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In vivo Monitoring of Transcriptional Dynamics After Lower-Limb Muscle Injury Enables Quantitative Classification of Healing.

Aguilar CA, Shcherbina A, Ricke DO, Pop R, Carrigan CT, Gifford CA, Urso ML, Kottke MA, Meissner A - Sci Rep (2015)

Bottom Line: Comprehensive dissection of the genome-wide datasets revealed the injured site to be a dynamic, heterogeneous environment composed of multiple cell types and thousands of genes undergoing significant expression changes in highly regulated networks.Four independent approaches were used to determine the set of genes, isoforms, and genetic pathways most characteristic of different time points post-injury and two novel approaches were developed to classify injured tissues at different time points.These results highlight the possibility to quantitatively track healing progression in situ via transcript profiling using high- throughput sequencing.

View Article: PubMed Central - PubMed

Affiliation: Massachusetts Institute of Technology - Lincoln Laboratory, Lexington, MA 02127, USA.

ABSTRACT
Traumatic lower-limb musculoskeletal injuries are pervasive amongst athletes and the military and typically an individual returns to activity prior to fully healing, increasing a predisposition for additional injuries and chronic pain. Monitoring healing progression after a musculoskeletal injury typically involves different types of imaging but these approaches suffer from several disadvantages. Isolating and profiling transcripts from the injured site would abrogate these shortcomings and provide enumerative insights into the regenerative potential of an individual's muscle after injury. In this study, a traumatic injury was administered to a mouse model and healing progression was examined from 3 hours to 1 month using high-throughput RNA-Sequencing (RNA-Seq). Comprehensive dissection of the genome-wide datasets revealed the injured site to be a dynamic, heterogeneous environment composed of multiple cell types and thousands of genes undergoing significant expression changes in highly regulated networks. Four independent approaches were used to determine the set of genes, isoforms, and genetic pathways most characteristic of different time points post-injury and two novel approaches were developed to classify injured tissues at different time points. These results highlight the possibility to quantitatively track healing progression in situ via transcript profiling using high- throughput sequencing.

No MeSH data available.


Related in: MedlinePlus

Dynamics of injured muscle tissue activated several days after injury.(a) Enriched KEGG pathways from differentially expressed genes for the middle time points (48–168 h). The size of the circle corresponds to the number of significant genes with each enriched pathway. Categories associated with growth emerge in contrast to the early period, which was characterized by inflammation and cell death. (b) Gene expression profiles of complement cascade trigger (C1qa) and two genes associated with different signaling pathways (Rbpj – Notch signaling, Hes6 – myoblast commitment and differentiation). The temporal activation of these different genes (and their associated networks and pathways) illustrates a progression of Complement and Notch activation, followed by Wnt signaling and myogenic differentiation. (red – injured samples, blue – uninjured samples, Rbpj – circles & dashed line, Hes6 – squares & solid line).
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f3: Dynamics of injured muscle tissue activated several days after injury.(a) Enriched KEGG pathways from differentially expressed genes for the middle time points (48–168 h). The size of the circle corresponds to the number of significant genes with each enriched pathway. Categories associated with growth emerge in contrast to the early period, which was characterized by inflammation and cell death. (b) Gene expression profiles of complement cascade trigger (C1qa) and two genes associated with different signaling pathways (Rbpj – Notch signaling, Hes6 – myoblast commitment and differentiation). The temporal activation of these different genes (and their associated networks and pathways) illustrates a progression of Complement and Notch activation, followed by Wnt signaling and myogenic differentiation. (red – injured samples, blue – uninjured samples, Rbpj – circles & dashed line, Hes6 – squares & solid line).

Mentions: A significant fraction of the upregulated genes in the early and middle time periods can be ascribed to invading immune cells (Fig. 3a), which in part act to phagocytize debris from the injured site. Concordantly, dramatic increases in expression of phagocytic and complement cascade genes were detected (Supp. Fig. 6) and Fig. 3b illustrates the expression profile of the C1qa gene, a complement cascade trigger. C1qa has previously been shown to inhibit muscle regeneration and stimulate the Wnt signaling pathway30, as well as induce expression of fibrotic genes and collagen production31 (Supp. Info S2 & Supp. Fig. 7). As Wnt signaling is viewed to increase in the middle time period, signatures of proliferating progenitors (Notch signaling3233, bone morphogenetic proteins34, secreted frizzled proteins35), which were upregulated in the early time period, begin to decline in expression. This temporal switch from Notch to Wnt36 is also accompanied by increases in expression of multiple genes associated with myogenic differentiation (Hes6 and Myod1, Myog, Myf6). Figure 3b demonstrates the expression profiles of RbpJ, the primary mediator of Notch signaling37, and HES6, a transcription factor that modulates myoblast commitment and differentiation38. As RbpJ and Notch signaling declines in the middle time period, Hes6 and Wnt signaling increase to promote myoblast differentiation. The temporal activation of these new sets of genes suggests their detection can assist to identify the onset of healing as well as establish the regenerative competence of a given individual after an acute traumatic LLMI.


In vivo Monitoring of Transcriptional Dynamics After Lower-Limb Muscle Injury Enables Quantitative Classification of Healing.

Aguilar CA, Shcherbina A, Ricke DO, Pop R, Carrigan CT, Gifford CA, Urso ML, Kottke MA, Meissner A - Sci Rep (2015)

Dynamics of injured muscle tissue activated several days after injury.(a) Enriched KEGG pathways from differentially expressed genes for the middle time points (48–168 h). The size of the circle corresponds to the number of significant genes with each enriched pathway. Categories associated with growth emerge in contrast to the early period, which was characterized by inflammation and cell death. (b) Gene expression profiles of complement cascade trigger (C1qa) and two genes associated with different signaling pathways (Rbpj – Notch signaling, Hes6 – myoblast commitment and differentiation). The temporal activation of these different genes (and their associated networks and pathways) illustrates a progression of Complement and Notch activation, followed by Wnt signaling and myogenic differentiation. (red – injured samples, blue – uninjured samples, Rbpj – circles & dashed line, Hes6 – squares & solid line).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4585378&req=5

f3: Dynamics of injured muscle tissue activated several days after injury.(a) Enriched KEGG pathways from differentially expressed genes for the middle time points (48–168 h). The size of the circle corresponds to the number of significant genes with each enriched pathway. Categories associated with growth emerge in contrast to the early period, which was characterized by inflammation and cell death. (b) Gene expression profiles of complement cascade trigger (C1qa) and two genes associated with different signaling pathways (Rbpj – Notch signaling, Hes6 – myoblast commitment and differentiation). The temporal activation of these different genes (and their associated networks and pathways) illustrates a progression of Complement and Notch activation, followed by Wnt signaling and myogenic differentiation. (red – injured samples, blue – uninjured samples, Rbpj – circles & dashed line, Hes6 – squares & solid line).
Mentions: A significant fraction of the upregulated genes in the early and middle time periods can be ascribed to invading immune cells (Fig. 3a), which in part act to phagocytize debris from the injured site. Concordantly, dramatic increases in expression of phagocytic and complement cascade genes were detected (Supp. Fig. 6) and Fig. 3b illustrates the expression profile of the C1qa gene, a complement cascade trigger. C1qa has previously been shown to inhibit muscle regeneration and stimulate the Wnt signaling pathway30, as well as induce expression of fibrotic genes and collagen production31 (Supp. Info S2 & Supp. Fig. 7). As Wnt signaling is viewed to increase in the middle time period, signatures of proliferating progenitors (Notch signaling3233, bone morphogenetic proteins34, secreted frizzled proteins35), which were upregulated in the early time period, begin to decline in expression. This temporal switch from Notch to Wnt36 is also accompanied by increases in expression of multiple genes associated with myogenic differentiation (Hes6 and Myod1, Myog, Myf6). Figure 3b demonstrates the expression profiles of RbpJ, the primary mediator of Notch signaling37, and HES6, a transcription factor that modulates myoblast commitment and differentiation38. As RbpJ and Notch signaling declines in the middle time period, Hes6 and Wnt signaling increase to promote myoblast differentiation. The temporal activation of these new sets of genes suggests their detection can assist to identify the onset of healing as well as establish the regenerative competence of a given individual after an acute traumatic LLMI.

Bottom Line: Comprehensive dissection of the genome-wide datasets revealed the injured site to be a dynamic, heterogeneous environment composed of multiple cell types and thousands of genes undergoing significant expression changes in highly regulated networks.Four independent approaches were used to determine the set of genes, isoforms, and genetic pathways most characteristic of different time points post-injury and two novel approaches were developed to classify injured tissues at different time points.These results highlight the possibility to quantitatively track healing progression in situ via transcript profiling using high- throughput sequencing.

View Article: PubMed Central - PubMed

Affiliation: Massachusetts Institute of Technology - Lincoln Laboratory, Lexington, MA 02127, USA.

ABSTRACT
Traumatic lower-limb musculoskeletal injuries are pervasive amongst athletes and the military and typically an individual returns to activity prior to fully healing, increasing a predisposition for additional injuries and chronic pain. Monitoring healing progression after a musculoskeletal injury typically involves different types of imaging but these approaches suffer from several disadvantages. Isolating and profiling transcripts from the injured site would abrogate these shortcomings and provide enumerative insights into the regenerative potential of an individual's muscle after injury. In this study, a traumatic injury was administered to a mouse model and healing progression was examined from 3 hours to 1 month using high-throughput RNA-Sequencing (RNA-Seq). Comprehensive dissection of the genome-wide datasets revealed the injured site to be a dynamic, heterogeneous environment composed of multiple cell types and thousands of genes undergoing significant expression changes in highly regulated networks. Four independent approaches were used to determine the set of genes, isoforms, and genetic pathways most characteristic of different time points post-injury and two novel approaches were developed to classify injured tissues at different time points. These results highlight the possibility to quantitatively track healing progression in situ via transcript profiling using high- throughput sequencing.

No MeSH data available.


Related in: MedlinePlus