Overview of SARS-CoV-2 variants in the federation of Bosnia and Herzegovina throughout four waves of the pandemic

Abstract

Aim

COVID-19 pandemic, caused by SARS-CoV-2, has had a profound impact on global health, including in Bosnia and Herzegovina, which faced unique challenges due to limited testing and high mortality rates. This analysis aimed to identify mutations and detect different SARS-CoV-2 lineages across four pandemic waves.

Methodology

A total of 127 SARS-CoV-2 samples were collected and sequenced from patients from the Federation of Bosnia and Herzegovina, providing a comprehensive overview of the viral genetic diversity in this region. Two sequencing platforms, Ion Torrent and Illumina, were used, whereby 37 samples were sequenced on the Ion Torrent platform, while others were sequenced on the Illumina platform.

Results

This study presents a genomic analysis of SARS-CoV-2 variants circulating in the Federation of Bosnia and Herzegovina over four distinct pandemic waves, spanning from March 2020 to April 2023. Examination of genomic variations across these waves revealed key mutations associated with transmission and potential virulence.

Conclusion

These genomic insights into SARS-CoV-2 evolution in Federation of Bosnia and Herzegovina emphasizes the importance of continuous surveillance to understand viral evolution and strengthen public health responses to future pandemics.

Keywords

COVID-19 next-generation sequencing SARS-CoV-2 surveillance variants

1. Introduction

In late December 2019, the world faced pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The COVID-19 disease was first noted to have occurred in Wuhan, China and since then, over 776 million people have been infected by this virus.¹ Like many other RNA viruses, SARS-CoV-2 undergoes highly rapid recombination.² A high mutation rate was leading to the emergence of different SARS-CoV-2 variants during the pandemic.^3,4 World Health Organization (WHO), Global Initiative on Sharing All Influenza Data (GISAID), Nextstrain and Phylogenetic Assignment of Named Global Outbreak Lineages (Pangolin) are the four most relevant nomenclature systems for classifying and naming SARS-CoV-2 lineages.⁵ Each of these platforms has its own norms and rules, which means that one variant can have multiple tracking names in different nomenclature systems.^6,7 These SARS-CoV-2 variations, which were spreading across the entire world, are known as the variants of interest (VOIs), variants of concern (VOCs), and variants under monitoring (VOMs). Among the most significant VOC variations which are considered as more contagious in comparison to the other classification groups are B.1.1.7 (Alpha variant), B.1.351 (Beta variant), P.1 (Gamma variant), B.1.617.2 (Delta variant), and B.1.1.529 (Omicron).^3,5

The genome of the SARS-CoV-2 virus is organized such that approximately two-thirds encode 16 non-structural proteins (Nsps), while the remaining third contains open reading frames (ORFs) that encode four main structural proteins and several auxiliary proteins. The structural proteins are: Spike (S), Matrix (M), Envelope (E) and Nucleocapsid (N) proteins, while the auxiliary proteins are ORF3a, ORF3b, ORF6, ORF7a, ORF7b, ORF8, ORF9a and ORF9b. The most significant and relevant mutations regarding the transmission and virulence of the SARS-CoV-2 virus are located in the gene encoding the S protein.^8,9

The SARS-CoV-2 virus has reached Bosnia and Herzegovina (BiH) on 5 March 2020 in the Republic of Srpska (RS) entity.¹⁰ The first COVID-19 case in the Federation of Bosnia and Herzegovina (FBiH) entity was reported on 9 March 2020 in Zenica. Bosnia and Herzegovina has one of the lowest SARS-CoV-2 test rates in Europe, and one of the highest rates of COVID-19 mortality worldwide. As of the end of August 2024, the number of confirmed COVID-19 cases in Bosnia and Herzegovina was 403,666. Due to the low SARS-CoV-2 PCR testing rate, the actual number of cases is likely much higher. There have been reported 16,392 confirmed COVID-related deaths, with a fatality rate of 4.06%.¹¹

Considering the specifics of COVID-19 progression in FBiH, we performed targeted sequencing of SARS-CoV-2 genome in 127 samples collected in different parts of FBiH and across four epidemiological waves of pandemic in order to perform comparison between the epidemiological reports from FBiH from this period and observed lineage shifts in our samples.

2. Materials and methods

2.1. Sample collection and SARS-CoV-2 detection

A total of 127 SARS-CoV-2 samples were collected in the SARS-CoV-2 routine testing laboratory from nasopharyngeal swabs of anonymized samples from the FBiH population and sequenced between May 2020 and March 2023. This study was approved by the Ethics Committee of Burch University, Faculty of Engineering, Natural, and Medical Sciences, Approval number: 04-25-2/23. RNA was extracted from the viral transport medium containing the immersed swabs using the GeneRotex 96 (Tianlong Science & Technology, Shaanxi, China) automated extractor based on magnetic particle technology.

The presence of SARS-CoV-2 was detected by real-time PCR and LAMP (loop-mediated isothermal amplification) methods. For the real-time PCR, the LabGun™ COVID-19 ExoFast RT-PCR Kit (LabGenomics Co. Ltd, Brussels, Belgium) was used, while the LAMP method utilized the WarmStart^® Colorimetric LAMP 2X Master Mix (DNA & RNA) (New England Biolabs, Ipswich, MA, USA) along with in-house primers for SARS-CoV-2 detection.

2.2. Next-generation sequencing

Two next-generation sequencing (NGS) platforms were used. The first platform Ion Torrent™ Ion GeneStudio™ S5 System (Applied Biosystems, Waltham, MA, USA) was utilized from May 2020 to August 2021, during which time 37 samples were sequenced. cDNA synthesis was performed using the Invitrogen™ SuperScript™ Vilo™ cDNA Synthesis Kit (Thermo Fisher Scientific, Waltham, MA, USA). Library preparation was conducted with the Ion AmpliSeq™ Library Kit Plus (Thermo Fisher Scientific), and target DNA amplification used the Ion AmpliSeq SARS-CoV-2 Research Panel (Thermo Fisher Scientific). Quantification of the libraries was performed by qPCR method on the QuantStudio™ 7 Flex Real-Time PCR System (Applied Biosystems) with the Ion Library TaqMan™ Quantitation Kit (Thermo Fisher Scientific). Chip loading was performed using Ion Chef™ Instrument (Thermo Fisher Scientific) and Ion 530™ Chip was used, which enables the read length of up to 400 bp. Ion GeneStudio™ S5 System (Thermo Fisher Scientific) was used for library sequencing, and Iterative Refinement Meta-Assembler software (IRMA) software generated the FASTA files for subsequent data analysis.

The Illumina MiSeq™ System (Illumina, San Diego, CA, USA), was used to sequence 90 samples between September 2021 and March 2023. Samples were sequenced using Illumina COVIDSeq Test (Illumina) following the manufacturer's instructions. RNA was reverse-transcribed, and libraries were prepared using two COVIDSEQ primer pools. Libraries were indexed using IDT for Illumina-PCR Indexes Set 4 (Illumina, San Diego, CA, USA). Prepared libraries were pooled and sequenced on Illumina MiSeq platform using MiSeq Reagent Kit v2 (300 cycles) (Illumina). FastQ files were generated by Illumina sequencing system.

2.3. Data analysis

Pangolin tool was used to identify the circulating SARS-CoV-2 lineages in FBiH across the four distinct waves of the COVID-19 pandemic. Sequence quality control was performed using the MultiQC tool. IRMA (Iterative Refinement Meta-Assembler) was used for assembly and for the alignment of the sequences which were obtained from the Ion Torrent platform and DRAGEN COVID Lineage 3.5.8 was used as the assembly method and for the alignment of the sequences obtained from Illumina platform.

The research period was divided into four pandemic waves identified by analyzing the weekly number of positive PCR test cases.¹² Using population projections from the Federal Bureau of Statistics of the Federation of Bosnia and Herzegovina,¹³ incidence rates were calculated and expressed per 100,000 inhabitants. The week of the first reported case was the beginning of the first wave. Each wave demonstrated a trend of increased weekly incidence until reaching its highest peak, followed by a trend of decreasing incidence. The end of each wave was defined as the point when incidence was at its lowest before the next increase in the FBiH.

3. Results

In this study, we identified four waves during the COVID-19 pandemic in the FBiH. Figure 1 shows the incidence of COVID-19 cases per 100,000 inhabitants in FBiH and highlights that the third wave was the longest, while the fourth wave had the greatest diversity of detected SARS-CoV-2 lineages. The data presented in the figure is based on the reports from the Federal Bureau of Statistics of the Federation of Bosnia and Herzegovina.¹³

Figure 1.

Incidence per 100,000 inhabitants and detected SARS-CoV-2 lineages across the four pandemic waves in the federation of Bosnia and Herzegovina.

Table 1 presents the key parameters across each wave of the pandemic. During the SARS-CoV-2 pandemic in the FBiH, the highest incidence rate was reached in the third wave accounting for 619.79 cases per 100,000 inhabitants, indicating a significant level of virus transmission within the population, while the highest mean incidence value of positive cases was observed during the second wave of the pandemic (130.11). These parameters provide a summary of the intensity and virulence during different time periods.

Table 1.

Overview of significant pandemic parameters across pandemic waves in the Federation of Bosnia and Herzegovina.

Wave	I (1–48 week)	II (49–69 week)	III (70–119 week)	IV (120–147 week)
Duration	09/03/2020–07/02/2021	08/02/2021–04/07/2021	05/07/2021–19/06/2022	20/06/2022–02/04/2023
Highest incidence per 100,000 inhabitants	332.73 (35^th week)	367.52 (55^th week)	619.79 (98^th week)	99.64 (126^th week)
Mean incidence value	83.68	130.11	127.13	29.73
The highest number of daily positive cases	1372 (04/11/2020) 35^th week	1583 (24/03/2021) 55^th week	2503 (25/01/2022) 99^th week	526 (25/03/2023) 146^th week

NGS results identified 40 distinct lineages of the SARS-CoV-2 virus, which showed the genetic diversity and the wide range of variants circulating within the population of the FBiH at that time. All SARS-CoV-2 sequences obtained in this study have been uploaded to the GISAID database and are available under the corresponding accession numbers (Table S1). We managed to identify lineage shifts in the predominant SARS-CoV-2 lineages across the four pandemic waves in the FBiH. During the first wave, lineage B.1 was the most prevalent, accounting for 37.5% of sequenced samples. In the second wave, the B.1.1.7 (Alpha) lineage became dominant, accounting for 68.18% of the sequences. By the third wave, lineage BA.2 had emerged as the most frequently detected, representing 44.61% of samples. In the fourth and final wave of this study, two lineages BA.5.1 and XBB.1.5, were found to have an equal representation of 15.62%. The distribution of other lineages in each wave is illustrated in Figure 2, showing obvious increase in the number of distinct lineages detected as pandemic progressed in time.

Figure 2.

Percentage distribution of SARS-CoV-2 lineages detected across four COVID-19 waves in FBiH.

The number of mutations within the SARS-CoV-2 genome varied across pandemic waves. The first wave exhibited the lowest mutation diversity, with an average of 23.25 mutations per sample. This average increased progressively in subsequent waves, reaching 42.27, 55.48, and 64.94 mutations per sample in the second, third and fourth waves, respectively. The Spike gene showed a clear increase in mutation frequency from the first until the end of the fourth wave, indicating greater genetic variability as the pandemic progressed. N protein showed increased number of mutations during first, third and fourth waves, while the Nsp3 region experienced a peak in mutations during the second wave. E and M proteins show relatively low mutation counts across all the waves, with only minor fluctuations (Figure 3).

Figure 3.

The number of mutations within the SARS-CoV-2 genome across pandemic waves in the Federation of Bosnia and Herzegovina.

D614G change in the Spike protein was detected in all sequenced samples in this study. Substitution P323L in Nsp12 domain was detected in 20 samples of the second wave except two samples belonging to B.1.1.7 lineage. During the third wave, this mutation was absent in samples associated with the Delta variant, except for those from the AY.45 lineage. Furthermore, it was not detected in one of the samples classified under the Omicron variant, specifically from the BA.2 sublineage. During the fourth wave, the P323L mutation was identified in all analyzed samples.

In the sequenced samples which were collected during the second wave, 93 mutations were identified in the Spike protein region, and 10 of these mutations were consistently observed in the majority of samples associated with the Alpha variant, namely D614G, H69del, N501Y, P681H, V70del, Y144del, A570D, D1118H, S982A, and T716I. The last four mutations listed were only observed during the second wave, while the remaining mutations were found in Omicron variant samples from the third and fourth waves as well. Lineage B.1.1.7 during the second wave demonstrated numerous mutations in regions other than Spike protein, with the most prevalent ones found in several key locations: Nsp3 (A890D, I1412 T, T183I), N (D3L, R203 K, S235F), NS8 (Q27stop, R52I, Y73C), Nsp6 (F108del, G107del, S106del), and Nsp12 (P323L).

In the Delta variant, the Spike protein mostly contained the following mutations: E156G, F157del, G142D, L452R, P681R, R158del, and T478 K. Additional mutations were detected in the second wave, including proteins N (D63G, G215C), NS3 (S26L), NS7a (T120I, V82A), Nsp3 (P1228L, P1469S), Nsp6 (T77A), and Nsp14 (A394 V). These mutations were present in the AY.122 lineage of the Delta subvariant during the second wave. Furthermore, the same mutations were observed at the onset of the third wave in Delta lineages AY.43, B.1.617.2, AY.9.2, AY.45, and AY.34.

For the Gamma variant, mutations in the Spike protein included E484 K, H655Y, and K417 T, while K977Q was identified in the Nsp3 region, and the A22 V substitution was detected in the Nsp9 region.

The continued spread of Delta subvariants marked the beginning of the third wave, while the later stages of this prolonged wave were predominantly defined by the appearance of the Omicron variant. A significant proportion of mutations observed during this wave were located in the Spike protein. Some Spike mutations, such as T95I, G142D, and T478 K, were present in both Delta and Omicron subvariants. In addition, Spike mutations specific to certain Omicron subvariants, such as BA.1.17.2, BA.1.1, and BA.1, were identified. These include ins214EPE, A67 V, G446S, G496S, H69del, L212I, L981F, N211del, N856 K, T547 K, V70del, V143del, S371L, Y144del, and Y145del. Furthermore, Spike mutations unique to Omicron subvariants BA.2, BA.2.9, BA.2.52, and BA.2.48 were identified, including A27S, D405N, L24del, P25del, P26del, R408S, S371F, T19I, T376A, and V213D.

The fourth wave continued to exhibit many of the same Spike protein mutations. For instance, D796Y, H655Y, N679 K, N764 K, N969 K, P681H, and Q954H were consistently observed across BA.5, BF, BQ, and XBB lineages. Additionally, mutations E484A, G339D, and N501Y were present in most BA.5 and BF sublineages and continued into XBB.1.9.1 and XBB.1.5. Other mutations were identified in all detected Omicron subvariants during the third and fourth waves, occurring in regions of the genome other than the Spike protein. These mutations were located in the E (T9I), M (A63 T and Q19E), N (E31del, G204R, P13L, R32del, and R203 K), Nsp5 (P132H), Nsp6 (G107del and S106del), and Nsp14 (I42 V).

4. Discussion

The COVID-19 pandemic has significantly impacted global health, with the emergence and spread of SARS-CoV-2 variants causing difficulties in public health responses in the FBiH. Understanding the genetic diversity of SARS-CoV-2 is crucial for tracking viral evolution, assessing transmissibility, and strategies for future pandemics.⁴ At the very beginning of the pandemic, only eight samples were sequenced in this study during that initial wave. This limited sequencing effort was largely due to the primary focus on detecting SARS-CoV-2 infections in patients, rather than on genomic sequencing. During the peak of positive cases in the first wave (week 35), the lineage B.1.258 was detected in the population. Along the Spike D614G and Nsp12 P323L changes, which were present in all sequenced samples in the first wave, the most notable mutations identified in the B.1.258 lineage are located in the Spike protein, specifically the deletions of H69 and V70. These deletions have been associated with increased viral infectivity.¹⁴

At the peak of recorded positive cases in the second wave, the Alpha lineage (B.1.1.7) was the dominant variant. Most changes occurred in Spike and Nsp3 regions which is characteristic of this lineage.¹⁵ The emergence of the Alpha variant and its associated Spike mutations (H69del, V70del, N501Y, and P681H) marked a significant turning point in the dynamics of SARS-CoV-2 transmission.¹⁶ The N501Y mutation in the Spike protein is located at the receptor binding domain (RBD), thus potentially increasing the binding affinity for the human angiotensin-converting enzyme 2 (ACE2) which plays a crucial role in viral invasion into the host cells.^17,18 Furthermore, the P681H mutation is positioned close to the furin cleavage site in the Spike protein, a region that is known to be important for both infection and transmission abilities of the virus.¹⁹ Additionally, it has been suggested that individuals infected with B.1.1.7 have a longer infectious period than those infected with other lineages.²⁰ This extended infectious period may help explain the increased transmissibility of the B.1.1.7 lineage.¹⁷

At the transition point between the second and third waves, subvariants of the Delta and Gamma variants emerged. At the end of the second wave, subvariants of the Alpha, Gamma and Delta variants were present in the FBiH population, indicating a period of variant diversity. However, the Gamma variant remained for a short period in the FBiH population, as the beginning of the third wave was marked by the dominance of the Delta variant. The quick succession from Alpha and Gamma to Delta highlights the competitive nature of SARS-CoV-2 variants, where more transmissible strains tend to outcompete the others. This competitive nature frequently leads to the emergence of new strains which have the advantage regarding transmission, thus leading to epidemic outbreaks worldwide.^21,22

Characteristic Spike protein mutations of the Delta variant include P681R, L452R, T478 K, D614G, T19R, G142D, E156G, F157del, R158del, and D950N, with P681R being a key mutation associated with the variant's increased transmissibility.^23,24 All of these mutations were found in all sequenced Delta subvariants in this study, except for the D950N mutation, which was observed only in two samples from the AY.122 and AY.45 lineages. The G142D mutation in the Spike protein, which may enhance the immune evasion capabilities and transmissibility,²⁵ was first identified in the Delta subvariant AY.122 during the second wave, and was also observed in all Delta and Omicron subvariant lineages during the third and fourth waves, except BA.5.2.6 and CH.1.1 lineages.

Certain mutations which enhance the viral replication capacity and virulence, such as Nsp12 G671S,²⁶ initially detected in the Delta variant during the second wave, reappeared in Omicron variants that emerged later in the pandemic, specifically in lineages CH.1.1, XBB.1.9.1, XBB.1.9, and XBB.1.5. Similarly, the mutation Spike H655Y which may enhance the Spike protein cleavage and fusion, resulting in more efficient viral replication and transmission²⁷ was initially detected only in Gamma variant in the second wave. This mutation remained present in the third wave across the lineages BA.17.2, BA.1.1, BA.1, BA.2, BA.2.9, BA.2.52, and BA.2.48, and it was also found in all Omicron lineages during the fourth wave.

The Delta variant demonstrated significantly greater transmissibility compared to both Alpha and Gamma variants, leading to a substantial increase in infections during the third wave. However, it was the arrival of the Omicron variant that resulted in the highest number of infections in a single day recorded since the pandemic began. Sequencing analysis in this study revealed substantial number of mutations in the Omicron variant, particularly in the Spike protein, which is associated with enhanced transmissibility. Notably, the majority of Spike protein mutations were shared across all Omicron subvariants, including D796Y, E484A, G339D, H655Y, K417N, N440 K, N501Y, N679 K, N764 K, N969 K, P681H, Q493R, Q498R, Q954H, S373P, S375F, S477N, and Y505H. These findings align with existing literature that highlights Omicron's unique mutation profile with the highest mutation diversity causing greater infectivity in comparison to other SARS-CoV-2 variants,²⁸ including critical mutations such as N501Y, E484A, T478 K, and K417N, which are believed to improve the variant's ability to bind to the ACE2 receptor.²⁹

Although BA.2 was the predominant lineage throughout the third wave, at the peak of this wave, BA.1.1 was the most frequently detected lineage among sequenced samples. This observation may be due to the increased transmissibility of Omicron sub-variants, including BA.1.1, BA.2, and BA.3, compared to both the original Omicron (BA.1) and Delta variants.³⁰ The peak in positive cases during the fourth wave coincided with the emergence of the BF.7 lineage, which, as noted by Gao et al.,³¹ demonstrated higher transmissibility than earlier SARS-CoV-2 variants.

The trend of an increased number of mutations persisted during the fourth wave of the pandemic.³² However, during this period, there is a significant decline in the number of reported positive cases in the database from the Institute for Public Health FBiH. This decrease can largely be attributed to the introduction of antigen tests on the market, which are not represented in the reported statistics. Consequently, the official count of positive cases in the fourth wave does not accurately reflect the true proportions of infections, as many individuals tested positive using antigen tests without their results being documented in the database. Therefore, it is important to recognize that the actual number of cases during the fourth wave was likely much higher than reported, indicating a potential underestimation of the variant's impact during this period.

5. Conclusion

In conclusion, the sequencing of 127 samples over four pandemic waves revealed significant genetic shifts in FBiH, with each wave dominated by different variants. The transition from Alpha to Delta, followed by the rapid rise of Omicron, underscores the competitive advantage of new mutations in enabling variants to outcompete previous ones. Notably, the Omicron variant exhibited the highest number of mutations, particularly in the Spike protein, which correlates with its significant infectivity and the largest outbreak in the region. Furthermore, this study highlights the challenges in accurately assessing infection rates, especially in the fourth wave, where antigen testing led to a likely underestimation of actual cases. Overall, these findings emphasize the importance of continuous genomic surveillance to understand SARS-CoV-2 evolution, which is essential for tracking viral adaptation and improving future pandemic efficiency. The significance of our study lies in its comprehensive analysis of how genetic changes in the SARS-CoV-2 virus impacted its transmission dynamics over four waves of the pandemic in the Federation of Bosnia and Herzegovina. The limitation of the study and our future focus will include data from different aspects of the pandemic such as public health measures and distribution of naturally acquired and vaccine induced immunity in different subpopulation groups. However, this study provides the most extensive dataset of SARS-CoV-2 sequences published for this subpopulation.

Supplemental Material

sj-docx-1-thc-10.1177_09287329251327020 - Supplemental material for Overview of SARS-CoV-2 variants in the federation of Bosnia and Herzegovina throughout four waves of the pandemic

Supplemental material, sj-docx-1-thc-10.1177_09287329251327020 for Overview of SARS-CoV-2 variants in the federation of Bosnia and Herzegovina throughout four waves of the pandemic by Ivana Čeko, Naida Mulahuseinović, Selma Durgut, Lana Salihefendić, Adna Ašić, Dino Pećar, Nejira Handžić, Sabina Šegalo, Lejla Lasić, Rijad Konjhodžić in Technology and Health Care

Footnotes

ORCID iDs

Selma Durgut

Sabina Šegalo

Ethics

Not applicable.

Author contributions

IČ – data curation, formal analysis, methodology, project administration, writing – original draft; NM – data curation, resources, software, writing – original draft; SD – investigation, methodology, writing – original draft; LS – investigation, methodology, writing – original draft; AA - investigation, methodology, writing – original draft; DP – methodology, visualization, writing – original draft; NH – investigation, methodology, writing – original draft; SŠ - investigation, methodology, writing – original draft; LL – funding acquisition, investigation, project administration, resources, supervision, writing – review and editing; RK – conceptualization, data curation, funding acquisition, investigation, project administration, resources, supervision, writing – review and editing

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was the part of the project entitled “Design and Optimization of SARS-CoV-2 Virus Detection Using the LAMP Method for Diagnostic Use” (no. of project 27-02-11-41251-7/21) financially supported by Ministry of Science, Higher Education, and Youth of Canton Sarajevo.

Conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability

All raw data are available from the corresponding author upon reasonable request.

Supplemental material

Supplemental material for this article is available online.

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