples to investigate their putative role as biomarkers for neurological diseases. Fluctuations in D-amino acids (D-AAs) levels can be related to the pathology of neurological diseases, for example, through their role in the modulation of N-methyl-D-aspartate receptors and neurotransmission. Because of the trace presence of these biomolecules in mammals and the complex nature of biological matrices, highly sensitive and selective analytical methods are essential. Derivatization strategies with chiral reagents are highlighted as critical tools for enhancing detection capabilities. The latest advances in chiral derivatization reactions, coupled to LC-MS/MS analysis, have improved the enantioselective quantification of these AAs and allow the separation of several chiral metabolites in a single analytical run. The enhanced performances of these methods can provide an accurate correlation between specific D-AA profiles and disease states, allowing for a better understanding of neurological diseases and drug effects on the brain.PMID:39596475 | DOI:10.3390/ijms252212410

Int J Mol Sci. 2024 Nov 18;25(22):12375. doi: 10.3390/ijms252212375.ABSTRACTBlood is an important component for maintaining animal lives and synthesizing sugars, lipids, and proteins in organs. Revealing the relationship between genes and metabolite expression and milk somatic cell count (SCC), milk fat percentage, milk protein percentage, and lactose percentage in blood is helpful for understanding the molecular regulation mechanism of milk formation. Therefore, we separated the buffy coat and plasma from the blood of Xinjiang Brown cattle (XJBC) and Chinese Simmental cattle (CSC), which exhibit high and low SCC/milk fat percentage/milk protein percentage/lactose percentages, respectively. The expression of genes in blood and the metabolites in plasma was detected via RNA-Seq and LC-MS/MS, respectively. Based on the weighted gene coexpression network analysis (WGCNA) and functional enrichment analysis of differentially expressed genes (DEGs), we further found that the expression of genes in the blood mainly affected the SCC and milk fat percentage. Immune or inflammatory-response-related pathways were involved in the regulation of SCC, milk fat percentage, milk protein percentage, and lactose percentage. The joint analysis of the metabolome and transcriptome further indicated that, in blood, the metabolism pathways of purine, glutathione, glycerophospholipid, glycine, arginine, and proline are also associated with SCC, while lipid metabolism and amino-acid-related metabolism pathways are associated with milk fat percentage and milk protein percentage, respectively. Finally, related SCC, milk fat percentage, and milk protein percentage DEGs and DEMs were mainly identified in the blood.PMID:39596441 | DOI:10.3390/ijms252212375

Int J Mol Sci. 2024 Nov 16;25(22):12320. doi: 10.3390/ijms252212320.ABSTRACTThe classical function of the mineralocorticoid receptor (MR) is to maintain electrolytic homeostasis and control extracellular volume and blood pressure. The MR is expressed in the central nervous system (CNS) and is involved in the regulation of the hypothalamic-pituitary-adrenal (HPA) axis as well as sleep physiology, playing a role in the non-rapid eye movement (NREM) phase of sleep. Some patients with psychiatric disorders have very poor sleep quality, and a relationship between MR dysregulation and this disorder has been found in them. In addition, the MR is involved in the regulation of the renal peripheral clock. One of the most common comorbidities observed in patients with chronic kidney disease (CKD) is poor sleep quality. Patients with CKD experience sleep disturbances, including reduced sleep duration, sleep fragmentation, and insomnia. To date, no studies have specifically investigated the relationship between MR activation and CKD-associated sleep disturbances. However, in this review, we analyzed the environment that occurs in CKD and proposed two MR-related mechanisms that may be responsible for these sleep disturbances: the circadian clock disruption and the high levels of MR agonist observed in CKD.PMID:39596384 | DOI:10.3390/ijms252212320

Int J Mol Sci. 2024 Nov 16;25(22):12310. doi: 10.3390/ijms252212310.ABSTRACTThe relationship between circulating metabolites and sarcopenia-related phenotypes remains unclear. We explored the causality between circulating metabolites and sarcopenia-related phenotypes. Instrumental variables for the human metabolome were derived from the recently published GWAS, which included 690 plasma metabolites. Summary statistics for four sarcopenia phenotypes (whole-body lean mass (WBLM), usual walking pace, appendicular lean mass (ALM), and handgrip strength (HGS)) (both sexes, males and females) were obtained from relevant GWASs. We used MR to evaluate the association between circulating metabolites and sarcopenia-related phenotypes. Colocalization analysis was utilized to determine whether two associated signals were consistent with a shared causal variant rather than the confounding effect of linkage disequilibrium. Subsequently, we explored associations between modifiable risk factors and sarcopenia-related metabolites to explore which metabolites may serve as potential intervention targets through lifestyle modification. Genetically predicted plasma levels of 95 known metabolites were associated with sarcopenia-related phenotypes, and 27 metabolites were supported by robust evidence of colocalization, among which 13 metabolites had a cross-sarcopenia effect. These metabolites primarily included acyl carnitines, amino acids and their derivatives, and phospholipids. Specifically, our analyses supported causal relationships between 23, 6, and 15 metabolites and ALM, HGS, and WBLM, respectively. Seven relevant metabolites might be associated with six modifiable factors. We identified 27 metabolite biomarkers with robust causal evidence for sarcopenia-related phenotypes, highlighting 13 metabolites with a cross-sarcopenia effect, and prioritized several metabolites as the potential interventional targets of lifestyle changes. Our study provided new insight into the etiology and prevention of sarcopenia.PMID:39596375 | DOI:10.3390/ijms252212310

Int J Mol Sci. 2024 Nov 16;25(22):12308. doi: 10.3390/ijms252212308.ABSTRACTSpinosad is an efficient and broad-spectrum environmentally friendly biopesticide, but its low yield in wild-type Saccharopolyspora spinosa limits its further application. ARTP/NTG compound mutagenesis was used in this study to improve the spinosad titer of S. spinosa and obtain a high-yield mutant-NT24. Compared with the wild-type strain, the fermentation cycle of NT24 was shortened by 2 days and its maximum titer of spinosad reached 858.3 ± 27.7 mg/L, which is 5.12 times more than for the same-period titer of the wild-type strain. In addition, RT-qPCR, resequencing, and targeted metabolomics showed that the upregulation of the key differential genes accD6, fadD, sdhB, oadA, and gntZ caused increased metabolic flux in the tricarboxylic acid cycle and pentose phosphate pathway, suggesting that the accumulation of pyruvate and short-chain acyl-CoA was the primary cause of spinosad accumulation in NT24. This study demonstrates the effectiveness of ARTP mutagenesis in S. spinosa, and provides new insights for the mechanism of spinosad biosynthesis and metabolic engineering in S. spinosa.PMID:39596372 | DOI:10.3390/ijms252212308

Int J Mol Sci. 2024 Nov 15;25(22):12274. doi: 10.3390/ijms252212274.ABSTRACTAdipocytes derived from 3T3-L1 cells are a gold standard for analyses of adipogenesis processes and the metabolism of fat cells. A widely used histological and immunohistochemical staining and mass spectrometry lipidomics are mainly aimed for examining lipid droplets (LDs). Visualizing other cellular compartments contributing to the cellular machinery requires additional cell culturing for multiple labeling. Here, we present the localization of the intracellular structure of the 3T3-L1-derived adipocytes utilizing vibrational spectromicroscopy, which simultaneously illustrates the cellular compartments and provides chemical composition without extensive sample preparation and in the naïve state. Both vibrational spectra (FTIR-Fourier transform infrared and RS-Raman scattering spectroscopy) extended the gathered chemical information. We proved that both IR and RS spectra provide distinct chemical information about lipid content and their structure. Despite the expected presence of triacylglycerols and cholesteryl esters in lipid droplets, we also estimated the length and unsaturation degree of the fatty acid acyl chains that were congruent with known MS lipidomics of these cells. In addition, the clustering of spectral images revealed that the direct surroundings around LDs attributed to lipid-associated proteins and a high abundance of mitochondria. Finally, by using quantified markers of biomolecules, we showed that the fixative agents, paraformaldehyde and glutaraldehyde, affected the cellular compartment differently. We concluded that PFA preserves LDs better, while GA fixation is better for cytochromes and unsaturated lipid analysis. The proposed analysis of the spectral images constitutes a complementary tool for investigations into the structural and molecular features of fat cells.PMID:39596337 | DOI:10.3390/ijms252212274

Int J Mol Sci. 2024 Nov 15;25(22):12273. doi: 10.3390/ijms252212273.ABSTRACTMaize (Zea mays L.) is highly sensitive to temperature during its growth and development stage. A 1 °C drop in temperature can delay maturity by 10 days, resulting in a yield reduction of over 10%. Low-temperature tolerance in maize is a complex quantitative trait, and different germplasms exhibit significant differences in their responses to low-temperature stress. To explore the differences in gene expression and metabolites between B144 (tolerant) and Q319 (susceptible) during germination under low-temperature stress and to identify key genes and metabolites that respond to this stress, high-throughput transcriptome sequencing was performed on the leaves of B144 and Q319 subjected to low-temperature stress for 24 h and their respective controls using Illumina HiSeqTM 4000 high-throughput sequencing technology. Additionally, high-throughput metabolite sequencing was conducted on the samples using widely targeted metabolome sequencing technology. The results indicated that low-temperature stress triggered the accumulation of stress-related metabolites such as amino acids and their derivatives, lipids, phenolic acids, organic acids, flavonoids, lignin, coumarins, and alkaloids, suggesting their significant roles in the response to low temperature. This stress also promoted gene expression and metabolite accumulation involved in the flavonoid biosynthesis pathway. Notably, there were marked differences in gene expression and metabolites related to the glyoxylate and dicarboxylate metabolism pathways between B144 and Q319. This study, through multi-omics integrated analysis, provides valuable insights into the identification of metabolites, elucidation of metabolic pathways, and the biochemical and genetic basis of plant responses to stress, particularly under low-temperature conditions.PMID:39596336 | DOI:10.3390/ijms252212273

Int J Mol Sci. 2024 Nov 14;25(22):12255. doi: 10.3390/ijms252212255.ABSTRACTIn flowering plants, the success of fertilization depends on the rapid polar extension of a pollen tube, which delivers sperm cells to the female gametophyte for fertilization. Numerous studies have shown that the microenvironment in planta is more conducive to the growth and development of pollen tubes than that in vitro. However, how stigma factors coordinate to regulate pollen tube growth is still poorly understood. Here, we demonstrate that in tobacco, mature stigma extract, but not immature stigma extract, facilitates pollen tube growth. Comparative transcriptomic and qRT-PCR analyses showed that the differentially expressed genes during stigma maturation were mainly enriched in the metabolism pathway. Through metabolome analyses, about 500 metabolites were identified to be differently accumulated; the significantly increased metabolites in the mature stigmas mainly belonged to alkaloids, flavonoids, and terpenoids, while the downregulated differential metabolites were related to lipids, amino acids, and their derivatives. Among the different kinds of plant hormones, the cis-form contents of zeatin were significantly increased, and more importantly, cis-zeatin riboside promoted pollen tube growth in vitro. Thus, our results reveal an overall landscape of gene expression and a detailed nutritional microenvironment established for pollen tube growth during the process of stigma maturation, which provides valuable clues for optimizing in vitro pollen growth and investigating the pollen-stigma interaction.PMID:39596319 | DOI:10.3390/ijms252212255

Int J Mol Sci. 2024 Nov 13;25(22):12199. doi: 10.3390/ijms252212199.ABSTRACTThe COVID-19 outbreak caused saturations of hospitals, highlighting the importance of early patient triage to optimize resource prioritization. Herein, our objective was to test if high definition metabolomics, combined with ML, can improve prognostication and triage performance over standard clinical parameters using COVID infection as an example. Using high resolution mass spectrometry, we obtained metabolomics profiles of patients and combined them with clinical parameters to design machine learning (ML) algorithms predicting severity (herein determined as the need for mechanical ventilation during patient care). A total of 64 PCR-positive COVID patients at the Poitiers CHU were recruited. Clinical and metabolomics investigations were conducted 8 days after the onset of symptoms. We show that standard clinical parameters could predict severity with good performance (AUC of the ROC curve: 0.85), using SpO2, first respiratory rate, Horowitz quotient and age as the most important variables. However, the performance of the prediction was substantially improved by the use of metabolomics (AUC = 0.92). Our small-scale study demonstrates that metabolomics can improve the performance of diagnosis and prognosis algorithms, and thus be a key player in the future discovery of new biological signals. This technique is easily deployable in the clinic, and combined with machine learning, it can help design the mathematical models needed to advance towards personalized medicine.PMID:39596265 | DOI:10.3390/ijms252212199

J Inflamm (Lond). 2024 Nov 26;21(1):49. doi: 10.1186/s12950-024-00419-5.ABSTRACTInflammation can be an unwanted consequence or cause of debilitating diseases of infectious and non-infectious aetiologies. Current anti-inflammatory medications have several deficiencies including lack of specificity and undesirable side effects. Herein, the potential of non-ionic surfactant vesicles (NISV) comprised of monopalmityol glycerol, dicetyl phosphate and cholesterol) as an anti-inflammatory drug and their mode of action is investigated. NISV were able to inhibit LPS-induced IL-6 from BMD macrophages. The individual components of NISV, monopalmityol glycerol, dicetyl phosphate and cholesterol did not affect LPS induced IL-6 levels, proving that formulation of NISV is essential for their anti-inflammatory effects. Transcriptomic analyses showed NISV mediated down-regulation of transcripts for inflammatory mediators in LPS stimulated macrophages. Notably, NISV downregulate NF-κB transcripts in LPS stimulated macrophages. Measurement of inflammatory mediators by cytometric bead array validated a number of transcriptomic findings as NISV were found to inhibit LPS induced IL-6, IL-12, and multiple chemokines. Further investigation demonstrated that NISV inhibited Poly(I:C) or Pam3csk4 induced inflammatory mediators. This indicates that the effects of NISV are distal to both MyD88 and TRIF signalling. Overall, the data generated highlights the potential of NISV as an anti-inflammatory therapeutic.PMID:39593021 | DOI:10.1186/s12950-024-00419-5

BMC Plant Biol. 2024 Nov 27;24(1):1128. doi: 10.1186/s12870-024-05831-w.ABSTRACTBACKGROUND: Larix gmelinii is an excellent stress resistant coniferous tree species with a wide distribution and important economic and ecological value. However, at seedling stage, L. gmelinii is extremely susceptible to abiotic stresses, and systematic research on the adaptation mechanisms of L. gmelinii seedlings to abiotic stress is still lacking.RESULTS: Phenotypic observation and physiological index detection showed that L. gmelinii seedlings wilted with needles withered and yellowish at later stages of drought and salt stress; Under low temperature, the seedlings grew slowly and turned red at later stage. Under all 3 abiotic stresses, the chlorophyll content in seedlings significantly decreased, while the MDA content significantly increased; The activity of SOD and CAT showed a trend of increasing first and then decreasing. Transcriptome analysis revealed that DEGs were mainly involved in carbohydrate and amino acid metabolism, phenylpropanoid biosynthesis, and flavonoid synthesis metabolism. Metabolomic analysis found unique DAMs under 3 stress treatments. The combined analysis of transcriptome and metabolome showed that the changing patterns of DEGs and DAMs in primary and secondary metabolism were consistent: carbohydrate were significantly accumulated under low temperature stress; amino acids showed the most significant changes under salt stress. The variation pattern of secondary metabolism was similar under both drought and salt stress, while anthocyanin accumulation was the most obvious only under low temperature stress.CONCLUSION: Our study provides insightful information about the different mechanisms that L. gmelinii seedlings employ in response to drought, low temperature or salt stress.PMID:39592952 | DOI:10.1186/s12870-024-05831-w

BMC Plant Biol. 2024 Nov 27;24(1):1132. doi: 10.1186/s12870-024-05834-7.ABSTRACTBACKGROUND: We have previously shown that the expression of a constitutively active nitrate reductase variant and the suppression of CLCNt2 gene function (belonging to the chloride channel (CLC) gene family) in field-grown tobacco reduces tobacco-specific nitrosamines (TSNA) accumulation in cured leaves and cigarette smoke. In both cases, TSNA reductions resulted from a strong diminution of free nitrate in the leaf, as nitrate is a precursor of the TSNA-producing nitrosating agents formed during tobacco curing and smoking. These nitrosating agents modify tobacco alkaloids to produce TSNAs, the most problematic of which are NNN (N-nitrosonornicotine) and NNK (4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone). The expression of a deregulated nitrate reductase enzyme (DNR) that is no longer responsive to light regulation is believed to diminish free nitrate pools by immediately channeling incoming nitrate into the nitrate assimilation pathway. The reduction in nitrate observed when the two tobacco gene copies encoding the vacuolar nitrate transporter CLCNt2 were down-regulated by RNAi-mediated suppression or knocked out using the CRISPR-Cas technology was mechanistically distinct; likely attributable to the inability of the tobacco cell to efficiently sequester nitrate into the vacuole where this metabolite is protected from further assimilation. In this study, we used transcriptomic and metabolomic analyses to compare the nitrate assimilation response in tobacco plants either expressing DNR or lacking CLCNt2 function.RESULTS: When grown in a controlled environment, both DNR and CLCNt2-KO (CLCKO) plants exhibited (1) reduced nitrate content in the leaf; (2) increased N-assimilation into the amino acids Gln and Asn; and (3) a similar pattern of differential regulation of several genes controlling stress responses, including water stress, and cell wall metabolism in comparison to wild-type plants. Differences in gene regulation were also observed between DNR and CLCKO plants, including genes encoding nitrite reductase and asparagine synthetase.CONCLUSIONS: Our data suggest that even though both DNR and CLCKO plants display common characteristics with respect to nitrate assimilation, cellular responses, water stress, and cell wall remodeling, notable differences in gene regulatory patterns between the two low nitrate plants are also observed. These findings open new avenues in using plants fixing more nitrogen into amino acids for plant improvement or nutrition perspectives.PMID:39592946 | DOI:10.1186/s12870-024-05834-7

Nat Metab. 2024 Nov 26. doi: 10.1038/s42255-024-01183-9. Online ahead of print.NO ABSTRACTPMID:39592844 | DOI:10.1038/s42255-024-01183-9

Commun Med (Lond). 2024 Nov 26;4(1):248. doi: 10.1038/s43856-024-00669-7.ABSTRACTBACKGROUND: Diagnosing complex illnesses like Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is complicated due to the diverse symptomology and presence of comorbid conditions. ME/CFS patients often present with multiple health issues, therefore, incorporating comorbidities into research can provide a more accurate understanding of the condition's symptomatology and severity, to better reflect real-life patient experiences.METHODS: We performed association studies and machine learning on 1194 ME/CFS individuals with blood plasma nuclear magnetic resonance (NMR) metabolomics profiles, and seven exclusive comorbid cohorts: hypertension (n = 13,559), depression (n = 2522), asthma (n = 6406), irritable bowel syndrome (n = 859), hay fever (n = 3025), hypothyroidism (n = 1226), migraine (n = 1551) and a non-diseased control group (n = 53,009).RESULTS: We present a lipoprotein perspective on ME/CFS pathophysiology, highlighting gender-specific differences and identifying overlapping associations with comorbid conditions, specifically surface lipids, and ketone bodies from 168 significant individual biomarker associations. Additionally, we searched for, trained, and optimised a machine learning algorithm, resulting in a predictive model using 19 baseline characteristics and nine NMR biomarkers which could identify ME/CFS with an AUC of 0.83 and recall of 0.70. A multi-variable score was subsequently derived from the same 28 features, which exhibited ~2.5 times greater association than the top individual biomarker.CONCLUSIONS: This study provides an end-to-end analytical workflow that explores the potential clinical utility that association scores may have for ME/CFS and other difficult to diagnose conditions.PMID:39592839 | DOI:10.1038/s43856-024-00669-7

Sci Rep. 2024 Nov 26;14(1):29321. doi: 10.1038/s41598-024-81003-y.ABSTRACTGamma delta (γδ) T cells, which reside in mucosal and epithelial tissues, are integral to immune responses and are involved in various cancers, autoimmune, and infectious diseases. To study human γδ T cells to a translational level, we developed γδ humanized TCR-T1 (HuTCR-T1) mice using our TruHumanization platform. We compared the metabolomic profiles from plasma samples of wild-type (WT), γδ HuTCR-T1 mice, and humans using UHPLC-MS/MS. Untargeted metabolomics and lipidomics were used to screen all detectable metabolites. Principal component analysis revealed that the metabolomic profiles of γδ HuTCR-T1 mice closely resemble those of humans, with a clear segregation of metabolites between γδ HuTCR-T1 and WT mice. Most humanized γδ metabolites were classified as lipids, followed by organic compounds and amino acids. Pathway analysis identified significant alterations in the metabolism of tryptophan, tyrosine, sphingolipids, and glycerophospholipids, shifting these pathways towards a more human-like profile. Immunophenotyping showed that γδ HuTCR-T1 mice maintained normal proportions of both lymphoid and myeloid immune cell populations, closely resembling WT mice, with only a few exceptions. These findings demonstrate that the γδ HuTCR-T1 mouse model exhibits a metabolomic profile that is remarkably similar to that of humans, highlighting its potential as a relevant model for investigating the role of metabolites in disease development and progression. This model also offers an opportunity to discover therapeutic human TCRs.PMID:39592837 | DOI:10.1038/s41598-024-81003-y

Commun Biol. 2024 Nov 26;7(1):1576. doi: 10.1038/s42003-024-07277-0.ABSTRACTCell membrane glycans contribute to immune recognition, signaling, and cellular adhesion and migration, and altered membrane glycosylation is a feature of cancer cells that contributes to cancer progression. The uptake and metabolism of glucose and other nutrients essential for glycan synthesis could underlie altered membrane glycosylation, but the relationship between shifts in nutrient metabolism and the effects on glycans have not been directly examined. We developed a method that combines stable isotope tracing with metabolomics to enable direct observations of glucose allocation to nucleotide sugars and cell-membrane glycans. We compared the glucose allocation to membrane glycans of two pancreatic cancer cell lines that are genetically identical but have differing energy requirements. The 8988-S cells had higher glucose allocation to membrane glycans and intracellular pathways relating to glycan synthesis, but the 8988-T cells had higher glucose uptake and commitment of glucose to non-glycosylation pathways. The cell lines differed in the requirements of glucose for energy production, resulting in differences in glucose bioavailability for glycan synthesis. The workflow demonstrated here enables studies on the effects of metabolic shifts on the commitment of nutrients to cell-membrane glycans. The results suggest that cell-membrane glycans are remodeled through shifts in glucose commitment to non-glycosylation pathways.PMID:39592729 | DOI:10.1038/s42003-024-07277-0

Commun Biol. 2024 Nov 26;7(1):1575. doi: 10.1038/s42003-024-07252-9.ABSTRACTMyostatin (MSTN) is a negative regulator of muscle growth, and its relationship with the gut microbiota is not well understood. In this study, we observed increase muscle area and branched-chain amino acids (BCAAs), an energy source of muscle, in myostatin knockout (MSTN-KO) cattle. To explore the link between increased BCAAs and rumen microbiota, we performed metagenomic sequencing, metabolome analysis of rumen fluid, and muscle transcriptomics. MSTN-KO cattle showed a significant increase in the phylum Bacteroidota (formerly Bacteroidetes), particularly the genus Prevotella (P = 3.12e-04). Within this genus, Prevotella_sp._CAG:732, Prevotella_sp._MSX73, and Prevotella_sp._MA2016 showed significant upregulation of genes related to BCAA synthesis. Functional enrichment analysis indicated enrichment of BCAA synthesis-related pathways in both rumen metagenomes and metabolomes. Additionally, muscle transcriptomics indicated enrichment in muscle fiber and amino acid metabolism, with upregulation of solute carrier family genes, enhancing BCAA transport. These findings suggest that elevated rumen Prevotella in MSTN-KO cattle, combined with MSTN deletion, synergistically improves muscle growth through enhanced BCAA synthesis and transport.PMID:39592704 | DOI:10.1038/s42003-024-07252-9

Sci Rep. 2024 Nov 26;14(1):29380. doi: 10.1038/s41598-024-79780-7.ABSTRACTUnderstanding the intricate interplay between nanoparticle-mediated cyanobacterial interactions is pivotal in elucidating their impact on the transcriptome and lipidome. In the present study, total fatty acid methyl esters (FAMEs) in the wild-type (B481-WT) and transformant (B481-SD) Fremyella diplosiphon strains treated with nanoscale zero-valent iron nanoparticles (nZVIs) were characterized, and transcriptome changes analyzed. Comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry revealed a 20-25% higher percentage of FAMEs in nZVI-treated F. diplosiphon strain B481-SD compared to B481-WT. Accumulation of alkanes was significantly higher (> 1.4 times) in both strains treated with 25.6 mg L-1 nZVIs compared to the untreated control. In addition, we observed significantly higher levels of monounsaturated FAMEs (11%) in B481-WT in 3.2 (11.34%) and 25.6 mg L-1 (11.22%) nZVI-treated cells when compared to the untreated control (7%). Analysis of the F. diplosiphon transcriptome treated with 3.2 mg L-1 revealed a total of 1811 and 1651 genes that were differentially expressed in B481-SD and B481-WT respectively. While the expression of iron uptake and ion channel genes was downregulated, genes coding for photosynthesis, pigment, and antioxidant enzymes were significantly (p < 0.05) upregulated in B481-SD treated with 3.2 mg L-1 nZVIs compared to the untreated control. This study on essential FAMEs and regulation of genes in nZVI-treated F. diplosiphon strains provides a molecular framework for optimization of metabolic pathways in this model species.PMID:39592694 | DOI:10.1038/s41598-024-79780-7

Mitochondrion. 2024 Nov 24:101991. doi: 10.1016/j.mito.2024.101991. Online ahead of print.ABSTRACTBACKGROUND: Low leukocyte mitochondrial DNA (mtDNA) abundance has been associated with a higher risk of atherosclerotic cardiovascular disease, but through unclear mechanisms. We aimed to investigate whether low mtDNA abundance is associated with worse metabolomic profiling, as being potential intermediate phenotypes, using cross-sectional and genetic studies.METHODS: Among 61,186 unrelated European participants from UK Biobank, we performed multivariable-adjusted linear regression analyses to examine the associations between mtDNA abundance and 168 NMR-based circulating metabolomic measures and nine metabolomic principal components (PCs) that collectively covered 91.5% of the total variation of individual metabolomic measures. Subsequently, we conducted Mendelian randomization (MR) to approximate the causal effects of mtDNA abundance on the individual metabolomic measures and their metabolomic PCs.RESULTS: After correction for multiple testing, low mtDNA abundance was associated with 130 metabolomic measures, predominantly lower concentrations of some amino acids and higher concentrations of lipids, lipoproteins and fatty acids; moreover, mtDNA abundance was associated with seven out of the nine metabolomic PCs. Using MR, genetically-predicted low mtDNA abundance was associated with lower lactate (standardized beta and 95% confidence interval: -0.17; -0.26, -0.08), and higher acetate (0.15; 0.07,0.23), and unsaturation degree (0.14; 0.08,0.20). Similarly, genetically-predicted low mtDNA abundance was associated with lower metabolomic PC2 (related to lower concentrations of lipids and fatty acids), and higher metabolomic PC9 (related to lower concentrations of glycolysis-related metabolites).CONCLUSION: Low mtDNA abundance is associated with metabolomic perturbations, particularly reflecting a pro-atherogenic metabolomic profile, which potentially could link low mtDNA abundance to higher atherosclerosis risk.PMID:39592086 | DOI:10.1016/j.mito.2024.101991