https://orcid.org/0000-0001-5429-9536
Figures
Abstract
Phlebotomine sand flies are vectors of the protozoan parasite Leishmania spp. Although the intestinal microbiota is involved in a wide range of biological and physiological processes and has the potential to alter vector competence, little is known about the impact of host species and environment on the gut microbiome. To address this issue, a comparative analysis of the microbiota of sand fly vector populations of Leishmania major and L. tropica in a mixed focus of cutaneous leishmaniasis in Tunisia was performed. Bacterial 16S rRNA gene amplification and Illumina MiSeq sequencing were used to characterize and compare the overall bacterial and fungal composition of field-collected sand flies: Phlebotomus papatasi, Ph. perniciosus, Ph. riouxi, and Ph. sergenti. Thirty-eight bacterial genera belonging to five phyla were identified in 117 female specimens. The similarities and differences between the microbiome data from different samples collected from three collections were determined using principal coordinate analysis (PCoA). Substantial variations in the bacterial composition were found between geographically distinct populations of the same sand fly species, but not between different species at the same location, suggesting that the microbiota content was structured according to environmental factors rather than host species. These findings suggest that host phylogeny may play a minor role in determining the insect gut microbiota, and its potential to affect the transmission of the Leishmania parasite appear to be very low. These results highlight the need for further studies to decode sand fly Leishmania-microbiota interactions, as even the same bacterial species, such as Enterococcus faecalis, can exert completely opposite effects when confronted with different pathogens within various host insects and vice versa.
Author summary
Leishmania major and L. tropica are the causative agents of cutaneous leishmaniasis in the Tataouine governorate of southeast Tunisia. In this study, the microbiota of Phlebotomus papatasi, Ph. perniciosus, Ph. riouxi, and Ph. sergenti, which were caught from three diverse ecotypes, were analyzed using 16S rRNA gene amplification and Illumina MiSeq sequencing. In total, 117 Leishmania-free and blood-non-fed female specimens were used individually in this study to avoid any bias caused by pooling samples. We found that the gut microbiota was mainly controlled by environmental habitats and other factors, as remarkable differences in microbiota composition within the same species collected from the same location was revealed. Moreover, the results suggested that host phylogeny may play a minor role in determining the insect gut microbiota, and the potential of the host factor to affect the transmission of the Leishmania parasite appeared to be very low. A better understanding of microorganism-insect-gut bacterial interactions is critical, as the interactions between pathogens and gut microbiota do not adhere to a consistent pattern of synergy or antagonism. Even the same bacterial species, such as Enterococcus faecalis, can exert opposing effects when confronted with different pathogens in various host insects
Citation: Tabbabi A, Mizushima D, Yamamoto DS, Zhioua E, Kato H (2024) Comparative analysis of the microbiota of sand fly vectors of Leishmania major and L. tropica in a mixed focus of cutaneous leishmaniasis in southeast Tunisia; ecotype shapes the bacterial community structure. PLoS Negl Trop Dis 18(9): e0012458. https://doi.org/10.1371/journal.pntd.0012458
Editor: Eric Calvo, National Institutes of Health, UNITED STATES OF AMERICA
Received: May 1, 2024; Accepted: August 14, 2024; Published: September 5, 2024
Copyright: © 2024 Tabbabi 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.
Data Availability: All read sequences were deposited in the Sequence Read Archive of NCBI under the accession numbers SRR27926631-SRR2792686 (https://www.ncbi.nlm.nih.gov/sra/PRJNA1074934).
Funding: HK was funded by the Japan Society for the Promotion of Science (JSPS) KAKENHI (Grant Numbers 17H01685, 20H03155 and 21K19193). https://www.mext.go.jp/en/index.htm. The funders play no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Leishmania major and L. tropica are the causative agents of cutaneous leishmaniasis (CL) in the governorate of Tataouine, southeast Tunisia [1]. CL caused by L. major has recently appeared as a consequence of vulnerable populations settling in new neighborhoods at the borders of some villages, where the environmental conditions and development of agricultural activities may be favorable for the transmission of L. major. In contrast, CL cases caused by L. tropica are scattered and prevail in communities living in villages built on the flanks of the rocky mountains of Tataouine [1].
Phlebotomus papatasi is a confirmed vector of L. major in southwest Asia and North Africa [2,3], including central and southern Tunisia, where reservoir host gerbils are abundant [3,4]. In the recently established settlements mentioned above, Ph. papatasi is the first species to occupy new homes owing to its specific habits. This species is considered endophilic and can adapt well to anthropogenic environments [5]. However, the spatial distribution of leishmaniasis cases caused by L. tropica makes it impossible to conclude anthroponotic transmission [1], even though L. tropica is habitually confirmed to be anthroponotic [6]. The North African gundi (Ctenodactylus gundi) is widespread in the mountainous areas of Tataouine and all emerging Tunisian foci of CL caused by L. tropica, highlighting its potential role as a host reservoir [4,7]. Interestingly, the same L. tropica genotype was identified in gundis, humans, and Ph. sergenti within the same southeastern Tunisian L. tropica foci [1,8–11]. These results suggest the possible existence of two transmission cycles of L. tropica in this region, with Ph. sergenti transmitting L. tropica among humans in and around habitats and transmitting the parasite pathogen among gundis in their mountain habitats. Ph. sergenti may also be transmitted to humans when they enter areas inhabited by gundi host reservoirs.
Sand flies live in groups and interact with diverse microbiota. Symbiotic interactions can be neutral, harmful, or have beneficial effects on key aspects of insect host fitness, such as development, fecundity, and lifespan [12–15], while the host, in turn, shapes the gut microbiome by changing nutrient availability through diet choice, host metabolism [16], or by triggering immune factors [17]. For example, the nutritive role of the Proteobacteria phylum in insect hosts by fixing atmospheric nitrogen has been demonstrated [18]. Similarly, previous studies on Lutzomyia longipalpis highlight the importance of bacteria in sand fly growth and development [12]. Conversely, insects tend to mount immune responses to maintain a complex balance between acceptance and rejection, thereby maintaining a peaceful coexistence [17]. The gut bacteria of sand flies can be acquired by their feeding habits (larvae feeding on dead soil organic matter); while, female adults gain blood and sugar meals (plant-fed) through interactions with ingested parasites [19,20]. Indeed, female sand flies become infected when they feed on an infected host and produce a correlative association between the gut microbiota and the ingested parasite, as the growth of Leishmania within the sand fly vector occur exclusively in the midgut and hindgut in the presence of symbiotic bacterial communities [20,21]. These microbes play a critical role in Leishmania parasite growth, development, and vector competence [20,22–26]. Furthermore, microbes egested during infected sand fly bites augment the severity of leishmaniasis by triggering neutrophil infiltration and facilitating parasitic infection [27]. Most studies have focused on Leishmania and its relationships with bacteria and have offered great potential candidates for paratransgenic applications or biological approaches for the control of sand fly populations to prevent Leishmania transmission [17,28].
Various factors including the host habitat, diet, developmental stage, and phylogeny affect insect gut microbiota [29–34]. Similar to many other arthropods, next-generation sequencing of the 16S rRNA gene recently revealed complex microbiomes in sand flies. Recently, the number of studies using high-throughput DNA sequencing to investigate the bacterial richness and diversity of sand flies has increased [23,35–40]. Although we appreciate the role of microorganisms and the advent of next-generation sequencing, the factors modulating the composition of the gut microbial community in sand flies are not yet well defined. Using pooled samples, it was recently shown that sand fly gut microbiota is shaped by both host species and geographical location [34,40,41].
In this study, we assessed the microbiota composition of four field-collected sand fly species. The impact of host and environmental variations on the bacterial and fungal contents transported by Leishmania-free sand flies was examined in two endemic foci of CL in southeast Tunisia during the period of transmission. Individual samples were used to avoid any bias caused by pooling samples. Tracing the microbiota of wild-caught sand flies will be of considerable benefit in the search for possible vector control candidates for a paratransgenic strategy.
Materials and methods
Study area
This study was conducted in the village of Ghomrassen and its borders, an arid bioclimatic area situated in the northern part of the Tataouine governorate in southeast Tunisia (Fig 1). CL caused by L. major has appeared in new neighborhoods at the borders of some villages [1]. Steppe species dominate sparse vegetation. The area is pastoral with irrigated olive groves and cereals surrounding the water points. However, CL caused by L. tropica is located in a mountainous area at a moderate altitude (300 m above sea level) [42]. The average annual temperature is 22°C and rainfall fluctuates between 88 and 157 mm (data available from the Tunisian Institute of Meteorology). The regional landscape was determined using basalt-rock escarpments. Gerbils (Meriones species) live in the surroundings of the village [11]. The North African gundi, C. gundi, is the most common wild rodent that inhabits rocky mountain areas [11]. Ghomrassen is a known historical mixed focus of leishmaniasis, where many CL cases caused by L. major and L. tropica have been detected in specific households located in new marginal neighborhoods and inside the village, respectively [1].
The map of Tunisia on the top left (A) was adapted from a map available at https://www.freeworldmaps.net/africa/tunisia/map.html and shows the geographical situation of the study village, Ghomrassen. The photograph on the top right (B) provides details of the geographical locations of the different sample collection sites: houses of L. tropica- caused CL patients (white circles), houses of L. major-caused CL patients (black circles), and Ctenodactylus gundi biotopes (white triangle). The photos below represent the houses of L. tropica-caused CL patients (C), houses of L. major-caused CL patients (D), and the rocky habitats of C. gundi (E) (free; no copyright photos).
Sample collection
Adult sand flies were collected in September 2022 by setting the Centers for Disease Control miniature light traps (John W. Hock Co., Gainesville, FL) at L. major and L. tropica sites around the CL cases. Four houses with human CL cases caused by L. major were situated in new marginal neighborhoods bordered by burrows inhabited by Meriones and cultivated vegetation. However, the four houses with human CL cases caused by L. tropica were built on the stony mountainside bordering the village. Sand flies were collected from animal sheds. In the rocky mountain, the natural ecotype of C. gundi, traps were placed inside and near the rocky habitats of this wild rodent. The traps were placed 2–3 h before sunset, operated overnight, and retrieved the following morning. Sand flies were washed with distilled water before ethanol fixation to reduce risk contamination. Whole sand fly bodies were subjected to microbiome analysis because we did not have sufficient facilities and equipment to dissect sand flies at the collection sites.
DNA extraction
Absolute ethanol-fixed sand flies were dried and suspended in 250 μl PBS or saline solution. One gram of 0.1 mm-diameter zirconia/silica beads (BioSpec Products, Bartlesville, OK, USA) was added to the extraction tubes to ease the mechanical crash of microbial cells by the bead crusher μT-12 (Taitec, Saitama, Japan) [43]. Lysed cells were spun down and 200 μL of the supernatant was collected for total DNA isolation. Genomic DNA was purified from each sand fly using the ReliaPrep DNA Clean-up and Concentration System kit (Promega Corporation, Madison, WI, USA) according to the manufacturer’s instructions.
Identification of sand flies
The collected sand fly specimens were identified by sequence analysis of the mitochondrial cytochrome oxidase I (COI) gene, as previously reported [44]. The sequences were viewed and edited using the BioEdit genetic analyzer. Each sequence was imported into the NCBI Database and nucleotide basic local alignment search tool was used to search for similarity with other sequences in the GenBank using the NCBI database search (https://www.ncbi.nlm.nih.gov/BLAST).
16S RNA gene-based identification of bacteria from sand flies by PCR and Illumina MiSeq sequencing
Two PCR steps were performed to amplify the variable region (V3-V4) of the 16S rDNA gene. In the first round, PCR amplification was performed in a thermocycler immediately after DNA extraction, using primers targeting the V3 and V4 regions of bacterial 16S rDNA. The following primers were used to amplify the hypervariable regions V3-V4 of the 16S rDNA gene: forward primer: (5′ TCGTCGGCAGCGTCA GATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-3′) and reverse primer (5′-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTA TCTAATCC-3′). Two other regions of the 16S rDNA gene (V1-V2 and V4) were used to evaluate the results of some samples obtained by V3-V4 amplification [34,45]. These regions were recommended by the Illumina protocol manual and showed high-quality sequence data, as previously reported [46]. PCR amplification was performed with 35 cycles of denaturation (95°C, 30 sec), annealing (55°C, 30 s), and polymerization (72°C, 30 sec) using AmpliTaq Gold 360 DNA polymerase. Each 1.5 μl portion of the PCR product was re-amplified with the index primers used to generate amplicon libraries for Illumina sequencing [47]. Amplification success was verified on a 1.5% agarose gel. Sequencing was performed using the Illumina MiSeq platform with MiSeq reagent kit version 3 (Illumina, Inc., San Diego, CA, USA). In this context, it is important to note that the main limitation of Illumina is sample loading sensitivity. Overloading the sequencing platform with too much DNA can lead to issues such as overlapping clusters and reduced sequencing quality. Consequently, the overall error rate of this sequencing technology is approximately 1%.
Detection of Leishmania species
To detect Leishmania parasites in sand flies, PCR was performed using primers specific for Leishmania minicircle kinetoplast DNA [48]. PCR was conducted in a volume of 15 μL using primers and AmpliTaq Gold 360 DNA polymerase. After initial denaturation at 95°C for 10 min, PCR amplification was performed with 35 cycles of denaturation (95°C, 1 min), annealing (55°C, 1 min), and polymerization (72°C, 1 min), followed by a final extension at 72°C for 10 min. The PCR products were analyzed on a 2% agarose gel.
Quantification of bacteria in sand flies
qPCR with TB Green Fast Mix (Takara Bio Inc., Shiga, Japan) was used to quantify the bacteria in whole sand flies using a Thermal Cycler Dice Real-Time System Lite (Takara Bio Inc., Shiga, Japan). The bacterial 16S rRNA gene was used as the target gene and glyceraldehyde 3-phosphate dehydrogenase (GAPGH) was used as the reference gene. The following primer sequences were used: 5′-ACHCCTACGG GDGGCWGCAG-3′ (16S-q-337F) and 5′-GTDTYACCGCGGYTGCTGGCAC-3′ (16S-q-514R) to amplify the bacterial 16S rRNA gene and 5′- TAATTGGGCTTCTGCTGGGG -3′ (Phgapdh-q-F) and 5′- ACCCTTCAAGTGAGCCGATG -3′ (Phgapdh-q-R) to amplify the GAPDH gene. Relative quantities of 16S rRNA genes were calculated using the ΔΔCt method.
ITS1-based identification of fungus from sand flies by PCR and Illumina MiSeq sequencing
The same protocol of bacterial DNA amplification, as described above, was used to amplify the fungal ITS1 region. Owing to different types of biases (specificity to fungi, mismatches, length, and taxonomy), various primer combinations targeting different parts of the ITS region were employed jointly, as approved by the Illumina protocol manual [49]. ITS regions were sequenced using the Illumina MiSeq platform and MiSeq reagent kit version 3.
Data processing and analysis
The reads generated from the MiSeq platform (2 × 301 bp, paired-end format) were produced as fastq files for importation into Quantitative Insights into Microbial Ecology 2 (QIIME2) (version 2020.2.0) [50]. Paired-end reads were trimmed and merged using the DADA2 program in the QIIME2 Plugin. Sequences were clustered into amplicon sequence variants (ASVs) using the QIIME2 program. ASVs were marginalized based on the SILVA version 138 dataset [51], with ≥99% sequence similarity.
Two alpha (abundance-based coverage estimator [ACE] and Pielou), and beta (distance matrix) diversity indices were used to estimate the diversity of sand fly populations in various areas. ACE is an index that reflects bacterial community richness. Pielou index reflects the diversity of bacterial communities. Principal coordinate analysis (PCoA), which is a powerful and popular multivariate analysis method to explore and visualize similarities or dissimilarities in data, was used to display the beta diversity indices of bacterial communities among sand flies [52]. Alpha and beta diversities were analyzed using QIIME2 at a sampling depth of 5055. The group significance of alpha and beta diversity indices was calculated with QIIME2 plugins using the Kruskal–Wallis test and permutational multivariate analysis of variance (PERMANOVA), respectively. Statistical significance was set at p<0.05.
Results
Sand fly collection and identification of sand fly species
A total of 117 Leishmania-free and blood-unfed females were used individually in this study. Sequences of the mitochondrial COI gene were used to identify the sand fly species. Four sand fly species including 85 Ph. papatasi, 15 Ph. perniciosus, 5 Ph. riouxi, and 12 Ph. sergenti were identified.
Microbiome profile of field-collected sand flies
High-throughput sequencing of the 16S rRNA gene was performed to investigate the bacterial diversity of four adult sand fly species caught from three different locations. Taxonomic compositions were compared in the same sand fly species at different sampling locations, and in different sand fly species from the same sampling locations at the phylum and genus levels. Thirty-eight genera belonging to five phyla (Actinobacteriota, Firmicutes, Proteobacteria, Bacteroidota, and Verrucomicrobiota) were identified, with a few unclassified taxa at different ranks (Fig 2). Actinobacteriota and Firmicutes were the most prevalent (39.1% and 36.3%, respectively) phyla. Among the 38 bacterial genera, 18 have never been reported in field-collected sand flies (Akkermansia, Chthoniobacter, Simkania, Candidatus fritschea, Cloacibacterium, Salinimicrobium, Pontibacter, Adhaeribacter, Alistipes, Bacteroides, Romboutsia, Coprostanoligenes, Salinicoccus, Atopostipes, Turicibacter, Streptomyces, Amycolatopsis, and Actinophytocola). Overall, twenty-two bacterial genera contained pathogenic species for humans (46.4%). In the case of Ph. papatasi, the pathogenic bacteria were slightly more abundant in L. major homes (47.3%) than in L. tropica homes (39.7%).
Impact of environmental habitat on microbiome structure
To study the effect of the ecological habitat of sand flies on the gut bacterial community, we compared two alpha (ACE and Pielou) and beta (distance matrix) diversity indices of the microbial community of each sand fly species at different sampling locations (16 flies in the gundi habitat, 43 flies in zoonotic CL [ZCL] homes, and 58 flies in ACL homes). The similarities and differences between the microbiome data from different samples collected from the three collections were explored and visualized using principal coordinate analysis (PCoA). As shown in Fig 3A, the PCoA plot revealed three different sample groups based on the environmental habitat, indicating that the microbial structures from the same area were close to each other, whereas those from different locations were discrete (PERMANOVA, F = 2.44, p<0.05). The observed pattern strongly suggests that all sand flies collected from different sites harbored distinct microbiota, highlighting a strong correlation between the sand fly microbiota association and the environment in which they reside. In this context, it is important to note that the bacterial composition of some samples appeared completely different from others, and further investigation is needed to confirm these results. Different primers were used to amplify bacterial DNA from the same sand fly sample and similar results were obtained (S1 Fig). Moreover, bacterial community richness, as measured by the ACE index, was significantly higher in L. major and L. tropica homes than in the gundi habitat (p<0.05), which may have been due to exposure to several bacterial sources (Fig 3B). In the case of Ph. papatasi, Actinobacteriota (mean: 44.3%; median: 41.3%) was more dominant bacterial genus in L. major homes than in L. tropica homes (mean: 33.2%; median: 28.5%) (Exact Wilcoxon rank sum test, W = 590, p = 0.06), while Firmicutes was the most frequently isolated from sand flies collected in L. tropica homes (mean: 37.3%; median: 37.6%) compared to L. major homes (mean: 28.1%; median: 27.2%) (Exact Wilcoxon rank sum test, W = 999, p = 0.03) (Figs 2 and S2). Overlap was clearly observed between microbes isolated from different areas, including a number of soil and environmental organisms, such as Corynebacterium species.
a) Bacterial PCoA plot illustrating beta diversity distance matrices of the Bray–Curtis distance comparing the sample distribution among the three locations. b) Bacterial box plots of the alpha diversity measure using ACE and Pielou diversity indices at the three locations. GH: Gundi habitat; LMH: L. major homes; LTH: L. tropica homes.
Impact of host species on microbiome structure
To study the effect of host species on the gut bacterial community, we compared the beta (distance matrix) diversity indices of the microbial communities of different host species from the same sampling locations. The similarities and differences between the microbiome data from different samples were explored and visualized using PCoA (Figs 2 and S3). The PCoA plot showed an overlap in the bacterial contents of 85 Ph. papatasi, 15 Ph. perniciosus, 5 Ph. riouxi (small sample size), and 12 Ph. sergenti (PERMANOVA, F = 1.5, p<0.05). This pattern suggested that all sand fly species harbored similar microbes, indicating that variations in the sand fly gut microbiota are not expressed by host genetic factors.
Fungal profile of field-collected sand flies
We characterized the fungal profiles of the same sand fly species collected from different sampling locations and of different host species from the same sampling locations. We identified a higher diversity than previously reported [39] (17 different genera belonging to 4 phyla), with a few unclassified taxa at different ranks (Fig 4). Among these, 10 genera were not associated with phlebotomines (Circinella, Vishniacozyma, Naganishia, Filobasidium, Cystofilobasidium, Sporobolomyces, Coprinopsis, Stemphylium, Alternaria, and Mycosphaerella). Chaetomium genus was recently identified in larvae reared on sand flies. Ascomycota phylum was more abundant than other genera (97.2%).
Impact of environmental habitat on fungal community
The fungal structure of sand fly species collected from the three collections was visualized using PCoA (Fig 5A), which showed that the environmental habitat shapes the fungal communities, as reported above, with bacteria (PERMANOVA, F = 5.5, p<0.05). Moreover, no difference in fungal community richness (ACE) was detected among the three locations; however, L. tropica homes showed the highest evenness of species distribution, as measured by the Pielou evenness index, compared with 2 other habitats (p<0.05) (Fig 5B). In the case of Ph. papatasi, Aspergillus (41.0%) was the most dominant fungal genus in L. major homes compared to L. tropica homes (24.5%), whereas Cladosporium was the most frequently isolated genus from sand flies collected in L. tropica homes (26.3%) compared to L. major homes (11.1%) (Fig 4).
a) Fungal PCoA plot illustrating beta diversity distance matrices of the Bray–Curtis distance comparing the sample distribution among the three locations. b) Fungal box plots of the alpha diversity measure using ACE and Pielou diversity indices at the three locations. GH: Gundi habitat; LMH: L. major homes; LTH: L. tropica homes.
Impact of host species on fungal community
The PCoA plot showed an overlap of the fungal communities of 85 Ph. papatasi, 15 Ph. perniciosus, 5 Ph. riouxi (small sample size limitation), and 12 Ph. sergenti, indicating that host species factors did not influence the overall composition of the fungal structure, as reported above, with bacteria (PERMANOVA, F = 1.6, p = 0.05) (S4 Fig).
Bacterial quantification
Any manipulation that reduces the size/diversity of natural microbiota affects the ability of Leishmania to establish infections in sand flies [24]. The relative quantity of the bacterial communities was assessed in Ph. papatsi at different sampling locations. Our results showed that the bacteria differed slightly between the sand fly ecotypes (Gundi habitat: 0.0007; L. major homes: 0.001; L. tropica homes: 0.0008); however, it was not possible to conclude clear outcomes regarding a quantitative interaction with Leishmania transmission areas (S5 Fig).
Discussion
Microbiota communities were determined in sand fly populations in a mixed focus of CL caused by L. major and L. tropica in Tunisia, and the effects of host species and environmental habitats on the bacterial structure were explored. Because of the difficulties associated with obtaining only midgut samples, as the present study was carried out for vector research and the collected sand flies had to be identified at the species level, whole sand fly bodies from different areas in Tunisia were employed in the microbiome analysis. Our findings revealed that Actinobacteria (39.1%), Firmicutes (36.3%), and Proteobacteria (19.5%) were the main phyla in the four adult sand fly species caught from three different locations. These results are partly in accordance with previous data illustrated by a meta-analysis of the respective gut microbiota of Old and New World sand flies, which showed that more than 57% of the identified bacteria belonged to the Proteobacteria phylum in Lutzomyia sp., whereas for Old World sand flies, Proteobacteria (47.0%) and Firmicutes (40.0%) were preponderant [23]. Bacteria of the Actinobacteria phylum account for 12.7% and 11.9% of Lutzomyia and Phlebotomus sand flies, respectively [23]. Actinobacteria defend ants, beetles, and wasps against detrimental microorganisms by producing antibiotics. The remarkable capacity of Actinobacteria to exploit a wide variety of carbon and nitrogen sources and their extensive repertoire of secondary metabolites predisposes this group to engage in protective symbioses [53]. Defensive mutualism with Actinobacteria may represent a general and widespread phenomenon in arthropod biology, ecology, and evolution.
The 117 studied samples were screened for Leishmania DNA and no positivity was detected. These findings were not surprising, because the rate of Leishmania infection in sand flies is estimated to be very low in nature, even in endemic areas [54]. The resident microbiota of sand flies has a strong effect on vector competence and can partly explain the origin of these results [20,38]. Among the bacterial genera associated with the sand fly midgut, a significant number of bacterial genera known to contain pathogenic species were recorded in the sand fly vectors of L. major and L. tropica, suggesting that sand flies may cause additional health concerns to humans and livestock. However, further studies are needed to determine the risk of these pathogenic bacteria, as their presence in the midgut is insufficient to indicate that sand flies are possible gut bacterial vectors. Furthermore, whether certain clinical outcomes of leishmaniasis are linked to bacteria potentially deposited during Leishmania-infected sand fly bites remains to be fully understood [55]. The relative prevalence of putative pathogens was slightly dependent on location, and there was no significant correlation between the habitat and prevalence of pathogenic bacteria. Ph. papatasi, which is the main ZCL vector in L. major, carries a different rate of pathogenic bacteria than the same species in L. tropica, in which there is no L. major transmission. Notably, in this study, alterations in the gut microbiota of Ph. sergenti were not clear due to a short collection period and density rarity. Extending the collection period may completely change the bacterial structure owing to seasonal variations [23].
Differences in the richness and diversity of gut bacterial composition were found between sand flies belonging to two distinct ZCL and CCL ecotypes, as well as between sand fly species. These findings suggest that the structural shape of the associated microbiota may influence susceptibility to Leishmania infection in both foci; however, it was not possible to elucidate their role or conclude clear outcomes regarding potential pathogenic effects or interactions with Leishmania. Any manipulation that reduces the richness/diversity of the natural microbiota affects the ability of Leishmania to establish infections in sand flies [20,38]. Previous studies have shown that treatment with antibiotics reduces the richness and diversity of the microbiota but increases Leishmania infection, indicating that the microbiota can be a barrier to the establishment and development of promastigotes in Ph. papatasi and Pintomyia evansi [38,56]. In contrast, antibiotic-mediated perturbation of the midgut microbiome in Ph. dubosqui and Lu. longipalpis cannot support Leishmania growth [20,24]. Collectively, these data suggest that the sand fly midgut microbiome is a critical factor for Leishmania growth and differentiation before disease transmission. It is essential to determine the bacterial species and mechanism(s) by which the bacterial microbiome may enhance or repress Leishmania development in the sand fly gut. Conversely, it has been demonstrated that pathogens such as Plasmodium falciparum, Zika, and Chikungunya viruses can shape the abundance and composition of the mosquito gut microbiome [57–60]. On the other hand, our results showed that the bacterial load changed slightly among the three different Ph. papatasi populations, suggesting a quantitative interaction with Leishmania parasites.
Although it is generally accepted that host species and ecological factors can have a strong impact on the gut microbiota of insects [30,61,62], little is known about the impact of these factors on sand fly microbiota. Substantial variations in gut bacterial composition were found between geographically distinct populations of the same sand fly species in the present study, suggesting that the sand fly gut microbiota is shaped by geographical location, potentially affecting pathogen acquisition and transmission by sand fly vectors. These findings highlight the need for further studies to decode the roles of environmental factors in determining the gut microbiome and, therefore, the susceptibility to Leishmania infection in sand fly vectors. However, the identification of the same bacterial composition in different host species from the same sampling location suggests from one side that host phylogeny may play a minor role in determining the insect gut microbiota, and its potential to affect the transmission of the Leishmania parasite appears to be very low. In this context, it is important to mentioned that due to the limitations of field sampling, sand flies were washed with distilled water and fixed with absolute ethanol, and then whole bodies were used for DNA extraction. The washing protocol is not exactly the same as in our previous study [39,40]. Therefore, a risk of contamination with bacteria on the body surface may be considered and may have an impact on the correlation between sand fly microbiota and their environment. Further studies using only midgut samples are needed to clarify this issue. Moreover, no inter-population genetic variations were observed, indicating the absence of environmental barriers between the three studied locations. A better understanding of the sand fly Leishmania-microbiota interactions is critical, as it is possible that even the same bacterial species can exert completely opposite effects when confronted with different pathogens within various host insects, and vice versa. However, some extrinsic and intrinsic factors (cited below) may bias this hypothesis. According to a phylosymbiosis study, closely related species often host similar microbiota [63]. It has recently been demonstrated in laboratory-colonized sand flies that phylogenetically closely related species have similar compositions of their associated microbial communities, which may explain the obtained results, as the four species belonged to the same Phlebotomus genus [40]. Moreover, the host taxa in these studies were mainly across genera and not at species level, limiting precise data analysis [34,40,41]. Recently, it has been shown that host phylogeny is a strong driver of microbiota structure in sand flies [34,40]. Another study showed that both environmental and host species factors can have a marked effect on microbial communities in the sand fly midgut, which is in agreement with our results [41]. Importantly, contrary to previously cited studies, we used individual samples to avoid any biased results, and a remarkable difference in microbiota structure within the same species collected from the same locations revealed a large individual variation in bacterial composition. Several factors are known to affect the structure of microbial communities, including host species, population genetic variability, blood-meal origin, larval and adult habitat, climate, temperature, humidity, location and period of collection, body size, sex, stage of life cycle, co-infection with pathogens and microorganisms, and resistance to insecticides [23,30,61–63,64–74].
In this study, we identified the Bacillus genus in Ph. papatasi and Ph. perniciosus, as expected, since the bacteria of this genus are found in almost all Old World sand fly species [23]. A recent meta-analysis of sand fly-associated bacteria showed that bacteria belonging to the Bacillus genus exhibit a host-specific distribution, with only Bacillus subtilis isolated from more than one sand fly species (Ph. halepensis, Ph. papatasi, and Ph. perniciosus) [23]. Its occurrence in several sand fly species and its nonpathogenic, easily culturable, and genetically malleable nature make it a potential candidate for paratransgenic or biological approaches for the control of sand fly populations to prevent Leishmania transmission. It has previously been used as a promising paratransgenic agent to impair parasite growth and reduce Leishmania transmission [23,75,76]. In addition to the Bacillus genus, we identified the Wolbachia genus from Ph. papatasi and Ph. perniciosus, which are known to be suitable paratransgenic agents and are used to develop paratransgenic mosquitoes [77–81]. Studies on sand flies have shown high infection rates of Wolbachia by Ph. papatasi and Ph. perniciosus (81.7% and 60.3%, respectively), but the impact of Wolbachia on Leishmania infection load remains unclear [82].
Only a few studies have attempted to identify fungal diversity in sand flies [39,83–85] and to the best of our knowledge, this is the first study to show the impact of host species and ecological factors on insect gut fungi. As reported above for bacteria, substantial variations in the gut fungal composition were found between geographically distinct populations of the same sand fly species, suggesting that the sand fly gut fungus is shaped by the environmental habitat, and the host phylogeny probably plays a minor role in determining insect gut fungi, and therefore, in susceptibility to Leishmania infection. However, it has been demonstrated that fungi can modulate vector competence in mosquitoes [86]. Among the detected fungi, 10 genera were not associated with phlebotomines, which expands our knowledge of their occurrence in sand flies. Ascomycetes, including Aspergillus and Cladosporium are opportunistic pathogens found in humans and other animal hosts [87]. These two genera were dominant in L. major and L. tropica homes. This suggests that sand flies may pose an additional threat to human and livestock health. However, the risk posed by these pathogenic fungi remains unclear. Interestingly, Malassezia genus was present in all sand fly species, which may pave the way for the functional characterization of sand fly-associated fungi. A previous study reported a relationship between L. infantum infection in dogs without skin lesions and increased growth of Malassezia pachydermatis with low phospholipase activity [88].
Conclusions
This study describes the complex microbial community structure in sand fly vectors of L. major and L. tropica with a mixed focus on CL in Tunisia. Our results showed that the microbiota content was structured according to environmental factors rather than the host species. Sand flies have adapted to survive in diverse habitats, feed on the blood of a wide range of hosts, and transmit various Leishmania species. Our findings suggest that the ecological diversity of sand flies may contribute to shaping the structure of the associated microbiota. However, the revelation of the same bacterial composition in different host species from the same sampling location suggests that host phylogeny may play a minor role in determining the insect gut microbiota and its potential to affect the transmission of the Leishmania parasite appears to be very low.
Supporting information
S1 Data. Excel spreadsheet containing, in separate sheets, the underlying numerical data and statistical analysis for Figs 2, 3A, 3B, S2, and S3.
https://doi.org/10.1371/journal.pntd.0012458.s001
(XLSX)
S2 Data. Excel spreadsheet containing, in separate sheets, the underlying numerical data and statistical analysis for Figs 4, 5A, 5B, and S4.
https://doi.org/10.1371/journal.pntd.0012458.s002
(XLSX)
S3 Data. Excel spreadsheet containing, in separate sheets, the underlying numerical data for S1 Fig.
https://doi.org/10.1371/journal.pntd.0012458.s003
(XLSX)
S4 Data. Excel spreadsheet containing, in separate sheets, the underlying numerical data for S5 Fig.
https://doi.org/10.1371/journal.pntd.0012458.s004
(XLSX)
S1 Fig. Bacterial genus composition of sand fly samples using different primers.
The asterisk indicates other-level classifications when Qiime2 failed to provide the genus level.
https://doi.org/10.1371/journal.pntd.0012458.s005
(TIF)
S2 Fig. Percentages of Actinobacteriota and Firmicutes in Ph. papatasi collected from L. major and L. tropica homes. The line indicates the median, and the lozenge indicates the mean.
GH: Gundi habitat; LMH: L. major homes; LTH: L. tropica homes.
https://doi.org/10.1371/journal.pntd.0012458.s006
(TIF)
S3 Fig. Bacterial PCoA plot illustrating beta diversity distance matrices of the Bray–Curtis distance compared with the sample distribution among the four species.
https://doi.org/10.1371/journal.pntd.0012458.s007
(TIF)
S4 Fig. Fungal PCoA plot illustrating beta diversity distance matrices of the Bray–Curtis distance compared with the sample distribution among the four species.
https://doi.org/10.1371/journal.pntd.0012458.s008
(TIF)
S5 Fig. Relative quantities of Ph. papatasi collected from three locations. GH: Gundi habitat; LMH: L. major homes; LTH: L. tropica homes.
https://doi.org/10.1371/journal.pntd.0012458.s009
(TIF)
Acknowledgments
We would like to thank Mr. Chouchen Said for his help in accessing homes and collecting sand flies.
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