Evidence map›Paper›PMID 42530014›Full record

ArticlePlant physiology2026

Toward simple, rapid, and deep plant proteome analysis with an in-cell proteomics strategy.

Deji Adekanye, Jasmine Parks, Meghana Kusuru, Jeffrey L Caplan, Yanbao Yu

Abstract read
In one paragraph

Article in Plant physiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Deji AdekanyeDepartment of Biological Sciences, University of Delaware, Newark, DE 19716, United States.ORCID 0009-0006-0123-2120
Jasmine ParksDepartment of Chemistry and Biochemistry, University of Delaware, Newark, DE 19716, United States.ORCID 0009-0009-2862-9082
Meghana KusuruDepartment of Computer and Information Sciences, University of Delaware, Newark, DE 19716, United States.ORCID 0009-0009-5310-2573
Jeffrey L CaplanDepartment of Biological Sciences, University of Delaware, Newark, DE 19716, United States.ORCID 0000-0002-3991-0912
Yanbao YuDepartment of Chemistry and Biochemistry, University of Delaware, Newark, DE 19716, United States.ORCID 0000-0003-2994-1974

Funding

Predictive Modeling & Optimal Control Framework for Model-Based Epidemic Response in DelawareP20GM103446 · NIGMS · UNIVERSITY OF DELAWARE · PI Shawn W Polson · 2012 to 2026
$67.2M
This renovation project will create over 1455 sq. ft. of state- of-the-art reseaP20GM104316 · NIGMS · UNIVERSITY OF DELAWARE · PI FOX, JOSEPH M · 2014 to 2024
$26.8M
Understanding synovial macrophage inflamm-aging within osteoarthritisP20GM139760 · NIGMS · UNIVERSITY OF DELAWARE · PI DAWN M ELLIOTT · 2021 to 2026
$19.1M
Zeiss LSM710 Inverted Confocal MicroscopeS10OD016361 · OD · UNIVERSITY OF DELAWARE · PI CAPLAN, JEFFREY L · 2015 to 2015
$444k
NIGMS NIH HHS P20 GM103446NIGMS NIH HHS P20 GM104316NIGMS NIH HHS P20 GM139760NIH HHS S10 OD016361
6 · The paper itself

Abstract

While liquid chromatography-mass spectrometry (LCMS) has revolutionized plant proteomics over the past decade, plant sample preparation remains a major challenge due to rigid cell walls, abundant secondary metabolites, and wide dynamic range of protein abundance. These hurdles demand laborious tissue disruption, complex precipitation, and extensive cleanup prior to LCMS analysis, limiting the widespread adoption of proteomic technologies within the plant biology community. To overcome these barriers, we introduced an "in-cell proteomics" strategy that bypasses cell lysis and protein extraction by performing digestion directly inside methanol-fixed cells. We systematically benchmarked this strategy against conventional lysate-based workflows across 4 model plants (Arabidopsis thaliana, Nicotiana benthamiana, Zea mays, and Sorghum bicolor) and 3 tissue types (leaves, pollen, and seeds). Combined with minimal input material and single-shot LCMS, the in-cell approach consistently identified 9,000 to 12,000 proteins from leaves, 7,000 to 9,000 from pollen grains, and approximately 8,000 from seeds. Our comprehensive dataset demonstrates that this in-cell digestion approach substantially simplifies plant sample preparation while delivering proteomic performance equivalent to established workflows. Finally, to demonstrate the biological utility of this approach, we characterized the proteomes of N. benthamiana leaves infected with 2 fungal strains that exhibit different host specificities. Our in-depth proteomic data revealed distinct host response signatures differentiating the host-adapted Colletotrichum destructivum from the nonhost-adapted Colletotrichum sublineola strain. Overall, this study provides a simple, unbiased alternative for plant proteomic analysis that can be readily applied to tackle complex agricultural and physiological challenges in plant biology.

Indexed as

Plant ProteinsProteomeProteomicsArabidopsisLiquid Chromatography-Mass SpectrometryNicotianaPlant LeavesPollenSeedsSorghumZea maysPlant ProteinsProteome

Identifiers

PMID42530014
PMCPMC13544443

What OpenQuestion holds

Textmetadata
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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.