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Multicolour flow cytometry (MFC) is used to measure multiple cellular markers at the single-cell level. Cellular markers may be coloured with different panels of fluorescently-labelled antibodies to enable cell identification or the detection of activated cells in pre-defined, gated’ specific cell subsets. The number of markers that can be used per measurement is technologically limited however, requiring every panel to be analysed in a separate aliquot measurement. The combined analyses of these dedicated panels may enhance the predictive ability of these measurements and could enrich the interpretation of the immunological information. Here we introduce a fusion method for MFC data, based on DAMACY (Discriminant Analysis of Multi-Aspect Cytometry data), which can combine information from complementary panels. This approach leads to both enhanced predictions and clearer interpretations in comparison with the analysis of separate measurements. We illustrate this method using two datasets: the response of neutrophils evoked by a systemic endotoxin challenge and the activated immune status of the innate cells, T cells and B cells in obese versus lean individuals. The data fusion approach was able to detect cells that do not individually show a difference between clinical phenotypes but do play a role in combination with other cells. This research received funding from the Netherlands Organization for Scientific Research (NWO) in the framework of the Technology Area COAST of the Fund New Chemical Innovations. Functions for Matlab are available at http://www.ru.nl/science/analyticalchemistry/research/software/.

Clinical complications of atherosclerosis are almost exclusively linked to destabilization of the atherosclerotic plaque. Batf3-dependent dendritic cells specialize in cross-presentation of necrotic tissue-derived epitopes to directly activate cytolytic CD8 Tcells. The mature plaque (necrotic, containing dendritic cells and CD8 Tcells) could offer the ideal environment for cross-presentation, resulting in cytotoxic immunity and plaque destabilization. Ldlr(-/-) mice were transplanted with batf3(-/-) or wt bone marrow and put on a western type diet. Hematopoietic batf3 deficiency sharply decreased CD8α(+) DC numbers in spleen and lymph nodes (80%; P 0,001). Concordantly, batf3(-/-) chimeras had a 75% reduction in OT-I cross-priming capacity in vivo. Batf3(-/-) chimeric mice did not show lower Tcell or other leukocyte subset numbers. Despite dampened cross-presentation capacity, batf3(-/-) chimeras had equal atherosclerosis burden in aortic arch and root. Likewise, batf3(-/-) chimeras and wt mice revealed no differences in parameters of plaque stability: plaque Tcell infiltration, cell death, collagen composition, and macrophage and vascular smooth muscle cell content were unchanged. These results show that CD8α(+) DC loss in hyperlipidemic mice profoundly reduces cross-priming ability, nevertheless it does not influence lesion development. Taken together, we clearly demonstrate that CD8α(+) DC-mediated cross-presentation does not significantly contribute to atherosclerotic plaque formation and stability.

Flow Cytometry is an analytical technology to simultaneously measure multiple markers per single cell. Ten thousands to millions of single cells can be measured per sample and each sample may contain a different number of cells. All samples may be bundled together, leading to a ‘multi-set’ structure. Many multivariate methods have been developed for Flow Cytometry data but none of them considers this structure in their quantitative handling of the data. The standard pre-processing used by existing multivariate methods provides models mainly influenced by the samples with more cells, while such a model should provide a balanced view of the biomedical information within all measurements. We propose an alternative ‘multi-set’ preprocessing that corrects for the difference in number of cells measured, balancing the relative importance of each multi-cell sample in the data while using all data collected from these expensive analyses. Moreover, one case example shows how multi-set pre-processing may benefit removal of undesired measurement-to-measurement variability and another where class-based multi-set pre-processing enhances the studied response upon comparison to the control reference samples. Our results show that adjusting data analysis algorithms to consider this multi-set structure may greatly benefit immunological insight and classification performance of Flow Cytometry data.

Myelin-containing macrophages and microglia are the most abundant immune cells in active multiple sclerosis (MS) lesions. Our recent transcriptomic analysis demonstrated that collectin placenta 1 (CL-P1) is one of the most potently induced genes in macrophages after uptake of myelin. CL-P1 is a type II transmembrane protein with both a collagen-like and carbohydrate recognition domain, which plays a key role in host defense. In this study we sought to determine the dynamics of CL-P1 expression on myelin-containing phagocytes and define the role that it plays in MS lesion development. We show that myelin uptake increases the cell surface expression of CL-P1 by mouse and human macrophages, but not by primary mouse microglia in vitro. In active demyelinating MS lesions, CL-P1 immunoreactivity was localized to perivascular and parenchymal myelin-laden phagocytes. Finally, we demonstrate that CL-P1 is involved in myelin internalization as knockdown of CL-P1 markedly reduced myelin uptake. Collectively, our data indicate that CL-P1 is a novel receptor involved in myelin uptake by phagocytes and likely plays a role in MS lesion development.

Obesity is associated with a disturbed adipose tissue (AT) function characterized by adipocyte hypertrophy, an impaired lipolysis and pro-inflammatory phenotype, which contributes to insulin resistance (IR). We investigated whether AT phenotype in different AT depots of obese individuals with and without type 2 diabetes mellitus (T2DM) is associated with whole-body IR. Subcutaneous (SC) and visceral (V) AT biopsies from 18 lean, 17 obese and 8 obese T2DM men were collected. AT phenotype was characterized by ex vivo measurement of basal and stimulated lipolysis (mature adipocytes), adipocyte size distribution (AT tissue sections) and AT immune cells (flow cytometry). In VAT, mean adipocyte size, CD45+ leukocytes and M1 macrophages were significantly increased in both obese groups compared to lean individuals. In SCAT, despite adipocyte hypertrophy, no significant differences in immune cell populations between groups were found. In SCAT, multiple linear regression analysis showed that none of the AT phenotype markers independently contributed to HOMA-IR while in VAT, mean adipocyte size was significantly related to HOMA-IR. In conclusion, beside adipocyte hypertrophy in VAT, M1 macrophage- or B-cell-mediated inflammation, may contribute to IR, while inflammation in hypertrophic SCAT does not seem to play a major role in IR. We thank all abdominal surgeons from the Jessa Hospital (Hasselt, Belgium) and Hospital East-Limburg (Genk, Belgium) for their contributions to subject recruitment. We thank University Biobank Limburg (UBiLim, Jessa Hospital, Belgium) for their technical support in sample handling and storage. Yvonne Essers, Nicole Hoebers, Maria Vroomen and Jose van de Gaar are greatly acknowledged for their technical support. This work was supported by the Internal resources from Hasselt University and Maastricht University. Part of the study was financed by The Netherlands Organization for Scientific Research (NWO) (Veni 916.12.056), The Netherlands Heart Foundation (2013T143) and a Seventh Framework Program (FP7) Grant (CIG 322070) to KW. The funding sources were not involved in any decision making with respect to this manuscript.

Immune cell accumulation in adipose tissue (AT) is associated with the development of AT inflammation, resulting in metabolic dysfunction. Circulating immune cell patterns may reflect immune cell accumulation in expanding AT. However, data linking human leukocytes in blood and AT is lacking. We investigated whether blood immune cell populations are associated with their counterparts in subcutaneous (scAT) or visceral AT (vAT). Flow cytometry was performed on blood, scAT and vAT from 16 lean and 29 obese men. Circulating natural killer (NK)-cells, classical monocytes and nonclassical monocytes were higher in obese individuals. vAT, but not scAT, of obese individuals contained more inflammatory CD11c+ “M1” macrophages and NK cells compared to lean individuals. Blood classical monocytes were associated with CD11c+ macrophages in vAT but not scAT. This association was unrelated to expression of the adhesion molecules CD11b and CD11c or of the chemokine receptor CX3CR1 on these monocytes. Other AT immune cells were not associated with their respective counterparts in blood. Finally, CD11c+ macrophages and CD4+ T-cells in vAT were associated with their counterparts in scAT. In conclusion, blood classical monocytes reflect CD11c+ macrophages in vAT. Maria Vroomen and José van de Gaar are greatly acknowledged for their technical support. This study was financed by The Netherlands Organization for Scientific Research (NWO) (Veni 916.12.056), The Netherlands Heart Foundation (2013T143) and a Seventh Framework Program (FP7) Grant (CIG 322070) to K.W.