Biology subjects

Bhattarai, A.

Publications and source records attributed to Bhattarai, A..

18 recordsLinked to original sources

bioRxiv2026

Efficient and Robust Genomic DNA Isolation and Next-Generation Sequencing Library Preparation from Recalcitrant Wild Grape Species

This protocol details the extraction of high-molecular-weight genomic DNA from grapevine tissues (wild and cultivated Vitis spp., including pathogen-infected samples) and the subsequent preparation of Illumina(R) whole-genome sequencing libraries using bead-bound Tn5 transposase. It is designed to overcome challenges from polyphenolic compounds and secondary metabolites in wild plants, providing a cost-effective workflow for large-scale population genomics. It includes recipes for buffers, incubation times, critical notes, and troubleshooting tips to maximize yield and library quality. Although designed for the grapevine DNA, this protocol is potentially applicable to other similar wild plant species HighlightsO_LIOptimized CTAB-PTB DNA extraction protocol for field-collected wild plant tissues. C_LIO_LIEffective removal of polyphenols and secondary metabolites associated with DNA using PTB. C_LIO_LICost-effective Illumina DNA Prep library preparation using bead-bound Tn5 transposase (Tagmentation). C_LIO_LIScalable workflow suitable for large-scale population genomics in Vitis species. C_LIO_LIValidated method for high-molecular-weight DNA and high-quality sequencing data. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=195 SRC="FIGDIR/small/713680v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@b637d4org.highwire.dtl.DTLVardef@10b563aorg.highwire.dtl.DTLVardef@14a32caorg.highwire.dtl.DTLVardef@4c9577_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2025

Multimodal MRI Insights into Glymphatic Clearance and Blood-Brain Barrier Integrity in Healthy Aging

Aging is associated with impaired CSF clearance in preclinical models, but its impact on blood-brain barrier (BBB) health and glymphatic function in humans remains unclear. We aimed to compare healthy younger and older adults using multimodal MRI to assess age-related changes in BBB permeability and glymphatic clearance, and to examine the relationships between these measures. Thirty participants were recruited (12 younger, 26 {+/-} 3 years; 18 older, 75 {+/-} 7 years). Diffusion-prepared arterial spin labeling measured the water exchange rate (Kw) across the BBB; free water (FW) imaging quantified extracellular free water in white matter; and diffusion tensor imaging along perivascular spaces (DTI-ALPS) assessed glymphatic function. Older individuals showed reduced whole-brain Kw (p=0.021), increased white matter FW (p=0.002), and reduced DTI-ALPS (p<0.001) compared to younger adults. Kw associated with both DTI-ALPS ({beta}=0.402x10-2, p=0.022) and FW ({beta}=-0.676x10-3, p=0.008). Reduced Kw may reflect impaired BBB function, while reduced DTI-ALPS and increased FW indicate impaired glymphatic clearance. FW partially mediated the relationship between Kw and DTI-ALPS, suggesting a potential mechanistic link. Overall, this study provides novel multimodal MRI insights into BBB and glymphatic alterations in healthy aging and may inform the development of MRI biomarkers to preserve cognitive health.

neuroscience↗

bioRxiv2025

Local differences in baseline sodium shape astrocytic potassium uptake by the NKA

Astrocytes are vital for the maintenance of ion and transmitter homeostasis in the extracellular space, with the inward Na gradient playing a pivotal role in these processes. Earlier studies not only reported a low baseline Na+ concentration ([Na+]) in astrocytes, but also suggested an equilibration of [Na+] within the gap-junction-coupled syncytium. This is consistent with the view that the basic homeostatic properties of astrocytes are largely identical due to their critical role in brain function. Here, we used multi-photon fluorescence lifetime imaging for a quantitative determination of astrocytic [Na+] in mouse forebrain tissue slices and in vivo. Contrary to the prevailing notion of a rather uniform Na distribution, we detected a previously unobserved subcellular and cellular heterogeneity in astrocytic [Na+], accompanied by differences in the capacity for Na+/K+-ATPase (NKA)-mediated uptake of extracellular K+. Biophysical modelling showed that this heterogeneity can be replicated by the reported differential expression of NKA isoforms in astrocytes together with a different strength of Na+ influx over the plasma membranes. Altogether, our results thus suggest the existence of functionally distinct astrocytes and astrocyte subdomains in which Na+ homeostasis is locally adapted to the specific requirements of surrounding neural networks.

neuroscience↗

bioRxiv2025

Generation and maintenance of apical rib-like actin fibers in epithelial support cells of the Drosophila eye

Heterogeneity and complexity of cytoskeletal structures, and how these are regulated, is poorly understood. Here we use cells of the Drosophila pupal eye as models to explore diversity in the actin cytoskeleton. We found that different F-actin structures emerge in primary (1{degrees}), secondary (2{degrees}), and tertiary (3{degrees}) pigment cells as they mature. 1{degrees} cells became characterized by dense accumulations of apical F-actin that we termed Apical Ribs of Actin Fibers (ARAFs). The formins Diaphanous and Dishevelled Associated Activator of Morphogenesis are essential for generation of ARAFs, which are connected into a network by -Actinin, the villin Quail, and Spectrins, and linked to the apical membrane by Quail and Spectrins. ARAFs are contractile, stress-fiber-like, and connect to adherens junctions. Impairing ARAFs indicated that this network maintains cortical tension and is crucial for 1{degrees}s to achieve their characteristic shapes. Our evaluation of the three-dimensional shape of 1{degrees}s reveals that ARAFs are essential for the rounding and elevation of the apical membrane. Hence, a toolkit of conserved actin regulatory proteins builds and maintains a network of apical stress fibers that governs the morphology of the cell. Summary StatementThis study describes a novel F-actin network that shapes the apical region of cells of the Drosophila eye and uncovers a set of proteins that build and maintain the network.

developmental biology↗

bioRxiv2024

The dual Ras Association (RA) Domains of Drosophila Canoe have differential roles in linking cell junctions to the cytoskeleton during morphogenesis

During embryonic development and adult homeostasis epithelial cells must change shape and move without disrupting the tissues dynamic architecture. This requires robust linkage of cell-cell adherens junctions to the force-generating actomyosin cytoskeleton. Drosophila Canoe and mammalian Afadin play key roles in this linkage. One central task for the field is defining how upstream inputs from Ras-family GTPases regulate Canoe and Afadin. They are unusual in that they share two tandem Ras-association (RA) domains, which, when deleted, virtually eliminate Canoe function. Previous work in vitro suggested RA1 and RA2 differ in their ability to bind GTPases, but their individual functions in vivo remain unknown. Combining bioinformatic and biochemical approaches, we find that both RA1 and RA2 bind to active Rap1 with similar affinities, and that conserved N-terminal extensions play a role in binding. We created Drosophila canoe mutants to test RA1 and RA2 function in vivo. Despite their similar affinities for Rap1, RA1 and RA2 play strikingly different roles. Deleting RA1 virtually eliminates Canoe function in morphogenesis, while mutants lacking RA2 are viable and fertile but have defects in junctional reinforcement in embryos and during pupal eye development. These data significantly expand our understanding of how adherens junction:cytoskeletal linkage is regulated.

cell biology↗

bioRxiv2024

Kinetic modeling of 18F-PI-2620 binding in the brain using an image-derived input function with total-body PET

Accurate quantification of tau binding from 18F-PI-2620 PET requires kinetic modeling and an input function. Here, we implemented a non-invasive Image-derived input function (IDIF) derived using the state-of-the-art total-body uEXPLORER PET/CT scanner to quantify tau binding and tracer delivery rate from 18F-PI-2620 in the brain. Additionally, we explored the impact of scan duration on the quantification of kinetic parameters. Total-body PET dynamic data from 15 elderly participants were acquired. Time-activity curves from the grey matter regions of interest (ROIs) were fitted to the two-tissue compartmental model (2TCM) using a subject-specific IDIF derived from the descending aorta. ROI-specific kinetic parameters were estimated for different scan durations ranging from 10 to 90 minutes. Logan graphical analysis was also used to estimate the total distribution volume (VT). Differences in kinetic parameters were observed between ROIs, including significant reduction in tracer delivery rate (K1) in the medial temporal lobe. All kinetic parameters remained relatively stable after the 60-minute scan window across all ROIs, with K1 showing high stability after 30 minutes of scan duration. Excellent correlation was observed between VT estimated using 2TCM and Logan plot analysis. This study demonstrated the utility of IDIF with total-body PET in investigating 18F-PI-2620 kinetics in the brain.

neuroscience↗

bioRxiv2024

A Deep Learning-Based Segmentation of Cells and Analysis (DL-SCAN)

With the recent surge in the development of highly selective probes, fluorescence microscopy has become one of the most widely used approaches to study cellular properties and signaling in living cells and tissues. Traditionally, microscopy image analysis heavily relies on manufacturer-supplied software, which often demands extensive training and lacks automation capabilities for handling diverse datasets. A critical challenge arises, if fluorophores employed exhibit low brightness and low Signal-to-Noise ratio (SNR). As a consequence, manual intervention may become a necessity, introducing variability in the analysis outcomes even for identical samples when analyzed by different users. This leads to the incorporation of blinded analysis which ensures that the outcome is free from user bias to a certain extent but is extremely time-consuming. To overcome these issues, we have developed a tool called DL-SCAN that automatically segments and analyzes fluorophore-stained regions of interest such as cell bodies in fluorescence microscopy images using a Deep Learning algorithm called Stardist. We demonstrate the programs ability to automate cell identification and study cellular ion dynamics using synthetic image stacks with varying SNR. This is followed by its application to experimental Na+ and Ca2+ imaging data from neurons and astrocytes in mouse brain tissue slices exposed to transient chemical ischemia. The results from DL-SCAN are consistent, reproducible, and free from user bias, allowing efficient and rapid analysis of experimental data in an objective manner. The open-source nature of the tool also provides room for modification and extension to analyze other forms of microscopy images specific to the dynamics of different ions in other cell types. Statement of SignificanceFluorescence microscopy is widely used to study the functional and morphological features of living cells. However, various factors, such as low SNR, background noise, drift in the signal, movement of the tissue, and the large size of the resulting imaging data, make the processing of fluorescence microscopy data prone to errors, user bias, and extremely time-consuming. These and other issues hinder the full utilization of these powerful experimental techniques. Our novel Deep Learning-based tool overcomes these issues by processing and analyzing fluorescence imaging data, e.g., enabling automated visualization of ion changes in living cells in brain slices. Yet the tool remains easy to use with a streamlined workflow.

neuroscience↗

bioRxiv2023

A genome sequence for the threatened whitebark pine

Whitebark pine (WBP, Pinus albicaulis) is a white pine of subalpine regions in western contiguous US and Canada. WBP has become critically threatened throughout a significant part of its natural range due to mortality from the introduced fungal pathogen white pine blister rust (WPBR, Cronartium ribicola) and additional threats from mountain pine beetle (Dendroctonus ponderosae), wildfire, and maladaptation due to changing climate. Vast acreages of WBP have suffered nearly complete mortality. Genomic technologies can contribute to a faster, more cost-effective approach to the traditional practices of identifying disease-resistant, climate-adapted seed sources for restoration. With deep-coverage Illumina short-reads of haploid megametophyte tissue and Oxford Nanopore long-reads of diploid needle tissue, followed by a hybrid, multistep assembly approach, we produced a final assembly containing 27.6 Gbp of sequence in 92,740 contigs (N50 537,007 bp) and 34,716 scaffolds (N50 2.0 Gbp). Approximately 87.2% (24.0 Gbp) of total sequence was placed on the twelve WBP chromosomes. Annotation yielded 25,362 protein-coding genes, and over 77% of the genome was characterized as repeats. WBP has demonstrated the greatest variation in resistance to WPBR among the North American white pines. Candidate genes for quantitative resistance include disease resistance genes known as nucleotide-binding leucine-rich-repeat receptors (NLRs). A combination of protein domain alignments and direct genome scanning was employed to fully describe the three subclasses of NLRs (TNL, CNL, RNL). Our high-quality reference sequence and annotation provide a marked improvement in NLR identification compared to previous assessments that leveraged de novo assembled transcriptomes.

genomics↗

bioRxiv2022

Welcome to the big leaves: best practices for improving genome annotation in non-model plant genomes

* Premise of the studyRobust standards to evaluate quality and completeness are lacking for eukaryotic structural genome annotation. Genome annotation software is developed with model organisms and does not typically include benchmarking to comprehensively evaluate the quality and accuracy of the final predictions. Plant genomes are particularly challenging with their large genome sizes, abundant transposable elements (TEs), and variable ploidies. This study investigates the impact of genome quality, complexity, sequence read input, and approach on protein-coding gene prediction. * MethodsThe impact of repeat masking, long-read, and short-read inputs, de novo, and genome-guided protein evidence was examined in the context of the popular BRAKER and MAKER workflows for five plant genomes. Annotations were benchmarked for structural traits and sequence similarity. * ResultsBenchmarks that reflect gene structures, reciprocal similarity search alignments, and mono-exonic/multi-exonic gene counts provide a more complete view of annotation accuracy. Transcripts derived from RNA-read alignments alone are not sufficient for genome annotation. Gene prediction workflows that combine evidence-based and ab initio approaches are recommended, and a combination of short and long-reads can improve genome annotation. Adding protein evidence from de novo assemblies, genome-guided transcriptome assemblies, or full-length proteins from OrthoDB generates more putative false positives as implemented in the current workflows. Post-processing with functional and structural filters is highly recommended. * DiscussionWhile annotation of non-model plant genomes remains complex, this study provides recommendations for inputs and methodological approaches. We discuss a set of best practices to generate an optimal plant genome annotation, and present a more robust set of metrics to evaluate the resulting predictions.

bioinformatics↗

bioRxiv2022

Pharmacological hallmarks of allostery at the M4 muscarinic receptor elucidated through structure and dynamics

Allosteric modulation of G protein-coupled receptors (GPCRs) is a major paradigm in drug discovery. Despite decades of research, a molecular level understanding of the general principals that govern the myriad pharmacological effects exerted by GPCR allosteric modulators remains limited. The M4 muscarinic acetylcholine receptor (M4 mAChR) is a well-validated and clinically relevant allosteric drug target for several major psychiatric and cognitive disorders. Here, we present high-resolution cryo-electron microscopy structures of the M4 mAChR bound to a cognate Gi1 protein and the high affinity agonist, iperoxo, in the absence and presence of two different positive allosteric modulators, LY2033298 or VU0467154. We have also determined the structure of the M4 mAChR-Gi1 complex bound to its endogenous agonist, acetylcholine (ACh). Structural comparisons, together with molecular dynamics, mutagenesis, and pharmacological validations, have provided in-depth insights into the role of structure and dynamics in orthosteric and allosteric ligand binding, global mechanisms of receptor activation, cooperativity, probe-dependence, and species variability; all key hallmarks underpinning contemporary GPCR drug discovery.

pharmacology and toxicology↗

bioRxiv2021

Mechanism of Tripeptide Trimming by γ-Secretase

The membrane-embedded {gamma}-secretase complex processively cleaves within the transmembrane domain of amyloid precursor protein (APP) to produce 37-to-43-residue amyloid {beta}-peptides (A{beta}) of Alzheimers disease (AD). Despite its importance in pathogenesis, the mechanism of processive proteolysis by {gamma}-secretase remains poorly understood. Here, mass spectrometry and western blotting were used to quantify the efficiency of the first tripeptide trimming step (A{beta}49[->]A{beta}46) of wildtype (WT) and familial AD (FAD) mutant APP substrate. In comparison to WT APP, the efficiency of this first trimming step was similar for the I45F, A42T and V46F APP FAD mutants, but substantially diminished for the I45T and T48P mutants. In parallel with biochemical experiments, all-atom simulations using a novel Peptide Gaussian accelerated molecular dynamics (Pep-GaMD) method were applied to investigate tripeptide trimming of A{beta}49 by {gamma}-secretase. The starting structure was active {gamma}-secretase bound to A{beta}49 and APP intracellular domain (AICD), as generated from our previous study that captured activation of {gamma}-secretase for the initial endoproteolytic cleavage of APP (Bhattarai et al., ACS Cent Sci, 2020, 6:969-983). Pep-GaMD simulations captured remarkable structural rearrangements of both the enzyme and substrate, in which hydrogen-bonded catalytic aspartates and water became poised for tripeptide trimming of A{beta}49 to A{beta}46. These structural changes required a positively charged N-terminus of endoproteolytic coproduct AICD, which could dissociate during conformational rearrangements of the protease and A{beta}49. The simulation findings were highly consistent with biochemical experimental data. Taken together, our complementary biochemical experiments and Pep-GaMD simulations have enabled elucidation of the mechanism of tripeptide trimming by {gamma}-secretase. Significance statementProduction of amyloid {beta}-peptide (A{beta}) of Alzheimers disease (AD) from its precursor protein requires a series of proteolytic events carried out by the membrane-embedded {gamma}-secretase complex. Mutations in the substrate and enzyme that produce A{beta} cause hereditary AD and these mutations affect tripeptide trimming of initially formed long A{beta} peptides by {gamma}-secretase. Little is known about the structural mechanism of this trimming process. Here, we have developed a molecular dynamic model for the first step of trimming (A{beta}49 to A{beta}46) by {gamma}-secretase. Conformational changes in the enzyme-substrate complex to set up this trimming step require the presence of N-terminally charged endoproteolytic cleavage co-product. Computational effects of AD-causing mutations in A{beta}49 on the trimming process were validated through biochemical experiments.

biochemistry↗

bioRxiv2021

Network diffusion model predicts neurodegeneration in limb-onset amyotrophic lateral sclerosis

The trans-neural propagation of phosphorylated 43-kDa transactive response DNA-binding protein (pTDP-43) contributes to neurodegeneration in Amyotrophic Lateral Sclerosis (ALS). We investigated whether Network Diffusion Model (NDM), a biophysical model of spread of pathology via the brain connectome, could capture the severity and progression of neurodegeneration (atrophy) in ALS. We measured degeneration in limb-onset ALS patients (n=14 at baseline, 12 at 6-months, and 9 at 12 months) and controls (n=12 at baseline) using FreeSurfer analysis on the structural T1-weighted Magnetic Resonance Imaging (MRI) data. The NDM was simulated on the canonical structural connectome from the IIT Human Brain Atlas. To determine whether NDM could predict the atrophy pattern in ALS, the accumulation of pathology modelled by NDM was correlated against atrophy measured using MRI. The cross-sectional analyses revealed that the network diffusion seeded from the inferior frontal gyrus (pars triangularis and pars orbitalis) significantly predicts the atrophy pattern in ALS compared to controls. Whereas, atrophy over time with-in the ALS group was best predicted by seeding the network diffusion process from the inferior temporal gyrus at 6-month and caudal middle frontal gyrus at 12-month. Our findings suggest the involvement of extra-motor regions in seeding the spread of pathology in ALS. Importantly, NDM was able to recapitulate the dynamics of pathological progression in ALS. Understanding the spatial shifts in the seeds of degeneration over time can potentially inform further research in the design of disease modifying therapeutic interventions in ALS.

neuroscience↗

bioRxiv2020

Mechanism of ligand recognition by human ACE2 receptor

Angiotensin converting enzyme 2 (ACE2) plays a key role in renin-angiotensin system regulation and amino acid homeostasis. Human ACE2 acts as the receptor for severe acute respiratory syndrome coronaviruses SARS-CoV and SARS-CoV-2. ACE2 is also widely expressed in epithelial cells of lungs, heart, kidney and pancreas. It is considered an important drug target for treating SARS-CoV-2, as well as pulmonary diseases, heart failure, hypertension, renal diseases and diabetes. Despite the critical importance, the mechanism of ligand binding to the human ACE2 receptor remains unknown. Here, we address this challenge through all-atom simulations using a novel ligand Gaussian accelerated molecular dynamics (LiGaMD) method. Microsecond LiGaMD simulations have successfully captured both binding and unbinding of the MLN-4760 inhibitor in the ACE2 receptor. In the ligand unbound state, the ACE2 receptor samples distinct Open, Partially Open and Closed conformations. Ligand binding biases the receptor conformational ensemble towards the Closed state. The LiGaMD simulations thus suggest a conformational selection mechanism for ligand recognition by the ACE2 receptor. Our simulation findings are expected to facilitate rational drug design of ACE2 against coronaviruses and other related human diseases.

biophysics↗

bioRxiv2020

Ligand Gaussian accelerated molecular dynamics (LiGaMD): Characterization of ligand binding thermodynamics and kinetics

Calculations of ligand binding free energies and kinetic rates are important for drug design. However, such tasks have proven challenging in computational chemistry and biophysics. To address this challenge, we have developed a new computational method "LiGaMD", which selectively boosts the ligand non-bonded interaction potential energy based on the Gaussian accelerated molecular dynamics (GaMD) enhanced sampling technique. Another boost potential could be applied to the remaining potential energy of the entire system in a dual-boost algorithm (LiGaMD_Dual) to facilitate ligand binding. LiGaMD has been demonstrated on host-guest and protein-ligand binding model systems. Repetitive guest binding and unbinding in the {beta}-cyclodextrin host were observed in hundreds-of-nanosecond LiGaMD simulations. The calculated binding free energies of guest molecules with sufficient sampling agreed excellently with experimental data (< 1.0 kcal/mol error). In comparison with previous microsecond-timescale conventional molecular dynamics simulations, accelerations of ligand kinetic rate constants in LiGaMD simulations were properly estimated using Kramers rate theory. Furthermore, LiGaMD allowed us to capture repetitive dissociation and binding of the benzamidine inhibitor in trypsin within 1 s simulations. The calculated ligand binding free energy and kinetic rate constants compared well with the experimental data. In summary, LiGaMD provides a promising approach for characterizing ligand binding thermodynamics and kinetics simultaneously, which is expected to facilitate computer-aided drug design.

biochemistry↗

bioRxiv2020

Mechanisms of γ-Secretase Activation and Substrate Processing

Amyloid {beta}-peptide, the principal component of characteristic cerebral plaques of Alzheimers disease (AD), is produced through intramembrane proteolysis of the amyloid precursor protein (APP) by {gamma}-secretase. Despite the importance in pathogenesis of AD, the mechanisms of intramembrane proteolysis and substrate processing by {gamma}-secretase remain poorly understood. Here, complementary all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method and biochemical experiments were combined to investigate substrate processing of wildtype and mutant APP by {gamma}-secretase. The GaMD simulations captured spontaneous activation of {gamma}-secretase, with hydrogen bonded catalytic aspartates and water poised for proteolysis of APP at the {varepsilon} cleavage site. Furthermore, GaMD simulations revealed that familial AD mutations I45F and T48P enhanced the initial {varepsilon} cleavage between residues Leu49-Val50, while M51F mutation shifted the {varepsilon} cleavage site to the amide bond between Thr48-Leu49. Detailed analysis of the GaMD simulations allowed us to identify distinct low-energy conformational states of {gamma}-secretase, different secondary structures of the wildtype and mutant APP substrate, and important active-site sub-pockets for catalytic function of the enzyme. The simulation findings were highly consistent with experimental analyses of APP proteolytic products using mass spectrometry and western blotting. Taken together, the GaMD simulations and biochemical experiments have enabled us to elucidate the mechanisms of {gamma}-secretase activation and substrate processing, which should facilitate rational computer-aided drug design targeting this functionally important enzyme.

biochemistry↗

bioRxiv2020

Retrospective Ensemble Docking of Allosteric Modulators in an Adenosine G-Protein-Coupled Receptor

BackgroundEnsemble docking has proven useful in drug discovery and development. It increases the hit rate by incorporating receptor flexibility into molecular docking as demonstrated on important drug targets including G-protein-coupled receptors (GPCRs). Adenosine A1 receptor (A1AR) is a key GPCR that has been targeted for treating cardiac ischemia-reperfusion injuries, neuropathic pain and renal diseases. Development of allosteric modulators, compounds binding to distinct and less conserved GPCR target sites compared with agonists and antagonists, has attracted increasing interest for designing selective drugs of the A1AR. Despite significant advances, more effective approaches are needed to discover potent and selective allosteric modulators of the A1AR. MethodsEnsemble docking that integrates Gaussian accelerated molecular dynamic (GaMD) simulations and molecular docking using Autodock has been implemented for retrospective docking of known positive allosteric modulators (PAMs) in the A1AR. ResultsEnsemble docking outperforms docking of the receptor cryo-EM structure. The calculated docking enrichment factors (EFs) and the area under the receiver operating characteristic curves (AUC) are significantly increased. ConclusionsReceptor ensembles generated from GaMD simulations are able to increase the success rate of discovering PAMs of A1AR. It is important to account for receptor flexibility through GaMD simulations and flexible docking. General SignificanceEnsemble docking is a promising approach for drug discovery targeting flexible receptors.

biophysics↗

bioRxiv2019

Serial assessment of iron in the motor cortex in limb-onset Amyotrophic Lateral Sclerosis using Quantitative Susceptibility Mapping

ObjectiveDysregulation of iron in the cerebral motor areas has been hypothesized to occur in individuals with Amyotrophic Lateral Sclerosis (ALS). There is still limited knowledge regarding iron dysregulation in the progression of ALS pathology. Our objectives were to use magnetic resonance based Quantitative Susceptibility Mapping (QSM) to investigate the association between iron dysregulation in the motor cortex and clinical manifestations in patients with limb-onset ALS, and to examine changes in the iron concentration in the motor cortex in these patients over a six-month period. MethodsIron concentration was investigated using magnetic resonance based -QSM in the primary motor cortex and the pre-motor area in thirteen limb-onset ALS patients (including five lumbar onset, six cervical onset and two flail arm patients), and eleven age and sex-matched healthy controls. Nine ALS patients underwent follow-up scans at six months. ResultsSignificantly increased QSM was observed in the left posterior primary motor area (p = 0.02, Cohens d = 0.9) and right anterior primary motor area (p = 0.02, Cohens d = 0.92) in all individuals with limb-onset ALS compared to healthy controls. Increased QSM was observed in the primary motor and pre-motor area at baseline in patients with lumbar onset ALS patients, but not cervical limb-onset ALS patients, compared to healthy controls. No significant change in QSM was observed at the six-month follow-up scans in the ALS patients. ConclusionsThe findings suggest that iron dysregulation can be detected in the motor cortex in limb-onset ALS, which does not appreciably change over a further 6 months. Individuals with lumbar onset ALS appear to be more susceptible to motor cortex iron dysregulation compared to the individuals with cervical onset ALS. Importantly, this study highlights the potential use of QSM as a radiological indicator in disease diagnosis, and in clinical trials in limb-onset ALS and its subtypes. HighlightsO_LISerial measurement of QSM in the motor cortex in limb-onset ALS was performed C_LIO_LIQSM changes in the motor cortex in ALS sub-groups were investigated C_LIO_LIHigher QSM was observed in the motor cortex in Lumbar ALS relative to controls C_LIO_LIQSM is sensitive to iron dysregulation in the motor cortex in limb-onset ALS C_LI

neuroscience↗

bioRxiv2019

G-Protein-Coupled Receptor-Membrane Interactions Depend on the Receptor Activation state

G-protein-coupled receptors (GPCRs) are the largest family of human membrane proteins and serve as primary targets of [~]1/3 of currently marketed drugs. In particular, adenosine A1 receptor (A1AR) is an important therapeutic target for treating cardiac ischemia-reperfusion injuries, neuropathic pain and renal diseases. As a prototypical GPCR, the A1AR is located within a phospholipid membrane bilayer and transmits cellular signals by changing between different conformational states. It is important to elucidate the lipid-protein interactions in order to understand the functional mechanism of GPCRs. Here, all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method were performed on both the inactive (antagonist bound) and active (agonist and G protein bound) A1AR, which was embedded in a 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC) lipid bilayer. In the GaMD simulations, the membrane lipids played a key role in stabilizing different conformational states of the A1AR. Our simulations further identified important regions of the receptor that interacted distinctly with the lipids in highly correlated manner. Activation of the A1AR led to differential dynamics in the upper and lower leaflets of the lipid bilayer. In summary, GaMD enhanced simulations have revealed strongly coupled dynamics of the GPCR and lipids that depend on the receptor activation state.

biophysics↗