Dataset Information

Detection of Plasmodium falciparum in laboratory-reared and naturally infected wild mosquitoes using near-infrared spectroscopy.

ABSTRACT: There is an urgent need for high throughput, affordable methods of detecting pathogens inside insect vectors to facilitate surveillance. Near-infrared spectroscopy (NIRS) has shown promise to detect arbovirus and malaria in the laboratory but has not been evaluated in field conditions. Here we investigate the ability of NIRS to identify Plasmodium falciparum in Anopheles coluzzii mosquitoes. NIRS models trained on laboratory-reared mosquitoes infected with wild malaria parasites can detect the parasite in comparable mosquitoes with moderate accuracy though fails to detect oocysts or sporozoites in naturally infected field caught mosquitoes. Models trained on field mosquitoes were unable to predict the infection status of other field mosquitoes. Restricting analyses to mosquitoes of uninfectious and highly-infectious status did improve predictions suggesting sensitivity and specificity may be better in mosquitoes with higher numbers of parasites. Detection of infection appears restricted to homogenous groups of mosquitoes diminishing NIRS utility for detecting malaria within mosquitoes.

SUBMITTER: Da DF

PROVIDER: S-EPMC8119679 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Detection of Plasmodium falciparum in laboratory-reared and naturally infected wild mosquitoes using near-infrared spectroscopy.

Da Dari F DF McCabe Ruth R Somé Bernard M BM Esperança Pedro M PM Sala Katarzyna A KA Blight Josua J Blagborough Andrew M AM Dowell Floyd F Yerbanga Serge R SR Lefèvre Thierry T Mouline Karine K Dabiré Roch K RK Churcher Thomas S TS

Scientific reports 20210513 1

There is an urgent need for high throughput, affordable methods of detecting pathogens inside insect vectors to facilitate surveillance. Near-infrared spectroscopy (NIRS) has shown promise to detect arbovirus and malaria in the laboratory but has not been evaluated in field conditions. Here we investigate the ability of NIRS to identify Plasmodium falciparum in Anopheles coluzzii mosquitoes. NIRS models trained on laboratory-reared mosquitoes infected with wild malaria parasites can detect the p ...[more]

PMID: 33986416

Similar Datasets

Project description:BackgroundPractical, field-ready age-grading tools for mosquito vectors of disease are urgently needed because of the impact that daily survival has on vectorial capacity. Previous studies have shown that near-infrared spectroscopy (NIRS), in combination with chemometrics and predictive modeling, can forecast the age of laboratory-reared mosquitoes with moderate to high accuracy. It remains unclear whether the technique has utility for identifying shifts in the age structure of wild-caught mosquitoes. Here we investigate whether models derived from the laboratory strain of mosquitoes can be used to predict the age of mosquitoes grown from pupae collected in the field.MethodsNIRS data from adult female Aedes albopictus mosquitoes reared in the laboratory (2, 5, 8, 12 and 15 days-old) were analysed against spectra from mosquitoes emerging from wild-caught pupae (1, 7 and 14 days-old). Different partial least squares (PLS) regression methods trained on spectra from laboratory mosquitoes were evaluated on their ability to predict the age of mosquitoes from more natural environments.ResultsModels trained on spectra from laboratory-reared material were able to predict the age of other laboratory-reared mosquitoes with moderate accuracy and successfully differentiated all day 2 and 15 mosquitoes. Models derived with laboratory mosquitoes could not differentiate between field-derived age groups, with age predictions relatively indistinguishable for day 1-14. Pre-processing of spectral data and improving the PLS regression framework to avoid overfitting can increase accuracy, but predictions of mosquitoes reared in different environments remained poor. Principal components analysis confirms substantial spectral variations between laboratory and field-derived mosquitoes despite both originating from the same island population.ConclusionsModels trained on laboratory mosquitoes were able to predict ages of laboratory mosquitoes with good sensitivity and specificity though they were unable to predict age of field-derived mosquitoes. This study suggests that laboratory-reared mosquitoes do not capture enough environmental variation to accurately predict the age of the same species reared under different conditions. Further research is needed to explore alternative pre-processing methods and machine learning techniques, and to understand factors that affect absorbance in mosquitoes before field application using NIRS.

Project description:Triatomine vectors transmit Trypanosoma cruzi, the etiological agent of Chagas disease in humans. Transmission to humans typically occurs when contaminated triatomine feces come in contact with the bite site or mucosal membranes. In the Southern Cone of South America, where the highest burden of disease exists, Triatoma infestans is the principal vector for T. cruzi. Recent studies of other vector-borne illnesses have shown that arthropod microbiota influences the ability of infectious agents to colonize the insect vector and transmit to the human host. This has garnered attention as a potential control strategy against T. cruzi, as vector control is the main tool of Chagas disease prevention. Here we characterized the microbiota in T. infestans feces of both wild-caught and laboratory-reared insects and examined the relationship between microbial composition and T. cruzi infection using highly sensitive high-throughput sequencing technology to sequence the V3-V4 region of the 16S ribosomal RNA gene on the MiSeq Illumina platform. We collected 59 wild (9 with T. cruzi infection) and 10 lab-reared T. infestans (4 with T. cruzi infection) from the endemic area of Arequipa, Perú. Wild T. infestans had greater hindgut bacterial diversity than laboratory-reared bugs. Microbiota of lab insects comprised a subset of those identified in their wild counterparts, with 96 of the total 124 genera also observed in laboratory-reared insects. Among wild insects, variation in bacterial composition was observed, but time and location of collection and development stage did not explain this variation. T. cruzi infection in lab insects did not affect α- or β-diversity; however, we did find that the β-diversity of wild insects differed if they were infected with T. cruzi and identified 10 specific taxa that had significantly different relative abundances in infected vs. uninfected wild T. infestans (Bosea, Mesorhizobium, Dietzia, and Cupriavidus were underrepresented in infected bugs; Sporosarcina, an unclassified genus of Porphyromonadaceae, Nestenrenkonia, Alkalibacterium, Peptoniphilus, Marinilactibacillus were overrepresented in infected bugs). Our findings suggest that T. cruzi infection is associated with the microbiota of T. infestans and that inferring the microbiota of wild T. infestans may not be possible through sampling of T. infestans reared in the insectary.

Dataset Information

Detection of Plasmodium falciparum in laboratory-reared and naturally infected wild mosquitoes using near-infrared spectroscopy.

Publications

Detection of Plasmodium falciparum in laboratory-reared and naturally infected wild mosquitoes using near-infrared spectroscopy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets