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Mondal, J.

Publications and source records attributed to Mondal, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Microenvironment Drives Reentrant Condensation of Aβ40

Within the framework of liquid-liquid phase separation (LLPS), biomolecular condensation orchestrates vital cellular processes and its dysregulation is implicated in severe pathological conditions. Recent studies highlight the role of intrinsically disordered proteins (IDPs) in LLPS, yet the influence of microenvironmental factors has remained a puzzling factor. Here, via computationally simulating the impact of solution conditions on LLPS behavior of neurologically pathogenic IDP A{beta}40, we chanced upon a salt-driven reentrant condensation phenomenon, wherein A{beta}40 aggregation increases with low salt concentrations (25-50 mM), followed by a decline with further salt increments.. An exploration into the thermodynamic and kinetic signatures of reentrant condensation unveils a nuanced interplay between protein electrostatics and ionic strength as potential drivers. Notably, the charged residues of the N-terminus exhibit a non-monotonic response to salt screening, intricately linked to the recurrence of reentrant behavior in hydrophobic core-induced condensation. Intriguingly, our findings also unveil the reappearance of similar reentrant condensation phenomena under varying temperature conditions. Collectively, our study illuminates the profoundly context-dependent nature of A{beta}40s liquid-liquid phase separation behavior, extending beyond its intrinsic molecular framework, where microenvironmental cues wield significant influence over its aberrant functionality.

biophysics↗

bioRxiv2024

Discovery of dynamic changes in 3D chromatin architecture through polymer physics model

The 3D organisation of the genome provides an intricate relationship between the chromatin architecture and its effects on the functional state of the cell. Recent advances in high-throughput sequencing and chromosome conformation capture technologies elucidated a comprehensive view of chromatin interactions on a genome-wide scale but provides only a 2D representation of how the chromatin is organised inside the cell nucleus. To quantitatively understand the structural alterations and dynamics of chromatin in 3D, we have developed a computational model that not only captures the hierarchical structural organisation but also provides mechanistic insights into the dynamics of spatial rearrangements of chromatin in developing lymphoid lineage cells. From the combination of approaches of polymer physics representing chromatin as a homopolymeric chain and incorporation of the biological information of chromosomal interactions inferred from the Hi-C data, we generated a coarse grained bead-on-a-string polymer model of chromatin to comprehend the mechanisms underlying the differential chromatin architecture. Our study showed that our simulated chromatin structure recapitulates the intrinsic features of chromatin organisation, including the fractal globule nature, compartmentalization, presence of topologically associating domains (TADs), phase separation and spatial preferences of genomic regions in the chromosomal territories. Comparative analyses of these simulated chromatin structures of differentiating B cell stages revealed compartmental switching and changes in the spatial positioning of lineage specific genomic regions. Analysis of the compactness of the switched regions showed insights into their acquired open-closed states for gene regulation and hence governing the cell fate through consequent structural rearrangement. Based on the remarkable performance of our model, we emphasise on its predictive potential by identifying switching of novel regions that demonstrated undergoing structural rearrangement which was subsequently validated through their differential expression patterns in vitro. These results reveal that although the chromatin organisation seems similar in most cell types, it undergoes distinct structural changes for the regulatory role of chromatin in sustaining cell specificity.

bioinformatics↗

bioRxiv2024

A Transformer Based Machine Learning of Molecular Grammar Inherent in Proteins Prone to Liquid Liquid Phase Separation

Understanding the molecular grammar that governs protein phase separation is essential for advancements in bioinformatics and protein engineering. This study leverages Generative Pre-trained Transformer (GPT)-based Protein Language Models (PLMs) to decode the complex grammar of proteins prone to liquid-liquid phase separation (LLPS). We trained three distinct GPT models on datasets comprising amino acid sequences with varying LLPS propensities: highly predisposed (LLPS+ GPT), moderate (LLPS-GPT), and resistant (PDB* GPT). As training progressed, the LLPS-prone model began to learn embeddings that were distinct from those in LLPS-resistant sequences. These models generated 18,000 protein sequences ranging from 20 to 200 amino acids, which exhibited low similarity to known sequences in the SwissProt database. Statistical analysis revealed subtle but significant differences in amino acid occurrence probabilities between sequences from LLPS-prone and LLPS-resistant models, suggesting distinct molecular grammar underlying their phase separation abilities. Notably, sequences from LLPS+ GPT showed fewer aromatic residues and a higher fraction of charge decoration. Short peptides (20-25 amino acids) generated from LLPS+ GPT underwent computational and wet-lab validation, demonstrating their ability to form phase-separated states in vitro. The generated sequences enriched the existing database and enabled the development of a robust classifier that accurately distinguishes LLPS-prone from non-LLPS sequences. This research marks a significant advancement in using computational models to explore and engineer the vast protein sequence space associated with LLPS-prone proteins.

biophysics↗

bioRxiv2024

Protein Translation Can Fluidize Bacterial Cytoplasm

The cytoplasm of bacterial cells is densely packed with highly polydisperse macromolecules that exhibit glassy dynamics. Research has revealed that metabolic activities in living cells can counteract the glassy nature of these macromolecules, allowing the cell to maintain critical fluidity for its growth and function. While it has been proposed that the crowded cytoplasm is responsible for this glassy behavior, a detailed explanation for how cellular activity induces fluidization remains elusive. In this study, we introduce and validate a novel hypothesis through computer simulations: protein synthesis in living cells contributes to the metabolism-dependent fluidization of the cytoplasm. The main protein synthesis machinery, ribosomes, frequently shift between fast and slow diffusive states. These states correspond to the independent movement of ribosomal subunits and the actively translating ribosome chains called polysomes, respectively. Our simulations demonstrate that the frequent transitions of the numerous ribosomes, which constitute a significant portion of the cell proteome, greatly enhance the mobility of other macromolecules within the bacterial cytoplasm. Considering that ribosomal protein synthesis is the largest consumer of ATP in growing bacterial cells, the translation process likely serves as the primary mechanism for fluidizing the cytoplasm in metabolically active cells.

biophysics↗

bioRxiv2024

An Integrated Machine Learning Approach Delineates Entropic Modulation of alpha-Synuclein by Small Molecule

The mis-folding and aggregation of intrinsically disordered proteins (IDPs) such as -synuclein (S) underlie the pathogenesis of various neurodegenerative disorders. However, targeting S with small molecules faces challenges due to its lack of defined ligand-binding pockets in its disordered structure. Here, we implement a deep artificial neural network based machine learning approach, which is able to statistically distinguish fuzzy ensemble of conformational substates of S in neat water from those in aqueous fasudil (small molecule of interest) solution. In particular, the presence of fasudil in the solvent either modulates pre-existing states of S or gives rise to new conformational states of S, akin to an ensemble-expansion mechanism. The ensembles display strong conformation-dependence in residue-wise interaction with the small molecule. A thermodynamic analysis indicates that small-molecule modulates the structural repertoire of S by tuning protein backbone entropy, however entropy of the water remains unperturbed. Together, this study sheds light on the intricate interplay between small molecules and IDPs, offering insights into entropic modulation and ensemble expansion as key biophysical mechanisms driving potential therapeutics.

biophysics↗

bioRxiv2024

ATP Prevents Aggregation of Protein via Modulating its Monomeric Conformation

Proteins occurring in significantly high concentrations in cellular environments (over 100 mg/mL) and functioning in crowded cytoplasm, often face the prodigious challenges of aggregation which are the pathological hallmark of aging and are critically responsible for a wide spectrum of rising human diseases. Here we combine a joint-venture of complementary wet-lab experiment and molecular simulation to discern the potential ability of adenosine triphosphate (ATP) as solubilizer of protein aggregates. We show that ATP prevents both condensation of aggregation-prone intrinsically disordered protein A{beta}40 and promotes dissolution of pre-formed aggregates. Computer simulation links ATPs solubilizing role to its ability to modulate proteins structural plasticity by unwinding protein conformation. We show that ATP is positioned as a superior biological solubilizer of protein aggregates over traditional chemical hydrotropes, potentially holding promises in therapeutic interventions in protein-aggregation related diseases. Going beyond its conventional activity as energy currency, the amphiphilic nature of ATP enables its protein-specific interaction that would enhance ATPs efficiency in cellular processes.

biochemistry↗

bioRxiv2023

Machine Learning Unravels Inherent Structural Patterns in Escherichia Coli Hi-C Matrices and Predicts DNA Dynamics

The large dimension of the Hi-C-derived chromosomal contact map, even for a bacterial cell, presents challenges in extracting meaningful information related to its complex organization. Here we first demonstrate that a machine-learnt (ML) low-dimensional embedding of a recently reported Hi-C interaction map of archetypal bacteria E. Coli can decode crucial underlying structural pattern. In particular, a three-dimensional latent space representation of (928x928) dimensional Hi-C map, derived from an unsupervised artificial neural network, automatically detects a set of spatially distinct domains that show close correspondences with six macro-domains (MDs) that were earlier proposed across E. Coli genome via recombination assay-based experiments. Subsequently, we develop a supervised random-forest regression model by machine-learning intricate relationship between large array of Hi-C-derived chromosomal contact probabilities and diffusive dynamics of each individual chromosomal gene. The resultant ML model dictates that a minimal subset of important chromosomal contact pairs (only 30 %) out of full Hi-C map is sufficient for optimal reconstruction of the heterogenous, coordinate-dependent sub-diffusive motions of chromosomal loci. Specifically the Ori MD was predicted to exhibit most substantial contribution in chromosomal dynamics among all MDs. Finally, the ML models, trained on wild-type E. Coli was tested for its predictive capabilities on mutant bacterial strains, shedding light on the structural and dynamic nuances of {Delta}MatP30MM and {Delta}MukBEF22MM chromosomes. Overall our results illuminate the power of ML techniques in unraveling the complex relationship between structure and dynamics of bacterial chromosomal loci, promising meaningful connections between our ML-derived insights and real-world biological phenomena.

biophysics↗

bioRxiv2023

Modulation of Liquid-liquid Phase separation of alpha-Synuclein by Saline and Crowded Environment

Intrinsically disordered protein -Synuclein (S) is implicated in Parkinsons disease due to its aberrant aggregation propensity. In a bid to identify the traits of its aggregation, here we computationally simulate the multi-chain association process of S in aqueous as well as under diverse environmental perturbations. In particular, the aggregation of S in aqueous and varied environmental condition led to marked concentration differences within protein aggregates, resembling liquid-liquid phase separation (LLPS). Both saline and crowded settings enhanced the LLPS propensity. However, the surface tension of S droplet responds differently to crowders (entropy-driven) and salt (enthalpy-driven). Conformational analysis reveals that the IDP chains would adopt extended conformations within aggregates and would maintain mutually perpendicular orientations to minimize inter-chain electrostatic repulsions. The droplet stability is found to stem from a diminished intra-chain interactions in the C-terminal regions of S, fostering inter-chain residue-residue interactions. Intriguingly, a graph theory analysis identifies small-world-like networks within droplets across environmental conditions, suggesting the prevalence of a consensus interaction patterns among the chains. Together these findings suggest a delicate balance between molecular grammar and environment-dependent nuanced aggregation behaviour of S.

biophysics↗

bioRxiv2023

A host AAA-ATPase exhibits bacteriolytic activity for clearance of microbial infection

An array of host cytosol guarding factors impede bacterial proliferation and preserve cellular sterility. Amongst them, proteasomal degradation of ubiquitinated pathogens has emerged as a critical mechanism for ensuring cytosolic sanctity. We wondered how proteasomes, with their small size and inability to extract membrane-bound proteins, can eradicate pathogens. Here, we unveil a unique strategy, wherein VCP/p97, a host AAA-ATPase, eliminates pathogens by exerting mechanical force that physically unfolds and pulls out ubiquitinated proteins from bacterial membrane. Combining a single-molecule approach along with molecular dynamic simulation and in-vitro reconstitution, we demonstrate that protein extraction by p97 causes extensive membrane lysis and release of cytosolic contents from phylogenetically diverse microbes. Additionally, in an in-vivo mouse sepsis model, this segregase-dependent bactericidal effect of p97 abrogated microbial proliferation in host tissues. Overall, we discovered a distinct innate antimicrobial function of p97, that protects the host against lethal bacterial infections. One Sentence SummaryA host AAA-ATPase exhibits bacteriolytic activity.

microbiology↗

bioRxiv2023

Identifying Selectivity Filters in Protein Biosensor for Ligand Screening

Specialized sensing mechanisms in bacteria enable the identification of cognate ligands with remarkable selectivity in highly xenobiotic-polluted environments, where these ligands are utilized as energy sources. Here, via an integrated all-atom computer simulation, biochemical assay and isothermal titration calorimetry approaches we determine the molecular basis of MopR, a phenol biosensors complex selection process of ligand entry. Our results reveal a set of strategically placed selectivity filters along the ligand entry pathway of MopR. These filters act as checkpoints, screening diverse aromatic ligands at the protein surface based on their chemical features and sizes. Ligands meeting specific criteria are allowed to enter the sensing site in an orientation-dependent manner. Sequence and structural analyses demonstrate the conservation of this ligand entry mechanism across the sensor class, with individual amino acids along the selectivity filter path playing a critical role in ligand selection. Together, this investigation highlights the importance of interactions with the ligand entry pathway, in addition to interactions within the binding pocket, for achieving ligand selectivity in biological sensing. The findings enhance our understanding of ligand selectivity in bacterial phenol biosensors and provide insights for the rational expansion of the biosensor repertoire, particularly for the biotechnologically relevant class of aromatic pollutants.

biochemistry↗

bioRxiv2023

On the Spatial Positioning of Ribosomes around chromosome in E. coli Cytoplasm

The spatial organization of ribosomes in the cytoplasm of Escherichia coli (E. coli) bacteria has been a subject of longstanding intrigue. Previous investigations suggested that ribosomes remain completely excluded from the chromosome-rich nucleoid region in a "poor solvent" like cytoplasm. Here, we present an integrated model of the bacterial cytoplasm, informed by experimental data, which updates this prevailing narrative. We demonstrate that ribosomes maintain a delicate balance of both attractive and repulsive interactions with the chromosome, contrary to the conventional notion of it acting as an inert crowder in cytoplasm. The multi-dimensional spatial distribution of free ribosomes (30S and 50S) and bound ribosomes (70S polysome) inside the cytoplasm reveals that the extent of mutual ribosome-chromosome segregation is relatively less pronounced due to the presence of non-negligible amount of ribosomes within the inner core of the cytoplasm. In particular, we identify a central void within the inner-most core of the nucleoid that lacks chromosomal DNA but can accommodate finite proportion of both free (11 %) and bound (18 %) ribosomes. Furthermore, our analysis of the chromosome mesh size and the conformation of bound ribosomes suggests that bound ribosomes remain elongated and would be able to navigate past the chromosome mesh to access the central void. Together by highlighting the dynamic nature of ribosome localization in E. coli, this investigation proposes that this segregation is crucial for maximizing the utilization of synthesized mRNA and facilitating efficient translation into proteins, which are essential for bacterial survival.

biophysics↗

bioRxiv2023

Discovery of a Novel 3site State as the Multi-Substrate Bound State of P450cam

Archetypal metalloenzyme Cytochrome P450cam (CYP101A1) catalyzes regioselective hydroxylation of its native substrate camphor in heme active site. However, the proposal of potential existence of additional substrate binding modes distal from the active site in P450cam and their concomitant roles in regulating recognition at active site have remained a matter of recurring discourse. Herein we report the discovery of a novel 3site state in P450cam, where three substrate molecules were observed to simultaneously bind to P450cam at three distinct sites including the heme active site. These three binding modes, hereby referred as catalytic, waiting and allosteric binding modes in 3site state, are allosterically inter-linked and function in mutually synergistic fashion. The 3site state possesses regio-selective conformations of substrate essential for catalysis and establishes substrate-ingress and product exit process to and from the active site via two distinct channels. The ensemble of three-state binding modes are found to be self-consistent with NMR pseudo-contact shift data obtained from TROSY-HSQC measurements and DEER based predictions. Binding of redox partner Putidaredoxin with 3site model retains closed conformation of 3site state, siding with NMR based hypothesis that the catalysis would take place in closed insulation of P450cam even in presence of its redox partner. Statement of SignificanceUbiquitous superfamily of mono-oxygenases cytochrome P450s are involved in broad range of metabolic process in all domains of life and are also important drug targets. Apart from the well known and established binding mode in heme active site, the substrate bindings at additional distal sites have been postulated in multitude of P450s. Using the archetypal bacterial cytochrome P450 i.e., P450cam, a novel 3site state of cytochrome P450 is elucidated in this work. The novel 3site state has two additional binding modes namely waiting and allosteric (also postulated previously), apart from known binding mode catalytic in the active site. The known functions of P450cam are found to be most optimally explained by this 3site state, instead of single substrate bound catalytic state. This state can be of critical importance for CYP superfamily at large and potentially be useful in understanding the non-Michaelis behaviour, observed in many P450s.

biochemistry↗

bioRxiv2023

Development of a Data-driven Integrative Model of Bacterial Chromosome

The chromosome of archetypal bacteria E. coli is known for a complex topology with 4.6 x 106 base pairs (bp) long sequence of nucleotide packed within a micrometer-sized celllular confinement. The inherent organization underlying this chromosome eludes general consensus due to the lack of a high-resolution picture of its conformation. Here we present our development of an integrative model of E. coli at a 500 bp resolution (https://github.com/JMLab-tifrh/ecoli_finer), which optimally combines a set of multi-resolution genome-wide experimentally measured data within a framework of polymer based architecture. In particular the model is informed with intra-genome contact probability map at 5000 bp resolution derived via Hi-C experiment and RNA-sequencing data at 500 bp resolution. Via dynamical simulations, this data-driven polymer based model generates appropriate conformational ensemble commensurate with chromosome architectures that E. coli adopts. As a key hallmark, the model chromosome spontaneously self-organizes into a set of non-overlapping macrodomains and suitably locates plectonemic loops near the cell membrane. As novel extensions, it predicts a contact probability map simulated at a higher resolution than precedent experiments and can demonstrate segregation of chromosomes in a partially replicating cell. Finally, the modular nature of the model helps us to devise control simulations to quantify the individual role of key features in hierarchical organization of the bacterial chromosome.

microbiology↗

bioRxiv2022

Small molecule modulates α-Synuclein conformation and its oligomerization via Entropy Expansion

Aberrant misfolding and progressive aggregation of the intrinsically disordered protein (IDP), -synuclein, are associated with the etiology of several neurodegenerative diseases. However, the structurally heterogeneous ensemble of this IDP and lack of a well-defined binding pocket make it difficult to probe the druggability of -synuclein. Here, by building a comprehensive statistical model of the fuzzy ensemble of a millisecond-long atomistic simulation trajectory of monomeric -synuclein interacting with the small-molecule drug fasudil, we identify exhaustive sets of metastable binding-competent states of -synuclein. The model reveals that the interaction with the drug primes this IDP to explore both more compact and more extended conformational sub-ensemble than those in neat water, thereby broadening its structural repertoire in presence of small-molecule via an entropy expansion mechanism. Subsequent simulation of the dimerisation process shows that similar motif of entropic-expansion mechanism helps fasudil to retard the self-aggregation propensity of -synuclein via trapping it into multiple distinct states of diverse compaction featuring aggregation-resistant long-range interactions. Furthermore, small-molecule binding interactions in dimerisation-competent relatively extended states have a screening effect that hinders the formation of stable dimer contacts. Together, the investigation demonstrates the ability of small-molecules to have an ensemble-modulatory effect on IDPs that can be effectively utilised in therapeutic strategies probing aggregation-related diseases.

biophysics↗

bioRxiv2022

Phenol Sensing in Nature Modulated via a Conformational Switch Governed by Dynamic Allostery

NtrC family of proteins sense external stimuli and accordingly stimulate stress and virulence pathways via activation of associated {sigma}54-dependent RNA polymerases. Here, we establish that MopR, an NtrC protein, harbors a dynamic bi-directional electrostatic network that connects the phenol pocket to two distal regions, namely the "G-hinge" and the "allo-steric-linker". While G-hinge influences the entry of phenol, the allosteric-linker passes the signal to the downstream ATPase domain. Phenol binding induces a rewiring of the electrostatic connections by eliciting dynamic allostery, and it was demonstrated that perturbation of the core relay residues results in a complete loss of ATPase stimulation. A mutation of the G-hinge,[~]20[A] from the phenol pocket, demonstrated altered flexibility by shifting the pattern of conformational states accessed, leading to a protein with 7-fold enhanced phenol binding ability and enhanced transcriptional activation. A global analysis illustrates that dynamic allostery-driven conserved community networks are universal and evolutionarily conserved across species.

biochemistry↗

bioRxiv2022

Impact of Inert Crowders on Host-Guest Recognition Process

Biological environments typically contain high concentrations (300-400 mg/mL) of different macromolecules at volume fractions as large as 30%-40%. Biomolecular processes, especially ubiquitous recognition phenomena, occurring in such crowded heterogeneous media would differ significantly compared to the dilute buffer solutions. Here we quantify the impact of inert crowders on prototypical host-guest recognition process by explicit-solvent molecular dynamics (MD) simulations in atomic resolution. We demonstrate that the crowders, especially when smaller in size, would facilitate the binding process of guest molecule by decreasing the free energy barrier for binding via excluded volume effect and desolvation of the host receptor. However, the extent of crowder-induced stabilization of host-guest complex is found to be significantly higher when the guest molecule is sterically constricted to approach the host along a centrosymmetric direction, contrary to its unrestricted, freely diffusive movement. A kinetic analysis of the recognition process reveals that the origin of relatively stronger crowder impact, during constricted movement of guest molecule, lies in significantly enhanced residence time of the guest inside the host by crowders, compared to freely diffusive ligand movement. Together our results suggest that the extent of im-pact of crowding on recognition processes would be contingent upon presence or absence of constriction on ligand movement. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/482924v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@130e57dorg.highwire.dtl.DTLVardef@12aa364org.highwire.dtl.DTLVardef@4d23ddorg.highwire.dtl.DTLVardef@6da639_HPS_FORMAT_FIGEXP M_FIG TOC graphic C_FIG

biophysics↗

bioRxiv2022

Conformational Ensemble of Monomeric α-Synuclein in Aqueous and Crowded Environments as revealed by Markov State Model

140-residue intrinsically disordered protein -synuclein (S) is known to be susceptible to environmental cues/crowders and adopts conformations that are vastly variable in the extent of secondary structure and tertiary interactions. Depending upon the nature of these interactions, some of the conformations may be suitable for its physiological functions while some may be predisposed to aggregate with other partners into higher ordered species or to phase separate. However, the inherently heterogenous and dynamic nature of S has precluded a clear demarcation of its monomeric precursor between aggregation-prone and functionally relevant aggregation-resistant states. Here, we optimally characterise a set of metastable conformations of S by developing a comprehensive Markov state model (MSM) using cumulative 108 {micro}s-long all-atom MD simulation trajectories of monomeric S. Notably, the dimension of the most populated metastable (85%) state (Rg [~] 2.59 ({+/-}0.45) nm) corroborates PRENMR studies of S monomer and undergoes kinetic transition at 0.1-150 {micro}s time-scale with weakly populated (0.06%) random-coil like ensemble (Rg [~] 5.85 ({+/-}0.43) nm) and globular protein-like state (14%) (Rg [~] 1.95 ({+/-}0.08) nm). The inter-residue contact maps identify a set of mutually interconverting aggregation-prone {beta}-sheet networks in the NAC region and aggregation-resistant long-range interactions between N- and C-terminus or helical conformations. The presence of crowding agents compacts the MSM-derived metastable conformations in a non-monotonic fashion and skews the ensemble by either introducing new tertiary contacts or reinforcing the innate contacts to adjust to the excluded-volume effects of such environments. These observations of crucial monomeric states would serve as important steps towards rationalising routes that trigger S-associated pathologies. Significance statement-synuclein, a neuronal protein, is often associated with neurogenerative diseases due to its tendency to self-assemble into higher ordered aggregates. While the monomeric precursor of this protein is intrinsically disordered, it is also known to be susceptible to biological environmental cues and adopts a wide range of conformations that are either primed for aggregation or remain in auto-inhibitory states. However, the inherently heterogenous nature of the monomeric form has prevented a clear dissection of aggregation-prone and functionally relevant aggregation-resistant states. Here, we resolve this via an atomistic characterisation of an optimal set of crucial metastable monomeric conformations via statistical modelling of computer simulated data. The investigation also sheds light on crowding-induced modulation of the ensemble and eventual fibrillation pathways.

biophysics↗

bioRxiv2022

DNA-functionalized Gold Nanorods for Targeted Triple-modal Optical Imaging and Photothermal Therapy of Triple-negative Breast Cancer

Targeted imaging and therapy for triple-negative breast cancer (TNBC) in the perioperative period are believed to be imperative for better disease management and improved life expectancy. Still, they are not yet available in clinical settings, and only a few nanoparticle-based theranostic agents potentially offer these capabilities. Herein, we develop an innovative class of biocompatible triple-modality nanoprobes (TMNPs) that offer optical imaging using optoacoustic, fluorescence, and surface-enhanced Raman scattering (SERS), as well as photothermal therapy (PTT) with near-infrared (NIR) light. The TMNPs are fabricated by immobilizing positively charged NIR fluorophores on negatively charged DNA-coated gold nanorods (AuNR), then silica encapsulation. The DNA-based design allows the screening of commercially available positively charged NIR fluorophores for the optimum fluorescence and SERS signals. After the design optimization, we functionalize TMNPs with folate groups to target folate receptor1 (FOLR1)-overexpressing TNBC in vitro and in vivo. Our results reveal that TMNPs preferentially accumulate in the FOLR1 positive tumors in TNBC patient-derived xenograft mouse models and show excellent imaging capabilities with all three imaging modalities. Selective exposure of the tumor with NIR laser further shows efficient thermal tissue ablation without causing systemic toxicity. Collectively, TMNP holds great promise for real-time multiplexed imaging of cancer biomarkers and therapeutic capability.

bioengineering↗