Multi-Excitation Raman Spectroscopy for Label-Free, Strain-Level Characterization of Bacterial Pathogens in Artificial Sputum Media
The current methods for diagnosis of acute and chronic infections are complex and skill-intensive. For complex clinical biofilm infections, it can take days from collecting and processing a patient’s sample to achieving a result. These aspects place a significant burden on healthcare providers, dela...
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Veröffentlicht in: | Analytical chemistry (Washington) 2022-01, Vol.94 (2), p.669-677 |
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creator | Lister, Adam P Highmore, Callum J Hanrahan, Niall Read, James Munro, Alasdair P. S Tan, Samuel Allan, Raymond N Faust, Saul N Webb, Jeremy S Mahajan, Sumeet |
description | The current methods for diagnosis of acute and chronic infections are complex and skill-intensive. For complex clinical biofilm infections, it can take days from collecting and processing a patient’s sample to achieving a result. These aspects place a significant burden on healthcare providers, delay treatment, and can lead to adverse patient outcomes. We report the development and application of a novel multi-excitation Raman spectroscopy-based methodology for the label-free and non-invasive detection of microbial pathogens that can be used with unprocessed clinical samples directly and provide rapid data to inform diagnosis by a medical professional. The method relies on the differential excitation of non-resonant and resonant molecular components in bacterial cells to enhance the molecular finger-printing capability to obtain strain-level distinction in bacterial species. Here, we use this strategy to detect and characterize the respiratory pathogens Pseudomonas aeruginosa and Staphylococcus aureus as typical infectious agents associated with cystic fibrosis. Planktonic specimens were analyzed both in isolation and in artificial sputum media. The resonance Raman components, excited at different wavelengths, were characterized as carotenoids and porphyrins. By combining the more informative multi-excitation Raman spectra with multivariate analysis (support vector machine) the accuracy was found to be 99.75% for both species (across all strains), including 100% accuracy for drug-sensitive and drug-resistant S. aureus. The results demonstrate that our methodology based on multi-excitation Raman spectroscopy can underpin the development of a powerful platform for the rapid and reagentless detection of clinical pathogens to support diagnosis by a medical expert, in this case relevant to cystic fibrosis. Such a platform could provide translatable diagnostic solutions in a variety of disease areas and also be utilized for the rapid detection of anti-microbial resistance. |
doi_str_mv | 10.1021/acs.analchem.1c02501 |
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The method relies on the differential excitation of non-resonant and resonant molecular components in bacterial cells to enhance the molecular finger-printing capability to obtain strain-level distinction in bacterial species. Here, we use this strategy to detect and characterize the respiratory pathogens Pseudomonas aeruginosa and Staphylococcus aureus as typical infectious agents associated with cystic fibrosis. Planktonic specimens were analyzed both in isolation and in artificial sputum media. The resonance Raman components, excited at different wavelengths, were characterized as carotenoids and porphyrins. By combining the more informative multi-excitation Raman spectra with multivariate analysis (support vector machine) the accuracy was found to be 99.75% for both species (across all strains), including 100% accuracy for drug-sensitive and drug-resistant S. aureus. The results demonstrate that our methodology based on multi-excitation Raman spectroscopy can underpin the development of a powerful platform for the rapid and reagentless detection of clinical pathogens to support diagnosis by a medical expert, in this case relevant to cystic fibrosis. Such a platform could provide translatable diagnostic solutions in a variety of disease areas and also be utilized for the rapid detection of anti-microbial resistance.</description><identifier>ISSN: 0003-2700</identifier><identifier>EISSN: 1520-6882</identifier><identifier>DOI: 10.1021/acs.analchem.1c02501</identifier><identifier>PMID: 34978813</identifier><language>eng</language><publisher>United States: American Chemical Society</publisher><subject>Anti-Bacterial Agents ; Bacteria ; Biofilms ; Carotenoids ; Chemistry ; Cystic fibrosis ; Diagnosis ; Drug resistance ; Excitation spectra ; Infections ; Medical personnel ; Methicillin-Resistant Staphylococcus aureus ; Microorganisms ; Multivariate analysis ; Pathogens ; Patients ; Porphyrins ; Pseudomonas aeruginosa ; Raman spectra ; Raman spectroscopy ; Respiratory diseases ; Spectroscopy ; Spectrum analysis ; Spectrum Analysis, Raman - methods ; Sputum ; Sputum - microbiology ; Staphylococcus aureus ; Staphylococcus aureus - chemistry ; Support vector machines ; Wavelengths</subject><ispartof>Analytical chemistry (Washington), 2022-01, Vol.94 (2), p.669-677</ispartof><rights>2022 American Chemical Society</rights><rights>Copyright American Chemical Society Jan 18, 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a422t-61a9e7dde463d1b75250c54bfcc0c56e37f800c9598e3eab69697b865e1803c23</citedby><cites>FETCH-LOGICAL-a422t-61a9e7dde463d1b75250c54bfcc0c56e37f800c9598e3eab69697b865e1803c23</cites><orcidid>0000-0001-8923-6666</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://pubs.acs.org/doi/pdf/10.1021/acs.analchem.1c02501$$EPDF$$P50$$Gacs$$H</linktopdf><linktohtml>$$Uhttps://pubs.acs.org/doi/10.1021/acs.analchem.1c02501$$EHTML$$P50$$Gacs$$H</linktohtml><link.rule.ids>314,780,784,2765,27076,27924,27925,56738,56788</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34978813$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lister, Adam P</creatorcontrib><creatorcontrib>Highmore, Callum J</creatorcontrib><creatorcontrib>Hanrahan, Niall</creatorcontrib><creatorcontrib>Read, James</creatorcontrib><creatorcontrib>Munro, Alasdair P. 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We report the development and application of a novel multi-excitation Raman spectroscopy-based methodology for the label-free and non-invasive detection of microbial pathogens that can be used with unprocessed clinical samples directly and provide rapid data to inform diagnosis by a medical professional. The method relies on the differential excitation of non-resonant and resonant molecular components in bacterial cells to enhance the molecular finger-printing capability to obtain strain-level distinction in bacterial species. Here, we use this strategy to detect and characterize the respiratory pathogens Pseudomonas aeruginosa and Staphylococcus aureus as typical infectious agents associated with cystic fibrosis. Planktonic specimens were analyzed both in isolation and in artificial sputum media. The resonance Raman components, excited at different wavelengths, were characterized as carotenoids and porphyrins. By combining the more informative multi-excitation Raman spectra with multivariate analysis (support vector machine) the accuracy was found to be 99.75% for both species (across all strains), including 100% accuracy for drug-sensitive and drug-resistant S. aureus. The results demonstrate that our methodology based on multi-excitation Raman spectroscopy can underpin the development of a powerful platform for the rapid and reagentless detection of clinical pathogens to support diagnosis by a medical expert, in this case relevant to cystic fibrosis. 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We report the development and application of a novel multi-excitation Raman spectroscopy-based methodology for the label-free and non-invasive detection of microbial pathogens that can be used with unprocessed clinical samples directly and provide rapid data to inform diagnosis by a medical professional. The method relies on the differential excitation of non-resonant and resonant molecular components in bacterial cells to enhance the molecular finger-printing capability to obtain strain-level distinction in bacterial species. Here, we use this strategy to detect and characterize the respiratory pathogens Pseudomonas aeruginosa and Staphylococcus aureus as typical infectious agents associated with cystic fibrosis. Planktonic specimens were analyzed both in isolation and in artificial sputum media. The resonance Raman components, excited at different wavelengths, were characterized as carotenoids and porphyrins. By combining the more informative multi-excitation Raman spectra with multivariate analysis (support vector machine) the accuracy was found to be 99.75% for both species (across all strains), including 100% accuracy for drug-sensitive and drug-resistant S. aureus. The results demonstrate that our methodology based on multi-excitation Raman spectroscopy can underpin the development of a powerful platform for the rapid and reagentless detection of clinical pathogens to support diagnosis by a medical expert, in this case relevant to cystic fibrosis. Such a platform could provide translatable diagnostic solutions in a variety of disease areas and also be utilized for the rapid detection of anti-microbial resistance.</abstract><cop>United States</cop><pub>American Chemical Society</pub><pmid>34978813</pmid><doi>10.1021/acs.analchem.1c02501</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0001-8923-6666</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Anti-Bacterial Agents Bacteria Biofilms Carotenoids Chemistry Cystic fibrosis Diagnosis Drug resistance Excitation spectra Infections Medical personnel Methicillin-Resistant Staphylococcus aureus Microorganisms Multivariate analysis Pathogens Patients Porphyrins Pseudomonas aeruginosa Raman spectra Raman spectroscopy Respiratory diseases Spectroscopy Spectrum analysis Spectrum Analysis, Raman - methods Sputum Sputum - microbiology Staphylococcus aureus Staphylococcus aureus - chemistry Support vector machines Wavelengths |
title | Multi-Excitation Raman Spectroscopy for Label-Free, Strain-Level Characterization of Bacterial Pathogens in Artificial Sputum Media |
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