Biology subjects

Ghosh, D.

Publications and source records attributed to Ghosh, D..

At least 73 records · Page 4Linked to original sources

bioRxiv2020

Manufacturing Stable Bacteriophage Powders Using Thin Film Freeze-drying Technology

Recently, therapeutic uses of bacteriophage (phage) are gaining increased attention, yet common liquid phage formulations require cold chain storage that limits their potential use. Phage therapy is considered as an alternative to antibiotics for bacterial infections and more significantly a promising solution for the ever-increasing prevalence of multi-drug resistance (MDR) pathogens. One of the most promising applications of this therapy is to treat pulmonary bacterial infections. To efficiently deliver therapeutic phage to the lungs, phage formulations that allow for nebulization or dry powder inhalation are under active development. Several conventional particle engineering technologies have been applied in the development of dry powder inhalers (DPI), including spray drying, spray freeze drying, and atmospheric spray freeze drying, but these processes have their own disadvantages that limit their use with bacteriophage formulations and delivery. In our work, we hypothesize that thin film freeze-drying (TFFD) can be used to produce brittle matrix powders containing phage that may be suitable for delivery by several routes of administration, including by nebulization after reconstitution and by intranasal or inhalation delivery of the resulting dry powder. Here we selected T7 bacteriophage as our model phage in a preliminary screening study and found that a binary excipient matrix of sucrose and leucine at ratios of 80:20 or 75:25 by weight, protected bacteriophage from the stresses encountered during the TFFD process. In addition, we confirm that incorporating a buffer system during the TFFD process significantly improved the survival of phage during the ultra-rapid freezing step of the TFFD process and subsequent sublimation step in the lyophilization process. This preservation of phage bioactivity was significantly better than that observed for formulations without a buffer system. The titer loss of phage in standard SM buffer (Tris/NaCl/MgSO4/gelatin) containing formulation was as low as 0.2 log plaque forming units (pfu), which indicates that phage functionality was preserved after the TFFD process. Moreover, the presence of buffers markedly reduced the geometric particle sizes as determined by a dry dispersion method using laser diffraction, which indicates that the TFFD phage powder formulations were easily sheared into smaller powder aggregates, an ideal property for facilitating pulmonary delivery through DPIs. From these findings, we show that TFFD is a particle engineering method that can successfully produce phage containing powders that possess the desired properties for bioactivity and inhalation therapy.

microbiology↗

bioRxiv2020

Molecular Elucidation of Pancreatic Elastase Inhibition by Baicalein

The serine protease, elastase exists in various forms and plays diverse roles in the human body. Pharmacological inhibition of elastase has been investigated for its therapeutic role in managing conditions such as diabetes, pneumonia and arthritis. Sivelestat, a synthetic molecule, is the only elastase inhibitor to have been approved by any major drug regulatory authority (PMDA, in this case) - but still has failed to attain widespread clinical usage owing to its high price, cumbersome administration and obscure long-term safety profile. In order to find a relatively better-suited alternative, screening was conducted using plant flavonoids, which yielded Baicalein - a molecule that showed robust inhibition against Pancreatic Elastase inhibition (IC50: 3.53 M). Other than having an IC50 almost 1/5th of that of sivelestats, baicalein is also cheaper, safer and easier to administer. While Microscale thermophoresis validated baicalein-elastase interaction, enzyme-kinetic studies, molecular docking and molecular dynamic simulation revealed the mode of inhibition to be non-competitive. Baicalein exhibited binding to a distinct allosteric site on the enzyme. The current study demonstrates the elastase inhibition properties of baicalein in an in-vitro and in-silico environment.

biochemistry↗

bioRxiv2020

Climate change and the migration of a pastoralist people c.3500 cal. years BP inferred from palaeofire and lipid biomarker records in the montane Western Ghats, India

Human migration in response to climate change during the Holocene has been recorded in many regions of the world. The Todas are a pastoralist people who are believed to have colonized the higher elevations (>2000 m asl) of the Nilgiris in the Western Ghats, India, not earlier than about 2000 cal. yr BP. Vegetation shifts in response to changing climate in tropical montane forest-grassland mosaic of the Ghats have been well documented using stable carbon isotopes and pollen profiles; however, there have been no corresponding investigations of human presence and activity at the highest elevations. We used a number of other proxies to infer the human ecology of this montane region. Radiocarbon dated (~22,000 cal. BP to the present) peat samples from the Sandynallah basin (2200m asl, Nilgiri hills, Tamil Nadu State) were used to reconstruct fire history, animal abundance, and human presence since the Last Glacial Maximum (LGM). While the macro-charcoal record indicates fires at the LGM, macro- and micro-charcoal counts indicate intense fire at ~3500 cal. yr BP, coprophilous fungal spores indicate a large population of herbivorous mammals, and steroid biomarkers indicate human faecal remains for the first time. This period is also characterized by dry arid conditions and dominant grassy vegetation as inferred from n-alkane signatures. We thus infer that a pastoralist people, most likely the Todas, migrated to the highest elevations of the Western Ghats along with their buffalo herds in response to prolonged or abrupt climate change in peninsular India, about 3500 cal. yr BP or at least 1500 years prior to what historical accounts assume.

ecology↗

bioRxiv2020

p53 Controls Murine Gammaherpesvirus Latency and Prevents Infection-Associated IgH/c- Myc Translocations

Gammaherpesviruses (GHVs) establish life-long infections and cause cancer in humans and other animals. To facilitate chronic infection, GHV oncoproteins promote cellular proliferation and differentiation. Aberrant cell-cycle progression driven by viral oncogenes should trigger activation of tumor suppressor p53, unless p53 is functionally deactivated during GHV latency establishment. However, interactions of GHVs with the p53 pathway during the establishment and maintenance of latent infection are poorly defined. Here we demonstrate in vivo that p53 is induced specifically in infected cells during latency establishment by murine gammaherpesvirus 68 (MHV68). In the absence of p53, MHV68 latency establishment was significantly increased, especially in germinal center B cells, and correlated with enhanced cellular proliferation. However, enhanced latency was not sustainable, and MHV68 exhibited a defect in long-term latency maintenance in p53-deficient mice. Moreover, IgH/c-Myc translocations were readily detected in B cells from infected p53-null mice indicating virus-driven genomic instability. These data demonstrate that p53 intrinsically restricts MHV68 latency establishment and reveal a paradigm in which a host restriction factor provides a long-term benefit to a chronic pathogen by limiting infection-associated damage.

microbiology↗

bioRxiv2020

Research productivity and collaboration of the NIH-funded HIV Vaccine Trials Network: a bibliometric analysis

ObjectivesTo assess the scientific productivity and impact of the HIV Vaccine Trials Network (HVTN) over the last two decades and to examine how research collaboration has evolved over this time in the HIV vaccine field. DesignThis section does not apply since this is a bibliometric study. MethodsA systematic bibliometric analysis was conducted to identify all HIV vaccine and HVTN associated publications from 1999-2019. All publications were sourced from the NLM Pubmed database and funding information was obtained from the SPIRES and iSearch databases. Both the InCites and iCite databases were utilized for impact metrics. Finally, HVTN clinical trials were obtained from clinicaltrials.gov. Multiple field normalized citation metrics, such as the relative citation ratio (RCR) and number of publications in the top 1% and 10% within their respective field, were used to gauge scientific impact of publications. Network analyses were used to examine collaboration among the most prolific researchers in the HIV vaccine research. SettingThis section does not apply since this is a bibliometric study. ParticipantsThis section does not apply since this is a bibliometric study. InterventionThis section does not apply since this is a bibliometric study. Results79 clinical trials were funded by the HVTN from 1999 to 2019. These were carried out via a network of trial sites in 23 countries and 94 cities around the world. In total, 465 publications (89.5% original research articles, 7.3% reviews, and 3.2% other) acknowledged funding from the HVTN. Impact analyses using multiple field normalized metrics revealed that HVTN publications are highly cited with a mean RCR of 1.8. 10,481 HIV vaccine related publications were used to analyze collaboration in this field. Compared to the field as a whole, publications attributed to the HVTN had significantly more authors per publication (p-value < 0.001) and our network analysis found that HVTN-associated authors also had a higher degree (p-value < 0.01). ConclusionsBibliometric analysis of the last two decades of HIV vaccine research by the HVTN revealed that in addition to conducting a large number of clinical trials worldwide, the network produced high impact publications and was associated with increased collaboration among researchers. ARTICLE SUMMARYO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LITo the best of our knowledge, this is the only study that has provided a systematic bibliometric analysis of the HVTN since its inception. C_LIO_LIStudies like this can illustrate overall outcomes of large clinical network programs. C_LIO_LIAdvanced field normalized metrics were used to provide the most accurate measures of productivity, impact, and collaboration. C_LIO_LIIdentification of HVTN publications using funding acknowledgements can lead to an underestimate of the number research articles since not all research articles include grant funding information. C_LIO_LIVariations in a single authors name across publications can make name disambiguation difficult when performing network analyses. C_LI

microbiology↗

bioRxiv2019

Defining the DmsA Signal Sequence Interaction with DmsD And TatBC

Redox - enzyme maturation proteins (REMP) ensure co-factor loading and folding of proteins targeted to the twin-arginine translocation (Tat) pathway. The details of the interaction of a REMP with the corresponding signal sequence of its substrate are not well understood. Here, we demonstrate the features of the signal sequence for the Tat substrate DmsA (ssDmsA) responsible for complex formation with its REMP, DmsD, and with the Tat membrane complex TatB & TatC (TatBC). A heterologously expressed ssDmsA/DmsD complex forms two stochiometric populations corresponding to monomeric and dimeric forms of the complex. The monomeric complex has a higher affinity for the TatBC complex than the dimeric, which imply higher level regulation process to ensure the maturation of protein before translocation. Results from various binding studies yielded the shortest signal peptide required for ssDmsA/DmsA interaction and the region responsible for the TatBC interaction. Further experiments like alanine scanning in this peptide highlight the possible residues that are essential for this complex formation.

microbiology↗

bioRxiv2019

Expanding AHL Acylases Horizon - Insights From Structural Analysis of Choloylglycine Hydrolases From Shewanella lohica PV-4

Acyl homoserine lactone acylases are quorum quenching enzymes that degrade the Gram negative bacterial autoinducer N-acyl homoserine lactone (AHL) and belong to the Ntn-hydrolases superfamily of enzymes. Recent findings reported AHL acylase activity of pencillin V acylases (PVA) which, alongside bile salt hydrolases, are members of the cholyolglycine hydrolase (CGH) family of the Ntn-hydrolases superfamily. The present study reports the unique activity profile of two CGHs from a marine bacterium Shewanella loihica-PV4, designated here as SlCGH1 and SlCGH2, including the structural analysis of SlCGH1. Both the enzymes exhibit AHL acylase activity while unexpectedly being inactive on standard CGH substrates PenV and bile salts. SlCGH1 differs from known homotetrameric CGHs in being a homodimer displaying a reduced active site volume attributed to loop orientation, which subsequently directs the substrate specificity. Moreover a ligand bound complex structure revealed an unusual bent conformation of the saturated acyl chain bound to the active site and also predicts a single oxyanion hole forming residue during catalysis instead of the usual two residues. Phylogenetic analysis reveals SlCGH1 homologs cluster separate from reported CGHs and AHL acylases. On the whole, SlCGH1 could represent a functionally distinct new sub-class of CGH as an adaptation to the marine environment and its structure could provide the structural framework for understanding such a novel subclass. We also make a modest proposal of a probable evolutionary link between AHL acylases and {beta} lactam acylases based on the overlap in activity and structural features.\n\nSignificanceCross-reactivity between AHL acylases and b lactam acylases has been recently identified giving us a vivid glimpse of a possible evolutionary relationship between the phenomena of quorum sensing and antibiotic resistance. We report here the first AHL acylase of the CGH structural framework. SlCGH1 from Shewanella loihica PV-4 is also the first report of a marine CGH with a unique activity and a new structural subclass of CGH family with AHL acylase activity. This finding highlights the vast diversity of AHL acylases and by extension quorum quenching enzymes as adaptation to different habitats. The results from this study also bolster the link between signal molecules and antibiotics, extending our understanding of the inadequately understood physiological roles of b-lactam acylases.

biochemistry↗

bioRxiv2019

Hyperinsulinemia promotes HMGB1 release leading to inflammation induced systemic insulin resistance: An interplay between pancreatic beta-cell and peripheral organs

Insulin resistance results from several pathophysiologic mechanisms, including chronic tissue inflammation and defective insulin signaling. Pancreatic {beta}-cells hypersecretion (hyperinsulinemia), is a central hallmark of peripheral insulin resistance. However, the underlying mechanism by which hyperinsulinemia perpetuates towards the development of insulin resistance remains unclear and is still a bigger therapeutic challenge. Here, we found hyperinsulinemia triggers inflammation and insulin resistance by stimulating TLR4-driven inflammatory cascades. We show that hyperinsulinemia activates the TLR4 signaling through HMGB1, an endogenous TLR4 ligand emanating from hyperinsulinemia exposed immune cells and peripheral organs like adipose tissue and liver. Further, our observation suggests hyperinsulinemia ensuring hyperacetylation, nuclear-to-cytoplasmic shuttling and release of HMGB1 into the extracellular space. HMGB1 was also found to be elevated in serum of T2DM patients. We found that extracellular HMGB1 plays a crucial role to promote proinflammatory responses and provokes systemic insulin resistance. Importantly, in-vitro and in-vivo treatment with naltrexone, a TLR4 antagonist led to an anti-inflammatory phenotype with protection from hyperinsulinemia mediated insulin resistance. In-vitro treatment with naltrexone directly enhanced SIRT1 activity, blocked the release of HMGB1 into extracellular milieu, suppressed release of proinflammatory cytokines and ultimately led to insulin-sensitizing effects. These observations elucidate a regulatory network between pancreatic {beta}-cells, macrophage and hepatocytes and assign an unexpected role of TLR4 - HMGB1 signaling axis in hyperinsulinemia mediated systemic insulin resistance.\n\nGraphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

physiology↗

bioRxiv2019

Leveraging Family History in Case-Control Analyses of Rare Variation

Standard methods for case-control association studies of rare variation often treat disease outcome as a dichotomous phenotype. However, both theoretical and experimental studies have demonstrated that subjects with a family history of disease can be enriched for risk variation relative to subjects without such history. Assuming family history information is available, this observation motivates the idea of replacing the standard dichotomous outcome variable used in case-control studies with a more informative ordinal outcome variable that distinguishes controls (0), sporadic cases (1), and cases with a family history (2), with the expectation that we should observe increasing number of risk variants with increasing category of the ordinal variable. To leverage this expectation, we propose a novel rare-variant association test that incorporates family history information based on our previous GAMuT framework (Broadaway et al., 2016) for rare-variant association testing of multivariate phenotypes. We use simulated data to show that, when family history information is available, our new method outperforms standard rare-variant association methods like burden and SKAT tests that ignore family history. We further illustrate our method using a rare-variant study of cleft lip and palate.

genetics↗

bioRxiv2019

Identification of peptide coatings that enhance diffusive transport of nanoparticles through the tumor microenvironment

In solid tumors, increasing drug penetration promotes their regression and improves the therapeutic index of compounds. However, the heterogeneous extracellular matrix (ECM) acts a steric and interaction barrier that hinders effective transport of therapeutics, including nanomedicines. Specifically, the interactions between the ECM and surface physicochemical properties of nanomedicines (e.g. charge, hydrophobicity) impedes their diffusion and penetration. To address the challenges using existing surface chemistries, we used peptide-presenting phage libraries as a high-throughput approach to screen and identify peptides as coatings with desired physicochemical properties that improve diffusive transport through the tumor microenvironment. Through iterative screening against the ECM and identification by next-generation DNA sequencing and analysis, we selected individual clones and measured their transport by diffusion assays. Here, we identified a net-neutral charge, hydrophilic peptide P4 that facilitates significantly higher diffusive transport of phage than negative control through in vitro tumor ECM. Through alanine mutagenesis, we confirmed that the hydrophilicity, charge, and their spatial ordering impact diffusive transport. P4 phage clone exhibited almost 200-fold improved uptake in ex vivo pancreatic tumor xenografts compared to the negative control. Nanoparticles coated with P4 exhibited [~]40-fold improvement in diffusivity in pancreatic tumor tissues, and P4-coated particles demonstrated less hindered diffusivity through the ECM compared to particles functionalized with gold standard poly(ethylene) glycol or iRGD peptide ligand. By leveraging the power of molecular diversity using phage display, we can greatly expand the chemical space of surface chemistries that can improve the transport of nanomedicines through the complex tumor microenvironment to ultimately improve their efficacy.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC=\"FIGDIR/small/659524v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (23K):\norg.highwire.dtl.DTLVardef@18bc04forg.highwire.dtl.DTLVardef@1feb597org.highwire.dtl.DTLVardef@14403e5org.highwire.dtl.DTLVardef@5bbf6c_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2019

A combinatorial biomolecular strategy to identify peptides for improved transport across the sputum of cystic fibrosis patients and the underlying epithelia

Drugs and drug delivery systems have to traverse multiple biological barriers to achieve therapeutic efficacy. In diseases of mucosal-associated tissues such as cystic fibrosis (CF), successful delivery of gene and drug therapies remains a significant challenge due to an abnormally concentrated viscoelastic mucus, which prevents ~99% of all drugs and particles from penetrating the mucus barrier and the underlying epithelia for effective therapy, resulting in decreased survival. We used combinatorial peptide-presenting phage libraries and next-generation sequencing to identify hydrophilic, close to net-neutral charged peptides that penetrate the mucus barrier ex vivo in sputum from CF patients with ~600-fold better penetration than a positively charged control. After mucus penetration, nanoparticles conjugated with our selected peptides successfully translocated into lung epithelial cells derived from CF patients and demonstrated up to three-fold improved cell uptake compared to non-modified carboxylated- and gold standard PEGylated-nanoparticles. The selected peptides act as surface chemistries with synergistic functions to significantly improve the ability of drug delivery systems to overcome the human mucosal barriers and provide efficient cellular internalization. Our screening strategy provides a biologically-based discovery assay that directly addresses transport through mucus and cell barriers and has the potential to advance drug and gene delivery to multiple mucosal barriers.

bioengineering↗

bioRxiv2019

M13 phage display to identify a permeating peptide against hyperconcentrated mucin

Mucus is an impregnable barrier for drug delivery across the epithelia for treatment of mucosal-associated diseases. While current carriers are promising for mucus penetration, their surface chemistries do not possess chemical complexity to probe and identify optimal physicochemical properties desired for mucus penetration. As initial study, we use M13 phage display presenting random peptides to select peptides that can facilitate permeation through hyperconcentrated mucin. Here, a net-neutral charge, hydrophilic peptide was identified to facilitate transport of phage and fluorophore conjugates through mucin barrier compared to controls. This initial finding warrants further study to understand how composition and spatial distribution of physicochemical properties of peptides can be optimized to improve transport across the mucus barrier.

bioengineering↗

bioRxiv2019

Intracellular nanoparticle delivery by oncogenic KRAS-mediated macropinocytosis

The RAS family of oncogenes (KRAS, HRAS, NRAS) are the most frequent mutations in cancers and regulate key signaling pathways that drive tumor progression. As a result, drug delivery targeting RAS-driven tumors has been a long-standing challenge in cancer therapy. Mutant RAS activates cancer cells to actively take up nutrients, including glucose, lipids, and albumin, via macropinocytosis to fulfill their energetic requirements to survive and proliferate. Here, we exploit this mechanism to deliver nanoparticles in cancer cells harboring activating KRAS mutations. We have synthesized stable albumin nanoparticles that demonstrate significantly greater uptake in cancer cells with activating mutations of KRAS than monomeric albumin (i.e. dissociated form of clinically-used nab-paclitaxel). From pharmacological inhibition and semi-quantitative fluorescent microscopy studies, these nanoparticles exhibit significantly increased uptake in mutant KRAS cancer cells than wild-type KRAS cells by macropinocytosis. Importantly, we demonstrate that their uptake is driven by KRAS. This nanoparticle-based strategy targeting RAS-driven macropinocytosis is a facile approach towards improved delivery into KRAS-driven cancers.

bioengineering↗

bioRxiv2019

Development of a Prediction Model for Incident Atrial Fibrillation using Machine Learning Applied to Harmonized Electronic Health Record Data

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, whose early detection could lead to significant improvements in outcomes through appropriate prescription of anticoagulation. Although a variety of methods exist for screening for AF, there is general agreement that a targeted approach would be preferred. Implicit within this approach is the need for an efficient method for identification of patients at risk. In this investigation, we examined the strengths and weaknesses of an approach based on application of machine-learning algorithms to electronic health record (EHR) data that has been harmonized to the Observational Medical Outcomes Partnership (OMOP) common data model. We examined data from a total of 2.3M individuals, of whom 1.16% developed incident AF over designated 6-month time intervals. We examined and compared several approaches for data reduction, sample balancing (re-sampling) and predictive modeling using cross-validation for hyperparameter selection, and out-of-sample testing for validation. Although no approach provided outstanding classification accuracy, we found that the optimal approach for prediction of 6-month incident AF used a random forest classifier, raw features (no data reduction), and synthetic minority oversampling technique (SMOTE) resampling (F1 statistic 0.12, AUC 0.65). This model performed better than a predictive model based only on known AF risk factors, and highlighted the importance of using resampling methods to optimize ML approaches to imbalanced data as exists in EHRs. Further studies using EHR data in other medical systems are needed to validate the clinical applicability of these findings.

epidemiology↗

bioRxiv2018

ASCOT identifies key regulators of neuronal subtype-specific splicing

Public archives of next-generation sequencing data are growing exponentially, but the difficulty of marshaling this data has led to its underutilization by scientists. Here we present ASCOT, a resource that allows researchers to summarize, visualize, and query alternative splicing patterns in public RNA-Seq data. ASCOT enables rapid identification of splice-variants across tens of thousands of bulk and single-cell RNA-Seq datasets in human and mouse. To demonstrate the utility of ASCOT, we first focused on the nervous system and identified many alternative exons used only by a single neuronal subtype. We then leveraged datasets from the ENCODE and GTEx consortiums to study the unique splicing patterns of rod photoreceptors and found that PTBP1 knockdown combined with overexpression of MSI1 and PCBP2 activates rod-specific exons in HepG2 liver cancer cells. Furthermore, we observed that MSI1 targets intronic UAG motifs proximal to the 5 splice site and interacts synergistically with PTBP1 downregulation. Finally, we show that knockdown of MSI1 in the retina abolishes rod-specific splicing. This work demonstrates how large-scale analysis of public RNA-Seq datasets can yield key insights into cell type-specific control of RNA splicing and underscores the importance of considering both annotated and unannotated splicing events. ASCOT splicing and gene expression data tables, software, and interactive browser are available at http://ascot.cs.jhu.edu.

neuroscience↗

bioRxiv2018

Radtools: R utilities for smooth navigation of medical image data

The radiology community has adopted several widely used standards for medical image files, including the popular DICOM (Digital Imaging and Communication in Medicine) and NIfTI (Neuroimaging Informatics Technology Initiative) standards. These file formats include image intensities as well as potentially extensive metadata. The NIfTI standard specifies a particular set of header fields describing the image and minimal information about the scan. DICOM headers can include any of over 4,000 available metadata attributes spanning a variety of topics. NIfTI files contain all slices for an image series, while DICOM files capture single slices and image series are typically organized into a directory. Each DICOM file contains metadata for the image series as well as the individual image slice.\n\nThe programming environment R is popular for data analysis due to its free and open code, active ecosystem of tools and users, and excellent system of contributed packages. Currently, many published radiological image analyses are performed with proprietary software or custom unpublished scripts. However, R is increasing in popularity in this area due to several packages for processing and analysis of image files. While these R packages handle image import and processing, no existing package makes image metadata conveniently accessible. Extracting image metadata, combining across slices, and converting to useful formats can be prohibitively cumbersome, especially for DICOM files.\n\nWe present radtools, an R package for smooth navigation of medical image data. Radtools makes the problem of extracting image metadata trivially simple, providing simple functions to explore and return information in familiar R data structures. Radtools also facilitates extraction of image data and viewing of image slices. The package is freely available under the MIT license at https://github.com/pamelarussell/radtools and is easily installable from the Comprehensive R Archive Network (https://cran.r-project.org/package=radtools).

cancer biology↗

bioRxiv2018

Powerful and Efficient Strategies for Genetic Association Testing of Symptom and Questionnaire Data in Psychiatric Genetic Studies

Genetic studies of psychiatric disorders often deal with phenotypes that are not directly measurable. Instead, researchers rely on multivariate symptom data from questionnaires and surveys like the PTSD Symptom Scale (PSS) and Beck Depression Inventory (BDI) to indirectly assess a latent phenotype of interest. Researchers subsequently collapse such multivariate questionnaire data into a univariate outcome to represent a surrogate for the latent phenotype. However, when a causal variant is only associated with a subset of collapsed symptoms, the effect will be challenging to detect using the univariate outcome. We describe a more powerful strategy for genetic association testing in this situation that jointly analyzes the original multivariate symptom data collectively using a statistical framework that compares similarity in multivariate symptom-scale data from questionnaires to similarity in common genetic variants across a gene. We use simulated data to demonstrate this strategy provides substantially increased power over standard approaches that collapse questionnaire data into a single surrogate outcome. We also illustrate our approach using GWAS data from the Grady Trauma Project and identify genes associated with BDI not identified using standard univariate techniques. The approach is computationally efficient, scales to genome-wide studies, and is applicable to correlated symptom data of arbitrary dimension (thereby aligning with National Institute of Mental Healths Research Domain Criteria).

genetics↗

bioRxiv2018

Development and Application of a High-Content Virion Display Human GPCR Array

G protein-coupled receptors (GPCRs) comprise the largest membrane protein family in humans and can respond to a wide variety of ligands and stimuli. Like other multi-pass membrane proteins, the biochemical properties of GPCRs are notoriously difficult to study because they must be embedded in lipid bilayers to maintain their native conformation and function. To enable an unbiased, high-throughput platform to profile biochemical activities of GPCRs in native conformation, we individually displayed 315 human non-odorant GPCRs (>85% coverage) in the envelope of human herpes simplex virus-1 and immobilized on glass to form a high-content Virion Display (VirD) array. Using this array, we found that 50% of the tested commercial anti-GPCR antibodies (mAbs) is ultra-specific, and that the vast majority of those VirD-GPCRs, which failed to be recognized by the commercial mAbs, could bind to their canonical ligands, indicating that they were folded correctly. Next, we used the VirD-GPCR arrays to examine binding specificity of two known peptide ligands and recovered expected interactions, as well as new off-target interactions, three of which were confirmed with real-time kinetics measurements. Finally, we explored the possibility of discovering novel pathogen targets by probing VirD-GPCR arrays with live group B Streptococcus (GBS), a common Gram-positive bacterium causing neonatal meningitis. Using cell invasion assays and a mouse model of hematogenous meningitis, we showed that inhibition of one of the five newly identified GPCRs, CysLTR1, greatly reduced GBS penetration in brain-derived endothelial cells and in mouse brains. Therefore, our work demonstrated that the VirD-GPCR array holds great potential for high-throughput, unbiased screening for small molecule drugs, affinity reagents, and deorphanization.

pharmacology and toxicology↗