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Quantitative whole-cell MALDI-TOF MS fingerprints distinguishes human monocyte sub-populations activated by distinct microbial ligands
BACKGROUND: Conventionally, human monocyte sub-populations are classified according to surface marker expression into classical (CD14(++)CD16(−)), intermediate (CD14(++)CD16(+)) and non-classical (CD14(+)CD16(++)) lineages. The involvement of non-classical monocytes, also referred to as proinflammat...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4425930/ https://www.ncbi.nlm.nih.gov/pubmed/25887592 http://dx.doi.org/10.1186/s12896-015-0140-1 |
Sumario: | BACKGROUND: Conventionally, human monocyte sub-populations are classified according to surface marker expression into classical (CD14(++)CD16(−)), intermediate (CD14(++)CD16(+)) and non-classical (CD14(+)CD16(++)) lineages. The involvement of non-classical monocytes, also referred to as proinflammatory monocytes, in the pathophysiology of diseases including diabetes mellitus, atherosclerosis or Alzheimer’s disease is well recognized. The development of novel high-throughput methods to capture functional states within the different monocyte lineages at the whole cell proteomic level will enable real time monitoring of disease states. RESULTS: We isolated and characterized (pan-) monocytes, mostly composed of classical CD16(−) monocytes, versus autologous CD16(+) subpopulations from the blood of healthy human donors (n = 8) and compared their inflammatory properties in response to lipopolysaccharides and M.tuberculosis antigens by multiplex cytokine profiling. Following resting and in vitro antigenic stimulation, cells were recovered and subjected to whole-cell mass spectrometry analysis. This approach identified the specific presence/absence of m/z peaks and therefore potential biomarkers that can discriminate pan-monocytes from their CD16 counterparts. Furthermore, we found that semi-quantitative data analysis could capture the subtle proteome changes occurring upon microbial stimulation that differentiate resting, from lipopolysaccharides or M. tuberculosis stimulated monocytic samples. CONCLUSIONS: Whole-cell mass spectrometry fingerprinting could efficiently distinguish monocytic sub-populations that arose from a same hematopoietic lineage. We also demonstrate for the first time that mass spectrometry signatures can monitor semi-quantitatively specific activation status in response to exogenous stimulation. As such, this approach stands as a fast and efficient method for the applied immunology field to assess the reactivity of potentially any immune cell types that may sustain health or promote related inflammatory diseases. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12896-015-0140-1) contains supplementary material, which is available to authorized users. |
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