Nathan Salomonis, PhD

Associate Professor, UC Department of Pediatrics

nathan.salomonis@cchmc.org

Visit the Salomonis LabVisit the Salomonis Lab

About

Biography

The long-term goal of the Salomonis Lab is to develop broadly reusable immune modulatory therapies to target mis-splicing. Our basic premise is that independent genetic drivers of malignancy rely on common splicing alterations that represent novel targets for therapy and disease prevention. The role of splicing dysregulation in disease is profound, with >50% genetic diseases attributed to splicing factor mutations or transcript mis-splicing.

My research addresses major questions related to how splicing alterations occur, in which cell states, their impact on lineage specification, and recurrence across malignancies. To address these challenges, my lab has developed highly used bioinformatics approaches to resolve splicing impacts in disease, integrate diverse single-cell modalities, and redefine disease subtypes. This work focuses on approaches to exploit cutting-edge multi-omic techniques, deep learning and machine learning. Over the last decade, we have used these approaches to reveal novel isoforms regulating stem cell differentiation, splicing factor-mediated disease mechanisms, new disease subtypes and metastable transitional cell states.

I participate in multiple cell atlas initiatives, including the HCA, HuBMAP and LungMAP. Our current work applies deep learning to design new cancer vaccines, create advanced interactive cell atlases, identify novel isoforms that alter tumor extracellular signaling and game theory to resolve clonal heterogeneity in cancer.

BS: University of California, Los Angeles, CA, 1998.

PhD: University of California, San Francisco, CA, 2008.

Postdoctoral Fellow: Gladstone Institutes, San Francisco, CA, 2012.

Interests

Bioinformatics; genomics; cancer genomics; single-cell RNA-Seq analysis; alternative splicing; pathway analysis; pathway visualization; pathway curation; SIDS; stem cell biology; cardiac specification; renal graft dysfunction

Research Areas

Biomedical Informatics, Fibrosis

Publications

Selected

Decision level integration of unimodal and multimodal single cell data with scTriangulate. Li, G; Song, B; Singh, H; Surya Prasath, VB; Leighton Grimes, H; Salomonis, N. Nature Communications. 2023; 14:406.

Selected

Quantifying tumor specificity using Bayesian probabilistic modeling for drug target discovery and prioritization. Li, G; Bhattacharjee, A; Salomonis, N. 2023; 4:2023.03.03.530994.

Selected

Retinoid X receptor promotes hematopoietic stem cell fitness and quiescence and preserves hematopoietic homeostasis. Menéndez-Gutiérrez, MP; Porcuna, J; Nayak, R; Paredes, A; Niu, H; Núñez, V; Paranjpe, A; Gómez, MJ; Bhattacharjee, A; Schnell, DJ; et al. Blood. 2023; 141:592-608.

Selected

Erythroblastic islands foster granulopoiesis in parallel to terminal erythropoiesis. Romano, L; Seu, KG; Papoin, J; Muench, DE; Konstantinidis, D; Olsson, A; Schlum, K; Chetal, K; Chasis, JA; Mohandas, N; et al. Blood. 2022; 140:1621-1634.

Selected

CellDrift: inferring perturbation responses in temporally sampled single-cell data. Jin, K; Schnell, D; Li, G; Salomonis, N; Prasath, VB S; Szczesniak, R; Aronow, BJ. Briefings in Bioinformatics. 2022; 23:bbac324.

Selected

Bromodomain inhibition overcomes treatment resistance in distinct molecular subtypes of melanoma. Dar, AA; Bezrookove, V; Nosrati, M; Ice, R; Patino, JM; Vaquero, EM; Parrett, B; Leong, SP; Kim, KB; Debs, RJ; et al. Proceedings of the National Academy of Sciences of USA. 2022; 119:e2206824119.

Selected

A census of the lung: CellCards from LungMAP. Sun, X; Perl, AK; Li, R; Bell, SM; Sajti, E; Kalinichenko, VV; Kalin, TV; Misra, RS; Deshmukh, H; Clair, G; et al. Developmental Cell. 2022; 57:112-145.e2.

Selected

LungMAP Portal Ecosystem: Systems-Level Exploration of the Lung. Gaddis, N; Fortriede, J; Guo, M; Bardes, EE; Kouril, M; Tabar, S; Burns, K; Ardini-Poleske, ME; Loos, S; Schnell, D; et al. 2021; Preprint:2021.12.05.471312.

Selected

Gain-of-function cardiomyopathic mutations in RBM20 rewire splicing regulation and re-distribute ribonucleoprotein granules within processing bodies. Fenix, AM; Miyaoka, Y; Bertero, A; Blue, SM; Spindler, MJ; Tan, KK B; Perez-Bermejo, JA; Chan, AH; Mayerl, SJ; Nguyen, TD; et al. Nature Communications. 2021; 12:6324.

Selected

DeepImmuno: deep learning-empowered prediction and generation of immunogenic peptides for T-cell immunity. Li, G; Iyer, B; Prasath, VB S; Ni, Y; Salomonis, N. Briefings in Bioinformatics. 2021; 22:bbab160.