Neural tissues generated from human pluripotent stem cells in vitro (known as neural organoids) are becoming useful tools to study human brain development, evolution and disease. The characterization of neural organoids using single-cell genomic methods has revealed a large diversity of neural cell types with molecular signatures similar to those observed in primary human brain tissue. However, it is unclear which domains of the human nervous system are covered by existing protocols. It is also difficult to quantitatively assess variation between protocols and the specific cell states in organoids as compared to primary counterparts. Single-cell transcriptome data from primary tissue and neural organoids derived with guided or un-guided approaches and under diverse conditions combined with large-scale integrative analyses make it now possible to address these challenges. Recent advances in computational methodology enable the generation of integrated atlases across many data sets. Here, we integrated 36 single-cell transcriptomics data sets spanning 26 protocols into one integrated human neural organoid cell atlas (HNOCA) totaling over 1.7 million cells. We harmonize cell type annotations by incorporating reference data sets from the developing human brain. By mapping to the developing human brain reference, we reveal which primary cell states have been generated in vitro, and which are under-represented. We further compare transcriptomic profiles of neuronal populations in organoids to their counterparts in the developing human brain. To support rapid organoid phenotyping and quantitative assessment of new protocols, we provide a programmatic interface to browse the atlas and query new data sets, and showcase the power of the atlas to annotate new query data sets and evaluate new organoid protocols. Taken together, the HNOCA will be useful to assess the fidelity of organoids, characterize perturbed and diseased states and facilitate protocol development in the future.

Nuclear RNA binding proteins (RBPs) are difficult to study because they often belong to large protein families and form extensive networks of auto- and cross- regulation. They are highly abundant and often localize to condensates with a slow turnover, requiring long depletion times or knockouts that cannot distinguish between direct and indirect or compensatory effects. Here, we developed a system that is optimized for the rapid degradation of nuclear RBPs, called hGRAD. It comes as a ʹone-fits-allʹ plasmid, and integration into any cell line that expresses endogenously GFP-tagged proteins allows an inducible, rapid and complete knockdown. We show that the nuclear RBPs SRSF3, SRSF5, SRRM2 and NONO are completely cleared from nuclear speckles and paraspeckles within two hours. hGRAD works in various cell types, is more efficient than other methods and does not require the expression of exogenous ubiquitin ligases. Combining SRSF5 hGRAD degradation with Nascent-seq uncovered highly dynamic transient transcript changes, compensatory mechanisms and that SRSF5 promotes transcript stability.

Nuclear RNA binding proteins (RBPs) are difficult to study because they often belong to large protein families and form extensive networks of auto- and crossregulation. They are highly abundant and many localize to condensates with a slow turnover, requiring long depletion times or knockouts that cannot distinguish between direct and indirect or compensatory effects. Here, we developed a system that is optimized for the rapid degradation of nuclear RBPs, called hGRAD. It comes as a "one-fits-all" plasmid, and integration into any cell line with endogenously GFP-tagged proteins allows for an inducible, rapid, and complete knockdown. We show that the nuclear RBPs SRSF3, SRSF5, SRRM2, and NONO are completely cleared from nuclear speckles and paraspeckles within 2 h. hGRAD works in various cell types, is more efficient than previous methods, and does not require the expression of exogenous ubiquitin ligases. Combining SRSF5 hGRAD degradation with Nascent-seq uncovered transient transcript changes, compensatory mechanisms, and an effect of SRSF5 on transcript stability.

Members of the arginine–serine-rich protein family (SR proteins) are multifunctional RNA-binding proteins that have emerged as key determinants for mRNP formation, identity and fate. They bind to pre-mRNAs early during transcription in the nucleus and accompany bound transcripts until they are translated or degraded in the cytoplasm. SR proteins are mostly known for their essential roles in constitutive splicing and as regulators of alternative splicing. However, many additional activities of individual SR proteins, beyond splicing, have been reported in recent years. We will summarize the different functions of SR proteins and discuss how multifunctionality can be achieved. We will also highlight the difficulties of studying highly versatile SR proteins and propose approaches to disentangle their activities, which is transferrable to other multifunctional RBPs.

Here we present a research of bacterial adhesion to two most often used materials in modern kitchens, namely food grade ceramics and Teflon. To test the bacterial adhesion on kitchen worktops Escherichia coli, Pseudomonas aeruginosa and Campylobacter jejuni were used as the most common foodborne contaminants. Contact angle, roughness and streaming potential measurements were used for surface characterization. Crystal violet staining and scanning electron microscopy were applied for bacterial adhesion analysis. We showed that the adhesion of tested bacteria strains was lower on the Teflon surface compared to the ceramics. The hydrophobicity of the surface substantially contributed to the bacterial adhesion rate. On the other hand, the surface roughness and charge did not play a crucial role in the adhesion process.