Monday , June 21 2021

Emergence of new variants and commutations of SARS-CoV-2 in India



A new study has revealed genetic changes in a group of similar severe variants of acute respiratory coronavirus syndrome 2 (SARS-CoV-2) in India.

Researchers write:

“We believe our report is one of the few studies aimed at providing a comprehensive picture of the evolutionary dynamics and patterns of commutation of SARS-CoV-2 strains that have been prevalent in the Indian population throughout 2020.”

The study “Genomic Control and Philodynamic Analysis Reveals the Formation of New Patterns of Mutations and Commutations within SARS-CoV2 Versions Distributed in India” is available as a prepress at bioRxiv* server while the article is reviewed among experts.

How they did it

The researchers performed genomic surveys of 54 SARS-CoV-2 positive samples from Kolkata, the capital of the Indian state of West Bengal. Patients ranged in age from 6-88 years with an overall male to female ratio of 1.7.

The samples were collected from August 2020 to October 2020 (Term3) and cover all but one of the SARS-CoV-2 genome sequences in West Bengal.

The group notes that the genetic sequences of Term3 differ from the Indian ones because they show a higher amount of “O” and 20A.

Term3 sequences also differ from the SARS-CoV-2 genetic sequences collected from April 2020 to July 2020 (term 2). In the Term2 region, the West Bengal region had an 82% higher amount of ‘G’ and an 83% higher amount of 20A log distribution than other Indian countries. They indicate that viral plaques are slowly developing in West Bengal.

Using the GSAID database, they analyzed their samples to genomic sequences on other continents. And except for North America and Europe, GR logs predominated on all other continents in the middle and end of 2020. Although North America did not show the prevalence of GR, they did show a higher frequency of GH logs. At the end of the year, Europe showed several increases in BV klara SARS-CoV-2 in Europe.

Common mutations, co-mutations and their association with disease severity in India.  A. The most common 5 mutations and 3 commutation patterns in India.  B. Most common 5 mutations and 3 mutations in major Indian counties.  Mutations that define logs are excluded on the chart.  C. The most common are 5 mutations and 3 mutations in different types of patients.  Different color codes are used for special commutation network motifs.  The network motifs were sorted and sorted exclusively.

Common mutations, co-mutations and their association with disease severity in India. A. The most common 5 mutations and 3 commutation patterns in India. B. Most common 5 mutations and 3 mutations in major Indian counties. Mutations that define logs are excluded on the chart. C. The most common are 5 mutations and 3 mutations in different types of patients. Different color codes are used for special commutation network motifs. The network motifs were sorted and sorted exclusively.

Occurrence of mutations during a pandemic

The researchers then monitored the evolutionary changes of SARS-CoV-2 in other areas of India. Genomic control from viral samples in Indian patients showed that GR and 20B are more prevalent in India.

When studying commutation changes in Indian states and union territories, the researchers observed the occurrence of nonclades defining mutations between Term2 and Term3. These results were comparable to the onset of a pandemic (term 1). Unique combinations of these mutations were more frequently reported towards the end of 2020.

Specifically, in term 2, Indian states such as Telangana, Maharashtra, and Karnataka showed five or more commutations. At the same time, the West Bengal area and Gujarat had SARS-CoV-2 strains with less than five commutations.

By term 3, there were more Telangana and Maharashtra sequences with higher commuting residues than in West Bengal. The increase in pronounced mutations may be associated with a significant increase in the number of coronavirus cases in Maharashtra and Karnataka compared to West Bengal and Gujarat during the “Term2” and “Term3” periods.

“Therefore, a higher number of commutations in these two conditions could be associated with a higher infectivity of the strains prevalent there.”

Mutations associated with disease severity

Based on its genomic control data, the team assessed how mutations affected the severity of COVID-19 disease. 806 of the 3,277 sequences could be used, as it included the patient’s COVID-19 status and if they were deceased, symptomatic, mild, and asymptomatic.

All sequences showed mutations in D614G and NSP12. However, people who had symptomatic COVID-19 infection or died from COVID-19 were more likely to show more mutations in NS9b (P10S), N (P13L), NSP12 (A97V), and NSP3 (T1198K) than patients who had were asymptomatic.

In 2003, there was also a tri-mutation triad [NSP6(L37F)-NSP12(P323L)-Spike(D614G)] in patients who are deceased or have a mild or symptomatic COVID-19 infection.

Among the five mutations, 3 mutations were observed in mild and symptomatic patients, and only the NSP6 mutation (L37F) occurred in asymptomatic patients.

The commutation network was shown in 51% of patients with asymptomatic disease and 20.41% of mild infections. However, a network of symptoms and deaths from mutations were not observed. Over time, new networks of mutations have been observed in various counties and Indian states.

Researchers suggest that specific mutations and unique combinations of SARS-CoV-2 mutations are associated with disease severity based on results.

* Important notice

bioRxiv publishes prior scientific reports that have not been peer reviewed and should not be considered definitive, guide clinical practice / health-related behavior, or treat it as established information.


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