Webinar Q&A follow up: the use of LC–MS in bioanalytical discovery

LC–MS for bioanalytical discovery

Thank you everyone who attended our live ‘Panel discussion: the use of LC–MS in bioanalytical discovery in association with Covance and SCIEX. Below are responses to the questions posed by our audience during the live event. We hope this is a useful resource and thank those who submitted these thoughtful questions.

(Q) What do you think about the use of native mass spectrometry in the discovery landscape?

Tom Covey, Principle Research Scientist, MDS/SCIEX (MA, USA): The first demonstration of the ability to observe non-covalent interactions between proteins and other molecules with an affinity for them in an electrospray mass spectrum dates to the early 1990’s the question has always been well does the presence of this gas phase cluster correlate with the biology that occurs in solution. It is just now that answers to this are emerging as the drug discovery process looks toward more affinity-based screening methods to compliment the activity-based screening methods that have dominated for so long. I am seeing several successful so-called ‘native’ affinity screens developing that show strong correlations to the activity-based screens and to the biology in general.

(Q) Is triple quad better than QTOF for protein digest analysis?

Shashyendra Singh Gautam, Sr. Scientist, Bioanalytical Research, Pharmaceutical Candidate Optimization, (BBRC; Karnataka, India): This is a very appropriate question and a few years back we also asked the same question to ourselves. In general, triple quadrupoles (QQQ) are more sensitive and QTOF more selective. To test this hypothesis we choose five drug-metabolizing enzymes that are present in the human liver (we made sure that their expressions are at least in the ng/ml level). We quantitated these enzymes on both QQQ and Q-TOF using the surrogate peptide approach in various in vitro systems. We observed that out of five enzymes, three were having more or less similar LLOQ’s, one of the enzymes showed a marked difference in the LLOQ triple quadrupole being more sensitive. However, there was one enzyme whose LLOQ was better in the Q-TOF, because there was a lot of background interferences observed in QQQ, for that particular peptide. We got this work published (J Chromatogr B. 2019 Feb 1: 1106-1107:11-18). The point is QQQ is more sensitive but we should be mindful that QTOF helps you to get away with noisy background and/or isobaric interferences and can be used as a tool for quantitation in those scenarios.

Tom Covey: Relates to what I said earlier. If you are monitoring known peptides and the number of simultaneous analytes is limited to say 20 or less the triple quad sensitivity is superior. When the peptides are unknown, or their numbers are great than OTOF is the way to go. The duty cycle advantage and ion transmission efficiency of the triple begin to disappear as switching between large numbers of analytes is required.

(Q) Will HRMS for protein biomarker quantification ever be able to compete (e.g., throughput, cost/analyte) with LBA/ELISA based multi-analyte panels?

Tom Covey: If we are talking about comparable assay speeds than the answer is a definite yes. If we are talking about sensitivity, we would have to go in and look at these on a case by case situation.

(Q) Is it still worth to focus on bottom-up LC-MS for large molecules or should time and money be spent to improve the analysis of intact proteins?

Shashyendra Singh Gautam: I think this question arises not only because of the science behind it but it also has something to do with human psychology – we are appreciative of apple-to-apple comparison. Both intact mass analysis and the ligand-binding assay measure the proteins in the entirety. Whereas the bottom-up technique uses a different approach, however, we should understand that being different doesn’t necessarily mean that the approach is wrong. We should also not forget there is a field of mass spectrometry-based ‘omics’, which heavily relies on bottom-up proteomics.

If you refer to last year’s White Paper on The Recent Issues of Bioanalysis, where they agree on the advantage of intact mass analysis, and also concluded that this technology is limited by complex data analysis, lack of sensitivity and have significant chromatographic challenges. The use of intact mass analysis will depend upon the question being asked (Bioanalysis 2019 Nov;11(22):2029-2048). In my opinion, money and time should be spent on improving intact mass analysis, especially on the algorithms. I also think that both of these approaches are part of mass spectrometry so it is advisable to take advantage of both the techniques and complement each other in answering the questions.

(Q) In transporter protein quantification, we see huge lab to lab variation. What are the potential reasons and how can we rely on one particular set of data?

Shashyendra Singh Gautam: Thank you very much for the question it’s a very relevant point and many labs have tried to quantitate these proteins to answer some key questions. There are two-parts to this answer the first part deals with why we see this variation from lab to lab and the reason, the short answer is because there is a lack of consensus among the various groups for how to go about the endogenous protein quantitation. Also to the fact that the protein standard of these transporter proteins is unavailable. We use the surrogate peptide approach to quantify them, these surrogate (quantotypic) peptides might change from lab to lab as most of them use a different protocols (extraction of membrane proteins and protein digestion), which give rise to different numbers.

Now the second part is how to rely on these numbers, one thing we should keep in mind is that the surrogate peptide approach is relative, it doesn’t give you an absolute value. Since these values are relative it doesn’t matter what numbers we are getting in different labs. However, the trend should not change. Usually, the trend does not change between the labs, but the numbers might. Those numbers should preferably be used only to validate the findings. We have done work on a similar line and got it published Journal of Pharmacology and Experimental Therapeutics Vol. 375, Issue 3, Dec 2020 ( https://doi.org/10.1124/jpet.120.000291 ). Where instead of relying only on the absolute number we have used the trend to validate our findings.