Biology subjects

Thakur, A.

Publications and source records attributed to Thakur, A..

At least 19 recordsLinked to original sources

bioRxiv2026

MXene Protein Corona Interfaces for Molecular Profiling of Alzheimers Disease

The protein corona (PC) that forms on the surface of nanomaterials upon contact with biological fluids provides a molecular snapshot of the hosts physiological and pathological state. Here, we investigate two-dimensional (2D) titanium carbide (Ti3C2Tx) MXene nanosheets as nanobiointerfaces for capturing Alzheimers disease (AD)-associated plasma protein signatures. Ti3C2Tx MXene flakes were incubated with plasma from clinically diagnosed AD patients and age-matched healthy controls (HC), leading to the formation of Ti3C2Tx MXene-PC complexes. Physicochemical characterization using dynamic light scattering, zeta potential analysis, and transmission electron microscopy revealed disease-dependent changes in hydrodynamic size, surface charge, and PC profile. Proteomic analysis of the isolated PC layers quantified 1,611 proteins without prior fractionation, demonstrating effective enrichment of low-abundance plasma components. Principal component analysis (PCA) revealed consistent separation between AD- and HC-derived Ti3C2Tx MXene-PC proteomes despite inter-individual heterogeneity. Differential abundance analysis identified selective enrichment of heterogeneous nuclear ribonucleoproteins (hnRNPs), annexins, and inflammatory mediators in AD-derived PC, implicating dysregulated RNA metabolism, membrane stress responses, and immune activation, hallmark processes in AD pathology. Our findings demonstrate that Ti3C2Tx MXene-PC interfaces act as selective molecular filters that reshape the detectable plasma proteome, enabling disease-associated molecular phenotyping and establishing a versatile nanointerface-driven framework for uncovering AD-related plasma signatures, providing a foundation for future translational diagnostic development.

biophysics↗

bioRxiv2026

Coordinated subpocket engagement underlies nitazene potency at the μ-opioid receptor.

Nitazenes are emerging synthetic opioids that exhibit exceptionally high potency at the {micro}-opioid receptor (MOR) and contribute to rising overdose fatalities worldwide. Despite extensive in vitro profiling, the structural determinants underlying their structure-activity relationships (SARs) remain unresolved. Here, we combine functional profiling with quantum mechanical calculations and molecular dynamics (MD) simulations to establish a MOR structure-based SAR for nitazenes. Across functional assays, systematic variation at the R1, R2, and R3 positions revealed non-additive effects on potency and identified optimal R1 chain length, R2 N-desethylation, and retention of the 5-nitro group as key determinants of high MOR potency. Consistent with this framework, N-desethyl isotonitazene emerged as the most potent analogue. Structural analysis of the cryo-EM MOR-Gi-fluornitrazene complex, together with MD simulations of multiple nitazene analogues, revealed a conserved trivalent binding architecture in which each substituent engages distinct subpockets. N-desethylation at R2 increases the positive electrostatic surface at the protonated amine, reduces steric constraints near transmembrane helix (TM) 7, strengthens R3 interactions, and allosterically modulates R1 engagement in a substituent-dependent manner. Additionally, optimal R1 chain length and shape stabilize the TM5-TM6 interface and influence activation-relevant TM6 dynamics, defining a unified SAR at R1 across nitazene and fentanyl scaffolds. Together, these findings indicate that nitazene potency reflects substituent-dependent coupling among R1, R2, and R3 within the MOR binding pocket, with R3 engagement distinguishing nitazenes from fentanyl. This framework establishes a coherent structural model of nitazene-MOR recognition that accounts for their unusually high potency and efficacy.

molecular biology↗

bioRxiv2026

A translational checkpoint couples proline sensing to mitochondrial proline catabolism in Candida glabrata

Proline catabolism represents a central metabolic and regulatory hub integrating nutrient sensing, stress adaptation, and energy production across diverse organisms. Despite its biological importance, the regulatory mechanisms controlling proline catabolism remain poorly understood in eukaryotic microbes. Here, we describe the transcriptional and translational coordination to catabolize the proline to maintain the cellular homeostasis under stress in the human fungal pathogen Candida glabrata. We identified proline utilisation trigger global translation repression to activates the stress-sensing kinase Gcn2, which phosphorylates eIF2, thereby promoting the activation of the transcription factor Gcn4. Activated Gcn4 upregulates the transcription factor Put3 and the proline transporter Put4. Put3 orchestrates expression of the mitochondrial catabolic enzymes Put1 and Put2, ensuring efficient proline utilization, mitochondrial function, and redox balance. Genetic disruption of PUT3 abolishes proline utilization, impairs mitochondrial function, and severely compromises cellular fitness. Importantly, Put3-mediated proline catabolism is also critical for C. glabrata survival within macrophages and for virulence in systemic infection models. These findings reveal a mechanistic link between proline catabolism, translational regulation, and amino acid sensing in C. glabrata. We propose a regulatory cascade wherein Gcn2-Gcn4-Put3 signaling aligns translational reprogramming with metabolic demands to optimize proline utilization. Thus, this study establishes proline catabolism as a signaling-driven adaptive mechanism essential for fungal metabolism and persistence, rather than merely a nutritional pathway. AUTHOR SUMMARYProline is a versatile amino acid that is essential for cellular metabolism, signaling, stress adaptation, and redox equilibrium. Proline catabolism has been implicated in cancer biology and is increasingly recognized as a key determinant of virulence in diverse pathogens. Although the enzymatic processes of proline use are well characterized, the regulatory mechanisms that sense proline availability and coordinate its metabolic integration remain poorly understood. Here, we identify a hitherto unknown regulatory axis linking proline catabolism to translational reprogramming in Candida glabrata, which seems to be similarly present in numerous fungi. We demonstrate that proline utilization triggers global translational repression via Gcn2-dependent phosphorylation of eIF2, thereby activating the transcription factor Gcn4. Gcn4 is essential for proline utilization, as it controls the expression of PUT3 and PUT4. Notably, PUT3 has no known human counterpart. Our findings establish proline as a metabolic signal that couples translational control to virulence, revealing new opportunities for antifungal intervention.

microbiology↗

bioRxiv2025

Multiple Allosteric Sites Allow for Synergistic Enhancement of GPCR Signaling

Allosteric modulation of G protein-coupled receptors (GPCRs) is an emerging therapeutic paradigm that has proven effective, yet the cooperative action of multiple modulators remains unexplored. Here, we reveal how positive allosteric modulators (PAMs) synergistically enable extraordinary signal amplification through the D1 dopamine receptor (D1R). We developed UNC9815 and UNC10062 as enhanced D1R PAMs from the parent compound MLS6585, and then employed cryo-electron microscopy to reveal concurrent occupancy of three distinct allosteric sites by PAMs of different scaffolds, including LY3154207, BMS-A1, and our UNC compounds. Remarkably, we discovered two adjacent allosteric pockets at the transmembrane helix (TM) 1-7 interface: BMS-A1 occupies an intracellular site promoting activation through TM7 conformational shifts, while the UNC compounds complementarily stabilize the extracellular side of the interface. When combined with LY3154207, this cooperative architecture enhances dopamine potency by more than 1,000-fold. These findings elucidate the first structural blueprint for multi-site GPCR cooperativity, unlocking transformative therapeutic strategies inaccessible to orthosteric and single- site allosteric drugs.

molecular biology↗

bioRxiv2025

Using AlphaFold2 to Predict the Conformations of Side Chains in Folded Proteins

AlphaFold has revolutionized protein structure prediction by accurately creating 3D structures from just the amino acid sequence. However, even with extensive research validating its overall accuracy, a key question remains: Can AlphaFold predict the conformation of individual amino acid residue side chains within a folded protein? This is important for the field of molecular modeling, particularly when predicting the effects of mutations on protein stability and ligand binding. AlphaFold generates a set of atomic coordinates not just for the mutated side chain but also for potential rearrangements across the entire protein structure. In this study we investigate the ability of ColabFold, an online implementation of AlphaFold2 (AF2), to predict the conformations of residue side chains in folded proteins. We find that over a set of 10 benchmark proteins, the side chain conformation prediction error of ColabFold is on average [~]14% for {chi}1 dihedral angles, and increases to [~]48% for {chi}3 dihedral angles. The prediction error is smaller for non-polar side chains and is somewhat improved using structural templates. ColabFold demonstrates a bias towards the most prevalent rotamer states in the protein data bank (PDB), potentially limiting its ability to capture rare side chain conformations effectively. As an application of AlphaFold to explore the structural consequences of strongly cooperative mutations on side chain rearrangements, we employ a Potts sequence-based statistical energy model to perform large scale mutational scans of two proteins ABL1 and PIM1 kinase, searching for the most strongly cooperative mutational pairs, and then use ColabFold to predict the structural signatures of this cooperativity on the interacting side chains. Our results demonstrate that integration of the sequence-based Potts model with AlphaFold into a single pipeline provides a new tool that can be used to explore the fundamental relationship between protein mutations, cooperative changes in structure, and fitness.

biophysics↗

bioRxiv2025

From discovery to translation: Endogenous substrates of OAT1 and OAT3 as clinical biomarkers for renal secretory function

The recent ICH M12 guidance on Drug Interaction Studies encourages the use of alternate approaches for predicting drug-drug interaction (DDI) potential of new chemical entities. One approach involves biomarkers, which are endogenous substrates of drug metabolizing enzymes and transporters (DMET) and can be used to assess the inhibitory potential of new chemical entities during Phase 1 clinical studies. Thus, biomarkers could potentially eliminate the need for dedicated DDI studies with exogenous probe substrates. Metabolomics, in conjunction with in vitro and/or in vivo preclinical models or clinical studies, can be used for biomarker discovery. We developed and applied a novel metabolomics-based DMET biomarker discovery (MDBD) approach to identify and qualify biomarkers of renal organic anion transporter 1 (OAT1) and OAT3. Untargeted metabolomics of pooled plasma and urine samples from a pharmacokinetic DDI study using the OAT1/3 inhibitor, probenecid, yielded 153 features identified as putative OAT1/3 biomarkers. Subsequently, in vitro transporter uptake assays using processed urine samples confirmed 57 of these features as OAT1 and/or OAT3 substrates. Finally, 23 features were clinically validated as OAT1/3 biomarkers through a detailed pharmacokinetic analysis (0-24 h) of plasma and urine samples. These biomarkers, either alone or as part of a panel, can predict OAT1/3-mediated DDIs and interindividual variability in the renal secretory clearance of organic anions across different populations, thereby enabling translational utility in clinical settings. The novel MDBD approach can be extended to discover biomarkers of other transporters and enzymes. SUMMARYUsing clinical and mechanistic in vitro approaches, 23 endogenous substrates of OAT1/3 were identified as potential clinical biomarkers of renal secretary elimination of organic anions.

pharmacology and toxicology↗

bioRxiv2025

LAG3+ CD8+ T cell Subset Boosts Bispecific Antibody Armed Activated T Cell Cytotoxicity Directed at Hormone Receptor+ Breast Cancers

Tumor clearance by T cells is impaired by insufficient tumor antigen recognition, insufficient tumor infiltration, and the immunosuppressive tumor microenvironment (TME). Although targeted T cell therapy circumvents failures in tumor antigen recognition, suppression by the TME and failure to infiltrate the tumor can hinder tumor clearance. Checkpoint inhibitors (CPI) promise to reverse T cell suppression and can be combined with bispecific antibody armed T cell (BATs) therapy to improve clinical outcomes. We hypothesize that adoptively transferred T cell function may be improved by the addition of CPI if the inhibitory pathway is functionally active. This study develops a kinetic-dynamic model of killing of hormone receptor-positive (HR+) breast cancer cells mediated by BATs using single-cell transcriptomic and temporal protein data to identify T cell phenotypes and quantify inhibitory receptor expression. LAG3, PD-1, and TIGIT were identified as inhibitory receptors expressed by cytotoxic effector CD8 BATs upon exposure to HR+ breast cancer cell lines. These data were combined with real-time tumor cytotoxicity data in a multivariate statistical analysis framework to predict the relevant contributions of T cells expressing each receptor to tumor reduction. A mechanistic kinetic-dynamic mathematical model was developed and parametrized using protein expression and cytotoxicity data for in silico validation of the findings of the multivariate statistical analysis. The model corroborated the predictions of the multivariate statistical analysis which identified LAG3+ BATs as the primary effectors, while TIGIT expression dampened cytotoxic function. These results inform CPI selection for BATs combination therapy and provide a framework to maximize BATs anti-tumor function. What is already known on this topicBispecific antibody armed T cell (BATs) therapies are adoptive T cell therapies that can effectively reroute T cell cytotoxicity toward cancerous cells, but lack consistent and durable anti-tumor responses. Checkpoint proteins expressed on the surface of activated T cells dampen immune responses and can be overstimulated in solid tumors to hamper tumor clearance by T cells. Checkpoint inhibitor drugs can improve T cell anti-tumor response by blocking checkpoint protein signaling but are only effective if the targeted checkpoint protein is expressed on the T cell and activated in the tumor microenvironment, highlighting an opportunity to enhance BAT efficacy by combining treatment with synergistic CPI. What this study addsThis study characterizes dynamic, time-resolved patterns in checkpoint protein expression by breast cancer-targeting adoptive T cells and predicts the significance of high-prevalence checkpoint proteins on T cell function. It also demonstrates the use of multivariate statistic and mathematical modeling toward rational design of targets and timing strategies for synergistic combination therapies. How this study might affect research, practice, or policyThe output of this study provides justification for therapeutic strategies combining adoptive T cell therapies with checkpoint inhibitor drugs targeting TIGIT and LAG3 as a means of improving patient responses in HER2-/HR+ breast cancers.

immunology↗

bioRxiv2024

Quantitative contributions of hepatic and renal organic cation transporters to the clinical pharmacokinetic cimetidine-metformin interaction

The widely prescribed oral anti-diabetic drug metformin is eliminated unchanged in the urine primarily through active tubular secretion. This process is mediated by organic cation transporter 2 (OCT2), an uptake transporter expressed on the basolateral membrane of renal proximal tubule cells. Metformin uptake into the liver, the site of action, is mediated by OCT1, which is expressed on the sinusoidal membrane of hepatocytes. Sixteen healthy adults participated in a clinical pharmacokinetic drug-drug interaction study in which they were orally administered metformin (50 mg) as a dual OCT1/2 substrate alone (baseline) and with cimetidine (400 mg) as an OCT inhibitor. Relative to baseline, metformin systemic plasma exposure increased by 24% (p<0.05) in the presence of cimetidine, which was accompanied by a disproportional decrease (8%) in metformin renal clearance (p=0.005). Genetic variants of OCT1 and OCT2 moderately impacted the significance and magnitude of the interaction. Collectively, we hypothesized that the cimetidine-metformin interaction involves inhibition of hepatic OCT1 as well as renal OCT2. We tested this hypothesis by developing a physiologically based pharmacokinetic (PBPK) model and assessing potential OCT biomarkers in plasma and urine to gain mechanistic insight into the transporters involved in this interaction. The PBPK model predicted that cimetidine primarily inhibits hepatic OCT1 and, to a lesser extent, renal OCT2. The unchanged renal clearance of potential OCT2 biomarkers following cimetidine exposure supports a minimal role for renal OCT2 in this interaction.

pharmacology and toxicology↗

bioRxiv2024

Evolutionary sequence and structural basis for the distinct conformational landscapes of Tyr and Ser/Thr kinases

Protein kinases are molecular machines with rich sequence variation that distinguishes the two main evolutionary branches - tyrosine kinases (TKs) from serine/threonine kinases (STKs). Using a sequence co-variation Potts statistical energy model we previously concluded that TK catalytic domains are more likely than STKs to adopt an inactive conformation with the activation loop in an autoinhibitory "folded" conformation, due to intrinsic sequence effects. Here we investigated the structural basis for this phenomenon by integrating the sequence-based model with structure-based molecular dynamics (MD) to determine the effects of mutations on the free energy difference between active and inactive conformations, using a novel thermodynamic cycle involving many (n=108) protein-mutation free energy perturbation (FEP) simulations in the active and inactive conformations. The sequence and structure-based results are consistent and support the hypothesis that the inactive conformation "DFG-out Activation Loop Folded", is a functional regulatory state that has been stabilized in TKs relative to STKs over the course of their evolution via the accumulation of residue substitutions in the activation loop and catalytic loop that facilitate distinct substrate binding modes in trans and additional modes of regulation in cis for TKs.

biophysics↗

bioRxiv2023

FORMATION OF MALIGNANT, METASTATIC SMALL CELL LUNG CANCERS THROUGH OVERPRODUCTION OF cMYC PROTEIN IN TP53 AND RB1 DEPLETED PULMONARY NEUROENDOCRINE CELLS DERIVED FROM HUMAN EMBRYONIC STEM CELLS

We recently described our initial efforts to develop a model for small cell lung cancer (SCLC) derived from human embryonic stem cells (hESCs) that were differentiated to form pulmonary neuroendocrine cells (PNECs), a putative cell of origin for neuroendocrine-positive SCLC. Although reduced expression of the tumor suppressor genes TP53 and RB1 allowed the induced PNECs to form subcutaneous growths in immune-deficient mice, the tumors did not display the aggressive characteristics of SCLC seen in human patients. Here we report that the additional, doxycycline-regulated expression of a transgene encoding wild-type or mutant cMYC protein promotes rapid growth, invasion, and metastasis of these hESC-derived cells after injection into the renal capsule. Similar to others, we find that the addition of cMYC encourages the formation of the SCLC-N subtype, marked by high levels of NEUROD1 RNA. Using paired primary and metastatic samples for RNA sequencing, we observe that the subtype of SCLC does not change upon metastatic spread and that production of NEUROD1 is maintained. We also describe histological features of these malignant, SCLC-like tumors derived from hESCs and discuss potential uses of this model in efforts to control and better understand this recalcitrant neoplasm.

cancer biology↗

bioRxiv2023

HYENA detects non-coding genes activated by distal enhancers in cancer

Somatic structural variations (SVs) in cancer can shuffle DNA content in the genome, relocate regulatory elements, and alter genome organization. Enhancer hijacking occurs when SVs relocate distal enhancers to activate proto-oncogenes. However, most enhancer hijacking studies have only focused on protein-coding genes. Here, we develop a computational algorithm "HYENA" to identify candidate oncogenes (both protein-coding and non-coding) activated by enhancer hijacking based on tumor whole-genome and transcriptome sequencing data. HYENA detects genes whose elevated expression is associated with somatic SVs by using a rank-based regression model. We systematically analyze 1,146 tumors across 25 types of adult tumors and identify a total of 108 candidate oncogenes including many non-coding genes. A long non-coding RNA TOB1-AS1 is activated by various types of SVs in 10% of pancreatic cancers through altered 3-dimensional genome structure. We find that high expression of TOB1-AS1 can promote cell invasion and metastasis. Our study highlights the contribution of genetic alterations in non-coding regions to tumorigenesis and tumor progression.

cancer biology↗

bioRxiv2022

PIC50: An open source tool for interconversion of PIC50 values and IC50 for efficient data representation and analysis

Half-maximal inhibitory concentration (IC50) is used to determine the potency of a drug against a variety of enzymes/ biological targets associated with the pathogenesis of multiple disorders. The IC50 values can be depicted in multiple ways, which makes it difficult to analyze the results presented in different concentrations. Representing data in the form of PIC50 values depicting the IC50 values as the negative logarithm of IC50 in molar concentration is considered to be a better approach as it not only makes data easily understandable but also eliminates the possibility of errors in data representation and reproducibility. Considering the importance of data representation for a better understanding of data and comparing efficacy and potency of the drugs, besides, the significance of PIC50 value in the field of CADD, we found that at present there is no single open-source software available to convert the IC50 values to PIC50 values and vice versa from millimolar to picomolar range. Therefore, in the present study, we develop a tool that could help researchers to interconvert IC50 values and PIC50 values in a reliable way to eliminate the possibility of errors. We validated our tool through three case studies where the data generated by our tool was found to be 100% accurate. Moreover, we present a case where data was published in literature with errors in calculated PIC50 values and demonstrated the importance and reliability of our tool.

bioinformatics↗

bioRxiv2022

2D-QSAR and Molecular Docking based virtual screening of the herbal molecules against Alzheimers Disorder: An approach to predict CNS activity

Acetylcholinesterase (AChE) is one of the key enzyme targets that have been used clinically for the management of Alzheimers Disorder (AD). Numerous reports in the literature predict and demonstrate in-vitro, and in-silico anticholinergic activity of synthetic and herbal molecules, however, the majority of them failed to reproduce the results in preclinical or clinical settings. To address these issues, we developed a 2D-QSAR model that could not only efficiently predict the AChE inhibitory activity of herbal molecules but also predicted their potential to cross BBB to exert their beneficial effects during AD. Applying this model, virtual screening of the herbal molecules was performed and amentoflavone, asiaticoside, astaxanthin, bahouside, biapigenin, glycyrrhizin, hyperforin, hypericin, and tocopherol were predicted as the most promising herbal molecules for inhibiting AChE. Results were validated through molecular docking studies against human AChE (PDB ID: 4EY7). To determine whether or not these molecules can cross BBB to inhibit AChE within the CNS for being beneficial for the management of AD, we determined a CNS PPO score, which was found in the range of 1 to 3.76. Overall, the best results were observed for amentoflavone and our results demonstrated a PIC50 value of 7.377 nM, molecular docking score of -11.5 kcal/mol, and CNS MPO score of 3.76. In conclusion, we successfully developed a reliable and efficient 2D-QSAR model and predicted amentoflavone to be the most promising molecule that could inhibit human AChE enzyme within the CNS and could prove beneficial for the management of AD.

bioinformatics↗

bioRxiv2022

The protozoan commensal Tritrichomonas musculis is a natural adjuvant for mucosal IgA.

Immunoglobulin(Ig) A antibodies are the most abundant antibodies supporting mucosal immune homeostasis and host-microbiota interactions. Driven by gut commensal microbes, IgA-secreting plasma cells (PC) differentiate through T cell-dependent (Td) or T cell independent (Ti) mechanisms. While commensal bacteria within the microbiota are known for their ability to promote IgA, the role of non-bacterial commensal microbes on the induction of IgA remains elusive. Here, we demonstrate that permanent colonization with the protozoan commensal Tritrichomonas musculis (T.mu) promotes T-cell dependent, IgA class-switch recombination and intestinal accumulation of IgA-secreting PC. T.mu colonization specifically drives the expansion of T follicular helper cells and a unique ICOS+ non-Tfh cell population, accompanied by an increase in germinal center B cells. Blockade of ICOS:ICOSL co-stimulation or MHCII-expression on B cells are central for the induction of IgA following colonization by T.mu, implicating a previously underappreciated mode of IgA induction following protozoan commensal colonization. Finally, the commensal T.mu further improves the induction of IgA-secreting plasma cells and their peripheral dissemination, even against non-protozoan, orally ingested antigens, identifying T.mu as natural adjuvant for IgA. Collectively, these findings propose a previously unknown, protozoa-driven mode of IgA induction that supports intestinal immune homeostasis even against non-microbial antigens.

immunology↗

bioRxiv2022

Evolutionary Divergence in the Conformational Landscapes of Tyrosine vs Serine/Threonine Kinases

Inactive conformations of protein kinase catalytic domains where the DFG motif has a "DFG-out" orientation and the activation loop is folded present a druggable binding pocket that is targeted by FDA-approved "type-II inhibitors" in the treatment of cancers. Tyrosine Kinases (TKs) typically show strong binding affinity with a wide spectrum of type-II inhibitors while Serine/Threonine Kinases (STKs) usually bind more weakly which we suggest here is due to differences in the folded to extended conformational equilibrium of the activation loop between TKs vs. STKs. To investigate this, we use sequence covariation analysis with a Potts Hamiltonian statistical energy model to guide absolute binding free-energy molecular dynamics simulations of 74 protein-ligand complexes. Using the calculated binding free energies together with experimental values, we estimated free-energy costs for the large-scale ([~]17-20[A]) conformational change of the activation loop by an indirect approach, circumventing the very challenging problem of simulating the conformational change directly. We also used the Potts statistical potential to thread large sequence ensembles over active and inactive kinase states. The structure-based and sequence-based analyses are consistent; together they suggest TKs evolved to have free-energy penalties for the classical "folded activation loop" DFG-out conformation relative to the active conformation that is, on average, 4-6 kcal/mol smaller than the corresponding values for STKs. Potts statistical energy analysis suggests a molecular basis for this observation, wherein the activation loops of TKs are more weakly "anchored" against the catalytic loop motif in the active conformation, and form more stable substrate-mimicking interactions in the inactive conformation. These results provide insights into the molecular basis for the divergent functional properties of TKs and STKs, and pharmacological implications for the target selectivity of type-II inhibitors.

biophysics↗

bioRxiv2022

GNNQQNY: Methodology for biophysical and structural understanding of aggregation

GNNQQNY sequence offers crucial information about the formation and structure of an amyloid fibril. In this study, we demonstrate a reproducible solubilisation protocol where the reduction of pH to 2.0 resulted in the generation of GNNQQNY monomers. The subsequent ultracentrifugation step removes the residual insoluble peptide from the homogeneous solution. This procedure ensures and allows the peptides to remain monomers till their aggregation is triggered by adjusting the pH to 7.2. The aggregation kinetics analysis showed a distinct lag-phase that is concentration-dependent, indicating nucleation-dependent aggregation kinetics. Nucleation kinetics analysis suggested a critical nucleus of size [~]7 monomers at physiological conditions. The formed nucleus acts as a template for further self-assembly leading to the formation of highly ordered amyloid fibrils. These findings suggest that the proposed solubilisation protocol provides the basis for understanding the kinetics and thermodynamics of amyloid nucleation and elongation in GNNQQNY sequences. This procedure can also be used for solubilising such small amyloidogenic sequences for their biophysical studies.

biophysics↗

bioRxiv2021

Protein reservoirs of seeds are composites of amyloid and amyloid-like structures

The seed protein functions and their localization in seed storage protein bodies (SSPB) are known for several decades. However, the structural and functional complexity of these SSPB is not known. Interestingly, the plant SSPB is morphologically similar to the amyloid-containing protein bodies found in other organisms and individual SSPB proteins were previously shown to form fibrillar structures under non-native conditions in-vitro. Therefore, we hypothesized that the seed storage protein bodies (SSPB) may have similar structures in-vivo for controlling seed functions. Since comprehensive in-vivo characterization of the SSPB and the structure-function relationship remains unexplored, we show firstly that wheat, barley, chickpea, and mungbean SSPB exhibit a speckled-pattern of amyloids interspersed in an amyloid-like matrix in-situ, suggesting their composite nature. This is confirmed by multiple amyloid-specific probes, biophysical characterization, electron-microscopy, peptide-fingerprinting, and differential degradation during germination. Moreover, the role of amyloid composites in seed germination is proved by the effect of signalling molecules and their correlation to germination parameters, using in-situ seed sections, ex-vivo protoplasts and in-vitro SSPB. These results would lay down foundation for understanding the amyloid composite structure during SSPB biogenesis and their structure-function evolution. It would further facilitate the exploration of molecular and atomic-level structural details of SSPB amyloids. SummaryO_ST_ABSRationaleC_ST_ABSThe function of plant seed storage protein bodies (SSPB) in germination is known for decades. SSPB have aggregated and electron-rich morphology. However their structural complexity remains elusive. Based on their morphological similarity to amyloid-containing protein-bodies of other organisms, and amyloid formation by some plant proteins under non-native conditions, we hypothesized that SSPB might contain in-vivo amyloid structures for modulating seed functions. MethodsTo unambiguously identify seed amyloids in the presence of complex carbohydrate-structures of plant tissues, multi-spectral methods were used including amyloid-staining probes, high-resolution-transmission-electron-microscopy, x-ray diffraction and infra-red-spectroscopy. SSPB amyloids role in germination was shown using amyloid probes, MS/MS analysis, and plant hormones/proteases in-situ seed-sections and ex-vivo protoplasts. Key resultsThe SSPB exhibit a composite structure of amyloid, amyloid-like aggregates and soluble proteins. During germination phases, the amyloids degrade slowly compared to the amyloid-like structures. Inhibition of amyloid degradation results in lower germination-index, confirming amyloids role in germination and seedling-growth. ConclusionThe study for the first time illustrates the presence of composite amyloid structures in-vivo in plant seeds and determines their function in seed germination and seedling-growth. It would open original research questions for decrypting composite amyloid structure formation during SSPB biogenesis and their evolutionary advancement across plant species.

plant biology↗

bioRxiv2020

SOX9 is sufficient to drive endothelial cells towards a mesenchymal fate by altering the chromatin landscape.

The transcription factor SOX9 is expressed in multiple tissues during embryogenesis and directs developmental processes. SOX9 is activated upon endothelial-to-mesenchymal transition (EndMT) in the developing heart, but its role in regulating this process is less clear. Using human umbilical vein endothelial cells as an EndMT model, we show that SOX9 expression alone is sufficient to activate mesenchymal enhancers and steer endothelial cells towards a mesenchymal fate. By genome-wide mapping of the chromatin landscape, we show that SOX9 acts as a pioneer transcription factor, having the ability to open chromatin and lead to deposition of active histone marks at a specific subset of previously silent enhancers, guided by SOX motifs and H2A.Z enrichment. This leads to a switch in enhancer activity states resulting in activation of mesenchymal genes and concurrent suppression of endothelial genes to drive EndMT. Moreover, we show that SOX9 chromatin binding is dynamic, but induces stable changes in the chromatin landscape. Our data also show widespread SOX9 chromatin scanning in silent chromatin that is not associated with SOX motifs or H2A.Z enrichment. Our study highlights the crucial developmental role of SOX9 and provides new insight into key molecular functions of SOX9 in the chromatin landscape and mechanisms of EndMT. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/293993v2_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1248576org.highwire.dtl.DTLVardef@b6420forg.highwire.dtl.DTLVardef@1aaffc5org.highwire.dtl.DTLVardef@17de585_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗