Recent advances (2019–2021) of capillary electrophoresis‐mass spectrometry for multilevel proteomics

Chen, Daoyang; McCool, Elijah N.; Yang, Zhongyue; Shen, Xiaojing; Lubeckyj, Rachele A.; Xu, Tian; Wang, Qianjie; Sun, Liangliang

doi:10.1002/mas.21714

Cited by 54 publications

(68 citation statements)

References 162 publications

(258 reference statements)

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“…Thanks to its both universality and selectivity as well as high sensitivity and rich information content, MS has become the most powerful detection mode for CE, CEC, and other separation methods. The recent developments in the area of MS detection in CE methods have been described in several reviews dealing with CE-MS in general [165][166][167][168] and with its application to peptide, protein, peptidomic, metabolomic, and proteomic analyses especially [9,10,15,16,43,[169][170][171]. Importance of MS as analytical and structure elucidation method has significantly increased in the last years due to its key role in the proteomics, peptidomics, metabolomics, and other omics technologies [172].…”

Section: Mass Spectrometrymentioning

confidence: 99%

Recent developments in capillary and microchip electroseparations of peptides (2019–mid 2021)

Kašička

2021

Electrophoresis

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The review provides a comprehensive overview of developments and applications of high performance capillary and microchip electroseparation methods (zone electrophoresis, isotachophoresis, isoelectric focusing, affinity electrophoresis, electrokinetic chromatography, and electrochromatography) for analysis, microscale isolation, and physicochemical characterization of peptides from 2019 up to approximately the middle of 2021. Advances in the investigation of electromigration properties of peptides and in the methodology of their analysis, such as sample preparation, sorption suppression, EOF control, and detection, are presented. New developments in the individual CE and CEC methods are demonstrated and several types of their applications are shown. They include qualitative and quantitative analysis, determination in complex biomatrices, monitoring of chemical and enzymatic reactions and physicochemical changes, amino acid, sequence, and chiral analyses, and peptide mapping of proteins. In addition, micropreparative separations and determination of significant physicochemical parameters of peptides by CE and CEC methods are described.

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Section: Mass Spectrometrymentioning

confidence: 99%

Recent developments in capillary and microchip electroseparations of peptides (2019–mid 2021)

Kašička

2021

Electrophoresis

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“…Many proteoform separation techniques have been used to increase proteoform coverage in top-down MS, , which is desirable in proteoform-wide studies for proteoform function analysis and proteoform biomarker discovery . Liquid chromatography (LC) and capillary zone electrophoresis (CZE) are two main techniques for proteoform separation in top-down proteomics. , In an LC experiment, proteoforms are separated based on their hydrophobicity, size, or other properties using an LC column. There are many LC methods, such as reversed-phase liquid chromatography (RPLC), size exclusion chromatography (SEC), and ion exchange chromatography (IEC) .…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Machine Learning Models for Proteoform Retention and Migration Time Prediction in Top-Down Mass Spectrometry

et al. 2022

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Reversed-phase liquid chromatography (RPLC) and capillary zone electrophoresis (CZE) are two primary proteoform separation methods in mass spectrometry (MS)-based topdown proteomics. Proteoform retention time (RT) prediction in RPLC and migration time (MT) prediction in CZE provide additional information for accurate proteoform identification and quantification. While existing methods are mainly focused on peptide RT and MT prediction in bottom-up MS, there is still a lack of methods for proteoform RT and MT prediction in topdown MS. We systematically evaluated eight machine learning models and a transfer learning method for proteoform RT prediction and five models and the transfer learning method for proteoform MT prediction. Experimental results showed that a gated recurrent unit (GRU)based model with transfer learning achieved a high accuracy (R = 0.978) for proteoform RT prediction and that the GRU-based model and a fully connected neural network model obtained a high accuracy of R = 0.982 and 0.981 for proteoform MT prediction, respectively.

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“…If IACE were to be incorporated in sample preparation prior to sample introduction into the capillary or microchip, the entire system could be automated, reduce analysis time, and overcome limitations in poor detection sensitivity. We will emphasize the advantages for the determination of proteoforms when compared with other methods described to enhance the analytical sensitivity of analytes, such as field-amplified sample stacking, large-volume sample stacking, pH-mediated stacking, isotachophoreris (ITP), stacking techniques in micellar electrokinetic chromatography (MEKC), soli-phase extraction, and tagging target analytes with various chromophores and detecting the derivatized substances with sensitive detectors [123,151,152,[173][174][175][176][177][178][179][180][181][182][183][184][185][186][187][188][189][190]. In some instances, IACE can be used in combination with other methods to enhance analytical sensitivity even further.…”

Section: Capillary Electrophoresis As a Useful Technology For The Separation Of Structurally Related Small Molecular-weight Substances Anmentioning

confidence: 99%

Immunoaffinity Capillary Electrophoresis in the Era of Proteoforms, Liquid Biopsy and Preventive Medicine: A Potential Impact in the Diagnosis and Monitoring of Disease Progression

Guzman¹,

Guzman

2021

Biomolecules

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Over the years, multiple biomarkers have been used to aid in disease screening, diagnosis, prognosis, and response to therapy. As of late, protein biomarkers are gaining strength in their role for early disease diagnosis and prognosis in part due to the advancements in identification and characterization of a distinct functional pool of proteins known as proteoforms. Proteoforms are defined as all of the different molecular forms of a protein derived from a single gene caused by genetic variations, alternative spliced RNA transcripts and post-translational modifications. Monitoring the structural changes of each proteoform of a particular protein is essential to elucidate the complex molecular mechanisms that guide the course of disease. Clinical proteomics therefore holds the potential to offer further insight into disease pathology, progression, and prevention. Nevertheless, more technologically advanced diagnostic methods are needed to improve the reliability and clinical applicability of proteomics in preventive medicine. In this manuscript, we review the use of immunoaffinity capillary electrophoresis (IACE) as an emerging powerful diagnostic tool to isolate, separate, detect and characterize proteoform biomarkers obtained from liquid biopsy. IACE is an affinity capture-separation technology capable of isolating, concentrating and analyzing a wide range of biomarkers present in biological fluids. Isolation and concentration of target analytes is accomplished through binding to one or more biorecognition affinity ligands immobilized to a solid support, while separation and analysis are achieved by high-resolution capillary electrophoresis (CE) coupled to one or more detectors. IACE has the potential to generate rapid results with significant accuracy, leading to reliability and reproducibility in diagnosing and monitoring disease. Additionally, IACE has the capability of monitoring the efficacy of therapeutic agents by quantifying companion and complementary protein biomarkers. With advancements in telemedicine and artificial intelligence, the implementation of proteoform biomarker detection and analysis may significantly improve our capacity to identify medical conditions early and intervene in ways that improve health outcomes for individuals and populations.

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Recent advances (2019–2021) of capillary electrophoresis‐mass spectrometry for multilevel proteomics

Cited by 54 publications

References 162 publications

Recent developments in capillary and microchip electroseparations of peptides (2019–mid 2021)

Recent developments in capillary and microchip electroseparations of peptides (2019–mid 2021)

Evaluation of Machine Learning Models for Proteoform Retention and Migration Time Prediction in Top-Down Mass Spectrometry

Immunoaffinity Capillary Electrophoresis in the Era of Proteoforms, Liquid Biopsy and Preventive Medicine: A Potential Impact in the Diagnosis and Monitoring of Disease Progression

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