Researchers from Stefan Kubicek’s and Christoph Bock’s teams, on the CeMM Analysis Heart for Molecular Drugs of the Austrian Academy of Sciences in Vienna, have developed a way to precisely assess the impact of particular medication in remoted pancreatic tissue through the use of a refined single-cell RNA sequencing methodology. Their study revealed in Genome Biology describes the method that they’ve developed to beat the issue of contaminating RNA molecules in single-cell transcriptomics, which allowed for correct outcomes of dynamic drug responses in pancreatic cells. These findings will help the event of focused drug therapies for the therapy of Kind 1 diabetes sooner or later.
The pancreas is an stomach organ that produces digestive enzymes in addition to hormones that regulate blood sugar ranges. This hormone-producing operate is localized to the islets of Langerhans, which represent clusters of various endocrine cell sorts. Amongst these are beta cells, which produce the hormone insulin wanted to decrease glucose (a kind of sugar) ranges in our blood, in addition to alpha cells, which generate the hormone glucagon answerable for elevating glucose ranges within the blood.
Kind 1 diabetes is a persistent illness during which the physique’s immune system mistakenly assaults and destroys the pancreas’ insulin-producing beta cells. Regenerative drugs goals to replenish beta cell mass, and thus help and in the end substitute the present insulin alternative therapies. Alterations to islet composition, together with inadequate beta cell operate and beta cell dedifferention, additionally contribute to sort II diabetes. Due to this fact, a deeper understanding of the identification and crosstalk of the completely different islet cell sorts results in a greater characterization of each types of diabetes and will contribute to the event of novel therapeutic ideas.
Single-cell transcriptomics is a robust method to characterize mobile identification. Beforehand, CeMM researchers from Christoph Bock’s and Stefan Kubicek’s teams at CeMM revealed the primary single cell transcriptomes from main human pancreatic islet cells. Advances within the know-how have since enabled its software to the era of worldwide human and mouse single cell transcriptome atlases. Regardless of these advances, single cell approaches stay technologically difficult on condition that the miniscule RNA quantity current is fully used up within the experiment. Due to this fact, it’s important to make sure the standard and purity of the ensuing single cell transcriptomes.
CeMM researchers within the two contributing laboratories recognized unexpectedly excessive hormone expression in non-endocrine cell sorts, each in their very own dataset in addition to different revealed single cell research. They got down to elucidate whether or not this could be the results of contamination by RNA molecules, for instance from dying cells, and the way it may very well be eliminated to acquire a extra dependable dataset. Such contamination appears current in single cell RNA-seq information from most tissues however was most seen in pancreatic islets. Islet endocrine cells are solely dedicated to the manufacturing of single hormones, and insulin in beta cells and glucagon in alpha cells are expressed to greater ranges than typical “housekeeping” genes. Thus, redistribution of those transcripts to different cell sorts was extremely pronounced. Primarily based on this remark, their objective was to develop, validate and apply a way to experimentally decide and computationally take away such contamination.
Of their investigation, CeMM researchers used spiked-in cells from completely different cell sorts, each mouse and human samples, that they added to their pancreatic islet samples. Importantly, the transcriptomes of those spike-in cell had been totally characterised. This allowed them to regulate internally and precisely the extent of RNA contamination in single cell RNA-seq, giving that the human transcripts detected within the mouse spike-in cells represent contaminating RNA. On this approach, they discovered that the samples had a contamination stage of as much as 20% and had been in a position to outline the contamination in every samples. They then developed a novel bioinformatics strategy to computationally take away contaminating reads from single cell transcriptomes.
Having now obtained a “decontaminated” transcriptome, from which the spurious sign has been eliminated, they proceeded to characterize how the mobile identification within the completely different cell sorts responded to the therapy with three completely different medication. They discovered that a small molecule inhibitor of the transcription issue FOXO1 induces dedifferentiation of each alpha and beta cells. Moreover, they studied artemether, which had been discovered to decrease the operate of alpha cells and will induce insulin manufacturing in each in vivo and in vitro research. The results of the drug artemether had been species-specific and cell-type-specific. In alpha cells, a fraction of cells enhance insulin expression and acquire points of beta cell identification, each in mouse and human samples. Importantly, researchers discovered that in human beta cells, there isn’t any important change in insulin expression, whereas in mouse islets, beta cells scale back their insulin expression and general beta cell identification.
This research is the results of a cross-disciplinary collaboration of the laboratories of Stefan Kubicek and Christoph Bock at CeMM with Patrick Collombat on the Institute of Biology Valrose (France). That is the primary research to use single cell sequencing to research dynamic drug response in intact remoted tissue, which benefitted from the excessive quantitative accuracy of the decontamination methodology. It supplies thus not solely a novel methodology for single-cell decontamination and extremely quantitative single-cell evaluation of drug responses in intact tissues, but in addition addresses an vital present query in islet cell biology and diabetes analysis. These findings might open up potential therapeutic avenues to deal with Kind 1 diabetes sooner or later.
Marquina-Sanchez et al. (2020). Single-cell RNA-seq with spike-in cells allows correct quantification of cell-specific drug results in pancreatic islets. Genome Biology. DOI: https://doi.org/10.1186/s13059-020-02006-2
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