Biology subjects

Murali, S.

Publications and source records attributed to Murali, S..

11 recordsLinked to original sources

bioRxiv2025

Genome-scale metabolic model guided metabolic flux analysis in the endophyte Alternaria burnsii NCIM1409

Camptothecin (CPT), a potent anticancer alkaloid, is traditionally derived from plants like Camptotheca acuminata and Nothapodytes nimmoniana, but sustainable production remains challenging. This study explores the metabolic network of the fungal endophyte Alternaria burnsii NCIM1409, known for camptothecin production, using genome sequencing, genome scale metabolic modeling, and 13C-based pathway mapping. A genome-scale metabolic model (AltGEM iDD1552) was reconstructed, comprising 2188 reactions, 2148 metabolites, and 1552 genes, along with manual curation to include camptothecin biosynthesis pathways. Flux balance analysis identified key enzymatic targets, including secologanin synthase and tryptophan decarboxylase, for enhancing CPT production. Further, metabolic analysis of A. burnsii subjected to 20%[U-13C6] glucose or 99% [1-13C] glucose revealed active glycolysis, the pentose phosphate pathway, and the TCA cycle. This integrative approach provides insights into A. burnsiis metabolic capabilities and highlights strategies for optimizing camptothecin biosynthesis, offering a foundation for sustainable production methods.

systems biology↗

bioRxiv2024

A Novel Human TBCK- Neuronal Cell Model Results in Severe Neurodegeneration and Partial Rescue with Mitochondrial Fission Inhibition

Background and ObjectivesTBCK syndrome is a rare fatal pediatric neurodegenerative disease caused by biallelic loss-of-function mutations in the TBCK gene. Previous studies by our lab and others have implicated mTOR, autophagy, lysosomes, and intracellular mRNA transport, however the exact primary pathologic mechanism is unknown. This gap has prevented the development of targeted therapies. MethodsWe employed a human neural progenitor cell line (NPC), ReNcell VM, which can differentiate into neurons and astrocytes, to understand the role of TBCK in mTORC1 activity and neuronal autophagy and cellular mechanisms of pathology. We used shRNA technology to knockdown TBCK in ReNcells. ResultsThese data showed that loss of TBCK did not inhibit mTORC1 activity in neither NPC nor neurons. Additionally, analysis of eight patient-derived cells and TBCK knock down HeLa cells showed that mTORC1 inhibition is inconsistent across different patients and cell types. We showed that TBCK knockdown in ReNcells affected NPC differentiation to neurons and astrocytes. Specifically, differentiation defects are coupled to cell cycle defects in NPC and increased cell death during differentiation. RNAseq analysis indicated the downregulation of several different neurodevelopmental and differentiation pathways. We observed a higher number of LC3-positive vesicles in the soma and neurites of TBCK knockdown cells. Further, TBCK knockdown altered mitochondrial dynamics and membrane potential in NPC, neurons and astrocytes. We found partial mitochondrial rescue with the mitochondrial fission inhibitor mdivi- 1. DiscussionThis work outlines a new Human Cell Model for TBCK-related neurodegeneration and the essential role of mitochondrial health and partial rescue with mitochondrial fission inhibitor. This data, along with human neurons and astrocytes, illuminate mechanisms of neurodegeneration and provide a possible novel therapeutic avenue for affected patients.

neuroscience↗

bioRxiv2024

Integrating molecular and clinical variables to predict myocardial recovery

Mechanical unloading and circulatory support with left ventricular assist devices (LVADs) mediate significant myocardial improvement in a subset of advanced heart failure (HF) patients. The clinical and biological phenomena associated with cardiac recovery are under intensive investigation. Left ventricular (LV) apical tissue, alongside clinical data, were collected from HF patients at the time of LVAD implantation (n=208). RNA was isolated and mRNA transcripts were identified through RNA sequencing and confirmed with RT-qPCR. To our knowledge this is the first study to combine transcriptomic and clinical data to derive predictors of myocardial recovery. We used a bioinformatic approach to integrate 59 clinical variables and 22,373 mRNA transcripts at the time of LVAD implantation for the prediction of post-LVAD myocardial recovery defined as LV ejection fraction (LVEF) [≥]40% and LV end-diastolic diameter (LVEDD) [≤]5.9cm, as well as functional and structural LV improvement independently by using LVEF and LVEDD as continuous variables, respectively. To substantiate the predicted variables, we used a multi-model approach with logistic and linear regressions. Combining RNA and clinical data resulted in a gradient boosted model with 80 features achieving an AUC of 0.731{+/-}0.15 for predicting myocardial recovery. Variables associated with myocardial recovery from a clinical standpoint included HF duration, pre-LVAD LVEF, LVEDD, and HF pharmacologic therapy, and LRRN4CL (ligand binding and programmed cell death) from a biological standpoint. Our findings could have diagnostic, prognostic, and therapeutic implications for advanced HF patients, and inform the care of the broader HF population. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=170 HEIGHT=200 SRC="FIGDIR/small/589326v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@17f0503org.highwire.dtl.DTLVardef@2231c1org.highwire.dtl.DTLVardef@f0ac56org.highwire.dtl.DTLVardef@c278f3_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2024

Lipid Nanoparticle-Associated Inflammation is Triggered by Sensing of Endosomal Damage: Engineering Endosomal Escape without Side Effects

Lipid nanoparticles (LNPs) have emerged as the dominant platform for RNA delivery, based on their success in the COVID-19 vaccines and late-stage clinical studies in other indications. However, we and others have shown that LNPs induce severe inflammation, and massively aggravate pre-existing inflammation. Here, using structure-function screening of lipids and analyses of signaling pathways, we elucidate the mechanisms of LNP-associated inflammation and demonstrate solutions. We show that LNPs hallmark feature, endosomal escape, which is necessary for RNA expression, also directly triggers inflammation by causing endosomal membrane damage. Large, irreparable, endosomal holes are recognized by cytosolic proteins called galectins, which bind to sugars on the inner endosomal membrane and then regulate downstream inflammation. We find that inhibition of galectins abrogates LNP-associated inflammation, both in vitro and in vivo. We show that rapidly biodegradable ionizable lipids can preferentially create endosomal holes that are smaller in size and reparable by the endosomal sorting complex required for transport (ESCRT) pathway. Ionizable lipids producing such ESCRT-recruiting endosomal holes can produce high expression from cargo mRNA with minimal inflammation. Finally, we show that both routes to non-inflammatory LNPs, either galectin inhibition or ESCRT-recruiting ionizable lipids, are compatible with therapeutic mRNAs that ameliorate inflammation in disease models. LNPs without galectin inhibition or biodegradable ionizable lipids lead to severe exacerbation of inflammation in these models. In summary, endosomal escape induces endosomal membrane damage that can lead to inflammation. However, the inflammation can be controlled by inhibiting galectins (large hole detectors) or by using biodegradable lipids, which create smaller holes that are reparable by the ESCRT pathway. These strategies should lead to generally safer LNPs that can be used to treat inflammatory diseases.

bioengineering↗

bioRxiv2023

Remote neuronal activity drives glioma infiltration via Sema4f

The tumor microenvironment (TME) plays an essential role in malignancy and neurons have emerged as a key component of the TME that promotes tumorigenesis across a host of cancers. Recent studies on glioblastoma (GBM) highlight bi-directional signaling between tumors and neurons that propagates a vicious cycle of proliferation, synaptic integration, and brain hyperactivity; however, the identity of neuronal subtypes and tumor subpopulations driving this phenomenon are incompletely understood. Here we show that callosal projection neurons located in the hemisphere contralateral to primary GBM tumors promote progression and widespread infiltration. Using this platform to examine GBM infiltration, we identified an activity dependent infiltrating population present at the leading edge of mouse and human tumors that is enriched for axon guidance genes. High-throughput, in vivo screening of these genes identified Sema4F as a key regulator of tumorigenesis and activity-dependent infiltration. Furthermore, Sema4F promotes the activity-dependent infiltrating population and propagates bi-directional signaling with neurons by remodeling tumor adjacent synapses towards brain network hyperactivity. Collectively, our studies demonstrate that subsets of neurons in locations remote to primary GBM promote malignant progression, while revealing new mechanisms of tumor infiltration that are regulated by neuronal activity.

cancer biology↗

bioRxiv2020

The influence of eye movements and their retinal consequences on bistable motion perception

Eye related movements such as blinks and microsaccades are modulated during bistable perceptual tasks, however, the role of such movements in these purely internal perceptual switches is not known. We conducted two experiments involving an ambiguous plaid stimulus, wherein participants had to continuously report their motion percept. To dissociate the effect of blinks and microsaccades from the visual consequences of such eye movements, we added external blanks and microshifts. Our results showed that while blanks facilitated a switch to the coherent motion percept, this was not the case for a switch to component percept. A similar difference was found with respect to blinks. While both types of perceptual switches were preceded by a decrease in blinks, only the switch to coherent percept was followed by an increase in blinks. These blink related findings, which we largely replicated and refined in a second study, indicate distinct internal processes underlying the two perceptual switches. Microsaccade rates, on the other hand, only showed a weak relation with perceptual switches but their direction was modulated by the perceived motion direction. Additionally, our data showed that microsaccades are differently modulated around internal (blinks) and external events (blanks, microshifts), indicating an interaction between different eye related movements. This study shows that eye movements such as blinks and microsaccades are modulated by purely internal perceptual events independent of task related motor or attentional demands. Eye movements therefore can uncover distinct internal perceptual processes that might otherwise be hard to dissociate.

neuroscience↗

bioRxiv2020

How the Motor Aspect of Speaking Influences the Blink Rate

The blink rate increases if a person indulges in a conversation compared to quiet rest. Since various factors were suggested to explain this increase, the present study tested the influence of motor activity, cognitive processes and auditory input on the blink rate but at the same time excluding any social interaction. While the cognitive and auditory factors only showed a minor influence, mere mouth movements during speaking highly increased the blink rate. Even more specific, lip movements, but less jaw movements, are likely responsible for the increase during a conversation. Such purely motor related influences on the blink rate advise caution when using blinks as neurological indicators during patient interviews.

neuroscience↗

bioRxiv2020

The Latency of Spontaneous Eye Blinks Marks Relevant Visual and Auditory Information Processing

Eye blinks are influenced by several external sensory and internal cognitive factors. However, neither the precise temporal effects of these factors on blinking nor how their timing compares between modalities is known. Our aim was to understand the influence of sensory input vs task-relevant information on blinks in the visual and auditory domain. Using a visual and an auditory temporal judgement task, we found that blinks were suppressed during stimulus presentation in both domains and the overall input length had a significant positive relationship with blink latency i.e. the end of blink suppression. Indeed, the effect of sensory input duration on blink latency was not significantly different between visual and auditory stimuli. The precise timing of blink latency was further modulated by the duration of the task relevant input, which was independent of the overall length of sensory input. The influence of task related changes embedded in the overall stimulation suggests an additional influence of top-down processes on blink timing. Intriguingly, embedded changes as short as 40 ms in the auditory domain and 100 ms in the visual domain are reflected in blink latency differences. Importantly, we could show that task accuracy and motor response was not the driving factor of blink modulation. Our results show a sensory domain independent modulation of blink latencies introduced by changes in the length of task-relevant information. Therefore, blinks not only mark the time of sensory input but also can act as precise indicator for periods of cognitive processing and attention.

neuroscience↗

bioRxiv2020

Primate phylogenomics uncovers multiple rapid radiations and ancient interspecific introgression

Our understanding of the evolutionary history of primates is undergoing continual revision due to ongoing genome sequencing efforts. Bolstered by growing fossil evidence, these data have led to increased acceptance of once controversial hypotheses regarding phylogenetic relationships, hybridization and introgression, and the biogeographical history of primate groups. Among these findings is a pattern of recent introgression between species within all major primate groups examined to date, though little is known about introgression deeper in time. To address this and other phylogenetic questions, here we present new reference genome assemblies for three Old World Monkey species: Colobus angolensis ssp. palliatus (the black and white colobus), Macaca nemestrina (southern pig-tailed macaque), and Mandrillus leucophaeus (the drill). We combine these data with 23 additional primate genomes to estimate both the species tree and individual gene trees using thousands of loci. While our species tree is largely consistent with previous phylogenetic hypotheses, the gene trees reveal high levels of genealogical discordance associated with multiple primate radiations. We use strongly asymmetric patterns of gene tree discordance around specific branches to identify multiple instances of introgression between ancestral primate lineages. In addition, we exploit recent fossil evidence to perform fossil-calibrated molecular dating analyses across the tree. Taken together, our genome-wide data help to resolve multiple contentious sets of relationships among primates, while also providing insight into the biological processes and technical artifacts that led to the disagreements in the first place.

evolutionary biology↗

bioRxiv2018

Reproductive longevity predicts mutation rates in primates

Mutation rates vary between species across several orders of magnitude, with larger organisms having the highest per-generation mutation rates. Hypotheses for this pattern typically invoke physiological or population-genetic constraints imposed on the molecular machinery preventing mutations1. However, continuing germline cell division in multicellular eukaryotes means that organisms with longer generation times and of larger size will leave more mutations to their offspring simply as a by-product of their increased lifespan2,3. Here, we deeply sequence the genomes of 30 owl monkeys (Aotus nancymaae) from 6 multi-generation pedigrees to demonstrate that paternal age is the major factor determining the number of de novo mutations in this species. We find that owl monkeys have an average mutation rate of 0.81 x 10-8 per site per generation, roughly 32% lower than the estimate in humans. Based on a simple model of reproductive longevity that does not require any changes to the mutational machinery, we show that this is the expected mutation rate in owl monkeys. We further demonstrate that our model predicts species-specific mutation rates in other primates, including study-specific mutation rates in humans based on the average paternal age. Our results suggest that variation in life history traits alone can explain variation in the per-generation mutation rate among primates, and perhaps among a wide range of multicellular organisms.

evolutionary biology↗

bioRxiv2017

Uncovering Medical Insights from Vast Amounts of Biomedical Data in Clinical Case Reports

Clinical case reports (CCRs) have a time-honored tradition in serving as an important means of sharing clinical experiences on patients presenting with atypical disease phenotypes or receiving new therapies. However, the huge amount of accumulated case reports are isolated, unstructured, and heterogeneous clinical data, posing a great challenge to clinicians and researchers in mining relevant information through existing indexing tools. In this investigation, in order to render CCRs more findable, accessible, interoperable, and reusable (FAIR) by the biomedical community, we created a resource platform, including the construction of a test dataset consisting of 1000 CCRs spanning 14 disease phenotypes, a standardized metadata template and metrics, and a set of computational tools to automatically retrieve relevant medical information and to analyze all published PubMed clinical case reports with respect to trends in publication journals, citations impact, MeSH Terms, drug use, distributions of patient demographics, and relationships with other case reports and databases. Our standardized metadata template and CCR test dataset may be valuable resources to advance medical science and improve patient care for researchers who are using machine learning approaches with a high-quality dataset to train and validate their algorithms. In the future, our analytical tools may be applied towards other large clinical data sources as well.

bioinformatics↗