Barzan, G.

Giovannozzi, A.

Mandrile, L.

Miozzi, L.

Noris, E.

Rossi., A.

Rotunno, S.

Sacco, A.

Vaira, A. M.

English

L. Mandrile

E. Noris

G. Barzan

A. Sacco

A. Giovannozzi

S. Rotunno

L. Miozzi

A. M. Vaira

A. Rossi.

PORTO@iris (Publications Open Repository TOrino - Politecnico di Torino)

04 August 2020POLITECNICO DI TORINORepository ISTITUZIONALEChemometric handling of Raman spectra for live systems monitoring and susceptibility tests / Mandrile, L.; Noris, E.;Barzan, G.; Sacco, A.; Giovannozzi, A.; Rotunno, S.; Miozzi, L.; Vaira, A. M.; Rossi., A.. - (2019). ((Intervento presentatoal convegno Mathematical and Statistical Methods for Metrology tenutosi a Torino nel Maggio 2019.OriginalChemometric handling of Raman spectra for live systems monitoring and susceptibility testsPublisher:PublishedDOI:Terms of use:openAccessPublisher copyright(Article begins on next page)This article is made available under terms and conditions as specified in the  corresponding bibliographic description inthe repositoryAvailability:This version is available at: 11583/2742277 since: 2019-07-16T11:39:49ZINRiMChemometric handling of Raman spectra for live systems monitoring and susceptibility tests Luisa Mandrile1, Emanuela Noris2, Giulia Barzan1, Alessio Sacco1, Andrea Giovannozzi1,  Silvia Rotunno2, Laura Miozzi2, Anna Maria Vaira2 and Andrea Rossi1 Key words: Chemometrics, Raman Spectroscopy, Principal Components Analysis, Partial least squares regression, Partial Least Squares Classification, Antibiotic susceptibility test, Virus susceptibility tests 1 The use of chemometrics for Raman spectroscopy data analysis and applications in life science Global population forecasts dictate a rapid adoption of sustainable and user-friendly  approaches to fulfil increasing food needs and improve control strategies in agro-food industry, pharmaceutical and medical field. Immunological assays, nucleic acid-based techniques (e.g. ELISA and PCR), colony forming unit test (CFU) and other classical cell vitality tests are time-consuming, destructive and expensive. Raman                                                           1  Luisa Mandrile, Istituto Nazionale di Ricerca Metrologica, Strada delle Cacce 91, 10135, Torino, Italy, e-mail: l.mandrile@inrim.it 2  Emanuela Noris, Institute for Sustainable Plant Protection, National Research Council of Italy, Strada delle Cacce 73, 10135, Torino, Italy e-mail: emanuela.noris@ipsp.cnr.it 2 Luisa Mandrile and Emanuela Noris spectroscopy (RS) combined with chemometric analysis can generate a chemical fingerprinting of a sample rapidly, at low operating costs and without sample pre-processing and destruction. [1, 2]       Here, we present two examples of application of Raman spectroscopy for live systems monitoring during acute effect of an exogenous agent, attesting the possibility to build predictive models to evaluate i) susceptibility to virus infection in plants and ii) to antibiotic treatment in bacteria cells in a defined time frame. Principal Components Analysis was used for easy data visualization and exploration. Correlations between measured spectra and the effect of the virus infection of tomato plants in the first case, and the effect of drug to biomolecular profile of E. coli in the latter were found, separating the ageing effect that occurs in biological samples over time. Subsequently, PLS-DA classification models [3] were calculated and validated to determine the sensitivity and specificity of RS for early detection of the exogenous agent. RS captured the effect of virus infection in tomato plants when the symptoms are still not evident in plant leaves, with accuracy higher than 70% and 85% for TYLCS and TSW viruses, respectively. Moreover RS allowed the detection of different drugs action on bacterial cell in 1 hour.    Figure 2: prediction results of induced resistance to ciprofloxacin (CP) provoked by triclosan (TR) with PLS-DA model of RS (3 LVs). Training (Red and black dots) and predicted (white and grey) set after a) 1 h and b)3 h of cell growth in presence and absence of antibiotics against Q residuals. References 1. Tineke V., Vercauteren A., Baeyens W., Van der Weken G., Verpoort F., Vergote G., and Remon J. P.. Applications of Raman spectroscopy in pharmaceutical analysis. TrAC 21:12 869-877 (2002). 2. Danting Y., and Ying Y. Applications of Raman spectroscopy in agricultural products and food analysis: A review. Appl Spec Rev 46: 7, 539-560 (2011) 3. Barker M, Rayens W Partial Least Squares for Discrimination. J Chemom 17, 166-173 (2003) Schröder, U‐ C, Kirchhoff J., Hübner U., Mayer G., Glaser U., Henkel T., Pfister W., Fritzsche W.,  Popp J., and Neugebauer U.. On‐ chip spectroscopic assessment of microbial susceptibility to antibiotics within 3.5 hours. J biophotonics 10: 11,  1547-1557. (2017) 

Chemometric handling of Raman spectra for live systems monitoring and susceptibility tests

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Chemometric handling of Raman spectra for live systems monitoring and susceptibility tests

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