Although the recent Zika virus (ZIKV) epidemic in the Americas and its link to birth defects have attracted a great deal of attention1,2, much remains unknown about ZIKV disease epidemiology and ZIKV evolution, in part owing to a lack of genomic data. Here we address this gap in knowledge by using 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 analysed 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 United States. We find that ZIKV circulated undetected in multiple regions for many months before the first locally transmitted cases were confirmed, highlighting the importance of surveillance of viral infections. We identify mutations with possible functional implications for ZIKV biology and pathogenesis, as well as those that might be relevant to the effectiveness of diagnostic tests.

Zika virus (ZIKV) is causing an unprecedented epidemic linked to severe congenital syndromes1,2. In July 2016, mosquito-borne ZIKV transmission was reported in the continental United States and since then, hundreds of locally-acquired infections have been reported in Florida3,4. To gain insights into the timing, source, and likely route(s) of ZIKV introduction, we tracked the virus from its first detection in Florida by sequencing ZIKV genomes from infected patients and Aedes aegypti mosquitoes. We show that at least four introductions, but potentially as many as 40, contributed to the outbreak in Florida and that local transmission likely started in the spring of 2016 - several months before initial detection. By analyzing surveillance and genetic data, we discovered that ZIKV moved among transmission zones in Miami. Our analyses show that most introductions are linked to the Caribbean, a finding corroborated by the high incidence rates and traffic volumes from the region into the Miami area. Our study provides an understanding of how ZIKV initiates transmission in new regions.

H3Africa is developing capacity for health-related genomics research in Africa

New therapeutic agents for the treatment of malaria, the world's most deadly parasitic disease, are urgently needed. Malaria afflicts 300 to 500 million people and results in 1 to 2 million deaths annually, and more than 85% of all malaria-related mortality involves young children and pregnant women in sub-Saharan Africa. The emergence of multidrug-resistant parasites, especially in Plasmodium falciparum, has eroded the efficacy of almost all currently available therapeutic agents. The discovery of new drugs, including drugs with novel cellular targets, could be accelerated with a whole-organism high-throughput screen (HTS) of structurally diverse small-molecule libraries. The standard whole-organism screen is based on incorporation of [ 3 H]hypoxanthine and has liabilities, such as limited throughput, high cost, multiple labor-intensive steps, and disposal of radioactive waste. Recently, screens have been reported that do not use radioactive incorporation, but their reporter signal is not robust enough for HTS. We report a P. falciparum growth assay that is technically simple, robust, and compatible with the automation necessary for HTS. The assay monitors DNA content by addition of the fluorescent dye 4 ,6-diamidino-2-phenylindole (DAPI) as a reporter of blood-stage parasite growth. This DAPI P. falciparum growth assay was used to measure the 50% inhibitory concentrations (IC 50 s) of a diverse set of known antimalarials. The resultant IC 50 s compared favorably with those obtained in the [ 3 H]hypoxanthine incorporation assay. Over 79,000 small molecules have been tested for antiplasmodial activity using the DAPI P. falciparum growth assay, and 181 small molecules were identified as highly active against multidrug-resistant parasites.

Plasmodium vivax, one of the five species of Plasmodium parasites that cause human malaria, is responsible for 25–40% of malaria cases worldwide. Malaria global elimination efforts will benefit from accurate and effective genotyping tools that will provide insight into the population genetics and diversity of this parasite. The recent sequencing of P. vivax isolates from South America, Africa, and Asia presents a new opportunity by uncovering thousands of novel single nucleotide polymorphisms (SNPs). Genotyping a selection of these SNPs provides a robust, low-cost method of identifying parasite infections through their unique genetic signature or barcode. Based on our experience in generating a SNP barcode for P. falciparum using High Resolution Melting (HRM), we have developed a similar tool for P. vivax. We selected globally polymorphic SNPs from available P. vivax genome sequence data that were located in putatively selectively neutral sites (i.e., intergenic, intronic, or 4-fold degenerate coding). From these candidate SNPs we defined a barcode consisting of 42 SNPs. We analyzed the performance of the 42-SNP barcode on 87 P. vivax clinical samples from parasite populations in South America (Brazil, French Guiana), Africa (Ethiopia) and Asia (Sri Lanka). We found that the P. vivax barcode is robust, as it requires only a small quantity of DNA (limit of detection 0.3 ng/μl) to yield reproducible genotype calls, and detects polymorphic genotypes with high sensitivity. The markers are informative across all clinical samples evaluated (average minor allele frequency > 0.1). Population genetic and statistical analyses show the barcode captures high degrees of population diversity and differentiates geographically distinct populations. Our 42-SNP barcode provides a robust, informative, and standardized genetic marker set that accurately identifies a genomic signature for P. vivax infections.

BackgroundComplex malaria infections are defined as those containing more than one genetically distinct lineage of Plasmodium parasite. Complexity of infection (COI) is a useful parameter to estimate from patient blood samples because it is associated with clinical outcome, epidemiology and disease transmission rate. This manuscript describes a method for estimating COI using likelihood, called COIL, from a panel of bi-allelic genotyping assays.MethodsCOIL assumes that distinct parasite lineages in complex infections are unrelated and that genotyped loci do not exhibit significant linkage disequilibrium. Using the population minor allele frequency (MAF) of the genotyped loci, COIL uses the binomial distribution to estimate the likelihood of a COI level given the prevalence of observed monomorphic or polymorphic genotypes within each sample.ResultsCOIL reliably estimates COI up to a level of three or five with at least 24 or 96 unlinked genotyped loci, respectively, as determined by in silico simulation and empirical validation. Evaluation of COI levels greater than five in patient samples may require a very large collection of genotype data, making sequencing a more cost-effective approach for evaluating COI under conditions when disease transmission is extremely high. Performance of the method is positively correlated with the MAF of the genotyped loci. COI estimates from existing SNP genotype datasets create a more detailed portrait of disease than analyses based simply on the number of polymorphic genotypes observed within samples.ConclusionsThe capacity to reliably estimate COI from a genome-wide panel of SNP genotypes provides a potentially more accurate alternative to methods relying on PCR amplification of a small number of loci for estimating COI. This approach will also increase the number of applications of SNP genotype data, providing additional motivation to employ SNP barcodes for studies of disease epidemiology or control measure efficacy. The COIL program is available for download from GitHub, and users may also upload their SNP genotype data to a web interface for simple and efficient determination of sample COI.Electronic supplementary materialThe online version of this article (doi:10.1186/1475-2875-14-4) contains supplementary material, which is available to authorized users.

The interaction of the human adenovirus proteinase (AVP) with various DNAs was characterized. AVP requires two cofactors for maximal activity, the 11-amino acid residue peptide from the C-terminus of adenovirus precursor protein pVI (pVIc) and the viral DNA. DNA binding was monitored by changes in enzyme activity or by fluorescence anisotropy. The equilibrium dissociation constants for the binding of AVP and AVP-pVIc complexes to 12-mer double-stranded (ds) DNA were 63 and 2.9 nM, respectively. DNA binding was not sequence specific; the stoichiometry of binding was proportional to the length of the DNA. Three molecules of the AVP-pVIc complex bound to 18-mer dsDNA and six molecules to 36-mer dsDNA. When AVP-pVIc complexes bound to 12-mer dsDNA, two sodium ions were displaced from the DNA. A Delta of -4.6 kcal for the nonelectrostatic free energy of binding indicated that a substantial component of the binding free energy results from nonspecific interactions between the AVP-pVIc complex and DNA. The cofactors altered the interaction of the enzyme with the fluorogenic substrate (Leu-Arg-Gly-Gly-NH)2-rhodamine. In the absence of any cofactor, the Km was 94.8 microM and the kcat was 0.002 s(-1). In the presence of adenovirus DNA, the Km decreased 10-fold and the kcat increased 11-fold. In the presence of pVIc, the Km decreased 10-fold and the kcat increased 118-fold. With both cofactors present, the kcat/Km ratio increased 34000-fold, compared to that with AVP alone. Binding to DNA was coincident with stimulation of proteinase activity by DNA. Although other proteinases have been shown to bind to DNA, stimulation of proteinase activity by DNA is unprecedented. A model is presented suggesting that AVP moves along the viral DNA looking for precursor protein cleavage sites much like RNA polymerase moves along DNA looking for a promoter.

The interaction of the human adenovirus proteinase (AVP) and AVP-DNA complexes with the 11-amino acid cofactor pVIc was characterized. The equilibrium dissociation constant for the binding of pVIc to AVP was 4.4 microM. The binding of AVP to 12-mer single-stranded DNA decreased the K(d) for the binding of pVIc to AVP to 0.09 microM. The pVIc-AVP complex hydrolyzed the substrate with a Michaelis constant (K(m)) of 3.7 microM and a catalytic rate constant (k(cat)) of 1.1 s(-1). In the presence of DNA, the K(m) increased less than 2-fold, and the k(cat) increased 3-fold. Alanine-scanning mutagenesis was performed to determine the contribution of individual pVIc side chains in the binding and stimulation of AVP. Two amino acid residues, Gly1' and Phe11', were the major determinants in the binding of pVIc to AVP, while Val2' and Phe11' were the major determinants in stimulating enzyme activity. Binding of AVP to DNA greatly suppressed the effects of the alanine substitutions on the binding of mutant pVIcs to AVP. Binding of either or both of the cofactors, pVIc or the viral DNA, to AVP did not dramatically alter its secondary structure as determined by vacuum ultraviolet circular dichroism. pVIc, when added to Hep-2 cells infected with adenovirus serotype 5, inhibited the synthesis of infectious virus, presumably by prematurely activating the proteinase so that it cleaved virion precursor proteins before virion assembly, thereby aborting the infection.