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Doug Lauffenburger


BS Chemical Engineering, University of Illinois, 1975
PhD Chemical Engineering, University of Minnesota, 1979

Lauffenburger lab website

Research summary

Research in the Lauffenburger laboratory aims generally at a quantitative and integrative understanding of the molecular regulatory networks – primarily, although not exclusively, proteomic signaling — that regulate cell phenotypic behaviors (e.g., death, proliferation, migration, differentiation, and protein secretion) in response to environmental stimuli. We are especially interested in constructing and validating computational models that predict how molecular interventions may beneficially modulate cell behavior. Efforts under auspices of the CDP Center program continue to focus on mammalian epithelial cell responses (predominantly hepatocytes) within inflammatory contexts, and development of advances in experimental and computational methods for understanding these responses. Three main project avenues are currently being pursued.

In ongoing project avenue one, we have continued to collaborate with the Sorger laboratory on logic modeling of multi-pathway network governance of cell survival, proliferation, and protein (e.g., cytokine, acute phase regulators, etc.) secretion. We have now established ‘constrained fuzzy logic’ [cFL] as a useful framework for modeling a variety of cell biological problems, including intracellular signaling in hepatocytes as well as cell-cell communication in immune cell populations.

In ongoing project avenue two, we have continued to collaborate with the Han laboratory to create microdevice technology capable of measuring kinase activities on a single-cell basis. Although other methods exist for measuring phosphoprotein levels on a single-cell basis (e.g., flow cytometry, fluorescence microscopy), we have learned from past CDP Center work that kinase activity measurements generally contain greater information content for predicting cell phenotypic responses. Moreover, we seek to measure these vital signaling properties in direct association with the cellular phenotypic behavior. We have constructed a combination of a single-cell lysis probe and a nanofluidic protein concentrator, and have demonstrated measurement of MK2 activity on a fluorescent substrate reporter from a single HepG2 cell whose phenotypic behavior we have observed via microscopic imaging before capture. Most recently, we have shown proof-of-concept for multi-plexing this approach to at least three different kinases from the same individual cell.

In ongoing project avenue three, we have continued to pursue micro-RNA [miR] measurements to our ‘cue-signal-response’ paradigm, since over the past few years a significant role for miRs in modulating signaling protein levels has emerged. We have established a Luminex-based technique for multi-plexed dynamic measurement of putative key miRs in hepatocytic cells (primary and lines) following inflammatory cytokine treatment, for purpose of generating partial least-squares regression [PLSR] models capable of predicting apoptosis responses in manner analogous to (or complementary to) our earlier successes using PLSR modeling centered on kinase activity and phosphoprotein levels. We initially demonstrated proof-of-concept of this new approach for Huh7 cells responding to permutations of TRAIL and Inf-g stimuli, based on time-courses of six miRs across 48 hours post-treatment. Interestingly, the miR measurement time-points seem to be the most important feature for predictive capability, rather than miR identities. Most recently, we have undertaken genome-wide miR-seq measurements, yielding thousands of distinct miRs as their expression is dynamically influenced by particular cytokine treatments. Computational analysis of this massive new data-set is now underway, using PLSR as well as principal component analysis [PCA] techniques.

Finally, this past year we completed a very interesting study on effects of IL7 ligand and receptor dynamics on proliferation and survival signaling in primary mouse T cells. We found that quite mild quantitative differences in IL7R expression levels among different T cell clones exhibiting variations in T cell receptor avidity for cognate antigen produced strong disparities in survival at low IL7 concentrations and in proliferation at high IL7 concentrations. Comparable differences were confirmed for wild-type T cells, that modulation of IL7 concentrations led to alteration of the T cell receptor avidity distribution across native mouse T cell populations. Thus, analogously to work in the Sorger laboratory on how quantitative protein expression level differences yield significant influences on distribution of cytokine-induced apoptosis behavior of epithelial cell lines we have found similar effects for lymphocytes including in vivo.

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This page last modified on June 19th, 2012