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 (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.

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.

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.

March 2019 dengue fever outbreak at the Kenyan south coast involving dengue virus serotype 3, genotypes III and V

The first description of a disease resembling dengue fever (DF) was in the 15th century slave trade era by Spanish sailors visiting the Tanzania coast. The disease, then associated with evil spirits is now known to be caused by four serotypes of dengue virus (DENV1-4) that are transmitted by Aedes mosquitoes. Kenya has experienced multiple outbreaks, mostly associated with DENV-2. In this study, plasma samples obtained from 37 febrile patients during a DF outbreak at Kenya's south coast in March 2019 were screened for DENV. Total RNA was extracted and screened for the alpha- and flavi-viruses by real-time polymerase chain reaction (qPCR). DENV-3 was the only virus detected. Shotgun metagenomics and targeted sequencing were used to obtain DENV whole genomes and the complete envelope genes (E gene) respectively. Sequences were used to infer phylogenies and time-scaled genealogies. Following Maximum likelihood and Bayesian phylogenetic analysis, two DENV-3 genotypes (III, n = 15 and V, n = 2) were found. We determined that the two genotypes had been in circulation since 2015, and that both had been introduced independently. Genotype III's origin was estimated to have been from Pakistan. Although the origin of genotype V could not be ascertained due to rarity of these sequences globally, it was most related to a 2006 Brazilian isolate. Unlike genotype III that has been described in East and West Africa multiple times, this was the second description of genotype V in Kenya. Of note, there was marked amino acid variances in the E gene between study samples and the Thailand DENV-3 strain used in the approved Dengvaxia vaccine. It remains to be seen whether these variances negatively impact the efficacy of the Dengvaxia or future vaccines.

The spleen bacteriome of wild rodents and shrews from Marigat, Baringo County, Kenya

BACKGROUND

There is a global increase in reports of emerging diseases, some of which have emerged as spillover events from wild animals. The spleen is a major phagocytic organ and can therefore be probed for systemic microbiome. This study assessed bacterial diversity in the spleen of wild caught small mammals so as to evaluate their utility as surveillance tools for monitoring bacteria in an ecosystem shared with humans.

METHODS

Fifty-four small mammals (rodents and shrews) were trapped from different sites in Marigat, Baringo County, Kenya. To characterize their bacteriome, DNA was extracted from their spleens and the V3-V4 regions of the 16S rRNA amplified and then sequenced on Illumina MiSeq. A non-target control sample was used to track laboratory contaminants. Sequence data was analyzed with Mothur v1.35, and taxomy determined using the SILVA database. The Shannon diversity index was used to estimate bacterial diversity in each animal and then aggregated to genus level before computing the means. Animal species within the rodents and shrews were identified by amplification of mitochondrial cytochrome b (cytb) gene followed by Sanger sequencing. CLC workbench was used to assemble the cytb gene sequences, after which their phylogenetic placements were determined by querying them against the GenBank nucleotide database.

RESULTS

cytb gene sequences were generated for 49/54 mammalian samples: 38 rodents (Rodentia) and 11 shrews (Eulipotyphyla). Within the order Rodentia, 21 Acomys, eight Mastomys, six Arvicanthis and three Rattus were identified. In the order Eulipotyphyla, 11 Crucidura were identified. Bacteria characterization revealed 17 phyla that grouped into 182 genera. Of the phyla, Proteobacteria was the most abundant (67.9%). Other phyla included Actinobacteria (16.5%), Firmicutes (5.5%), Chlamydiae (3.8%), Chloroflexi (2.6%) and Bacteroidetes (1.3%) among others. Of the potentially pathogenic bacteria, Bartonella was the most abundant (45.6%), followed by Anaplasma (8.0%), Methylobacterium (3.5%), Delftia (3.8%), Coxiella (2.6%), Bradyrhizobium (1.6%) and Acinetobacter (1.1%). Other less abundant (<1%) and potentially pathogenic included Ehrlichia, Rickettsia, Leptospira, Borrelia, Brucella, Chlamydia and Streptococcus. By Shannon diversity index, Acomys spleens carried more diverse bacteria (mean Shannon diversity index of 2.86, p = 0.008) compared to 1.77 for Crocidura, 1.44 for Rattus, 1.40 for Arvicathis and 0.60 for Mastomys.

CONCLUSION

This study examined systemic bacteria that are filtered by the spleen and the findings underscore the utility of 16S rRNA deep sequencing in characterizing complex microbiota that are potentially relevant to one health issues. An inherent problem with the V3-V4 region of 16S rRNA is the inability to classify bacteria reliably beyond the genera. Future studies should utilize the newer long read methods of 16S rRNA analysis that can delimit the species composition.

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.

Serological Evidence of Yersiniosis, Tick-Borne Encephalitis, West Nile, Hepatitis E, Crimean-Congo Hemorrhagic Fever, Lyme Borreliosis, and Brucellosis in Febrile Patients Presenting at Diverse Hospitals in Kenya

Data on pathogen prevalence is crucial for informing exposure and disease risk. We evaluated serological evidence of tick-borne encephalitis (TBE), West Nile (WN), Hepatitis E virus (HEV), Crimean-Congo Hemorrhagic Fever (CCHF), Yersiniosis, Lyme Disease (LD), and brucellosis in 1033 patients presenting with acute febrile illness at 9 health care facilities from diverse ecological zones of Kenya: arid and semiarid (Garissa District Hospital, Lodwar District Hospital, Marigat District Hospital, Gilgil District Hospital), Lake Victoria basin (Kisumu District Hospital, Alupe District Hospital, Kombewa Sub-County Hospital), Kisii highland (Kisii District Hospital), and coastal (Malindi District Hospital). Epidemiological information of the patients such as geography, age, gender, and keeping animals were analyzed as potential risk factors. Of the 1033 samples, 619 (59.9%) were seropositive to at least one pathogen by IgM (current exposure), IgG/IgM (recent exposure), and IgG (past exposure). Collective seroprevalence for current, recent, and past to the pathogens was 9.4%, 5.1%, and 21.1% for LD; 3.6%, 0.5%, and 12.4% for WN; 0.9%, 0.5%, and 16.9% for HEV; 5.8%, 1.3%, and 3.9% for brucellosis; 5.7%, 0.2%, and 2.3% for yersiniosis; 1.7%, 0%, and 6.2% for TBE; and 0.4%, 0%, and 1.9% for CCHF. Brucellosis risk was higher in patients recruited at Garissa District Hospital (odds ratio [OR] = 3.41), HEV (OR = 2.45) and CCHF (OR = 5.46) in Lodwar District Hospital, LD in Alupe District Hospital (OR = 5.73), Kombewa Sub-district hospital (OR = 8.17), and Malindi District hospital (OR = 3.3). Exposure to LD was highest in the younger age group, whereas yersiniosis did not vary with age. Age was a significant risk for WN, brucellosis, CCHF, TBE, and HEV and in those aged >14 years there was an increased risk to WN (OR = 2.30, p < 0.0001), brucellosis (OR = 1.84, p = 0.005), CCHF (OR = 4.35, p = 0.001), TBE (OR = 2.78, p < 0.0001), and HEV (OR = 1.94, p = 0.0001). We conclude that LD is pervasive and constitutes a significant health burden to the study population, whereas yersiniosis and CCHF are not significant threats. Going forward, community-based studies will be needed to capture the true seroprevalence rates and the associated risk factors.

Phylogenetic Variants of Rickettsia africae, and Incidental Identification of "Candidatus Rickettsia Moyalensis" in Kenya

Background

Rickettsia africae, the etiological agent of African tick bite fever, is widely distributed in sub-Saharan Africa. Contrary to reports of its homogeneity, a localized study in Asembo, Kenya recently reported high genetic diversity. The present study aims to elucidate the extent of this heterogeneity by examining archived Rickettsia africae DNA samples collected from different eco-regions of Kenya.

Methods

To evaluate their phylogenetic relationships, archived genomic DNA obtained from 57 ticks a priori identified to contain R. africae by comparison to ompA, ompB and gltA genes was used to amplify five rickettsial genes i.e. gltA, ompA, ompB, 17kDa and sca4. The resulting amplicons were sequenced. Translated amino acid alignments were used to guide the nucleotide alignments. Single gene and concatenated alignments were used to infer phylogenetic relationships.

Results

Out of the 57 DNA samples, three were determined to be R. aeschlimanii and not R. africae. One sample turned out to be a novel rickettsiae and an interim name of “Candidatus Rickettsia moyalensis” is proposed. The bonafide R. africae formed two distinct clades. Clade I contained 9% of the samples and branched with the validated R. africae str ESF-5, while clade II (two samples) formed a distinct sub-lineage.

Conclusions

This data supports the use of multiple genes for phylogenetic inferences. It is determined that, despite its recent emergence, the R. africae lineage is diverse. This data also provides evidence of a novel Rickettsia species, Candidatus Rickettsia moyalensis.

Rickettsia africae is a bacterium mainly vectored by Amblyomma and Rhipicephalus species of ticks. It is the etiological agent of African tick bite fever (ATBF), a spotted fever rickettsiosis that presents as an acute febrile illness characterized by petecheal skin hemorrhages, from which the name is derived. This bacterium is probably the most important in sub-Saharan Africa, including Kenya, in terms of incidence and prevalence. This notwithstanding, the disease is poorly understood and is often mistreated as malaria, and therefore qualifies as a highly neglected disease. This study examined the genetic relationships of R. africae collected from diverse eco-regions of Kenya. We present data that indicate high genetic diversity in Kenya’s R. africae and corroborate a recent study that reported similar genetic diversity in R. africae samples collected from a localized area in western Kenya. Importantly, we describe a divergent lineage and propose the name Candidatus Rickettsia moyalensis.

Humoral immune responses to Plasmodium falciparum among HIV-1-infected Kenyan adults

INTRODUCTION

Humoral immune responses play a pivotal role in naturally acquired immunity to malaria. Understanding which humoral responses are impaired among individuals at higher risk for malaria may improve our understanding of malaria immune control and contribute to vaccine development.

METHODS

We compared humoral responses with 483 Plasmodium falciparum antigens between adults in, Kisumu (high, year-long malaria transmission leading to partial immunity), and adults in Kisii (low, seasonal malaria transmission). Then within each site, we compared malaria-specific humoral responses between those at higher risk for malaria (CD4(+) ≤500) and those at lower risk for malaria (CD4(+) >500). A protein microarray chip containing 483 P. falciparum antigens and 71 HIV antigens was used. Benjamini-Hochberg adjustments were made to control for multiple comparisons.

RESULTS

Fifty-seven antigens including CSP, MSP1, LSA1 and AMA1 were identified as significantly more reactive in Kisumu than in Kisii. Ten of these antigens had been identified as protective in an earlier study. CD4(+) T-cell count did not significantly impact humoral responses.

CONCLUSION

Protein microarrays are a useful method to screen multiple humoral responses simultaneously. This study provides useful clues for potential vaccine candidates. Modest decreases in CD4 counts may not significantly impact malaria-specific humoral immunity.