Using Fourier transform IR spectroscopy to analyze biological materials
Advances in sample preparation and computation analysis make FTIR of biological materials a rapidly expanding research area. Researchers from a number of universities have collaborated to provide procedures for FTIR analysis of biological samples. IR spectroscopy is an excellent method for biologica...
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| Vydáno v: | Nature protocols Ročník 9; číslo 8; s. 1771 - 1791 |
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| Hlavní autoři: | , , , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
London
Nature Publishing Group UK
01.08.2014
Nature Publishing Group |
| Témata: | |
| ISSN: | 1754-2189, 1750-2799, 1750-2799 |
| On-line přístup: | Získat plný text |
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| Abstract | Advances in sample preparation and computation analysis make FTIR of biological materials a rapidly expanding research area. Researchers from a number of universities have collaborated to provide procedures for FTIR analysis of biological samples.
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. |
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| AbstractList | 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. 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.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. Advances in sample preparation and computation analysis make FTIR of biological materials a rapidly expanding research area. Researchers from a number of universities have collaborated to provide procedures for FTIR analysis of biological samples. 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. |
| Audience | Academic |
| Author | Bhargava, Rohit Martin, Francis L Strong, Rebecca J Walsh, Michael J Bassan, Paul Obinaju, Blessing Wood, Bayden R Trevisan, Júlio Fogarty, Simon W Lasch, Peter Hughes, Caryn Fullwood, Nigel J Sulé-Suso, Josep Baker, Matthew J Dorling, Konrad M Heys, Kelly A Butler, Holly J Martin-Hirsch, Pierre L Fielden, Peter R Sockalingum, Ganesh D Gardner, Peter |
| AuthorAffiliation | 6 Department of Chemistry, Lancaster University, Lancaster, UK 2 Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK 1 Centre for Materials Science, Division of Chemistry, University of Central Lancashire, Preston, UK 4 Manchester Institute of Biotechnology (MIB), University of Manchester, Manchester, UK 12 Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton, Victoria, Australia 3 School of Computing and Communications, Lancaster University, Lancaster, UK 10 Institute for Science and Technology in Medicine, School of Medicine, Keele University, Stoke-on-Trent, UK 7 Division of Biomedical and Life Sciences, School of Health and Medicine, Lancaster University, Lancaster, UK 8 Proteomics and Spectroscopy (ZBS 6), Robert-Koch-Institut, Berlin, Germany 9 Equipe MéDIAN-Biophotonique et Technologies pour la Santé, Université de Reims Champagne-Ardenne, UnitéMEDyC, CNRS UMR7369, UFR Pharmacie, SFR CAP-Santé FED4231, Reims, France 5 Depart |
| AuthorAffiliation_xml | – name: 10 Institute for Science and Technology in Medicine, School of Medicine, Keele University, Stoke-on-Trent, UK – name: 5 Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA – name: 6 Department of Chemistry, Lancaster University, Lancaster, UK – name: 12 Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton, Victoria, Australia – name: 8 Proteomics and Spectroscopy (ZBS 6), Robert-Koch-Institut, Berlin, Germany – name: 1 Centre for Materials Science, Division of Chemistry, University of Central Lancashire, Preston, UK – name: 3 School of Computing and Communications, Lancaster University, Lancaster, UK – name: 9 Equipe MéDIAN-Biophotonique et Technologies pour la Santé, Université de Reims Champagne-Ardenne, UnitéMEDyC, CNRS UMR7369, UFR Pharmacie, SFR CAP-Santé FED4231, Reims, France – name: 2 Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK – name: 4 Manchester Institute of Biotechnology (MIB), University of Manchester, Manchester, UK – name: 11 Department of Pathology, College of Medicine Research Building (COMRB), University of Illinois at Chicago, Chicago, Illinois, USA – name: 7 Division of Biomedical and Life Sciences, School of Health and Medicine, Lancaster University, Lancaster, UK |
| Author_xml | – sequence: 1 givenname: Matthew J surname: Baker fullname: Baker, Matthew J organization: Division of Chemistry, Centre for Materials Science, University of Central Lancashire, Present address: WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow, UK – sequence: 2 givenname: Júlio surname: Trevisan fullname: Trevisan, Júlio organization: Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, School of Computing and Communications, Lancaster University – sequence: 3 givenname: Paul surname: Bassan fullname: Bassan, Paul organization: Manchester Institute of Biotechnology (MIB), University of Manchester – sequence: 4 givenname: Rohit surname: Bhargava fullname: Bhargava, Rohit organization: Department of Bioengineering, University of Illinois at Urbana-Champaign – sequence: 5 givenname: Holly J surname: Butler fullname: Butler, Holly J organization: Centre for Biophotonics, Lancaster Environment Centre, Lancaster University – sequence: 6 givenname: Konrad M surname: Dorling fullname: Dorling, Konrad M organization: Division of Chemistry, Centre for Materials Science, University of Central Lancashire – sequence: 7 givenname: Peter R surname: Fielden fullname: Fielden, Peter R organization: Department of Chemistry, Lancaster University – sequence: 8 givenname: Simon W surname: Fogarty fullname: Fogarty, Simon W organization: Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Division of Biomedical and Life Sciences, School of Health and Medicine, Lancaster University – sequence: 9 givenname: Nigel J surname: Fullwood fullname: Fullwood, Nigel J organization: Division of Biomedical and Life Sciences, School of Health and Medicine, Lancaster University – sequence: 10 givenname: Kelly A surname: Heys fullname: Heys, Kelly A organization: Centre for Biophotonics, Lancaster Environment Centre, Lancaster University – sequence: 11 givenname: Caryn surname: Hughes fullname: Hughes, Caryn organization: Manchester Institute of Biotechnology (MIB), University of Manchester – sequence: 12 givenname: Peter surname: Lasch fullname: Lasch, Peter organization: Proteomics and Spectroscopy (ZBS 6), Robert-Koch-Institut – sequence: 13 givenname: Pierre L surname: Martin-Hirsch fullname: Martin-Hirsch, Pierre L organization: Centre for Biophotonics, Lancaster Environment Centre, Lancaster University – sequence: 14 givenname: Blessing surname: Obinaju fullname: Obinaju, Blessing organization: Centre for Biophotonics, Lancaster Environment Centre, Lancaster University – sequence: 15 givenname: Ganesh D surname: Sockalingum fullname: Sockalingum, Ganesh D organization: Equipe MéDIAN-Biophotonique et Technologies pour la Santé, Université de Reims Champagne-Ardenne, UnitéMEDyC, CNRS UMR7369, UFR Pharmacie, SFR CAP-Santé FED4231 – sequence: 16 givenname: Josep surname: Sulé-Suso fullname: Sulé-Suso, Josep organization: Institute for Science and Technology in Medicine, School of Medicine, Keele University – sequence: 17 givenname: Rebecca J surname: Strong fullname: Strong, Rebecca J organization: Centre for Biophotonics, Lancaster Environment Centre, Lancaster University – sequence: 18 givenname: Michael J surname: Walsh fullname: Walsh, Michael J organization: Department of Pathology, College of Medicine Research Building (COMRB), University of Illinois at Chicago – sequence: 19 givenname: Bayden R surname: Wood fullname: Wood, Bayden R organization: Centre for Biospectroscopy and School of Chemistry, Monash University – sequence: 20 givenname: Peter surname: Gardner fullname: Gardner, Peter organization: Manchester Institute of Biotechnology (MIB), University of Manchester – sequence: 21 givenname: Francis L surname: Martin fullname: Martin, Francis L email: f.martin@lancaster.ac.uk organization: Centre for Biophotonics, Lancaster Environment Centre, Lancaster University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24992094$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | 631/92/56 Algorithms Analytical Chemistry Biological analysis Biological samples Biological Techniques Cells Chemistry Colon - pathology Computational Biology/Bioinformatics Cytology Data acquisition Data analysis Data processing Fourier transforms Histocytological Preparation Techniques Humans Infrared spectroscopy Life Sciences Medical screening Medicine Microarrays Microscopy Organic Chemistry Physiological aspects Protocol Quality control Sample preparation Software Spectroscopy, Fourier Transform Infrared - instrumentation Spectroscopy, Fourier Transform Infrared - methods |
| Title | Using Fourier transform IR spectroscopy to analyze biological materials |
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