Biology subjects

Levin, I.

Publications and source records attributed to Levin, I..

5 recordsLinked to original sources

bioRxiv2025

StabilizeIT: An Automated Workflow for Protein Stabilization

The industrial application of enzymes is often hampered by poor stability and low expression yields. While computational tools can predict stabilizing mutations, many are bound by restrictive licenses that hinder their broader adoption. To address this, we developed StabilizeIT, a powerful, open-access webserver for enhancing protein stability and expression. StabilizeIT integrates a pipeline of curated open-source tools such as ProteinMPNN, AlphaFold2 and SaProt with our state-of-the-art model, SolvIT, which accurately predicts heterologous expression titers in E. coli. This unique combination allows for the simultaneous optimization of melting temperature (Tm) and solubility. The pipeline exhibits remarkable speed, generating dozens of high-quality candidates with predicted high titers and increased stability in under an hour, streamlining the path to experimental validation. To demonstrate its efficacy, StabilizeIT was used to engineer multiple enzymes in our novel biosynthetic pathway for Hyaluronic Acid. The resulting variants showed greatly enhanced thermal stability and expression, proving the pipelines real-world utility. StabilizeIT is now available to the community, offering an accessible and validated solution to accelerate the development of robust proteins for diverse applications. The webserver is freely available at https://stabilizeit.enzymit.com

bioinformatics↗

bioRxiv2025

Vocal Interactions Between Singing Humpback Whales (Megaptera novaeangliae)

Humpback whales construct predictably patterned sequences within multi-hour sessions of sound production. These sequences (called "songs") are some of the most structurally and acoustically complex vocal patterns produced by any mammal. Humpback whale song production is highly dynamic in that individuals constantly modify the properties of songs across multiple time scales throughout their adult lives. Past analyses of co-vocalizing humpback whales suggest that singers within earshot of one another may dynamically and interactively adjust their vocalizations in reaction to what they hear. The current study investigated whether singing humpback whales coordinate their production of overlapping sound patterns either by modulating how long they produce similar patterns or by dynamically adjusting the spectral properties of individual sounds and/or sound sequences. Our results show that the vocal adjustments singing humpback whales make when singing in dyads are diverse and appear to depend on the acoustic context. These findings confirm that individual singers flexibly adjust song features in real-time. When pairs of singers adjust song content, they do so in ways that may increase or decrease the acoustic similarity of concurrent sound patterns. No evidence was found of singers adjusting the number or timing of sound pattern repetitions to alter pattern overlap. However, most singers modified how they produced units after a second singer began singing. The current results suggest that co-singing humpback whales attend to the vocal actions of other audible singers and may sometimes modulate song content to initiate social interactions from long distances. Understanding how singing whales vocally interact can clarify the relevance of singing in coordinating vertebrate behavior.

animal behavior and cognition↗

bioRxiv2025

Contribution of the Tobamovirus resistance gene Tm-1 to control of ToBRFV resistance in tomato

Tomato brown rugose fruit virus (ToBRFV) is a rapidly spreading pathogen that poses a significant threat to tomato production worldwide. We previously identified a locus on tomato chromosome 11 controlling tolerance to the virus. We further established that combining this locus with one that maps to the Tm-1 region on chromosome 2 confers resistance to the virus. Here we sought to determine whether, and how, the Tm-1 gene itself is involved in ToBRFV resistance. Overexpression of Tm-1 in a tolerant genotype significantly reduced viral accumulation, conferring resistance to ToBRFV. On the other hand, overexpression of Tm-1 in a susceptible genotype only delayed symptom appearance. Moreover, effective RNAi-silencing of Tm-1 in the resistant genotype yielded susceptible plants. These findings show that the Tm-1 gene interacts genetically with the locus controlling tolerance on chromosome 11 and that this interaction is critical for achieving effective resistance to ToBRFV. In addition, the symptomatic plants obtained following silencing of Tm-1 in the resistant genotype indicate that tolerance is also dependent on normal expression levels of the recessive tm-1 allele.

plant biology↗

bioRxiv2023

Context-Dependent Design of Induced-fit Enzymes using Deep Learning Generates Well Expressed, Thermally Stable and Active Enzymes

The potential of engineered enzymes in practical applications is often constrained by limitations in their expression levels, thermal stability, and the diversity and magnitude of catalytic activities. De-novo enzyme design, though exciting, is challenged by the complex nature of enzymatic catalysis. An alternative promising approach involves expanding the capabilities of existing natural enzymes to enable functionality across new substrates and operational parameters. To this end we introduce CoSaNN (Conformation Sampling using Neural Network), a novel strategy for enzyme design that utilizes advances in deep learning for structure prediction and sequence optimization. By controlling enzyme conformations, we can expand the chemical space beyond the reach of simple mutagenesis. CoSaNN uses a context-dependent approach that accurately generates novel enzyme designs by considering non-linear relationships in both sequence and structure space. Additionally, we have further developed SolvIT, a graph neural network trained to predict protein solubility in E.Coli, as an additional optimization layer for producing highly expressed enzymes. Through this approach, we have engineered novel enzymes exhibiting superior expression levels, with 54% of our designs expressed in E.Coli, and increased thermal stability with more than 30% of our designs having a higher Tm than the template enzyme. Furthermore, our research underscores the transformative potential of AI in protein design, adeptly capturing high order interactions and preserving allosteric mechanisms in extensively modified enzymes. These advancements pave the way for the creation of diverse, functional, and robust enzymes, thereby opening new avenues for targeted biotechnological applications.

bioinformatics↗

bioRxiv2017

Exact graph-based analysis of scientific articles on clinical trials

This article describes Amorpha, a software package based on new concept of exact graph-based linguistic analysis. Analytical capabilities of Amorpha are demonstrated using analysis of scientific abstracts on clinical trials from PubMed. Current trends in therapy of breast cancer and psoriatic arthritis were analyzed using 400 abstracts on breast cancer and 131 abstracts on psoriatic arthritis. The spectrum of diseases that currently treated with paclitaxel was extracted from 400 most recent abstracts on paclitaxel.\n\nIn addition to text representation, analytical results are presented as graph images showing essential concepts of a text. Amorpha is not designed specifically to analyze clinical trials and will be also useful for analysis of biological scientific articles and regulatory documents. Amorpha does not require any preliminary knowledge base, ensures full coverage of target text and 100% accuracy of obtained results.

bioinformatics↗