Dynamic Gut Microbiome across Life History of the Malaria Mosquito Anopheles gambiae in Kenya

The mosquito gut represents an ecosystem that accommodates a complex, intimately associated microbiome. It is increasingly clear that the gut microbiome influences a wide variety of host traits, such as fitness and immunity. Understanding the microbial community structure and its dynamics across mosquito life is a prerequisite for comprehending the symbiotic relationship between the mosquito and its gut microbial residents. Here we characterized gut bacterial communities across larvae, pupae and adults of Anopheles gambiae reared in semi-natural habitats in Kenya by pyrosequencing bacterial 16S rRNA fragments. Immatures and adults showed distinctive gut community structures. Photosynthetic Cyanobacteria were predominant in the larval and pupal guts while Proteobacteria and Bacteroidetes dominated the adult guts, with core taxa of Enterobacteriaceae and Flavobacteriaceae. At the adult stage, diet regime (sugar meal and blood meal) significantly affects the microbial structure. Intriguingly, blood meals drastically reduced the community diversity and favored enteric bacteria. Comparative genomic analysis revealed that the enriched enteric bacteria possess large genetic redox capacity of coping with oxidative and nitrosative stresses that are associated with the catabolism of blood meal, suggesting a beneficial role in maintaining gut redox homeostasis. Interestingly, gut community structure was similar in the adult stage between the field and laboratory mosquitoes, indicating that mosquito gut is a selective eco-environment for its microbiome. This comprehensive gut metatgenomic profile suggests a concerted symbiotic genetic association between gut inhabitants and host

Population Structure of the Malaria Vector Anopheles sinensis (Diptera: Culicidae) in China: Two Gene Pools Inferred by Microsatellites

BACKGROUND: Anopheles sinensis is a competent malaria vector in China. An understanding of vector population structure is important to the vector-based malaria control programs. However, there is no adequate data of A. sinensis population genetics available yet. METHODOLOGY/PRINCIPAL FINDINGS: This study used 5 microsatellite loci to estimate population genetic diversity, genetic differentiation and demographic history of A. sinensis from 14 representative localities in China. All 5 microsatellite loci were highly polymorphic across populations, with high allelic richness and heterozygosity. Hardy-Weinberg disequilibrium was found in 12 populations associated with heterozygote deficits, which was likely caused by the presence of null allele and the Wahlund effect. Bayesian clustering analysis revealed two gene pools, grouping samples into two population clusters; one includes six and the other includes eight populations. Out of 14 samples, six samples were mixed with individuals from both gene pools, indicating the coexistence of two genetic units in the areas sampled. The overall differentiation between two genetic pools was moderate (F(ST) = 0.156). Pairwise differentiation between populations were lower within clusters (F(ST) = 0.008-0.028 in cluster I and F(ST) = 0.004-0.048 in cluster II) than between clusters (F(ST) = 0.120-0.201). A reduced gene flow (Nm = 1-1.7) was detected between clusters. No evidence of isolation by distance was detected among populations neither within nor between the two clusters. There are differences in effective population size (Ne = 14.3-infinite) across sampled populations. CONCLUSIONS/SIGNIFICANCE: Two genetic pools with moderate genetic differentiation were identified in the A. sinensis populations in China. The population divergence was not correlated with geographic distance or barrier in the range. Variable effective population size and other demographic effects of historical population perturbations could be the factors affecting the population differentiation. The structured populations may limit the migration of genes under pressures/selections, such as insecticides and immune genes against malaria

Gradient throwing characteristics of oscillating slat shovel for rhizome crop harvesters

An oscillating slat shovel has presented a promising application potential in the energy-saving and efficient harvesting of deep rhizome crops. This new type of shovel slat integrated harvesting device was developed by gradient amplitude and gradient vibration technology. This study aims to clarify the working characteristics of oscillating slat shovels and the mechanism of throwing separation. The throwing coefficient was selected to characterize the throwing separation ability of the slat shovel work-plane. A motion analysis was made to calculate the swing acceleration of the slat shovel work-plane. An analytical equation of the throwing coefficient was then established to combine with the working process, the periodic variation of the throwing coefficient, and the influence of parameters, including the amplitude, vibration frequency, and working length. The results showed that the throwing coefficient gradually increased at each point of the slat shovel work-plane, indicating outstanding gradient throwing characteristics and strong throwing ability. The maximum throwing coefficient was 9.98-19.72 in the separation area. After that, an investigation was made to determine the influence of the structure and working parameters of the oscillating slat shovel on the soil throwing separation performance. The EDEM-MBD coupling simulation model of the single pendulum shovel gate was established to simplify the structural model and the interaction between the rhizome, soil, and working components, where the indicators were set as the traction resistance, driving torque, the maximum separation distance between the soil and the slat (separation distance), and the ratio of the separated soil quality of each functional area of the work-plane to the total soil mass (separation ratio). A single-factor test was carried out with the amplitude, vibration frequency, and forward speed as factors. The results indicated that: 1) There were outstanding strong-weak cycles in the traction resistance and driving torque, due to the gradient throwing characteristics of oscillating slat shovel, soil viscosity, and plasticity. In the strong period, there was a large interaction force between shovel slat and soil, where the maximum separation distance occurred at the middle point of the separation area at the end point of the cutting stroke. 2) The amplitude was negatively correlated to the traction resistance, but positively correlated with the driving torque and separation distance. The vibration frequency was negatively correlated to the traction resistance, driving torque, and separation spacing. The forward velocity was positively correlated to traction resistance, driving torque, but negatively correlated to the separation distance. 3) There was a small influence of amplitude and vibration frequency on the separation ratio. There was a low separation of oscillating slat shovel, with the increase of forward velocity. 4) A combination of parameters was achieved when the amplitude was 7-11 mm in the strong period, where the average traction resistance was about 1 580.93-2 019.9 N, the maximum driving torque was about 224.04-322.11 N·m , and the maximum separation distance was about 59.58-98.3 mm. 5) The average traction resistance was about 1 416.43-1 866.38 N, the maximum driving torque was about 315.28-364.19 N·m, and the maximum separation distance was about 78.43-94.67 mm when the vibration frequency was 6.67-10.67 Hz. 6) The average traction resistance was about 1 429.43-2 110.48 N, the maximum driving torque was about 241.27-387.78 N·m, and the maximum separation distance was about 62.5-102.5 mm when the forward speed was 0.2-0.4 m/s.An optimal combination of parameters was selected for the field experiment: the amplitude was 9 mm, vibration frequency was 9.4 Hz, working speed was 0.32 m/s. The licorice harvesting test indicated that the traction resistance was about 32.17 kN, the driving torque was about 802.02 N·m, the excavation depth was about 468 mm, and the cleaning rate was about 96.42 %.Consequently, the oscillating slat shovel harvesting device can be feasible for the smooth and orderly operation, as well as the higher separation performance of rhizome-soil, where all the operation indexes met the national standards. This finding can provide a new method and design reference for the energy-saving and efficient harvesting of rhizomes, especially deep rhizome crops

Anopheles gambiae genome reannotation through synthesis of ab initio and comparative gene prediction algorithms

BACKGROUND: Complete genome annotation is a necessary tool as Anopheles gambiae researchers probe the biology of this potent malaria vector. RESULTS: We reannotate the A. gambiae genome by synthesizing comparative and ab initio sets of predicted coding sequences (CDSs) into a single set using an exon-gene-union algorithm followed by an open-reading-frame-selection algorithm. The reannotation predicts 20,970 CDSs supported by at least two lines of evidence, and it lowers the proportion of CDSs lacking start and/or stop codons to only approximately 4%. The reannotated CDS set includes a set of 4,681 novel CDSs not represented in the Ensembl annotation but with EST support, and another set of 4,031 Ensembl-supported genes that undergo major structural and, therefore, probably functional changes in the reannotated set. The quality and accuracy of the reannotation was assessed by comparison with end sequences from 20,249 full-length cDNA clones, and evaluation of mass spectrometry peptide hit rates from an A. gambiae shotgun proteomic dataset confirms that the reannotated CDSs offer a high quality protein database for proteomics. We provide a functional proteomics annotation, ReAnoXcel, obtained by analysis of the new CDSs through the AnoXcel pipeline, which allows functional comparisons of the CDS sets within the same bioinformatic platform. CDS data are available for download. CONCLUSION: Comprehensive A. gambiae genome reannotation is achieved through a combination of comparative and ab initio gene prediction algorithms

Fine Pathogen Discrimination within the APL1 Gene Family Protects Anopheles gambiae against Human and Rodent Malaria Species

Genetically controlled resistance of Anopheles gambiae mosquitoes to Plasmodium falciparum is a common trait in the natural population, and a cluster of natural resistance loci were mapped to the Plasmodium-Resistance Island (PRI) of the A. gambiae genome. The APL1 family of leucine-rich repeat (LRR) proteins was highlighted by candidate gene studies in the PRI, and is comprised of paralogs APL1A, APL1B and APL1C that share ≥50% amino acid identity. Here, we present a functional analysis of the joint response of APL1 family members during mosquito infection with human and rodent Plasmodium species. Only paralog APL1A protected A. gambiae against infection with the human malaria parasite P. falciparum from both the field population and in vitro culture. In contrast, only paralog APL1C protected against the rodent malaria parasites P. berghei and P. yoelii. We show that anti-P. falciparum protection is mediated by the Imd/Rel2 pathway, while protection against P. berghei infection was shown to require Toll/Rel1 signaling. Further, only the short Rel2-S isoform and not the long Rel2-F isoform of Rel2 confers protection against P. falciparum. Protection correlates with the transcriptional regulation of APL1A by Rel2-S but not Rel2-F, suggesting that the Rel2-S anti-parasite phenotype results at least in part from its transcriptional control over APL1A. These results indicate that distinct members of the APL1 gene family display a mutually exclusive protective effect against different classes of Plasmodium parasites. It appears that a gene-for-pathogen-class system orients the appropriate host defenses against distinct categories of similar pathogens. It is known that insect innate immune pathways can distinguish between grossly different microbes such as Gram-positive bacteria, Gram-negative bacteria, or fungi, but the function of the APL1 paralogs reveals that mosquito innate immunity possesses a more fine-grained capacity to distinguish between classes of closely related eukaryotic pathogens than has been previously recognized