Skip to content
DraconiticResearch
Search Sources API
197,768 studies31 sourcesUpdated 20 min ago
Peer-reviewedCC BY 4.0Immunology

Evaluation of Methods for Identifying Human Monocytes by Flow Cytometry: TLR2 May be an Optimal Marker

  • Mie Wolff Kristensen1
  • Katrine Skjøt Harbo1
  • Thomas Vorup‐Jensen1
  • Marianne Hokland1
  • Morten Nørgaard Andersen1,2,3,4
4 affiliations
  1. 1Department of Biomedicine Aarhus University Aarhus Denmark
  2. 2Department of Hematology Aarhus University Hospital Aarhus Denmark
  3. 3Department of Clinical Medicine Aarhus University Aarhus Denmark
  4. 4Department of Molecular Medicine (MOMA) Aarhus University Hospital Aarhus Denmark
Read full textPDFDOICite

Abstract

Monocytes play crucial roles in the pathobiology of a wide range of medical conditions, including infection, autoimmunity, cardiovascular disease, and malignancies. Studies using flow cytometry revealed the complexity of monocyte biology, including identification of three human monocyte subsets: classical (CD14pos CD16neg), intermediate (CD14pos CD16pos) and non‐classical (CD14neg/dim CD16pos) monocytes. Still, gating strategies used for identification of monocytes by flow cytometry vary substantially between studies, which may significantly impact results and hamper reproducibility. However, to our knowledge, no previous study has evaluated several different gating strategies for identification of the total circulating monocyte population in humans. Here, healthy donor peripheral blood mononuclear cells (PBMCs, n = 10) were analysed by flow cytometry to compare seven commonly used gating strategies for defining human monocytes: (1) negative selection (CD3neg CD19neg CD56neg CD66neg), (2) FSC‐SSC, (3) CD14pos, (4) CD64pos, (5) HLA‐DRpos, (6) CD14—HLA‐DR and (7) TLR2pos. We show that the different gating strategies significantly impacted the enumeration of non‐classical monocytes, but less so for classical and intermediate monocyte populations. Compared to negative selection gating (considered the reference standard), the FSC‐SSC‐based gating showed the highest degree of contamination by other cell types, whereas CD14pos, CD64pos, CD14‐HLA‐DR and HLA‐DRpos gating showed highest degree of exclusion of monocytes, particularly non‐classical monocytes. In comparison, TLR2pos gating showed both the least contamination and least erroneous exclusion of monocytes when compared to negative selection gating. These results based on ‘manual gating’ were supported by more objective t‐SNE and clustering analyses. In conclusion, TLR2pos gating and negative selection‐based gating displayed both minimal contamination and exclusion of true monocytes, with TLR2pos gating yielding the overall purest monocyte population. Thus, adapting to more uniform gating strategies for monocyte analysis, such as a TLR2 based gating strategy, may increase data quality and reproducibility between laboratories.

Related

  1. FlowLOT: Linearized Optimal Transport for Flow Cytometry Analysis
    Naqib Sad Pathan, Mohammad Shifat-E-Rabbi, Kristofor E. Pas +3
    arXivPreprintarXiv licenceFull textBioinformatics & computational biologyarXiv
  2. Identifying the source population of naturally recolonised rhinoceros (Rhinoceros unicornis) in Laokhowa-Burhachapori Wildlife Sanctuary, Assam, through multidisciplinary methods
    S. Kumar, J. Soun, D. Biswas +5
    bioRxivPreprintAll rights reservedFull textEcologybioRxiv
  3. Identifying future geriatric nurses: psychometric evaluation of the German Willingness to Work with Elderly People Scale among nursing students.
    Shengze Zhi, Burcu Akpınar Söylemez, Jiao Sun +1
    Frontiers in psychologyPeer-reviewedCC BYFull textNeuroscienceEurope PMCPMC
  4. Evaluation of methods for AlphaFold-based integrative modeling
    K. Majila, S. Viswanath
    bioRxivPreprintCC BYFull textBioinformatics & computational biologybioRxiv
  5. Systematic evaluation of transcript normalization methods and quantification pipelines across long-read sequencing platforms
    A. Paniagua, F. Jetzinger, S. Tarazona +1
    bioRxivPreprintCC BY-NCFull textBioinformatics & computational biologybioRxiv

Cite

BibTeXRIS
BibTeX
@article{kristensen2026evaluation,
  title = {{Evaluation of Methods for Identifying Human Monocytes by Flow Cytometry: TLR2 May be an Optimal Marker}},
  author = {Mie Wolff Kristensen and Katrine Skjøt Harbo and Thomas Vorup‐Jensen and Marianne Hokland and Morten Nørgaard Andersen},
  journal = {Immunology},
  year = {2026},
  month = sep,
  doi = {10.1111/imm.70195},
  url = {https://doi.org/10.1111/imm.70195},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Evaluation of Methods for Identifying Human Monocytes by Flow Cytometry: TLR2 May be an Optimal Marker
AU  - Mie Wolff Kristensen
AU  - Katrine Skjøt Harbo
AU  - Thomas Vorup‐Jensen
AU  - Marianne Hokland
AU  - Morten Nørgaard Andersen
PY  - 2026
DA  - 2026/09/07
JO  - Immunology
DO  - 10.1111/imm.70195
UR  - https://doi.org/10.1111/imm.70195
AB  - Monocytes play crucial roles in the pathobiology of a wide range of medical conditions, including infection, autoimmunity, cardiovascular disease, and malignancies. Studies using flow cytometry revealed the complexity of monocyte biology, including identification of three human monocyte subsets: classical (CD14pos CD16neg), intermediate (CD14pos CD16pos) and non‐classical (CD14neg/dim CD16pos) monocytes. Still, gating strategies used for identification of monocytes by flow cytometry vary substantially between studies, which may significantly impact results and hamper reproducibility. However, to our knowledge, no previous study has evaluated several different gating strategies for identification of the total circulating monocyte population in humans. Here, healthy donor peripheral blood mononuclear cells (PBMCs, n = 10) were analysed by flow cytometry to compare seven commonly used gating strategies for defining human monocytes: (1) negative selection (CD3neg CD19neg CD56neg CD66neg), (2) FSC‐SSC, (3) CD14pos, (4) CD64pos, (5) HLA‐DRpos, (6) CD14—HLA‐DR and (7) TLR2pos. We show that the different gating strategies significantly impacted the enumeration of non‐classical monocytes, but less so for classical and intermediate monocyte populations. Compared to negative selection gating (considered the reference standard), the FSC‐SSC‐based gating showed the highest degree of contamination by other cell types, whereas CD14pos, CD64pos, CD14‐HLA‐DR and HLA‐DRpos gating showed highest degree of exclusion of monocytes, particularly non‐classical monocytes. In comparison, TLR2pos gating showed both the least contamination and least erroneous exclusion of monocytes when compared to negative selection gating. These results based on ‘manual gating’ were supported by more objective t‐SNE and clustering analyses. In conclusion, TLR2pos gating and negative selection‐based gating displayed both minimal contamination and exclusion of true monocytes, with TLR2pos gating yielding the overall purest monocyte population. Thus, adapting to more uniform gating strategies for monocyte analysis, such as a TLR2 based gating strategy, may increase data quality and reproducibility between laboratories.
SN  - 0019-2805
SN  - 1365-2567
ER  -