Recurrent emergence and transmission of a SARS-CoV-2 Spike deletion ΔH69/ΔV70


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SARS-CoV-2 Spike amino acid replacements in the receptor binding domain (RBD) occur relatively frequently and some have a consequence for immune recognition. Here we report recurrent emergence and significant onward transmission of a six nucleotide deletion in the Spike gene, which results in loss of two amino acids: ΔH69/ΔV70. Of particular note this deletion often co-occurs with the receptor binding motif amino acid replacements N501Y, N439K and Y453F. In addition, we report a sub-lineage of over 350 sequences bearing seven spike mutations across the RBD (N501Y, A570D), S1 (ΔH69/V70) and S2 (P681H, T716I, S982A and D1118H) in England. Some of these mutations have possibly arisen as a result of the virus evolving from immune selection pressure in infected individuals. Enhanced surveillance for the ΔH69/ΔV70 deletion with and without RBD mutations should be considered as a priority.


SARS-CoV-2’s Spike surface glycoprotein engagement of ACE2 is essential for virus entry and infection1, and the receptor is found in respiratory and gastrointestinal tracts2. Despite this critical interaction and related mutational constraints, it appears the RBD can tolerate mutations in this region3,4, raising the real possibility of virus escape from vaccines and monoclonal antibodies. Spike mutants exhibiting reduced susceptibility to monoclonal antibodies have been identified in in vitro screens5,6. Some of these have been found in clinical isolates7. The unprecedented scale of whole-genome SARS-CoV-2 sequencing has enabled identification and epidemiological analysis of transmission. As of December 11th’ there were 246,534 SARS-CoV-2 sequences available in the GISAID initiative (

We recently documented de novo emergence of antibody escape mediated by Spike in an individual treated with convalescent plasma (CP), on the background of D614G8. Similarly, deletions in the NTD have been reported to provide an escape for N-Terminal Domain-specific neutralizing antibodies11. Dynamic changes in the prevalence of Spike variants ΔH69/ΔV70 (an out of frame deletion) and D796H variant followed repeated use of CP, and in vitro the mutant displayed reduced susceptibility to the CP and multiple other sera, whilst retaining infectivity comparable to wild type8. We hypothesized that Spike ΔH69/ΔV70 arises either as a compensatory change and/or antibody evasion mechanism as suggested for other NTD deletions1, and therefore aimed to characterize specific circumstances around the emergence of ΔH69/ΔV70 globally. Here we analyzed the publicly available GISAID data for circulating SARS-CoV-2 sequences containing ΔH69/ΔV70.


We have presented data demonstrating multiple, independent, and circulating lineages of SARS-CoV-2 variants bearing a Spike ΔH69/ΔV70. This deletion spanning six nucleotides, is mostly due to an out of frame deletion of six nucleotides, has frequently followed receptor binding amino acid replacements (N501Y, N439K and Y453F that have been shown to reduce binding with monoclonal antibodies) and its prevalence is rising in parts of Europe, with the greatest increases since August 2020.

A recent analysis highlighted the potential for enhanced transmissibility of viruses with deletions in the N terminal domain, including ΔH69/ΔV7011. The potential for SARS-CoV-2 mutations to rapidly emerge and fix is exemplified by D614G, an amino acid replacement in S2 that alters linkages between S1 and S2 subunits on adjacent protomers as well as RBD orientation, infectivity, and transmission1214. The example of D614G also demonstrates that mechanisms directly impacting important biological processes can be indirect. Similarly, a number of possible mechanistic explanations may underlie ΔH69/ΔV70. For example, the fact that it sits on an exposed surface might be suggestive of immune interactions and escape, although allosteric interactions could alternatively lead to higher infectivity.

The finding of a sub-lineage of over 350 sequences bearing seven spike mutations across the RBD (N501Y, A570D), S1 (ΔH69/ΔV70) and S2 (P681H, T716I, S982A and D1118H) in England requires careful monitoring. The detection of a high number of novel mutations suggests this lineage has either been introduced from a geographic region with very poor sampling or viral evolution may have occurred in a single individual in the context of a chronic infection8.

Given the emergence of multiple clusters of variants carrying RBD mutations and the ΔH69/ΔV70 deletion, limitation of transmission takes on a renewed urgency. Concerted global vaccination efforts with wide coverage should be accelerated. Continued emphasis on testing/tracing, social distancing and mask wearing are essential, with investment in other novel methods to limit transmission15. Detection of the deletion by rapid diagnostics should be a research priority as such tests could be used as a proxy for antibody escape mutations to inform surveillance at global scale.

Conflicts of interest

RKG has received consulting fees from UMOVIS lab, Gilead Sciences and ViiV Healthcare, and a research grant from InvisiSmart Technologies.


Phylogenetic Analysis

All available full-genome SARS-CoV-2 sequences were downloaded from the GISAID database ( on 26th November. Duplicate and low-quality sequences (>5% N regions) were removed, leaving a dataset of 194,265 sequences with a length of >29,000bp. All sequences were realigned to the SARS-CoV-2 reference strain MN908947.3, using MAFFT v7.473 with automatic flavour selection and the –keeplength –addfragments options17. Major SARS-CoV-2 clade memberships were assigned to all sequences using the Nextclade server v0.9 (

Maximum likelihood phylogenetic trees were produced using the above curated dataset using IQ-TREE v2.1.2 18. Evolutionary model selection for trees were inferred using ModelFinder 19 and trees were estimated using the GTR+F+I model with 1000 ultrafast bootstrap replicates20. All trees were visualised with Figtree v.1.4.4 (, rooted on the SARS-CoV-2 reference sequence and nodes arranged in descending order. Nodes with bootstraps values of <50 were collapsed using an in-house script.

Pseudotype virus preparation

Viral vectors were prepared by transfection of 293T cells by using Fugene HD transfection reagent (Promega). 293T cells were transfected with a mixture of 11ul of Fugene HD, 1μg of pCDNAΔ19Spike-HA, 1ug of p8.91 HIV-1 gag-pol expression vector22,23, and 1.5μg of pCSFLW (expressing the firefly luciferase reporter gene with the HIV-1 packaging signal). Viral supernatant was collected at 48 and 72h after transfection, filtered through 0.45um filter and stored at −80°C as previously described24. Infectivity was measured by luciferase detection in target TZMBL transduced to express TMPRSS2 and ACE2.

Normalisation of virus titre by SG-PERT to measure RT activity in lentivirus preparation

Supernatant was subjected to SG-PERT as previously described.25

Homology modelling

Prediction of conformational change in the spike N-terminal assessed by homology modelling of the NTD (residues 14-306) predicted by homology modelling using SWISS-MODEL26 with template chain A of PDB 7C2L27 and aligned with 7C2L using PyMOL. Figures prepared with PyMOL (Schrödinger) using PDBs 7C2L, 6ZGE28 and 6ZGG28.

About KSRA

The Kavian Scientific Research Association (KSRA) is a non-profit research organization to provide research / educational services in December 2013. The members of the community had formed a virtual group on the Viber social network. The core of the Kavian Scientific Association was formed with these members as founders. These individuals, led by Professor Siavosh Kaviani, decided to launch a scientific / research association with an emphasis on education.

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FULL Paper PDF file:

Recurrent emergence and transmission of a SARS



SA KempRP DatirDA CollierIATM FerreiraA CarabelliW HarveyDL RobertsonRK Gupta




Recurrent emergence and transmission of a SARS-CoV-2 Spike deletion ΔH69/ΔV70

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Professor Siavosh Kaviani was born in 1961 in Tehran. He had a professorship. He holds a Ph.D. in Software Engineering from the QL University of Software Development Methodology and an honorary Ph.D. from the University of Chelsea.

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Somayeh Nosrati was born in 1982 in Tehran. She holds a Master's degree in artificial intelligence from Khatam University of Tehran.

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Nasim Gazerani was born in 1983 in Arak. She holds a Master's degree in Software Engineering from UM University of Malaysia.