https://orcid.org/0000-0001-5716-4725
Figures
Abstract
Bacterial content of mosquitoes has given rise to the development of innovative tools that influence and seek to control malaria transmission. This study identified the bacterial microbiota in field-collected female adults of the Anopheles hyrcanus group and three Anopheles species, Anopheles nivipes, Anopheles philippinensis, and Anopheles vagus, from an endemic area in the southeastern part of Ubon Ratchathani Province, northeastern Thailand, near the Lao PDR-Cambodia-Thailand border. A total of 17 DNA libraries were generated from pooled female Anopheles abdomen samples (10 abdomens/ sample). The mosquito microbiota was characterized through the analysis of DNA sequences from the V3−V4 regions of the 16S rRNA gene, and data were analyzed in QIIME2. A total of 3,442 bacterial ASVs were obtained, revealing differences in the microbiota both within the same species/group and between different species/group. Statistical difference in alpha diversity was observed between An. hyrcanus group and An. vagus and between An. nivipes and An. vagus, and beta diversity analyses showed that the bacterial community of An. vagus was the most dissimilar from other species. The most abundant bacteria belonged to the Proteobacteria phylum (48%-75%) in which Pseudomonas, Serratia, and Pantoea were predominant genera among four Anopheles species/group. However, the most significantly abundant genus observed in each Anopheles species/group was as follows: Staphylococcus in the An. hyrcanus group, Pantoea in the An. nivipes, Rosenbergiella in An. philippinensis, and Pseudomonas in An. vagus. Particularly, Pseudomonas sp. was highly abundant in all Anopheles species except An. nivipes. The present study provides the first study on the microbiota of four potential malaria vectors as a starting step towards understanding the role of the microbiota on mosquito biology and ultimately the development of potential tools for malaria control.
Citation: Boonroumkaew P, Rodpai R, Saeung A, Aupalee K, Saingamsook J, Poolphol P, et al. (2023) Bacterial community structure of Anopheles hyrcanus group, Anopheles nivipes, Anopheles philippinensis, and Anopheles vagus from a malaria-endemic area in Thailand. PLoS ONE 18(8): e0289733. https://doi.org/10.1371/journal.pone.0289733
Editor: Shawky M. Aboelhadid, Beni Suef University Faculty of Veterinary Medicine, EGYPT
Received: April 28, 2023; Accepted: July 25, 2023; Published: August 17, 2023
Copyright: © 2023 Boonroumkaew 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 sequence reads have been deposited at the NCBI Sequence Read Archive (SRA) under project accession number PRJNA953178.
Funding: This research was supported by the Fundamental Fund of Khon Kaen University from the National Science, Research and Innovation Fund (NSRF). The funders had no role in 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
Several Anopheles species are medically important vectors of certain infectious agents, including protozoan parasites of the genus Plasmodium that cause human malaria. Malaria is a widespread and life-threatening disease that results in high levels of morbidity and mortality with an estimated 247 million cases in 2021 from 84 malaria-endemic countries in African, Central and South American, and Asian regions including Thailand [1]. A total of 77 formally named Anopheles species have been reported in Thailand [2, 3, 4, 5], but only seven of these (i.e., Anopheles dirus, Anopheles baimaii, Anopheles minimus, Anopheles aconitus, Anopheles maculatus, Anopheles sawadwongporni, and Anopheles pseudowillmori) are considered significant malaria vectors [6]. In eastern Thailand, Anopheles epiroticus is reported as a secondary vector, while members of the Anopheles barbirostris complex are incriminated as potential vectors in the western region of the country [6]. The Anopheles hyrcanus group, as well as Anopheles nivipes, Anopheles philippinensis, and Anopheles vagus, are also described as secondary and/or potential vectors of malaria parasites in many Asian countries, including India [7, 8], Bangladesh [9], Myanmar [10], Cambodia [11], China-Laos border regions [11], and Thailand [11, 12]. Furthermore, some Anopheles species are regarded as vectors of filarial nematode diseases, including lymphatic filariasis, mansonellosis, and loiasis [13].
Mosquito gut microbiota can influence the development, digestion, immunity, metabolism, and other physiological functions of their hosts [14, 15]. Several studies in African countries, including Kenya [16, 17], Ghana [18], Senegal [19], Mali [20], Ethiopia [21], Burkina Faso [22, 23], Cameroon [24] and the Republic of Guinea [22], as well as in Asian countries, i.e., Vietnam [25], Thailand [26], China [27], and India [28, 29] have shown that variations in gut microbiota affect the ability of insects, especially Anopheles mosquitoes, to transmit pathogens.
To accelerate progress towards malaria elimination, the World Health Organization (WHO) has launched the Global Technical Strategy (GTS) for 2030, which aims to decrease global malaria incidence and mortality rates by at least 90% by 2030 [30]. One of these strategies is to control mosquito populations by using biocontrol tools that involve the natural microbial communities associated with mosquitoes [31], which have a possible impact on malaria transmission and severity [32].
The aim of this study is to characterize the bacterial community structure of four Anopheles species/group from an endemic area of Thailand based on V3 and V4 regions of the 16S rRNA gene. This study sheds new light on the microbiota of these potential malaria vectors, which is crucial for understanding the role of the microbiota in mosquito biology. Ultimately, the findings of this study can also assist in the development of potential tools for controlling mosquito-borne diseases.
Materials and methods
Ethics statement
The protocol related to human (No. 291/2019) and animal (No. 16/2019) used in this study was approved by the Research Ethics Committee of the Faculty of Medicine, Chiang Mai University, Thailand. This study was also approved by the Animal Ethics Committee of the Faculty of Medicine, Khon Kaen University, Thailand (AMEDKKU 012/2022).
Female adult mosquito collections and species identification
Between 2019 and 2021, adult mosquitoes were collected using two methods: human landing catches (HLC) and buffalo bait collections (BBC) at Ban Huai Kha village, Buntharik District, Ubon Ratchathani Province (14.6029N, 105.3893E) (Fig 1) on two consecutive nights. The mosquitoes were collected throughout the study period, covering three seasons (hot, rainy, and cold). Briefly, HLC was performed only outdoors close to homes. One team of two human collectors gathered mosquitoes between the hours of 18:00 and 24:00, and a second team did this between 00:00 and 06:00. For buffalo bait collection (BBC), one buffalo was tethered and surrounded by a bed net suspended 30 cm above the ground level. The buffalo was exposed to mosquitoes entering the net uninterrupted for 45 minutes each hour [12]. All Anopheles mosquitoes resting on inside walls of the net after having bitten the buffalo were collected using an aspirator during the remaining 15 minutes each hour. The ambient air temperature and relative humidity were recorded each hour of collection using a digital hygro-thermometer. All Anopheles mosquitoes were morphologically identified to species group, complex, or species under stereomicroscopes using illustrated morphological keys [2]. It is very difficult to identify species within the An. hyrcanus group based on morphology alone [33]. Then, we termed our specimens belonging to An. hyrcanus group. The head and thorax were separated from the abdomen using sterile forceps for detection of Plasmodium parasites by molecular method [34]. The four most abundant species/group collected, including An. hyrcanus group, An. nivipes, An. philippinensis, and An. vagus were selected for the following experiments. Ten abdomens of each Anopheles species collected on the same day at around the same time were pooled per sample; An. hyrcanus group (HYR; n = 4 pools), An. nivipes (NIV; n = 5 pools), An. philippinensis (PHI; n = 4 pools), and An. vagus (VAG; n = 4 pools) and kept at -20°C until DNA extraction for further investigation of malaria and bacterial community structure.
DNA extraction from abdomens and detection of Plasmodium spp.
Genomic DNA extractions were performed using the PureLink® Genomic DNA Mini Kit (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. DNA concentration and purity were monitored using a NanoDrop Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA).
The presence of Plasmodium spp. DNA was investigated based on partial cox1 gene amplification using DNA samples extracted from separated abdomen specimens. The PCR reactions were performed following Echeverry et al. (2017) [34] with some modifications. Briefly, each PCR reaction was carried out in a 25 μL reaction volume, containing: 1 unit of Platinum Taq DNA polymerase (Invitrogen, Carlsbad, CA, USA), 2 μL of 2.5 mM dNTPs mix (200 μM) (New England Biolabs, Ipswich, Massachusetts, USA), 0.75 μL of 50 mM MgCl2 (1.5 mM), 2.5 μL of 10x PCR buffer (1x) (Invitrogen), 1 μL of 10 μM each of COX-IF (5’ -AGA ACG AAC GCT TTT AAC GCC TG-3’) (0.5 μM) and COX-IR (3’-ACT TAA TGG TGG ATA TAA AGT CCA TCC wGT-5’) primers (0.5 μM), 1 μL of DNA sample, and made up to 25 μL with sterile water. The amplification process commenced at 94°C with a 5 min heat-activation step, followed by 40 cycles of 94°C for 1 min, 62°C for 1 min and 72°C for 90 s with a 10 min final extension step at 72°C. Along with every PCR performed, DNA extracted from laboratory Plasmodium falciparum and Plasmodium vivax in-vitro cultures was used as positive controls.
Bacterial 16S rRNA gene amplification and sequencing
Seventeen DNA samples from pools of ten abdomens of each Anopheles species: An. hyrcanus group (HYR; n = 4 pools), An. nivipes (NIV; n = 5 pools), An. philippinensis (PHI; n = 4 pools), and An. vagus (VAG; n = 4 pools) were used for amplification and sequencing. The universal region-specific primers 341F (5’-CCT AYG GGR BGC ASC AG-3’) and 806R (5’-GGA CTA CNN GGG TAT CTA AT-3’) (NovogeneAIT Genomics Pte. Ltd., Singapore) tagged with sample-identifying barcodes to amplify the V3−V4 regions of the 16S rRNA gene were used. PCR products of approximately 400–450 bp in length were generated. PCR products of the expected size were selected by 2% agarose gel electrophoresis and used for library preparation. At each step of the process, quality control was carried out to maintain the accuracy and reliability of the sequencing data according to the Illumina sequencing system (NovogeneAIT Genomics). The libraries were generated by end-repair, A-tailing, and ligation with Illumina adapters, then assessed using Qubit and qPCR for quantification and a bioanalyzer for size distribution detection. Quantified libraries were sequenced on an Illumina paired-end platform (performed by NovogeneAIT Genomics Pte. Ltd., Singapore) to generate 250 bp paired-end raw reads.
Bioinformatics and statistical analyses
The 16S rRNA gene reads were processed using the QIIME2 pipeline (https://qiime2.org/). The paired-end reads were assigned to samples based on their unique barcodes, truncated by cutting off the barcode and primer sequences, and merged using FLASH (version 1.2.11, http://ccb.jhu.edu/software/FLASH/) [35]. This process generated the raw reads. Quality filtering of these was performed using the fastp software (version 0.20.0) to obtain high-quality clean reads [36]. The reads were compared with the Silva database (https://www.arbsilva.de/) using Vsearch (version 2.15.0) [37] to detect chimeric sequences, which were removed to obtain the effective reads used for subsequent analysis [38]. The sequences have been deposited in the NCBI database under the accession number PRJNA953178.
The effective reads were denoised using DADA2 in the QIIME2 program (version 2020.06) to obtain initial amplicon sequence variants (ASVs). Note that a single species can have more than one ASV associated with it if there is intra-specific variation in this portion of the 16S rRNA gene. Each ASV was compared with the Silva database using the classify-sklearn algorithm in QIIME2 software to obtain the taxonomy annotation [39, 40] and the abundance of each taxon at the level of kingdom, phylum, class, order, family, genus, and species. Moreover, the abundance of ASVs was used to generate a rarefaction curve for estimating the species/group richness and diversity in the microbiota of four Anopheles species/group. Alpha diversity within and between groups was calculated in QIIME2, including observed-species, Chao1, Shannon, Simpson, ACE, and Faith’s alpha metrics. Alpha diversity comparisons were performed using the Kruskal–Wallis nonparametric test. Beta diversity was investigated by weighted UniFrac distance and unweighted UniFrac distance to measure the differences between samples (implemented in QIIME2). The results displayed graphically here were visualized using R software (version 3.5.3).
Results
Overall distribution of bacteria within different Anopheles species
A total of 2,659 Anopheles females belonging to one group (An. hyrcanus group) in the subgenus Anopheles and nine species/group (An. dirus s.l., An. karwari, An. kochi, An. maculatus group, An. minimus s.l., An. nivipes, An. philippinensis, An. tessellatus and An. vagus) in the subgenus Cellia were collected throughout study period. The four most abundant taxa were An. hyrcanus group (78.15%) followed by An. philippinensis (14.70%), An. nivipes (5.00%) and An. vagus (0.90%). No Plasmodium DNA was discovered using PCR in any of the 17 pooled female Anopheles abdomen samples. Bacterial diversity and abundance were calculated separately for each pool: An. hyrcanus group (HYR; n = 4 pools), An. nivipes (NIV; n = 5 pools), An. philippinensis (PHI; n = 4 pools), and An. vagus (VAG; n = 4 pools). The output statistics are shown in S1 Table. A total of 2,033,707 effective reads (S1 Table) was obtained from all samples, with the number of reads per pool ranging from 74,854 to 143,839. They were assigned to 3,442 bacterial ASVs (S2 Table). The alpha rarefaction curve represents the sequence to a sufficient depth of the sample, with most reaching saturation, which was sufficient to capture the scope of microbial diversity and indirectly reflect the abundances of our Anopheles species/group (S1 Fig). Overall, the microbiota of four Anopheles species/group consisted of taxa belonging to 36 phyla, 90 classes, 223 orders, 368 families, 747 genera, and 598 species (S3 Table). The greatest number of ASVs was found in An. vagus. Twenty-eight ASVs were present in all samples, and each Anopheles species also had some unique ASVs (Fig 2 and S4 Table). Shared ASVs were dominant bacteria and a small number of ASVs were different between samples in the same Anopheles species/group (S5 Table).
Each ellipse represents one group. Values represent the number of ASVs in each overlapping or unique segment.
Bacterial microbiota composition within different Anopheles species
The microbiota of four Anopheles species/group were differed between the same and between species/group (S4 and S5 Tables). Proteobacteria were found in most samples as the main constituent of a shared and conserved core microbiota at the phylum level, accounting for 47.5% of reads in An. hyrcanus group, 60.0% in An. nivipes, 75.4% in An. philippinensis, and 67.6% in An. vagus. Firmicutes were the second most abundant phylum, with the other seven phyla ranging from 9.8% to less than 1% in abundance (Fig 3A).
The top ten taxa in terms of relative abundance at phylum level (A) and family level (B).
At the family level, the microbiota revealed more variation between the different Anopheles species. The Pseudomonadaceae was dominant in An. vagas and An. hyrcanus group, whereas Erwiniaceae was dominant in An. philippinensis and An. nivipes, followed by Moraxellaceae. Carnobacteriaceae and Burkholderiaceae were abundant in An. hyrcanus group and An. vagas, respectively (Fig 3B).
Seven of the ten most abundant genera of the microbiota were gram-negative taxa, including Pseudomonas, Serratia, Rosenbergiella, Ralstonia, Acinetobacter and Pantoea. Gram-positive bacteria were represented by the genera Staphylococcus and Carnobacterium. The most abundant genera represented in An. hyrcanus group included Elizabethkingia, Staphylococcus, Glutamicibacter, Carnobacterium, Thermus, and Asaia. For An. nivipes, the most abundant genera included Cutibacterium, Lysinibacillus, Pantoea, Lactococcus, and Novispirillum. For An. philippinensis, Rosenbergiella was the highest significant, followed by Bacillus, Acinetobacter, and Romboutsia. For An. vagus, the most abundant genera included Pseudomonas, Porphyromonas, Veillonella, Granulicatella, Streptococcus, Massilia, Ralstonia, and Cupriavidus (Fig 4A).
Taxonomic abundance cluster heatmap showing the relative abundance of the 35 most abundant genera (A). The ten most abundant taxa at species level (B).
Pseudomonas sp. was very abundant in all mosquito species except An. nivipes. Carnobacterium maltaromaticum and Pseudomonas aeruginosa were found to be abundant in An. hyrcanus group. The most abundant species found in An. nivipes was Spironema culicis, followed by Lactococcus lactis and Novispirillum itersonii. Elizabethkingia meningoseptica, Asaia krungthepensis, Cedecea neteri, and Staphylococcus saprophyticus were abundant in all species except An. nivipes (Fig 4B).
Bacterial community richness and diversity
For alpha diversity, observed species, ACE, and Chao1 indices that measure bacterial community richness, and the phylogenetic diversity (Faith’s PD) index all revealed a significant difference between An. hyrcanus group and An. vagus and between An. nivipes and An. vagus (p < 0.05 in each case). In addition, the bacterial diversity was assessed using the Shannon and Simpson indices, which showed no significant differences between the Anopheles species/group (Fig 5).
Observed species; the number of species directly observed; the higher the index, the more species detected, ACE and Chao1; the indices estimate the species richness in sample groups, Faith’s PD; a phylogenetic diversity index, Shannon and Simpson; the indices reflect the ASVs diversity within and among sample pools. Kruskal-Wallis-Pairwise were used to detect statistically significant differences between mosquito species (*indicates p value < 0.05).
The differences of bacterial communities between samples were analyzed in terms of beta-diversity. The dissimilarity coefficient between pairwise sample groups was plotted using unweighted and weighted UniFrac distance matrix which showed beta diversity ranging from 0.51 to 0.75 (Fig 6A) and from 0.24 to 0.43 (Fig 6B), respectively.
Heatmaps of beta diversity matrix of the microbiota were plotted based on unweighted (A) and weighted (B) UniFrac distance matrix to reflect the dissimilarity mosquito species. The smaller the value, the lower the differences in species diversity between the two sample groups.
Discussion
Field-collected female adults of four Anopheles species/group were sampled from a malaria-endemic area in the southeastern part of Ubon Ratchathani Province, northeastern Thailand, near the Lao PDR-Cambodia-Thailand border [41]. All samples were negative for Plasmodium DNA by PCR. For this result, we were not able to analyze and compare the bacterial microbiota between non-infected and infected Anopheles mosquitoes. However, the limit information on the gut microbiota of these four Anopheles species/group were obtained, which was required for further study when positive malaria samples are available for comparison. There were several studies that investigated the correlations between midgut microbiota and the mosquito malaria infection status [23, 42]. The abundance of Enterobacteriaceae in the midgut of An. gambiae correlated significantly with P. falciparum infection status [42]. A positive correlation between the Weeksellaceae and Acetobacteraceae families and the presence of Plasmodium gametocytes in the blood meal was also observed in An. gambiae s.l. [23]. Additionally, five bacterial genera, including Aerococcus, Megasphaera, Peptostreptococcus, Roseomonas and Streptococcus were detected exclusively in the abdomen of P. vivax-infected An. minimus [26].
Here, the abdominal bacterial community structure of four Anopheles species/group was profiled using the 16S rRNA gene V3–V4 regions. The relative abundance of the main bacterial genera varied among Anopheles species. To our knowledge, this is the first report of bacterial diversity in these four Anopheles species/group. The bacterial communities differed significantly among the four species/group in terms of alpha diversity and taxonomic diversity at different taxonomic levels. Importantly, the microbiota of An. vagus was found to be significantly more diverse than that of the An. hyrcanus group and An. nivipes in terms of observed species, ACE, Chao1, and phylogenetic diversity (Faith’s PD). According to UniFrac distance, An. vagus was the most dissimilar from other species. This result possibly be due to the differences microbial diversity in habitats and breeding places between the four Anopheles species/group. Anopheles vagus larvae are commonly found in a wide variety of groundwater habitats, in water jars and in holes. While the main species in the An. hyrcanus group immature stages are likely found in rice fields, marshy and swampy areas, ponds, and other similar habitats that contain emergent vegetation as well as the larvae of An. nivipes, and An. philippinensis are found in clean water with considerable vegetation [2].
Proteobacteria and Firmicutes phyla predominated in the midguts of our field-collected Anopheles, in agreement with previous studies [25, 42, 43, 44]. The Pseudomonadaceae, a member of the Proteobacteria phylum, was present in all four mosquito species/group but was least abundant in An. nivipes. Previous study has reported that blood-fed mosquitoes favor the rapid proliferation of members of the Pseudomonadaceae [45]. It is possible that our field-collected Anopheles acquired different blood meals under natural conditions, which correspond to the observed differences in their gut microbiota. Several families (Pseudomonadaceae, Aeromonadaceae and Enterobacteriaceae) reported in this study are core microbiota of many Anopheles species in Africa, Asia, and America [46].
The most abundant bacterial genera identified in this study, such as Enterobacter, Aeromonas, Pantoea, Pseudomonas, Elizabethkingia, Klebsiella and Serratia were also the most abundant according to previous reports [26, 46]. Among these, some taxa have been suggested as promising candidates for paratransgenic modifications in vector-control strategies [47]. Serratia affects Plasmodium development in Anopheles species, thereby rendering it a potential candidate for the development of a malaria transmission intervention strategy [48, 49, 50, 51, 52]. Similarly, the popular candidate bacteria Pantoea, Enterobacter, and Pseudomonas were able to significantly inhibit the development of Plasmodium in the mosquito host [48, 53, 54]. However, there is a notably lower abundance of these bacteria in An. vagus compared to the other three Anopheles species. These findings indicate that bacterial composition varies among different Anopheles species. Anopheles vagus was dominated by Pseudomonas, Ralstonia, Cupriavidus, and Streptococcus. Previously, Streptococcus had been reported as one of five bacterial genera detected in Anopheles minimus infected with Plasmodium vivax in a malaria-endemic region of western Thailand [26]. The genus Rosenbergiella was the most abundant taxon in An. philippinensis. This genus is commonly present in flower nectar and in other insects worldwide, such as Gastrolina depressa and Brithys crini [55, 56], but this is the new record from Anopheles species. The factors that affect the high abundance of Rosenbergiella in the abdomens of female An. philippinensis need further investigation.
At the species level, An. nivipes revealed more evenness in bacterial taxa than did other mosquitoes, with Spironema culicis being the most abundant. Although Spironema culicis has been previously isolated from Culex nigripalpus, a vector of Saint Louis Encephalitis and West Nile viruses in Florida, USA [57], it has not been reported to dominate the gut of Anopheles mosquitoes before. Significantly, Pseudomonas aeruginosa and Carnobacterium maltaromaticum were found to be dominant in the abdomens of female An. hyrcanus group. Carnobacterium maltaromaticum is related to plant defense detoxification mechanisms and pathways [58]. Pseudomonas aeruginosa can form biofilm [59] and inhibit P. falciparum sporogonic development as previously reported in An. stephensi [54]. The presence of these taxa in high abundance in some mosquito species but not in others warrants future investigation into the underlying biological factors explaining this variation.
Our findings provide a snapshot of the microbiota in four Anopheles species/group that are potential vectors of malaria in Thailand. More work is required before using these bacteria in any field applications aimed at limiting the transmission of malaria. The microbiota should be further investigated for possible effects on filarial parasites within the mosquito host. In the future, manipulation of the microbiota may become an important prevention strategy for blocking the transmission of Plasmodium and/or filarial worms in vectors as well as for developing new diagnostics, treatments, and prevention methods for these parasites in humans.
A limitation of the study is that our samples were collected in the field, with no attempt made to standardize environmental parameters of the collection sites. The microbiota of the mosquitoes may have been influenced by such local parameters. Further work is needed to include control samples from bacterial environments such as the water from their breeding places, etc. in the collection areas to facilitate identification and subsequent removal of contaminant sequences.
Supporting information
S1 Table. Results of the processed sequencing data.
https://doi.org/10.1371/journal.pone.0289733.s001
(XLSX)
S2 Table. Complete list of bacterial amplicon sequence variants found across all sample groups.
https://doi.org/10.1371/journal.pone.0289733.s002
(XLSX)
S3 Table. List of each taxonomic rank in the bacteria kingdom (phylum, class, order, family, genus, species) across all sample groups.
https://doi.org/10.1371/journal.pone.0289733.s003
(XLSX)
S4 Table. List of amplicon sequence variants (ASVs) indicates unique and shared ASVs among the four Anopheles species/group.
https://doi.org/10.1371/journal.pone.0289733.s004
(XLSX)
S5 Table. Shared and unique amplicon sequence variants (ASVs) in each Anopheles species/group.
https://doi.org/10.1371/journal.pone.0289733.s005
(XLSX)
S1 Fig.
Rarefaction curves and depth of the richness and diversity indices included the Chao1 (A-B), Faith’s PD (C-D), observed species (E-F), and Shannon (G-H) of the microbial communities. A, C, E, and G represented data from each Anopheles group. B, D, F, and H represented data from each sample. (HYR: An. hyrcanus group; NIV: An. nivipes; PHI: An. philippinensis; VAG: An. vagus).
https://doi.org/10.1371/journal.pone.0289733.s006
(TIF)
References
- 1.
World Health Organization. World Malaria Report 2022. Geneva. 2022. Available from: https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2022.
- 2. Rattanarithikul R, Harrison BA, Harbach RE, Panthusiri P, Coleman RE. Illustrated keys to the mosquitoes of Thailand IV. Anopheles. Southeast Asian J Trop Med Public Health. 2006; 37: 1–128.
- 3. Somboon P, Thongwat D, Harbach RE. Anopheles (Cellia) rampae n. sp., alias chromosomal form K of the Oriental Maculatus Group (Diptera: Culicidae) in Southeast Asia. Zootaxa. 2011; 810: 47–55.
- 4. Tainchum K, Kongmee M, Manguin S, Bangs MJ, Chareonviriyaphap T. Anopheles species diversity and distribution of the malaria vectors of Thailand. Trends Parasitol. 2015; 31: 109–119. pmid:25697632
- 5. Taai K, Harbach RE. Systematics of the Anopheles barbirostris species complex (Diptera: Culicidae: Anophelinae) in Thailand. Zool J Linn Soc 2015; 174: 244–264.
- 6. Tananchai C, Manguin S, Bangs MJ, Chareonviriyaphap T. Malaria vectors and species complexes in Thailand: implications for vector control. Trends Parasitol. 2019; 35: 544−558. pmid:31182384
- 7. Bhattacharyya DR, Prakash A, Sarma NP, Mohapatra PK, Singh S, Sarma DK, et al. Molecular evidence for the involvement of Anopheles nivipes (Diptera: Culicidae) in the transmission of Plasmodium falciparum in north-eastern India. Ann Trop Med Parasitol. 2010; 104: 331−336. pmid:20659394
- 8. Dhiman S, Yadav K, Rabha B, Goswami D, Hazarika S, Tyagi V. Evaluation of insecticides susceptibility and malaria vector potential of Anopheles annularis s.l. and Anopheles vagus in Assam, India. PLoS One. 2016; 11: e0151786. pmid:27010649
- 9. Al-Amin HM, Kafi MAH, Chakma S, Mohon AN, Khan WA, Haque R, et al. Host selection of field-collected Anopheles jeyporiensis and Anopheles nivipes in Bangladesh. Am J Trop Med Hyg. 2019; 100: 1421−1423. pmid:30994103
- 10. Zhong D, Aung PL, Mya MM, Wang X, Qin Q, Soe MT, et al. Community structure and insecticide resistance of malaria vectors in northern-central Myanmar. Parasit Vectors. 2022; 15: 155. pmid:35505366
- 11. Zhang C, Yang R, Wu L, Luo C, Yang Y, Deng Y, et al. Survey of malaria vectors on the Cambodia, Thailand and China-Laos Borders. Malar J. 2022; 21(1): 399. pmid:36585690
- 12. Poolphol P, Harbach RE, Sriwichai P, Aupalee K, Sattabongkot J, Kumpitak C, et al. Natural Plasmodium vivax infections in Anopheles mosquitoes in a malaria endemic area of northeastern Thailand. Parasitol Res. 2017; 116(12): 3349−3359. pmid:29082435
- 13. Wilairatana P, Kotepui KU, Mala W, Wangdi K, Kotepui M. Prevalence, probability, and characteristics of malaria and filariasis co-infections: A systematic review and meta-analysis. PLoS Negl Trop Dis. 2022; 16(10): e0010857. pmid:36269701
- 14. Minard G, Mavingui P, Moro CV. Diversity and function of bacterial microbiota in the mosquito holobiont. Parasit Vectors. 2013; 6: 146. https://doi.org/10.1186/1756-3305-6-146. pmid:23688194
- 15. Coon KL, Vogel KJ, Brown MR, Strand MR. Mosquitoes rely on their gut microbiota for development. Mol Ecol. 2014; 23(11): 2727–2739. pmid:24766707
- 16. Wang Y, Gilbreath TM, Kukutla P, Yan G, Xu J. Dynamic gut microbiome across life history of the malaria mosquito Anopheles gambiae in Kenya. PLoS One. 2011; 6(9): e24767. pmid:21957459
- 17. Omoke D, Kipsum M, Otieno S, Esalimba E, Sheth M, Lenhart A, et al. Western Kenyan Anopheles gambiae showing intense permethrin resistance harbour distinct microbiota. Malar J. 2021; 8;20(1): 77. pmid:33557825
- 18. Akorli J, Namaali PA, Ametsi GW, Egyirifa RK, Pels NAP. Generational conservation of composition and diversity of field-acquired midgut microbiota in Anopheles gambiae (sensu lato) during colonization in the laboratory. Parasit Vectors. 2019; 12(1): 27. pmid:30635018
- 19. Bassene H, Niang EHA, Fenollar F, Dipankar B, Doucouré S, Ali E, et al. 16S metagenomic comparison of Plasmodium falciparum-infected and noninfected Anopheles gambiae and Anopheles funestus microbiota from Senegal. Am J Trop Med Hyg. 2018; 99(6): 1489−1498. pmid:30350766
- 20. Krajacich BJ, Huestis DL, Dao A, Yaro AS, Diallo M, Krishna A, et al. Investigation of the seasonal microbiome of Anopheles coluzzii mosquitoes in Mali. PLoS One. 2018; 13(3): e0194899. pmid:29596468
- 21. Berhanu A, Abera A, Nega D, Mekasha S, Fentaw S, Assefa A, et al. Isolation and identification of microflora from the midgut and salivary glands of Anopheles species in malaria endemic areas of Ethiopia. BMC Microbiol. 2019; 19(1): 85. pmid:31035931
- 22. Cuesta EB, Coulibaly B, Bukhari T, Eiglmeier K, Kone R, Coulibaly MB, et al. Comprehensive ecological and geographic characterization of eukaryotic and prokaryotic microbiomes in African Anopheles. Front Microbiol. 2021; 12: 635772. pmid:34054746
- 23. Fofana A, Gendrin M, Romoli O, Yarbanga GAB, Ouédraogo GA, Yerbanga RS, et al. Analyzing gut microbiota composition in individual Anopheles mosquitoes after experimental treatment. iScience. 2021; 24(12): 103416. pmid:34901787
- 24. Sandeu MM, Maffo CGT, Dada N, Njiokou F, Hughes GL, Wondji CS. Seasonal variation of microbiota composition in Anopheles gambiae and Anopheles coluzzii in two different eco-geographical localities in Cameroon. Med Vet Entomol. 2022; 36(3): 269−282. pmid:35579271
- 25. Ngo CT, Romano-Bertrand S, Manguin S, Jumas-Bilak E. Diversity of the bacterial microbiota of Anopheles mosquitoes from Binh Phuoc Province, Vietnam. Front Microbiol. 2016; 7: 2095. pmid:28066401
- 26. Tainchum K, Dupont C, Chareonviriyaphap T, Jumas-Bilak E, Bangs MJ, Manguin S. Bacterial microbiome in wild-caught Anopheles mosquitoes in Western Thailand. Front Microbiol. 2020; 11: 965. pmid:32508784
- 27. Feng Y, Tang J, Zhu D, Zhang Y, Zhu G, Wang J. The microbiota of three Anopheles species in China. J Am Mosq Control Assoc. 2021; 37(1): 38−40. pmid:33857314
- 28. Kalappa DM, Subramani PA, Basavanna SK, Ghosh SK, Sundaramurthy V, Uragayala S, et al. Influence of midgut microbiota in Anopheles stephensi on Plasmodium berghei infections. Malar J. 2018; 17(1): 385. pmid:30359252
- 29. Pereira MH, Mohanty AK, Garg S, Tyagi S, Kumar A. Characterization of midgut microbiome of Anopheles stephensi Liston. J Vector Borne Dis. 2021; 58(1): 74−84.
- 30.
World Health Organization. Global technical strategy for malaria 2016–2030, 2021 update. World Health Organization. 2021. Available from: https://apps.who.int/iris/handle/10665/342995.
- 31. Jupatanakul N, Pengon J, Selisana SMG, Choksawangkarn W, Jaito N, Saeung A, et al. Serratia marcescens secretes proteases and chitinases with larvicidal activity against Anopheles dirus. Acta Trop. 2020; 212: 105686. pmid:32866458
- 32. Omondi ZN, Caner A. An overview on the impact of microbiota on malaria transmission and severity: Plasmodium-vector-host axis. Acta Parasitol. 2022; 67(4): 1471−1486. pmid:36264525
- 33.
Mosquito Taxonomic Inventory. Anopheles classification. Available from: https://mosquito-taxonomic-inventory.myspecies.info/node/11358.
- 34. Echeverry DF, Deason NA, Makuru V, Davidson J, Xiao H, Niedbalski J, et al. Fast and robust single PCR for Plasmodium sporozoite detection in mosquitoes using the cytochrome oxidase I gene. Malar J. 2017; 16(1): 230. pmid:28569159
- 35. Magoč T, Salzberg SL. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics. 2011; 27(21): 2957−2963. pmid:21903629
- 36. Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018; 34(17): i884−i890. pmid:30423086
- 37. Rognes T, Flouri T, Nichols B, Quince C, Mahé F. VSEARCH: a versatile open source tool for metagenomics. PeerJ. 2016; 4: e2584. pmid:27781170
- 38. Hess M, Sczyrba A, Egan R, Kim TW, Chokhawala H, Schroth G, et al. Metagenomic discovery of biomass degrading genes and genomes from cow rumen. Science. 2011; 331(6016): 463−467. pmid:21273488
- 39. Bokulich NA, Kaehler BD, Rideout JR, Dillon M, Bolyen E, Knight R, et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome. 2018; 6(1): 90. pmid:29773078
- 40. Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019; 37(8): 852−857. pmid:31341288
- 41. Sumarnrote A, Corbel V, Overgaard HJ, Celhay O, Marasri N, Fustec B, et al. Plasmodium infections in Anopheles mosquitoes in Ubon Ratchathani Province, Northeastern Thailand during a malaria outbreak. J Am Mosq Control Assoc. 2018; 34(1): 11−17. pmid:31442122
- 42. Boissière A, Tchioffo MT, Bachar D, Abate L, Marie A, Nsango SE, et al. Midgut microbiota of the malaria mosquito vector Anopheles gambiae and interactions with Plasmodium falciparum infection. PLoS Pathog. 2012; 8(5): e1002742. pmid:22693451
- 43. Gimonneau G, Tchioffo MT, Abate L, Boissière A, Awono-Ambéné PH, Nsango SE, et al. Composition of Anopheles coluzzii and Anopheles gambiae microbiota from larval to adult stages. Infect Genet Evol. 2014; 28: 715−724. pmid:25283802
- 44. E Silva B, Matsena Zingoni Z, Koekemoer LL, Dahan-Moss YL. Microbiota identified from preserved Anopheles. Malar J. 2021; 20(1): 230. pmid:34022891
- 45. Das De T, Sharma P, Tevatiya S, Chauhan C, Kumari S, Yadav P, et al. Bidirectional microbiome-gut-brain-axis communication influences metabolic switch-associated responses in the mosquito Anopheles culicifacies. Cells. 2022; 11(11): 1798. pmid:35681493
- 46. Villegas LM, Pimenta PF. Metagenomics, paratransgenesis and the Anopheles microbiome: a portrait of the geographical distribution of the anopheline microbiota based on a meta-analysis of reported taxa. Mem Inst Oswaldo Cruz. 2014; 109(5): 672−684. pmid:25185007
- 47. Mancini MV, Damiani C, Accoti A, Tallarita M, Nunzi E, Cappelli A, et al. Estimating bacteria diversity in different organs of nine species of mosquito by next generation sequencing. BMC Microbiol. 2018; 18(1): 126. pmid:30286722
- 48. Bahia AC, Dong Y, Blumberg BJ, Mlambo G, Tripathi A, BenMarzouk-Hidalgo OJ, et al. Exploring Anopheles gut bacteria for Plasmodium blocking activity. Environ Microbiol. 2014; 16(9): 2980−2994. pmid:24428613
- 49. Wang S, Dos-Santos ALA, Huang W, Liu KC, Oshaghi MA, Wei G, et al. Driving mosquito refractoriness to Plasmodium falciparum with engineered symbiotic bacteria. Science. 2017; 357(6358): 1399−1402. pmid:28963255
- 50. Bai L, Wang L, Vega-Rodríguez J, Wang G, Wang S. A gut symbiotic bacterium Serratia marcescens renders mosquito resistance to Plasmodium infection through activation of mosquito immune responses. Front Microbiol. 2019; 10: 1580. pmid:31379768
- 51. Gonzalez-Ceron L, Santillan F, Rodriguez MH, Mendez D, Hernandez-Avila JE. Bacteria in midguts of field-collected Anopheles albimanus block Plasmodium vivax sporogonic development. J Med Entomol. 2003; 40(3): 371−374. pmid:12943119
- 52. Bando H, Okado K, Guelbeogo WM, Badolo A, Aonuma H, Nelson B, et al. Intra-specific diversity of Serratia marcescens in Anopheles mosquito midgut defines Plasmodium transmission capacity. Sci Rep. 2013; 3: 1641. pmid:23571408
- 53. Dennison NJ, Saraiva RG, Cirimotich CM, Mlambo G, Mongodin EF, Dimopoulos G. Functional genomic analyses of Enterobacter, Anopheles and Plasmodium reciprocal interactions that impact vector competence. Malar J. 2016; 15(1): 425. pmid:27549662
- 54. Pumpuni CB, Beier MS, Nataro JP, Guers LD, Davis JR. Plasmodium falciparum: inhibition of sporogonic development in Anopheles stephensi by gram-negative bacteria. Exp Parasitol. 1993; 77(2): 195−199. pmid:8375488
- 55. González-Serrano F, Pérez-Cobas AE, Rosas T, Baixeras J, Latorre A, Moya A. The gut microbiota composition of the moth Brithys crini reflects insect metamorphosis. Microb Ecol. 2020; 79(4): 960−970. pmid:31796995
- 56. Ma M, Chen X, Li S, Luo J, Han R, Xu L. Composition and diversity of gut bacterial community in different life stages of a leaf beetle Gastrolina depressa. Microb Ecol. 2022; pmid:35648155
- 57. Duguma D, Hall MW, Smartt CT, Debboun M, Neufeld JD. Microbiota variations in Culex nigripalpus disease vector mosquito of west nile virus and saint louis encephalitis from different geographic origins. PeerJ. 2019; 6: e6168. pmid:30643680
- 58. Xia X, Gurr GM, Vasseur L, Zheng D, Zhong H, Qin B, et al. Metagenomic sequencing of diamondback moth gut microbiome unveils key holobiont adaptations for herbivory. Front Microbiol. 2017; 8: 663. pmid:28491055
- 59. de Kievit TR. Quorum sensing in Pseudomonas aeruginosa biofilms. Environ Microbiol. 2009; 11(2): 279−288. pmid:19196266