Microarray and cDNA sequence analysis of transcription during nerve-dependent limb regeneration
© Monaghan et al; licensee BioMed Central Ltd. 2009
Received: 22 December 2008
Accepted: 13 January 2009
Published: 13 January 2009
Microarray analysis and 454 cDNA sequencing were used to investigate a centuries-old problem in regenerative biology: the basis of nerve-dependent limb regeneration in salamanders. Innervated (NR) and denervated (DL) forelimbs of Mexican axolotls were amputated and transcripts were sampled after 0, 5, and 14 days of regeneration.
Considerable similarity was observed between NR and DL transcriptional programs at 5 and 14 days post amputation (dpa). Genes with extracellular functions that are critical to wound healing were upregulated while muscle-specific genes were downregulated. Thus, many processes that are regulated during early limb regeneration do not depend upon nerve-derived factors. The majority of the transcriptional differences between NR and DL limbs were correlated with blastema formation; cell numbers increased in NR limbs after 5 dpa and this yielded distinct transcriptional signatures of cell proliferation in NR limbs at 14 dpa. These transcriptional signatures were not observed in DL limbs. Instead, gene expression changes within DL limbs suggest more diverse and protracted wound-healing responses. 454 cDNA sequencing complemented the microarray analysis by providing deeper sampling of transcriptional programs and associated biological processes. Assembly of new 454 cDNA sequences with existing expressed sequence tag (EST) contigs from the Ambystoma EST database more than doubled (3935 to 9411) the number of non-redundant human-A. mexicanum orthologous sequences.
Many new candidate gene sequences were discovered for the first time and these will greatly enable future studies of wound healing, epigenetics, genome stability, and nerve-dependent blastema formation and outgrowth using the axolotl model.
Salamanders are fascinating vertebrate organisms because they routinely regenerate complex tissues. Within only a few weeks of losing a piece of limb to a hungry predator or scalpel-wielding scientist, a salamander perfectly reforms the missing structure. In the early history of salamander regeneration research, scientists innovated elegant experimental designs to probe the anatomical basis of regeneration . More recently and in parallel with the discovery of conserved regulatory genes and developmental pathways among metazoans, scientists have focused attention on candidate molecules and signaling pathways whose functions were deduced first from studies of model organisms. In particular, much research has been devoted to understanding aspects of limb regeneration associated with wound healing that recapitulate limb development; this strategy has yielded many useful insights and molecular probes [2–14]. Although it is clear that key regulatory molecules play important roles in the development of all organisms, it is not clear that a framework for understanding regeneration can be constructed using a generic and limited molecular toolkit. There is a need to go beyond candidate molecules and use unbiased approaches to characterize the molecular complexity underlying salamander regeneration.
Recent research resource development for the Mexican axolotl now allows classic regeneration experiments to be re-examined with powerful and unbiased genomic approaches. One particularly elegant experiment performed almost 200 years ago showed that salamander limb regeneration requires the presence of peripheral nerves. Todd  found in 1823 that limb regeneration does not occur if the sciatic nerve of the hindlimb is severed shortly before or immediately after a more distal limb amputation. Subsequent research showed that the brachial nerves entering the forelimb are required to promote limb outgrowth and patterning of a new limb [16, 17]. Within a few days of limb amputation, cells proximal to the amputation plane dedifferentiate and accumulate to form a blastema. Blastema cells proliferate and progressively differentiate during regeneration to give rise to all mesodermal structures of a typical vertebrate limb . Upon amputation, nerve fibers in the vicinity of the amputation plane extend into the blastema and play a supportive role in cell proliferation [11, 19]. Transection of the spinal nerves that enter the limb in the axolotl leads to a decrease in cycling cells and there is resorption of distal tissues of the amputated limb. Histological and cell proliferation analyses suggest that early cellular events are similar between denervated and innervated limbs, but denervated limbs are incapable of blastema formation because they do not support significant cell proliferation and outgrowth [20–25].
Although limb regeneration is a complex developmental process, nerve dependency and other aspects of regeneration have often been conceptualized as having a simple molecular basis, involving relatively few regulatory factors. For example, Ferretti and Brockes  hypothesized that in the absence of nerves, Schwann cells produce an inhibitory factor that prevents blastema cell proliferation. This mechanism is supported by experimental results although the hypothetical factor has not been identified [27, 28]. Alternative mechanisms for nerve dependency have also been proposed for several factors with growth promoting effects [29–33]. A recent study identified newt anterior gradient protein (nAG) as a blastema cell growth-promoting factor in vitro, whose over-expression was sufficient to rescue regeneration of denervated and amputated limbs in vivo . Most recently, nerve-dependent expression of the transcription factor sp9 has been identified as an early marker of dedifferentiation of the wound epithelium and the initiation of limb regeneration . While considerable progress has been made in investigating the functions of candidate regulatory factors and signaling pathways, a broader systems-level perspective is needed to understand why multiple aspects of limb regeneration are dependent upon the presence of a nerve.
Genomic tools are now available that allow global characterization of the regeneration process in salamanders. Expressed sequence tag (EST) information has facilitated the development of an Ambystoma salamander Affymetrix microarray platform [35–38]. This platform and a high-throughput 454 cDNA sequencing approach were used in this study to compare transcript abundance among uninjured limbs, regenerating limbs, and limbs denervated at the time of amputation. The results show that innervated (NR) and denervated (DL) limbs exhibited similar (but not identical) gene expression patterns at five days post amputation (dpa) but then diverged as a blastema formed under the influence of nerves. The results are discussed within the context of previous studies of nerve dependency, highlighting specific genes and biological processes that are associated with blastema formation and outgrowth, and more generally, the Mexican axolotl's unparalleled ability to regenerate limbs.
Morphology and histology of denervated and innervated limbs
Transcription during normal limb regeneration: Deviations of NR limbs from baseline
Significant gene ontology terms for changed genes
NR5 and NR14 (N = 111)
NR5 and NR14 (N = 104)
extracellular region (N = 14; 9.05E-07)
muscle contraction (N = 13; 1.81E-10)
collagen catabolism (N = 5; 4.35E-06)
cytoplasm (N = 51; 8.41E-07)
collagen (N = 6; 4.05E-05)
ion transport (N = 12; 9.44E-06)
NR5 only (N = 110)
NR5 only (N = 49)
extracellular region (N = 15; 1.23E-05)
extrinsic to membrane (N = 3; 6.10E-03)
response to stimulus (N = 17; 1.00E-02)
signal transduction (N = 21; 2.89E-03)
Ion transport (N = 9; 2.57E-03)
NR14 only (N = 53)
NR14 only (N = 93)
DNA metabolic process (N = 8; 4.41E-04)
muscle contraction (N = 18; 5.43E-19)
calcium ion binding (N = 11; 4.98E-04)
DL5 and DL14 (N = 170)
DL5 and DL14 (N = 109)
extracellular region (N = 23; 6.64E-10)
muscle contraction (N = 15; 6.62E-13)
lysosome (N = 11; 3.04E-08)
cytoplasm (N = 53; 1.46E-06)
ion transport (N = 13; 1.42E-05)
mitochondrial membrane (N = 12; 3.49E-04)
hydrolase activity (N = 26; 3.60E-05)
response to stress (N = 21; 1.02E-03)
signal transduction (N = 22; 5.40E-03)
collagen catabolism (N = 5; 5.09E-05)
DL5 only (N = 68)
DL5 only (N = 58)
extracellular region (N = 9; 3.68E-04)
extrinsic to membrane (N = 3; 4.64E-03)
response to stimulus (N = 12; 3.70E-03)
DL14 only (N = 69)
DL14 only (N = 111)
extracellular region (N = 7; 4.10E-03)
muscle contraction (N = 9; 4.26E-05)
immune response (N = 5; 7.80E-03)
mitochondrion (N = 27; 6.71E-07)
cytoplasmic (N = 43; 2.58E-03)
M phase (N = 9; 1.40E-03)
glucose metabolic process (N = 6; 2.97E-03)
Although many genes exhibited similar deviations from baseline at 5 and 14 dpa, unique gene expression changes were identified at each time point (Table 1; Additional files 1 and 2). The unique NR5 genes were associated with gene ontology (GO) terms that implicate extracellular protein changes and signal transduction pathways of the early wounding response. These terms included response to stimulus, signal transduction, extracellular region, and ion transport. The unique NR14 genes were associated with GO terms that implicate cell division and DNA metabolism including ccnd2, ccnb1, rrm1, rrm2, nasp, rrc1, and cdc20. The unique gene expression changes that were identified at 5 and 14 dpa support the idea of temporal progression from an early wound-healing phase to a blastema outgrowth phase during normal limb regeneration.
Transcription within denervated limbs: Deviations of DL limbs from baseline
As was observed in NR limbs, hundreds of genes were identified as significant when comparing DL5 and DL14 mRNA levels with baseline levels measured at Day 0 (Table 1; Additional files 1 and 2). Some of the same or similar GO terms that were associated with NR limbs were identified as significantly enriched in DL limbs. This was not unexpected because both DL and NR limbs undergo tissue histolysis at the limb stump and carry out an early wound-healing response (Figure 1). For example, extracellular region and MMP genes were upregulated at 5 and 14 dpa, as was seen in NR limbs (Figure 2; Additional file 1). As in NR limbs, muscle contraction (Figure 4), cytoplasmic, and collagen genes (Figure 3; col4a1, col4a2, col8a1) were downregulated in both DL5 and DL14 limbs (Additional file 2). Moreover, 83% of the genes that were identified as significant in NR5 limbs were also significant (and in the same direction) in DL5 limbs. These results indicate that many transcriptional events are nerve-independent during early regeneration.
Denervated limbs are known to cease growth following limb amputation. Several groups of genes may explain this observation including the downregulation of genes associated with the M phase of cell division, mitochondrial transcripts, and genes associated with glucose metabolism (Table 1; Additional file 2). Furthermore, DL14 limbs were morphologically similar to DL5 limbs because denervation prevented blastema formation (Figure 1). Consistent with this observation, many of the genes that were identified as upregulated in DL5 limbs were also identified as significant in DL14 limbs (69%). These genes are associated with the following GO terms: lysosome, response to stress, hydrolyse activity, signal transducer activity, and ion transport. Overall, these terms suggest protraction and expansion of wound-healing responses in DL14 limbs, as well as changes in cellular metabolism and cell division.
Transcript abundance differences between NR and DL limbs
In the preceding two sections, transcriptional patterns of NR and DL limbs were described relative to baseline levels at Day 0. Here, we report genes found to be significant when comparing NR and DL limbs. In general, few significant changes in gene expression were observed when NR5 and DL5 transcripts were compared directly. Transcripts for 16 genes were more abundant in NR5 limbs and 17 were more abundant in DL5 limbs, and these differences were small in terms of fold-level change (< 3-fold difference between NR5 and DL5; Additional file 3). Eighteen of these genes exhibited significant sequence similarity to human or salamander presumptive gene sequences; the others are unknown. The genes with significantly more transcripts in NR5 limbs are associated with intracellular (for example dnase1l3, uap1, acy3, nans, myl4) and extracellular functions, including membrane proteins (for example psca, umod, and emp1) and collagen binding (serpinh1). The genes with significantly more transcripts in DL5 limbs are associated with extracellular functions or the immune response (for example igll1, CD74, hmox1, neil1, marco, sftpd, mmp9, mrc1). All but one of the significant 5 dpa genes showed the same directional deviation at 14 dpa; myl1was 1.5-fold higher in the NR limb at 5 dpa, but 2.2-fold lower at 14 dpa. Thus, as was observed when comparing DL5 and NR5 mRNA abundances with baseline levels, relatively few gene expression differences were identified between NR and DL limbs at 5 dpa, and the magnitude of these differences was small. These results further support the idea that transcription during limb regeneration is predominantly nerve-independent at 5 dpa.
Genes from Clusters 2 and 3 were generally expressed in the same direction between NR14 and DL14 limbs; however, the magnitude of expression differed. Genes in Cluster 2 presented transcript abundances that generally exceeded baseline levels, with higher levels observed in DL14 limbs. This pattern suggests that most of these genes were activated in the same direction in the presence or absence of nerves, but denervation caused higher transcript abundances. Twenty-two percent of the genes in Cluster 2 are associated with the GO term cellular response to stimulus (n = 14) and a significant proportion localized to the lysosome (n = 6), including lgmn, ctsk, ctss, asah, atp6v0d1, and neu1. Genes in Cluster 3 presented transcript abundances that were generally lower than baseline levels, with much lower levels observed in NR14 limbs. With relatively few genes in this cluster, no biological process was identified as significantly enriched. However, inspection of the genes in Cluster 3 again supports the idea that some genes may function in muscle contraction (actc1, myh7, and fhl1) and tissue repair (hsp27 and hebp2). In summary, mRNA levels for genes from Clusters 2 and 3 were quantitatively affected by the presence or absence of a nerve.
454 cDNA sequence analysis of nerve dependency
454 DNA sequence reads that were generated for each cDNA limb library
Gene ontology breakdown of the 9411 salamander genes with presumptive human orthologs
response to stress
transcription factor activity
mRNA abundance estimates and gene discovery from 454 cDNA sequence data
The number of times that a non-redundant transcript was sampled by 454 cDNA sequencing was used to estimate mRNA abundances. The transcript counts for 1150 Ambystoma EST contigs (genes) differed significantly among limb cDNA pools that were created for each of the limb types (Additional file 5). It was possible to assign a putative ortholog to 563 of these genes; the remaining genes were considered anonymous. This final list of genes was compared with the significant gene lists from the microarray analysis. It was determined that for 271 of the 1150 significant genes from the 454 cDNA sequencing analysis, a portion of the gene sequence was represented by a probe set on the Ambystoma GeneChip. Of these, 104 genes were identified as significant by both methodologies and mRNA abundances for these genes were highly positively correlated (Additional file 6; median Spearman's correlation = 0.87). The 167 genes found to be significant by 454 cDNA sequencing, but not by microarray analysis, were mostly characterized by low fold changes from baseline (median fold change as estimated from 454 cDNA sequencing counts = 1.75); or conversely, registered low hybridization intensities in the microarray analysis (median rank among 4844 probe sets = 343).
Gene ontology results from 454 sequencing
Most significant GO term
Day 0 (N = 127)
striated muscle contraction (N = 17)
NR5 (N = 84)
macromolecule metabolism (N = 40)
DL5 (N = 59)
macromolecule catabolism (N = 12)
NR14 (N = 54)
DNA metabolism (N = 6)
DL14 (N = 43)
protein biosynthesis (N = 14)
Significantly changed retrovirus-like genes
end. retroviral w
hyp. prot. LOC57523
zinc finger protein 9
gypsy 1 polyprot.
chromobox hom. 1
NBB2750 hyp. protein
paternally exp. 10
paternally exp. 10
Significantly changed wound-healing genes
Early wound-healing response during limb regeneration
Previous studies have documented anatomical similarities between innervated and denervated limbs at early stages of regeneration [20, 43, 44]. This study shows that there are also many transcriptional similarities. This suggests that many aspects of the early wound-healing phase of limb regeneration are not dependent upon post-amputation, nerve-derived factors (Table 6). Instead, humoral immune and local tissue responses appear to be key. Many genes that are associated with wound-healing and tissue-repair activities including stress, inflammation, cell survival, immunity, and extracellular matrix remodeling were upregulated from baseline in 5 dpa limbs (Figure 2; Table 6). It is probably no coincidence that essentially all of the early stress-associated genes that were previously identified as significantly regulated (using the same Ambystoma GeneChip) during early spinal cord regeneration , and during the innate immune response of axolotls to a deadly viral pathogen , were also identified as significant in this study. Many of these genes appear to be expressed similarly in all vertebrates in response to stress, including junb, irf1, hmox1, apoE, mmps, ptx3, gal3, gadd45g, and tgfb. Additionally, significantly more 'extracellular' genes were identified at 5 dpa than expected by chance, including genes that code for matrix remodeling proteins and secreted molecules whose functions are associated with growth factor binding, cell signaling, survival, death, adhesion, migration, and proliferation. The early wound-healing response initiates local environmental changes of the injury site that are pivotal to subsequent phases of regeneration.
The 5 dpa time point was chosen in this study to identify critical nerve-dependent signaling events that are stimulated within the first few days of regeneration (see ). Comparison of DL5 and NR5 data revealed few overall gene expression differences. The 5 dpa time point captured many transcriptional responses that are induced by injury and/or amputation but relatively few that are associated with known or suspected neurotrophic signaling pathways. More comprehensive sampling and deeper sequencing is needed to detail early nerve-dependent transcriptional responses because several genes that are known to be nerve-responsive during the wound-healing phase were not identified in this study (for example sp9, ; prrx1, tbx5, ).
Downregulation of genes associated with differentiated muscle
This study documented dramatic decreases in the relative abundance of mRNAs coding for skeletal muscle contractile proteins, including myosins, actins, actinins, titin, tropomyosins, and troponins. Many of these changes were also detected by 454 cDNA sequence analysis (Figure 4). This strong, muscle-specific transcriptional signature was observed because approximately half of uninjured forelimb nuclei in 7 to 9 cm axolotls, and likely more than half the cross-sectional area, derive from muscle . It is unlikely that the downregulation of muscle genes is due to retraction of the muscle towards the shoulder because muscle transcripts are much more downregulated at 14 dpa than 5 dpa in both denervated and innervated limbs. Considering that limb tissue samples in this study included ~1 mm of undamaged tissue proximal to the amputation plane, the results suggest that injury to skeletal muscle induces tissue-wide loss of muscle contractile transcripts. It is possible that the decrease in muscle transcripts is due to muscle wasting, caused by a lack of mechanical stress. It is interesting to speculate that this response maybe associated with the degeneration or cellularization of multinucleated muscle fibers into mononucleated cells, which occurs in both denervated and innervated amputated limbs [41, 46–50]. It is interesting to note that muscle-specific genes, including actc1, actn2, atp2a2, my1pf, tncc, tnni2, tnni3, are downregulated during early stages of mammalian skeletal muscle regeneration , and this is accomplished without blastema formation. Skeletal muscle regeneration in mammals and other vertebrates involves resident stem (satellite) cells [52, 53]. It is possible that muscle-specific genes are downregulated as an integral step of a conserved, skeletal muscle regeneration program of vertebrates. Candidate transcriptional repressor genes were identified in this study including id3 , tardbp , cnot , msx1 [6, 57] and msx2. It will be important in future studies to determine if the dramatic decrease in muscle transcripts is due to activation of muscle stem (satellite) cells, muscle loss, muscle dysfunction/wasting, or whether these transcriptional patterns have an active role in regeneration.
Genes associated with epigenetic reprogramming and genomic stability
Blastema formation requires a large number of progenitor cells derived from quiescent stem cells or differentiated cell types. It is generally known that reprogramming of differentiated cells is accompanied by epigenetic changes such as histone and DNA modifications [58, 59]. Few candidates have been identified previously as bringing about epigenetic changes necessary for cellular reprogramming during regeneration [60, 61]. This study identified several genes whose functions are associated with epigenetic phenomena, including chromatin remodeling, DNA methylation, and transcriptional regulation. These include uhrf1 , lmnb2, parp1 , thymopoietin , and a gene with high sequence identity to SAM-dependent methyltransferases (Cluster_227434_Contig1; SRV_05867_a_at).
After cellular reprogramming and during limb outgrowth, blastemal cells undergo tremendous cell proliferation. During blastema cell proliferation, telomere lengths and overall genome stability must be maintained to prevent cell death. This study identified several candidate genes from NR14 limbs that are known to function in genome stability, telomere homeostasis, and DNA repair. These include parp1 , hmgb2 , fen1 , aurka , aurkb , and pif1, a DNA helicase that maintains genome stability and binds to telomerase from yeast to humans . It is also important to note that many transcripts were identified from NR and DL limbs that code for retroelement components (Table 5; for example polyproteins, gag proteins, reverse transcriptases, and recombinases). Retrotransposons are normally transcriptionally silenced in differentiated somatic cells by epigenetic mechanisms, but become active upon changes in epigenetic status; these may also regulate nearby gene expression [71, 72]. It is unclear if upregulation of retroelement transcripts affects genome stability and/or is necessary for regeneration.
Genes associated with nerve-dependent blastema outgrowth
In this study, blastemas were not observed in NR5 limbs or DL14 limbs, and only formed on NR14 limbs. Nerve-dependent limb outgrowth occurs as a result of blastemal cell proliferation. Two early cell proliferation biomarkers, umod and psca, were identified as significantly different between NR5 and DL5 limbs. umod probably locates to the wound epithelium as it is upregulated in apical skin cells during thyroid hormone-induced metamorphosis of axolotl epidermis (unpublished data). It is possible that psca is a membrane receptor of blastema cells because it shows structural similarity to prod1, a surface protein that is implicated in proximal-distal positional identity of blastemal cells during newt limb regeneration . Most of the cell proliferation biomarkers were identified at 14 dpa, when a blastema was present in NR limbs but absent in DL limbs. Thus, between 5 and 14 dpa, blastemal cells underwent considerable cell proliferation in the presence of nerves. Because the limb blastema continues to expand after 14 dpa, the blastema-specific genes that were identified in this study are probably transcribed at much higher levels at later time points. A clear signature of cell proliferation, including genes that function in the cell cycle, mitosis, and nucleotide synthesis, was observed in NR14 limbs. In contrast, these genes were slightly downregulated in denervated limbs at this time (Table 1; Figure 5). Thus, transcripts associated with cell proliferation are maintained at steady state (no increased proliferation) in NR and DL limbs for at least five days. This early, nerve-independent portion of the limb regeneration program may allow time for re-innervation of the injury site and production of nerve-derived molecules in sufficient quantity to initiate and sustain blastemal cell proliferation.
Multiple gene products have been hypothesized to be neurotrophic factors provided by nerves to sustain blastema cell proliferation. These include growth-promoting factors such as fibroblast growth factors [11, 31], substance P , neuregulin , and transferrin . Transferrin and neuregulin were sampled by 454 sequencing, but were not identified as differentially expressed by our analysis. fgf8 and fgf10 were screened out of the microarray analysis due to low expression, but post-hoc analysis suggested that both are upregulated in NR14 limbs compared to control and DL14 limbs (Additional file 7). Expression of these molecules is known to be nerve-dependent in blastemas of Xenopus  and axolotls [3, 4, 76]. Other molecules that have previously been associated with the blastema during limb regeneration were not included in our statistical analyses due to low hybridization intensity, but were later found to be differentially expressed in NR14 limbs, including hoxd10, hoxa13, hoxa11, and msx1 (Additional file 7). Recently, Kumar et al  identified a growth-promoting extracellular ligand (nAG) that rescues aspects of nerve dependency of limb regeneration in newts. Probesets for nAG are represented on the Ambystoma GeneChip and transcripts for this gene were sampled by 454 cDNA sequencing. nAG mRNA was transcribed at a high level in all tissues, but did not differ significantly between NR, DL, or control limbs. It is possible that the effects of nAG and other neurotrophic candidates are associated with quantitative variation of mRNA transcript abundances over fine temporal and spatial scales. Such variation would have been missed in this analysis of three time points and sampling of mRNAs from heterogeneous tissues. Furthermore, it is possible that the increase in nAG immunoreactivity observed by Kumar et al  is regulated at the level of translation and would not be observed using microarray or sequencing approaches. Overall, we found that several, but not all, genes previously shown to be directly downstream of neurotrophic factors are expressed at higher mRNA levels in the blastema versus control and denervated samples.
Singer  emphasized that the neurotrophic factor underlying nerve dependency was growth promoting and quantitative in effect. He showed that the trophic effect of nerves could be titred by surgically manipulating the number of nerves innervating the limb . Other lines of research showed that nerve-derived factors were not necessary for traversing cell cycle checkpoints, as an equivalent number of presumptive blastema cells are initially observed to enter S phase in denervated and innervated limbs [21, 77–79]. Instead, the neurotrophic factor appears to be necessary to complete the cell cycle and this may be non-trivial considering the cost of replicating a large salamander genome. These studies suggest that nerves either directly or indirectly provide limiting macromolecules that are needed to accomplish cell division. According to this reasoning and assuming a correlation between transcript and protein abundance for specific mRNA species, transcripts associated with nerve dependency would be expected to exceed baseline levels in NR limbs during regeneration, and decrease in abundance in DL limbs. This study identified many human-axolotl presumptive orthologs and anonymous axolotl transcripts that showed this pattern. For example, psat codes for a protein that regulates the second enzymatic step of the phosphorylated pathway in mammals, which produces L-serine . PSAT expression (protein and mRNA) is high among cell types with high rates of proliferation, including cancer cell lines [81, 82]. Strikingly, psat registered the largest mRNA abundance difference between NR14 and DL14 limbs among probesets on the Ambystoma GeneChip (8.2-fold change), and this result was verified by both 454 cDNA sequencing (NR14 = 20.1, DL14 = 3) and real-time PCR (8.37-fold change; data not shown). We also found that the third enzyme in the phosphorylated pathway, psph, was 3.58-fold higher in NR14 versus DL14 by real-time PCR (data not shown). PSAT and PSPH may have neurotrophic potential but more likely function to provide proliferating cells with a limiting and conditionally important substance (L-serine) that is required for synthesis of macromolecules, amino acids, and purines that are needed to accomplish mitosis . The fact that macromolecular synthesis and cell proliferation are both depressed in denervated limbs [83–86] supports the idea that PSAT activity is associated with nerve-derived factors that contribute to blastema outgrowth.
Comparison of microarray and cDNA sequencing approaches
Microarray analysis and 454 cDNA sequencing offer different advantages for dissecting complex biological processes. The strength of microarray analysis is the precision that this approach provides for estimating transcript abundances for a specific panel of genes. Such gene panels provide standardized markers for identifying shared and unique patterns of transcription among experiments. In turn, identification of such patterns provides systems-level insight. For example and as was discussed above, cross-experiment comparisons of axolotl transcription helped distinguish general stress responses from local regenerative responses. A relatively conservative fold level threshold (> 1.5-fold) was used in this study to identify significant genes in the microarray analysis and lowly expressed genes (in the lowest quartile) were removed from consideration. These conservative approaches potentially exclude important genes but likely discover 'real' transcriptional differences between samples. A lower threshold could be applied to extract more information from the dataset and future studies would likely benefit by increasing replication of GeneChips to detect significant differences for lowly expressed genes. With respect to 454 cDNA sequencing, two goals were accomplished: gene discovery and estimation of transcript abundance. However, accomplishment of both goals required a trade-off in the allocation of resources toward deep sequencing versus replication. Sequencing resources were used to deeply sequence Day 0, NR, and DL cDNA libraries instead of shallowly sequencing replicate libraries for these time points. This strategy identified thousands of new gene sequences that will greatly enrich future regeneration studies. Future studies will benefit from experimental designs that replicate deep sequencing of cDNA libraries and this will be possible as sequencing costs decrease. Still, it was encouraging to find in this study that 38% of genes that were identified as differentially expressed by 454 cDNA sequencing and found on the microarray GeneChip were identified as significant by both of these technologies, and transcript abundances for these genes were highly positively correlated.
This study addressed the nerve dependency of limb regeneration by characterizing downstream cellular events that are affected when an intact nerve supply is removed from an amputated salamander limb. Microarray analysis showed that the early wound response is largely nerve-independent, but transcriptional profiles diverge between denervated and innervated limbs when the innervated limb starts to regenerate. Pyrosequencing supported these microarray results while substantially increasing sequence information from the salamander transcriptome. This study shows the utility of next-generation sequencing platforms for gaining transcriptome information [87–89]. This new DNA sequence information will greatly enrich future regeneration studies using the axolotl.
Mexican axolotls were obtained from the Ambystoma Genetic Stock Center at the University of Kentucky. Siblings were reared individually under ab libitum conditions to 60 to 70 mm snout to vent length. The 3rd, 4th, and 5th spinal nerves that enter the left limb were severed at the brachial plexus behind the shoulder. Denervated left and innervated right limbs were amputated at mid-stylopod and allowed to regenerate for 5 and 14 days. Animal care and use procedures were approved by the University of Kentucky Internal Animal Care and Use Committee.
Limbs were collected at 5 and 14 dpa and fixed in 4% paraformaldehyde, 1× PBS overnight at 4°C. Tissues were cryoprotected in sucrose, embedded in TissueTek, and sectioned at 16 μm. Eosin Y and Gill's hematoxylin #2 (Sigma-Aldrich, St. Louis, MO, USA) were used to stain cytoplasm and nuclei. DIC and brightfield images were taken on an Olympus AX80 microscope (Center Valley, PA, USA).
RNA extraction and microarray analysis
DL and NR limbs were collected approximately 1 mm proximal to the amputation plane 5 dpa and 14 dpa. Nine animals were used for each time point and limbs were pooled into three groups of three. Left and right limbs were paired within animals when possible in making the pools for the 5 and 14 dpa time points. The day 0 pools were created using only the right limbs of nine different individuals that were collected within minutes following limb amputation. RNA was extracted using Trizol Reagent (Invitrogen, Carlsbad, CA, USA) followed by RNeasy minicolumns (Qiagen, Valencia, CA, USA). RNA quality was assessed by spectrophotometry using a Nanodrop ND-1000 (Nanodrop, Wilmington, DE, USA) and run on a Bioanalyzer 2100 (Agilent, Santa Clara, CA, USA). The Ambystoma microarray platform was produced by the Voss lab and Affymetrix and has been described elsewhere [35, 37]. Total RNA was used to produce cRNA probes for GeneChip hybridizations (Affymetrix, Santa Clara, CA, USA) at the University of Kentucky Microarray Core Facility according to standard Affymetrix protocols. Probe level quality control analyses were performed as described in . Data processing and statistical analysis was performed using the Affy Bioconductor package for the R statistical environment . Background correction, normalization, and probe set summarization were performed via the robust multi-array average (RMA) algorithm of . Correlation matrices (Pearson's r) for replicate GeneChips at the probe-set level were produced to assess correlation between GeneChips (minimum r = 0.9787, maximum r = 0.9952). Probe-sets were removed if mean signal intensity was less than the mean of the lowest quartile across all 15 GeneChips (mean ± standard deviation = 7.748 ± 0.031). Some microarray technologies may provide unreliable hybridization estimates for lowly expressed genes . For this reason, a stringent cut-off was applied that removed the bottom quartile of genes for significance testing. Probe-set filtering yielded 3656 probe-sets for significance testing.
The limma package [93, 94] available from Bioconductor was used to conduct three analyses to statistically identify differentially expressed genes. In the first analysis, linear models were fit to each gene. These models used coefficients to denote each of the five treatments by sampling time combinations. The following coefficients were contrasted: Day 0 versus NR 5 dpa (NR5), Day 0 versus DL 5 dpa (DL5), Day 0 versus NR 14 dpa (NR14), Day 0 versus DL 14 dpa (DL14), NR5 versus NR14, and DL5 versus DL14. The other two analyses were equivalent to paired t-tests and compared NR5 versus DL5, and NR14 versus DL14. Multiple testing was corrected using an FDR cut-off of 0.05 and then a fold-change filter (≥ 1.5-fold change) was implemented to derive final gene lists. All microarray data are available at . The identity of differentially expressed salamander transcripts was inferred from presumptive human orthologs. Orthology was assumed for all salamander transcripts that exhibited significant sequence similarity to protein coding sequences from human RefSeq and nr databases (BLASTx, e < 1 × 10-7). K-means gene clustering was performed using the Genesis software package . Presumptive human-salamander orthologs were further annotated using GO terms and tools provided by the Database for Annotation, Visualization, and Integrated Discovery . Significantly over-represented GO terms (EASE score p < 0.01) were identified for specific treatment/sampling time combinations. Certain GO terms were excluded from the results if similar information was represented by a similar GO term. The null expectation for GO term representation was obtained by assigning GO terms to 3271 EST contigs from Ambystoma ESTdb .
454 cDNA Sequence Analysis
The same total RNA samples that were used in the microarray analysis were used to produce cDNA templates for 454 pyrosequencing. cDNA libraries were generated for Day 0, NR5, NR14, DL5, and DL14 RNA samples using the Super SMART cDNA Synthesis protocol (Clontech, Mountain View, CA). Single-stranded cDNA template was amplified using the Advantage 2 PCR Kit (Clontech) and size selected according to manufacturer's instructions. cDNAs were sequenced using the Genome Sequencer FLX System (Roche Applied Science, Indianapolis, IN). SeqClean was used for vector/poor quality trimming, bacterial contaminant screening, and identification of A. mexicanum mitochondrial DNA and rDNA sequences . Retained sequences were pre-clustered using PaCE and then assembled using CAP3 with a 90% sequence similarity threshold [99, 100]. Contigs (including singletons) were searched using BLAST algorithms against the Ambystoma ESTdb, human and nr RefSeq databases, and Xenopus laevis and X. tropicalis Unigene sets. Annotated queries that returned a significant BLAST hit were assigned the gene identifier of the best-matching subject sequence. All of these new 454 sequence reads have been submitted to the Short Read Archive (SRA) at the National Center for Biotechnology Information (NCBI), accession SRA004195.2. 454 Sequences were assembled with previous EST data and are available at Sal-Site .
The number of times each 454 DNA sequence read matched a unique EST contig from the Ambystoma ESTdb was recorded, and these count data were used to estimate mRNA abundances for presumptive axolotl genes. The following method was used to identify differentially expressed genes among 10,275 contigs that were sampled ≥ 5 times across all five cDNA libraries. First, 5000 random draws were taken from a multinomial distribution to derive expected count data for each gene (k = 5 cDNA libraries, n = the sum of counts across all libraries for a given gene, and p 1, p 2, p 3, p 4, and p 5 = expected proportion of counts per library given unequal sampling among cDNA libraries). Then, χ2 statistics were calculated, on a gene-by-gene basis, for each of these random draws. P-values for each gene were estimated by calculating the proportion of randomized χ2 statistics that were ≥ to the χ2 statistic associated with the observed data. Contigs with P-values ≤ 0.001 were considered differentially expressed. Upon examination of this dataset, it was noticed that 589 of the significant EST contigs were uniquely derived from different cDNA libraries and these tended to form small (< 250 bp) contigs that did not match previous sequences in the Ambystoma ESTdb. These sequences were considered cloning/sequencing artifacts and removed from the dataset. This yielded a final dataset of 1150 significant genes. GO analyses were performed as described above with the exception that human default GO term frequencies were used to establish null expectations (EASE score p < 0.02).
This project was supported by grants R24-RR016344 and P20-RR016741 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of NCRR or NIH. The project was also supported by a Roche genome sequencing award, funding from the Kentucky Spinal Cord and Brain Injury Research Trust, the California Institute for Regenerative Medicine, and the Kentucky Bioinformatics Research Infrastructure Network. The Spinal Cord and Brain Injury Research Center and the NSF supported Ambystoma Genetic Stock Center (DBI-0443496) provided resources and facilities. We thank Ananth Kalyanaraman for running PaCE clustering at Washington State University. Arnold Stromberg and Phil Crowly provided statistical advice.
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