Evidence map›Paper›PMID 31427819›Full record

ArticleNature biotechnology2019

Immuno-SABER enables highly multiplexed and amplified protein imaging in tissues.

Sinem K Saka, Yu Wang, Jocelyn Y Kishi, Allen Zhu, Yitian Zeng, Wenxin Xie, Koray Kirli, Clarence Yapp, Marcelo Cicconet, Brian J Beliveau and 8 more

Abstract read
In one paragraph

Article in Nature biotechnology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 253 papers.

0numbers the graph read from it
0cells of the map it votes in
253citing 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

253 citing papers in PubMed.

  1. Immunophenotyping by Spatial Biology.Methods in molecular biology (Clifton, N.J.) · 2027
    Article
  2. Article
  3. Review
  4. Review
  5. Emerging technologies in the spatial proteomics landscape.Analytical and bioanalytical chemistry · 2026
    Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
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  15. Article
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  18. Article
  19. A Guide for Spatial Omics Technologies: Innovation, Evaluation, and Application.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  20. Review

193 more citing papers are in PubMed but not listed here.

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

18 authors.

Sinem K Saka *Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA. sinem.saka@wyss.harvard.edu.
Yu Wang *Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA. yuwang01@fas.harvard.edu.ORCID http://orcid.org/0000-0001-9764-0546
Jocelyn Y KishiWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
Allen ZhuWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
Yitian ZengWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
Wenxin XieWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
Koray KirliDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Clarence YappImage and Data Analysis Core, Harvard Medical School, Boston, MA, USA.
Marcelo CicconetImage and Data Analysis Core, Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0003-2649-1509
Brian J BeliveauWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.ORCID http://orcid.org/0000-0003-1314-3118
Sylvain W LapanDepartment of Genetics, Harvard Medical School, Boston, MA, USA.
Siyuan YinWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
Millicent LinWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
Edward S BoydenMedia Lab, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-0419-3351
Pascal S KaeserDepartment of Neurobiology, Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0002-1558-1958
German PihanPathology Department, Beth Israel Deaconess Medical Center, Boston, MA, USA.
George M ChurchWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
Peng YinWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA. py@hms.harvard.edu.ORCID http://orcid.org/0000-0002-2769-6357

Funding

Center for Genomically Engineered OrgansRM1HG008525 · NHGRI · HARVARD MEDICAL SCHOOL · PI CHURCH, GEORGE M · 2015 to 2019
$10.2M
High-throughput single-molecule protein identification via super-resolution imagingDP1GM133052 · NIGMS · HARVARD UNIVERSITY · PI YIN, PENG · 2018 to 2022
$6.6M
Dissecting the assembly of vertebrate neurotransmitter release sites-Research Supplements to Promote Diversity in Health-Related ResearchR01MH113349 · NIMH · HARVARD MEDICAL SCHOOL · PI Pascal Simon Kaeser · 2017 to 2026
$6.1M
Molecular Dissection of Active Zone Functions in Neurotransmitter ReleaseR01NS083898 · NINDS · HARVARD MEDICAL SCHOOL · PI Pascal Simon Kaeser · 2014 to 2026
$5.9M
Super-Resolution ImagingP30NS072030 · NINDS · HARVARD MEDICAL SCHOOL · PI REGEHR, WADE G · 2011 to 2020
$5.8M
Exploring a Novel Paradigm of Schizophrenia and Bipolar DisorderR01MH113279 · NIMH · HARVARD MEDICAL SCHOOL · PI CHURCH, GEORGE M, YANKNER, BRUCE A · 2016 to 2020
$4.7M
Super-resolution imaging via programmable autonomous blinkingR01EB018659 · NIBIB · HARVARD MEDICAL SCHOOL · PI YIN, PENG · 2013 to 2017
$3.3M
Decoding chromosome structure with multiplexed super-resolution microscopyR01GM124401 · NIGMS · HARVARD UNIVERSITY · PI YIN, PENG · 2018 to 2021
$2.5M
Ultra-Multiplexed Nanoscale In Situ Proteomics for Understanding Synapse TypesU01MH106011 · NIMH · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BATHE, MARK, BOYDEN, EDWARD S. · 2014 to 2016
$2.2M
High-Throughput, Highly Multiplexed In Situ Proteomic Imaging of Human TissuesUG3HL145600 · NHLBI · HARVARD UNIVERSITY · PI YIN, PENG · 2018 to 2019
$833k
Regulation of Cell Type Identity in Retinal Bipolar Cell PrecursorsK99EY028215 · NEI · HARVARD MEDICAL SCHOOL · PI LAPAN, SYLVAIN · 2017 to 2018
$194k
NEI NIH HHS K99 EY028215NHGRI NIH HHS RM1 HG008525NHLBI NIH HHS UG3 HL145600NIBIB NIH HHS R01 EB018659NIGMS NIH HHS DP1 GM133052NIGMS NIH HHS R01 GM124401NIMH NIH HHS R01 MH113279NIMH NIH HHS R01 MH113349NIMH NIH HHS U01 MH106011NINDS NIH HHS P30 NS072030NINDS NIH HHS R01 NS083898
6 · The paper itself

Abstract

Spatial mapping of proteins in tissues is hindered by limitations in multiplexing, sensitivity and throughput. Here we report immunostaining with signal amplification by exchange reaction (Immuno-SABER), which achieves highly multiplexed signal amplification via DNA-barcoded antibodies and orthogonal DNA concatemers generated by primer exchange reaction (PER). SABER offers independently programmable signal amplification without in situ enzymatic reactions, and intrinsic scalability to rapidly amplify and visualize a large number of targets when combined with fast exchange cycles of fluorescent imager strands. We demonstrate 5- to 180-fold signal amplification in diverse samples (cultured cells, cryosections, formalin-fixed paraffin-embedded sections and whole-mount tissues), as well as simultaneous signal amplification for ten different proteins using standard equipment and workflows. We also combined SABER with expansion microscopy to enable rapid, multiplexed super-resolution tissue imaging. Immuno-SABER presents an effective and accessible platform for multiplexed and amplified imaging of proteins with high sensitivity and throughput.

Indexed as

Staining and LabelingAnimalsAntibodiesCell LineDNADNA Barcoding, TaxonomicFluorescent DyesHumansImmunohistochemistryIn Situ Hybridization, FluorescenceMiceMicroscopy, FluorescenceProteinsRetinaAntibodiesDNAFluorescent DyesProteins

Identifiers

PMID31427819
PMCPMC6728175

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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.