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利用最大熵模型评估气候变化对1884年罗森巴赫金黄色葡萄球菌全球分布的生态影响。

Evaluation of ecological consequences on the global distribution of Staphylococcus aureus Rosenbach 1884 due to climate change, using Maxent modeling.

作者信息

Alqahtani Monerah S M, Shahin Gasser, Abdelalim Ibrahim T I, Khalaf Sameh M H

机构信息

Biology Department, Faculty of Science, King Khalid University, 61413, Abha, Saudi Arabia.

Faculty of Biotechnology, October University for Modern Sciences & Arts (MSA University), 6th October City, 12566, Egypt.

出版信息

Sci Rep. 2025 Apr 3;15(1):11457. doi: 10.1038/s41598-025-87534-2.

Abstract

Staphylococcus aureus is a primary cause of many infections in humans, and its rising prevalence and drug resistance are serious public health concerns. While there is evidence that climate change can influence the distribution and abundance of microbial species, the precise effects on S. aureus are not well characterized. The purpose of this study is to predict the potential influence of climate change on the global distribution of Staphylococcus aureus in 2050 and 2070 using GIS and Maxent modeling. S. aureus occurrence data was acquired from global databases and coupled with bioclimatic variables to simulate current and future habitat suitability under several climate change scenarios (RCP 2.6 and 8.5). The Maxent modeling approach was used to forecast geographical patterns of S. aureus distribution, providing insights into locations that may see increased prevalence of this essential species as a result of climate change. The study's findings can be used to inform public health measures and focused surveillance activities aimed at reducing the burden of Staphylococcus aureus infection.

摘要

金黄色葡萄球菌是人类多种感染的主要病因,其日益增加的流行率和耐药性是严重的公共卫生问题。虽然有证据表明气候变化会影响微生物物种的分布和丰度,但对金黄色葡萄球菌的确切影响尚未得到充分描述。本研究的目的是利用地理信息系统(GIS)和最大熵(Maxent)建模预测2050年和2070年气候变化对全球金黄色葡萄球菌分布的潜在影响。从全球数据库获取金黄色葡萄球菌的发生数据,并与生物气候变量相结合,以模拟在几种气候变化情景(代表性浓度路径2.6和8.5)下当前和未来的栖息地适宜性。采用Maxent建模方法预测金黄色葡萄球菌分布的地理模式,深入了解由于气候变化可能导致该重要菌种流行率增加的地点。该研究结果可用于为旨在减轻金黄色葡萄球菌感染负担的公共卫生措施和重点监测活动提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1911/11968831/f52e7511e11f/41598_2025_87534_Fig1_HTML.jpg

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