Biology subjects

Bhattarai, S.

Publications and source records attributed to Bhattarai, S..

16 recordsLinked to original sources

bioRxiv2026

Accelerated amyloid neurodegeneration in HIV-1-infected APP-KI Alzheimer's disease mice

STRUCTURED ABSTRACTO_ST_ABSINTRODUCTIONC_ST_ABSA higher incidence of dementia, including Alzheimer s-like pathology, is observed in aged people living with HIV-1. However, mechanisms linking HIV-1 to Alzheimers disease (AD) pathology remain unclear, due to the lack of animal models that allow for concurrent study. METHODSWe created a novel APP knock-in (KI) AD mouse, NOG/APPKM670,671NL/IL-34 (hNAIL) that permits study of progressive brain HIV-1 replication. The mice harbor human microglia-like cells. Four-month-old CD34+ human cell reconstituted mice infected with the HIV-1ADA strain facilitated studies of HIV-1 replication on AD pathologies. RESULTSHIV-1 replication increased A{beta} levels and reduced synaptic and neuronal integrity. Spatial transcriptomics demonstrated distinct A{beta} and HIV-1 transcriptional patterns, whereas dual diseased combinations amplified AD pathology. Neurons showed highest transcriptional change, with genes linked to neuroinflammation, protein trafficking, and synaptic dysfunction. DISCUSSIONThe hNAIL mice enable interrogation of HIV-AD comorbidities, with a future potential for the development of novel therapeutic interventions.

neuroscience↗

bioRxiv2025

Robust Colonization of Nasal Microbiota Across the Respiratory Tract and the Gut Modulates Innate Immune Response in a Germ-Free Pig Model

The use of antibiotics in swine production has contributed to improved health and growth rates but also led to significant challenges, including the emergence of antibiotic-resistant bacteria and disruptions in the microbiome. This study employs a germ-free pig model to investigate the transplantation of the nasal microbiome into the respiratory tract, exploring its potential to colonize multiple body sites and its impact on host immunity. Using germ-free piglets inoculated with nasal microbiota from healthy donors, we examined the dynamics of microbial community formation across the respiratory and gastrointestinal tracts and assessed the effects of antibiotic intervention. Our findings reveal that specific taxa, predominantly from the phyla Proteobacteria and Firmicutes, cross colonized both respiratory as well as gastrointestinal tract. This cross- colonization highlights the adaptability of nasal microbiota and suggests a significant role in modulating host immunity through the gut-lung axis. The administration of the antibiotic tulathromycin on day 11 post-inoculation altered both nasal and gut microbiota compositions, reducing microbial diversity and impacting immune gene expression and cytokine profiles. These results underscore the complex interactions within the gut-lung axis and emphasize the implications of antibiotic use on microbial health and host immunity. Understanding these interactions provides crucial insights into alternative strategies for managing health in swine production without relying on antibiotics. Our study advocates for a reevaluation of antibiotic practices and supports the development of microbiome-centered interventions in swine health management.

microbiology↗

bioRxiv2025

A mechanistic understanding of the effect of Staphylococcus aureus VraS histidine kinase single point mutation on antibiotic resistance

Bacterial genomic mutations in Staphylococcus aureus (S. aureus) have been detected in isolated resistant clinical strains, yet their mechanistic effect on the development of antimicrobial resistance remains unclear. The resistance-associated regulatory systems acquire adaptive mutations under stress conditions that may lead to a gain of function effect and contribute to the resistance phenotype. Here, we investigate the effect of a single-point mutation (T331I) in VraS histidine kinase, part of the VraSR two-component system in S. aureus. VraSR senses and responds to environmental stress signals by upregulating gene expression for cell wall synthesis. A combination of enzyme kinetics, microbiological, and transcriptomic analysis revealed the mechanistic effect of the mutation on VraS and S. aureus. Michaelis Mentens kinetics show that the VraS mutation caused an increase in the autophosphorylation rate of VraS and enhanced its catalytic efficiency. The introduction of the mutation through recombineering coupled with CRISPR-Cas9 counterselection to the Newman strain wild-type (WT) genome doubled the minimum inhibitory concentration of three cell wall-targeting antibiotics. The mutation caused an enhanced S. aureus growth rate at sub-lethal doses of the antibiotics, confirming the causative effect of mutation on bacterial persistence. Transcriptomic analysis showed a genome-wide alteration in gene expression levels and protein-protein interaction network of the mutant compared to the WT strain after exposure to vancomycin. The results suggest that vraS mutation causes several mechanistic changes at the protein and cellular levels that favor bacterial survival under antibiotic stress and cause the mutation-harboring strains to become the dominant population during infection. ImportanceRising antimicrobial resistance (AMR) is a global health problem. Mutations in the two- component system have been linked to drug- resistance in Staphylococcus aureus, yet the exact mechanism through which these mutations work is understudied. We investigated the T331I mutation in the vraS gene linked to sensing and responding to cell wall stress. The mutation caused changes at the protein level by increasing the catalytic efficiency of VraS kinase activity. Introducing the mutation to the genome of an S. aureus strain resulted in changes in the phenotypic antibiotic susceptibility, growth kinetics, and genome-wide transcriptomic alterations. By a combination of enzyme kinetics, microbiological, and transcriptomic approaches, we highlight how small genetic changes can significantly impact bacterial physiology and survival under antibiotic stress. Understanding the mechanistic basis of antibiotic resistance is crucial to guide the development of novel therapeutic agents to combat AMR.

microbiology↗

bioRxiv2024

AntiCPs-CompML: A Comprehensive Fast Track ML method to predict Anti-Corona Peptides

This work introduces AntiCPs-CompML, a novel Machine learning framework for the rapid identification of anti-coronavirus peptides (ACPs). ACPs, acting as viral shields, offer immense potential for COVID-19 therapeutics. However, traditional laboratory methods for ACP discovery are slow and expensive. AntiCPs-CompML addresses this challenge by utilizing three primary features for peptide sequence analysis: Amino Acid Composition (AAC), Pseudo Amino Acid Composition (PAAC), and Composition-Transition-Distribution (CTD). The framework leverages 26 different machine learning algorithms to effectively predict potential anti-coronavirus peptides. This capability allows for the analysis of vast datasets and the identification of peptides with hallmarks of effective ACPs. AntiCPs-CompML boasts unprecedented speed and cost-effectiveness, significantly accelerating the discovery process while enhancing research efficiency by filtering out less promising options. This method holds promise for developing therapeutic drugs for COVID-19 and potentially other viruses. Our model demonstrates strong performance with an F1 Score of 92.12% and a Roc AUC of 76% in the independent test dataset. Despite these promising results, we are continuously working to refine the model and explore its generalizability to unseen datasets. Future enhancements will include featurebased and oversampling augmentation strategies addressing the limitation of anti-covid peptide data for comprehensive study, along with concrete feature selection algorithms, to further refine the models predictive power. AntiCPs-CompML ushers in a new era of expedited anti-covid peptides discovery, accelerating the development of novel antiviral therapies.

bioinformatics↗

bioRxiv2024

H3F3A K27M Mutations Drives a Repressive Transcriptome by Modulating Chromatin Accessibility, Independent of H3K27me3 in Diffuse Midline Glioma

BackgroundHeterozygous histone H3.3K27M mutation is a primary oncogenic driver of Diffuse Midline Glioma (DMG). H3.3K27M inhibits the Polycomb Repressive Complex 2 (PRC2) methyltransferase complex, leading to a global reduction and redistributing of the repressive H3 lysine 27 tri-methylation. This rewiring of the epigenome is thought to promote gliomagenesis. MethodsWe established novel, isogenic DMG patient-derived cell lines that have been CRISPR-Cas9 edited to H3.3 WT or H3.3K27M alone and in combination with EZH2 and EZH1 co-deletion, inactivating PRC2 methyltransferase activity of PRC2 and eliminating H3K27me3. ResultsRNA-seq and ATAC-seq analysis of these cells revealed that K27M has a novel epigenetic effect that appears entirely independent of its effects on PRC2 function. While the loss of the PRC2 complex led to a systemic induction of gene expression (including HOX gene clusters) and upregulation of biological pathways, K27M led to a balanced gene deregulation but having an overall repressive effect on the biological pathways. Importantly, the genes uniquely deregulated by the K27M mutation, independent of methylation loss, are closely associated with changes in chromatin accessibility, with upregulated genes becoming more accessible. Notably, the PRC2- independent function of K27M appears necessary for tumorigenesis as xenografts of our H3.3K27M/EZH1/2 WT cells developed into tumors, while H3.3/EZH1/2 KO cells did not. ConclusionWe demonstrate that K27M mutation alters chromatin accessibility and uniquely deregulates genes, independent of K27 methylation. We further show the mutations role in altering biological pathways and its necessity for tumor development. Key PointsO_LIWe revealed genes regulated by H3.3K27M mutation and PRC2 in DMG. C_LIO_LIH3.3K27M mutation alters chromosome accessibility independent of H3K27me3. C_LIO_LIPRC2-independent effects of K27M mutation are crucial for tumor development. C_LI Importance of the StudyThis study is the first to demonstrate that H3F3A K27M mutations drive a repressive transcriptome by modulating chromatin accessibility independently of H3K27 trimethylation in Diffuse Midline Glioma (DMG). By isolating the effects of H3.3 K27me3 loss from those of the K27M mutation, we identified common and unique genes and pathways affected by each. We found that genes uniquely deregulated by K27M showed increased chromatin accessibility and upregulated gene expression, unlike other gene subsets affected by PRC2 knockout. Importantly, we determined the PRC2-independent function of K27M is also essential for tumorigenesis, as xenografts of H3.3 K27M/PRC2 WT cell lines formed tumors, while H3.3WT/PRC2 WT and K27M/PRC2 knockout cells did not. This research builds upon and advances prior studies, such as those identifying EZH2 as a therapeutic target in H3.3K27M DMGs, by revealing critical new pathways for gliomagenesis. The translational significance lies in identifying novel therapeutic targets against this aggressive pediatric cancer. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=189 SRC="FIGDIR/small/594522v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@61edd6org.highwire.dtl.DTLVardef@145935dorg.highwire.dtl.DTLVardef@cde85aorg.highwire.dtl.DTLVardef@5184b7_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2023

An osmolarity dependent mechanism partially ameliorates retinal cysts and rescues cone function in a mouse model of X-linked Retinoschisis.

IntroductionX-linked retinoschisis (XLRS) is a vitreoretinal dystrophy caused by RS1 gene mutations which disrupt retinoschisin protein function. A vital protein for maintaining retinal architecture, the absence of functional retinoschisin leads to the development of intraretinal cysts. The preliminary goal of this study was to investigate a low dose gene therapy in Rs1 knockout (Rs1-KO) mice; however, our experiments revealed an unexpected therapeutic effect of a hypertonic buffer, which led to further exploration of this effect. Methods10 Rs1-KO mice were subretinally injected with an AAV2/4 vector containing the RS1 gene driven by an Ef1 promoter. 16 Rs1-KO mice were subretinally injected with a hypertonic buffer (180 mM NaCl 0.001% F68/PBS (pH 7.4)) or an isotonic buffer (155.2 mM NaCl 0.001% F68/PBS, pH 7.0) as a sham control. Endpoints included electroretinogram (ERG), optical coherence tomography (OCT), and a visually guided swim assay (VGSA). An immunohistochemistry assay was used to quantify cone density in buffer injected and treatment-naive eyes. ResultsUnexpectedly, hypertonic buffer-injected eyes had significantly reduced cyst severity at 1 month post-injection (MPI) (p=<0.0001), significantly higher amplitudes in cone-dominant ERGs persisting to 5 months post-injection (5 Hz flicker; p=0.0018; 3.0 Flash; p=0.0060) and demonstrated improved navigational vision in the light compared to untreated Rs1-KO eyes (p<0.0001). To investigate the role of tonicity on this effect, an isotonic buffer-injected cohort was created (155.2 mM NaCl 0.001% F68/PBS, pH 7.0) (n=6). Surprisingly, hypertonic buffer-injected eyes exhibited a greater reduction in cyst severity and demonstrated improved cone-dominant ERG metrics over isotonic buffer-injected eyes. Using an immunohistochemistry assay, we demonstrated greater cone density in hypertonic buffer-injected eyes than untreated controls (p=0.0147), suggesting a possible cone preservation mechanism. Moreover, our findings reveal a negative correlation between the peak severity of cysts and long-term cone-dominant ERG metrics, implying that effectively managing cysts could yield enduring benefits for cone function. Discussion/ConclusionThis study presents evidence that cyst resolution can be triggered through an osmosis-dependent pathway, and cyst resolution can have long term effects on cone signaling and survival, offering potential insights for the development of novel treatments for patients with XLRS.

genetics↗

bioRxiv2023

Alzheimer mutations stabilize synaptotoxic γ-secretase-substrate complexes

Alzheimers disease is characterized pathologically by cerebral deposition of 42-residue amyloid {beta}-peptide (A{beta}42), proteolytically produced from amyloid precursor protein (APP) by {beta}- and {gamma}-secretases.1 Although mutations in APP and presenilin, the catalytic component of {gamma}-secretase, cause familial Alzheimers disease (FAD), a role for A{beta}42 as the primary disease driver has not been clearly established and remains controversial.2,3 Here we show through comprehensive analysis of the multi-step proteolysis of APP substrate C99 by {gamma}-secretase that FAD mutations are consistently deficient in early proteolytic events, not later events that produce secreted A{beta} peptides. Cryo-electron microscopy revealed that a substrate mimetic traps {gamma}-secretase at the transition state for intramembrane proteolysis, and this structure closely aligns with activated enzyme-substrate complex captured by molecular dynamics simulations. In silico simulations and fluorescence lifetime imaging microscopy in cultured cells support stabilization by FAD mutations of enzyme-substrate and/or enzyme-intermediate complexes. Neuronal expression of C99 and/or presenilin-1 in Caenorabditis elegans led to age-dependent synaptic loss only when one of the transgenes carried an FAD mutation. Designed mutations that stabilize the enzyme-substrate complex and block proteolysis likewise led to synaptic loss. Collectively, these findings implicate the stalled process--not the released products--of {gamma}-secretase cleavage of substrates in FAD pathogenesis.

neuroscience↗

bioRxiv2023

A benzoxazolylurea inhibits VraS and enhances antimicrobials against vancomycin intermediate-resistant Staphylococcus aureus

Vancomycin intermediate-resistant Staphylococcus aureus (VISA) is a pathogen of concern. VraS, a histidine kinase, facilitates the VISA phenotype. Here, we reveal a benzoxazolylurea that directly inhibits VraS and enhances vancomycin to below the clinical breakpoint against an archetypal VISA strain. To the best of our knowledge, this is the first direct VraS inhibitor ever reported that shows significant enhancement of vancomycin against VISA.

pharmacology and toxicology↗

bioRxiv2023

Predicting neoadjuvant treatment response in triple-negative breast cancer using machine learning

BackgroundNeoadjuvant chemotherapy (NAC) is the standard treatment for early-stage triple negative breast cancer (TNBC). The primary endpoint of NAC is a pathological complete response (pCR). NAC results in pCR in only 30%-40% of TNBC patients. Tumor-infiltrating lymphocytes (TILs), Ki67 and phosphohistone H3 (pH3) are a few known biomarkers to predict NAC response. Currently, systematic evaluation of the combined value of these biomarkers in predicting NAC response is lacking. In this study, the predictive value of markers derived from H&E and IHC stained biopsy tissue was comprehensively evaluated using a supervised machine learning (ML)-based approach. Identifying predictive biomarkers could help guide therapeutic decisions by enabling precise stratification of TNBC patients into responders and partial or non-responders. MethodsSerial sections from core needle biopsies (n=76) were stained with H&E, and immunohistochemically for the Ki67 and pH3 markers, followed by whole slide image (WSI) generation. The resulting WSI triplets were co-registered with H&E WSIs serving as the reference. Separate mask region-based CNN (MRCNN) models were trained with annotated H&E, Ki67 and pH3 images for detecting tumor cells, stromal and intratumoral TILs (sTILs and tTILs), Ki67+, and pH3+ cells. Top image patches with a high density of cells of interest were identified as hotspots. Best classifiers for NAC response prediction were identified by training multiple ML models, and evaluating their performance by accuracy, area under curve, and confusion matrix analyses. ResultsHighest prediction accuracy was achieved when hotspot regions were identified by tTIL counts and each hotspot was represented by measures of tTILs, sTILs, tumor cells, Ki67+, and pH3+ features. Regardless of the hotspot selection metric, a complementary use of multiple histological features (tTILs, sTILs) and molecular biomarkers (Ki67 and pH3) resulted in top ranked performance at the patient level. ConclusionsOverall, our results emphasize that prediction models for NAC response should be based on biomarkers in combination rather than in isolation. Our study provides compelling evidence to support the use of ML-based models to predict NAC response in patients with TNBC.

cancer biology↗

bioRxiv2022

A Spatial Attention Guided Deep Learning System for Prediction of Pathological Complete Response Using Breast Cancer Histopathology Images

Predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC) patients accurately is direly needed for clinical decision making. pCR is also regarded as a strong predictor of overall survival. In this work, we propose a deep learning system to predict pCR to NAC based on serial pathology images stained with hematoxylin and eosin (H&E) and two immunohistochemical biomarkers (Ki67 and PHH3). To support human prior domain knowledge based guidance and enhance interpretability of the deep learning system, we introduce a human knowledge derived spatial attention mechanism to inform deep learning models of informative tissue areas of interest. For each patient, three serial breast tumor tissue sections from biopsy blocks were sectioned, stained in three different stains, and integrated. The resulting comprehensive attention information from the image triplets is used to guide our prediction system for prognostic tissue regions. The experimental dataset consists of 26,419 pathology image patches of 1,000 x 1,000 pixels from 73 TNBC patients treated with NAC. Image patches from randomly selected 43 patients are used as a training dataset and images patches from the rest 30 are used as a testing dataset. By the maximum voting from patch-level results, our proposed model achieves a 93% patient-level accuracy, outperforming baselines and other state-of-the-art systems, suggesting its high potential for clinical decision making. The codes, the documentation, and example data are available on an open source at: https://github.com/jkonglab/PCR_Prediction_Serial_WSIs_biomarkers

bioinformatics↗

bioRxiv2022

Knockout of Bbs10 results in lack of cone electrical function and progressive retinal degeneration of rods and cones

Bardet Biedl Syndrome (BBS) is an autosomal recessive disorder caused by mutations in at least 22 different genes. A constant feature is early onset retinal degeneration leading to blindness, with variable central obesity, polydactyly, renal failure, and developmental anomalies. BBS type 10 (BBS10) is a common form caused by mutations in the BBS10 gene encoding a chaperonin-like protein. There are currently no treatments for the progressive vision loss. To aid in treatment development, a BBS10 mouse model was developed by knocking out the Bbs10 gene. Using optical coherence tomography (OCT), electroretinography (ERG), and a visually guided swim assay (VGSA), we demonstrate that Bbs10-/- mice have progressive retinal degeneration. Cone electrical function was absent although cones were anatomically present on histology and retained partial function based on VGSA. The retinal outer nuclear layer (photoreceptor nuclei) progressively thinned as demonstrated on OCT and histology, and rod electrical activity decreased over time on ERG. These phenotypes are more rapidly progressive than retinal degeneration in the Bbs1M390R/M390R knock-in mouse. They are consistent with a cone-rod dystrophy distinct from typical rod-cone degeneration in retinitis pigmentosa and recapitulate aspects of retinal degeneration observed in humans with BBS10. This study has implications for BBS10 gene therapy.

genetics↗

bioRxiv2021

Discovery of aryl aminothiazole γ-secretase modulators with novel effects on amyloid β-peptide production

A series of analogs based on a prototype aryl aminothiazole {gamma}-secretase modulator (GSM) were synthesized and tested for their effects on the profile of 37-to-42-residue amyloid {beta}-peptides (A{beta}), generated through processive proteolysis of precursor protein substrate by {gamma}-secretase. Certain substitutions on the terminal aryl D ring resulted in an altered profile of A{beta} production compared to that seen with the parent molecule. Small structural changes led to concentration-dependent increases in A{beta}37 and A{beta}38 production without parallel decreases in their precursors A{beta}40 and A{beta}42, respectively. The new compounds therefore apparently also stimulate carboxypeptidase trimming of A{beta} peptides [≥]43 residues, providing novel chemical tools for mechanistic studies of processive proteolysis by {gamma}-secretase. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

biochemistry↗

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

Design of Transmembrane Mimetic Structural Probes to Trap Different Stages of γ-Secretase-Substrate Interaction

The transmembrane domain (TMD) of the amyloid precursor protein of Alzheimers disease is processively cut by {gamma}-secretase through endoproteolysis and tricarboxypeptidase "trimming". We recently developed a prototype substrate TMD mimetic for structural analysis--composed of a helical peptide inhibitor linked to a transition-state analog--that simultaneously engages a substrate exosite and the active site and is pre-organized to trap the carboxypeptidase transition state. Here we developed variants of this prototype designed to allow visualization of transition states for endoproteolysis, TMD helix unwinding, and lateral gating of substrate, identifying potent inhibitors for each class. These TMD mimetics exhibited non-competitive inhibition and occupy both exosite and active site as demonstrated by inhibitor cross competition experiments and photoaffinity probe binding assays. The new probes should be important structural tools for trapping different stages of substrate recognition and processing via ongoing cryo-electron microscopy with {gamma}-secretase, ultimately aiding rational 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↗

bioRxiv2019

Transcriptomic profiling of plaque psoriasis and cutaneous T cell subsets during treatment with secukinumab

The IL17A inhibitor secukinumab is efficacious for the treatment of psoriasis. In order to define its mechanism of action, it is important to understand its impact on psoriatic whole skin tissue as well as specific skin-resident immune cell populations such as T lymphocytes. In this study, we treated 15 moderate-to-severe plaque psoriasis patients with secukinumab and characterized the longitudinal transcriptomic changes of whole lesional skin tissue and cutaneous CD4+ T effector cells (Teffs), CD4+ T regulatory cells (Tregs), and CD8+ T effector cells during 12 weeks of treatment. Secukinumab was clinically effective, with 100%, 47%, and 27% of patients in the study achieving PASI75, PASI90, and PASI100 by week 12, respectively. At baseline prior to treatment, we observed that IL17A overexpression predominates in psoriatic CD8+ T cells rather than Teffs, supporting the importance of IL-17-secreting CD8+ T cells (Tc17) compared to IL-17-secreting CD4+ T cells (Th17) cells in the pathogenesis of psoriasis. Although secukinumab targets only IL17A, we observed rapid reduction of IL17A, IL17F, IL23A, IL23R, and IFNG expression in lesional skin as soon as 2 weeks after initiation of treatment and normalization of expression by week 12. Secukinumab treatment resulted in resolution of 89-97% of psoriasis-associated expression differences in both bulk tissue and T cell subsets by week 12 of treatment. Overall, secukinumab appears to rapidly reverse many of the molecular hallmarks of psoriasis.

genomics↗