Publications

Background The microbiome of disease vectors can be a key determinant of their ability to transmit parasites. Conversely, parasite infection may modify vector microbiomes. We are exploring the interactions between the Biomphalaria glabrata snail microbiome and the blood fluke Schistosoma mansoni, responsible for an estimated 200,000 human deaths each year. Snail hosts vary in their susceptibility to schistosome parasites, and the underlying mechanisms driving this variation are not fully understood. We have previously shown that the snail hemolymph (i.e., blood) and organs harbor a diverse microbiome. Here we investigate the impact of schistosome infection on snail microbiomes, hypothesizing that invading schistosomes can alter the snail microbiomes in both composition and abundance over the course of infection, as developing schistosome parasites are in close contact with the host tissues.

Result We generated cohorts of uninfected and S. mansoni infected snails. We collected snail hemolymph and hepatopancreas (i.e., liver) at 8 timepoints during the pre-patent and patent periods of schistosome infection. We quantified bacterial density using qPCR and profiled the microbiome composition of all samples by sequencing the V4 region of the 16S rRNA. Schistosome infection had surprisingly no effect on bacterial density and limited effect on the microbiome composition, affecting mainly the hemolymph during the pre-patent period (at day 7 and 21). Organ and hemolymph microbiomes were relatively stable overtime for both infected and uninfected snail cohorts. The sample type (hemolymph, hepatopancreas) was the major driver of the differences observed in microbiome composition.

Conclusions The limited impact of schistosome infection on the host snail microbiomes might be explained by the long-term interaction of the two partners and the fact that parasite fitness is closely dependent on host fitness. Further investigations into the interactions between snails, their microbiomes, and schistosome parasites are essential for developing strategies to disrupt the parasite lifecycle and, consequently, schistosomiasis transmission.

The microbiome is increasingly recognized to shape many aspects of its host biology and is a key determinant of health and disease. The microbiome may influence transmission of pathogens by their vectors, such as mosquitoes or aquatic snails. We previously sequenced the V4 region of the bacterial 16S rRNA gene from the hemolymph (blood) of Biomphalaria spp. snails, vectors of the human blood fluke schistosome. We showed that snail hemolymph harbored an abundant and diverse microbiome. This microbiome is distinct from the water environment and can discriminate snail species and populations. As hemolymph bathes snail organs, we then investigated the heterogeneity of the microbiome in these organs.

We dissected ten snails for each of two different species (B. alexandrina and B. glabrata) and collected their hemolymph and organs (ovotestis, hepatopancreas, gut, and stomach). We also ground in liquid nitrogen four whole snails of each species. We sampled the water in which the snails were living (environmental controls). Sequencing the 16S rRNA gene revealed organ-specific microbiomes. These microbiomes harbored a lower diversity than the hemolymph microbiome, and the whole-snail microbiome. The organ microbiomes tend to cluster by physiological function. In addition, we showed that the whole-snail microbiome is more similar to hemolymph microbiome.

These results are critical for future work on snail microbiomes and show the necessity of sampling individual organ microbiomes to provide a complete description of snail microbiomes.

Pathogen genomics is a powerful tool for tracking infectious disease transmission. In malaria, identity-by-descent (IBD) is used to assess the genetic relatedness between parasites and has been used to study transmission and importation. In theory, IBD can be used to distinguish genealogical relationships to reconstruct transmission history or identify parasites for genotype-to-phenotype quantitative-trait-locus experiments. MalKinID (Malaria Kinship Identifier) is a new likelihood-based classification model designed to identify genealogical relationships among malaria parasites based on genome-wide IBD proportions and IBD segment distributions. MalKinID was calibrated to the genomic data from three laboratory-based genetic crosses (yielding 440 parent-child and 9060 full-sibling comparisons). MalKinID identified lab generated F1 progeny with >80% sensitivity and showed that 0.39 (95% CI 0.28, 0.49) of the second-generation progeny of a NF54 and NHP4026 cross were F1s and 0.56 (0.45, 0.67) were backcrosses of an F1 with the parental NF54 strain. In simulated outcrossed importations, MalKinID accurately reconstructs genealogy history with high precision and sensitivity, with F1-scores exceeding 0.84. However, when importation involves inbreeding, such as during serial co-transmission, the precision and sensitivity of MalKinID declined, with F1-scores of 0.76 (0.56, 0.92) and 0.23 (0.0, 0.4) for PC and FS and <0.05 for second-degree and third-degree relatives. Genealogical inference is most powered 1) when outcrossing is the norm or 2) when multi-sample comparisons based on a predefined pedigree are used. MalKinID lays the foundations for using IBD to track parasite transmission history and for separating progeny for quantitative-trait-locus experiments.

Background: Genomic analysis has revealed extensive contamination among laboratory-maintained microbes including malaria parasites, Mycobacterium tuberculosis, and Salmonella spp. Here, we provide direct evidence for recent contamination of a laboratory schistosome parasite population, and we investigate its genomic consequences. The Brazilian Schistosoma mansoni population SmBRE has several distinctive phenotypes, showing poor infectivity, reduced sporocyst number, low levels of cercarial shedding and low virulence in the intermediate snail host, and low worm burden and low fecundity in the vertebrate rodent host. In 2021 we observed a rapid change in SmBRE parasite phenotypes, with a 10-fold increase in cercarial production and fourfold increase in worm burden.

Methods: To determine the underlying genomic cause of these changes, we sequenced pools of SmBRE adults collected during parasite maintenance between 2015 and 2023. We also sequenced another parasite population (SmLE) maintained alongside SmBRE without phenotypic changes.

Results: While SmLE allele frequencies remained stable over the 8-year period, we observed sudden changes in allele frequency across the genome in SmBRE between July 2021 and February 2023, consistent with expectations of laboratory contamination. (i) SmLE-specific alleles increased in the SmBRE population from 0 to 41-46% across the genome between September and October 2021, reflecting the timing and magnitude of the contamination event. (ii) After contamination, strong selection (s ≅0.23) drove the replacement of low-fitness SmBRE with high-fitness SmLE alleles. (iii) Allele frequency changed rapidly across the whole genome, except for a region on chromosome 4, where SmBRE alleles remained at high frequency.

Conclusions: We were able to detect contamination in this case because SmBRE shows distinctive phenotypes. However, this would likely have been missed with phenotypically similar parasites. These results provide a cautionary tale about the importance of tracking the identity of parasite populations, but also showcase a simple approach to monitor changes within populations using molecular profiling of pooled population samples to characterize single-nucleotide polymorphisms. We also show that genetic drift results in continuous change even in the absence of contamination, causing parasites maintained in different labs (or sampled from the same lab at different times) to diverge.

Background: Genomic analysis has revealed extensive contamination among laboratory-maintained microbes including malaria parasites, Mycobacterium tuberculosis, and Salmonella spp. Here, we provide direct evidence for recent contamination of a laboratory schistosome parasite population, and we investigate its genomic consequences. The Brazilian Schistosoma mansoni population SmBRE has several distinctive phenotypes, showing poor infectivity, reduced sporocyst number, low levels of cercarial shedding and low virulence in the intermediate snail host, and low worm burden and low fecundity in the vertebrate rodent host. In 2021 we observed a rapid change in SmBRE parasite phenotypes, with a 10-fold increase in cercarial production and fourfold increase in worm burden.

Methods: To determine the underlying genomic cause of these changes, we sequenced pools of SmBRE adults collected during parasite maintenance between 2015 and 2023. We also sequenced another parasite population (SmLE) maintained alongside SmBRE without phenotypic changes.

Results: While SmLE allele frequencies remained stable over the 8-year period, we observed sudden changes in allele frequency across the genome in SmBRE between July 2021 and February 2023, consistent with expectations of laboratory contamination. (i) SmLE-specific alleles increased in the SmBRE population from 0 to 41–46% across the genome between September and October 2021, reflecting the timing and magnitude of the contamination event. (ii) After contamination, strong selection (s ≅0.23) drove the replacement of low-fitness SmBRE with high-fitness SmLE alleles. (iii) Allele frequency changed rapidly across the whole genome, except for a region on chromosome 4, where SmBRE alleles remained at high frequency.

Conclusions: We were able to detect contamination in this case because SmBRE shows distinctive phenotypes. However, this would likely have been missed with phenotypically similar parasites. These results provide a cautionary tale about the importance of tracking the identity of parasite populations, but also showcase a simple approach to monitor changes within populations using molecular profiling of pooled population samples to characterize single-nucleotide polymorphisms. We also show that genetic drift results in continuous change even in the absence of contamination, causing parasites maintained in different labs (or sampled from the same lab at different times) to diverge.

Pathogen genomics is a powerful tool for tracking infectious disease transmission. In malaria, identity-by-descent (IBD) is used to assess the genetic relatedness between parasites and has been used to study transmission and importation. In theory, IBD can be used to distinguish genealogical relationships to reconstruct transmission history or identify parasites for quantitative-trait-locus experiments. MalKinID (Malaria Kinship Identifier) is a new classification model designed to identify genealogical relationships among malaria parasites based on genome-wide IBD proportions and IBD segment distributions. MalKinID was calibrated to the genomic data from three laboratory-based genetic crosses (yielding 440 parent-child [PC] and 9060 full-sibling [FS] comparisons). MalKinID identified lab generated F1 progeny with >80% sensitivity and showed that 0.39 (95% CI 0.28, 0.49) of the second-generation progeny of a NF54 and NHP4026 cross were F1s and 0.56 (0.45, 0.67) were backcrosses of an F1 with the parental NF54 strain. In simulated outcrossed importations, MalKinID reconstructs genealogy history with high precision and sensitivity, with F1-scores exceeding 0.84. However, when importation involves inbreeding, such as during serial co-transmission, the precision and sensitivity of MalKinID declined, with F1-scores (the harmonic mean of precision and sensitivity) of 0.76 (0.56, 0.92) and 0.23 (0.0, 0.4) for PC and FS and <0.05 for second-degree and third-degree relatives. Disentangling inbred relationships required adapting MalKinID to perform multi-sample comparisons. Genealogical inference is most powered when 1) outcrossing is the norm or 2) multi-sample comparisons based on a predefined pedigree are used. MalKinID lays the foundations for using IBD to track parasite transmission history and for separating progeny for quantitative-trait-locus experiments.

The trematodes that cause schistosomiasis in humans require aquatic snails as intermediate hosts. Identifying the genes in snails at which allelic variation controls resistance to infection by schistosomes could lead to novel ways to break the cycle of transmission. We therefore mapped genetic variation within the BS90 population of Biomphalaria glabrata snails that controls their resistance to infection by the SmLE population of Schistosoma mansoni. A marker in the PTC2 genomic region strongly associates with variation in resistance. The S-haplotype, which confers increased susceptibility, appears to be almost completely dominant to the R-haplotype, which confers increased resistance. This result suggests a model in which the parasite must match a molecule on the host side to successfully infect. The genomic region surrounding our marker shows high structural and sequence variability between haplotypes. It is also highly enriched for genes that code for single-pass transmembrane (TM1) genes. Several of the TM1 genes present on the S-haplotype lack orthologs on the R-haplotype, which makes them intriguing candidate genes in a model of dominant susceptibility. These results add to a growing body of work that suggests TM1 genes, especially those in this exceptionally diverse genomic region, may play an important role in snail-schistosome compatibility polymorphisms.

 Piperaquine (PPQ) is widely used in combination with dihydroartemisinin as a first-line treatment against malaria. Multiple genetic drivers of PPQ resistance have been reported, including mutations in the Plasmodium falciparum chloroquine resistance transporter (pfcrt) and increased copies of plasmepsin II/III (pm2/3). We generated a cross between a Cambodia-derived multidrug-resistant KEL1/PLA1 lineage isolate (KH004) and a drug-susceptible Malawian parasite (Mal31). Mal31 harbors a wild-type (3D7-like) pfcrt allele and a single copy of pm2/3, while KH004 has a chloroquine-resistant (Dd2-like) pfcrt allele with an additional G367C substitution and multiple copies of pm2/3. We recovered 104 unique recombinant parasites and examined a targeted set of progeny representing all possible combinations of variants at pfcrt and pm2/3. We performed a detailed analysis of competitive fitness and a range of PPQ susceptibility phenotypes with these progenies, including PPQ survival assay, area under the dose response curve, and a limited point IC50. We find that inheritance of the KH004 pfcrt allele is required for reduced PPQ sensitivity, whereas copy number variation in pm2/3 further decreases susceptibility but does not confer resistance in the absence of additional mutations in pfcrt. A deep investigation of genotype-phenotype relationships demonstrates that progeny clones from experimental crosses can be used to understand the relative contributions of pfcrt, pm2/3, and parasite genetic background to a range of PPQ-related traits. Additionally, we find that the resistance phenotype associated with parasites inheriting the G367C substitution in pfcrt is consistent with previously validated PPQ resistance mutations in this transporter.

BACKGROUND: The microbiome is increasingly recognized to shape many aspects of its host biology and is a key determinant of health and disease. The microbiome may influence transmission of pathogens by their vectors, such as mosquitoes or aquatic snails. We previously sequenced the bacterial 16S V4 ribosomal DNA of the hemolymph (blood) of Biomphalaria spp. snails, one of the vectors of the human blood fluke schistosome. We showed that snail hemolymph harbored an abundant and diverse microbiome. This microbiome is distinct from the water environment and can discriminate snail species and populations. As hemolymph bathes snail organs, we then investigated the heterogeneity of the microbiome in these organs.

RESULTS: We dissected ten snails for each of two different species (B. alexandrina and B. glabrata) and collected their organs (ovotestis, hepatopancreas, gut, and stomach). We also ground in liquid nitrogen four whole snails of each species. We sampled the water in which the snails were living (environmental controls). Sequencing the 16S V4 rDNA revealed organ-specific microbiomes. These microbiomes harbored a lower diversity than the hemolymph microbiome, and the whole-snail microbiome. The organ microbiomes tend to cluster by physiological function. In addition, we showed that the whole-snail microbiome is more similar to hemolymph microbiome.

CONCLUSIONS: These results are critical for future work on snail microbiomes and show the necessity of sampling individual organ microbiomes to provide a complete description of snail microbiomes.

BACKGROUND: The role of pathogen genotype in determining disease severity and immunopathology has been studied intensively in microbial pathogens including bacteria, fungi, protozoa, and viruses, but is poorly understood in parasitic helminths. The medically important blood fluke Schistosoma mansoni is an excellent model system to study the impact of helminth genetic variation on immunopathology. Our laboratory has demonstrated that laboratory schistosome populations differ in sporocyst growth and cercarial production in the intermediate snail host and worm establishment and fecundity in the vertebrate host. Here, we (i) investigate the hypothesis that schistosome genotype plays a significant role in immunopathology and related parasite life history traits in the vertebrate mouse host and (ii) quantify the relative impact of parasite and host genetics on infection outcomes.

METHODS: We infected BALB/c and C57BL/6 mice with four different laboratory schistosome populations from Africa and the Americas. We quantified disease progression in the vertebrate host by measuring body weight and complete blood count (CBC) with differential over an infection period of 12 weeks. On sacrifice, we assessed parasitological (egg and worm counts, fecundity), immunopathological (organ measurements and histopathology), and immunological (CBC with differential and cytokine profiles) characteristics to determine the impact of parasite and host genetics.

RESULTS: We found significant variation between parasite populations in worm numbers, fecundity, liver and intestine egg counts, liver and spleen weight, and fibrotic area, but not in granuloma size. Variation in organ weight was explained by egg burden and by intrinsic parasite factors independent of egg burden. We found significant variation between infected mouse lines in cytokines (IFN-γ, TNF-α), eosinophil, lymphocyte, and monocyte counts.

CONCLUSIONS: This study showed that both parasite and host genotype impact the outcome of infection. While host genotype explains most of the variation in immunological traits, parasite genotype explains most of the variation in parasitological traits, and both host and parasite genotype impact immunopathology outcomes.