RAPID: Improving QIIME 2 and UniFrac for Viruses to Respond to COVID-19

RAPID：改进 QIIME 2 和 UniFrac，使病毒能够响应 COVID-19

• 批准号: 2038509
• 负责人: Rob Knight
• 金额: $ 20万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-15 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2038509&HistoricalAwards=false
• 关键词: RAPID; Improving; QIIME; UniFrac; Viruses

The current COVID-19 pandemic prompts an urgent response including improved bioinformatics tools to help the community analyze relevant datasets from infected patients and their environments. This project will update the popular QIIME pipeline for microbiome analysis, which is very widely used by people studying bacteria and archaea in the microbiome, optimizing it for researchers studying viruses. This will bring features such as data provenance tracking and reproducibility of analysis workflows to the viral research community. Such features enhance the reliability of bioinformatics work in a rapidly paced of research environment such as emergency response to a pandemic, where processing errors are more likely. The intellectual merit of this work will be to move studies of viral communities from a nonphylogenetic to a phylogenetic basis, accelerate time-to-result, and to make QIIME 2 far more useful to the increasing number of researchers moving from bacterial community analysis to viral community analysis in response to the COVID-19 pandemic. Specific enhancements to be implemented are to build a reference database of viral sequences from diverse genome, metagenome, and metatranscriptome sources; to enhance storage and compute to resolve limitations posed by large-scale datasets generated for SARS-CoV-2; to extend computational pipelines to accommodate the recombination and lack of recognizable common phylogenetic tree roots characteristic of viruses; and to support genome assembly from reads recruiting to viral databases. Results will be disseminated as new QIIME 2 plugins, for broad distribution to the community, including the development of new educational materials and new workshop modules.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

当前的COVID-19大流行促使我们采取紧急应对措施，包括改进生物信息学工具，以帮助社区分析受感染患者及其环境的相关数据集。该项目将更新用于微生物组分析的流行QIIME管道，该管道被研究微生物组中的细菌和古菌的人们广泛使用，并为研究病毒的研究人员进行优化。这将为病毒研究社区带来数据来源跟踪和分析工作流程的可重复性等功能。这些功能提高了生物信息学工作在快速节奏的研究环境中的可靠性，例如对大流行病的紧急响应，其中处理错误更有可能。这项工作的智力价值将是将病毒群落的研究从非系统发育转移到系统发育的基础上，加快获得结果的时间，并使QIIME 2对越来越多的研究人员更有用，这些研究人员从细菌群落分析转向病毒群落分析，以应对COVID-19大流行。具体的增强措施包括：建立一个来自不同基因组、宏基因组和元转录组来源的病毒序列参考数据库;增强存储和计算能力，以解决为SARS-CoV-2生成的大规模数据集带来的局限性;扩展计算管道，以适应病毒的重组和缺乏可识别的共同系统发生树根特征;并支持从读取募集到病毒数据库的基因组组装。结果将作为新的QIIME 2插件广泛传播给社区，包括开发新的教育材料和新的研讨会模块。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

OGUs enable effective, phylogeny-aware analysis of even shallow metagenome community structures

• DOI: 10.1101/2021.04.04.438427
• 发表时间: 2021-04
• 期刊: bioRxiv
• 作者: Qiyun Zhu;Shi Huang;Antonio Gonzalez;Imran McGrath;Daniel McDonald;N. Haiminen;George Armstrong;Y. Vázquez-Baeza;Julian Yu;Justin Kuczynski;G. D. Sepich-Poore;Austin D. Swafford;Promi Das;Justin P. Shaffer;F. Lejzerowicz;P. Belda-Ferre;A. Havulinna;G. Méric;T. Niiranen;L. Lahti;V. Salomaa;Ho-Cheol Kim;Mohit Jain;M. Inouye;J. Gilbert;R. Knight

Unlocking capacities of genomics for the COVID-19 response and future pandemics.

• DOI: 10.1038/s41592-022-01444-z
• 发表时间: 2022-04
• 期刊: NATURE METHODS
• 影响因子: 48
• 作者: Knyazev, Sergey;Chhugani, Karishma;Sarwal, Varuni;Ayyala, Ram;Singh, Harman;Karthikeyan, Smruthi;Deshpande, Dhrithi;Baykal, Pelin Icer;Comarova, Zoia;Lu, Angela;Porozov, Yuri;Vasylyeva, Tetyana, I;Wertheim, Joel O.;Tierney, Braden T.;Chiu, Charles Y.;Sun, Ren;Wu, Aiping;Abedalthagafi, Malak S.;Pak, Victoria M.;Nagaraj, Shivashankar H.;Smith, Adam L.;Skums, Pavel;Pasaniuc, Bogdan;Komissarov, Andrey;Mason, Christopher E.;Bortz, Eric;Lemey, Philippe;Kondrashov, Fyodor;Beerenwinkel, Niko;Lam, Tommy Tsan-Yuk;Wu, Nicholas C.;Zelikovsky, Alex;Knight, Rob;Crandall, Keith A.;Mangul, Serghei
• 通讯作者: Mangul, Serghei

The ViReflow pipeline enables user friendly large scale viral consensus genome reconstruction.

• DOI: 10.1038/s41598-022-09035-w
• 发表时间: 2022-03-24
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Moshiri N;Fisch KM;Birmingham A;DeHoff P;Yeo GW;Jepsen K;Laurent LC;Knight R
• 通讯作者: Knight R

Bacterial metatranscriptomes in wastewater can differentiate virally infected human populations

废水中的细菌宏转录组可以区分病毒感染的人群

• DOI: 10.1101/2022.02.23.481658
• 发表时间: 2022
• 期刊: bioRxiv
• 作者: Rodolfo A Salido;Cameron Martino;Smruthi Karthikeyan;Shi Huang;Gibraan Rahman;Antonio Gonzalez;Livia S. Zaramela;Kristen L Beck;Shrikant Bhute;Kalen Cantrell
• 通讯作者: Kalen Cantrell