Biology subjects

Niang, A.

Publications and source records attributed to Niang, A..

4 recordsLinked to original sources

bioRxiv2021

Cuticular hydrocarbons are associated with mating success and insecticide resistance in malaria vectors

Anopheles coluzzii females, important malaria vectors in Africa, mate only once in their lifetime. Mating occurs in aerial swarms with a high male-to-female ratio, where the traits underlying male mating success are largely unknown. Here, we investigated whether cuticular hydrocarbons (CHCs) influence mating success in natural mating swarms in Burkina Faso. As insecticides are widely used in this area for malaria control, we also determined whether CHCs affect insecticide resistance levels. We find that mated males have higher CHC abundance than unmated controls, suggesting CHCs could be a determinant of mating success. Additionally, mated males have higher insecticide resistance under pyrethroid challenge, and we show a link between resistance intensity and CHC abundance. Taken together, our results reveal overlapping roles played by CHCs in mate choice and insecticide resistance, and point to sexual selection for insecticide resistance traits that limit the efficacy of our best malaria control tools.

ecology↗

bioRxiv2020

The genomic epidemiology of multi-drug resistant nontyphoidal Salmonella causing invasive disease in sub-Saharan Africa

BackgroundInvasive nontyphoidal Salmonella (iNTS) is one of the leading causes of bacteraemia in sub-Saharan Africa. Multi-drug resistance (MDR) and further resistance to third generation cephalosporins and fluoroquinolones have emerged in multiple iNTS serotypes. Molecular epidemiological investigations of nontyphoidal Salmonella are needed to better understand the genetic characteristics and transmission dynamics associated with major MDR iNTS serotypes across the continent. MethodsA total of 166 nontyphoidal Salmonella isolates causing invasive disease were collected from a multi-centre study in eight African countries between 2010 and 2014, and whole-genome sequenced to investigate the geographical distribution, antimicrobial genetic determinants and population structure of iNTS serotypes-genotypes. Phylogeographical reconstruction was further conducted in context of the existing genomic framework of iNTS serotypes Typhimurium and Enteritidis. Population-based incidence of MDR-iNTS disease was also estimated. ResultsSalmonella enterica subsp. Enterica serotype Typhimurium (S. Typhimurium) sequence-type (ST) 313 and Salmonella enterica subsp. Enterica serotype Enteritidis (S. Enteritidis) ST11 were predominant, and both exhibited high frequencies of MDR. Salmonella enterica subsp. Enterica serotype Dublin (S. Dublin) ST10 emerged in West Africa. Mutations in the gyrA gene were identified in S. Enteritidis and S. Typhimurium in Ghana; and ST313 carrying blaCTX-M-15 was found in Kenya. Inter-country transmission of MDR ST313 lineage II and the West African Clade of MDR ST11 between Ghana and neighbouring countries including Mali, Burkina Faso, and Nigeria were evident. The incidence of MDR-iNTS disease exceeded 100/100,000-person years-of-observation (PYO) in children aged <5 years in several West African countries. ConclusionsMultiple MDR iNTS serotypes-sequence types, predominantly S. Typhimurium ST313 and S. Enteritidis ST11, are co-circulating in sub-Saharan Africa with evidence of transmission between West African countries. The development of safe and effective iNTS vaccines coupled with appropriate antimicrobial stewardship and adequate epidemiological monitoring are essential to limit the impact of these pathogens in Africa.

genomics↗

bioRxiv2020

Rapid ageing and species identification of natural mosquitoes for malaria surveillance

The malaria parasite, which is transmitted by several Anopheles mosquito species, requires more time to reach its human-transmissible stage than the average lifespan of a mosquito. Monitoring the species-specific age structure of mosquito populations is critical to evaluating the impact of vector control interventions on malaria risk. We developed a rapid, cost-effective surveillance method based on deep learning of mid-infrared spectra of mosquitoes cuticle that simultaneously identifies the species and the age of three main malaria vectors, in natural populations. Using over 40,000 ecologically and genetically diverse females, we could speciate and age grade An. gambiae, An. arabiensis, and An. coluzzii with up to 95% accuracy. Further, our model learned the age of new populations with minimal sampling effort and detected the impact of control interventions on simulated mosquito populations, measured as a shift in their age structures. We anticipate our method to be applied to other arthropod vector-borne diseases.

zoology↗

bioRxiv2018

Prediction of malaria mosquito species and population age structure using mid-infrared spectroscopy and supervised machine learning

Despite the global efforts made in the fight against malaria, the disease is resurging. One of the main causes is the resistance that Anopheles mosquitoes, vectors of the disease, have developed to insecticides. Anopheles must survive for at least 12 days to possibly transmit malaria. Therefore, to evaluate and improve malaria vector control interventions, it is imperative to monitor and accurately estimate the age distribution of mosquito populations as well as total population sizes. However, estimating mosquito age is currently a slow, imprecise, and labour-intensive process that can only distinguish under-from over-four-day-old female mosquitoes. Here, we demonstrate a machine-learning based approach that utilizes mid-infrared spectra of mosquitoes to characterize simultaneously, and with unprecedented accuracy, both age and species identity of females of the malaria vectors Anopheles gambiae and An. arabiensis mosquitoes within their respective populations. The prediction of the age structures was statistically indistinguishable from true modelled distributions. The method has a negligible cost per mosquito, does not require highly trained personnel, is substantially faster than current techniques, and so can be easily applied in both laboratory and field settings. Our results show that, with larger mid-infrared spectroscopy data sets, this technique can be further improved and expanded to vectors of other diseases such as Zika and Dengue.

bioinformatics↗