Publications

Deciphering the regulatory code of gene expression and interpreting the transcriptional effects of genome variation are critical challenges in human genetics. Modern experimental technologies have resulted in an abundance of data, enabling the development of sequence-based deep learning models that link patterns embedded in DNA to the biochemical and regulatory properties contributing to transcriptional regulation, including modeling epigenetic marks, 3D genome organization, and gene expression, with tissue and cell-type specificity. Such methods can predict the functional consequences of any noncoding variant in the human genome, even rare or never-before-observed variants, and systematically characterize their consequences beyond what is tractable from experiments or quantitative genetics studies alone. Recently, the development and application of interpretability approaches have led to the identification of key sequence patterns contributing to the predicted tasks, providing insights into the underlying biological mechanisms learned and revealing opportunities for improvement in future models.

In cells, transcription is tightly regulated on multiple layers. The condensation of the transcription machinery into distinct phases is hypothesized to spatio-temporally fine tune RNA polymerase II behaviour during two key stages, transcription initiation and the elongation of the nascent RNA transcripts. However, it has remained unclear whether these phases would mix when present at the same time or remain distinct chemical environments; either as multi-phase condensates or by forming entirely separate condensates. Here we combine particle-based multi-scale simulations and experiments in the model organism C. elegans to characterise the biophysical properties of RNA polymerase II condensates. Both simulations and the in vivo work describe a lower critical solution temperature (LCST) behaviour of RNA Polymerase II, with condensates dissolving at lower temperatures whereas higher temperatures promote condensate stability, which highlights that these condensates are physio-chemically distinct from heterochromatin condensates. The LCST behavior of CTD correlates with gradual shifts in the transcription program but is largely uncoupled from the classical stress response. Expanding the simulations we model how the degree of phosphorylation of the disordered C-terminal domain of RNA polymerase II (CTD), which is characteristic for each step of transcription, controls the existence and morphology of multi-phasic condensates. We show that the two phases putatively underpinning the initiation of transcription and transcription elongation constitute distinct chemical environments and are in agreement with RNA polymerase II condensates observed in C. elegans embryos by super resolution microscopy. Our analysis shows how depending on its post transcriptional modifications and its interaction partner a single protein can form multiple partially engulfed condensates, potentially promoting the selective recruitment of additional factors to these two phases.

Active nematics exhibit spontaneous flows through a well-known linear instability of the uniformly-aligned quiescent state. Here we show that even a linearly stable uniform state can experience a nonlinear instability, resulting in a discontinuous transition to spontaneous flows. In this case, quiescent and flowing states may coexist. Through a weakly nonlinear analysis and a numerical study, we trace the bifurcation diagram of striped patterns and show that the underlying pitchfork bifurcation switches from supercritical (continuous) to subcritical (discontinuous) by varying the flow-alignment parameter. We predict that the discontinuous spontaneous flow transition occurs for a wide range of parameters, including systems of contractile flow-aligning rods. Our predictions are relevant to active nematic turbulence and can potentially be tested in experiments on either cell layers or active cytoskeletal suspensions.

Short interfering RNA (siRNA) therapeutics have soared in popularity due to their highly selective and potent targeting of faulty genes, providing a non-palliative approach to address diseases. Despite their potential, effective transfection of siRNA into cells requires the assistance of an accompanying vector. Vectors constructed from non-viral materials, while offering safer and non-cytotoxic profiles, often grapple with lackluster loading and delivery efficiencies, necessitating substantial milligram quantities of expensive siRNA to confer the desired downstream effects. We detail the recombinant synthesis of a diverse series of coiled-coil supercharged protein (CSP) biomaterials systematically designed to investigate the impact of two arginine point mutations (Q39R and N61R) and decahistidine tags on liposomal siRNA delivery. The most efficacious variant, N8, exhibits a twofold increase in its affinity to siRNA and achieves a twofold enhancement in transfection activity with minimal cytotoxicity in vitro. Subsequent analysis unveils the destabilizing effect of the Q39R and N61R supercharging mutations and the incorporation of C-terminal decahistidine tags on α-helical secondary structure. Cross-correlational regression analyses reveal that the amount of helical character in these mutants is key in N8's enhanced siRNA complexation and downstream delivery efficiency.

Post-translational modifications (PTMs) of proteins play a vital role in their function and stability. These modifications influence protein folding, signaling, protein-protein interactions, enzyme activity, binding affinity, aggregation, degradation, and much more. To date, over 400 types of PTMs have been described, representing chemical diversity well beyond the genetically encoded amino acids. Such modifications pose a challenge to the successful design of proteins, but also represent a major opportunity to diversify the protein engineering toolbox. To this end, we first trained artificial neural networks (ANNs) to predict eighteen of the most abundant PTMs, including protein glycosylation, phosphorylation, methylation, and deamidation. In a second step, these models were implemented inside the computational protein modeling suite Rosetta, which allows flexible combination with existing protocols to model the modified sites and understand their impact on protein stability as well as function. Lastly, we developed a new design protocol that either maximizes or minimizes the predicted probability of a particular site being modified. We find that this combination of ANN prediction and structure-based design can enable the modification of existing, as well as the introduction of novel, PTMs. The potential applications of our work include, but are not limited to, glycan masking of epitopes, strengthening protein-protein interactions through phosphorylation, as well as protecting proteins from deamidation liabilities. These applications are especially important for the design of new protein therapeutics where PTMs can drastically change the therapeutic properties of a protein. Our work adds novel tools to Rosetta’s protein engineering toolbox that allow for the rational design of PTMs.

The receptor tyrosine kinase (RTK)/Extracellular Signal-Regulated Kinase (ERK) signaling pathway controls cell proliferation, differentiation, and survival. How ERK activation is relayed to its phosphorylation targets is not well understood. The transcriptional repressor Capicua (Cic) has emerged as a key target for ERK-mediated downregulation in Drosophila and mammals, and mutations in human CIC result in cancer and neurological diseases. Phosphorylation by ERK is critical for Cic downregulation, but the identities of phosphosites in Drosophila Cic are unknown. Here, we identify sites of phosphorylation in Cic that are directly targeted by ERK and validate their developmental functions in vivo using mutant Cic variants. Cic phosphosites are distributed throughout the length of the protein, and a group of centrally located sites appears to have a primary role in Cic downregulation. Cic mutated in 20 high-confidence sites behaves as a “super-repressor” in vivo that is largely insensitive to ERK-mediated downregulation, despite fully retaining the ability to bind to ERK. No single site is sufficient to turn off Cic activity; instead, we find that ERK must phosphorylate multiple sites in Cic simultaneously to achieve full downregulation. This multisite phosphorylation likely targets phosphodegrons that are recognized by ubiquitin ligases such as Ago/FBXW7 and contributes to Cic degradation. This study advances our understanding of the molecular mechanisms of signal interpretation downstream of the RTK/ERK signaling network.

Synthetic biology is creating genetically engineered organisms at an increasing rate for many potentially valuable applications, but this potential comes with the risk of misuse or accidental release. To begin to address this issue, we have developed a system called GUARDIAN that can automatically detect signatures of engineering in DNA sequencing data, and we have conducted a blinded test of this system using a curated Test and Evaluation (T&E) data set. GUARDIAN uses an ensemble approach based on the guiding principle that no single approach is likely to be able to detect engineering with perfect accuracy. Critically, ensembling enables GUARDIAN to detect sequence inserts in 13 target organisms with a high degree of specificity that requires no subject matter expert (SME) review.

Neurons from layer II of the entorhinal cortex (ECII) are the first to accumulate tau protein aggregates and degenerate during prodromal Alzheimer’s disease. Gaining insight into the molecular mechanisms underlying this vulnerability will help reveal genes and pathways at play during incipient stages of the disease. Here, we use a data-driven functional genomics approach to model ECII neurons in silico and identify the proto-oncogene DEK as a regulator of tau pathology.

We show that epigenetic changes caused by Dek silencing alter activity-induced transcription, with major effects on neuronal excitability. This is accompanied by the gradual accumulation of tau in the somatodendritic compartment of mouse ECII neurons in vivo, reactivity of surrounding microglia, and microglia-mediated neuron loss. These features are all characteristic of early Alzheimer’s disease.

The existence of a cell-autonomous mechanism linking Alzheimer’s disease pathogenic mechanisms in the precise neuron type where the disease starts provides unique evidence that synaptic homeostasis dysregulation is of central importance in the onset of tau pathology in Alzheimer’s disease.

Organophosphates (OPs) are a class of neurotoxic acetylcholinesterase inhibitors including widely used pesticides as well as nerve agents such as VX and VR. Current treatment of these toxins relies on reactivating acetylcholinesterase, which remains ineffective. Enzymatic scavengers are of interest for their ability to degrade OPs systemically before they reach their target. Here we describe a library of computationally designed variants of phosphotriesterase (PTE), an enzyme that is known to break down OPs. The mutations G208D, F104A, K77A, A80V, H254G, and I274N broadly improve catalytic efficiency of VX and VR hydrolysis without impacting the structure of the enzyme. The mutation I106 A improves catalysis of VR and L271E abolishes activity, likely due to disruptions of PTE's structure. This study elucidates the importance of these residues and contributes to the design of enzymatic OP scavengers with improved efficiency.