Evidence map›Paper›PMID 33199915›Full record

ArticleNature chemical biology2021

Cell type-selective secretome profiling in vivo.

Wei Wei, Nicholas M Riley, Andrew C Yang, Joon T Kim, Stephanie M Terrell, Veronica L Li, Marta Garcia-Contreras, Carolyn R Bertozzi, Jonathan Z Long

Open access · greenAbstract read
In one paragraph

Article in Nature chemical biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers.

0numbers the graph read from it
0cells of the map it votes in
83citing papers in PubMed
7.5field-weighted citation impact, top 2% of its field
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

83 citing papers in PubMed, 132 citations in OpenAlex.

  1. Review
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  9. HNature chemical biology · 2026
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23 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

9 authors at 3 institutions in 1 country.

Wei Wei *Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-8110-0705
Nicholas M Riley *Stanford ChEM-H, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-1536-2966
Andrew C YangDepartment of Bioengineering, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-6756-4746
Joon T KimDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Stephanie M TerrellDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-7776-4621
Veronica L LiDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Marta Garcia-ContrerasDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-8014-7966
Carolyn R BertozziStanford ChEM-H, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-4482-2754
Jonathan Z LongDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA. jzlong@stanford.edu.ORCID http://orcid.org/0000-0003-2631-7463
Stanford University · USHoward Hughes Medical Institute · USStanford Medicine · US

Funding

Stanford Islet Research CoreP30DK116074 · NIDDK · STANFORD UNIVERSITY · PI HASSAN CHAIB · 2017 to 2026
$19.5M
Chemical interrogation of metabolic tissue crosstalkDP1DK130641 · NIDDK · STANFORD UNIVERSITY · PI LONG, JONATHAN Z · 2021 to 2025
$3.9M
Chemical control of energy metabolism by N-acyl amino acidsR01DK124265 · NIDDK · STANFORD UNIVERSITY · PI LONG, JONATHAN Z · 2020 to 2024
$2.0M
Stanford Chem-H Chemistry/Biology Interface Predoctoral Training ProgramT32GM120007 · NIGMS · STANFORD UNIVERSITY · PI BERTOZZI, CAROLYN · 2016 to 2020
$1.2M
CIRCULATING FACTORS THAT REGULATE BROWN AND BEIGE FATR00DK105203 · NIDDK · STANFORD UNIVERSITY · PI LONG, JONATHAN Z · 2018 to 2020
$728k
Uniting Mass Spectrometry and Glycoscience to Investigate Cancer BiologyK00CA212454 · NCI · STANFORD UNIVERSITY · PI RILEY, NICHOLAS M · 2018 to 2021
$331k
Circulating Factors that Regulate Brown and Beige FatK99DK105203 · NIDDK · DANA-FARBER CANCER INST · PI LONG, JONATHAN Z · 2015 to 2016
$182k
NCI NIH HHS K00 CA212454NIDDK NIH HHS DP1 DK130641NIDDK NIH HHS K99 DK105203NIDDK NIH HHS P30 DK116074NIDDK NIH HHS R00 DK105203NIDDK NIH HHS R01 DK124265NIGMS NIH HHS T32 GM120007
6 · The paper itself

Abstract

Secreted polypeptides are a fundamental axis of intercellular and endocrine communication. However, a global understanding of the composition and dynamics of cellular secretomes in intact mammalian organisms has been lacking. Here, we introduce a proximity biotinylation strategy that enables labeling, detection and enrichment of secreted polypeptides in a cell type-selective manner in mice. We generate a proteomic atlas of hepatocyte, myocyte, pericyte and myeloid cell secretomes by direct purification of biotinylated secreted proteins from blood plasma. Our secretome dataset validates known cell type-protein pairs, reveals secreted polypeptides that distinguish between cell types and identifies new cellular sources for classical plasma proteins. Lastly, we uncover a dynamic and previously undescribed nutrient-dependent reprogramming of the hepatocyte secretome characterized by the increased unconventional secretion of the cytosolic enzyme betaine-homocysteine S-methyltransferase (BHMT). This secretome profiling strategy enables dynamic and cell type-specific dissection of the plasma proteome and the secreted polypeptides that mediate intercellular signaling.

Indexed as

AnimalsBetaine-Homocysteine S-MethyltransferaseBiotinBiotinylationBlood ProteinsGene ExpressionHEK293 CellsHepatocytesHumansInjections, IntraperitonealMaleMiceMice, Inbred C57BLMuscle CellsMyeloid CellsOrgan SpecificityBetaine-Homocysteine S-MethyltransferaseBhmt protein, mouseBiotinBlood ProteinsProteome

Identifiers

PMID33199915
PMCPMC7904581
OpenAlexW3099296701

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.