A promising approach to overcome hypoxic conditions in tissue engineered constructs is to use the potential of endothelial cells (EC) to form networks in vitro when co-cultured with a supporting cell type in a 3D environment. Adipose tissue-derived stromal cells (ASC) as well as bone marrow-derived stromal cells (BMSC) have been shown to support vessel formation of EC in vitro, but only very few studies compared the angiogenic potential of both cell types using the same model. Here, we aimed at investigating the ability of ASC and BMSC to induce network formation of EC in a co-culture model in fibrin. While vascular structures of BMSC and EC remained stable over the course of 3 weeks, ASC-EC co-cultures developed more junctions and higher network density within the same time frame. Both co-cultures showed positive staining for neural glial antigen 2 (NG2) and basal lamina proteins. This indicates that vessels matured and were surrounded by perivascular cells as well as matrix molecules involved in stabilization. Gene expression analysis revealed a significant increase of vascular endothelial growth factor (VEGF) expression in ASC-EC co-culture compared to BMSC-EC co-culture. These observations were donor-independent and highlight the importance of organotypic cell sources for vascular tissue engineering.
The plasma levels of tissue-specific microRNAs can be used as diagnostic, disease severity and prognostic biomarkers for chronic and acute diseases and drug-induced injury. Thereby, the combination of diverse microRNAs into biomarker signatures using multivariate statistics seems especially powerful from the perspective of tissue and condition specific microRNA shedding into the plasma. Although next-generation sequencing (NGS) technology enables one to analyse circulating microRNAs on a genome-scale level, it suffers from potential biases (e.g., adapter ligation bias) and lacks absolute transcript quantitation as well as tailor-made quality controls. In order to develop a robust NGS discovery assay for genome-scale quantitation of circulating microRNAs, we first evaluated the sensitivity, repeatability and ligation bias of four commercially available small RNA library preparation protocols. The protocol from RealSeq Biosciences was selected based on its performance and usability and coupled with a novel panel of exogenous small RNA spike-in controls to enable quality control and absolute quantitation, thus ensuring comparability of data across independent NGS experiments. The established microRNA Next-Generation-Sequencing Discovery Assay (miND) was validated for its relative accuracy, precision, analytical measurement range and sequencing bias and was considered fit-for-purpose for microRNA biomarker discovery. Summarized, all these criteria were met, and thus, our analytical platform is considered fit-for-purpose for microRNA biomarker discovery from biofluids in the setting of any diagnostic, prognostic or patient stratification need. The established miND assay was tested on serum, cerebrospinal fluid (CSF), synovial fluid (SF) and extracellular vesicles (EV) extracted from cell culture medium of primary cells and proved its potential to be used across different sample types.
As extracellular vesicles (EVs) have become a prominent topic in life sciences, a growing number of studies are published on a regular basis addressing their biological relevance and possible applications. Nevertheless, the fundamental question of the true vesicular nature as well as possible influences on the EV secretion behavior have often been not adequately addressed. Furthermore, research regarding endothelial cell-derived EVs (EndoEVs) often focused on the large vesicular fractions comprising of microvesicles (MV) and apoptotic bodies. In this study we aimed to further extend the current knowledge of the influence of pre-isolation conditions, such as cell density and conditioning time, on EndoEV release from human umbilical vein endothelial cells (HUVECs). We combined fluorescence nanoparticle tracking analysis (NTA) and the established fluorescence-triggered flow cytometry (FT-FC) protocol to allow vesicle-specific detection and characterization of size and surface markers. We found significant effects of cell density and conditioning time on both abundance and size distribution of EndoEVs. Additionally, we present detailed information regarding the surface marker display on EVs from different fractions and size ranges. Our data provide crucial relevance for future projects aiming to elucidate EV secretion behavior of endothelial cells. Moreover, we show that the influence of different conditioning parameters on the nature of EndoEVs has to be considered.
In contrast to traditional methods like real-time polymerase chain reaction, next-generation sequencing (NGS), and especially small RNA-seq, enables the untargeted investigation of the whole small RNAome, including microRNAs (miRNAs) but also a multitude of other RNA species. With the promising application of small RNAs as biofluid-based biomarkers, small RNA-seq is the method of choice for an initial discovery study. However, the presentation of specific quality aspects of small RNA-seq data varies significantly between laboratories and is lacking a common (minimal) standard. The miRNA NGS Discovery pipeline (miND) aims to bridge the gap between wet lab scientist and bioinformatics with an easy to setup configuration sheet and an automatically generated comprehensive report that contains all essential qualitative and quantitative results that should be reported. Besides the standard steps like preprocessing, mapping, visualization, and quantification of reads, the pipeline also incorporates differential expression analysis when given the appropriate information regarding sample groups. Although miND has a focus on miRNAs, other RNA species like tRNAs, piRNA, snRNA, or snoRNA are included and mapping statistics are available for further analysis. miND has been developed and tested on a multitude of data sets with various RNA sources (tissue, plasma, extracellular vesicles, urine, etc.) and different species. miND is a Snakemake based pipeline and thus incorporates all advantages using a flexible workflow management system. Reference databases are downloaded, prepared and built with an included (but separate) workflow and thus can easily be updated to the most recent version but also stored for reproducibility. In conclusion, the miND pipeline aims to streamline the bioinformatics processing of small RNA-seq data by standardizing the processing from raw data to a final, comprehensive and reproducible report.
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