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Driving Speed, Sensitivity and Precision in Modern Proteomics
Industry Insight

Driving Speed, Sensitivity and Precision in Modern Proteomics

Driving Speed, Sensitivity and Precision in Modern Proteomics
Industry Insight

Driving Speed, Sensitivity and Precision in Modern Proteomics


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This year, the American Society of Mass Spectrometry (ASMS) annual conference came to us in a somewhat different format– virtual. What remained the same as previous years, however, was the sharing of exciting developments in analytical technologies for proteomics and metabolomics.

Bruker Daltonics
 announced a variety of new products for highly sensitive and high-throughput analyses, including the world’s first commercial matrix-assisted laser desorption/ionization (MALDI)-2 post-ionization (PI) source and trapped ion mobility spectrometry (TIMS)/ parallel accumulation–serial fragmentation (PASEF)-enabled 4D-Proteomics methods that leverage the large-scale, real-time availability of accurate collision cross sections (CCS). CCS values can be utilized as an additional identification point in data dependent analysis, and in data independent analysis, the CCS value works as a unique signature to align features.

Technology Networks
 spoke with Rohan Thakur, Executive Vice President of Life Sciences Mass Spectrometry at Bruker Daltonics, to discuss the announcement, and to learn how he anticipates the novel technologies will impact clinical research.

Molly Campbell (MC): Firstly, can you talk about the past year for TIMS time of flight (TOF)? What have been some of the stand-out research projects utilizing the technology, in your opinion?

Rohan Thakur (RT):
 The user community’s response to adopting the timsTOF platform (Pro and the fleX) has been better than expected as users have realized for themselves  the benefits of TIMS technology, including  higher sensitivity due to time focusing, MOMA or mobility offset and mass alignment for uncompromised and deep proteome coverage. A major benefit of the timsTOF Pro has been the enablement of “short-gradients” within bottom-up proteomics, which in turn has made translational proteomics a reality. Before the timsTOF Pro, most mass spectrometry (MS) proteomics labs had to choose between "depth of coverage" or "time of analysis". The launch of the timsTOF Pro made depth of coverage with short-gradients possible, which allowed proteomics scientists to go from running 10 samples a day to routinely running 100 samples a day. The most satisfying aspect here was that researchers quickly realized they could analyze precious samples from large cohort studies as the timsTOF has the robustness performance with sustained high sensitivity and scan speed that is demanded by translational proteomics studies.

Previously, this combination was unavailable on older generation mass spectrometers.
Dr Roman Fischer’s sepsis proteome characterization work (100 samples/day throughput with nearly 5000 plasma samples analyzed) at Oxford University and Dr Catherine Wong’s COVID-19 related large cohort studies from the Beijing Center for Life Sciences have shown the impact a product like the timsTOF Pro can have on their translational research. Seminal work by Professor Matthias Mann’s group, where they used deep learning techniques from a million training samples to predict peptide CCS in an effort to use this critical fourth dimension benefitting the proteomics landscape, is another project that stands out. 

MC: Can you discuss the rationale behind developing MALDI-2, and how the increased sensitivity is achieved?

RT
: The rationale came from customers who wanted to see more classes of molecules that could be analyzed by MALDI, and the overall improvements in sensitivity for molecules that respond to the MALDI guided regions of interest or SpatialOMx, where endogenous molecular signatures from metabolites, lipids, and glycans can provide greater insight into which regions of tissue could be isolated for further omics analysis via LC-MS, was a second driving factor. Both factors are especially relevant in pharmaceutical research, for instance related to cancer studies. The improvement in sensitivity is achieved by firing a second laser (MALDI-2 PI) into the expanding plume activated by the first laser (regular MALDI), where the additional energy results in a charge transfer reaction, resulting in higher ionization efficiency. Since the process requires MALDI operation at elevated pressures, this works perfectly on the dual source (electrospray ionization/MALDI) timsTOF fleX platform.

MC: How do you envision the increased sensitivity of the MALDI-2 powered timsTOF fleX will enhance the study of small molecules and lipids in the context of studying diseases?

RT
: Pharmaceutical research that focuses on cancer will benefit from MALDI-2 PI, as it will allow scientists to relate transcriptomic changes to SpatialOMx. The key here is to locate specific cellular populations that can be isolated for deeper interrogation via proteomics, lipidomics and metabolomics, via the analysis of the tissue imaging techniques that can reveal changes in lipids or cell surface glycans within the tumor, at the tumor boundary and distal to the tumor. Such studies were not possible in the past, and the timsTOF fleX allows you to do all these experiments with sensitivity and on a single instrument. Add to this the TIMS dimension and the value of information per pixel increases significantly in the MALDI experiment; again, doing this at the speed of 10Khz and at 10 µm spatial resolution is a first. You can use the CCS value of the xenobiotic or the endogenous molecule within the different tissue sections, and then use that same value when you do the LC-MS analysis on the same instrument. The timsTOF fleX allows for a tremendous gain in productivity for a research lab due to its versatility.

MC: Considering the increased capabilities for analyzing pharmacokinetics and pharmacodynamics of drug compounds – what impact could these advances in qMSI have on drug development timeframes?

RT
: Getting critical information earlier is a significant advantage in the drug development process, as it allows for an efficiency gain for the overall process. You can advance promising new chemical entities (NCE) because of the higher fidelity of information (has the drug hit the right target within the right tissue?) or stop NCEs that show toxicity early. This can result in a higher number of NCEs advancing forward in the process, which increases your chances of finding the drug candidate with the right efficacy, while minimizing surprises from off-target effects. So perhaps not an impact on timeline as such, but potentially, a gain in efficiency, augmenting the process of bringing safer drugs to market. 

MC: Can you expand on the decision to combine PASEF with parallel reaction monitoring (PRM)?

RT: 
The gas phase separation of peptides due to TIMS has a tremendous advantage for PRM experiments, because it acts both as an additional CCS based ion selector (thereby reducing isobaric chemical noise) and a sensitivity boost (time focusing effect of the PASEF scan function), in addition to optimizing precursor ion selection for the resolving quadrupole. Now, you can synchronize the quadrupole isolation to the unique peptide CCS value and m/z, allowing for much higher accuracy, selectivity and precision for label-free quantification.

MC: Having spoken to researchers training deep learning networks to accurately predict CCS values for molecules, this seems to be an exciting area that holds promise for novel molecule discovery and identification. How will the latest innovations on the timsTOF platform enhance such work?

RT:
 Ion mobility has been around for almost 15 years, however it was the advent of "TIMS-derived CCS values" for every precursor ion detected that drove deep learning techniques to probe into understanding how a gas phase property could be further mined for information. This is because of the unique reproducibility and stability of the CCS measurement from the TIMS device, which has allowed data scientists to confidently use TIMS-derived CCS to develop deep learning algorithms, enabling prediction of peptide CCS values. Measuring experimental peptide CCS values against predicted CCS values in the millions of peaks typically observed in a bottom-up proteomics experiment has many benefits – the most basic ability being able to look ahead for post-translational modifications for tandem MS selection, but the possibilities are endless.   

Rohan Thakur was speaking to Molly Campbell, Science Writer for Technology Networks.

Meet The Author
Molly Campbell
Molly Campbell
Senior Science Writer
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