Screening and Whole Genome Sequencing of SARS-CoV-2 Circulating During the First Three Waves of the COVID-19 Pandemic in Libreville and the Haut-Ogooué Province in Gabon

Abstract

Since the onset of the COVID-19 pandemic, the SARS-CoV-2 viral dynamics in Africa have been less documented than on other continents. In Gabon, a Central African country, a total number of 37,511 cases of COVID-19 and 281 deaths have been reported as of December 8, 2021. After the first COVID-19 case was reported on March 12, 2020, in the capital Libreville, the country experienced two successive waves. The first one, occurred in March 2020 to August 2020, and the second one in January 2021 to May 2021. The third wave began in September 2021 and ended in November 2021. In order to reduce the data gap regarding the dynamics of SARS-CoV-2 in Central Africa, we performed a retrospective genotyping study using 1,006 samples collected from COVID-19 patients in Gabon from 2020 to 2021. Using SARS-CoV-2 variant screening by Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) and whole genome sequencing (WGS), we genotyped 809 SARS-CoV-2 samples through qRT-PCR and identified to generated 291 new genomes. It allowed us to describe specific mutations and changes in the SARS-CoV-2 variants in Gabon. The qRT-PCR screening of 809 positive samples from March 2020 to September 2021 showed that 119 SARS-CoV-2 samples (14.7%) were classified as VOC Alpha (Pangolin lineage B.1.1.7), one (0.1%) was a VOC Beta (B.1.351), and 198 (24.5 %) were VOC Delta (B.1.617.2), while 491 samples (60.7%) remained negative for the variants sought. The B1.1 variant was predominant during the first wave while the VOC Alpha dominated the second wave. The B1.617.2 Delta variant is currently the dominant variant of the third wave. Similarly, the analysis of the 291 genome sequences indicated that the dominant variant during the first wave was lineage B.1.1, while the dominant variants of the second wave were lineages B.1.1.7 (50.6%) and B.1.1.318 (36.4%). The third wave started with the circulation of the Delta variant (B.1.617). Finally, we compared these results to the SARS-CoV-2 sequences reported in other African, European, American and Asian countries. Sequences of Gabonese SARS-CoV-2 strains presented the highest similarities with those of France, Belgium and neighboring countries of Central Africa, as well as West Africa.

Keywords: Gabon; Libreville and Haut-Ogooué; SARS-CoV-2; variant; whole genome sequencing.

Figure 1

Map of Gabon and its neighboring countries in Central Africa. Number of COVID-19 cases and deaths in December 2021.

Figure 2

Number of positive cases of COVID-19 and deaths between March 2020 and September 2021 in Gabon. (A) Number of COVID-19 Cases per month; (B) Number of deaths associated with COVID-19 per month; (C) Cumulative number of COVID-19 cases and SARS-CoV-2 associated deaths.

Figure 3

Number of cases of VOCs Alpha, Beta, Delta screened by qPCR.

Figure 4

Distribution of samples screened by qPCR during the different waves and whole genome sequencing. qPCR results are in green; Samples first tested by qPCR and sequenced are in blue; Complete genome sequences are in red. *, genomes from samples tested by qPCR and sequenced; ^a, first wave; ^b, second wave; ^c, third wave.

Figure 5

Distribution of SARS-CoV-2 strains during the three Gabonese pandemic waves. “Others” represented the others genomes we found: lineage A, B.1.356, B.1.128, B.1.1.409, B.1.1.121, B.1.1.275, L.3, B.1.620, B.1.525.

Figure 6

Molecular Phylogenetic analysis by Maximum Likelihood method using 65 sequences from strains circulating during the first wave and the first inter-wave in Gabon and 36 SARS-CoV-2 sequences available in GISAID. The evolutionary history was inferred by using the Maximum Likelihood method based on the Jukes-Cantor model. The tree with the highest log likelihood (−41732.01) is shown. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach, and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 101 nucleotide sequences. All positions with <80% site coverage were eliminated. That is, fewer than 20% alignment gaps, missing data, and ambiguous bases were allowed at any position. There were a total of 28295 positions in the final dataset. Evolutionary analyses were conducted in MEGA7. The red circles correspond to the genomes identified in this study.

Figure 7

Molecular Phylogenetic analysis by Maximum Likelihood method using one sequence from VOC Delta circulating during the first inter-wave in Gabon and 37 SARS-CoV-2 sequences available in GISAID. The evolutionary history was inferred by using the Maximum Likelihood method based on the Jukes-Cantor model. The tree with the highest log likelihood (−41765.89) is shown. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach, and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 38 nucleotide sequences. All positions with <80% site coverage were eliminated. That is, fewer than 20% alignment gaps, missing data, and ambiguous bases were allowed at any position. There were a total of 27791 positions in the final dataset. Evolutionary analyses were conducted in MEGA7. The red circle correspond to the genome identified in this study.

Figure 8

Molecular Phylogenetic analysis by Maximum Likelihood method using 154 sequences from strains circulating during the second wave in Gabon and 51 SARS-CoV-2 sequences available in GISAID. The evolutionary history was inferred by using the Maximum Likelihood method based on the Jukes-Cantor model. The tree with the highest log likelihood (−47967.94) is shown. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach, and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 205 nucleotide sequences. All positions with <80% site coverage were eliminated. That is, fewer than 20% alignment gaps, missing data, and ambiguous bases were allowed at any position. There were a total of 28844 positions in the final dataset. Evolutionary analyses were conducted in MEGA7. The red circles correspond to the genomes identified in this study.

Figure 9

Molecular Phylogenetic analysis by Maximum Likelihood method using 72 sequences from strains circulating during the second inter-wave and the third wave in Gabon and 35 SARS-CoV-2 sequences available in GISAID. The evolutionary history was inferred by using the Maximum Likelihood method based on the Jukes-Cantor model. The tree with the highest log likelihood (−45247.72) is shown. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach, and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 107 nucleotide sequences. All positions with <80% site coverage were eliminated. That is, fewer than 20% alignment gaps, missing data, and ambiguous bases were allowed at any position. There were a total of 28863 positions in the final dataset. Evolutionary analyses were conducted in MEGA7. The red circles correspond to the genomes identified in this study.