Dataset Information

Fast Screening and Primary Diagnosis of COVID-19 by ATR-FT-IR.

ABSTRACT: The outbreak of coronavirus disease 2019 (COVID-19) has led to substantial infections and mortality around the world. Fast screening and diagnosis are thus crucial for quick isolation and clinical intervention. In this work, we showed that attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FT-IR) can be a primary diagnostic tool for COVID-19 as a supplement to in-use techniques. It requires only a small volume (?3 ?L) of the serum sample and a shorter detection time (several minutes). The distinct spectral differences and the separability between normal control and COVID-19 were investigated using multivariate and statistical analysis. Results showed that ATR-FT-IR coupled with partial least squares discriminant analysis was effective to differentiate COVID-19 from normal controls and some common respiratory viral infections or inflammation, with the area under the receiver operating characteristic curve (AUROC) of 0.9561 (95% CI: 0.9071-0.9774). Several serum constituents including, but not just, antibodies and serum phospholipids could be reflected on the infrared spectra, serving as "chemical fingerprints" and accounting for good model performances.

SUBMITTER: Zhang L

PROVIDER: S-EPMC7805601 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Fast Screening and Primary Diagnosis of COVID-19 by ATR-FT-IR.

Zhang Liyang L Xiao Meng M Wang Yao Y Peng Siqi S Chen Yu Y Zhang Dong D Zhang Dongheyu D Guo Yuntao Y Wang Xinxin X Luo Haiyun H Zhou Qun Q Xu Yingchun Y

Analytical chemistry 20210111 4

The outbreak of coronavirus disease 2019 (COVID-19) has led to substantial infections and mortality around the world. Fast screening and diagnosis are thus crucial for quick isolation and clinical intervention. In this work, we showed that attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FT-IR) can be a primary diagnostic tool for COVID-19 as a supplement to in-use techniques. It requires only a small volume (∼3 μL) of the serum sample and a shorter detection time (severa ...[more]

PMID: 33427452

Similar Datasets

Project description:Rat ear cartilage was studied using Fourier transform-infrared (FT-IR) microspectroscopy to expand the current knowledge which has been established for relatively more complex cartilage types. Comparison of the FT-IR spectra of the ear cartilage extracellular matrix (ECM) with published data on articular cartilage, collagen II and 4-chondroitin-sulfate standards, as well as of collagen type I-containing dermal collagen bundles (CBs) with collagen type II, was performed. Ear cartilage ECM glycosaminoglycans (GAGs) were revealed histochemically and as a reduction in ECM FT-IR spectral band heights (1140-820 cm-1) after testicular hyaluronidase digestion. Although ear cartilage is less complex than articular cartilage, it contains ECM components with a macromolecular orientation as revealed using polarization microscopy. Collagen type II and GAGs, which play a structural role in the stereo-arrangement of the ear cartilage, contribute to its FT-IR spectrum. Similar to articular cartilage, ear cartilage showed that proteoglycans add a contribution to the collagen amide I spectral region, a finding that does not recommend this region for collagen type II quantification purposes. In contrast to articular cartilage, the symmetric stretching vibration of -SO3- groups at 1064 cm-1 appeared under-represented in the FT-IR spectral profile of ear cartilage. Because the band corresponding to the asymmetric stretching vibration of -SO3- groups (1236-1225 cm-1) overlapped with that of amide III bands, it is not recommended for evaluation of the -SO3- contribution to the FT-IR spectrum of the ear cartilage ECM. Instead, a peak (or shoulder) at 1027-1016 cm-1 could be better considered for this intent. Amide I/amide II ratios as calculated here and data from the literature suggest that protein complexes of the ear cartilage ECM are arranged with a lower helical conformation compared to pure collagen II. The present results could motivate further studies on this tissue under pathological or experimental states involving ear cartilage.

Project description:The reliability of Fourier-transform infrared (FT-IR) spectroscopy for Klebsiella pneumoniae typing and outbreak control has been previously assessed, but issues remain in standardization and reproducibility. We developed and validated a reproducible FT-IR with attenuated total reflectance (ATR) workflow for the identification of K. pneumoniae lineages. We used 293 isolates representing multidrug-resistant K. pneumoniae lineages causing outbreaks worldwide (2002-2021) to train a random forest classification (RF) model based on capsular (KL)-type discrimination. This model was validated with 280 contemporaneous isolates (2021-2022), using wzi sequencing and whole-genome sequencing as references. Repeatability and reproducibility were tested in different culture media and instruments throughout time. Our RF model allowed the classification of 33 capsular (KL)-types and up to 36 clinically relevant K. pneumoniae lineages based on the discrimination of specific KL- and O-type combinations. We obtained high rates of accuracy (89%), sensitivity (88%), and specificity (92%), including from cultures obtained directly from the clinical sample, allowing to obtain typing information the same day bacteria are identified. The workflow was reproducible in different instruments throughout time (>98% correct predictions). Direct colony application, spectral acquisition, and automated KL prediction through Clover MS Data analysis software allow a short time-to-result (5 min/isolate). We demonstrated that FT-IR ATR spectroscopy provides meaningful, reproducible, and accurate information at a very early stage (as soon as bacterial identification) to support infection control and public health surveillance. The high robustness together with automated and flexible workflows for data analysis provide opportunities to consolidate real-time applications at a global level. IMPORTANCE We created and validated an automated and simple workflow for the identification of clinically relevant Klebsiella pneumoniae lineages by FT-IR spectroscopy and machine-learning, a method that can be extremely useful to provide quick and reliable typing information to support real-time decisions of outbreak management and infection control. This method and workflow is of interest to support clinical microbiology diagnostics and to aid public health surveillance.

Dataset Information

Fast Screening and Primary Diagnosis of COVID-19 by ATR-FT-IR.

Publications

Fast Screening and Primary Diagnosis of COVID-19 by ATR-FT-IR.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets