Discriminant Analysis PCA-LDA Assisted Surface-Enhanced Raman Spectroscopy for Direct Identification of Malaria-Infected Red Blood Cells

Various methods for detecting malaria have been developed in recent years, each with its own set of advantages. These methods include microscopic, antigen-based, and molecular-based analysis of blood samples. This study aimed to develop a new, alternative procedure for clinical use by using a large data set of surface-enhanced Raman spectra to distinguish normal and infected red blood cells. PCA-LDA algorithms were used to produce models for separating P. falciparum (3D7)-infected red blood cells and normal red blood cells based on their Raman spectra. Both average normalized spectra and spectral imaging were considered. However, these initial spectra could hardly differentiate normal cells from the infected cells. Then, discrimination analysis was applied to assist in the classification and visualization of the different spectral data sets. The results showed a clear separation in the PCA-LDA coordinate. A blind test was also carried out to evaluate the efficiency of the PCA-LDA separation model and achieved a prediction accuracy of up to 80%. Considering that the PCA-LDA separation accuracy will improve when a larger set of training data is incorporated into the existing database, the proposed method could be highly effective for the identification of malaria-infected red blood cells.

Human Microglia Respond to Malaria-Induced Extracellular Vesicles

Microglia are the chief immune cells of the brain and have been reported to be activated in severe malaria. Their activation may drive towards neuroinflammation in cerebral malaria. Malaria-infected red blood cell derived-extracellular vesicles (MiREVs) are produced during the blood stage of malaria infection. They mediate intercellular communication and immune regulation, among other functions. During cerebral malaria, the breakdown of the blood–brain barrier can promote the migration of substances such as MiREVs from the periphery into the brain, targeting cells such as microglia. Microglia and extracellular vesicle interactions in different pathological conditions have been reported to induce neuroinflammation. Unlike in astrocytes, microglia–extracellular vesicle interaction has not yet been described in malaria infection. Therefore, in this study, we aimed to investigate the uptake of MiREVs by human microglia cells and their cytokine response. Human blood monocyte-derived microglia (MoMi) were generated from buffy coats of anonymous healthy donors using Ficoll-Paque density gradient centrifugation. The MiREVs were isolated from the Plasmodium falciparum cultures. They were purified by ultracentrifugation and labeled with PKH67 green fluorescent dye. The internalization of MiREVs by MoMi was observed after 4 h of co-incubation on coverslips placed in a 24-well plate at 37 °C using confocal microscopy. Cytokine-gene expression was investigated using rt-qPCR, following the stimulation of the MoMi cells with supernatants from the parasite cultures at 2, 4, and 24 h, respectively. MiREVs were internalized by the microglia and accumulated in the perinuclear region. MiREVs-treated cells increased gene expression of the inflammatory cytokine TNFα and reduced gene expression of the immune suppressive IL-10. Overall, the results indicate that MiREVs may act on microglia, which would contribute to enhanced inflammation in cerebral malaria.