Person:
Bautista Santa Cruz, José Manuel

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First Name
José Manuel
Last Name
Bautista Santa Cruz
URI
https://hdl.handle.net/20.500.14352/80584
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Veterinaria
Department
Bioquímica y Biología Molecular
Area
Bioquímica y Biología Molecular
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2018 - 201912020 - 20241
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    Plasmodium species differentiation by non-expert on-line volunteers for remote malaria field diagnosis
    (Malaria Journal, 2018) Ortiz-Ruiz, Alejandra; Postigo, María; Gil-Casanova, Sara; Cuadrado, Daniel; Bautista Santa Cruz, José Manuel; Rubio, José Miguel; Luengo-Oroz, Miguel; Linares Gómez, María
    Background: Routine feld diagnosis of malaria is a considerable challenge in rural and low resources endemic areas mainly due to lack of personnel, training and sample processing capacity. In addition, diferential diagnosis of Plasmodium species has a high level of misdiagnosis. Real time remote microscopical diagnosis through on-line crowdsourc‑ing platforms could be converted into an agile network to support diagnosis-based treatment and malaria control in low resources areas. This study explores whether accurate Plasmodium species identifcation—a critical step during the diagnosis protocol in order to choose the appropriate medication—is possible through the information provided by non-trained on-line volunteers. Methods: 88 volunteers have performed a series of questionnaires over 110 images to diferentiate species (Plasmodium falciparum, plasmodium ovale, Plasmodium vivax, Plasmodium malariae, Plasmodium knowlesi) and parasite stag‑ ing from thin blood smear images digitalized with a smartphone camera adapted to the ocular of a conventional light microscope. Visual cues evaluated in the surveys include texture and colour, parasite shape and red blood size. Results: On-line volunteers are able to discriminate Plasmodium species (P. falciparum, P. malariae, P. vivax, P. ovale, P. knowlesi) and stages in thin-blood smears according to visual cues observed on digitalized images of parasitized red blood cells. Friendly textual descriptions of the visual cues and specialized malaria terminology is key for volunteers learning and efciency. Conclusions: On-line volunteers with short-training are able to diferentiate malaria parasite species and parasite stages from digitalized thin smears based on simple visual cues (shape, size, texture and colour). While the accuracy of a single on-line expert is far from perfect, a single parasite classifcation obtained by combining the opinions of multiple on-line volunteers over the same smear, could improve accuracy and reliability of Plasmodium species identifcation in remote malaria diagnosis.
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    Shotgun Characterization of the Circulating IgM Antigenome of an Infectious Pathogen by Immunocapture-LC–MS/MS from Dried Serum Spots
    (Journal of Proteome Research, 2024) Abad González, Paloma; Coronado Brieva, Montserrat; Vincelle-Nieto, África; Pérez Benavente, Susana; Fobil, Julius N.; Puyet Catalina, Antonio; Díez Martín, Amalia; Reyes Palomares, Armando Adolfo; Azcárate, Isabel G.; Bautista Santa Cruz, José Manuel
    One of the main challenges in compiling the complete collection of protein antigens from pathogens for the selection of vaccine candidates or intervention targets is to acquire a broad enough representation of them to be recognized by the highly diversified immunoglobulin repertoire in human populations. Dried serum spot sampling (DSS) retains a large repertoire of circulating immunoglobulins from each individual that can be representative of a population, according to the sample size. In this work, shotgun proteomics of an infectious pathogen based on DSS sampling coupled with IgM immunoprecipitation, liquid chromatography–mass spectrometry (LC–MS/MS), and bioinformatic analyses was combined to characterize the circulating IgM antigenome. Serum samples from a malaria endemic region at different clinical statuses were studied to optimize IgM binding efficiency and antibody leaching by varying serum/immunomagnetic bead ratios and elution conditions. The method was validated using Plasmodium falciparum extracts identifying 110 of its IgM-reactive antigens while minimizing the presence of human proteins and antibodies. Furthermore, the IgM antigen recognition profile differentiated between malaria-infected and noninfected individuals at the time of sampling. We conclude that a shotgun proteomics approach offers advantages in providing a high-throughput, reliable, and clean way to identify IgM-recognized antigens from trace amounts of serum. The mass spectrometry raw data and metadata have been deposited with ProteomeXchange via MassIVE with the PXD identifier PXD043800.