Epidemiological studies and meta-analyses have shown a strong association between high seroprevalence of Toxoplasma gondii (T. gondii) and schizophrenia. Schizophrenic patients showed higher levels of anti-Toxoplasma immunoglobulins M and G (IgM and IgG) when compared to healthy controls. Previously, in a rat model, we demonstrated that the progeny of mothers immunized with T. gondii lysates before gestation had behavioral and social impairments during adulthood. Therefore, we suggested that T. gondii infection can trigger autoreactivity by molecularly mimicking host brain proteins. Here, we aimed to identify the occurrence of antigenic mimicry between T. gondii epitopes and host brain proteins. Using a bioinformatic approach, we predicted T. gondii RH-88 B cell epitopes and compared them to human cell-surface proteins involved in brain development and differentiation (BrainS). Five different algorithms for B-cell-epitope prediction were used and compared, resulting in 8584 T. gondii epitopes. We then compared T. gondii predicted epitopes to BrainS proteins by local sequence alignments using BLASTP. T. gondii immunogenic epitopes significantly overlapped with 42 BrainS proteins. Among these overlapping proteins essential for brain development and differentiation, we identified HSP90 and NOTCH receptors as the proteins most likely to be targeted by the maternally generated pathogenic antibodies due to their topological overlap at the extracellular region of their sequence. This analysis highlights the relevance of pregestational clinical surveillance and screening for potential pathogenic anti-T. gondii antibodies. It also identifies potential targets for the design of vaccines that could prevent behavioral and cognitive impairments associated with pre-gestational T. gondii exposure.

Three-dimensional cultures are powerful tools to recapitulate animal and human tissues. Under the influence of specific growth factors, adult stem cells differentiate and organize into 3D cultures named organoids. The molecular phenotyping of these structures is an essential step for validating an organoid model. However, the limited number of organoids generated in culture yields very low amounts of genetic material, making phenotyping difficult. Recently, digital PCR (dPCR) techniques have become available for the highly sensitive detection of genetic material at low concentrations. The aim of this work was to apply dPCR to the identification of the various cell populations expected to be present in murine duodenal organoids. Results show the potential use of dPCR as a genetic characterization tool for organoids.