DLK regulates a distinctive transcriptional regeneration program after peripheral nerve injury.
TL;DR: It is suggested that DLK-dependency might provide a selective filter for regeneration-associated genes among the injury-responsive transcriptome through its role as a central regulator of injury responses.
About: This article is published in Neurobiology of Disease.The article was published on 2019-02-05 and is currently open access. It has received 40 citations till now. The article focuses on the topics: Peripheral nerve injury & Sciatic nerve injury.
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TL;DR: Transcriptomic plasticity, previously thought of as a driver of chronic pain, is exposed as a programed response to many types of injury and a potential mechanism for regulating sensation during wound healing.
Abstract: In mice, spared nerve injury replicates symptoms of human neuropathic pain and induces upregulation of many genes in somatosensory neurons. Here we used single cell transcriptomics to probe the effects of partial infraorbital transection of the trigeminal nerve at the cellular level. Uninjured neurons were unaffected by transection of major nerve branches, segregating into many different classes. In marked contrast, axotomy rapidly transformed damaged neurons into just two new and closely-related classes where almost all original identity was lost. Remarkably, sensory neurons also adopted this transcriptomic state following various minor peripheral injuries. By genetically marking injured neurons, we showed that the injury-induced transformation was reversible, with damaged cells slowly reacquiring normal gene expression profiles. Thus, our data expose transcriptomic plasticity, previously thought of as a driver of chronic pain, as a programed response to many types of injury and a potential mechanism for regulating sensation during wound healing.
71 citations
Cites background from "DLK regulates a distinctive transcr..."
...These genes probably contribute to restoration of normal peripheral innervation of tissue during wound healing (Shin et al., 2019)....
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...(a) Selected up-regulated genes, their proposed functional role and previous assignment as injury-related transcripts (Cobos et al., 2018; Guan et al., 2016; Shin et al., 2019; Wlaschin et al., 2018) and/or as genes involved in neural regeneration (Mahar and Cavalli, 2018)....
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...One well-characterized effect of SNI is the upregulation of genes in response to injury (Cobos et al., 2018; Guan et al., 2016; Shin et al., 2019; Wlaschin et al., 2018)....
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...(b) Selected down-regulated genes, their functional classification and previous assignment as injury-related transcripts (Shin et al., 2019)....
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TL;DR: It is found that stimulating DLK activity predisposes axons to SARM1-dependent degeneration, and enhancedDLK activity reduces axon survival factor abundance and renders axons more susceptible to trauma and metabolic insult.
Abstract: Axon degeneration is a prominent component of many neurological disorders. Identifying cellular pathways that contribute to axon vulnerability may identify new therapeutic strategies for maintenance of neural circuits. Dual leucine zipper kinase (DLK) is an axonal stress response MAP3K that is chronically activated in several neurodegenerative diseases. Activated DLK transmits an axon injury signal to the neuronal cell body to provoke transcriptional adaptations. However, the consequence of enhanced DLK signaling to axon vulnerability is unknown. We find that stimulating DLK activity predisposes axons to SARM1-dependent degeneration. Activating DLK reduces levels of the axon survival factors NMNAT2 and SCG10, accelerating their loss from severed axons. Moreover, mitochondrial dysfunction independently decreases the levels of NMNAT2 and SCG10 in axons, and in conjunction with DLK activation, leads to a dramatic loss of axonal NMNAT2 and SCG10 and evokes spontaneous axon degeneration. Hence, enhanced DLK activity reduces axon survival factor abundance and renders axons more susceptible to trauma and metabolic insult.
52 citations
TL;DR: This study demonstrates both molecular and cellular differences in the nerve injury-induced immune response between DRG and SCG and between WT and Ccr2−/− mice.
Abstract: Neuroinflammation accompanies neural trauma and most neurological diseases. Axotomy in the peripheral nervous system (PNS) leads to dramatic changes in the injured neuron: the cell body expresses a distinct set of genes known as regeneration-associated genes, the distal axonal segment degenerates and its debris is cleared, and the axons in the proximal segment form growth cones and extend neurites. These processes are orchestrated in part by immune and other non-neuronal cells. Macrophages in ganglia play an integral role in supporting regeneration. Here, we explore further the molecular and cellular components of the injury-induced immune response within peripheral ganglia. Adult male wild-type (WT) and Ccr2
−/−
mice were subjected to a unilateral transection of the sciatic nerve and axotomy of the superior cervical ganglion (SCG). Antibody arrays were used to determine the expression of chemokines and cytokines in the dorsal root ganglion (DRG) and SCG. Flow cytometry and immunohistochemistry were utilized to identify the cellular composition of the injury-induced immune response within ganglia. Chemokine expression in the ganglia differed 48 h after nerve injury with a large increase in macrophage inflammatory protein-1γ in the SCG but not in the DRG, while C-C class chemokine ligand 2 was highly expressed in both ganglia. Differences between WT and Ccr2
−/−
mice were also observed with increased C-C class chemokine ligand 6/C10 expression in the WT DRG compared to C-C class chemokine receptor 2 (CCR2)−/− DRG and increased CXCL5 expression in CCR2−/− SCG compared to WT. Diminished macrophage accumulation in the DRG and SCG of Ccr2
−/−
mice was found compared to WT ganglia 7 days after nerve injury. Interestingly, neutrophils were found in the SCG but not in the DRG. Cytokine expression, measured 7 days after injury, differed between ganglion type and genotype. Macrophage activation was assayed by colabeling ganglia with the anti-inflammatory marker CD206 and the macrophage marker CD68, and an almost complete colocalization of the two markers was found in both ganglia. This study demonstrates both molecular and cellular differences in the nerve injury-induced immune response between DRG and SCG and between WT and Ccr2
−/−
mice.
49 citations
TL;DR: In this article, the authors performed a single-cell transcriptional profiling of mouse dorsal root ganglia (DRG) in response to peripheral (sciatic nerve crush) and central axon injuries (dorsal root crush and spinal cord injury).
Abstract: Sensory neurons with cell bodies in dorsal root ganglia (DRG) represent a useful model to study axon regeneration. Whereas regeneration and functional recovery occurs after peripheral nerve injury, spinal cord injury or dorsal root injury is not followed by regenerative outcomes. Regeneration of sensory axons in peripheral nerves is not entirely cell autonomous. Whether the DRG microenvironment influences the different regenerative capacities after injury to peripheral or central axons remains largely unknown. To answer this question, we performed a single-cell transcriptional profiling of mouse DRG in response to peripheral (sciatic nerve crush) and central axon injuries (dorsal root crush and spinal cord injury). Each cell type responded differently to the three types of injuries. All injuries increased the proportion of a cell type that shares features of both immune cells and glial cells. A distinct subset of satellite glial cells (SGC) appeared specifically in response to peripheral nerve injury. Activation of the PPARα signaling pathway in SGC, which promotes axon regeneration after peripheral nerve injury, failed to occur after central axon injuries. Treatment with the FDA-approved PPARα agonist fenofibrate increased axon regeneration after dorsal root injury. This study provides a map of the distinct DRG microenvironment responses to peripheral and central injuries at the single-cell level and highlights that manipulating non-neuronal cells could lead to avenues to promote functional recovery after CNS injuries or disease.
39 citations
TL;DR: It is found that prominin-1 interacts with the type I TGF-β receptor ALK4, and that they synergistically induce phosphorylation of Smad2, and the results suggest that Prom1 and cholesterol metabolism pathways are possible therapeutic targets for the promotion of neural recovery after injury.
Abstract: Axon regeneration is regulated by a neuron-intrinsic transcriptional program that is suppressed during development but that can be reactivated following peripheral nerve injury Here we identify Prom1, which encodes the stem cell marker prominin-1, as a regulator of the axon regeneration program Prom1 expression is developmentally down-regulated, and the genetic deletion of Prom1 in mice inhibits axon regeneration in dorsal root ganglion (DRG) cultures and in the sciatic nerve, revealing the neuronal role of Prom1 in injury-induced regeneration Elevating prominin-1 levels in cultured DRG neurons or in mice via adeno-associated virus-mediated gene delivery enhances axon regeneration in vitro and in vivo, allowing outgrowth on an inhibitory substrate Prom1 overexpression induces the consistent down-regulation of cholesterol metabolism-associated genes and a reduction in cellular cholesterol levels in a Smad pathway-dependent manner, which promotes axonal regrowth We find that prominin-1 interacts with the type I TGF-β receptor ALK4, and that they synergistically induce phosphorylation of Smad2 These results suggest that Prom1 and cholesterol metabolism pathways are possible therapeutic targets for the promotion of neural recovery after injury
28 citations
References
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TL;DR: By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
Abstract: DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
31,015 citations
TL;DR: The Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure outperforms other aligners by a factor of >50 in mapping speed.
Abstract: Motivation Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. Results To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. Availability and implementation STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
30,684 citations
TL;DR: The command-line tool cutadapt is developed, which supports 454, Illumina and SOLiD (color space) data, offers two adapter trimming algorithms, and has other useful features.
Abstract: When small RNA is sequenced on current sequencing machines, the resulting reads are usually longer than the RNA and therefore contain parts of the 3' adapter. That adapter must be found and removed error-tolerantly from each read before read mapping. Previous solutions are either hard to use or do not offer required features, in particular support for color space data. As an easy to use alternative, we developed the command-line tool cutadapt, which supports 454, Illumina and SOLiD (color space) data, offers two adapter trimming algorithms, and has other useful features. Cutadapt, including its MIT-licensed source code, is available for download at http://code.google.com/p/cutadapt/
20,255 citations
TL;DR: The results suggest that Cufflinks can illuminate the substantial regulatory flexibility and complexity in even this well-studied model of muscle development and that it can improve transcriptome-based genome annotation.
Abstract: High-throughput mRNA sequencing (RNA-Seq) promises simultaneous transcript discovery and abundance estimation. However, this would require algorithms that are not restricted by prior gene annotations and that account for alternative transcription and splicing. Here we introduce such algorithms in an open-source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed >430 million paired 75-bp RNA-Seq reads from a mouse myoblast cell line over a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Over the time series, 330 genes showed complete switches in the dominant transcription start site (TSS) or splice isoform, and we observed more subtle shifts in 1,304 other genes. These results suggest that Cufflinks can illuminate the substantial regulatory flexibility and complexity in even this well-studied model of muscle development and that it can improve transcriptome-based genome annotation.
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TL;DR: The survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.
Abstract: Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.
13,102 citations