Evidence map›Paper›PMID 41742681›Full record

ArticleProteomics2026

Single-Cell Nanodroplet Processing Proteomics Pipeline for Analysis of Human-Derived Microglia.

Ashley N Ives, James M Fulcher, Alex R Bautista, Reta Birhanu Kitata, Sarah M Williams, David A Bennett, Philip L De Jager, Vladislav A Petyuk

Abstract read
In one paragraph

Article in Proteomics, 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. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Ashley N IvesEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA.
James M FulcherEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA.
Alex R BautistaCenter For Translational and Computational Neuroimmunology, Department of Neurology & Taub Institute for Research on Alzheimer's disease and the Aging Brain, Columbia University Medical Center, New York, USA.
Reta Birhanu KitataBiological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA.
Sarah M WilliamsEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA.
David A BennettDepartment of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA.
Philip L De JagerCenter For Translational and Computational Neuroimmunology, Department of Neurology & Taub Institute for Research on Alzheimer's disease and the Aging Brain, Columbia University Medical Center, New York, USA.
Vladislav A PetyukBiological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA.

Funding

RISK FACTORS, PATHOLOGY, AND CLINICAL EXPRESSIONS OF ADR01AG015819 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1998 to 2024
$21.4M
Multi-omic network-directed proteoform discovery, dissection and functional validation to prioritize novel AD therapeutic targetsU01AG061356 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BENNETT, DAVID ALAN, DE JAGER, PHILIP L · 2018 to 2022
$13.7M
NIA NIH HHS R01 AG015819NIA NIH HHS U01 AG061356NIH National Institute P30 AG10161NIH National Institute P30 AG72975NIH National Institute R01 AG17917
6 · The paper itself

Abstract

Single-cell omics tools provide unique insights into heterogeneous cell populations and their responses to stimuli. For example, single-cell RNA sequencing has identified several transcriptionally distinct populations of microglia, which are resident immune cells of the central nervous system (CNS) that are responsive to CNS injury, infection, and neurodegeneration. To date, single-cell studies of microglia have focused on RNA-sequencing or cytometry by time of flight (CyTOF), which provide indirect readouts of protein abundance or quantification of a limited number of targets. Herein, we present a workflow based on FACS-assisted isolation, cryopreservation, and nanodroplet-based processing for single-cell mass spectrometry proteomics analysis of the postmortem human brain cortex-derived microglia. From a single microglial cell, 1039 proteins could be identified on average. As a proof-of-principle, we applied single-cell proteomics for exploring the heterogeneity of brain microglia at the cellular level. This pilot proteomics data partially recapitulates the prior microglia subtypes. Specifically, we determined that mitochondrial proteins, in particular members of NADH dehydrogenase (Complex I), cytochrome b-c1 (Complex III), cytochrome c oxidase (Complex IV), F1-ATPase (Complex V), and Na+/K+-ATPase complex, drive variation across microglia. This pipeline offers the potential for identifying functionally and analytically relevant protein targets for microglia in Alzheimer's disease and other neurological disorders. SIGNIFICANCE OF THE STUDY: Microglia are a key brain cell type that may contribute to pathogenesis in neurodegenerative disease. Transcriptomic profiling of microglia from the central nervous system of humans and animal models has identified several subtypes of microglia, and complementary proteomic profiling of microglia is likely to provide functionally and therapeutically relevant targets. Single-cell proteomics studies of human-derived microglia are lacking. This work describes a label-free, single-cell proteomics approach for microglia isolated by fluorescence-activated cell sorting from a human donor that yields comparable numbers of identifications in comparison to prior single-cell RNA sequencing studies of microglia. This approach holds promise for enabling large-scale proteomics-based subtyping of microglia and studying their roles in neurodegenerative diseases.

Indexed as

MicrogliaProteomeProteomicsSingle-Cell AnalysisFlow CytometryHumansProteomelabel‐free quantificationmicrogliasingle‐cell proteomics

Identifiers

PMID41742681
PMCPMC13106911

What OpenQuestion holds

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LicenceCC BY
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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.