Doris‘ paper entitled ‘Multivariate Control of Transcript to Protein Variability in Single Mammalian Cells’ has been accepted for publication. Congratulations!!
This work reports that correlations between mRNA and protein abundance of the same gene across thousands of single cells are often quite high, and that single cells that are outliers of such linear correlations are, moreover, the result of a gene-specific adaptation of mRNA-to-protein ratios to properties of the phenotypic state and microenvironment of individual cells. Accounting for this allows an accurate prediction of protein abundance in single cells. Using gene induction of JUN illustrates that these properties of single cells can influence mRNA-protein relationships at multiple levels in sometimes non-intuitive ways, involving adaptation of transcription, nuclear export, protein translation, and mRNA decay. Finally, the work shows that also subcellular patterns of JUN transcripts vary non-randomly between single cells and are adapted to the extent of local cell crowding, which may contribute to determining cell-to-cell variability in mRNA-to-protein ratios.
Gabriele‘s work on developing iterative indirect immunofluorescence imaging (4i) is online. check it out here.
Gabriele has been awarded the UZH BioEntrepreneur-Fellowship based on his project to apply 4i in precision medicine. Congratulations!!
Arpan‘s work on DYRK3 is now online. Check it out here.
Gabriele‘s paper entitled ‘Multiplexed protein maps link subcellular organization to cellular states’ has been accepted for publication. Congratulations!!
This work reports the development of iterative indirect immunofluoresence imaging (4i), which allows 40-plex immunostaining of hundreds of thousands of single cells using conventional primary and secondary antibodies in high-throughput. Combined with cellular computer vision, this generates a wealth of quantitative information about biological samples from the millimeter to the nanometer scale. It also reports a novel pixel-based computational approach that allows the unsupervised comprehensive quantification of protein sub-compartmentalization within various multicellular, cellular, and pharmacological contexts. These approaches have enormous potential for biomedicine in both fundamental research, diagnostics and personalized medicine.
Arpan‘s paper entitled ‘Kinase-controlled phase transition of membrane-less organelles in mitosis’ has been accepted for publication. Congratulations!!
This work shows that the dual-specificity kinase DYRK3 drives the dissolution of membrane-less organelles as cells undergo cell division, and adds to our increasing evidence that DYRK kinases represent a novel class of cellular regulators that control liquid phase transitions in cells (see also Wippich et al., 2013).
Reinoud’s paper is featured on the cover of the January 2018 issue of Molecular Systems Biology.
Reinoud‘s paper entitled ‘Large-scale image-based profiling of single-cell phenotypes in arrayed CRISPR-Cas9 gene perturbation screens’ has been accepted for publication in Molecular Systems Biology. Congratulations!!
This now gives us the ability to obtain multivariate quantitative profiles of large numbers of single-cell gene perturbation phenotypes in high-throughput arrayed CRISPR-Cas9-based screens.
On June 4, Ola Sabet joined our lab as a postdoctoral fellow. Ola did her PhD in the laboratory of Philippe Bastiaens at the Max Planck Institute for Molecular Physiology in Dortmund, Germany. In her PhD work, she developed a conformational biosensor of receptor kinase activity in living cells with which she revealed the importance of quantifying the dynamic and spatial segregation of signalling molecules to understand signaling output. For more details, check here
In our lab, Ola will push the boundaries of temporal and spatial resolution in large-scale image-based systems biology approaches.
On June 1, Diego Villamaina joined our lab as a Big Data and IT specialist. Diego did his PhD at the University of Geneva and his postdoc at the ETH Zurich in Physical Chemistry, during which he became interested in developing computational tools and software for scientific data processing and visualisation. For more details, check here.
In our lab, Diego will be responsible for IT infrastructure and the further development of our computational framework for the interactive visualization and distributed analysis of large-scale microscopy image datasets.