Plasmodium falciparum population structure inferred by msp1 amplicon sequencing of parasites collected from febrile patients in Kenya.

BACKGROUND: Multiplicity of infection (MOI) is an important measure of Plasmodium falciparum diversity, usually derived from the highly polymorphic genes, such as msp1, msp2 and glurp as well as microsatellites. Conventional methods of deriving MOI lack fine resolution needed to discriminate minor clones. This study used amplicon sequencing (AmpliSeq) of P. falciparum msp1 ï»¿(Pfmsp1) to measure spatial and temporal genetic diversity of P. falciparum. METHODS: 264 P. falciparum positive blood samples collected from areas of differing malaria endemicities between 2010 and 2019 were used. Pfmsp1 gene was amplified and amplicon libraries sequenced on Illumina MiSeq. Sequences were aligned against a reference sequence (NC_004330.2) and clustered to detect fragment length polymorphism and amino acid variations. RESULTS: Children < 5 years had higher parasitaemia (median = 23.5 ± 5 SD, p = 0.03) than the > 5-14 (= 25.3 ± 5 SD), and those > 15 (= 25.1 ± 6 SD). Of the alleles detected, 553 (54.5%) were K1, 250 (24.7%) MAD20 and 211 (20.8%) RO33 that grouped into 19 K1 allelic families (108-270 bp), 14 MAD20 (108-216 bp) and one RO33 (153 bp). AmpliSeq revealed nucleotide polymorphisms in alleles that had similar sizes, thus increasing the K1 to 104, 58 for MAD20 and 14 for RO33. By AmpliSeq, the mean MOI was 4.8 (± 0.78, 95% CI) for the malaria endemic Lake Victoria region, 4.4 (± 1.03, 95% CI) for the epidemic prone Kisii Highland and 3.4 (± 0.62, 95% CI) for the seasonal malaria Semi-Arid region. MOI decreased with age: 4.5 (± 0.76, 95% CI) for children < 5 years, compared to 3.9 (± 0.70, 95% CI) for ages 5 to 14 and 2.7 (± 0.90, 95% CI) for those > 15. Females' MOI (4.2 ± 0.66, 95% CI) was not different from males 4.0 (± 0.61, 95% CI). In all regions, the number of alleles were high in the 2014-2015 period, more so in the Lake Victoria and the seasonal transmission arid regions. CONCLUSION: These findings highlight the added advantages of AmpliSeq in haplotype discrimination and the associated improvement in unravelling complexity of P. falciparum population structure.

COVID-19 mass testing and sequencing: Experiences from a laboratory in Western Kenya.

Background: The Basic Science Laboratory (BSL) of the Kenya Medical Research Institute/Walter Reed Project in Kisumu, Kenya addressed mass testing challenges posed by the emergent coronavirus disease 2019 (COVID-19) in an environment of global supply shortages. Before COVID-19, the BSL had adequate resources for disease surveillance and was therefore designated as one of the testing centres for COVID-19. Intervention: By April 2020, the BSL had developed stringent safety procedures for receiving and mass testing potentially infectious nasal specimens. To accommodate increased demand, BSL personnel worked in units: nucleic acid extraction, polymerase chain reaction, and data and quality assurance checks. The BSL adopted procedures for tracking sample integrity and minimising cross-contamination. Lessons learnt: Between May 2020 and January 2022, the BSL tested 63 542 samples, of which 5375 (8.59%) were positive for COVID-19; 1034 genomes were generated by whole genome sequencing and deposited in the Global Initiative on Sharing All Influenza Data database to aid global tracking of viral lineages. At the height of the pandemic (August and November 2020, April and August 2021 and January 2022), the BSL was testing more than 500 samples daily, compared to 150 per month prior to COVID-19. An important lesson from the COVID-19 pandemic was the discovery of untapped resilience within BSL personnel that allowed adaptability when the situation demanded. Strict safety procedures and quality management that are often difficult to maintain became routine. Recommendations: A fundamental lesson to embrace is that there is no 'one-size-fits-all' approach and adaptability is the key to success.

Temporal lineage replacements and dominance of imported variants of concern during the COVID-19 pandemic in Kenya.

Background: Kenya's COVID-19 epidemic was seeded early in March 2020 and did not peak until early August 2020 (wave 1), late-November 2020 (wave 2), mid-April 2021 (wave 3), late August 2021 (wave 4), and mid-January 2022 (wave 5). Methods: Here, we present SARS-CoV-2 lineages associated with the five waves through analysis of 1034 genomes, which included 237 non-variants of concern and 797 variants of concern (VOC) that had increased transmissibility, disease severity or vaccine resistance. Results: In total 40 lineages were identified. The early European lineages (B.1 and B.1.1) were the first to be seeded. The B.1 lineage continued to expand and remained dominant, accounting for 60% (72/120) and 57% (45/79) in waves 1 and 2 respectively. Waves three, four and five respectively were dominated by VOCs that were distributed as follows: Alpha 58.5% (166/285), Delta 92.4% (327/354), Omicron 95.4% (188/197) and Beta at 4.2% (12/284) during wave 3 and 0.3% (1/354) during wave 4. Phylogenetic analysis suggests multiple introductions of variants from outside Kenya, more so during the first, third, fourth and fifth waves, as well as subsequent lineage diversification. Conclusions: The data highlights the importance of genome surveillance in determining circulating variants to aid interpretation of phenotypes such as transmissibility, virulence and/or resistance to therapeutics/vaccines.