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Roest, H. P.

Publications and source records attributed to Roest, H. P..

2 recordsLinked to original sources

Integration of lymphatic vasculature to a human lymph node-on-chip enhances physiological immune properties

To study systemic human innate and adaptive immune responses in detail, competent in vitro lymph node (LN) models with LN stromal cells (LNSCs) are required to recapitulate the physiological microenvironment. The multicellular organisation of LNs possesses a challenge for designing such microphysiological systems (MPS), particularly with the structural complexity of LNs and the lymphatic vasculature. Here, we established an organotypic LN model with integrated lymphatics in an organ-on-chip (OoC) platform containing a printed sacrificial structure, and studied the influence of a perfused lymphatic endothelial cell (LEC)-lined channel on the LN-on-chip microenvironment. Upon one-week of culture under lymphatic flow, LECs lined the tubular structure forming a lymphatic vessel through the LN model, and stable metabolic conditions within the LN-on-chip were confirmed. Interestingly, LECs in the LN-on-chip displayed the phenotype found in human LNs with upregulation of LEC-specific LN markers, such as atypical chemokine receptor 4 (ACKR4). The presence of the LEC-lined perfused vessel in the LN-on-chip resulted in the increase of native immune cells, most notably B cells, and the secretion of survival and migratory signals, namely interleukin-7 (IL-7) and CC motif chemokine ligand 21 (CCL21). Likewise, LECs promoted the abundance of immune cell clusters closer to the vessel. As such, these features represent an enhanced physiological microenvironment to allow for immune cell migration and interactions for efficient LN functioning. This approach paves the way for LN integration into multi-OoC (MOC) platforms to investigate immunological crosstalk between tissue-derived factors, immune cell trafficking and organ-specific adaptive immune responses.

bioengineering↗

Unbiased method for spectral analysis of cells with great diversity of autofluorescence spectra

Autofluorescence is an intrinsic feature of cells, caused by the natural emission of light by its cellular content, that can complicate analysis of flow cytometry data. Different cell types have different autofluorescence spectra and even within one cell type heterogeneity of autofluorescence spectra can be present, for example as a consequence of activation status or metabolic changes. By using full spectrum flow cytometry, the emission spectrum of a fluorochrome is captured by a set of detectors across a range of wavelengths, creating an unique spectrum for this fluorochrome, that is used to unmix the signal of a full stained sample into the signals of the different fluorochromes. Importantly, this technology can also be used to identify the aut-ofluorescence signal of an unstained sample, which can be used for unmixing purposes and to separate the autofluorescence signal from the fluorophore signals. However, this only works if the sample has one homogeneous autofluorescence spectrum. To analyze samples with a heterogeneous autofluorescence spectral profile, we here setup an unbiased workflow to detect all different autofluorescence spectra present in a sample to take them along as autofluorescence signatures during the unmixing of the full stained samples. First, clusters of cells with similar autofluorescence spectra are identified by unbiased dimensional reduction and clustering. Then, unique autofluorescence clusters are determined and are used to improve the unmixing accuracy of the full stained sample. This unbiased method allows for the identification of all autofluorescence spectra present in a sample, independent of cell types and intensity of the autofluorescence spectra. Furthermore, this method is equally useful for spectral analysis of different biological samples, including tissue cell suspensions, peripheral blood mononuclear cells and in vitro cultures of (primary) cells.

cell biology↗