A Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human Serum

Serum is an important candidate in proteomics analysis as it potentially carries key markers on health status and disease progression. However, several important diagnostic markers found in the circulatory proteome and the low-molecular-weight (LMW) peptidome have become analytically challenging due...

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Main Authors: Thulya Chakkumpulakkal Puthan Veettil, Bayden R. Wood
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/22/12/4528
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author Thulya Chakkumpulakkal Puthan Veettil
Bayden R. Wood
author_facet Thulya Chakkumpulakkal Puthan Veettil
Bayden R. Wood
author_sort Thulya Chakkumpulakkal Puthan Veettil
collection DOAJ
description Serum is an important candidate in proteomics analysis as it potentially carries key markers on health status and disease progression. However, several important diagnostic markers found in the circulatory proteome and the low-molecular-weight (LMW) peptidome have become analytically challenging due to the high dynamic concentration range of the constituent protein/peptide species in serum. Herein, we propose a novel approach to improve the limit of detection (LoD) of LMW amino acids by combining mid-IR (MIR) and near-IR spectroscopic data using glycine as a model LMW analyte. This is the first example of near-IR spectroscopy applied to elucidate the detection limit of LMW components in serum; moreover, it is the first study of its kind to combine mid-infrared (25–2.5 μm) and near-infrared (2500–800 nm) to detect an analyte in serum. First, we evaluated the prediction model performance individually with MIR (ATR-FTIR) and NIR spectroscopic methods using partial least squares regression (PLS-R) analysis. The LoD was found to be 0.26 mg/mL with ATR spectroscopy and 0.22 mg/mL with NIR spectroscopy. Secondly, we examined the ability of combined spectral regions to enhance the detection limit of serum-based LMW amino acids. Supervised extended wavelength PLS-R resulted in a root mean square error of prediction (RMSEP) value of 0.303 mg/mL and R<sup>2</sup> value of 0.999 over a concentration range of 0–50 mg/mL for glycine spiked in whole serum. The LoD improved to 0.17 mg/mL from 0.26 mg/mL. Thus, the combination of NIR and mid-IR spectroscopy can improve the limit of detection for an LMW compound in a complex serum matrix.
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spelling doaj.art-1621d836f20a48feb2e0a268408436892023-11-23T18:54:51ZengMDPI AGSensors1424-82202022-06-012212452810.3390/s22124528A Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human SerumThulya Chakkumpulakkal Puthan Veettil0Bayden R. Wood1Centre for Biospectroscopy, Monash University, Clayton, VIC 3800, AustraliaCentre for Biospectroscopy, Monash University, Clayton, VIC 3800, AustraliaSerum is an important candidate in proteomics analysis as it potentially carries key markers on health status and disease progression. However, several important diagnostic markers found in the circulatory proteome and the low-molecular-weight (LMW) peptidome have become analytically challenging due to the high dynamic concentration range of the constituent protein/peptide species in serum. Herein, we propose a novel approach to improve the limit of detection (LoD) of LMW amino acids by combining mid-IR (MIR) and near-IR spectroscopic data using glycine as a model LMW analyte. This is the first example of near-IR spectroscopy applied to elucidate the detection limit of LMW components in serum; moreover, it is the first study of its kind to combine mid-infrared (25–2.5 μm) and near-infrared (2500–800 nm) to detect an analyte in serum. First, we evaluated the prediction model performance individually with MIR (ATR-FTIR) and NIR spectroscopic methods using partial least squares regression (PLS-R) analysis. The LoD was found to be 0.26 mg/mL with ATR spectroscopy and 0.22 mg/mL with NIR spectroscopy. Secondly, we examined the ability of combined spectral regions to enhance the detection limit of serum-based LMW amino acids. Supervised extended wavelength PLS-R resulted in a root mean square error of prediction (RMSEP) value of 0.303 mg/mL and R<sup>2</sup> value of 0.999 over a concentration range of 0–50 mg/mL for glycine spiked in whole serum. The LoD improved to 0.17 mg/mL from 0.26 mg/mL. Thus, the combination of NIR and mid-IR spectroscopy can improve the limit of detection for an LMW compound in a complex serum matrix.https://www.mdpi.com/1424-8220/22/12/4528serum proteomicsattenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopynear-infrared spectroscopychemometricsmultimodal data fusionglycine
spellingShingle Thulya Chakkumpulakkal Puthan Veettil
Bayden R. Wood
A Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human Serum
Sensors
serum proteomics
attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy
near-infrared spectroscopy
chemometrics
multimodal data fusion
glycine
title A Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human Serum
title_full A Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human Serum
title_fullStr A Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human Serum
title_full_unstemmed A Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human Serum
title_short A Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human Serum
title_sort combined near infrared and mid infrared spectroscopic approach for the detection and quantification of glycine in human serum
topic serum proteomics
attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy
near-infrared spectroscopy
chemometrics
multimodal data fusion
glycine
url https://www.mdpi.com/1424-8220/22/12/4528
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