Biology subjects

George, A.

Publications and source records attributed to George, A..

At least 55 records · Page 3Linked to original sources

bioRxiv2022

Human endometrial KISS1R inhibits stromal cell decidualization in a manner associated with a reduction in ESR1 levels

Defective endometrial stromal cell decidualization is a major cause of recurrent implantation failure (RIF), a condition with a prevalence of [~]15%. To treat RIF, a stronger understanding of the endometrial factors that regulate decidualization is required. Here we studied the role of the kisspeptin receptor (KISS1R) in regulating human endometrial stromal cell (HESC) decidualization. Our data revealed KISS1R inhibits HESC decidualization in vitro in a manner associated with a striking reduction in ESR1 protein levels. To determine whether KISSR inhibition of decidualization results from reduced ESR1 levels we expressed the dominant negative ESR1-46 isoform in decidualizing HESCs. We found that expression of ESR1-46 in decidualizing HESCs ablated the expression of ESR1-66 and ESR1-54 isomers, and blocked decidualization. Interestingly, when ESR1-64 was co-expressed with ESR1-46, ESR1-66 and ESR1-54 expression was restored and decidualization was rescued. Taken together, these results suggest that KISS1R inhibits HESC decidualization by downregulating ESR1 levels. Based on our findings, we suggest that by inhibiting HESC decidualization, KISS1R regulates the depth of embryo invasion of the stroma, a requirement for a successful pregnancy.

cell biology↗

bioRxiv2022

Quantifying cooperative multisite binding through Bayesian inference

Multistep protein-protein interactions underlie most biological processes, but their characterization through methods such as isothermal titration calorimetry (ITC) is largely confined to simple models that provide little information on the intermediate, individual steps. In this study, we primarily examine the essential hub protein LC8, a small dimer that binds disordered regions of 100+ client proteins in two symmetrical grooves at the dimer interface. Mechanistic details of LC8 binding have remained elusive, hampered in part by ITC data analyses employing simple models that treat bivalent binding as a single event with a single binding affinity. We build on existing Bayesian ITC approaches to quantify thermodynamic parameters for multi-site binding interactions impacted by significant uncertainty in protein concentration. Using a two-site binding model, we model LC8 binding and identify positive cooperativity with high confidence for multiple client peptides. Application of an identical model to two-site binding between the coiled-coil dimer NudE and the intermediate chain of dynein reveals little evidence of cooperativity, in contrast to LC8. We propose that cooperativity in the LC8 system drives the formation of saturated 2:2 bound states, which play a functional role in many LC8 complexes. In addition to these system-specific findings, our work advances general ITC analysis in two ways. First, we describe a previously unrecognized mathematical ambiguity in concentrations in standard binding models and clarify how it impacts the precision with which binding parameters can be determined in cases of high uncertainty in analyte concentrations. Second, building on observations in the LC8 system, we develop a system-agnostic heat map of practical parameter identifiability calculated from synthetic data which demonstrates that certain binding parameters intrinsically inflate parameter uncertainty in ITC analysis, independent of experimental uncertainties. Author SummaryMulti-site protein-protein interactions govern many protein functions throughout the cell. Precise determination of thermodynamic constants of multi-site binding is a significant biophysical challenge, however. The application of complex models to multi-step interactions is difficult and hampered further by complications arising from uncertainty in analyte concentrations. To address these issues, we utilize Bayesian statistical techniques which calculate the likelihood of parameters giving rise to experimental observations to build probability density distributions for thermodynamic parameters of binding. To demonstrate the method and improve our understanding how the hub protein LC8 promotes dimerization of its 100+ binding partners, we test the pipeline on several of these partners and demonstrate that LC8 can bind clients cooperatively, driving interactions towards a fully bound functional state. We additionally examine an interaction between the dimer NudE and the intermediate chain of dynein, which does not appear to bind with cooperativity. Our work provides a solid foundation for future analysis of more complicated binding interactions, including oligomeric complexes formed between LC8 and clients with multiple LC8-binding sites.

biophysics↗

bioRxiv2022

Precise modelling and correction of a spectrum of β-thalassemic mutations in human erythroid cells by base editors

{beta}-thalassemia and HbE result from mutations in the {beta}-globin locus that impedes the production of functional {beta}-hemoglobin and represents one of the most common genetic disorders worldwide. Recent advances in genome engineering have opened up new therapeutic opportunities to directly correct these pathogenic mutations using base editors that install transition mutations (A>G and C>T) in the target region with minimal generation of indels. Herein, for the first time, we demonstrate the usage of base editor in the correction of point mutations spanning multiple regions of the HBB gene, including promoter, intron and exon. To this end, we have engineered human erythroid cells harbouring the diverse HBB mutations, thus eliminating the requirement of patient CD34+ HSPCs with desired mutations for the primary screening by base editors. We further performed precise creation and correction of individual HBB point mutations in human erythroid cells using base editors, which were effectively corrected in the HBB-engineered erythroid model. Intriguingly, most bystander effects produced by the base editor at the target site were reported to exhibit normal hemoglobin variants. Overall, our study provides the proof-of-concept for the precise, efficient and scarless creation and correction of various pathogenic mutations at the coding and non-coding regions of HBB gene in human erythroid cells using base editors and establishes a novel therapeutic platform for the treatment of {beta}-thalassemia/HbE patients. This study can be further explored in correcting the other monogenic disorders caused due to single base substitutions.

genomics↗

bioRxiv2022

Severe drought events trigger long-term salt marsh dieback in the Southeastern and Gulf of Mexico USA

The frequency of salt marsh dieback events has increased over the last 25 years with unknown consequences to the resilience of the ecosystem to accelerated sea level rise (SLR). Salt marsh ecosystems impacted by sudden vegetation dieback events were previously thought to recover naturally within a few months to years. In this study, we provide evidence that approximately 14% of total marsh area has not revegetated 10-years after a dieback event in Charleston, SC. Dieback onset coincided with a severe drought in 2012, and a second dieback event occurred in 2016 after a historic flood influenced by Hurricane Joaquin in October of 2015, with unvegetated zones reaching nearly 30% of total marsh area in 2017. Most affected areas were associated with lower elevation zones in the interior of the marsh (midmarsh). During the 2013 dieback event, we estimate that unvegetated midmarsh area expanded by 300%. Grass planting was shown to be an effective restoration practice, with restored plants having greater aboveground biomass than relict sites after two years of transplanting. A positive restoration outcome indicated that the stressors that caused the initial dieback are no longer present. Despite that, many dieback areas have not recovered naturally even as they are located within the typical elevation range of a healthy vegetated marsh. A mechanistic modelling approach was used to assess the effects of vegetation dieback on salt marsh resilience to SLR. Predictions indicate that a highly productive restored marsh (2000 g m-2 y-1) would persist at a moderate SLR rate of 60 cm 100 y-1, whereas a non- restored mudflat would lose all of its elevation capital after 100 years. Thus, rapid restoration of marsh dieback is critical to avoid further degradation. Also, failure to incorporate the increasing frequency and intensity of extreme climatic events which trigger irreversible marsh diebacks underestimates salt marsh vulnerability to climate change. At an elevated SLR rate of 122 cm 100 y-1, most likely an extreme climate change scenario, even highly productive ecosystems augmented by sediment placement would not keep pace with SLR. Thus, climate change mitigation actions are also urgently needed to preserve present-day marsh ecosystems.

ecology↗

bioRxiv2022

CyTOF-Lec: Single-cell glycomics analysis reveals glycan features defining cells differentially susceptible to HIV

High-parameter single-cell phenotyping has enabled in-depth classification and interrogation of immune cells, but to date has not allowed for glycan characterization. Here, we develop CyTOF-Lec as an approach to simultaneously characterize many protein and glycan features of human immune cells at the single-cell level. We implemented CyTOF-Lec to compare glycan features between different immune subsets from blood and multiple tissue compartments, and to characterize HIV-infected cell cultures. Using bioinformatics approaches to distinguish preferential infection of cellular subsets from viral-induced remodeling, we demonstrate that HIV upregulates the levels of cell surface fucose and sialic acid in a cell- intrinsic manner, and that memory CD4+ T cells co-expressing high levels of fucose and sialic acid are highly susceptible to HIV infection. Sialic acid levels were found to distinguish memory CD4+ T cell subsets expressing different amounts of viral entry receptors, pro-survival factors, homing receptors, and activation markers, and to play a direct role in memory CD4+ T cells susceptibility to HIV infection. The ability of sialic acid to distinguish memory CD4+ T cells with different susceptibilities to HIV infection was experimentally validated through sorting experiments. Together, these results suggest that HIV remodels not only cellular proteins but also glycans, and that glycan expression can differentiate memory CD4+ T cells with vastly different susceptibility to HIV infection.

immunology↗

bioRxiv2022

Sudden unexpected death in epilepsy is prevented by blocking postictal hypoxia

Epilepsy is at times a fatal disease. Sudden unexpected death in epilepsy (SUDEP) is the leading cause of mortality in people with intractable epilepsy and is defined by exclusion; non-accidental, non-toxicologic, and non-anatomic causes of death. While SUDEP often follows a bilateral tonic-clonic seizure, the mechanisms that ultimately lead to terminal apnea and then asystole remain elusive and there is a lack preventative treatments. Based on the observation that discrete seizures lead to local vasoconstriction, resulting in hypoperfusion, hypoxia and behavioural disturbances in the forebrain (Farrell et al., 2016), we reasoned that similar mechanisms may play a role in SUDEP when seizures invade the brainstem. Here we tested this neurovascular-based hypothesis of SUDEP in awake non-anesthetized mice by pharmacologically preventing seizure-induced vasoconstriction, with cyclooxygenase-2 or L-type calcium channel antagonists. In both acute and chronic mouse models of SUDEP, ibuprofen and nicardipine extended life. We also examined the potential role of spreading depolarization in the acute model of SUDEP. These data provide a proof of principle for the neurovascular hypothesis of SUDEP and the use of currently available treatments to prevent it.

neuroscience↗

bioRxiv2022

Hydrodynamic and Polyelectrolyte Properties of Actin Filaments: Theory and Experiments

Actin filaments polyelectrolyte and hydrodynamic properties, their interactions with the biological environment, and external force fields play an essential role in their biological activities in eukaryotic cellular processes. In this article, we introduce a unique approach that combines dynamics and electrophoresis light scattering experiments, an extended semiflexible worm-like chain model, and an asymmetric polymer length distribution theory to characterize the polyelectrolyte and hydrodynamic properties of actin filaments in aqueous electrolyte solutions. A fitting approach was used to optimize the theories and filament models for hydrodynamic conditions. We used the same sample and experimental conditions and considered several g-actin and polymerization buffers to elucidate the impact of their chemical composition, reducing agents, pH values, and ionic strengths on the filament translational diffusion coefficient, electrophoretic mobility, structure factor, asymmetric length distribution, effective filament diameter, electric charge, zeta potential, and semiflexibility. Compared to those values obtained from molecular structure models, our results revealed a lower value of the effective G-actin charge and a more significant value of the effective filament diameter due to the formation of the double layer of the electrolyte surrounding the filaments. Contrary to the data usually reported from electron micrographs, the lower values of our results for the persistence length and average contour filament length agree with the significant difference in the association rates at the filament ends that shift to sub-micro lengths, the maximum of the length distribution.

neuroscience↗

bioRxiv2021

Deep neural network analysis employing diffusion basis spectrum imaging metrics as classifiers improves prostate cancer detection and grading

Structural and cellular complexity of prostatic histopathology limits the accuracy of noninvasive detection and grading of prostate cancer (PCa). We addressed this limitation by employing a novel diffusion basis spectrum imaging (DBSI) to derive structurally-specific diffusion fingerprints reflecting various underlying prostatic structural and cellular components. We further developed diffusion histology imaging (DHI) by combining DBSI-derived structural fingerprints with a deep neural network (DNN) algorithm to more accurately classify different histopathological features and predict tumor grade in PCa. We examined 243 patients suspected with PCa using in vivo DBSI. The in vivo DBSI-derived diffusion metrics detected coexisting prostatic pathologies distinguishing inflammation, PCa, and benign prostatic hyperplasia. DHI distinguished PCa from benign peripheral and transition zone tissues with over 95% sensitivity and specificity. DHI also demonstrated over 90% sensitivity and specificity for Gleason score noninvasively. We present DHI as a novel diagnostic tool capable of noninvasive detection and grading of PCa. One sentence summaryDiffusion histology imaging noninvasively and accurately detects and grades prostate cancer.

bioinformatics↗

bioRxiv2021

Estimation of in-scanner head pose changes during structural MRI using a convolutional neural network trained on eye tracker video

IntroductionIn-scanner head motion is a common cause of reduced image quality in neuroimaging, and causes systematic brain-wide changes in cortical thickness and volumetric estimates derived from structural MRI scans. There are few widely available methods for measuring head motion during structural MRI. Here, we train a deep learning predictive model to estimate changes in head pose using video obtained from an in-scanner eye tracker during an EPI-BOLD acquisition with participants undertaking deliberate in-scanner head movements. The predictive model was used to estimate head pose changes during structural MRI scans, and correlated with cortical thickness and subcortical volume estimates. Methods21 healthy controls (age 32 {+/-} 13 years, 11 female) were studied. Participants carried out a series of stereotyped prompted in-scanner head motions during acquisition of an EPI-BOLD sequence with simultaneous recording of eye tracker video. Motion-affected and motion-free whole brain T1-weighted MRI were also obtained. Image coregistration was used to estimate changes in head pose over the duration of the EPI-BOLD scan, and used to train a predictive model to estimate head pose changes from the video data. Model performance was quantified by assessing the coefficient of determination (R2). We evaluated the utility of our technique by assessing the relationship between video-based head pose changes during structural MRI and (i) vertex-wise cortical thickness and (ii) subcortical volume estimates. ResultsVideo-based head pose estimates were significantly correlated with ground truth head pose changes estimated from EPI-BOLD imaging in a hold-out dataset. We observed a general brain-wide overall reduction in cortical thickness with increased head motion, with some isolated regions showing increased cortical thickness estimates with increased motion. Subcortical volumes were generally reduced in motion affected scans. ConclusionsWe trained a predictive model to estimate changes in head pose during structural MRI scans using in-scanner eye tracker video. The method is independent of individual image acquisition parameters and does not require markers to be to be fixed to the patient, suggesting it may be well suited to clinical imaging and research environments. Head pose changes estimated using our approach can be used as covariates for morphometric image analyses to improve the neurobiological validity of structural imaging studies of brain development and disease.

neuroscience↗

bioRxiv2020

Visualizing the cytosolic delivery of bioconjugated QDs into T cell lymphocytes

The aggregation state and endosomal trapping of engineered nanocarriers once internalized into cells remain poorly characterized. Here, we visualized the membrane penetrating dynamics of semiconductor quantum dots (QDs) into the cytosol of T cells on a single-cell and single-nanoparticle basis. We water solubilized CdSe/CdZnS QDs with polymer encapsulants functionalized with a cell-penetrating peptide composed of an Asp-Ser-Ser (DSS) repeat sequence. T cells tolerated the 24-h incubation with QDs at concentrations of 5 nM or lower. Single-particle imaging demonstrated that the number of internalized nanoparticles was dependent upon the concentration of the probes for both control (peptide-free) and DSS-QDs. DSS-QDs were mostly distributed as monomers, whereas the control QDs were aggregated into clusters. Single-particle tracking using total internal reflection and highly inclined illumination showed that DSS-QDs were stationary near the activating surface and mobile within the cytosol of the T cell. A correlation exhibited between the mobility and aggregation state of individual QD clusters, with monomeric DSS-QDs showing the highest mobility. In addition, monomeric DSS-QDs displayed much faster diffusion than the endosomes. A small-molecule endosome marker confirmed the absence of colocalization between endosomes and DSS-QDs, indicating their endosomal escape. The ability to deliver and track individual QDs in the cytosol of live T cells creates inroads for the optimization of drug delivery and gene therapy through the use of nanoparticles.

bioengineering↗

bioRxiv2020

SARS-CoV-2-specific T cells exhibit unique features characterized by robust helper function, lack of terminal differentiation, and high proliferative potential

Convalescing COVID-19 patients mount robust T cell responses against SARS-CoV-2, suggesting an important role for T cells in viral clearance. To date, the phenotypes of SARS-CoV-2-specific T cells remain poorly defined. Using 38-parameter CyTOF, we phenotyped longitudinal specimens of SARS-CoV-2-specific CD4+ and CD8+ T cells from nine individuals who recovered from mild COVID-19. SARS-CoV-2-specific CD4+ T cells were exclusively Th1 cells, and predominantly Tcm with phenotypic features of robust helper function. SARS-CoV-2-specific CD8+ T cells were predominantly Temra cells in a state of less terminal differentiation than most Temra cells. Subsets of SARS-CoV-2-specific T cells express CD127, can homeostatically proliferate, and can persist for over two months. Our results suggest that long-lived and robust T cell immunity is generated following natural SARS-CoV-2 infection, and support an important role for SARS-CoV-2-specific T cells in host control of COVID-19.

immunology↗

bioRxiv2020

BoneMA - Synthesis and Characterization of a Methacrylated Bone-derived Hydrogel for Bioprinting of Vascularized Tissues

It has long been proposed that recapitulating the extracellular matrix (ECM) of native human tissues in the laboratory may enhance the regenerative capacity of engineered scaffolds in-vivo. Organ- and tissue-derived decellularized ECM biomaterials have been widely used for tissue repair, especially due to their intrinsic biochemical cues that can facilitate repair and regeneration. The main purpose of this study was to synthesize a new photocrosslinkable human bone-derived ECM hydrogel for bioprinting of vascularized scaffolds. To that end, we demineralized and decellularized human bone fragments to obtain a bone matrix, which was further processed and functionalized with methacrylate groups to form a photocrosslinkable methacrylate bone ECM hydrogel - BoneMA. The mechanical properties of BoneMA were tunable, with the elastic modulus increasing as a function of photocrosslinking time, while still retaining the nanoscale features of the polymer networks. The intrinsic cell-compatibility of the bone matrix ensured the synthesis of a highly cytocompatible hydrogel. The bioprinted BoneMA scaffolds supported vascularization of endothelial cells and within a day led to the formation of interconnected vascular networks. We propose that such a quick vascular network formation was due to the host of pro-angiogenic biomolecules present in the bone ECM matrix. Further, we also demonstrate the bioprintability of BoneMA in microdimensions as injectable ECM-based building blocks for microscale tissue engineering in a minimally invasive manner. We conclude that BoneMA may be a useful hydrogel system for tissue engineering and regenerative medicine.

bioengineering↗

bioRxiv2019

What is that molecular machine really doing? Automated exploration of alternative transporter mechanisms

Motivated by growing evidence for pathway heterogeneity and alternative functions of molecular machines, we demonstrate a computational approach for investigating two questions: (1) Are there multiple mechanisms (state-space pathways) by which a machine can perform a given function, such as cotransport across a membrane? (2) How can additional functionality, such as proofreading/error-correction, be built into machine function using standard biochemical processes? Answers to these questions will aid both the understanding of molecular-scale cell biology and the design of synthetic machines. Focusing on transport in this initial study, we sample a variety of mechanisms by employing Metropolis Markov chain Monte Carlo. Trial moves adjust transition rates among an automatically generated set of conformational and binding states while maintaining fidelity to thermodynamic principles and a user-supplied fitness/functionality goal. Each accepted move generates a new model. The simulations yield both single and mixed reaction pathways for cotransport in a simple environment with a single substrate along with a driving ion. In a "competitive" environment including an additional decoy substrate, several qualitatively distinct reaction pathways are found which are capable of extremely high discrimination coupled to a leak of the driving ion, akin to proofreading. The array of functional models would be difficult to find by intuition alone in the complex state-spaces of interest. Author summaryMolecular machines, which operate on the nanoscale, are proteins/complexes that perform remarkable tasks such as the selective absorption of nutrients into the cell by transporters. These complex machines are often described using a fairly simple set of states and transitions that may not account for the stochasticity and heterogeneity generally expected at the nanoscale at body temperature. New tools are needed to study the full array of possibilities. This study presents a novel in silico method to systematically generate testable molecular-machine kinetic models and explore alternative mechanisms, applied first to membrane transport proteins. Our initial results suggest these transport machines may contain mechanisms which detoxify the cell of an unwanted toxin, as well as significantly discriminate against the import of the toxin. This novel approach should aid the experimental study of key physiological processes such as renal glucose re-absorption, rational drug design, and potentially the development of synthetic machines.

biophysics↗

bioRxiv2018

Eps8 is a convergence point integrating EGFR and integrin trafficking and crosstalk

Crosstalk between adhesion and growth factor receptors plays a critical role in tissue morphogenesis and repair, and aberrations contribute substantially to neoplastic disease. However, the mechanisms by which adhesion and growth factor receptor signalling are integrated, spatially and temporally, are unclear.\n\nWe used adhesion complex enrichment coupled with quantitative proteomic analysis to identify rapid changes to adhesion complex composition and signalling following growth factor stimulation. Bioinformatic network and ontological analyses revealed a substantial decrease in the abundance of adhesion regulatory proteins and co-ordinators of endocytosis within 5 minutes of EGF stimulation. Together these data suggested a mechanism of EGF-induced receptor endocytosis and adhesion complex turnover.\n\nCombinatorial interrogation of the networks allowed a global and dynamic view of adhesion and growth factor receptor crosstalk to be assembled. By interrogating network topology we identified Eps8 as a putative node integrating 5{beta}1 integrin and EGFR functions. Importantly, EGF stimulation promoted internalisation of both 5{beta}1 and EGFR. However, perturbation of Eps8 increased constitutive internalisation of 5{beta}1 and EGFR; suggesting that Eps8 constrains 5{beta}1 and EGFR endocytosis in the absence of EGF stimulation. Consistent with this, Eps8 regulated Rab5 activity and was required for maintenance of adhesion complex organisation and for EGF-dependent adhesion complex disassembly. Thus, by co-ordinating 5{beta}1 and EGFR trafficking mechanisms, Eps8 is able to control adhesion receptor and growth factor receptor bioavailability and cellular contractility.\n\nWe propose that during tissue morphogenesis and repair, Eps8 functions to spatially and temporally constrain endocytosis, and engagement, of 5{beta}1 and EGFR in order to precisely co-ordinate adhesion disassembly, cytoskeletal dynamics and cell migration.

cell biology↗

bioRxiv2018

Cell-intrinsic genetic regulation of peripheral memory-phenotype T cell frequencies

Memory T and B lymphocyte numbers are thought to be regulated by recent and cumulative microbial exposures. We report here that memory-phenotype lymphocyte frequencies in B, CD4 and CD8 T-cells in 3-monthly serial bleeds from healthy young adult humans were relatively stable over a 1-year period, while recently activated -B and -CD4 T cell frequencies were not, suggesting that recent environmental exposures affected steady state levels of recently activated but not of memory lymphocyte subsets. Frequencies of memory B and CD4 T cells were not correlated, suggesting that variation in them was unlikely to be determined by cumulative antigenic exposures. Immunophenotyping of adult siblings showed high concordance in memory, but not of recently activated lymphocyte subsets, suggesting genetic regulation of memory lymphocyte frequencies. To explore this possibility further, we screened effector memory (EM)-phenotype T cell frequencies in common independent inbred mice strains. Using two pairs from these strains that differed predominantly in either CD4EM and/or CD8EM frequencies, we constructed bi-parental bone marrow chimeras in F1 recipient mice, and found that memory T cell frequencies in recipient mice were determined by donor genotypes. Together, these data suggest cell-autonomous determination of memory T niche size, and suggest mechanisms maintaining immune variability.

immunology↗

bioRxiv2017

Mechanisms of KCNQ1 Channel Dysfunction in Long QT Syndrome Involving Voltage Sensor Domain Mutations

Loss-of-function (LOF) mutations in human KCNQ1 are responsible for susceptibility to a life-threatening heart rhythm disorder, the congenital long-QT syndrome (LQTS). Hundreds of KCNQ1 mutations have been identified, but the molecular mechanisms responsible for impaired function are poorly understood. Here, we investigated the impact of 51 KCNQ1 variants located within the voltage sensor domain (VSD), with an emphasis on elucidating effects on cell surface expression, protein folding and structure. For each variant, the efficiency of trafficking to the plasma membrane, the impact of proteasome inhibition, and protein stability were assayed. The results of these experiments, combined with channel functional data, provided the basis for classifying each mutation into one of 6 mechanistic categories. More than half of the KCNQ1 LOF mutations destabilize the structure of the VSD, resulting in mistrafficking and degradation by the proteasome, an observation that underscores the growing appreciation that mutation-induced destabilization of membrane proteins may be a common human disease mechanism. Finally, we observed that 5 of the folding-defective LQTS mutants are located in the VSD S0 helix, where they interact with a number of other LOF mutation sites in other segments of the VSD. These observations reveal a critical role for the S0 helix as a central scaffold to help organize and stabilize the KCNQ1 VSD and, most likely, the corresponding domain of many other ion channels.\n\nOne Sentence SummaryLong QT syndrome-associated mutations in KCNQ1 most often destabilize the protein, leading to mistrafficking and degradation.

biochemistry↗

bioRxiv2017

High Throughput Functional Evaluation of KCNQ1 Decrypts Variants of Unknown Significance

BackgroundThe explosive growth in known human gene variation presents enormous challenges to current approaches for variant classification that impact diagnosis and treatment of many genetic diseases. For disorders caused by mutations in cardiac ion channels, such as congenital long-QT syndrome (LQTS), in vitro electrophysiological evidence has high value in discriminating pathogenic from benign variants, but these data are often lacking because assays are cost-, time- and labor-intensive.\n\nMethods and ResultsWe implemented a strategy for performing high throughput, functional evaluations of ion channel variants that repurposed an automated electrophysiology platform developed previously for drug discovery. We demonstrated success of this approach by evaluating 78 variants in KCNQ1, a major LQTS gene. We benchmarked our results with traditional electrophysiological approaches and observed a high level of concordance. Our results provided functional data useful for classifying ~70% of previously unstudied KCNQ1 variants annotated with uninformative descriptions in the public database ClinVar. Further, we show that rare and ultra-rare KCNQ1 variants in the general population exhibit functional properties ranging from normal to severe loss-of-function indicating that allele frequency is not a reliable predictor of channel function.\n\nConclusionsOur results illustrate an efficient and high throughput paradigm linking genotype to function for a human cardiac channelopathy that will enable data-driven classification of large numbers of variants and create new opportunities for precision medicine.

genetics↗

bioRxiv2017

RetSynth: Solving all optimal retrosynthesis solutions using dynamically constrained integer linear programming

MotivationNaive determination of all the optimal pathways to production of a target chemical on an arbitrarily defined chassis organism is computationally intractable. Methods like linear integer programming can provide a singular solution to this problem, but fail to provide all optimal pathways.\n\nResultsHere we present RetSynth, an algorithm for determining all optimal biological retrosynthesis solutions, given a starting biological chassis and target chemical. By dynamically scaling constraints, additional pathway search scales relative to the number of fully independent branches in the optimal pathways, and not relative to the number of reactions in the database or size of the metabolic network. This feature allows all optimal pathways to be determined for a very large number of chemicals and for a large corpus of potential chassis organisms.\n\nAvailabilityThis algorithm is distributed as part of the RetSynth software package, under a BSD 2-clause license at https://www.github.com/sandialabs/RetSynth/

synthetic biology↗