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: 10211940
• 负责人: Tatiana T. Marquez-Lago
• 金额: $ 64.85万
• 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/10211940
• 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; design; 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; 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.

尽管进行了数十年的研究和多次试验，但目前还没有针对巨细胞病毒(CMV)的特许疫苗 然而，敦促努力更好地了解其传播动力学。巨细胞病毒是组织侵袭性疾病的常见原因。 疾病发生在婴儿和免疫功能低下的人身上，很容易通过接触传播 有各种各样的体液。在传播方式中，通过母乳(HM)传播CMV被认为是 对人口流行有最大的全球影响。决定CMV传播的因素在很大程度上仍然存在 未知，包括CMV与HM微生物区系和代谢物的相互作用。一般而言，共生微生物区系 会极大地影响对病毒感染的敏感性，而代谢物，如人乳低聚糖(HMOS)， 不仅可以喂养人类微生物区系，而且还可以作为可溶性诱饵受体，阻止病毒的附着 病原体侵袭上皮细胞。此外，短链和中链脂肪酸是微生物的产物 已知会影响免疫反应的发酵和微生物区系也可以通过 次生代谢。因此，该提案的目的是更好地定义CMV传播动力学， 考虑不同的因素和时间尺度，系统地、定量地研究 影响巨细胞病毒母婴传播的HM代谢组和微生物组的相互作用。 我们的初步数据很容易地表明CMV血清阴性和血清阳性母亲有不同的HM 微生物组和代谢组生态学。特别是，我们发现了明显的差异，区分血清阳性 不脱落、脱落但不传播、脱落并传播CMV的母亲。这些结果 导致了中心假设，即HM微生物区系和代谢物的某些组合可以预防CMV 这些组合因个体的不同而有所不同，但遵循可追踪和可复制的原则。 模式。我们建议通过追求以下三个具体目标来检验中心假设：(1)确定 高样本密度的CMV传播动力学和CMV背后的HM微生物群生态 传播与非传播；(2)识别和验证CMV传播中涉及的关键代谢物 以及(3)确定CMV传播的因果关系和分子机制 在数学建模和人工智能的辅助下抑制。总的来说，我们提议的研究将 通过阐明CMV与宿主的相互作用和不同时间的CMV传播动态来广泛影响该领域 规模，验证阻止CMV传播的因素，并提供有助于提前到达的模型和工具 临床资源。这些研究也有可能为理性奠定基础，并转化为理性 不取代HM的个性化HM和微生物-代谢组干预的设计。