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      Midgut Microbiota of the Malaria Mosquito Vector Anopheles gambiae and Interactions with Plasmodium falciparum Infection

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          Abstract

          The susceptibility of Anopheles mosquitoes to Plasmodium infections relies on complex interactions between the insect vector and the malaria parasite. A number of studies have shown that the mosquito innate immune responses play an important role in controlling the malaria infection and that the strength of parasite clearance is under genetic control, but little is known about the influence of environmental factors on the transmission success. We present here evidence that the composition of the vector gut microbiota is one of the major components that determine the outcome of mosquito infections. A. gambiae mosquitoes collected in natural breeding sites from Cameroon were experimentally challenged with a wild P. falciparum isolate, and their gut bacterial content was submitted for pyrosequencing analysis. The meta-taxogenomic approach revealed a broader richness of the midgut bacterial flora than previously described. Unexpectedly, the majority of bacterial species were found in only a small proportion of mosquitoes, and only 20 genera were shared by 80% of individuals. We show that observed differences in gut bacterial flora of adult mosquitoes is a result of breeding in distinct sites, suggesting that the native aquatic source where larvae were grown determines the composition of the midgut microbiota. Importantly, the abundance of Enterobacteriaceae in the mosquito midgut correlates significantly with the Plasmodium infection status. This striking relationship highlights the role of natural gut environment in parasite transmission. Deciphering microbe-pathogen interactions offers new perspectives to control disease transmission.

          Author Summary

          During their development in the mosquito vector, Plasmodium parasites undergo complex developmental steps and incur severe bottlenecks. The largest parasite losses occur in the mosquito midgut where robust immune responses are activated. Variability in P. falciparum infection levels indicates that parasite transmission is the result of complex interactions between vectors and parasites, which rely on both genetic and environmental factors. However, in contrast to genetically encoded factors, the role of environmental factors in parasite transmission has received little attention. In this study, we characterized the midgut microbiota of mosquitoes derived from diverse breeding sites using pyrosequencing. We show that the composition of the midgut microbiota in adult mosquitoes exhibits great variability, which is likely determined by bacterial richness of the larval habitats. When field mosquitoes were collected at late immature stages in natural breeding sites and the emerging females challenged with Plasmodium falciparum in the laboratory, significant correlation was observed between P. falciparum infection and the presence of Enterobacteriaceae in the mosquito midgut. Greater understanding of these malaria-bacteria interactions may lead to novel malaria control strategies.

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          R: A Language and Environment for Statistical Computing.

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            Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors.

            In vertebrates, including humans, individuals harbor gut microbial communities whose species composition and relative proportions of dominant microbial groups are tremendously varied. Although external and stochastic factors clearly contribute to the individuality of the microbiota, the fundamental principles dictating how environmental factors and host genetic factors combine to shape this complex ecosystem are largely unknown and require systematic study. Here we examined factors that affect microbiota composition in a large (n = 645) mouse advanced intercross line originating from a cross between C57BL/6J and an ICR-derived outbred line (HR). Quantitative pyrosequencing of the microbiota defined a core measurable microbiota (CMM) of 64 conserved taxonomic groups that varied quantitatively across most animals in the population. Although some of this variation can be explained by litter and cohort effects, individual host genotype had a measurable contribution. Testing of the CMM abundances for cosegregation with 530 fully informative SNP markers identified 18 host quantitative trait loci (QTL) that show significant or suggestive genome-wide linkage with relative abundances of specific microbial taxa. These QTL affect microbiota composition in three ways; some loci control individual microbial species, some control groups of related taxa, and some have putative pleiotropic effects on groups of distantly related organisms. These data provide clear evidence for the importance of host genetic control in shaping individual microbiome diversity in mammals, a key step toward understanding the factors that govern the assemblages of gut microbiota associated with complex diseases.
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              Defining the healthy "core microbiome" of oral microbial communities

              Background Most studies examining the commensal human oral microbiome are focused on disease or are limited in methodology. In order to diagnose and treat diseases at an early and reversible stage an in-depth definition of health is indispensible. The aim of this study therefore was to define the healthy oral microbiome using recent advances in sequencing technology (454 pyrosequencing). Results We sampled and sequenced microbiomes from several intraoral niches (dental surfaces, cheek, hard palate, tongue and saliva) in three healthy individuals. Within an individual oral cavity, we found over 3600 unique sequences, over 500 different OTUs or "species-level" phylotypes (sequences that clustered at 3% genetic difference) and 88 - 104 higher taxa (genus or more inclusive taxon). The predominant taxa belonged to Firmicutes (genus Streptococcus, family Veillonellaceae, genus Granulicatella), Proteobacteria (genus Neisseria, Haemophilus), Actinobacteria (genus Corynebacterium, Rothia, Actinomyces), Bacteroidetes (genus Prevotella, Capnocytophaga, Porphyromonas) and Fusobacteria (genus Fusobacterium). Each individual sample harboured on average 266 "species-level" phylotypes (SD 67; range 123 - 326) with cheek samples being the least diverse and the dental samples from approximal surfaces showing the highest diversity. Principal component analysis discriminated the profiles of the samples originating from shedding surfaces (mucosa of tongue, cheek and palate) from the samples that were obtained from solid surfaces (teeth). There was a large overlap in the higher taxa, "species-level" phylotypes and unique sequences among the three microbiomes: 84% of the higher taxa, 75% of the OTUs and 65% of the unique sequences were present in at least two of the three microbiomes. The three individuals shared 1660 of 6315 unique sequences. These 1660 sequences (the "core microbiome") contributed 66% of the reads. The overlapping OTUs contributed to 94% of the reads, while nearly all reads (99.8%) belonged to the shared higher taxa. Conclusions We obtained the first insight into the diversity and uniqueness of individual oral microbiomes at a resolution of next-generation sequencing. We showed that a major proportion of bacterial sequences of unrelated healthy individuals is identical, supporting the concept of a core microbiome at health.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Pathog
                PLoS Pathog
                plos
                plospath
                PLoS Pathogens
                Public Library of Science (San Francisco, USA )
                1553-7366
                1553-7374
                May 2012
                May 2012
                31 May 2012
                : 8
                : 5
                : e1002742
                Affiliations
                [1 ]UMR MIVEGEC (IRD 224- CNRS 5290- UM1- UM2), Montpellier, France
                [2 ]Laboratoire de Recherche sur le Paludisme, IRD-OCEAC, BP288, Yaoundé, Cameroun
                [3 ]UMR 7138 Systématique Adaptation Evolution, Université de Nice-Sophia Antipolis, Parc Valrose, France
                [4 ]CNRS UPR 9022, Inserm U963, Université de Strasbourg, Strasbourg, France
                [5 ]Área Departamental de Engenharia Electrónica e Computação, Faculdade de Ciências e Tecnologia, Universidade do Algarve, Faro, Portugal
                Institut Pasteur, France
                Author notes

                Conceived and designed the experiments: AB RC IM. Performed the experiments: AB MTT LA AM SEN PHAA RC IM. Analyzed the data: AB DB LA HRS RC IM. Contributed reagents/materials/analysis tools: EAL RC IM. Wrote the paper: AB RC IM.

                Article
                PPATHOGENS-D-11-02633
                10.1371/journal.ppat.1002742
                3364955
                22693451
                2e494119-b5b0-46f1-a0ee-feebe27ea2fd
                Boissière et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 30 November 2011
                : 26 April 2012
                Page count
                Pages: 12
                Categories
                Research Article
                Biology
                Ecology
                Evolutionary Biology
                Genetics
                Genomics
                Immunology
                Microbiology
                Population Biology

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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