Method of detecting the presence of a pathogen in a biological liquid
A kit, system and method for the detection of a pathogen, in particular SARS-CoV-2, by surface enhanced Raman spectroscopy (SERS) obtained from a sample brought into contact with non-magnetic native metal nanoparticles. The kit includes the non-magnetic native metal nanoparticles and a software designed to detect the presence of the pathogen in the sample.
1 . A method for detecting SARS-CoV-2 in at least one surface enhanced Raman spectroscopy (SERS) signal obtained from a sample brought into contact with non-magnetic native metal nanoparticles, the method being implemented by a computer and comprising:
a reception of each surface enhanced Raman spectroscopy (SERS) signal obtained from the sample brought into contact with the non-magnetic native metal nanoparticles;
an implementation of a classification model configured to associate each surface enhanced Raman spectroscopy signal received with at least one class representative of a presence or absence of the pathogen in the sample,
wherein the classification model is configured to apply at least one treatment relating to at least three peaks in the surface enhanced Raman spectroscopy signal among:
a peak at a Raman offset between 419 cm −1 and 459 cm −1 , or
a peak at a Raman offset between 566 cm −1 and 606 cm −1 , or
a peak at a Raman offset between 646 cm −1 and 686 cm −1 , or
a peak at a Raman offset between 719 cm −1 and 759 cm −1 , or
a peak at a Raman offset between 839 cm −1 and 879 cm −1 , or
a peak at a Raman offset between 962 cm −1 and 1002 cm −1 , or
a peak at a Raman offset between 1006 cm −1 and 1046 cm −1 , or
a peak at a Raman offset between 1121 cm −1 and 1161 cm −1 , or
a peak at a Raman offset between 1190 cm −1 and 1230 cm −1 , or
a peak at a Raman offset between 1339 cm −1 and 1379 cm −1 , or
a peak at a Raman offset between 1529 cm −1 and 1569 cm −1 , or
a peak at a Raman offset between 1591 cm −1 and 1631 cm −1 , or
a peak at a Raman offset between 1662 cm −1 and 1702 cm −1 , or
a peak at a Raman offset between 1722 cm −1 and 1762 cm −1 , or
a peak at a Raman offset between 1796 cm −1 and 1836 cm −1 , or
a peak at a Raman offset between 2058 cm −1 and 2098 cm −1 , or
a peak at a Raman offset between 2110 cm −1 and 2150 cm −1 , or
a peak at a Raman offset between 2322 cm −1 and 2362 cm −1 , or
a peak at a Raman offset between 2460 cm −1 and 2500 cm −1 .
2 . The method according to claim 1 , wherein the classification model comprises at least one among: a neural network, a random forest, a support vector machine, a relevance vector machine, a PLSDA, and/or a Bayesian model.
3 . The method according to claim 1 , comprising, between the reception and the implementation of the classification model, a preprocessing step of each surface enhanced Raman spectroscopy signal, the preprocessing step comprising the implementation of at least one of the following pretreatments: a reduction of average, a standard normal variation, normalization by the maximum, normalization by extrema, smoothing by a Savitzky-Golay algorithm, reduction or correction of baseline, a derivation of order 1 or 2.
4 . The method according to claim 1 , comprising, between the reception and the implementation of the classification model, an automatic choice of the used classification model from several predetermined classification models based on:
a form of sample collection; or
a spectrometer model delivering each surface enhanced Raman spectroscopy signal; or
data relating to a subject from whom the sample was taken; or
a sample transport medium; or
the pathogen(s) to be detected.
5 . The method according to claim 1 , wherein the reception of each surface enhanced Raman spectroscopy signal comprises:
a) the contact between said sample and non-magnetic native metal nanoparticles to obtain a solution or a suspension;
b) the deposit of said solution or suspension on a medium; and
c) the detection of each surface enhanced Raman spectroscopy signal emitted by the deposit.
6 . The method according to claim 5 , wherein the sample is dissolved before contacting a centrifugation pellet comprising said non-magnetic native metal nanoparticles.
7 . The method according to claim 1 , wherein the non-magnetic native metal nanoparticles have a diameter between 50 and 200 nm.
8 . The method according to claim 1 , wherein the non-magnetic native metal nanoparticles comprise non-magnetic nanoparticles of a first metal and non-magnetic nanoparticles of a second metal, the nanoparticles of the first metal being different from the nanoparticles of the second metal.
9 . The method according to claim 8 , wherein the non-magnetic metal nanoparticles of the first metal are gold particles and the non-magnetic metal nanoparticles of the second metal are silver nanoparticles.
10 . The method according to claim 1 , wherein the reception of each surface enhanced Raman spectroscopy signal comprises:
an excitation light emission of wavelength between 750 and 800 nm, said excitation light reaching the sample,
a capture, by a sensor or a spectrometer, of a reflected, transmitted, scattered or backscattered light by the sample while said excitation light reaches the sample.
11 . The method according to claim 10 , wherein said excitation light reaches the sample, and the spectrometer or sensor implements the capture step while the sample has been brought into contact with the non-magnetic native metal nanoparticles.
12 . A kit for detecting the presence of a pathogen in a sample by surface enhanced Raman spectroscopy (SERS), said kit comprising non-magnetic native metal nanoparticles and a software and/or software medium configured to detect the presence of said pathogen in said sample by implementing a method according to claim 1 .
13 . The kit according to claim 12 , wherein the non-magnetic native metal nanoparticles comprise non-magnetic nanoparticles of a first metal and non-magnetic nanoparticles of a second metal, the nanoparticles of the first metal being different from the nanoparticles of the second metal.
14 . The kit according to claim 13 , wherein the non-magnetic metal nanoparticles of the first metal are gold nanoparticles and the non-magnetic metal nanoparticles of the second metal are silver nanoparticles.
15 . The kit according to claim 12 , wherein the pathogen detectable is one of the elements of the group comprising viruses, prions, parasites, fungi, yeasts and bacteria and is in particular SARS-CoV-2.
16 . The kit according to claim 12 , wherein the non-magnetic native metal nanoparticles have an average diameter between 50 and 200 nm.
17 . A method detecting the presence of a pathogen in a sample by surface enhanced Raman spectroscopy (SERS), comprising detecting the presence of said pathogen in said sample with the non-magnetic native metal nanoparticles and the software and/or software medium configured to detect the presence of said pathogen in said sample of the kit according to claim 12 .
18 . The method according to claim 17 , wherein said software further provides a diagnosis of the disease related to the presence of said pathogen.