Analyses of spike protein from first deposited sequences of SARS-CoV2 from West Bengal, India

Introduction

The SARS-CoV2 (a member of Coronaviruses) outbreak occurred in Wuhan, China in the year 2019, and was recently declared a pandemic, which has affected countries worldwide. To design antiviral therapeutics/vaccines it is important to understand the genetic sequence, structure and function of the viral proteins. When a virus tries to adapt to a new environment, in a new host, in a new geographical location and a new population, it may make changes to its genetic make-up which in turn bring slight modifications in viral proteins. Such variations would help the virus to utilize the host’s machinery to best in favour virus survival and propagation. Since the host’s immune system eventually learns to identify an infecting pathogen and starts producing protective antibodies, a virus often changes its structural proteins so that it escapes the host’s immune system and continues to infect the host cells. Coronaviruses have been long known to undergo rapid mutations in its RNA genome¹. Such mutations are reflected in changes in the amino acid sequences of its structural and non-structural proteins.

The spike protein is a structural protein of SARS-CoV2 that forms a homotrimer on the surface of the vital lipid envelope². This trimer is made up of monomers consisting of S1 and S2 subunits. S1 subunit helps in attachment to the host cell receptor, while S2 subunit helps in fusion to host cell and entry. Thus, the spike protein has been an area of interest for designing vaccine and antiviral candidates against SARS-CoV2. Since the spike protein tends to mutate, it is important to obtain a broad mutation profile of this protein from extensive genome sequencing from different geographical locations of the world. Targeting areas of the spike protein that do not undergo mutation, i.e. conserved regions, would be the key to designing effective broad spectrum antivirals or vaccine.

Methods

Results and discussion

The first set of five sequencing data from clinical isolates of SARS-CoV2 from the state of West Bengal, India was submitted on 27/2/2020 by the National Institute of Biomedical Genomics (NIBMG) in collaboration with ICMR-National Institute of Cholera and Enteric Diseases (ICMR-NICED). The sequences were submitted to the GISAID database.

We downloaded all the sequences from West Bengal (Table 1) and performed a nucleotide translation to obtain respective spike protein sequences. All these spike protein sequences were first aligned in CLUSTAL Omega to check for similarities or differences. We found that at position 723, all the isolates from West Bengal except EPI_ISL_430466 had ‘T’ (other isolates had ‘I’). Also, at position 1124, two of the isolates (EPI_ISL_430468 and EPI_ISL_430464) showed mutation from ‘G’ to ‘V’. We used spike protein sequence translated from one of these sequences (EPI_ISL_430468) as representative of SARS-CoV2 spike from West Bengal for our further comparison with other states.

Since, we had access to sequences for SARS-CoV2 only from three states in India (Kerala, Gujarat and now West Bengal), we compared all those sequences to detect possible changes (Figure 1). We considered the original Wuhan sequence as the wild type for comparison. We found six different amino acid positions that were mutated in these isolates overall. We had recently published the details with respect to the spike protein mutations in Kerala³ and Gujarat isolates⁴.

Figure 1. Mutation analysis of isolates from Kolkata, Gujarat and Kerala.

(A) Multiple sequence alignment of Spike protein sequence of Kolkata isolate with sequences obtained from other parts of India. Sites of mutation are showed in Red. (B) Tabulation of amino acid mutations among isolates from kolkata. Mutations are shown in red. Number/s in parenthesis show number of osolates that showed the amino acid type. (C) Tabulation of amino acid present at the points of mutation for isolates from different parts of india.

Here, we report that in West Bengal isolates there were three mutations in the spike protein. One of these mutations was D614G in the S1 domain. This lies near the receptor bending domain at a downstream position. Another mutation, T723I lie further downstream in the S protein in the S2 domain. Mutation G1124V is the third mutation and lie in the S2 domain. While D614G was also found in the isolate from Gujarat but not in Kerala isolates, T723I and G1124V mutation were exclusively found in the isolates of West Bengal. None of the isolates from other parts of India had this mutation.

Although T723I was also exclusive for West Bengal, it appeared only in one isolate. Thus, we characterized mutation G1124V which appeared in two of the isolates. Both glycine (G) and valine (V) are non-polar amino acids with aliphatic R groups. Glycine has no side chain whereas valine is bulkier due to its side chain. A change from glycine to valine can thus potentially disrupt the local folding of the protein. For example, it was shown that G to V change in a P-glycoprotein changed its drug specificities⁶.

Secondary structure prediction showed changes in and around the site of mutation (Figure 2). In the mutant spike there was a loss of turn structure from position 1124 and addition of four helices at positions 1123, 1124, 1125 and 1126. This change in secondary structure might lead to change in function of S2. S2 helps in fusion process of the spike protein and thus mutation in S2 may have altered receptor spike interactions and thus infectivity.

Figure 2. Effect of mutation at position 1124 on secondary structure of Spike protein.

(A) Secondary structure of Spike protein of Wuhan isolate (the area around the residue 1124 has been shown); (B) secondary structure of Spike protein of Kolkata isolate showing effect of mutation on the secondary structure.

To correlate if changes in secondary structure are also reflected in the dynamics of the protein in its tertiary structure, we performed normal mode analyses and studied protein stability and flexibility. Change in vibrational entropy energy (ΔΔSVib ENCoM) between the wild type Wuhan isolate and the West Bengal isolate was -4.445 kcal.mol^-1.K^-1 (Figure 3). The ΔΔG was 0.905 kcal/mol and the ΔΔG ENCoM was 4.756 kcal/mol. All these suggested a stabilizing mutation in this type of spike. The interatomic interactions have been shown in Figure 4.

Figure 3. Δ Vibrational Entropy Energy Between Wild-Type and Mutant.

Δ Vibrational Entropy Energy Between Wild-Type and Mutant ΔΔSVib ENCoM: -4.445 kcal.mol-1.K-1. Amino acids were coloured as per the vibrational entropy change due to mutation. Blue represents rigidification of structure.

Figure 4. Interatomic interaction.

Wild-type and mutant residues are coloured in light-green and are also represented as sticks alongside with the surrounding residues which are involved on any type of interactions.

Analyses of atomic fluctuations and deformation energies showed visible changes (Figure 5). Atomic fluctuations calculate the measure of absolute atomic motion whereas deformation energies detect the measure of flexibility of a protein. Figure 5 shows the visual representations of the atomic fluctuation and deformation energies where positions that could be visibly detected to be different have been marked.

Figure 5. Visual analysis of fluctuations and deformation energies.

Magnitude of (A) atomic fluctuation and (B) deformation has been shown using thin to thick lines coloured blue (low), white (moderate) and red (high).

This is the first report of mutations of such types in the isolates of the state of West Bengal and further sequencing followed by sequence analyses would help expanding the knowledge about variations of spike protein in human SARS-CoV. These variations might lead to virus diversification and eventual emergence of variants, antibody escape mutants, strains and serotypes. Also, mutations might help the virus to expand its tissue tropism and adjust with the host environment better. Therefore, elaborate studies on sequence variations should be done, which would in turn help in better therapeutic targeting.

Data availability