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赋能、授权、成功:一场生物信息学研讨会——利用基于网络的开放工具监测细菌抗菌药物耐药性

Enable, empower, succeed: a bioinformatics workshop Harnessing open web-based tools for surveillance of bacterial antimicrobial resistance.

作者信息

Founou Luria Leslie, Lawal Opeyemi U, Djiyou Armando, Odih Erkison Ewomazino, Amoako Daniel Gyamfi, Fadanka Stephane, Aworh Mabel Kamweli, Lukhele Sindiswa, Nikolic Dusanka, Matimba Alice, Founou Raspail Carrel

机构信息

Reproductive, Maternal, Newborn and Child Health (ReMARCH) Research Unit, Research Institute of the Centre of Expertise and Biological Diagnostic of Cameroon (CEDBCAM-RI), Yaoundé, Cameroon.

Bioinformatics & Applied Machine Learning Research Unit, EDEN Biosciences Research Institute (EBRI), EDEN Foundation, Yaoundé, Cameroon.

出版信息

BMC Microbiol. 2025 Mar 19;25(1):156. doi: 10.1186/s12866-025-03865-0.

DOI:10.1186/s12866-025-03865-0
PMID:40102762
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11921729/
Abstract

BACKGROUND

Antimicrobial resistance (AMR) poses a significant threat to global health, particularly in Western sub-Saharan Africa where 27.3 deaths per 100,000 lives are affected, and surveillance and control measures are often limited. Genomics research plays a crucial role in understanding the emergence, spread and containment measures of AMR. However, its implementation in such settings is particularly challenging due to limited human capacity. This manuscript outlines a three-day bioinformatics workshop in Cameroon, highlighting efforts to build human capacity for genomics research to support AMR surveillance using readily accessible and user-friendly web-based tools. The workshop introduced participants to basic next-generation sequencing concepts, data file formats used in bacterial genomics, data sharing procedures and considerations, as well as the use of web-based bioinformatics software to analyse genomic data, including in silico prediction of AMR, phylogenetics analyses, and a quick introduction to Linux© command line.

RESULTS

Briefly, a substantial increase in participants' confidence in bioinformatics knowledge and skills was observed before and after the workshop. Notably, before the workshop most participants lacked confidence in their ability to identify next-generation sequencing technologies or workflows (64%) and analyse genetic data using web-based bioinformatics tools (81%). After the workshop, majority of participants were extremely confident using NCBI BLAST and other web-based bioinformatics tools for data analysis with a score ≥ 5 among which 45%, 9% and 18% had a score of 8, 9, and 10, respectively.

CONCLUSION

Our findings highlight the effectiveness of this training approach in empowering local researchers and bridging the bioinformatics gap in genomics surveillance of AMR in resource-constrained settings. We provide a detailed description of the relevant training approaches used, including workshop structure, the selection and planning, and utilization of freely available web-based tools, and the evaluation methods employed. Our approach aimed to overcome limitations such as inadequate infrastructure, limited access to computational resources, and scarcity of expertise. By leveraging the power of freely available web-based tools, we demonstrated how participants can acquire fundamental bioinformatics skills, enhance their understanding of biological data analysis, and contribute to the field, even in an underprivileged environment. Building human capacity for genomics research globally, and especially in resource-constrained settings, is imperative for ensuring global health and sustainable containment of AMR.

摘要

背景

抗菌药物耐药性(AMR)对全球健康构成重大威胁,特别是在撒哈拉以南非洲西部地区,每10万人中有27.3人受到影响,而且监测和控制措施往往有限。基因组学研究在了解AMR的出现、传播和遏制措施方面发挥着关键作用。然而,由于人力有限,在这种环境中实施基因组学研究尤其具有挑战性。本手稿概述了在喀麦隆举办的为期三天的生物信息学研讨会,重点介绍了利用易于获取且用户友好的基于网络的工具,建设基因组学研究人力以支持AMR监测的努力。该研讨会向参与者介绍了基本的下一代测序概念、细菌基因组学中使用的数据文件格式、数据共享程序和注意事项,以及使用基于网络的生物信息学软件分析基因组数据,包括AMR的计算机模拟预测、系统发育分析,以及对Linux©命令行的简要介绍。

结果

简而言之,在研讨会前后,观察到参与者对生物信息学知识和技能的信心大幅增强。值得注意的是,在研讨会之前,大多数参与者对自己识别下一代测序技术或工作流程的能力(64%)以及使用基于网络的生物信息学工具分析遗传数据的能力(81%)缺乏信心。研讨会之后,大多数参与者对使用NCBI BLAST和其他基于网络的生物信息学工具进行数据分析极为自信,得分≥5,其中45%、9%和18%的参与者得分分别为8、9和10。

结论

我们的研究结果凸显了这种培训方法在增强当地研究人员能力以及弥合资源受限环境中AMR基因组监测方面生物信息学差距方面的有效性。我们详细描述了所采用的相关培训方法,包括研讨会结构、免费可用的基于网络的工具的选择、规划和使用,以及所采用的评估方法。我们的方法旨在克服诸如基础设施不足、获取计算资源有限以及专业知识匮乏等限制。通过利用免费可用的基于网络的工具的力量,我们展示了参与者如何能够获得基本的生物信息学技能,增强他们对生物数据分析的理解,并为该领域做出贡献,即使是在贫困环境中。在全球范围内,特别是在资源受限的环境中建设基因组学研究的人力,对于确保全球健康和可持续遏制AMR至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89b1/11921729/3ff3269c08eb/12866_2025_3865_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89b1/11921729/8d6565122837/12866_2025_3865_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89b1/11921729/ab86718d3ee2/12866_2025_3865_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89b1/11921729/d2734bf05541/12866_2025_3865_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89b1/11921729/3ff3269c08eb/12866_2025_3865_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89b1/11921729/8d6565122837/12866_2025_3865_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89b1/11921729/ab86718d3ee2/12866_2025_3865_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89b1/11921729/d2734bf05541/12866_2025_3865_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89b1/11921729/3ff3269c08eb/12866_2025_3865_Fig2_HTML.jpg

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