Webinar Review: Advances in MS-based Single-cell Proteomics

Over the course of the semester, our trainees are reviewing webinars in their given fields and preparing abstracts to help colleagues outside their discipline make an informed choice about watching them. As our program bridges diverse disciplines, these abstracts are beneficial for our own group in helping one another gain key knowledge in each other’s fields. We are happy to share these here for anyone else who may find them helpful.

Advances in MS-based Single-cell Proteomics

Dr. Tao Liu


OCCPR Webinar Series

Sara BellAnalysis by Sara Bell:

In this webinar, Dr. Tao Liu provides an overview of advances in mass spectrometry based single cell proteomics occurring at Pacific Northwest National Lab. Mass spectrometry (MS) proteomics is a common workflow for characterization of proteins and their post-translational modifications. MS provides high throughput analysis and deep proteomic coverage, but generally large sample sizes are required. Using large “bulk” samples can be useful for high quality data, but it only provides a look at the population average of the sample of interest. In many clinical applications such as cancer research, understanding the heterogeneity of samples can be of extreme importance. To understand heterogeneity in samples, scientists can use single cell methods. For MS, single cell analysis has lower proteome coverage but is sensitive and provides the ability to characterize sub populations of cells. The goal of Dr. Liu’s work is to miniaturize sample preparation platforms for use on volume limited samples such as single cells. In this talk, Dr. Liu describes a few new methods for small volume sample preparation and signal amplification in MS analysis.

Towards minimizing sample loss, “nanodroplet processing in one pot for trace samples” (nanoPOTS) can be used to perform all sample preparation steps in one nanoliter well. Coupling automated sample preparation and nanoPOTS reduces sample loss since analyte is contained to one well and automation helps reduce error. This advancement in sample preparation was further coupled with a method known as “boosting to amplify signal with isobaric labeling” (BASIL). Using BASIL, Liu labels individual nanoPOTS wells with a series of isotopic labels – one unique label per well. All wells can then be pooled and analyzed together to increase the ion count for MS detection. Using the information gained by the isotopic labeling, characteristic data for individual wells can then be extracted from the bulk data. In this way, small volumes can be analyzed by reducing sample loss in nanoPOTS and gaining detection sensitivity through BASIL. Liu summarizes the constraints of this method’s detection capabilities and the resulting limits on the amount of boosting that is possible through BASIL. They also provide multiple experimental applications of these methods while providing comparisons of their method to typical bulk analyses. In particular, this method is well suited for single cell analysis since it preserves information on single cell heterogeneity.

Overall, Dr. Liu describes interesting developments in working with small volumes in a way that avoids sample loss and increases sensitivity and coverage of the analysis. Liu introduces a variety of methods building off nanoPOTS & BASIL all of which could not be fully covered in the allotted time. Due to this, I would recommend reading the articles cited for more in-depth explanations about any of the methods that are relevant to your work. However, Liu does clearly state the advantages and unmet challenges associated with this type of sampling and analysis.