Biology subjects

Ravikumar, A.

Publications and source records attributed to Ravikumar, A..

6 recordsLinked to original sources

bioRxiv2026

Sustainable Technology for the Fabrication of Liposomal Phases

Liposomes are self-assembled lipid vesicles capable of encapsulating both hydrophilic and hydrophobic therapeutics, making them versatile platforms in drug delivery and biomedical technology. In this study, the limitations of the classical thin-film hydration method were critically evaluated, and a sustainable, systematically optimized strategy was established for generating defined liposomal lamellar phases. Hydration conditions were optimized, and 4 mL of buffer per 10 mg of lipid was determined to be optimal for effective rehydration and improved statistical reliability of vesicle measurements. A refined probe-sonication protocol (20% amplitude, 5 s ON/55 s OFF pulse) enabled controlled transformation of multivesicular vesicles into stable multilamellar and unilamellar vesicles at net ON-times of 90 s and 185 s, respectively, without overheating or contamination. In addition, a Python-based machine-learning tool was developed for vesicle size characterization. Collectively, these optimizations provided a reproducible and sustainable framework for preparing liposomes across different lamellar phases.

biophysics↗

bioRxiv2024

Mapping kinase domain resistance mechanisms for the MET receptor tyrosine kinase via deep mutational scanning

Mutations in the kinase and juxtamembrane domains of the MET Receptor Tyrosine Kinase are responsible for oncogenesis in various cancers and can drive resistance to MET-directed treatments. Determining the most effective inhibitor for each mutational profile is a major challenge for MET-driven cancer treatment in precision medicine. Here, we used a deep mutational scan (DMS) of [~]5,764 MET kinase domain variants to profile the growth of each mutation against a panel of 11 inhibitors that are reported to target the MET kinase domain. We validate previously identified resistance mutations, pinpoint common resistance sites across type I, type II, and type I [1/2] inhibitors, unveil unique resistance and sensitizing mutations for each inhibitor, and verify non-cross-resistant sensitivities for type I and type II inhibitor pairs. We augment a protein language model with biophysical and chemical features to improve the predictive performance for inhibitor-treated datasets. Together, our study demonstrates a pooled experimental pipeline for identifying resistance mutations, provides a reference dictionary for mutations that are sensitized to specific therapies, and offers insights for future drug development.

cancer biology↗

bioRxiv2023

Uncovering Protein Ensembles: Automated Multiconformer Model Building for X-ray Crystallography and Cryo-EM

In their folded state, biomolecules exchange between multiple conformational states that are crucial for their function. Traditional structural biology methods, such as X-ray crystallography and cryogenic electron microscopy (cryo-EM), produce density maps that are ensemble averages, reflecting molecules in various conformations. Yet, most models derived from these maps explicitly represent only a single conformation, overlooking the complexity of biomolecular structures. To accurately reflect the diversity of biomolecular forms, there is a pressing need to shift towards modeling structural ensembles that mirror the experimental data. However, the challenge of distinguishing signal from noise complicates manual efforts to create these models. In response, we introduce the latest enhancements to qFit, an automated computational strategy designed to incorporate protein conformational heterogeneity into models built into density maps. These algorithmic improvements in qFit are substantiated by superior Rfree and geometry metrics across a wide range of proteins. Importantly, unlike more complex multicopy ensemble models, the multiconformer models produced by qFit can be manually modified in most major model building software (e.g. Coot) and fit can be further improved by refinement using standard pipelines (e.g. Phenix, Refmac, Buster). By reducing the barrier of creating multiconformer models, qFit can foster the development of new hypotheses about the relationship between macromolecular conformational dynamics and function.

biophysics↗

bioRxiv2020

Automated continuous evolution of proteins in vivo

We present automated continuous evolution (ACE), a platform for the hands-free directed evolution of biomolecules. ACE pairs OrthoRep, a genetic system for continuous targeted mutagenesis of user-selected genes in vivo, with eVOLVER, a scalable and automated continuous culture device for precise, multi-parameter regulation of growth conditions. By implementing real-time feedback-controlled tuning of selection stringency with eVOLVER, genes of interest encoded on OrthoRep autonomously traversed multi-mutation adaptive pathways to reach desired functions, including drug resistance and improved enzyme activity. The durability, scalability, and speed of biomolecular evolution with ACE should be broadly applicable to protein engineering as well as prospective studies on how selection parameters and schedules shape adaptation.

synthetic biology↗

bioRxiv2019

Cold storage reveals distinct metabolic perturbations in processing and non-processing cultivars of potato

Cold-induced sweetening (CIS) causes a great loss to the potato (Solanum tuberosum L.) processing industry wherein selection of potato genotypes using biochemical information through marker-trait associations has found to be advantageous. In the present study, we have performed nuclear magnetic resonance (NMR) spectroscopy-based metabolite profiling on tubers from five potato cultivars (Atlantic, Frito Lay-1533, Kufri Jyoti, Kufri Pukhraj, and PU1) differing in their CIS ability and processing characteristics at harvest and after one month of cold storage at 4{degrees}C. A total of 39 water-soluble metabolites were detected using 1H NMR. Multivariate statistical analysis indicated significant differences in metabolite profiles between processing and non-processing potato cultivars. Further analysis revealed distinct metabolite perturbations as induced by cold storage in both types of cultivars wherein significantly affected metabolites were categorized mainly as sugars, sugar alcohols, amino acids, and organic acids. Significant metabolic perturbations were used to carry out metabolic pathway analysis that in turn tracked 130 genes encoding enzymes (involved directly and/or indirectly) involved in CIS pathway using potato genome sequence survey data. Based on the metabolite perturbations, the possible relevant metabolite biomarkers, significantly affected metabolic pathways, and key candidate genes responsible for the observed metabolite variation were identified. Overall, studies provided new insights in further manipulation of specific metabolites playing a crucial role in determining the cold-induced ability and processing quality of potato cultivars for improved quality traits.\n\nHighlightMetabolomic profiling using 1D 1H-NMR and bioinformatics analysis of potato cultivars for the identification of metabolites and genes controlling biochemical pathways in cold-stored potato tubers

plant biology↗

bioRxiv2018

Scalable continuous evolution of genes at mutation rates above genomic error thresholds

Directed evolution is a powerful approach for engineering biomolecules and understanding adaptation1-3. However, experimental strategies for directed evolution are notoriously low-throughput, limiting access to demanding functions, multiple functions in parallel, and the study of molecular evolution in replicate. Here, we report OrthoRep, a yeast orthogonal DNA polymerase-plasmid pair that stably mutates ~100,000-fold faster than the host genome in vivo, exceeding error thresholds of genomic replication that lead to single-generation extinction4. User-defined genes in OrthoRep continuously and rapidly evolve through serial passaging, a highly scalable process. Using OrthoRep, we evolved drug resistant malarial DHFRs 90 times and uncovered a more complex fitness landscape than previously realized5-9. We find rare fitness peaks that resist the maximum soluble concentration of the antimalarial pyrimethamine - these resistant variants support growth at pyrimethamine concentrations >40,000-fold higher than the wild-type enzyme can tolerate - and also find that epistatic interactions direct adaptive trajectories to convergent outcomes. OrthoRep enables a new paradigm of routine, high-throughput evolution of biomolecular and cellular function.

synthetic biology↗