François Sougal

Ngambia Freitas

Flobert Njiokou

Jean Marc

Tsagmo Ngoune

Guilhem Sempere

David Berthier

Anne Geiger
email: anne.geiger@ird.fr

Modulation of trypanosome establishment in Glossina palpalis palpalis by its microbiome in the Campo sleeping sickness focus, Cameroon

Keywords: Glossina palpalis palpalis, Trypanosome, microbiome, Sleeping sickness, Nagana, Metabarcoding

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

2

Abstract

The purpose of this study was to investigate factors involved in vector competence by analyzing whether the diversity and relative abundance of the different bacterial genera inhabiting the fly's gut could be associated with its trypanosome infection status. This was investigated on 160 randomly selected G. p. palpalis flies -80 trypanosome-infected, 80 uninfected -collected in 5 villages of the Campo trypanosomiasis focus in South Cameroon. Trypanosome species were identified using specific primers, and the V4 region of the 16S rRNA gene of bacteria was targeted for metabarcoding analysis in order to identify the bacteria and determine microbiome composition.

A total of 261 bacterial genera were identified of which only 114 crossed two barriers: a threshold of 0.01% relative abundance and the presence at least in 5 flies. The secondary symbiont Sodalis glossinidius was identified in 50% of the flies but it was not considered since its relative abundance was much lower than the 0.01% relative abundance threshold. The primary symbiont Wigglesworthia displayed 87% relative abundance, the remaining 13% were prominently constituted by the genera Spiroplasma, Tediphilus, Acinetobacter and Pseudomonas. Despite a large diversity in bacterial genera and in their abundance observed in micobiome composition, the statistical analyzes of the 160 tsetse flies showed an association with flies' infection status and the sampling sites. Furthermore, tsetse flies harboring Trypanosoma congolense Savanah type displayed a different composition of bacterial flora compared to uninfected flies. In addition, our study revealed that 36 bacterial genera were present only in uninfected flies, which could therefore suggest a possible involvement in flies' refractoriness; with the exception of Cupriavidus, they were however of low relative abundance. Some genera, including Acinetobacter, Cutibacterium, Pseudomonas and Tepidiphilus, although present both in infected and uninfected flies, were found to be associated with uninfected status of tsetse flies. Hence their effective role deserves to be further evaluated in order to determine whether some of them could become targets for tsetse control of fly vector competence and

Introduction

Tsetse flies (Glossina sp.) are biological vectors of trypanosomes responsible of human African Trypanosomiasis (HAT) or sleeping sickness and of animal African Trypanosomosis (AAT) or nagana in 36 sub-Saharan African countries. They are medically and agriculturally important hematophagous dipterans. Indeed, both human and animal diseases exhibit severe health and social impacts and cause heavy economic losses in endemic countries [START_REF] Shaw | Estimating the costs of tsetse control options: an example for Uganda[END_REF][START_REF] Welburn | Priorities for the elimination of sleeping sickness[END_REF]. In humans, Trypanosoma brucei rhodesiense (Tbr) and T. b. gambiense (Tbg) are responsible for the acute form of HAT in East and South Africa (2% of the total HAT cases), and for the chronic form in West and Central Africa (98% of the cases; fewer than 3000 cases were reported in 2015), respectively [START_REF] Büscher | Human african trypanosomiasis[END_REF][START_REF] Lindner | New who guidelines for treatment of gambiense human african trypanosomiasis including fexinidazole: Substantial changes for clinical practice[END_REF].

Wild and domestic animals can also be infected with T. congolense, T. vivax and other trypanosome subspecies such as T. b. brucei [START_REF] Nakayima | Molecular epidemiological studies on animal trypanosomiases in Ghana[END_REF][START_REF] Tessema | African trypanosomes: Virulence factors, pathogenicity and host responses[END_REF][START_REF] Kato | Clinical profiles, disease outcome and co-morbidities among t. B. Rhodesiense sleeping sickness patients in uganda[END_REF].

Sixty-five million people are still at risk for HAT, though the number of new cases is currently the lowest ever recorded [START_REF] Who | Trypanosomiasis, human African (sleeping sickness)[END_REF] thanks to entomological surveillance, medical diagnosis and drug treatment, as well as vector control. Based on this promising trend, the World Health Organization (WHO) neglected tropical diseases road map targeted elimination of HAT due to T. b. gambiense as a public health problem by 2020 and interruption of transmission (zero cases) for 2030 [START_REF] Franco | Monitoring the elimination of human african trypanosomiasis: Update to 2016[END_REF]. Over the past century, HAT has already been close to elimination (mid-1960s), but several outbreaks were recorded in the 1970s following a relaxation of epidemiological surveillance [START_REF] Brun | Human african trypanosomiasis[END_REF]). In addition to this limit, no vaccine has been developed as a consequence of the frequent switch of the variant surface glycoprotein (VSG) protein of the parasite's coat which allow it to evade the mammalian host immune system [START_REF] Horn | Antigenic variation in African trypanosomes[END_REF]. In addition, treatments are not always carried out regularly since human populations living in the bush are far from hospitals and dispensaries. Furthermore, available drugs are responsible of many side effects, or are facing resistance of trypanosomes, thus compromising the efficacy of the chemotherapy [START_REF] Delespaux | Drugs and drug resistance in African trypanosomiasis[END_REF][START_REF] Geiger | Bacterial Diversity Associated with Populations of Glossina spp. from Cameroon and Distribution within the Campo Sleeping Sickness Focus[END_REF][START_REF] Baker | Drug resistance in African trypanosomiasis: the melarsoprol and pentamidine story[END_REF].

To mitigate the issues faced by current measures that had led in resurgence of the disease in the past, new alternative control strategies are needed and vector control appears as the most efficient strategy to tackle these vector-borne diseases. Its action can be directly evaluated through either the reduction of tsetse fly populations or of their vector competence, both resulting in a decrease in parasite transmission. As far as tsetse fly is concerned, understanding the mechanisms involved in its susceptibility or resistance to trypanosomes infection represent important avenues for HAT and AAT control/elimination [START_REF] Geiger | Trypanosoma-tsetse fly interactions: current and potential future research directions[END_REF].

Tsetse fly populations had been successfully reduced using the Sterile Insect Technique (SIT) [START_REF] Mogi | Advances in Disease Vector Research[END_REF] or insecticide and colour-treated nets, so-called tiny targets, as well as cattle dipping, odor baited trapping, and insecticide spraying, and the transmission of the disease has therefore been significantly reduced [START_REF] Mahamat | Adding tsetse control to medical activities contributes to decreasing transmission of sleeping sickness in the Mandoul focus (Chad)[END_REF]. Despite the success gathered [START_REF] Kariithi | Enhancing vector refractoriness to trypanosome infection: achievements, challenges and perspectives[END_REF] with this approaches, today large-scale insecticide spraying, for example, is no longer used to avoid destroying the diversity of the ecosystem's entomological fauna. The development of methods that can just interfere with the ability of tsetse flies to harbor trypanosomes appears more appropriate than their complete eradication. Indeed, growing evidence has shown that genetic engineering approach (para-transgenesis for example) [START_REF] De Vooght | Towards improving tsetse fly paratransgenesis: stable colonization of Glossina morsitans morsitans with genetically modified Sodalis[END_REF] is a promising approach to block the transmission of parasites. Furthermore, the microbiome of vectors has been reported to be able to modulate/interfere with the installation, survival and the parasite growth into the fly, hence its transmission from one host to another [START_REF] Abraham | Pathogen-mediated manipulation of arthropod microbiota to promote infection[END_REF][START_REF] Weiss | Microbiome influences on insect host vector competence[END_REF]. Recent studies using insect microbiota to control and prevent vector-borne diseases [START_REF] Carrington | Field-and clinically derived estimates of Wolbachia-mediated blocking of dengue virus transmission potential in Aedes aegypti mosquitoes[END_REF][START_REF] Hoffmann | Successful establishment of Wolbachia in Aedes populations to suppress dengue transmission[END_REF][START_REF] Bian | The endosymbiotic bacterium Wolbachia induces resistance to dengue virus in Aedes aegypti[END_REF] support the need to further explore this avenue. This approach is in line with the 6 WHO "One Health" Concept which recognizes that the health of people and that of animals are closely linked due to their common shared environment.

Like most hematophagous insects, the tsetse fly harbors bacterial symbionts maternally transmitted to offspring, including Wigglesworthia, its primary symbiont which essentially contribute to the fly's survival by producing and releasing nutrients and vitamins that are insufficiently present in the diet of the latter, and that it is unable to synthesize. In addition, tsetse flies harbor communities of indigenous bacteria acquired from the environment [START_REF] Dale | Sodalis gen. nov. and Sodalis glossinidius sp. nov., a microaerophilic secondary endosymbiont of the tsetse fly Glossina morsitans morsitans[END_REF][START_REF] Wang | Tsetse fly microbiota: form and function[END_REF][START_REF] Aksoy | Analysis of multiple tsetse fly populations in Uganda reveals limited diversity and species-specific gut microbiota[END_REF]. In most cases, exogenous microbiome comprises less than 1% of tsetse's cumulative enteric microbiota [START_REF] Aksoy | Analysis of multiple tsetse fly populations in Uganda reveals limited diversity and species-specific gut microbiota[END_REF] and their function is yet to be elucidated. Due to their close proximity (gut) these bacteria may interact with the parasite harbored by tsetse flies, for example by exchanging various molecules (Geiger et al., 2010). It thus appears important to identify bacteria naturally harbored by tsetse flies, that are associated with a susceptible or refractory status to trypanosome infection, and that could be used in the gut of the fly to block the establishment of the parasite. In this study, we are investigating whether the taxonomic composition and relative abundance of distinct bacterial taxa harbored by Glossina palpalis palpalis may be associated with Trypanosoma sp. infection status as well as with the sampling sites on the field.

Materials and Methods

1. Sampling area

Tsetse flies were sampled in April 2018 in five villages Campo beach, Ipono, Mvas, Itdonde-Fang, Mabiogo of the Campo focus (2°20' N, 9°52' E), situated in the South region of Cameroon. The Campo focus is known to be hypo-endemic to sleeping sickness where HAT cases are still diagnosed every year (PNLTHA/Cameroon), and where AAT is still active (Figure 1). Campo is located on the Atlantic Coast side, along the Ntem River which separates Cameroon from Equatorial Guinea. In this focus, previous studies reported the presence of several tsetse fly species, namely G. p. palpalis, G. pallicera, G. caliginea (that could be a vector for T. b. gambiense), and G. nigrofusca [START_REF] Simo | Tsetse fly host preference from sleeping sickness foci in Cameroon: Epidemiological implications[END_REF].

Tsetse fly trapping and sampling

Pyramidal traps [START_REF] Gouteux | Le piège pyramidal à tsé-tsé (Diptera: Glossinidae) pour la capture et la lutte. Essais comparatifs et description de nouveaux systèmes de capture[END_REF] were deployed in appropriate tsetse fly biotopes (this could be equatorial forest, riversides, farmlands, cocoa lands) in each village for four consecutive days and their geographical position recorded using a global positioning system (GPS) device. The traps were put out overnight and visited twice a day (10 a.m. and 3 p.m.) and the captured flies recovered to prevent desiccation. In the field laboratory, the tsetse fly species (G. p. palpalis, G. pallicera, G. caliginea and G. nigrofusca) were determined using morphological taxonomic keys [START_REF] Grébaut | Spatial and Temporal Patterns of Human African Trypanosomosis (HAT) Transmission Risk in the Bipindi Focus, in the Forest Zone of Southern Cameroon[END_REF]). Prior to dissection, all G. p. palpalis were sorted, using morphological criteria, into teneral -young flies that had never taken a blood mealand non-teneral flies. Only the non-teneral flies were selected for further analysis. A total of 160 flies were randomly selected for dissection among the 540 non-teneral flies.

3. Dissection of tsetse flies

Prior to dissection, the bench was sterilized using 5% sodium hypochlorite, and each fly was sterilized by immersion successively in 5% sodium hypochlorite for 10 min and twice in 70% ethanol, each for 10 min. Dissection was carried out under sterile conditions, that is in a drop of sterile 0.9% NaCl near the flame of a Bunsen burner. The dissecting instruments were carefully cleaned after the dissection of each fly to prevent cross-contamination. After dissection, tsetse fly whole guts were observed under an optic microscope (magnification x100) to detect the presence of trypanosomes; the tsetse guts were transferred into Eppendorf tubes containing 95% ethanol and stored at room temperature on the field and at -20 °C in the laboratory until further analysis.

4. DNA Extraction

Once in the laboratory, the gut samples were thawed, ethanol was removed by pipetting. The remaining material was air dried. It was disrupted using piston pellets and the DNA was extracted using the DNeasy tissue kit (Qiagen, Paris, France) according to manufacturer instructions. A total of 100 µl of elution buffer was used to recover the DNA extracted from each sample. The concentration of the DNA extracted was measured using a nanodrop (ThermoFisher Scientific, Paris). The DNA samples were stored at -80°C until use.

5. Trypanosome identification by PCR

PCR amplification of parasite DNA was performed using specific primers (Table 1); it was processed as described by [START_REF] Herder | Identification of trypanosomes in wild animals from Southern Cameroon using the polymerase chain reaction (PCR)[END_REF]: an initial denaturation step at 94°C for 5 min was followed by 40 amplification cycles. Each cycle included a denaturation step at 94°C for 30 s, an annealing step for 30 s at 55°C for T. brucei s.l. identification, 60°C for T. congolense or 62°C for T. b. gambiense, and an extension step at 72°C for 1 min. A final extension was performed at 72°C for 10 min. The amplified products were separated on 2% agarose gel containing ethidium bromide and visualized under UV light. Positive (reference trypanosomes DNA) and negative controls (containing PCR reagents and water instead of DNA) were included in each set of PCR amplification experiment.

6. Meta-barcoding Analysis and Taxonomic assignment

PCR amplification was performed on the highly variable V4 region of the 16S rRNA gene. This region was chosen since it was previously shown that it enables the identification of more bacterial genera than the sequencing of the V3V4 region [START_REF] Tsagmo Ngoune | The composition and abundance of bacterial communities residing in the gut of Glossina palpalis palpalis captured in two sites of southern Cameroon[END_REF]. More importantly, we have chosen primers allowing to detect a wider variety of bacteria than those used by [START_REF] Jacob | Intestinal Bacterial Communities of Trypanosome-Infected and Uninfected Glossina palpalis palpalis from Three Human African Trypanomiasis Foci in Cameroon[END_REF][START_REF] Tsagmo Ngoune | The composition and abundance of bacterial communities residing in the gut of Glossina palpalis palpalis captured in two sites of southern Cameroon[END_REF]. In practice, the amplification was performed using the forward primer 5'-CAGCAGCCGCGGTAATAC-3' and the reverse primer 5'-CGCATTTCACCGCTACAC-3', according to the manufacturer (MR DNA Laboratoryhttp://www.mrdnalab.com/shallowater, USA) protocol. The length of the amplicons was between 100 bp to 450 bp. Then the DNA fragments (from each sample (50ng)) was prior linked to adaptors and used to prepare the individual barcode library using Nextera DNA Sample Preparation Kit (Illumina, Singapore). Experion Automated Electrophoresis Station (Bio-Rad, Hercules, USA) was used to determine library insert size. Each PCR reaction was performed in 20 μl (final volume) of a mixture containing 2μl DNA template, 5μl molecular biology-grade water, 10μl HotStarTaq Plus Master Mix, 0.5μl forward primer (10mM), 0.5μl reverse primer (10mM) and 2μl CoralLoad Concentrate. The cycling parameters were a denaturation step at 95°C for 5 min followed by 30 amplification cycles, each cycle including a denaturation step at 94°C for 30 s, an annealing step at 53°C for 40 s, and an extension step at 72°C for 1 min. A final extension was performed at 72°C for 10 min.

PCR products were checked on 2% agarose gel containing ethidium bromide and visualized under UV light to determine the success of amplification. All individual barcoded samples were pooled in equimolar proportions according on their DNA concentrations. Pooled samples were purified using calibrated Ampure XP beads and used to prepare illumina DNA libraries. Pooled library (12pM) was loaded on a 600 Cycles v3 Reagent cartridge (Illumina) and the paired-end sequencing was performed at MR DNA (www.mrdnalab.com, Shallowater, TX, USA) on the Illumina MiSeq sequencing platform according to the manufacturer's guidelines.

Before executing the metabarcoding pipeline, we generated a specific reference file for the assignment step by running CutAdapt v1.18 [START_REF] Martin | Cutadapt removes adapter sequences from high-throughput sequencing reads[END_REF] with the above-mentioned primers to extract V4 reference sequences from the SILVA [START_REF] Yarza | Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences[END_REF]) SSU database (release 132).

CutAdapt was used again in the first stage of the bioinformatics workflow in order to filter on read quality with a threshold value of 20. Then, VSearch v2.10.2 [START_REF] Rognes | VSEARCH: a versatile open source tool for metagenomics[END_REF] The STAMPA pipeline (https://github.com/frederic-mahe/stampa) was then used to proceed with taxonomic assignment of the sequences representing Operational Taxonomic Units (OTU) by similarity with those in the specific reference file preliminarily obtained from SILVA SSU records, which lead to an OTU table. Finally, to retain targeted taxa at the genus level, some filtering was applied on these OTUs, that consisted in eliminating clusters with a high expected error (above 0.0002), or which were considered marginal (representing less than 3 sequences and observed in a single sample).

7. Data Analysis

Statistical analyses were performed using Calypso 8.84 ® (Zakrewski et al. 2016) software.

Rarefaction curves were first performed to check the sequencing depth and to ensure the description and thus the identification of the quasi-totality of the OTUs present in the samples (Zakrewski et al. 2016).

Diversity estimates (α-diversity for within-groups analyses, and β-diversity for between groups comparisons) were calculated with respect to the origin of the flies as well as to their infection status. The α-diversity of the flies' microbiome, which measures the overall diversity including both abundance and evenness of the OTUs, was estimated with the Shannon index; β-diversity analysis was performed to investigate whether there are some differences in the fly microbiota according to infection status and sampling sites. Variation patterns were visualized with principal coordinate analysis (PCoA) using the Bray-Curtis index and their comparison was formally assessed by non-parametric multivariate statistical test, the permutational analysis of variance (PERMANOVA). A complementary method, the Canonical Correspondence Analysis (CCA), was applied. CCA is a multivariate method used to explore complex associations between measured variables and multiple explanatory variables (or confounding factors).

Significant differences in bacterial richness between the infected and uninfected flies, and between the different sampling sites were tested using the non-parametric Kruskal-Wallis test. In order to determine whether or not there is an association between the bacterial flora and the infection status of the fly, we have divided our sample in two groups: the first one was representing bacteria present in both uninfected and infected flies and the second included bacteria occurring only either among infected or uninfected flies. The search for potential genera significantly associated with specific group of flies (infected flies, uninfected flies, flies from each village) was performed using the Wilcoxon rank test and LEfSe (Linear discriminant analysis Effect Size) algorithm [START_REF] Segata | Metagenomic biomarker discovery and explanation[END_REF].

For all these analyses, the threshold for significance was set to 5%. Whatever the analysis, a bacterial taxon was considered only in case it was present in at least 5 individuals and with an abundance higher than 0.01% in each group depending on the parameter of interest (trypanosome infected vs uninfected; comparison between different villages).

Although every care systematically used in the field of microbiological research has been taken to avoid contamination of the samples, the occurrence of such a possibility cannot be entirely excluded. However given that a bacterial taxon was considered only in case it was present in at least 5 individuals and with an abundance higher than 0.01%; it can be estimated that most of the possible contaminants were excluded from the study. Trypanosoma brucei sensu-lato (Tbsl) [11 (13.75%) single infections; 7 (8.75%) mixed infections]; 5 flies were infected with Trypanosoma brucei gambiense (Tbg), all of them were mixed infected. One fly harbored the 4 trypanosome species together.

Results

1. Geographic origin of collected tsetse flies and trypanosome-infection status

As shown in

2. Sequencing quality control

Raw sequencing data of the V4 region generated a total of 37,573,904 paired-end reads and 96.1% were merged, representing 36,112,664 paired-end reads. Out of these merged reads, 79.8% (29,994,337 reads) were of good quality, representing enough sequencing depth with only a few bad sequences, and therefore were retained for further analyses. The rarefaction curves (Figure 2) confirmed the sequencing quality, with the saturation of most of them between 100,000 and 250,000 reads showing that the sequencing effort was sufficient to characterize most of the OTUs.

Global characterization of flies' microbiota

The microbiota composition of the midguts of sampled tsetse flies consisted of 14 phyla + 1 "Uncultured bacteria" corresponding to 261 taxa when assigned at the genus level. However, only 114 bacterial genera belonging to 12 phyla + the "uncultured bacteria" (Supplementary Table S2) were considered because only these genera were recorded at least once in a sampling site (Supplementary Table S3) with a relative abundance greater than the 0.01% abundance threshold. Proteobacteria were present in all the 160 samples and had a mean relative abundance of 90.7% of the total microbiota, while the other phyla (as well as their respective relative abundances) were unevenly distributed across the different flies processed. The predominance of Proteobacteria was mainly due to the very high relative abundance of Wigglesworthia (87.22%), the primary symbiont of the tsetse fly which plays a crucial role in fly's survival. The phylum Tenericutes included only one genus (Spiroplasma) with a relative abundance of 6.2%; Actinobacteria, Bacteroidetes and Firmicutes were present with a mean relative abundance of 0.83, 0.60 and 0.86%, respectively.

By looking more closely the distribution of the bacterial community of the samples, 10 of them presented profiles displaying large abundance differences with reference to the global mean repartition of the bacterial phyla (Supplementary Table S4). So, while the Proteobacteria phylum is, on average, the most abundant, this is not the case, for example in samples 1, 39, 41, 57 and 120 where the most abundant phylum is Tenericutes. In sample 155, the relative abundance of Bacteroidetes, Firmicutes, Proteobacteria were 21.20%, 17.37% and 41.9%, respectively. In sample 20 and 44 the respective relative abundances were 50.29% and 46.82% for Proteobacteria, 19.71% and 13.84% for Actinobacteria, 11% and 9.7% for Bacteroidetes and 10.73% and 14.48% for Firmicutes. Finally, despite the prominence of Proteobacteria phylum, the bacterial genera it includes, as well as their respective relative abundance, are themselves very unevenly distributed as shown in Supplementary Table S5 for the 10 selected flies, where the relative abundance of Wigglesworthia itself varies between 4.1 and 95.4% (mean relative abundance: 87.2%), and where, in sample 155, Tepidiphilus, a genus including 4 extremophilic (thermophilic) bacterial species becomes prominent with 31.6% relative abundance.

We compared the abundance of 11 taxa that displayed highest relative abundance in infected and / or in uninfected flies. Statistically significant differences were observed (Table 3) that, in contrast to Wigglesworthia, associates low relative abundance of the genera Acinetobacter (p=0.051), Bacillus (p=0.008), Cutibacterium (p=0.00012), Pseudomonas (p=0.0063) and Tepidiphilus (p=0.025) to susceptibility of the tsetse fly to trypanosome infection. In addition, when compiling the use of Wilcoxon rank test and LEfSe score as well as relative abundances in infected or uninfected flies, it appeared that the genera Bacteroides (p=0.0042), Georgenia (p=0.0097), Prosthecobacter (p=0.035), even though of low abundance, were also shown to be associated with fly infection. Moreover, as shown in Supplementary Table S7, 36 bacterial genera were shown to be associated to uninfected flies only (they are listed in Table 4). Most of them were present in uninfected flies in low relative abundance (between 0.01 and 0.03%), whereas Paenibacillus and Ralstonia exhibited a relative abundance around 0.03%, two others, Legionela and Novosphingobium, a relative abundance around 0.04%, and Cupriavidus a relative abundance of 0.21%. In contrast, Cellulosimicrobium and Geobacillus were present only in infected flies with a relative abundance of 0.013 and 0.018%, respectively.

6. Bacterial diversity in flies (alpha-diversity)

Globally no statistically significant differences were observed when comparing the bacterial diversity of either Trypanosoma infected flies to uninfected ones (p=0.11) (Figure 3A), or when comparing the flies from different villages (p=0.22) (Figure 3B). In contrast, significant differences were observed when comparing the microbiota richness of the infected flies versus uninfected (p=0.003) (Figure 3C) as well as when comparing microbiota richness among flies from different villages (p=6.2x10 -5 ) (Figure 3D). Thus, we investigated whether a given species of trypanosome could be associated to these differences. A significant difference in the composition of bacterial flora was shown in flies hosting TcS when compared to the microbiota composition of uninfected ones (p=0.047; Figure 3E), while no significant differences were shown when comparing the microbiota composition of respectively Tbrsl (p=0.83; Figure 3F) or TcF (p=0.57; Figure 3G) infected flies with uninfected flies.

7. Multivariate analysis (beta-diversity)

The Principal Coordinate Analysis (PCoA), showing the distribution of the 160 samples (flies) according to their microbiota composition (bacterial distribution) (Figure 4), has highlighted 4 groups depending on the collection site (Figure 4C) and the permutational variance analysis (PERMANOVA) based on each of these components (bacterial distribution and relative abundance) showed that there was statistically significant differences between the composition of the fly microbiota by sampling site with a p-value=0.0003. Furthermore, when the samples were identified by their infection status, the distribution of samples from infected and non-infected flies in general or non-infected flies and flies infected by different subspecies of trypanosomes are homogeneous. This was observed whatever the 4 clusters (Figure 4A, 4B), although multivariate analysis showed statistically significant differences depending on infectious status (p=0.0003) and the subspecies of parasites (p=0.0001).

To refine the results, a Canonical Correspondence Analysis (CCA) (Figure 5), was performed which has pinpointed these differences in taxa composition between infected flies and uninfected flies (p-value=0.001). Finally a hierarchical clustering resulted in a dendrogram which revealed the existence of several clusters associated neither with the infection status of tsetse flies, nor with the sampling sites where the flies were originated from (Figure 6). All these results may indicate that beyond the bacterial composition and or sampling sites (environment differences), there are other factors that could modulate the flies' microbiome composition.

Discussion

The present study is part of a general project aiming at investigating the bacterial flora of fieldcollected tsetse flies and attempting to determine their possible involvement in the establishment of the trypanosome into the gut of the tsetse flies, hence in modulating the flies' vector competence. Previous studies conducted by [START_REF] Jacob | Intestinal Bacterial Communities of Trypanosome-Infected and Uninfected Glossina palpalis palpalis from Three Human African Trypanomiasis Foci in Cameroon[END_REF][START_REF] Tsagmo Ngoune | The composition and abundance of bacterial communities residing in the gut of Glossina palpalis palpalis captured in two sites of southern Cameroon[END_REF] characterized the intestinal microflora of tsetse flies from several HAT and AAT active foci in the Southern region of Cameroon, including the Campo sleeping sickness focus where the tsetse flies included in the present study were collected. In this study, the bacterial composition of the microbiome of 80 flies infected by trypanosomes, and that of 80 uninfected flies were analyzed using the taxo-genomics approach based on the sequencing of the hyper variable V4 region of the small 16S rRNA gene. It resulted in the identification of 261 bacterial genera of which only 114 exhibited relative abundance higher than the 0.01% threshold, while 83 genera were identified by [START_REF] Jacob | Intestinal Bacterial Communities of Trypanosome-Infected and Uninfected Glossina palpalis palpalis from Three Human African Trypanomiasis Foci in Cameroon[END_REF], and only 10 by Tsagmo Ngoune et al. ( 2019) with similar methods. Despite these large differences in the number of bacteria, most of them belonged to the previously identified four phyla, Actinobacteria, Bacteroides, Firmicutes and the Proteobacteria, together with an additional phylum, Tenericutes that was only represented by the genus Spiroplasma. These phyla are commonly characterized, in variable abundance, in the intestine of a variety of insects [START_REF] Andreotti | Assessment of bacterial diversity in the cattle tick Rhipicephalus (Boophilus) microplus through tag-encoded pyrosequencing[END_REF][START_REF] Boissière | Midgut Microbiota of the Malaria Mosquito Vector Anopheles gambiae and Interactions with Plasmodium falciparum Infection[END_REF][START_REF] Zouache | Bacterial diversity of fieldcaught mosquitoes, Aedes albopictus and Aedes aegypti, from different geographic regions of Madagascar[END_REF][START_REF] Terenius | Midgut bacterial dynamics in Aedes aegypti[END_REF][START_REF] Dillon | Composition of Acridid gut bacterial communities as revealed by 16S rRNA gene analysis[END_REF][START_REF] Geib | Effect of host tree species on cellulase activity and bacterial community composition in the gut of larval Asian longhorned beetle[END_REF]Gouveia et al. 2008). Compared to these insects, tsetse flies present a crucial difference in so far as the Proteobacteria are overabundant; on average this phylum represents around 90% relative abundance, followed by Tenericutes with only one species (Spiroplasma) showing a relative abundance around 6%, while each of the three other phyla (Actinobacteria, Bacteroides and Firmicutes) usually account only for about 1%.

Moreover, Proteobacteria overabundance is due to that of one bacterium, Wigglesworthia, the tsetse flies obligate primary symbiont hosted by all the flies, contributing to fly fitness [START_REF] Snyder | Wigglesworthia morsitans" Folate (Vitamin B 9) Biosynthesis Contributes to Tsetse Host Fitness[END_REF]. The overabundance of Wigglesworthia as compared to that of the other tsetse fly intestinal bacteria is systematically reported in the literature [START_REF] Wang | Tsetse fly microbiota: form and function[END_REF][START_REF] Aksoy | Analysis of multiple tsetse fly populations in Uganda reveals limited diversity and species-specific gut microbiota[END_REF][START_REF] Snyder | Wigglesworthia morsitans" Folate (Vitamin B 9) Biosynthesis Contributes to Tsetse Host Fitness[END_REF][START_REF] Jacob | Intestinal Bacterial Communities of Trypanosome-Infected and Uninfected Glossina palpalis palpalis from Three Human African Trypanomiasis Foci in Cameroon[END_REF][START_REF] Tsagmo Ngoune | The composition and abundance of bacterial communities residing in the gut of Glossina palpalis palpalis captured in two sites of southern Cameroon[END_REF], and is considered as responsible for the disruption of a proper identification of low abundant bacteria, and therefore for an underestimation of the fly's gut bacteria diversity. All these phyla are unequally distributed across the 160 samples. Supplementary Tables S3 andS4 provide an overview of the very important diversity in species richness among 10 selected samples. So, the relative abundance of the Proteobacteria was 22.4% in sample 39 while it was 98.9% in sample 94; that of Tenericutes (Spiroplasma) was from 0.16% in sample while it was 115 to 77.2% in sample 39.

Wigglesworthia itself, despite its overabundance "status", is highly unevenly distributed: 4.14% of relative abundance in sample 155, 95.4% in sample 94, and 43.96 % in sample 1, which represents respectively 9.9%, 96.4% and 99.5% of the Proteobacteria relative abundance.

Finally, large diversity was also shown regarding Proteobacteria other than Wigglesworthia. For example, the relative abundance of Pseudomonas was 0.05% in sample 1 while it was 5% (100 times more) in sample 8; more surprisingly, while relative abundance of Wigglesworthia was only 4.1% in sample 155, that of the Tepidiphilus (a genus that includes four species of extremophilic bacteria (Xiao-Tong et al., 2020) reached 31.6%. Where and how did tsetse fly ingest such kind of bacteria that are found in thermophilic water treatment sludge, petroleum reservoir or terrestrial hot spring? [START_REF] Manaia | Tepidiphilus margaretifer gen. nov. sp. nov., isolated from a thermophilic aerobic digester[END_REF][START_REF] Salinas | Petrobacter succinatimandens gen. Nov., sp. nov., a moderately thermophilic, nitrate-reducing bacterium isolated from an Australian oil weil[END_REF][START_REF] Poddar | Taxonomic study of the genus Tepidiphilus: transfer of Petrobacter succinatimandens to the genus Tepidiphilus as Tepidiphilus succinatimandens com. nov. emended description of the genus Tepidiphilus and description of Tepidiphilus thermophiles sp.nov. isolated from a terrestrial hot spring[END_REF]. It was reported that the tsetse fly could ingest bacteria present on the epidermis [START_REF] Poinar | Serratia marcescens as a pathogen of tsetse flies[END_REF] of humans or a variety of vertebrates [START_REF] Moloo | Survival and reproductive performance of female Glossina morsitans morsitans when maintained on the blood of different species of wild mammals[END_REF][START_REF] Simo | Tsetse fly host preference from sleeping sickness foci in Cameroon: Epidemiological implications[END_REF] or on plants' nectar [START_REF] Colman | Do diet and taxonomy influence insect gut bacterial communities?[END_REF][START_REF] Solano | Do tsetse flies only feed on blood?[END_REF] when they feed on them.

In order to check if there would be a bacterial dynamic during this last decade, we have made a listing and a comparison of the bacteria present during the previous studies carried out in this 20 site. One may note that the comparison has only an "indicative" value since different technics were used in these studies for microbiome composition determination i.e. culture-dependant, and molecular with different regions amplified and different primers used (total 16S, V3V4 or V4 only). One may also remember that the molecular method allows identifying bacteria that have been ingested by the flies, but that it does not certify they are still alive and are established in the tsetse fly. The number of identified bacteria was also very different: 261 in the present investigation, 10 in 2019 and 83 in 2017 (molecular methods) and 9 in 2011 (culture method).

One may also note that the very low number of bacteria reported in 2019 (Tsagmo Ngoune et al.

2019) was possibly due to the exceptionally high relative abundance of Wigglesworthia (98.9%) which most probably disrupted identifying low abundant bacteria. Supplementary Table S7 shows the bacteria genera identified in flies collected during at least two entomological campaigns. Fifty-six bacteria corresponded to the criteria except for Sphingobacterium which was identified only when using the culture method, while Tsukamurella, Lactococcus, Staphylococcus, Acinetobacter, Pseudomonas, Serratia and Spiroplasma, were found in flies from 3 sampling campaigns. Of interest is that some of the 56 bacteria are able to secrete antiparasitic compounds [START_REF] Poinar | Serratia marcescens as a pathogen of tsetse flies[END_REF][START_REF] Azambuja | Isolation of Serratia marcescens in the midgut of Rhodnius prolixus: impact on the establishment of the parasite Trypanosoma cruzi in the vector[END_REF]). Such bacteria may impact the establishment of protozoan parasites in their insect vectors as it was reported for mosquitoes [START_REF] Pumpuni | Bacterial population dynamics in three anopheline species: the impact on Plasmodium sporogonic development[END_REF][START_REF] Beier | Effect of paraaminobenzenoic acid, insulin, and gentamicin on Plasmodium falciparum development in Anopheline mosquitoes (Diptera: Culicidae)[END_REF][START_REF] Straif | Midgut bacteria in Anopheles gambiae and A. funestus (Diptera: Culicidae) from Kenya and Mali[END_REF]). So, for example, bacteria belonging to the genus Enterobacter spp. are able to produce pigments, such as prodigiosin [START_REF] Moss | Bacterial pigments[END_REF], which is toxic to Plasmodium falciparum [START_REF] Lazaro | Heptyl prodigiosin, a bacterial metabolite is antimalarial in vivo and non-mutagenic in vitro[END_REF] and to Trypanosoma cruzi [START_REF] Azambuja | Isolation of Serratia marcescens in the midgut of Rhodnius prolixus: impact on the establishment of the parasite Trypanosoma cruzi in the vector[END_REF]. S. marcescens isolated from Rhodnius prolixus has been reported to be able to lyse Trypanosoma cruzi in vitro [START_REF] Azambuja | Isolation of Serratia marcescens in the midgut of Rhodnius prolixus: impact on the establishment of the parasite Trypanosoma cruzi in the vector[END_REF]. Similarly regarding Pseudomonas fluorescens strains that were shown to be able to lyse T. cruzi [START_REF] Mercado | Lysis of Trypanosoma cruzi by Pseudomonas fluorescens[END_REF]. Given that similar bacteria species have been isolated from the midgut of tsetse flies, further investigations deserve to be undertaken in order to verify whether they could modulate the tsetse fly vector competence.

Regarding Sodalis, the tsetse flies' secondary symbiont that was previously shown to favor fly infection with the trypanosome [START_REF] Farikou | Tsetse fly blood meal modification and trypanosome identification in two sleeping sickness foci in the forest of southern Cameroon[END_REF][START_REF] Hamidou Soumana | The transcriptional signatures of Sodalis glossinidius in the Glossina palpalis gambiensis flies negative for Trypanosoma brucei gambiense contrast with those of this symbiont in tsetse flies positive for the parasite: possible involvement of a Sodalis-hosted prophage in fly Trypanosoma refractoriness?[END_REF], this bacterium was identified in very low abundance, thus below the fixed threshold. It was also of low abundance in flies collected during 2 other campaigns [START_REF] Tsagmo Ngoune | The composition and abundance of bacterial communities residing in the gut of Glossina palpalis palpalis captured in two sites of southern Cameroon[END_REF][START_REF] Jacob | Intestinal Bacterial Communities of Trypanosome-Infected and Uninfected Glossina palpalis palpalis from Three Human African Trypanomiasis Foci in Cameroon[END_REF]. Possibly differences in abundance and prevalence between previous and present investigations may be due to differences in the molecular approach, former being performed with Sodalis specific primers. Nevertheless, its maternal transmission from one generation to the next makes it, via para-transgenesis, a good vector for in situ expression of anti-parasitic molecules able to prevent the establishment of the parasite in the gut of tsetse flies.

The large diversity of bacteria, the very low abundance of most of them, and their uneven distribution make difficult the analysis of a possible association between the composition of the microbiome and the susceptibility / resistance of the fly to trypanosome infection. The same is true regarding a possible association with the fly sampling sites and, consequently, with a possible effect of ecological factors on the composition of the microbiome. Several statistical models have been used to analyze the data, additional ones deserve to be tested in further investigations. Despite these difficulties, original results have been obtained. So, 36 bacterial genera have been identified only in uninfected flies. The interest of this finding has however to be modulated since their relative abundance was very low. In fact, the relative abundance of 26 genera out of 36 was lesser than 0.02%, it was between 0.02% and 0.05% for 9 of them, and finally only one bacterial genus, Cupriavidus, had a real significant relative abundance of 0.22%.

Similarly, the presence or the absence of several bacterial genera seems to be specifically associated to trypanosome infection of the tsetse flies or to the fly collection sites.

Statistical analyzes -Shannon Index, PCoA, CCA and Hierarchical clustering -provide conflicting results. However, some of them express a tendency towards an association between the microbiome, its diversity in terms of composition and individual bacteria abundance, and the infection of these flies by the trypanosome (p=0.0003); similarly, regarding the association between microbiome and sampling site (p=0.0003). These results differ from those that [START_REF] Jacob | Intestinal Bacterial Communities of Trypanosome-Infected and Uninfected Glossina palpalis palpalis from Three Human African Trypanomiasis Foci in Cameroon[END_REF][START_REF] Tsagmo Ngoune | The composition and abundance of bacterial communities residing in the gut of Glossina palpalis palpalis captured in two sites of southern Cameroon[END_REF] recorded in the same region; the difference would come from the fact that they focused on the comparison between foci and not between the sampling sites (villages) within a given focus (here the Campo focus). It should be noted that in the five investigated villages the main anthropogenic activity is fishing. Besides, depending on the villages, agriculture, livestock, hunting and logging are carried out at different levels of intensity, which would promote differences in the environmental wild and domestic fauna thus in the diversity of bacteria that tsetse flies could possibly ingest when taking their blood meal.

The aim of this study was to investigate the association between the microbiome composition of the tsetse fly and the presence of trypanosomes, that may modulate its vector competence, even though the complexity of the interactions is not well identified at this stage (one may also remember that as for the gut identified bacteria, the molecular method allows identifying trypanosomes that have been ingested by the flies, but that it does not assess they are still alive and are establish in the tsetse fly). Tsetse flies harboring Trypanosoma congolense "Savanah type" exhibited a different composition of bacterial flora compared to uninfected flies.

Importantly, some bacteria were strongly associated with uninfected status of tsetse flies. The culture of bacteria and their functional analysis would inform on how they can modulate tsetse flies' vector competence, likely useful to the parasite transmission by para-transgenic approach.

Moreover, Mirzaei and Maurice (2017) introduced an additional contributor, bacteriophages, which might be able to modulate the composition of the human microbiome. Results reported by Hamidou Soumana et al. ( 2014) showed that feeding tsetse flies, whether susceptible or refractory to parasite infection, with infected blood meal resulted in a strong alteration of Sodalis gene expression. Most surprisingly was that genes involved in ''lysozyme activity, bacteriolytic enzyme, defense response, peptidoglycan catabolic process, cytolysis, cell death, cell wall macromolecule catabolic process'' were among the most overexpressed genes in flies refractory to trypanosome infection. This finding, together with the puzzling results described in the literature, highlights the possible role of a bacteriophage as a major actor in tsetse fly refractoriness; this role potentially would result in both decreasing Sodalis population density (given that the symbiont favors tsetse fly infection by the trypanosomes), and in triggering the fly's innate immune response. The involvement of bacteriophages cannot be excluded since the analysis of Sodalis transcriptome revealed the presence, into the bacterial genome, of DNA sequences of viral origin. This indicates the presence of a prophage integrated into the Sodalis genome and means the bacterium, or some of its strains, to be lysogenic. This enlarges the field of investigation which deserves to be continued as to attempt to decipher the complex interactions between the three partners, the tsetse fly, the intestinal bacteria and the trypanosome, since the results, although partial, recorded in the tsetse flies as well as in other insect vectors of parasites, indicate that they intervene in their vector competence.

Conclusive remarks and perspectives

The molecular approach used in this study makes it possible to identify bacteria that might be of interest if alive, as they could then be isolated from the gut, cultivated and tested for their real activity as effectors able to modify some biological characteristics of their host -here the modulation of the vector competence of the tsetse fly. In previous investigation we used the culture dependent method which allowed the isolation of several bacteria from the gut of the tsetse fly [START_REF] Geiger | First isolation of Enterobacter, Enterococcus, and Acinetobacter spp. as inhabitants of the tsetse fly (Glossina palpalis palpalis) midgut[END_REF][START_REF] Martin | Cutadapt removes adapter sequences from high-throughput sequencing reads[END_REF] and even to identify Serratia glossinae, a novel bacterial species (Geiger et al, 2010). Similar approach was performed in East Africa, namely by [START_REF] Malele | Bacterial diversity obtained by culturable approaches in the gut of G. pallidipes population from a non-sleeping sickness focus in Tanzania: preliminary results[END_REF].

Aside, a comparative study of the microbiome of female and male tsetse flies could provide important information knowing that bacteria, such as Sodalis, can be transmitted matrilineally from one generation to the next. Analyzing the microbiome of field captured teneral flies could give a response. Such bacteria could become alternatives to Sodalis in the context of a paratransgenic approach. Table 1. Primers used for PCR amplification of trypanosomes' DNA (Farikou et TcS, Tbsl and TcF refer to single infections. These species are also involved in mixed infection. Tbg was involved in mixed infections only.

Tables

  ) and CutAdapt were used alternately in conducting the following tasks: (i) for each sample, merging forward and reverse reads together based on their overlapping areas; (ii) read demultiplexing to generate a single fastq file per sample; (iii) clipping barcodes and primers; (iv) removing sequences containing unknown bases; (v) computing expected error rate; and (vi) dereplicating reads at the sample-level. A single fasta file was then created by pooling remaining sequences together and passed to VSearch for global dereplication. The clustering stage was performed on the remaining unique sequences using Swarm v2.2.2 (Mahé et al. 2015). VSearch was then launched again to mark chimeric clusters.

Figures legends Figure 1 .

 legends1 Figures legends

Figure 2 .

 2 Figure 2. Rarefaction curves performed for all sequenced samples (16S ribosomal subunit, V4

Figure 3 .

 3 Figure 3. Comparison of tsetse flies microbiome diversities. A, C: flies infection status; B, D:

Figure 4 .

 4 Figure 4. Distribution of the tsetse flies samples according to their microbiota composition

Figure 5 .

 5 Figure 5. Differences in taxa composition between infected and uninfected tsetse flies based on

Figure 6 .

 6 Figure 6. Relationship between different samples (represented by their identifier) according to

Table 2 (

 2 Supplementary Table S1 provides individual data), among the 160 flies analyzed 40 % were collected in Campo-beach, 29% in Mvas, 13% in Ipono, 12% in Mabiogo, and 6% in Itdonde-Fang. Fifty percent of these sampled flies were infected with at least one trypanosome species or subspecies, among which 42.1% in Campo-beach, 38% in Ipono, 47.8% in Mvas, 70% in Itdonde-Fang and 84.2% in Mabiogo. Out of the 80 infected flies, 61 (76.25%) were Trypanosoma congolense Savannah-type (TcS) infected [50 (62.5%) single infected; 11 (13.75%) mixed infected]; 13 flies were infected with Trypanosoma congolense Forest-type (TcF) [6 (7.5%) single infections, 7 (8.75%) mixed infections]; 18 (22.5%) were infected with

Table 2 .

 2 Global distribution of simple and mixed tsetse fly infections in the different villages of the Campo focus

	village	Nber of flies analyzed	Nber of infected flies (%)	TcS (%)	Tbsl (%)	TcF (%)	Tc (F & S) (%)	Tbsl & TcS (%)	Tbsl & Tbg (%)	Tbg & TcS (%)	Tc(F & S) & Tbg & Tbsl (%)
	Campo-beach	64	27 (42.1)	11	6	2	3	2	1	1	1
	Ipono	21	8 (38)	0	5	2	0	0	1	0	0
	Mvas	46	22 (47.8)	17	0	2	3	0	0	0	0
	Itdonde-Fang	10	7 (70)	6	0	0	0	0	0	1	0
	Mabiogo	19	16 (84.2)	16	0	0	0	0	0	0	0
	Total	160	80 (50)	50 (31.25)	11 (6.8)	6 (3.75)	6 (3.75)	2 (1.25)	2 (1.25)	2 (1.25)	1 (0.62)

Table 3 .

 3 Comparative relative abundance, in trypanosome-infected and uninfected tsetse flies, of 11 mainly represented bacterial genera

	Bacterial genera	Relative abundance (%)	p-value
		Non-infected flies	Infected flies	(I vs NI)
		(NI)	(I)
	Acinetobacter	1.65	0.24	0.051
	Bacillus	0.25	0.19	0.008
	Chryseobacterium	0.19	0.28	0.2
	Cutibacterium	0.32	0.13	0.00012
	Leuconostoc	0.2	0.21	0.48
	Pseudomonas	0.98	0.29	0.0063
	Spiroplasma	4.78	7.7	0.12
	Tepidiphilus	1.54	1.22	0.025
	Undibacterium	0.23	0.13	0.25
	Wigglesworthia	86.45	87.96	0.032
	Uncultured Bacterium	0.45	0.24	0.45

I: Infected; NI: Non-infected

Table 4 .

 4 Bacterial genera which are present only in uninfected flies

	Taxonomy	Abundance
	Cupriavidus	0.2159
	Legionella	0.0477
	Novosphingobium	0.0412
	Ralstonia	0.0354
	Paenibacillus	0.0311
	Luteolibacter	0.0249
	Alloprevotella	0.0239
	Lachnospiraceae	0.0232
	Altererythrobacter	0.0210
	Glutamicibacter	0.0203
	Hydrogenophilus	0.0184
	Gemella	0.0173
	Chthoniobacter	0.0167
	Comamonas	0.0160
	Jeotgalicoccus	0.0156
	Ruminococcus	0.0155
	Turicella	0.0154
	Fimbriiglobus	0.0149
	Pseudarcicella	0.0146
	Rikenellaceae	0.0144
	Fodinicola	0.0139
	Sporichthyaceae	0.0133

Acknowledgements

We would like to thank Nana Djeunga Hugues Clotaire who provided language help and proof reading of this paper.

Funding

The authors thank the Labex Parafrap and the Institut de Recherche pour le Développement (IRD) for their financial support. FSNF is a PhD student supported by Allocations de recherche pour une thèse au Sud (ARTS) fellowship from the IRD/Labex Parafrap.

The collection of samples was supported by International Atomic Energy Agency (IAEA) funding.

4. Distribution of the bacteria in flies with reference to the 5 sampling sites

Supplementary Table S3 shows the distribution of the taxa and their relative abundance according to the sampling sites. Regarding Wigglesworthia, its relative abundance was prominent in all sites (more than 85% in Ipono, 86% in Campo-beach and Mvas, 89% in Mabiogo and 96% in Itdonde-Fang), despite the large differences of occurrences in some individuals (for example, the Wigglesworthia relative abundance was lowest (4.1%) in sample 155 from Mabiogo. It was highest (95.4%) in sample 94 from Campo beach, while it was only 17.9% in sample 8 trapped in the same village) (Supplementary Table S4). In contrast, relative abundance of Spiroplasma varied from 1.7% in flies from Itdonde-Fang to 9.1% in those from Ipono. Similarly, Acinetobacter relative abundance was 0.057% in Mabiogo vs 2.65% in Mvass, and that of Pseudomonas was 0.05% and 1.58% in Mabiogo and Mvas, respectively. Apart such diversity regarding taxa present in flies from all foci, several other taxa with relative abundances higher than the 0.01% threshold, were only present in a given collection site. These taxa and corresponding sampling sites are presented in Supplementary Table S6. In contrast, some taxa (Aerococcus, Brachybacterium, Kocuria, Nesterenkonia and Prevotella) were specifically absent (abundance threshold <0.01) in Itdonde-Fang site; similarly, Leuconostoc was absent in Mabiogo. Finally, some taxa were not detected at all in some sites; this is the case of Anaerospora in flies from Mvas; Janibacter, Dyadobacter, Phascolarctobacterium and Zymophilus in Mabiogo, Myxosarcina, Anaerospora, Zymophilus, Pseudoxanthomonas in Itdonde-Fang, and Proteiniphilum, Anaerospora in Ipono.

5. Comparative abundance of the bacteria in infected and uninfected tsetse flies

Supplementary Table S7 presents the relative abundance of the overall bacterial genera in infected and uninfected flies. The relative abundance of the genus Wigglesworthia was very high (87.2%), both in infected and uninfected flies, though the abundance of this symbiont was significantly higher among infected flies compared to non-infected ones (p=0.032) (Table 3).

Author contribution

AG conceived the experiments. FSNF, JMTN, and FN performed the experiments. FSNF, JMTN, GS and AG analyzed the data. AG contributed reagents/ materials/analysis tools. FSNF, JMTN, FN, DB and AG wrote the paper.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Florian Chouchou
email: florianchouchou@gmail.com

Muriel Augustini

Teddy Caderby

Nathan Caron

Nicolas A Turpin

Georges Dalleau

The importance of sleep and physical activity on well-being during COVID-19 lockdown: Reunion island as a case study

Keywords: COVID-19, Lockdown, Well-being, Sleep, Physical activity, Anxiety

Background: Lockdown has been one of the major worldwide strategies to control the spread of coronavirus disease 2019 . Its consequences on the well-being of individuals needs to be better understood. The objective of this work was to evaluate the impact of lockdown on the well-being of a general population and the factors associated with this potential impairment of well-being in a population that has been only lightly affected by COVID-19 such as in Reunion island, an overseas French department.

Methods: An online survey was proposed to the population of Reunion Island between the 35 th and 54 th days of lockdown relative to pre-and per-lockdown periods. Well-being was measured by the 5-item World Health Organization Well-Being Index, with some questions about sleep habits (Pittsburgh questionnaire), weekly physical activity (IPAQ), health, and lifestyle.

Results: Four hundred volunteers answered the survey. They reported a 15.7% decrease in well-being (p<0.001), accompanied by increased anxiety (p<0.001), decreased weekly physical activity (p<0.001), delayed and poorer quality sleep (p<0.001). Multivariate logistical analysis showed that impairment in well-being during lockdown was independently associated with an increase in anxiety (odds ratio (OR): 4.77 (3.26-6.98), p<0.001), decrease in weekly physical activity (OR: 0.58 (0.43-0.79), p<0.001), and poor-quality sleep (OR: 0.29 (0.19-0.43), p<0.001).

Conclusions:

This study suggested an impairment in well-being during lockdown, associated with anxiety, lack of physical activity and sleep disruptions. Public policies must consider these factors as levers for improving the well-being of the population in order to effectively combat the spread of COVID-19.

Introduction

In the absence of effective treatment for coronavirus disease 2019 (COVID- [START_REF] Margaritis | How to deal with COVID-19 epidemic-related lockdown physical inactivity and sedentary increase in youth? Adaptation of Anses' benchmarks[END_REF], lockdown appeared as an effective strategy to control its spread [START_REF] Gregori | A first estimation of the impact of public health actions against COVID-19 in Veneto (Italy)[END_REF]. The French government applied strict lockdown measures for 54 days, reducing the spread of the disease in France, COVID-19 hospitalizations and deaths [START_REF] Salje | Estimating the burden of SARS-CoV-2 in France[END_REF]. Mental health problems are one of the main causes of disease burden in the world [START_REF] Whiteford | Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010[END_REF], and the lockdown has short-and long-term negative psychological effects [START_REF] Brooks | The psychological impact of quarantine and how to reduce it: rapid review of the evidence[END_REF]. It is therefore essential to know how to limit its deleterious effects.

People who were isolated for two weeks due to contact with MERS patients suffered from high rates of anxiety symptoms and anger during isolation, and showed mental health effects even at four to six months after removal from isolation.

Mental health could be defined as a state of well-being [START_REF] Oswald | Objective Confirmation of Subjective Measures of Human Well-Being: Evidence from the U[END_REF][START_REF] Topp | The WHO-5 Well-Being Index: A Systematic Review of the Literature[END_REF]. During COVID-19 lockdown, where daily rhythms are disrupted and freedom of movement and assembly are limited, physical inactivity [START_REF] Mcmahon | Physical activity in European adolescents and associations with anxiety, depression and wellbeing[END_REF], stress [START_REF] Malone | The Relationship of Anxiety and Depression to Subjective Well-Being in a Mainland Chinese Sample[END_REF] and sleep disturbances [START_REF] Tang | Changes in Sleep Duration, Quality, and Medication Use Are Prospectively Associated With Health and Well-being: Analysis of the UK Household Longitudinal Study[END_REF] can be a source of mental discomfort. In France, freedom of movement has been limited to basic necessities, essential medical appointments, and professional travel that cannot be replaced by teleworking [START_REF]Épidémie Coronavirus (Covid-19) -Confinement : ce qui est interdit, ce qui est permis[END_REF].

Individual outside physical activity (PA) was still possible within the limit of 1 hour daily and within a maximum one-kilometre area around the home. A clear understanding of the impact of COVID-19 lockdown effects could provide a lever to improve the well-being and improve effectiveness of lockdown and public policies against COVID-19 spread.

Accordingly, the objective of this work was to investigate the impact of lockdown and its related factors on well-being in the general population. We hypothesized that sleep habits and weekly physical activity would contribute to well-being impairment during lockdown.

Methods

Study sample

An online survey was proposed to the adult population (age ≥ 18 y) of Reunion island between the 35 th and 54 th days of lockdown. Four hundred volunteers answered the online survey. This study was applied according to the rules of the French Data Protection Authority (CNIL) and all subjects gave their written informed consent to participate.

Online survey

Responders were asked to answer all questions applying to himself/herself twice, when considering the last month before and during the lockdown. The 5-item World Health Organization Well-Being (WHO-5) index was proposed to participants to measure their subjective well-being. The overall WHO-5 score was rated from 0 (absence of well-being) to 100 (maximal well-being) [START_REF] Topp | The WHO-5 Well-Being Index: A Systematic Review of the Literature[END_REF]. This questionnaire has presented a good internal consistency, with a Cronbach coefficient alpha of 0.84 in the general population [START_REF] Bech | Measuring well-being rather than the absence of distress symptoms: a comparison of the SF-36 Mental Health subscale and the WHO-Five well-being scale[END_REF]. Six items of the Pittsburgh Sleep Quality Index (PSQI) were selected and included one question about sleep quality, one about sleep latency, and those about sleep duration, bedtime and morning awakening [START_REF] Buysse | The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research[END_REF]. This questionnaire has shown an adequate internal consistency (Cronbach coefficient alpha of 0.69) [START_REF] Spira | Reliability and validity of the Pittsburgh Sleep Quality Index and the Epworth Sleepiness Scale in older men[END_REF]. Responders were also asked if they frequently felt anxious, using a scale ranging from never to always (including 6 levels). The level of PA during work and leisure was investigated using selected questions from the International Physical Activity Questionnaire (IPAQ) [START_REF] Craig | International physical activity questionnaire: 12-country reliability and validity[END_REF]. These questions evaluated the duration and frequency of moderate and intense PAs. Energy expenditure was assumed to correspond to 4 METs/min for moderate PA and 6 METs/min for intense PA [START_REF] Craig | International physical activity questionnaire: 12-country reliability and validity[END_REF][START_REF] Ainsworth | Compendium of Physical Activities: a second update of codes and MET values[END_REF]. Sociodemographic and lifestyle information were collected.

Statistical analyses

All statistical analyses were performed using Statview® software (SAS Institute, Inc., Cary, NC, USA).

Answers concerning the before and during lockdown periods were compared using two-sided Wilcoxon, two-sided repeated-measures analyses of variance (RM-ANOVA), or Pearson's two-sided χ² test when appropriate. Effect size was calculated based on eta squared for the parametric variables, Cramer's V for the nominal variables, and the ratio z to the square root of the sample for the nonparametric variables.

Adjusted multivariate logistic regression analyses were performed to explain overall WHO-5 indexes in quartiles, expressed as odds ratio (OR) and using a 95% confidence interval (95%CI), including as independent variables: body mass index, work status under lockdown, age, sex, presence of chronic disease, changes in anxiety, sleep, and PA during lockdown. Significance was set at p<0.05.

Results

Out of all responders (233 women, age: 29.8 ± 11.5 y), none of them reported being infected by COVID-19. A majority (362, 90.5%) were working or students before lockdown. During lockdown, 198 (61%) worked at home, 40 (11.0%) worked at their usual workplace, 15 (4.2%) worked at both, and 73 (20.2%) lost their activity. The majority of responders (393 subjects, 98.3%) reported a good health prior to lockdown. Sixty-eight responders reported having chronic diseases including respiratory, cardiovascular, cancer, or metabolic diseases.

The analysis revealed a decrease in overall WHO-5 score by 15.7% (Table 1), greater anxiety scores, and significant changes in sleep habits during lockdown: the responders went to bed later, fell asleep later and woke up later in the morning. They also reported longer night sleep with more frequent and longer naps, but with a decrease in sleep quality. There was an increase in time spent in the sitting position, a decrease in weekly PA, a slight decrease in moderate weekly PA, and a higher decrease in intense weekly PA.

Those reporting the highest decrease in well-being (4 th and 3 rd quartiles) also reported the highest decrease in their total (p<0.05), moderate (p<0.05) and intense (p<0.05) weekly PAs (Figure 1A). They also reported the greatest impairments in anxiety (p<0.05), sleep quality (p<0.05), bedtime (p<0.05), sleep latency (p<0.05), and morning awakening (p<0.05) (Figure 1B). Adjusted multivariate logistical analyses revealed that the impairment in well-being in those individuals was independently associated with age, a reduction in weekly PA, an increase in anxiety, and a poor sleep quality (Table 2).

Discussion

The current study sought to study the effect of lockdown on the mental health of the Reunion island population. Our results suggested a deep impairment in well-being during lockdown, associated with several independent factors including age, anxiety, lack of PA and disrupted sleep.

Mental health has both positive and negative dimensions: the positive dimension refers to notions of well-being and coping skills; while the negative one includes psychological distress and psychiatric disorders [START_REF] Topp | The WHO-5 Well-Being Index: A Systematic Review of the Literature[END_REF]. Thus, mental health is not considered as only the absence of depression/anxiety symptoms but also as some degree of psychological well-being [START_REF] Bech | Measuring well-being rather than the absence of distress symptoms: a comparison of the SF-36 Mental Health subscale and the WHO-Five well-being scale[END_REF]. Moreover, a subjective definition of well-being has the quality of being correlated with both economic [START_REF] Oswald | Objective Confirmation of Subjective Measures of Human Well-Being: Evidence from the U[END_REF] and neurobiological aspects [START_REF] Urry | Making a life worth living: neural correlates of well-being[END_REF]. Studying mental wellbeing by the WHO-5 index is a strategy for understanding what individuals experience. Two thresholds are considered: a threshold ≤50 is used to detect patients suffering from depression and a change in threshold of 10 points on the WHO-5 scale marks a clinical change [START_REF] Topp | The WHO-5 Well-Being Index: A Systematic Review of the Literature[END_REF]. Here, a major decrease in the WHO-5 scores seemed to appear during lockdown in Reunion (Figure 1A), exceeding these thresholds were 131 (32%) responders who reported a WHO-5 score ≤50 (vs. 77 (19%) before lockdown). Accordingly, a recent Chinese study showed that COVID-19 lockdown affected the psychological health of the population in Hubei province, including more depression, anxiety and impaired well-being [START_REF] Ahmed | Epidemic of COVID-19 in China and associated Psychological Problems[END_REF]. More generally, previous studies on isolation have shown short-and long-term negative psychosocial effects [START_REF] Brooks | The psychological impact of quarantine and how to reduce it: rapid review of the evidence[END_REF], mainly following isolation in response to severe acute respiratory syndrome in 2003. Consistent with COVID-19 lockdown observations, these studies mainly described a high prevalence of various symptoms of psychological distress and negative responses, including fear, sadness, emotional disturbance, depression, stress, low mood, irritability, or anger [START_REF] Brooks | The psychological impact of quarantine and how to reduce it: rapid review of the evidence[END_REF]. In the long term, these subjects were at risk to report anxiety, alcohol abuse or dependency and post-traumatic stress symptoms [START_REF] Jeong | Mental health status of people isolated due to Middle East Respiratory Syndrome[END_REF].

Sedentary behaviors expose populations to well-known risks related to insufficient PA, including cardiovascular or psychological risks [START_REF] Margaritis | How to deal with COVID-19 epidemic-related lockdown physical inactivity and sedentary increase in youth? Adaptation of Anses' benchmarks[END_REF]. Here, we observed that responders reported a decrease in their weekly overall, moderate and intense PAs (Figure 1B); which was also independently correlated with a deterioration in their well-being (Table 1). These results are consistent with two recent studies about COVID-19 lockdown in Portugal [START_REF] Antunes | Exploring Lifestyle Habits, Physical Activity, Anxiety and Basic Psychological Needs in a Sample of Portuguese Adults during COVID-19[END_REF] and Belgium [START_REF] Constandt | Exercising in Times of Lockdown: An Analysis of the Impact of COVID-19 on Levels and Patterns of Exercise among Adults in Belgium[END_REF], in which both reported a decrease in energy expenditure during COVID-19 lockdown. We can therefore think that the lack of PA is a determining factor in the wellbeing under lockdown.

Sleep habits were previously proposed as lifestyle factors that could be an important component of mental health during lockdown [START_REF] Kokou-Kpolou | Insomnia during COVID-19 pandemic and lockdown: Prevalence, severity, and associated risk factors in French population[END_REF]. We observed that most individuals reported longer and shifted sleeps. This shift in the sleep habits was associated with impaired well-being in our study (Figure 1C, Table 1). This result is consistent with longitudinal, transversal or experimental studies revealing that reduced or disrupted sleep is a risk factor for depression and anxiety [START_REF] Simon | Sleep Loss and the Socio-Emotional Brain[END_REF]. Changes in the duration or timing of light exposure, the lack of PA, and absence or disruptions of socioprofessional synchronizers have the potential to desynchronize circadian rhythms, affect mood [START_REF] Rajaratnam | Health in a 24-h society[END_REF], and finally contribute to the impairment of well-being. Thus, it is reasonable to suppose that disruption of circadian rhythms would contribute to impairment in sleep quality and well-being.

Taken together, these results suggest that measures and advice to promote PA at home or outside, as was the case in France (1 h/d and close to home), or advice on sleep hygiene could improve the well-being of populations during lockdown. Finally, it can be thought that improving the well-being of individuals during lockdown may allow them to better comply with the rules of the lockdown and may help to better fight against the spread of COVID-19.

There are several limitations of the present study. The relatively small sample size may limit to the generalizability of these results. However, these results are consistent with previously published studies [START_REF] Ahmed | Epidemic of COVID-19 in China and associated Psychological Problems[END_REF][START_REF] Antunes | Exploring Lifestyle Habits, Physical Activity, Anxiety and Basic Psychological Needs in a Sample of Portuguese Adults during COVID-19[END_REF][START_REF] Constandt | Exercising in Times of Lockdown: An Analysis of the Impact of COVID-19 on Levels and Patterns of Exercise among Adults in Belgium[END_REF]. The study population was relatively young, although age has been found to be an important factor in well-being impairment in this population. Thus, the possibility emerges that older populations may have a greater impairment in wellbeing than has been reported in the current study and previous ones. This issue needs to be explored in future work.

Conclusion

In an anxiety provoking context such as COVID-19 lockdown, limitation of PAs and sleep disturbances could contribute to an alteration in well-being, reaching clinical threshold in a large proportion of responders. The public policies put in place must consider these factors as levers for improving the well-being of the population in order to effectively combat the spread of COVID-19.

Figure 1 .

 1 Figure 1. Relationship between physical activity, sleep and individual well-being during

Table 1 . Changes in anxiety, weekly physical activity, sleep habits and quality before and during COVID-19 lockdown.Table 2 . Odds ratios (OR) for change in well-being with the COVID-19 containment according to WHO-5 score quartiles (95% confidence interval, 95% CI).

 12 Adjustment for sex, age, body mass index chronic disease, and work status during lockdown, plus all variables presented in the Table. It can be noted that age, physical activity, sleep quality and anxiety since lockdown are independently associated with impairment of individual well-being.

Conflict of interest

None of the authors has any conflict of interest to disclose.