Back

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

Lopez, T.; Honigfort, D.; Mah, A.; Thompson, C.; Dien, V.; Dawood, M.; Frankel, E.; Fuller, D.; Jamison, C.; Kelley, R.; Kwon, J.; Liu, Y.; Ren, P.; Saha, S.; Wang, H.; Wong, J.; Zhao, D.; Abtahi, M.; Altomare, A.; Bajari, R.; Bellizzi, A.; Bracamonte, S.; Bradfield, A.; Brown-Greaves, C.; Bui, C.; Charov, K.; Constandse, R.; Cullion, K.; Damron, W.; Dangelo, M.; Davis, L.; Dawood, N.; Dhonde, R.; Elango, K.; Espinosa, S.; Garcia, F.; Gavrila, V.; Gomez, L.; Hastings, D.; Hoang, D.; Juan, W.; Kia, A.; Kim, M.; Krivit, M.; Lama, R.; Mandla, K.; Martinez, A.; Mass, M.; Miller, A.; Neysmith, J.;

2025-05-08 genomics
10.1101/2025.05.03.651997 bioRxiv
Show abstract

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.

Matching journals

The top 11 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.