Search Results (307)

Background: Type 2 diabetes (T2D) is a global health epidemic with rising prevalence within Asian populations, particularly amongst individuals with high visceral adiposity and ectopic organ fat, the so-called Thin-Outside, Fat-Inside phenotype. Metabolomic and microbiome shifts may herald T2D onset, presenting potential biomarkers and mechanistic insight into metabolic dysregulation. However, multi-omics datasets across ethnicities remain limited. Methods: We performed cross-sectional multi-omics analyses on 171 adults (99 Asian Chinese, 72 European Caucasian) from the New Zealand-based TOFI_Asia cohort at 4-years follow-up. Paired plasma and faecal samples were analysed using untargeted metabolomic profiling (polar/lipid fractions) and shotgun metagenomic sequencing, respectively. Sparse multi-block partial least squares regression and discriminant analysis (DIABLO) unveiled signatures associated with ethnicity, glycaemic status, and sex. Results: Ethnicity-based DIABLO modelling achieved a balanced error rate of 0.22, correctly classifying 76.54% of test samples. Polar metabolites had the highest discriminatory power (AUC = 0.96), with trigonelline enriched in European Caucasians and carnitine in Asian Chinese. Lipid profiles highlighted ethnicity-specific signatures: Asian Chinese showed enrichment of polyunsaturated triglycerides (TG.16:0_18:2_22:6, TG.18:1_18:2_22:6) and ether-linked phospholipids, while European Caucasians exhibited higher levels of saturated species (TG.16:0_16:0_14:1, TG.15:0_15:0_17:1). The bacteria Bifidobacterium pseudocatenulatum, Erysipelatoclostridium ramosum, and Enterocloster bolteae characterised Asian Chinese participants, while Oscillibacter sp. and Clostridium innocuum characterised European Caucasians. Cross-omic correlations highlighted negative correlations of Phocaeicola vulgatus with amino acids (r = −0.84 to −0.76), while E. ramosum and C. innocuum positively correlated with long-chain triglycerides (r = 0.55–0.62). Conclusions: Ethnicity drove robust multi-omic differentiation, revealing distinctive metabolic and microbial profiles potentially underlying the differential T2D risk between Asian Chinese and European Caucasians. Full article

Breast cancer (BC) is a neoplasm characterized by high heterogeneity and is influenced by intrinsic molecular subtypes and clinical stage, aspects that remain underexplored in the Colombian population. This study aimed to characterize metabolic alterations associated with subtypes and disease progression in a group of newly diagnosed, treatment-naive Colombian women using an untargeted metabolomics approach. To improve metabolite coverage, samples were analyzed using LC-QTOF-MS and GC-QTOF-MS, along with amino acid profiling. The Luminal B subtype exhibited elevated levels of long-chain acylcarnitines and higher free fatty acid concentrations than the other subtypes. It also presented elevated levels of carbohydrates and essential glycolytic intermediates, suggesting that this subtype may adopt a hybrid metabolic phenotype characterized by increased glycolytic flux as well as enhanced fatty acid catabolism. Tumor, Node, and Metastasis (TNM) staging analysis revealed progressive metabolic reprogramming of BC. In advanced stages, a sustained increase in phosphatidylcholines and a decrease in lysophosphatidylcholines were observed, reflecting lipid alterations associated with key roles in tumor progression. In early stages (I-II), plasma metabolites with high discriminatory power were identified, such as glutamic acid, ribose, and glycerol, which are associated with dysfunctions in energy and carbohydrate metabolism. These results highlight metabolomics as a promising tool for the early diagnosis, clinical follow-up, and molecular characterization of BC. Full article

This study employs a machine learning approach to identify a small-molecule-based signature capable of predicting Alzheimer’s disease (AD). Utilizing metabolomics data from the plasma of a well-characterized cohort of 94 AD patients and 62 healthy controls; metabolite levels were assessed using the Biocrates MxP^® Quant 500 platform. Data preprocessing involved removing low-quality samples, selecting relevant biochemical groups, and normalizing metabolite data based on demographic variables such as age, sex, and fasting time. Linear regression models were used to identify concomitant parameters that consisted of the data for a given metabolite within each of the biochemical families that were considered. Detection of these “concomitant” metabolites facilitates normalization and allows sample comparison. Residual analysis revealed distinct metabolite profiles between AD patients and controls across groups, such as amino acid-related compounds, bile acids, biogenic amines, indoles, carboxylic acids, and fatty acids. Correlation heatmaps illustrated significant interdependencies, highlighting specific molecules like carnosine, 5-aminovaleric acid (5-AVA), cholic acid (CA), and indoxyl sulfate (Ind-SO₄) as promising indicators. Linear Discriminant Analysis (LDA), validated using Leave-One-Out Cross-Validation, demonstrated that combinations of four or five molecules could classify AD with accuracy exceeding 75%, sensitivity up to 80%, and specificity around 79%. Notably, optimal combinations integrated metabolites with both a tendency to increase and a tendency to decrease in AD. A multivariate strategy consistently identified included 5-AVA, carnosine, CA, and hypoxanthine as having predictive potential. Overall, this study supports the utility of combining data of plasma small molecules as predictors for AD, offering a novel diagnostic tool and paving the way for advancements in personalized medicine. Full article

Plasmodium vivax malaria continues to pose a significant and enduring public health challenge across the Americas. Transmission-blocking vaccines (TBVs), which target gametocyte surface antigens such as Pvs47 and Pvs48/45, are being investigated as promising tools to interrupt transmission and advance toward disease elimination. To investigate the genetic diversity and phylogeographic structure of the pvs47 and pvs48/45 genes in P. vivax, we conducted molecular analyses on samples collected from seven malaria-endemic regions of Honduras using PCR-based sequencing, population genetics, and phylogenetic approaches. This study presents the first complete characterization of the pvs47 gene and expands the available data on pvs48/45 in P. vivax from Honduras. We observed a low level of genetic diversity with no evidence of geographic structuring within the country. At a global scale, Honduran sequences shared variants with other Latin American strains and exhibited region-specific amino acid signatures. These findings suggest that local selective pressures, possibly driven by mosquito vector compatibility, are shaping the evolution of these TBV candidate genes. Our results underscore the importance of regional surveillance to inform the development and deployment of effective transmission-blocking strategies. Full article

This review examines human digestive physiology and metabolic adaptations in the context of evolutionary dietary patterns, particularly those emphasizing carnivorous and scavenging behaviors. By integrating metabolomic data with archaeological, anatomical, and microbiological evidence, the study explores how early hominins adapted to intermittent but energy-dense animal-based diets. The analysis highlights the development of hepatic insulin resistance, enhanced fat and protein metabolism, and shifts in gut microbiota diversity as physiological signatures of meat consumption. Comparative evaluations of digestive enzyme profiles, intestinal morphology, and salivary composition underscore humans’ omnivorous flexibility and partial carnivorous specialization. Additionally, biomarkers such as ketone bodies, branched-chain amino acids, and trimethylamine-N-oxide are identified as metabolic indicators of habitual meat intake. These adaptations, though once evolutionarily advantageous, are discussed in relation to current metabolic disorders in modern nutritional contexts. Overall, this review presents a metabolomic framework for understanding the evolutionary trajectory of human digestion and its implications for health and dietary recommendations. Full article

The large portion of the eukaryotic genomes was considered non-functional and called the “dark matter” of the genome, now appearing as regulatory hubs coding for RNAs without the potential for making proteins, known as non-coding RNA. Long non-coding RNA (lncRNA) is defined as functional RNA molecules having lengths larger than 200 nucleotides without the potential for coding for proteins. Thousands of lncRNAs are identified in different plants and animals. LncRNAs are characterized by a low abundance, fewer exons than mRNA, tissue-specific expression, and low sequence conservation compared to protein-coding genes (PCGs). LncRNAs, like PCGs, are regulated by promoters and enhancers with characteristic chromatin signatures, DNA methylation, multiple exons, introns, and alternate splicing. LncRNAs interact with DNA, mRNA, microRNA, and proteins, including chromatin/histone modifiers, transcription factors/repressors, epigenetic regulators, spliceosomal, and RNA-binding proteins. Recent observations indicate that lncRNAs code for small peptides, also called micropeptides (<100 amino acids), and are involved in the development and growth of plants, suggesting the bi-functional activities of lncRNAs. LncRNAs have emerged as the major regulators of diverse functions, principally by altering the transcription of target genes. LncRNAs are involved in plant growth, development, immune responses, and various physiological processes. Abiotic, biotic, nutrient, and other environmental stresses alter the expressions of numerous lncRNAs. Understanding the mechanisms of actions of lncRNAs opens up the possibility of improving agronomic traits by manipulating lncRNAs. However, further studies are required in order to find the interactions among the deregulated lncRNAs and validate the findings from high-throughput studies to harness their potential in crop improvement. Full article

The mechanisms of chemoreception in fig wasps (Hymenoptera, Agaonidae) are of primary importance in their co-evolutionary relationship with the fig trees they pollinate. As the supplementary receptors to odorant receptors (ORs) and gustatory receptors (GRs) in insects, we compare the evolutionary characters of ionotropic receptors (IRs) among 25 fig wasp taxa in six genera. In total, we identified 205 IRs in 25 fig wasps, with each taxon recording from 5 to 12 IR genes. We found 189 IR genes clustered into 18 orthologous groups that can be divided into three types: IRco, antennal IRs, and divergent IRs. More IRs belong to antennal IRs in fig wasps, which can be sensitive to acids, aldehydes, polyamines, salt, amino acids, and temperature/humidity according to homology comparison. Additionally, some IR genes in fig wasps do not cluster with those of outgroup species (e.g., Drosophila melanogaster, Apis mellifera), suggesting they may represent a unique group and may have special functions in fig wasps. Divergent IRs are very few, with large sequence variation between species. Compared to ORs and GRs in fig wasps, gene sequences in most IR orthologous groups are more conserved between genera, with the lowest sequence similarity in 10 orthologous groups (including three IRco) exhibiting above 58.5%. Gene sequences are consistent with the phylogenetic relationships among fig wasps, which is the same as ORs and GRs. Strong purifying selection of IR genes was detected, as shown by the low ω values. Signatures of positive selection were detected in loci from three orthologous groups. Our results provide important molecular information for further studies on chemosensory mechanisms in fig wasps. Full article

Arginine plays a critical role in biomolecular interactions due to its guanidinium side chain, which enables multivalent electrostatic and hydrogen bonding contacts. In this study, atomistic molecular dynamics simulations were conducted across a broad concentration range (26–605 mM) to investigate the thermodynamic and structural features of arginine self-assembly in aqueous solution. Key observables—including hydrogen bond count, radius of gyration, contact number, and isobaric heat capacity—were analyzed to characterize emergent behavior. A three-regime aggregation pattern (dilute, cooperative, and saturated) was identified and quantitatively modeled using the Hill equation, revealing a non-linear transition in clustering behavior. Spatial analyses were supplemented with trajectory-based clustering and radial distribution functions. The heat capacity peak observed near 360 mM was interpreted as a thermodynamic signature of hydration rearrangement. Trajectory analyses utilized both GROMACS tools and the MDAnalysis library. While force field limitations and single-replica sampling are acknowledged, the results offer mechanistic insight into how arginine concentration modulates molecular organization—informing the understanding of biomolecular condensates, protein–nucleic acid complexes, and the design of functional supramolecular systems. The findings are in strong agreement with experimental observations from small-angle X-ray scattering and differential scanning calorimetry. Overall, this work establishes a cohesive framework for understanding amino acid condensation and reveals arginine’s concentration-dependent behavior as a model for weak, reversible molecular association. Full article

In this study, we investigated the functional role of Peroxiredoxin 5 (SmPrx5) in the cuttlefish Sepiella maindroni. The full-length SmPrx5 cDNA is 934 base pairs (bp) in length, comprising a 31 bp 5′ untranslated region (UTR), a 330 bp 3′ UTR, and an open reading frame (ORF) of 573 bp that encodes a polypeptide consisting of 190 amino acids. Sequence analysis revealed the presence of a conserved peroxidase catalytic motif VPGAFTPGCSQTHLPG and the signature domain DGTGLTCSL, indicating that SmPrx5 belongs to the 2-Cys Prx subfamily. Quantitative real-time PCR (RT-qPCR) analysis demonstrated that SmPrx5 is broadly expressed across various tissues in S. maindroni, with particularly high expression levels observed in the testes, hemocytes, liver, and ovaries. Upon challenge with Vibrio alginolyticus, SmPrx5 expression was significantly upregulated in both the liver and hemocytes, peaking at 24 h post-infection and gradually returning to baseline levels within 48 h. Furthermore, the recombinant SmPrx5 protein exhibited notable antioxidant activity in vitro, suggesting its involvement in the oxidative stress response. These findings enhance our understanding of the molecular mechanisms underlying immune defense in marine cephalopods and highlight the potential role of Prx5 in host immunity. Full article

Catechol-like compounds are found throughout biology in the form of both redox-active and metal-binding functional groups. Within the marine environment, catechol groups are known to coordinate strongly with vanadate and ferric ions, and this binding is regulated through redox mechanisms. While investigating marine melanin formation in vitro, we found that DOPA, a catechol-containing amino acid, reacts with both metals differently when provided with sulfite, a weak reductant, and selenite, a weak oxidant. Both compounds interacted with the DOPA–vanadium complex, but only selenite, the more redox-labile chalcogenide, led to the creation of melanin particulates. When DOPA, vanadate, and selenite are present together, a metal-binding spectra shift and a melanin variant are rapidly observed. This variant was found to form large, elongated filaments with a low carboxylic acid content and a unique electron paramagnetic resonance signature. When compared to enzymatically produced melanin, this chemically synthesized variant was more thermally and biologically inert, exhibiting a lower redox activity. The results demonstrate that the regulation of the redox environment from metal–catechol interactions can help to control both the chemical and physical properties of melanin aggregates, suggesting a scalable and cell- and enzyme-free synthesis pathway for applications that may require inert materials of strict composition. Full article

Background: Childhood obesity is a growing global health concern. Metabolomics, the comprehensive study of metabolites within biological systems, offers a powerful approach to better define the phenotype and understand the complex biochemical alterations associated with obesity. The aim of this systematic review was to summarize current knowledge in the field of metabolomics in childhood obesity and to identify metabolic signatures or biomarkers associated with overweight/obesity (Ov/Ob) and Metabolically Unhealthy Obesity (MUO) in children and adolescents. Methods: We performed a systematic search of Medline and Scopus databases according to PRISMA guidelines. We included only longitudinal prospective studies or randomized controlled trials with ≥12 months of follow-up, as well as meta-analyses of the above that assessed the relation between metabolic signatures related to obesity and Body Mass Index (BMI) or other measures of adiposity in children and adolescents aged 2–19 years with overweight or obesity. Initially, 595 records were identified from PubMed and 1565 from Scopus. After removing duplicates and screening for relevance, 157 reports were assessed for eligibility. From the additional search, 75 new records were retrieved, of which none were eligible for our study. Finally, 7 reports were included in the present systematic review (4 reporting on Ov/Ob and 4 on MUO). Results: The presented studies suggest that the metabolism of amino acids and lipids is primarily affected by childhood obesity. Metabolites like glycoprotein acetyls, the Apolipoprotein B/Apolipoprotein A-1 ratio, and lactate have emerged as potential biomarkers for insulin resistance and metabolic syndrome, highlighting their potential value in clinical applications. Conclusions: There is a need for future longitudinal studies to assess metabolic changes over time, interventional studies to evaluate the efficacy of therapeutic strategies, and large-scale population studies to explore metabolic diversity across different demographics. Our findings reveal specific biomarkers in the amino acid and lipid pathway that may serve as early indicators of childhood obesity and its associated cardiometabolic complications. Full article

The human immunodeficiency virus (HIV-1) infiltrates the central nervous system (CNS) early in infection, leading to HIV-associated neurocognitive impairments, particularly pronounced in children who exhibit neurodevelopmental delay. Viral proteins, including the transactivator of transcription protein (Tat) and viral protein R (Vpr) are pivotal in HIV-1 neuropathogenesis, with their amino acid sequence variation influencing disease progression. Due to the difficulty of collecting cerebrospinal fluid from children, few studies have examined whether key Tat and Vpr neuropathogenic signatures found in blood are also present in the cerebrospinal fluid (CSF) of children with HIV. We employed Sanger sequencing for Tat and Vpr sequence analysis using retrospectively collected CSF samples from a South African pediatric HIV-1 subtype C cohort (n = 4). We compared our CSF-derived sequences with pediatric blood-derived sequences (n = 43) from various geographical regions, sourced from the Los Alamos database. Neuropathogenic amino acid variants were identified in Tat and Vpr sequences derived from CSF samples of South African pediatric participants No significant differences were found between subtype C sequences from CSF and blood. Regional analysis highlighted unique amino acid signatures. Obtaining pediatric CSF for HIV-1 sequencing is highly challenging. Despite a small sample size, this study offers rare insights into Tat and Vpr sequences in children, improving understanding of the potential HIV-1 brain pathogenesis in pediatric populations. Full article

The neurobehavioral changes in food allergy mice have not been comprehensively studied, and the mechanism underlying them remains unclear. Our study aims to fully investigate neurobehavioral changes in OVA (ovalbumin)-sensitized food allergy mice and explore the potential mechanism via the gut microbiota–brain axis. We established the food allergy mouse (C57BL/6J male) model with OVA, evaluating the anaphylactic symptoms and the levels of Th2 signature cytokine and allergy-related antibodies in serum. Using behavioral tests, we measured anxiety, depression, social behavior, repetitive behavior, attention, and spatial memory in control and OVA mice. In addition, we analyzed the prefrontal cortex for measuring inflammation-related indicators and gathered serum for untargeted metabolomics analysis and feces for 16S rDNA sequencing. OVA mice exhibited anaphylactic symptoms and significantly elevated serum IgE and Th2 signature cytokine levels. In addition to anxiety-like, depression-like, and repetitive behaviors, OVA mice also displayed less social interest and damaged attention. TNF-α, IL-1β, and IL-6 levels and the activation of microglia in the prefrontal cortex of OVA mice were significantly increased, which might explain the neuronal damage. Using multi-omics technology, amino acid metabolism disruption, particularly carboxylic acids and derivatives, was observed in OVA mice, which was remarkably correlated with the altered abundance of gut microbiota related to food allergy. Behaviors in OVA-induced food allergy mice were extensively impaired. The disruption of amino acid metabolism associated with gut microbiota dysbiosis in OVA mice might play a pivotal role in impairing neural immune homeostasis and neuronal damage, which could be responsible for behavioral abnormalities. Full article

Dihydroartemisinin (DHA) is a bioactive phytopharmaceutical with diverse pharmacological potential, predominantly because of its established antiplasmodial efficacy. Here, we investigated the effects of DHA on metabolic homeostasis in Madin-Darby bovine kidney cells in the context of dose-specific adaptation of metabolism and regulation of biochemistry pathway changes. According to our findings, extensive changes in metabolism were revealed by PCA, accounting for a variability of 59.4% to distinguish contrasting metabolic signatures from normal cells. Metabolomic characterization demonstrated 67 constituting metabolites of baseline cellular processes, while 32 and 44 metabolites have demonstrated differential abundance in low- and high-dose treatments, respectively. Impaired metabolism of glycerophospholipid, amino acid, and nucleotide biosynthesis was reported with implications such as regulation of membrane reorganization, nitrogen metabolism, and cellular bioenergetics. Bioindicators of high-volume lysophosphatidylcholine (18:0) and choline phosphate revealed a lipid homeostatic change, in addition to imbalances in glutamic acid and proline levels. Pathway regulation further modulated ABC transporters and arachidonic acid signaling as implications of systemic phytopharmaceutical-modulated reorganization of metabolism. Hence, the study gives mechanistic insight into DHA-initiated modulation of cellular metabolism in MDBK cells, elucidating its status as a cellular metabolism regulator. Findings confirm the potential of DHA as a phytopharmaceutical in modulating diseases of metabolism, further solidifying its relevance in evidence-based traditional herbal remedies and natural compound therapeutics. Full article

The analysis of blood metabolites may help identify individuals at risk of having COPD and offer insights into its underlying pathophysiology. This study aimed to identify COPD-related metabolic alterations and generate a biological signature potentially useful for screening purposes. Plasma metabolomic profiles from 91 COPD patients and 91 controls were obtained using complementary semi-targeted and untargeted LC-MS approaches. Univariate analysis identified metabolites with significant differences between groups, and enrichment analysis highlighted the most affected metabolic pathways. Multivariate analysis, including ROC curve assessment and machine learning algorithms, was applied to assess the discriminatory capacity of selected metabolites. After adjustment for major potential confounders, 56 metabolites showed significant differences between COPD patients and controls. The enrichment analysis revealed that COPD-associated metabolic alterations primarily involved lipid metabolism (especially fatty acids and acylcarnitines), followed by amino acid pathways and xenobiotics. A panel of 10 metabolites, mostly related to lipid metabolism, demonstrated high discriminatory performance for COPD (ROC-AUC: 0.916; 90.1% sensitivity and 89% specificity). These findings may contribute to improving screening strategies and a better understanding of COPD-related metabolic changes. However, our findings remain exploratory and should be interpreted with caution, needing further validation and mechanistic studies. Full article