Publications by authors named "Priyanka Chaurasia"

10 Publications

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SARS-CoV-2-specific CD8 T-cell responses and TCR signatures in the context of a prominent HLA-A*24:02 allomorph.

Immunol Cell Biol 2021 Jun 4. Epub 2021 Jun 4.

Department of Microbiology and Immunology, University of Melbourne, Peter Doherty Institute for Infection and Immunity, Melbourne, 3000.

In-depth understanding of human T cell-mediated immunity in COVID-19 is needed if we are to optimize vaccine strategies and immunotherapies. Identification of SARS-CoV-2 T cell epitopes and generation of peptide-HLA tetramers facilitates direct ex vivo analyses of SARS-CoV-2-specific T cells and their T cell receptor (TCR) repertoires. We utilized a combination of peptide prediction and in vitro peptide stimulation to validate novel SARS-CoV-2 epitopes restricted by HLA-A*24:02, one of the most prominent HLA class I alleles, especially in Indigenous and Asian populations. Of the peptides screened, three spike-derived peptides generated CD8 IFN-γ responses above background, S (QYIKWPWYI), S (NYNYLYRLF) and S (VFKNIDGYF), with S generating immunodominant CD8 IFN-γ responses. Using peptide-HLA-I tetramers, we performed direct ex vivo tetramer enrichment for HLA-A*24:02-restricted CD8 T cells in COVID-19 patients and pre-pandemic controls. The precursor frequencies for HLA-A*24:02-restricted epitopes were within the range previously observed for other SARS-CoV-2 epitopes for both COVID-19 patients and pre-pandemic individuals. Naïve A24/SARS-CoV-2-specific CD8 T cells increased ~7.5-fold above the average precursor frequency during COVID-19, gaining effector and memory phenotypes. Ex vivo single-cell analyses of TCRαβ repertoires found that the A24/S CD8 T cell TCRαβ repertoire was driven by a common TCRβ chain motif, while the A24/S CD8 TCRαβ repertoire was diverse across COVID-19 patients. Our study provides an in depth characterisation and important insights into SARS-CoV-2-specific CD8 T cell responses associated with a prominent HLA-A*24:02 allomorph. This contributes to our knowledge on adaptive immune responses during primary COVID-19 and could be exploited in vaccine or immunotherapeutic approaches.
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http://dx.doi.org/10.1111/imcb.12482DOI Listing
June 2021

CD8 T cells specific for an immunodominant SARS-CoV-2 nucleocapsid epitope display high naive precursor frequency and TCR promiscuity.

Immunity 2021 05 15;54(5):1066-1082.e5. Epub 2021 Apr 15.

Department of Infectious Diseases, Austin Hospital, Heidelberg, VIC 3084, Australia; Department of Medicine and Radiology, The University of Melbourne, Parkville, VIC 3000, Australia; Data Analytics Research and Evaluation (DARE) Centre, Austin Health and The University of Melbourne, Heidelberg, VIC 3084, Australia.

To better understand primary and recall T cell responses during coronavirus disease 2019 (COVID-19), it is important to examine unmanipulated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific T cells. By using peptide-human leukocyte antigen (HLA) tetramers for direct ex vivo analysis, we characterized CD8 T cells specific for SARS-CoV-2 epitopes in COVID-19 patients and unexposed individuals. Unlike CD8 T cells directed toward subdominant epitopes (B7/N, A2/S, and A24/S) CD8 T cells specific for the immunodominant B7/N epitope were detected at high frequencies in pre-pandemic samples and at increased frequencies during acute COVID-19 and convalescence. SARS-CoV-2-specific CD8 T cells in pre-pandemic samples from children, adults, and elderly individuals predominantly displayed a naive phenotype, indicating a lack of previous cross-reactive exposures. T cell receptor (TCR) analyses revealed diverse TCRαβ repertoires and promiscuous αβ-TCR pairing within B7/NCD8 T cells. Our study demonstrates high naive precursor frequency and TCRαβ diversity within immunodominant B7/N-specific CD8 T cells and provides insight into SARS-CoV-2-specific T cell origins and subsequent responses.
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http://dx.doi.org/10.1016/j.immuni.2021.04.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8049468PMC
May 2021

Effect of Mindfulness Meditation on Intraocular Pressure and Trabecular Meshwork Gene Expression: A Randomized Controlled Trial.

Am J Ophthalmol 2021 03 22;223:308-321. Epub 2020 Oct 22.

Dr. Rajendra Prasad Center for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India.

Purpose: To evaluate the effect of mindfulness meditation (MM) on intraocular pressure (IOP) and trabecular meshwork (TM) gene expression in patients with medically uncontrolled primary open angle glaucoma (POAG).

Design: Parallel arm, single-masked, randomized controlled trial.

Methods: Sixty POAG patients with IOP ≥21 mm Hg taking maximal topical medication and scheduled for trabeculectomy were included in this study at a tertiary eye care center in India. Thirty patients (Group 1) underwent 3 weeks of 45-minute daily MM sessions in addition to medical therapy while Group 2 continued medical therapy only. Primary outcome was change in IOP (ΔIOP) after 3 weeks of MM. Secondary outcomes were probability of success, percentage of reduction in IOP, effect on diurnal variations of IOP, changes in quality of life (QoL), and changes in gene expression patterns in TM.

Results: At 3 weeks, a significant decrease in IOP was seen in Group 1 (20.16 ± 3.3 to 15.05 ± 2.4mm Hg; P = .001), compared to Group 2 (21.2 ± 5.6 to 20.0 ± 5.8mm Hg; P = .38). ΔIOP was significantly higher in Group 1 than in Group 2 (5.0 ± 1.80 vs. 0.20 ± 3.03mm Hg; P = .001). Analysis of gene expression revealed significant upregulation of nitric oxide synthetase (NOS1 and NOS3) and neuroprotective genes with downregulation of proinflammatory genes in Group 1 in comparison to Group 2 (P = .001).

Conclusions: MM was associated with significant decrease in IOP and changes in TM gene expression, indicating its direct impact on ocular tissues.
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http://dx.doi.org/10.1016/j.ajo.2020.10.012DOI Listing
March 2021

Suboptimal SARS-CoV-2-specific CD8 T cell response associated with the prominent HLA-A*02:01 phenotype.

Proc Natl Acad Sci U S A 2020 09 10;117(39):24384-24391. Epub 2020 Sep 10.

Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia;

An improved understanding of human T cell-mediated immunity in COVID-19 is important for optimizing therapeutic and vaccine strategies. Experience with influenza shows that infection primes CD8 T cell memory to peptides presented by common HLA types like HLA-A2, which enhances recovery and diminishes clinical severity upon reinfection. Stimulating peripheral blood mononuclear cells from COVID-19 convalescent patients with overlapping peptides from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to the clonal expansion of SARS-CoV-2-specific CD8 and CD4 T cells in vitro, with CD4 T cells being robust. We identified two HLA-A*02:01-restricted SARS-CoV-2-specfic CD8 T cell epitopes, A2/S and A2/Orf1ab Using peptide-HLA tetramer enrichment, direct ex vivo assessment of A2/SCD8 and A2/Orf1abCD8 populations indicated that A2/SCD8 T cells were detected at comparable frequencies (∼1.3 × 10) in acute and convalescent HLA-A*02:01 patients. These frequencies were higher than those found in uninfected HLA-A*02:01 donors (∼2.5 × 10), but low when compared to frequencies for influenza-specific (A2/M1) and Epstein-Barr virus (EBV)-specific (A2/BMLF) (∼1.38 × 10) populations. Phenotyping A2/SCD8 T cells from COVID-19 convalescents ex vivo showed that A2/SCD8 T cells were predominantly negative for CD38, HLA-DR, PD-1, and CD71 activation markers, although the majority of total CD8 T cells expressed granzymes and/or perforin. Furthermore, the bias toward naïve, stem cell memory and central memory A2/SCD8 T cells rather than effector memory populations suggests that SARS-CoV-2 infection may be compromising CD8 T cell activation. Priming with appropriate vaccines may thus be beneficial for optimizing CD8 T cell immunity in COVID-19.
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http://dx.doi.org/10.1073/pnas.2015486117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7533701PMC
September 2020

Bent conformation of a backbone pilin N-terminal domain supports a three-stage pilus assembly mechanism.

Commun Biol 2018 17;1:94. Epub 2018 Jul 17.

Laboratory of Structural Microbiology, Regional Centre for Biotechnology, NCR Biotech Science Cluster, Faridabad, 121001, India.

Effective colonization of host cells by some Gram-positive bacteria often involves using lengthy, adhesive macromolecular structures called sortase-dependent pili. Among commensals, the gut-adapted GG strain encodes the operons for two varieties of these pili (SpaCBA and SpaFED), with each structure consisting of backbone, tip, and basal pilin subunits. Although the tertiary structure was recently solved for the backbone subunit (SpaA) of the SpaCBA pilus, no structural information exists for its counterpart in the SpaFED pilus. Here, we report several crystal structures for the SpaD backbone pilin, two of which capture the N-terminal domain in either the closed (linear) or open (bent) conformation. To our knowledge, this is the first observation of the bent conformation in Gram-positive pilin structures. Based on this bent conformation, we suggest a three-stage model, which we call the expose-ligate-seal mechanism, for the docking and assembly of backbone pilins into the sortase-dependent pilus.
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http://dx.doi.org/10.1038/s42003-018-0100-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6123636PMC
July 2018

Technology adoption and prediction tools for everyday technologies aimed at people with dementia.

Annu Int Conf IEEE Eng Med Biol Soc 2016 Aug;2016:4407-4410

A wide range of assistive technologies have been developed to support the elderly population with the goal of promoting independent living. The adoption of these technology based solutions is, however, critical to their overarching success. In our previous research we addressed the significance of modelling user adoption to reminding technologies based on a range of physical, environmental and social factors. In our current work we build upon our initial modeling through considering a wider range of computational approaches and identify a reduced set of relevant features that can aid the medical professionals to make an informed choice of whether to recommend the technology or not. The adoption models produced were evaluated on a multi-criterion basis: in terms of prediction performance, robustness and bias in relation to two types of errors. The effects of data imbalance on prediction performance was also considered. With handling the imbalance in the dataset, a 16 feature-subset was evaluated consisting of 173 instances, resulting in the ability to differentiate between adopters and non-adopters with an overall accuracy of 99.42 %.
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http://dx.doi.org/10.1109/EMBC.2016.7591704DOI Listing
August 2016

Modelling assistive technology adoption for people with dementia.

J Biomed Inform 2016 10 30;63:235-248. Epub 2016 Aug 30.

Department of Psychology, Utah State University, Logan, UT 84322-4440, USA.

Purpose: Assistive technologies have been identified as a potential solution for the provision of elderly care. Such technologies have in general the capacity to enhance the quality of life and increase the level of independence among their users. Nevertheless, the acceptance of these technologies is crucial to their success. Generally speaking, the elderly are not well-disposed to technologies and have limited experience; these factors contribute towards limiting the widespread acceptance of technology. It is therefore important to evaluate the potential success of technologies prior to their deployment.

Materials And Methods: The research described in this paper builds upon our previous work on modelling adoption of assistive technology, in the form of cognitive prosthetics such as reminder apps and aims at identifying a refined sub-set of features which offer improved accuracy in predicting technology adoption. Consequently, in this paper, an adoption model is built using a set of features extracted from a user's background to minimise the likelihood of non-adoption. The work is based on analysis of data from the Cache County Study on Memory and Aging (CCSMA) with 31 features covering a range of age, gender, education and details of health condition. In the process of modelling adoption, feature selection and feature reduction is carried out followed by identifying the best classification models.

Findings: With the reduced set of labelled features the technology adoption model built achieved an average prediction accuracy of 92.48% when tested on 173 participants.

Conclusions: We conclude that modelling user adoption from a range of parameters such as physical, environmental and social perspectives is beneficial in recommending a technology to a particular user based on their profile.
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http://dx.doi.org/10.1016/j.jbi.2016.08.021DOI Listing
October 2016

New insights about pilus formation in gut-adapted Lactobacillus rhamnosus GG from the crystal structure of the SpaA backbone-pilin subunit.

Sci Rep 2016 06 28;6:28664. Epub 2016 Jun 28.

Regional Centre for Biotechnology, NCR Biotech Science Cluster, Faridabad-121 001, India.

Thus far, all solved structures of pilin-proteins comprising sortase-assembled pili are from pathogenic genera and species. Here, we present the first crystal structure of a pilin subunit (SpaA) from a non-pathogen host (Lactobacillus rhamnosus GG). SpaA consists of two tandem CnaB-type domains, each with an isopeptide bond and E-box motif. Intriguingly, while the isopeptide bond in the N-terminal domain forms between lysine and asparagine, the one in the C-terminal domain atypically involves aspartate. We also solved crystal structures of mutant proteins where residues implicated in forming isopeptide bonds were replaced. Expectedly, the E-box-substituted E139A mutant lacks an isopeptide bond in the N-terminal domain. However, the C-terminal E269A substitution gave two structures; one of both domains with their isopeptide bonds present, and another of only the N-terminal domain, but with an unformed isopeptide bond and significant conformational changes. This latter crystal structure has never been observed for any other Gram-positive pilin. Notably, the C-terminal isopeptide bond still forms in D295N-substituted SpaA, irrespective of E269 being present or absent. Although E-box mutations affect SpaA proteolytic and thermal stability, a cumulative effect perturbing normal pilus polymerization was unobserved. A model showing the polymerized arrangement of SpaA within the SpaCBA pilus is proposed.
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http://dx.doi.org/10.1038/srep28664DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4923907PMC
June 2016

Purification, crystallization and preliminary X-ray diffraction analysis of SpaD, a backbone-pilin subunit encoded by the fimbrial spaFED operon in Lactobacillus rhamnosus GG.

Acta Crystallogr F Struct Biol Commun 2015 Jan 1;71(Pt 1):103-6. Epub 2015 Jan 1.

Regional Centre for Biotechnology, Gurgaon, Haryana 122 016, India.

SpaD is the predicted backbone-pilin subunit of the SpaFED pilus, whose loci are encoded by the fimbrial spaFED operon in Lactobacillus rhamnosus GG, a Gram-positive gut-adapted commensal strain with perceived probiotic benefits. In this study, soluble recombinant SpaD protein was overproduced in Escherichia coli and then purified by Ni2+-chelating affinity and gel-filtration chromatography. After limited proteolysis with α-chymotrypsin, good-quality crystals of SpaD were obtained which diffracted beyond 2.0 Å resolution. These crystals belonged to the orthorhombic space group P2(1)2(1)2(1), with unit-cell parameters a=50.11, b=83.27, c=149.65 Å. For phasing, sodium iodide-derivatized crystals were prepared using the halide quick-soaking method and diffraction data were collected in-house to a resolution of 2.2 Å. An interpretable electron-density map was successfully obtained using single-wavelength anomalous diffraction (SAD).
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http://dx.doi.org/10.1107/S2053230X14027216DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4304758PMC
January 2015

Duration discretisation for activity recognition.

Technol Health Care 2012 ;20(4):277-95

School of Computing and Information Engineering, University of Ulster, Coleraine, Northern Ireland, UK.

Activity recognition has become a key component within smart environments that aim at providing assistive solutions for their users. Learning high level activities from low level sensor data depends on several parameters, one of which is the duration of the activities themselves. Nevertheless, directly incorporating continuous duration values into a model is a complex process and may not prove to be very qualitative. In this paper we aim at discretising activity related durations using different clustering algorithms. We explore the possibility of discretising duration data through the use of rudimentary clustering algorithms such as visual inspection to more established methods such as model based clustering. In addition, a probabilistic model is built that predicts both person and activities from the observed values of sensor sequence, time and discrete duration values. Each of the models created is compared in terms of its performance in the prediction of activities. Following analysis of the results attained it has been found that irrespective of the clustering algorithm used for duration discretisation, incorporating the duration information increases the prediction performance. Prediction accuracy was improved by almost 3% when the model was built incorporating durations.
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http://dx.doi.org/10.3233/THC-2012-0677DOI Listing
April 2013