A role for pH dynamics regulating transcription factor DNA binding selectivity.

Intracellular pH (pHi) dynamics regulates diverse cell processes such as proliferation, dysplasia, and differentiation, often mediated by the protonation state of a functionally critical histidine residue in endogenous pH sensing proteins. How pHi dynamics can directly regulate gene expression and whether transcription factors can function as pH sensors has received limited attention. We tested the prediction that transcription factors with a histidine in their DNA binding domain (DBD) that forms hydrogen bonds with nucleotides can have pH-regulated activity, which is relevant to more than 85 transcription factors in distinct families, including FOX, KLF, SOX and MITF/Myc. Focusing on FOX family transcription factors, we used unbiased SELEX-seq to identify pH-dependent DNA binding motif preferences, then confirm pH-regulated binding affinities for FOXC2, FOXM1, and FOXN1 to a canonical FkhP DNA motif that are 2.5 to 7.5 greater at pH 7.0 compared with pH 7.5. For FOXC2, we also find greater activity for an FkhP motif at lower pHi in cells and that pH-regulated binding and activity are dependent on a conserved histidine (His122) in the DBD. RNA-seq with FOXC2 also reveals pH-dependent differences in enriched promoter motifs. Our findings identify pH-regulated transcription factor-DNA binding selectivity with relevance to how pHi dynamics can regulate gene expression for myriad cell behaviours.

Identifying FUS amyotrophic lateral sclerosis disease signatures in patient dermal fibroblasts.

Amyotrophic lateral sclerosis (ALS) is a rapidly progressing, highly heterogeneous neurodegenerative disease, underscoring the importance of obtaining information to personalize clinical decisions quickly after diagnosis. Here, we investigated whether ALS-relevant signatures can be detected directly from biopsied patient fibroblasts. We profiled familial ALS (fALS) fibroblasts, representing a range of mutations in the fused in sarcoma (FUS) gene and ages of onset. To differentiate FUS fALS and healthy control fibroblasts, machine-learning classifiers were trained separately on high-content imaging and transcriptional profiles. "Molecular ALS phenotype" scores, derived from these classifiers, captured a spectrum from disease to health. Interestingly, these scores negatively correlated with age of onset, identified several pre-symptomatic individuals and sporadic ALS (sALS) patients with FUS-like fibroblasts, and quantified "movement" of FUS fALS and "FUS-like" sALS toward health upon FUS ASO treatment. Taken together, these findings provide evidence that non-neuronal patient fibroblasts can be used for rapid, personalized assessment in ALS.

BCR::ABL1 kinase N-lobe mutants confer moderate to high degrees of resistance to asciminib.

ABSTRACT: Secondary kinase domain mutations in BCR::ABL1 represent the most common cause of resistance to tyrosine kinase inhibitor (TKI) therapy in patients with chronic myeloid leukemia. The first 5 approved BCR::ABL1 TKIs target the adenosine triphosphate (ATP)-binding pocket. Mutations confer resistance to these ATP-competitive TKIs and those approved for other malignancies by decreasing TKI affinity and/or increasing ATP affinity. Asciminib, the first highly active allosteric TKI approved for any malignancy, targets an allosteric regulatory pocket in the BCR::ABL1 kinase C-lobe. As a non-ATP-competitive inhibitor, the activity of asciminib is predicted to be impervious to increases in ATP affinity. Here, we report several known mutations that confer resistance to ATP-competitive TKIs in the BCR::ABL1 kinase N-lobe that are distant from the asciminib binding pocket yet unexpectedly confer in vitro resistance to asciminib. Among these is BCR::ABL1 M244V, which confers clinical resistance even to escalated asciminib doses. We demonstrate that BCR::ABL1 M244V does not impair asciminib binding, thereby invoking a novel mechanism of resistance. Molecular dynamic simulations of the M244V substitution implicate stabilization of an active kinase conformation through impact on the α-C helix as a mechanism of resistance. These N-lobe mutations may compromise the clinical activity of ongoing combination studies of asciminib with ATP-competitive TKIs.

MV-based relative electron density estimation (iMREDe) for MR-LINAC dose calculation.

BACKGROUND: MR-LINAC systems have been increasingly utilized for real-time imaging in adaptive treatments worldwide. Challenges in MR representation of air cavities and subsequent estimation of electron density maps impede planning efficiency and may lead to dose calculation uncertainties. PURPOSE: To demonstrate the generation of accurate electron density maps using the primary MV beam with a flat-panel imager. METHODS: The ViewRay MRIdian MR-LINAC system was modeled digitally for Monte Carlo simulations. Iron shimming, the magnetic field, and the proposed flat panel detector were included in the model. The effect of the magnetic field on the detector response was investigated. Acquisition of projections over 360 degrees was simulated for digital phantoms of the Catphan 505 phantom and a patient treated for Head and Neck cancer. Shim patterns on the projections were removed and detector noise linearity was assessed. Electron density maps were generated for the digital patient phantom using the flat-panel detector and compared with actual treatment planning CT generated electron density maps of the same patient. RESULTS: The effect of the magnetic field on the detector point-spread function (PSF) was found to be substantial for field strengths above 50 mT. Shims correction in the projection images using air normalization and in-painting effectively removed reconstruction artifacts without affecting noise linearity. The relative difference between reconstructed electron density maps from the proposed method and electron density maps generated from the treatment planning CT was 11% on average along all slices included in the iMREDe reconstruction. CONCLUSIONS: The proposed iMREDe technique demonstrated the feasibility of generating accurate electron densities for the ViewRay MRIdian MR-LINAC system with a flat-panel imager and the primary MV beam. This work is a step towards reducing the time and effort required for adaptive radiotherapy in the current ViewRay MR-LINAC systems.

A kV-MV approach to CBCT metal artifact reduction using multi-layer MV-CBCT.

Objective. To demonstrate that complete cone beam CT (CBCT) scans from both MV-energy and kV-energy LINAC sources can reduce metal artifacts in radiotherapy guidance, while maintaining standard-of-care x-ray doses levels.Approach. MV-CBCT and kV-CBCT scans are acquired at half normal dose. The impact of lowered dose on MV-CBCT data quality is mitigated by the use of a 4-layer MV-imager prototype and reduced LINAC energy settings (2.5 MV) to improve photon capture. Additionally, the MV-CBCT is used to determine the 3D position and pose of metal implants, which in turn is used to guide model-based poly-energetic correction and interleaving of the kV-CBCT and MV-CBCT data. Certain edge-preserving regularization steps incorporated into the model-based correction algorithm further reduce MV data noise.Main results. The method was tested in digital phantoms and a real pelvis phantom with large 2.5″ spherical inserts, emulating hip replacements of different materials. The proposed method demonstrated an appealing compromise between the high contrast of kV-CBCT and low artifact content of MV-CBCT. Contrast-to-noise improved 3-fold compared to MV-CBCT with a clinical 1-layer architecture at matched dose (37 mGy) and edge blur levels. Visual delineation of the bladder and prostate improved noteably over kV- or MV-CBCT alone.Significance. The proposed method demonstrates that a full MV-CBCT scan can be combined with kV-CBCT to reduce metal artifacts without resorting to complicated beam collimation strategies to limit the MV-CBCT dose contribution. Additionally, significant improvements in CNR can be achieved as compared to metal artifact reduction through current clinical MV-CBCT practices.

Monte Carlo model of a prototype flat-panel detector for multi-energy applications in radiotherapy.

BACKGROUND: The incorporation of multi-energy capabilities into radiotherapy flat-panel detectors offers advantages including enhanced soft tissue visualization by reduction of signal from overlapping anatomy such as bone in 2D image projections; creation of virtual monoenergetic images for 3D contrast enhancement, metal artefact reduction and direct acquisition of relative electron density. A novel dual-layer on-board imager offering dual energy processing capabilities is being designed. As opposed to other dual-energy implementation techniques which require separate acquisition with two different x-ray spectra, the dual-layer detector design enables simultaneous acquisition of high and low energy images with a single exposure. A computational framework is required to optimize the design parameters and evaluate detector performance for specific clinical applications. PURPOSE: In this study, we report on the development of a Monte Carlo (MC) model of the imager including model validation. METHODS: The stack-up of the dual-layer imager (DLI) was implemented in GEANT4 Application for Tomographic Emission (GATE). The DLI model has an active area of 43×43 cm2 , with top and bottom Cesium Iodide (CsI) scintillators of 600 and 800 µm thickness, respectively. Measurement of spatial resolution and imaging of dedicated multi-material dual-energy (DE) phantoms were used to validate the model. The modulation transfer function (MTF) of the detector was calculated for a 120 kVp x-ray spectrum using a 0.5 mm thick tantalum edge rotated by 2.5o . For imaging validation, the DE phantom was imaged using a 140 kVp x-ray spectrum. For both validation simulations, corresponding measurements were done using an initial prototype of the imager. Agreement between simulations and measurement was assessed using normalized root mean square error (NRMSE) and 1D profile difference for the MTF and phantom images respectively. Further comparison between measurement and simulation was made using virtual monoenergetic images (VMIs) generated from basis material images derived using precomputed look-up tables. RESULTS: The MTF of the bottom layer of the dual-layer model shows values decreasing more quickly with spatial frequency, compared to the top layer, due to the thicker bottom scintillator thickness and scatter from the top layer. A comparison with measurement shows NRMSE of 0.013 and 0.015 as well as identical MTF50 of 0.8 mm1 and 1.0 mm1 for the top and bottom layer respectively. For the DE imaging of the DE-phantom, although a maximum deviation of 3.3% is observed for the 10 mm aluminum and Teflon inserts at the top layer, the agreement for all other inserts is less than 2.2% of the measured value at both layers. Material decomposition of simulated scatter-free DE images gives an average accuracy in PMMA and aluminum composition of 4.9% and 10.3% for 11-30 mm PMMA and 1-10 mm aluminum objects respectively. A comparison of decomposed values using scatter containing measured and simulated DE images shows good agreement within statistical uncertainty. CONCLUSION: Validation using both MTF and phantom imaging shows good agreement between simulation and measurements. With the present configuration of the digital prototype, the model can generate material decomposed images and virtual monoenergetic images.

Integration of Genomic Sequencing Drives Therapeutic Targeting of PDGFRA in T-Cell Acute Lymphoblastic Leukemia/Lymphoblastic Lymphoma.

PURPOSE: Patients with relapsed or refractory T-cell acute lymphoblastic leukemia (T-ALL) or lymphoblastic lymphoma (T-LBL) have limited therapeutic options. Clinical use of genomic profiling provides an opportunity to identify targetable alterations to inform therapy. EXPERIMENTAL DESIGN: We describe a cohort of 14 pediatric patients with relapsed or refractory T-ALL enrolled on the Leukemia Precision-based Therapy (LEAP) Consortium trial (NCT02670525) and a patient with T-LBL, discovering alterations in platelet-derived growth factor receptor-α (PDGFRA) in 3 of these patients. We identified a novel mutation in PDGFRA, p.D842N, and used an integrated structural modeling and molecular biology approach to characterize mutations at D842 to guide therapeutic targeting. We conducted a preclinical study of avapritinib in a mouse patient-derived xenograft (PDX) model of FIP1L1-PDGFRA and PDGFRA p.D842N leukemia. RESULTS: Two patients with T-ALL in the LEAP cohort (14%) had targetable genomic alterations affecting PDGFRA, a FIP1-like 1 protein/PDGFRA (FIP1L1-PDGFRA) fusion and a novel mutation in PDGFRA, p.D842N. The D842N mutation resulted in PDGFRA activation and sensitivity to tested PDGFRA inhibitors. In a T-ALL PDX model, avapritinib treatment led to decreased leukemia burden, significantly prolonged survival, and even cured a subset of mice. Avapritinib treatment was well tolerated and yielded clinical benefit in a patient with refractory T-ALL. CONCLUSIONS: Refractory T-ALL has not been fully characterized. Alterations in PDGFRA or other targetable kinases may inform therapy for patients with refractory T-ALL who otherwise have limited treatment options. Clinical genomic profiling, in real time, is needed for fully informed therapeutic decision making.

Searching for molecular hypoxia sensors among oxygen-dependent enzymes.

The ability to sense and respond to changes in cellular oxygen levels is critical for aerobic organisms and requires a molecular oxygen sensor. The prototypical sensor is the oxygen-dependent enzyme PHD: hypoxia inhibits its ability to hydroxylate the transcription factor HIF, causing HIF to accumulate and trigger the classic HIF-dependent hypoxia response. A small handful of other oxygen sensors are known, all of which are oxygen-dependent enzymes. However, hundreds of oxygen-dependent enzymes exist among aerobic organisms, raising the possibility that additional sensors remain to be discovered. This review summarizes known and potential hypoxia sensors among human O2-dependent enzymes and highlights their possible roles in hypoxia-related adaptation and diseases.

Signal peptide mimicry primes Sec61 for client-selective inhibition.

Preventing the biogenesis of disease-relevant proteins is an attractive therapeutic strategy, but attempts to target essential protein biogenesis factors have been hampered by excessive toxicity. Here we describe KZR-8445, a cyclic depsipeptide that targets the Sec61 translocon and selectively disrupts secretory and membrane protein biogenesis in a signal peptide-dependent manner. KZR-8445 potently inhibits the secretion of pro-inflammatory cytokines in primary immune cells and is highly efficacious in a mouse model of rheumatoid arthritis. A cryogenic electron microscopy structure reveals that KZR-8445 occupies the fully opened Se61 lateral gate and blocks access to the lumenal plug domain. KZR-8445 binding stabilizes the lateral gate helices in a manner that traps select signal peptides in the Sec61 channel and prevents their movement into the lipid bilayer. Our results establish a framework for the structure-guided discovery of novel therapeutics that selectively modulate Sec61-mediated protein biogenesis.

Dissecting the effects of GTPase and kinase domain mutations on LRRK2 endosomal localization and activity.

Parkinson's disease-causing leucine-rich repeat kinase 2 (LRRK2) mutations lead to varying degrees of Rab GTPase hyperphosphorylation. Puzzlingly, LRRK2 GTPase-inactivating mutations-which do not affect intrinsic kinase activity-lead to higher levels of cellular Rab phosphorylation than kinase-activating mutations. Here, we investigate whether mutation-dependent differences in LRRK2 cellular localization could explain this discrepancy. We discover that blocking endosomal maturation leads to the rapid formation of mutant LRRK2+ endosomes on which LRRK2 phosphorylates substrate Rabs. LRRK2+ endosomes are maintained through positive feedback, which mutually reinforces membrane localization of LRRK2 and phosphorylated Rab substrates. Furthermore, across a panel of mutants, cells expressing GTPase-inactivating mutants form strikingly more LRRK2+ endosomes than cells expressing kinase-activating mutants, resulting in higher total cellular levels of phosphorylated Rabs. Our study suggests that the increased probability that LRRK2 GTPase-inactivating mutants are retained on intracellular membranes compared to kinase-activating mutants leads to higher substrate phosphorylation.

Mutations in α-synuclein, TDP-43 and tau prolong protein half-life through diminished degradation by lysosomal proteases.

BACKGROUND: Autosomal dominant mutations in α-synuclein, TDP-43 and tau are thought to predispose to neurodegeneration by enhancing protein aggregation. While a subset of α-synuclein, TDP-43 and tau mutations has been shown to increase the structural propensity of these proteins toward self-association, rates of aggregation are also highly dependent on protein steady state concentrations, which are in large part regulated by their rates of lysosomal degradation. Previous studies have shown that lysosomal proteases operate precisely and not indiscriminately, cleaving their substrates at very specific linear amino acid sequences. With this knowledge, we hypothesized that certain coding mutations in α-synuclein, TDP-43 and tau may lead to increased protein steady state concentrations and eventual aggregation by an alternative mechanism, that is, through disrupting lysosomal protease cleavage recognition motifs and subsequently conferring protease resistance to these proteins. RESULTS: To test this possibility, we first generated comprehensive proteolysis maps containing all of the potential lysosomal protease cleavage sites for α-synuclein, TDP-43 and tau. In silico analyses of these maps indicated that certain mutations would diminish cathepsin cleavage, a prediction we confirmed utilizing in vitro protease assays. We then validated these findings in cell models and induced neurons, demonstrating that mutant forms of α-synuclein, TDP-43 and tau are degraded less efficiently than wild type despite being imported into lysosomes at similar rates. CONCLUSIONS: Together, this study provides evidence that pathogenic mutations in the N-terminal domain of α-synuclein (G51D, A53T), low complexity domain of TDP-43 (A315T, Q331K, M337V) and R1 and R2 domains of tau (K257T, N279K, S305N) directly impair their own lysosomal degradation, altering protein homeostasis and increasing cellular protein concentrations by extending the degradation half-lives of these proteins. These results also point to novel, shared, alternative mechanism by which different forms of neurodegeneration, including synucleinopathies, TDP-43 proteinopathies and tauopathies, may arise. Importantly, they also provide a roadmap for how the upregulation of particular lysosomal proteases could be targeted as potential therapeutics for human neurodegenerative disease.

Fighting Plasmodium chloroquine resistance with acetylenic chloroquine analogues.

Malaria is among the tropical diseases that cause the most deaths in Africa. Around 500,000 malaria deaths are reported yearly among African children under the age of five. Chloroquine (CQ) is a low-cost antimalarial used worldwide for the treatment of Plasmodium vivax malaria. Due to resistance mechanisms, CQ is no longer effective against most malaria cases caused by P. falciparum. The World Health Organization recommends artemisinin combination therapies for P. falciparum malaria, but resistance is emerging in Southeast Asia and some parts of Africa. Therefore, new medicines for treating malaria are urgently needed. Previously, our group identified the 4-aminoquinoline DAQ, a CQ analog containing an acetylenic bond in its side chain, which overcomes CQ resistance in K1 P. falciparum strains. In this work, the antiplasmodial profile, drug-like properties, and pharmacokinetics of DAQ were further investigated. DAQ showed no cross-resistance against standard CQ-resistant strains (e.g., Dd2, IPC 4912, RF12) nor against P. falciparum and P. vivax isolates from patients in the Brazilian Amazon. Using drug pressure assays, DAQ showed a low propensity to generate resistance. DAQ showed considerable solubility but low metabolic stability. The main metabolite was identified as a mono N-deethylated derivative (DAQM), which also showed significant inhibitory activity against CQ-resistant P. falciparum strains. Our findings indicated that the presence of a triple bond in CQ-analogues may represent a low-cost opportunity to overcome known mechanisms of resistance in the malaria parasite.

Cysteine Oxidation in Proteins: Structure, Biophysics, and Simulation.

Cysteine side chains can exist in distinct oxidation states depending on the pH and redox potential of the environment, and cysteine oxidation plays important yet complex regulatory roles. Compared with the effects of post-translational modifications such as phosphorylation, the effects of oxidation of cysteine to sulfenic, sulfinic, and sulfonic acid on protein structure and function remain relatively poorly characterized. We present an analysis of the role of cysteine reactivity as a regulatory factor in proteins, emphasizing the interplay between electrostatics and redox potential as key determinants of the resulting oxidation state. A review of current computational approaches suggests underdeveloped areas of research for studying cysteine reactivity through molecular simulations.

Assessing the Activation of Tyrosine Kinase KIT through Free Energy Calculations.

KIT is a type 3 receptor tyrosine kinase that plays a crucial role in cellular growth and proliferation. Mutations in KIT can dysregulate its active-inactive equilibrium. Activating mutations drive cancer growth, while deactivating mutations result in the loss of skin and hair pigmentation in a disease known as piebaldism. Here, we propose a method based on molecular dynamics and free energy calculations to predict the functional effect of KIT mutations. Our calculations may have important clinical implications by defining the functional significance of previously uncharacterized KIT mutations and guiding targeted therapy.

Structure-based discovery of nonopioid analgesics acting through the α2A-adrenergic receptor.

Because nonopioid analgesics are much sought after, we computationally docked more than 301 million virtual molecules against a validated pain target, the α2A-adrenergic receptor (α2AAR), seeking new α2AAR agonists chemotypes that lack the sedation conferred by known α2AAR drugs, such as dexmedetomidine. We identified 17 ligands with potencies as low as 12 nanomolar, many with partial agonism and preferential Gi and Go signaling. Experimental structures of α2AAR complexed with two of these agonists confirmed the docking predictions and templated further optimization. Several compounds, including the initial docking hit '9087 [mean effective concentration (EC50) of 52 nanomolar] and two analogs, '7075 and PS75 (EC50 4.1 and 4.8 nanomolar), exerted on-target analgesic activity in multiple in vivo pain models without sedation. These newly discovered agonists are interesting as therapeutic leads that lack the liabilities of opioids and the sedation of dexmedetomidine.

Droughts and societal change: The environmental context for the emergence of Islam in late Antique Arabia.

In Arabia, the first half of the sixth century CE was marked by the demise of Himyar, the dominant power in Arabia until 525 CE. Important social and political changes followed, which promoted the disintegration of the major Arabian polities. Here, we present hydroclimate records from around Southern Arabia, including a new high-resolution stalagmite record from northern Oman. These records clearly indicate unprecedented droughts during the sixth century CE, with the most severe aridity persisting between ~500 and 530 CE. We suggest that such droughts undermined the resilience of Himyar and thereby contributed to the societal changes from which Islam emerged.

Settlement, environment, and climate change in SW Anatolia: Dynamics of regional variation and the end of Antiquity.

This paper develops a regional dataset of change at 381 settlements for Lycia-Pamphylia in southwest Anatolia (Turkey) from volume 8 of the Tabula Imperii Byzantini-a compilation of historical toponyms and archaeological evidence. This region is rich in archaeological remains and high-quality paleo-climatic and -environmental archives. Our archaeological synthesis enables direct comparison of these datasets to discuss current hypotheses of climate impacts on historical societies. A Roman Climatic Optimum, characterized by warmer and wetter conditions, facilitating Roman expansion in the 1st-2nd centuries CE cannot be supported here, as Early Byzantine settlement did not benefit from enhanced precipitation in the 4th-6th centuries CE as often supposed. However, widespread settlement decline in a period with challenging archaeological chronologies (c. 550-650 CE) was likely caused by a "perfect storm" of environmental, climatic, seismic, pathogenic and socio-economic factors, though a shift to drier conditions from c. 460 CE appears to have preceded other factors by at least a century.

GraPES: The Granule Protein Enrichment Server for prediction of biological condensate constituents.

Phase separation-based condensate formation is a novel working paradigm in biology, helping to rationalize many important cellular phenomena including the assembly of membraneless organelles. Uncovering the functional impact of cellular condensates requires a better knowledge of these condensates' constituents. Herein, we introduce the webserver GraPES (Granule Protein Enrichment Server), a user-friendly online interface containing the MaGS and MaGSeq predictors, which provide propensity scores for proteins' localization into cellular condensates. Our webpage contains models trained on human (Homo sapiens) and yeast (Saccharomyces cerevisiae) stress granule proteins. MaGS utilizes experimentally-based protein features for prediction, whereas MaGSeq is an entirely protein sequence-based implementation. GraPES is implemented in HTML/CSS and Javascript and is freely available for public use at https://grapes.msl.ubc.ca/. Documentation for using the provided webtools, descriptions of their methodology, and implementation notes can be found on the webpage.