Biology subjects

Dalal, D.

Publications and source records attributed to Dalal, D..

4 recordsLinked to original sources

bioRxiv2026

A mathematical model of tumor growth driven by oxygen lactate exosome feedback

Solid tumors develop within a heterogeneous microenvironment shaped by coupled biochemical and metabolic processes. As a tumor grows, oxygen gradients develop from the periphery towards the core, giving rise to hypoxic regions. Hypoxia induces a metabolic shift from oxidative phosphorylation to glycolysis, leading to elevated lactate production. Experimental studies further indicate that increased lactate levels enhance the secretion of tumor-derived exosomes carrying proteins, mRNA, and lipids, which in turn promote tumor cell proliferation. Together, these interactions form a feedback loop linking oxygen availability, lactate accumulation, and exosome-mediated signaling. Despite growing experimental evidence for each component, the impact of this coupled oxygen lactate exosome axis on tumor growth dynamics has not yet been systematically explored from a mathematical perspective. It remains unclear how the oxygen lactate exosome axis affects tumor growth - impact of nonlocal effects. In this paper, we develop a mechanistic mathematical model to investigate how this feedback mechanisms affects tumor growth. We first consider an in vitro setting oxygen levels are spatially homogeneous and vary periodically in time between normoxic and hypoxic states, capturing key features of cyclic hypoxia observed in vivo. Numerical simulations reveal that exosome mediated feedback has a pronounced effect on tumor volume under chronic hypoxia. In addition, we observe that the tumor volume decreases as the period of cyclic hypoxia increases. We then extend the model to an in vivo framework by incorporating oxygen diffusion and consumption, allowing spatial heterogeneity to emerge. Simulations reveal that tumor cells in normoxic regions benefit indirectly from enhanced exosome secretion driven by lactate produced in hypoxic regions. Overall, the results show how spatially mediated metabolic signaling can amplify tumor growth and aggressiveness, and illustrate how mathematical modeling can increase understanding of non local feedback mechanisms within the tumor microenvironment.

systems biology↗

bioRxiv2026

A mathematical investigation of the interplay between vasculature and intratumoral cellular heterogeneity during tumor progression

Tumors consist of heterogeneous phenotypic cells, such as normoxic cells, which are highly proliferative, and hypoxic cells, which are less proliferative. Their phenotypic switching depends on tumor microenvironmental factors, such as oxygen and nutrient concentrations supplied by local blood vessels. However, during ongoing angiogenesis, the process of sprouting new blood vessels at the tumor site from pre-existing blood vessels, and how this phenotypic switching affects and impacts tumor growth, remains poorly understood. In this article, we formulate a mathematical model to elucidate the crosstalk between vasculature and tumor cellular heterogeneity during tumor progression. The model results show a strong agreement with the experimental data. Our simulation results demonstrate that ongoing angiogenesis increases tumor growth rate. In addition, we observe that the influence of hypoxic cells on phenotypic switching from normoxic to hypoxic is more pronounced than their influence on the transition from hypoxic to normoxic. Furthermore, we perform a global sensitivity analysis using the Sobol's method to assess the importance of the model's parameters. It highlights that the volume at which blood vessels attain half-maximal rate has the maximum effect on the model.

systems biology↗

bioRxiv2026

Computational Design and Atomistic Validation of a High-Affinity VHH Nanobody Targeting the PI/RuvC Interface of Streptococcus pyogenes Cas9: A Bivalent Hub Strategy for CRISPR-Cas9 Enhancement

The CRISPR-Cas9 system has revolutionized genome engineering, yet its full therapeutic potential remains constrained by challenges in precisely modulating its activity and specificity. Here we report a fully computational end-to-end pipeline for the de novo design of a single-domain VHH nanobody (NbSpCas9-v1) targeting a structurally conserved, non-catalytic epitope at the PAM-interacting (PI) and RuvC-III interface of Streptococcus pyogenes Cas9 (SpCas9; PDB: 4UN3). Nanobody sequences were generated using BoltzGen, a generative diffusion binder design framework, and co-folded with SpCas9 using Boltz-2 to evaluate structural confidence and binding affinity. The top-ranked model (SpCas9_4UN3_Bivalent_Hub_v1) achieved a complex pLDDT of 0.8406, an aggregate score of 0.8016, and an ipTM of >0.8, indicating high confidence in the nanobody-antigen interface. The designed 1,616-residue quaternary complex (SpCas9 + sgRNA + DNA + nanobody) was subjected to 10 ns of all-atom molecular dynamics (MD) simulation using the AMBER14SB force field within the GROMACS/OpenMM framework. The complex stabilized at RMSD [~]6 [A] with a radius of gyration of 39-44 [A], confirming thermodynamic stability under physiological conditions (310 K, 0.15 M NaCl). A conserved 96.3 [A] inter-molecular distance between the nanobody centroid and the HNH catalytic residue H840 establishes NbSpCas9-v1 as a distal, non-inhibitory binder -- ideally suited for a Bivalent Hub architecture recruiting secondary effectors to the Cas9 ribonucleoprotein (RNP). The nanobody-Cas9 interface is stabilized by 8 hydrogen bonds, 4 salt bridges, and [~]1,850 [A]2 of buried solvent-accessible surface area. These results provide a rigorous structural and dynamic foundation for experimental validation of VHH-based CRISPR-Cas9 enhancers and modulators. GRAPHICAL ABSTRACTThe computational workflow proceeds from SpCas9 crystal structure acquisition (PDB: 4UN3) through BoltzGen nanobody design, Boltz-2 structural co-folding, 10 ns explicit-solvent MD validation, and Bivalent Hub functional characterization. The PyMOL rendering below shows the full quaternary complex at atomistic resolution.

bioinformatics↗

bioRxiv2020

Multiplex single-molecule kinetics of nanopore-coupled polymerases

DNA polymerases have revolutionized the biotechnology field due to their ability to precisely replicate stored genetic information. Screening variants of these enzymes for unique properties gives the opportunity to identify polymerases with novel features. We have previously developed a single-molecule DNA sequencing platform by coupling a DNA polymerase to a -hemolysin pore on a nanopore array. Here, we use this approach to demonstrate a single-molecule method that enables rapid screening of polymerase variants in a multiplex manner. In this approach, barcoded DNA strands are complexed with polymerase variants and serve as templates for nanopore sequencing. Nanopore sequencing of the barcoded DNA reveals both the barcode identity and kinetic properties of the polymerase variant associated with the cognate barcode, allowing for multiplexed investigation of many polymerase variants in parallel on a single nanopore array. Further, we develop a robust classification algorithm that discriminates kinetic characteristics of the different polymerase mutants. As a proof of concept, we demonstrate the utility of our approach by screening a library of ~100 polymerases to identify variants for potential applications of biotechnological interest. We anticipate our screening method to be broadly useful for applications that require polymerases with unique or altered physical properties.

synthetic biology↗