James E. Gentile

Extensive circadian and light regulation of the transcriptome in the malaria mosquito Anopheles gambiae.

BackgroundMosquitoes exhibit 24 hr rhythms in flight activity, feeding, reproduction and development. To better understand the molecular basis for these rhythms in the nocturnal malaria vector Anopheles gambiae, we have utilized microarray analysis on time-of-day specific collections of mosquitoes over 48 hr to explore the coregulation of gene expression rhythms by the circadian clock and light, and compare these with the 24 hr rhythmic gene expression in the diurnal Aedes aegypti dengue vector mosquito.ResultsIn time courses from An. gambiae head and body collected under light:dark cycle (LD) and constant dark (DD) conditions, we applied three algorithms that detect sinusoidal patterns and an algorithm that detects spikes in expression. This revealed across four experimental conditions 393 probes newly scored as rhythmic. These genes correspond to functions such as metabolic detoxification, immunity and nutrient sensing. This includes glutathione S-transferase GSTE5, whose expression pattern and chromosomal location are shared with other genes, suggesting shared chromosomal regulation; and pulsatile expression of the gene encoding CYP6M2, a cytochrome P450 that metabolizes pyrethroid insecticides. We explored the interaction of light and the circadian clock and highlight the regulation of odorant binding proteins (OBPs), important components of the olfactory system. We reveal that OBPs have unique expression patterns as mosquitoes make the transition from LD to DD conditions. We compared rhythmic expression between An. gambiae and Ae. aegypti heads collected under LD conditions using a single cosine fitting algorithm, and report distinct similarities and differences in the temporal regulation of genes involved in tRNA priming, the vesicular-type ATPase, olfaction and vision between the two species.ConclusionsThese data build on our previous analyses of time-of-day specific regulation of the An. gambiae transcriptome to reveal additional rhythmic genes, an improved understanding of the co-regulation of rhythms in gene expression by the circadian clock and by light, and an understanding of the time-of-day specific regulation of some of these rhythmic processes in comparison with a different species of mosquito. Improved understanding of biological timing at the molecular level that underlies key physiological aspects of mosquito vectors may prove to be important to successful implementation of established and novel insect control methods.

Daily Rhythms in Mosquitoes and Their Consequences for Malaria Transmission

The 24-h day involves cycles in environmental factors that impact organismal fitness. This is thought to select for organisms to regulate their temporal biology accordingly, through circadian and diel rhythms. In addition to rhythms in abiotic factors (such as light and temperature), biotic factors, including ecological interactions, also follow daily cycles. How daily rhythms shape, and are shaped by, interactions between organisms is poorly understood. Here, we review an emerging area, namely the causes and consequences of daily rhythms in the interactions between vectors, their hosts and the parasites they transmit. We focus on mosquitoes, malaria parasites and vertebrate hosts, because this system offers the opportunity to integrate from genetic and molecular mechanisms to population dynamics and because disrupting rhythms offers a novel avenue for disease control.

An agent-based model of the population dynamics of Anopheles gambiae

BackgroundAgent-based models (ABMs) have been used to model the behaviour of individual mosquitoes and other aspects of malaria. In this paper, a conceptual entomological model of the population dynamics of Anopheles gambiae and the agent-based implementations derived from it are described. Hypothetical vector control interventions (HVCIs) are implemented to target specific activities in the mosquito life cycle, and their impacts are evaluated.MethodsThe core model is described in terms of the complete An. gambiae mosquito life cycle. Primary features include the development and mortality rates in different aquatic and adult stages, the aquatic habitats and oviposition. The density- and age-dependent larval and adult mortality rates (vector senescence) allow the model to capture the age-dependent aspects of the mosquito biology. Details of hypothetical interventions are also described.ResultsResults show that with varying coverage and temperature ranges, the hypothetical interventions targeting the gonotrophic cycle stages produce higher impacts than the rest in reducing the potentially infectious female (PIF) mosquito populations, due to their multi-hour mortality impacts and their applicability at multiple gonotrophic cycles. Thus, these stages may be the most effective points of target for newly developed and novel interventions. A combined HVCI with low coverage can produce additive synergistic impacts and can be more effective than isolated HVCIs with comparatively higher coverages. It is emphasized that although the model described in this paper is designed specifically around the mosquito An. gambiae, it could effectively apply to many other major malaria vectors in the world (including the three most efficient nominal anopheline species An. gambiae, Anopheles coluzzii and Anopheles arabiensis) by incorporating a variety of factors (seasonality cycles, rainfall, humidity, etc.). Thus, the model can essentially be treated as a generic Anopheles model, offering an excellent framework for such extensions. The utility of the core model has also been demonstrated by several other applications, each of which investigates well-defined biological research questions across a variety of dimensions (including spatial models, insecticide resistance, and sterile insect techniques).

Divide and conquer: a four-fold docking experience of agent-based models

Verification and validation (V&V) techniques are used in agent-based modeling (ABM) to determine whether the model is an accurate representation of the real system. Docking is a form of V&V that tries to align multiple simulation models. In a previous paper, we described the docking process of an ABM that simulates the life cycle of Anopheles gambiae. Results showed that the implementations were docked for adult but not for aquatic mosquito populations. In this paper, following the ‘Divide and Conquer’ paradigm, we compartmentalize the simulation world to prohibit the propagation of errors between compartments. Using four separate implementations that sprung from the same core model, we describe a series of docking experiments, analyze the results, and show how they lead to a successful dock. The complete four-fold docking encompasses verification between the four implementations, as well as validation against the core model with respect to these implementations.

Modelling sterile insect technique to control the population of Anopheles gambiae

BackgroundThere is a renewed effort to develop novel malaria control strategies as even well-implemented existing malaria control tools may fail to block transmission in some regions. Currently, transgenic implementations of the sterile insect technique (SIT) such as the release of insects with a dominant lethal, homing endonuclease genes, or flightless mosquitoes are in development. These implementations involve the release of transgenic male mosquitoes whose matings with wild females produce either no viable offspring or no female offspring. As these technologies are all in their infancy, little is known about the relative efficiencies of the various implementations.MethodsThis paper describes agent-based modelling of emerging and theoretical implementations of transgenic SIT in Anopheles gambiae for the control of malaria. It reports on female suppression as it is affected by the SIT implementation, the number of released males, and competitiveness of released males.ConclusionsThe simulation experiments suggest that a late-acting bisex lethal gene is the most efficient of the four implementations we simulated. They demonstrate 1) the relative impact of release size on a campaign’s effectiveness 2) late-acting genes are preferred because of their ability to exploit density dependent larval mortality 3) late-acting bisex lethal genes achieve elimination before their female-killing counterparts.

Face Detection Algorithm and Feature Performance on FRGC 2.0 Imagery

The performance of three well known face detection algorithms and four alternative types of features are characterized using face data from the Face Recognition Grand Challenge. The three algorithms are a semi-naive Bayesian classifier, a neural network called a SNoW, and a cascade classifier using Haar wavelets. For the first two algorithms, ROC analysis is used to assess the relative value of wavelet features compared to simpler pixel features. No universally best feature is observed, and for imagery acquired under uncontrolled lighting, pixels perform slightly better than wavelets. The cascade classifier is found to be impossible to train in the same fashion as the other algorithms, but it is also found to perform very well using a training configuration supplied along with the algorithm as part of the OpenCV library.