Evidence map›Paper›PMID 42020410›Full record

ArticleNature communications2026

High-speed multiplexed DNA-PAINT imaging of nuclear organization using an expanded sequence repertoire.

Abhinav Banerjee, Micky Anand, Mansi Srivastava, Vedanth Shree Vidwath, Mahipal Ganji

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Abhinav Banerjee *Department of Biochemistry, Indian Institute of Science, Malleswaram, Bangalore, India.ORCID 0000-0002-3985-3014
Micky Anand *Department of Biochemistry, Indian Institute of Science, Malleswaram, Bangalore, India.ORCID 0000-0002-0050-5143
Mansi SrivastavaDepartment of Biochemistry, Indian Institute of Science, Malleswaram, Bangalore, India.
Vedanth Shree VidwathDepartment of Biochemistry, Indian Institute of Science, Malleswaram, Bangalore, India.
Mahipal GanjiDepartment of Biochemistry, Indian Institute of Science, Malleswaram, Bangalore, India. ganji@iisc.ac.in.ORCID 0000-0001-8176-3322

Funding

DBT India Alliance (Wellcome Trust/DBT India Alliance) IA/I/21/2/505928Department of Biotechnology, Ministry of Science and Technology (DBT) BT/PR40186/BTIS/137/3/2020
6 · The paper itself

Abstract

DNA-Points Accumulation for Imaging in Nanoscale Topography (DNA-PAINT) enables multiplexed super-resolution imaging of biological samples. We expand the repertoire of speed-optimized DNA-PAINT sequences to visualize up to twelve targets in a sequential manner. By implementing Exchange-PAINT protocol, we demonstrate 12-plex super-resolved imaging of DNA origami nanostructures within four hours with a localization precision of 3-5 nm. Using these sequences, we demonstrate 9-plex super-resolution imaging of diverse nuclear targets. Further, we present a comprehensive analysis pipeline to quantify nanoscale chromatin organization in single cells. Combining multiplexed imaging with this pipeline enabled us to capture loss of chromatin contacts with nuclear speckles upon global transcription inhibition. This work highlights the ability to simultaneously image multiple targets at accelerated speeds while maintaining high spatial resolution, enabling in-depth mapping of the nuclear landscape. These speed-optimized imager sequences for multiplexed super-resolution imaging will drive its further adoption for diverse cellular imaging applications.

Indexed as

Cell NucleusDNAChromatinDNA NanostructuresHumansMicroscopy, FluorescenceChromatinDNA

Identifiers

PMID42020410
PMCPMC13103312

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.