The transcriptional program in the response of human fibroblasts to serum Iyer et. al. (1999) Presented by: Paya Sarraf Brendan Finicle

Normal fibroblasts require growth factors supplied by serum to proliferate in cell culture FibroblastArrested in G 0 (Quiescent) – serum + serum Entry into cell cycle Rapid proliferation

Growth factor signaling induces a proliferative response via transcriptional changes Growth Factors Mitogens Growth Factors Mitogens Signal cascade Turner, N. and Grose, R Fibroblast growth factor signaling: from development to cancer. Nature Rev. Cancer. 10: Transcription of target genes required for proliferation Outstanding questions: What is the temporal regulation of the transcriptional program in response to serum? Can we cluster groups of genes based on their temporal expression patterns?

What was known? Unknown? Fibroblasts are a useful tool for studying cell cycle progression. However, the extent of their involvement in wound healing was not fully explored Microarrays had recently been developed (1995) by one of the authors in this paper (Pat Brown) at Stanford; their usefulness and efficacy was just starting to become appreciated.

cDNA microarray hybridization to moniter temporal changes in mRNA levels. Serum deprivedSerum for t=x mRNA cDNA Microarray containing 8613 human genes + serum = sample = red – serum = reference = green Yellow = no change Red = increase in sample’s mRNA relative to reference Green = decrease in sample’s mRNA relative to reference

Microarray shows relative differences in gene expression in response to serum Figure 1: Three independent microarrays comparing RNA isolated at 8- hours after addition of serum 1 = protein disulfide isomerase-related protein P5; 2 = IL-8 precursor; 3 = EST AA057170; 4 = VEGF

Analyzing microarray data as temporal clusters Let’s break it down

Breaking it down – Analyzing microarray data as temporal clusters Fold change - Early transcription response - Late transcription response

Is their microarray data reliable? Fig. 3. Expression levels using the TaqMan PCR Assay show a very similar expression profiles ●When there were multiple microarray elements for the same gene (the case for ~ 5% of the genes), the resulting gene expression profiles were nearly identical.

Addition of serum induces rapid transcriptional changes Fig. 4. The expression profiles of 4A and 4B show the activation of genes involved in signal transduction and genes that encode transcription factors, as expected.

Addition of serum induces mediators of proliferation Fig. 5A. Genes that are responsible for controlling the proliferative response show distinctive patterns of regulation. ●Genes highlighted by red arrows are responsible for the inhibition of the cell cycle so it would make sense for them to be downregulated. ●What questions can we ask about WEE1-like kinase? ●What can we postulate regarding the genes highlighted by the black arrows?

Addition of serum induces expression of genes involved in wound repair Fig. 5. Authors intended to study cycle cycle transitions, but found genes which were not to be known to be regulated in fibroblasts, which: Participated in clotting and clot dissolution and local vasoconstriction (endothelin-1) Promoted chemotaxis and activation of neutrophils (COX-2) Promoted angiogenesis (VEGF)

Microarrays as a method of discovery Fig. 5H. Genes originally not implicated in wound healing may indeed have a role.

Temporal clustering of genes can aid in gene discovery Fig. 2. The temporal expression profiles of Cluster D and Cluster F ●9 of the 40 genes in Cluster D have are known to roles in cell cycle progression; Cluster F signal proliferation. This points to the possibility that other unnamed genes in the cluster may have similar functions.

What could they have improved? Perhaps the inclusion of too many genes in Fig. 4 and 5., –Hard to avoid given the less frequent use of supplemental figures in There is not much for the authors to improve; in fact, the protocol that the authors used to construct their microarray is very similar to the protocol Professor Blumberg used to construct the microarray in his lab today.

Papers for further reading Swamy SM, Tan P, Zhu YZ, Lu J, Achuth HN, Moochhala S. Role of phenytoin in wound healing: microarray analysis of early transcriptional responses in human dermal fibroblasts. Biochem Biophys Res Commun Feb 13;314(3): Feezor RJ, Paddock HN, Baker HV, Varela JC, Barreda J, Moldawer LL, Schultz GS, Mozingo DW. Temporal patterns of gene expression in murine cutaneous burn wound healing. Physiol Genomics Feb 13;16(3):341-8.

Main points and key techniques cDNA microarray of 8600 genes to explore the temporal patterns of gene expression of fibroblasts exposed to serum and reference quiescent fibroblasts. Discovered that genes can be clustered into groups based on their temporal patterns of expression. This data may help characterize other unnamed genes in the cluster. Used this data to not only elucidate the transition from G 0 to a proliferation state but also to conclude that fibroblasts play a larger role in wound healing than previously suspected.