Identification of Metabolic Alterations in Breast Cancer Using Mass Spectrometry-Based Metabolomic Analysis

Neuroprotection of rhubarb extract against cerebral ischaemia-reperfusion injury via the gut-brain axis pathway

BACKGROUND

The gut-brain axis (GBA) plays a central role in cerebral ischaemia-reperfusion injury (CIRI). Rhubarb, known for its purgative properties, has demonstrated protective effects against CIRI. However, it remains unclear whether this protective effect is achieved through the regulation of the GBA.

AIM

This study aims to investigate the mechanism by which rhubarb extract improves CIRI by modulating the GBA pathway.

METHODS

We identified the active components of rhubarb extract using LC-MS/MS. The model of middle cerebral artery occlusion (MCAO) was established to evaluate the effect of rhubarb extract. We conducted 16S rDNA sequencing and untargeted metabolomics to analyze intestinal contents. Additionally, we employed HE staining, TUNEL staining, western blot, and ELISA to assess intestinal barrier integrity. We measured the levels of inflammatory cytokines in serum via ELISA. We also examined blood-brain barrier (BBB) integrity using Evans blue (EB) penetration, transmission electron microscopy (TEM), western blot, and ELISA. Neurological function scores and TTC staining were utilized to evaluate neurological outcomes.

RESULTS

We identified twenty-six active components in rhubarb. Rhubarb extract enhanced α-diversity, reduced the abundance of Enterobacteriaceae, and partially rectified metabolic disorders in CIRI rats. It also ameliorated pathological changes, increased the expressions of ZO-1, Occludin, and Claudin 1 in the colon, and reduced levels of LPS and d-lac in serum. Furthermore, it lowered the levels of IL-1β, IL-6, IL-10, IL-17, and TNF-α in serum. Rhubarb extract mitigated BBB dysfunction, as evidenced by reduced EB penetration and improved hippocampal microstructure. It upregulated the expressions of ZO-1, Occludin, Claudin 1, while downregulating the expressions of TLR4, MyD88, and NF-κB. Similarly, rhubarb extract decreased the levels of IL-1β, IL-6, and TNF-α in the hippocampus. Ultimately, it reduced neurological function scores and cerebral infarct volume.

CONCLUSION

Rhubarb effectively treats CIRI, potentially by inhibiting harmful bacteria, correcting metabolic disorders, repairing intestinal barrier function, alleviating BBB dysfunction, and ultimately improving neurological outcomes.

Danggui Shaoyao San: comprehensive modulation of the microbiota-gut-brain axis for attenuating Alzheimer's disease-related pathology

Background: Alzheimer's disease (AD), an age-associated neurodegenerative disorder, currently lacks effective clinical therapeutics. Traditional Chinese Medicine (TCM) holds promising potential in AD treatment, exemplified by Danggui Shaoyao San (DSS), a TCM formulation. The precise therapeutic mechanisms of DSS in AD remain to be fully elucidated. This study aims to uncover the therapeutic efficacy and underlying mechanisms of DSS in AD, employing an integrative approach encompassing gut microbiota and metabolomic analyses. Methods: Thirty Sprague-Dawley (SD) rats were allocated into three groups: Blank Control (Con), AD Model (M), and Danggui Shaoyao San (DSS). AD models were established via bilateral intracerebroventricular injections of streptozotocin (STZ). DSS was orally administered at 24 g·kg-1·d-1 (weight of raw herbal materials) for 14 days. Cognitive functions were evaluated using the Morris Water Maze (MWM) test. Pathological alterations were assessed through hematoxylin and eosin (HE) staining. Bloodstream metabolites were characterized, gut microbiota profiled through 16S rDNA sequencing, and cortical metabolomics analyzed. Hippocampal proinflammatory cytokines (IL-1β, IL-6, TNF-α) were quantified using RT-qPCR, and oxidative stress markers (SOD, CAT, GSH-PX, MDA) in brain tissues were measured with biochemical assays. Results: DSS identified a total of 1,625 bloodstream metabolites, predominantly Benzene derivatives, Carboxylic acids, and Fatty Acyls. DSS significantly improved learning and spatial memory in AD rats and ameliorated cerebral tissue pathology. The formulation enriched the probiotic Ligilactobacillus, modulating metabolites like Ophthalmic acid (OA), Phosphocreatine (PCr), Azacridone A, Inosine, and NAD. DSS regulated Purine and Nicotinate-nicotinamide metabolism, restoring balance in the Candidatus Saccharibacteria-OA interplay and stabilizing gut microbiota-metabolite homeostasis. Additionally, DSS reduced hippocampal IL-1β, IL-6, TNF-α expression, attenuating the inflammatory state. It elevated antioxidative enzymes (SOD, CAT, GSH-PX) while reducing MDA levels, indicating diminished oxidative stress in AD rat brains. Conclusion: DSS addresses AD pathology through multifaceted mechanisms, encompassing gut microbiome regulation, specific metabolite modulation, and the mitigation of inflammation and oxidative stress within the brain. This holistic intervention through the Microbial-Gut-Brain Axis (MGBA) underscores DSS's potential as an integrative therapeutic agent in combatting AD.

Serum Metabolomics of Retinoblastoma: Assessing the Differential Serum Metabolic Signatures of Unilateral and Bilateral Patients

Retinoblastoma (Rb) is the most common pediatric eye cancer. To identify the biomarkers for early diagnosis and monitoring the progression of Rb in patients, mapping of the alterations in their metabolic profiles is essential. The present study aims at exploring the metabolic disparity in serum from Rb patients and controls using NMR-based metabolomics. A total of 72 metabolites, including carbohydrates, amino acids, and organic acids, were quantified in serum samples from 24 Rb patients and 26 controls. Distinct clusters of Rb patients and controls were obtained using the partial least-squares discriminant analysis (PLS-DA) model. Further, univariate and multivariate analyses of unilateral and bilateral Rb patients with respect to their age-matched controls depicted their distinct metabolic fingerprints. Metabolites including 2-phosphoglycerate, 4-aminobutyrate, proline, O-phosphocholine, O-phosphoethanolamine, and Sn-glycero-3-phosphocholine (Sn-GPC) showed significant perturbation in both unilateral and bilateral Rb patients. However, metabolic differences among the bilateral Rb cases were more pronounced than those in unilateral Rb cases with respect to controls. In addition to major discriminatory metabolites for Rb, unilateral and bilateral Rb cases showed specific metabolic changes, which might be the result of their differential genetic/somatic mutational backgrounds. This further suggests that the aberrant metabolic perturbation in bilateral patients signifies the severity of the disease in Rb patients. The present study demonstrated that identified serum metabolites have potential to serve as a noninvasive method for detection of Rb, discriminate bilateral from unilateral Rb patients, and aid in better understanding of the RB tumor biology.

Danggui Shaoyao San ameliorates the lipid metabolism via the PPAR signaling pathway in a Danio rerio (zebrafish) model of hyperlipidemia

The escalating prevalence of hyperlipidemia has a profound impact on individuals' daily physiological well-being. The traditional Chinese medicine (TCM) prescription Danggui Shaoyao San (DSS) has demonstrated significant clinical efficacy and promising prospects for clinical application. Leveraging network pharmacology and bioinformatics, we hypothesize that DSS can ameliorate lipid metabolic disorders in hyperlipidemia by modulating the PPAR signaling pathway. In this study, we employed a zebrafish model to investigate the impact of DSS on lipid metabolism in hyperlipidemia. Body weight alterations were monitored by pre- and postmodeling weight measurements. Behavioral assessments and quantification of liver biochemical markers were conducted using relevant assay kits. Pathways associated with lipid metabolism were identified through network pharmacology and GEO analysis, while PCR was utilized to assess genes linked to lipid metabolism. Western blotting was employed to analyze protein expression levels, and liver tissue underwent Oil Red O and immunofluorescence staining to evaluate liver lipid deposition. Our findings demonstrate that DSS effectively impedes weight gain and reduces liver lipid accumulation in zebrafish models with elevated lipid levels. The therapeutic effects of DSS on lipid metabolism are mediated through its modulation of the PPAR signaling pathway, resulting in a significant reduction in lipid accumulation within the body and alleviation of certain hyperlipidemia-associated symptoms.

Mussel mass mortality in the Clinch River, USA: metabolomics detects affected pathways and biomarkers of stress

Biologists monitoring freshwater mussel (order Unionida) populations rely on behavioral, often subjective, signs to identify moribund ("sick") or stressed mussels, such as gaping valves and slow response to probing, and they lack clinical indicators to support a diagnosis. As part of a multi-year study to investigate causes of reoccurring mortality of pheasantshell (Ortmanniana pectorosa; synonym Actinonaias pectorosa) in the Clinch River, Virginia and Tennessee, USA, we analyzed the hemolymph metabolome of a subset of mussels from the 2018 sampling period. Mussels at the mortality sites were diagnosed in the field as affected (case) or unaffected (control) based on behavioral and physical signs. Hemolymph was collected in the field by non-lethal methods from the anterior adductor muscle for analysis. We used ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectroscopy to detect targeted and untargeted metabolites in hemolymph and compared metabolomic profiles by field assessment of clinical status. Targeted biomarker analysis found 13 metabolites associated with field assessments of clinical status. Of these, increased gamma-linolenic acid and N-methyl-l-alanine were most indicative of case mussels, while adenine and inosine were the best indicators of control mussels. Five pathways in the targeted analysis differed by clinical status; two of these, purine metabolism and glycerophospholipid metabolism, were also indicated in the untargeted analysis. In the untargeted nalysis, 22 metabolic pathways were associated with clinical status. Many of the impacted pathways in the case group were catabolic processes, such as degradation of amino acids and fatty acids. Hierarchical clustering analysis matched clinical status in 72% (18 of 25) of mussels, with control mussels more frequently (5 of 16) not matching clinical status. Our study demonstrated that metabolomic analysis of hemolymph is suitable for assessing mussel condition and complements field-based indicators of health.

Omics Technologies Improving Breast Cancer Research and Diagnostics

Breast cancer (BC) has yielded approximately 2.26 million new cases and has caused nearly 685,000 deaths worldwide in the last two years, making it the most common diagnosed cancer type in the world. BC is an intricate ecosystem formed by both the tumor microenvironment and malignant cells, and its heterogeneity impacts the response to treatment. Biomedical research has entered the era of massive omics data thanks to the high-throughput sequencing revolution, quick progress and widespread adoption. These technologies-liquid biopsy, transcriptomics, epigenomics, proteomics, metabolomics, pharmaco-omics and artificial intelligence imaging-could help researchers and clinicians to better understand the formation and evolution of BC. This review focuses on the findings of recent multi-omics-based research that has been applied to BC research, with an introduction to every omics technique and their applications for the different BC phenotypes, biomarkers, target therapies, diagnosis, treatment and prognosis, to provide a comprehensive overview of the possibilities of BC research.

Serum metabolic profile and metabolome genome-wide association study in chicken

BACKGROUND

Chickens provide globally important livestock products. Understanding the genetic and molecular mechanisms underpinning chicken economic traits is crucial for improving their selective breeding. Influenced by a combination of genetic and environmental factors, metabolites are the ultimate expression of physiological processes and can provide key insights into livestock economic traits. However, the serum metabolite profile and genetic architecture of the metabolome in chickens have not been well studied.

RESULTS

Here, comprehensive metabolome detection was performed using non-targeted LC-MS/MS on serum from a chicken advanced intercross line (AIL). In total, 7,191 metabolites were used to construct a chicken serum metabolomics dataset and to comprehensively characterize the serum metabolism of the chicken AIL population. Regulatory loci affecting metabolites were identified in a metabolome genome-wide association study (mGWAS). There were 10,061 significant SNPs associated with 253 metabolites that were widely distributed across the entire chicken genome. Many functional genes affect metabolite synthesis, metabolism, and regulation. We highlight the key roles of TDH and AASS in amino acids, and ABCB1 and CD36 in lipids.

CONCLUSIONS

We constructed a chicken serum metabolite dataset containing 7,191 metabolites to provide a reference for future chicken metabolome characterization work. Meanwhile, we used mGWAS to analyze the genetic basis of chicken metabolic traits and metabolites and to improve chicken breeding.

Two effective models based on comprehensive lipidomics and metabolomics can distinguish BC versus HCs, and TNBC versus non-TNBC

BACKGROUND

Lipidomics and metabolomics are closely related to tumor phenotypes, and serum lipoprotein subclasses and small-molecule metabolites are considered as promising biomarkers for breast cancer (BC) diagnosis. This study aimed to explore potential biomarker models based on lipidomic and metabolomic analysis that could distinguish BC from healthy controls (HCs) and triple-negative BC (TNBC) from non-TNBC.

METHODS

Blood samples were collected from 114 patients with BC and 75 HCs. A total of 112 types of lipoprotein subclasses and 30 types of small-molecule metabolites in the serum were detected by ¹ H-NMR. All lipoprotein subclasses and small-molecule metabolites were subjected to a three-step screening process in the order of significance (p < 0.05), univariate regression (p < 0.1), and lasso regression (nonzero coefficient). Discriminant models of BC versus HCs and TNBC versus non-TNBC were established using binary logistic regression.

RESULTS

We developed a valid discriminant model based on three-biomarker panel (formic acid, TPA2, and L6TG) that could distinguish patients with BC from HCs. The area under the receiver operating characteristic curve (AUC) was 0.999 (95% confidence interval [CI]: 0.995-1.000) and 0.990 (95% CI: 0.959-1.000) in the training and validation sets, respectively. Based on the panel (D-dimer, CA15-3, CEA, L5CH, glutamine, and ornithine), a discriminant model was established to differentiate between TNBC and non-TNBC, with AUC of 0.892 (95% CI: 0.778-0.967) and 0.905 (95% CI: 0.754-0.987) in the training and validation sets, respectively.

CONCLUSION

This study revealed lipidomic and metabolomic differences between BC versus HCs and TNBC versus non-TNBC. Two validated discriminatory models established against lipidomic and metabolomic differences can accurately distinguish BC from HCs and TNBC from non-TNBC.

IMPACT

Two validated discriminatory models can be used for early BC screening and help BC patients avoid time-consuming, expensive, and dangerous BC screening.

High-Coverage Serum Metabolomics Reveals Metabolic Pathway Dysregulation in Diabetic Retinopathy: A Propensity Score-Matched Study

Background: Diabetic retinopathy (DR) is a major diabetes-related disease linked to metabolism. However, the cognition of metabolic pathway alterations in DR remains scarce. We aimed to corroborate alterations of metabolic pathways identified in prior studies and investigate novel metabolic dysregulations that may lead to new prevention and treatment strategies for DR.

Methods: In this case-control study, we tested 613 serum metabolites in 69 pairs of type 2 diabetic patients (T2DM) with DR and propensity score-matched T2DM without DR via ultra-performance liquid chromatography-tandem mass spectrometry system. Metabolic pathway dysregulation in DR was thoroughly investigated by metabolic pathway analysis, chemical similarity enrichment analysis (ChemRICH), and integrated pathway analysis. The associations of ChemRICH-screened key metabolites with DR were further estimated with restricted cubic spline analyses.

Results: A total of 89 differentially expressed metabolites were identified by paired univariate analysis and partial least squares discriminant analysis. We corroborated biosynthesis of unsaturated fatty acids, glycine, serine and threonine metabolism, glutamate and cysteine-related pathways, and nucleotide-related pathways were significantly perturbed in DR, which were identified in prior studies. We also found some novel metabolic alterations associated with DR, including the disturbance of thiamine metabolism and tryptophan metabolism, decreased trehalose, and increased choline and indole derivatives in DR.

Conclusions: The results suggest that the metabolism disorder in DR can be better understood through integrating multiple biological knowledge databases. The progression of DR is associated with the disturbance of thiamine metabolism and tryptophan metabolism, decreased trehalose, and increased choline and indole derivatives.

Mapping Aspergillus niger Metabolite Biomarkers for In Situ and Early Evaluation of Table Grapes Contamination

The Aspergillus niger exometabolome was recently investigated using advanced gas chromatography in tandem with multivariate analysis, which allowed a metabolite biomarker pattern to be proposed. Microbial metabolomics patterns have gained enormous relevance, mainly due to the amount of information made available, which may be useful in countless processes. One of the great challenges in microbial metabolomics is related to applications in more complex systems of metabolomics information obtained from studies carried out in culture media, as complications may occur due to the dynamic nature of biological systems. Thus, the main objective of this research was to evaluate the applicability of the A. niger metabololite biomarkers pattern for in situ and early evaluation of table grapes contamination, used as study model. A. niger is a ubiquitous fungus responsible for food contamination, being reported as one of the main agents of the black mold disease, a serious post-harvest pathology of table grapes. This work included analysis from 1 day of growth time of pure A. niger cultures, A. niger cultures obtained from previously contaminated grapes, and finally, an in situ solid-phase microextraction (SPME) approach directly on previously contaminated table grapes. Supervised multivariate analysis was performed which revealed that after 1 day of inoculation it was possible to detect A. niger biomarkers, which can be extremely useful in making this type of method possible for the rapid detection of food contamination. The results obtained confirm the potential applicability of the pattern of A. niger biomarkers for early detection of the fungi (after 1 day of contamination), and may be further explored for access food susceptibility to fungi contamination, based on direct analysis of the food item.

A Metabolic Choreography of Maize Plants Treated with a Humic Substance-Based Biostimulant under Normal and Starved Conditions

Humic substance (HS)-based biostimulants show potentials as sustainable strategies for improved crop development and stress resilience. However, cellular and molecular mechanisms governing the agronomically observed effects of HS on plants remain enigmatic. Here, we report a global metabolic reprogramming of maize leaves induced by a humic biostimulant under normal and nutrient starvation conditions. This reconfiguration of the maize metabolism spanned chemical constellations, as revealed by molecular networking approaches. Plant growth and development under normal conditions were characterized by key differential metabolic changes such as increased levels of amino acids, oxylipins and the tricarboxylic acid (TCA) intermediate, isocitric acid. Furthermore, under starvation, the humic biostimulant significantly impacted pathways that are involved in stress-alleviating mechanisms such as redox homeostasis, strengthening of the plant cell wall, osmoregulation, energy production and membrane remodelling. Thus, this study reveals that the humic biostimulant induces a remodelling of inter-compartmental metabolic networks in maize, subsequently readjusting the plant physiology towards growth promotion and stress alleviation. Such insights contribute to ongoing efforts in elucidating modes of action of biostimulants, generating fundamental scientific knowledge that is necessary for development of the biostimulant industry, for sustainable food security.

Analysis of Increased EGFR and IGF-1R Signaling and Its Correlation with Socio-Epidemiological Features and Biological Profile in Breast Cancer Patients: A Study in Northern Brazil

INTRODUCTION

Breast cancer (BC) is the second most frequent cancer worldwide. It is known that a subset of BC has amplification, and overexpression of the epidermal growth factor receptor (EGFR) and high expression of the insulin-like growth factor receptor-1 (IGF-1R) are correlated with a favorable prognosis. This study aimed to evaluate the prognostic and predictive values of the EGFR and IGF-1R in tumor samples from patients with BC and their correlation with socio-epidemiological features.

PATIENTS AND METHODS

We analyzed socio-epidemiological, clinical-pathological data and tumor tissues from 124 patients with BC undergoing treatment, to assess levels of EGFR and IGF-1R mRNA and protein. The predictive performance included the calculation of area-under-the-curve (AUC) to discriminate groups of patients with high and low mRNA expression associated with survival analysis within each molecular group of BC.

RESULTS

We found a significant expression increase (p <0.001) in EGFR associated with body mass index, angiolymphatic invasion, compromised lymph nodes and follow-up in 58.1% of the triple-negative and HER overexpression tumors. The increase in IGF-IR was significant (p <0.001) in 41.9% of luminal tumors A and B. ROC analysis showed that EGFR had a higher predictive performance (AUC = 0.891) than IGF-1R (AUC = 0.60). The Kaplan-Meier analysis indicated that only the high expression of EGFR was associated with a decreased probability of survival for patients, what did not happen with IGF-1R.

CONCLUSION

Our results suggest that EGFR and IGF-1R expression patterns associated with the clinical characteristics of patients and biological profile influenced the evolution of BC.