Optimization of Protein Quantification From Soil Samples

Abstract

Protein profiling of soil samples has the potential to enhance our understanding of soil ecosystems and guide the development of sustainable soil management practices. In that context, there is a need to develop robust proteomic workflows, starting with reliable protein quantification. Total protein quantification with the Lowry assay is a relatively easy, rapid, and cheap method, but requires interference corrections due to reactivity with a wide range of compounds that occur in soil, plant, and other biological matrices. Here, we propose sample-specific corrections for soil protein extracts. We benchmarked our approach against other protein quantification methods, including other Lowry corrections, total hydrolysable amino acids, and Qubit total protein assay. Our sample-specific Lowry corrections did not overestimate or underestimate protein content when compared to the other methods tested. As a practical contribution, this work provides a calibration method for the Lowry assay using protein reference values in a multivariate regression approach to enable simple and high-throughput total protein quantification of soil samples.