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链霉菌基因调控网络的全局重建、推理和评估。

Curation, inference, and assessment of a globally reconstructed gene regulatory network for Streptomyces coelicolor.

机构信息

Regulatory Systems Biology Research Group, Laboratory of Systems and Synthetic Biology, Center for Genomics Sciences, Universidad Nacional Autónoma de México, Av. Universidad s/n, Col. Chamilpa, 62210, Cuernavaca, Morelos, México.

Bioprocess Research Group, Department of Chemical Engineering, Universidad de Antioquia, Calle 70 No. 52-21, Medellín, Colombia.

出版信息

Sci Rep. 2022 Feb 18;12(1):2840. doi: 10.1038/s41598-022-06658-x.

Abstract

Streptomyces coelicolor A3(2) is a model microorganism for the study of Streptomycetes, antibiotic production, and secondary metabolism in general. Even though S. coelicolor has an outstanding variety of regulators among bacteria, little effort to globally study its transcription has been made. We manually curated 29 years of literature and databases to assemble a meta-curated experimentally-validated gene regulatory network (GRN) with 5386 genes and 9707 regulatory interactions (~ 41% of the total expected interactions). This provides the most extensive and up-to-date reconstruction available for the regulatory circuitry of this organism. Only ~ 6% (534/9707) are supported by experiments confirming the binding of the transcription factor to the upstream region of the target gene, the so-called "strong" evidence. While for the remaining interactions there is no confirmation of direct binding. To tackle network incompleteness, we performed network inference using several methods (including two proposed here) for motif identification in DNA sequences and GRN inference from transcriptomics. Further, we contrasted the structural properties and functional architecture of the networks to assess the reliability of the predictions, finding the inference from DNA sequence data to be the most trustworthy approach. Finally, we show two applications of the inferred and the curated networks. The inference allowed us to propose novel transcription factors for the key Streptomyces antibiotic regulatory proteins (SARPs). The curated network allowed us to study the conservation of the system-level components between S. coelicolor and Corynebacterium glutamicum. There we identified the basal machinery as the common signature between the two organisms. The curated networks were deposited in Abasy Atlas ( https://abasy.ccg.unam.mx/ ) while the inferences are available as Supplementary Material.

摘要

链霉菌 A3(2) 是研究链霉菌、抗生素生产和一般次级代谢的模式微生物。尽管链霉菌具有细菌中种类繁多的调节剂,但对其转录的全局研究却很少。我们手动整理了 29 年的文献和数据库,组装了一个经过元整理的实验验证的基因调控网络 (GRN),其中包含 5386 个基因和 9707 个调控相互作用(41%的总预期相互作用)。这提供了该生物调控回路最广泛和最新的重建。只有6%(534/9707)得到了实验的支持,这些实验证实了转录因子与靶基因上游区域的结合,即所谓的“强”证据。而对于其余的相互作用,没有直接结合的确认。为了解决网络不完整的问题,我们使用几种方法(包括这里提出的两种)进行网络推断,以识别 DNA 序列中的基序和从转录组学推断 GRN。此外,我们对比了网络的结构特性和功能架构,以评估预测的可靠性,发现从 DNA 序列数据推断是最可靠的方法。最后,我们展示了推断和整理网络的两个应用。推断使我们能够为关键链霉菌抗生素调控蛋白 (SARPs) 提出新的转录因子。整理后的网络使我们能够研究链霉菌和谷氨酸棒状杆菌之间系统水平成分的保守性。在那里,我们确定了基本机制是两种生物之间的共同特征。整理后的网络已被存储在 Abasy Atlas(https://abasy.ccg.unam.mx/)中,而推断结果则可作为补充材料获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/609f/8857197/2c05268cacdd/41598_2022_6658_Fig1_HTML.jpg

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