EFFECTS OF INFANT NUTRITION ON FECAL RESISTOME ESTABLISHMENT

项目摘要 我的研究兴趣包括新生儿肠道微生物组的发展，目前的重点是 社区编码的功能，如抗生素耐药性或代谢功能。我工作了， 2009年在Gautam Dantas博士的实验室;在这段时间里，我精通了各种各样的知识 微生物学和基因组学研究工作所需的台式技术，已经在 统计学和计算机编程，并获得了分析越来越大和复杂的经验， 宏基因组数据的集合。我与遗传学，微生物学， 胃肠病学、统计学和消化病学，发表了多篇论文。该提案还包括 生物信息学和计算生物学的教学培训，重点是提高我的技能， 在编程，统计学和系统生物学的知识，以及研究计划，将补充我的 正式的课程，提供充分的机会，让我应用这些技能。我将继续与我的 导师Gautam Dantas博士，人类肠道和土壤细菌的社区功能专家， 医学博士菲利普塔尔是一位医生兼科学家，他是儿科微生物组研究领域的领导者， 指导年轻科学家走向独立的记录。我的监督委员会包括巴拉克·科恩， 博士，计算和系统生物学专家William Shannon博士，生物统计学专家， F.塞申斯科尔，医学博士，在遗传学和转化研究的专家。对这些人的持续指导 具有不同专业领域的合作者将加强我的教学和实践培训， 我作为一名学术精神病学家的临床经验，将为我作为一个独立的职业生涯做好准备。 研究人类微生物组对新生儿健康影响的医生科学家。 本提案中描述的研究项目具有潜在的临床相关性，因为细菌耐药性 抗生素对人类健康的威胁迫在眉睫。人类肠道中的抗生素抗性基因 微生物群（粪便抗性组）是流行病学上重要的遗传库， 对人类病原体的抵抗力。了解粪便耐药基因携带的临床决定因素， 导致新的战略，以打击传播的耐药生物在人类社区。我们最近的工作 表明健康儿童的粪便耐药基因组比以前怀疑的要多样化得多， 表明粪便耐药基因组在婴儿早期建立，婴儿耐药基因组与他们的 母亲在出生后1-2个月内发育，与双胞胎兄弟姐妹相似。本提案的目的是 检验婴儿饮食显著影响粪便耐药性组和粪便微生物群落的假设 发展 我和我的导师丹塔斯博士和塔尔博士先前的工作表明，功能宏基因组 选择是广泛取样儿科粪便耐药体的有效手段。我们将使用高通量 功能宏基因组选择与下一代测序和计算管道相结合 我们实验室开发的（功能宏基因组选择的平行组装和注释，PARFuMS）， 研究母乳喂养和配方奶粉喂养的婴儿在出生后第一年的纵向粪便耐药性组发展 喂养（牛奶和大豆配方奶都代表），重点是与喂养相关的变化 过渡（例如从母乳到配方奶，开始固体食物）。本研究中使用的样本具有 已在知情同意书的情况下采集，用于IRB批准的单独研究，并储存在Dantas中 实验室对一小部分样品进行功能性宏基因组选择将用于鉴定抗性基因 在临床上是重要的，也是这个群体独有的。我们将使用表型相关数据， 功能宏基因组选择，以量化特异性抗性基因与遗传之间的相关性， 基序和抗性表型，这将增强现有的抗性基因数据库， 信息，并将提供一个框架，以确定最具潜在危险的抗性基因， 在统计学上将它们与不期望的抗性表型联系起来。更大样本的鸟枪测序 这套系统将允许高分辨率，定量数据的微生物群的系统发育组成和预测 微生物编码功能。我们将使用这一丰富的数据集将临床变量与 耐药基因组，以及检查耐药基因组发展的系统发育变化的影响。这 综合研究战略是新颖的，因为据我们所知，这将是第一次纵向研究， 早期婴儿营养对粪便抵抗组和微生物组建立的影响，并将整合 功能宏基因组技术和全基因组鸟枪测序与新的计算 为纵向耐药基因组研究明确开发的策略。开发的计算策略， 本研究将为未来的社区范围内的其他纵向调查提供理论框架 微生物功能在这个建议的工作将结合我的临床经验，我建议的教学 生物信息学方面的培训，以及我在宏基因组学方面的指导经验，为我的职业生涯做好了准备， 一个独立的调查员，对人类的发展特性进行基于假设的研究， 微生物组并将这些知识转化为影响儿童健康的结果。

Project Summary My research interests include the development of the neonatal enteric microbiome, with a current focus on community-encoded functions such as antibiotic resistance or metabolic functions. I have worked since 2009 in the laboratory of Gautam Dantas, Ph.D.; during this time I have become proficient in a variety of benchtop techniques necessary for work in microbiology and genomics research, have taken classes in statistics and computer programming, and gained experience analyzing increasingly large and complex collections of metagenomic data. I have collaborated with colleagues with expertise in genetics, microbiology, gastroenterology, statistics, and neonatology, resulting in several publications. This proposal includes further didactic training in bioinformatics and computational biology, with a focus on enhancing my skills and knowledge in programming, statistics, and systems biology, as well as a research plan that will complement my formal coursework by providing ample opportunity for me to apply these skills. I will continue to work with my mentors Gautam Dantas, Ph.D., an expert in community-wide functions of human gut and soil bacteria and Phillip Tarr, MD, an physician-scientist who is a leader in the field of pediatric microbiome research, and has a track record of mentoring junior scientists to independence. My oversight committee includes Barak Cohen, Ph.D., an expert in computational and systems biology, William Shannon, Ph.D., an expert in biostatistics, and F. Sessions Cole, MD, an expert in genetics and translational research. The ongoing mentorship of these collaborators with diverse areas of expertise will enhance my didactic and hands-on training and, combined with my clinical experience as an academic neonatologist, will prepare me for an independent career as a physician scientist investigating the impact of the human microbiome on neonatal health. The research project described in this proposal is potentially clinically relevant, as bacterial resistance to all antibiotics urgently threatens human health. The antibiotic resistance genes harbored by the human gut microbiota (fecal resistome) are an epidemiologically important genetic reservoir that can potentially transfer resistance to human pathogens. Understanding the clinical determinants of fecal resistance gene carriage may lead to novel strategies to combat the spread of resistant organisms in human communities. Our recent work has indicated that the fecal resistome of healthy children is far more diverse than previously suspected, and suggests that the fecal resistome is established in early infancy, with infant resistomes being distinct from their mothers' in by 1-2 months of life and developing similarly to their twin siblings'. The goal of this proposal is to test the hypothesis that infant diet significantly influences fecal resistome and fecal microbial community development. Prior work by me and my mentors Dr. Dantas and Dr. Tarr has shown that functional metagenomic selections are an efficient means of broadly sampling pediatric fecal resistomes. We will use high-throughput functional metagenomic selections coupled with next-generation sequencing and a computational pipeline developed in our lab (Parallel Assembly and Annotation of Functional Metagenomic Selections, PARFuMS) to study longitudinal fecal resistome development in the first year of life in infants that are breastfed and formula fed (cow's milk and soy formula both represented) with an emphasis on changes associated with feeding transitions (e.g. from breastmilk to formula, initiating solid food). The samples to be used in this study have already been collected with informed consent for a separate IRB-approved study, and are stored in the Dantas lab. Functional metagenomic selections on a small subset of samples will be used to identify resistance genes that are clinically important and unique to this cohort. We will use the phenotype-linked data generated by functional metagenomic selections to quantify the correlation between specific resistance genes and genetic motifs and resistance phenotypes, which will enhance existing resistance gene databases with functional information and will provide a framework for identifying the most potentially dangerous resistance genes by statistically linking them with undesirable resistance phenotypes. Shotgun sequencing of a much larger sample set will allow high-resolution, quantitative data on the phylogenetic composition of the microbiota and predicted microbiome-encoded functions. We will use this rich dataset to correlate clinical variables with changes in the resistome, as well as to examine the effects of phylogenetic shifts on resistome development. This comprehensive research strategy is novel because it will be, to our knowledge, the first longitudinal study of the effects of early infant nutrition on fecal resistome and microbiome establishment, and will integrate functional metagenomic techniques and whole-genome shotgun sequencing with novel computational strategies developed expressly for longitudinal resistome study. The computational strategies developed for this study will provide a theoretical framework for future longitudinal investigations of other community-wide microbial functions. The work in this proposal will integrate with my clinical experience, my proposed didactic training in bioinformatics, and my mentored experience with metagenomics to prepare me for a career as an independent investigator conducting hypothesis-based research on thedevelopmental properties of the human microbiome and translating this knowledge to impact child health outcomes.