In Vitro Fiber-Probe-Based Identification of Pathogens in Biofilms by Raman Spectroscopy

生物膜 拉曼光谱 化学 纤维 胞外聚合物 微生物学 细菌 生物 光学 物理 遗传学 有机化学
作者
Haodong Shen,Petra Rösch,Mathias W. Pletz,Jürgen Popp
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:94 (13): 5375-5381 被引量:11
标识
DOI:10.1021/acs.analchem.2c00029
摘要

Biofilms are the preferred habitat of microorganisms on living and artificial surfaces. Biofilm-related infections, such as infections of medical implants, are difficult to treat, and due to a reduced cultivability of the included bacteria, difficult to diagnose. Therefore, it is highly important to rapidly identify and investigate biofilms on implant surfaces, e.g., during surgery. In this study, we present fiber-probe-based Raman spectroscopy with an excitation wavelength of 785 nm, which was applied to investigate six different pathogen species involved in biofilm-related infections. Biofilms were cultivated in a drip flow reactor, which can model a biofilm growth environment. The signals collected from a fiber probe allowed us to collect Raman spectra not only from the embedded bacterial and yeast cells but also the surrounding extracellular polymeric substance matrix. This information was used in a classification model. The model consists of a principal component analysis in combination with linear discriminant analysis and was examined by applying a leave-one-batch-out cross-validation. This model achieved a classification accuracy of 93.8%. In addition, the identification accuracy increased up to 97.5% when clinical strains were used for identification. A fiber-probe-based Raman spectroscopy method combined with a chemometric analysis might therefore serve as a fast, accurate, and portable strategy for the species identification of biofilm-related infections, e.g., during surgical procedures.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
梦丽有人发布了新的文献求助10
刚刚
3秒前
Twonej应助cl采纳,获得30
3秒前
JamesPei应助柯擎汉采纳,获得10
4秒前
脑洞疼应助张凤采纳,获得10
5秒前
hay发布了新的文献求助10
5秒前
5秒前
肉丸完成签到 ,获得积分10
6秒前
6秒前
teeth发布了新的文献求助10
7秒前
8秒前
hydrogen完成签到,获得积分10
9秒前
kun发布了新的文献求助10
9秒前
9秒前
9秒前
FashionBoy应助yana采纳,获得10
9秒前
xulin完成签到,获得积分10
10秒前
eternity136发布了新的文献求助10
12秒前
甜甜的枫发布了新的文献求助10
13秒前
扎根发布了新的文献求助10
14秒前
量子星尘发布了新的文献求助10
14秒前
上官若男应助小李子采纳,获得10
15秒前
15秒前
15秒前
16秒前
lkk完成签到,获得积分10
16秒前
17秒前
mjh完成签到,获得积分10
17秒前
飞飞翔的小马完成签到,获得积分10
17秒前
18秒前
18秒前
18秒前
张凤发布了新的文献求助10
19秒前
liaotao完成签到 ,获得积分10
19秒前
19秒前
20秒前
一折悲画扇完成签到,获得积分10
20秒前
clearlove发布了新的文献求助10
23秒前
23秒前
清秀的悒完成签到,获得积分10
24秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The Cambridge History of China: Volume 4, Sui and T'ang China, 589–906 AD, Part Two 1000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1000
Russian Foreign Policy: Change and Continuity 800
Real World Research, 5th Edition 800
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 800
Superabsorbent Polymers 700
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5711883
求助须知:如何正确求助?哪些是违规求助? 5206296
关于积分的说明 15265590
捐赠科研通 4864003
什么是DOI,文献DOI怎么找? 2611125
邀请新用户注册赠送积分活动 1561399
关于科研通互助平台的介绍 1518729