Unraveling regulatory networks in biological nutrient removal (BNR) microbiomes

解开生物营养去除（BNR）微生物组中的调控网络

• 批准号: 1803055
• 负责人: Daniel Noguera
• 金额: $ 33万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1803055&HistoricalAwards=false
• 关键词: Unraveling; regulatory; networks; biological; nutrient

A large fraction of the energy cost in operating a wastewater treatment plant is supplying oxygen to the microorganisms performing the treatment process. These costs would decrease if treatment plants could be operated under low-oxygen conditions. It remains unknown how microorganisms adapt to low-oxygen conditions and whether treatment plants can be effectively operated with minimal oxygen aeration. This project will reveal how key microorganisms in wastewater treatment systems regulate their internal gene networks in response to plant operations with minimal aeration. Other impacts of the project include educational activities related to mentoring high school, undergraduate, and graduate students, and advancing the understanding of gene regulation in natural and engineered environments. If successful, this project will provide transformative information that can help protect the Nation's water security through advanced treatment processes to remove both reactive nitrogen and phosphorus.This proposal seeks to develop and test a framework to study transcriptional regulation in complex microbiomes. Specifically, the framework will be used to investigate transcriptional regulatory networks (TRNs) in an ammonia-oxidizing bacterium and a polyphosphate accumulating organism identified as major contributors to a biological nutrient removal (BNR) microbiome. This microbiome is maintained in a high-rate BNR bioreactor operated using cycles of anaerobic and micro-aerobic conditions. The proposed framework involves: (i) the use of metagenomic data to assemble genomes of key organisms; time-series metatranscriptomic data to identify gene expression patterns in the organisms of interest; (ii) chromatin immunoprecipitation (ChIP) followed by genome-scale DNA sequencing (ChIP-seq) to identify genes directly targeted by a specific transcription factor (TF); and (iii) an in silico phylogenomic approach to predict sets of co-regulated genes in assembled genomes. The project consists of four Tasks. Task 1 focuses on improving genome assembly by using novel tools, obtaining long DNA sequence reads with an emerging sequencing technology, and creating enrichments of the organisms of interest. Task 2 relates to the use ChIP-seq to experimentally identify genes in Nitrosomonas strain UW-LDO-1 targeted by ANR. Task 3 will use ChIP-seq to target RegA, ANR, and DNR - three TFs hypothesized to control aerobic and anoxic respiration in Accumulibacter strain UW-TNR-IC. Task 4 consists of an in silico reconstruction of large-scale TRNs of Nitrosomonas UW-LDO-1 and Accumulibacter UW-TNR-IC. The effective use of this integrative systems biology methodology is transformational because it is the first attempt at assembling a TRN in uncultured microbes using a combination of experimental and computational approaches. This project will provide the first analysis of how respiration is regulated at the transcription level in two key organisms.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.

运营污水处理厂的能源成本的很大一部分是为执行处理过程的微生物提供氧气。如果处理厂可以在低氧条件下运行，这些成本将会降低。微生物是如何适应低氧条件的，以及处理厂能否在最低氧曝气条件下有效运行，这些都尚不清楚。该项目将揭示污水处理系统中的关键微生物如何调节其内部基因网络，以响应最小曝气的工厂操作。该项目的其他影响包括与指导高中生、本科生和研究生有关的教育活动，以及促进对自然和工程环境中基因调控的理解。如果成功，该项目将提供变革性信息，通过先进的处理工艺去除活性氮和磷，有助于保护国家的水安全。本提案旨在开发和测试一个框架来研究复杂微生物组的转录调控。具体来说，该框架将用于研究氨氧化细菌和多磷酸盐积累生物体中的转录调控网络（trn），这些生物体被确定为生物营养去除（BNR）微生物组的主要贡献者。这种微生物群维持在高速率BNR生物反应器中，使用厌氧和微氧条件循环运行。提议的框架包括：(i)使用宏基因组数据来组装关键生物的基因组；时间序列亚转录组学数据，以确定感兴趣的生物体中的基因表达模式；（ii）染色质免疫沉淀（ChIP），然后进行基因组级DNA测序（ChIP-seq），以鉴定特定转录因子（TF）直接靶向的基因；（iii）一种预测组装基因组中共调控基因集的计算机系统基因组学方法。该项目由四个任务组成。任务1的重点是通过使用新的工具来改善基因组组装，用新兴的测序技术获得长DNA序列，并创造感兴趣的生物体的丰富。任务2是利用ChIP-seq实验鉴定ANR靶向亚硝基单胞菌UW-LDO-1的基因。任务3将使用ChIP-seq靶向RegA、ANR和DNR，这三种TFs被假设控制了积累杆菌菌株UW-TNR-IC的有氧和缺氧呼吸。任务4包括亚硝基单胞菌UW-LDO-1和积累杆菌UW-TNR-IC的大规模trn的计算机重建。这种综合系统生物学方法的有效使用是变革性的，因为它是首次尝试使用实验和计算方法相结合的方法在未培养的微生物中组装TRN。该项目将首次分析两种关键生物的呼吸是如何在转录水平上受到调节的。该奖项反映了美国国家科学基金会的法定使命，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。