Evidence map›Paper›PMID 39974879›Full record

ArticlebioRxiv : the preprint server for biology2025

Simultaneous profiling of native-state proteomes and transcriptomes of neural cell types using proximity labeling.

Christina C Ramelow, Eric B Dammer, Hailian Xiao, Lihong Cheng, Prateek Kumar, Claudia Espinosa-Garcia, Maureen M Sampson, Ruth S Nelson, Sneha Malepati, Dilpreet Kour and 7 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Christina C RamelowDepartment of Neurology, Emory University, Atlanta, GA.ORCID 0000-0001-5443-1074
Eric B DammerCenter for Neurodegenerative Disease, Emory University.ORCID 0000-0003-2947-7606
Hailian XiaoDepartment of Neurology, Emory University, Atlanta, GA.
Lihong ChengCenter for Neurodegenerative Disease, Emory University.
Prateek KumarDepartment of Neurology, Yale University, New Haven, CT.
Claudia Espinosa-GarciaDepartment of Neurology, Yale University, New Haven, CT.ORCID 0000-0002-9909-9092
Maureen M SampsonDepartment of Human Genetics, Emory University.ORCID 0000-0003-1536-3229
Ruth S NelsonDepartment of Neurology, Yale University, New Haven, CT.
Sneha MalepatiDepartment of Neurology, Yale University, New Haven, CT.
Dilpreet KourDepartment of Neurology, Yale University, New Haven, CT.ORCID 0009-0006-4865-2376
Rashmi KumariDepartment of Neurology, Yale University, New Haven, CT.
Qi GuoCenter for Neurodegenerative Disease, Emory University.
Pritha BagchiEmory Integrated Proteomics Core, Emory University.ORCID 0000-0001-7229-9476
Duc M DuongDepartment of Biochemistry, Emory University.
Nicholas T SeyfriedDepartment of Neurology, Emory University, Atlanta, GA.ORCID 0000-0002-4507-624X
Steven A SloanDepartment of Human Genetics, Emory University.ORCID 0000-0001-7769-7684
Srikant RangarajuDepartment of Neurology, Emory University, Atlanta, GA.ORCID 0000-0003-2765-1500

Funding

Implementing a Maternal health and PRegnancy Outcomes Vision for Everyone (IMPROVE)UL1TR002378 · NCATS · EMORY UNIVERSITY · PI Andres J Garcia, Elizabeth O. Ofili · 2017 to 2026
$92.1M
Neuron and microglia-specific proteomic signatures of ERK mediated mechanisms of Alzheimer’s diseaseR01AG075820 · NIA · YALE UNIVERSITY · PI RANGARAJU, SRIKANT, SEYFRIED, NICHOLAS THOMAS · 2021 to 2025
$5.1M
Molecular Drivers of Human GliogenesisR01MH125956 · NIMH · EMORY UNIVERSITY · PI SLOAN, STEVEN A · 2021 to 2025
$3.0M
Microglia-specific proteomic mechanisms and biomarkers of neuroinflammation in Alzheimer’s diseaseR01AG071587 · NIA · YALE UNIVERSITY · PI RANGARAJU, SRIKANT · 2024 to 2025
$1.5M
Astrocyte-specific in vivo molecular signatures of APOE genetic risk in Alzheimer's diseaseF31AG079597 · NIA · EMORY UNIVERSITY · PI RAMELOW, CHRISTINA CATHERINE · 2023 to 2024
$97k
NCATS NIH HHS UL1 TR002378NIA NIH HHS F31 AG079597NIA NIH HHS R01 AG071587NIA NIH HHS R01 AG075820NIMH NIH HHS R01 MH125956
6 · The paper itself

Abstract

Deep molecular phenotyping of cells at transcriptomic and proteomic levels is an essential first step to understanding cellular contributions to development, aging, injury, and disease. Since proteome and transcriptome level abundances only modestly correlate with each other, complementary profiling of both is needed. We report a novel method called simultaneous protein and RNA -omics (SPARO) to capture the cell type-specific transcriptome and proteome simultaneously from both in vitro and in vivo experimental model systems. This method leverages the ability of biotin ligase, TurboID, to biotinylate cytosolic proteins including ribosomal and RNA-binding proteins, which allows enrichment of biotinylated proteins for proteomics as well as protein-associated RNA for transcriptomics. We validated this approach first using well-controlled in vitro systems to verify that the proteomes and transcriptomes obtained reflect the ground truth, bulk proteomes and transcriptomes. We also show that the effect of a biological stimulus (e.g., neuroinflammatory activation by lipopolysaccharide) can be faithfully captured. We also applied this approach to obtain native-state proteomes and transcriptomes from two key neural cell types, astrocytes and neurons, thereby validating the in vivo application of SPARO. Next, we used these data to interrogate protein-mRNA concordance and discordance across these cell types, providing insights into groups of molecular processes that exhibit uniform or cell type-specific patterns of mRNA-protein discordance.

Indexed as

astrocytesmicrogliamRNA-protein concordanceneuronsproteomicsProximity labelingtranscriptomics

Identifiers

PMID39974879
PMCPMC11838394

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

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.