Using open-source parts and 3D-printed components, the Lee lab develops a robotic system for mammalian cell cultures that accurately reproduces user-defined concentration profiles for one or more stimuli, such as cytokines or drugs. The team applies the dynamic stimulation system to investigate NF-kB signaling in single cells exposed to time-varying concentrations of TNF, a molecular network that is often deregulated in autoimmunity and cancer. Cellular responses to dynamic stimuli reveals context-dependent sensitivities and new classes of single cell responses that are distinct from the canonical NF-kB response during persistent stimulation. Guided by computational modeling, the team show that new response classes can be modulated with chemicals that target rates for basal cellular processes, including transcription and translation.
Taken together, the work shows that dynamic stimuli can be used to more accurately recapitulate biological complexity, to reveal hidden capabilities of biological systems, and to provide new opportunities to rationally manipulate disease-associated signaling mechanisms.
Mokashi CS, Schipper DL, Qasaimeh MA, Lee REC. A System for Analog Control of Cell Culture Dynamics to Reveal Capabilities of Signaling Networks. (2019) iScience [Epub ahead of print]
Pathway-level information extractor (PLIER): a new tool to quantify pathway level effects in gene expression data
A major challenge in gene expression analysis is to accurately infer relevant biological insights, such as variation in cell-type proportion or pathway activity, from global gene expression studies. We present pathway-level information extractor (PLIER), a broadly applicable solution for this problem that outperforms available cell proportion inference algorithms and can automatically identify specific pathways that regulate gene expression. Our method improves interstudy replicability and reveals biological insights when applied to trans-eQTL (expression quantitative trait loci) identification.
Mao W, Zaslavsky E, Hartmann BM, Sealfon SC, Chikina M. Pathway-level information extractor (PLIER) for gene expression data. Nature Methods; 16, 607–610 (2019)
||Maria Chikina, PhD
George Oster (1940-2018), professor of Cell and Developmental Biology at the University of California, Berkeley, is a pioneer and world leader in biophysics, mathematical biology, and applied mathematics. He is also a great mentor who guided numerous young researchers along their career paths.
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Photo: Informal group meetings almost every morning in a local cafe (taken in year 2005).
A team of University of Pittsburgh neuroscientists and computational biologists have moved another step toward preventing brain cell death after an acute stroke event. In a paper published this week in the Proceedings of the National Academy of Sciences, they describe how first-in-class molecules discovered by student Zhaofeng Ye and Professor Carlos J. Camacho stops a key protein-protein interaction from opening the door to stroke-triggered damage to neurons.
Dr. Carlos Camacho
Yeh CY, Ye Z, Moutal A, Gaur S, Henton AM, Kouvaros S, Saloman J Hartnett-Scott KA, Tzounopoulos T, Khanna R, Aizenman E, Camacho C. Defining the Kv2.1-syntaxin molecular interaction identifies a first-in-class small molecule neuroprotectant. Proc Natl Acad Sci USA. 2019 Jul 15. pii: 201903401. doi: 10.1073/pnas.1903401116.