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对导致人类哺乳期乳腺炎的细菌进行全基因组测序,并结合对其抗生素耐药性谱的检测。

Whole-genome sequencing of bacteria accountable for lactational mastitis in humans combined with an examination of their antibiotic resistance profiles.

作者信息

Dalwadi Priyanka, Nathani Neelam, Chauhan Kshipra, Mansuri Jasmine, Koringa Prakash, Bhatt Vaibhav, Kunjadiya Anju P

机构信息

P. G. Department of Applied and Interdisciplinary Sciences, Sardar Patel University, V. V. Nagar, Gujarat, 388 120, India.

School of Applied Sciences & Technology, Gujarat Technological University, Ahmedabad, 382 424, Gujarat, India.

出版信息

Braz J Microbiol. 2024 Dec;55(4):3827-3838. doi: 10.1007/s42770-024-01519-3. Epub 2024 Sep 25.

Abstract

Lactational mastitis, a common condition affecting nursing mothers, is characterized by mammary gland inflammation during lactation. This inflammatory response typically occurs due to bacterial infection. The discomfort and pain associated with lactational mastitis can significantly impact a mother's ability to breastfeed comfortably and may lead to the cessation of breastfeeding altogether if left untreated. Antibiotics are commonly prescribed to target the bacteria causing the infection and alleviate symptoms, aiming to treat the infection. Nevertheless, a notable worry linked to antibiotic use is the emergence of antibiotic resistance, compounded by the possible persistence of antibiotics in milk. Additionally, lactational mastitis is characterized by its polymicrobial nature. In this study, bacteria were isolated from infected breast milk samples and whole-genome sequencing was performed on eleven isolates to accurately identify the bacteria and assess their antibiotic resistance profiles. Using Galaxy tools and the ResFinder database, we identified Bacillus paraanthracis, Bacillus altitudinis, Staphylococcus aureus, Bacillus cereus, Escherichia coli, Alcaligenes faecalis, and Bacillus licheniformis, along with antibiotic-resistant genes like fosB1, cat86, erm (D), blaZ, and mdf (A). ABRicate aided in antimicrobial resistance (AMR) gene analysis, and CARD visualized their distribution. Our study demonstrates that the severity of infection is directly proportional to an increase in somatic cell count (SCC). This research sheds light on microbial diversity in lactational mastitis milk and provides crucial insights into antibiotic-resistance genes. Utilizing bioinformatics tools, such as those employed in this study, can inform the design of effective treatment strategies for lactational mastitis infections.

摘要

哺乳期乳腺炎是一种影响哺乳期母亲的常见病症,其特征是哺乳期乳腺发炎。这种炎症反应通常是由细菌感染引起的。与哺乳期乳腺炎相关的不适和疼痛会严重影响母亲舒适地进行母乳喂养的能力,如果不加以治疗,可能会导致完全停止母乳喂养。通常会开具抗生素来针对引起感染的细菌并缓解症状,以治疗感染。然而,与使用抗生素相关的一个显著担忧是抗生素耐药性的出现,再加上抗生素可能会残留在乳汁中。此外,哺乳期乳腺炎具有多微生物的特性。在本研究中,从受感染的母乳样本中分离出细菌,并对11株分离菌进行了全基因组测序,以准确鉴定细菌并评估它们的抗生素耐药谱。使用Galaxy工具和ResFinder数据库,我们鉴定出了副炭疽芽孢杆菌、高地芽孢杆菌、金黄色葡萄球菌、蜡样芽孢杆菌、大肠杆菌、粪产碱菌和地衣芽孢杆菌,以及fosB1、cat86、erm (D)、blaZ和mdf (A)等抗生素耐药基因。ABRicate辅助进行抗菌药物耐药性(AMR)基因分析,CARD可视化它们的分布。我们的研究表明,感染的严重程度与体细胞计数(SCC)的增加成正比。这项研究揭示了哺乳期乳腺炎乳汁中的微生物多样性,并提供了对抗生素耐药基因的关键见解。利用生物信息学工具,如本研究中使用的那些工具,可以为哺乳期乳腺炎感染的有效治疗策略设计提供参考。

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