The emergence of single-cell proteomics (SCP) is set to revolutionize the field of precision medicine – a diagnostic approach that develops treatments to fit specific genetic and molecular characteristics.
Understanding the etiology of complex diseases is rooted in cellular biochemistry. But before you can develop effective and targeted therapeutics, you need to identify how the metabolic pathways, expression and regulation of proteins change in diseased versus normal cells.
Also, when you analyze large groups of heterogenous cells together (e.g., tissues, plasma, etc.) in traditional proteomics approaches, a significant amount of information about the content of individual cell types is effectively lost or averaged out.
A deep understanding of disease states hinges on insight into the behavior of these individual cell types. The problem is the average “simple” cell has millions of proteins, so you need high-performance LC-MS technology to elucidate changes in protein expression, most importantly, without bias.
That’s where successful proteomics researchers like Karl Mechtler (Institute of Molecular Pathology, Vienna) shine. Our new manuscript in Biorxiv in collaboration with Dr. Mechtler’s group demonstrates a high throughput, proteome coverage, and quantitative precision in single-cell proteomics using our low-flow tools.
The major takeaway points from our groundbreaking work are:
- Higher LC-MS sensitivity was achieved by employing a low nano-flow rate (100 nL/min) and narrow I.D. columns (50 µm)
- High sample throughput (100 samples/day) is possible by using a trap-and-elute workflow and optimized methods
- A 10-min elution window provides high MS utilization (~70 percent) without sacrificing data quality
- Reproducible inter-lab performance was observed in single-cell and standard diluted samples
- State-of-the-art separation technology enabled the identification of >2,200 and >1,700 protein groups from 250 pg diluted standard and single-cell samples, respectively, using library-free DIA searches
To our knowledge, this study represents the most comprehensive proteome coverage in the SCP workflow space to date.
Teamwork truly makes the dreamwork!
P.S. Don’t forget to explore our top three proteomics tools today: