验证了大肠杆菌生物膜形成的计算机模型,ACS Synthetic Biology

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验证了大肠杆菌生物膜形成的计算机模型
ACS Synthetic Biology ( IF 3.7 ) Pub Date : 2022-01-13 , DOI: 10.1021/acssynbio.1c00445
Purnendu Bhowmik _{1,

2} , Sreenath Rajagopal ₁ , Rothangamawi Victoria Hmar ₁ , Purnima Singh ₁ , Pragya Saxena ₁ , Prakruthi Amar ₁ , Teby Thomas ₃ , Rajani Ravishankar ₁ , Savitha Nagaraj ₄ , Nainesh Katagihallimath _{1,

2} , Ramanujan Kadambi Sarangapani ₁ , Vasanthi Ramachandran _{1,

2} , Santanu Datta ₁

Affiliation

使用大肠杆菌作为具有代表性的生物膜形成者，我们在此报告了通过模拟将自由生活的细菌实体转化为自我包裹的多细胞生物膜的事件而构建的计算机模型的发展。整理了与参与生物膜形成的途径相关的约 300 个基因的已发表文献，创建了静态图，并使用常微分方程与它们各自的代谢物适当地相互连接。适当地表示了调节细菌生长模式响应环境变化的短暂转换的遗传网络的精确相互作用以及由此产生的细胞外基质的多组分合成。随后，通过使用 R 和 python 环境模拟组分浓度随时间的变化来分析计算机模型。该模型通过模拟和验证关键基因敲除 (KO) 和系统敲除对生物膜形成的影响进行了验证，从而确保结果与报道的文献具有可比性。同样，实验室和致病的特定基因 KO构建和评估大肠杆菌。MiaA、YdeO 和 YgiV 被发现在生物膜发育中至关重要。此外，qRT-PCR 证实了生物膜形成临床分离株的表达升高。本研究报告的结果为识别在多个行业中应用的生物膜抑制剂提供了机会。该模型的应用可以扩展到医疗保健部门，特别是开发新的辅助疗法，以防止医疗植入物中的生物膜并减少与生物膜相关的耐药性多微生物慢性感染的出现。此处报告的计算机框架是开源的，可用于进一步增强。

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Validated In Silico Model for Biofilm Formation in Escherichia coli

Using Escherichia coli as the representative biofilm former, we report here the development of an in silico model built by simulating events that transform a free-living bacterial entity into self-encased multicellular biofilms. Published literature on ∼300 genes associated with pathways involved in biofilm formation was curated, static maps were created, and suitably interconnected with their respective metabolites using ordinary differential equations. Precise interplay of genetic networks that regulate the transitory switching of bacterial growth pattern in response to environmental changes and the resultant multicomponent synthesis of the extracellular matrix were appropriately represented. Subsequently, the in silico model was analyzed by simulating time-dependent changes in the concentration of components by using the R and python environment. The model was validated by simulating and verifying the impact of key gene knockouts (KOs) and systematic knockdowns on biofilm formation, thus ensuring the outcomes were comparable with the reported literature. Similarly, specific gene KOs in laboratory and pathogenic E. coli were constructed and assessed. MiaA, YdeO, and YgiV were found to be crucial in biofilm development. Furthermore, qRT-PCR confirmed the elevation of expression in biofilm-forming clinical isolates. Findings reported in this study offer opportunities for identifying biofilm inhibitors with applications in multiple industries. The application of this model can be extended to the health care sector specifically to develop novel adjunct therapies that prevent biofilms in medical implants and reduce emergence of biofilm-associated resistant polymicrobial-chronic infections. The in silico framework reported here is open source and accessible for further enhancements.

更新日期：2022-01-13

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