Biology subjects

Mohapatra, S.

Publications and source records attributed to Mohapatra, S..

34 records · Page 2Linked to original sources

bioRxiv2023

Flock response to sustained asynchronous predator attacks

Collective behaviour is a ubiquitous emergent phenomenon where organisms share information and conduct complicated manoeuvres as a group. Dilution of predation risk is presumed to be a major proponent contributing towards the emergence of such fascinating behaviour. However, the role of multiple sources of predation risk in determining the characteristics of the escape manoeuvres remains largely unexplored. The current work aims to address this paucity by examining the response of a flock to multiple persistently pursuing predators, using an agent-based approach employing a force-based model. Collective features such as herding, avoiding and split-and-join are observed across a wide spectrum of systemic conditions. The transition from one response state to another is examined as a function of the relative angle of predator attack, a parameter exclusive to multi-predator systems. Other concomitant parameters, such as the frequency of attacks and compatibility of target selection tactics of the predators, have a significant effect on the escape probability of the prey (i.e., the success rate of escape manoeuvres). A quantitative analysis has been carried out to determine the most successful combination of target selection while also focusing on beneficial ancillary effects such as flock splitting. The long-term dynamics of the system indicate a faster decay of prey numbers (higher prey mortality) at higher coordination strength due to a monotonically decreasing relation between coordination strength and prey speed supplanted by coincidental synchrony of predator attacks. The work highlights the non-additive nature of the effects of predation in a multi-predator system and urges further scrutiny of group hunting dynamics in such systems. Author summaryCollective motion is a natural phenomenon observed across a wide range of length and time scales. One purported reason for the development of such behaviour is to reduce the individual risk of predation through the many-eyes effect and group manoeuvring in case of attacks. However, the behaviour of the prey flock can turn out to be starkly different when there are multiple predators involved. We examine the response of the flock in the presence of multiple predators and find the circumstances leading to the occurrence of different escape manoeuvres. We observe the stricter penalty warranted on the flock due to certain manoeuvres, such as split-and-join, due to the asynchronous and persistent nature of the predator attacks. We also identify the issues with superfluous coordination among prey and its ramifications in terms of prey mortality. The combined effect of the predators is found to outpace the sum of individual predator prowess. The current work emphasises the distinct dynamics of a multi-predator system and puts forth pertinent queries regarding synchronisation among predators and group hunting tactics.

biophysics↗

bioRxiv2023

In silico analysis of the altered protein structure and functions caused by existing synaptic gene mutations in Indian population having neurological disorders

Neurological disorders encompass a diverse range of conditions that affect individuals cognitive, emotional, and social functioning. Though these disorders are multifactorial, genetic factors play a significant role in the pathogenesis. Especially, synaptic gene mutations or synaptic protein dysfunction are shown to be closely associated with neuropathology. This study aims at understanding the critical role of synaptic compartment by conducting comprehensive analysis of existing synaptic gene mutations responsible for the development of three significant disorders in the Indian population: autism spectrum disorder (ASD), epilepsy and schizophrenia (SZ). Our in-silico analysis predicts that mutations in synaptic genes RPL10 (rs387906727), GABRA1 (rs121434579) and DRD2 (rs1801028) corresponding to ASD, epilepsy and SZ respectively, are deleterious. Of these, SZ-related mutations in DRD2 (D(2) dopamine receptor) are deleterious and due to its genetic association also with ASD as well sociosexual behavior, this study focuses on DRD2. In silico analysis using molecular docking revealed an abnormal interaction between D(2) dopamine receptor and neuronal calcium sensor 1, which may hamper neurotransmitter regulation. We further employed a post-weaning social isolation mice model of SZ to investigate the D(2) dopamine receptor expression levels in hippocampus and social behavioral changes. We observed a reduced immunofluorescent intensities of D(2) dopamine receptor and NCS1 compared to group-housed controls in hippocampus and a trend towards an impaired sociosexual behavior characterized by anogenital sniffing in a male-female social interaction test. Altogether, our study helps to further our understanding of synaptic signaling in the context of SZ and decode the probable mechanism by which disrupted synaptic signaling and protein-protein interaction may lead to the disease pathology and further aid in identifying novel therapeutic targets.

neuroscience↗

bioRxiv2023

Analysis of root volatiles and functional characterization of a root-specific germacrene A synthase in Artemisia pallens

Davana (Artemisia pallens) is a valuable aromatic herb within the Asteraceae family, highly prized for its essential oil (EO) produced in the aerial parts. However, the root volatiles and their specific composition, and genes responsible for root volatiles have remained unexplored until now. Here, we show that A. pallens roots possess distinct oil bodies and yields [~]0.05% of EO, which is primarily composed of sesquiterpenes {beta}-elemene, neryl isovalerate, {beta}-selinene, and -selinene, and trace amounts of monoterpenes {beta}-myrcene, D-limonene. This shows that, besides aerial parts, roots of davana can also be a source of unique EO. Moreover, we functionally characterized a terpene synthase (ApTPS1) that exhibited high in silico expression in the root transcriptome. The recombinant ApTPS1 showed the formation of {beta}-elemene and germacrene A with E,E-farnesyl diphosphate (FPP) as a substrate. Further, detailed analysis of assay products revealed that {beta}-elemene was the thermal rearrangement product of germacrene A. Furthermore, the functional expression of ApTPS1 in Saccharomyces cerevisiae confirmed the in vivo {beta}-elemene/germacrene A synthase activity of ApTPS1. At the transcript level, ApTPS1 displayed predominant expression in root, with significantly lower level of expression in other tissues. This expression pattern of ApTPS1 positively correlated with the tissue-specific accumulation level of {beta}-elemene. Overall, these findings provide fundamental insights into the EO profile of davana roots, and the contribution of ApTPS1 in the formation of a major root volatile. Main conclusionThe study demonstrated that Artemisia pallens roots can be a source of terpene-rich essential oil and root-specific ApTPS1 forms germacrene-A contributing to major root volatiles.

plant biology↗

bioRxiv2023

Design of Cytotoxic T Cell Epitopes by Machine Learning of Human Degrons

Antigen processing is critical for producing epitope peptides that are presented by HLA molecules for T cell recognition. Therapeutic vaccines aim to harness these epitopes for priming cytotoxic T cell responses against cancer and pathogens, but insufficient processing often reduces vaccine efficacy through limiting the quantity of epitopes released. Here, we set out to improve antigen processing by harnessing protein degradation signals called degrons from the ubiquitin-proteasome system. We used machine learning to generate a computational model that ascribes a proteasomal degradation score between 0 and 100. Epitope peptides with varying degron activities were synthesized and translocated into cells using nontoxic anthrax proteins: protective antigen (PA) and the N-terminus of lethal factor (LFN). Immunogenicity studies revealed epitope sequences with a low score (<25) show pronounced T-cell activation but epitope sequences with a higher score (>75) provide limited activation. This work sheds light on the sequence-activity relationships between proteasomal degradation and epitope immunogenicity, through conserving the epitope region but varying the flanking sequence. We anticipate that future efforts to incorporate proteasomal degradation signals into vaccine designs will lead to enhanced cytotoxic T cell priming by vaccine therapeutics in clinical settings.

immunology↗

bioRxiv2023

Computational prediction of gamma-oryzanol as potential agonist of human peroxisome proliferator-activated receptor gamma (ppar-γ)

Diabetes mellitus is one of the complex metabolic disorders associated with individuals leading sedentary lifestyles. It leads to several complications rendering the normal function of vital organs like heart, liver, kidney, eye and brain. Scientists and doctors across the globe are involved in research for understanding the complex genetics of this disorder and formulating newer therapeutics accordingly. The finding of potential chemical entities and their underlying agonists or antagonist activities significantly controls the disorder but with some consequences. Thus there is demand for natural compounds and indigenous treatment methods for controlling the disorder with least or no adverse consequences. In the current work we present computational prediction of gamma-oryzanol as potential agonist of human peroxisome proliferator-activated receptor gamma (PPAR-{gamma}). A group of four gamma-oryzanol compound structures reported in PubChem database were downloaded and docked in the ligand binding site of five different human PPAR-{gamma} structures reported in PDB database. It was observed that most of the gamma-oryzanol compounds occupied themselves in the ligand binding P1, P2, P3, P4 sites with similar orientations as that of co-crystal agonists. Their binding conformations were assisted by some reasonable docking scores (-7 to -11 kcal/mol) and hydrogen bond interactions with some important conserved amino acid residues lining the ligand binding site. Additionally we have done a comparative molecular dynamics studies to reveal the flexibility of gamma-oryzanol in the ligand binding site in comparison to the co-crystal agonist and a scaffold analysis using the structure of six agonists and gamma-oryzanol for fetching potential scaffolds which may helpful in designing of new chemical entities.

bioinformatics↗

bioRxiv2023

Copper drives prion protein phase separation and modulates aggregation

Prion diseases are characterized by prion protein (PrP) transmissible aggregation and toxicity in the brain. The physiological function of PrP seems related to sequestering and internalization of redox-active Cu2+. It is unclear whether Cu2+ contributes to PrP aggregation, recently shown to be mediated by PrP condensation. We investigated the role of Cu2+ and oxidation in PrP condensation and aggregation using multiple biophysical and biochemical methods. We find that Cu2+ promotes PrP condensation at the cell surface and in vitro through co-partitioning. Molecularly, Cu2+ inhibited PrP {beta}-structure and hydrophobic residues exposure. Oxidation, induced by H2O2, triggered liquid-to-solid transition of PrP:Cu2+ condensates and promoted amyloid-like PrP aggregation. In cells, overexpression of PrPC initially protected against Cu2+ cytotoxicity but led to PrPC aggregation upon extended copper exposure. Our data suggest that PrP condensates function as a buffer for copper that prevent copper toxicity but can transition into PrP aggregation at prolonged oxidative stress.

biophysics↗

bioRxiv2023

Structural insights into ligand-recognition, activation, and signaling-bias at the complement C5a receptor, C5aR1

Activation of the complement cascade is a critical part of our innate immune response against invading pathogens, and it operates in a concerted fashion with the antibodies and phagocytic cells towards the clearance of pathogens. The complement peptide C5a, generated during the activation of complement cascade, is a potent inflammatory molecule, and increased levels of C5a are implicated in multiple inflammatory disorders including the advanced stages of COVID-19 pathophysiology. The proximal step in C5a-mediated cellular and physiological responses is its interaction with two different seven transmembrane receptors (7TMRs) known as C5aR1 and C5aR2. Despite a large body of functional data on C5a-C5aR1 interaction, direct visualization of their interaction at high-resolution is still lacking, and it represents a significant knowledge gap in our current understanding of complement receptor activation and signaling. Here, we present cryo-EM structures of C5aR1 activated by its natural agonist C5a, and a G-protein-biased synthetic peptide ligand C5apep, in complex with heterotrimeric G-proteins. The C5a-C5aR1 structure reveals the ligand binding interface involving the N-terminus and extracellular loops of the receptor, and we observe that C5a exhibits a significant conformational change upon its interaction with the receptor compared to the basal conformation. On the other hand, the structural details of C5apep-C5aR1 complex provide a molecular basis to rationalize the ability of peptides, designed based on the carboxyl-terminus sequence of C5a, to act as potent agonists of the receptor, and also the mechanism underlying their biased agonism. In addition, these structural snapshots also reveal activation-associated conformational changes in C5aR1 including outward movement of TM6 and a dramatic rotation of helix 8, and the interaction interface for G-protein-coupling. In summary, this study provides previously lacking molecular basis for the complement C5a recognition and activation of C5aR1, and it should facilitate structure-based discovery of novel lead molecules to target C5aR1 in inflammatory disorders.

biophysics↗

bioRxiv2023

Massively parallel single molecule tracking of sequence-dependent DNA mismatch repair in vivo

Whether due to mutagens or replication errors, DNA mismatches arise spontaneously in vivo. Unrepaired mismatches are sources of genetic variation and point mutations which can alter cellular phenotype and cause dysfunction, diseases, and cancer. To understand how diverse mismatches in various sequence contexts are recognized and repaired, we developed a high-throughput sequencing-based approach to track single mismatch repair outcomes in vivo and determined the mismatch repair efficiencies of 5682 distinct singly mispaired sequences in E. coli. We found that CC mismatches are always poorly repaired, whereas local sequence context is a strong determinant of the hypervariable repair efficiency of TT, AG, and CT mismatches. Single molecule FRET analysis of MutS interactions with mismatched DNA showed that well-repaired mismatches have a higher effective rate of sliding clamp formation. The hypervariable repair of TT mismatches can cause selectively enhanced mutability if a failure to repair would result in synonymous codon change or a conservative amino acid change. Sequence-dependent repair efficiency in E. coli can explain the patterns of substitution mutations in mismatch repair-deficient tumors, human cells, and C. elegans. Comparison to biophysical and biochemical analyses indicate that DNA physics is the primary determinant of repair efficiency by its impact on the mismatch recognition by MutS.

biophysics↗

bioRxiv2022

A machine learning approach to identify the engagement of a brain network targeted by non-invasive brain-stimulation

Transcranial direct current stimulation (tDCS) can noninvasively modulate behavior, cognition, and physiologic brain functions depending on polarity and dose of stimulation as well as montage of electrodes. Concurrent tDCS-fMRI presents a novel way to explore the parameter space of non-invasive brain stimulation and to inform the experimenter as well as the participant if a targeted brain region or a network of spatially separate brain regions has been engaged and modulated. We compared a multi-electrode (ME) with a single electrode (SE) montage and both active conditions with a no-stimulation (NS) control condition to assess the engagement of a brain network and the ability of different electrode montages to modulate network activity. The multi-electrode montage targeted nodal regions of the right Arcuate Fasciculus Network (AFN) with anodal electrodes placed over the skull position of the posterior superior temporal/middle temporal gyrus (STG/MTG), supramarginal gyrus (SMG), posterior inferior frontal gyrus (IFG) and a return cathodal electrode over the left supraorbital region. In comparison, the single electrode montage used only one anodal electrode over a nodal brain region of the AFN, but varied the location between STG/MTG, SMG, and posterior IFG for different participants. Whole-brain rs-fMRI was obtained every three seconds. The tDCS-stimulator was turned on at 3 minutes after the scanning started. A 4D rs-fMRI data set was converted to dynamic functional connectivity (DFC) matrices using a set of ROI pairs belonging to the AFN as well as other unrelated brain networks. In this study, we evaluated the performance of five algorithms to classify the DFC matrices from the three conditions (ME, SE, NS) into three different categories. The highest accuracy of 0.92 was obtained for the classification of the ME condition using the K Nearest Neighbor (KNN) algorithm. In other words, applying the classification algorithm allowed us to identify the engagement of the AFN and the ME condition was the best montage to achieve such an engagement. The top 5 ROI pairs that made a major contribution to the classification of participants rs-fMRI data were identified using model performance parameters; ROI pairs were mainly located within the right AFN. This proof-of-concept study using a classification algorithm approach can be expanded to create a real-time feedback system at a participant level to detect the engagement and modulation of a brain network that spans multiple brain lobes.

neuroscience↗

bioRxiv2022

Engineering functional membrane-membrane interface by InterSpy

Engineering synthetic interfaces between membranes has potential applications in designing non-native cellular communication pathways and creating synthetic tissues. Here, InterSpy is introduced as a synthetic biology tool consisting of a heterodimeric protein engineered to form and maintain membrane-membrane interfaces between apposing synthetic as well as cell membranes through SpyTag/SpyCatcher interaction. Inclusion of split fluorescent protein fragments in the designed InterSpy toolkit allows tracking the formation of membrane-membrane interface and reconstitution of functional fluorescent protein in the space between apposing membranes. We first demonstrate InterSpy by testing split protein designs using a mammalian cell-free expression system. By utilizing co-translational helix insertion, cell-free synthesized InterSpy fragments are incorporated into the membrane of liposomes and supported lipid bilayers with a desired topology. Functional reconstitution of split fluorescent protein between the membranes is strictly dependent on SpyTag/SpyCatcher. Finally, since InterSpy is fully genetically encoded, the engineered system is adapted to cells and showcased. InterSpy demonstrates the power of cell-free expression systems in functional reconstitution of synthetic membrane interfaces via proximity-inducing proteins. This technology may also prove useful for synthetic biology where cell-cell contacts and communication are recreated in a controlled manner using minimal components.

synthetic biology↗

bioRxiv2022

Targeting an evolutionarily conserved "E-L-L" motif in the spike protein to develop a small molecule fusion inhibitor against SARS-CoV-2

As newer variants of SARS-CoV-2 continue to pose major threats to global human health and economy, identifying novel druggable antiviral targets is the key towards sustenance. Here, we identify an evolutionary conserved "E-L-L" motif present within the HR2 domain of all human and non-human coronavirus spike (S) proteins that play a crucial role in stabilizing the post-fusion six-helix bundle (6-HB) structure and thus, fusion-mediated viral entry. Mutations within this motif reduce the fusogenicity of the S protein without affecting its stability or membrane localization. We found that posaconazole, an FDA-approved drug, binds to this "E-L-L" motif resulting in effective inhibition of SARS-CoV-2 infection in cells. While posaconazole exhibits high efficacy towards blocking S protein-mediated viral entry, mutations within the "E-L-L" motif rendered the protein completely resistant to the drug, establishing its specificity towards this motif. Our data demonstrate that posaconazole restricts early stages of infection through specific inhibition of membrane fusion and viral genome release into the host cell and is equally effective towards all major variants of concerns of SARS-CoV-2 including beta, kappa, delta, and omicron. Together, we show that this conserved essential "E-L-L" motif is an ideal target for the development of prophylactic and therapeutic interventions against SARS-CoV-2.

biochemistry↗

bioRxiv2022

Visual Perception of 3D Space and Shape in Time - Part III: 2D Shape Recognition by Log-Scaling

Human vision has a remarkable ability to recognize complex 3D objects such as faces that appear with any size and 3D orientations at any 3D location. If we initially memorize a face only with a normalized size and viewed from directly head on, the direct comparison between the one-sized memory and a new incoming image would demand tremendous mental frame translations in 7D. How can we perform such a demanding task so promptly and reliably as we experience the objects in the world around us? Intriguingly, our primary visual cortex exhibits a 2D retinotopy with a log-polar coordinate system, where scaling up/down of shape is converted to linear frame translation. As a result, mental scaling can be performed by linearly translating the memory or the perceptual image until they overlap with each other. According to our new model of NHT (Neural Holography Tomography), alpha brainwaves traveling at a constant speed can conduct this linear translation. With this scheme, every scaling up/down by a factor of two should take the same amount of extra mental time to recognize a smaller/larger face. To test this hypothesis, we designed a reaction time (RT) experiment, where participants were first asked to memorize sets of unfamiliar faces with a given specific size (4{degrees} or 8{degrees}). Following the memorization phase, similar stimuli with a wide range of sizes (from 1{degrees} to 32{degrees}) were presented, and RTs were recorded. As predicted, the increase in RT was proportional to the scaling factor in the log scale. Furthermore, we observed that RTs were fastest for 8{degrees} faces even if the memorized face was 4{degrees}. This supports our hypothesis that we always memorize faces at the exact size of ~8 {degrees}. To our surprise, the increases in RT were also consistent with the mentally-estimated depth sensation, which indicates that the apparent size of the recognized face can create a proper depth sensation.

neuroscience↗

bioRxiv2021

Inhibition of SARS-CoV-2 spike protein palmitoylation reduces virus infectivity

Spike glycoproteins of almost all enveloped viruses are known to undergo post-translational attachment of palmitic acid moieties. The precise role of such palmitoylation of the spike protein in membrane fusion and infection is not completely understood. Here, we report that palmitoylation of the first five cysteine residues of the c-terminal cysteine-rich domain of the SARS-CoV-2 spike are indispensable for infection and palmitoylation deficient spike mutants are defective in trimerization and subsequent membrane fusion. The DHHC9 palmitoyltransferase interacts with and palmitoylates the spike protein in the ER and Golgi, and knockdown of DHHC9 results in reduced fusion and infection of SARS-CoV-2. Two bis-piperazine backbone-based DHHC9 inhibitors inhibit SARS-CoV-2 spike protein palmitoylation and the resulting progeny virion particles released are defective in fusion and infection. This establishes these palmitoyltransferase inhibitors as potential new intervention strategies against SARS-CoV-2.

molecular biology↗

bioRxiv2020

Interpretable Deep Learning for De Novo Design of Cell-Penetrating Abiotic Polymers

There are more amino acid permutations within a 40-residue sequence than atoms on Earth. This vast chemical search space hinders the use of human learning to design functional polymers. Here we couple supervised and unsupervised deep learning with high-throughput experimentation to drive the design of high-activity, novel sequences reaching 10 kDa that deliver antisense oligonucleotides to the nucleus of cells. The models, in which natural and unnatural residues are represented as topological fingerprints, decipher and visualize sequence-activity predictions. The new variants boost antisense activity by 50-fold, are effective in animals, are nontoxic, and can also deliver proteins into the cytosol. Machine learning can discover functional polymers that enhance cellular uptake of biotherapeutics, with significant implications toward developing therapies for currently untreatable diseases. One sentence summaryDeep learning generates de novo large functional abiotic polymers that deliver antisense oligonucleotides to the nucleus.

bioinformatics↗

bioRxiv2020

Identification of QTLs for high grain yield and component traits in New Plant Types of rice

A panel of 60 genotypes consisting of New Plant Types (NPTs) along with indica, tropical and temperate japonica genotypes were phenotypically evaluated for four seasons in irrigated situation for grain yield per se and component traits. Twenty NPT genotypes were found to be promising with an average grain yield of 5.45 to 8.8 t/ha. A total of 85 SSR markers were used in the study to identify QTLs associated with grain yield per se and related traits. Sixty-six (77.65%) markers were found to be polymorphic. The PIC values varied from 0.516 to 0.92 with an average of 0.704. A moderate level of genetic diversity (0.39) was detected among genotypes. Variation to the tune of 8% within genotypes, 68% among the genotypes within the population and 24% among the populations were observed (AMOVA). The association analysis using GLM and MLM models led to the identification of 30 and 10 SSR markers were associated with 70 and 16 QTLs, respectively. Thirty novel QTLs linked with 16 SSRs were identified to be associated with eleven traits, namely, tiller number (qTL-6.1, qTL-11.1, qTL-4.1), panicle length (qPL-1.1, qPL-5.1, qPL-7.1, qPL-8.1), flag leaf length (qFLL-8.1, qFLL-9.1), flag leaf width (qFLW-6.2, qFLW-5.1, qFLW-8.1, qFLW-7.1), total no. of grains (qTG-2.2, qTG-a7.1), thousand-grain weight (qTGW-a1.1, qTGW-a9.2, qTGW-5.1, qTGW-8.1), fertile grains (qFG-7.1), seed length-breadth ratio (qSlb-3.1), plant height (qPHT-6.1, qPHT-9.1), days to 50% flowering (qFD-1.1) and grain yield per se (qYLD-5.1, qYLD-6.1a, qYLD-11.1). This information could be useful for identification of highly potential parents for development of transgressive segregants. Moreover, super rice genotypes could be developed through pyramiding of these QTLS for important yield traits for prospective increment in yield potentiality and breaking yield ceiling.

plant biology↗

bioRxiv2018

Modified Pearson Correlation Coefficient for Two-color Imaging in Spherocylindrical Cells

The revolution in fluorescence microscopy enables sub-diffraction-limit (\"superresolution\") localization of hundreds or thousands of copies of two differently labeled proteins in the same live cell. In typical experiments, fluorescence from the entire three-dimensional (3D) cell body is projected along the z-axis of the microscope to form a 2D image at the camera plane. For imaging of two different species, here denoted \"red\" and \"green\", a significant biological question is the extent to which the red and green spatial distributions are positively correlated, anti-correlated, or uncorrelated. A commonly used statistic for assessing the degree of linear correlation between two image matrices R and G is the Pearson Correlation Coefficient (PCC). PCC should vary from -1 (perfect anti-correlation) to 0 (no linear correlation) to +1 (perfect positive correlation). However, in the special case of spherocylindrical bacterial cells such as E. coli or B. subtilis, we show that the PCC fails both qualitatively and quantitatively. PCC returns the same +1 value for 2D projections of distributions that are either perfectly correlated in 3D or completely uncorrelated in 3D. The PCC also systematically underestimates the degree of anti-correlation between the projections of two perfectly anti-correlated 3D distributions. The problem is that the projection of a random spatial distribution within the 3D spherocylinder is non-random in 2D, whereas PCC compares every matrix element of R or G with the constant mean value[Formula] or[Formula] . We propose a modified Pearson Correlation Coefficient (MPCC) that corrects this problem for spherocylindrical cell geometry by using the proper reference matrix for comparison with R and G. Correct behavior of MPCC is confirmed for a variety of numerical simulations and on experimental distributions of HU and RNA polymerase in live E. coli cells. The MPCC concept should be generalizable to other cell shapes.

biophysics↗