Biology subjects

Agarwal, A.

Publications and source records attributed to Agarwal, A..

At least 73 records · Page 4Linked to original sources

bioRxiv2021

Smartphone-assisted real-time estimation of chlorophyll and carotenoid contents in spinach following the inversion of red and green color features

PurposeChlorophyll (Chl) content is a reliable indicator of leaf nitrogen content and plant health status. Currently available methods for image-based Chl estimation require complex mathematical derivations and high-throughput imaging set-up along with multiplex image-preprocessing steps. Further, the influence of carotenoid (CAR) content has been largely ignored in the process. The present study describes a smartphone-based leaf image analysis method for real-time estimation of Chl content and Chl/CAR ratio. MethodsColor features were obtained from RGB (red, green, blue) images of spinach leaves using a smartphone, and inverse R and G values were calculated. Correlation analysis of color indices and photosynthetic pigment (PP) contents was performed, followed by principal component analysis (PCA). Linear mathematical modeling was performed for describing regression equations for predicting PP contents. Results1/R and 1/G showed strong positive linear correlation (0.93 < r2 < 0.96) with Chl and CAR contents, respectively. Furthermore, 1/R+1/G and [1/R]/[1/G] presented strong positive linear correlation with Chl + CAR (r2 = 0.95) and Chl/CAR (r2 = 0.88), respectively. PCA confirmed the association of color indices with the respective PP features, which were subsequently estimated using the correlation models. A smartphone-based companion application was developed using the linear models for non-invasive, real-time estimation of Chl content and Chl/CAR ratio. ConclusionThe ratios 1/R and 1/G indicate the contents of Chl and CAR via linear models. The smartphone application developed using the linear models enables real-time estimation of Chl content and Chl/CAR ratio without complicated image preprocessing steps or mathematical derivations.

plant biology↗

bioRxiv2021

Fine-tuning the transcriptional regulatory model of adaptation response to phosphate stress in maize (Zea mays L.)

The post green revolution agriculture is based on generous application of fertilizers and high-yielding genotypes that are suited for such high input regimes. Cereals, like maize (Zea mays L.) are capable of utilizing less than 20% of the applied inorganic phosphate (Pi) - a non-renewable fertilizer resource. A greater understanding of the molecular mechanisms underlying the acquisition, transportation and utilization of Pi may lead to strategies to enhance phosphorus use efficiency (PUE) in field crops. In this study, we selected 12 Pi responsive genes in maize and carried out their comparative transcriptional expression in root and leaf tissues of a hydroponically grown Pi stress tolerant maize inbred line HKI-163, under sufficient and deficient Pi conditions. Pi starvation led to significant increase in root length; marked proliferation of root hairs and lesser number of crown roots. Eleven genes were significantly up or down regulated in Pi deficient condition. The putative acid phosphatase, ZmACP5, expression was up regulated by 162.81 and 74.40 fold in root and leaf tissues, respectively. The RNase, ZmRNS1 showed 115 fold up regulation in roots under Pi deprivation. Among the two putative high affinity Pi transporters ZmPht1;4 was found specific to root, whereas ZmPht2 was found to be up regulated in both root and leaf tissues. The genes involved in Pi homeostasis pathway (ZmSIZ1, SPX1 and Pho2) were up regulated in root and leaf. In light of the expression profiling of selected regulatory genes, an updated model of transcriptional regulation under Pi starvation in maize has been proposed.

plant biology↗

bioRxiv2021

High-resolution structural and functional deep brain imaging using adaptive optics three-photon microscopy

Multi-photon microscopy has become a powerful tool to visualize the morphology and function of neural cells and circuits in the intact mammalian brain. Yet, tissue scattering, optical aberrations, and motion artifacts degrade the achievable image quality with depth. Here we developed a minimally invasive intravital imaging methodology by combining three-photon excitation, indirect adaptive optics correction, and active electrocardiogram gating to achieve near-diffraction limited resolution up to a depth of 1.2mm in the mouse brain. We demonstrate near-diffraction-limited imaging of deep cortical and sub-cortical dendrites and spines as well as of calcium transients in deep-layer astrocytes in vivo.

bioengineering↗

bioRxiv2021

An Intrinsically Disordered Pathological Variant of the Prion Protein Y145Stop Transforms into Self-Templating Amyloids via Liquid-Liquid Phase Separation

Biomolecular condensation via liquid-liquid phase separation of intrinsically disordered proteins/regions (IDPs/IDRs) along with other biomolecules is thought to govern critical cellular functions, whereas, aberrant phase transitions are associated with a range of deadly neurodegenerative diseases. Here we show, a naturally occurring pathological truncation variant of the prion protein (PrP) by a mutation of a tyrosine residue at 145 to a stop codon (Y145Stop) yielding a highly disordered N-terminal IDR that spontaneously phase-separates into liquid-like droplets. Phase separation of this N-terminal segment that is rich in positively charged and aromatic residues is promoted by the electrostatic screening and a multitude of other transient, intermolecular, noncovalent interactions. Single-droplet Raman measurements in conjunction with an array of bioinformatic, spectroscopic, microscopic, and mutagenesis studies revealed that the intrinsic disorder and dynamics are retained in the liquid-like condensates. Lower concentrations of RNA promote the phase transition of Y145Stop at low micromolar protein concentrations under physiological condition. Whereas, higher RNA to protein ratios inhibit condensation indicating the role of RNA in modulating the phase behavior of Y145Stop. Highly dynamic liquid-like droplets eventually transform into dynamically-arrested, ordered, {beta}-rich, amyloid-like aggregates via liquid-to-solid transition upon aging. These amyloid-like aggregates formed via phase separation display the self-templating characteristic and are capable of recruiting and autocatalytically converting monomeric Y145Stop into amyloid fibrils. In contrast to this disease-associated intrinsically disordered Y145 truncated variant, the wild-type full-length PrP exhibited a much lower propensity for phase separation and liquid-to-solid maturation into amyloid-like aggregates hinting at a potentially crucial, chaperone-like, protecting role of the globular C-terminal domain that remains largely conserved in vertebrate evolution. Such an intriguing interplay in the modulation of the protein phase behavior will have much broader implications in cell physiology and disease.

biophysics↗

bioRxiv2020

Analysis and Forecasting of Global of RT-PCR Primers for SARS-CoV-2

Rapid tests for active SARS-CoV-2 infections rely on reverse transcription polymerase chain reaction (RT-PCR). RT-PCR uses reverse transcription of RNA into complementary DNA (cDNA) and amplification of specific DNA (primer and probe) targets using polymerase chain reaction (PCR). The technology makes rapid and specific identification of the virus possible based on sequence homology of nucleic acid sequence and is much faster than tissue culture or animal cell models. However the technique can lose sensitivity over time as the virus evolves and the target sequences diverge from the selective primer sequences. Different primer sequences have been adopted in different geographic regions. As we rely on these existing RT-PCR primers to track and manage the spread of the Coronavirus, it is imperative to understand how SARS-CoV-2 mutations, over time and geographically, diverge from existing primers used today. In this study, we analyze the performance of the SARS-CoV-2 primers in use today by measuring the number of mismatches between primer sequence and genome targets over time and spatially. We find that there is a growing number of mismatches, an increase by 2% per month, as well as a high specificity of virus based on geographic location.

bioinformatics↗

bioRxiv2020

A cross-species drug discovery pipeline to identify and validate new treatments for osteosarcoma

PurposeOsteosarcoma is a rare but aggressive bone cancer that occurs primarily in children. Like other rare cancers, treatment advances for osteosarcoma have stagnated, with little improvement in survival for the past several decades. Developing new treatments has been hampered by extensive genomic heterogeneity and limited access to patient samples to study the biology of this complex disease. Experimental designTo overcome these barriers, we combined the power of comparative oncology with patient-derived models of cancer and high-throughput chemical screens in a cross-species drug discovery pipeline. ResultsCoupling in vitro high-throughput drug screens on low-passage and established cell lines with in vivo validation in patient-derived xenografts we identify the proteasome and CRM1 nuclear export pathways as therapeutic sensitivities in osteosarcoma, with dual inhibition of these pathways inducing synergistic cytotoxicity. ConclusionsThese collective efforts provide an experimental framework and set of new tools for osteosarcoma and other rare cancers to identify and study new therapeutic vulnerabilities.

cancer biology↗

bioRxiv2020

Differential in vitro activity of individual drugs and bedaquiline-rifabutin combinations against actively multiplying and nutrient-starved Mycobacterium abscessus

Current treatment options for lung disease caused by Mycobacterium abscessus complex infections have limited effectiveness. To maximize the use of existing antibacterials and to help inform regimen design for treatment, we assessed the in vitro bactericidal activity of single drugs against actively multiplying and net non-replicating M. abscessus populations in nutrient-rich and nutrient starvation conditions, respectively. As single drugs, bedaquiline and rifabutin exerted bactericidal activity only against nutrient-starved and actively growing M. abscessus, respectively. However, when combined, both bedaquiline and rifabutin were able to specifically contribute bactericidal activity at relatively low, clinically relevant concentrations against both replicating and non-replicating bacterial populations. The addition of a third drug, amikacin, further enhanced the bactericidal activity of the bedaquiline-rifabutin combination against nutrient-starved M. abscessus. Overall, these in vitro data suggest that bedaquiline-rifabutin may be a potent backbone combination to support novel treatment regimens for M. abscessus infections. This rich dataset of differential time-and concentration-dependent activity of drugs, alone and together, against M. abscessus also highlights several issues affecting interpretation and translation of in vitro findings.

microbiology↗

bioRxiv2020

in-silica Analysis of SARS-CoV-2 viral strain using Reverse Vaccinology Approach: A Case Study for USA

The recent pandemic of COVID19 that has struck the world is yet to be battled by a potential cure. Countless lives have been claimed due to the existing pandemic and the societal normalcy has been damaged permanently. As a result, it becomes crucial for academic researchers in the field of bioinformatics to combat the existing pandemic. The study involved collecting the virulent strain sequence of SARS-nCoV19 for the country USA against human host through publically available bioinformatics databases. Using in-silica analysis and reverse vaccinology, two leader proteins were identified to be potential vaccine candidates for development of a multi-epitope drug. The results of this study can provide further researchers better aspects and direction on developing vaccine and immune responses against COVID19. This work also aims at promoting the use of existing bioinformatics tools to faster streamline the pipeline of vaccine development. The Situation of COVID19A new infection respiratory disease was first observed in the month of December 2019, in Wuhan, situated in the Hubei province, China. Studies have indicated that the reason of this disease was the emergence of a genetically-novel coronavirus closely related to SARS-CoV. This coronavirus, now named as nCoV-19, is the reason behind the spread of this fatal respiratory disease, now named as COVID-19. The initial group of infections is supposedly linked with the Huanan seafood market, most likely due to animal contact. Eventually, human-to-human interaction occurred and resulted in the transmission of the virus to humans. [13]. Since then, nCoV-19 has been rapidly spreading within China and other parts of World. At the time of writing this article (mid-March 2020), COVID-19 has spread across 146 countries. A count of 164,837 cases have been confirmed of being diagnosed with COVID-19, and a total of 6470 deaths have occurred. The cumulative cases have been depicting a rising trend and the numbers are just increasing. WHO has declared COVID-19 to be a "global health emergency". [14]. Current Scenario and ObjectivesCurrently, research is being conducted on a massive level to understand the immunology and genetic characteristics of the disease. However, no cure or vaccine of nCoV-19 has been developed at the time of writing this article. Though, nCoV-19 and SARS-CoV are almost genetically similar, the respiratory syndrome caused by both of them, COVID-19 and SARS respectively, are completely different. Studies have indicated that - "SARS was more deadly but much less infectious than COVID-19". -World Health Organization

bioinformatics↗

bioRxiv2020

Integrated genomic view of SARS-CoV-2 in India

India first detected SARS-CoV-2, causal agent of COVID-19 in late January-2020, imported from Wuhan, China. March-2020 onwards; importation of cases from rest of the countries followed by seeding of local transmission triggered further outbreaks in India. We used ARTIC protocol based tiling amplicon sequencing of SARS-CoV-2 (n=104) from different states of India using a combination of MinION and MinIT from Oxford Nanopore Technology to understand introduction and local transmission. The analyses revealed multiple introductions of SARS-CoV-2 from Europe and Asia following local transmission. The most prevalent genomes with patterns of variance (confined in a cluster) remain unclassified, here, proposed as A4-clade based on its divergence within A-cluster. The viral haplotypes may link their persistence to geo-climatic conditions and host response. Despite the effectiveness of non-therapeutic interventions in India, multipronged strategies including molecular surveillance based on real-time viral genomic data is of paramount importance for a timely management of the pandemic.

microbiology↗

bioRxiv2020

Convergent evolution of p38/MAPK activation in hormone resistant prostate cancer mediates pro-survival, immune evasive, and metastatic phenotypes

Adaptation of cancer cells to targeted therapy follows ecological paradigms observed in natural populations that encounter resource depletion and changing environments, including activation of pro-survival mechanisms, migration to new locations, and escape of predation. We identified the p38 MAPK pathway as a common molecular driver of these three responses during the adaptation to hormone therapy resistance in prostate cancer. The p38 pathway is activated in therapy-resistant cells and mechanistically drives these three convergent responses through sustained AR activity, enhanced invasion and metastasis, and immune evasion. Targeting p38 signaling may represent a new therapeutic strategy to treat men with metastatic, hormone therapy-resistant prostate cancer.

cancer biology↗

bioRxiv2020

Integrative and Conjugative Elements (ICE) and Associated Cargo Genes within and across Hundreds of Bacterial Genera

Horizontal gene transfer mediated by integrative and conjugative elements (ICE) is considered an important evolutionary mechanism of bacteria. It allows organisms to quickly evolve new phenotypic properties including antimicrobial resistance (AMR) and virulence. The rate of ICE-mediated cargo gene exchange has not yet been comprehensively studied within and between bacterial taxa. In this paper we report a big data analysis of ICE and associated cargo genes across over 200,000 bacterial genomes representing 1,345 genera. Our results reveal that half of bacterial genomes contain one or more known ICE features ("ICE genomes"), and that the associated genetic cargo may play an important role in the spread of AMR genes within and between bacterial genera. We identify 43 AMR genes that appear only in ICE genomes and never in non-ICE genomes. A further set of 95 AMR genes are found >5x more often in ICE versus non-ICE genomes. In contrast, only 29 AMR genes are observed more frequently (at least 5:1) in non-ICE genomes compared to ICE genomes. Analysis of NCBI antibiotic susceptibility assay data reveals that ICE genomes are also over-represented amongst phenotypically resistant isolates, suggesting that ICE processes are critical for both genotypic and phenotypic AMR. These results, as well as the underlying big data resource, are important foundational tools for understanding bacterial evolution, particularly in relation to important bacterial phenotypes such as AMR.

microbiology↗

bioRxiv2020

A repository of web-based bioinformatics resources developed in India

IndiaBioDb (https://webs.iiitd.edu.in/raghava/indiabiodb/) is a manually curated comprehensive repository of bioinformatics resources developed and maintained by Indian researchers. This repository maintains information about 543 freely accessible functional resources that include around 258 biological databases. Each entry provides a complete detail about a resource that includes the name of resources, web link, detail of publication, information about the corresponding author, name of institute, type of resource. A user-friendly searching module has been integrated, which allows users to search our repository on any field. In order to retrieve categorized information, we integrate the browsing facility in this repository. This database can be utilized for extracting the useful information regarding the present scenario of bioinformatics inclusive of all research labs funded by government and private bodies of India. In addition to web interface, we also developed mobile to facilitate the scientific community.

bioinformatics↗

bioRxiv2019

Survey of Public Assay Data: Opportunities and Challenges to Understanding Antimicrobial Resistance

ABSTRACTComputational learning methods allow researchers to make predictions, draw inferences, and automate generation of mathematical models. These models are crucial to solving real world problems, such as antimicrobial resistance, pathogen detection, and protein evolution. Machine learning methods depend upon ground truth data to achieve specificity and sensitivity. Since the data is limited in this case, as we will show during the course of this paper, and as the size of available data increases super-linearly, it is of paramount importance to understand the distribution of ground truth data and the analyses it is suited and where it may have limitations that bias downstream learning methods. In this paper, we focus on training data required to model antimicrobial resistance (AR). We report an analysis of bacterial biochemical assay data associated with whole genome sequencing (WGS) from the National Center for Biotechnology Information (NCBI), and discuss important implications when making use of assay data, utilizing genetic features as training data for machine learning models. Complete discussion of machine learning model implementation is outside the scope of this paper and the subject to a later publication. The antimicrobial assay data was obtained from NCBI BioSample, which contains descriptive information about the physical biological specimen from which experimental data is obtained and the results of those experiments themselves.[1] Assay data includes minimum inhibitory concentrations (MIC) of antibiotics, links to associated microbial WGS data, and treatment of a particular microorganism with antibiotics. We observe that there is minimal microbial data available for many antibiotics and for targeted taxonomic groups. The antibiotics with the highest number of assays have less than 1500 measurements each. Corresponding bias in available assays makes machine learning problematic for some important microbes and for building more advanced models that can work across microbial genera. In this study we focus, therefore, on the antibiotic with most assay data (tetracycline) and the corresponding genus with the most available sequence (Acinetobacter with 14000 measurements across 49 antibiotic compounds). Using this data for training and testing, we observed contradictions in the distribution of assay outcomes and report methods to identify and resolve such conflicts. Per antibiotic, we find that there can be up to 30% of (resolvable) conflicting measurements. As more data becomes available, automated training data curation will be an important part of creating useful machine learning models to predict antibiotic resistance. CCS CONCEPTS* Applied computing [->] Computational biology; Computational genomics; Bioinformatics;

bioinformatics↗

bioRxiv2019

Human pseudoislet system enables detection of differences in G-protein-coupled-receptor signaling pathways between α and β cells

G-protein-coupled-receptors (GPCRs) modulate insulin secretion from {beta} cells and glucagon secretion from cells. Here, we developed an integrated approach to study the function of primary human islet cells using genetically modified pseudoislets that resemble native islets across multiple parameters. We studied the Gi and Gq GPCR pathways by expressing the designer receptors exclusively activated by designer drugs (DREADDs) hM4Di or hM3Dq. Activation of Gi signaling reduced insulin and glucagon secretion, while activation of Gq signaling stimulated glucagon secretion but had both stimulatory and inhibitory effects on insulin secretion. Further, we developed a microperifusion system that allowed synchronous acquisition of GCaMP6f biosensor signal and hormone secretory profiles and showed that the dual effects for Gq signaling occur through changes in intracellular Ca2+. By combining pseudoislets with a microfluidic system, we co-registered intracellular signaling dynamics and hormone secretion and demonstrated differences in GPCR signaling pathways between human {beta} and cells.

cell biology↗

bioRxiv2019

Astrocyte redox dysregulation causes prefrontal hypoactivity: sulforaphane treats non-ictal pathophysiology in ALDH7A1-mediated epilepsy

A fundamental but unanswered question in neuropsychiatry is whether the psychiatric symptoms of epilepsy are caused by the same or a separate pathophysiology as seizures. To address this question, we investigated a monogenic form of epilepsy (pyridoxine-dependent epilepsy) caused by aldehyde dehydrogenase 7a1 (ALDH7A1) mutations. ALDH7A1 global knockout mice exhibited both seizure-associated and affective behavioral phenotypes. However, seizure phenotypes were caused by ALDH7A1 deletion in hepatocytes whereas affective behaviors were caused by ALDH7A1 deletion in astrocytes. Deletion in astrocytes disrupted astrocyte redox homeostasis, impairing regulation of extracellular ion concentrations and reducing neuronal activity in the prelimbic cortex. Sulforaphane, which activates the NRF2 antioxidant pathway, restored prelimbic neuronal activity and rescued affective behaviors in ALDH7A1 knockout mice, but did not prevent seizures. These studies implicate astrocyte redox homeostasis and prelimbic hypoactivity in the psychiatric manifestations of a congenital form of epilepsy, which are mechanistically and therapeutically separate from the seizure pathophysiology. TeaserAntioxidant imbalance in astrocytes reduces neuronal activity, causing psychiatric symptoms in epilepsy distinct from seizures.

neuroscience↗

bioRxiv2019

CD146+CD107a+ Mesenchymal Stem/Stromal Cells with Signature Attributes Correlate to Therapeutic Potency as \"First Responders\" to Injury and Inflammation

CD146+ bone marrow-derived Mesenchymal Stem/Stromal Cells (BM-MSC) play key roles in the perivascular niche, skeletogenesis and hematopoietic support, however elucidation of therapeutic potency has yet to be determined. Here, inflammatory challenge to crude BM-MSC captured a baseline of signatures including enriched expression of CD146+ with CD107a+, CXCR4+, and LepR+, transcriptional profile, enhanced secretory capacity, robust secretome and immunomodulatory function with stimulated target immune cells. These responses were significantly more pronounced in CD146+ (POS)-selected subpopulation than in the CD146- (NEG). Mechanistically, POS uniquely mediated robust immunosuppression while inducing significant frequencies of Naive and Regulatory T cells in vitro. Moreover, POS promoted a pivotal M1-to-M2 macrophage shift in vivo, ameliorating inflammation/fibrosis of joint synovium and fat pad of the knee, failed by NEG. This study provides high-content evidence of CD146+CD107a+ BM-MSC, herein deemed first responders to inflammation, as the underrepresented subpopulation within crude BM-MSC with innately higher secretory capacity and therapeutic potency.\n\nHIGHLIGHTSO_LISignature phenotypic, transcriptional, and secretome profiles were identified and enriched in human CD146+ (POS)-selected subpopulation in response to inflammation\nC_LIO_LIInflammatory challenge consistently altered stemness (LIF) and differentiation master regulators (SOX9, RUNX2, PPAR{gamma}) in crude, POS, and NEG BM-MSC, and deduced unique expressions in POS compared to NEG\nC_LIO_LIPOS BM-MSC mediated the strongest immunomodulation, e.g. target immune cell suppression, Treg induction, diminished T cell differentiation\nC_LIO_LIPOS BM-MSC promoted the largest M1-to-M2 shift in vivo alleviating induced synovitis and infrapatellar fat pad fibrosis of the knee\nC_LI

cell biology↗

bioRxiv2019

Inhibition of neutral sphingomyelinase-2 facilitates remyelination

For reasons that are not completely understood, remyelination is often incomplete, producing thin myelin sheaths with disorganized structure. We investigated the cellular basis for this altered myelin structure, and found that the response of oligodendrocyte progenitor cells (OPCs), and mature oligodendrocytes to TNF and IL-1{beta} is modified by the expression of the sphingomyelin hydrolase nSMase2. OPCs do not express nSMase2, and exhibit a protective response to these cytokines manifest by decreased ceramide, increased sphingosine 1-phosphate, and increased cell motility. Mature oligodendrocytes express nSMase2, and respond to TNF and IL-1{beta} with a stress phenotype, evidenced by increased ceramide, decreased sphingosine, and active caspase 3. Pharmacological inhibition or a targeted genetic deletion of nSMase2 in vivo increased myelin thickness, and enhanced myelin compaction. These results suggest that inhibition of nSMase2 improves the quality of new myelin by protecting maturing/myelinating oligodendrocytes. Pharmacological inhibition of nSMase2 following a demyelinating event could stabilize the structure of these newly formed myelin sheaths and protect them from secondary demyelination.

molecular biology↗

bioRxiv2019

Noninvasive sleep monitoring in large-scale screening of knock-out mice reveals novel sleep-related genes

Sleep is a critical process that is well-conserved across mammalian species, and perhaps most animals, yet its functions and underlying mechanisms remain poorly understood. Identification of genes and pathways that can influence sleep may shed new light on these functions. Genomic screens enable the detection of previously unsuspected molecular processes that influence sleep. In this study, we report results from a large-scale phenotyping study of sleep-wake parameters for a population of single-gene knockout mice. Sleep-wake parameters were measured using a high throughput, non-invasive piezoelectric system called PiezoSleep. Knockout mice generated on a C57BL6/N (B6N) background were monitored for sleep and wake parameters for five days. By analyzing data from over 6000 mice representing 343 single gene knockout lines, we identified 122 genes influencing traits like sleep duration and bout length that have not been previously implicated in sleep, including those that affect sleep only during a specific circadian phase. PiezoSleep also allows assessment of breath rates during sleep and this was integrated as a supplemental tool in identifying aberrant physiology in these knockout lines. Sex differences were evident in both normal and altered sleep behavior. Through a combination of genetic and phenotypic associations, and known QTLs for sleep, we propose a set of candidate genes playing specific roles in sleep. The high \"hit rate\" demonstrates that many genes can alter normal sleep behaviors through a variety of mechanisms. Further investigation of these genes may provide insight into the pathways regulating sleep, functional aspects of sleep, or indirect potentially pathological processes that alter normal sleep.

neuroscience↗