Targeted protein quantification using sparse reference labeling

Proteomics in the pharmaceutical and biotechnology industry: a look to the next decade

INTRODUCTION

Pioneering technologies such as proteomics have helped fuel the biotechnology and pharmaceutical industry with the discovery of novel targets and an intricate understanding of the activity of therapeutics and their various activities in vitro and in vivo. The field of proteomics is undergoing an inflection point, where new sensitive technologies are allowing intricate biological pathways to be better understood, and novel biochemical tools are pivoting us into a new era of chemical proteomics and biomarker discovery. In this review, we describe these areas of innovation, and discuss where the fields are headed in terms of fueling biotechnological and pharmacological research and discuss current gaps in the proteomic technology landscape.

AREAS COVERED

Single cell sequencing and single molecule sequencing. Chemoproteomics. Biological matrices and clinical samples including biomarkers. Computational tools including instrument control software, data analysis.

EXPERT OPINION

Proteomics will likely remain a key technology in the coming decade, but will have to evolve with respect to type and granularity of data, cost and throughput of data generation as well as integration with other technologies to fulfill its promise in drug discovery.

Ion mobility-enhanced MS(E)-based label-free analysis reveals effects of low-dose radiation post contextual fear conditioning training on the mouse hippocampal proteome

Recent advances in the field of biodosimetry have shown that the response of biological systems to ionizing radiation is complex and depends on the type and dose of radiation, the tissue(s) exposed, and the time lapsed after exposure. The biological effects of low dose radiation on learning and memory are not well understood. An ion mobility-enhanced data-independent acquisition (MS(E)) approach in conjunction with the ISOQuant software tool was utilized for label-free quantification of hippocampal proteins with the goal of determining protein alteration associated with low-dose whole body ionizing radiation (X-rays, 1Gy) of 5.5-month-old male C57BL/6J mice post contextual fear conditioning training. Global proteome analysis revealed deregulation of 73 proteins (out of 399 proteins). Deregulated proteins indicated adverse effects of irradiation on myelination and perturbation of energy metabolism pathways involving a shift from the TCA cycle to glutamate oxidation. Our findings also indicate that proteins associated with synaptic activity, including vesicle recycling and neurotransmission, were altered in the irradiated mice. The elevated LTP and decreased LTD suggest improved synaptic transmission and enhanced efficiency of neurotransmitter release which would be consistent with the observed comparable contextual fear memory performance of the mice following post-training whole body or sham-irradiation.

SIGNIFICANCE

This study is significant because the biological consequences of low dose radiation on learning and memory are complex and not yet well understood. We conducted a IMS-enhanced MS(E)-based label-free quantitative proteomic analysis of hippocampal tissue with the goal of determining protein alteration associated with low-dose whole body ionizing radiation (X-ray, 1Gy) of 5.5-month-old male C57BL/6J mice post contextual fear conditioning training. The IMS-enhanced MS(E) approach in conjunction with ISOQuant software was robust and accurate with low median CV values of 0.99% for the technical replicates of samples from both the sham and irradiated group. The biological variance was as low as 1.61% for the sham group and 1.31% for the irradiated group. The applied data generation and processing workflow allowed the quantitative evaluation of 399 proteins. The current proteomic analysis indicates that myelination is sensitive to low dose radiation. The observed protein level changes imply modulation of energy metabolism pathways in the radiation exposed group, specifically changes in protein abundance levels suggest a shift from TCA cycle to glutamate oxidation to satisfy energy demands. Most significantly, our study reveals deregulation of proteins involved in processes that govern synaptic activity including enhanced synaptic vesicle cycling, and altered long-term potentiation (LTP) and depression (LTD). An elevated LTP and decreased LTD suggest improved synaptic transmission and enhanced efficiency of neurotransmitter release which is consistent with the observed comparable contextual fear memory performance of the mice following post-training whole body or sham-irradiation. Overall, our results underscore the importance of low dose radiation experiments for illuminating the sensitivity of biochemical pathways to radiation, and the modulation of potential repair and compensatory response mechanisms. This kind of studies and associated findings may ultimately lead to the design of strategies for ameliorating hippocampal and CNS injury following radiation exposure as part of medical therapies or as a consequence of occupational hazards.

Protein-Based Classifier to Predict Conversion from Clinically Isolated Syndrome to Multiple Sclerosis

Multiple sclerosis is an inflammatory, demyelinating, and neurodegenerative disease of the central nervous system. In most patients, the disease initiates with an episode of neurological disturbance referred to as clinically isolated syndrome, but not all patients with this syndrome develop multiple sclerosis over time, and currently, there is no clinical test that can conclusively establish whether a patient with a clinically isolated syndrome will eventually develop clinically defined multiple sclerosis. Here, we took advantage of the capabilities of targeted mass spectrometry to establish a diagnostic molecular classifier with high sensitivity and specificity able to differentiate between clinically isolated syndrome patients with a high and a low risk of developing multiple sclerosis. Based on the combination of abundances of proteins chitinase 3-like 1 and ala-β-his-dipeptidase in cerebrospinal fluid, we built a statistical model able to assign to each patient a precise probability of conversion to clinically defined multiple sclerosis. Our results are of special relevance for patients affected by multiple sclerosis as early treatment can prevent brain damage and slow down the disease progression.

An integrated quantification method to increase the precision, robustness, and resolution of protein measurement in human plasma samples

Background

Current quantification methods for mass spectrometry (MS)-based proteomics either do not provide sufficient control of variability or are difficult to implement for routine clinical testing.

Results

We present here an integrated quantification (InteQuan) method that better controls pre-analytical and analytical variability than the popular quantification method using stable isotope-labeled standard peptides (SISQuan). We quantified 16 lung cancer biomarker candidates in human plasma samples in three assessment studies, using immunoaffinity depletion coupled with multiple reaction monitoring (MRM) MS. InteQuan outperformed SISQuan in precision in all three studies and tolerated a two-fold difference in sample loading. The three studies lasted over six months and encountered major changes in experimental settings. Nevertheless, plasma proteins in low ng/ml to low μg/ml concentrations were measured with a median technical coefficient of variation (CV) of 11.9% using InteQuan. The corresponding median CV using SISQuan was 15.3% after linear fitting. Furthermore, InteQuan surpassed SISQuan in measuring biological difference among clinical samples and in distinguishing benign versus cancer plasma samples.

Conclusions

We demonstrated that InteQuan is a simple yet robust quantification method for MS-based quantitative proteomics, especially for applications in biomarker research and in routine clinical testing.

Electronic supplementary material

The online version of this article (doi:10.1186/1559-0275-12-3) contains supplementary material, which is available to authorized users.