Blocking CMV transmission through the human milk metabolome and microbiome

阻断 CMV 通过母乳代谢组和微生物组传播

• 批准号: 10381682
• 负责人: Tatiana T. Marquez-Lago
• 金额: $ 62.76万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10381682
• 关键词: Age-Months; Antibodies; Antiviral Agents; Artificial Intelligence; Bile Acids; Biomedical Engineering; Body Fluids; Caring; Cells; Child; Chromatography; Chronic; Clinical; Coculture Techniques; Communities; Cytomegalovirus; Data; Disease; Ecology; Epithelial Cells; Etiology; Exposure to; Fatty Acids; Fermentation; Foundations; Gender; Goals; Human; Human Milk; Immune response; Immune system; Immunocompromised Host; Individual; Infant; Infant Development; Infection prevention; Interdisciplinary Study; Intervention; Investigation; Lactation; Life; Machine Learning; Maternal Age; Measures; Medium chain fatty acid; Metabolism; Metagenomics; Modeling; Molecular; Mothers; Newborn Infant; Oligosaccharides; Passive Immunization; Pattern; Population; Prevalence; Public Health; Reproducibility; Research; Resources; Risk; Role; Saliva; Sampling; Shotguns; Site; Supplementation; Testing; Time; Tissues; Translating; Translations; Urine; Vaccines; Viral Antibodies; Viral Load result; Virus Diseases; Virus Shedding; Woman; base; blocking factor; blood group; cofactor; commensal microbes; comparative; congenital infection; density; disability; gut microbiota; human microbiota; improved; insight; mathematical model; metabolome; metabolomics; metatranscriptomics; microbial; microbiome; microbiota; microbiota metabolites; milk microbiome; multiple omics; non-genetic; offspring; opportunistic pathogen; pathogenic virus; personalized intervention; predictive modeling; prevent; programs; rational design; receptor; seropositive; tandem mass spectrometry; tool; transmission process; viral transmission

Despite decades-long research and multiple trials, there is no licensed vaccine against Cytomegalovirus (CMV) yet, urging efforts to better understand its transmission dynamics. CMV is a frequent cause of tissue-invasive disease in infants and immunocompromised individuals, and transmission happens easily and through contact with various body fluids. Among transmission modes, CMV transmission via human milk (HM) is recognized to have the largest global impact on population prevalence. Factors determining CMV transmission remain largely unknown, including CMV interactions with HM microbiota and metabolites. In general, commensal microbiota can greatly impact sensitivity to viral infections while, metabolites, such as human milk oligosaccharides (HMOs), not only feed human microbiota but can also act as soluble decoy receptors, blocking the attachment of viral pathogens to epithelial cells. Additionally, short chain and medium chain fatty acids are products of microbial fermentation, known to influence immune responses, and microbiota can also produce antivirals through secondary metabolism. Therefore, the objective of this proposal is to better define CMV transmission dynamics, considering different factors and timescales, and to systematically and quantitatively study the role and interactions of the HM metabolome and microbiome influencing CMV transmission from women to their infants. Our preliminary data readily shows that CMV seronegative and seropositive mothers have distinct HM microbiome and metabolome ecologies. In particular, we found clear differences distinguishing seropositive mothers that are non-shedding, shedding but not transmitting, and shedding and transmitting CMV. These results led to the central hypothesis, which is that certain combinations of HM microbiota and metabolites prevent CMV transmissions, and that these combinations vary among individual dyads, but follow traceable and reproducible patterns. We propose to test the central hypothesis by pursuing the following three specific aims: (1) Determine CMV transmission dynamics with high sample density and HM microbiome ecologies underlying CMV transmission versus non-transmission; (2) Identify and validate key metabolites involved in CMV transmission and non-transmission; and (3) Define causality and identify molecular mechanisms of CMV transmission inhibition assisted by mathematical modeling and artificial intelligence. Collectively, our proposed research will broadly impact the field by elucidating CMV-host interactions and CMV transmission dynamics in various time scales, validating factors blocking CMV transmission, and providing models and tools to help advance the arrival of clinical resource. These studies also have the potential to lay the groundwork for, and translate into, rational design of personalized HM and microbiome-metabolome interventions without replacing HM.

尽管经过数十年的研究和多次试验，目前尚无针对巨细胞病毒（CMV）的许可疫苗。