Population genetics and molecular xenomonitoring of Biomphalaria freshwater snails along the southern shoreline of Lake Malawi, Mangochi District, Malawi

doi:10.21203/rs.3.rs-4611543/v1

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Population genetics and molecular xenomonitoring of Biomphalaria freshwater snails along the southern shoreline of Lake Malawi, Mangochi District, Malawi

https://doi.org/10.21203/rs.3.rs-4611543/v1

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Background

Intestinal schistosomiasis was confirmed endemic in Mangochi District, Malawi, in May of 2018 following an unexpected encounter with discreet populations of Biomphalaria spp. freshwater snails during routine malacological surveillance activities. Since then, only limited malacological surveillance of Biomphalaria has been carried out, and so the distribution of Biomphalaria populations in this area is currently unclear. Additionally, sites of active Schistosoma mansoni transmission in this area are also unknown. Here, through extensive malacological surveillance, we aimed to formally document the distribution of Biomphalaria in Mangochi District. We also aimed to identify active intestinal schistosomiasis transmission sites in this area through subjecting all collected Biomphalaria to a recently developed S. mansoni-specific molecular xenomonitoring PCR.

Methods

Three malacological surveys were carried out along the southern shoreline of Lake Malawi, Mangochi District, Malawi, in November 2021, July 2022 and October/November 2022. All collected Biomphalaria were subjected to cercarial shedding analysis to identify active Schistosoma infections. Shed cercariae were then genotyped to species level using a standard multi-locus PCR and Sanger sequencing protocol. Following this, a subset of Biomphalaria from each collection site were also genotyped to species level using a standard PCR and Sanger sequencing protocol. All collected Biomphalaria were then subjected to a recently developed S. mansoni-specific molecular xenomonitoring PCR to identify infected, but non-shedding, Biomphalaria.

Results

A total of 589 Biomphalaria were collected across all three surveys. One single Biomphalaria (0.17%) was found to be actively shedding Schistosoma cercariae, which were molecularly confirmed as S. mansoni. All genotyped Biomphalaria (n = 42) were molecularly identified as Bi. pfeifferi. A further 19 Biomphalaria, collected from four different surveillance sites, were found to be infected with S. mansoni through molecular xenomonitoring. Intestinal schistosomiasis transmission was therefore identified at four different foci in Mangochi District.

Discussion

Our study highlights the importance of molecular approaches to investigate Biomphalaria populations and monitor Biomphalaria associated intestinal schistosomiasis transmission in endemic areas. As such, the continued development and use of such approaches, in particular the development and use of molecular xenomonitoring assays that can be carried out in resource-poor schistosomiasis-endemic settings, is encouraged. The revision of ongoing schistosomiasis control programmes in Mangochi District, in line with World Health Organization recommendations, is also encouraged.

Biomphalaria pfeifferi

intestinal schistosomiasis

Malawi

phylogenetics

molecular xenomonitoring

water sanitation and hygiene (WASH)

waterborne pathogens

One Health

Schistosomiasis is a neglected tropical disease (NTD) caused by infection with parasitic trematodes of the genus Schistosoma that can lead to debilitating morbidity and mortality (1). Whilst it is estimated that over 230 million people are currently infected globally, over 90% of all cases occur within sub-Saharan Africa (2). Of these, around one-third are deemed intestinal schistosomiasis, caused predominantly by infection with Schistosoma mansoni but also less commonly by infection with Schistosoma intercalatum and Schistosoma guineensis in some restricted areas of central Africa (3, 4). Schistosoma mansoni is transmitted by obligate freshwater snail intermediate hosts of the genus Biomphalaria (Gastropoda: Planorbidae) (5). Human infection occurs through contact with contaminated bodies of freshwater, where infectious S. mansoni larval stages (cercariae) shed from infected Biomphalaria spp. hosts contact their definitive human host and penetrate the skin. As such, intestinal schistosomiasis is often highly prevalent in rural areas lacking adequate water, sanitation, and hygiene (WASH) infrastructure (6).

As each Biomphalaria species can differ in their ability to transmit S. mansoni (7, 8), malacological surveillance and accurate species identification of Biomphalaria in intestinal schistosomiasis-endemic areas is not only of taxonomic interest but can also contribute to a better understanding of disease transmission dynamics and risk of human infection. However, differentiating between Biomphalaria species based on morphological features such as shell conchology is difficult and requires specially trained and skilled malacologists (9). To overcome these challenges, molecular methods such as PCR are routinely used to reliably identify and differentiate Biomphalaria species, typically though genotyping of mitochondrial cytochrome oxidase subunit 1 (cox1) DNA, mitochondrial 16S DNA, and/or the nuclear internal transcribed spacer (ITS) DNA region (10).

Malacological surveillance with collection of Biomphalaria can also allow active sites of intestinal schistosomiasis transmission to be identified through cercarial shedding analysis (8, 11, 12). Cercarial shedding can, however, often be misleading owing to morphological similarities between human-infecting and non-human-infecting trematode cercariae. For example, S. mansoni and Schistosoma rodhaini (a morphologically indistinguishable rodent-infecting sister species of S. mansoni) are both transmitted by Biomphalaria (13, 14). As such, molecular methods are also needed to reliably identify Schistosoma cercaria species. This is typically done through genotyping both mitochondrial (maternally inherited) and nuclear (inherited equally from both parents) DNA loci, as this multi-locus approach allows any potential Schistosoma spp. hybrids with recent multi-species ancestry to be identified (15, 16). Cercarial shedding can also be insensitive, primarily because not all freshwater snails harbouring mature, or patent, Schistosoma infections will actively shed cercariae at collection and because freshwater snails harbouring prepatent infections will also not shed cercariae (8, 11, 12). For these reasons, the World Health Organization (WHO) recommends molecular xenomonitoring of freshwater snail intermediate hosts of Schistosoma particularly in low-endemicity areas, as this approach can be used to detect Biomphalaria infections with S. mansoni missed by cercarial shedding (13, 17, 18).

Lake Malawi is one of seven African Great lakes. With an approximate water surface area of 29,600 Km², Lake Malawi occupies approximately one-fifth of Malawi whilst also bordering Tanzania and Mozambique along its eastern shoreline. The lake’s most southern shoreline, however, borders Mangochi District; one of Malawi’s 28 districts. Owing to insufficient WASH infrastructure, many members of Mangochi’s multiple communities rely on the lake as a source of drinking water, food (via fishing), a place to bathe, a place to tend livestock, and for recreation. As such, human water-contact with the lake’s shoreline is commonplace, resulting in a high prevalence of waterborne diseases in this area, including intestinal and urogenital schistosomiasis, and giardiasis (19–21).

Until recently, intestinal schistosomiasis was not considered locally endemic in Mangochi District as no species of Biomphalaria was known to inhabit the southernmost shoreline of Lake Malawi. However, during routine malacological surveillance in November of 2017, discreet populations of Bi. pfeifferi snails were unexpectedly encountered in submerged beds of Vallisneria freshwater vegetation (22). Subsequently, in May of 2018, an outbreak of intestinal schistosomiasis was confirmed despite annual and ongoing mass drug administration (MDA) campaigns in this area used to reduce transmission of urogenital schistosomiasis (20). One year later, malacological surveillance and subsequent cercarial shedding of Biomphalaria was carried out in an attempt to identify intestinal schistosomiasis transmission sites along this shoreline of Lake Malawi (22). Despite this effort, only one of 201 collected Biomphalaria was found to be actively shedding S. mansoni cercariae. As such, a subset of collected Biomphalaria (n = 76), were screen for S. mansoni infection using a real-time molecular xenomonitoring PCR targeting the genus-specific Schistosoma internal transcribed spacer 2 (ITS2) region. Whilst Schistosoma DNA was detected in a high proportion of Biomphalaria (31%), it is unclear whether this was derived from invading S. mansoni or S. rodhaini, or even potentially from S. haematobium-group trematodes that had penetrated the soft tissues of Biomphalaria but failed to establish an infection. It is also possible that other species of non-Schistosoma trematodes may cross-react with this ITS2-targeting primer/probe combination, and so more extensive molecular xenomonitoring of Biomphalaria collected in this area, using a S. mansoni-specific assay, is needed to fully assess the prevalence of Biomphalaria infections with S. mansoni and identify intestinal schistosomiasis transmission sites.

Here, through extensive malacological surveillance, we aimed to formally document the distribution of Biomphalaria along the southern shoreline of Lake Malawi. We also aimed to identify active intestinal schistosomiasis transmission sites in this area through subjecting all collected Biomphalaria to a recently developed S. mansoni-specific molecular xenomonitoring PCR (23). The purpose of this study was to therefore gain a more thorough understanding of Biomphalaria associated transmission of intestinal schistosomiasis in Mangochi District five years post-outbreak to better inform and strengthen future disease control efforts.

A schematic flow-diagram outlining the study design used can be seen in Fig. 1.

2.1 Malacological surveys and sample sites

Three malacological surveys were carried out along, and near to, the southern shoreline of Lake Malawi, Mangochi District, Malawi. These surveys took place during the following dates: survey 1: November 2021; survey 2: July 2022; survey 3: October/November 2022. In total, 41 individual sites were surveyed at least once during all three surveys (see Additional file 1, Table S1).

2.1.1 Collection of Biomphalaria freshwater snails

Freshwater snails were collected according to a standard protocol (18). Collections were carried out by three trained and experienced technicians for 15 minutes per sampling site. Brief descriptions of all sampling sites (e.g., water depth, degree of vegetation, whether sites were temporal pools located away from the lake’s edge or were at the lake’s edge) were recorded. Biomphalaria were initially identified to genus level based on shell morphology according to previous morphological descriptions (24) and collected into small screwcap pots containing lake water and lake vegetation for short-term (< 3 hours) transportation. Shortly after collection, Biomphalaria were maintained in aquaria, also containing lake water and lake vegetation, according to collection site.

2.2 Cercarial shedding of Biomphalaria and collection of Schistosoma cercariae

Cercarial shedding was carried out according to a standard protocol (25). In brief, the day following collection, Biomphalaria were transferred from aquaria to small transparent plastic ‘shedding’ pots according to collection site. Each shedding pot contained ~ 100 mL clean, bottled water and no more than 30 Biomphalaria. Shedding pots were then placed in a shaded outdoor area (and so not in direct sunlight) between 9:00 am and 16:00 pm to coincide with S. mansoni cercarial shedding patterns as described previously (26). Following light exposure, the bottled water was decanted into a clean petri dish and examined under dissecting microscope to check for motile, furococercous Schistosoma cercariae according to previous morphological descriptions (27). Any groups of Biomphalaria found to be shedding Schistosoma cercariae were recorded and all Biomphalaria were returned to their original aquaria.

The day following initial cercarial shedding, any groups of Biomphalaria found to be shedding Schistosoma cercariae were then individually separated into wells of a 12 well ‘shedding’ plate containing ~ 5 mL clean, bottled water. Shedding plates were then also placed in the same shaded outdoor area between 9:00 am and 16:00 and then examined under dissecting microscope for the presence of Schistosoma cercariae as described above. Any Biomphalaria found to be shedding Schistosoma cercariae were recorded and their corresponding cercariae were individually captured using a micropipette (2.5 µl) and deposited onto Whatman FTA cards for DNA preservation. A description of which Biomphalaria had shed which preserved cercariae was then written onto FTA cards. FTA cards were then stored at ambient temperature according to manufactures instructions.

A record of all shedding and non-shedding Biomphalaria was made, and any shedding Biomphalaria were individually preserved in 100% ethanol within a labelled 2 mL screwcap tube whereas any non-shedding Biomphalaria were pooled according to collection site and preserved in 100% ethanol within labelled 20 mL glass screwcap tubes. All FTA cards and ethanol preserved Biomphalaria were transported to the NHM under ambient conditions for molecular analyses.

2.3 Molecular characterisation of Biomphalaria

2.3.1 DNA extraction: Ethanol preserved Biomphalaria

DNA was individually isolated from all collected Biomphalaria using the BioSprint 96 workstation and BioSprint 96 DNA Blood Kit [QIAGEN, UK] according to a previously outlined protocol that includes using double volume of lysis buffers and an overnight incubation lysis step (23, 28). This magnetic bead-based DNA extraction protocol was chosen as it allows for rapid and high throughput multiple-sample processing using a 96-well plate format.

2.3.2 Mitochondrial cox1 genotyping

Three randomly selected Biomphalaria collected from each malacological survey site across all surveys (n = 42 Biomphalaria) were genotyped. This was done using PCR to amplify a 700 bp region of the Biomphalaria mitochondrial cox1 gene according to a standard protocol (9). Details of all primer sequences, reaction mixes used, and PCR conditions are described in Additional file 2, Tables S1A, S1B and S1C, respectively. All Biomphalaria cox1 PCRs included a positive control using Bi. pfeifferi DNA provided by the Schistosome and Snail Resource (SSR) (29) and a negative control using ddH₂O in place of template DNA. Amplicons were visualised by running 4 µl of PCR products mixed with 1.5 µl 5x loading buffer blue [Bioline, UK] stained with GelRed on a 1% agarose gel. Biomphalaria cox1 PCR products were then purified using the QIAquick PCR purification kit [QIAGEN, UK] according to manufacturer’s instructions and Sanger sequenced in the forward direction using a dilution of the LCO_1490_FW forward primer. Sequence data was visualised, trimmed, and edited as needed using Geneious Prime version 2023.01 [Biomatters, LTD] before being identified using the Basic Local Alignment Search Tool (BLAST) algorithm within the NCBI database (30).

2.3.3 Phylogenetic and diversity analysis

2.3.3.1 Templeton Crandall and Sing (TCS) haplotype network

To assess Bi. pfeifferi cox1diversity, a cox1 haplotype analysis was performed using all generated Bi. pfeifferi cox1 sequence data as well as cox1 sequence data generated using eight Bi. pfeifferi recently collected in Chikwawa District, Malawi (approximately 250 Km south of Mangochi District along the southern-flowing Shire River), [Nkolokosa et al., 2024], 13 East African Bi. pfeifferi cox1 sequences and five West African Bi. pfeifferi cox1 sequences (Additional file 3, Table S1). All cox1 data were aligned using the multiple alignment with fast fourier transform (MAFFT) algorithm within Geneious Prime (default MAFFT parameter settings). The MAFFT alignment was then visualised, trimmed (to ensure uniform ends across all sequences), examined, and edited as needed before being exported from Geneious Prime in Nexus file format and imported into PopART version 1.7 (31). Within PopART, a TCS network (32) was generated to allow examination of haplotype group structuring.

2.3.3.2 Maximum likelihood phylogenetic tree

To further assess Bi. pfeifferi cox1 diversity and lineages, the MAFFT alignment was then aligned to a Bi. glabrata cox1 outgroup sequence (laboratory-bread 1742 strain, originating in Brazil (33)), as well as a Bi. sudanica cox1 sequence (originating in Uganda, Lake Albert), both downloaded from the GenBank repository (Accession numbers: NC005439 and OQ849931, respectively). The alignment was visualised, trimmed examined, and edited as above before being exported from Geneious Prime in Nexus file format and imported into MEGA11 (Pennsylvania, USA), (34). Within MEGA11, a bootstrapped maximum likelihood (ML) phylogenetic tree was constructed using a Hasegawa-Kishino-Yano (HKY85) evolutionary model with 10,000 iterations after having calculated the most appropriate evolutionary model for phylogenetic analysis of these data.

2.4 Molecular characterisation of Schistosoma cercariae.

Individual Schistosoma cercariae where characterised using a multi-locus approach targeting both the mitochondrial (maternally inherited) cox1 and nuclear (inherited equally from both parents) ITS DNA regions (35).

2.4.1 DNA extraction: FTA preserved cercariae

DNA was isolated from up to 20 individual Whatman FTA card-preserved Schistosoma cercariae, per shedding Biomphalaria, according to a standard protocol (36).

2.4.2 Mitochondrial cox1 and nuclear ITS genotyping

PCR was used to amplify a 956 bp region of the Schistosoma mitochondrial cox1 gene according to a standard protocol (37). Details of all primer sequences, reaction mixes used, and PCR conditions are described in Additional file 2, Tables S2A, S2B and S2C, respectively. Cox1 PCRs included a positive control using S. mansoni DNA collectively isolated from three S. mansoni adult worms provided by the SSR and a negative control using ddH₂O in place of template DNA. Amplicons were visualised by running 4 µl of PCR products mixed with 1.5 µl 5x loading buffer blue [Bioline, UK] stained with GelRed on a 1% agarose gel. PCR products were purified as described above and Sanger sequenced in the reverse direction using a dilution of the Schisto_3’ reverse primer. Sequence data was visualised, trimmed, and edited as needed using Geneious Prime version 2023.01 [Biomatters, LTD] before being identified using the Basic Local Alignment Search Tool (BLAST) algorithm within the NCBI database (30).

PCR was then used to amplify the complete Schistosoma nuclear internal transcribed spacer (ITS) region (~ 1005 bp) according to a standard protocol (37). Details of all primer sequences, reaction mixes used, and PCR conditions are described in Additional file 2, Tables S3A, S3B and S3C, respectively. ITS PCRs included one positive and one negative control as with cox1 PCRs. Amplicons were visualised as described above. PCR products were purified as described above and Sanger sequenced in the reverse direction using a dilution of the ETTS1 reverse primer. Sequence data was visualised, trimmed, edited, and identified as with cox1 PCRs.

2.5 Biomphalaria molecular xenomonitoring

A recently developed high throughput, S. mansoni-specific molecular xenomonitoring PCR assay was used to detect either patent, but non-shedding, S. mansoni infections, or prepatent S. mansoni infections within Biomphalaria (23). This assay can also be used to detect Biomphalaria infections with other Trematoda species, including S. rodhaini.

2.5.1 Molecular xenomonitoring PCRs

Molecular xenomonitoring was performed using DNA isolated from all Biomphalaria collected across all surveys. Details of all primer sequences, reaction mixes used, and PCR conditions are described in Additional file 2, Tables S4A, S4B and S4C, respectively. Molecular xenomonitoring PCRs were carried out in batches of 92 samples in a 96 well PCR plate format. PCRs included one positive control using gDNA isolated from a non-infected Bi. pfeifferi provided by the SSR, one positive control using S. mansoni gDNA collectively isolated from three S. mansoni adult worms provided by the SSR, one positive control using S. rodhaini gDNA collectively isolated from three S. rodhaini adult worms provided by the SSR, and one negative control using ddH₂O in place of template DNA. PCR amplicons were visualised by running 7.5 µl PCR product mixed with 2 µl 5x loading buffer blue [Bioline, UK] stained with GelRed on a 2% agarose gel.

Samples that amplified only the Biomphalaria ITS locus (considered an internal DNA extraction and PCR reaction control) were considered negative for Trematoda infection of any sort, including S. mansoni. Samples that successfully amplified all three target loci were considered positive for S. mansoni infection, as well as potentially other species of Trematoda. Samples that amplified only the Biomphalaria and Trematoda ITS loci were considered positive for non-S. mansoni Trematoda infection. Samples that failed to amplify the Biomphalaria ITS locus (regardless of Trematoda ITS and S. mansoni ND5 amplification outcome), were considered to have failed PCR and were repeated. Samples that failed to amplify this locus during the repeat screen were considered to have failed DNA extraction and were omitted from any further analysis.

2.5.2 Confirmatory S. mansoni. ND5 genotyping

All samples that successfully amplified all three target loci were subjected to a secondary singleplex PCR to amplify only the S. mansoni NADH dehydrogenase subunit 5 (ND5) locus for Sanger sequencing (23). Amplicons were visualised in the same manner as multiplex molecular xenomonitoring PCRs. Schistosoma mansoni ND5 PCR products were purified as described above and Sanger sequenced in the forward direction using a dilution of the ND52 forward primer. Sequence data was visualised, trimmed, edited, and identified as described above.

2.5.2.1 Templeton Crandall and Sing (TCS) haplotype network

To assess S. mansoni ND5 diversity, an ND5 haplotype analysis was performed using all generated S. mansoni ND5 sequence data. To do this, a MAFFT alignment was performed using sequence data within Geneious Prime (default MAFFT parameter settings). The MAFFT alignment was then visualised, examined, and edited as described above. The alignment was then exported from Geneious Prime in Nexus file format and imported into PopART version 1.7. Within PopART, a TCS network was generated to allow examination of haplotype group structuring.

2.5.3 Conformation of Biomphalaria infections with other Trematoda species

To identify Trematoda species other than S. mansoni infecting Biomphalaria, all samples that successfully amplified only Biomphalaria and Trematoda ITS loci only were also subjected to a secondary singleplex PCR, again to amplify only the Biomphalaria ITS and Trematoda ITS loci. To do this, the molecular xenomonitoring PCR was repeated however S. mansoni ND5 forward and reverse primers were replaced with ddH₂O. Amplicons were visualised in the same manner as multiplex molecular xenomonitoring PCRs and the ~ 1005 bp Trematoda ITS gel band was excised using a fresh scalpel. Excised gel bands were purified using the QIAquick Gel purification kit [QIAGEN, UK] according to manufacturer’s instructions and were then purified as described above prior to Sanger sequencing in forward direction using a dilution of the ETTS2 forward primer. Sequence data was visualised, trimmed, and edited as needed using Geneious Prime version 2023.01 [Biomatters, LTD] before being identified using the Basic Local Alignment Search Tool (BLAST) algorithm within the NCBI database (30).

3.1 Malacological surveillance and cercarial shedding of Biomphalaria

A total of 589 Biomphalaria were collected across all three surveys (survey 1: n = 285; survey 2: n = 107; survey 3: n = 197). Of all 41 sites surveyed, Biomphalaria were collected from 13 individual sites (31.7%) during at least one survey (Fig. 2; Additional file 1, Table S1), all of which were either shallow temporal pools close to the lake’s edge, or shallow shores of the lake’s edge. More sites were surveyed along the lake’s eastern shoreline owing to greater obstruction by dense vegetation on the lake’s western shoreline. One single Biomphalaria (0.17%) was found to be actively shedding Schistosoma cercariae during cercarial shedding analyses (during survey 3) at survey site 27 (Fig. 2; Additional file 1, Table S2). A total of 81 Schistosoma cercariae shed from this snail were captured and preserved onto a Whatman FTA card for molecular analysis.

3.2 Molecular characterisation of Biomphalaria

DNA was successfully extracted from all collected Biomphalaria. Of these, 42 were identified as Bi. pfeifferi though cox1 analysis. All 42 Bi. pfeifferi cox1 forward sequences were uploaded to the GenBank repository, (Accession numbers: PP524927-PP524968). The Bi. pfeifferi cox1 TCS haplotype network can be seen in Fig. 3 and the Bi. pfeifferi cox1 Maximum Likelihood phylogenetic tree can be seen in Fig. 4.

No diversity was found between any Mangochi District Bi. pfeifferi cox1 sequence data (current study), with all samples representing a single haplotype. This haplotype was also identified in two Bi. pfeifferi from Zimbabwe (Madziwa District and Mishonland District) and was most closely related to a single B. pfeifferi cox1 haplotype found in three Bi. pfeifferi again from Zimbabwe (Madziwa District and Mazowe Reservoir). In addition, no diversity was found between any Malawi, Chikwawa District B. pfeifferi cox1 sequence data and this haplotype was not found in any other Bi. pfeifferi analysed. Three single nucleotide polymorphisms (SNPs) were found between the Mangochi District B. pfeifferi cox1 haplotype (current study) and the Malawi, Chikwawa District B. pfeifferi cox1 haplotype. Overall, very little cox1 diversity was observed across all Bi. pfeifferi cox1 data, however different haplotypes were found from different countries (Senegal, Uganda, Kenya, Zimbabwe, and Malawi), with clustering observed between haplotypes found in Zimbabwe and Malawi and a greater degree of divergence observed between samples from Senegal (west Africa) and Malawi. This structuring was also observed within the maximum likelihood phylogenetic tree, which formed a monophyletic clade that included the Mangochi District Bi. pfeifferi cox1 haplotype, all five Zimbabwe Bi. pfeifferi cox1 haplotypes, and the Malawi, Chikwawa District Bi. pfeifferi cox1 haplotype.

3.3 Molecular characterisation of Schistosoma cercariae.

3.3.1 Schistosoma cercariae mitochondrial cox1 and nuclear ITS PCR and genotyping

Five Schistosoma cercariae shed from the single shedding Biomphalaria were successfully genotyped to species level. All five were identified as S. mansoni across both cox1 and ITS loci. No genetic variation was observed between cox1 sequence data or between ITS sequence data. All five S. mansoni cox1 sequences and all five S. mansoni ITS sequences were uploaded to the GenBank repository (35), (Accession numbers: PP529587-PP529591 and PP510205-PP510209, respectively).

3.4 Biomphalaria molecular xenomonitoring

All 589 Biomphalaria were screened for S. mansoni and other Trematoda species infections using molecular xenomonitoring. A total of 14 (2.4%) samples failed to amplify the Biomphalaria internal control ITS locus, and so were repeated. All 14 successfully amplified the Biomphalaria ITS locus during the repeat molecular xenomonitoring PCR. All three target loci were amplified when using DNA extracted from the one Bi. pfeifferi shedding S. mansoni cercariae, as well as 19 additional non-shedding Biomphalaria.

The S. mansoni ND5 locus was successfully amplified during the secondary S. mansoni ND5 singleplex PCR in all 20 Biomphalaria samples that had amplified all three target loci during the initial molecular xenomonitoring PCR. All 20 ND5 amplicons were confirmed as S. mansoni though ND5 analysis, confirming infection with S. mansoni. The prevalence of S. mansoni infection in these 589 Biomphalaria was therefore increased from 0.17% using cercarial shedding to 3.4% through use of the molecular xenomonitoring PCR. Biomphalaria infected with S. mansoni were identified at four of the 41 (9.6%) malacological survey sites (Fig. 5). At site 13, three of 175 collected Biomphalaria (1.7%) were infected with S. mansoni, whereas at site 18, two of 66 collected Biomphalaria (3%) were infected with S. mansoni and at site 27, five of 151 collected Biomphalaria (4%) were infected with S. mansoni. At site 21, however, nine of 80 Biomphalaria (11.25%) were infected with S. mansoni, the highest prevalence of Biomphalaria infections across all malacological surveillance sites. The number of malacological surveillance sites where intestinal schistosomiasis transmission was identified was therefore increased from just one using cercarial shedding to four using molecular xenomonitoring.

The S. mansoni ND5 TCS haplotype network can be seen in Fig. 6. Two distinct clusters were formed, each comprised of three unique haplotypes. One unique haplotype comprised of two S. mansoni ND5 sequences was identified at site 13. No other haplotypes were found at this site. One unique haplotype comprised of one S. mansoni ND5 sequence was identified at site 21. The remaining four haplotypes were present at more than one single site, two of which were present at three sites (sites 18, 21 and 27). All 20 S. mansoni ND5 sequences were uploaded to the GenBank repository (Accession numbers: PP889740 – PP889759).

Only the Biomphalaria ITS and Trematoda ITS loci were amplified in 12 further Biomphalaria DNA samples, indicating infection with non-S. mansoni trematodes. The Trematoda ITS gel band was successfully excised and genotyped in all 12 of these samples. Of these, six were identified as Uvulifer spp., which were all present at site 13 and the remaining six were identified as Petasiger spp., which were present at sites 18, 20, 21 and 27 (Additional file 1, Table S2), though ITS analysis. No genetic variation was found between any Uvulifer spp. ITS sequence data or between any Petasiger spp. ITS sequence data. All six Uvulifer spp. ITS sequences and all six Petasiger spp. ITS sequences were uploaded to the GenBank repository (Accession numbers: PP510464-PP510469 and PP510476-PP501481, respectively).

Here, we carried out extensive malacological surveillance along the southern shoreline of Lake Malawi, Mangochi District, Malawi, to measure the distribution and diversity of Biomphalaria freshwater snail intermediate hosts of S. mansoni. We then used a range of molecular approaches to genotype a subset of collected Biomphalaria to species level and to screen all collected Biomphalaria for infection with S. mansoni to identify intestinal schistosomiasis transmission sites in this area. This was done to gain a more thorough understanding of Biomphalaria associated transmission of intestinal schistosomiasis in Mangochi District five years post-outbreak to better inform and strengthen future disease control efforts.

Biomphalaria were collected at multiple surveillance sites and all genotyped specimens were identified as Bi. pfefferi, which is the most widely distributed and commonly implicated intermediate host and vector of S. mansoni across sub-Saharan Africa (24). No cox1 variation was found between all genotyped Mangochi District Bi. pfeifferi, suggesting a potential single and recent colonisation event of Bi. pfeifferi in this area. According to cox1 analysis, all Bi. pfeifferi genotyped here were most closely related to Bi. pfeifferi collected in Zimbabwe, with two Zimbabwean isolates from different locations sharing identical cox1 sequence data to Mangochi District Bi. pfeifferi, and so perhaps these Bi. pfeifferi identified in Mangochi District originated from Zimbabwe, as suggested previously (22). Interestingly, enough genetic variation was found between the unique Malawi, Chikwawa District haplotype and the Malawi, Mangochi District haplotype to suggest that the Chikwawa District Bi. pfeifferi population may have in fact invaded from populations outside of Malawi, rather than migrated south along the Shire River from Mangochi District and diverged, as might have been initially assumed. Further analysis to confirm this, however, is needed, particularly as the cox1 phylogenetic tree generated here suggests that all Malawian Bi. pfeifferi (inclusive of Mangochi and Chikwawa Districts) and all Zimbabwean Bi. pfeifferi share a common ancestor. It is worth noting that no other species of Biomphalaria, such as Bi. sudanica or Bi. choanomphala, was identified, although limited deep water (> 1 metre) surveillance took place, which is the preferred microhabitat of Bi. choanomphala (24).

This recent introduction of Biomphalaria into Mangochi District can likely be, in part, attributed to environmental changes caused by ongoing climate change (40, 41). In recent years, Mangochi District, and Malawi more broadly, have been severely impacted by atypical and extreme weather conditions such as tropical cyclones and remarkably heavy rainfall with subsequent flooding, particularly in low-altitude areas such as the upper Shire River margins (42). Whilst flooding can transport and introduce Biomphalaria into new habitats from surrounding areas, such extreme weather events can also dramatically alter freshwater environments more generally, and thus more favourable Biomphalaria habitats can arise (40, 41). As an example, temporal freshwater pools, which would typically evaporate during dry seasons, may instead remain as permanent waterbodies in which Bi. pfeifferi can propagate. Such waterbodies may therefore quickly become active sites of intestinal schistosomiasis transmission. As different Biomphalaria species, which can differ in their ability to transmit S. mansoni, have different habitat preferences, a clear understanding of how climate change can alter the environment with respect to current and potential Biomphalaria habitats is needed to better understand ongoing and future transmission of intestinal schistosomiasis. Molecular approaches to identify Biomphalaria species, such as those used here, will be crucial in these investigations.

As found previously in this area (22), just one (0.17%) of all 589 collected Biomphalaria was found to be actively shedding S. mansoni cercariae. Through molecular xenomonitoring, however, a total of 20 (3.4%) Biomphalaria, were found to be infected with S. mansoni; 12 of which were collected from malacological surveillance sites that were not deemed intestinal schistosomiasis transmission sites through cercarial shedding analysis. The prevalence of Biomphalaria infection with S. mansoni was therefore increased from 0.17–3.4%, and the number of identified intestinal schistosomiasis transmission sites was increased from one to four, through use of molecular xenomonitoring. Interestingly, at one such site (site 21; see Additional file 1, Table S1), not only was a relatively high number of Biomphalaria collected (n = 80), but a high proportion (11.25%) of Biomphalaria were found to be infected with S. mansoni using molecular xenomonitoring despite none of these actively shedding S. mansoni cercariae during cercarial shedding analysis. Furthermore, of note, this site is a short distance (~ 1.5 Km) from Samama School, at which 55% of school-aged children in attendance were found to be infected with S. mansoni during recent parasitological surveillance in November of 2021 [Archer et al., under review].

In addition, through molecular xenomonitoring, six unique S. mansoni mitochondrial ND5 haplotypes were identified, which clustered into two distinct groups. A similar degree of mitochondrial DNA genetic diversity was found amongst S. mansoni miracidia cox1 haplotypes (infecting school-aged children) also recently identified in this area [Archer et al., under review]. Furthermore, during these previous cox1 analyses, two genetically distinct S. mansoni cox1 linage groups (II and IV), (43), were identified within the miracidia population, which may be reflected here in these ND5 haplotypes. Interestingly, it should also be noted that just one unique S. mansoni ND5 haplotype was identified at site 13, which is far removed (~ 12–15 Km) from the remaining three surveillance sites where S. mansoni transmission was found (all of which are within ~ 3 Km of each other), suggesting a focal population of S. mansoni at site 13 that is genetically distinct from S. mansoni populations further south along the lake’s shoreline. At the remaining three intestinal schistosomiasis transmission sites (sites 18, 21 and 27), multiple S. mansoni haplotypes were identified and found to be present at multiple sites, suggesting mixing of S. mansoni populations in this area, likely by human hosts visiting multiple different lake water contact points but also potentially through movement of Biomphalaria between surveyed sites.

Infection with non-Schistosoma trematodes was also detected in 12 Biomphalaria collected at multiple malacological surveillance sites. Six of these were identified as Uvulifer spp., which were all present at site 13. This diplostomid trematode has a three-host life cycle: specific genera of freshwater snails including Biomphalaria (44), freshwater sunfish, and piscivorous birds such as kingfisher (highly prevalent along this shoreline of Lake Malawi (45)). The remaining six were identified as Petasiger spp., which were present at sites 18, 20, 21 and 27. Petasiger spp. trematodes also utilise a three-host life cycle: a range of genera of freshwater snails including Biomphalaria and Bulinus, freshwater fish and tadpoles, and piscivorous birds such as cormorants (again, highly prevalent along this shoreline of Lake Malawi) (46). Whilst there appears to be no available studies investigating whether established Uvulifer spp. or Petasiger spp. infections within Biomphalaria impact S. mansoni development and transmission, other trematode species have been found to influence S. mansoni development within Biomphalaria (47), and so this may also be the case for these infecting Trematoda. This, however, requires further investigation to clarify.

Study limitations and future work

Given the limited diversity found across Bi. pfeifferi cox1hapolotypes analysed in this study, more thorough analysis of additional Bi. pfeifferi DNA loci, e.g., mitochondrial 16S or nuclear ITS regions, or even whole mitochondrial genome analysis, would likely provide further insights into Mangochi District Bi. pfeifferi phylogenies, population structuring, and origins (10). In addition, whilst molecular xenomonitoring can be used to detect Schistosoma infections in freshwater snail hosts that have been missed by cercarial shedding, this approach does have limitations. PCR-based molecular approaches such as end-point PCR used here, or real-time/quantitative PCR, are expensive and require specialised laboratory personnel. In addition, PCR also requires sophisticated laboratory infrastructure seldom available in schistosomiasis-endemic areas. As such, the continued development of more portable, rapid, and easy-to-use nucleic acid amplification technologies that can be carried out at the point-of-need, such as loop-mediated isothermal amplification (LAMP) and recombinase polymerase/aided amplification (RPA/RAA), for molecular xenomonitoring purposes is encouraged here (48, 49). Furthermore, the continued development of DNA extraction technologies capable of isolating DNA from freshwater snail tissues in resource-poor settings is also encouraged (49).

Through extensive malacological surveillance and through use of molecular approaches, we confirm that Biomphalaria are now present at many locations along the southern shoreline of Lake Malawi, Mangochi District, Malawi. We also confirm that many of these locations are active intestinal schistosomiasis transmission sites. When compared to previous malacological surveys in this area, it would appear that Bi. pfeifferi populations are rapidly expanding not only across this southern shoreline of Lake Malawi, but also further south of Malawi in Chikwawa District. As such, the revision of ongoing schistosomiasis control programmes in Mangochi District, such as the implementation of bi-annual mass drug administration using praziquantel, significantly improving access to adequate water and sanitation hygiene (WASH) infrastructure, freshwater snail population control, and further delivery of schistosomiasis education and health programmes to promote behaviours that limit the risk of contracting and transmitting schistosomiasis is therefore encouraged, in line with WHO recommendations.

Our study also highlights the importance of molecular approaches to investigate Biomphalaria populations and monitor Biomphalaria associated intestinal schistosomiasis transmission in endemic areas. As such, the continued development and use of such approaches, in particular the development and use of molecular xenomonitoring assays that can be carried out in resource-poor schistosomiasis-endemic settings, is encouraged. These will be especially needed in low-endemicity areas and will aid in improving disease control efforts, significantly reducing disease-related morbidities experienced by those afflicted by intestinal schistosomiasis.

BLAST: Basic Local Alignment Search Tool

Cox1: Cytochrome oxidase subunit 1

ITS: Internal transcribed spacer

LAMP: Loop-mediated isothermal amplification

MAFFT: Multiple alignment with fast fourier transform

ML: Maximum likelihood

ND5: NADH dehydrogenase subunit 5

NTD: Neglected tropical disease

PCR: Polymerase chain reaction

RPA/RAA: Recombinase polymerase/aided amplification

SNP: Single nucleotide polymorphism

SSR: Schistosome and Snail Resource

TCS network: Templeton Crandall and Sing haplotype network

WASH: Water and sanitation hygiene

WHO: World Health Organization

Acknowledgements

The authors would like to thank the Schistosome Collections at the Natural History Museum (SCAN) repository as well as Dr Adam Cieplinski and Dr Fernanda Sales Coelho of the Schistosome Snail Resource (SSR), (Wellcome Trust Biomedical Resource Grant 221368/Z/20/Z (2021-2026)) for provision of Schistosoma material. We are also grateful to Claire Griffin of the Natural History Museum, London’s Molecular Biology Laboratories for assistance in Sanger sequencing.

Funding

JA is supported by a Medical Research Council Doctoral Training Programme (MRC-DTP) fellowship held at the Liverpool School of Tropical Medicine. JA was also awarded a London Centre for Neglected Tropical Disease Research (LCNTDR) student travel grant. SMY was funded through a London School of Hygiene and Tropical Medicine (LSHTM) MSc Research Project fund (2023). The Hybridisations in UroGenital Schistosomiasis (HUGS) study is funded by a Wellcome Trust Joint Investigator Award 220818/Z/20/Z.

Availability of data and materials

All data will be made available upon request.

Authors’ contributions

John Archer: Conceptualisation, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualisation, Project administration, Funding acquisition.

Lucas J. Cunningham: Resources, Writing - review & editing.

Alexandra Juhász: Resources, Writing - review & editing.

Sam Jones: Resources, Writing - review & editing.

Amber L. Reed: Resources, Writing - review & editing.

Shi Min Yeo: Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - review & editing, Visualisation,

Bright Mainga: Resources, Writing - review & editing.

Priscilla Chammudzi: Resources, Writing - review & editing.

Donales R. Kapira: Resources, Writing - review & editing.

David Lally: Resources, Writing - review & editing.

Gladys Namacha: Resources, Writing - review & editing.

Peter Makaula: Resources, Writing - review and editing, Project administration.

James E. LaCourse: Resources, Writing - review & editing,Project administration.

Sekeleghe, A. Kayuni: Resources, Writing - review and editing, Project administration.

Bonnie L. Webster: Conceptualisation, Methodology, Investigation, Resources, Writing - review & editing, Funding acquisition.

Janelisa Musaya: Conceptualisation, Methodology, Investigation, Resources, Writing - review & editing, Funding acquisition.

J. Russell Stothard: Conceptualisation, Methodology, Investigation, Resources, Writing - review & editing, Funding acquisition.

Ethics approval and consent to participate

Not applicable

Consent for publication

Not applicable

Competing interests

The authors report no conflicts of interest.

Author contact

JA: [email protected]

LJC: [email protected]

AJ: [email protected]

SJ: [email protected]

ALR: [email protected]

SMY: [email protected]

BM: [email protected]

PC: [email protected]

DRK: [email protected]

DL: [email protected]

GN: [email protected]

PM: [email protected]

JEL: [email protected]

SAK: [email protected]

BLW: [email protected]

JM: [email protected]

JRS: [email protected]

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No competing interests reported.

molecularepidemiologyBiomphalariaLakeMalawiADDITIONALFILE1.docx
Supplementary information Additional file 1: Malacological surveillance and molecular xenomonitoring data
molecularepidemiologyBiomphalariaLakeMalawiADDITIONALFILE2.docx
Additional file 2: Molecular methods
molecularepidemiologyBiomphalariaLakeMalawiADDITIONALFILE3.docx
Additional file 3: Biomphalaria pfeifferi cox1 reference data and GenBank accession numbers used for phylogenetic analyses

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Population genetics and molecular xenomonitoring of Biomphalaria freshwater snails along the southern shoreline of Lake Malawi, Mangochi District, Malawi

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Abstract

Figures

1. Introduction

2. Methods

2.1 Malacological surveys and sample sites

2.1.1 Collection of Biomphalaria freshwater snails

2.2 Cercarial shedding of Biomphalaria and collection of Schistosoma cercariae

2.3 Molecular characterisation of Biomphalaria

2.3.1 DNA extraction: Ethanol preserved Biomphalaria

2.3.2 Mitochondrial cox1 genotyping

2.3.3 Phylogenetic and diversity analysis

2.3.3.1 Templeton Crandall and Sing (TCS) haplotype network

2.3.3.2 Maximum likelihood phylogenetic tree

2.4 Molecular characterisation of Schistosoma cercariae.

2.4.1 DNA extraction: FTA preserved cercariae

2.4.2 Mitochondrial cox1 and nuclear ITS genotyping

2.5 Biomphalaria molecular xenomonitoring

2.5.1 Molecular xenomonitoring PCRs

2.5.2 Confirmatory S. mansoni. ND5 genotyping

2.5.2.1 Templeton Crandall and Sing (TCS) haplotype network

2.5.3 Conformation of Biomphalaria infections with other Trematoda species

3. Results

3.1 Malacological surveillance and cercarial shedding of Biomphalaria

3.2 Molecular characterisation of Biomphalaria

3.3 Molecular characterisation of Schistosoma cercariae.

3.3.1 Schistosoma cercariae mitochondrial cox1 and nuclear ITS PCR and genotyping

3.4 Biomphalaria molecular xenomonitoring

4. Discussion

5. Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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