New advances in quantitative proteomics research and current applications in asthma

ABSTRACT

Introduction

Asthma is the most common chronic respiratory disease and has been declared a global public health problem by the World Health Organization. Due to the high heterogeneity and complexity, asthma can be classified into different ‘phenotypes’ and it is still difficult to assess the phenotypes and stages of asthma by traditional methods. In recent years, mass spectrometry-based proteomics studies have made significant progress in sensitivity and accuracy of protein identification and quantitation, and are able to obtain differences in protein expression across samples, which provides new insights into the mechanisms and classification of asthma.

Areas covered

In this article, we summarize research strategies in quantitative proteomics, including labeled, label-free and targeted quantification, and highlight the advantages and disadvantages of each. In addition, new applications of quantitative proteomics and the current status of research in asthma have also been discussed. In this study, online resources such as PubMed and Google Scholar were used for literature retrieval.

Expert opinion

The application of quantitative proteomics in asthma has an important role in identifying asthma subphenotypes, revealing potential pathogenesis and therapeutic targets. But the proteomic studies on asthma are not sufficient, as most of them are in the phase of biomarker discovery.

KEYWORDS:

• Quantitative proteomics
• label-based quantification
• label-free quantification
• targeted quantification
• asthma
• biomarkers

Article highlights

• Different quantitative proteomics approaches, including labeled, label-free and targeted quantification were presented, and their advantages, drawbacks and technical advances were summarized.

• Overview of the current status of research and application of quantitative proteomics in asthma.

• Future highlights and expert opinions on how to promote the use and development of quantitative proteomics in the study of disease.

Abbreviations

2-DE: two-dimensional electrophoresis

LC-MS: liquid chromatography-mass spectrometry

m/z: mass-to-charge ratio

SILAC: stable isotope labeling with amino acids in cell culture

TMT: tandem mass tag

iTRAQ: isobaric tags for relative and absolute quantification

LC-MS/MS: liquid chromatography-tandem mass spectrometry

HCD: high-energy collision dissociation

ETD: electron transfer dissociation

CID: collision-induced dissociation

TOF: time-of-flight

LFQ: label-free quantification

SC: spectral counting

XIC: extracted ion chromatogram

DE: dynamic exclusion

DIA: data-independent acquisition

AMRT: accurate mass and retention time

HPP:human protein project

SRM: selected reaction monitoring

MRM: multiple reaction monitoring

PRM: parallel reaction monitoring

IS-PRM: internal standard triggered-parallel reaction monitoring

TQMS or QQQ: triple quadrupole mass spectrometer

MS: mass spectrometry

HRAM: high resolution/accurate mass

‘Transitions’: precursor-product ion pairs

SIL: stable isotope-labeled internal standard peptides

BALF: bronchoalveolar lavage fluid

2DE-MS: two-dimensional electrophoresis and mass spectrometry

MALDI-TOF: matrix-assisted laser adsorption–time of flight

ApoE: Apolipoprotein E

COPD: chronic obstructive pulmonary diseases

IL33: Interleukin 33

IPA: Ingenuity pathway analysis

IGFAL: insulin-like growth factor-binding protein acid labile subunit

MSAA: moderate to severe allergic asthma

UA: uncontrolled asthma

CA: controlled asthma

TLR-4: Toll-like receptor 4

AGEs: advanced glycation end products

SR: steroid resistance

SSA: steroid-sensitive asthma

SRA: steroid-resistant asthma

VDBP: vitamin D-binding protein

PDIA6: protein disulfide isomerase associated 6

GRP78: 78 KDa glucose-regulated protein precursor

Declaration of interests

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This work was supported by the National Natural and Science Foundation of China (Project No. 82002949); State Key Lab of Respiratory Disease, Guangzhou Medical University (Project No. SKLRD-OP-202010); State Key Laboratory of Respiratory Disease, Guangdong-Hong Kong-Macao Joint Laboratory of Respiratory Infectious Disease (Project No. 02-000-2101-5061); Medical Scientific Research Foundation of Guangdong Province (Project No. A2021231); Project 111 (Project No. D18010); Guangzhou Institute of Respiratory Health Open Project (Funds provided by China Evergrande Group, Project No. 2020GIRHHMS01).