Subunits of an E3 Ligase Complex as Degrons for Efficient Degradation of Cytosolic, Nuclear, and Membrane Proteins

Protein degradation is a highly regulated cellular process crucial to enable the high dynamic range of the response to external and internal stimuli and to balance protein biosynthesis to maintain cell homeostasis. Within mammalian cells, hundreds of E3 ubiquitin ligases target specific protein substrates and could be repurposed for synthetic biology. Here, we present a systematic analysis of the four protein subunits of the multiprotein E3 ligase complex as scaffolds for the designed degrons. While all of them were functional, the fusion of a fragment of Skp1 with the target protein enabled the most effective degradation. Combination with heterodimerizing peptides, protease substrate sites, and chemically inducible dimerizers enabled the regulation of protein degradation. While the investigated subunits of E3 ligases showed variable degradation efficiency of the membrane and cytosolic and nuclear proteins, the bipartite SSD (SOCSbox-Skp1(ΔC111)) degron enabled fast degradation of protein targets in all tested cellular compartments, including the nucleus and plasma membrane, in different cell lines and could be chemically regulated. These subunits could be employed for research as well as for diverse applications, as demonstrated in the regulation of Cas9 and chimeric antigen receptor proteins.

Robust Saliva-Based RNA Extraction-Free One-Step Nucleic Acid Amplification Test for Mass SARS-CoV-2 Monitoring

Early diagnosis with rapid detection of the virus plays a key role in preventing the spread of infection and in treating patients effectively. In order to address the need for a straightforward detection of SARS-CoV-2 infection and assessment of viral spread, we developed rapid, sensitive, extraction-free one-step reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and reverse transcription loop-mediated isothermal amplification (RT-LAMP) tests for detecting SARS-CoV-2 in saliva. We analyzed over 700 matched pairs of saliva and nasopharyngeal swab (NSB) specimens from asymptomatic and symptomatic individuals. Saliva, as either an oral cavity swab or passive drool, was collected in an RNA stabilization buffer. The stabilized saliva specimens were heat-treated and directly analyzed without RNA extraction. The diagnostic sensitivity of saliva-based RT-qPCR was at least 95% in individuals with subclinical infection and outperformed RT-LAMP, which had at least 70% sensitivity when compared to NSBs analyzed with a clinical RT-qPCR test. The diagnostic sensitivity for passive drool saliva was higher than that of oral cavity swab specimens (95% and 87%, respectively). A rapid, sensitive one-step extraction-free RT-qPCR test for detecting SARS-CoV-2 in passive drool saliva is operationally simple and can be easily implemented using existing testing sites, thus allowing high-throughput, rapid, and repeated testing of large populations. Furthermore, saliva testing is adequate to detect individuals in an asymptomatic screening program and can help improve voluntary screening compliance for those individuals averse to various forms of nasal collections.

A guide to the design of synthetic gene networks in mammalian cells

Synthetic biology aims to harness natural and synthetic biological parts and engineering them in new combinations and systems, producing novel therapies, diagnostics, bioproduction systems, and providing information on the mechanism of function of biological systems. Engineering cell function requires the rewiring or de novo construction of cell information processing networks. Using natural and synthetic signal processing elements, researchers have demonstrated a wide array of signal sensing, processing and propagation modules, using transcription, translation, or post-translational modification to program new function. The toolbox for synthetic network design is ever-advancing and has still ample room to grow. Here, we review the diversity of synthetic gene networks, types of building modules, techniques of regulation, and their applications.

CRISPRa-mediated FOXP3 gene upregulation in mammalian cells

BACKGROUND

Forkhead box P3+ (FOXP3 +) regulatory T cells (Tregs) are a subset of lymphocytes, critical for the maintenance of immune homeostasis. Loss-of-function mutations of the FOXP3 gene in animal models and humans results in loss of differentiation potential into Treg cells and are responsible for several immune-mediated inflammatory diseases. Strategies of increasing FOXP3 expression represent a potential approach to increase the pool of Tregs within the lymphocyte population and may be employed in therapies of diverse autoimmune conditions. In the present study, a dCas9 CRISPR-based method was systematically employed to achieve upregulation and sustained high expression of endogenous FOXP3 in HEK293 and human Jurkat T cell lines through targeting of the core promotor, three known regulatory regions of the FOXP3 gene (CNS1-3), and two additional regions selected through extensive bioinformatics analysis (Cage1 and Cage2).

RESULTS

Using an activator-domain fusion based dCas9 transcription activator, robust upregulation of FOXP3 was achieved, and an optimal combination of single guide RNAs was selected, which exerted an additive effect on FOXP3 gene upregulation. Simultaneous targeting of FOXP3 and EOS, a transcription factor known to act in concert with FOXP3 in initiating a Treg phenotype, resulted in upregulation of FOXP3 downstream genes CD25 and TNFR2. When compared to ectopic expression of FOXP3 via plasmid electroporation, upregulation of endogenous FOXP3 via the Cas9-based method resulted in prolonged expression of FOXP3 in Jurkat cells.

CONCLUSIONS

Transfection of both HEK293 and Jurkat cells with dCas9-activators showed that regulatory regions downstream and upstream of FOXP3 promoter can be very potent transcription inducers in comparison to targeting the core promoter. While introduction of genes by conventional methods of gene therapy may involve a risk of insertional mutagenesis due to viral integration into the genome, transient up- or down-regulation of transcription by a CRISPR-dCas9 approach may resolve this safety concern. dCas9-based systems provide great promise in DNA footprint-free phenotype perturbations (perturbation without the risk of DNA damage) to drive development of transcription modulation-based therapies.

Design of fast proteolysis-based signaling and logic circuits in mammalian cells

Cellular signal transduction is predominantly based on protein interactions and their post-translational modifications, which enable a fast response to input signals. Owing to difficulties in designing new unique protein-protein interactions, designed cellular logic has focused on transcriptional regulation; however, that process has a substantially slower response, because it requires transcription and translation. Here, we present de novo design of modular, scalable signaling pathways based on proteolysis and designed coiled coils (CC) and implemented in mammalian cells. A set of split proteases with highly specific orthogonal cleavage motifs was constructed and combined with strategically positioned cleavage sites and designed orthogonal CC dimerizing domains with tunable affinity for competitive displacement after proteolytic cleavage. This framework enabled the implementation of Boolean logic functions and signaling cascades in mammalian cells. The designed split-protease-cleavable orthogonal-CC-based (SPOC) logic circuits enable response to chemical or biological signals within minutes rather than hours and should be useful for diverse medical and nonmedical applications.

Data Science Issues in Studying Protein–RNA Interactions with CLIP Technologies

An interplay of experimental and computational methods is required to achieve a comprehensive understanding of protein–RNA interactions. UV crosslinking and immunoprecipitation (CLIP) identifies endogenous interactions by sequencing RNA fragments that copurify with a selected RNA-binding protein under stringent conditions. Here we focus on approaches for the analysis of the resulting data and appraise the methods for peak calling, visualization, analysis, and computational modeling of protein–RNA binding sites. We advocate that the sensitivity and specificity of data be assessed in combination for computational quality control. Moreover, we demonstrate the value of analyzing sequence motif enrichment in peaks assigned from CLIP data and of visualizing RNA maps, which examine the positional distribution of peaks around regulated landmarks in transcripts. We use these to assess how variations in CLIP data quality and in different peak calling methods affect the insights into regulatory mechanisms. We conclude by discussing future opportunities for the computational analysis of protein–RNA interaction experiments.