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: 10613510
• 负责人: Tatiana T. Marquez-Lago
• 金额: $ 57.94万
• 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/10613510
• 关键词: Age Months; Antibodies; Antiviral Agents; Artificial Intelligence; Bile Acids; Biomedical Engineering; Blood typing procedure; Body Fluids; Caring; Cells; Child; Chromatography; Chronic; Clinical; Coculture Techniques; Communities; Cytomegalovirus; Data; Dimensions; Disease; Ecology; Epithelial Cells; Etiology; Exposure to; Fatty Acids; Fermentation; Foundations; Gender; Goals; Human; Human Microbiome; Human Milk; Immune response; Immune system; Immunocompromised Host; Individual; Infant; Infant Development; Infection prevention; Interdisciplinary Study; Intervention; Investigation; Lactation; Licensing; Life; Maps; 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; blocking factor; blood group; cofactor; commensal microbes; comparative; congenital infection; density; disability; gut microbiota; human microbiota; improved; insight; machine learning prediction; mathematical model; metabolome; metabolomics; metatranscriptomics; microbial; microbial products; microbiome; microbiota; milk microbiome; multiple omics; non-genetic; offspring; opportunistic pathogen; pathogenic virus; personalized intervention; predictive modeling; prevent; programs; rational design; receptor; risk mitigation; seropositive; tandem mass spectrometry; tool; translational framework; 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.

尽管进行了长达数十年的研究和多次试验，但仍没有针对巨细胞病毒（CMV）的许可疫苗 然而，敦促努力更好地了解其传播动态。CMV是组织侵袭性的常见原因， 婴儿和免疫功能低下的人容易患病，并且很容易通过接触传播 各种体液混合在一起在传播模式中，通过母乳（HM）的CMV传播被认为是 对全球人口流行率的影响最大。决定巨细胞病毒传播的因素仍然主要是 未知，包括CMV与HM微生物群和代谢物的相互作用。总的来说， 可以极大地影响对病毒感染的敏感性，而代谢物，如母乳低聚糖（HMO）， 不仅喂养人类微生物群，而且还可以作为可溶性诱饵受体，阻止病毒的附着， 病原体到上皮细胞。此外，短链和中链脂肪酸是微生物代谢的产物。 发酵，已知会影响免疫反应，微生物群也可以通过 次生代谢因此，本提案的目的是更好地定义CMV传播动态， 考虑到不同的因素和时间尺度，并系统和定量研究的作用， HM代谢组和微生物组的相互作用影响CMV从女性传播到婴儿。 我们的初步数据显示，CMV血清阴性和血清阳性的母亲有不同的HM 微生物组和代谢组生态学。特别是，我们发现血清阳性 不脱落、脱落但不传播以及脱落并传播CMV的母亲。这些结果 导致了中心假设，即HM微生物群和代谢物的某些组合可以预防CMV 传输，这些组合在个别的二对体之间变化，但遵循可追踪和可再现的 模式.我们建议通过追求以下三个具体目标来测试中心假设：（1）确定 高样本密度的CMV传播动力学和CMV相关的HM微生物组生态学 传播与非传播;（2）识别和验证参与CMV传播的关键代谢物 和非传播;（3）定义因果关系并确定CMV传播的分子机制 数学建模和人工智能辅助抑制。总的来说，我们提出的研究将 通过阐明CMV-宿主相互作用和CMV在不同时间的传播动力学，广泛影响该领域 规模，验证阻碍CMV传播的因素，并提供模型和工具，以帮助提前到达 临床资源。这些研究也有可能为合理的 设计个性化的HM和微生物组-代谢组干预措施，而无需替代HM。