As biotech companies continue to leverage proteomics profiling for critical research such as biomarker discovery, on- & off-target validation, and mechanism of action studies, researchers are more frequently asking: "How can I extract more insights from my precious sample?"
While proteomics has undoubtedly advanced our understanding of disease biology, it can sometimes fall short of delivering the depth or specificity needed to address the biological question of interest. Now, powerful new technologies are enabling a more comprehensive view than ever before. Data-independent acquisition (DIA) proteomics is an exciting new bottom-up approach that can provide a more complete picture of protein expression, signaling interactions, and post-translational modifications (PTMs) to maximize discovery workflows.
“We identified and quantified over 3 times as many proteins with DIA on the Orbitrap Astral platform compared to our previous generation instruments.”
~ Matt Stokes, CST Director of Proteomics
However, the expense of cutting-edge instrumentation can make these insights unattainable for many labs. The Proteomics Analytical Services team at CST is excited to have installed a state-of-the-art DIA proteomics device—the Orbitrap Astral Mass Spectrometer from Thermo Scientific. According to our findings, the Orbital Astral analyzer can deliver three times as much data as traditional, data-dependent acquisition (DDA) proteomics.
If you’re looking for increased sensitivity, reproducibility, and coverage in your analyses, we invite you to access this powerful instrumentation and unlock biological insights that might otherwise be unavailable to you.
Read on for a more detailed comparison of the results achieved via the DDA vs DIA methods, and how state-of-the-art proteomics tools can access data that traditional proteomics analyses might be missing.
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Mass spectrometry-based, bottom-up proteomics has developed into one of the most powerful technologies for large-scale, high-throughput proteome profiling. For discovery-based or untargeted proteomics, the bottom-up method enables the monitoring of biology in real time and can provide extensive molecular evidence for discrete changes in protein abundance or processing. When coupled with the PTMScan workflow, researchers can survey the modulation of cellular pathways that trigger disease progression or response to targeted drug therapy.
As mentioned, there are two prominent liquid chromatography-mass spectrometry (LC-MS) data acquisition strategies for quantifying proteins in a given sample: data-dependent acquisition (DDA) and data-independent acquisition (DIA).
The following analogy can help explain the difference between the two:
The DDA method is akin to taking a photograph with a low-resolution camera on printed film, while the DIA approach is like capturing an extremely high-definition digital image. In this analogy, the DDA acquired “image” is pixelated and may not have enough resolution to confidently distinguish small features within the photo for a more in-depth perspective, whereas the DIA image is much higher resolution and allows one to discern small features within the photo and zoom in to obtain more detail about small objects within the photo. The DIA acquired image is a digitized, high-definition copy of the photo, which can be further interrogated to gain more insight.
Released in 2023, the Orbitrap Asymmetric Track Lossless (Astral) analyzer is a powerful mass spectrometry instrument that leverages a DIA workflow. It has the speed, sensitivity, and resolution to quantify substantially more peptides compared to previous Orbitrap instruments.
To illustrate the impact of a DIA workflow on discovery proteomics, we compared the Orbitrap Astral analyzer’s performance against a series of predecessor instruments including the Q Exactive HF (QE), Orbitrap Fusion Lumos Tribrid (Lumos), and Orbitrap Ascend Tribrid (Ascend), using a tryptic digest of mouse liver protein over an LC runtime of 45 minutes.
The table below summarizes the results obtained from the two different methods:
DIA - Astral |
DDA - Older Instuments |
|
Proteome Coverage |
Fragments and measures all detectable peptides in a sample to achieve high proteome coverage | Fragments only a subset of peptides for partial proteome coverage. |
Results of CST Evaluation of Both Methods |
||
Protein Groups Quantified |
Over 10,000 (mouse liver tissue) |
Between 2,500 - 3,600 (mouse liver tissue) |
Reproducibility & Data Completeness |
The measured peptide intensities in the study produce a data matrix that is 93% complete. | The measured peptide intensities in the study produce a data matrix that is only 69% complete. |
Sensitivity & Identification of Low Abundance Proteins |
Greater than 2-fold increase in quantified peptides (~45,000), including many more lower abundant proteins, extending the overall dynamic range by at least an order of magnitude. | Less than half the number of quantified peptides (~20,000), with less coverage of lower abundant proteins. |
The remainder of this blog post explores the DDA and DIA methods in more detail, and compares the amount and quality of data obtained from our experiments leveraging the two techniques.
To understand the difference between the DDA and DIA, it’s important to first recognize the different methods of peptide fragmentation and acquisition.
In the DDA method, the mass spectrometer alternates between a full-range survey scan—which measures all peptides eluting from the LC column at any given moment in time—and a series of narrow-range scans, which isolate a limited subset of co-eluting peptides. Following peptide acquisition, individual peptides are prioritized for fragmentation based on the real-time analysis of co-eluting peptide analyte signal intensities from the survey scan. This process is repeated for the entire LC gradient length, with the goal of identifying as many unique peptides of interest as possible to maximize coverage of the sample.
Conversely, the DIA method leverages the increased resolution (>10K), higher mass accuracy (<10 ppm), and faster scan speeds of newer instruments to generate higher-quality data for nearly infinitely multiplexed analyses. Rather than selecting a focused subset of peptides for fragmentation, the DIA method uses a full-range survey scan in addition to wider isolation windows to capture and fragment a wide range of co-eluting peptides at once. This process generates chimeric fragmentation data from multiple co-eluting peptides during each time interval, enabling comprehensive coverage of the sample's proteome.
Figure 1 shows a comparison of the DDA vs DIA methods, illustrating the different isolation windows and how they affect peptide acquisition.
Figure 1. Comparison of the DDA vs DIA proteomics methods for peptide fragmentation showing a schematic diagram of an LCMS chromatogram (A), showing the precursor MS1 survey scan (B) of the intact, co-eluting tryptic peptides at 30 minutes and the subsequent fragmentation scans (C) that would occur for both DDA and DIA workflows using either narrow isolation windows to select a subset of peptides (DDA) or large isolation windows to fragment all peptides (DIA) at each time interval.
As mentioned, we compared the Orbitrap Astral analyzer’s performance against a series of predecessor instruments using a tryptic digest of mouse liver protein over an LC runtime of 45 minutes.
Our findings are summarized below. They show that the DIA method can identify three times as many protein groups as the DDA method, and provides increased sensitivity and better experimental reproducibility.
The Orbitrap Astral system identified over 10,000 protein groups compared to 2,500 - 3,600 from traditional DDA methods, as shown in Figure 2.
Figure 2. The number of protein groups identified on the Astral using DIA & DDA acquisition methods, compared to previous generation Orbitrap instruments.
The Orbitrap Astral system also has the ability to run a DDA proteomics workflow. Using this method of peptide acquisition, the device identified 6,600 protein groups, still far less than the DIA method.
To further illustrate the difference between the DIA and DDA methods, we analyzed the same set of mouse liver samples using both DIA and DDA methods on the Orbitrap Astral instrument. Figure 3 shows a heatmap of the protein groups identified among the two sample sets, in which the DIA method delivered a more complete data matrix with fewer missing values. Because the DDA workflow conducts random samplings of the analytes throughout the LCMS run and captures far less data, there is much more white space (or empty values) compared to DIA results.
Therefore, the DIA results show much better reproducibility (~93%) among the replicates (less white space) and between the two sample types, compared to that of DDA (~69%).
Figure 3. Heatmap matrix showing the proteome analysis of female and male mouse livers (n=3) profiled with either DDA or DIA methods using the Orbitrap Astral instrument.
A comparison of the two data sets showed that the DIA method is also significantly more sensitive than the DDA method, with more than a twofold increase in quantitative measurements, resulting in a more complete data matrix (Figure 4). With more quantitative values in the data matrix (~45,000 vs ~20,000), statistical tests can be applied across many more data points for a more comprehensive analysis with better analytical redundancy and statistical power.
Figure 4. Bar chart comparison of the data sets, showing over two-fold more quantitative measurements.
The histogram below shows the binned abundance measurements of proteins identified in both the DIA and DDA methods (Figure 5). The results clearly illustrate that the DIA method is able to identify and quantify many more lower abundant proteins (between 0.1 and 3.1) from the mouse liver samples than the DDA analysis of the same samples. The increased depth of proteome coverage obtained by the DIA analysis is demonstrated by the elongated distribution along the x-axis, by at least an order of magnitude.
Even low-abundance proteins can significantly impact cell health, and potential disease biomarkers exist in the low-abundance proteome. The more comprehensive view of protein expression available with the DIA method can help uncover drug targets that might have been missed with DDA analysis.
With the advanced DIA functionality and extreme sensitivity of the Orbitrap Astral analyzer, deep coverage can be achieved for a wide range of proteomic studies in a variety of areas, including:
Our Proteomics Services team has over 20 years of experience and can provide customized experimental design and guidance for your project. We’ll also work with you to understand your experimental goals and can help ensure the results are meaningful and will advance your discovery research efforts.
Reach out to us to learn more about Proteomics Analytical Services at CST and how you can de-risk your projects by taking advantage of the increased sensitivity and reproducibility of this cutting-edge device.