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. 2015 Nov 24;13(8):1705-16.
doi: 10.1016/j.celrep.2015.10.032. Epub 2015 Nov 12.

Transcriptional Landscape of Cardiomyocyte Maturation

Hideki Uosaki  1 , Patrick Cahan  2 , Dong I Lee  3 , Songnan Wang  1 , Matthew Miyamoto  1 , Laviel Fernandez  1 , David A Kass  3 , Chulan Kwon  4
Affiliations

Transcriptional Landscape of Cardiomyocyte Maturation

Hideki Uosaki et al. Cell Rep. .

Abstract

Decades of progress in developmental cardiology has advanced our understanding of the early aspects of heart development, including cardiomyocyte (CM) differentiation. However, control of the CM maturation that is subsequently required to generate adult myocytes remains elusive. Here, we analyzed over 200 microarray datasets from early embryonic to adult hearts and identified a large number of genes whose expression shifts gradually and continuously during maturation. We generated an atlas of integrated gene expression, biological pathways, transcriptional regulators, and gene regulatory networks (GRNs), which show discrete sets of key transcriptional regulators and pathways activated or suppressed during CM maturation. We developed a GRN-based program named MatStat(CM) that indexes CM maturation status. MatStat(CM) reveals that pluripotent-stem-cell-derived CMs mature early in culture but are arrested at the late embryonic stage with aberrant regulation of key transcription factors. Our study provides a foundation for understanding CM maturation.

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Figures

Figure 1
Figure 1. Principal Component Analysis of CM maturation
(A) Scheme of the experiments. We obtained cardiac microarray datasets from GEO, ranging from early embryonic to adult hearts. Using the datasets, we dictated transcriptional landscape of cardiomyocyte maturation with gene expression profile, biological function (KEGG pathway), upstream transcriptional regulators (using IPA) and reconstructing GRNs. Those analyses were integrated to generate an atlas and prediction of cardiomyocyte maturation. (B–C) PCA plots of 213 microarray datasets. Early (E8–11, N=17, green), mid (E12–14, N=39, black), late (E16–18, N=26, orange) embryonic, postnatal (P3–10, N=16, blue) and adult (N=114, red). (B) Plot of PC1 and PC2. Linear regression lines for each stage were shown. Samples were clustered and aligned through PC1 axis as maturation progress. (C) Plot of PC2 and PC3. Most of samples were clustered and no pattern for maturation was evident. (D) Proportion of variances in each principal component. PC1 and 2 represented approximately 60% of variance in original data. (E) Box plot of PC1 value for each stage. Box represents 25 to 75 percentile, mid lines indicate median and the whiskers show the smallest to largest values. Outliers (more than 2SD) were shown as circles. See also Figure S1 and Table S1.
Figure 2
Figure 2. Atlas of Transcriptional Landscape during CM maturation
(A–D) Volcano plots of the gene expression changes from one stage to the next. The genes with more than two-fold change and moderate P values of less than 0.01 were colored in red. (E–H) Time course of the changes (log2 fold) of individual genes identified in the volcano plots. Red and blue lines indicate a change of gene increased and decreased one stage to the next, respectively. Black line indicate mean of expression changes of the increased or decreased genes. Error bars indicate standard deviations. (E) Genes changed from early to mid embryonic hearts. (F) Genes changed from mid to late embryonic hearts. (G) Genes changed from late embryonic to neonatal hearts. (H) Genes changed from neonatal to adult hearts. (I–P) KEGG pathways enriched in the differentially regulated genes (P < 0.05 was considered as enriched). Text color represents the pathway categories, Blue: Metabolisms, Red: Cardiac, Orange: PPAR, Green: Cell Cycle and Black: Others. (I–L) Pathways enriched in upregulated genes at the corresponding stages. (M–P) Pathways enriched in downregulated genes at the corresponding stages. (Q–S) Heatmaps of the activation Z-scores of upstream transcriptional regulators, correspond to activation changes from one stage to the next. Red: Higher in later stage, Blue: Lower in later stage. (Q) Transiently activated regulators, (R) Transiently inactivated regulators, and (S) Incrementally changing regulators. See also Figure S2 and Table S2–3.
Figure 3
Figure 3. MatStatCM: GRN-Based Prediction System for CM Maturation
(A–D) Stage-specific GRNs. GRNs of early-embryonic (A), mid-embryonic (B), late-embryonic/neonatal (C) and adult (D) heart. Each node represents a member of GRN, and factors highlighted in red are transcriptional regulators identified in GRN at each stage. Relationships between regulators and members are shown in lines. All nodes are listed in Table S4. (E–H) Assessment of performance with independent datasets from E9 (E, GSE28186), E13–15 (F, GSE32078), E18 (G, GSE8199) and P7-adult (H, GSE38754). Each column represents one microarray dataset and classified values of GRN status for each stage were shown as heatmap. See also Figure S3 and Table S4.
Figure 4
Figure 4. Maturation of PSC-CMs after Long-Term Culture
(A) Immunostaining of PSC-CMs with a-actinin at days 10–30. Scale bar = 20µm. (B) PCA of 213 microarray, superimposed with PSC-CMs at days 10–30. (C) MatStatCM analysis. GRN status of PSC-CMs was similar to early embryonic hearts at day 10, and became mid to late embryonic heart at days 20–30. (D) GRN statuses of PSC-CMs were assessed using the GRN classifiers of each maturation stage. Means + S.D. are shown (n = 3). (E) Ca++ transient of embryonic (E12), neonatal, adult CMs and PSC-CMs. Cells were stimulated every two seconds. (F) Statistics of time (t) to peak 50% and time (t) to baseline (bl) 50% of Ca++ transient. Mean + S.E.M. (n ≥ 9) Codes for imposing PSC-CM data to PCA and analyzing with MatStatCM can be found in Supplemental Data.
Figure 5
Figure 5. Comparison of Regulator Activities
Heatmaps of the differences of transcriptional regulator activities in PSC-CMs compared to late/neonatal (left column) and adult (right column). Text color represents activity changes between neonatal and adult stages. Red: activated, Blue: inactivated. Identified regulators were classified to eight. Venn diagram of classification is shown in the middle. (i–iv) Transcriptional regulators had activities in PSC-CMs similar to either late embryonic/neonatal or adult hearts: (i) similar to adult and higher than late embryonic/neonatal, (ii) similar to late embryonic/neonatal and lower than adult, (iii) similar to late embryonic/neonatal and higher than adult, and (iv) similar to adult and lower than late embryonic/neonatal. (v–vi) Transcriptional regulators had activities in-betweens of the in-vivo counterparts: the regulators were activated (v), and inactivated (vi) from late embryonic/neonate to adult. (vii–viii) Misregulated transcriptional regulators in vitro: (vii) Transcriptional regulators had higher activities in PSC-CMs compared to late embryoic/neonatal and adult heart, and (viii) transcriptional regulators had lower activities in PSC-CMs compared to late embryoic/neonatal and adult heart. See also Figure S4.
Figure 6
Figure 6. Summary of the Study
Using microarray analysis, we developed an atlas (A) and a prediction method of CM maturation (B). (A) An atlas of CM maturation including temporal transcriptional activity and pathway activity changes. (B) Prediction of CM maturation. We developed a prediction method based on GRN, named MatStatCM. (C) We determined PSC-CM maturation progressed but arrested at late embryonic to neonatal stage. There were two groups of transcriptional regulators: (1) the activities of transcriptional regulators were between late embryo/neonate and adult, and (2) too high or too low, compared to the in-vivo counterpart.
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References

    1. Ahmadian M, Suh JM, Hah N, Liddle C, Atkins AR, Downes M, Evans RM. PPARγ signaling and metabolism: the good, the bad and the future. Nat Med. 2013;19:557–566. - PMC - PubMed
    1. Boström P, Mann N, Wu J, Quintero PA, Plovie ER, Panáková D, Gupta RK, Xiao C, Macrae CA, Rosenzweig A, et al. C/EBPβ controls exercise-induced cardiac growth and protects against pathological cardiac remodeling. Cell. 2010;143:1072–1083. - PMC - PubMed
    1. Cahan P, Li H, Morris SA, Lummertz da Rocha E, Daley GQ, Collins JJ. CellNet: Network Biology Applied to Stem Cell Engineering. Cell. 2014;158:903–915. - PMC - PubMed
    1. Cao X, Wang J, Wang Z, Du J, Yuan X, Huang W, Meng J, Gu H, Nie Y, Ji B, et al. MicroRNA profiling during rat ventricular maturation: A role for miR-29a in regulating cardiomyocyte cell cycle re-entry. FEBS Lett. 2013;587:1548–1555. - PubMed
    1. Chan Y-C, Ting S, Lee Y-K, Ng K-M, Zhang J, Chen Z, Siu CW, Oh SKW, Tse H-F. Electrical stimulation promotes maturation of cardiomyocytes derived from human embryonic stem cells. J Cardiovasc Transl Res. 2013;6:989–999. - PubMed

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