The use of confocal laser scanning microscopy to analyze the process of parasitic protozoon-host cell interaction

In this communication we review the results obtained with the confocal laser scanning microscope to characterize the interaction of epimastigote and trypomastigote forms of Trypanosoma cruzi and tachyzoites of Toxoplasma gondii with host cells. Early events of the interaction process were studied by the simultaneous localization of sites of protein phosphorylation, revealed by immunocytochemistry, and sites of actin assembly, revealed by the use of labeled phaloidin. The results obtained show that proteins localized in the interaction sites are phosphorylated. The process of formation of the parasitophorous vacuole was monitored by labeling the host cell surface with fluorescent probes for lipids (PKH26), proteins (DTAF) and sialic acid (FITC-thiosemicarbazide) before interaction with the parasites. Evidence was obtained indicating transfer of components of the host cell surface to the parasite surface in the beginning of the interaction process. We also analyzed the distribution of cytoskeletal structures (microtubules and microfilaments visualized with specific antibodies), mitochondria (visualized with rhodamine 123), the Golgi complex (visualized with C6-NBD-ceramide) and the endoplasmic reticulum (visualized with anti-reticulin antibodies and DIOC6) during the evolution of intracellular parasitism. The results obtained show that some, but not all, structures change their position during evolution of the intracellular parasitism

The use of confocal laser scanning microscopy to analyze the process of parasitic protozoon-host cell interaction

In this communication we review the results obtained with the confocal laser scanning microscope to characterize the interaction of epimastigote and trypomastigote forms of Trypanosoma cruzi and tachyzoites of Toxoplasma gondii with host cells. Early events of the interaction process were studied by the simultaneous localization of sites of protein phosphorylation, revealed by immunocytochemistry, and sites of actin assembly, revealed by the use of labeled phaloidin. The results obtained show that proteins localized in the interaction sites are phosphorylated. The process of formation of the parasitophorous vacuole was monitored by labeling the host cell surface with fluorescent probes for lipids (PKH26), proteins (DTAF) and sialic acid (FITC-thiosemicarbazide) before interaction with the parasites. Evidence was obtained indicating transfer of components of the host cell surface to the parasite surface in the beginning of the interaction process. We also analyzed the distribution of cytoskeletal structures (microtubules and microfilaments visualized with specific antibodies), mitochondria (visualized with rhodamine 123), the Golgi complex (visualized with C6-NBD-ceramide) and the endoplasmic reticulum (visualized with anti-reticulin antibodies and DIOC6) during the evolution of intracellular parasitism. The results obtained show that some, but not all, structures change their position during evolution of the intracellular parasitism

Breast cancer risks associated with missense variants in breast cancer susceptibility genes

Background: Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain. Methods: We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated. Results: The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set. Conclusions: These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.</p

Breast cancer risks associated with missense variants in breast cancer susceptibility genes

Background Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain. Methods We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated. Results The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set. Conclusions These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.Genome Instability and Cance

Breast cancer risks associated with missense variants in breast cancer susceptibility genes.

BACKGROUND: Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain. METHODS: We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated. RESULTS: The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set. CONCLUSIONS: These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility