SNU CBE

Model-driven experimental design workflow expands understanding of regulatory role of Nac in Escherichia coli

2023 · NAR Genomics and Bioinformatics

저자

Joon Young Park, Sang‐Mok Lee, Ali Ebrahim, Zoe K. Scott-Nevros, Jaehyung Kim, Laurence Yang, Anand V. Sastry, 서상우 (Sang Woo Seo), Bernhard Ørn Palsson, Donghyuk Kim

연구주제

Bacterial Genetics and Biotechnology · Microbial Metabolic Engineering and Bioproduction

NTIS 과학기술표준분류

가장 가까운 분류(생명과학 > 융합바이오 > 시스템생물학)가 화학·화공 범위 밖이다. 배정 근거: AI 키워드가 잡은 NTIS 과제의 분류.

AI 연구 키워드·방법

대장균 유전체 규모 대사 모델(GEM) 질소 제한 전사조절 네트워크

model driven experimental design

키워드 (OpenAlex)

NAC NtrC transcriptional regulation nitrogen limitation Escherichia coli transcription factor activation genome-scale metabolic models alternative nitrogen sources

초록

Abstract The establishment of experimental conditions for transcriptional regulator network (TRN) reconstruction in bacteria continues to be impeded by the limited knowledge of activating conditions for transcription factors (TFs). Here, we present a novel genome-scale model-driven workflow for designing experimental conditions, which optimally activate specific TFs. Our model-driven workflow was applied to elucidate transcriptional regulation under nitrogen limitation by Nac and NtrC, in Escherichia coli. We comprehensively predict alternative nitrogen sources, including cytosine and cytidine, which trigger differential activation of Nac using a model-driven workflow. In accordance with the prediction, genome-wide measurements with ChIP-exo and RNA-seq were performed. Integrative data analysis reveals that the Nac and NtrC regulons consist of 97 and 43 genes under alternative nitrogen c…

이 논문을 지원한 국가R&D 과제 (NTIS 성과)

NTIS 성과DB(2020–24)에서 DOI 매칭 없음

인접 그래프

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교수 1

서상우

연구주제 1

Bacterial Genetics and Biotechnology

키워드 4

대장균 · 전사조절 네트워크 · 유전체 규모 대사 모델(GEM) · 질소 제한