DOI: 10.5061/dryad.547d7wm91
title: Metagenomics data of the bacterial community in Bemisia tabaci from Burkina Faso

description: Microbial symbionts are widespread in insects and some of them have been
 associated to adaptive changes. Primary symbionts (P-symbionts) have a
 nutritional role that allows their hosts to feed on unbalanced diets
 (plant sap, wood, blood). Most of them have undergone genome reduction,
 but their genomes still retain genes involved in pathways that are
 necessary to synthesize the nutrients that their hosts need. However, in
 some P-symbionts, essential pathways are incomplete and secondary
 symbionts (S-symbionts) are required to complete parts of their
 degenerated functions. The P-symbiont of the phloem sap-feeder Bemisia
 tabaci, Portiera aleyrodidarium, lacks genes involved in the synthesis of
 vitamins, cofactors, and also of some essential amino-acids. Seven
 S-symbionts have been detected in the B. tabaci species complex.
 Phenotypic and genomic analyses have revealed various effects, from
 reproductive manipulation to fitness benefits, notably some of them have
 complementary metabolic capabilities to Portiera, suggesting that their
 presence may be obligatory. In order to get the full picture of
 the symbiotic community of this pest, we investigated, through
 metabarcoding approaches, the symbiont content of individuals from Burkina
 Faso, a West African country where B. tabaci induces severe crop damage.
 While no new putative B. tabaci S-symbiont was identified,
 Hemipteriphilus, a symbiont only described in B. tabaci populations from
 Asia, was detected for the first time on this continent. Phylogenetic
 analyses however reveal that it is a different strain than the reference
 found in Asia. Specific diagnostic PCRs showed a high prevalence of these
 S-symbionts and especially of Hemipteriphilus in different genetic groups.
 These results suggest that Hemipteriphilus may affect the biology of B.
 tabaci and provide fitness advantage in some B. tabaci populations.
description: Sampling was done in nine
 localities in Burkina Faso, Western Africa, in March and April (dry
 season) 2015 and 2016 on vegetables, ornamental plants and
 weeds. Seventy-two field-collected whiteflies from
 Burkina Faso were used to characterize the bacterial community through
 qPCRs using primers specific to each symbiont. They were chosen in order
 that all genetic groups, all localities and all host plants were
 represented. We also included 18 adults coming from laboratory lines
 belonging to MED-Q1 and MED-Q2 genetic groups reared for years in the
 « Laboratoire de Biométrie et Biologie Evolutive ». The universal
 bacterial primer set
 319F-<i>TCG-TCG-GCA-GCG-TCA-GAT-GTG-TAT-AAG-AGA-CAG</i><b>-</b>CCT-ACG-GGN-GGC-WGC-AG and 805R-<i>GTC-TCG-TGG-GCT-CGG-AGA-TGT-GTA-TAA-GAG-ACA-G</i>GA-CTA-CHV-GGG-TAT-CTA-ATC-C was used to amplify 486 bp of the V3-V4 hypervariable regions of the <i>16SrDNA</i> gene. The primers were synthesized with overhang adapters (in italic) for index attachment and Illumina sequencing adapters. For each sample, triplicates were performed, consisting of three PCR reactions using 4µL of DNA template and 25 cycles of PCR. Each amplification product was checked on an agarose gel to verify that there was specific amplification only. For some of them, a bioanalyzer verification was also performed. Then, all the replicates were pooled by sample before purification and to proceed to the further preparation of the library according to the protocol outlined by Illumina (« 16S metagenomic Sequencing Library Preparation »), n°15044223 Rev.B. The pooled library was PE-sequenced using the Illumina MiSeq reagent kit version 3 for 600 cycles (2x300pb) by Biofidal (Vaulx enVelin, France). The sequencing data in FASTQ format were processed and analyzed with the QIIME2 software suite version 2018.8. The raw Illumina reads were imported into QIIME2, demultiplexed, and then denoised, trimmed and filtered with DADA2 pipeline to remove noisy and chimeric sequences, to construct denoised paired-end sequences and to dereplicate them. This produced a table containing representative sequences also called amplicon sequence variant or ASV. The taxonomy assignment of ASVs was then performed by using feature-classifier classify-sklearn against the database Greengenes 13_8 (99% OTUs from 515F/806R region of sequences).