Biology subjects

Kumar, R.

Publications and source records attributed to Kumar, R..

At least 163 records · Page 9Linked to original sources

bioRxiv2023

A bovine pulmosphere model and multiomics analyses identify a signature of early host response to Mycobacterium tuberculosis infection

Interactions between the tubercle bacilli and lung cells during the early stages of tuberculosis (TB) are crucial for disease outcomes. Conventional 2D cell culture inadequately replicates the multicellular complexity of lungs. We introduce a 3D pulmosphere model for Mycobacterium tuberculosis infection in bovine systems, demonstrating through comprehensive transcriptome and proteome analyses that these 3D structures closely replicate the diverse cell populations and abundant extracellular matrix proteins, emphasizing their similarity to the in vivo pulmonary environment. While both avirulent BCG and virulent M. tuberculosis-infected pulmospheres exhibit commonalities in the upregulation of several host signaling pathways, distinct features such as upregulation of ECM receptors, neutrophil chemotaxis, interferon signaling, and RIG-1 signaling pathways characterize the unique early response to virulent M. tuberculosis. Moreover, a signature of seven genes/proteins, including IRF1, CCL5, CXCL8, CXCL10, ICAM1, COL17A1, and CFB, emerges as indicative of the early host response to M. tuberculosis infection. Overall, this study presents a superior ex vivo multicellular bovine pulmosphere TB model, with implications for discovering disease biomarkers, enabling high-throughput drug screening, and improving TB control strategies.

systems biology↗

bioRxiv2023

Machine Learning Elucidates Design Features of Plasmid DNA Lipid Nanoparticles for Cell Type-Preferential Transfection

For cell and gene therapies to become more broadly accessible, it is critical to develop and optimize non-viral cell type-preferential gene carriers such as lipid nanoparticles (LNPs). Despite the effectiveness of high throughput screening (HTS) approaches in expediting LNP discovery, they are often costly, labor-intensive, and often do not provide actionable LNP design rules that focus screening efforts on the most relevant chemical and formulation parameters. Here we employed a machine learning (ML) workflow using well-curated plasmid DNA LNP transfection datasets across six cell types to maximize chemical insights from HTS studies and has achieved predictions with 5-9% error on average depending on cell type. By applying Shapley additive explanations to our ML models, we unveiled composition-function relationships dictating cell type-preferential LNP transfection efficiency. Notably, we identified consistent LNP composition parameters that enhance in vitro transfection efficiency across diverse cell types, such as ionizable to helper lipid ratios near 1:1 or 10:1 and the incorporation of cationic/zwitterionic helper lipids. In addition, several parameters were found to modulate cell type-preferentiality, including the ionizable and helper lipid total molar percentage, N/P ratio, cholesterol to PEGylated lipid ratio, and the chemical identity of the helper lipid. This study leverages HTS of compositionally diverse LNP libraries and ML analysis to understand the interactions between lipid components in LNP formulations; and offers fundamental insights that contribute to the establishment of unique sets of LNP compositions tailored for cell type-preferential transfection.

bioengineering↗

bioRxiv2023

Lack of Purple Acid Phosphatase SlPAP26b compromises the phosphorous starvation response in tomato independent of SlPHR1 and SlPHL1

The scarcity of soil phosphorus (P), an essential macronutrient, often limits plant growth and development. Enhanced secretion of intracellular and secretory acid phosphatases is essential to maintain cellular inorganic P (Pi) homeostasis in plants. Herein, using transcriptomics and proteomics approach, we observed upregulation of several purple acid phosphatases (PAPs), including SlPAP1, SlPAP10b, SlPAP12, SlPAP15, SlPAP17b, SlPAP26a, and SlPAP26b in Pi-deficient tomato seedlings. Higher transcript levels of SlPAP17b and SlPAP26b in the older senescing leaves than the younger leaves indicated active involvement of these PAPs in Pi remobilization. Subsequent detailed characterization of SlPAP17b, SlPAP26a, and SlPAP26b revealed a prominent role of SlPAP26b in Pi homeostasis. Silencing of SlPAP26b led to an exacerbated P starvation response as these plants exhibited smaller shoots, lower soluble Pi, total P levels, and higher sucrose than their EV controls under Pi deprivation. SlPAP26b-silenced plants also showed misregulation of P starvation inducible genes such as phosphate transporters and glycerolipid remodellers, even under Pi-sufficient conditions. Whereas SlPAP26b levels were induced by external sucrose, its expression was found to be independent of the Myb class master regulators of P starvation response, SlPHR1 and SlPHL1. Altogether, this study identifies a prominent role of SlPAP26b in the Pi compensation network in tomato seedlings.

plant biology↗

bioRxiv2023

Artificially inserted G-quadruplex DNA secondary structures induce long-distance chromatin activation

Although the role of G-quadruplex (G4) DNA structures has been suggested in chromosomal looping this was not tested directly. Here, to test causal function, an array of G4s, or control sequence that does not form G4s, were inserted within chromatin in cells. In vivo G4 formation of the inserted G4 sequence array, and not the control sequence, was confirmed using G4-selective antibody. Compared to the control insert, we observed a remarkable increase in the number of 3D chromatin looping interactions from the inserted G4 array. This was evident within the immediate topologically associated domain (TAD) and throughout the genome. Locally, recruitment of enhancer histone marks and the transcriptional coactivator p300/Acetylated-p300 increased in the G4-array, but not in the control insertion. Resulting promoter-enhancer interactions and gene activation were clear up to 5 Mb away from the insertion site. Together, these show the causal role of G4s in enhancer function and long-range chromatin interactions. Mechanisms of 3D topology are primarily based on DNA-bound architectural proteins that induce/stabilize long-range interactions. Involvement of the underlying intrinsic DNA sequence/structure in 3D looping shown here therefore throws new light on how long-range chromosomal interactions might be induced or maintained.

molecular biology↗

bioRxiv2023

Reversal of pulmonary veno-occlusive disease phenotypes by inhibition of the integrated stress response

Pulmonary veno-occlusive disease (PVOD) is a rare form of pulmonary hypertension arising from EIF2AK4 gene mutations or mitomycin C (MMC) administration. The lack of effective PVOD therapies is compounded by a limited understanding of the mechanisms driving the vascular remodeling in PVOD. We show that the administration of MMC in rats mediates the activation of protein kinase R (PKR) and the integrated stress response (ISR), which lead to the release of the endothelial adhesion molecule VE-Cadherin in the complex with Rad51 to the circulation, disruption of endothelial barrier, and vascular remodeling. Pharmacological inhibition of PKR or ISR attenuates the depletion of VE-Cadherin, elevation of vascular permeability, and vascular remodeling instigated by MMC, suggesting potential clinical intervention for PVOD. Finally, the severity of PVOD phenotypes was increased by a heterozygous BMPR2 mutation that truncates the carboxyl tail of BMPR2, underscoring the role of deregulated BMP signal in the development of PVOD.

cell biology↗

bioRxiv2023

Fine-grained modelling of ATP dependence of decision-making capacity in genetic regulatory networks

Cellular decision-making is fundamental to life, from developmental biology to environmental responses and antimicrobial resistance. Many regulatory processes that drive cellular decisions rely on gene expression, which requires energy in the form of ATP. As even genetically identical cells can have dramatically different ATP levels, bioenergetic status can be an important source of variability in cellular decision-making. Existing studies have investigated this energy dependence but often use coarse-grained modelling approaches (which are not always readily connected to the underlying molecular processes of gene regulation). Here we use a fine-grained mathematical model of gene expression in a two-gene decision-making regulatory network to explore cellular decision-making capacity as energy availability varies. We simulate both a deterministic model, to explore the emergence of different cell fate attractors as ATP levels vary, and a stochastic case to explore how ATP influences the noisy dynamics of stochastic cell decision-making. Higher energy levels typically support increased decision-making capacity (higher numbers of, and more separated, cell states that can be selected), and the fine-grained modelling reveals some differences in behaviour from previous coarse-grained modelling approaches.

systems biology↗

bioRxiv2023

Holistic in silico developability assessment of novel classes of small proteins using publicly available sequence-based predictors

The development of novel therapeutic proteins is a lengthy and costly process, with an average attrition rate of 91% (Thomas et al., 2021). To increase the probability of success and ensure robust drug supply beyond approval, it is essential to assess the developability profile of new potential drug candidates as early and broadly as possible in development (Jain et al., 2023). Predicting these properties in silico is expected to be the next leap in innovation as it would enable significantly reduced development timelines combined with broader screens at lower costs. However, developing predictive algorithms typically requires substantial datasets generated under very defined conditions, a limiting factor especially for new classes of therapeutic proteins that hold immense clinical promise. Here we describe a strategy for assessing the developability of a novel class of small therapeutic Anticalin(R) proteins using machine learning in conjunction with a knowledge-driven approach. The knowledge-driven approach considers developability attributes such as aggregation propensity, charge variants, immunogenicity, specificity, thermal stability, hydrophobicity, and potential post-translational modifications, to calculate a holistic developability score. Based on sequence-derived descriptors as input parameters we established novel statistical models designed to predict the developability scores for Anticalin proteins. The best models yielded low root mean square errors across the entire dataset and were further validated by removing input data from individual screening campaigns and predicting developability scores for those drug candidates. The adoption of the described workflow will enable significantly streamlined preclinical development of Anticalin drug candidates and could potentially be applied to other therapeutic protein scaffolds.

biochemistry↗

bioRxiv2023

Support Vector Machine based prediction models for drug repurposing and designing novel drugs for colorectal cancer

Colorectal cancer (CRC) has witnessed a concerning increase in incidence and poses a significant therapeutic challenge due to its poor prognosis. There is a pressing demand to identify novel drug therapies to combat CRC. In this study, we addressed this need by utilizing the library of CRC pharmacological profiles of anticancer drugs and developed QSAR models for prediction of alternative and promiscuous anti-cancer compounds for CRC treatment. Our QSAR models demonstrated their robustness by achieving high correlation of determination (R2) after 10-fold cross validation. For 12 CRC cell lines, R2 ranges from 0.609-0.827. Highest performance was achieved for SW1417 and GP5d cell lines with R2, 0.827 and 0.786, respectively. Further, we listed the most common descriptors in the drug profiles of the CRC cell lines and we also checked the correlation of the descriptors with the drug activity. The KRFP314 fingerprint was the predominantly occurring descriptor, with the KRFPC314 fingerprint following closely in prevalence within the drug profiles of the CRC cell lines. Beyond predictive modeling, we also successfully validated drug-to-oncogene relationship via in-silico methods and identified FDA-approved drugs which could be used as potential anti-CRC drugs, paving the way for subsequent in vitro or in vivo experiments to validate their efficacy. To provide easy accessibility and utility of our research findings, we have incorporated these models into a free-to-use user-friendly prediction webserver named, "ColoRecPred" hosted on project.iith.ac.in/cgntlab/colorecpred. This web-based tool can be used to screen for potential anti-cancer compounds for CRC.

pharmacology and toxicology↗

bioRxiv2023

Deep learning-guided selection of antibody therapies with enhanced resistance to current and prospective SARS-CoV-2 Omicron variants

Most COVID-19 antibody therapies rely on binding the SARS-CoV-2 receptor binding domain (RBD). However, heavily mutated variants such as Omicron and its sublineages, which are characterized by an ever increasing number of mutations in the RBD, have rendered prior antibody therapies ineffective, leaving no clinically approved antibody treatments for SARS-CoV-2. Therefore, the capacity of therapeutic antibody candidates to bind and neutralize current and prospective SARS-CoV-2 variants is a critical factor for drug development. Here, we present a deep learning-guided approach to identify antibodies with enhanced resistance to SARS-CoV-2 evolution. We apply deep mutational learning (DML), a machine learning-guided protein engineering method to interrogate a massive sequence space of combinatorial RBD mutations and predict their impact on angiotensin-converting enzyme 2 (ACE2) binding and antibody escape. A high mutational distance library was constructed based on the full-length RBD of Omicron BA.1, which was experimentally screened for binding to the ACE2 receptor or neutralizing antibodies, followed by deep sequencing. The resulting data was used to train ensemble deep learning models that could accurately predict binding or escape for a panel of therapeutic antibody candidates targeting diverse RBD epitopes. Furthermore, antibody breadth was assessed by predicting binding or escape to synthetic lineages that represent millions of sequences generated using in silico evolution, revealing combinations with complementary and enhanced resistance to viral evolution. This deep learning approach may enable the design of next-generation antibody therapies that remain effective against future SARS-CoV-2 variants.

immunology↗

bioRxiv2023

p38-MAPK is prerequisite for the synthesis of SARS-CoV-2 protein

The inhibition of p38 mitogen-activated protein kinase (p38-MAPK) by small molecule chemical inhibitors was previously shown to impair severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2) replication, however, mechanisms underlying antiviral activity remains unexplored. In this study, reduced growth of SARS-CoV-2 in p38- knockout Vero cells, together with enhanced viral yield in cells transfected with construct expressing p38, suggested that p38-MAPK is essential for the propagation of SARS-CoV-2. The SARS-CoV-2 was also shown to induce phosphorylation (activation) of p38, at time when transcription/translational activities are considered to be at the peak levels. Further, we demonstrated that p38 supports viral RNA/protein synthesis without affecting viral attachment, entry, and budding in the target cells. In addition, we demonstrated that long-term culture of SARS-CoV-2 in the presence of p38 inhibitor SB203580 does not easily select resistant viral mutants. In conclusion, we provide mechanistic insights on the regulation of SARS-CoV-2 replication by p38 MAPK.

microbiology↗

bioRxiv2023

SignEEG v1.0 : Multimodal Electroencephalography and Signature Database for Biometric Systems

Handwritten signatures in biometric authentication leverage unique individual characteristics for identification, offering high specificity through dynamic and static properties. However, this modality faces significant challenges from sophisticated forgery attempts, underscoring the need for enhanced security measures in common applications. To address forgery in signature-based biometric systems, integrating a forgery-resistant modality, namely, noninvasive electroencephalography (EEG), which captures unique brain activity patterns, can significantly enhance system robustness by leveraging multimodalitys strengths. By combining EEG, a physiological modality, with handwritten signatures, a behavioral modality, our approach capitalizes on the strengths of both, significantly fortifying the robustness of biometric systems through this multimodal integration. In addition, EEGs resistance to replication offers a high-security level, making it a robust addition to user identification and verification. This study presents a new multimodal SignEEG v1.0 dataset based on EEG and hand-drawn signatures from 70 subjects. EEG signals and hand-drawn signatures have been collected with Emotiv Insight and Wacom One sensors, respectively. The multimodal data consists of three paradigms based on mental, & motor imagery, and physical execution: i) thinking of the signatures image, (ii) drawing the signature mentally, and (iii) drawing a signature physically. Extensive experiments have been conducted to establish a baseline with machine learning classifiers. The results demonstrate that multimodality in biometric systems significantly enhances robustness, achieving high reliability even with limited sample sizes. We release the raw, pre-processed data and easy-to-follow implementation details.

neuroscience↗

bioRxiv2023

Ccr4-Not ubiquitin ligase signaling regulates ribosomal protein homeostasis and inhibits 40S ribosomal autophagy

The Ccr4-Not complex containing the Not4 ubiquitin ligase regulates gene transcription and mRNA decay, yet it also has poorly defined roles in translation, proteostasis, and endolysosomal-dependent nutrient signaling. To define how Ccr4-Not mediated ubiquitin signaling regulates these additional processes, we performed quantitative proteomics in the yeast Saccharomyces cerevisiae lacking the Not4 ubiquitin ligase, and also in cells overexpressing either wild-type or functionally inactive ligase. Herein, we provide evidence that both increased and decreased Ccr4-Not ubiquitin signaling disrupts ribosomal protein (RP) homeostasis independently of reduced RP mRNA changes or reductions in known Not4 ribosomal substrates. Surprisingly, we also find that both Not4-mediated ubiquitin signaling, and the Ccr4 subunit, actively inhibit 40S ribosomal autophagy. This 40S autophagy is independent of canonical Atg7-dependent macroautophagy, thus indicating microautophagy activation is responsible. Furthermore, the Not4 ligase genetically interacts with endolysosomal pathway effectors to control both RP expression and 40S autophagy efficiency. Overall, we demonstrate that balanced Ccr4-Not ligase activity maintains RP homeostasis, and that Ccr4-Not ubiquitin signaling interacts with the endolysosomal pathway to both regulate RP expression and inhibit 40S ribosomal autophagy.

molecular biology↗

bioRxiv2023

DENND6A couples Arl8b to a Rab34/RILP/dynein complex regulating retrograde lysosomal trafficking and autophagy

Lysosomes help maintain cellular proteostasis, and defects in lysosomal positioning and function lead to diseases including neurodegenerative disorders. The spatiotemporal distribution of lysosomes is regulated by small GTPases, including Rabs, which are activated by guanine nucleotide exchange factors (GEFs). DENN domain-bearing proteins are the largest family of Rab GEFs. Using a cell-based assay, we screened the DENN domain protein family member DENND6A for potential GEF activity toward all 60 Rabs and identified 20 potential DENND6A substrates, including Rab34. Here, we demonstrate that DENND6A activates Rab34, which recruits a RILP/dynein complex to the lysosomes, promoting lysosomal retrograde trafficking from the cell periphery to the minus ends of microtubules. Further, we identify DENND6A as an effector of Arl8b, a major regulatory GTPase on lysosomes. Initially known for promoting anterograde transport of lysosomes, Arl8b also facilitates lysosomal retrograde transport. We demonstrate that Arl8b recruits DENND6A to peripheral lysosomes to activate Rab34 and initiate retrograde transport, regulating nutrient-dependent lysosomal juxtanuclear repositioning and loss of DENND6A impairs autophagic flux. Our findings support a model whereby Arl8b/DENND6A/Rab34-dependent lysosomal retrograde trafficking controls autophagy.

cell biology↗

bioRxiv2023

A geminivirus AC5 protein interacts with plant hormonal signalling and impacts plant defence

Geminiviruses are a large group of plant viruses responsible for yield loss in various crops, mainly in the tropical and sub-tropical regions. Geminiviruses encode six to nine multifunctional proteins, which interact with plant components to cause pathogenesis. One of the least studied geminiviral proteins is AC5. This study presents the first evidence of an AC5 protein interacting with a component of the abscisic acid signalling pathway, resulting in a depressed state. We show that the AC5 protein, encoded by Sri Lankan cassava mosaic virus is important for symptom development and virus accumulation in the experimental host Nicotiana benthamiana. The above interaction perturbs the abscisic acid signalling pathways, leading to compromised expression of defense-related genes and insensitivity to abscisic acid in transgenic Arabidopsis plants. This suggests a novel role of AC5 to facilitate virus propagation. Furthermore, we show that transiently suppressing the expression in N. benthamiana PP2C with which AC5 interacts, results in a reduction in viral titers possibly due to augmented ABA signaling and its defense-related roles. This research provides valuable insights into how geminiviral proteins manipulate ABA-mediated defence pathways, paving the way for further investigation into the underlying mechanisms and potential applications in plant protection against viral infections.

plant biology↗

bioRxiv2023

Downregulation of a cell polarity protein potentiates Chikungunya Virus infection in host cells

During cellular infections, alphaviruses produce a 6 kDa membrane protein (6K) and a transframe variant (TF) of 6K through ribosomal frameshifting. The role of these proteins in alphavirus biology is largely unknown. Here, we show that TF of Chikungunya virus plays a unique and critical role in promoting virus propagation by manipulating host cell boundaries. TF achieves this by targeting and downregulating human Scribble, a component of the polarity complex that controls cellular morphology and apoptosis, leading to its punctate localization, ubiquitination, and subsequent degradation via the proteasomal pathway. The TF-Scribble interaction is mediated by a newly discovered PDZ-domain binding motif (PBM) in TF, with the PDZ domains of Scribble, as demonstrated by co-localization during viral infection and further by co-immunoprecipitation and proteomics analysis. This PBM is unique to TF and is absent in 6K; thus, 6K cannot modulate Scribble localization in infected cells. shRNA-mediated knockdown of Scribble potentiates CHIKV propagation highlighting the requirement of TF for the downregulation of Scribble. While wildtype CHIKV drastically alters cell-cell boundaries, a mutated version of CHIKV generated through reverse genetics ({Delta}TF CHIKV), which produces 6K but not TF, is unable to trigger similar morphological alterations due to its inability to engage Scribble, ultimately resulting in suboptimal virus propagation. A cryoEM reconstruction of {Delta}TF CHIKV at a global resolution of 3.6 [A], one of the highest reported among all alphavirus structures, indicates that the assembly of glycoprotein spikes and nucleocapsid is unaffected. Thus, the loss of TF affects the ultimate stage of cellular egress in the virus life cycle, and not earlier stages such as entry, replication or assembly. Our work thus establishes a novel function for the TF component of alphaviruses in modulating host morphology, potentiating virus transmission, and also distinguishes the functionality of TF from that of 6K in alphavirus biology. TeaserA novel functionality of Chikungunya Virus in modulating cell boundaries to allow efficient virus propagation

cell biology↗

bioRxiv2023

Restriction of the growth and biofilm formation of ESKAPE pathogens by caprine gut-derived probiotic bacteria

The accelerated rise of antimicrobial resistance (AMR) poses a significant global health risk, necessitating the exploration of alternative strategies for combating pathogenic infections. Biofilm-related infections, which are unresponsive to standard antibiotics, often require the use of higher-order antimicrobials with toxic side effects and a potential for disrupting the microbiome. Probiotic therapy, with its diverse benefits and inherent safety, is emerging as a promising approach for preventing and treating various infections and as an alternative to antibiotic therapy. In this study, we isolated novel probiotic bacteria from the gut of domestic goats (Capra hircus) and evaluated their antimicrobial and antibiofilm activities against the ESKAPE group of pathogens. We performed comprehensive microbiological, biochemical, and molecular characterizations, including analysis of the 16S-rRNA gene V1-V3 region and the 16S-23S ISR region, on 20 caprine gut-derived lactic acid bacteria (LAB). Among these, six selected LABs demonstrated substantial biofilm formation in anaerobic conditions, and exhibited robust cell surface hydrophobicity and autoaggregation properties highlighting their superior enteric colonization capability. Notably, these LAB isolates exhibited broad-spectrum growth inhibitory and anti-biofilm properties against ESKAPE pathogens. Additionally, the LAB isolates were susceptible to antibiotics listed by the European Food Safety Authority (EFSA), within the prescribed Minimum Inhibitory Concentration limits, suggesting their safety as feed additives. The remarkable probiotic characteristics exhibited by the caprine gut-derived LAB isolates in this study strongly endorse their potential as compelling alternatives to antibiotics and as direct-fed microbial (DFM) feed supplements in the livestock industry, addressing the escalating need for antibiotic-free animal products.

microbiology↗

bioRxiv2023

GATA-regulated transcriptional program dictate cell fate equilibrium to establish the maternal-fetal exchange interface and fetal development

The placenta establishes a maternal-fetal exchange interface to transport nutrients and gases between the mother and the fetus. Establishment of this exchange interface relies on the development of multinucleated syncytiotrophoblasts (SynT) from trophoblast progenitors and defect in SynT development often leads to pregnancy failure and impaired embryonic development. Here, we show that mouse embryos with conditional deletion of GATA2 and GATA3 in labyrinth trophoblast progenitors have underdeveloped placenta and die [~] embryonic day 9.5 (E9.5). Single cell RNA Seq (scRNA-Seq) analysis revealed excessive accumulation of multipotent labyrinth trophoblast progenitors upon conditional deletion of GATA factors. The GATA factor-deleted multipotent progenitors were unable to differentiate to matured SynTs. We also show that the GATA factor-mediated priming of trophoblast progenitors for SynT differentiation is a conserved event during human placentation. Loss of either GATA2 or GATA3 in cytotrophoblast (CTB)-derived human trophoblast stem cells (human TSCs) drastically inhibits SynT differentiation potential. Identification of GATA2 and GATA3 target genes along with comparative bioinformatics analyses revealed that GATA factors directly regulate hundreds of common genes in human TSCs, including genes that are essential for SynT development and implicated in preeclampsia and fetal growth retardation. Thus, our study uncovers a conserved molecular mechanism, in which coordinated function of GATA2 and GATA3 promote trophoblast progenitor-to-SynT commitment ensuring establishment of the maternal-fetal exchange interface.

developmental biology↗

bioRxiv2023

Macromolecular Crowding Promotes Reentrant Liquid-Liquid Phase Separation of Human Serum Transferrin and Prevents Surface-Induced Fibrillation

Protein aggregation and inactivation upon surface immobilization are major limiting factors for analytical applications in biotechnology related fields. Protein immobilization on solid surfaces often requires multi-step surface passivation which is time consuming and inefficient. Herein, we have discovered that biomolecular condensates of biologically active human serum transferrin (Tf) can effectively prevent surface-induced fibrillation and preserve the native-like conformation of phase separated Tf over a period of 30-days. It has been observed that macromolecular crowding promotes homotypic liquid-liquid phase separation (LLPS) of Tf through enthalpically driven multivalent hydrophobic interactions possibly via the involvement of its low complexity domain (residue 3-20) containing hydrophobic amino acids. The present LLPS of Tf is a rare example of salt-mediated reentrant phase separation in a broad range of salt concentrations (0-3 M) solely via the involvement of hydrophobic interactions. Notably, no liquid-to-solid-like phase transition has been observed over a period of 30-days, suggesting the intact conformational integrity of phase separated Tf as revealed from single droplet Raman, circular dichroism, and Fourier transform infrared spectroscopy measurements. More importantly, we discovered that the phase separated condensates of Tf completely inhibit the surface-induced fibrillation of Tf, illustrating the protective role of these liquid-like condensates against denaturation and aggregation of biomolecules. The cell mimicking aqueous compartments of biomolecular condensates with a substantial amount of interfacial water preserve the structure and functionality of biomolecules. Our present study highlights an important functional aspect of biologically active protein condensates and may have wide-ranging implications in cell physiology and biotechnological applications.

biochemistry↗