Evaluating and mitigating clinical samples matrix effects on TX-TL cell-free performance.

Area of Science:

• Biotechnology
• Molecular Diagnostics
• Biochemistry

Background:

• Cell-free biosensors offer a versatile platform for medical diagnostics.
• Performance of cell-free systems is often hindered by matrix effects from biological samples.
• Standard cell-free systems exhibit significant inhibition in clinical matrices like serum, plasma, urine, and saliva.

Purpose of the Study:

• To systematically evaluate matrix effects on cell-free biosensor performance using sfGFP and luciferase reporters.
• To identify strategies for mitigating inhibition caused by clinical sample matrices.
• To develop a more robust cell-free system applicable across diverse sample types for improved diagnostics.

Main Methods:

• Comparative analysis of cell-free system performance in serum, plasma, urine, and saliva.
• Assessment of various inhibitors, including RNase inhibitor, for matrix effect mitigation.
• Development of a novel engineered strain for endogenous RNase inhibitor production to overcome buffer interference.
• Quantification of reporter gene expression (sfGFP, luciferase) and interpatient variability.

Main Results:

• Clinical samples significantly inhibited cell-free system performance.
• RNase inhibitor demonstrated efficacy in mitigating matrix effects.
• Commercial buffer glycerol interfered with RNase inhibitor efficacy.
• The engineered strain producing RNase inhibitor improved reporter levels and reduced interpatient variability without extra preparation steps.

Conclusions:

• Matrix effects pose a substantial challenge for cell-free biosensor diagnostics in clinical samples.
• A novel cell-free system with endogenous RNase inhibitor production enhances robustness and reduces variability across diverse clinical samples.
• This improved cell-free system represents a significant advancement towards reliable point-of-care diagnostics.