The origin of island populations of the African malaria mosquito, Anopheles coluzzii.

Anopheles coluzzii is a major malaria vector throughout its distribution in west-central Africa. Here we present a whole-genome study of 142 specimens from nine countries in continental Africa and three islands in the Gulf of Guinea. This sample set covers a large part of this species' geographic range. Our population genomic analyses included a description of the structure of mainland populations, island populations, and connectivity between them. Three genetic clusters are identified among mainland populations and genetic distances (FST) fits an isolation-by-distance model. Genomic analyses are applied to estimate the demographic history and ancestry for each island. Taken together with the unique biogeography and history of human occupation for each island, they present a coherent explanation underlying levels of genetic isolation between mainland and island populations. We discuss the relationship of our findings to the suitability of São Tomé and Príncipe islands as candidate sites for potential field trials of genetic-based malaria control strategies.

Abundance of conserved CRISPR-Cas9 target sites within the highly polymorphic genomes of Anopheles and Aedes mosquitoes.

A number of recent papers report that standing genetic variation in natural populations includes ubiquitous polymorphisms within target sites for Cas9-based gene drive (CGD) and that these "drive resistant alleles" (DRA) preclude the successful application of CGD for managing these populations. Here we report the results of a survey of 1280 genomes of the mosquitoes Anopheles gambiae, An. coluzzii, and Aedes aegypti in which we determine that ~90% of all protein-encoding CGD target genes in natural populations include at least one target site with no DRAs at a frequency of ≥1.0%. We conclude that the abundance of conserved target sites in mosquito genomes and the inherent flexibility in CGD design obviates the concern that DRAs present in the standing genetic variation of mosquito populations will be detrimental to the deployment of this technology for population modification strategies.

Transcontinental dispersal of Anopheles gambiae occurred from West African origin via serial founder events.

The mosquito Anopheles gambiae s.s. is distributed across most of sub-Saharan Africa and is of major scientific and public health interest for being an African malaria vector. Here we present population genomic analyses of 111 specimens sampled from west to east Africa, including the first whole genome sequences from oceanic islands, the Comoros. Genetic distances between populations of A. gambiae are discordant with geographic distances but are consistent with a stepwise migration scenario in which the species increases its range from west to east Africa through consecutive founder events over the last ~200,000 years. Geological barriers like the Congo River basin and the East African rift seem to play an important role in shaping this process. Moreover, we find a high degree of genetic isolation of populations on the Comoros, confirming the potential of these islands as candidate sites for potential field trials of genetically engineered mosquitoes for malaria control.

Introgression between Anopheles gambiae and Anopheles coluzzii in Burkina Faso and its associations with kdr resistance and Plasmodium infection.

BACKGROUND: Insecticide resistance in Anopheles coluzzii mosquitoes has become widespread throughout West Africa including in Burkina Faso. The insecticide resistance allele (kdr or L1014F) is a prime indicator that is highly correlated with phenotypic resistance in West Africa. Studies from Benin, Ghana and Mali have suggested that the source of the L1014F is introgression of the 2L divergence island via interspecific hybridization with Anopheles gambiae. The goal of this study was to characterize local mosquito populations in the Nouna Department, Burkina Faso with respect to: (i) the extent of introgression between An. coluzzii and An. gambiae, (ii) the frequency of the L1014F mutation and (iii) Plasmodium infection rates. METHODS: A total of 95 mosquitoes were collected from ten sites surrounding Nouna town in Kossi Province, Burkina Faso in 2012. The species composition, the extent of introgression in An. coluzzii mosquitoes and their Plasmodium infection rates were identified with a modified version of the "Divergence Island SNP" (DIS) genotyping assay. RESULTS: The mosquito collection contained 70.5% An. coluzzii, 89.3% of which carried a 3 Mb genomic region on the 2L chromosome with L1014F insecticide resistance mutation that was introgressed from An. gambiae. In addition, 22.4% in the introgressed An. coluzzii specimens were infected with Plasmodium falciparum, whereas none of the non-introgressed ("pure") An. coluzzii were infected. CONCLUSION: This paper is the first report providing divergence island SNP genotypes for natural population of Burkina Faso and corresponding Plasmodium infection rates. These observations warrant further study and could have a major impact on future malaria control strategies in Burkina Faso.

Genome-wide divergence among invasive populations of Aedes aegypti in California.

BACKGROUND: In the summer of 2013, Aedes aegypti Linnaeus was first detected in three cities in central California (Clovis, Madera and Menlo Park). It has now been detected in multiple locations in central and southern CA as far south as San Diego and Imperial Counties. A number of published reports suggest that CA populations have been established from multiple independent introductions. RESULTS: Here we report the first population genomics analyses of Ae. aegypti based on individual, field collected whole genome sequences. We analyzed 46 Ae. aegypti genomes to establish genetic relationships among populations from sites in California, Florida and South Africa. Based on 4.65 million high quality biallelic SNPs, we identified 3 major genetic clusters within California; one that includes all sample sites in the southern part of the state (South of Tehachapi mountain range) plus the town of Exeter in central California and two additional clusters in central California. CONCLUSIONS: A lack of concordance between mitochondrial and nuclear genealogies suggests that the three founding populations were polymorphic for two main mitochondrial haplotypes prior to being introduced to California. One of these has been lost in the Clovis populations, possibly by a founder effect. Genome-wide comparisons indicate extensive differentiation between genetic clusters. Our observations support recent introductions of Ae. aegypti into California from multiple, genetically diverged source populations. Our data reveal signs of hybridization among diverged populations within CA. Genetic markers identified in this study will be of great value in pursuing classical population genetic studies which require larger sample sizes.

The fate of genes that cross species boundaries after a major hybridization event in a natural mosquito population.

Animal species are able to acquire new genetic material via hybridization and subsequent introgression. However, little is known about how foreign genomic material is incorporated into a population over time and what genes are susceptible to introgression. Here, we follow the closely related mosquito sister species Anopheles coluzzii and Anopheles gambiae in a sympatric natural population in Mali at multiple time points spanning a period of 25 years. During this period, we observed the temporary breakdown of mating barriers, which allowed us to explore the fate of alleles that crossed the species boundary in a natural population. Whole genome sequencing of 74 individuals revealed introgression within only 34 genes (0.26% of total genes) from A. gambiae to A. coluzzii, the majority contained within a 4 Mb region on the 2L chromosome which includes the insecticide resistance gene (AGAP004707). We designed a genotyping assay to follow 25 of the 34 introgressed alleles over time and found that all A. gambiae alleles, except four, reached a frequency of 50% in the A. coluzzii population within 4 years (~50 generations) and increased to ~80% within 6 years (~75 generations). However, the frequency of all introgressed alleles, except three, decreased to ~60% in 2016. This suggests an ongoing process of purifying selection in the population against DNA of foreign ancestry, except for alleles that are under positive selection, resulting in a complex genomic landscape. This study shows that stable introgression is limited to only specific genes even within closely related species.

Mitochondrial genomes of Anopheles arabiensis, An. gambiae and An. coluzzii show no clear species division.

Here we report the complete mitochondrial sequences of 70 individual field collected mosquito specimens from throughout Sub-Saharan Africa. We generated this dataset to identify species specific markers for the following Anopheles species and chromosomal forms: An. arabiensis, An. coluzzii (The Forest and Mopti chromosomal forms) and An. gambiae (The Bamako and Savannah chromosomal forms).  The raw Illumina sequencing reads were mapped to the NC_002084 reference mitogenome sequence. A total of 783 single nucleotide polymorphisms (SNPs) were detected on the mitochondrial genome, of which 460 are singletons (58.7%). None of these SNPs are suitable as molecular markers to distinguish among An. arabiensis, An. coluzzii and An. gambiae or any of the chromosomal forms. The lack of species or chromosomal form specific markers is also reflected in the constructed phylogenetic tree, which shows no clear division among the operational taxonomic units considered here.

Complete mitogenome sequence of Aedes (Stegomyia) aegypti derived from field isolates from California and South Africa.

The Aedes aegypti mitogenome (Mt) sequences of field isolates from California and South Africa revealed a deletion between position 14,522 and 14,659 of the Mt contig of the AaegL5 reference genome. The length of the mitogenome of the California isolate was 16,659 bp and had 99.0% similarity with the AaegL5 Mt contig. The South African isolate sequence was 16,600 bp long and had 97.9% similarity with the reference. The region between 1496 and 1664 bp is similar to a nuclear pseudogene that might be a copy of a portion of the mitochondrial genome.

Model-based quantification of metabolic interactions from dynamic microbial-community data.

An important challenge in microbial ecology is to infer metabolic-exchange fluxes between growing microbial species from community-level data, concerning species abundances and metabolite concentrations. Here we apply a model-based approach to integrate such experimental data and thereby infer metabolic-exchange fluxes. We designed a synthetic anaerobic co-culture of Clostridium acetobutylicum and Wolinella succinogenes that interact via interspecies hydrogen transfer and applied different environmental conditions for which we expected the metabolic-exchange rates to change. We used stoichiometric models of the metabolism of the two microorganisms that represents our current physiological understanding and found that this understanding - the model - is sufficient to infer the identity and magnitude of the metabolic-exchange fluxes and it suggested unexpected interactions. Where the model could not fit all experimental data, it indicates specific requirement for further physiological studies. We show that the nitrogen source influences the rate of interspecies hydrogen transfer in the co-culture. Additionally, the model can predict the intracellular fluxes and optimal metabolic exchange rates, which can point to engineering strategies. This study therefore offers a realistic illustration of the strengths and weaknesses of model-based integration of heterogenous data that makes inference of metabolic-exchange fluxes possible from community-level experimental data.

Systems modeling approaches for microbial community studies: from metagenomics to inference of the community structure.

Microbial communities play important roles in health, industrial applications and earth's ecosystems. With current molecular techniques we can characterize these systems in unprecedented detail. However, such methods provide little mechanistic insight into how the genetic properties and the dynamic couplings between individual microorganisms give rise to their dynamic activities. Neither do they give insight into what we call "the community state", that is the fluxes and concentrations of nutrients within the community. This knowledge is a prerequisite for rational control and intervention in microbial communities. Therefore, the inference of the community structure from experimental data is a major current challenge. We will argue that this inference problem requires mathematical models that can integrate heterogeneous experimental data with existing knowledge. We propose that two types of models are needed. Firstly, mathematical models that integrate existing genomic, physiological, and physicochemical information with metagenomics data so as to maximize information content and predictive power. This can be achieved with the use of constraint-based genome-scale stoichiometric modeling of community metabolism which is ideally suited for this purpose. Next, we propose a simpler coarse-grained model, which is tailored to solve the inference problem from the experimental data. This model unambiguously relate to the more detailed genome-scale stoichiometric models which act as heterogeneous data integrators. The simpler inference models are, in our opinion, key to understanding microbial ecosystems, yet until now, have received remarkably little attention. This has led to the situation where the modeling of microbial communities, using only genome-scale models is currently more a computational, theoretical exercise than a method useful to the experimentalist.

Resolving phenylalanine metabolism sheds light on natural synthesis of penicillin G in Penicillium chrysogenum.

The industrial production of penicillin G by Penicillium chrysogenum requires the supplementation of the growth medium with the side chain precursor phenylacetate. The growth of P. chrysogenum with phenylalanine as the sole nitrogen source resulted in the extracellular production of phenylacetate and penicillin G. To analyze this natural pathway for penicillin G production, chemostat cultures were switched to [U-(13)C]phenylalanine as the nitrogen source. The quantification and modeling of the dynamics of labeled metabolites indicated that phenylalanine was (i) incorporated in nascent protein, (ii) transaminated to phenylpyruvate and further converted by oxidation or by decarboxylation, and (iii) hydroxylated to tyrosine and subsequently metabolized via the homogentisate pathway. The involvement of the homogentisate pathway was supported by the comparative transcriptome analysis of P. chrysogenum cultures grown with phenylalanine and with (NH(4))(2)SO(4) as the nitrogen source. This transcriptome analysis also enabled the identification of two putative 2-oxo acid decarboxylase genes (Pc13g9300 and Pc18g01490). cDNAs of both genes were cloned and expressed in the 2-oxo-acid-decarboxylase-free Saccharomyces cerevisiae strain CEN.PK711-7C (pdc1 pdc5 pdc6Δ aro10Δ thi3Δ). The introduction of Pc13g09300 restored the growth of this S. cerevisiae mutant on glucose and phenylalanine, thereby demonstrating that Pc13g09300 encodes a dual-substrate pyruvate and phenylpyruvate decarboxylase, which plays a key role in an Ehrlich-type pathway for the production of phenylacetate in P. chrysogenum. These results provide a basis for the metabolic engineering of P. chrysogenum for the production of the penicillin G side chain precursor phenylacetate.