Quantitative probability estimation of light-induced inactivation of SARS-CoV-2

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dc.contributor.authorQuintana Benito, Jaime
dc.contributor.authorAlda, Irene
dc.contributor.authorAlda Serrano, Javier
dc.date.accessioned2024-03-05T20:07:47Z
dc.date.available2024-03-05T20:07:47Z
dc.date.issued2024-02-09
dc.descriptionReceived: 14 August 2023; Accepted: 07 February 2024; Published: 09 February 2024;
dc.description.abstractDuring the COVID pandemic caused by the SARS-CoV-2 virus, studies have shown the efficiency of deactivating this virus via ultraviolet light. The damage mechanism is well understood: UV light disturbs the integrity of the RNA chain at those locations where specific nucleotide neighbors occur. In this contribution, we present a model to address certain gaps in the description of the interaction between UV photons and the RNA sequence for virus inactivation. We begin by exploiting the available information on the pathogen’s morphology, physical, and genomic characteristics, enabling us to estimate the average number of UV photons required to photochemically damage the virus’s RNA. To generalize our results, we have numerically generated random RNA sequences and checked that the distribution of pairs of nucleotides susceptible of damage for the SARS-CoV-2 is within the expected values for a random-generated RNA chain. After determining the average number of photons reaching the RNA for a preset level of fluence (or photon density), we applied the binomial probability distribution to evaluate the damage of nucleotide pairs in the RNA chain due to UV radiation. Our results describe this interaction in terms of the probability of damaging a single pair of nucleotides, and the number of available photons. The cumulative probability exhibits a steep sigmoidal shape, implying that a relatively small change in the number of affected pairs may trigger the inactivation of the virus. Our light-RNA interaction model quantitatively describes how the fraction of affected pairs of nucleotides in the RNA sequence depends on the probability of damaging a single pair and the number of photons impinging on it. A better understanding of the underlying inactivation mechanism would help in the design of optimum experiments and UV sanitization methods. Although this paper focuses on SARS-CoV-2, these results can be adapted for any other type of pathogen susceptible of UV damage.
dc.description.departmentDepto. de Ă“ptica
dc.description.departmentSecciĂłn Deptal. de Ă“ptica (Ă“ptica)
dc.description.facultyFac. de Ă“ptica y OptometrĂ­a
dc.description.refereedTRUE
dc.description.sponsorshipComunidad de Madrid (España)
dc.description.statuspub
dc.identifier.citationQuintana, J., Alda, I. & Alda, J. Quantitative probability estimation of light-induced inactivation of SARS-CoV-2. Sci Rep 14, 3386 (2024). https://doi.org/10.1038/s41598-024-54006-y
dc.identifier.doi10.1038/s41598-024-54006-y
dc.identifier.officialurlhttps://doi.org/10.1038/s41598-024-54006-y
dc.identifier.relatedurlhttps://www.nature.com/articles/s41598-024-54006-y#citeas
dc.identifier.urihttps://hdl.handle.net/20.500.14352/101984
dc.issue.number3386
dc.journal.titleScientific Reports
dc.language.isoeng
dc.publisherSpringer
dc.relation.projectIDCOV20-01244-CM
dc.rightsAttribution 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject.cdu681.7.015.4
dc.subject.cdu535-31
dc.subject.cdu616.98:578.834
dc.subject.cdu614.4
dc.subject.keywordUltraviolet light
dc.subject.keywordOptical disinfection
dc.subject.keywordLight-virus interaction
dc.subject.ucmÓptica (Física)
dc.subject.ucmEnfermedades infecciosas
dc.subject.unesco2209 Ă“ptica
dc.subject.unesco2420 VirologĂ­a
dc.subject.unesco2209.22 RadiaciĂłn Ultravioleta
dc.titleQuantitative probability estimation of light-induced inactivation of SARS-CoV-2
dc.typejournal article
dc.type.hasVersionVoR
dspace.entity.typePublication
relation.isAuthorOfPublication993d54a7-f485-489e-81a9-ec91d5f4c809
relation.isAuthorOfPublicationa5f0b8a9-10aa-4bf8-9527-e94b095468b8
relation.isAuthorOfPublication.latestForDiscovery993d54a7-f485-489e-81a9-ec91d5f4c809
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