Polysome-profiling in small tissue samples.

Area of Science:

• Molecular Biology
• Genomics
• Translational Research

Background:

• Polysome-profiling is a standard technique for analyzing translatomes, but it is labor-intensive and requires large sample volumes.
• Current methods are inconvenient for large experimental designs or samples with limited RNA quantity, such as those from biobanks.

Purpose of the Study:

• To develop an optimized, non-linear sucrose gradient method for polysome-profiling.
• To reduce sample handling and improve the efficiency of isolating translated mRNA.
• To enable translatome analysis in small tissue samples and facilitate large-scale studies.

Main Methods:

• Optimization of a non-linear sucrose gradient for polysome enrichment.
• Coupling the optimized method with smart-seq2 single-cell RNA sequencing.
• Application of the technique to serum-starved HCT-116 cells with varying p53 status.

Main Results:

• The optimized non-linear gradient reproducibly enriches translated mRNA in one to two fractions, reducing sample handling 5-10 fold.
• Translatomes obtained using the optimized method are comparable to those from standard linear gradients.
• p53 status was shown to influence mRNA abundance, translational efficiency, and protein levels, with evidence of translational buffering.

Conclusions:

• The optimized non-linear sucrose gradient method offers a more efficient and convenient approach to polysome-profiling.
• This technique is suitable for analyzing translatomes in small tissues, primary cells, and frozen biobank samples.
• The method facilitates large-scale studies and provides insights into gene regulation, such as the role of p53 in translational control.