Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks.

A fundamental problem in biomedical research is the low number of observations available, mostly due to a lack of available biosamples, prohibitive costs, or ethical reasons. Augmenting few real observations with generated in silico samples could lead to more robust analysis results and a higher reproducibility rate. Here, we propose the use of conditional single-cell generative adversarial neural networks (cscGAN) for the realistic generation of single-cell RNA-seq data. cscGAN learns non-linear gene-gene dependencies from complex, multiple cell type samples and uses this information to generate realistic cells of defined types. Augmenting sparse cell populations with cscGAN generated cells improves downstream analyses such as the detection of marker genes, the robustness and reliability of classifiers, the assessment of novel analysis algorithms, and might reduce the number of animal experiments and costs in consequence. cscGAN outperforms existing methods for single-cell RNA-seq data generation in quality and hold great promise for the realistic generation and augmentation of other biomedical data types.

SEAweb: the small RNA Expression Atlas web application.

We present the Small RNA Expression Atlas (SEAweb), a web application that allows for the interactive querying, visualization and analysis of known and novel small RNAs across 10 organisms. It contains sRNA and pathogen expression information for over 4200 published samples with standardized search terms and ontologies. In addition, SEAweb allows for the interactive visualization and re-analysis of 879 differential expression and 514 classification comparisons. SEAweb's user model enables sRNA researchers to compare and re-analyze user-specific and published datasets, highlighting common and distinct sRNA expression patterns. We provide evidence for SEAweb's fidelity by (i) generating a set of 591 tissue specific miRNAs across 29 tissues, (ii) finding known and novel bacterial and viral infections across diseases and (iii) determining a Parkinson's disease-specific blood biomarker signature using novel data. We believe that SEAweb's simple semantic search interface, the flexible interactive reports and the user model with rich analysis capabilities will enable researchers to better understand the potential function and diagnostic value of sRNAs or pathogens across tissues, diseases and organisms.

A novel method for culturing stellate astrocytes reveals spatially distinct Ca2+ signaling and vesicle recycling in astrocytic processes.

Interactions between astrocytes and neurons rely on the release and uptake of glial and neuronal molecules. But whether astrocytic vesicles exist and exocytose in a regulated or constitutive fashion is under debate. The majority of studies have relied on indirect methods or on astrocyte cultures that do not resemble stellate astrocytes found in vivo. Here, to investigate vesicle-associated proteins and exocytosis in stellate astrocytes specifically, we developed a simple, fast, and economical method for growing stellate astrocyte monocultures. This method is superior to other monocultures in terms of astrocyte morphology, mRNA expression profile, protein expression of cell maturity markers, and Ca2+ fluctuations: In astrocytes transduced with GFAP promoter-driven Lck-GCaMP3, spontaneous Ca2+ events in distinct domains (somata, branchlets, and microdomains) are similar to those in astrocytes co-cultured with other glia and neurons but unlike Ca2+ events in astrocytes prepared using the McCarthy and de Vellis (MD) method and immunopanned (IP) astrocytes. We identify two distinct populations of constitutively recycling vesicles (harboring either VAMP2 or SYT7) specifically in branchlets of cultured stellate astrocytes. SYT7 is developmentally regulated in these astrocytes, and we observe significantly fewer synapses in wild-type mouse neurons grown on Syt7-/- astrocytes. SYT7 may thus be involved in trafficking or releasing synaptogenic factors. In summary, our novel method yields stellate astrocyte monocultures that can be used to study Ca2+ signaling and vesicle recycling and dynamics in astrocytic processes.