Biology subjects

Chandran, A.

Publications and source records attributed to Chandran, A..

14 recordsLinked to original sources

bioRxiv2025

Dual effect of alpha-synuclein disease variants on condensate formation

-synuclein is a pre-synaptic protein1,2 implicated in synucleinopathies like Parkinsons disease and Dementia with Lewy Bodies, where it accumulates in intracellular aggregates termed Lewy bodies and Lewy neurites3. Recent studies have reported that -synuclein undergoes phase separation to form biomolecular condensates both in vitro and in mammalian cells4-7. -synuclein condensates are thought to contribute to disease through progressive aggregation5,8,9. Here we show that specific PD-associated -synuclein variants fail to form biomolecular condensates. We demonstrate that only two -synuclein variants associated with familial disease, E46K and E83Q, enhance condensate formation in vitro and in cells. However, variants including A30G, G51D, and A53E fail to form or have reduced levels of condensate formation in cells. The same phenotypes are reflected in the budding yeast model showing differential inclusion formation. In iPSC-derived neurons, the propensity of -synuclein variants to undergo VAMP2-mediated phase separation reflects the level of synaptic enrichment. We show that the intrinsic propensity of -synuclein to form condensates and the ability to bind lipid membranes are important to mediate condensate formation in cells. Our results emphasize that -synuclein pathology follows divergent pathways, with both increased and decreased condensate formation contributing to disease. This study establishes biomolecular condensates as a key intermediate in -synuclein dysfunction, providing a novel foundation for translational research.

neuroscience↗

bioRxiv2025

Interpreting biochemical text with language models:a machine learning framework for reaction extraction and cheminformatic validation

Recent advancements in large language models (LLMs) offer new opportunities for automating the manual curation of biochemical reaction databases from scientific literature. In this study, we present an integrated pipeline that enhances LLM-based extraction of enzymatic reactions with machine learning and cheminformatics-informed validation. Using BRENDA-linked PubMed articles, we evaluate GPT-4s ability to extract reactions and infer missing chemical entities in textual descriptions of enzymatic reactions. Extracted reactions are converted to SMILES and InChI notations before being encoded into molecular fingerprint similarity scores and atom mapping metrics. These cheminformatics metrics are then used to train machine learning classifiers that validate GPT extractions. We employ a Positive-Unlabeled learning approach with synthetic invalid reactions to train various classifiers and assess model performances. The best classifier is then benchmarked on GPT extractions. Our findings show that GPT can accurately infer incomplete reactions and cheminformatics tools can serve as effective predictors of reaction validity. This work demonstrates a scalable framework for automated and reliable curation of enzymatic reaction databases, highlighting the potential of combining LLMs with cheminformatics and machine learning for reliable scientific knowledge extraction. Author SummaryCurating databases of biochemical reactions is a time-consuming and manual task, yet it plays a vital role in advancing research in biology and chemistry. Many scientific articles describe important enzymatic reactions, but often do so in incomplete ways--such as mentioning only the starting molecule or the enzyme, and leaving out the rest. In this work, we explore how recent advancements in artificial intelligence, specifically large language models like GPT, can help extract such information automatically from scientific literature. We show that these models can not only find reactions in text, but also infer missing parts of reactions based on the surrounding context. To make sure these inferred reactions are chemically plausible, we use computational chemistry tools that analyze the structure of the molecules involved. We then train a machine learning model to help us automatically detect which reactions are likely to be valid. This combination of tools offers a new way to speed up and improve how biochemical knowledge is extracted from the growing body of scientific literature. Our study suggests that this kind of automation could help scientists keep biological databases up to date and reduce the burden of manual data entry.

bioinformatics↗

bioRxiv2025

Evolution of T cell responses in the tuberculin skin test reveals generalisable Mtb-reactive T cell metaclones.

T cells contribute to immune protection and pathogenesis in tuberculosis, but measurements of polyclonal responses have failed to resolve correlates of outcome. We report the first temporal evaluation of the human in vivo clonal repertoire of Mtb-reactive T cell responses, by T cell receptor (TCR) sequencing at the site of a standardised antigenic challenge. Initial recruitment of non-Mtb reactive T cells is followed by enrichment of Mtb-reactive clones arising from oligoclonal T cell proliferation. We introduce a modular computational pipeline, Metaclonotypist, to sensitively cluster distinct TCRs with shared epitope specificity, which we apply here to establish a catalogue of public Mtb-reactive HLA-restricted T cell metaclones. Although most in vivo Mtb-reactive T cells are private, 10 metaclones were sufficient to identify Mtb-T cell reactivity across our study population (N[≥]128), indicating striking population level immunodominance of specific TCR-peptide interactions that may offer novel approaches to patient stratification and vaccine development.

immunology↗

bioRxiv2024

Multiomics-based assessment of 2D and 3D human iPSC-cardiomyocyte models of insulin resistance demonstrate metabolic and contractile dysfunction that recapitulates diabetic cardiomyopathy.

In type II diabetes (T2DM), the heart is exposed to hyperglycaemia, hyperlipidaemia, and hyperinsulinaemia, leading to insulin resistance and metabolic dysfunction, culminating in diabetic cardiomyopathy (DbCM). Human-centric models of DbCM are needed to provide mechanistic insights and therapeutic targets in a translationally relevant setting. We hypothesised that culturing human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) in an "insulin resistance" (IR) media, and assessing this using a systems biology approach, would offer a comprehensive evaluation of dysregulated pathways, establishing their suitability as a model of DbCM. Culturing hiPSC-CMs in 2D or 3D as engineered heart tissue (EHT) in IR media induced insulin resistance and activated numerous pathways implicated in DbCM, including metabolic remodelling, mitochondrial dysfunction, extracellular matrix remodelling, and endoplasmic reticulum stress. Pathways involved in fatty acid oxidation were upregulated, while those involved in glucose metabolism were downregulated, which was validated using radioisotope flux measurements. Adaptation to hypoxia, a key component of post-ischaemic remodelling, was blunted in the 2D IR hiPSC-CMs. Combining proteomic and transcriptomic analyses in the IR 3D EHT revealed significant enrichment of DbCM pathways, with subnetworks enriched for several metabolic and diabetes-related pathways. Additionally, IR 3D EHT displayed impaired relaxation, mimicking the diastolic dysfunction observed in T2DM patients. In conclusion, culturing hiPSC-CM in 2D or 3D in an IR media activates multiple mechanisms implicated in the development of DbCM, with IR 3D EHT also recapitulating the diastolic dysfunction present in patients with T2DM.

molecular biology↗

bioRxiv2024

The perineurium integrates leptin with its sympathetic outflow to protect against obesity

The regulatory mechanism of leptins afferent action in the brain, constituting a negative feedback loop, is contingent upon the efferent sympathetic innervation of white and brown adipose tissues. Nonetheless, the peripheral regulation governing the relative strengths of the afferent and efferent arms remains ambiguous. Using single-cell RNA sequencing on murine sympathetic ganglia, we identified the unique expression of both the leptin receptor (LepR) and the beta 2 adrenergic receptor (Adrb2) in perineurial cells that form a barrier around sympathetic ganglia and nerve bundles in adipose tissues. We show that LepR+ Sympathetic Perineurial Cells (SPCs) are molecularly similar to endothelial cells and that conditional knockout of Adrb2 in LepR+ SPCs predisposes mice to obesity without affecting food intake. Notably, we found that hyperleptinemia associated with obesity causes apoptosis in SPCs, leading to a significant erosion of the perineurial barrier and concomitant adipose sympathetic neuropathy. We further show that this deleterious effect can be reversed by sympathomimetic beta 2 adrenergic receptor agonism. These results have relevance to human obesity, as we observed a synergistic effect of highly common polymorphisms of LEPR and ADRB2 on the risk of increased BMI in a large European population. We propose that SPCs are the nexus of leptin action by integrating the afferent and efferent arms of the neuroendocrine loop to influence its setpoint.

neuroscience↗

bioRxiv2024

Single-cell transcriptome and T cell receptor profiling of the tuberculin skin test

The tuberculin skin test (TST) is a cutaneous delayed hypersensitivity reaction to antigen from Mycobacterium tuberculosis (Mtb). We provide the first single cell sequencing characterisation of the human TST reaction, based on skin suction blisters induced at the site of the TST on day 2 in 31 individuals. Integrated single cell RNA and TCR sequencing showed the immune response to be dominated by T cells, with smaller populations of NK cells and myeloid cells. T cells comprised CD4, CD8, gamma/delta and NK T cells, with 50% of all T cells identified as cytotoxic and 14% as regulatory. Interferon gamma gene expression was strongest in CD8 T cells, and distinct CD4 T helper lineages could not unambiguously be identified at this time point. Amongst myeloid cells, 63% displayed antimicrobial gene expression and 28% were functionally polarised towards antigen presentation with higher levels of HLA class 2 expression. We derived and validated transcriptional signatures for cell types and cellular functions relevant to the immune landscape of the TST. These data help to improve our understanding of the immune response to Mtb and enable further exploration of bulk transcriptomic data through context-specific cellular deconvolution.

immunology↗

bioRxiv2022

Large clones of pre-existing T cells drive early immunity against SARS-COV-2 and LCMV infection.

We analyzed the dynamics of the earliest T cell response to SARS-COV-2. A wave of TCRs strongly but transiently expand during infection, frequently peaking the same week as the first positive PCR test. These expanding TCR CDR3s were enriched for sequences functionally annotated as SARS-COV-2 specific. Most epitopes recognized by the expanding TCRs were highly conserved between SARS-COV-2 strains, but not with circulating human coronaviruses. Many expanding CDR3s were also present at high precursor frequency in pre-pandemic TCR repertoires. A similar set of early response TCRs specific for lymphocytic choriomeningitis virus epitopes were also found at high frequency in the pre-infection naive repertoire. High frequency naive precursors may allow the T cell response to respond rapidly during the crucial early phases of acute viral infection. One-Sentence SummaryHigh frequency naive precursors underly the rapid T cell response during the crucial early phases of acute viral infection.

immunology↗

bioRxiv2021

Immunoinformatic Approach for the identification of T Cell and B Cell Epitopes in the Surface Glycoprotein and Designing a Potent Multiepitope Vaccine Construct Against SARS-CoV-2 including the new UK variant

The emergence of a novel coronavirus in China in late 2019 has turned into a SARS-CoV-2 pandemic affecting several millions of people worldwide in a short span of time with high fatality. The crisis is further aggravated by the emergence and evolution of new variant SARS-CoV-2 strains in UK during December, 2020 followed by their transmission to other countries. A major concern is that prophylaxis and therapeutics are not available yet to control and prevent the virus which is spreading at an alarming rate, though several vaccine trials are in the final stage. As vaccines are developed through various strategies, their immunogenic potential may drastically vary and thus pose several challenges in offering both arms of immunity such as humoral and cell-mediated immune responses against the virus. In this study, we adopted an immunoinformatics-aided identification of B cell and T cell epitopes in the Spike protein, which is a surface glycoprotein of SARS-CoV-2, for developing a new Multiepitope vaccine construct (MEVC). MEVC has 575 amino acids and comprises adjuvants and various cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes that possess the highest affinity for the respective HLA alleles, assembled and joined by linkers. The computational data suggest that the MEVC is non-toxic, non-allergenic and thermostable with the capability to elicit both humoral and cell-mediated immune responses. The population coverage of various countries affected by COVID-19 with respect to the selected B and T cell epitopes in MEVC was also investigated. Subsequently, the biological activity of MEVC was assessed by bioinformatic tools using the interaction between the vaccine candidate and the innate immune system receptors TLR3 and TLR4. The epitopes of the construct were analyzed with that of the strains belonging to various clades including the new variant UK strain having multiple unique mutations in S protein. Due to the advantageous features, the MEVC can be tested in vitro for more practical validation and the study offers immense scope for developing a potential vaccine candidate against SARS-CoV-2 in view of the public health emergency associated with COVID-19 disease caused by SARS-CoV-2.

bioinformatics↗

bioRxiv2021

A simple, cost-effective and automation-friendly direct PCR approach for bacterial community analysis

Bacterial communities in water, soil, and humans play an essential role in environmental ecology and human health. PCR-based amplicon analysis, such as 16S ribosomal RNA sequencing, is a fundamental tool for quantifying and studying microbial composition, dynamics, and interactions. However, given the complexity of microbial communities, a substantial number of samples becomes necessary to analyses that parse the factors that determine microbial composition. A common bottleneck in performing these kinds of experiments is genomic DNA (gDNA) extraction, which is time-consuming, expensive, and often biased on the types of species. Direct PCR methods are a potentially simpler and more accurate alternative to gDNA extraction methods that do not require the intervening purification step. In this study, we evaluated three variations of direct PCR methods using diverse heterogeneous bacterial cultures, ZymoBIOMICS Microbial Community Standards, and groundwater. By comparing direct PCR methods with DNeasy blood and tissue kits and DNeasy Powersoil kits, we found a specific variant of the direct PCR method exhibits a comparable overall efficiency to the conventional DNeasy Powersoil protocol. We also found the method showed higher efficiency for extracting gDNA from the gram negative strains compared to DNeasy blood and tissue protocol. This direct PCR method is 1600 times cheaper ($0.34 for 96 samples), 10 times simpler (15 min hands-on time for 96 samples) than DNeasy Powersoil protocol. The direct PCR method can also be fully automated, and is compatible with small volume samples, thereby permitting scaling of samples and replicates needed to support high-throughput large-scale bacterial community analysis. IMPORTANCEUnderstanding bacterial interaction and assembling in complex microbial communities using 16S ribosomal RNA sequencing normally requires a large experimental load. However, the current DNA extraction methods including cell disruption and genomic DNA purification are normally biased, costly, time and labor consuming, and not amenable to miniaturization by droplets or 1536 well plates due to the significant DNA loss during purification step for tiny volume and low cell density samples. Direct PCR method could potentially solve these problems. In this study, we demonstrate a direct PCR method which exhibits similar efficiency as the widely used method - DNeasy Powersoil protocol, while 1600 times cheaper and 10 times faster to execute. This simple, cost-effective, and automation friendly direct PCR based 16S ribosomal RNA sequencing method allows us to study the dynamics, microbial interaction and assembly of varying microbial communities in a high throughput fashion.

microbiology↗

bioRxiv2019

Targeting the Pregnane X Receptor Using Microbial Metabolite Mimicry

The human pregnane X receptor (PXR), a master regulator of drug metabolism, has important roles in intestinal homeostasis and abrogating inflammation. Existing PXR ligands have substantial off-target toxicity. Based on prior work that established microbial (indole) metabolites as PXR ligands, we proposed microbial metabolite mimicry as a novel strategy for drug discovery that allows to exploit previously unexplored parts of chemical space. Here we report functionalized indole-derivatives as first-in-class non-cytotoxic PXR agonists, as a proof-of-concept for microbial metabolite mimicry. The lead compound, FKK6, binds directly to PXR protein in solution, induces PXR specific target gene expression in, cells, human organoids, and mice. FKK6 significantly represses pro-inflammatory cytokine production cells and abrogates inflammation in mice expressing the human PXR gene. The development of FKK6 demonstrates for the first time that microbial metabolite mimicry is a viable strategy for drug discovery and opens the door to mine underexploited regions of chemical space.

biochemistry↗

bioRxiv2019

Proposed model of the Dictyostelium cAMP receptors bound to cAMP

3,5-cyclic adenosine monophosphate (cAMP) is well known as a ubiquitous intracellular messenger regulating a diverse array of cellular processes. However, for a group of social amoebae or Dictyostelia undergoing starvation, intracellular cAMP is secreted in a pulsatile manner to their exterior. This then uniquely acts as a first messenger, triggering aggregation of the starving amoebae followed by their developmental progression towards multicellular fruiting bodies formation. Such developmental signalling for extracellularly-acting cAMP is well studied in the popular dictyostelid, Dictyostelium discoideum, and is mediated by a distinct family ( class E) of G protein-coupled receptors (GPCRs) collectively designated as the cAMP receptors (cARs). Whilst the biochemical aspects of these receptors are well characterised, little is known about their overall 3D architecture and structural basis for cAMP recognition and subtype-dependent changes in binding affinity. Using a ligand docking-guided homology modelling approach, we hereby present for the first time, plausible models of active forms of the cARs from D. discoideum. Our models highlight some structural features that may underlie the differential affinities of cAR isoforms for cAMP binding and also suggest few residues that may play important roles for the activation mechanism of this GPCR family.

biochemistry↗

bioRxiv2019

Alpha-Synuclein is a Target of Fic-mediated Adenylylation/AMPylation: Implications for Parkinson’s Disease

During disease, cells experience various stresses that manifest as an accumulation of misfolded proteins and eventually lead to cell death. To combat this stress, cells activate a pathway called UPR (Unfolded Protein Response) that functions to maintain ER (endoplasmic reticulum) homeostasis and determines cell fate. We recently reported a hitherto unknown mechanism of regulating ER stress via a novel post-translational modification (PTM) called Fic-mediated Adenylylation/AMPylation. Specifically, we showed that the human Fic (filamentation induced by cAMP) protein, HYPE/FicD, catalyzes the addition of an AMP (adenosine monophosphate) to the ER chaperone, BiP, to alter the cells UPR-mediated response to misfolded proteins. Here, we report that we have now identified a second target for HYPE - alpha-Synuclein (Syn), a presynaptic protein involved in Parkinsons disease (PD). Aggregated Syn has been shown to induce ER stress and elicit neurotoxicity in PD models. We show that HYPE adenylylates Syn and reduces phenotypes associated with Syn aggregation in vitro, suggesting a possible mechanism by which cells cope with Syn toxicity.\n\nHIGHLIGHTSO_LIAggregated forms of the presynaptic protein Syn cause neurotoxicity and induce ER stress in cellular and animal models of Parkinsons disease.\nC_LIO_LIWe have identified Syn as a novel target for the human Fic protein, HYPE, a key regulator of ER homeostasis.\nC_LIO_LIHYPE adenylylates Syn and reduces the aggregation of recombinant Syn\nC_LIO_LIFic-mediated adenylylation/AMPylation is a possible mechanism by which cells cope with Syn toxicity.\nC_LI\n\nGraphic Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

biochemistry↗

bioRxiv2018

Exploration of inositol 1,4,5-trisphosphate (IP3) regulated dynamics of N-terminal domain of IP3 receptor reveals early phase molecular events during receptor activation

Inositol 1, 4, 5-trisphosphate (IP3) binding at the N-terminus (NT) of IP3 receptor (IP3R) allosterically triggers the opening of a Ca2+-conducting pore located ~ 100 [A] away from the IP3-binding core (IBC). However, the precise mechanism of IP3 binding and correlated domain dynamics in the NT that are central to the IP3R activation, remains unknown. Our all-atom molecular dynamics (MD) simulations recapitulate the characteristic twist motion of the suppresser domain (SD) and reveal correlated clam closure dynamics of IBC with IP3-binding, complementing existing suggestions on IP3R activation mechanism. Our study further reveals the existence of inter-domain dynamic correlation in the NT and establishes the SD to be critical for the conformational dynamics of IBC. Also, a tripartite interaction involving Glu283-Arg54-Asp444 at the SD - IBC interface seemed critical for IP3R activation. Intriguingly, during the sub-microsecond long simulation, we observed Arg269 undergoing an SD-dependent flipping of hydrogen bonding between the first and fifth phosphate groups of IP3. This seems to play a major role in determining the IP3 binding affinity of IBC in the presence/absence of the SD. Our study thus provides atomistic details of early molecular events occurring within the NT during and following IP3 binding that lead to channel gating.

bioinformatics↗

bioRxiv2018

Metformin Intervention Prevents Cardiac Dysfunction in a Murine Model of Adult Congenital Heart Disease

Congenital heart disease (CHD) is the most frequent birth defect worldwide and the number of adult patients with CHD, now referred to as ACHD, is increasing. However the mechanisms whereby ACHD predisposes patients to heart dysfunction are still unclear. ACHD is strongly associated with metabolic syndrome, but how ACHD interacts with poor modern lifestyle choices and other comorbidities, such as hypertension, obesity and diabetes, is mostly unknown. Using a genetic mouse model of ACHD we showed that ACHD mice placed under metabolic stress (high fat diet) displayed decreased heart function. Comprehensive physiological, biochemical and molecular analysis showed that ACHD hearts exhibited early changes in energy metabolism that preceded cardiac dysfunction. Restoration of metabolic balance by metformin prevented the development of heart dysfunction in ACHD mice. This study reveals that early metabolic impairment reinforces heart dysfunction in ACHD predisposed individuals and diet or pharmacological interventions can be used to modulate heart function and attenuate heart failure and may be an important avenue for intervention in ACHD.

genetics↗