High prevalence of an alpha variant lineage with a premature stop codon in ORF7a in Iraq, winter 2020-2021.

Since the first reported case of coronavirus disease 2019 (COVID-19) in China, SARS-CoV-2 has been spreading worldwide. Genomic surveillance of SARS-CoV-2 has had a critical role in tracking the emergence, introduction, and spread of new variants, which may affect transmissibility, pathogenicity, and escape from infection or vaccine-induced immunity. As anticipated, the rapid increase in COVID-19 infections in Iraq in February 2021 is due to the introduction of variants of concern during the second wave of the COVID-19 pandemic. To understand the molecular epidemiology of SARS-CoV-2 during the second wave in Iraq (2021), we sequenced 76 complete SARS-CoV-2 genomes using NGS technology and identified genomic mutations and proportions of circulating variants among these. Also, we performed an in silico study to predict the effect of the truncation of NS7a protein (ORF7a) on its function. We detected nine different lineages of SARS-CoV-2. The B.1.1.7 lineage was predominant (80.20%) from February to May 2021, while only one B.1.351 strain was detected. Interestingly, the phylogenetic analysis showed that multiple strains of the B.1.1.7 lineage clustered closely with those from European countries. A notable frequency (43.33%) of stop codon mutation (NS7a Q62stop) was detected among the B.1.1.7 lineage sequences. In silico analysis of NS7a with Q62stop found that this stop codon had no considerable effect on the function of NS7a. This work provides molecular epidemiological insights into the spread variants of SARS-CoV-2 in Iraq, which are most likely imported from Europe.

Introduction

In late December 2019, an outbreak of pneumonia of unknown etiology was announced in Wuhan, China. A relative unknown coronavirus named “Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)” was then identified as the causative agent of COVID-19 [1]. On March 11, 2020, the WHO declared the COVID-19 outbreak a pandemic [2], affecting humans worldwide [3]. SARS-CoV-2 is highly infectious and has caused over 234 million confirmed cases of COVID-19 globally, including over 4.8 million deaths reported by the WHO as of October 3, 2021.

In Iraq, the first SARS-CoV-2 case was diagnosed in February 24, 2020 [4]. Since then, over 695,489 cases and more than 13,000 deaths were confirmed by the end of February 2021 [5]. The epidemiological situation displayed a slight improvement at the end of the first wave (week 1, 2021). However, the number of cases has risen with the beginning of the second wave in week 5, 2021 [6].

Emerging RNA viruses are a global health concern due to their potentially high transmission rate, high mutation rates, and aggressive competition to host cellular functions. As a result of SARS-CoV-2 mutation dynamics, several variants of concern have emerged, of which there is evidence of increased transmission, a surge in hospitalization, critical care unit admissions, and fatalities to varying degrees compared with the wild-type Wuhan-1 strain [7, 8], and/or evidence of decreased neutralization by antibodies raised against previous infection or vaccine [9]. In particular, amino acid replacements in the spike protein can lead to enhanced binding with the host ACE2 receptor causing increased transmissibility and potentially higher virulence [5, 10]. Similar to influenza A virus and, to a lesser extent, seasonal human coronaviruses, SARS-CoV-2 can be expected to accumulate adaptive amino acid replacements in its glycoprotein, resulting in antigenic drift [11]. However, due to the biological differences in influenza A virus (IAV) (which is a segmented negative-stranded RNA virus with a higher overall evolutionary rate compared to coronaviruses) and seasonal coronaviruses, (which have been circulating among the human population for a long time), genomic surveillance of SARS-CoV-2 is needed to detect and assess the effect of such mutations [11]. The global effort for SARS-CoV-2 sequencing has led to efficient tracking of circulating lineages as well as tracking of mutations that may lead to changes in vaccine efficacy, PCR detection, and virus transmissibility [12, 13]. Therefore, surveying the molecular epidemiology/spatiotemporal changes in the SARS-CoV-2 genome and understanding its mutations are important. Yet, there is a significant underrepresentation of SARS-CoV-2 sequences from middle- and low-income countries in the global dataset [14].

Recently, four variants have been identified by the WHO to be of particular concern (VOCs): Alpha variant (B.1.1.7), first reported in the UK; Beta (B.1.351), first reported in South Africa in October 2020; P.1, a descendant of variant Gamma (B.1.1.28), first reported in Brazil, and Delta (B.1.617.2), first reported in India [15]. Only a limited number of SARS-CoV-2 sequences are currently available from Iraq (https://www.gisaid.org/). The first sequence of Iraqi patients available from the first wave showed the presence of a GH clade with the D614G mutation [16]. In the current study, we sequenced 76 SARS-CoV-2 genomes to produce baseline data for the genomic surveillance of SARS-CoV-2 in Iraq. Our work summarizes sequences, emerging mutations, and the evolutionary relationships of SARS-CoV-2 in Iraq between December 2020 and February 2021.

Materials and methods

Sampling

Combined naso- and oropharyngeal swabs were collected from 76 patients (46 males and 30 females, age ranging between 13 and 85 years) in Samawa, Iraq (31.3188° N, 45.2806° E) during the second epidemic wave of COVID-19 in Iraq (between December 27, 2020 and February 28, 2021). Of these patients, five (6.6%) died, eight (10.5%) had severe disease, and the remaining 63 (82.9%) had mild to moderate infections. The samples were analyzed with STAT-NAT COVID-19 MULTI real-time PCR kits (Sentinel, Milano, Italy), based on two targets in RdRP and Orf1b genes, to detect the presence of SARS-CoV-2. The real-time PCR assay was conducted using the Mx3000P qPCR system (Agilent Technologies, Waldbronn, Germany). A total of 76 samples that had a high copy number of the virus (Ct values <24) were selected for whole genome sequencing.

The study was conducted according to the guidelines of the declaration of Helsinki and was approved by the scientific research ethics committee of Al Muthanna University within the collaborative protocol of joint work between the College of Science and Public Health Department, Al-Muthanna Directorate (July 30, 2020–8928). All participants provided written informed consent and agreed to use their medical records for research purposes.

SARS-CoV-2 sequencing

RNA isolation was carried out using TRIzol reagent (ThermoFisher Scientific, MA, USA) from a viral transport media (VTM) sample (3:1 ratio) according to the manufacturer’s procedure. The LunaScript RT Super Mix Kit (New England Biolabs, UK) was used for first-strand cDNA synthesis. A multiplex PCR approach following the ARTIC protocol was used to amplify the viral genome using Q5 High Fidelity DNA Polymerase (New England BioLabs, UK). The NEBNext Ultra II library prep kit was used for Illumina sequencing library preparation. The libraries were quantified using the Qubit 4 with the dsDNA High Sensitivity Kit (ThermoFisher Scientific, MA, USA).

High throughput sequencing was performed using the Illumina NovaSeq 6000 system with a read length of 250 bp, which produced a range of 1.3 to 3.3 million paired-end sequence reads per sample. Additionally, sequencing reads with low-quality (quality score <30) and short sequence (<50 nt) were removed using Trimmomatic [17], assembled using BWA-MEM [18], variant called using LoFreq [19], and consensus called using SAMtools [20], implemented in the HaVoC pipeline [21].

Genome sequence analysis

Mutation analysis of the SARS-CoV-2 genome was interpreted using the GISAID CoVsurver “CoVsurver enabled by GISAID” [22] and Coronapp web application [23]. Lineage and clade assignment were identified using Pangolin (version v.3.1.7) [24] and the Nextstrain web server [25].

Homology structure of mutant ORF7a and molecular docking

The 3D model of the mutant ORF7a was built using the Swiss-model web server, and the crystal structure of ORF7a (pdb:7ci3) was used as a template. Structural comparison was performed between the selected template and the built model to assign their similarity and dissimilarity using TM-align [26] and FATCAT web tools [27]. The PROCHECK web server was used to validate the best-fit model based on the stereochemical properties and geometry of the structure [28]. The quality of the model was evaluated by establishing a plot between phi and psi of the polypeptide residues using the Ramachandran plot server [29]. Subsequently, the model structure was refined using a 3D refine web server [30]. Finally, the refined model structure was prepared for docking by adding polar hydrogen atoms and Gasteiger charges using the Autodock tool 1.5.6 [31]. The model, along with the wild ORF7a, was subjected to the HADDOCK 2.4 web server to investigate the protein-protein interactions [32].

Phylogenetic tree

Genome sequence alignment was performed using alignment of multiple complete SARS-CoV-2 genomes (MAFFT online version April 11, 2020) [33]. To analyze the SARS-CoV-2 genome samples derived from the Iraqi patients in a phylogenetic relatedness, a data set of 146 available SARS-CoV-2 complete genomes from different countries was collected from GISAID available on May 25, 2021 (S1 Table). The phylogenetic tree was mapped by a maximum likelihood estimation using a fit substitution model (ModelFinder) and replicate number with 1000 bootstrap on IQ-TREE (version: 1.6.10) [34] with ultrafast bootstrap support. ITOL v6 tools [35] were used for the visualization of the phylogenetic tree.

Results

The COVID-19 pandemic caused by SARS-CoV-2 has caused significant morbidity and mortality worldwide. During the first wave in Iraq, (February–December 2020), implementation of the restrictions (lockdowns) was related to a significant reduction in daily reported cases and mortality, followed by phased relaxation in restrictions. During the second wave (Fig 1), the cumulative number of cases reached more than a million by late May 2021 [6].

Fig 1

COVID-19 cases/week and fatalities/week rates during first and second waves in Iraq [6].

Genetic clades and lineages of SARS-CoV-2

We identified nine different genetic lineages, including two variants of concern: B.1.1.7 (Alpha variant) and B.1.351 (Beta variant), in Iraq. Among the sequenced samples, alpha variant B.1.1.7 (n = 61, 80.2%) was the most prevalent lineage, whereas only one B.1.351 was detected (n = 1, 1.3%). Seven other SARS-CoV-2 lineages were detected: B (1.3%), B.1.1 (7.8%), B.1.177.21 (1.3%), B1.36 (1.3%), B.1.621.1 (1.3%), B.1.1.374 (1.3%), and B.1.438 (3.9%) (Fig 2).

Fig 2

Distribution of GISAID clades (a) and Pango lineages (b) of the Iraqi sequenced strains.

Lineages B.1.1.7 and genetic clades GR and GRY show the most prevalent in SARS-CoV-2 strains.

The first designation of the B.1 lineage was reported in Iraq on June 30, 2020 [16]. Our results suggest turnover of circulating lineages, resulting as the dominance of the Alpha variant (B.1.1.7) during the last three months of sampling (December–February 2021).

Genomic mutation analysis

Analysis of the amino acid changes between SARS-CoV-2 strains in this study and the reference genome of virus EPI_ISL_402124 (hCoV-19/Wuhan/WIV04/2019) identified numerous mutations detected in the 5’UTR, NSP2, NSP3, NSP4, NSP6, NSP12b, NSP13, NSP15, NSP16, Spike, ORF6, ORF7, ORF8, 3’UTR, and N.

Multiple spike protein mutations

The most common cluster of spike protein mutations were H69del, V70del, Y144del, A570D, D614G, P681H, T716I, S982A, and D1118H, which were detected in both GRY (n = 33, 43.4%) and GR (n = 34, 38.1%) (S2 Table).

The most notable strain in this study, one out of 76, was identified as a Beta variant, B.1.351 lineage with spike mutation profile: D80A, D215G, L242del, A243del, L244del, E484K, N501Y, D614G, and A701V, which are linked to the South African variant (20H/501Y.V2). In addition, spike mutations A222V and L18F were found in the Iraqi strain of clade O (n = 1, 1.3%). Using the web application Coronapp [22], the amino acid change D614G in the spike glycoprotein was detected at a high frequency of sequences (n = 73, 96%) (Fig 3).

Fig 3

Frequency of spike mutations in 76 SARS-CoV-2 genomes provided datasets.

D614G with the most frequent mutation appears in 73 of the original spike proteins data set. Red-dots indicate amino acid replacement mutations and blue-dots indicate silent mutations.

In addition, a rare amino acid change S605A, which is located in the S1 subunit of the spike protein, was detected in one of the sequenced viruses (EPI_ISL_1524356) According to GISAID data (accessed in May 2021), this amino acid substitution has been reported in three strains, one from Iraq in this study and two from India and the USA.

Novel aa changes

Among the detected mutations, four novel aa changes were identified (E45V/NSP3, M41K/NSP16, W128M/NS3, and V256D/NS3). In this study, the collected strains that individually carried these amino acid changes were EPI_ISL_2467922, EPI_ISL_2467921, EPI_ISL_1524366, and EPI_ISL_2467913, respectively.

NS7a Q62stop

Amino acid change NS7a Q62stop occurred in 26 strains sequenced in this study (S3 Table) and recorded in 77 countries before.

Deletion mutations

Are shown in Fig 4, comprising high frequencies of S106, G107, and F108del in NSP6 (n = 62, 81.6%), spike H69del (n = 53, 69.7%), and Y145del (n = 51, 67.1%).

Fig 4

Deletion mutations recorded in 67 of genomic SARS-CoV-2 sequences.

Molecular docking of ORF7a stop mutation

We found a high prevalence of premature stop codon Q62stop among the Iraqi Alpha variant strains. SARS-CoV-2 ORF7a is a transmembrane protein (type I) composed of 122 amino acids (15, 81, 21, and 5 amino acids composed to N-terminal, luminal domain, transmembrane segment, and cytoplasmic tail, respectively). It has been reported [36] that this accessory protein modulates the immune response of the host by binding with the host lymphocyte function-associated antigen I (LFA-1). Previous studies have suggested that the amino acids T39, E41, N43, Q62, A66, and K72 play a key role in the function of ORF7a [36]. Among these six active residues, two (A66 and K72) were truncated by a premature stop codon. The truncated amino acids are mainly located in one β sheet strand (βG) in the ectodomain. Only four amino acids are located in the β sheet strand βf (Fig 5). To predict the potential effect of the stop codon (Q62*) on the function of the ORF7a protein, we constructed a 3D model of the mutant ORF7a. The crystal structure of ORF7a (PDB: 7ci3) was used as the template. The crystal structure (PDB: 3f78) of LFA-1 was also used in the molecular docking simulation. The similarity and dissimilarity between the selected template and model were performed using TM-align and FATCAT, where the optimal structural similarity was evaluated based on the obtained TM score (0.70, TM-score > 0.5, indicating that the two proteins have the same fold). A flexible protein structure comparison between the model and template was achieved using FATCAT, where the obtained p-value (1.55e-15) and RMSD (0.06 Å) indicate that the two protein structures are significantly similar. After validation, quality check, adding polar hydrogen atoms, and adding Gasteiger charge of the selected model, it was then subjected to molecular docking alongside the wild ORF7a to assess the protein-protein interaction of ORF7a and LFA-1 I-domain (pdb: 7ci3). The latter is located on the cell membrane of human leukocytes, which is the target of ORF7a (Fig 5). The molecular docking results suggested that there was no considerable difference in the binding affinity of the mutant and wild ORF7a, and the HADDOCK scores were -67.0 and -63.6 for mutant and wild ORF7a, respectively (Table 1). The visualization of the active residue interactions showed that the functional amino acids Glu41, Gly42, Thr39. and Gly38 were contributing to hydrogen bonding with LFA-1 in both ORF7a structures (Fig 5), while the contribution of Ala66 was absent in the mutant structure.

Fig 5

The overall structure and protein-protein interactions of the ORF7a-LFA-1 complex for (a) wild ORF7a, (b) mutant ORF7a, and (c) LFA-1 superposition to wild ORF7a (Yellow) and mutant (Blue), with the truncated region highlighted in turquoise.

Table 1

ORF7a-LFA-1 interaction score for both wild and mutant ORF7a protein.

	Wild ORF7a	Mutant ORF7a
HADDOCK score	-67.0 +/- 7.4	-63.6 +/- 3.2
Cluster size	7	11
RMSD from the overall Lowest-energy structure	0.9 +/- 0.5	1.4 +/- 1.0
Van der Waals energy	-39.0 +/- 5.2	-38.3 +/- 2.7
Electrostatic energy	-157.4 +/- 9.9	-148.5 +/- 8.7
Desolvation energy	0.9 +/- 1.8	0.9 +/- 2.5
Restraints violation energy	25.1 +/- 14.8	34.6 +/- 24.9
Buried Surface Area	1276.1 +/- 64.2	1248.8 +/- 61.9
Z-Score	-2.1	-1.7

The phylogenetic tree confirmed the presence of different lineages belonging to multiple clusters (Fig 6). Seventy-six strains from the Iraqi population were distributed to nine different SARS-CoV-2 lineages, including B, B.1.1, B.1.177.21, B.1.621.1, B.1.1.374, B.1.351, B.1.1.7, B1.36, and B.1.438 corresponding to clades L, O, G, GH, GR, and GRY. The Iraqi strains of lineage B.1.1.7 were split into multiple sub-clusters most likely reflecting a large number of transmission chains in Iraq.

Fig 6

Maximum-likelihood phylogenetic tree based on complete genomic sequences of SARS-CoV-2 constructed from 150 complete genome sequences from GISAID accessed 25 May 2021 and 76 sequences (yellow color) from Iraq.

B.1.1.7 was observed to split into GRY and GR and it was dominated by viruses as the largest clusters. Replicate number with 1,000 bootstrap on IQ-TREE.

Discussion

Complete-genome sequencing and phylogenetic analysis of SARS-CoV-2 strains is an essential approach for tracking the virus evolution and understanding the circulation of SARS-CoV-2 variants in Iraq. However, there is little genetic information about the SARS-CoV-2 outbreak in Iraq. Therefore, the current study aimed to provide some rudimentary information about the genotypes of SARS-CoV-2 that are circulating in the country.

In this analysis, 76 SARS-CoV-2 complete genomes were sequenced from Iraq. From these genomes, we identified nine lineages. Of these, four genome sequences accompanied four novel mutations (A2853T, T20780A, TG25774AT, and T26159A) that caused a change in the amino acids E45V (NSP3), M41K (NSP16), W128M (NS3), and V256D (NS3). As shown in resolved structures of proteins from related strains, the position at NSP16 that has the aa change M41K is incorporated in ligand binding and viral oligomerization interfaces. Also, the aa change W128M (NS3) is involved in the host cell protein/RNA interaction of SARS-CoV-2 [22], while the effect of the remaining mutations E45V (NSP3) and V256D (NS3) has not yet been investigated.

As expected, most (n = 73, 96%) of the sequences from the second epidemic wave in Iraq contained the amino acid replacement D614G in the spike proteins (Fig 3). D614G was the first mutation in the spike glycoprotein that was first identified in Germany in January 2020 and became the dominant mutation in all the circulating strains worldwide by June 2020 [37].

The first SARS-CoV-2 genome sequence was reported on June 30, 2020, during the first wave occurrence in Iraq and belonged to the B.1/GH clade. According to the clade distribution, this clade diminished during the second wave. The B.1.1.7/GR and GRY clades were the most prevalent, which is consistent with the global distribution of SARS-CoV-2 clades in different countries.

Here, we report the first confirmed case of Alpha/B.1.1.7 variant of concern in Iraq (EPI_ISL_1524332), in a sample collected in December 27, 2020, followed by the recording of 60 cases (GISAID). Since then, the number of infected cases has risen to over seven thousand cases per day. This is likely due to the emergence of this variant, which is characterized by high transmissibility and pathogenicity.

The Beta variant (B.1.351) was first reported in South Africa in October 2020, and concerns about this variant are associated with high transmissibility, pathogenicity, and the limited protection of some vaccines against the infection [38]. Interestingly, we identified one strain belonging to B.1.351 for the first time in Iraq on February 26, 2021, which was collected from a patient without a history of travel, suggesting that this variant has been circulating locally before this date.

The Mu variant (B.1.621) has a set of interested mutations which raises the controversy about it has potential resistance to currently available COVID-19 vaccines (closer to what was raised about B.1.351) [39]. The Mu variant was detected in one Iraqi sample in February 2021, about a month after it was first emerged in Colombia.

Furthermore, we analyzed mutation profiles in the spike proteins of the alpha variant (B.1.1.7), showing that there is a genomic diversity of this variant in Iraq, which could be attributed to a variety of infection sources. It has been reported that the deletion 69–70 in the S protein causes a negative result from RT-PCR assays specific target for S-gene [40]. This specific deletion has occurred at high frequency in different countries and is currently geographically widespread. According to our results, this deletion was identified in 53 strains among 61 of the Alpha variant (Fig 4). In addition to this deletion, a cluster of aa mutations (Y144del, N501Y, A570D, D614G, P681H, T716I, S982A, and D1118H) were noticed in the spike proteins of the strains belonging to the Alpha variant (S2 Table). Fortunately, most of these aa changes are located outside the RBD; hence, they likely do not affect vaccine efficacy. On the other hand, a rare spike mutation (S605A) was detected in one strain (EPI_ISL_1524356). It has been reported that this mutation leads to the removal of a potential N-glycosylation site at position 603, where the motif at positions 603–605 changes from NTS (glycocylated) to NTA (non-glycocylated) and may also affect the antigenic properties of the virus “CoVsurver enabled by GISAID”. Contrastingly, we detected a stop codon mutation (Q62*) at the ORF7a (NS7a) coding region (27577) in most of the Iraqi strains belonging to the Alpha variant, resulting in a truncated NS7a protein. The accessory protein ORF7 of SARS-CoV-2 is involved in modulation of host immune responses [36]. This motivated us to use an in silico approach to investigate the effect of Q62* on the function of NS7a using molecular docking scores (Table 1). The results predicted that NS7a was still able to bind to its target (LFA-1). Consistently, some strains with Q62* were derived from patients with severe infections, suggesting that truncated NS7a may not reduce the pathogenicity of the virus. Nevertheless, there is a possibility that the Q62 stop mutation affects ORF7a function, as Ongaro et al. computationally explored additional possible binding motifs in Orf7a for LFA-1, and they concluded in their study that the different binding modes of ORF7a cannot be ruled out [41]. Therefore, in vitro studies are required to explore the effect of the stop codon Q62* on the function of ORF7a.

The phylogenetic tree indicated that Iraqi B.1.1.7 strains form several subclusters, suggesting multiple introductions followed by local transmission, and most of the Iraqi strains clustered with the European strains, which may either reflect true importations or be due to unequal sampling efforts.

Conclusions

The present study has a limited sample size, which may not represent the complete genomic diversity of SARS-CoV-2 in Iraq. It should be noted that the detected genomes may represent only locally distributed viral variations during the second epidemic wave, and the total diversity of SARS-CoV-2 circulating in Iraq is most likely significantly higher. Sequence analysis showed the transformation of the previously circulating strains from the first wave to the dominance of Alpha variants that most likely surged during the second epidemic wave, as in most other countries. In addition, one Beta variant (B.1.351) was detected. Furthermore, we detected a prevalent NS7a Q62stop mutation among the Alpha variant strains in Iraq. In silico analysis suggested that there was no considerable difference in the binding affinity of mutant and wild NS7a to LFA-I, however, this mutation may have an effect on the binding affinity of NS7a towards another targets, especially there may be another targets that may interact directly or indirectly with NS7a, therefore more investigation is needed to explore the effect of Q62stop mutation on the function of NS7a protein.

Acknowledgement to the contributors of the SARS-CoV-2 sequences used in this study.

(DOCX)

Click here for additional data file.

A set of aa changes located in spike.

(DOCX)

Click here for additional data file.

GenBank accession numbers of SARS-CoV-2 strains analyzed in this study.

(DOCX)

Click here for additional data file.

11 Jan 2022

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Reviewer #1: The manuscript represents a welcome contribution to the analysis of circulating SARS-CoV-2 variants and strains. The laboratory and analytical tools are adequate and the description of the work is, on the whole, clear. The major drawback is the limited number of sequences generated and analyzed which cannot be representative to the actual population of strains circulating at the time in the country. There is no information about the selection criteria for the samples that were analyzed either; some of the comments in the discussion chapter as well as in conclusions are therefore overstated. The manuscript offers only a limited view of the circulating sequences in Iraq at the time; the text should be correspondingly changed to reflect this.

Specific comments:

Lines 33-35: analysis of only 76 genomes cannot contribute to understanding the molecular epidemiology of the second COVID-19 wave in Iraq.

Line 54: there is not enough data to support the statement that the developing countries have been selectively affected

Line 67: there is not enough evidence of increased severity of disease in VOCs.

Sampling: what are the selection criteria for the 76 samples? A “high copy number” is mentioned; what was the threshold Ct in the particular RT-PCR setting?

Fig 6: the distribution of lineages in the tree is not clearly enough represented and colored

Lines 304-306: possible consequences of the novel mutations should be further discussed.

Lines 368-369: only a very limited sample of genomic sequences of SARS-CoV-2 from Iraq are actually reported.

Reviewer #2: Observations:

-On line 42, the authors state that there is a high frequency of this stop codon mutation (88%). However, they also state (line 239) that this mutation occurred in 26 strains as in Supplementary table S3. Therefore, the authors need to either explain the difference or to modify accordingly on this line to: 34.21% if related to the all 76 sequenced strains, or to 43.33% if related to the 60 B.1.1.7 strains only.

-On line 130, the authors state that the NovaSeq system produced 1.222.270 reads – I guess this is the average per sample? Otherwise, if compared to the 76 sequenced samples, the average would be about 16k reads per sample, which is very low. Novaseq generates plenty of data if there’s nothing wrong with the samples to be sequenced.

-On lines 132 to 133, there should be “assembled”, “called” and “called”.

-On line 211, the authors state that there are 33 strains that belong to GRY and 29 that belong to GR. In the Supplementary table S2 there are 4 other strains that belong to GH and 1 to O clade, therefore totalling 67 strains. The authors should also mention what happens with the other 9 sequenced strains (up to 76) – do they have any mutation; to what clades they belong to?

-On lines 228 to 231, the authors suddenly mention a rare S605A mutation, without prior description. They could discuss on the possible effects that this mutation produces (if any): where is located, what happens or would happen with the local conformation of the Spike, etc. Is there a good coverage on this mutation? Also, there’s a typo – it should be “the S605A mutation IN THE spike gene”.

-Similarly, on lines 233-234, a short discussion would be advised for the other 4 novel mutations. Do these mutations have a high sequencing coverage?

-On lines 251 to 256, the authors mention a paper about the possible binding potential of ORF7a to LFA-1 and MAC-1, based on docking studies. They also discuss about some aminoacids that are important for the function of ORF7a. They don’t tell if those aminoacids fold in close proximity in 3D. They also don’t state what happens with the conformation locally, since there are truncated aminoacids due to Q62stop codon.

-On lines 267 to 272, the authors forgot to mention the PDB code for the LFA-1 3D structure, used in the docking simulation. They say that there’s no significant difference in the binding affinity but would’ve been useful to add some details on the docking simulation (how many docking conformations were generated and how do they cluster, and if there are multiple clusters, what were the ΔGs for each cluster). For instance, another study by Ongaro et al., JCIM, May 2021, suggests more than a possible binding motif between Orf7a and LFA-1, as well as the conformational similarity between ORF7a and ICAM3. So, it would be useful to share the whole image of the docking simulation.

-On line 274, in Figure 5 the authors show only two images, side by side, of the WT and mutant ORF7a. The viewing angle is not the same – one structure is rotated with respect to the other. It would’ve been better to represent the two structures superimposed and represented not as a solvent-accessible surface but rather as cartoon or CA-trace ribbon, in order to see the secondary structures in the protein. Also, a zoom-in into the region of Q62stop codon (in order to see the local changes) would be more relevant, and maybe represent as side-chain some of the interface residues (from each protein) involved in the interaction, especially near Q62.

-On line 290, there should be “sequences” instead of “sequencing”.

-On lines 311 to 317, starting with “Despite the D614G….” – there is redundant information that can be removed.

-On lines 346 to 348, the Supplementary table S3, to which the authors refer, contains epidemiological info, and underlines only the stop codon mutation, without any connection to the other mutations discussed in the phrase.

-On lines 374 to 375, the authors suggest that there is no significant difference in the binding affinity. I would underline the fact that authors consider only this LFA-1 possible interactor, but neglect to address other interactors that may interact directly or indirectly (through a network of interactors) with ORF7a, as can be found when searching for similar data in interactomics databases such as BioGrid.

-The phylogenetic tree figure could be improved: it’s hard to see in the chosen representation how the strains split/cluster; there is no highlight on the clades or on lineages; no outgroup mention.

**********

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23 Feb 2022

Response to Decision Letter and Reviewer Comments

Manuscript number: PONE-D-21-36713

Title: High prevalence of an alpha variant lineage with a premature stop codon in ORF7a in Iraq, winter 2020-2021

Reviewers' Comments:

Reviewer #1

The manuscript represents a welcome contribution to the analysis of circulating SARS-CoV-2 variants and strains. The laboratory and analytical tools are adequate and the description of the work is overall, clear. The major drawback is the limited number of sequences generated and analyzed which cannot be representative to the actual population of strains circulating at the time in the country. There is no information about the selection criteria for the samples that were analyzed either; some of the comments in the discussion chapter as well as in conclusions are therefore overstated. The manuscript offers only a limited view of the circulating sequences in Iraq at the time; the text should be correspondingly changed to reflect this.

Specific comments:

Lines 33-35: analysis of only 76 genomes cannot contribute to understanding the molecular epidemiology of the second COVID-19 wave in Iraq.

We agree that this number of genome sequences is not enough to cover the COVID-19 molecular epidemiology of the whole country.

However, we think this study can give some insight on the strains circulated during the second wave of COVID-19 in Iraq although its pilot study. We have now addressed the limitations of the study is more clearly in lines 382-386.

Line 54: there is not enough data to support the statement that the developing countries have been selectively affected

We agree, and revised this phrase and the reference [3] to:

''affecting humans worldwide. [3]

[3 ] Deng G, Shi J, Li Y, Liao Y. The COVID‐19 pandemic: shocks to human capital and policy responses. Account Finance. 2021;61(4):5613-5630. https://doi.org/10.1111/acfi.12770

Line 67: there is not enough evidence of increased severity of disease in VOCs.

According to your recommendations, the phrase has been modified to mean that all SARS-CoV-2 VOCs are associated with an increase in hospitalization, including ICU, and deaths, but there is a different degree of each one compared to the wild-type strains. There is no strong evidence to say that SARS-CoV-2 VOCs cause the severity of the disease, but we can say they have a significant impact on the risk of hospitalization, ICU admissions, and deaths (7).

Other analysis suggests that B.1.1.7 is not only more transmissible than pre-existing SARS-CoV-2 variants, but may also cause more severe illness, that the study depicted the 1,61 x higher case fatality ratio of alpha (B.1.1.7) as compared to "wild type" in the UK (8).

7- Lin L, Liu Y, Tang X, He D. The Disease Severity and Clinical Outcomes of the SARS-CoV-2 Variants of Concern. Front. Public Health. 2021;9:775224. doi: 10.3389/fpubh.2021.775224

8- Davies, N.G., Jarvis, C.I., CMMID COVID-19 Working Group. et al. Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7. Nature 593, 270–274 (2021). https://doi.org/10.1038/s41586-021-03426-1

Sampling: what are the selection criteria for the 76 samples? A “high copy number” is mentioned; what was the threshold Ct in the particular RT-PCR setting?

We have now included this information to the manuscript. The threshold CT value <24 was used for all samples.

Fig 6: the distribution of lineages in the tree is not clearly enough represented and colored

In Figure 6, the lineages of strains have been added.

Lines 304-306: possible consequences of the novel mutations should be further discussed.

According to your recommendation, we have added a short discussion about the effect (including ligand binding, viral oligomerization and host cell protein/RNA interactions) of these mutations in the discussion section (lines 314-319). However, for some of the mutations, the phenotypic effect is not known or is difficult to predict.

Lines 368-369: only a very limited sample of genomic sequences of SARS-CoV-2 from Iraq are actually reported

According to your recommendation, we have stated a limitation of the study at the start of the conclusion:

“The present study has a limited sample size, which may not represent the complete genomic diversity of SARS-CoV-2 in Iraq. It should be noted that the detected genomes may represent only locally distributed viral variations during the second epidemic wave, and the total diversity of SARS-CoV-2 circulating in Iraq is most likely significantly higher”.

Reviewer #2

-On line 42, the authors state that there is a high frequency of this stop codon mutation (88%). However, they also state (line 239) that this mutation occurred in 26 strains as in Supplementary table S3. Therefore, the authors need to either explain the difference or to modify accordingly on this line to: 34.21% if related to the all 76 sequenced strains, or to 43.33% if related to the 60 B.1.1.7 strains only.

Thank you very much for your correction. This was a typo, and the percentage is corrected (43.33%).

-On line 130, the authors state that the NovaSeq system produced 1.222.270 reads – I guess this is the average per sample? Otherwise, if compared to the 76 sequenced samples, the average would be about 16k reads per sample, which is very low. Novaseq generates plenty of data if there’s nothing wrong with the samples to be sequenced.

This is added to the text ‘a range of 1.4 to 3.3 million paired-end sequence reads per sample.’

-On lines 132 to 133, there should be “assembled”, “called” and “called”.

These phrases have been changed accordingly.

-On line 211, the authors state that there are 33 strains that belong to GRY and 29 that belong to GR. In the Supplementary table S2 there are 4 other strains that belong to GH and 1 to O clade, therefore totalling 67 strains. The authors should also mention what happens with the other 9 sequenced strains (up to 76) – do they have any mutation; to what clades they belong to?

We appreciate for pointing out this inconsistency. The missing 9 sequences were added to the supplementary table S2 and distributed according to mutations and lineages as follows (GR, n=6), (O, n=1), (L, n=1) and (G, n=1).

On line 211, we reported only the clades that carry the most common cluster of spike protein mutations “H69del, V70del, Y144del, A570D, D614G, P681H, T716I, S982A, and D1118H”, where the remaining clades (G, GH, O, and L) are not involved since they don’t carry this mutation.

-On lines 228 to 231, the authors suddenly mention a rare S605A mutation, without prior description. They could discuss on the possible effects that this mutation produces (if any): where is located, what happens or would happen with the local conformation of the Spike, etc. Is there a good coverage on this mutation? Also, there’s a typo – it should be “the S605A mutation IN THE spike gene”.

Thank you for pointing this out. We have now revised the corresponding text and added discussion on lines 357-364. Also, the typo is corrected in the text.

-Similarly, on lines 233-234, a short discussion would be advised for the other 4 novel mutations. Do these mutations have a high sequencing coverage?

We have added a short discussion about the effects of these mutations in the discussion section (lines 313–318). The sequencing coverage of these 4 mutations has a range from 80553 to 14774x.

-On lines 251 to 256, the authors mention a paper about the possible binding potential of ORF7a to LFA-1 and MAC-1, based on docking studies. They also discuss about some amino acids that are important for the function of ORF7a. They don’t tell if those amino acids fold in close proximity in 3D. They also don’t state what happens with the conformation locally, since there are truncated amino acids due to Q62stop codon.

We agree with the reviewer’s assessment, accordingly, the corresponding text has been revised and the following phrase added lines 256-258:

“The truncated amino acids are mainly located in one β sheet strand (βG) in the ectodomain. Only four amino acids are located in the β sheet strand βf (Fig 5).”

Fig 5 has replaced by a new one to visualize the functional amino acids, as well as the following phrase added lines 275-279 and the caption of Figure 5: lines 281-283:

“The visualization of the active residue interactions showed that the functional amino acids Glu41, Gly42, Thr39. and Gly38 were contributing to hydrogen bonding with LFA-1 in both ORF7a structures (Fig 5), while the contribution of Ala66 was absent in the mutant structure.”

-On lines 267 to 272, the authors forgot to mention the PDB code for the LFA-1 3D structure, used in the docking simulation. They say that there is no significant difference in the binding affinity but would have been useful to add some details on the docking simulation (how many docking conformations were generated and how do they cluster, and if there are multiple clusters, what were the ΔGs for each cluster). For instance, another study by Ongaro et al., JCIM, May 2021, suggests more than a possible binding motif between Orf7a and LFA-1, as well as the conformational similarity between ORF7a and ICAM3. So, it would be useful to share the whole image of the docking simulation.

We have added the pdb code   of LFA-1 (PDB: 3f78) as recommended (lines 265-266).

It seems that we used the word "significant" incorrectly, where we didn’t mean statistically significant. All we wanted to say is that the difference in the binding affinity between both systems (wild and mutant) is not large (quantitatively not statistically), so to remove the confusion, we replaced the word "significant" with "considerable" in line 273.

In their study, Ongaro et al reported the ΔGs and clustering of the docking results. Because they were searching for a binding motif, it seemed like a blind docking, so we performed only one docking simulation for each ORF7a structure (wild and mutant).

-On line 274, in Figure 5 the authors show only two images, side-by-side, of the WT and mutant ORF7a. The viewing angle is not the same – one structure is rotated with respect to the other. It would’ve been better to represent the two structures superimposed and represented not as a solvent-accessible surface but rather as cartoon or CA-trace ribbon, in order to see the secondary structures in the protein. Also, a zoom-in into the region of Q62stop codon (in order to see the local changes) would be more relevant, and maybe represent as side-chain some of the interface residues (from each protein) involved in the interaction, especially near Q62.

In Figure 5, the two structures have been superimposed and represented by Ribbon and the truncated region has been highlighted. The overall structures and protein-protein interactions of the ORF7a-LFA-1 complex for the wild ORF7a and mutant ORF7a as well as a zoomed-in view of the interaction region have been presented.

-On line 290, there should be “sequences” instead of “sequencing”.

Revised accordingly.

-On lines 311 to 317, starting with “Despite the D614G….” – there is redundant information that can be removed.

This has been removed as recommended.

-On lines 346 to 348, the Supplementary table S3, to which the authors refer, contains epidemiological info, and underlines only the stop codon mutation, without any connection to the other mutations discussed in the phrase.

Thanks for the comment. It is a typo, since the intended table is S2 instead of S3, where table S2 contains the corresponding mutations. So it has been corrected to “Supplementary table S2”.

-On lines 374 to 375, the authors suggest that there is no significant difference in the binding affinity. I would underline the fact that authors consider only this LFA-1 possible interactor, but neglect to address other interactors that may interact directly or indirectly (through a network of interactors) with ORF7a, as can be found when searching for similar data in interactomics databases such as BioGrid.

Thank you for notifying us that there may be another possible interactor. The following phrase has been added to the corresponding text on lines 369-373 and reference 40 “Nonetheless, there is a possibility that the Q62 stop mutation affects ORF7a function, as Ongaro et al. computationally explored additional possible binding motifs in Orf7a for LFA-1.They concluded in their study that the different binding modes of ORF7a can not be ruled out [40]. Therefore, in vitro studies are required to explore the effect of the stop codon Q62* on the function of ORF7a.”

-The phylogenetic tree figure could be improved: it’s hard to see in the chosen representation how the strains split/cluster; there is no highlight on the clades or on lineages; no outgroup mention.

In Figure 6, the lineages of strains have been added..

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

17 Mar 2022

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Additional Editor Comments:

The sample size is not statistically significant. At least 500 sample needs to be analyzed before inferring something.

Patients were selected just on the basis of viral titre (a high copy number of the virus (Ct values

110 <24)), the questions is were these patients immune competent before they caught infection? Do these patients have no comorbidity? The manuscript lacks information about clinical details of subjects.

Those who died, did have any other disease that after infection might have resulted in death? Because the major portion of enrolled patients had mild to moderate symptoms in spite of high copy number of the virus.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

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The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

Reviewer #2: I Don't Know

**********

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The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

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29 Mar 2022

Dear Editor

Thank you very much for your valuable review. Here is a point-by-point response to the editor's comments.

As mentioned in response to the first and second reviewers, we agree that this number of genome sequences is not enough to cover the COVID-19 molecular epidemiology of the entire country. However, due to the limited sequencing capacity, there is currently very little information on the SARS-CoV-2 variants circulating in Iraq. Given that the global availability of SARS-CoV-2 genomic surveillance is extremely biased, we believe that covering this gap in mid-and low-income countries is highly valuable, and, albeit imperfect, the current study provides insight into the strains circulated during the second wave of COVID-19 in Iraq.

We have now more clearly addressed the limitations of the study in lines 382–386.

"The present study has a limited sample size, which may not represent the complete genomic diversity of SARS-CoV-2 in Iraq. It should be noted that the detected genomes may represent only locally distributed viral variations during the second epidemic wave, and the total diversity of SARS-CoV-2 circulating in Iraq is most likely significantly higher".

Regarding clinical details, we have now added information on comorbidities to Table S3. As mentioned earlier, the sample size is too small to correlate any variables with the disease outcome or clinical manifestations, and therefore, we are reluctant to speculate on these in the manuscript. Instead, we focus on genomic characterization and in silico assessment of the potential phenotypic effects of the observed amino acid substitutions.

Submitted filename: Response to Editor.docx

Click here for additional data file.

6 Apr 2022

High prevalence of an alpha variant lineage with a premature stop codon in ORF7a in Iraq, winter 2020-2021

PONE-D-21-36713R2

Dear Dr. Nihad Al-Rashedi ,

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Additional Editor Comments (optional):

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Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

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The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

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Reviewer #2: Yes

**********

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Reviewer #2: N/A

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Reviewer #1: (No Response)

Reviewer #2: Yes

**********

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17 May 2022

PONE-D-21-36713R2

High prevalence of an alpha variant lineage with a premature stop codon in ORF7a in Iraq, winter 2020-2021

Dear Dr. Al-Rashedi:

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