Africa in the era of pathogen genomics: Unlocking data barriers.

Rapid expansion of pathogen sequencing capacity in Africa has led to a paradigm shift from relying on others to locally generating genomic data and sharing it with the global community. However, several barriers remain to be unlocked for timely processing, analysis, dissemination, and effective use of pathogen sequence data for pandemic prevention, preparedness, and response.

Africa Needs a New Public Health Order to Tackle Infectious Disease Threats.

The SARS-CoV-2 pandemic has revealed that Africa needs a new public health order to be resilient, to adapt, and to cope with 21st-century disease threats. The new order will need strengthened continental and national public health institutions; local manufacturing of vaccines, therapeutics, and diagnostics; attraction, training, and retention of a public health workforce; and fostering of respectful local and international partnerships.

Urgent need for a non-discriminatory and non-stigmatizing nomenclature for monkeypox virus.

We propose a novel, non-discriminatory classification of monkeypox virus diversity. Together with the World Health Organization, we named three clades (I, IIa and IIb) in order of detection. Within IIb, the cause of the current global outbreak, we identified multiple lineages (A.1, A.2, A.1.1 and B.1) to support real-time genomic surveillance.

Sensitive, Highly Multiplexed Sequencing of Microhaplotypes From the Plasmodium falciparum Heterozygome.

BACKGROUND: Targeted next-generation sequencing offers the potential for consistent, deep coverage of information-rich genomic regions to characterize polyclonal Plasmodium falciparum infections. However, methods to identify and sequence these genomic regions are currently limited. METHODS: A bioinformatic pipeline and multiplex methods were developed to identify and simultaneously sequence 100 targets and applied to dried blood spot (DBS) controls and field isolates from Mozambique. For comparison, whole-genome sequencing data were generated for the same controls. RESULTS: Using publicly available genomes, 4465 high-diversity genomic regions suited for targeted sequencing were identified, representing the P. falciparum heterozygome. For this study, 93 microhaplotypes with high diversity (median expected heterozygosity = 0.7) were selected along with 7 drug resistance loci. The sequencing method achieved very high coverage (median 99%), specificity (99.8%), and sensitivity (90% for haplotypes with 5% within sample frequency in dried blood spots with 100 parasites/µL). In silico analyses revealed that microhaplotypes provided much higher resolution to discriminate related from unrelated polyclonal infections than biallelic single-nucleotide polymorphism barcodes. CONCLUSIONS: The bioinformatic and laboratory methods outlined here provide a flexible tool for efficient, low-cost, high-throughput interrogation of the P. falciparum genome, and can be tailored to simultaneously address multiple questions of interest in various epidemiological settings.

Parasite genetic diversity reflects continued residual malaria transmission in Vhembe District, a hotspot in the Limpopo Province of South Africa.

BACKGROUND: South Africa aims to eliminate malaria transmission by 2023. However, despite sustained vector control efforts and case management interventions, the Vhembe District remains a malaria transmission hotspot. To better understand Plasmodium falciparum transmission dynamics in the area, this study characterized the genetic diversity of parasites circulating within the Vhembe District. METHODS: A total of 1153 falciparum-positive rapid diagnostic tests (RDTs) were randomly collected from seven clinics within the district, over three consecutive years (2016, 2017 and 2018) during the wet and dry malaria transmission seasons. Using 26 neutral microsatellite markers, differences in genetic diversity were described using a multiparameter scale of multiplicity of infection (MOI), inbreeding metric (Fws), number of unique alleles (A), expected heterozygosity (He), multilocus linkage disequilibrium (LD) and genetic differentiation, and were associated with temporal and geospatial variances. RESULTS: A total of 747 (65%) samples were successfully genotyped. Moderate to high genetic diversity (mean He = 0.74 ± 0.03) was observed in the parasite population. This was ascribed to high allelic richness (mean A = 12.2 ± 1.2). The majority of samples (99%) had unique multi-locus genotypes, indicating high genetic diversity in the sample set. Complex infections were observed in 66% of samples (mean MOI = 2.13 ± 0.04), with 33% of infections showing high within-host diversity as described by the Fws metric. Low, but significant LD (standardised index of association, ISA = 0.08, P < 0.001) was observed that indicates recombination of distinct clones. Limited impact of temporal (FST range - 0.00005 to 0.0003) and spatial (FST = - 0.028 to 0.023) variation on genetic diversity existed during the sampling timeframe and study sites respectively. CONCLUSIONS: Consistent with the Vhembe District's classification as a 'high' transmission setting within South Africa, P. falciparum diversity in the area was moderate to high and complex. This study showed that genetic diversity within the parasite population reflects the continued residual transmission observed in the Vhembe District. This data can be used as a reference point for the assessment of the effectiveness of on-going interventions over time, the identification of imported cases and/or outbreaks, as well as monitoring for the potential spread of anti-malarial drug resistance.

Optimization of whole-genome sequencing of Plasmodium falciparum from low-density dried blood spot samples.

BACKGROUND: Whole-genome sequencing (WGS) is becoming increasingly useful to study the biology, epidemiology, and ecology of malaria parasites. Despite ease of sampling, DNA extracted from dried blood spots (DBS) has a high ratio of human DNA compared to parasite DNA, which poses a challenge for downstream genetic analyses. The effects of multiple methods for DNA extraction, digestion of methylated DNA, and amplification were evaluated on the quality and fidelity of WGS data recovered from DBS. METHODS: Low parasite density mock DBS samples were created, extracted either with Tween-Chelex or QIAamp, treated with or without McrBC, and amplified with one of three different amplification techniques (two sWGA primer sets and one rWGA). Extraction conditions were evaluated on performance of sequencing depth, percentiles of coverage, and expected SNP concordance. RESULTS: At 100 parasites/µL, Chelex-Tween-McrBC samples had higher coverage (5 × depth = 93% genome) than QIAamp extracted samples (5 × depth = 76% genome). The two evaluated sWGA primer sets showed minor differences in overall genome coverage and SNP concordance, with a newly proposed combination of 20 primers showing a modest improvement in coverage over those previously published. CONCLUSIONS: Overall, Tween-Chelex extracted samples that were treated with McrBC digestion and are amplified using 6A10AD sWGA conditions had minimal dropout rate, higher percentages of coverage at higher depth, and more accurate SNP concordance than QiaAMP extracted samples. These findings extend the results of previously reported methods, making whole genome sequencing accessible to a larger number of low density samples that are commonly encountered in cross-sectional surveys.

Confirmation of the absence of local transmission and geographic assignment of imported falciparum malaria cases to China using microsatellite panel.

BACKGROUND: Current methods to classify local and imported malaria infections depend primarily on patient travel history, which can have limited accuracy. Genotyping has been investigated as a complementary approach to track the spread of malaria and identify the origin of imported infections. METHODS: An extended panel of 26 microsatellites (16 new microsatellites) for Plasmodium falciparum was evaluated in 602 imported infections from 26 sub-Saharan African countries to the Jiangsu Province of People's Republic of China. The potential of the 26 microsatellite markers to assign imported parasites to their geographic origin was assessed using a Bayesian method with Markov Chain Monte Carlo (MCMC) as implemented in the program Smoothed and Continuous Assignments (SCAT) with a modification to incorporate haploid genotype data. RESULTS: The newly designed microsatellites were polymorphic and are not in linkage disequilibrium with the existing microsatellites, supporting previous findings of high rate of recombination in sub-Saharan Africa. Consistent with epidemiology inferred from patients' travel history, no evidence for local transmission was found; nearly all genetically related infections were identified in people who travelled to the same country near the same time. The smoothing assignment method assigned imported cases to their likely geographic origin with an accuracy (Angola: 59%; Nigeria: 51%; Equatorial Guinea: 40%) higher than would be achieved at random, reaching statistical significance for Angola and Equatorial Guinea. CONCLUSIONS: Genotyping using an extended microsatellite panel is valuable for malaria case classification and programme evaluation in an elimination setting. A Bayesian method for assigning geographic origin of mammals based on genetic data was adapted for malaria and showed potential for identification of the origin of imported infections.

High Genetic Diversity of Plasmodium falciparum in the Low-Transmission Setting of the Kingdom of Eswatini.

BACKGROUND: To better understand transmission dynamics, we characterized Plasmodium falciparum genetic diversity in Eswatini, where transmission is low and sustained by importation. METHODS: Twenty-six P. falciparum microsatellites were genotyped in 66% of confirmed cases (2014-2016; N = 582). Population and within-host diversity were used to characterize differences between imported and locally acquired infections. Logistic regression was used to assess the added value of diversity metrics to classify imported and local infections beyond epidemiology data alone. RESULTS: Parasite population in Eswatini was highly diverse (expected heterozygosity [HE] = 0.75) and complex: 67% polyclonal infections, mean multiplicity of infection (MOI) 2.2, and mean within-host infection fixation index (FWS) 0.84. Imported cases had comparable diversity to local cases but exhibited higher MOI (2.4 vs 2.0; P = .004) and lower mean FWS (0.82 vs 0.85; P = .03). Addition of MOI and FWS to multivariate analyses did not increase discrimination between imported and local infections. CONCLUSIONS: In contrast to the common perception that P. falciparum diversity declines with decreasing transmission intensity, Eswatini isolates exhibited high parasite diversity consistent with high rates of malaria importation and limited local transmission. Estimates of malaria transmission intensity from genetic data need to consider the effect of importation, especially as countries near elimination.

Applying next-generation sequencing to track falciparum malaria in sub-Saharan Africa.

Next-generation sequencing (NGS) technologies are increasingly being used to address a diverse range of biological and epidemiological questions. The current understanding of malaria transmission dynamics and parasite movement mainly relies on the analyses of epidemiologic data, e.g. case counts and self-reported travel history data. However, travel history data are often not routinely collected or are incomplete, lacking the necessary level of accuracy. Although genetic data from routinely collected field samples provides an unprecedented opportunity to track the spread of malaria parasites, it remains an underutilized resource for surveillance due to lack of local awareness and capacity, limited access to sensitive laboratory methods and associated computational tools and difficulty in interpreting genetic epidemiology data. In this review, the potential roles of NGS in better understanding of transmission patterns, accurately tracking parasite movement and addressing the emerging challenges of imported malaria in low transmission settings of sub-Saharan Africa are discussed. Furthermore, this review highlights the insights gained from malaria genomic research and challenges associated with integrating malaria genomics into existing surveillance tools to inform control and elimination strategies.

Drug-Resistance and Population Structure of Plasmodium falciparum Across the Democratic Republic of Congo Using High-Throughput Molecular Inversion Probes.

A better understanding of the drivers of the spread of malaria parasites and drug resistance across space and time is needed. These drivers can be elucidated using genetic tools. Here, a novel molecular inversion probe (MIP) panel targeting all major drug-resistance mutations and a set of microsatellites was used to genotype Plasmodium falciparum infections of 552 children from the 2013-2014 Demographic and Health Survey conducted in the Democratic Republic of the Congo (DRC). Microsatellite-based analysis of population structure suggests that parasites within the DRC form a homogeneous population. In contrast, sulfadoxine-resistance markers in dihydropteroate synthase show marked spatial structure with ongoing spread of double and triple mutants compared with 2007. These findings suggest that parasites in the DRC remain panmictic despite rapidly spreading antimalarial-resistance mutations. Moreover, highly multiplexed targeted sequencing using MIPs emerges as a cost-effective method for elucidating pathogen genetics in complex infections in large cohorts.

Antibodies to Intercellular Adhesion Molecule 1-Binding Plasmodium falciparum Erythrocyte Membrane Protein 1-DBLß Are Biomarkers of Protective Immunity to Malaria in a Cohort of Young Children from Papua New Guinea.

Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) mediates parasite sequestration to the cerebral microvasculature via binding of DBLß domains to intercellular adhesion molecule 1 (ICAM1) and is associated with severe cerebral malaria. In a cohort of 187 young children from Papua New Guinea (PNG), we examined baseline levels of antibody to the ICAM1-binding PfEMP1 domain, DBLß3PF11_0521, in comparison to four control antigens, including NTS-DBLα and CIDR1 domains from another group A variant and a group B/C variant. Antibody levels for the group A antigens were strongly associated with age and exposure. Antibody responses to DBLß3PF11_0521 were associated with a 37% reduced risk of high-density clinical malaria in the follow-up period (adjusted incidence risk ratio [aIRR] = 0.63 [95% confidence interval {CI}, 0.45 to 0.88; P = 0.007]) and a 25% reduction in risk of low-density clinical malaria (aIRR = 0.75 [95% CI, 0.55 to 1.01; P = 0.06]), while there was no such association for other variants. Children who experienced severe malaria also had significantly lower levels of antibody to DBLß3PF11_0521 and the other group A domains than those that experienced nonsevere malaria. Furthermore, a subset of PNG DBLß sequences had ICAM1-binding motifs, formed a distinct phylogenetic cluster, and were similar to sequences from other areas of endemicity. PfEMP1 variants associated with these DBLß domains were enriched for DC4 and DC13 head structures implicated in endothelial protein C receptor (EPCR) binding and severe malaria, suggesting conservation of dual binding specificities. These results provide further support for the development of specific classes of PfEMP1 as vaccine candidates and as biomarkers for protective immunity against clinical P. falciparum malaria.

Phylogeography of var gene repertoires reveals fine-scale geospatial clustering of Plasmodium falciparum populations in a highly endemic area.

Plasmodium falciparum malaria is a major global health problem that is being targeted for progressive elimination. Knowledge of local disease transmission patterns in endemic countries is critical to these elimination efforts. To investigate fine-scale patterns of malaria transmission, we have compared repertoires of rapidly evolving var genes in a highly endemic area. A total of 3680 high-quality DBLα-sequences were obtained from 68 P. falciparum isolates from ten villages spread over two distinct catchment areas on the north coast of Papua New Guinea (PNG). Modelling of the extent of var gene diversity in the two parasite populations predicts more than twice as many var gene alleles circulating within each catchment (Mugil = 906; Wosera = 1094) than previously recognized in PNG (Amele = 369). In addition, there were limited levels of var gene sharing between populations, consistent with local parasite population structure. Phylogeographic analyses demonstrate that while neutrally evolving microsatellite markers identified population structure only at the catchment level, var gene repertoires reveal further fine-scale geospatial clustering of parasite isolates. The clustering of parasite isolates by village in Mugil, but not in Wosera was consistent with the physical and cultural isolation of the human populations in the two catchments. The study highlights the microheterogeneity of P. falciparum transmission in highly endemic areas and demonstrates the potential of var genes as markers of local patterns of parasite population structure.

Boosting pathogen genomics and bioinformatics workforce in Africa.

Next-generation sequencing (NGS) of genomic data has established its fundamental value in public health surveillance, research and development, and precision medicine. In Africa, severe shortages of competent experts in genomics and bioinformatics, few opportunities for research, and inadequate genomic infrastructure have had a knock-on effect on the use of NGS technologies for research and public health practice. Several reasons-ranging from poor funding, inadequate infrastructure for training and practice, to brain drain-might partly account for the scarcity of genomics and bioinformatics expertise in the region. In recognition of these shortcomings and the importance of NGS genomic data, which was amplified during the COVID-19 pandemic in mid-2021, the Africa Centres for Disease Control and Prevention (Africa CDC) through the Africa Pathogen Genomics Initiative began building and expanding Africa's workforce in pathogen surveillance. By the end of 2022, the Africa CDC in collaboration with its partners and centres of excellence had trained 413 personnel, mostly from public health institutions, in 53 (96%) of 55 African Union Member States. Although this training has increased genomics, bioinformatics, and genomic epidemiology literacy, and genomic-informed pathogen surveillance, there is still a need for a strategic and sustainable public health workforce development in Africa.

Population structure and genetic connectivity of Plasmodium falciparum in pre-elimination settings of Southern Africa.

To accelerate malaria elimination in the Southern African region by 2030, it is essential to prevent cross-border malaria transmission. However, countries within the region are highly interconnected due to human migration that aids in the movement of the parasite across geographical borders. It is therefore important to better understand Plasmodium falciparum transmission dynamics in the region, and identify major parasite source and sink populations, as well as cross-border blocks of high parasite connectivity. We performed a meta-analysis using collated parasite allelic data generated by microsatellite genotyping of malaria parasites from Namibia, Eswatini, South Africa, and Mozambique (N = 5,314). The overall number of unique alleles was significantly higher (P ≤ 0.01) in Namibia (mean A = 17.3 ± 1.46) compared to South Africa (mean A = 12.2 ± 1.22) and Eswatini (mean A = 13.3 ± 1.27, P ≤ 0.05), whilst the level of heterozygosity was not significantly different between countries. The proportion of polyclonal infections was highest for Namibia (77%), and lowest for Mozambique (64%). A was significant population structure was detected between parasites from the four countries, and patterns of gene flow showed that Mozambique was the major source area and Eswatini the major sink area of parasites between the countries. This study showed strong signals of parasite population structure and genetic connectivity between malaria parasite populations across national borders. This calls for strengthening the harmonization of malaria control and elimination efforts between countries in the southern African region. This data also proves its potential utility as an additional surveillance tool for malaria surveillance on both a national and regional level for the identification of imported cases and/or outbreaks, as well as monitoring for the potential spread of anti-malarial drug resistance as countries work towards malaria elimination.

Unlocking the Potential of Genomic Data to Inform Typhoid Fever Control Policy: Supportive Resources for Genomic Data Generation, Analysis, and Visualization.

The global response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic demonstrated the value of timely and open sharing of genomic data with standardized metadata to facilitate monitoring of the emergence and spread of new variants. Here, we make the case for the value of Salmonella Typhi (S. Typhi) genomic data and demonstrate the utility of freely available platforms and services that support the generation, analysis, and visualization of S. Typhi genomic data on the African continent and more broadly by introducing the Africa Centres for Disease Control and Prevention's Pathogen Genomics Initiative, SEQAFRICA, Typhi Pathogenwatch, TyphiNET, and the Global Typhoid Genomics Consortium.

Genomic Epidemiology of SARS-CoV-2 in Seychelles, 2020-2021.

Seychelles, an archipelago of 155 islands in the Indian Ocean, had confirmed 24,788 cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the 31st of December 2021. The first SARS-CoV-2 cases in Seychelles were reported on the 14th of March 2020, but cases remained low until January 2021, when a surge was observed. Here, we investigated the potential drivers of the surge by genomic analysis of 1056 SARS-CoV-2 positive samples collected in Seychelles between 14 March 2020 and 31 December 2021. The Seychelles genomes were classified into 32 Pango lineages, 1042 of which fell within four variants of concern, i.e., Alpha, Beta, Delta and Omicron. Sporadic cases of SARS-CoV-2 detected in Seychelles in 2020 were mainly of lineage B.1 (lineage predominantly observed in Europe) but this lineage was rapidly replaced by Beta variant starting January 2021, and which was also subsequently replaced by the Delta variant in May 2021 that dominated till November 2021 when Omicron cases were identified. Using the ancestral state reconstruction approach, we estimated that at least 78 independent SARS-CoV-2 introduction events occurred in Seychelles during the study period. The majority of viral introductions into Seychelles occurred in 2021, despite substantial COVID-19 restrictions in place during this period. We conclude that the surge of SARS-CoV-2 cases in Seychelles in January 2021 was primarily due to the introduction of more transmissible SARS-CoV-2 variants into the islands.

Genomic-informed pathogen surveillance in Africa: opportunities and challenges.

The ongoing COVID-19 pandemic has highlighted the need to incorporate pathogen genomics for enhanced disease surveillance and outbreak management in Africa. The genomics of SARS-CoV-2 has been instrumental to the timely development of diagnostics and vaccines and in elucidating transmission dynamics. Global disease control programmes, including those for tuberculosis, malaria, HIV, foodborne pathogens, and antimicrobial resistance, also recommend genomics-based surveillance as an integral strategy towards control and elimination of these diseases. Despite the potential benefits, capacity remains low for many public health programmes in Africa. The COVID-19 pandemic presents an opportunity to reassess and strengthen surveillance systems and potentially integrate emerging technologies for preparedness of future epidemics and control of endemic diseases. We discuss opportunities and challenges for integrating pathogen genomics into public health surveillance systems in Africa. Improving accessibility through the creation of functional continent-wide networks, building multipathogen sequencing cores, training a critical mass of local experts, development of standards and policies to facilitate best practices for data sharing, and establishing a community of practice of genomics experts are all needed to use genomics for improved disease surveillance in Africa. Coordination and leadership are also crucial, which the Africa Centres for Disease Control and Prevention seeks to provide through its institute for pathogen genomics.

A review of the frequencies of Plasmodium falciparum Kelch 13 artemisinin resistance mutations in Africa.

Artemisinin resistance (AR) emerged in South East Asia 13 years ago and the identification of the resistance conferring molecular marker, Plasmodium falciparum Kelch 13 (Pfk13), 7 years ago has provided an invaluable tool for monitoring AR in malaria endemic countries. Molecular Pfk13 surveillance revealed the resistance foci in the Greater Mekong Subregion, an independent emergence in Guyana, South America, and a low frequency of mutations in Africa. The recent identification of the R561H Pfk13 AR associated mutation in Tanzania, Uganda and in Rwanda, where it has been associated with delayed parasite clearance, should be a concern for the continent. In this review, we provide a summary of Pfk13 resistance associated propeller domain mutation frequencies across Africa from 2012 to 2020, to examine how many other countries have identified these mutations. Only four African countries reported a recent identification of the M476I, P553L, R561H, P574L, C580Y and A675V Pfk13 mutations at low frequencies and with no reports of clinical treatment failure, except for Rwanda. These mutations present a threat to malaria control across the continent, since the greatest burden of malaria remains in Africa. A rise in the frequency of these mutations and their spread would reverse the gains made in the reduction of malaria over the last 20 years, given the lack of new antimalarial treatments in the event artemisinin-based combination therapies fail. The review highlights the frequency of Pfk13 propeller domain mutations across Africa, providing an up-to-date perspective of Pfk13 mutations, and appeals for an urgent and concerted effort to monitoring antimalarial resistance markers in Africa and the efficacy of antimalarials by re-establishing sentinel surveillance systems.

Spatial and genetic clustering of Plasmodium falciparum and Plasmodium vivax infections in a low-transmission area of Ethiopia.

The distribution of malaria infections is heterogeneous in space and time, especially in low transmission settings. Understanding this clustering may allow identification and targeting of pockets of transmission. In Adama district, Ethiopia, Plasmodium falciparum and P. vivax malaria patients and controls were examined, together with household members and immediate neighbors. Rapid diagnostic test and quantitative PCR (qPCR) were used for the detection of infections that were genetically characterized by a panel of microsatellite loci for P. falciparum (26) and P. vivax (11), respectively. Individuals living in households of clinical P. falciparum patients were more likely to have qPCR detected P. falciparum infections (22.0%, 9/41) compared to individuals in control households (8.7%, 37/426; odds ratio, 2.9; 95% confidence interval, 1.3-6.4; P = .007). Genetically related P. falciparum, but not P. vivax infections showed strong clustering within households. Genotyping revealed a marked temporal cluster of P. falciparum infections, almost exclusively comprised of clinical cases. These findings uncover previously unappreciated transmission dynamics and support a rational approach to reactive case detection strategies for P. falciparum in Ethiopia.