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Quick sequencing offers a better chance at COVID control

A technician prepares test samples inside a Covid-19 genome sequencing laboratory at the Institute of Liver and Biliary Sciences in New Delhi, India. Credit: T. Narayan/Bloomberg via Getty Images

The SARS-CoV-2 virus has an opportunity to change every time it replicates in a host. Though not all mutations affect the ability of the virus to spread or cause disease, scientists sequence and search for the changes that increase its infectivity. These are uploaded on an open-access genomic database of the Global Initiative on Sharing All Influenza Data (GISAID).

Researchers at the Institute of Bioinformatics and Applied Biotechnology in Bangalore analysed the genomic metadata of GISAID to study if sequencing of SARS-CoV-2 genomes improved over the pandemic, whether the number of SARS-CoV-2 sequenced genomes per 1000 COVID-19 cases (sequencing efficiency) increased with time, and if the sample ‘Collection to Genome Submission Time Lag’ (CSTlag) decreased with time1.

IBAB computational evolutionary microbiologist Gaurav Sharma and his colleagues Utkarsha Mahanta and Gayatri Saberwal compared sequencing in countries of six continents to find that all of them were more efficient in 2021 than in 2020. Interestingly, many Asian countries – Nepal, Maldives, Pakistan, Bahrain, and Israel – showed an almost five-fold increase in sequencing. India and Indonesia slightly improved their SARS-CoV-2 genome surveillance from 1.2 to around 3.5 per 1000 cases, while Singapore went from 27 to 41.

Number of sequences per 1000 cases in various countries in 2020 and 2021

Country

2020

2021

USA

9.37

42.85

UK

72.13

122.42

Germany

5.68

48.70

France

5.69

13.13

Sweden

6.35

103.46

Croatia

0.57

27.18

Ghana

4.86

20.91

South Africa

6.14

8.60

Nepal

0.07

1.56

Maldives

1.38

9.62

Pakistan

0.32

1.79

Bahrain

1.62

8.91

Israel

4.26

22.50

India

1.20

3.32

Indonesia

1.18

3.57

Nigeria

4.60

21.93

Singapore

27

41

Some other studies also proved the positive impact of genome sequencing. One demonstrated that patients infected with SARS-CoV-2 strains containing the D614G mutation in the gene, that encodes for the spike protein, had higher viral loads in the upper respiratory tract2. Another reported that this mutation caused a conformational shift of the spike protein toward a state that allowed for more efficient binding with the receptor of host cells3.

Characterization of the D614G variant allowed scientists to better understand viral entry mechanisms, which could then lead to the development of therapeutic agents or vaccines that effectively block SARS-CoV-2 infection.

Such sequence information is useful for computational tools that design therapeutic interventions based on small molecules, says Rakesh K. Mishra, a geneticist and director at the Tata Institute for Genetics and Society in Bengaluru.

Some SARS-CoV-2 variants evolved and then disappeared immediately while others with key mutations adapted well, enabling their rapid spread. One such variant was Omicron which contained multiple mutations and was seen to have higher transmissibility and reinfection risk in comparison to other variants of concern4.

“Genome sequencing allows us to know what variants are circulating in the population,” says Shahid Jameel, a virologist and a fellow of the Green Templeton College at the University of Oxford, UK. “Pursued at a reasonable frequency, it allows the public health system to know which variants are emerging in the population,” he told Nature India. Knowing each variant’s unique transmission and immune evasion properties allows public health systems to respond better, Jameel says.

Sharing sequencing data with researchers also has implications for vaccine design and the use of monoclonal antibodies for treatment, according to virologist Chitra Pattabiraman, formerly at the National Institute of Mental Health and Neurosciences in Bengaluru. Alongside sequencing, it is important to submit the sequenced data to GISAID at the earliest, she says. “It is the speediest way to help track and control the spread and transmission of emerging variants.”

Analysing nearly 7 million SARS-CoV-2 samples submitted by 208 countries to GISAID, the IBAB team found that CSTlag – the time between identifying mutations and submitting them – reduced on an average from 85 days in 2020 to 19 days in 2021, meaning each sequence was submitted 78% more rapidly by 2021.

The US has sharply improved its CSTlag from 156 to 23, the UK from 26 to 9 days, and Germany from 196 to 15 days. India is at tenth place in this list having improved its CSTlag from 159 in 2020 to 66 days in 2021 – a 58% reduction in the time gap between identifying a sequence and submitting it.

“Sometimes the research based on a sequenced genome can miss something. Once it is part of the GISAID, other researchers can identify those missing mutations or variants or other important information,” Sharma said.

doi: https://doi.org/10.1038/d44151-022-00057-x

References

  1. Mahanta, U. et al. Front. Public. Health. (2022) DOI: 10.1039/fpubh.2022.887955

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  2. Korber, B. et al. Cell. 182, 812-827 (2020) DOI: 10.1016/j.cell.2020.06.043

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  3. Yurkovetskiy, L. et al. Cell. 183, 739-751 (2020) DOI: 10.1016/j.cell.2020.09.032

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  4. Chen, Z. et al. Nat. Genet. 54, 499-507 (2022) DOI: 10.1038/s41588-022-01033-y

    PubMed  Article  Google Scholar 

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