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.

尽管进行了数十年的研究和多次试验，但仍未针对巨细胞病毒（CMV）进行许可疫苗 但是，敦促努力更好地了解其传输动态。 CMV是组织侵入性的经常原因 婴儿和免疫功能低下的个体的疾病，并且传播很容易发生并通过接触发生 具有各种体液。在传输模式中，通过人牛奶（HM）的CMV传输被认为是 对全球人口流行具有最大的影响。确定CMV传输的因素大大保持 未知，包括与HM微生物群和代谢产物的CMV相互作用。通常，共生微生物群 可以极大地影响对病毒感染的敏感性，而代谢产物，例如人乳寡糖（HMOS）， 不仅喂养人类微生物群，而且还可以充当可溶性诱饵受体，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的产物 发酵，已知会影响免疫反应，微生物群也可以通过 次要代谢。因此，该建议的目的是更好地定义CMV传输动力学， 考虑不同的因素和时间尺度，并系统地和定量研究角色和 HM代谢组和微生物组的相互作用影响了从女性到婴儿的CMV传播。 我们的初步数据很容易表明CMV血清阴性和血清阳性母亲具有独特的HM 微生物组和代谢组生态学。特别是，我们发现区分血清阳性的明显差异 非裂缝，脱落但不传播以及脱落和传输CMV的母亲。这些结果 导致中央假设，即HM微生物群和代谢产物的某些组合阻止CMV 传输，这些组合在单个二元组之间有所不同，但遵循可追溯和可重复的 模式。我们建议通过追求以下三个特定目的来检验中心假设：（1）确定 CMV传输动力学具有较高的样品密度和HM微生物组生态学 传输与非传输； （2）识别和验证与CMV传输有关的关键代谢产物 和非传输； （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的抑制作用。总的来说，我们拟议的研究将 通过阐明CMV-host的相互作用和CMV传输动态来广泛影响该领域 秤，验证因素阻止CMV传输，并提供模型和工具以帮助推进到达 临床资源。这些研究还有可能为理性奠定基础并转化为理性 个性化HM和微生物组 - 代谢组干预措施的设计，而无需更换HM。