Biology subjects

Raj, R.

Publications and source records attributed to Raj, R..

14 recordsLinked to original sources

bioRxiv2026

Active Nucleosome Sliding, Eviction, and Reassembly Dynamics Can Regulate Chromatin Condensate Organization

At the nucleosome scale, chromatin is an actively remodeled polymeric system whose organization is continuously reshaped by ATP-dependent remodelers that slide, evict, and reassemble nucleosomes along DNA. However, how the local structural rearrangements generated by such remodeling events influence condensate-scale organization and dynamics remains poorly understood. Here, we introduce a coarse-grained model of chromatin condensates composed of short polymers that explicitly incorporates enzyme-assisted nucleosome sliding together with nucleosome eviction and reassembly, coupled to Langevin relaxation dynamics. By explicitly accounting for the DNA length sequestered within individual nucleosomes, the model captures the steric constraints and local conformational relaxation that accompany nucleosome sliding, eviction, and reassembly. We find that nucleosome activity drives condensate swelling, enhances condensate-size fluctuations, and promotes internal mixing. In condensates containing both active and passive polymers, differences in nucleosome activity further induce radial segregation, with active polymers enriched near the periphery and passive polymers concentrated in the interior. These results identify active nucleosome remodeling as a physical mechanism for regulating chromatin condensate structure, fluidity, and spatial organization.

biophysics↗

bioRxiv2026

Interplay of Structural Heterogeneity and Active Remodeling Controls Chromatin Condensate Organization and Dynamics

Chromatin is an actively remodeled polymeric system whose organization emerges from the interplay of equilibrium interactions and ATP-dependent processes. Recent in vitro experiments show that nucleosome spacing and ATP-dependent remodeler activity significantly influence chromatin condensate properties. Here, guided by these observations, we develop a hierarchy of coarse-grained models that systematically dissect the roles of nucleosome spacing, remodeler-mediated binding-unbinding, and active force generation in governing condensate dynamics. We demonstrate that nucleosome spacing heterogeneity is a key determinant of condensate material properties. Condensates formed from regularly spaced fibers exhibit enhanced internal mixing, whereas those assembled from disordered spacing develop pronounced structural correlations, increased entanglement, and suppressed internal dynamics. Incorporating remodeler-like binding-unbinding non-equilibrium kinetics drives local structural reorganization, leading to condensate swelling and a substantial acceleration of internal relaxation. In a condensate of heterogeneous fibers, contrasts in spacing and activity robustly drive spatial segregation, giving rise to stable core-shell architectures. Strikingly, when dipolar forces are coupled to hydrodynamic interactions, serving as a minimal representation of active nucleosome translocation, condensates exhibit enhanced center-of-mass motion. Together, our results establish a predictive coarse-grained framework that quantitatively links structural heterogeneity and active processes to emergent chromatin-like condensate organization, mechanics, and transport. SIGNIFICANCE STATEMENTChromatin forms dynamic condensates in living cells that play important roles in genome organization and regulation. Recent in vitro experiments have shown that condensate properties are strongly influenced by the arrangement of nucleosomes, the protein complexes around which DNA is wrapped, along chromatin fibers and by ATP-dependent remodeling activity. However, the mechanisms linking these molecular processes to condensate behavior remain poorly understood. Using a hierarchy of coarse-grained models, we identify the distinct roles of structural heterogeneity, remodeler-mediated kinetics, and active force generation in chromatin condensates. By providing a mechanistic explanation for experimental observations, our work establishes a physical framework connecting chromatin architecture and energy-consuming processes to condensate organization, dynamics, and function.

biophysics↗

bioRxiv2025

The functional organization of chromosome territories in single nuclei during zygotic genome activation

Chromosome territories (CTs) are intricately organized and regulated within the nucleus. Despite remarkable advances in our understanding of genome packaging and gene expression, the interplay among CTs, pairing of parental homologous chromosomes, and genome function during development remains elusive. Here, we employ an Oligopaints-based high-resolution imaging approach to examine variable CT organization in single nuclei during the developmental process of zygotic genome activation. We reveal large-scale chromosome changes with extensive homolog pairing at the whole-chromosome level that decreases locally due to spatial variability in chromosome conformations. In the absence of one homolog copy, the dynamics of CT compaction and RNA polymerase II recruitment are supported by transcriptional changes in haploid embryos. Finally, global inhibition of transcription results in decreased CT opening and no significant impact on CT pairing levels. These findings enhance our understanding of parental genome folding and regulation, which may inform strategies for chromosome-based diseases.

developmental biology↗

bioRxiv2025

Elusive scents: neurocomputational mechanisms of verbal omissions in free odor naming

Odor naming is considered a particularly challenging cognitive test, but the underlying cause of this difficulty is unknown. People often fail to report any source label to identify common odors, resulting in omissions (i.e., a lack of response). Here, with the support of a computational model, we offer a hypothesis about the neural network mechanisms underlying odor naming omissions. Based on an evaluation of behavioral data from almost 40,000 odor naming attempts, we suggest that high omission rates are driven by odors that are referred to by multiple linguistic labels. To explain this observation at the systems level, where olfactory perception and language (semantic) processing are produced by interacting cortical systems, we developed a computational model consisting of two associatively coupled attractor memory networks (odor and language networks), and investigated the effect of Hebbian-like learning on the simulated task performance. We used distributed network representations for the odor percepts and word label mental objects, and accounted for their statistical inter-relationships (correlations) extracted from collected data on odor perceptual similarity, and from a large Swedish odor language corpus, respectively. We evaluated a novel hypothesis, that Bayesian-Hebbian synaptic plasticity mechanisms can explain behavioral omissions in odor naming tasks, casting new light on the underlying mechanisms of this frequently observed memory phenomenon. Due to the nature of Bayesian-Hebbian associative learning connecting the two networks, there was a progressively weaker coupling for odors paired with multiple different labels in the encoding process (one-to-many mapping). Thus, when the model was cued with perceptual odor stimuli that established multiple word label associations (one-to-many mapping), the olfactory language network often produced subthreshold network responses, resulting in elevated omissions (opposite to one-to-few mapping scenario that led to improved performance scores). Our results are of theoretical interest, as they suggest a biologically plausible mechanism to explain a common, but poorly understood, behavioral phenomenon.

neuroscience↗

bioRxiv2024

U1 snRNP-Specific U1C Acts as the Gatekeeper of the Survival of Motor Neurons (SMN) Complex in snRNP Biogenesis

The stability and abundance of spliceosomal snRNPs are determined by the assembly of an Sm protein ring (Sm core) on each snRNA, a process facilitated by the survival of motor neuron (SMN) complex. Whereas the SMN complexs role as a chaperone is well-established, the mechanisms that regulate its activity remain unclear. Our study identifies U1C, a U1 snRNP-specific protein, as a key regulator of the SMN complex. U1C together with U1-70K facilitates U1 snRNP formation, rendering the SMN complex accessible for other snRNAs to assemble Sm cores. Remarkably, a prevalent cancer-associated mutation in U1 snRNA near the U1C binding site not only disrupts Sm core assembly but also sequesters the SMN complex, inhibiting canonical snRNP formation. Our findings provide mechanistic insights into how snRNP-specific proteins regulate the SMN complex and suggest that U1 snRNA mutations in numerous cancers disrupt the SMN complex, leading to perturbation in various RNA metabolism pathways. HighlightsO_LIU1C facilitates the formation of Sm core not only on U1 snRNA but also on other snRNAs. C_LIO_LIU1C together with U1-70K promotes U1 snRNP formation, enabling the SMN complex to recruit Gemin5/other snRNAs complex. C_LIO_LIThe divalent binding of U1C to the SMN complex is mediated by U1Cs N-terminus helix, interacting with U1-70K, and its arginine-methylated C-terminus domain, binding to the SMN protein. C_LIO_LIMultiple U1 snRNA mutations in cancer patients defect in Sm core assembly and potentially sequester the SMN complex, thereby inhibiting canonical snRNP formation. C_LI

biochemistry↗

bioRxiv2023

Meta-omic profiling reveals ubiquity of genes encoding for the high value nitrogen rich biopolymer cyanophycin in activated sludge microbiomes

Recovering nitrogen (N) from municipal wastewater is a promising approach to prevent nutrient pollution, reduce energy use, and transition towards a circular N bioeconomy, but remains a technologically challenging endeavor. Existing N recovery techniques are optimized for high-strength, low-volume wastewater. Therefore, developing methods to concentrate dilute N from mainstream wastewater will bridge the gap between existing technologies and practical implementation. The N-rich biopolymer cyanophycin is a promising candidate for N bioconcentration and recovery due to its solubility characteristics and potential for high levels of accumulation in a limited number of bacterial isolates. However, the cyanophycin synthesis pathway is poorly explored in natural and engineered microbiomes. In this study, we analyzed over 3700 publicly available metagenome assembled genomes (MAGs) and found that the cyanophycin synthesis gene cphA was ubiquitous across common activated sludge bacteria. Surprisingly, we found that cphA was present in all analyzed genomes of the common phosphorus accumulating organisms (PAO) Ca. Accumulibacter and Tetrasphaera, suggesting potential for simultaneous N and P bioconcentration in the same organisms. Using metatranscriptomic data, we also confirmed the expression of cphA in lab-scale bioreactors enriched with PAO. Our findings suggest that cyanophycin synthesis is a ubiquitous metabolic pathway in activated sludge microbiomes and therefore may have potential for integration in existing biological nutrient removal and recovery processes. We anticipate this work to be a starting point for future evaluations of combined N and P bioaccumulation, with the ultimate goal of advancing widespread adoption of nutrient recovery from municipal wastewater.

ecology↗

bioRxiv2023

Distributable, Metabolic PET Reporting of Tuberculosis

Tuberculosis remains a large global disease burden for which treatment regimens are protracted and monitoring of disease activity difficult. Existing detection methods rely almost exclusively on bacterial culture from sputum which limits sampling to organisms on the pulmonary surface. Advances in monitoring tuberculous lesions have utilized the common glucoside [18F]FDG, yet lack specificity to the causative pathogen Mycobacterium tuberculosis (Mtb) and so do not directly correlate with pathogen viability. Here we show that a close mimic that is also positron-emitting of the non-mammalian Mtb disaccharide trehalose - 2-[18F]fluoro-2-deoxytrehalose ([18F]FDT) - can act as a mechanism-based enzyme reporter in vivo. Use of [18F]FDT in the imaging of Mtb in diverse models of disease, including non-human primates, successfully co-opts Mtb-specific processing of trehalose to allow the specific imaging of TB-associated lesions and to monitor the effects of treatment. A pyrogen-free, direct enzyme-catalyzed process for its radiochemical synthesis allows the ready production of [18F]FDT from the most globally-abundant organic 18F-containing molecule, [18F]FDG. The full, pre-clinical validation of both production method and [18F]FDT now creates a new, bacterium-specific, clinical diagnostic candidate. We anticipate that this distributable technology to generate clinical-grade [18F]FDT directly from the widely-available clinical reagent [18F]FDG, without need for either bespoke radioisotope generation or specialist chemical methods and/or facilities, could now usher in global, democratized access to a TB-specific PET tracer.

biochemistry↗

bioRxiv2023

Zinc nano-fertilization enhances wheat productivity and biofortification

Zinc (Zn) malnutrition has emerged as one of the major health challenges in developing nations across the globe. Development of Zn management protocols in staple food crops using modern scientific tools to enhance Zn concentration in grains along with augmented crop yields became utmost necessary. In this context a 2-year experiment was carried out to assess the effects of zinc oxide nanoparticles (ZnO-NPs) vis-a-vis bulk zinc sulfate (ZnSO4) on wheat growth, yield and Zn concentration in plant parts. Four levels of application of ZnO-NPs (0, 20, 25 and 30 mg kg-1) were compared with ZnSO4 (equal to Zinc concentration in ZnO-NPs). Results revealed that seed vigor was significantly (p <0.05) higher under 25 and 30 mg kg-1 soil ZnO-NPs treatments over ZnSO4. Among the crop yield parameters such as tillers (plant-1), grain weight (plant-1), biomass (plant-1) and grain yield were significantly (p <0.05) higher under ZnO-NPs 25 mg kg-1 treated soil as compared to any other treatment. Zinc concentration in grains increased with dose of ZnO-NPs and it was significantly more than ZnSO4 treated soil at each treatment level. ZnO-NPs and ZnSO4 treatments did not affect photosynthetic rate and chlorophyll (SPAD) content significantly. In conclusion, 25 mg kg-1 ZnO-NPs application could be recommended in wheat cultivation to improve growth, yield and grain Zn biofortification.

plant biology↗

bioRxiv2022

A Local Hebbian Rule Based Model of Invariant Object Representation and Classification.

Our recognition of an object is consistent across conditions, unaffected by motion, perspective, rotation, and corruption. This robustness is thought to be enabled by invariant object representations, but how the brain achieves it remains unknown1. In artificial neural networks, learning to represent objects is simulated as an optimization process2. The system reduces discrepancies between actual and desired outputs by updating specific connections through mechanisms such as error backpropagation3. These operations are biologically implausible primarily because they require individual connections at all levels to be sensitive to errors found at the late stages of the network4,5. On the other hand, learning in the nervous system occurs locally, and synaptic changes depend only on pre- and post-synaptic activities6,7. It is unclear how local updates translate into coordinated changes across large populations of neurons and lead to sophisticated cognitive functions. Here we demonstrate that it is possible to achieve robust and invariant object representations in naturally observed network architectures using only biologically realistic local learning rules. Adopting operations fundamentally different from current ANN models, unsupervised recurrent networks can learn to represent and categorize objects through sensory experiences without propagating or detecting errors. This white box, fully interpretable networks can extract clean images from their corrupted forms and produce representations prospectively robust against unfamiliar perturbations. Continuous learning does not cause catastrophic forgetting commonly observed in ANNs. Without explicit instructions, the networks can classify objects and represent the identity of 3D objects regardless of perspective, size, or position. These findings have substantial implications for understanding how biological brains achieve invariant object representation and for developing biologically realistic intelligent networks that are efficient and robust.

neuroscience↗

bioRxiv2022

GPC3-Unc5D complex structure and role in cell migration

Neural migration is a critical step during brain development that requires the interactions of cell-surface guidance receptors. Cancer cells often hijack these mechanisms to disseminate. Here we reveal crystal structures of Uncoordinated-5 receptor D (Unc5D) in complex with morphogen receptor glypican-3 (GPC3), forming an octameric glycoprotein complex. In the complex, four Unc5D molecules pack into an antiparallel bundle, flanked by four GPC3 molecules. Central glycan-glycan interactions are formed by N-linked glycans emanating from GPC3 (N241 in human) and C-mannosylated tryptophans of the Unc5D thrombospondin-like domains. MD simulations, mass-spectrometry and structure-based mutants validate the crystallographic data. Anti-GPC3 nanobodies enhance or weaken Unc5-GPC3 binding. Using these tools in vivo, we show that Unc5/GPC3 guide migrating pyramidal neurons in the mouse cortex, and cancer cells in an embryonic xenograft neuroblastoma model. The results demonstrate a conserved structural mechanism of cell-guidance, with the potential for wide- ranging biomedical implications in development and cancer biology.

neuroscience↗

bioRxiv2021

Interchromosomal interaction of homologous Stat92E alleles regulates transcriptional switch during stem-cell differentiation

The strength of pairing of homologous chromosomes differs in a locus-specific manner and is correlated to gene expression states. However, the functional impact of homolog pairing on local transcriptional activity is still unclear. Drosophila male germline stem cells (GSCs) constantly divide asymmetrically to produce one GSC and one differentiating gonialblast (GB). The GB then enters the differentiation program in which stem cell specific genes are quickly downregulated. Here we demonstrate that a change in local pairing state of the Stat92E locus is required for the downregulation of the Stat92E gene during differentiation. Using OligoPaint fluorescent in situ hybridization (FISH), we show that the interaction between homologous regions of Stat92E is always tight in GSCs and immediately loosened in GBs. When one of the Stat92E locus was absent or relocated to another chromosome, Stat92E did not pair and failed to downregulate, suggesting that the pairing is required for switching of transcriptional activity. The defect in downregulation of Stat92E was also observed upon knockdown of global pairing or anti-pairing factors. Moreover, the Stat92E enhancer element, but not cis-transcription, is required for the change in pairing state, indicating that it is not a consequence of transcriptional changes. GSCs are known to inherit pre-existing histones H3 and H4, while newly synthesized histones are distributed in GBs. When this histone inheritance was compromised, the change in Stat92E pairing did not occur, suggesting that it is an intrinsically programmed process during asymmetric stem cell division. We propose that the change of local pairing state may be a common process to reprogram gene activity during cell-differentiation.

developmental biology↗

bioRxiv2020

Influence of spatial arrangement, biofertilizers and bioirrigation on the performance of legume-millet intercropping system in rainfed areas of southern India

Biofertilization via the inoculation with arbuscular mycorrhizal fungi (AMF), combined with rhizobia and plant growth promoting rhizobacteria (PGPR), are beginning to become established as an effective and sustainable measure to improve yields. Biofertilization might have a particular potential to boost the yield of intercropping systems in rainfed areas because AMF can form a common mycorrhizal network (CMN) that can transfer nutrients and water between two plants and balance as such belowground competition. In this study, we tested if biofertilizers can enhance the yield of intercropping systems using a pigeon pea (PP) - finger millet (FM) intercropping system grown for two consecutive growing seasons (2016/17 and 2017/18) at two contrasting sites in Bengaluru and Kolli Hills, India. To validate the process of bioirrigation (transfer of water between rhizosphere of two plants), we tested, for the first time, if the spatial arrangement of intercropped plants using either a row-wise or a mosaic design affected yield and water relations with and without biofertilizers. Our results demonstrate that intercropping can improve the straw and grain yield in PP-FM intercropping compared to the respective monocultures but that intercropping effects vary depending on the site characteristic such as climate and soil type. Spatial arrangement of component plants affected the total, straw and grain biomass in intercropping treatments, but this effect also varied across sites. Most importantly, the results from the 2017-18 growing season clearly demonstrated a positive effect of biofertilizer on biomass yield, and this effect was irrespective of site, spatial arrangement, mixed or monoculture. Despite a yield increase in intercropping, we did not see a positive effect of biofertilization on water relations of FM possibly due to interspecific competition for soil moisture where PP dominated. In summary, our study shows the potential of biofertilizers to increase the yield of intercropping systems in rainfed dryland agriculture.

ecology↗

bioRxiv2019

Phenylephrine induces relaxation of longitudinal strips from small arteries of goat legs

Alpha adrenergic stimulation is known to produce vasoconstriction. We have earlier shown that, in spiral strips of small arteries Phenylephrine (PE) caused vasorelaxation under high nitric oxide (NO) environment. However on further experimentation it was realized that the PE-induced vasorelaxant response occurred only with longitudinal strips of small arteries even under normal NO environment while circular strips showed contraction with PE even under high NO environment. Such PE-induced vasorelaxation of longitudinal strips was blocked by Phentolamine, an alpha-adrenergic receptor blocker. On delineation of specific receptor subtype, PE-induced relaxation was found to be mediated through alpha 1D receptor. However, this phenomenon is specific to small artery, as longitudinal smooth muscle of aorta showed only contractile response to adrenergic stimulation. There is no prior report of longitudinal smooth muscle in small artery up to our knowledge. The results of this study and histological examination of vessel sections suggest the presence of longitudinal smooth muscle in small artery and their relaxant response to alpha adrenergic stimulation is a novel phenomenon.

physiology↗

bioRxiv2019

A Dependency Capturing Code for Robust Object Representation

Sensory inputs conveying information about the environment are often noisy and incomplete, yet the brain can achieve remarkable consistency in object recognition. This cognitive robustness is thought to be enabled by transforming the varying input patterns into invariant representations of objects, but how this transformation occurs computationally remains unclear. Here we propose that sensory coding should follow a principle of maximal dependence capturing to encode associations among structural components that can uniquely identify objects. We show that a computational framework incorporating dimension expansion and a specific form of sparse coding can capture structures that contain maximum information about specific objects, allow redundancy coding, and enable consistent representation of object identities. Using symbol and face recognition, we demonstrate that a two-layer system can generate representations that remain invariant under conditions of occlusion, corruption, or high noise.

neuroscience↗