Biology subjects

Agarwal, A.

Publications and source records attributed to Agarwal, A..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Two-fold Red Excess (TREx): A simple and novel digital color index that enables non-invasive real-time health assessment of green-leaved as well as anthocyanin-rich crops

BackgroundDigital color indices provide a reliable means for assessing plant health status by enabling real-time estimation of chlorophyll (Chl) content, and are thus adopted widely for crop monitoring. However, as all prevalent leaf color indices used for this purpose have been developed using green-leaved plants, they do not perform reliably for anthocyanin (Anth)-rich red-leaved varieties. Hence, the present study investigates digital color indices for six types of leafy vegetables with different levels of Anth to identify congruent trends that could be implemented universally for non-invasive crop monitoring irrespective of species and leaf Anth content. For this, datasets from three digital color spaces, viz., RGB (Red, Green, Blue), HSV (Hue, Saturation, Value), and L*a*b* (Lightness, Redness-greenness, Yellowness-blueness), as well as various derived plant color indices were compared with SPAD Chl meter readings and Anth/Chl ratio of n = 320 leaf samples. ResultsWhile most digital color features and indices presented abrupt shifts between Anth-rich and green-leaved samples, the newly-developed color index Two-fold Red Excess (TREx) as well as the color feature R showed very strong correlation with SPAD readings (R2 > 0.84), and did not exhibit any deviation due to leaf Anth content. Moreover, both parameters could predict SPAD values reliably (R2 > 0.75). Further, logarithmic decline of G/R and Augmented Green-Red Index (AGRI) with increasing Anth/Chl ratio (R2 > 0.82) revealed that relative Anth content affected digital color indices markedly by shifting the R:G balance until the Anth/Chl ratio reached a certain threshold. ConclusionThe present study provides the first in-depth assessment of variations in RGB-based digital color indices due to high leaf Anth contents, and uses the data for Anth-rich as well as green-leaved crops belonging to different species to develop a universal digital color index TREx that can be used as a reliable alternative to handheld Chl meters for rapid high-throughput monitoring of green-leaved as well as red-leaved crop varieties.

plant biology↗

bioRxiv2024

Unveiling epigenetic regulatory elements associated with breast cancer development

Breast cancer is the most common cancer in women and the 2nd most common cancer worldwide, yearly impacting over 2 million females and causing 650 thousand deaths. It has been widely studied, but its epigenetic variation is not entirely unveiled. We aimed to identify epigenetic mechanisms impacting the expression of breast cancer related genes to detect new potential biomarkers and therapeutic targets. We considered The Cancer Genome Atlas database with over 800 samples and several omics datasets such as mRNA, miRNA, DNA methylation, which we used to select 2701 features that were statistically significant to differ between cancer and control samples using the Monte Carlo Feature Selection and Interdependency Discovery algorithm, from an initial total of 417,486. Their biological impact on cancerogenesis was confirmed using: statistical analysis, natural language processing, linear and machine learning models as well as: transcription factors identification, drugs and 3D chromatin structure analyses. Classification of cancer vs control samples on the selected features returned high classification weighted Accuracy from 0.91 to 0.98 depending on feature-type: mRNA, miRNA, DNA methylation, and classification algorithm. In general, cancer samples showed lower expression of differentially expressed genes and increased {beta}-values of differentially methylated sites. We identified mRNAs whose expression is well explained by miRNA expression and differentially methylated sites {beta}-values. We recognized differentially methylated sites possibly affecting NRF1 and MXI1 transcription factors binding, causing a disturbance in NKAPL and PITX1 expression, respectively. Our 3D models showed more loosely packed chromatin in cancer. This study successfully points out numerous possible regulatory dependencies.

cancer biology↗

bioRxiv2024

Hypoxia promotes airway differentiation in the human lung epithelium

Human early embryos develop under physiological hypoxia, but how hypoxia regulates human organogenesis remains little known. We have investigated oxygen availability effects on the human lung epithelium using organoids. We find first-trimester lung epithelial progenitors remain undifferentiated under normoxia, but spontaneously differentiate towards multiple airway cell types and inhibit alveolar differentiation under hypoxia. Using chemical and genetic tools, we demonstrate that hypoxia-induced airway differentiation is dependent on HIF (Hypoxia-Inducible Factor) pathways, with HIF1 and HIF2 differentially regulating fate decisions. Transcription factors KLF4 and KLF5 are direct targets of the HIF pathway and promote progenitor differentiation to basal and secretory cells. Chronic hypoxia also induces transdifferentiation of human alveolar type 2 cells to airway cells via the HIF pathway, mimicking alveolar bronchiolization processes in lung disease. Our results reveal roles for hypoxia and HIF signalling during human lung development and have implications for aberrant cell fate decisions in chronic lung diseases.

developmental biology↗

bioRxiv2024

Infrared thermography for plant stress detection in vertical farms: Investigating spatiotemporal variations and exploring solutions via machine learning

Application of infrared thermography (IRT) for real-time plant stress detection has grown rapidly in recent years. Although the technology has been well established for crops grown in fields and glasshouses, its feasibility for vertical farms has not been tested extensively. In this study, temporal monitoring of stress induced by root dehydration in purple basil plantlets inside a vertical farm was performed to identify bottlenecks in real-time stress detection via IRT. Subsequently, potential solutions were investigated via machine learning by implementing support vector machines for supervised classification. Edge effects as well as proximity to air vents were identified as the major causes of positional variation in plant temperature that could lead to misprediction of stress. Binary, ternary, and quaternary classification models were trained using thermal images from two, three, and four levels of stress, respectively, to assess model performance. Binary classification models trained with plants experiencing medial and high levels of stress were able to identify stressed plants with high accuracy (81-94%). Further, binary models trained using plants under medial levels of stress generated a continuous probability distribution for stress prediction when plotted against plant temperature. In contrast, models trained using samples experiencing high stress generated distinct probabilistic clusters for the unstressed and highly stressed plants, but were unable to classify medial stress samples reliably. Similarly, ternary and quaternary models were able to better predict very high and very low levels of stress than intermediate stress levels. Hence, our findings suggest that binary classification models trained using samples under medial levels of stress would be helpful in overcoming spatiotemporal variations in canopy thermal profile by providing reliable probabilistic estimates of plant stress within a vertical farming system. Key pointsO_LIPlant stress detection in vertical farms via thermal imaging may be challenging because perceptible plant temperature can be strongly influenced by its microenvironment. C_LIO_LIThermal image analysis via supervised machine learning allows the development of robust prediction models that can overcome such factors to identify stressed plants. C_LIO_LIBinary classification machine learning models can reliably identify stressed plants as well as provide probabilistic estimates for the degree of stress. C_LI

plant biology↗

bioRxiv2024

Assessing nutritional pigment content and plant health status of green and red leafy vegetables by image analysis: Catching the 'red herring' of plant digital color processing

Estimating pigment content in leafy vegetables via digital image analysis is a reliable method for real-time assessment of plant health status and nutritive value. However, the present leaf color analysis models developed using green-leafed plants do not perform reliably while analyzing images of anthocyanin-rich leaves, often giving misleading or "red herring" trends. Hence, the present study investigates variations in different digital color features for six types of leafy vegetables with varying levels of laminar anthocyanin to identify holistic digital color analysis models that could be implemented for real-time assessment of health status as well as nutritional pigment contents of leafy vegetables irrespective of laminar anthocyanin status. For this, datasets from three digital color spaces, viz., RGB (red, green, blue), HSI (hue, saturation, intensity), and L*a*b* (lightness, redness-greenness, yellowness-blueness), were compared with pigment contents of n = 320 leaf samples, and were analyzed via linear and non-linear regression using single variables, multiple linear regression, Support Vector regression, and Random Forest regression to predict chlorophyll and anthocyanin contents. While most digital color features presented abrupt shifts between anthocyanin-rich and low-anthocyanin samples, the R digital color feature did not show any deviation due to leaf anthocyanin content and was found to have the best correlation with SPAD chlorophyll meter readings (R2 = 0.83). Concomitantly, H (R2 = 0.82) and a* (R2 = 0.79) features correlated most strongly with leaf anthocyanin content. In general, prediction of pigment contents was more accurate when data from all channels within a color space was analyzed simultaneously. Further, most reliable estimates of pigment content were provided by Support Vector and Random Forest regression models (0.7 < R2 < 0.85). Thus, the present findings demonstrate how digital color analysis of green as well as anthocyanin-rich leafy vegetables could be implemented for assessing plant health status and nutritional pigment content non-invasively.

plant biology↗

bioRxiv2024

Improved cohesin HiChIP protocol and bioinformatic analysis for robust detection of chromatin loops and stripes

Chromosome Conformation Capture (3C) methods, including Hi-C (a high-throughput variation of 3C), detect pairwise interactions between DNA regions, enabling the reconstruction of chromatin architecture in the nucleus. HiChIP is a modification of the Hi-C experiment, which includes a chromatin immunoprecipitation step (ChIP), allowing genome-wide identification of chromatin contacts mediated by a protein of interest. In mammalian cells, cohesin protein complex is one of the major players in the establishment of chromatin loops. We present an improved cohesin HiChIP experimental protocol. Using comprehensive bioinformatic analysis, we show that performing cohesin HiChIP with two cross-linking agents (formaldehyde [FA] and EGS) instead of the typically used FA alone, results in a substantially better signal-to-noise ratio, higher ChIP efficiency and improved detection of chromatin loops and architectural stripes. Additionally, we propose an automated pipeline called nf-HiChIP (https://github.com/SFGLab/hichip-nf-pipeline) for processing HiChIP samples starting from raw sequencing reads data and ending with a set of significant chromatin interactions (loops), which allows efficient and timely analysis of multiple samples in parallel, without the need of additional ChIP-seq experiments. Finally, using novel approaches for biophysical modelling and stripe calling we generate accurate loop extrusion polymer models for a region of interest and a detailed picture of architectural stripes, respectively.

genomics↗

bioRxiv2024

Commensal or pathogen: computational vectorizing microbial genomes for de novo risk assessment and virulence feature discovery in Klebsiella pneumoniae

Bacterial pathogenicity has traditionally focused on gene-level content with experimentally-confirmed functional properties. Hence, significant inferences are made based on similarity to known pathotypes and DNA-based genomic subtyping for risk. Herein, we achieved de novo prediction of human virulence in Klebsiella pneumoniae by expanding known virulence genes with spatially proximal gene discoveries linked by functional domain architectures across all prokaryotes. This approach identified gene ontology functions not typically associated with virulence sensu stricto. By leveraging machine learning models with these expanded discoveries, public genomes were assessed for virulence prediction using categorizations derived from isolation sources captured in available metadata. Performance for de novo strain-level virulence prediction achieved 0.81 F1-Score. Virulence predictions using expanded "discovered" functional genetic content were superior to that restricted to extant virulence database content. Additionally, this approach highlighted the incongruence in relying on traditional phylogenetic subtyping for categorical inferences. Our approach represents an improved deconstruction of genome-scale datasets for functional predictions and risk assessment intended to advance public health surveillance of emerging pathogens.

microbiology↗

bioRxiv2023

Leukemic mutation FLT3-ITD is retained in dendritic cells and disrupts their homeostasis leading to expanded Th17 frequency

Dendritic cells (DC) are mediators of adaptive immune responses to pathogens and tumors. DC development is determined by signaling through the receptor tyrosine kinase Fms-like tyrosine kinase 3 (FLT3) in bone marrow myeloid progenitors. Recently the naming conventions for DC phenotypes have been updated to distinguish between "Conventional" DCs (cDCs) and plasmacytoid DCs (pDCs). Activating mutations of FLT3, including Internal Tandem Duplication (FLT3-ITD), are associated with poor prognosis for leukemia patients. To date, there is little information on the effects of FLT3-ITD in DC biology. We examined the cDC phenotype and frequency in bone marrow aspirates from patients with acute myeloid leukemia (AML) to understand the changes to cDCs associated with FLT3-ITD. When compared to healthy donor (HD) we found that a subset of FLT3-ITD+ AML patient samples have overrepresented populations of cDCs and disrupted phenotypes. Using a mouse model of FLT3-ITD+ AML, we found that cDCs were increased in percentage and number compared to control wild-type (WT) mice. Single cell RNA-seq identified FLT3-ITD+ cDCs as skewed towards a cDC2 T-bet-phenotype, previously shown to promote Th17 T cells. We assessed the phenotypes of CD4+ T cells in the AML mice and found significant enrichment of both Treg and Th17 CD4+ T cells. Furthermore, co-culture of AML mouse- derived DCs and naive OT-II cells preferentially skewed T cells into a Th17 phenotype. Together, our data suggests that FLT3-ITD+ leukemia-associated cDCs polarize CD4+ T cells into Th17 subsets, a population that has been shown to be negatively associated with survival in solid tumor contexts. This illustrates the complex tumor microenvironment of AML and highlights the need for further investigation into the effects of FLT3-ITD mutations on DC phenotypes.

immunology↗

bioRxiv2023

Calcium-permeable AMPA receptors govern PV neuron feature selectivity

The brain helps us survive by forming internal representations of the external world1,2. Excitatory cortical neurons are often precisely tuned to specific external stimuli3,4. However, inhibitory neurons, such as parvalbumin-positive (PV) interneurons, are generally less selective5. PV interneurons differ from excitatory cells in their neurotransmitter receptor subtypes, including AMPA receptors6,7. While excitatory neurons express calcium-impermeable AMPA receptors containing the GluA2 subunit, PV interneurons express receptors that lack the GluA2 subunit and are calcium-permeable (CP-AMPARs). Here we demonstrate a causal relationship between CP-AMPAR expression and the low feature selectivity of PV interneurons. We find a low expression stoichiometry of GluA2 mRNA relative to other subunits in PV interneurons which is conserved across ferrets, rodents, marmosets, and humans, causing abundant CP-AMPAR expression. Replacing CP-AMPARs in PV interneurons with calcium-impermeable AMPARs increased their orientation selectivity in the visual cortex. Sparse CP-AMPAR manipulations demonstrated that this increase was cell-autonomous and could occur well beyond development. Interestingly, excitatory-PV interneuron connectivity rates and unitary synaptic strength were unaltered by CP-AMPAR removal, suggesting that the selectivity of PV interneurons can be altered without drastically changing connectivity. In GluA2 knockout mice, where all AMPARs are calcium-permeable, excitatory neurons showed significantly reduced orientation selectivity, suggesting that CP-AMPARs are sufficient to drive lower selectivity regardless of cell type. Remarkably, hippocampal PV interneurons, which usually exhibit low spatial tuning, became more spatially selective after removing CP-AMPARs, indicating that CP-AMPARs suppress the feature selectivity of PV interneurons independent of modality. These results reveal a novel role of CP-AMPARs in maintaining a low-selectivity sensory representation in PV interneurons and suggest a conserved molecular mechanism that distinguishes the unique synaptic computations of inhibitory and excitatory neurons.

neuroscience↗

bioRxiv2023

VAMP2 regulates phase separation of alpha-synuclein

SummaryAlpha-synuclein (aSYN) is a small synaptic protein that is linked to Parkinsons disease (PD) and other synucleinopathies. aSYN has been shown to undergo protein phase separation. We found that aSYN phase separation, in vitro and in cells, is regulated by vesicle-associated membrane protein 2 (VAMP2), the vesicular SNARE protein. We show that aSYN phase separation is promoted by C-terminal electrostatic interaction, which in cells is mediated via interaction with VAMP2. The condensate formation is specific for the R-SNARE VAMP2 and critically dependent on aSYNs capacity to bind to lipid membranes. In vitro, the addition of VAMP2 decreases the saturation concentration of aSYN phase separation, which is mediated by its juxtamembrane domain. Our results delineate a molecular mechanism for the regulation of aSYN phase separation, indicating a potential switch from the dispersed to the phase-separated state during vesicle cycling. HighlightsO_LIAlpha-synuclein phase separation is regulated by electrostatic interactions C_LIO_LIVAMP2 initiates alpha-synuclein condensation in cells C_LIO_LIPositive charges within the juxtamembrane domain of VAMP2 initiate alpha-synuclein phase separation in vitro C_LIO_LIAlpha-synuclein condensates nucleate on lipid membranes and assemble vesicular structures in cells C_LI

cell biology↗

bioRxiv2023

Conservation of chromatin organization within human and primate centromeres

The focal attachment of the kinetochore to the centromere is essential for genome maintenance, yet the highly repetitive nature of satellite regional centromeres, such as those in humans, limits our understanding of their chromatin organization. We demonstrate that single-molecule chromatin fiber sequencing (Fiber-seq) can uniquely co-resolve kinetochore and surrounding chromatin architectures along point centromeres, revealing largely homogeneous single-molecule kinetochore occupancy along each chromosome. In contrast, extension of Fiber-seq to regional satellite centromeres exposed marked per-molecule heterogeneity in their chromatin organization. Regional CENP-A-marked centromere cores uniquely contain a dichotomous chromatin organization (dichromatin) composed of compacted nucleosome arrays punctuated with highly accessible chromatin patches. CENP-B occupancy phases dichromatin to the underlying alpha-satellite repeat within centromere cores, but is not necessary for dichromatin formation. Centromere core dichromatin is a conserved feature between humans despite the marked divergence of their underlying alpha-satellite organization and is similarly a conserved feature along regional centromeres that lack satellite repeats in gibbon. Overall, the chromatin organization of regional centromeres is defined by marked per-molecule heterogeneity, likely buffering kinetochore attachment against sequence and structural variability within regional centromeres. HighlightsO_LIDichotomous accessible and compacted chromatin (dichromatin) marks centromere cores C_LIO_LIHighly accessible chromatin patches punctuate sites of kinetochore attachment C_LIO_LIDichromatin can form irrespective of CENP-B occupancy C_LIO_LIConservation within centromeres is mediated at the level of chromatin, not DNA C_LI

genomics↗

bioRxiv2023

Inhibition of miR-214 expression by small molecules alleviates head and neck cancer metastasis by targeting ALCAM/TFAP2 signaling.

Predominantly, head and neck cancer (HNC) is considered a regional disease and develops in the nasal cavity, oral cavity, tongue, pharynx, and larynx. In the advanced stage, the HNC spread into distant organs. By the time head and neck cancer diagnosed, the estimated metastasis is occurred in 10-40% cases. The most important vital organs affected by distant metastasis are the lungs, bones, and liver. Despite several advancements in chemotherapies, no significant changes are observed as 5-year survival rate remains the same. Therefore, it is crucial to decipher molecular mechanisms contributing to the metastatic dissemination of head and neck cancer. Here, we tested a novel ALCAM/TFAP2 signaling by targeting multidisciplinary miR-214 expression in head and cancer cells. Our results revealed that HNC cell lines (CAL27, SCC-9, SCC-4, and SCC-25) exhibit higher expression of miR-214 compared with normal human bronchial epithelial (NHBE) cells. Higher expression of miR-214 drives the invasive potential of these cell lines. Down-regulation of miR-214 in CAL27 and SCC-9 cells either using an anti-miR-214 inhibitor (50nM) or a small molecule of green tea (EGCG) inhibited cell invasion. Treating CAL27 and SCC-9 cells with EGCG also reduces ALCAM expression, a key activated leukocyte cell adhesion molecule, potentially blocking mesenchymal phenotype. Dietary administration of EGCG significantly inhibits distant metastasis of SCC-9 cells into the lungs, liver, and kidneys. Our results also demonstrate that the reduction of miR-214 expression influences in vitro cell movement and extravasation, as evident by reduced CD31 expression, a neovascularization marker. Together, these studies suggest that identifying bioactive molecules that can inhibit distant metastasis regulated by the miRNAs may provide potent interventional approaches and a better understanding of the complex functions of miRNAs and their therapeutic targets for clinical application.

cancer biology↗

bioRxiv2023

Enhanced performance of gene expression predictive models with protein-mediated spatial chromatin interactions

There have been multiple attempts to predict the expression of the genes based on the sequence, epigenetics, and various other factors. To improve those predictions, we have decided to investigate adding protein-specific 3D interactions that play a major role in the compensation of the chromatin structure in the cell nucleus. To achieve this, we have used the architecture of one of the state-of-the-art algorithms, ExPecto (J. Zhou et al., 2018), and investigated the changes in the model metrics upon adding the spatially relevant data. We have used ChIA-PET interactions that are mediated by cohesin (24 cell lines), CTCF (4 cell lines), and RNAPOL2 (4 cell lines). As the output of the study, we have developed the Spatial Gene Expression (SpEx) algorithm that shows statistically significant improvements in most cell lines.

genomics↗

bioRxiv2023

pyCapsid: Identifying dominant dynamics and quasi-rigid mechanical units in protein shells

Structured AbstractO_ST_ABSSummaryC_ST_ABSpyCapsid is a Python package developed to facilitate the characterization of the dynamics and mechanical units of protein shells and other protein complexes. The package was developed in response to the rapid increase of high-resolution structures, particularly capsids of viruses, requiring multiscale biophysical analyses. Given a protein shell, pyCapsid generates the collective vibrations of its amino-acid residues, identifies quasi-rigid mechanical regions, and maps the results back to the input proteins for interpretation. pyCapsid summarizes the main results in a report that includes publication-quality figures. Availability and ImplementationpyCapsids source code is available under MIT License on GitHub (https://github.com/luquelab/pycapsid). It is compatible with Python 3.8-3.10 and has been deployed in two leading Python package-management systems, PIP (https://pypi.org/project/pyCapsid/) and Conda (https://anaconda.org/luque_lab/pycapsid). Installation instructions and tutorials are available in the GitHub Page-style online documentation (https://luquelab.github.io/pyCapsid). Additionally, a cloud-based implementation of pyCapsid is available as a Google Colab notebook (https://colab.research.google.com/github/luquelab/pyCapsid/blob/main/notebooks/pyCapsid_colab_notebook.ipynb). pyCapsid Colab does not require installation and generates the same report and outputs as the installable version. Users can post issues regarding pyCapsid in the GitHub repository (https://github.com/luquelab/pyCapsid/issues).

bioinformatics↗

bioRxiv2023

Differentially deregulated microRNAs contribute to ultraviolet radiation-induced photocarcinogenesis through immunomodulation: An-analysis of microRNAs expression profiling.

MicroRNAs (miRNAs) are short non-coding RNA molecules (18-25 nucleotides) that regulate several fundamental biological processes. Emerging evidence has shown more than 1500 miRNAs functions in the cell cycle, proliferation, apoptosis, oxidative stress, immune response, DNA damage, and epigenetics alterations. miRNAs are bidirectionally in nature and act as a tumor suppressor and as an oncogene through crosstalk between tumor cells and immune cells. Although the roles of miRNAs in several cancers are well studied, little is known about ultraviolet B (UVB) radiation-induced skin cancer. Here, we performed a comprehensive screening of 1281 miRNAs in tumor tissues and compared their expression with normal skin. Our results demonstrate that the expression levels of 587 miRNAs were altered in tumor tissues compared to their expression in normal skin. The expression of 337 miRNAs was upregulated from 1.5-12 folds, while the expression of 250 miRNAs was downregulated up to 1.5-10 folds in tumors. Further, intraperitoneal injection of a mimic of down-regulated miR-15b (30nM) and an inhibitor of upregulated miR-133a (20nM) protect UVB-induced suppression of contact hypersensitivity (CHS) response. In conclusion, we identified a network of altered miRNAs in tumors that can serve as prognostic biomarkers and therapeutic targets to manage photocarcinogenesis effectively.

cancer biology↗

bioRxiv2023

Catenin signaling controls phrenic motor neuron development and function during a narrow temporal window

Phrenic Motor Column (PMC) neurons are a specialized subset of motor neurons (MNs) that provide the only motor innervation to the diaphragm muscle and are therefore essential for survival. Despite their critical role, the mechanisms that control phrenic MN development and function are not well understood. Here, we show that catenin-mediated cadherin adhesive function is required for multiple aspects of phrenic MN development. Deletion of {beta}- and{gamma} -catenin from MN progenitors results in perinatal lethality and a severe reduction in phrenic MN bursting activity. In the absence of catenin signaling, phrenic MN topography is eroded, MN clustering is lost and phrenic axons and dendrites fail to grow appropriately. Despite the essential requirement for catenins in early phrenic MN development, they appear to be dispensable for phrenic MN maintenance, as catenin deletion from postmitotic MNs does not impact phrenic MN topography or function. Our data reveal a fundamental role for catenins in PMC development and suggest that distinct mechanisms are likely to control PMC maintenance.

neuroscience↗

bioRxiv2022

Activation of β2-adrenergic receptors in microglia alleviates neuropathic hypersensitivity in mice

Drugs enhancing the availability of noradrenaline are gaining prominence in the therapy of chronic neuropathic pain. However, underlying mechanisms are not well understood, and research has thus far focused on 2-adrenergic receptors and neuronal excitability. Adrenergic receptors are also expressed on glial cells, but their roles toward antinociception are not well deciphered. This study addresses the contribution of {beta}2-adrenergic receptors ({beta}2-ARs) to the therapeutic modulation of neuropathic pain in mice. We report that selective activation of {beta}2-ARs with Formoterol inhibits pro-inflammatory signaling in microglia ex-vivo and nerve injury-induced structural remodeling and functional activation of microglia in vivo. Systemic delivery of Formoterol inhibits behaviors related to neuropathic pain, such as mechanical hypersensitivity, cold allodynia and the aversive component of pain, and reverses chronically established neuropathic pain. Using conditional gene targeting for microglia-specific deletion of {beta}2-ARs, we demonstrate that the anti-allodynic effects of Formoterol are primarily mediated by microglia. Although Formoterol also reduces astrogliosis at late stages of neuropathic pain, these functions are unrelated to {beta}2-AR signaling in microglia. Our results underline the value of developing microglial {beta}2-AR agonists for relief from neuropathic pain and clarify mechanistic underpinnings. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/520924v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@166c767org.highwire.dtl.DTLVardef@ad3be9org.highwire.dtl.DTLVardef@1383f5eorg.highwire.dtl.DTLVardef@1c852b1_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

BCLncRDB: A comprehensive database of LncRNAs associated with breast cancer

MotivationBreast cancer, the most common cancer in women, is characterized by high morbidity and mortality worldwide. Recent evidence has shown that long non-coding RNAs (lncRNAs) play a crucial role in the development and progression of breast cancer. Despite this, no database exists primarily for lncRNAs associated with only breast cancer. ResultsWe developed BCLncRDB, a manually curated, comprehensive database of lncRNAs associated with breast cancer. For this, we collected, processed, and analyzed data on breast cancer-associated lncRNAs from different sources, including published literature and TCGA. Currently, our database contains 5,279 unique breast cancer-lncRNA associations. It has the following features: (I) Differentially expressed and methylated lncRNAs, (II) Stage and subtype-specific lncRNAs, and (III) Drugs, Subcellular localization, Sequence, and Chromosome information. Thus, the BCLncRDB provides a dedicated platform for exploring breast cancer-related lncRNAs to advance and support the ongoing research on this disease. Availability and implementationThe database BCLncRDB is publicly available for use at http://sls.uohyd.ac.in/new/bclncrdb. Contactvaibhav@uohyd.ac.in

bioinformatics↗