Optogenetic Control Reveals Differential Promoter Interpretation of Transcription Factor Nuclear Translocation Dynamics
2020; 11 (4): 336-+
Gene expression is thought to be affected not only by the concentration of transcription factors (TFs) but also the dynamics of their nuclear translocation. Testing this hypothesis requires direct control of TF dynamics. Here, we engineer CLASP, an optogenetic tool for rapid and tunable translocation of a TF of interest. Using CLASP fused to Crz1, we observe that, for the same integrated concentration of nuclear TF over time, changing input dynamics changes target gene expression: pulsatile inputs yield higher expression than continuous inputs, or vice versa, depending on the target gene. Computational modeling reveals that a dose-response saturating at low TF input can yield higher gene expression for pulsatile versus continuous input, and that multi-state promoter activation can yield the opposite behavior. Our integrated tool development and modeling approach characterize promoter responses to Crz1 nuclear translocation dynamics, extracting quantitative features that may help explain the differential expression of target genes.
View details for DOI 10.1016/j.cels.2020.08.009
View details for Web of Science ID 000582118000003
View details for PubMedID 32898473
View details for PubMedCentralID PMC7648432
De novo design of bioactive protein switches
2019; 572 (7768): 205-+
Allosteric regulation of protein function is widespread in biology, but is challenging for de novo protein design as it requires the explicit design of multiple states with comparable free energies. Here we explore the possibility of designing switchable protein systems de novo, through the modulation of competing inter- and intramolecular interactions. We design a static, five-helix 'cage' with a single interface that can interact either intramolecularly with a terminal 'latch' helix or intermolecularly with a peptide 'key'. Encoded on the latch are functional motifs for binding, degradation or nuclear export that function only when the key displaces the latch from the cage. We describe orthogonal cage-key systems that function in vitro, in yeast and in mammalian cells with up to 40-fold activation of function by key. The ability to design switchable protein functions that are controlled by induced conformational change is a milestone for de novo protein design, and opens up new avenues for synthetic biology and cell engineering.
View details for DOI 10.1038/s41586-019-1432-8
View details for Web of Science ID 000479172800039
View details for PubMedID 31341284
View details for PubMedCentralID PMC6733528
Modular and tunable biological feedback control using a de novo protein switch
2019; 572 (7768): 265-+
De novo-designed proteins1-3 hold great promise as building blocks for synthetic circuits, and can complement the use of engineered variants of natural proteins4-7. One such designer protein-degronLOCKR, which is based on 'latching orthogonal cage-key proteins' (LOCKR) technology8-is a switch that degrades a protein of interest in vivo upon induction by a genetically encoded small peptide. Here we leverage the plug-and-play nature of degronLOCKR to implement feedback control of endogenous signalling pathways and synthetic gene circuits. We first generate synthetic negative and positive feedback in the yeast mating pathway by fusing degronLOCKR to endogenous signalling molecules, illustrating the ease with which this strategy can be used to rewire complex endogenous pathways. We next evaluate feedback control mediated by degronLOCKR on a synthetic gene circuit9, to quantify the feedback capabilities and operational range of the feedback control circuit. The designed nature of degronLOCKR proteins enables simple and rational modifications to tune feedback behaviour in both the synthetic circuit and the mating pathway. The ability to engineer feedback control into living cells represents an important milestone in achieving the full potential of synthetic biology10,11,12. More broadly, this work demonstrates the large and untapped potential of de novo design of proteins for generating tools that implement complex synthetic functionalities in cells for biotechnological and therapeutic applications.
View details for DOI 10.1038/s41586-019-1425-7
View details for Web of Science ID 000479172800051
View details for PubMedID 31341280
Multi-directional dynamic model for traumatic brain injury detection.
Journal of neurotrauma
Given the worldwide adverse impact of traumatic brain injury (TBI) on the human population, its diagnosis and prediction are of utmost importance. Historically, many studies have focused on associating head kinematics to brain injury risk. Recently, there has been a push towards using computationally expensive finite element (FE) models of the brain to create tissue deformation metrics of brain injury. Here, we develop a new brain injury metric, the Brain Angle Metric (BAM), based on the dynamics of a 3 degree-of-freedom lumped parameter brain model. The brain model is built based on the measured natural frequencies of an FE brain model simulated with live human impact data. We show it can be used to rapidly estimate peak brain strains experienced during head rotational accelerations that cause mild TBI. On our dataset, the simplified model correlates with peak principal FE strain (R2=0.82). Further, coronal and axial brain model displacement correlated with fiber-oriented peak strain in the corpus callosum (R2=0.77). Our proposed injury metric BAM uses the maximum angle predicted by our brain model and is compared against a number of existing rotational and translational kinematic injury metrics on a dataset of head kinematics from 27 clinically diagnosed injuries and 887 non-injuries. We found that BAM performed comparably to peak angular acceleration, translational acceleration, and angular velocity in classifying injury and non-injury events. Metrics which separated time traces into their directional components had improved model deviance to those which combined components into a single time trace magnitude. Our brain model can be used in future work to rapidly approximate the peak strain resulting from mild to moderate head impacts and to quickly assess brain injury risk.
View details for DOI 10.1089/neu.2018.6340
View details for PubMedID 31856650
MULTI-DIRECTIONAL DYNAMIC INJURY METRIC FOR MILD BRAIN TRAUMA DETECTION
MARY ANN LIEBERT, INC. 2017: A47
View details for Web of Science ID 000404530400125