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J Biomech. 2015 Dec 16;48(16):4327-32. doi: 10.1016/j.jbiomech.2015.10.045. Epub 2015 Nov 5.

Mapping the osteocytic cell response to fluid flow using RNA-Seq.

Author information

1
Division of Musculoskeletal Sciences, Department of Orthopaedics and Rehabilitation, Penn State College of Medicine, Hershey, PA 17033, USA; Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA.
2
Institute for Personalized Medicine, Departments of Biochemistry and Molecular Biology and Pharmacology, Penn State College of Medicine, Hershey, PA 17033, USA.
3
Division of Musculoskeletal Sciences, Department of Orthopaedics and Rehabilitation, Penn State College of Medicine, Hershey, PA 17033, USA; Department of Biomedical Engineering, Penn State College of Engineering, University Park, PA 16802, USA; Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA. Electronic address: hjdonahue@vcu.edu.

Abstract

Bone adaptation to mechanical loading is regulated via signal transduction by mechano-sensing osteocytes. Mineral-embedded osteocytes experience strain-induced interstitial fluid flow and fluid shear stress, and broad shifts in gene expression are key components in the signaling pathways that regulate bone turnover. RNA sequencing analysis, or RNA-Seq, enables more complete characterization of mechano-responsive transcriptome regulation than previously possible. We hypothesized that RNA-Seq of osteocytic MLO-Y4 cells reveals both expected and novel gene transcript regulation in cells previously fluid flowed and analyzed using gene microarrays. MLO-Y4 cells were flowed for 2h with 1Pa oscillating fluid shear stress and post-incubated 2h. RNA-Seq of original samples detected 55 fluid flow-regulated gene transcripts (p-corrected <0.05), the same number previously detected by microarray. However, RNA-Seq demonstrated greater dynamic range, with all 55 transcripts increased >1.5-fold or decreased <0.67-fold whereas 10 of 55 met this cut-off by microarray. Analyses were complimentary in patterns of regulation, though only 6 transcripts were significant in both RNA-Seq and microarray analyses: Cxcl5, Cxcl1, Zc3h12a, Ereg, Slc2a1, and Egln1. As part of a broad inflammatory response inferred by gene ontology analyses, we again observed greatest up-regulation of inflammatory C-X-C motif chemokines, and newly implicated HIF-1α and AMPK signaling pathways. Importantly, we detected both expected fluid flow-sensitive transcripts (e.g. Nos2 [iNOS], Ptgs2 [COX-2], Ccl7) and transcripts not previously identified as flow-sensitive, e.g. Ccl2. We found RNA-Seq advantageous over microarrays because of its greater dynamic range and ability to analyze unbiased estimation of gene expression, informing our understanding of osteocyte signaling.

KEYWORDS:

Fluid flow; Gene expression; Mechanotransduction; Osteocyte; RNA-Seq; Signaling

PMID:
26573903
DOI:
10.1016/j.jbiomech.2015.10.045
[Indexed for MEDLINE]

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