Proteomics of human biological fluids for biomarker discoveries: technical advances and recent applications

Dayon, Loı̈c; Cominetti, Ornella; Affolter, Michael

doi:10.1080/14789450.2022.2070477

Cited by 52 publications

(55 citation statements)

References 247 publications

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“…[25][26][27] Using an antibody-based assay, the panel of biomarkers of interest can be chosen, and only a few microliters of sample are required. 24 The PEA technology can evaluate a much greater number of proteins, compared to standard enzyme-linked immuno-sorbent assays (ELISA), but so far, very few studies have used this method studying tear uid. 19,24,28,29 , and little is known about the optimal pre-processing method, which is crucial for between-study comparisons.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of pre-processing methods for tear fluid proteomics using the Olink platform

Vergouwen

Schotting

Endermann

et al. 2023

Preprint

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Tear fluid forms a potential source for biomarker identification, and can be minimal invasively collected via Schirmer strips. The lack of knowledge on the processing of Schirmer strips however complicates the analysis and between-study comparisons. We studied two different pre-processing methods, specifically the use of punches of the strip versus elution of the strip in PBS buffer. Tear fluid filled Schirmer strips were collected from 5 healthy participants, and divided into two halves over the length of the strip. In either part, punches or eluates were obtained from 4 different locations, from the first part touching the eye (head) to the end, to assess the protein distribution along the strips. The levels of 92 inflammatory proteins were measured in the punches/eluates using Olink Target 96. The punch method yielded higher protein detectability compared to the elution method (76% vs 66%; p ≤ 0.001). However, 3 out of 5 punches from the head failed quality control. Protein levels over the remaining parts of the strips were similar. Based on our findings we encourage using the punch method of any part of the strip except the head with Olink Target 96 or other suitable techniques.

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Section: Discussionmentioning

confidence: 99%

Evaluation of pre-processing methods for tear fluid proteomics using the Olink platform

Vergouwen

Schotting

Endermann

et al. 2023

Preprint

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“…With advancements in proteomics technologies, it is possible to simultaneously perform protein identification and quantification of expression profiles for thousands of proteins. Proteomic analysis has become a powerful method for characterizing the molecular profiles of patients, allowing analysis of both tissues [ 11 ] and biological fluids [ 12 ].…”

Section: Proteomic Strategiesmentioning

confidence: 99%

“…Changes in serum protein levels may reflect alterations in inflammation that do not provide information about the disease process [ 13 ]. Therefore, an organ-specific disease sampling of fluid compartments near the diseased tissue (e.g., synovial fluid, urine, cerebrospinal fluid) can provide a more reliable source of potential diagnostic and therapeutic biomarkers than serum [ 11 , 12 , 13 ].…”

Section: Proteomic Strategiesmentioning

confidence: 99%

“…Recent advances in ESI sources have greatly improved sensitivity, and this technique is now the most commonly used in large-scale qualitative and quantitative proteomics. In the present review, we focus on the most recent proteomics technologies, which combine liquid chromatography and electrospray ionization tandem MS (LC-ESI MS/MS or LC-MS/MS) and represent the most effective and commonly used approaches for proteome analysis [ 8 , 11 , 16 ], as well as current and future MS-based proteomics strategies for the study of rare genetic and metabolic disorders.…”

Section: Proteomic Strategiesmentioning

confidence: 99%

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Proteomics in Inherited Metabolic Disorders

Chantada-Vázquez

Bravo

Gouveia

et al. 2022

IJMS

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Inherited metabolic disorders (IMD) are rare medical conditions caused by genetic defects that interfere with the body’s metabolism. The clinical phenotype is highly variable and can present at any age, although it more often manifests in childhood. The number of treatable IMDs has increased in recent years, making early diagnosis and a better understanding of the natural history of the disease more important than ever. In this review, we discuss the main challenges faced in applying proteomics to the study of IMDs, and the key advances achieved in this field using tandem mass spectrometry (MS/MS). This technology enables the analysis of large numbers of proteins in different body fluids (serum, plasma, urine, saliva, tears) with a single analysis of each sample, and can even be applied to dried samples. MS/MS has thus emerged as the tool of choice for proteome characterization and has provided new insights into many diseases and biological systems. In the last 10 years, sequential window acquisition of all theoretical fragmentation spectra mass spectrometry (SWATH-MS) has emerged as an accurate, high-resolution technique for the identification and quantification of proteins differentially expressed between healthy controls and IMD patients. Proteomics is a particularly promising approach to help obtain more information on rare genetic diseases, including identification of biomarkers to aid early diagnosis and better understanding of the underlying pathophysiology to guide the development of new therapies. Here, we summarize new and emerging proteomic technologies and discuss current uses and limitations of this approach to identify and quantify proteins. Moreover, we describe the use of proteomics to identify the mechanisms regulating complex IMD phenotypes; an area of research essential to better understand these rare disorders and many other human diseases.

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“…For this reason, the application of metagenomics is not likely to significantly improve JEV RNA detection. Uniquely untargeted and powerful, the application of liquid-chromatography mass-spectrometry (LC-MS) proteomics techniques to clinical samples represent a relatively novel approach to improve diagnosis of JE (13,14). Such an approach is based on the hypothesis that there is a protein signature in CSF specific for JE, and that this could be harnessed in an antibody-based point-of-care test.…”

Section: Introductionmentioning

confidence: 99%

Deep proteomics network and machine learning analysis of human cerebrospinal fluid in Japanese encephalitis virus infection

Bharucha

Gangadharan

Kumar

et al. 2022

Preprint

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Japanese encephalitis virus (JEV) is a mosquito-borne flavivirus, and leading cause of neurological infection in Asia and the Pacific, with recent emergence in multiple territories in Australia in 2022. Patients may experience devastating socioeconomic consequences; JEV infection (JE) predominantly affects children in poor rural areas, has a 20-30% case fatality rate, and 30-50% of survivors suffer long-term disability. JEV RNA is rarely detected in patient samples, and the standard diagnostic test is an anti-JEV IgM ELISA with sub-optimal specificity; there is no means of detection in more remote areas. We aimed to test the hypothesis that there is a diagnostic protein signature of JE in human cerebrospinal fluid (CSF), and contribute to understanding of the host response and predictors of outcome during infection. We retrospectively tested a cohort of 163 patients recruited as part of the Laos central nervous system infection study. Application of liquid chromatography and tandem mass spectrometry (LC-MS/MS), using extensive offline fractionation and tandem mass tag labelling, enabled a comparison of the CSF proteome in 68 JE patient vs 95 non-JE neurological infections. 5,070 proteins were identified, including 4,805 human proteins and 265 pathogen proteins. We incorporated univariate analysis of differential protein expression, network analysis and machine learning techniques to build a ten-protein diagnostic signature of JE with >99% diagnostic accuracy. Pathways related to JE infection included neuronal damage, anti-apoptosis, heat shock and unfolded protein responses, cell adhesion, macrophage and dendritic cell activation as well as a reduced acute inflammatory response, hepatotoxicity, activation of coagulation, extracellular matrix and actin regulation. We verified the results by performing DIA LC-MS/MS in 16 (10%) of the samples, demonstrating 87% accuracy using the same model. Ultimately, antibody-based validation will be required, in a larger group of patients, in different locations and in field settings, to refine the list to 2-3 proteins that could be harnessed in a rapid diagnostic test.

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Proteomics of human biological fluids for biomarker discoveries: technical advances and recent applications

Cited by 52 publications

References 247 publications

Evaluation of pre-processing methods for tear fluid proteomics using the Olink platform

Evaluation of pre-processing methods for tear fluid proteomics using the Olink platform

Proteomics in Inherited Metabolic Disorders

Deep proteomics network and machine learning analysis of human cerebrospinal fluid in Japanese encephalitis virus infection

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