Microarrays enable researchers to monitor the expression of thousands of genes simultaneously. However, the sensitivity, accuracy, specificity, and reproducibility are major challenges for this technology. Cross-hybridization, combination with splice variants, is a prime source for the discrepancies in differential gene expression calls among various microarray platforms. Removing (either from production or downstream bioinformatic analysis) and/or redesigning the microarray probes prone to cross-hybridization is a reasonable strategy to increase the hybridization specificity and hence, the accuracy of the microarray measurements.
DNA microarrays enable researchers to monitor the expression of thousands of genes simultaneously. However, the sensitivity, accuracy, specificity, and reproducibility are major challenges for this technology. Cross-hybridization, combination with splice variants, is a prime source for the discrepancies in differential gene expression calls among various microarray platforms. Removing (either from production or downstream bioinformatic analysis) and/or redesigning the microarray probes prone to cross-hybridization is a reasonable strategy to increase the hybridization specificity and hence, the accuracy of the microarray measurements.
Microarrays enable researchers to monitor the expression of thousands of genes simultaneously. However, the sensitivity, accuracy, specificity, and reproducibility are major challenges for this technology. Cross-hybridization, combination with splice variants, is a prime source for the discrepancies in differential gene expression calls among various microarray platforms. Removing (either from production or downstream bioinformatic analysis) and/or redesigning the microarray probes prone to cross-hybridization is a reasonable strategy to increase the hybridization specificity and hence, the accuracy of the microarray measurements.
Microarrays enable researchers to monitor the expression of thousands of genes simultaneously. However, the sensitivity, accuracy, specificity, and reproducibility are major challenges for this technology. Cross-hybridization, combination with splice variants, is a prime source for the discrepancies in differential gene expression calls among various microarray platforms. Removing (either from production or downstream bioinformatic analysis) and/or redesigning the microarray probes prone to cross-hybridization is a reasonable strategy to increase the hybridization specificity and hence, the accuracy of the microarray measurements.
The most widely used method for protein quantification is by spectrophotometry. The concentration of the protein in the samples is measured at an absorbance of 280 nm. The absorbance of the sample protein is then plotted against a standard curve. This method allows for total protein quantification in a sample (cell and tissue extracts). Before analysing the concentration of protein in the sample, it is important to choose the right test method. For high protein concentration samples (above 5 - 160 mg/ml) the best method is to use the Biuret test. For low concentrations samples (between 1 - 2000µg/ml) the best methods are Lowry assay, BCA assay, Bradford assay and coomassie blue (for exact sensitivity of the test kits you use, refer to manufacturer's protocol). If the samples contain detergents like Triton X-100 then BCA assay is the best choice. For samples that have proteins larger than 3 KDa in size Bradford assay is the best choice. Each method has advantages and disadvantages, plan your analysis considering your sample characteristics.
The most widely used method for protein quantification is by spectrophotometry. The concentration of the protein in the samples is measured at an absorbance of 280 nm. The absorbance of the sample protein is then plotted against a standard curve. This method allows for total protein quantification in a sample (cell and tissue extracts). Before analysing the concentration of protein in the sample, it is important to choose the right test method. For high protein concentration samples (above 5 - 160 mg/ml) the best method is to use the Biuret test. For low concentrations samples (between 1 - 2000µg/ml) the best methods are Lowry assay, BCA assay, Bradford assay and coomassie blue (for exact sensitivity of the test kits you use, refer to manufacturer's protocol). If the samples contain detergents like Triton X-100 then BCA assay is the best choice. For samples that have proteins larger than 3 KDa in size Bradford assay is the best choice. Each method has advantages and disadvantages, plan your analysis considering your sample characteristics.
Get tips on using Nucleofector™ Kits for Human T Cells to perform DNA transfection Mammalian cells - Primary cells CD8+ T cells
Get tips on using Nucleofector™ Kits for Human T Cells to perform DNA transfection Mammalian cells - Primary cells CD4+ T cells
Isolating RNA from tissues and paraffin-embedded tissue samples can be challenging due to cross-linking of biomolecules and fragmented nucleic acids. The best solution is to slice the tissues into smaller pieces and make a homogenate solution (using tissue homogenizer or grinding liquid nitrogen frozen samples) in presence of RNAse inhibitors. The homogenization process should be carried out on dry ice to maintain the integrity of RNA.
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