Abstract Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject’s phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs. 

/pdf/small-molecule-metabolites-discovery-of-biomarkers-and-3d30vx3k.pdf

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Abstract Preterm birth (PTB) is the leading cause of neonatal morbidity and mortality. The vaginal microbiome has been associated with PTB, yet the mechanisms underlying this association are not fully understood. Understanding microbial genetic adaptations to selective pressures, especially those related to the host, may yield insights into these associations. Here, we analyze metagenomic data from 705 vaginal samples collected during pregnancy from 40 women who delivered preterm spontaneously and 135 term controls from the Multi-Omic Microbiome Study-Pregnancy Initiative. We find that the vaginal microbiome of pregnancies that ended preterm exhibited unique genetic profiles. It was more genetically diverse at the species level, a result which we validate in an additional cohort, and harbored a higher richness and diversity of antimicrobial resistance genes, likely promoted by transduction. Interestingly, we find that Gardnerella species drove this higher genetic diversity, particularly during the first half of the pregnancy. We further present evidence that Gardnerella spp. underwent more frequent recombination and stronger purifying selection in genes involved in lipid metabolism. Overall, our population genetics analyses reveal associations between the vaginal microbiome and PTB and suggest that evolutionary processes acting on vaginal microbes may play a role in adverse pregnancy outcomes such as PTB. 

pdf/microdiversity-of-the-vaginal-microbiome-is-associated-with-1hhcr2xhw0.pdf

Microdiversity of the vaginal microbiome is associated with preterm birth

An interdisciplinary fetal-neonatal neurology (FNN) program over the first 1,000 days teaches perspectives of the neural exposome that are applicable across the life span. This curriculum strengthens neonatal neurocritical care, pediatric, and adult neurology training objectives. Teaching at maternal-pediatric hospital centers optimally merges reproductive, pregnancy, and pediatric approaches to healthcare. Phenotype–genotype expressions of health or disease pathways represent a dynamic neural exposome over developmental time. The science of uncertainty applied to FNN training re-enforces the importance of shared clinical decisions that minimize bias and reduce cognitive errors. Trainees select mentoring committee participants that will maximize their learning experiences. Standardized questions and oral presentations monitor educational progress. Master or doctoral defense preparation and competitive research funding can be goals for specific individuals. FNN principles applied to practice offer an understanding of gene–environment interactions that recognizes the effects of reproductive health on the maternal-placental-fetal triad, neonate, child, and adult. Pre-conception and prenatal adversities potentially diminish life-course brain health. Endogenous and exogenous toxic stressor interplay (TSI) alters the neural exposome through maladaptive developmental neuroplasticity. Developmental disorders and epilepsy are primarily expressed during the first 1,000 days. Communicable and noncommunicable illnesses continue to interact with the neural exposome to express diverse neurologic disorders across the lifespan, particularly during the critical/sensitive time periods of adolescence and reproductive senescence. Anomalous or destructive fetal neuropathologic lesions change clinical expressions across this developmental-aging continuum. An integrated understanding of reproductive, pregnancy, placental, neonatal, childhood, and adult exposome effects offers a life-course perspective of the neural exposome. Exosome research promises improved disease monitoring and drug delivery starting during pregnancy. Developmental origins of health and disease principles applied to FNN practice anticipate neurologic diagnoses with interventions that can benefit successive generations. Addressing health care disparities in the Global South and high-income country medical deserts require constructive dialogue among stakeholders to achieve medical equity. Population health policies require a brain capital strategy that reduces the global burden of neurologic diseases by applying FNN principles and practice. This integrative neurologic care approach will prolong survival with an improved quality of life for persons across the lifespan confronted with neurological disorders.

Interdisciplinary fetal-neonatal neurology training applies neural exposome perspectives to neurology principles and practice

Lactobacillus species contribute to cervicovaginal health by their production of lactic acid and other antimicrobial compounds. Yet, much is still unknown regarding the metabolic potential of lesser-studied but common vaginal lactobacilli. ABSTRACT In reproductive-age women, the vaginal microbiome is typically dominated by one or a few Lactobacillus species, including Lactobacillus crispatus, Lactobacillus iners, Lactobacillus paragasseri, Lactobacillus mulieris, and Lactobaccillus crispatus, has been associated with optimal cervicovaginal health; however, much is still unknown about how other lactobacilli metabolically contribute to cervicovaginal health. We hypothesized that metabolites of each Lactobacillus species differ and uniquely contribute to health and homeostasis. To address this hypothesis, we utilized a human three-dimensional (3D) cervical epithelial cell model in conjunction with genomics analyses and untargeted metabolomics to determine the metabolic contributions of less-studied vaginal lactobacilli—L. iners, L. paragasseri, and L. mulieris. Our study validated that vaginal lactobacilli exhibit a close phylogenetic relationship. Genomic findings from publicly available strains and those used in our study indicated that L. iners is metabolically distinct from other species of lactobacilli, likely due to a reduced genome size. Lactobacilli and mock controls were distinguishable based on global metabolic profiles. We identified 95 significantly altered metabolites (P < 0.05) between individual lactobacilli and mock controls. Metabolites related to amino acid metabolism were shared among the lactobacilli. N-Acetylated amino acids with potential antimicrobial properties were significantly elevated in a species-specific manner. L. paragasseri and L. iners shared aromatic, but not carbohydrate-derived, lactic acid metabolites with potential antimicrobial properties that may contribute to homeostasis of the cervicovaginal environment. Additionally, L. iners uniquely altered lipid metabolism, which may be a sign of adaptation to the cervicovaginal niche. Overall, these findings further elucidate the metabolic contributions of three key vaginal Lactobacillus species in gynecological health. IMPORTANCE Lactobacillus species contribute to cervicovaginal health by their production of lactic acid and other antimicrobial compounds. Yet, much is still unknown regarding the metabolic potential of lesser-studied but common vaginal lactobacilli. Here, we used untargeted metabolomics coupled with our 3D cervical epithelial cell model to identify metabolic differences among vaginal Lactobacillus species (Lactobacillus iners, Lactobacillus paragasseri, and Lactobacillus mulieris) and how those differences related to maintaining homeostasis of the cervical epithelium. Human 3D cell models are essential tools for studying host-bacteria interactions and reducing confounding factors inherent in clinical studies. Therefore, these unique models allowed us to decipher the putative lactobacilli mechanisms that contribute to their roles in health or disease. Metabolic analyses revealed distinct profiles of each Lactobacillus species but also shared metabolic contributions associated with antimicrobial activity: amino acid metabolism, N-acetylated amino acids, and aromatic lactic acids. These patterns provided validation of metabolites associated with health in clinical studies and provided novel targets, including immunomodulatory and antimicrobial metabolites, for postbiotic therapies.

Commensal Lactobacilli Metabolically Contribute to Cervical Epithelial Homeostasis in a Species-Specific Manner

Microbes are commonly sensitive to shifts in the physiological and pathological state of their hosts, including mothers and babies. From this perspective, the microbiome may be a good indicator for diseases during pregnancy and has the potential to be used for perinatal health monitoring. This is embodied in the application of microbiome from multi body sites for auxiliary diagnosis, early prediction, prolonged monitoring, and retrospective diagnosis of pregnancy and infant complications, as well as nutrition management and health products developments of mothers and babies. Here we summarized the progress in these areas and explained that the microbiome of different body sites is sensitive to different diseases and their microbial biomarkers may overlap between each other, thus we need to make a diagnosis prudently for those diseases. Based on the microbiome variances and additional anthropometric and physical data, individualized responses of mothers and neonates to meals and probiotics/prebiotics were predictable, which is of importance for precise nutrition and probiotics/prebiotics managements and developments. Although a great deal of encouraging performance was manifested in previous studies, the efficacy could be further improved by combining multi-aspect data such as multi-omics and time series analysis in the future. This review reconceptualizes maternal and infant health from a microbiome perspective, and the knowledge in it may inspire the development of new options for the prevention and treatment of adverse pregnancy outcomes and bring a leap forward in perinatal health care.

/pdf/maternal-and-infant-microbiome-next-generation-indicators-305f6fin.pdf

Maternal and infant microbiome: next-generation indicators and targets for inter-generational health and nutrition care.

Spontaneous preterm birth (sPTB) is a leading cause of maternal and neonatal morbidity and mortality, yet its prevention and early risk stratification are limited. Previous investigations have suggested that vaginal microbes and metabolites may be implicated in sPTB. Here we performed untargeted metabolomics on 232 second-trimester vaginal samples, 80 from pregnancies ending preterm. We find multiple associations between vaginal metabolites and subsequent preterm birth, and propose that several of these metabolites, including diethanolamine and ethyl glucoside, are exogenous. We observe associations between the metabolome and microbiome profiles previously obtained using 16S ribosomal RNA amplicon sequencing, including correlations between bacteria considered suboptimal, such as Gardnerella vaginalis, and metabolites enriched in term pregnancies, such as tyramine. We investigate these associations using metabolic models. We use machine learning models to predict sPTB risk from metabolite levels, weeks to months before birth, with good accuracy (area under receiver operating characteristic curve of 0.78). These models, which we validate using two external cohorts, are more accurate than microbiome-based and maternal covariates-based models (area under receiver operating characteristic curve of 0.55-0.59). Our results demonstrate the potential of vaginal metabolites as early biomarkers of sPTB and highlight exogenous exposures as potential risk factors for prematurity. 

/pdf/preterm-birth-is-associated-with-xenobiotics-and-predicted-fg791h43.pdf

Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Steve Waugh

Author Tools

Chat about Author

Papers

Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome