The species translation challenge—A systems biology perspective on human and rat bronchial epithelial cells

Abstract

The biological responses to external cues such as drugs, chemicals, viruses and hormones, is an essential question in biomedicine and in the field of toxicology, and cannot be easily studied in humans. Thus, biomedical research has continuously relied on animal models for studying the impact of these compounds and attempted to ‘translate’ the results to humans. In this context, the SBV IMPROVER (Systems Biology Verification for Industrial Methodology for PROcess VErification in Research) collaborative initiative, which uses crowd-sourcing techniques to address fundamental questions in systems biology, invited scientists to deploy their own computational methodologies to make predictions on species translatability. A multi-layer systems biology dataset was generated that was comprised of phosphoproteomics, transcriptomics and cytokine data derived from normal human (NHBE) and rat (NRBE) bronchial epithelial cells exposed in parallel to more than 50 different stimuli under identical conditions. The present manuscript describes in detail the experimental settings, generation, processing and quality control analysis of the multi-layer omics dataset accessible in public repositories for further intra- and inter-species translation studies.

Network-Based Analysis of Nutraceuticals in Human Hepatocellular Carcinomas Reveals Mechanisms of Chemopreventive Action

“…A custom 15‐plex was used to determine in cell lysates the levels of test phosphoproteins: ribosomal protein S6 kinase alpha‐1 (RSK1), heat shock protein beta‐1 (HSPB1, alternate name HSP27), cAMP‐responsive element‐binding protein‐1 (CREB1), protein kinase B (AKT1), p38 mitogen‐activated protein kinase (P38MAPK), mammalian target of rapamycin (TOR), glycogen synthase kinase‐3 beta (GSK3B), dual specificity mitogen‐activated protein kinase kinase‐1 (MEK1), extracellular signal‐regulated kinase‐1 (ERK1), Src homology 2 domain‐containing protein‐tyrosine phosphatase‐2 (SHP2), c‐Jun N‐terminal kinase‐2 (JNK2), dual specificity mitogen‐activated protein kinase kinase 6 (MP2K6), ribosomal protein S6 (RPS6), p70 ribosomal S6 kinase (P70S6K), and nuclear factor‐kappa B (NFKB). Custom antibody‐coupled beads were technically validated as described before ( Supplementary Figures S2‐S5, Supplementary Table S3 ).…”

Prediction of combination therapies based on topological modeling of the immune signaling network in Multiple Sclerosis

“…Subsequently, we developed a multiplex xMAP phosphoprotein panel tailored to logic modeling and aiming to maximize the coverage of the MS-specific network. The panel, which combined previously and newly developed assays, was then optimized to maximize accuracy, reproducibility as well as network coverage (see Supplementary Table S3 and Supplementary Methods S1 ) (26) . After optimization, we selected a set of 17 phosphoproteins with adequate signal to noise ratio that were used for the in vitro assays: AKT1, CREB1, FAK1, GSK3A, HSPB1, IKBA, JUN, MK12, MK03, MP2K1, PTN11, STAT1, STAT3, STAT5, STAT6, TF65, WNK1 ( Supplementary Table S4 ).…”

From expression footprints to causal pathways: contextualizing large signaling networks with CARNIVAL

“…CARNIVAL uses a comprehensive collection of pathway resources available in OmniPath as PKN (16) , though other sources can be used. We performed a benchmarking study using the SBVimprover Species Translation Challenge dataset (17) and compared its performance to an alternative causal reasoning network contextualization tool CausalR (13) . As a case study, we apply CARNIVAL to glomerular gene expression data on IgA nephropathy (IgAN) to gain insights on the cellular processes that regulate its pathophysiology.…”