EAGER: Computational Rapid Identification and Putative Characterization of Understudied Microbial Community Gene Products

EAGER:正在研究的微生物群落基因产物的计算快速识别和推定表征

基本信息

  • 批准号:
    1453942
  • 负责人:
  • 金额:
    $ 25.64万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2014
  • 资助国家:
    美国
  • 起止时间:
    2014-09-15 至 2016-08-31
  • 项目状态:
    已结题

项目摘要

Metagenomic sequencing projects generate thousands to millions of uncharacterized microbial genes that are almost completely ignored in all fields of research. Addressing this problem will fundamentally transform how scientists exploring microbial communities or new microbial isolates will interpret their genetic material and the function of that material. This potentially high payoff is balanced by a high risk in that microbial community information has not previously been mined in order to address this issue. In the absence of more extensive preliminary data, or one or more years of prior validation, this necessitates the application of previously untried approaches to prioritize and characterize the targeted microbial genes. Lastly, while the downstream methods to be applied here for gene function prediction will be adapted from eukaryotic model systems, this will require both application in a completely new area (culture-independent prokaryotes) and the intersection of multiple disciplines (computational gene function prediction, data integration, and network mining with microbial community studies and microbiology). Current technologies generate novel nucleotide sequence information at a rate that greatly outpaces our capability to functionally characterize those sequences. From one third to more typically over three quarters of proteins in newly-sequenced prokaryotic genomes and communities cannot be functionally characterized. The increase in metagenomic sequencing results in millions of recently identified, completely uncharacterized microbial genes representing a significant need for efficient computational gene prioritization and characterization systems. This project will first leverage metagenomic sequences in a novel effort to prioritize the uncharacterized genes for further study in order to break from current approaches targeting genes from well-studied gene families. Second, integrative, network-based approaches will be used to accelerate and automate the assignment of putative function for subsequent validation in high-priority gene targets. Both new approaches will be implemented as freely available, documented software and distributed to the broader research community along with pilot datasets. A postdoctoral fellow, a graduate student and undergraduate students will receive cutting edge training in integrative experimental and computational approaches during the two-year project.
宏基因组测序项目产生了成千上万个未被表征的微生物基因,这些基因在所有研究领域几乎完全被忽视。解决这个问题将从根本上改变科学家探索微生物群落或新的微生物分离物将如何解释其遗传物质和该物质的功能。这种潜在的高回报与高风险相平衡,因为微生物群落信息以前没有被挖掘出来以解决这个问题。在缺乏更广泛的初步数据,或一年或多年的事先验证的情况下,这就需要应用以前未尝试过的方法来确定目标微生物基因的优先级和特征。最后,虽然这里应用于基因功能预测的下游方法将改编自真核模型系统,但这将需要在一个全新的领域(不依赖培养的原核生物)和多学科的交叉(计算基因功能预测、数据集成和微生物群落研究和微生物学的网络挖掘)中应用。目前的技术产生新的核苷酸序列信息的速度大大超过了我们对这些序列进行功能表征的能力。在新测序的原核生物基因组和群落中,有三分之一到四分之三以上的蛋白质不能被功能表征。宏基因组测序的增加导致数百万新近发现的完全未表征的微生物基因,这代表了对高效计算基因优先级和表征系统的重大需求。该项目将首先利用宏基因组序列,以一种新颖的方式优先考虑未表征的基因进行进一步研究,以打破目前针对已充分研究的基因家族的基因的方法。其次,综合的、基于网络的方法将用于加速和自动化假设功能的分配,以便在高优先级基因靶标中进行后续验证。这两种新方法都将作为免费提供的文档化软件实施,并与试点数据集一起分发给更广泛的研究社区。在为期两年的项目中,一名博士后、一名研究生和一名本科生将接受综合实验和计算方法的前沿培训。

项目成果

期刊论文数量(0)
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专利数量(0)

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Curtis Huttenhower其他文献

Response of the gut microbiome and metabolome to dietary fiber in healthy dogs
健康犬肠道微生物组和代谢组对膳食纤维的反应
  • DOI:
    10.1128/msystems.00452-24
  • 发表时间:
    2024-12-16
  • 期刊:
  • 影响因子:
    4.600
  • 作者:
    Amrisha Bhosle;Matthew I. Jackson;Aaron M. Walsh;Eric A. Franzosa;Dayakar V. Badri;Curtis Huttenhower
  • 通讯作者:
    Curtis Huttenhower
Sa594 THE GUT MICROBIOME MODULATES THE BENEFICIAL EFFECTS OF VITAMIN D ON CARDIOVASCULAR RISK
  • DOI:
    10.1016/s0016-5085(21)02050-3
  • 发表时间:
    2021-05-01
  • 期刊:
  • 影响因子:
  • 作者:
    Wenjie Ma;Mingyang Song;Long H. Nguyen;Raaj S. Mehta;Dong Wang;Jacques Izard;Wendy Garrett;Edward Giovannucci;Eric B. Rimm;Curtis Huttenhower;Andrew Chan
  • 通讯作者:
    Andrew Chan
1252 AN EMPIRICAL DIETARY PATTERN ASSOCIATED WITH GUT MICROBIAL FEATURES IN RELATION TO COLORECTAL CANCER RISK
  • DOI:
    10.1016/s0016-5085(23)01587-1
  • 发表时间:
    2023-05-01
  • 期刊:
  • 影响因子:
  • 作者:
    Chun-Han Lo;Raaj Mehta;Long H. Nguyen;Yiqing Wang;Wenjie Ma;Kai Wang;Shuji Ogino;Jeffrey Meyerhardt;Kimmie Ng;Jacques Izard;Eric B. Rimm;Wendy S. Garrett;Curtis Huttenhower;Edward Giovannucci;Andrew T. Chan;Mingyang Song
  • 通讯作者:
    Mingyang Song
P03-014-23 Differences in Gut Microbiome Composition by Bowel Movement Frequency and Proton Pump Inhibitor Use: The Boston Puerto Rican Health Study
  • DOI:
    10.1016/j.cdnut.2023.100525
  • 发表时间:
    2023-07-01
  • 期刊:
  • 影响因子:
  • 作者:
    Deepika Dinesh;Jong Soo Lee;Scott Gordon;Kelsey Mangano;Tammy Scott;Curtis Huttenhower;Katherine Tucker;Natalia Palacios
  • 通讯作者:
    Natalia Palacios
174: DIET AND GUT MICROBIAL INTERACTIONS IN IRRITABLE BOWEL SYNDROME SUBTYPES
  • DOI:
    10.1016/s0016-5085(22)60085-4
  • 发表时间:
    2022-05-01
  • 期刊:
  • 影响因子:
  • 作者:
    Yiqing Wang;Wenjie Ma;Raaj Mehta;Long H. Nguyen;Mingyang Song;David A. Drew;Francesco Asnicar;Curtis Huttenhower;Nicola Segata;Jonathan Wolf;Tim Spector;Sarah Berry;Kyle Staller;Andrew Chan
  • 通讯作者:
    Andrew Chan

Curtis Huttenhower的其他文献

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{{ truncateString('Curtis Huttenhower', 18)}}的其他基金

CAREER: Scalable Computational Models for Multicellular Systems Biology
职业:多细胞系统生物学的可扩展计算模型
  • 批准号:
    1053486
  • 财政年份:
    2011
  • 资助金额:
    $ 25.64万
  • 项目类别:
    Continuing Grant

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    60601030
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    17.0 万元
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