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Nat Protoc. 2014 Aug;9(8):1771-91. doi: 10.1038/nprot.2014.110. Epub 2014 Jul 3.

Using Fourier transform IR spectroscopy to analyze biological materials.

Author information

1
1] Centre for Materials Science, Division of Chemistry, University of Central Lancashire, Preston, UK. [2] Present address: WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow, UK.
2
1] Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK. [2] School of Computing and Communications, Lancaster University, Lancaster, UK.
3
Manchester Institute of Biotechnology (MIB), University of Manchester, Manchester, UK.
4
Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
5
Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK.
6
Centre for Materials Science, Division of Chemistry, University of Central Lancashire, Preston, UK.
7
Department of Chemistry, Lancaster University, Lancaster, UK.
8
1] Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK. [2] Division of Biomedical and Life Sciences, School of Health and Medicine, Lancaster University, Lancaster, UK.
9
Division of Biomedical and Life Sciences, School of Health and Medicine, Lancaster University, Lancaster, UK.
10
Proteomics and Spectroscopy (ZBS 6), Robert-Koch-Institut, Berlin, Germany.
11
Equipe MéDIAN-Biophotonique et Technologies pour la Santé, Université de Reims Champagne-Ardenne, UnitéMEDyC, CNRS UMR7369, UFR Pharmacie, SFR CAP-Santé FED4231, Reims, France.
12
Institute for Science and Technology in Medicine, School of Medicine, Keele University, Stoke-on-Trent, UK.
13
Department of Pathology, College of Medicine Research Building (COMRB), University of Illinois at Chicago, Chicago, Illinois, USA.
14
Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton, Victoria, Australia.

Abstract

IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing.

PMID:
24992094
PMCID:
PMC4480339
DOI:
10.1038/nprot.2014.110
[Indexed for MEDLINE]
Free PMC Article

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