Biology subjects

Ravindran, A.

Publications and source records attributed to Ravindran, A..

14 recordsLinked to original sources

bioRxiv2026

Endogenous Opioid System Modulates Neural Activation During Emotion Regulation

Emotion regulation is critical for adaptive functioning and mental health. Functional neuroimaging studies have identified distributed frontal, parietal, and limbic networks involved in emotion regulation, particularly during cognitive reappraisal. However, the neurochemical mechanisms underlying individual differences in emotion regulation remain poorly understood. The endogenous opioid system is a promising candidate because -opioid receptor systems acts as a stress buffer and modulates emotional responses to both rewarding and aversive stimuli We used positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) to examine whether baseline -opioid receptor (MOR) availability is associated with haemodynamic responses during emotion regulation through reappraisal. Participants underwent [11C]carfentanil PET imaging to quantify MOR availability and subsequently completed an fMRI task involving passive viewing of emotional images and cognitive reappraisal of their emotions during image viewing As expected, fMRI revealed engagement of the dorsolateral prefrontal cortex and inferior parietal lobule during cognitive reappraisal. Baseline MOR availability predicted blood oxygenation level-dependent (BOLD) responses in frontal, temporal, and parietal regions: individuals with higher MOR availability showed a larger difference between regulation and viewing trials in the temporal pole, angular gyrus, anterior insula, thalamus, and inferior frontal gyrus. These associations were driven primarily by stronger responses during passive viewing, although some regions also showed evidence of reduced responses during active reappraisal. These findings suggest that higher endogenous opioid tone is associated with stronger recruitment of distributed frontal, temporal, and parietal networks during emotional stimulus processing as well as attenuation of activity in some of these regions during cognitive reappraisal. Thus, while higher MOR availability is associated with enhanced neural responsiveness to emotional stimuli, these responses can nevertheless be effectively modulated through deliberate emotion regulation.

neuroscience↗

bioRxiv2025

SWARM: A Single-Molecule Workflow for High-Precision Profiling of RNA Modifications

Nanopore direct RNA sequencing promises to decode the epitranscriptome by detecting multiple modifications on individual RNA molecules, but its potential for biological discovery is hampered by high false-positive rates. We present SWARM, an AI-based framework designed to overcome this fundamental limitation. Its key innovation is a crosstalk-aware training strategy that incorporates non-target modifications and orthogonally validated cellular signals, enabling high-precision detection of m6A, pseudouridine ({Psi}), and m5C at single-nucleotide and single-molecule resolution. Using rigorous in vitro and cellular RNA benchmarks, SWARM outperforms existing tools and maintains strong agreement with orthogonal methods. Applying SWARM across mammalian tissues reveals thousands of novel modification sites with confirmed motifs and localisation patterns. Our high-resolution multi-tissue modification map revealed no evidence of widespread m6A-{Psi} interplay in predominant writer contexts, challenging models of a coordinated epitranscriptomic code. We further discovered a previously unrecognised splicing-shaped mode of {Psi} deposition, whereby TRUB1-mediated pseudouridylation preferentially occurs after exon-exon ligation, consistent with local RNA structure stabilisation. SWARM provides a robust, universally applicable tool for epitranscriptome discovery.

bioinformatics↗

bioRxiv2025

Deciphering Global Patterns of Marine Microbial Community Assembly and Network Stability

Microbial community assembly processes can help us understand ecology, evolution, and climatic influences on community composition while presenting opportunities for biotechnological applications and improved marine conservation. In this study, we have investigated species richness patterns, community assembly mechanisms, and interaction patterns of marine microbial communities by analysing 16S rRNA amplicon sequencing data from 4,611 samples collected from major ocean microbiome projects. Using neutral community models, the iCAMP framework, and co-occurrence network analyses, we showed that stochastic processes drive microbial community assembly across all latitude zones. Drift was the primary driver of community assembly in polar communities. The polar microbial communities exhibited the highest modularity and network robustness, but were more vulnerable to hub removal. While previous studies have attributed higher stability of the polar communities to environmental filtering, our analyses reveal that the resilience of the community is dependent on a few central taxa. By classifying the genera as generalists and specialists, we further highlight the role played by the specialist taxa in maintaining the stability of the marine microbial community, especially under the pressures of climate change and global warming. Overall, our findings offer a latitudinal perspective on ocean microbial community stability and the effect of anthropogenic disturbances on these communities.

systems biology↗

bioRxiv2025

FracFixR: A compositional statistical framework for absolute proportion estimation between fractions in RNA sequencing data

MotivationRNA fractionation followed by sequencing is widely used to study RNA localization, translation, and subcellular compartmentalization. Interpreting fractionated RNA-seq data poses a fundamental compositional challenge: library preparation and sequencing depth obscure the original proportions of RNA fractions, which can bias comparisons - particularly when biological changes shift RNA distribution across fractions. This bias compromises comparisons of fraction-specific RNA profiles and limits the utility of standard differential expression methods. Existing approaches using transcript frequency ratios or standard normalization fail to account for the compositional nature of fractionated samples and cannot estimate the unrecoverable "lost" fraction. ResultsWe developed FracFixR, a statistical framework that reconstructs original fraction proportions by modeling the compositional relationship between whole and fractionated RNA samples. Using non-negative linear regression on carefully selected transcripts, FracFixR estimates global fraction weights, corrects individual transcript frequencies, and quantifies unrecoverable material. The framework includes methods for differential proportion testing between conditions using binomial GLM, logit, or beta-binomial models. We rigorously validated FracFixR using synthetic data with known ground truth and real polysome profiling data from multiple cell lines, demonstrating accurate reconstruction of fraction weights (Pearson correlation > 0.85) and enabling detection of differentially translated transcripts between cancer subtypes. Availability and implementationFracFixR is implemented as an R package freely available on GitHub at https://github.com/Arnaroo/FracFixR.

bioinformatics↗

bioRxiv2025

Metagenomic Profiling of Drinking Water Microbiomes: Insights into Microbial Diversity and Antimicrobial Resistance

Monitoring microbial components in drinking water is as essential as tracking its chemical composition. Although traditional culture-based methods provide valuable insight into microbial morphology and behaviour, their scope is restricted to culturable species. With the advent of high-throughput sequencing, we can now detect a wider range of microbes in any ecosystem, along with efficient insights into their functional potential and metabolic capabilities. In this study, metagenomic analyses were performed to fully understand the microbiome of drinking water supplied through public distribution systems in an Indian city. Our findings identified bacteria from the phyla Pseudomonadota, Planctomycetota, Bacteroidota, and Actinomycetota, consistent with previous studies of drinking water microbiomes of other countries. At the species level, Afipia carboxidovorans, Klebsiella pneumoniae, Pseudomonas aeruginosa, Sphingopyxis macrogoltabida, and Variovorax paradoxus were identified as members of the core microbiome. It was observed that the temperature of the water samples, even as little as a 5{o}C increase, influenced the composition and diversity of the microbial communities. No significant correlation was detected between the abundance of microbial species and the metal concentration in the sample. In addition, we traced the distribution of antibiotic resistance genes (ARGs), finding widespread resistance to aminoglycosides, tetracyclines, and macrolides in samples. In particular, ARGs such as adeF and ermR, which are known to be associated with multidrug resistance, were detected. Although this study did not directly assess the pathogenicity or mobility of these genes, their presence in potable water raises potential public health concerns due to the possibility of horizontal gene transfer (HGT) in environmental settings. Therefore, continuous monitoring of antibiotic resistance genes (ARGs) is imperative to accurately evaluate long-term risks and to guide evidence-based water quality management strategies. In summary, this study provides a comprehensive metagenomic overview of drinking water microbiota, ARGs, and water quality, offering a foundation for future surveillance and risk mitigation strategies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/636216v3_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@819c0org.highwire.dtl.DTLVardef@1d29372org.highwire.dtl.DTLVardef@1ce3cf9org.highwire.dtl.DTLVardef@1050997_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

High-Accuracy RNA Integrity Definition for Unbiased Transcriptome Comparisons with INDEGRA

RNA sample integrity variability introduces biases and obscures natural RNA degradation, posing a significant challenge in transcriptomics. To address this, we developed the Direct Transcriptome Integrity (DTI) measure, a universal and robust RNA integrity metric based on nanopore sequencing. By accurately modeling RNA fragmentation, DTI provides a reliable assessment of sample quality. Integrated into the INDEGRA package (freely available at https://github.com/Arnaroo/INDEGRA), we provide tools to correct false discoveries and enable precise differential expression and RNA degradation analyses, even for challenging sample types. INDEGRA software can be used to accurately measure RNA DTI stability metric, isolate biological component of RNA degradation from technical biases, compare biological RNA stability transcriptome-wide and suppress false degradation-induced differential gene expression hits to allow broad comparisons across samples of different quality DTI offers a straightforward and accurate method for assessing RNA degradation, characterizing both overall sample integrity and transcript-specific degradation rates using direct RNA sequencing (DRS) data. Calculated through INDEGRA, DTI reveals inter- and intra-transcript variability in degradation, while INDEGRA separates RNA degradation from mapping inaccuracies, and connects degradation profiles to RNA fragmentation rates. By leveraging INDEGRA, researchers can minimize false differential transcript abundance findings caused by variations in overall sample integrity, while preserving genuine transcript-specific differences in stability and degradation. INDEGRA supports integration with widely used differential transcript abundance tools like DESeq2, limma-voom, and edgeR, enabling seamless analysis pipelines. INDEGRA enhances the accuracy and reliability of RNA quantification in high-throughput data and simplifies comparisons across diverse transcriptomic datasets, including those derived from different tissues, species, or experimental protocols.

bioinformatics↗

bioRxiv2024

The conserved landscape of RNA modifications and transcript diversity across mammalian evolution

Gene expression programs underpin the development of shared phenotypes, yet the importance of transcript complexity in shaping mammalian evolution remains unclear. Here we present a comprehensive long-read direct RNA sequencing atlas of full-length transcripts and their m6A modifications across six tissues (hippocampus, frontal cortex, cerebellum, testes, skeletal muscle, and liver) in five mammals (human, mouse, rat, dog, and cow) and a non-mammalian out-group (chicken). Our analysis reveals that 29% of genes have multiple mammalian-conserved alternative transcripts, with 31% of these genes showing tissue-specific switching of the major transcript isoforms. We uncover extensive conservation of coordinated splicing events, primarily driven by tissue-specific mutually associated exon splicing, particularly in neural tissues and cytoskeletal genes. At the epitranscriptome level, we find that 14.2% of m6A RNA modifications are conserved across mammals, with 39% of analysed genes containing a conserved m6A RNA modification. Our work provides unprecedented insight into the evolution of transcript complexity and the epitranscriptome, highlighting their potential roles in shaping mammalian phenotypic diversity and providing a valuable resource for understanding post-transcriptional regulation across mammalian evolutionary time.

genomics↗

bioRxiv2023

Coronary Artery Disease risk variant dampens the expression of CALCRL by reducing HSF binding to shear stress responsive enhancer in endothelial cells

Coronary artery disease (CAD) is one of the major causes of mortality worldwide. Recent genome-wide association studies have started to unravel the genetic architecture of the disease. Such efforts have identified Calcitonin receptor-like (CALCRL), an important mediator of the endothelial fluid shear stress response, associated with CAD risk variants. In this study we functionally characterized the non-coding regulatory elements carrying CAD risks SNPs and studied their role in the regulation of CALCRL expression in endothelial cells. We demonstrate that rs880890-harboring regulatory element exhibits high enhancer activity and significant allelic bias with A allele showing 40% more activity than G allele. We also observed that the A allele of rs880890 is favored over the G allele under shear stress. CRISPR deletion of rs880890-enhancer resulted in downregulation of CALCRL expression. EMSA further showed that heat shock factors are binding to the enhancer with a preference for A allele over the G allele. In line with this, HSF1 knockdown resulted in a significant decrease in CALCRL expression. CALCRL knockdown as well as variant perturbation experiments confirmed the role of CALCRL in the regulation of eNOS, apelin, angiopoietin, prostaglandins and endothelin-1 signaling pathways while demonstrating a significant decrease in cell proliferation and tube formation. Overall, our results demonstrate the existence of an endothelial-specific heat shock factor regulated transcriptional enhancer carrying a CAD risk SNP rs880890 that regulates CALCRL expression. Better understanding of CALCRL gene regulation and the role of SNPs in modulation of CALCRL expression could provide important steps towards understanding genetic regulation of shear stress signaling responses.

genetics↗

bioRxiv2022

Alkalinity modulates a unique suite of genes to recalibrate growth and pH homeostasis

Alkaline soils pose a conglomerate of constraints to plants, restricting the growth and fitness of non-adapted species in habitats with low active proton concentrations. To thrive under such conditions, plants have to compensate for a potential increase in cytosolic pH and restricted softening of the cell wall to invigorate cell elongation in a proton-depleted environment. To discern mechanisms that aid in the adaptation to external pH, we grew plants on media with pH values ranging from 4.5 to 8.5. Growth was severely restricted at pH 4.5 and above pH 6.5, and associated with decreasing chlorophyll levels at alkaline pH. Bicarbonate treatment worsened plant performance, suggesting effects that differ from those exerted by pH as such. Transcriptional profiling of roots subjected to short-term transfer from optimal (pH 5.5) to alkaline (pH 7.5) media unveiled a large set of differentially expressed genes that were partially congruent with genes affected by low pH, bicarbonate and nitrate, but showed only a very small overlap with genes responsive to the availability of iron. Further analysis of selected genes disclosed pronounced responsiveness of their expression over a wide range of external pH values. Alkalinity altered the expression of various proton/anion co-transporters, possibly to recalibrate cellular proton homeostasis. Co-expression analysis of pH-responsive genes identified a module of genes encoding proteins with putative functions in the regulation of root growth, which appears to be conserved in plants subjected to low pH or bicarbonate. Our analysis provides an inventory of pH-sensitive genes and allows comprehensive insights into processes that are orchestrated by external pH.

plant biology↗

bioRxiv2022

Real-time biochemical-free targeted sequencing of RNA species with RISER

The heterogeneous composition of cellular transcriptomes poses a major challenge for detecting weakly expressed RNA classes, as they can be obscured by abundant RNAs. Although biochemical protocols can enrich or deplete specified RNAs, they are time-consuming, expensive and can compromise RNA integrity. Here we introduce RISER, a biochemical-free technology for the real-time enrichment or depletion of RNA classes. RISER performs selective rejection of molecules during direct RNA sequencing by identifying RNA classes directly from nanopore signals with deep learning and communicating with the sequencing hardware in real time. By targeting the dominant messenger and mitochondrial RNA classes for depletion, RISER reduced their respective read counts by more than 85%, resulting in an increase in sequencing depth of up to 93% for long non-coding RNAs. We also applied RISER for the depletion of globin mRNA in whole blood, achieving a decrease in globin reads by more than 90% as well as a significant increase in non-globin reads. Furthermore, using a GPU or a CPU, RISER is faster than GPU-accelerated basecalling and mapping. RISERs modular and retrainable software and intuitive command-line interface allow easy adaptation to other RNA classes. RISER is available at https://github.com/comprna/riser.

bioinformatics↗

bioRxiv2022

Identification of m6A and m5C RNA modifications at single-molecule resolution from Nanopore sequencing

The epitranscriptome embodies many new and largely unexplored functions of RNA. A significant roadblock hindering progress in epitranscriptomics is the identification of more than one modification in individual transcript molecules. We address this with CHEUI (CH3 (methylation) Estimation Using Ionic current). CHEUI predicts N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual molecules from the same sample, the stoichiometry at transcript reference sites, and differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals to achieve high single-molecule, transcript-site, and stoichiometry accuracies in multiple tests using synthetic RNA standards and cell line data. CHEUIs capability to identify two modification types in the same sample reveals a co-occurrence of m6A and m5C in individual mRNAs in cell line and tissue transcriptomes. CHEUI provides new avenues to discover and study the function of the epitranscriptome.

bioinformatics↗

bioRxiv2021

Lipid Alterations in African American Prostate Cancer

African-American (AA) men are more than twice as likely to die of prostate cancer (PCa) than European American (EA) men. Previous in-silico analysis revealed enrichment of altered lipid metabolic pathways in pan-cancer AA tumors. Here, we performed global unbiased lipidomics profiling on 48 matched localized PCa and benign adjacent tissues (30 AA, 24 ancestry-verified, and 18 EA, 8 ancestry verified) and quantified 429 lipids belonging to 15 lipid classes. Significant alterations in long chain polyunsaturated lipids was observed between PCa and benign adjacent tissues, low and high Gleason tumors, as well as associated with early biochemical recurrence, both in the entire cohort, and within AA patients. Altered levels of cholesteryl esters, and phosphatidyl inositols delineated AA and EA PCa, while levels of triglycerides, phosphatidyl glycerol, phosphatidyl choline, phosphatidic acid and cholesteryl esters distinguished AA and EA PCa patients with biochemical recurrence. These first-in-field results implicate lipid alterations as biological factors for prostate cancer disparities.

cancer biology↗

bioRxiv2021

Immunoprofiling reveals novel mast cell receptors and a continuous nature of human lung mast cell heterogeneity

BackgroundImmunohistochemical analysis of granule-associated proteases have revealed that human lungs mast cells constitute a heterogeneous population of cells, with distinct subpopulations identified. However, a systematic and comprehensive analysis of cell surface markers to study human lung mast cell heterogeneity is yet to be performed. MethodsHuman lung mast cells were obtained from lung lobectomies and the expression of 332 cell surface markers were analyzed using flow cytometry and the LEGENDScreen kit. Markers that exhibited a high variance were selected for additional analyses to reveal whether they correlated and if discrete mast cell subpopulations were discernable. ResultsWe identified expression of 102 surface markers on human lung mast cells. Several markers showed a high continuous variation of expression within the mast cell population. Six of these markers correlated: SUSD2, CD49a, CD326, CD34, CD66 and HLA-DR. The expression of these markers also correlated to the size and granularity of the mast cells. However, no marker produced an expression profile consistent with a bi- or multimodal distribution. ConclusionsLEGENDScreen analysis identified more than 100 cell surface markers on mast cells, out of which 23 have to our knowledge not previously described on human mast cells. Several of the newly described markers are known to be involved in sensing the microenvironment, and their identification can shed new light on mast cell functions. The exhaustive expression profiling of the 332 surface markers failed to detect distinct mast cell subpopulations. Instead, we demonstrate a continuous nature of human lung mast cell heterogeneity.

immunology↗

bioRxiv2020

BigDataProcessor2: A free and open-source Fiji plugin for inspection and processing of TB sized image data

Modern bioimaging and related areas such as sensor technology has seen tremendous development the last years allowing several contemporary imaging techniques, electron microscopy (EM) and light sheet microscopy in particular, to generate datasets frequently reaching the size of several terabytes (TB). As a consequence, even seemingly simple data operations such as cropping, chromatic- and drift-corrections and even visualisation, poses challenges when applied to thousands of time points or tiles. To address this we developed BigDataProcessor2 - a Fiji plugin facilitating processing workflows for TB sized image datasets. Availability and implementationBigDataProcessor2 is available as a Fiji plugin via the BigDataProcessor update site. The application is implemented in Java and the code is publicly available on GitHub (https://github.com/bigdataprocessor/bigdataprocessor2). Contactchristian.tischer@embl.de, nils.norlin@med.lu.se

bioinformatics↗