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Updated: May 2, 2026
Characterization of Human Monocyte Subsets by Whole Blood Flow Cytometry Analysis
Published on: October 17, 2018
Properties of human blood monocytes. I. CD91 expression and log orthogonal light scatter provide a robust method to
Dorothy Hudig1, Kenneth W Hunter, W John Diamond
1Department of Microbiology and Immunology, University of Nevada School of Medicine, Reno, Nevada, 89557.
Insights
CD91 is a superior marker for identifying human monocytes compared to CD14 or CD33. Flow cytometry using anti-CD91 offers more accurate monocyte counts than standard clinical instruments.
Area of Science:
- Immunology
- Cell Biology
Background:
- Accurate identification of human blood monocytes is crucial for immunological studies.
- Existing methods using markers like CD14 may lead to undercounting monocytes.
- Developing reliable monocyte identification markers is an ongoing research area.
Purpose of the Study:
- To identify a more consistent and accurate marker for human monocyte identification.
- To compare the efficacy of CD91, CD14, and CD33 as monocyte markers.
- To evaluate flow cytometry with anti-CD91 against standard clinical hematology analyzers.
Main Methods:
- Blood samples from 200 healthy adults were analyzed.
- Flow cytometry (FCM) was performed using multiple antibody combinations.
- A Beckman LH750 hematology analyzer was used for comparison.
Main Results:
- CD91 was consistently expressed on monocytes across subjects.
- A significant portion of monocytes (14.3%) showed low or negligible CD14 expression, leading to undercounting by FCM.
- CD33 expression varied considerably among subjects.
- The hematology analyzer systematically overcounted monocytes.
Conclusions:
- CD91 is a more reliable marker for monocyte identification than CD14 or CD33.
- FCM with anti-CD91 provides more accurate monocyte enumeration than current clinical CBC instruments.
- Combining anti-CD91 with anti-CD14 and anti-CD16 aids in identifying diagnostically relevant monocyte subsets.
Background:
This study was designed to improve identification of human blood monocytes by using antibodies to molecules that occur consistently on all stages of monocyte development and differentiation.
Methods:
We examined blood samples from 200 healthy adults without clinically diagnosed immunological abnormalities by flow cytometry (FCM) with multiple combinations of antibodies and with a hematology analyzer (Beckman LH750).
Results:
CD91 (α2 -macroglobulin receptor) was expressed only by monocytes and to a consistent level among subjects [mean median fluorescence intensity (MFI) = 16.2 ± 3.2]. Notably, only 85.7 ± 5.82% of the CD91(+) monocytes expressed high levels of the classical monocyte marker CD14, with some CD91(+) CD16(+) cells having negligible CD14, indicating that substantial FCM under-counts will occur when monocytes are identified by high CD14. CD33 (receptor for sialyl conjugates) was co-expressed with CD91 on monocytes but CD33 expression varied by nearly ten-fold among subjects (mean MFI = 17.4 ± 7.7). In comparison to FCM analyses, the hematology analyzer systematically over-counted monocytes and eosinophils while lymphocyte and neutrophil differential values generally agreed with FCM methods.
Conclusions:
CD91 is a better marker to identify monocytes than CD14 or CD33. Furthermore, FCM (with anti-CD91) identifies monocytes better than a currently used clinical CBC instrument. Use of anti-CD91 together with anti-CD14 and anti-CD16 supports the identification of the diagnostically significant monocyte populations with variable expression of CD14 and CD16.
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