Evidence map›Paper›PMID 42037520›Full record

ArticleCurrent protocols2026

Cell Painting PLUS: An Iterative Staining-Elution Protocol for High-Content Phenotypic Screenings.

Marlene Wedler, Elena von Coburg, Jose M Muino, Lars Valentin, Nils Körber, Sebastian Dunst, Shu Liu

Abstract read
In one paragraph

Article in Current protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Marlene WedlerGerman Centre for the Protection of Laboratory Animals (Bf3R) and Experimental Toxicology, German Federal Institute for Risk Assessment (BfR), Berlin, Germany.ORCID https://orcid.org/0009-0004-4702-1324
Elena von CoburgGerman Centre for the Protection of Laboratory Animals (Bf3R) and Experimental Toxicology, German Federal Institute for Risk Assessment (BfR), Berlin, Germany.ORCID https://orcid.org/0009-0001-8546-8854
Jose M MuinoGerman Centre for the Protection of Laboratory Animals (Bf3R) and Experimental Toxicology, German Federal Institute for Risk Assessment (BfR), Berlin, Germany.ORCID https://orcid.org/0000-0002-6403-7262
Lars ValentinInnovation Centre Food Chain Modelling and Artificial Intelligence, Department Information Technology, German Federal Institute for Risk Assessment (BfR), Berlin, Germany.
Nils KörberCentre for Artificial Intelligence in Public Health Research, Robert Koch Institute, Berlin, Germany.ORCID https://orcid.org/0009-0003-2506-4297
Sebastian DunstGerman Centre for the Protection of Laboratory Animals (Bf3R) and Experimental Toxicology, German Federal Institute for Risk Assessment (BfR), Berlin, Germany.ORCID https://orcid.org/0000-0002-3414-1640
Shu LiuGerman Centre for the Protection of Laboratory Animals (Bf3R) and Experimental Toxicology, German Federal Institute for Risk Assessment (BfR), Berlin, Germany.ORCID https://orcid.org/0000-0002-2904-0271

Funding

European Union's Horizon 2020 Research and Innovation Programme 964537(RISK-HUNT3RProject)German Federal Ministry of Research, Technology and Space (BMFTR) 16LW0137K(MORPHEUS)
6 · The paper itself

Abstract

Cell Painting (CP) methods use a combination of fluorescent dyes to label multiple cellular compartments simultaneously, enabling the comprehensive analysis of phenotypic changes through morphological profiling. Here, we present a detailed protocol for the Cell Painting PLUS (CPP) method along with an automated image and data analysis strategy. In CPP, the iterative staining, elution, and re-staining of cells with seven fluorescent dyes enable multiplexed analysis of nine cellular compartments and organelles. Each dye is captured in individual imaging channels to specifically distinguish effects on the plasma membrane, actin cytoskeleton, cytoplasmic and nucleolar RNA, lysosomes, nuclear DNA, endoplasmic reticulum, mitochondria, and Golgi apparatus. During the image analysis procedure, 894 morphological features (readouts) are extracted from single cells to generate comprehensive phenotypic profiles that resemble morphological perturbations. For efficient processing of the extracted features, we provide an automated data analysis workflow, which includes quality control, data normalization, and various data visualization tools. This workflow is based on a customized CPPAnalyzer Jupyter notebook and a CPPManager KNIME workflow, which can be easily applied without any special bioinformatics knowledge. In this way, CPP expands the multiplexing capacity, customizability, and, importantly, organelle specificity of the available CP-based screening methods. © 2026 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Seeding of U2OS, MCF-7, or HepG-2 cells in multiwell plates and treatment of cells with compounds Support Protocol 1: Preparation of assay-ready compound plate Alternate Protocol: Seeding and differentiation of primary RPTEC-TERT1 cells in multiwell plates Basic Protocol 2: Staining and imaging of cells using Cell Painting PLUS Basic Protocol 3: Image analysis Basic Protocol 4: Data normalization and data quality control Basic Protocol 5: Visualization of data using CPPManager KNIME workflow.

Indexed as

High-Throughput Screening AssaysStaining and LabelingFluorescent DyesHumansImage Processing, Computer-AssistedPhenotypeFluorescent Dyescell‐based assaysCell Painting PLUS (CPP)high‐throughput high‐content screeningsmorphological profilingnew approach methodologies (NAMs)

Identifiers

PMID42037520
PMCPMC13112130

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Registered trials

None linked

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.