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The Anopheles Coluzzii Microbiome and Its Interaction with the Intracellular Parasite Wolbachia Timothy J

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The Anopheles Coluzzii Microbiome and Its Interaction with the Intracellular Parasite Wolbachia Timothy J www.nature.com/scientificreports OPEN The Anopheles coluzzii microbiome and its interaction with the intracellular parasite Wolbachia Timothy J. Straub1,2*, W. Robert Shaw2, Perrine Marcenac2, Simon P. Sawadogo3, Roch K. Dabiré3, Abdoulaye Diabaté3, Flaminia Catteruccia2 & Daniel E. Neafsey1,2* Wolbachia, an endosymbiotic alpha-proteobacterium commonly found in insects, can inhibit the transmission of human pathogens by mosquitoes. Biocontrol programs are underway using Aedes aegypti mosquitoes trans-infected with a non-natural Wolbachia strain to reduce dengue virus transmission. Less is known about the impact of Wolbachia on the biology and vectorial capacity of Anopheles mosquitoes, the vectors of malaria parasites. A naturally occurring strain of Wolbachia, wAnga, infects populations of the major malaria vectors Anopheles gambiae and Anopheles coluzzii in Burkina Faso. Previous studies found wAnga infection was negatively correlated with Plasmodium infection in the mosquito and wAnga infuenced mosquito egg-laying behavior. Here, we investigate wAnga in natural populations of An. coluzzii and its interactions with other resident microbiota using targeted 16S sequencing. Though we fnd no major diferences in microbiota composition associated with wAnga infection, we do fnd several taxa that correlate with the presence or absence of wAnga in female mosquitoes following oviposition, with the caveat that we could not rule out batch efects due to the unanticipated impact of wAnga on oviposition timing. These data suggest wAnga may infuence or interact with the Anopheles microbiota, which may contribute to the impact of wAnga on Anopheles biology and vectorial capacity. Despite progress in control eforts over the past decade, malaria remains a major global health problem, with over 200 million reported cases each year 1. Te most lethal form of malaria is caused by the parasite Plasmodium falciparum, which remains endemic across much of sub-Saharan Africa. Vector control has been the most impor- tant contributor to reduction in global mortality and morbidity 2–6. A recent stall in the decline of malaria 1,6, and the increasingly widespread observations of insecticide resistance in mosquito populations 7, however, highlight the need for novel approaches to malaria vector control. Manipulation of mosquito microbiota, and in particular the introduction of the alphaproteobacterial endo- symbiont Wolbachia, is an example of a promising new avenue of vector control8,9. Wolbachia infection reduces the capacity of Aedes mosquitoes to transmit dengue virus and other arboviruses through mechanisms that are incompletely understood, but which may include manipulation of the mosquito innate immune response, nutri- ent competition, and life-shortening of the mosquito 10–12. In Ae. aegypti, transinfected Wolbachia has been shown to signifcantly alter the mosquito microbiome, suggesting the existence of complex interactions between resident microbes that may also infuence vectorial capacity13. Wolbachia can be vertically transmitted from mother to ofspring through infection of the germ line, thus allowing it to persist across generations once introduced. In Aedes and many other arthropod hosts, the spread of Wolbachia is enhanced through a phenomenon termed cytoplasmic incompatibility (CI), in which uninfected females that mate with infected males produce sterile broods, giving a strong reproductive advantage to infected females4,14. Wolbachia has recently been detected with PCR-based and whole-genome sequencing approaches in several important African malaria vector species, Anopheles coluzzii, Anopheles gambiae, and An. arabiensis15–21. Tese 1Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02144, USA. 2Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA. 3Institut de Recherche en Sciences de La Santé/Centre Muraz, O1 BP 390, Bobo-Dioulasso 01, Burkina Faso. *email: [email protected]; [email protected] SCIENTIFIC REPORTS | (2020) 10:13847 | https://doi.org/10.1038/s41598-020-70745-0 1 Vol.:(0123456789) www.nature.com/scientificreports/ One day Three days 50 43 Days in captivity 78 Two days Oviposition 2 23 20 Oviposited 29 21 76 Did not oviposit Mortality 20 17 Collected Alive 19 10 21 38 38 2 3 3 Collected Dead wAnga + – BF US location Extraction wAnga+ samples: 18/19 10/10 5/21 25/28 3/10 26/28 6/10 0/2 6/20 0/3 3/17 0/3 Figure 1. Breakdown of samples collected. A total of 171 samples were captured and then collected for DNA extraction afer up to 3 days in captivity (top row, numbers indicate samples collected on each given day). Mosquitoes were collected for extraction afer oviposition (second row, in beige), upon death in captivity regardless of oviposition (mortality, third row, in red), or at the end of 3 days in captivity regardless of oviposition or death. Due to study design, virtually all samples collected early (i.e., one and 2 days in captivity) underwent DNA extraction in Burkina Faso (BF, yellow circles), while the rest were extracted at a later date in the United States (US, blue circles). wAnga infection status was performed using a nested PCR, with the infection rate signifed by the size of the bright blue and yellow arcs in the last row. Te fraction of wAnga-positive samples for each bottom pie chart are specifed by the numbers in the bottom row. Due to the accelerated oviposition impact of wAnga, wAnga infection correlated with days in captivity (p = 8.4 × 10–9), oviposition (p = 7.2 × 10–10), whether the mosquito was collected still alive or dead (p = 0.0094), and DNA extraction location (p < 10–15). p-values reported are from Fisher’s Exact Tests and have been corrected for multiple hypothesis testing using Benjamini-Hochberg. fndings, although called into question by a recent study22, have challenged the notion that anopheline mosquitoes do not harbor natural Wolbachia infections. Te Wolbachia strain identifed in Burkina Faso, named wAnga, has been found to exhibit very low infection intensity in An. gambiae and An. coluzzii15,16. Moreover, wAnga is present at low to intermediate frequencies in wild populations, most likely because it does not induce CI 16. Wolbachia infections are negatively correlated with P. falciparum in An. coluzzii16,19, raising interest in understanding the mechanism by which these bacteria afect the capacity of Anopheles mosquitoes to transmit malaria parasites. To aid in understanding the biological efects of wAnga infection on An. coluzzii, and the potential avenues by which it could be impacting malaria vectorial capacity, we collected blood-fed adult female mosquitoes in Burkina Faso. Using 16S-based assays on DNA extracted from mosquito carcasses, we found that while there are no major diferences in the microbiome composition between mosquitoes with vs. without wAnga, certain bacterial taxa appear to be positively or negatively associated with this Wolbachia strain. Tis could suggest that some residents of the Anopheles microbiota may promote the ability of wAnga to colonize the mosquito host, while others may disrupt it. Interpretation of these associations between wAnga and other microbes is compli- cated by the biological efects of wAnga infection on An. coluzzii oviposition timing 16, motivating further studies to explore the interaction of these efects on microbiome profle. Results The An. coluzzii microbiota. We analysed 171 mosquitoes (Fig. 1), 102 of which were determined to be infected with wAnga by 16S PCR16, by targeted 16S rRNA sequencing and obtained a mean of 72,656 reads per sample (Supplementary Fig. 1a); 144 samples exhibited at least 10,000 reads and were retained for further analy- sis. We observed a total of 3,189 operational taxonomic units (OTUs) at 97% identity; fltering to remove low abundance and rare OTUs (defned by those seen in only one sample or fewer than 50 reads across all samples) reduced this number to 916 OTUs. (Supplementary Fig. 1a). Only four OTUs were “core” (i.e. present in every one of the 144 mosquitoes), three of which were assigned to Acinetobacter and one to Comamonadaceae, all of which were within Proteobacteria. Tese core OTUs ranged in relative abundance within individual mosquitoes, sometimes as high as 80% of all bacteria (Supplementary Fig. 1b). Alpha rarefaction analyses indicated that we sequenced to a sufcient depth such that we are accurately estimating the diversity of the microbiota of the mosquitoes, and that the presence or absence of a given OTU is not likely due to insufcient sequencing depth (Supplementary Fig. 1c). SCIENTIFIC REPORTS | (2020) 10:13847 | https://doi.org/10.1038/s41598-020-70745-0 2 Vol:.(1234567890) www.nature.com/scientificreports/ b 1.00 a 1.00 e e 0.75 0.75 undanc undanc 0.50 0.50 e Ab e Ab Relativ 0.25 Relativ 0.25 0.00 Moraxellaceae Actinomycetales Pseudomonadaceae 0.00 Proteobacteria Actinobacteria Comamonadaceae Oxalobacteraceae Neisseriaceae Firmicutes Bacteroidetes Staphylococcaceae Flavobacteriaceae Enterobacteriaceae Campylobacteraceae c 1.00 e 0.75 undanc 0.50 Ab ve 0.25 Relati 0.00 Acinetobacter Variovorax Staphylococcus Pseudomonas Micrococcineae Comamonas Vogesella Arcobacter Providencia Elizabethkingia Figure 2. Te bacterial composition of the An. coluzzii microbiota. Per sample distributions of phyla (a), families (b), and genera (c) are shown. X axis represents individual mosquitoes and Y axis indicates the relative abundance of each taxon, which are colour-coded. For
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