Metabolomic analysis uncovered an association of serum phospholipid levels with estrogen-induced mammary tumors in female ACI/Seg rats

Integrative Analysis of Vaginal Microorganisms and Serum Metabolomics in Rats With Estrous Cycle Disorder Induced by Long-Term Heat Exposure Based on 16S rDNA Gene Sequencing and LC/MS-Based Metabolomics

Long term heat exposure (HE) leads to estrous cycle disorder (ECD) in female rats and damages reproductive function. However, the regulation mechanism of vaginal microorganisms and serum metabolomics remains unclear. This study aimed to explore the effects of microbes on the vaginal secretions of rats with ECD and describe the serum metabolomics characteristics and their relationship with vaginal microorganisms. The alterations in the serum levels of neurotransmitters were used to verify the possible regulatory pathways. The relative abundance, composition, and colony interaction network of microorganisms in the vaginal secretions of rats with ECD changed significantly. The metabolomics analysis identified 22 potential biomarkers in the serum including lipid metabolism, amino acid metabolism, and mammalian target of rapamycin and gonadotropin-releasing hormone (GnRH) signaling pathways. Further, 52 pairs of vaginal microbiota–serum metabolites correlations (21 positive and 31 negative) were determined. The abundance of Gardnerella correlated positively with the metabolite L-arginine concentration and negatively with the oleic acid concentration. Further, a negative correlation was found between the abundance of Pseudomonas and the L-arginine concentration and between the metabolite benzoic acid concentration and the abundance of Adlercreutzia. These four bacteria–metabolite pairs had a direct or indirect relationship with the estrous cycle and reproduction. The glutamine, glutamate, and dopamine levels were significantly uncontrolled. The former two were closely related to GnRH signaling pathways involved in the development and regulation of HE-induced ECD in rats. Serum neurotransmitters partly reflected the regulatory effect of vaginal microorganisms on the host of HE-induced ECD, and glutamatergic neurotransmitters might be closely related to the alteration in vaginal microorganisms. These findings might help comprehend the mechanism of HE-induced ECD and propose a new intervention based on vaginal microorganisms.

Developmental exposure of California mice to endocrine disrupting chemicals and potential effects on the microbiome-gut-brain axis at adulthood

Xenoestrogens are chemicals found in plant products, such as genistein (GEN), and in industrial chemicals, e.g., bisphenol A (BPA), present in plastics and other products that are prevalent in the environment. Early exposure to such endocrine disrupting chemicals (EDC) may affect brain development by directly disrupting neural programming and/or through the microbiome-gut-brain axis. To test this hypothesis, California mice (Peromyscus californicus) offspring were exposed through the maternal diet to GEN (250 mg/kg feed weight) or BPA (5 mg/kg feed weight, low dose- LD or 50 mg/kg, upper dose-UD), and dams were placed on these diets two weeks prior to breeding, throughout gestation, and lactation. Various behaviors, gut microbiota, and fecal metabolome were assessed at 90 days of age. The LD but not UD of BPA exposure resulted in individuals spending more time engaging in repetitive behaviors. GEN exposed individuals were more likely to exhibit such behaviors and showed socio-communicative disturbances. BPA and GEN exposed females had increased number of metabolites involved in carbohydrate metabolism and synthesis. Males exposed to BPA or GEN showed alterations in lysine degradation and phenylalanine and tyrosine metabolism. Current findings indicate cause for concern that developmental exposure to BPA or GEN might affect the microbiome-gut-brain axis.

Profiling analysis of phospholipid fatty acids in serum as a complement to the comprehensive fatty acids method

Fatty acids (FAs) are mostly found in blood as triglycerides, phospholipids (PLs) and cholesteryl esters. Determination of FAs is typically carried out in serum or plasma by a comprehensive method (known as the classical FAMEs method since FAs are determined as Fatty Acids Methyl Esters), which is based on liquid-liquid extraction, derivatization by transesterification, and determination by gas chromatography (GC) coupled to a suited detection technique. However, this method does not favor the determination of FAs that are chemically conjugated in PLs due to kinetics impediment. For this reason, we have developed a selective method to determine the FAs profile of PLs in serum based on solid-phase extraction (SPE) for isolation of PLs and determination of the FAME derivatives by GC-mass spectrometry (GC-MS). The method was applied to serum samples collected from twenty-five individuals to compare the FAs profile versus that provided by the non-selective protocol based on liquid-liquid extraction of lipid families. Statistical analysis revealed compositional changes in the FAs profile with special emphasis on the content of saturated (SFAs) and monounsaturated FAs (MUFAs). Thus, SFAs passed from 34.0% with the classical method to 49.3% in PLs while MUFAs went from 24.4% to 11.4%. This study proves that the proposed method provides complementary results to the comprehensive method and, therefore, both methods can be combined to evaluate the effect of intervention diets and their connection to metabolic diseases.

Metabolomic studies of breast cancer in murine models: A review

BACKGROUND

Metabolomic strategies have been extensively used to search for biomarkers of disease, including cancer, in biological complex mixtures such as cells, tissues and biofluids. In breast cancer research, murine models are of great value and metabolomics has been increasingly applied to characterize tumor or organ tissues, or biofluids, for instance to follow-up metabolism during cancer progression or response to specific therapies.

SCOPE OF REVIEW

This review briefly introduces the different murine models used in breast cancer research and proceeds to present the metabolomic studies reported so far to describe the deviant metabolic behavior associated to breast cancer, in each type of model: xenografts (cell- or patient-derived), spontaneous (naturally-occurring or genetically engineered) and carcinogen-induced. The type of sample and strategies followed are identified, as well as the main findings from of study.

MAJOR CONCLUSIONS

Metabolomics has gradually become relevant in characterizing murine models of breast cancer, using either Nuclear Magnetic Resonance (NMR) or Mass Spectromety (MS). Both tissue and biofluids are matrixes of interest in this context, although in some type of models, reports have focused primarily on the former. The aims of tissue studies have comprised the search for mechanistic knowledge of carcinogenesis, metastasis development and response/resistance to therapies. Biofluid metabolomics has mainly aimed at finding non-invasive biomarkers for early breast cancer detection or prognosis determination.

GENERAL SIGNIFICANCE

Metabolomics provides exquisite detail on murine tumor and systemic metabolism of breast cancer. This knowledge paves the way for the discovery of new biomarkers, potentially translatable to in vivo non-invasive patient follow-up.

Metabolomics: a promising diagnostic and therapeutic implement for breast cancer

Breast cancer (BC) is the most commonly diagnosed cancer among women and the leading cause of cancer death. Despite the advent of numerous diagnosis and treatment methods in recent years, this heterogeneous disease still presents great challenges in early diagnosis, curative treatments and prognosis monitoring. Thus, finding promising early diagnostic biomarkers and therapeutic targets and approaches is meaningful. Metabolomics, which focuses on the analysis of metabolites that change during metabolism, can reveal even a subtle abnormal change in an individual. In recent decades, the exploration of cancer-related metabolomics has increased. Metabolites can be promising biomarkers for the screening, response evaluation and prognosis of BC. In this review, we summarized the workflow of metabolomics, described metabolite signatures based on molecular subtype as well as reclassification and then discussed the application of metabolomics in the early diagnosis, monitoring and prognosis of BC to offer new insights for clinicians in breast cancer diagnosis and treatment.

Early genistein exposure of California mice and effects on the gut microbiota-brain axis

Human offspring encounter high amounts of phytoestrogens, such as genistein (GEN), through maternal diet and soy-based formulas. Such chemicals can exert estrogenic activity and thereby disrupt neurobehavioral programming. Besides inducing direct host effects, GEN might cause gut dysbiosis and alter gut metabolites. To determine whether exposure to GEN affects these parameters, California mice (Peromyscus californicus) dams were placed 2 weeks prior to breeding and throughout gestation and lactation on a diet supplemented with GEN (250 mg/kg feed weight) or AIN93G phytoestrogen-free control diet (AIN). At weaning, offspring socio-communicative behaviors, gut microbiota and metabolite profiles were assayed. Exposure of offspring to GEN-induced sex-dependent changes in gut microbiota and metabolites. GEN exposed females were less likely to investigate a novel female mouse when tested in a three-chamber social test. When isolated, GEN males and females exhibited increased latency to elicit their first call, suggestive of reduced motivation to communicate with other individuals. Correlation analyses revealed interactions between GEN-induced microbiome, metabolome and socio-communicative behaviors. Comparison of GEN males with AIN males revealed the fraction of calls above 20 kHz was associated with daidzein, α-tocopherol, Flexispira spp. and Odoribacter spp. Results suggest early GEN exposure disrupts normal socio-communicative behaviors in California mice, which are otherwise evident in these social rodents. Such effects may be due to GEN disruptions on neural programming but might also be attributed to GEN-induced microbiota shifts and resultant changes in gut metabolites. Findings indicate cause for concern that perinatal exposure to GEN may detrimentally affect the offspring microbiome-gut-brain axis.

Metabolomics of neonatal blood spots reveal distinct phenotypes of pediatric acute lymphoblastic leukemia and potential effects of early-life nutrition

Early-life exposures are believed to influence the incidence of pediatric acute lymphoblastic leukemia (ALL). Archived neonatal blood spots (NBS), collected within the first days of life, offer a means to investigate small molecules that reflect early-life exposures. Using untargeted metabolomics, we compared abundances of small-molecule features in extracts of NBS punches from 332 children that later developed ALL and 324 healthy controls. Subjects were stratified by early (1-5 y) and late (6-14 y) diagnosis. Mutually-exclusive sets of metabolic features - representing putative lipids and fatty acids - were associated with ALL, including 9 and 19 metabolites in the early- and late-diagnosis groups, respectively. In the late-diagnosis group, a prominent cluster of features with apparent 18:2 fatty-acid chains suggested that newborn exposure to the essential nutrient, linoleic acid, increased ALL risk. Interestingly, abundances of these putative 18:2 lipids were greater in infants who were fed formula rather than breast milk (colostrum) and increased with the mother's pre-pregnancy body mass index. These results suggest possible etiologic roles of newborn nutrition in late-diagnosis ALL.

Current Status and Future Prospects of Clinically Exploiting Cancer-specific Metabolism-Why Is Tumor Metabolism Not More Extensively Translated into Clinical Targets and Biomarkers?

Tumor cells exhibit a specialized metabolism supporting their superior ability for rapid proliferation, migration, and apoptotic evasion. It is reasonable to assume that the specific metabolic needs of the tumor cells can offer an array of therapeutic windows as pharmacological disturbance may derail the biochemical mechanisms necessary for maintaining the tumor characteristics, while being less important for normally proliferating cells. In addition, the specialized metabolism may leave a unique metabolic signature which could be used clinically for diagnostic or prognostic purposes. Quantitative global metabolic profiling (metabolomics) has evolved over the last two decades. However, despite the technology’s present ability to measure 1000s of endogenous metabolites in various clinical or biological specimens, there are essentially no examples of metabolomics investigations being translated into actual utility in the cancer clinic. This review investigates the current efforts of using metabolomics as a tool for translation of tumor metabolism into the clinic and further seeks to outline paths for increasing the momentum of using tumor metabolism as a biomarker and drug target opportunity.