Biology subjects

Adhikari, S.

Publications and source records attributed to Adhikari, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Agrobacterium-mediated Cuscuta campestris transformation as a tool for understanding plant-plant interactions

Cuscuta campestris, a stem parasitic plant, has served as a valuable model plant for the exploration of plant-plant interactions and molecular trafficking. However, a major barrier to C. campestris research is that a method to generate stable transgenic plants has not yet been developed. Here, we describe the development of a Cuscuta transformation protocol using various reporter genes (GFP, GUS, or RUBY) and morphogenic genes (CcWUS2 and CcGRF/GIF), ultimately leading to a robust protocol for Agrobacterium-mediated C. campestris transformation. The stably transformed and regenerated RUBY C. campestris plants produced haustoria, the signature organ of parasitic plants, and these were functional in forming host attachments. The locations of T-DNA integration in the parasite genome were confirmed through TAIL-PCR. Transformed C. campestris also produced flowers and transgenic seeds exhibiting betalain pigment, providing proof of germline transmission of the RUBY transgene. Furthermore, the RUBY reporter is not only a useful selectable marker for the Agrobacterium-mediated transformation, but also provides insight into the movement of molecules from C. campestris to the host during parasitism. Thus, the protocol for transformation of C. campestris reported here overcomes a major obstacle to Cuscuta research and opens new possibilities for studying parasitic plants and their interactions with hosts.

plant biology↗

bioRxiv2024

An Integrated Machine Learning Approach Delineates Entropic Modulation of alpha-Synuclein by Small Molecule

The mis-folding and aggregation of intrinsically disordered proteins (IDPs) such as -synuclein (S) underlie the pathogenesis of various neurodegenerative disorders. However, targeting S with small molecules faces challenges due to its lack of defined ligand-binding pockets in its disordered structure. Here, we implement a deep artificial neural network based machine learning approach, which is able to statistically distinguish fuzzy ensemble of conformational substates of S in neat water from those in aqueous fasudil (small molecule of interest) solution. In particular, the presence of fasudil in the solvent either modulates pre-existing states of S or gives rise to new conformational states of S, akin to an ensemble-expansion mechanism. The ensembles display strong conformation-dependence in residue-wise interaction with the small molecule. A thermodynamic analysis indicates that small-molecule modulates the structural repertoire of S by tuning protein backbone entropy, however entropy of the water remains unperturbed. Together, this study sheds light on the intricate interplay between small molecules and IDPs, offering insights into entropic modulation and ensemble expansion as key biophysical mechanisms driving potential therapeutics.

biophysics↗

bioRxiv2023

CNC Knitting Micro-Resolution Mosquito Bite Blocking Textiles

Mosquitoes and other biting arthropods transmit diseases worldwide, causing over 700,000 deaths each year, and costing about 3 billion annually for Aedes species alone. These insects also pose a significant threat to agricultural animals. While clothing could provide a simple solution to vector-borne diseases, modern textiles do not effectively block mosquito bites. To address this issue, we have designed three micro-resolution knitted structures, with five adjustable parameters, that can block bites. These designs were integrated into a computer numerical control knitting robot for mass production of bite-blocking garments with minimal human labor. We then quantified the comfort of blocking garments. Our knits enable individuals to protect themselves from insects amidst their day-to-day activities without impacting the environment. One Sentence SummaryWe create micro-resolution mosquito bite blocking knits produced by robotic manufacturing to protect humans against vector-borne disease.

bioengineering↗

bioRxiv2023

An improved rhythmicity analysis method using Gaussian Processes detects cell-density dependent circadian oscillations in stem cells

Detecting oscillations in time series remains a challenging problem even after decades of research. In chronobiology, rhythms in time series (for instance gene expression, eclosion, egg-laying and feeding) datasets tend to be low amplitude, display large variations amongst replicates, and often exhibit varying peak-to-peak distances (non-stationarity). Most currently available rhythm detection methods are not specifically designed to handle such datasets. Here we introduce a new method, ODeGP (Oscillation Detection using Gaussian Processes), which combines Gaussian Process (GP) regression with Bayesian inference to provide a flexible approach to the problem. Besides naturally incorporating measurement errors and non-uniformly sampled data, ODeGP uses a recently developed kernel to improve detection of non-stationary waveforms. An additional advantage is that by using Bayes factors instead of p-values, ODeGP models both the null (non-rhythmic) and the alternative (rhythmic) hypotheses. Using a variety of synthetic datasets we first demonstrate that ODeGP almost always outperforms eight commonly used methods in detecting stationary as well as non-stationary oscillations. Next, on analyzing existing qPCR datasets that exhibit low amplitude and noisy oscillations, we demonstrate that our method is more sensitive compared to the existing methods at detecting weak oscillations. Finally, we generate new qPCR time-series datasets on pluripotent mouse embryonic stem cells, which are expected to exhibit no oscillations of the core circadian clock genes. Surprisingly, we discover using ODeGP that increasing cell density can result in the rapid generation of oscillations in the Bmal1 gene, thus highlighting our methods ability to discover unexpected patterns. In its current implementation, ODeGP (available as an R package) is meant only for analyzing single or a few time-trajectories, not genome-wide datasets.

systems biology↗

bioRxiv2022

Repurposing of Drugs against mutated strain of Eurasian Avian like H1N1 (EA H1N1) Swine flu, Genotype-4 (G4) virus

Mutation, reassortment and recombination have led to the evolution and the emergence of more pathogenic and new subtypes of influenza virus. The surge of highly mutated viruses has prompted the need of coherent solution for the so called "medical holocaust" viral outbreaks. The genotype 4 of EAH1N1 strain has been circulating in the swine population as a dominant genotype, exhibiting even human to human transmission. This has risen the possibility of causing another global health threat as a lethal viral outbreak in the future. The Computer Aided Drug Discovery (CADD) could be a prudent mechanism to develop new drug candidates against such disease for its mitigation. In this regard, the computational in silico methods had been envisaged in this research for the prediction of lead compounds against the selected proteins of EA H1N1 G4 strain, namely Haemagglutinin (HA) and Polymerase acidic protein(PA). The research focused on the selection of the target viral protein and molecular docking for the identification of putative ligands. It was followed by the identification of the probable mutations and assessment of effectiveness of identified drugs against their respective targets. Total of 3 compounds Enalapril, Enalaprilat and Ivabradine have been identified as a potential inhibitor of HA and PA protein that were prioritized on the basis of preference index parameter and binding energy of compound with the respective target. Besides, the probable mutations in each target protein in future were predicted and all these 3 top hits were found to be effective against mutated variant of these proteins. Thus, Enalapril, Enalaprilat and Ivabradine could be the lead compounds to explore further as multi target inhibiting drugs against wild and mutant variant of target proteins.

bioinformatics↗

bioRxiv2022

IDENTIFICATION AND QUANTIFICATION OF MATRISOME PROTEINS OF MOUSE KIDNEYS

Extracellular matrix (ECM) is essential for tissue homeostasis. Understanding the matrisome (ECM proteome) composition and mechanisms of ECM control in health and disease is crucial for discovering therapeutic agents and diagnostic tools for inflammatory, fibrotic and cancerous conditions. The challenging obstacle in the ECM analysis is the need to optimise matrisome enrichment methods for different organs, diseases, and species. Currently, there is no optimized protocol nor a publicly available matrisome database for mouse kidneys. This limits the power of murine models in renal diseases and development research. In this study, we comparatively explored the matrisome of healthy C57BL/6 mice using two matrisome extraction methods, including the Millipore Compartment Fractionation (Method-1) and the Sequential Extraction (Method-2) approaches. We examined the efficiency of these methods in matrisome profiling by LC-MS/MS, protein identification and label-free quantification using MaxQuant. As a result of the study, 113 matrisome proteins were identified, including 22 proteins that have not been previously listed in the Matrisome Database (MD). Method-2 allowed identification and quantification of all core and ECM-associated matrisome proteins detected by Method-1 and additionally revealed more core matrisome and ECM-associated proteins. By characterisation of the murine renal matrisome enhanced by our methodological insights, this study provides critically important information for biological and medical kidney research.

molecular biology↗

bioRxiv2022

Computational Design of Two New Vitamin K Epoxide Reductase Inhibitors

Vitamin K epoxide reductase (VKOR) inhibitors are commonly used to treat atrial fibrillation and ischemic stroke. However, due to the side effects and poor absorbance of existing drugs, there is urgent need for developing better VKOR inhibitor drugs. In this work, computational bioisosteric replacement and chemical intuition were used to design two novel VKOR inhibitors. The new candidates are predicted to have improved ADMET and binding properties compared to existing drugs.

biochemistry↗

bioRxiv2021

Th1, Th2 and Th17 inflammatory pathways synergistically correlate with cardiometabolic processes. A case study in COVID-19.

A predominant source of complication in SARS-CoV-2 patients arises from the cytokine storm, an elevated expression of inflammatory helper T-cell associated cytokines that can lead to tissue damage and organ failure. The high inflammatory burden of this viral infection often results in cardiovascular comorbidities. A better understanding of the interaction between the cytokine storm and cardiovascular proteins might inform medical decisions and therapeutic approaches. We hypothesized that all major helper T-cell inflammatory pathways (Th1, Th2 and Th17) synergistically contribute to cardiometabolic modifications in serum of COVID-19 patients. We proved our hypothesis by integrating Th1, Th2 and Th17 cytokines to predict expression of cardiometabolic proteins profiled by OLINK proteomics.

bioinformatics↗

bioRxiv2021

Longitudinal in vivo changes in radial peripapillary capillaries and optic nerve head structure in non-human primates with early experimental glaucoma

PurposeThere is conflicting evidence as to whether a loss of radial peripapillary capillaries (RPCs) precedes neuronal loss in glaucoma. We examined the time-course of in vivo changes in RPCs, optic nerve head (ONH) structure, and retinal nerve fiber layer thickness (RNFLT) in experimental glaucoma (EG). MethodsSpectral domain optical coherence tomography images were acquired before and approximately every 2 weeks after inducing unilateral EG in 9 rhesus monkeys to quantify mean anterior lamina cribrosa surface depth (ALCSD), minimum rim width (MRW), and RNFLT. Perfused RPC density was measured from adaptive optics scanning laser ophthalmoscope images acquired on the temporal half of the ONH. The time of first significant change was quantified as when values fell and remained outside of the 95% confidence interval established from control eyes. ResultsMean ALCSD and/or MRW were the first parameters to change in 8 EG eyes. RPC density changed first in the 9th. At their first points of change, mean ALCSD posteriorly deformed by 100.2 {+/-} 101.2 m, MRW thinned by 82.3 {+/-} 65.9 m, RNFLT decreased by 25 {+/-} 14 m, and RPC density decreased by 4.5 {+/-} 2.1%. RPC density decreased before RNFL thinning in 5 EG eyes. RNFLT decreased before RPC density decreased in 2 EG eyes, while 2 EG eyes had simultaneous changes. ConclusionsIn most EG eyes, RPC density decreased before (or simultaneous with) a change in RNFLT, suggesting that vascular factors may play a role in axonal loss in some eyes in early glaucoma.

bioengineering↗

bioRxiv2021

Characterizing Locus Specific Chromatin Structure and Dynamics with Correlative Conventional and Super Resolution imaging in living cells

The dynamic rearrangement of chromatin is critical for gene regulation, but mapping both the spatial organization of chromatin and its dynamics remains a challenge. Many structural conformations are too small to be resolved via conventional fluorescence microscopy and the long acquisition time of super-resolution PALM imaging precludes the structural characterization of chromatin below the optical diffraction limit in living cells due to chromatin motion. Here we develop a correlative conventional fluorescence and PALM imaging approach to quantitatively map time-averaged chromatin structure and dynamics below the optical diffraction limit in living cells. By assigning localizations to a locus as it moves, we reliably discriminate between bound and searching dCas9 molecules, whose mobility overlap. Our approach accounts for changes in DNA mobility and relates local chromatin motion to larger scale domain movement. In our experimental system, we show that compacted telomeres have a higher density of bound dCas9 molecules, but the relative motion of those molecules is more restricted than in less compacted telomeres. Correlative conventional and PALM imaging therefore improves the ability to analyze the mobility and time-averaged nanoscopic structural features of locus specific chromatin with single molecule precision and yields unprecedented insights across length and time scales.

biophysics↗

bioRxiv2020

A Recombinant Protein Biomarker DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins

Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). Here, we employed a mixture of recombinant proteins in DDA libraries to subsequently detect cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 human recombinant proteins that had been previously implicated as possible cancer biomarkers in both our own and other studies. The rPSL was then used to identify proteins from non-depleted colorectal cancer (CRC) plasmas by SWATH-MS. Most (32/36) of the proteins in the rPSL were reliably identified in plasma samples, including 8 proteins (BTC, CXCL10, IL1B, IL6, ITGB6, TGF, TNF, TP53) not previously detected using high-stringency MS in human plasmas according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and post-digestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 were identified using DDA-MS. The 20 additional proteins exclusively identified by using the rPSL approach with SWATH were mostly lower abundance (i.e., <10ng/ml) plasma proteins. To mitigate FDR concerns, and replicating a more typical approach, the DDA rPSL was also merged into a human plasma DDA library. When SWATH identification was repeated using this merged library, the majority (33/36) of low abundance plasma proteins from the rPSL could still be identified using high-stringency HPP Guidelines v3.0 protein inference criteria.

biochemistry↗

bioRxiv2020

Elucidating dynamics and regulation of alternative splicing in osteogenic differentiation

Nearly all human multi-exonic genes undergo alternative splicing (AS) via regulation by RNA-binding proteins (RBPs), but few studies have examined the temporal dynamics of AS and its regulation during cell differentiation in the bone niche. We sought to evaluate how AS, under the control of RBPs, affects cell fate commitment during induced osteogenic differentiation of human bone marrow-derived multipotent stem/stromal progenitor cells (MSPCs). We generated a time-course RNA sequencing (RNA-seq) dataset representative of induced MSPC differentiation to osteoblasts. Our analysis revealed widespread AS changes, coordinated with differential RBP expression, at multiple time points, including many AS changes in non-differentially expressed genes. We also developed a computational approach to profile the dynamics and regulation of AS by RBPs using time-course RNA-seq data, by combining temporal patterns of exon skipping and RBP expression with RBP binding sites in the vicinity of regulated exons. In total we identified nine RBPs as potential key splicing regulators during MSPC osteogenic differentiation. Perturbation of one candidate, KHDRBS3, inhibited osteogenesis and bone formation in vitro, validating our computational prediction of "driver" RBPs. Overall, our work highlights a high degree of complexity in the splicing regulation of MSPC osteogenic differentiation. Our computational approach may be applied to other time-course data to explore dynamic AS changes and associated regulatory mechanisms in other biological processes or disease trajectories.

bioinformatics↗

bioRxiv2020

Computational design of two new soluble epoxide hydrolase (sEH) inhibitors

Inhibitors of soluble epoxide hydrolase (sEH) enzymes have shown great potential for the treatment of neuropathic pain. However, current sEH inhibitors have poor physicochemical properties and has not been proven to be safe for human treatments yet. New inhibitor designs could have the potential to improve current drugs efficacy, and so in this work, chemical intuition and bioisosteric replacement were used to computationally design two novel sEH inhibitors. These new candidates showed good pharmacokinetic properties and presented better docking scores compared to a known sEH inhibitor, t-TUCB, used in the treatment of pain in horses. Homology analysis revealed that Mus musculus may not be suitable organism for preclinical trials studies of these novel inhibitors.

pharmacology and toxicology↗

bioRxiv2020

Computationally Guided Design of Novel Selective Serotonin Reuptake Inhibitors

Current selective serotonin reuptake inhibitor (SSRI) drugs such as paroxetine, fluoxetine and escitalopram are prescribed for mental health conditions such as anxiety and depression. However, there are still several unpleasant side effects which fuels the need for new designs. In this work, computational studies were conducted to design two novel drug candidates with improved docking scores than paroxetine, an existing SSRI drug. Homology analysis was carried out to determine the suitability of an organism for preclinical trials and revealed laboratory mouse (Mus musculus) to be a good candidate.

pharmacology and toxicology↗

bioRxiv2020

Quantitative live-cell PALM reveals nanoscopic Faa4 redistributions and dynamics on lipid droplets during metabolic transitions of yeast

Lipid droplets (LDs) are dynamic lipid storage organelles needed for lipid homeostasis. Cells respond to metabolic changes by regulating the spatial distribution of LDs, as well as enzymes required for LD growth and turnover. Due to LD size below the optical diffraction limit, bulk fluorescence microscopy cannot observe the density and dynamics of specific LD enzymes. Here, we employ quantitative photo-activated localization microscopy (PALM) to study the density of the fatty acid activating protein Faa4 on LDs during log, stationary and lag phases in live yeast cells with single-molecule sensitivity and 30 nm resolution. During the log phase LDs co-localize with the Endoplasmic Reticulum (ER) where the highest Faa4 densities are measured. During transition to the stationary phase LDs translocate to the vacuolar surface and lumen with a ~2-fold increased surface area and a ~2.5-fold increase in Faa4 density, suggesting its role in LD expansion. The increased Faa4 density on LDs is caused by its ~5-fold increased expression level. When lipolysis is induced in stationary-phase cells by diluting them for 2 hrs in fresh medium, Faa4 shuttles to the vacuole through the two observed routes of ER- and lipophagy. The observed vacuolar localization of Faa4 may help activating fatty acids for membrane expansion and reduces Faa4 expression to levels found in the log phase.

biophysics↗

bioRxiv2020

Novel role of AGT gene in aplastic anaemia among paediatric patients based on gene expression profiling

ObjectivesSevere aplastic anemia is characterized by a hypocellular bone marrow and peripheral cytopenia. Mesenchymal stem cells (MSCs) play a crucial role in haematopoietic stem cells (HSCs) development and the microenvironment suitable for haematopoiesis. Investigation of the therapeutic targets by paediatric patient-specific gene expression analysis of the MSCs can be important for diagnosis. MethodsThe study was based on freely available miRNA and host gene expression in NCBI GEO dataset. Microarray based gene expression profiles (GSE33812) of MSCs for five paediatric aplastic anaemia patients and healthy controls were generated using Agilent-014850 platform and the data was downloaded from the database. ResultsMSCs gene expression profiling distinguished between healthy controls, children with aplastic anemia. Angioteninogen (AGT) gene involved in ERK1/ERK2 cascade, cyotokine secretion, metabolic processes was strongly down-regulated among all the patients with aplastic anemia. Emerging role of various transcription factors binding to this gene was identified as a new avenue of therapeutic application. ConclusionsAs a potential diagnostic tool, patient-specific gene expression profiling of MSCs made it possible to make the difficult diagnosis of most patients with aplastic anemia.

bioinformatics↗

bioRxiv2019

Gene regulatory networks associated with lateral root and nodule development in soybean

Legume plants such as soybean produce two major types of root lateral organs, lateral roots and root nodules. A robust computational framework was developed to predict potential gene regulatory networks (GRNs) associated with root lateral organ development in soybean. A genome-scale expression dataset was obtained from soybean root nodules and lateral roots and subjected to biclustering using QUBIC. Biclusters (BCs) and transcription factor (TF) genes with enriched expression in lateral root tissues were converged using different network inference algorithms to predict high confident regulatory modules that are repeatedly retrieved in different methods. The ranked combination of results from all different network inference algorithms into one ensemble solution identified 21 GRN modules of 182 co-regulated genes networks potentially involved in root lateral organ development stages in soybean. The pipeline correctly predicted previously known nodule- and LR-associated TFs including the expected hierarchical relationships. The results revealed high scorer AP2, GRF5, and C3H co-regulated GRN modules during early nodule development; and GRAS, LBD41, and ARR18 co-regulated GRN modules late during nodule maturation. Knowledge from this work supported by experimental validation in the future is expected to help determine key gene targets for biotechnological strategies to optimize nodule formation and enhance nitrogen fixation.

plant biology↗

bioRxiv2018

Unraveling the mechanism of the cadherin-catenin-actin catch bond

The adherens junctions between epithelial cells involve a protein complex formed by E-cadherin, {beta}-catenin, -catenin and F-actin. The stability of this complex was a puzzle for many years, since in vitro studies could reconstitute various stable subsets of the individual proteins, but never the entirety. The missing ingredient turned out to be mechanical tension: a recent experiment that applied physiological forces to the complex with an optical tweezer dramatically increased its lifetime, a phenomenon known as catch bonding. However, in the absence of a crystal structure for the full complex, the microscopic details of the catch bond mechanism remain mysterious. Building on structural clues that point to -catenin as the force transducer, we present a quantitative theoretical model for how the catch bond arises, fully accounting for the experimental lifetime distributions. The model allows us to predict the energetic changes induced by tension at the interface between -catenin and F-actin. It also identifies a significant energy barrier due to a network of salt bridges between two conformational states of {beta}-catenin. By stabilizing one of these states, this barrier could play a role in how the complex responds to additional in vivo binding partners like vinculin. Since significant conformational energy barriers are a common feature of other adhesion systems that exhibit catch bonds, our model can be adapted into a general theoretical framework for integrating structure and function in a variety of force-regulated protein complexes.

biophysics↗