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Orchestrating the Transcriptome and Proteome in Time and Space:<br/>Quantitative Modeling of Protein Production, Degradation and Localization in Mammalian Systems

Final Report Summary - EXPRESSION DYNAMICS (Orchestrating the Transcriptome and Proteome in Time and Space:Quantitative Modeling of Protein Production, Degradation and Localization in Mammalian Systems)

During my outgoing phase in the Regev lab at the Broad Institute, my primary and most immediate goal was to systematically study the dynamics of gene expression control of mammalian cells, using the model system of bone marrow-derived dendritic cells (DCs) responding to lipopolysaccharide (LPS). First, I wanted to evaluate the contribution of protein production and degradation to changes in overall protein levels following LPS stimulation. Second, I planned to integrate the generated data with data about the dynamics of the RNA life cycle to build an unprecedented quantitative genome-scale model of the temporal dynamics of gene expression, from transcription to protein degradation. Third, I wanted to combine ribosomal footprinting with proteomics to study the translational potential of short non-canonical ORFs (sncORFs) encoded on putative lincRNAs. Finally, I wanted to use refined measurements to monitor candidate key components that may affect the immune response of DCs and will use systematic perturbation followed by signature-scale monitoring to validate and refine their roles. All of these goals have been met. Here is a summary of the scientific work addressing the originally stated objectives:

I developed an integrated experimental and computational strategy to quantitatively assess how protein levels are maintained in the context of a dynamic response and applied it to the model response of DCs stimulated with LPS. I combined measurements of protein production and degradation and mRNA dynamics to build a quantitative genomic model of the differential regulation of gene expression in LPS-stimulated DCs. Changes in mRNA abundance played a dominant role in determining most dynamic fold changes in protein levels. Conversely, the preexisting proteome of proteins performing basic cellular functions was remodeled primarily through changes in protein production or degradation, accounting for over half of the absolute change in protein molecules in the cell. My results supported a model where the induction of novel cellular functions is primarily driven through transcriptional changes, whereas regulation of protein production or degradation updates the levels of preexisting functions as required for an activated state (Jovanovic et al., Science, 2015). Overall, the novel approach I developed for building quantitative genome-scale models of the temporal dynamics of protein expression is broadly applicable to other dynamic systems.
Although this genome-scale model provides significant insight about the temporal dynamics of gene expression and identifies genes and groups of genes regulated by similar modes of actions, it does not itself yet provide information about which genes regulate these expression changes. In an ideal case we would obtain such a list of candidate regulators in an unbiased and orthogonal approach, such as genetic screening.
I therefore adapted new CRISPR technology to develop a marker based genome-wide CRISPR screen in mouse primary bone marrow DCs using Cas-9 expressing transgenic mice. I stimulated DCs infected with a genome wide library of lentiviruses, containing 6 guide RNAs per mouse gene (total of ~ 126,000 guides), with LPS, and monitored their responses by intra-cellular staining for the anti-inflammatory cytokine TNF-α, an early response marker of LPS stimulation. Cells that failed to respond to LPS (i.e. caused by a mutation in a positive regulator) or that responded strongly (i.e. caused by a mutation in a negative regulator) were isolated by Fluorescence Activated Cell Sorting (FACS) and guides expressed in these cells were detected by deep sequencing. We found many of the known regulators of Tlr4 signaling, as well as dozens of previously unknown candidates that we validated. By measuring protein markers and mRNA profiles in DCs that are deficient in known or candidate regulators, we classified the genes into functional modules with distinct effects on the canonical responses to LPS. My findings uncover new facets of innate immune circuits in primary cells and provide a genetic approach for dissection of mammalian cell circuits (Parnas*, Jovanovic*, Eisenhaure*, et al., Cell, 2015, *contributed equally). This marker based genome wide screen in primary mammalian cells will allow me to apply unbiased genetic screening in nearly every available system of interest as long as I can sort for the expression of a marker of interest.
Finally, to study the translational potential of short non-canonical ORFs (sncORFs) encoded on putative lincRNAs, we, in collaboration with Jonathan Weissman’s group, integrated proteomics and ribosome profiling data to predict with high confidence protein coding genes, which led to a co-author publication. We developed an experimental and analytical framework, for systematic identification and quantification of translation. We identified thousands of novel ORFs, including micropeptides and variants of known proteins, that bear the hallmarks of canonical translation and exhibit translation levels and dynamics comparable to that of annotated ORFs (Fields*, Rodriguez*, Jovanovic, et al., Molecular Cell, 2015, *contributed equally).

The goal for the returning phase to the Schuman lab at the Max Planck Institute of Brain Research was to apply the newly acquired skills, methods and knowledge gained during my outgoing phase to systematically study gene expression in neurons upon synaptic stimulation. In addition, I wanted to look at gene expression control in somata and dendrites separately, thus considering both spatial and temporal regulation of translation in mammalian cells.

In order to achieve these goals, we started several projects, which are still ongoing and will continue to as a collaboration between the Schuman lab and my newly formed research group at Columbia University, USA:
First, we established a pulsed SILAC approach in mouse primary cortical neurons and applied it together with RNA sequencing to assess how protein levels are maintained in the context of several synaptic stimulation schemes in primary neurons. This will allow us to assess globally and for several thousands of genes at which level (RNA, mRNA translation and/or protein degradation) the protein changes are regulated upon synaptic stimulation. Moreover, as we applied several different stimulation schemes, we will be able to determine if neurons apply the same or different strategies to regulate the necessary gene expression changes upon stimulation.
Second, in order to gain local resolution, we established growth conditions for primary cortical neurons on porous membranes. These membranes have pores that are of sufficient size to allow neural dendrites to grow through to the lower side, while the bigger cell body cannot pass the pores and will stay on the upper side of the membrane. We established that we can isolate enough protein from the “somatic” (upper membrane side) and especially the “dendritic” (lower membrane side) layer and proteomic measurement indeed confirmed that the protein content between these two compartments differs significantly, the “somatic” layer being enriched for example for nuclear proteins, while the “dendritic” layer is significantly enriched for proteins associated for example with synaptic functions. Currently, we are collecting pulsed SILAC proteomic and RNA sequencing data for both layers separately and under different synaptic stimulation schemes, in order to see if there are local differences in gene expression regulation within cortical neurons.
Third, we wanted to not just look at gene expression regulation in fully mature neurons, but also determine how gene expression changes are regulated during neuronal development. Therefore, we set up in the Schuman lab an established, but very challenging, differentiation protocol of mouse embryonic stem cells (ESCs) to mature glutaminergic neurons. We also collected pulsed SILAC proteomic and RNA sequencing based transcriptomic data at several (semi-)stable stages during ESC differentiation in order to study globally the shifts in gene expression regulation during differentiation of ESCs into fully mature neurons, a question so far unanswered in regards to protein synthesis and degradation.

This systems biology project complies perfectly with specific research objectives emphasized by the European Commission (EC). Systems biology has become one major focus to enhance the research excellence of the ERA. The project is clearly in line with cutting edge projects in systems biology, as it quantifies, models and understands the complexity of the dynamic changes induced in two disease related mammalian cell system upon perturbation. The work so far pushed the limits of the most advanced ‘omics technologies in order to generate large-scale, high quality data sets that provided the basis for sophisticated modeling approaches in order to describe quantitatively the contributions of the fundamental processes of gene expression to the final protein levels. Results provided by the project are: (1) a global quantitative model of gene expression dynamics of LPS stimulated DCs; (2) the identification and validation of new key regulators and therefore therapeutic targets of the immune response of DCs, cells critical for diseases such as cancer and autoimmunity; (3) proving the feasibility of such an extensive systems approach in a complex system and therefore providing the blueprint for further systems approaches (4) applying this blueprint to globally model temporal and spatial gene expression dynamics of stimulated neurons; (5) and of ESC to mature neuron differentiation.
The economic usefulness of the already established methods is also exemplified by the patent application that is based on the established marker based genome wide CRISPER/Cas9 screen.

Patent Application: