Generate Deeper Insights with Platinum® Protein Identification

Explore our application notes to discover how Platinum’s Next-Generation Protein Sequencing can enhance your protein identification.

• Comparison of Protein Sequencing Analysis of CDNF, IL6, and FGF2 on Platinum and Mass Spectrometry

  In this application note, we compare protein sequencing analysis of CDNF using Quantum-Si’s Platinum protein sequencing platform with mass spectrometry. The Platinum workflow offers an accessible and convenient solution for protein identification without the need for expensive equipment and expertise allowing researchers to gain deeper proteomic insights and make informed decisions about their protein samples.

  Download the application note now to unlock a new level of understanding in your protein research.

  Download the Application Note

  

  While both mass spectrometry and the Quantum Si platform correctly identified the CDNF protein, the workflow was dramatically different.

  Read the application note to see how the Platinum workflow can save you time and effort without compromising results.

  

  

  Here we showcase CDNF peptide identification results from mass spectrometry and Platinum sequencing. Platinum sequencing resulted in unique identification of 6 peptides and demonstrates Platinum’s ability for accurate protein identification through a simplified workflow.

• Protein Identification using Next-Generation Protein Sequencing™ of In-Gel Digested Proteins – TECH NOTE

  Western blot, a prevalent method for protein identification, often faces challenges due to the need for quality antibodies and the inability to differentiate similar-sized proteins. This application note introduces a non-antibody-based approach, detailing an in-gel protein digestion and peptide extraction procedure. This innovative method integrates with Quantum-Si’s library preparation and protein sequencing workflows, allowing for the separation, enrichment, and identification of proteins using Quantum-Si’s Platinum next-generation protein sequencing™ instrument.

  Curious about revolutionizing your protein identification process? Download the full application note to dive deeper!

  Download the Tech Note

  

  Here we showcase an SDS-PAGE representation of CDNF Samples before the band excision process. The visual provides a clear indication of the bands that were selected for in-gel digestion and subsequent sequencing, marked by distinct orange and blue arrows. This serves as a foundational step in understanding the sample preparation process.

  

  Figure 2. Representative Traces, Coverage, and Pulse Duration Data for the Peptides Identified in the 10 μg Sample of CDNF. Five recognizers were used to identify 12 amino acids (F, Y, W, L, I, V, A, S, N, Q, R, and K), enabling identification of 5 peptides as shown in the figure.

  This graph compares the relative number of peptide alignments for each in-gel digested sample and reveals that both the 5 µg and 10 µg samples produced a higher number of aligned CDNF peptides compared to the smaller samples. Additionally, the 10 µg Band B sample also yielded a significant count of CDNF-aligned peptides, providing valuable insights into the efficiency and results of the in-gel digestion process.

  

• Sequencing and Identification of Proteins from Five-Protein Mixtures on Platinum® – APP NOTE

  This application note introduces Quantum-Si’s Platinum instrument, which allows for the direct sequencing and identification of proteins in complex mixtures. By eliminating the need for targeted antibody-based assays, this technology offers a solution to detect multiple proteins simultaneously. We present a method for optimizing sample preparation and demonstrate the feasibility of identifying five distinct recombinant proteins in a mixture.

  Download the full application note to learn more about this groundbreaking protein sequencing platform.

  Download the Application Note

  

  We tested the feasibility of detecting multiple proteins on Platinum by combining a mixture of five recombinant proteins (CDNF, FGF2, IL4, GMFB, and PDIA1) and employing protein sequencing to identify them.

  To determine if overall peptide coverage would be affected by different library preparation methods, we compared two different mixes with increased complexity.
  Read the application note for an in-depth discussion of our methods and results.