Biology subjects

Yousefi, H.

Publications and source records attributed to Yousefi, H..

6 recordsLinked to original sources

bioRxiv2026

A massively parallel synthetic gene atlas for learning compact cis-regulatory grammar across cellular contexts

Virtual-cell models increasingly learn from large perturbation atlases, but their view of cis regulation remains limited to endogenous genes embedded in broad native regulatory contexts. Here we introduce Therna Biosciences' Chronos platform and its first public dataset release, comprising two complementary modules of a massively parallel synthetic gene atlas: Penta-47x27K for 5' UTRs/internal-promoter elements and Tria-47x28K for 3' UTR stability elements. Together, these datasets measure ~60,000 compact cis-regulatory elements across approximately 50 cell lines in one pooled experiment. The choice of cell lines here, provided to us courtesy of Tahoe Tx, was rooted in our aim to make this dataset maximally useful for the virtual-cell modeling community. At Therna, we routinely apply Chronos -- part of our RNA-Logix(TM) platform -- beyond cancer cell-line pools, to systems such as primary cells and organoids, via LNP-formulated mRNA delivery. Chronos captures both transcriptional and post-transcriptional gene expression control. Episomal DNA delivery measures DNA-normalized mRNA output, while direct RNA delivery with longitudinal sampling reliably quantifies RNA decay. The RNA-delivery arm uses chemically modified synthetic mRNA incorporating N1-methylpseudouridine, a modification widely used in mRNA therapeutics. To resolve high-complexity libraries of up to 30,000 elements, Chronos pushes the sensitivity limits of single-cell RNA sequencing to quantify individual RNA molecules within single cells. By massively expanding gene regulatory networks with synthetic genes whose variable regulatory code is short and defined, Chronos provides an auxiliary cis-regulatory lens for virtual-cell modeling and enables context-specific cis-trans regulatory interactions to be learned directly.

systems biology↗

bioRxiv2026

Systematic identification of chromatin organizers as tuners of intratumoral heterogeneity

Intratumoral transcriptional heterogeneity (ITH) enables tumor cells to explore diverse phenotypic states, fueling therapeutic resistance and metastatic progression. Yet systematic approaches for identifying non-genetic regulators of this phenotype have been lacking. Here, we develop a multi-scale screening framework that integrates bulk patient transcriptomics, functional in vivo genetic screening, and single-cell transcriptomic and epigenomic profiling to nominate chromatin organizers that modulate ITH in breast cancer. From an initial set of 41 candidates nominated in silico, we identify RNF8 and MIS18A as factors whose perturbation produces coordinated shifts in transcriptomic variability and chromatin accessibility dispersion at the single-cell level, without altering mean expression or genomic copy number. MIS18A acts through a centromere-independent, DNA-methylation-associated pathway. Modulating RNF8 or MIS18A expression tunes chemotherapeutic sensitivity and metastatic potential in vivo: knockdown sensitizes cells and reduces metastatic burden, whereas overexpression confers resistance and promotes progression. Higher expression of both genes predicts shorter patient survival. These findings identify RNF8 and MIS18A as chromatin-level stochastic tuners of transcriptional variability in cancer and provide a generalizable framework for discovering regulators of non-genetic tumor heterogeneity.

cancer biology↗

bioRxiv2025

Integrative analysis of mRNA stability regulation uncovers a metastasis-suppressive program in breast cancer

Heterogeneity in cancer gene expression is typically linked to genetic and epigenetic alterations, yet post-transcriptional regulation likely influences these patterns as well. However, the quantitative contribution of post-transcriptional mechanisms to cancer transcriptome dynamics remains unclear. Here, we systematically measured mRNA dynamics across diverse breast cancer models, revealing that mRNA stability significantly shapes gene expression variability. To decipher the regulatory grammar underlying these dynamics, we developed GreyHound, an interpretable multimodal deep-learning framework integrating RNA sequence features and RNA-binding protein (RBP) expression. GreyHound identified an extensive network of RBPs and their regulons underlying variations in mRNA stability. Among these, we uncovered a metastasis-suppressive regulatory axis centered on the RNA-binding protein RBMS3 and its post-transcriptional control of the redox regulator TXNIP. Functional and molecular analyses revealed that RBMS3 depletion resulted in targeted transcript destabilization, which was associated with poor clinical outcomes and enhanced metastatic potential in xenograft models. Using in vivo epistasis studies, we confirmed that RBMS3 regulation of TXNIP mRNA stability drives this metastasis-suppressive program. These findings position the RBMS3-TXNIP regulatory axis as a key post-transcriptional mechanism in breast cancer and illustrate how interpretable models of RNA dynamics can uncover hidden regulatory programs in disease.

cancer biology↗

bioRxiv2024

A generative framework for enhanced cell-type specificity in rationally designed mRNAs

mRNA delivery offers new opportunities for disease treatment by directing cells to produce therapeutic proteins. However, designing highly stable mRNAs with programmable cell type-specificity remains a challenge. To address this, we measured the regulatory activity of 60,000 5 and 3 untranslated regions (UTRs) across six cell types and developed PARADE (Prediction And RAtional DEsign of mRNA UTRs), a generative AI framework to engineer untranslated RNA regions with tailored cell type-specific activity. We validated PARADE by testing 15,800 de novo-designed sequences across these cell lines and identified many sequences that demonstrated superior specificity and activity compared to existing RNA therapeutics. mRNAs with PARADE-engineered UTRs also exhibited robust tissue-specific activity in animal models, achieving selective expression in the liver and spleen. We also leveraged PARADE to enhance mRNA stability, significantly increasing protein output and therapeutic durability in vivo. These advancements translated to notable increases in therapeutic efficacy, as PARADE-designed UTRs in oncosuppressor mRNAs, namely PTEN and P16, effectively reduced tumor growth in patient-derived neuroglioma xenograft models and orthotopic mouse models. Collectively, these findings establish PARADE as a versatile platform for designing safer, more precise, and highly stable mRNA therapies.

systems biology↗

bioRxiv2024

Self-Assembled Monolayer Transporters Enable Reagentless Analysis of Small Molecule Analytes

The detection of small molecules beyond glucose remains an ongoing challenge in the field of biomolecular sensing owing to their small size, diverse structures, and lack of alternative non-enzymatic sensing methods. Here, we present a new reagentless electrochemical approach for small molecule detection that involves directed movement of electroactive analytes through a self-assembled monolayer to an electrode surface. Using this method, we demonstrate detection of several physiologically relevant small molecules as well as the capacity for the system to operate in several biological fluids. We anticipate that this mechanism will further improve our capacity for small molecule measurement and provide a new generalizable monolayer-based technique for electrochemical assessment of various electroactive analytes.

bioengineering↗

bioRxiv2020

Reagentless Biomolecular Analysis Using a Nanoscale Molecular Pendulum

The ability to sense biological inputs using self-contained devices unreliant on external reagents or reporters would open countless opportunities to collect information about our health and environment. Currently, a very limited set of molecular inputs can be detected using this type of sensor format. The development of versatile reagentless sensors that could track molecular analytes in biological fluids remains an unmet need. Here, we describe a new universal sensing mechanism that is compatible with the analysis of proteins that are important physiological markers of stress, allergy, cardiovascular health, inflammation and cancer. The sensing mechanism we developed is based on the measurement of field-induced directional diffusion of a nanoscale molecular pendulum tethered to an electrode surface and the sensitivity of electron-transfer reaction kinetics to molecular size. Using time-resolved electrochemical measurements of diffusional motion, the presence of an analyte bound to a sensor complex can be continuously tracked in real time. We show that this sensing approach is compatible with making measurements in blood, saliva, urine, tears and sweat and that the sensors can collect data in situ in living animals. The sensor platform described enables a broad range of applications in personalized health monitoring.

bioengineering↗