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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

Inflammatory and immune response transcriptional programs activated after traumatic muscle injury.(a) Gene expression profiles of pro- and anti-inflammatory genes (IL-1b & Socs3 and Il-6 & Arid5a), which show similar activation profiles and are part of networks with opposing function, (red – injured samples, blue – uninjured samples, IL-1b – squares & solid line, Socs3 – circles & dashed line, IL-6 – squares & solid line, Arid5a – circles & dashed line). Arid5a operates to reduce IL-6 stability, indicating the inflammatory response to injury is transcriptionally regulated on multiple levels. (b) Heatmaps of significantly up-regulated (red) or down-regulated (blue) genes for different functional categories. (c) Example of alternative splicing detected during early time period. Il1rl1 (ST2) undergoes an increase expression in the ST2L isoform (blue), which has previously been shown to promote proliferation and activation of anti-inflammatory macrophages.
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f2: Inflammatory and immune response transcriptional programs activated after traumatic muscle injury.(a) Gene expression profiles of pro- and anti-inflammatory genes (IL-1b & Socs3 and Il-6 & Arid5a), which show similar activation profiles and are part of networks with opposing function, (red – injured samples, blue – uninjured samples, IL-1b – squares & solid line, Socs3 – circles & dashed line, IL-6 – squares & solid line, Arid5a – circles & dashed line). Arid5a operates to reduce IL-6 stability, indicating the inflammatory response to injury is transcriptionally regulated on multiple levels. (b) Heatmaps of significantly up-regulated (red) or down-regulated (blue) genes for different functional categories. (c) Example of alternative splicing detected during early time period. Il1rl1 (ST2) undergoes an increase expression in the ST2L isoform (blue), which has previously been shown to promote proliferation and activation of anti-inflammatory macrophages.

Mentions: Pro-inflammatory2021 and chemotactic protein members2223 such as IL-6, IL-1β and CCl2 were, as expected, rapidly upregulated in the early time period (Supp. Info S1 & Supp. Fig. 4). Anti- inflammatory genes24 such as Socs3, CD24 and IL-10rα and posttranscriptional regulators such as AT-rich interactive domain-containing protein 5a (Arid5a)25 and Regnase-1 (Zc3h12a)26 were also upregulated (Fig. 2a and Supp. Info S1). Arid5a and Regnase-1 have previously been shown to regulate inflammatory mRNA stability (such as IL-6), highlighting tight control of the inflammatory response and sensitivity of the RNA-Seq data. Transcripts encompassing a family of pro-apoptotic loci and anti-apoptotic loci were also detected in the early time period (Fig. 2b), which are likely the result of invading immune cells release of oxygen free radicals and other reactive oxygen species that induce secondary tissue damage and cell death. This observation of secondary tissue damage also agrees well with the histological analysis (Supp. Fig. 1). Alternative promoter usage and isoform switching events were also identified within the early period (Supp. Fig. 5). A novel example is the receptor for the “alarmin” gene27 (IL-1rl1 or St2), which was previously shown to activate upon tissue damage and restrain inflammation28. Figure 2c shows an increase in expression of the St2l isoform in the injured samples (blue isoform), which peaked at 10 h and remained elevated until 336 h. The St2l isoform has also previously been shown to promote proliferation and activation of anti-inflammatory macrophages29 and regulatory T-cells8, both of which critically restrain inflammation and influence various muscle repair and regeneration pathways. Collectively, these observations are consistent with previous studies of muscle tissue injury567182021222327, whereby transcripts associated with inflammation, invading immune cells, cytokine signaling, apoptosis, anoikis, and proliferation were observed immediately after injury. Detection of these transcripts also serve as excellent indicators to determine injury severity by observing shifts in the balance of pro- and anti-inflammatory molecules (such as CD24 and CCl2), which influence the degree of secondary damage102021.


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)

Inflammatory and immune response transcriptional programs activated after traumatic muscle injury.(a) Gene expression profiles of pro- and anti-inflammatory genes (IL-1b & Socs3 and Il-6 & Arid5a), which show similar activation profiles and are part of networks with opposing function, (red – injured samples, blue – uninjured samples, IL-1b – squares & solid line, Socs3 – circles & dashed line, IL-6 – squares & solid line, Arid5a – circles & dashed line). Arid5a operates to reduce IL-6 stability, indicating the inflammatory response to injury is transcriptionally regulated on multiple levels. (b) Heatmaps of significantly up-regulated (red) or down-regulated (blue) genes for different functional categories. (c) Example of alternative splicing detected during early time period. Il1rl1 (ST2) undergoes an increase expression in the ST2L isoform (blue), which has previously been shown to promote proliferation and activation of anti-inflammatory macrophages.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f2: Inflammatory and immune response transcriptional programs activated after traumatic muscle injury.(a) Gene expression profiles of pro- and anti-inflammatory genes (IL-1b & Socs3 and Il-6 & Arid5a), which show similar activation profiles and are part of networks with opposing function, (red – injured samples, blue – uninjured samples, IL-1b – squares & solid line, Socs3 – circles & dashed line, IL-6 – squares & solid line, Arid5a – circles & dashed line). Arid5a operates to reduce IL-6 stability, indicating the inflammatory response to injury is transcriptionally regulated on multiple levels. (b) Heatmaps of significantly up-regulated (red) or down-regulated (blue) genes for different functional categories. (c) Example of alternative splicing detected during early time period. Il1rl1 (ST2) undergoes an increase expression in the ST2L isoform (blue), which has previously been shown to promote proliferation and activation of anti-inflammatory macrophages.
Mentions: Pro-inflammatory2021 and chemotactic protein members2223 such as IL-6, IL-1β and CCl2 were, as expected, rapidly upregulated in the early time period (Supp. Info S1 & Supp. Fig. 4). Anti- inflammatory genes24 such as Socs3, CD24 and IL-10rα and posttranscriptional regulators such as AT-rich interactive domain-containing protein 5a (Arid5a)25 and Regnase-1 (Zc3h12a)26 were also upregulated (Fig. 2a and Supp. Info S1). Arid5a and Regnase-1 have previously been shown to regulate inflammatory mRNA stability (such as IL-6), highlighting tight control of the inflammatory response and sensitivity of the RNA-Seq data. Transcripts encompassing a family of pro-apoptotic loci and anti-apoptotic loci were also detected in the early time period (Fig. 2b), which are likely the result of invading immune cells release of oxygen free radicals and other reactive oxygen species that induce secondary tissue damage and cell death. This observation of secondary tissue damage also agrees well with the histological analysis (Supp. Fig. 1). Alternative promoter usage and isoform switching events were also identified within the early period (Supp. Fig. 5). A novel example is the receptor for the “alarmin” gene27 (IL-1rl1 or St2), which was previously shown to activate upon tissue damage and restrain inflammation28. Figure 2c shows an increase in expression of the St2l isoform in the injured samples (blue isoform), which peaked at 10 h and remained elevated until 336 h. The St2l isoform has also previously been shown to promote proliferation and activation of anti-inflammatory macrophages29 and regulatory T-cells8, both of which critically restrain inflammation and influence various muscle repair and regeneration pathways. Collectively, these observations are consistent with previous studies of muscle tissue injury567182021222327, whereby transcripts associated with inflammation, invading immune cells, cytokine signaling, apoptosis, anoikis, and proliferation were observed immediately after injury. Detection of these transcripts also serve as excellent indicators to determine injury severity by observing shifts in the balance of pro- and anti-inflammatory molecules (such as CD24 and CCl2), which influence the degree of secondary damage102021.

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