Considerations when Creating a Library-Free Proteomics Experiment without the OneOmics™ Suite

For research use only. Not for use in diagnostic procedures.

Answer

Library-free proteomics experiments require highly reproducible sample-handling protocols and data analysis. The DIA-NN software is embedded in the OneOmics™ suite, where analysis can be completed with an acquired ion library. However, a library-free approach (using in silica generated ion library) can be done directly in DIA-NN software without using any SCIEX software or acquired ion libraries. The library-free proteomics approach with DIA-NN software is described here: https://community.sciex.com/2022/04/29/creating-a-library-from-a-fasta-file-for-library-free-data-analysis/ .

Samples in a label-free study are in their unlabeled, native state. A list of samples in biological or technical sample sets are sequentially analyzed by LC-MS/MS. These samples are DDA type samples if a label-free workflow is applied. Library-free experiments with DIA-NN use DIA (SWATH) type samples. Evaluating samples in a single sequence on the same instrument can lead to significant variation. Normalization of the data takes into account any bias in the data sets and allows for sample-to-sample comparison. SCIEX uses a variety of normalization options, which are described here: https://community.sciex.com/2021/08/06/what-are-my-normalization-options-in-markerview-software-and-when-should-i-use-them/
 
Label-free quantification enables the analysis of an unlimited number of samples without introduction of any labels, thus keeping costs low and minimizing the sample preparation steps, making this the preferred approach for biomarker research.

The challenges of the library-free and label-free proteomics is poor reproducibility, requiring many technical replicates and leading to low quantification accuracy and can be a drawback compared to labeling-based strategies. On the other hand, this label-free approach provides the largest dynamic range and the highest proteome coverage for identification. [Book, Springer, Quantitative Methods in Proteomics, Marcus, K., et al., ISBN: 978-1-0716-1024-4. Published: 05 May 2021].