Identification of a conserved set of upregulated genes in mouse skeletal muscle hypertrophy and regrowth

Abstract

The purpose of this study was to compare the gene expression profile of mouse skeletal muscle undergoing two forms of growth (hypertrophy and regrowth) with the goal of identifying a conserved set of differentially expressed genes. Expression profiling by microarray was performed on the plantaris muscle subjected to 1, 3, 5, 7, 10, and 14 days of hypertrophy or regrowth following 2 wk of hind-limb suspension. We identified 97 differentially expressed genes (≥2-fold increase or ≥50% decrease compared with control muscle) that were conserved during the two forms of muscle growth. The vast majority (∼90%) of the differentially expressed genes was upregulated and occurred at a single time point (64 out of 86 genes), which most often was on the first day of the time course. Microarray analysis from the conserved upregulated genes showed a set of genes related to contractile apparatus and stress response at day 1, including three genes involved in mechanotransduction and four genes encoding heat shock proteins. Our analysis further identified three cell cycle-related genes at day and several genes associated with extracellular matrix (ECM) at both days 3 and 10. In conclusion, we have identified a core set of genes commonly upregulated in two forms of muscle growth that could play a role in the maintenance of sarcomere stability, ECM remodeling, cell proliferation, fast-to-slow fiber type transition, and the regulation of skeletal muscle growth. These findings suggest conserved regulatory mechanisms involved in the adaptation of skeletal muscle to increased mechanical loading.

the loss of skeletal muscle mass is of clinical importance because it is associated with increased morbidity and mortality, as well as a marked deterioration in the quality of life (35, 43, 68). A broad patient population is affected by significant losses in muscle mass, including those afflicted by various systemic diseases (cancer, sepsis, HIV-AIDS), chronic physical inactivity as a result of long-term bed rest, rheumatoid arthritis, limb immobilization, and sarcopenia. While the personal cost is clear, the healthcare costs of muscle wasting such as those associated with sarcopenia have an important economic impact (24). Recently, there has been a heightened interest in defining the cellular and molecular mechanisms regulating skeletal muscle mass, given the growing recognition that skeletal muscle has a significant influence on whole-body metabolism (55) as well as organismal aging (13).

One strategy that is being pursued in an effort to develop a more effective treatment to prevent or restore the loss of muscle mass under the aforementioned conditions is to exploit our understanding of muscle growth. Although significant progress has been made, the recent identification of novel catabolic and anabolic signaling pathways suggests there still may be heretofore unrecognized genes/pathways involved in the regulation of skeletal muscle mass (21, 22, 25). The objective of this study was to compare the gene expression profile of skeletal muscle undergoing two forms of skeletal muscle growth (hypertrophy and regrowth after atrophy) with the purpose of identifying a conserved set of differentially expressed genes. A similar approach using different models of skeletal muscle atrophy was successfully employed to discover muscle ring finger 1 and muscle atrophy F box/atrogin-1, two skeletal muscle-specific ubiquitin ligases that have a central role in promoting atrophy (7, 17).

We used gene expression profiling by microarray to test our hypothesis that there exists a set of differentially expressed genes that is conserved in both hypertrophy and regrowth following atrophy in the mouse plantaris muscle. Several studies have used microarray to examine gene expression during skeletal muscle hypertrophy (8, 10, 38, 39, 53, 59, 63) and regrowth following atrophy (2, 6, 12, 16, 56), but no studies, to the best of our knowledge, have determined whether there is a set of differentially expressed genes that are conserved between both types of muscle growth.

To test our hypothesis, gene microarray analysis was performed on muscle subjected to 1, 3, 5, 7, 10, and 14 days of regrowth following 14 days of hind-limb suspension, and the genes that were upregulated (≥2-fold increase) and downregulated (≥50% decrease) were identified at each time point. This regrowth data set was then compared with the differentially expressed genes of our previously described hypertrophy data set to find those genes that shared a similar pattern of expression (10). From the commonly upregulated genes, analysis by the Database for Annotation, Visualization and Integrated Discovery (DAVID) identified several sets of genes related to the following groups: “contractile apparatus,” “stress response,” “cell-cycle control,” and “extracellular matrix” (ECM). The finding of a core set of conserved genes in two forms of skeletal muscle growth suggests that these genes may be important for regulating muscle mass and remodeling, thereby providing novel therapeutic targets for the treatment of skeletal muscle loss.

MATERIALS AND METHODS

Animal care.

All procedures involving the use of animals were approved by the University of Kentucky Institutional Animal Care and Use Committee. Eighty-four male C57BL/6J mice (The Jackson Laboratory, Bar Harbor, ME), 5 mo of age, were housed in a temperature- and humidity-controlled facility on a 14-h:10-h light/dark cycle with access to food and water ad libitum.

Experimental design.

The purpose of this study was to compare two models of skeletal muscle growth with the goal of identifying a set of differentially expressed genes that is conserved in the two forms of muscle growth. The first model was hypertrophy induced by synergist ablation; the plantaris muscle was collected after 1, 3, 5, 7, 10, and 14 days of synergist ablation (see Fig. 1A). The second model was regrowth following muscle atrophy induced by 14 days of hind-limb unloading; the plantaris muscle was collected at the same time points as the hypertrophy model but following reloading (see Fig. 1B).

Fig. 1.

Design of the experiments hypertrophy induced by synergist ablation (A) and regrowth following muscle atrophy (B).

Models of muscle regrowth.

The hind-limb suspension and reloading protocol as described by Jackson and colleagues (23) was used to induce regrowth of the mouse plantaris muscle. Following 14 days of hind-limb suspension, mice were released from the suspension apparatus and allowed to freely move about the cage for the designated period of time. At the designated time points (0, 1, 3, 5, 7, 10, and 14 days of reloading), the plantaris muscles were excised, weighed, and processed for downstream analyses. Although the plantaris muscle does not atrophy to the same degree as the soleus muscle following hind-limb suspension, the plantaris has been reported to show a significant (∼20%) decrease in mass following 2 wk of unloading (44). We used the plantaris muscle to allow for a direct comparison to muscle undergoing muscle hypertrophy induced by synergist ablation, as previously described by Chaillou and coworkers (10). Mice and procedures used for the hypertrophy study were the same as those previously described (10). For each model, 42 animals were used (n = 6 per time point).

RNA isolation.

Total RNA was isolated from plantaris muscle stored in RNAlater (Ambion, Austin, TX) at 4°C using TRIzol reagent (Invitrogen, Carlsbad, CA) according to the manufacturer's directions. RNA samples were treated with TURBO DNase (Ambion) to remove genomic DNA contamination. The total RNA concentration and purity were assessed by measuring the optical density (230, 260, and 280 nm) with the Nanodrop 1000 Spectrophotometer (ThermoFisher Scientific, Wilmington, DE). RNA integrity was assessed using the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA); the average RNA integrity number value was 9.46 ± 0.10 and 8.67 ± 0.08 (scale 1–10) for RNA isolated from plantaris muscle undergoing hypertrophy or regrowth, respectively, indicating high-quality RNA with minimal degradation.

Microarray and microarray data analysis.

The microarray hybridization and processing were performed at the University of Kentucky Microarray Core Facility according to the manufacturer's protocol (Affymetrix, Santa Clara, CA). Affymetrix chips (Mouse Gene 1.0 ST) were used to provide coverage of 28,000 protein-coding transcripts and 7,000 noncoding transcripts, of which ∼2,000 are long intergenic noncoding transcripts. As previously published (10), two gene chips were processed for the hypertrophy study at each time point from 250 ng of total RNA. The total RNA was derived from a pooled sample of either the right or left plantaris muscles from six animals. We pooled RNA samples based on the experimental results reported by Kendziorski et al. (26), showing that gene expression from a pooled RNA sample is similar to the average from the individuals comprising the pooled sample. Gene expression data from each chip (chip 1 for the right leg, chip 2 for the left leg) were averaged at each time point and uploaded to Partek Genomics Suite (St. Louis, MO) to identify differentially expressed genes. Given that the gene expression between the two chips from the hypertrophy study (10) was highly correlated (r > 0.99, analysis determined using Partek Genomics Suite) and did not present any significant changes (no changes ≥2-fold increase or ≥50% decrease in gene expression with P < 0.05, ANOVA performed on the 2 sets of chip1 and chip2), only one chip was used to assess gene expression at each time point for the regrowth study; 250 ng of total RNA derived from a pooled sample of the left plantaris muscles from six animals was processed at each time point for the regrowth study.

The criteria for a gene to be considered differentially expressed was a greater than twofold increase or a ≥50% decrease in expression in the experimental group relative to the control group obtained at day 0; a statistical approach was not possible given the limited number of gene chips. We and others have previously used this stringent cutoff to reliably identify differentially expressed genes by microarray analysis (10, 50, 70). At this step of the analysis, we did not set a lower cutoff for the signal intensity to include gene expressed at a low level that might show a significant upregulation in response to mechanical overload or reloading. It is noteworthy that the control group in the hypertrophy study corresponds to nonoverloaded sham muscle, whereas the control group in the regrowth study is the plantaris muscle from mice subjected to 14 days of hind-limb suspension without any reloading (Fig. 1B). Gene expression data has been made available at GEO (http://www.ncbi.nlm.nih.gov/geo) for the hypertrophy study (GSE47098) and regrowth study (GSE56798).

Ingenuity Pathway Analysis (IPA; Ingenuity Systems, Redwood, CA) was used to identify differentially expressed genes during both hypertrophy and regrowth at each time point. The two sets of differentially expressed genes were then compared to find genes that showed a similar pattern of expression during hypertrophy and regrowth. Functional annotation of the set of commonly expressed genes was performed using DAVID, a web-accessible program (http://david.abcc.ncifcrf.gov) (19). Functional groups passed filtering if they reached statistical significance <0.05 (Bonferroni adjusted P value). Upstream Regulator Analysis, an analytics algorithm available in IPA, was then used to determine the predicted upstream regulators that are connected to the genes associated with the functional groups (32).

cDNA synthesis and mRNA analysis by qPCR.

Reverse transcription was performed using 1 μg of total RNA (n = 6 at each time point) with oligo(dT) primer and Superscript III reverse transcriptase (Invitrogen) according the manufacturer's instructions. TaqMan probe and primers for quantitative PCR (qPCR) reactions were obtained from Applied Biosystems as follows: Ankrd1, Mm00496512_m1; Ankrd2, Mm00508030_m1; Csrp3, Mm00443379_m1; Spp1, Mm00436767_m1; Postn, Mm00450111_m1; Ccnd1, Mm00432359_m1; Gapdh, Mm99999915_g1; Rpl38, Mm03015864_g1; Ddit4, Mm00512504_g1. qPCR was performed using TaqMan Gene expression Master Mix (2×) (Invitrogen), using 5 μl of diluted cDNA (1/10 dilution from stock cDNA mixture for Ddit4, Rpl38, and Gapdh; 1/20 dilution from stock cDNA mixture for Ankrd1, Ankrd2, and Csrp3) and 1 μl of primer mix in a 20-μl final volume. qPCR was performed using an ABI 7500 RT-PCR system (Invitrogen). Quantification cycles (Cq) were determined by ABI 7500 software v2.0.1. Absolute quantification was achieved by exponential conversion of the Cq using the qPCR efficiency. qPCR efficiency was estimated from standard curves obtained by serial dilutions (1-log range) of a pooled sample for each RT set from either the hypertrophy or regrowth study (54). Relative quantification of the target mRNA was obtained after the normalization with Rpl38 gene for the regrowth study. Given that Rpl38 expression was not constant in hypertrophy study (data not shown), relative quantification of target mRNA was obtained after the normalization with the geometric mean of exponential conversion of the Cq of three reference genes (Rpl38, Gapdh, and Ddit4). Importantly, the geometric mean based on these genes was unchanged across the hypertrophy time course.

Statistical analysis.

The muscle mass, total RNA concentration, and qPCR data are presented as means ± SE. The changes in muscle mass and total RNA concentration were analyzed using a one-way ANOVA followed by a Dunnett's post hoc test. The changes in gene expression (qPCR) were determined using unpaired t-tests or Mann-Whitney tests when heterogeneity of variance and absence of distribution normality were observed. For these statistical analyses, the level of significance was set at P < 0.05.

RESULTS

The present study is a complement to a previous study, in which we performed a transcriptome analysis of skeletal muscle hypertrophy induced by synergist ablation (10). In that study, we presented total RNA concentration data as a measure of the change in ribosome content in response to a hypertrophic stimulus. To facilitate a direct comparison with the regrowth total RNA concentration data, it is presented again in Fig. 2B.

Fig. 2.

Plantaris muscle mass (A) and total RNA concentration (B) during hypertrophy and regrowth following muscle atrophy. All results are expressed as the means ± SE. *Significantly different from day 0 during hypertrophy. #Significantly different from day 0 during regrowth.

Skeletal muscle mass and total RNA content during muscle growth.

To compare the muscle growth in response to mechanical overload induced by synergist ablation (hypertrophy) and reloading following a 14-day period of hind-limb unloading (regrowth), we measured plantaris muscle mass. Consistent with previous studies using these two models of skeletal muscle growth, the absolute muscle mass significantly increased by ∼62% and ∼15% after 14 days of mechanical overload and reloading, respectively (44, 46) (Fig. 2A). The early increase in muscle mass observed after 1 day of mechanical overload most likely reflects muscle edema and fiber swelling resulting from the inflammatory response associated with surgical ablation; in contrast, the changes in muscle mass observed between days 7 and 14 are the result of myofibrillar protein accretion. It is noteworthy that the body mass was not affected over the time course in the two models of muscle growth (data not shown).

Given that ribosomal RNA is the major fraction of the RNA pool (∼85%), total RNA concentration was measured to provide an indication of the change in translation capacity, presumably by an increase in ribosome biogenesis. As shown in Fig. 2B, the total RNA concentration remained constant during regrowth, whereas, in contrast, it progressively increased during hypertrophy until day 7 and then plateaued for the remainder of the time course. We also recently reported that several genes involved in ribosome biogenesis or encoding of ribosome proteins were upregulated during hypertrophy following synergist ablation (9), whereas the expression of the majority of these genes remained unchanged during regrowth (data not shown). Together, these results indicate that greater levels of muscle growth, such as those observed with hypertrophy, are associated with an increase in ribosome biogenesis, whereas more modest levels of growth as seen with regrowth do not appear to involve ribosome biogenesis.

Differentially expressed genes during hypertrophy and regrowth.

To obtain a comprehensive view of gene expression during muscle growth, we used IPA software to identify differentially expressed genes after 1, 3, 5, 7, 10, and 14 days of muscle growth (hypertrophy and regrowth). As shown in Fig. 3A, about 2,000 genes were differentially expressed (≥2-fold increase or ≥50% decrease in gene expression) after 1 day of mechanical overload, a number that progressively increased to reach about 3,500 genes after 7 days and then decreased through day 14. Among the differentially expressed genes identified during this 14-day period of mechanical overload, the majority (60–70%) was upregulated at any given time point. Over the same period of time, the number of differentially expressed genes during regrowth was roughly 10-fold less (250 to 392 genes) than with hypertrophy (Fig. 3B). In contrast, the vast majority (75–96%) of differentially expressed genes with regrowth was downregulated.

Fig. 3.

Number of genes differentially expressed during hypertrophy (A) and regrowth (B) and number of conserved genes differentially expressed during hypertrophy and regrowth (C). The genes were initially selected by Partek Genomics Suite from a 2-fold increase or a 50% decrease in gene expression between 1) the overloaded muscle and nonoverloaded muscle (hypertrophy) and 2) the reloaded muscle and 14-day unloaded muscle by hind-limb suspension (regrowth). These genes were then uploaded in Ingenuity Pathway Analysis software to identify from the mapped genes 1) the number of upregulated and downregulated during hypertrophy (A) and regrowth (B) and 2) the number of genes commonly upregulated and downregulated during hypertrophy and regrowth (C).

The two sets of differentially expressed genes were then compared to identify genes that shared a conserved pattern of expression during both types of muscle growth. On the basis of IPA analysis, the number of genes that were differentially expressed during both hypertrophy and regrowth peaked at day 1 and then progressively decreased across the time course except at day 10, where a modest increase in the number of conserved genes was observed (Fig. 3C). Interestingly, among the genes that were upregulated after 1 and 3 days of regrowth (91 and 57 genes, respectively; Fig. 3B), a large portion of these genes (65% and 47%, respectively; Fig. 3C) was also upregulated during hypertrophy. In contrast, despite a significant number of downregulated genes during regrowth (Fig. 3B), only a small number of these genes shared a conserved pattern of expression during hypertrophy (Fig. 3C).

The expression of the conserved upregulated genes during both hypertrophy and regrowth is presented in Table 1. Among these 86 genes, all except four genes (Ankrd2, Csrp3, Flnc, and Xirp1) showed a larger increase in expression during hypertrophy than regrowth. A dramatic increase in gene expression (>10-fold) was observed for 10 genes during hypertrophy (Ankrd1, Cd68, Ccl8, Postn, Rrad, Serpine1, Spp1, Timp1, Tnc, and Wfdc17), whereas only Ankrd1 showed a similar increase during regrowth. Nine genes were commonly upregulated during both regrowth and hypertrophy for at least three out of the six time points: Csrp3, Il2rg, Postn, and Timp1 (5 time points), Col1a1 (4 time points), Ankrd1, Cd68, Plk1, and Spp1 (3 time points). The expression of the 11 conserved downregulated genes during hypertrophy and regrowth is presented in Table 2. Among the genes identified, almost all of them were more downregulated during hypertrophy rather than during regrowth. Moreover, only one gene (Dhrs7c) was commonly downregulated for at least half of the time course (3 time points).

Table 1.

Expression of the common upregulated genes during hypertrophy and regrowth

			Fold Change
			Day 1		Day 3		Day 5		Day 7		Day 10		Day 14
Type	Symbol	Gene Name	RG	H	RG	H	RG	H	RG	H	RG	H	RG	H
Binding protein	CASQ2	Calsequestrin 2					2.3	3.6
	CDKN1A	Cyclin-dependent kinase inhibitor 1A	2.7	6.8
	CGREF1	Cell growth regulator with EF-hand domain 1	2.1	6.8
	CLEC12A	C-type lectin domain family 12, member A									2.0	3.8
	EHD4	EH-domain-containing 4	2.9	3.7
	ENAH	Enabled homolog	4.1	2.6	2.1	2.5
	GADD45A	Growth arrest and DNA-damage-inducible, α	2.9	7.0
	KIF11	Kinesin family member 11									2.1	2.7
	MKI67	Antigen identified by monoclonal antibody Ki-67			2.5	4.2					2.8	2.5
	MT1H	Metallothionein 1H	2.3	6.4	2.4	5.3
	PTX4	Pentraxin 4, long									2.3	2.6
	RGCC	Regulator of cell cycle	3.0	5.9
	S100A8	S100 calcium-binding protein A8	2.9	5.7	3.2	2.0
	TIAM2	T-cell lymphoma invasion and metastasis 2	2.3	2.5
	TTC9	Tetratricopeptide repeat domain 9	2.6	2.5	2.2	3.3
	WDR1	WD repeat domain 1	2.2	2.0
	XIRP1	Xin actin-binding repeat-containing 1	7.5	4.4	3.0	2.4
Chaperone protein	DNAJB1	DnaJ (Hsp40) homolog, subfamily B, member 1	“2.4”	“5.5”
	HSP90AA1	Heat shock protein 90 kDa α (cytosolic), class A member 1	“3.0”	“3.9”
	HSPA1A	Heat shock 70 kDa protein 1A	“4.9”	“6.0”
	HSPB1	Heat shock 27 kDa protein 1	“2.7”	“2.3”	2.2	2.2
Cyclin	CCNA2	Cyclin A2			2.2	7.5					2.6	4.0
	CCND1	Cyclin D1			2.1	4.0			2.1	3.1
Cytokine	CCL8	Chemokine (C-C motif) ligand 8			2.2	11.9
	SPP1	Secreted phosphoprotein 1	2.4	10.3	2.2	16.6					3.4	4.4
Cytoskeleton protein	FLNC	Filamin C, γ	4.3	2.2
	GAS2L3	Growth arrest-specific 2 like 3	2.2	4.2
	NES	Nestin	2.0	3.6
	TUBB6	Tubulin, β6 class V	2.8	9.2
Extracellular matrix protein	COL1A1	Collagen, type I, α1					2.0	6.3	2.1	8.1	2.5	7.8	2.1	7.4
	COL1A2	Collagen, type I, α2									2.0	6.5
	COL8A1	Collagen, type VIII, α1			2.1	4.2
	FN1	Fibronectin 1									2.2	4.3
	POSTN	Periostin, osteoblast specific factor			5.5	6.2	4.2	10.5	2.1	11.9	3.3	11.9	2.1	10.5
	TNC	Tenascin C			2.2	11.8
Enzyme	AMPD3	Adenosine monophosphate deaminase 3	2.7	6.2
	AZIN1	Antizyme inhibitor 1	2.4	2.9
	CES2C	Carboxylesterase 2C	2.2	2.2
	CH25H	Cholesterol 25-hydroxylase	2.3	3.8
	EGLN3	EGL nine homolog 3	2.1	2.6
	RRAD	Ras-related associated with diabetes	2.8	16.2
	RRAS2	Related RAS viral (r-Ras) oncogene homolog 2	2.2	2.4
	SRXN1	Sulfiredoxin 1	3.0	8.7
Growth factor	HBGEF	Heparin-binding EGF-like growth factor	3.4	8.3
Histone	HIST1H2AD	Histone cluster 1, H2ad			2.8	2.9					3.0	2.2
	HIST1H2BD	Histone cluster 1, H2bd			2.0	2.5
	HIST1H3A	Histone cluster 1, H3a									2.4	2.4
	HIST2H3C	Histone cluster 2, H3c									2.4	2.4
Kinase	PLK1	Polo-like kinase 1			2.0	7.7			2.1	7.8	2.4	3.0
Membrane protein	CD52	CD52 molecule									2.2	4.3
	CD68	CD68 molecule	4.1	9.6	3.3	12.3	2.2	10.3
	EMB	Embigin	2.4	8.6
	FXYD5	FXYD domain-containing ion transport regulator 5	2.1	5.0
	IFITM6	Interferon-induced transmembrane protein 6			2.0	2.8
Other	C9ORF174	Chromosome 9 open reading frame 174					2.6	2.2
	GM5105	Predicted gene 5105	2.1	3.3
	KLHL30	Kelch-like 30	2.5	2.4
	NR4A3	Nuclear receptor subfamily 4, group A, member 3	3.6	3.2
Peptidase	ADAMTS9	ADAM metallopeptidase with thrombospondin type 1 motif, 9	2.2	4.6							2.1	2.0
	OTUD1	OTU domain-containing 1	4.2	7.1
	USP28	Ubiquitin specific peptidase 28	3.1	2.8
Protease inhibitor	SERPINA3	Serpin peptidase inhibitor, clade A, member 3			2.3	2.1
	SERPINE1	Serpin peptidase inhibitor, clade E, member 1	2.7	12.7	2.1	15.6
	TIMP1	TIMP metallopeptidase inhibitor 1	3.4	20.3	3.1	33.0	3.1	29.1	2.9	21.5	3.0	13.4
	WFDC17	WAP four-disulfide core domain 17			2.0	11.5
Sarcomeric protein	ACTC1	Actin-α, cardiac muscle 1							3.0	6.5
	ANKRD1	Ankyrin repeat domain 1	12.2	24.9	4.4	16.8	2.7	11.8
	ANKRD2	Ankyrin repeat domain 2	6.8	2.1
	CSRP3	Cysteine and glycine-rich protein 3	8.6	2.6	6.1	2.7	4.5	2.4			2.8	2.2	2.2	2.5
	MYL6B	Myosin, light chain 6B, alkali, smooth muscle and nonmuscle					2.3	4.3
Transcription regulator	ATF3	Activating transcription factor 3	8.5	9.2	2.0	3.4
	IFRD1	Interferon-related developmental regulator 1	2.8	4.1
	KBTBD5	Kelch repeat and BTB (POZ) domain-containing 5	3.3	6.1
	LMCD1	LIM and cysteine-rich domains 1	3.5	2.6
	RCAN1	Regulator of calcineurin 1	3.1	2.4
	RUNX1	Runt-related transcription factor 1	3.1	9.3
Transmembrane receptor	EDA2R	Ectodysplasin A2 receptor	2.3	2.1
	IGSF6	Immunoglobulin superfamily, member 6									2.1	3.6
	IL2RG	Interleukin 2 receptor-γ	2.6	5.1	2.1	7.5	2.0	8.5	2.0	7.8	2.3	6.2
	PVR	Poliovirus receptor	2.5	8.2
	TLR4	Toll-like receptor 4	2.3	6.5
	TNFRSF12A	Tumor necrosis factor receptor superfamily, member 12A	3.7	4.3
	TNFRSF22	Tumor necrosis factor receptor superfamily, member 22	3.1	7.4
Transporter	ATP13A3	ATPase type 13A3	2.2	2.7
	LCN2	Lipocalin 2	2.0	4.3
	SLC22A4	Solute carrier family 22, member 4	2.1	4.1

The gene expression was determined by microarray, and the results indicate the fold change relative to day 0. RG, regrowth; H, hypertrophy. For clarity, several functional annotations were regrouped by the terms contractile apparatus and extracellular matrix. Bold font refers to cell-cycle control group; italic font refers to extracellular matrix group; underlined font refers to contractile apparatus group; font in quotation marks refers to stress response group; note that HSPB1 falls under both contractile apparatus and stress response groups.

Table 2.

Expression of the common downregulated genes during hypertrophy and regrowth

			Fold Change
			Day 1		Day 3		Day 5		Day 7		Day 10		Day 14
Type	Symbol	Gene Name	RG	H	RG	H	RG	H	RG	H	RG	H	RG	H
Binding protein	CHAC1	ChaC, cation transport regulator homolog 1			0.43	0.47	0.46	0.29
	SH3RF2	SH3 domain-containing ring finger 2					0.49	0.31
Enzyme	CYP2C40	Cytochrome P450, family 2, subfamily c, polypeptide 40									0.48	0.19
	CYP4A22	Cytochrome P450, family 4, subfamily A, polypeptide 22							0.48	0.16
	DHRS7C	Dehydrogenase/reductase (SDR family) member 7C			0.46	0.14	0.45	0.20			0.50	0.30
	INMT	Indolethylamine N-methyltransferase					0.49	0.13
Other	A930018M24Rik	RIKEN cDNA A930018M24 gene	0.41	0.16
	SPT1	Salivary protein 1							0.42	0.45
	SNORD116	Small nucleolar RNA, C/D box 116			0.29	0.46
Transmembrane receptor	CHRNE	Cholinergic receptor, nicotinic-ϵ	0.49	0.35	0.49	0.21
	MC5R	Melanocortin 5 receptor					0.47	0.29

The gene expression was determined by microarray, and the results indicate the fold change relative to day 0.

Functional annotations associated with the conserved upregulated genes.

Functional annotation of the set of conserved differentially expressed genes was performed at each time point using DAVID. The functional groups considered significantly enriched (Bonferroni adjusted P < 0.05) from the set of conserved upregulated genes are presented in Table 3. The genes associated with the different functional groups and their respective fold change in expression relative to control are presented in Table 1. It is noteworthy that no functional groups were identified from the conserved downregulated genes. Consistent with the number of conserved upregulated genes (see Fig. 3C), significantly enriched functional groups were only identified at days 1, 3, and 10.

Table 3.

Functional annotations identified from the common upregulated genes during hypertrophy and regrowth

	Functional Annotation	Number of Genes	Adjusted P Value
Day 1	I band	5	0.002
	Sarcomere	5	0.010
	Contractile fiber part	5	0.013
	Myofibril	5	0.016
	Contractile fiber	5	0.019
	Stress response	4	0.047
Day 3	Extracellular matrix	5	0.027
	Cell cycle control	3	0.040
Day 10	Extracellular matrix	6	0.000
	Proteinaceous extracellular matrix	6	0.002
	Extracellular matrix-receptor interaction	4	0.002
	Extracellular matrix part	4	0.011
	Extracellular region part	7	0.018

The functional annotations were determined from DAVID, using a Bonferroni adjusted P value <0.05. Given that the 5 first functional annotations identified at day 1 were closely related and were associated with the same genes, they were regrouped by the term contractile apparatus in Table 1. Similarly, the 5 functional annotations identified at day 10 were closely related and were regrouped by the term extracellular matrix in Table 1.

Five functional groups closely related to contractile apparatus were found to be significantly enriched at day 1 (I band, sarcomere, contractile fiber part, myofibril, and contractile fiber) and contained the same genes: three genes encoding proteins involved in mechanotransduction (Ankrd1, Ankrd2, and Csrp3), one gene related to actin crosslinking (Flnc), and one heat shock protein (HSP)-encoding gene (Hspb1). On the basis of the microarray data (Table 1), the increased expression of these genes was higher during hypertrophy for Ankrd1, during regrowth for Ankrd2, Csrp3, and Flnc, and similar between the two models of growth for Hspb1. The functional group stress response was also identified at day 1 and contained four HSP-encoding genes (Dnajb1, Hsp90aa1, Hspa1a, and Hspb1). The increased expression observed from microarray analysis was higher during hypertrophy for Dnajb1 and remained roughly similar during both hypertrophy and regrowth for the three other genes (Table 1).

The functional group ECM and cell-cycle control were significantly enriched at day 3. The genes associated with the ECM group encode three extracellular matrix proteins (Col8a1, Postn, and Tnc), one cytokine (Spp1), and one protease inhibitor (Timp1). For all ECM-related genes, the fold change increase determined from our microarray analysis was higher during hypertrophy than regrowth (Table 1). The three genes related to cell-cycle control encode two cyclin proteins (Ccna2 and Ccnd1) and a nuclear protein (Mki67), and their increased expression was higher during hypertrophy than regrowth at day 3 (Table 1).

The five functional groups identified at day 10 were all related to the ECM and shared the same set of genes. Seven genes were associated with these functional groups and encode four extracellular matrix proteins (Col1a1, Col1a2, Fn1, and Postn), one peptidase (Adamts9), one cytokine (Spp1), and one protease inhibitor (Timp1). The fold change increase determined from our microarray analysis was higher during hypertrophy than regrowth for all of these genes, except for Adamts9 (Table 1). It is noteworthy that three genes related to ECM were conserved at both days 3 and 10 (Postn, Spp1, and Timp1; Table 1).

Upstream regulators predicted from the genes associated with the functional groups.

We used Upstream Regulator Analysis, a tool available in IPA, to identify possible upstream regulators that were connected to the genes associated with the functional groups. Although these genes were upregulated during both regrowth and hypertrophy, the fold changes in gene expression were different in these two models of muscle growth. For this reason, the expression of the genes associated with the functional groups was not taken into account when performing the analysis. For each functional group, only the top three predicted upstream regulators identified from the overlap P value are presented (Table 4). Among the upstream regulators identified, Dysf, a gene involved in skeletal muscle repair (27), was predicted to affect the expression of Ankrd1, as well as the three HSP-encoding genes Dnajb1, Hspa1a, and Hspb1. The genes encoding the heat shock transcription factors 1 and 2 (Hsf1 and Hsf2) were predicted to promote the expression of several components of the group stress response. In addition, Pdgfb, a growth factor-encoding gene, was predicted to activate several ECM components at both days 3 and 10. Except for Scxa/Scxb, which was only upregulated in response to hypertrophy, none of the predicted upstream regulators was differentially expressed according to the defined criteria (i.e., ≥2-fold increase or a ≥50% decrease in gene expression). Although we cannot exclude the possibility that the expression of these predicted upstream regulators is affected at the protein level, our data suggest that these factors may not be essential for the regulation of the genes associated with the functional groups.

Table 4.

Upstream regulators predicted from the genes associated with the functional groups

						Fold Change
	Functional Annotation	Upstream Regulator	Gene Name	Overlap P Value	Target Molecules	RG	H
Day 1	Contractile apparatus	LIPE	Lipase, hormone sensitive	2,83E-06	ANKRD1 (-), ANKRD2 (-), CSRP3 (-)	0,98	0,76
		RAF1	V-raf-1 murine leukemia viral oncogene homolog 1	1,23E-05	ANKRD1 (+), ANKRD2 (+), HSPB1 (+)	0,96	0,79
		DYSF	Dysferlin	1,67E-04	ANKRD1 (#), HSPB1 (#)	1,56	1,66
	Stress response	HSF1	Heat shock transcription factor 1	3,67E-09	DNAJB1 (+), HSP90AA1 (+), HSPA1A (+), HSPB1 (+)	1,07	0,70
		DYSF	Dysferlin	2,70E-07	DNAJB1 (#), HSPA1A (#), HSPB1 (#)	1,56	1,66
		HSF2	Heat shock transcription factor 2	1,03E-05	HSPA1A (+), HSPB1 (+)	1,54	1,00
Day 3	Cell-cycle control	ADRA2B	Adrenoceptor α2B	1,12E-07	CCND1 (-), MKI67 (-)	0,99	0,62
		RASSF1	Ras association (RalGDS/AF-6) domain family member 1	1,87E-07	CCNA2 (-), CCND1 (-)	1,26	1,85
		TFF2	Trefoil factor 2	2,80E-07	CCNA2 (+), CCND1 (+)	0,83	1,02
	Extracellular matrix	SCXA/SCXB	Scleraxis homolog A	9,10E-09	POSTN (-), SPP1 (+), TNC (-)	1,23	2,66
		PDGFB	Platelet-derived growth factor β polypeptide	1,53E-07	SPP1 (+), TIMP1 (+), TNC (+)	1,22	1,24
		SP1	SP1 transcription factor	2,43E-06	COL8A1 (+), SPP1 (#), TIMP1 (#), TNC (+)	1,00	1,23
Day 10	Extracellular matrix	PDGFB	Platelet-derived growth factor β polypeptide	1,16E-12	COL1A1 (+), COL1A2 (#), FN1 (+), SPP1 (+), TIMP1 (+)	1,20	1,22
		BMP2	Bone morphogenetic protein 2	6,13E-12	COL1A1 (+), COL1A2 (+), FN1 (+), POSTN (+), SPP1 (+), TIMP1 (+)	1,19	1,00
		TGFB2	Transforming growth factor, β2	2,86E-11	COL1A1 (+), COL1A2 (+), FN1 (+), SPP1 (-), TIMP1 (+)	1,11	1,23

The predicted upstream regulators were determined from Ingenuity Pathway Analysis (IPA), using the commonly upregulated genes associated with each functional group (see Tables 1 and 3). For each functional group, the top 3 predicted upstream regulators were identified from the overlap P value (i.e., a low overlap P value is associated with a highly predicted upstream regulator).+, upstream regulator predicted to activate the target molecule; -, upstream regulator predicted to inhibit the target molecule; #, upstream regulator predicted to affect the target molecule. The state of regulation (activated, inhibited, or affected) was defined by IPA based on findings from the literature. The fold change indicates the fold change in gene expression of the predicted upstream regulators, based on our microarray data.

Validation of gene expression data by qPCR.

To confirm our microarray results, qPCR was performed to assess the mRNA expression of several differentially expressed genes. We chose the three contractile apparatus-related genes Ankrd1, Ankrd2, and Csrp3 because they encode mechano-sensor proteins previously shown to act as regulators of transcription to promote structural stability of the sarcomere (4, 30). We also determined by qPCR the mRNA expression of Ccnd1, a cell-cycle-related gene associated with cell proliferation during skeletal muscle hypertrophy (1). In addition, the mRNA expression of the two ECM-related genes (Spp1 and Postn) was validated because these genes are thought to be involved in regulating ECM remodeling in skeletal muscle (37, 49, 65, 67).

The expression of these genes was in agreement with the array findings being increased during both hypertrophy and regrowth (Figs. 4, 5, and 6). The pattern of gene expression was similar for Ankrd1, Ankrd2, and Csrp3 after 1 and 3 days of reloading (12-16-fold change at day 1 and 7-12-fold change at day 3; Fig. 4, A–C). In response to the hypertrophic stimulus, the expression of Ankrd1 was dramatically increased (56- and 19-fold change at days 1 and 3, respectively; Fig. 4A), whereas the expression of Ankrd2 and Csrp3 was modestly increased (about 2.5–4.0-fold changes; Fig. 4, B and C). Similarly, the expression of Spp1 and Postn was either highly or dramatically increased during hypertrophy (25- and 6-fold change for Spp1 at days 3 and 10, respectively; 15- and 82-fold change for Postn at days 3 and 10, respectively; Fig. 5), whereas the increased expression was more moderate for these genes during regrowth [3.5-fold (P = 0.06) and 10-fold change for Spp1 at days 3 and 10, respectively; 11- and 9-fold change for Postn at days 3 and 10, respectively; Fig. 5, A and B]. At day 3, the expression of Ccnd1 was highly and modestly increased during hypertrophy and regrowth, respectively (9.5- and 2-fold-change; Fig. 6).

Fig. 4.

Analysis by qPCR of the expression of ankyrin repeat domain 1 (Ankrd1) (A), Ankrd2 (B), and cysteine and glycine-rich protein 3 (Csrp3) (C), 3 contractile apparatus-related genes involved in mechanotransduction. The results indicate the fold change relative to day 0 (i.e., relative to the nonoverloaded muscle during hypertrophy and relative to the 14-day unloaded muscle by hind-limb suspension during regrowth). All results are expressed as the means ± SE (n = 4–6 per group at each time point). *Significantly different from day 0 during hypertrophy. #Significantly different from day 0 during regrowth.

Fig. 5.

Analysis by qPCR of the expression of secreted phosphoprotein 1 (Spp1) (A) and periostin (Postn) (B), 2 genes associated with extracellular matrix remodeling. The results indicate the fold change relative to day 0 (i.e., relative to the nonoverloaded muscle during hypertrophy and relative to the 14-day unloaded muscle by hind-limb suspension during regrowth). All results are expressed as the means ± SE (n = 4–6 per group at each time point). *Significantly different from day 0 during hypertrophy. #Significantly different from day 0 during regrowth.

Fig. 6.

Analysis by qPCR of the expression of the cell-cycle-related gene cyclin D1 (Ccnd1). The results indicate the fold change relative to day 0 (i.e., relative to the nonoverloaded muscle during hypertrophy and relative to the 14-day unloaded muscle by hind-limb suspension during regrowth). All results are expressed as the means ± SE (n = 4–6 per group at each time point). *Significantly different from day 0 during hypertrophy. #Significantly different from day 0 during regrowth.

DISCUSSION

This study was designed to compare the gene-expression profile of skeletal muscle undergoing two forms of growth (hypertrophy induced by synergist ablation and regrowth following muscle atrophy) with the purpose of identifying a conserved set of differentially expressed genes. The major findings of the study are the following: 1) the number of differentially expressed genes correlated with the magnitude of muscle growth, being ∼10-fold higher during hypertrophy than regrowth; 2) the majority of upregulated genes during the first 3 days of regrowth was also upregulated during hypertrophy, whereas almost all of the differentially expressed downregulated genes were not shared between the two models; 3) several functional groups were associated with the conserved upregulated genes, including stress response group, some groups related to contractile apparatus, ECM, and cell-cycle control; 4) among the genes associated with these functional groups, we identified three genes involved in mechanotransduction (Ankrd1, Ankrd2, and Csrp3) and four HSP-encoding genes at day 1, several ECM-related genes at both days 3 and 10, and three cell-cycle-related genes at day 3.

Mechanotransduction and muscle growth.

Mechanical loading is a major stimulus involved in skeletal muscle adaptation during growth (15), and several components of the sarcomere participate in the signal transduction of mechanical stress. One of the main findings of this study is the identification of five upregulated genes related to contractile apparatus during the first day of hypertrophy and regrowth. Among these genes, Ankrd1 and Ankrd2 encoded two members of the muscle ankyrin repeat protein (MARP) family that interact with titin at the sarcomeric I-band (30) and the Csrp3 gene, which encodes muscle LIM protein, another titin-interacting protein at Z-disk (34).

Ankrd1 and Ankrd2 have been shown to be cardiac and skeletal muscle specific, respectively (30), whereas Csrp3 was found to be enriched in both types of striated muscle (51). The expression of these genes was reported to be upregulated during mechanical stress as the result of eccentric contraction (5), mechanical stretch (47), jumping exercise (36), and running (66), whereas expression of Ankrd2 and Csrp3 is downregulated in response to reduced contractile activity and inactivity (52, 57). In addition to their structural role, these sarcomere-related proteins are able to translocate into the nucleus, where they may act as transcriptional coactivators (30, 31). Inactivation of Csrp3 (4) or all three MARP family members (Ankrd1, Ankrd2, and Darp) (3) revealed no obvious effects on the cellular morphology of muscle under resting conditions; however, Barash and colleagues (3) provided evidence that the triple MARP knockout affects the resting sarcomere length and increases muscle injury in response to eccentric exercise. These findings support the idea that these sarcomere-related proteins may act as mechano-sensors to contribute to the maintenance of structural stability and organization within the sarcomere in response to mechanical stress. Furthermore, the inactivation of the three MARP family member genes did not affect the fiber size of the soleus muscle (3), whereas smaller slow fibers were observed in the soleus muscle of Csrp3-null mice compared with control mice (4). It will be important for future studies to determine the necessity of each MARP gene in the regulation of skeletal muscle growth in response to increased mechanical load.

Ankrd2 protein is highly expressed in slow- compared with fast-twitch muscles (42), whereas Csrp3 expression is induced by calcineurin, and its interaction with this phosphatase further promotes slow myosin heavy chain expression (11). Our results indicate that the conserved upregulation of Csrp3 during hypertrophy and regrowth, two situations associated with a fast-to-slow fiber type transition (45, 48), is accompanied by an increased expression of Rcan1 (see Table 1), a well-recognized marker of calcineurin activity (69). Altogether, these findings are consistent with the notion that Ankrd2 and Csrp3 could be involved in the conversion of the fast-to-slow phenotype associated with skeletal muscle growth. Interestingly, the expression pattern of these three sarcomere-related genes is similar during regrowth (see Fig. 4), suggesting that they may share a conserved transcriptional regulation in response to reloading. During hypertrophy, Ankrd1 expression is dramatically increased, whereas the increased expression of Ankrd2 and Csrp3 is more modest. This result is in agreement with a recent study showing a pronounced increase in Ankrd1 expression, but not in Ankrd2, in response to jumping exercise in humans, suggesting that Ankrd1 expression is sensitive to high mechanical forces placed on the muscle (36).

Stress response and muscle growth.

Our analysis also revealed the upregulation of four HSP-encoding genes associated with stress response after 1 day of muscle growth. HSPs are a group of proteins classified into several families based on their relative molecular weight. Three of these genes (Dnajb1, Hsp90aa1, and Hspa1a) encode protein members of different families of HSPs (HSP40, HSP90, and HSP70, respectively), whereas Hspb1 gene synthetizes the small HSP, HSP27. The expression of these HSPs is strongly sensitive to variations of contractile activity. HSP90, HSP70, and HSP27 are highly expressed in response to mechanical overload (20), whereas their expression decreases during unloading (58). Although HSP40 has not been extensively studied in skeletal muscle, an increased expression was observed after an eccentric exercise in humans (39).

In a similar manner as the three mechano-sensors described above, these HSP genes seem to have a critical role in protecting skeletal muscle against damage following mechanical stress. Indeed, the overexpression of HSP70 reduces muscle damage and enhances the recovery of muscle function following lengthening contractions (40). HSP40, which is overexpressed after an eccentric exercise (39), may have an additive positive effect, as it is a cochaperone regulator of HSP70. Furthermore, HSP27 is able to translocate to disrupted Z-disks after lengthening contractions (29), whereas HSP90 is required for the myofilament assembly during muscle development (14); these findings suggest that HSP27 and HSP90 may also be essential for the stabilization and repair of damaged sarcomeres.

The expression of HSP90, HSP70, and HSP27 is tightly regulated in response to changes in skeletal muscle mass, being increased during hypertrophy (20) and decreased during disuse atrophy (58). The question arises whether these changes in expression are indicative of a direct role in the regulation of muscle mass or rather just a consequence of changes in mechanical stress. Recently, it was demonstrated that skeletal muscles from Hsp70-null mice displayed a deficit in fiber size (61), whereas the overexpression of HSP70 prevented muscle fiber atrophy induced by immobilization (60). The latter study showed that HSP70 prevents disuse atrophy through the inhibition of forkhead box O3a and NF-κB activities. Likewise, HSP70 was proposed to interact with and stabilize the active (phosphorylated) form of Akt (33). Together, these findings suggest that HSP70 could promote skeletal muscle growth through the inhibition of catabolic pathways and activation of anabolic factors.

The expression of HSP90, HSP70, and HSP27 appears to be fiber type specific, having a higher level of expression in the slow-twitch, oxidative soleus muscle than the fast-twitch, glycolytic plantaris muscle (20). Moreover, HSP70 and HSP90 were able to activate calcineurin in vitro (62) although HSP70-null mice did not appear to have a change in fiber-type composition of the soleus muscle (61). Currently, it remains to be examined whether the overexpression of HSP genes could contribute to the fast-to-slow fiber type transition observed in these two models of increased contractile activity.

Cell-cycle control and muscle growth.

In the present study, we identified a small set of genes related to the functional group cell-cycle control after 3 days of muscle growth. These genes encode two cyclin proteins (Ccna2 and Ccnd1) and a nuclear protein (Mki67) that are commonly used as markers of cell proliferation. However, it is necessary to consider whether the proliferative cells originate from myogenic cells (i.e., satellite cells) and/or from nonmuscle cells, such as immune cells. Although the necessity of satellite cells in skeletal muscle hypertrophy is under debate, it has been well established that satellite cell addition does occur during muscle hypertrophy induced by synergist ablation (41). Although the results remains controversial for the soleus muscle (23, 44), regrowth of the plantaris muscle following hind-limb suspension does not require the addition of satellite cells (44). Moreover, our microarray data revealed that the gene expression of the myogenic regulatory factors (MyoD, Myf5, myogenin, and MRF4), which are indicative of satellite cell activity, remained unchanged or slightly increased during regrowth, whereas moderate/high increased expressions were observed during hypertrophy (data not shown). Our results provide additional lines of evidence that the activity of satellite cells is indeed differentially regulated in the plantaris muscle in these two models of growth, being only increased during hypertrophy (23, 41). Interestingly, the increased expression of the cell-cycle-related genes is associated with the upregulation of Il2rg and Cd68 (see Table 1), two genes highly expressed in immune cells, whereas other markers of inflammatory response are increased after 1 day of muscle growth (Tnfrsf12a, Tnrsf22). Altogether, our results suggest that the upregulation of the three cell-cycle-related genes most probably reflect the proliferation of cells involved in inflammatory response during regrowth, whereas it may also reflect the proliferation of satellite cells during hypertrophy.

ECM remodeling and muscle growth.

The ECM plays an essential role in the force transmission and the maintenance of muscle structural integrity in response to mechanical load (28). Here, we showed that several genes related to the ECM were upregulated during hypertrophy and regrowth. Among these genes, several encode structural proteins (fibronectin 1, tenascin C, and components of collagen types I and VIII) and enzymes involved in the regulation of ECM turnover (TIMP1 and ADAMTS9). Of particular interest was the finding that the magnitude of mechanical load applied on the muscle appeared to determine the degree of change in the expression of genes involved in ECM remodeling.

Our microarray analysis revealed that the ECM-related gene Spp1 is commonly upregulated in both models of skeletal muscle growth, with the highest change observed during hypertrophy. The Spp1 gene encodes osteopontin, a cytokine that has been shown to be overexpressed in damaged skeletal muscle (65, 67). Osteopontin was found to be involved in the regulation of muscle inflammation, necrosis, fibrosis, and regeneration, but its function seems to be dependent on the duration (acute vs. chronic) of muscle injury (65, 67). Osteopontin may also be a regulator of skeletal muscle mass because osteopontin-null female mice displayed a reduction in the size of several muscle groups (18). Similarly to Spp1, the expression of Postn (periostin) was dramatically and moderately increased during hypertrophy and regrowth, respectively. Interestingly, this change in Postn expression is associated with the upregulation of fibonectin 1, tenascin C, and some members of collagen families (see Table 1), which have been shown to directly interact with periostin (64). Periostin is overexpressed in response to muscle injury and was proposed to impair skeletal muscle regeneration, as well as promote cardiac hypertrophy and fibrosis accumulation following pressure overload (37, 49). Currently, it remains to be determined whether the magnitude of Spp1 and Postn upregulation observed in these two forms of muscle growth may reflect the severity of ECM remodeling and fibrosis.

Conclusion.

Our microarray analysis revealed that most of the genes that shared a similar expression pattern during muscle hypertrophy and regrowth following atrophy were upregulated. In particular, we identified three genes involved in mechanotransduction and four HSP-encoding genes that could contribute to the maintenance of the sarcomere stability in response to unaccustomed mechanical stress. Among these genes, Csrp3 and Hspa1a may also be beneficial to promote muscle growth. Furthermore, our findings suggest that the increased expression of three cell-cycle-related genes could reflect the proliferation of immune cells during regrowth although this change may also result from the proliferation of satellite cells during hypertrophy. We also showed that several ECM-related genes were overexpressed during muscle growth, with the highest changes being observed during muscle hypertrophy. Interestingly, we identified two genes (Spp1 and Postn) that may play a central role in the regulation of the ECM associated with mechanical stress. The identification of several genes that may be beneficial for muscle growth and remodeling provides targets for future studies investigating the treatment of skeletal muscle loss and dysfunction.

GRANTS

This work was supported by AR45617 and Merck (to K. Esser).

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the authors.

AUTHOR CONTRIBUTIONS

Author contributions: T.C., J.R.J., J.H.E., T.J.K., and J.R.-W. performed experiments; T.C. analyzed data; T.C., J.R.J., E.E.D.-V., and J.J.M. interpreted results of experiments; T.C. prepared figures; T.C. and J.J.M. drafted manuscript; T.C., J.R.J., K.A.E., E.E.D.-V., and J.J.M. approved final version of manuscript; J.R.J., J.H.E., K.A.E., E.E.D.-V., and J.J.M. conception and design of research; J.R.J., K.A.E., E.E.D.-V., and J.J.M. edited and revised manuscript.