Evidence map›Paper›PMID 39596304›Full record

ArticleInternational journal of molecular sciences2024

High-Throughput Tear Proteomics via In-Capillary Digestion for Biomarker Discovery.

James Xiao, Kyla Frenia, Kathleen C Garwood, Jeremy Kimmel, Leanne T Labriola

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

James XiaoRetina Department, Sewickley Eye Group, Sewickley, PA 15143, USA.
Kyla FreniaDepartment of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA.ORCID 0009-0001-2713-918X
Kathleen C GarwoodDepartment of Decision and System Sciences, Saint Joseph's University, Philadelphia, PA 19131, USA.
Jeremy KimmelDepartment of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA.
Leanne T LabriolaRetina Department, Sewickley Eye Group, Sewickley, PA 15143, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tear fluid has emerged as a valuable resource for biomarker discovery; however, the limited sample volume, the dynamic composition, and the variability introduced by collection methods all present significant challenges to the analysis and interpretation of the results. A majority of tear proteomic studies have utilized Schirmer strips for tear fluid collection; however, microcapillary collection can provide a superior collection method for proteomic studies when analysis procedures are optimized. We developed a novel, high-throughput in-capillary trypsin digestion workflow that requires as little as 0.5 μL of tear fluid for bottom-up shotgun proteomics. The use of a single microcentrifuge tube for both tear collection and sample processing simplifies sample handling and minimizes both the sample loss and experimental errors associated with sample transfers. This streamlined approach also reduces sample processing time to under 2 h before overnight trypsin digestion, compared to the 5-8 h required by the other methods. Our method uses liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify more proteins with greater efficiency than the existing techniques. With this workflow, we identified 500-800 proteins per 0.5 μL sample without peptide fractionation, allowing for at least three technical replicates. The results showed a four-fold increase in the number of proteins identified in the samples. This approach validates the use of microcapillary tear collection, and the innovative processing technique significantly increases the throughput of tear proteomics for biomarker discovery.

Indexed as

BiomarkersProteomicsTandem Mass SpectrometryTearsChromatography, LiquidHigh-Throughput Screening AssaysHumansProteomeTrypsinBiomarkersProteomeTrypsinbiomarker discoveryLC–MS/MSPOCTpoint-of-care testingtear biomarkertear proteomics

Identifiers

PMID39596304
PMCPMC11594680

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.