title: Extracellular matrix microarrays to study inductive signaling for endoderm specification.
abstract: During tissue development, stem and progenitor cells are faced with fate decisions coordinated by microenvironmental cues. Although insights have been gained from in vitro and in vivo studies, the role of the microenvironment remains poorly understood due to the inability to systematically explore combinations of stimuli at a large scale. To overcome such restrictions, we implemented an extracellular matrix (ECM) array platform that facilitates the study of 741 distinct combinations of 38 different ECM components in a systematic, unbiased and high-throughput manner. Using embryonic stem cells as a model system, we derived definitive endoderm progenitors and applied them to the array platform to study the influence of ECM, including the interactions of ECM with growth factor signaling, on the specification of definitive endoderm cells towards the liver and pancreas fates. We identified ECM combinations that influence endoderm fate decisions towards these lineages, and demonstrated the utility of this platform for studying ECM-mediated modifications to signal activation during liver specification. In particular, defined combinations of fibronectin and laminin isoforms, as well as combinations of distinct collagen subtypes, were shown to influence SMAD pathway activation and the degree of hepatic differentiation. Overall, our systematic high-throughput approach suggests that ECM components of the microenvironment have modulatory effects on endoderm differentiation, including effects on lineage fate choice and cell adhesion and survival during the differentiation process. This platform represents a robust tool for analyzing effects of ECM composition towards the continued improvement of stem cell differentiation protocols and further elucidation of tissue development processes.
  
  
  CONCLUSIONS
  Cellular microarrays can provide the capability to perform high-throughput investigations into the role of microenvironmental signals in a variety of cell functions. This study demonstrates the utility of a high-throughput cellular microarray approach for analyzing the effects of extracellular matrix (ECM) in liver and pancreas differentiation of endoderm progenitor cells. Despite an appreciation that ECM is likely involved in these processes, the influence of ECM, particularly combinations of matrix proteins, had not been systematically explored. In addition to the identification of relevant ECM compositions, this study illustrates the capability of the cellular microarray platform to be integrated with a diverse range of cell fate measurements, which could be broadly applied towards the investigation of cell fate regulation in other tissue development and disease contexts.
authors.affiliation: Massachusetts Institute of Technology, Cambridge, MA, United States; Department of Bioengineering and IBB-Institute for Bioengineering and Biosciences, Instituto Superior Técnico, Universidade de Lisboa, Portugal.
authors.forename: D F Braga
authors.initials: DFB
authors.lastname: Malta
authors.affiliation: Massachusetts Institute of Technology, Cambridge, MA, United States.
authors.forename: N E
authors.initials: NE
authors.lastname: Reticker-Flynn
authors.affiliation: Department of Bioengineering and IBB-Institute for Bioengineering and Biosciences, Instituto Superior Técnico, Universidade de Lisboa, Portugal.
authors.forename: C L
authors.initials: CL
authors.lastname: da Silva
authors.affiliation: Department of Bioengineering and IBB-Institute for Bioengineering and Biosciences, Instituto Superior Técnico, Universidade de Lisboa, Portugal.
authors.forename: J M S
authors.initials: JMS
authors.lastname: Cabral
authors.affiliation: Massachusetts Institute of Technology, Cambridge, MA, United States.
authors.forename: H E
authors.initials: HE
authors.lastname: Fleming
authors.affiliation: University of Pennsylvania, Philadelphia, PA, United States.
authors.forename: K S
authors.initials: KS
authors.lastname: Zaret
authors.affiliation: Massachusetts Institute of Technology, Cambridge, MA, United States; The Howard Hughes Medical Institute, Cambridge, MA, United States; Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 021392, United States; Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
authors.forename: S N
authors.initials: SN
authors.lastname: Bhatia
authors.affiliation: University of Illinois at Urbana-Champaign, Urbana, IL, United States. Electronic address: gunderhi@illinois.edu.
authors.forename: G H
authors.initials: GH
authors.lastname: Underhill
mesh_terms: D000818:Animals; D015415:Biomarkers / Q000378:metabolism; D019521:Body Patterning; D002448:Cell Adhesion; D002452:Cell Count; D002454:Cell Differentiation; D019070:Cell Lineage; D004707:Endoderm / Q000166:cytology / Q000196:embryology*; D005109:Extracellular Matrix / Q000378:metabolism*; D007797:Laminin / Q000378:metabolism; D008099:Liver / Q000166:cytology; D051379:Mice; D046228:Microarray Analysis / Q000379:methods*; D010179:Pancreas / Q000166:cytology; D010766:Phosphorylation; D051381:Rats; D012015:Reference Standards; D015398:Signal Transduction; D051785:Smad Proteins / Q000378:metabolism
chemical_list: D015415:Biomarkers; D007797:Laminin; D051785:Smad Proteins
keywords: Extracellular matrix; High-throughput; Liver; Microarray; Pancreas