September 1, 2014 (Vol. 34, No. 15)

Workflow Advance Enables Quantification of 2,300+ Proteins in Liver Microtissues

Liver toxicity is still amongst the primary reasons why drug candidates have to be withdrawn from the market, and early prediction of drug safety remains a challenge in preclinical phases of drug development. In an attempt to reduce these exceptionally expensive market withdrawals, a new workflow methodology—Hyper Reaction Monitoring (HRM™)—has been adopted to quantify early changes in protein expression upon drug treatment.

Biomarker discovery projects and mode of action studies in drug discovery require the multiplexed quantification of thousands of proteins in parallel.

Traditionally, this has been approached using shotgun mass spectrometry (LC-MS/MS). This acquisition method can be used to generate comprehensive protein inventories of samples.

Its semi-stochastic nature, however, often leads to the generation of missing data points in a sample series. These gaps can complicate data interpretation (Figure 1A).

Near-Gap-Free Data Matrices

The recently introduced data-independent acquisition (DIA) approach results in near-gap-free data matrices. This approach, called SWATH-MS, combines the high content of thousands of quantified proteins per sample from shotgun proteomics with the reproducibility and precision of selected reaction monitoring (SRM) for individual proteins.

Biognosys, a leader in the application of SWATH-MS, provides expert HRM™-MS workflow services consisting of the creation of extensive assay libraries, the DIA, and the subsequent matching of the assays in the library for targeted quantification of all detectable proteins over whole sample series (for the HRM-MS workflow see Figure 1B). The assay libraries, which effectively constitute a protein inventory, are created using deep proteome mapping with LC-MS/MS.

Proprietary sample-preparation techniques enable our customers to benefit from years of experience generated with multiple sample types within Biognosys. Powerful software analysis is carried out using Spectronaut™, a unique fully automated tool for statistically valid analysis of HRM-MS data that enables efficient processing of thousands of peptide signals in large sample cohorts.

Figure 1. HRM-MS workflow and conceptual advantage. (A) Traditional shotgun LC-MS/MS generates missing data points when repeatedly acquiring signals from the same sample due to the semi-stochastic nature of the acquisition method. HRM-MS data matrices are nearly free of gaps thanks to data-independent acquisition and subsequent targeted data analysis. (B) The HRM-MS workflow consists of three essential steps: data-independent acquisition of all detectable peptide signals in the samples, the use of a comprehensive assay library that is matched to the recorded signals, and extraction of information on protein quantities in the sample.

Toxicity in Liver Microtissues

3D InSight™ human liver microtissues (InSphero) were exposed to acetaminophen concentrations between 9.77 µM and 2,500 µM. The IC50 was 2,300 µM determined by a cell viability assay. A specific assay library for human liver microtissues was generated using LC-MS/MS and contained over 2,400 proteins. Many proteins included in the library were characteristic liver proteins.

HRM-MS analysis resulted in 2,361 full protein profiles over all samples in the tested concentration range. As sample materials are commonly precious, all analyses were carried out using as little as 12,000 cells as starting material.

Pairwise comparison of acetaminophen-exposed liver microtissues at the different concentrations showed that with increasing acetaminophen concentration more proteins were significantly regulated while most of the proteins in the library remained, as expected, unchanged (Figure 2A). Functional annotation revealed cellular processes that were activated or deactivated, such as oxidation reduction for upregulated proteins and fatty acid metabolism for downregulated candidates. These findings corresponded well with the known effects of oxidative stress and liver damage occurring in liver after acetaminophen exposure.

The most striking change in protein expression level was observed for cytochrome P450 1A2 (gene name CYP1A2), a protein that is known to be involved in phase I metabolism of acetaminophen. A significant upregulation was found even at the lowest concentration (Figure 2). This is especially noteworthy as the traditional cell viability assay did not show any effect at that concentration, which is known to be well below the therapeutic acetaminophen concentration in vivo.

The HRM-MS method revealed a promising candidate for very early marker of liver toxicity upon acetaminophen treatment. Raw data from HRM-MS generated with Spectronaut™ are displayed in Figure 2B.

In addition to the global analysis, HRM-MS allows for a targeted analysis of any protein of interest that is covered in the assay library. Enzymes involved in phase II metabolism such as UDP-glucuronosyltransferases (UGTs) or sulfotransferases (SULTs) play an important role for the conjugation and elimination of acetaminophen. These enzymes can be monitored over the entire concentration range and show significant increases at higher doses of acetaminophen (Figure 2C).

Figure 2. Global proteomic profiling using HRM-MS in human liver microtissues after acetaminophen exposure at subtoxic and toxic concentrations. (A) Log2 fold-changes for individual protein levels compared to untreated control. Each line represents one protein. While most of the protein levels remain constant, proteins that are regulated upon treatment are easily identified. (B) Raw data for selected proteins at 2,500 µM acetaminophen—left: downregulation of ACOX1 upon acetaminophen exposure; middle: upregulation of CYP1A; right: constant level of “housekeeper” protein GAPDH. (C) Targeted analysis of selected proteins of interest. Enzymes involved in phase-II metabolism are upregulated at higher acetaminophen doses.


HRM-MS is a key next-generation targeted proteomics technique allowing the reproducible quantification of thousands of proteins in individual samples. This novel technique enables researchers to:

  • uncover deeper insights into the complete visible proteome.
  • conduct unbiased global discovery of significantly regulated proteins upon treatment or along time lines.
  • enhance information on protein regulation along specific pathways of interest.
  • achieve a greater understanding of the mode of action or mechanism of toxicity induced by drug treatment.

This range of applications suggests HRM-MS is the tool of choice where the goal is to identify relevant target proteins against a large proteome background.

Claudia Escher, Ph.D., is head of scientific operations and Russell Golson ([email protected]) is business development consultant at Biognosys.

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