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Additional file 2. Supplementary figures.

Although the COVID-19 pandemic has left no country untouched there has been limited research to understand clinical and immunological responses in African populations. Here we characterise patients hospitalised with suspected (PCR-negative/IgG-positive) or confirmed (PCR-positive) COVID-19, and healthy community controls (PCR-negative/IgG-negative). PCR-positive COVID-19 participants were more likely to receive dexamethasone and a beta-lactam antibiotic, and survive to hospital discharge than PCR-negative/IgG-positive and PCR-negative/IgG-negative participants. PCR-negative/IgG-positive participants exhibited a nasal and systemic cytokine signature analogous to PCR-positive COVID-19 participants, predominated by chemokines and neutrophils and distinct from PCR-negative/IgG-negative participants. PCR-negative/IgG-positive participants had increased propensity for Staphylococcus aureus and Streptococcus pneumoniae colonisation. PCR-negative/IgG-positive individuals with high COVID-19 clinical suspicion had inflammatory profiles analogous to PCR-confirmed disease and potentially represent a target population for COVID-19 treatment strategies.

Metagenomic sequencing has the potential to transform microbial detection and characterization, but new tools are needed to improve its sensitivity. Here we present CATCH, a computational method to enhance nucleic acid capture for enrichment of diverse microbial taxa. CATCH designs optimal probe sets, with a specified number of oligonucleotides, that achieve full coverage of, and scale well with, known sequence diversity. We focus on applying CATCH to capture viral genomes in complex metagenomic samples. We design, synthesize, and validate multiple probe sets, including one that targets the whole genomes of the 356 viral species known to infect humans. Capture with these probe sets enriches unique viral content on average 18-fold, allowing us to assemble genomes that could not be recovered without enrichment, and accurately preserves within-sample diversity. We also use these probe sets to recover genomes from the 2018 Lassa fever outbreak in Nigeria and to improve detection of uncharacterized viral infections in human and mosquito samples. The results demonstrate that CATCH enables more sensitive and cost-effective metagenomic sequencing.

Despite great attention given to the recent Zika virus (ZIKV) epidemic in the Americas and its link to birth defects1,2, much remains unknown about ZIKV disease epidemiology and ZIKV evolution, in part due to a lack of genomic data. We applied multiple sequencing approaches to generate 110 ZIKV genomes from clinical and mosquito samples from 10 countries and territories, greatly expanding the observed viral genetic diversity from this outbreak. We analyzed the timing and patterns of introductions into distinct geographic regions; our phylogenetic evidence suggests rapid expansion of the outbreak in Brazil and multiple introductions of outbreak strains into Puerto Rico, Honduras, Colombia, other Caribbean islands, and the continental US. We find that ZIKV circulated undetected in multiple regions for many months before the first locally transmitted cases were confirmed, highlighting the importance of viral surveillance. We identify mutations with possible functional implications for ZIKV biology and pathogenesis, as well as those potentially relevant to the effectiveness of diagnostic tests.

Insecticide resistance in mosquito populations threatens recent successes in malaria prevention. Elucidating patterns of genetic structure in malaria vectors to predict the speed and direction of the spread of resistance is essential to get ahead of the ‘resistance curve’ and to avert a public health catastrophe. Here, applying a combination of microsatellite analysis, whole genome sequencing and targeted sequencing of a resistance locus, we elucidated the continent-wide population structure of a major African malaria vector, Anopheles funestus. We identified a major selective sweep in a genomic region controlling cytochrome P450-based metabolic resistance conferring high resistance to pyrethroids. This selective sweep occurred since 2002, likely as a direct consequence of scaled up vector control as revealed by whole genome and fine-scale sequencing of pre- and post-intervention populations. Fine-scaled analysis of the pyrethroid resistance locus revealed that a resistance-associated allele of the cytochrome P450 monooxygenase CYP6P9a has swept through southern Africa to near fixation, in contrast to high polymorphism levels before interventions, conferring high levels of pyrethroid resistance linked to control failure. Population structure analysis revealed a barrier to gene flow between southern Africa and other areas, which may prevent or slow the spread of the southern mechanism of pyrethroid resistance to other regions. By identifying a genetic signature of pyrethroid-based interventions, we have demonstrated the intense selective pressure that control interventions exert on mosquito populations. If this level of selection and spread of resistance continues unabated, our ability to control malaria with current interventions will be compromised., Author Summary Malaria control currently relies heavily on insecticide-based vector control interventions. Unfortunately, resistance to insecticides threatens the continued effectiveness of these measures. Metabolic resistance, caused by increased detoxification of insecticides, presents the greatest threat to vector control, yet it remains unclear how these mechanisms are linked to underlying genetic changes driven by the massive selection pressure from these interventions, such as the widespread use of Long Lasting Insecticide Nets (LLINs) across Africa. Therefore, understanding the direction and speed at which this operationally important form of resistance spreads through mosquito populations is essential if we are to get ahead of the ‘resistance curve’ and avert a public health catastrophe. Here, using microsatellite markers, whole genome sequencing and fine-scale sequencing at a major resistance locus, we elucidated the Africa-wide population structure of Anopheles funestus, a major African malaria vector, and detected a strong selective sweep occurring in a genomic region controlling cytochrome P450-based metabolic pyrethroid resistance in this species. Furthermore, we demonstrated that this selective sweep is driven by the scale-up of insecticide-based malaria control in Africa, highlighting the risk that if this level of selection and spread of resistance continues unabated, our ability to control malaria with current interventions will be compromised.

Resistance to pyrethroids, the sole insecticide class recommended for treating bed nets, threatens the control of major malaria vectors, including Anopheles funestus Effective management of resistance requires an understanding of the dynamics and mechanisms driving resistance. Here, using genome-wide transcription and genetic diversity analyses, we show that a shift in the molecular basis of pyrethroid resistance in southern African populations of this species is associated with a restricted gene flow. Across the most highly endemic and densely populated regions in Malawi, An. funestus is resistant to pyrethroids, carbamates, and organochlorides. Genome-wide microarray-based transcription analysis identified overexpression of cytochrome P450 genes as the main mechanism driving this resistance. The most up-regulated genes include cytochrome P450s (CYP) CYP6P9a, CYP6P9b and CYP6M7. However, a significant shift in the overexpression profile of these genes was detected across a south/north transect, with CYP6P9a and CYP6P9b more highly overexpressed in the southern resistance front and CYP6M7 predominant in the northern front. A genome-wide genetic structure analysis of southern African populations of An. funestus from Zambia, Malawi, and Mozambique revealed a restriction of gene flow between populations, in line with the geographical variation observed in the transcriptomic analysis. Genetic polymorphism analysis of the three key resistance genes, CYP6P9a, CYP6P9b, and CYP6M7, support barriers to gene flow that are shaping the underlying molecular basis of pyrethroid resistance across southern Africa. This barrier to gene flow is likely to impact the design and implementation of resistance management strategies in the region.

Background Pyrethroid resistance in the major malaria vector Anopheles funestus is rapidly expanding across Southern Africa. It remains unknown whether this resistance has a unique origin with the same molecular basis or is multifactorial. Knowledge of the origin, mechanisms and evolution of resistance are crucial to designing successful resistance management strategies. Results Here, we established the resistance profile of a Zambian An. funestus population at the northern range of the resistance front. Similar to other Southern African populations, Zambian An. funestus mosquitoes are resistant to pyrethroids and carbamate, but in contrast to populations in Mozambique and Malawi, these insects are also DDT resistant. Genome-wide microarray-based transcriptional profiling and qRT-PCR revealed that the cytochrome P450 gene CYP6M7 is responsible for extending pyrethroid resistance northwards. Indeed, CYP6M7 is more over-expressed in Zambia [fold-change (FC) 37.7; 13.2 for qRT-PCR] than CYP6P9a (FC15.6; 8.9 for qRT-PCR) and CYP6P9b (FC11.9; 6.5 for qRT-PCR), whereas CYP6P9a and CYP6P9b are more highly over-expressed in Malawi and Mozambique. Transgenic expression of CYP6M7 in Drosophila melanogaster coupled with in vitro assays using recombinant enzymes and assessments of kinetic properties demonstrated that CYP6M7 is as efficient as CYP6P9a and CYP6P9b in conferring pyrethroid resistance. Polymorphism patterns demonstrate that these genes are under contrasting selection forces: the exceptionally diverse CYP6M7 likely evolves neutrally, whereas CYP6P9a and CYP6P9b are directionally selected. The higher variability of CYP6P9a and CYP6P9b observed in Zambia supports their lesser role in resistance in this country. Conclusion Pyrethroid resistance in Southern Africa probably has multiple origins under different evolutionary forces, which may necessitate the design of different resistance management strategies. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-817) contains supplementary material, which is available to authorized users.

We used a high-density single-nucleotide polymorphism array to genotype 75 Plasmodium falciparum isolates recently collected from Senegal and The Gambia to search for signals of selection in this malaria endemic region. We found little geographic or temporal stratification of the genetic diversity among the sampled parasites. Through application of the iHS and REHH haplotype-based tests for positive selection, we found evidence of recent selective sweeps at a known drug resistance locus, at several known antigenic loci, and at several genomic regions not previously identified as sites of recent selection. We discuss the value of deep population-specific genomic analyses for identifying selection signals within sampled endemic populations of parasites, which may correspond to local selection pressures such as distinctive therapeutic regimes or mosquito vectors.