Cargando…

Probing the mutation independent interaction of DNA probes with SARS-CoV-2 variants through a combination of surface-enhanced Raman scattering and machine learning

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution has been characterized by the emergence of sets of mutations impacting the virus characteristics, such as transmissibility and antigenicity, presumably in response to the changing immune profile of the human population. The prese...

Descripción completa

Detalles Bibliográficos
Autores principales: Moitra, Parikshit, Chaichi, Ardalan, Abid Hasan, Syed Mohammad, Dighe, Ketan, Alafeef, Maha, Prasad, Alisha, Gartia, Manas Ranjan, Pan, Dipanjan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8938299/
https://www.ncbi.nlm.nih.gov/pubmed/35367703
http://dx.doi.org/10.1016/j.bios.2022.114200
_version_ 1784672523373248512
author Moitra, Parikshit
Chaichi, Ardalan
Abid Hasan, Syed Mohammad
Dighe, Ketan
Alafeef, Maha
Prasad, Alisha
Gartia, Manas Ranjan
Pan, Dipanjan
author_facet Moitra, Parikshit
Chaichi, Ardalan
Abid Hasan, Syed Mohammad
Dighe, Ketan
Alafeef, Maha
Prasad, Alisha
Gartia, Manas Ranjan
Pan, Dipanjan
author_sort Moitra, Parikshit
collection PubMed
description Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution has been characterized by the emergence of sets of mutations impacting the virus characteristics, such as transmissibility and antigenicity, presumably in response to the changing immune profile of the human population. The presence of mutations in the SARS-CoV-2 virus can potentially impact therapeutic and diagnostic test performances. We design and develop here a unique set of DNA probes i.e., antisense oligonucleotides (ASOs) which can interact with genetic sequences of the virus irrespective of its ongoing mutations. The probes, developed herein, target a specific segment of the nucleocapsid phosphoprotein (N) gene of SARS-CoV-2 with high binding efficiency which do not mutate among the known variants. Further probing into the interaction profile of the ASOs reveals that the ASO-RNA hybridization remains unaltered even for a hypothetical single point mutation at the target RNA site and diminished only in case of the hypothetical double or triple point mutations. The mechanism of interaction among the ASOs and SARS-CoV-2 RNA is then explored with a combination of surface-enhanced Raman scattering (SERS) and machine learning techniques. It has been observed that the technique, described herein, could efficiently discriminate between clinically positive and negative samples with ∼100% sensitivity and ∼90% specificity up to 63 copies/mL of SARS-CoV-2 RNA concentration. Thus, this study establishes N gene targeted ASOs as the fundamental machinery to efficiently detect all the current SARS-CoV-2 variants regardless of their mutations.
format Online
Article
Text
id pubmed-8938299
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Elsevier B.V.
record_format MEDLINE/PubMed
spelling pubmed-89382992022-03-22 Probing the mutation independent interaction of DNA probes with SARS-CoV-2 variants through a combination of surface-enhanced Raman scattering and machine learning Moitra, Parikshit Chaichi, Ardalan Abid Hasan, Syed Mohammad Dighe, Ketan Alafeef, Maha Prasad, Alisha Gartia, Manas Ranjan Pan, Dipanjan Biosens Bioelectron Article Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution has been characterized by the emergence of sets of mutations impacting the virus characteristics, such as transmissibility and antigenicity, presumably in response to the changing immune profile of the human population. The presence of mutations in the SARS-CoV-2 virus can potentially impact therapeutic and diagnostic test performances. We design and develop here a unique set of DNA probes i.e., antisense oligonucleotides (ASOs) which can interact with genetic sequences of the virus irrespective of its ongoing mutations. The probes, developed herein, target a specific segment of the nucleocapsid phosphoprotein (N) gene of SARS-CoV-2 with high binding efficiency which do not mutate among the known variants. Further probing into the interaction profile of the ASOs reveals that the ASO-RNA hybridization remains unaltered even for a hypothetical single point mutation at the target RNA site and diminished only in case of the hypothetical double or triple point mutations. The mechanism of interaction among the ASOs and SARS-CoV-2 RNA is then explored with a combination of surface-enhanced Raman scattering (SERS) and machine learning techniques. It has been observed that the technique, described herein, could efficiently discriminate between clinically positive and negative samples with ∼100% sensitivity and ∼90% specificity up to 63 copies/mL of SARS-CoV-2 RNA concentration. Thus, this study establishes N gene targeted ASOs as the fundamental machinery to efficiently detect all the current SARS-CoV-2 variants regardless of their mutations. Elsevier B.V. 2022-07-15 2022-03-22 /pmc/articles/PMC8938299/ /pubmed/35367703 http://dx.doi.org/10.1016/j.bios.2022.114200 Text en © 2022 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Moitra, Parikshit
Chaichi, Ardalan
Abid Hasan, Syed Mohammad
Dighe, Ketan
Alafeef, Maha
Prasad, Alisha
Gartia, Manas Ranjan
Pan, Dipanjan
Probing the mutation independent interaction of DNA probes with SARS-CoV-2 variants through a combination of surface-enhanced Raman scattering and machine learning
title Probing the mutation independent interaction of DNA probes with SARS-CoV-2 variants through a combination of surface-enhanced Raman scattering and machine learning
title_full Probing the mutation independent interaction of DNA probes with SARS-CoV-2 variants through a combination of surface-enhanced Raman scattering and machine learning
title_fullStr Probing the mutation independent interaction of DNA probes with SARS-CoV-2 variants through a combination of surface-enhanced Raman scattering and machine learning
title_full_unstemmed Probing the mutation independent interaction of DNA probes with SARS-CoV-2 variants through a combination of surface-enhanced Raman scattering and machine learning
title_short Probing the mutation independent interaction of DNA probes with SARS-CoV-2 variants through a combination of surface-enhanced Raman scattering and machine learning
title_sort probing the mutation independent interaction of dna probes with sars-cov-2 variants through a combination of surface-enhanced raman scattering and machine learning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8938299/
https://www.ncbi.nlm.nih.gov/pubmed/35367703
http://dx.doi.org/10.1016/j.bios.2022.114200
work_keys_str_mv AT moitraparikshit probingthemutationindependentinteractionofdnaprobeswithsarscov2variantsthroughacombinationofsurfaceenhancedramanscatteringandmachinelearning
AT chaichiardalan probingthemutationindependentinteractionofdnaprobeswithsarscov2variantsthroughacombinationofsurfaceenhancedramanscatteringandmachinelearning
AT abidhasansyedmohammad probingthemutationindependentinteractionofdnaprobeswithsarscov2variantsthroughacombinationofsurfaceenhancedramanscatteringandmachinelearning
AT digheketan probingthemutationindependentinteractionofdnaprobeswithsarscov2variantsthroughacombinationofsurfaceenhancedramanscatteringandmachinelearning
AT alafeefmaha probingthemutationindependentinteractionofdnaprobeswithsarscov2variantsthroughacombinationofsurfaceenhancedramanscatteringandmachinelearning
AT prasadalisha probingthemutationindependentinteractionofdnaprobeswithsarscov2variantsthroughacombinationofsurfaceenhancedramanscatteringandmachinelearning
AT gartiamanasranjan probingthemutationindependentinteractionofdnaprobeswithsarscov2variantsthroughacombinationofsurfaceenhancedramanscatteringandmachinelearning
AT pandipanjan probingthemutationindependentinteractionofdnaprobeswithsarscov2variantsthroughacombinationofsurfaceenhancedramanscatteringandmachinelearning