Biology subjects

Honigfort, D.

Publications and source records attributed to Honigfort, D..

4 recordsLinked to original sources

bioRxiv2026

CytosMPS: an automated multimodal pooled screening platform for protein, morphology and transcriptomics

Cytos Multimodal Pooled Screening (CytosMPS) measures CRISPR guide identity, morphology, native 3' transcriptome, and protein abundance and localization in the same fixed cells. Following IL-1{beta} stimulation, cells with higher nuclear NF-{kappa}B show lower phospho-p38/HSP27 and higher NFKBIA/DUSP1 in the same cell, a measurement neither imaging nor transcriptomics alone provides. TGFBR2 and CTNNB1 perturbations produce distinct multimodal phenotypes. Guide representation and perturbation transcriptional responses agree with an orthogonal single-cell transcriptomic platform.

cell biology↗

bioRxiv2025

Direct In-Sample Sequencing of the 3' Transcriptome Expands the Capabilities of Optical Pooled Screens

We present a platform that directly sequences single guide RNAs and endogenous 3'UTRs in fixed cells while simultaneously measuring protein abundance and cellular morphology. We demonstrate platform capability by performing optical pooled screening of CRISPR-perturbed lung cancer cells. This approach unites direct in-sample RNA sequencing with complementary phenotypic readouts, enabling comprehensive, scalable, and functional genomics analyses within a single experiment.

genomics↗

bioRxiv2025

Unraveling Tyrosine-Kinase Inhibitor Resistance in NSCLC Cells via Same-cell Measurement of RNA, Protein, and Morphological Responses

Non-small cell lung cancer (NSCLC) frequently develops resistance to tyrosine kinase inhibitors (TKIs), limiting the long-term success of targeted therapies. A deeper understanding of resistance mechanisms at the molecular and cellular levels may enable the development of more effective treatment strategies. Here, we applied the Teton detection assay on the AVITI24 platform to measure concurrently RNA, protein, and cellular morphology in NSCLC cell lines treated with the TKIs gefitinib and osimertinib. This single-cell, multiomic analysis revealed distinct expression and morphological profiles between drug-sensitive and resistant cells, including differences in MAPK-related pathway activity. Stratifying responses at the single-cell level uncovered subtle responses not detectable in bulk measurements. We identified CDK4/6 activity as a route of cell survival under TKI treatment and demonstrated that co-treatment with the CDK4/6 inhibitor palbociclib enhanced TKI efficacy. The ability to measure multiomics and cellular morphology in the same cells opens new avenues for future studies aimed at improving personalized treatment strategies in NSCLC and overcoming the obstacles posed by drug resistance.

genomics↗

bioRxiv2025

High-Throughput Multiomics Profiling of Model Systems Using the AVITI24 Platform

We present a multiomics platform comprising Teton, a detection assay system, and AVITI24, a dual-flowcell instrument that performs both cellular imaging and sequencing readout. Teton integrates a compartmentalized flowcell for cell culture with methods to measure morphology, RNA, and protein at subcellular resolution. The platform quantifies morphological features through cell painting of 6 cellular components, RNA expression of up to 350 transcripts via sequencing of oligonucleotides hybridized to mRNA, and protein expression of up to 200 targets using antibody-linked oligonucleotide sequencing. The flow cell accommodates >1 million cells in a 10 cm squared open-well format or can be subdivided into 12 or 48 wells to support experiments with multiple conditions or time points. We describe and validate the detection methods of the platform and showcase its capabilities by co-culturing three cancer cell lines and elucidating the cellular pathways triggered by various drug treatments as a function of time. Using multiple time points enables us to capture the dynamics of cellular processes including receptor activation and signaling cascades. The results demonstrate how different cancer cells evade TNF-induced apoptosis by activating compensatory signaling programs that maintain survival despite pro-apoptotic cues. Our model system replicates previously published results and highlights the versatility of the platform in enabling rapid, high-throughput analysis of complex cellular responses in varied biological contexts.

genomics↗