Biology subjects

Alperovich, N. Y.

Publications and source records attributed to Alperovich, N. Y..

3 recordsLinked to original sources

bioRxiv2026

GROQ-seq Datasets Across Transcription Factors (LacI, RamR, VanR), T7 RNA Polymerase and TEV Protease

Predicting any proteins function from its sequence alone would be a significant breakthrough in molecular biology. Although machine learning approaches have sought to tackle this, their limited generalizability reflects the absence of sufficiently large, open, diverse, and unified datasets. To address this data gap, we developed a high-throughput experimental platform called GROQ-seq (Growth-based Quantitative Sequencing). In GROQ-seq, a proteins function can be linked to a sequencing-based readout that enables scalable characterization of large variant libraries in Escherichia coli. Here, we present pilot datasets demonstrating its performance across three distinct protein function classes: transcription factors, polymerases, and proteases. The objective of this report is to present the datasets and to provide users with a clear and transparent characterization of their properties, including both the strengths and limitations.

bioengineering↗

bioRxiv2025

Genetically encoded RNA strand exchange circuits for programmable protein expression and computation in cells

Programmable cellular information processing could advance biomanufacturing of chemicals and medicine, and enable smart, living therapeutics and diagnostics1,2. Nucleic acids circuits based on toehold mediated strand exchange (TMSE) show tremendous potential for cellular programming due to their scalable, composable, and biocompatible parts3-6. However, these circuits are constrained primarily to in vitro applications because genetically encoding them is challenging and the principles of TMSE in cells remain unknown. Here we show the first demonstration of genetically encoded RNA strand exchange circuits, designed analogously to state-of-the-art TMSE circuits, in living cells. To elucidate the design principles of TMSE in cells, we develop toehold exchange riboregulators, which convert TMSE to protein expression, enabling precise control of protein translation rate. We find many of the design principles and parts used for TMSE in vitro transfer to Escherichia coli, allowing construction of multi-layer cascades and logic elements. We also identify caveats where strand exchange in cells differ substantially from cell-free systems, even in lysate from the same bacterial strain7, suggesting active cellular processes are involved. Our results further highlight bounds on strand exchange circuit architectures feasible in cells. We anticipate this study will lay the groundwork for developing advanced cellular circuits, bringing nucleic acid computing from the test tube to the cell8-10 and enabling new applications by connecting TMSE to gene expression. More broadly, our results have implications for RNA:RNA interactions and gene regulation in bacteria and provide a synthetic system for exploring such phenomena.

synthetic biology↗

bioRxiv2024

Prevention of ribozyme catalysis through cDNA synthesis enables accurate RT-qPCR measurements of context-dependent ribozyme activity

Self-cleaving ribozymes are important tools in synthetic biology, biomanufacturing, and nucleic acid therapeutics. These broad applications deploy ribozymes in many genetic and environmental contexts, which can influence activity. Thus, accurate measurements of ribozyme activity across diverse contexts are crucial for validating new ribozyme sequences and ribozyme-based biotechnologies. Ribozyme activity measurements that rely on RNA extraction, such as RNA sequencing or reverse transcription-quantitative polymerase chain reaction (RT-qPCR), are generalizable to most applications and have high sensitivity. However, the activity measurement is indirect, taking place after RNA is isolated from the environment of interest and copied to DNA. So these measurements may not accurately reflect the activity in the original context. Here we develop and validate an RT-qPCR method for measuring context-dependent ribozyme activity using a set of self-cleaving RNAs for which context-dependent ribozyme cleavage is known in vitro. We find that RNA extraction and reverse transcription conditions can induce substantial ribozyme cleavage resulting in incorrect activity measurements with RT-qPCR. To restore the accuracy of the RT-qPCR measurements, we introduce an oligonucleotide into the sample preparation workflow that inhibits ribozyme activity. We then apply our method to measure ribozyme cleavage of RNAs produced in Escherichia coli (E. coli). These results have broad implications for many ribozyme measurements and technologies.

synthetic biology↗