https://orcid.org/0000-0003-3293-5276
Figures
Abstract
This study explores the use of Matrix-Assisted Laser Desorption/Ionization Time-of-Flight mass spectrometry (MALDI-TOF MS) to identify and differentiate Biomphalaria snails infected with the parasite S. mansoni, which causes schistosomiasis. The study was conducted on two snail species, Biomphalaria pfeifferi (collected in the field in Senegal) and Biomphalaria glabrata (a laboratory strain). The snails were infected in the laboratory with S. mansoni miracidia, and their infection was confirmed by cercariae emission tests and quantitative PCR (qPCR). MALDI-TOF MS was then used to analyse proteins from infected and uninfected snails to identify spectral differences. Based on protein profiles, the results of MALDI-TOF mass spectrometry made it possible to accurately differentiate between S. mansoni-infected snails and uninfected snails. An increase in the number of peaks detected and their intensity was observed for the spectra of S. mansoni-infected snails compared to uninfected snails. The application of principal component analysis (PCA) to these mass spectrometry profiles confirmed the discrimination between the two groups according to their infection status. In addition, specific discriminating peaks were identified for each snail species, allowing for the distinction of infected from uninfected snails. The present study revealed, for the first time, that MALDI-TOF MS appears to be a rapid, reliable, and specific tool for the diagnosis of schistosomiasis in snails, offering promising prospects for the surveillance and control of this disease in endemic areas. However, further work is needed to establish a MALDI-TOF MS reference spectra database specific to Schistosoma parasites and to standardise sample collection, storage, and preparation in order to apply this technique in the field.
Author summary
This study investigates the use of Matrix-Assisted Laser Desorption/Ionisation Time-of-Flight mass spectrometry (MALDI-TOF MS) to identify Biomphalaria snails infected with the Schistosoma mansoni parasite, which causes schistosomiasis. Researchers focused on two snail species: Biomphalaria pfeifferi from Senegal and a laboratory strain of Biomphalaria glabrata. Infected snails were confirmed through tests that measured the emission of cercariae and quantitative PCR (qPCR). The MALDI-TOF MS analysis revealed distinct protein profiles between infected and uninfected snails. In particular, infected snails showed a higher number of spectral peaks and greater peak intensity. By applying principal component analysis (PCA) to the mass spectrometry data, the study successfully differentiated between the two groups based on their infection status. Notably, specific peaks were identified that distinguished each snail species. This research demonstrates that MALDI-TOF MS can serve as a quick and reliable method for diagnosing schistosomiasis in snails, which could enhance disease surveillance and control in affected regions. However, further work is necessary to develop a comprehensive reference database and standardise protocols for field application.
Citation: Sy D, Almeras L, Diarra AZ, Doucoure S, Sarr YM, L’Ollivier C, et al. (2026) Rapid identification of Biomphalaria spp. and diagnosis of Schistosoma mansoni infestation using MALDI-TOF mass spectrometry. PLoS Negl Trop Dis 20(3): e0013236. https://doi.org/10.1371/journal.pntd.0013236
Editor: Anand Setty Balakrishnan, Central University of Tamil Nadu, INDIA
Received: July 4, 2025; Accepted: March 3, 2026; Published: March 24, 2026
Copyright: © 2026 Sy 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 relevant data generated during this study are included in the manuscript.
Funding: This work was supported by a grant from the French Government managed by the French National Research Agency (ANR) under the “Investissements d’avenir (Investments for the Future)” programme with the reference ANR-10-IAHU-03 (Méditerranée Infection), and by the Conseil Régional Provence Alpes Côte d’Azur, Contrat Plan Etat-Région, and the European funding FEDER IHUPERF. The Institut de Recherche pour le Développement (IRD) funded the EMR MINES: Infectious, Neglected, and Emerging Diseases in the South. DS received a doctoral scholarship from the Méditerranée Infection Foundation. 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
Schistosomiasis is a parasitic infection caused by contact with surface water contaminated by the parasite of the genus Schistosoma [1,2]. This parasitic disease is very serious and affects more than 190 million people worldwide [3]. Seventy-eight countries are currently facing problems resulting from human schistosomiasis, the majority of them in sub-Saharan Africa [4]. Freshwater snails can be intermediate hosts for many parasites of medical and veterinary interest [5], and the genus Biomphalaria contributes to the transmission of Schistosoma mansoni, responsible for intestinal schistosomiasis [6]. Biomphalaria pfeifferi is a freshwater snail which is widely distributed in sub-Saharan Africa and Madagascar, as well as in some areas of the Sahara and Southwest Asia [7]. Another species, Biomphalaria glabrata is native to South America [8]. Meanwhile, in Senegal, the only species of the genus Biomphalaria is Biomphalaria (Bi.) pfeifferi, an intermediate host of the parasite S. mansoni [9]. It is, therefore, clear that several strategies are needed to control schistosomiasis, including controlling the infestation dynamics of molluscs in endemic contact areas [10].
Several diagnostic methods for parasite surveillance have been developed to monitor the evolutionary dynamics of schistosomiasis in endemic areas [11]. These include manual cercariometry [12,13], positive phototropism [14], the superposition technique [15], and centrifugation [16]. However, to detect infestation with these methods, the parasite must be in its final stage of evolution. Techniques such as qPCR [17] and molecular detection and identification [18] have emerged to detect parasites at an early stage. These two methods, however, cannot be implemented in the field and require significant preparation time. Recently, an innovative approach has emerged for the identification and diagnosis of pathogens and their vectors, based on protein profiling: matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) [19,20]. MALDI-TOF MS has proven to be a rapid, reliable, and specific method for identifying parasites, bacteria, viruses, and arthropod vectors, representing significant potential in the field of clinical microbiology and disease control [21]. However, it has also enabled us to identify the intermediate host snails of the parasite Schistosoma [22]. In addition, Huguenin et al. were able to identify and differentiate different species of parasites of the genus Schistosoma [23]. The primary objective of this study was to discriminate between the two species of Biomphalaria, Bi. pfeifferi and Bi. glabrata, using MALDI-TOF MS and then to assess whether MALDI-TOF MS could detect the S. mansoni parasite in the snails.
Materials and methods
Ethics statement
The experimental protocol was approved by the Senegal Ethics Committee (Comité National d’Ethique pour la Recherche en Santé, CNERS, Reference No. 000073/MSAS/DPRS/CNERS) and received clearance from the head of Nagoya in Senegal (Reference No. 001339). The snail infection protocol complies with national and international guidelines on animal welfare.
Snail collection
Specimens of B. pfeifferi and B. glabrata infested with S. mansoni were obtained during a previous a study evaluating the compatibility of these two intermediate hosts with a strain of S. mansoni from Senegal [24]. The B. pfeifferi strain originates from northern Senegal, in the Senegal River valley area, while the B. glabrata strain, native to Recife, Brazil, was obtained from the Host–Pathogen–Environment Interactions (IHPE) laboratory in Perpignan, France.
PCR-based S. mansoni detection
The presence of the S. mansoni parasite in snails was confirmed by the qPCR system as previously described [25]. Briefly, we used the forward primers SRA1 and antisense primers SRS2 and the probe SRP. The PCR mixing conditions were 20 μl of reaction mix containing 5 μl of template DNA, 3.5 μl of sterile ultrapure water, 0.5 μl of each primer, 0.5 μl of probe, and 10 μl of Master Mix (product ref). Amplification was performed on a CFX96 thermal cycler (BIO-RAD, Hercules, CA, USA). The PCR programme was initiated by a three-minute purification at 95 °C, followed by ten minutes’ denaturation at 95 °C, and 40 cycles of 30 seconds of denaturation and hybridisation at 55 °C for 30 seconds, maintained at 4 °C [25]. In each run, a negative control (sterile water) and a positive control (DNA extracted from S. mansoni worms) were used. PCR results were considered positive if the cycle threshold (CT) was less than 35 cycles.
MALDI TOF MS-based S. mansoni detection
Snail preparation.
The soft part from the shell was carefully removed and the foot was dissected under a Leica ES2 10x/30x stereomicroscope using a sterile slide. The remaining parts of the snail were stored at -20 °C for further study. The dissected part was first rinsed with 70% ethanol and then distilled water for two minutes. It was dried, deposited on a sterile filter paper, and cut into small pieces [22]. The foot samples were then added to an extraction solution composed of a mixture of 70% formic acid (Sigma-Aldrich, Lyon, France), 50% acetonitrile (Fluka, Buchs, Switzerland), and 80% HPLC water. For each sample, 30 μL of the mixed solution and glass beads (Sigma-Aldrich, St. Louis, Missouri, USA) was homogenised using a Tissue Lyser II (Qiagen, Germany) with optimised parameters (three one-minute cycles at a frequency of 30 Hertz), as described previously [26]. All homogenates were centrifuged at 2000 g for 30 seconds, and 1.5 μL of each supernatant was spotted onto a steel target plate (Bruker Daltonics GmBh, Bremen, Germany) in four spots. One microlitre of a CHCA matrix suspension composed of saturated alpha-cyano-4-hydroxycinnamic acid (Sigma, Lyon, France), 50% acetonitrile, 2.5% trifluoroacetic acid (Aldrich, Dorset, UK), and 47.5% of HPLC grade water was directly deposited onto each spot on the target plate to allow co-crystallisation, then dried at room temperature before being inserted into the MALDI-TOF MS instrument (Bruker Daltonics) [27].
Analysis of MALDI-TOF MS spectra.
Mass spectrometry analysis was performed using a Microflex LT MALDI-TOF mass spectrometer (Bruker Daltonics) with the Flex Control software (Bruker Daltonics). Measurements were performed in linear positive ion mode in a 2 kDA–20 kDa mass range. Each spectrum corresponds to ions obtained from 240 laser shots performed in six regions of a single spot. Spectral profiles were visualised using Flex Analysis, version 3.3, and then exported to the MALDI Biotyper (Bruker Daltonics) software version 3.0 and ClinProTools v.2.2 (Bruker Daltonics) for further data processing (smoothing, baseline subtraction, peak selection). The reproducibility of MS spectra was assessed by comparing the Main Spectrum Profile (MSP) obtained from the four spots of each sample with the MALDI Biotyper (Bruker Daltonics). The composite correlation index (CCI) tool of the MALDI Biotyper was also used to assess spectral variations within and between snails which were infected with S. mansoni and those that were not [28]. In addition, ClinProTools was used to identify discriminatory peaks between infected and non-infected snails not only within species but also between the two species. The most discriminatory common peaks between infected and non-infected snails were analysed with ClinProTools to compare the two groups and estimate the impact of infestation. The ClinProTools default parameters for spectrum preparation were applied as described by 29 [29]. Based on the peak list obtained per species, the five and eight most intense peaks of snails infected by Bi. pfeifferi and Bi. glabrata, respectively were selected for inclusion in the genetic algorithm (GA) model. The peaks selected by the operator provided a recognition capacity (RC) value related to the highest cross-validation (CV) value. The presence or absence of all discriminatory peak masses generated by the GA model was checked by comparing the average spectra of each species per body part.
DNA sequence-based snail species confirmation.
To confirm the identification of Biomphalaria species, we sequenced three infected and three uninfected specimens of each species that displayed a good MALDI-TOF MS spectrum and a high MALDI Biotyper (Bruker Daltonics) log score value (LSV) ≥ 2. To identify the snail species, we sequenced the following gene fragments: COX (CO1 (LC1490): GGTCAACAAATCATAAAGATATTGG; CO2 (HCO2198): TAAACTTCAGGGTGACCAAAAAATCA); ITS (ETTS1: TGCTTAAGTTCAGCGGGT; ETTS10: GCATACTGCTTTGAACATCG) [30], and 18S (18S F: AGTATGGTTGCAAAGCTGAAACTTA; 18S R: TACAAAGGGCAGGGACGTAAT) [31], as previously described. To confirm the amplification of DNA, the PCR products were run on a 1% agarose gel at 180 V, 400 mA for 15 minutes. For a PCR to be considered positive, the detection of a 363-base pair band was required. Positive samples were purified and sequenced using the same primers with BigDye version 1-1 Cycle Sequencing Ready Reaction Mix (Applied Biosystems, Foster City, CA) and run on an ABI 3100 automated sequencer (Applied Biosystems). Sequences were assembled and corrected using the ChromasPro (version 1.34) software (Technelysium Pty. Ltd., Tewantin, Australia) and identified using BLAST queries (https://blast.ncbi.nlm.nih.gov/Blast.cgi) against the NCBI GenBank nucleotide database.
Results
Snail species DNA sequence-based confirmation
Seven snails specimens, five of which were infected with S. mansoni, and three uninfected snails of each species, were subjected to standard PCR and sequencing using three different genes (Cox, ITS and 18S). BLAST analysis of B. pfeifferi and B. glabrata sequences showed coverage percentages of 98% to 100% and identity percentages ranging from 97% to 100% with the sequences of their counterparts in GenBank (Table 1).
MALDI-TOF MS spectra analysis
The MALDI-TOF MS spectra of uninfected Biomphalaria snails were selected to assess the ability of this tool to discriminate between the two species. We obtained high intensity spectra, i.e., greater than 2000 au, when 20 uninfected Biomphalaria snails were subjected to MALDI TOF MS. These spectra appeared visually reproducible for each species (Fig 1A). To confirm the reproducibility of the spectra, cluster analyses were performed, resulting in the MSP dendrogram (Fig 1B). Three specimens of each species were selected. The clustering of specimens of the same species on the same branch with a high distance between them and the absence of intertwining species demonstrate the reproducibility and specificity of each Biomphalaria species protein profile.
(1) Comparison of MALDI-TOF MS spectra obtained from the snails feet of three distinct specimens of Bi. pfeifferi (A, B, C) and Bi. glabrata (D, E, F). (m/z, mass-to-charge ratio). (2) MSP dendrogram of the MALDI-TOF MS spectra of three specimens per species. The dendrogram was created using the Biotyper v3.0 software, and the distance units correspond to the relative similarity of the MS spectra.
Since the correct classification of the snail species relies primarily on the intensity of the resulting MS spectra, the five most intense peaks were selected from the uninfected Biomphalaria snails. This resulted in a total of eight peaks discriminating between the Biomphalaria species (Table 2). These eight peaks were subjected to the genetic algorithm (GA) model of ClinProTools 2.2 software. The combination of the presence or absence of these five most intense peaks displayed Cross-Validation (CV) and Recognition Capacity (RC) values equal to 100%. These five peaks were also evaluated against the infested groups. This enabled us to determine the percentage of compatibility between the groups. Values of 84% and 80% were obtained for infested Bi. glabrata and infested Bi. pfeifferi, respectively.
The two Biomphalaria species formed two distinct MALDI-TO spectra groups. In Fig 2, the infected group is in green and the uninfected group is in red. The separation of infected and uninfected snails was much clearer in the Bi. glabrata species, with ~85% of variance being explained, while only ~80% of the variance was explained in the Bi. pfeifferi species.
(A). Bi. glabrata infected (n = 20, green dots) or not infected (n = 10, red dots) with S. mansoni. (B). Bi. pfeifferi infected (n = 20, green dots) or not infected (n = 10, red dots) with S. mansoni. (C). Expression curve of variance versus principal component of Bi. glabrata. (D). Expression curve of variance versus principal component of Bi. pfeifferi..
Within the Bi. glabrata snail group, 16 peaks differentiated snails infected with the S. mansoni parasite from uninfected snails. Statistical analyses showed a P-value less than.005 (P < .005) in the PTTA Analysis of Variance test (Table 3). This indicates that these peaks are informative and discriminatory on the infestation parameter. Using ClinProTools software, principal component analysis generated a cross-validation percentage of 97.67% and a recognition ability of 100%.
Within the Bi. pfeifferi snail group, 17 peaks distinguished snails infected with the S. mansoni parasite from uninfected snails. Statistical analyses showed highly significant P values (Table 4) in the PTTA Analysis of Variance test. This indicates that these peaks are informative and discriminatory on the infestation parameter. Using ClinProTools software, principal component analysis generated a cross-validation percentage of 95.32% and a recognition ability of 98.32%.
Discussion
First, MALDI TOF MS made it possible to discriminate between two snail species of the same genus. Specific and reproducible spectra were obtained for each species with 100% reliability. In addition, we identified Bi. glabrata for the first time, using MALDI TOF MS with good quality spectra (LSV > 2). This confirms the efficiency and reliability of MALDI-TOF in identifying snail species, as confirmed by Hamlili et al. [22] in their previous study.
Second, we were able to clearly and accurately discriminate between infected and uninfected Biomphalaria snails using MALDI-TOF MS. MALDI-TOF, initially limited to identifying intermediate host snails [22], is capable of differentiating parasite infestations within the host. Since this device is a tool based on the ionisation of an organism’s proteins [28], MALDI-TOF detected the presence of other proteins on samples that were positive for cercariae emission and real-time PCR, which is different from the proteins detected in uninfected snails. This resulted in a difference in spectra between the group of infected and uninfected snails. Thus, the visualised spectra confirm a difference in protein expression between infected Biomphalaria and uninfected Biomphalaria. The reproducibility in the spectra of infected snails indicates the presence of the same proteins in these snails. The same observations were made in the uninfected snails. Given that there is no MALDI-TOF spectra database to identify Schistosoma parasites, the parasite species remain to be identified.
The validation percentages and intra-species recognition capacity obtained confirm that MALDI-TOF is indeed capable of differentiating Schistosoma infestation within the same species. On the one hand, we observed different peaks, which indicate the expression of distinct proteins, and on the other we observed similar peaks in both infected and uninfected groups. In this case, the distinction lies in the intensity and regularity of expression in all individuals. In other words, the presence of the parasite can modulate the expression of certain proteins in the snail, thus making it possible to differentiate between infected snails and those that are not. Similarly, it has been demonstrated that MALDI-TOF MS could differentiate filaria-infected mosquitoes from uninfected mosquitoes, with a specificity of 100% and a sensitivity of 92% [32].
The slight difference in the validation percentages and the recognition capacity between Bi. pfeifferi and Bi. glabrata may be explained by the origin of the collected samples. The Bi. pfeifferi samples were collected in the field, while our Bi. glabrata strain had been raised in the laboratory for years. Thus, uncontrolled environmental conditions such as the physicochemical parameters of the water and the instability of the climate, but also water pollution can influence MALDI-TOF MS spectra and contribute to the differences between the spectra of field and laboratory snails. Indeed, MALDI-TOF MS has been found to be capable of tracing the geospatial origin of snails [33].
Conclusion
This study demonstrates the effectiveness of Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) mass spectrometry as an innovative tool for the identification and differentiation between snails of the genus Biomphalaria infected with Schistosoma mansoni, the causative agent of schistosomiasis. By combining speed, reliability, and specificity, this method offers promising prospects for diagnosing and monitoring this parasitic disease in endemic areas, particularly in sub-Saharan Africa, where schistosomiasis is a major public health problem. The good quality MALDI-TOF spectra generated in this study will be used to enrich our in-house MALDI-TOF spectral database and further blind tests are planned to assess the capacity of MALDI-TOF MS to diagnose Schistosoma parasite infestations of snails collected in the field and to propose a standardised sample collection, storage, and preparation protocol. Finally, this technological advance will contribute towards developing an integrated approach aimed at reducing the public health impact of schistosomiasis and contributing to global efforts to eradicate this disease by 2030, in line with WHO targets.
References
- 1. De Boni L, Msimang V, De Voux A, Frean J. Trends in the prevalence of microscopically-confirmed schistosomiasis in the South African public health sector, 2011-2018. PLoS Negl Trop Dis. 2021;15(9):e0009669. pmid:34529659
- 2. Riaz S, Ahmed H, Kiani SA, Afzal MS, Simsek S, Celik F, et al. Knowledge, attitudes and practices related to neglected tropical diseases (schistosomiasis and fascioliasis) of public health importance: a cross-sectional study. Front Vet Sci. 2023;10:1088981. pmid:36925606
- 3. Shi L, Zhang J-F, Li W, Yang K. Development of new technologies for risk identification of schistosomiasis transmission in China. Pathogens. 2022;11(2):224. pmid:35215167
- 4. Tchuem Tchuenté L-A, Rollinson D, Stothard JR, Molyneux D. Moving from control to elimination of schistosomiasis in sub-Saharan Africa: time to change and adapt strategies. Infect Dis Poverty. 2017;6(1):42. pmid:28219412
- 5.
Dreyfuss G, Rondelaud D. Les mollusques dans la transmission des helminthoses humaines et vétérinaires. 2011. https://doi.org/10.4267/2042/48064
- 6. Chu KY. The validity of baseline data for measuring incidence rates of Schistosoma haematobium infection in the molluscicided area, UAR-0049 project. Ann Trop Med Parasitol. 1976;70(3):365–7. pmid:987758
- 7. Brown DS. Freshwater Snails of Africa and Their Medical Importance. 0 ed. CRC Press. 1994.
- 8. Dejong RJ, Morgan JAT, Wilson WD, Al-Jaser MH, Appleton CC, Coulibaly G, et al. Phylogeography of Biomphalaria glabrata and B. pfeifferi, important intermediate hosts of Schistosoma mansoni in the New and Old World tropics. Mol Ecol. 2003;12(11):3041–56. pmid:14629384
- 9. Moyroud J, Breuil J, Dulat Ch, Coulanges P. Les mollusques, hôtes intermediaires desbilharzioses humaines a madagascar. Etat actuel desconnaissances. Archives-Institut-Pasteur-de-Madagascar. 1982;50:39–65. Available from: https://www.pasteur.mg/wp-content/uploads/2015/08/Archives-Institut-Pasteur-de-Madagascar-1982-50-39-65.pdf
- 10. King CH. Toward the elimination of schistosomiasis. New England Journal of Medicine. 2009;360:106–9.
- 11. McPhail BA, Froelich K, Reimink RL, Hanington PC. Simplifying schistosome surveillance: using molecular cercariometry to detect and quantify cercariae in water. Pathogens. 2022;11:565.
- 12. Sato MO, Rafalimanantsoa A, Ramarokoto C, Rahetilahy AM, Ravoniarimbinina P, Kawai S, et al. Usefulness of environmental DNA for detecting Schistosoma mansoni occurrence sites in Madagascar. Int J Infect Dis. 2018;76:130–6. pmid:30201503
- 13. Theron A. A differential filtration technique for the measurement of schistosome cercarial densities in standing waters. Bull World Health Organ. 1979;57(6):971–5. pmid:317025
- 14. Klock JW. A method for the direct quantitative recovery of Schistosoma mansoni cercariae from natural waters of Puerto Rico. Bull World Health Organ. 1961;25(4–5):738–40. pmid:14457071
- 15. Sandt DG. Evaluation of an overlay technique for the recovery of Schistosoma mansoni cercariae. Bull World Health Organ. 1972;47(1):125–7. pmid:4538898
- 16. Butler JM Jr, Ferguson FF, Palmer JR. New field device for quantitative recovery of Schistosoma mansoni cercariae. Public Health Rep (1896). 1967;82(3):250–2. pmid:4960500
- 17. Jothikumar N, Mull BJ, Brant SV, Loker ES, Collinson J, Secor WE, et al. Real-time PCR and sequencing assays for rapid detection and identification of avian schistosomes in environmental samples. Appl Environ Microbiol. 2015;81(12):4207–15. pmid:25862226
- 18. Pennance T, Archer J, Lugli EB, Rostron P, Llanwarne F, Ali SM, et al. Development of a Molecular Snail Xenomonitoring Assay to Detect Schistosoma haematobium and Schistosoma bovis Infections in their Bulinus Snail Hosts. Molecules. 2020;25(17):4011. pmid:32887445
- 19. Costa MM, Corbel V, Ben Hamouda R, Almeras L. MALDI-TOF MS profiling and its contribution to mosquito-borne diseases: a systematic review. Insects. 2024;15:651.
- 20. Sevestre J, Diarra AZ, Laroche M, Almeras L, Parola P. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry: an emerging tool for studying the vectors of human infectious diseases. Future Microbiol. 2021;16:323–40. pmid:33733821
- 21. Sánchez-Juanes F, Calvo Sánchez N, Belhassen García M, Vieira Lista C, Román RM, Álamo Sanz R, et al. Applications of MALDI-TOF mass spectrometry to the identification of parasites and arthropod vectors of human diseases. Microorganisms. 2022;10(11):2300. pmid:36422371
- 22. Hamlili FZ, Thiam F, Laroche M, Diarra AZ, Doucouré S, Gaye PM, et al. MALDI-TOF mass spectrometry for the identification of freshwater snails from Senegal, including intermediate hosts of schistosomes. PLoS Negl Trop Dis. 2021;15(9):e0009725. pmid:34516582
- 23. Huguenin A, Kincaid-Smith J, Depaquit J, Boissier J, Ferté H. MALDI-TOF: A new tool for the identification of Schistosoma cercariae and detection of hybrids. PLoS Negl Trop Dis. 2023;17(3):e0010577. pmid:36976804
- 24. Sarr M, Diop M, Bakhoum AJ, Doucoure S, Sow D, Bâ CT, et al. The Senegalese and Brazilian strains of Schistosoma mansoni exhibit high compatibility with Biomphalaria pfeifferi and Biomphalaria glabrata. Parasit Vectors. 2025;18(1):314. pmid:40745319
- 25. Wichmann D, Panning M, Quack T, Kramme S, Burchard G-D, Grevelding C, et al. Diagnosing schistosomiasis by detection of cell-free parasite DNA in human plasma. PLoS Negl Trop Dis. 2009;3(4):e422. pmid:19381285
- 26. Yssouf A, Flaudrops C, Drali R, Kernif T, Socolovschi C, Berenger J-M, et al. Matrix-assisted laser desorption ionization-time of flight mass spectrometry for rapid identification of tick vectors. J Clin Microbiol. 2013;51(2):522–8. pmid:23224087
- 27. Nebbak A, Willcox AC, Bitam I, Raoult D, Parola P, Almeras L. Standardization of sample homogenization for mosquito identification using an innovative proteomic tool based on protein profiling. Proteomics. 2016;16(24):3148–60. pmid:27862981
- 28. Diarra AZ, Laroche M, Berger F, Parola P. Use of MALDI-TOF MS for the Identification of Chad Mosquitoes and the Origin of Their Blood Meal. Am J Trop Med Hyg. 2019;100(1):47–53. pmid:30526738
- 29. Briolant S, Costa MM, Nguyen C, Dusfour I, Pommier de Santi V, Girod R, et al. Identification of French Guiana anopheline mosquitoes by MALDI-TOF MS profiling using protein signatures from two body parts. PLoS One. 2020;15(8):e0234098. pmid:32817616
- 30. Kane RA, Stothard JR, Emery AM, Rollinson D. Molecular characterization of freshwater snails in the genus Bulinus: a role for barcodes?. Parasit Vectors. 2008;1:15.
- 31. Webster BL, Southgate VR, Littlewood DTJ. A revision of the interrelationships of Schistosoma including the recently described Schistosoma guineensis. Int J Parasitol. 2006;36(8):947–55. pmid:16730013
- 32. Tahir D, Almeras L, Varloud M, Raoult D, Davoust B, Parola P. Assessment of MALDI-TOF mass spectrometry for filariae detection in Aedes aegypti mosquitoes. PLoS Negl Trop Dis. 2017;11(12):e0006093. pmid:29261659
- 33. Gaye PM, Doucouré S, Sow D, Sokhna C, Ranque S. Identification of Bulinus forskalii as a potential intermediate host of Schistosoma hæmatobium in Senegal. PLoS Negl Trop Dis. 2023;17(5):e0010584. pmid:37159452