Background and context
Neurodegenerative diseases share a curious feature: The causative mutations involves ubiquitously expressed genes, yet only certain cell types are vulnerable. This might be because the dependency on the mutated gene is not the same across cell types, or because only some cell types are equipped with protective mechanisms against the deleterious consequences of the mutation.
Amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA) are neurodegenerative diseases involving most somatic motor neurons. They both spare somatic motor neurons controlling eye movement, which makes them nice models to study the mechanism underlying the difference in vulnerability between different cell types. Using these two diseases as a model, preprints from the Hedlund Lab introduced two novel methods to tackle this long-held question in neurodegeneration.
Key findings: LCM-seq
To understand why certain somatic motor neurons can tolerate SMN deficiency, Nichterwitz et al. devised a protocol, LCM-seq, in which they collected neurons of specific types with laser capture microdissection according to their location and then profiled the collected neurons with RNA-seq. The authors compared the transcriptome of different cell types, including susceptible somatic motor neurons, non-susceptible somatic motor neurons, visceral motor neurons, and other cholinergic neurons from the red nucleus. To understand the dynamic regulation during disease progression, they also performed analysis over different time points, including a pre-symptomatic stage (2 days after birth, P2), an early-symptomatic stage (P5), and a symptomatic stage (P10) on a mouse model of spinal muscular atrophy (SMA).
The authors first used hierarchical clustering to show that the transcriptome of somatic motor neuron samples, no matter resistant or not, segregated according to their disease status, while transcriptome of visceral motor neurons and red nucleus neurons did not. This segregation suggests that despite having a dysregulated transcriptome, somatic motor neurons resistant to SMA harbor a protective mechanism different from visceral motor neurons and red nucleus neurons. In all SMA somatic motor neuron samples, activation of p53 pathway was observed, consistent with a previous study . Nonetheless, resistant and susceptible somatic motor neurons responded to SMA differently, sharing at most 20% of dysregulated genes in a late stage (P10). Specifically, genes involved in DNA damage repair and anti-apoptotic factors were activated in late-stage resistant somatic motor neurons, which could prevent cell death. Furthermore, genes involved in neurotransmitter release, including Syt1, Syt5, and Cplx2, were also upregulated in resistant neurons, thereby possibly compensating for neuromuscular junction dysfunction.
Together, by performing cell type-specific temporal profiling of transcriptomic changes in spinal muscular atrophy, this study revealed potential protective mechanisms that resistant somatic motor neurons utilize to maintain normal function in SMA.
Key findings: Axon-seq
In embryonic stem cell-derived spinal motor neurons, Nijssen et al. developed Axon-seq, which makes use of a novel microfluidic system allowing lysis of only axons growing in a compartment separated from soma.
RNA-seq of axon compartments revealed a unique transcriptome profile different from soma: the axon trascriptome contains fewer detected genes and is enriched in transcripts related to local translation, mitochondrial function, and nonsense-mediated decay. These enriched genes are consistent with the high energy demand at axon terminals and the need of local regulation.
To understand if axonal local regulation is dysregulated in neurodegenerative diseases, the authors further applied Axon-seq to stem cell-derived motor neurons overexpressing human SOD1G93Amutant protein, a well-established model of amyotrophic lateral sclerosis. Interestingly, most dysregulation uncovered by Axon-seq was only detectable in axons: 98% (119 in 121) differentially detected transcripts in SOD1G93A motor axons were only dysregulated in axon compartments but not in soma compartments. Among these axonal gene dysregulations, some are known to be detrimental in neurons, but their involvement in ALS has not been reported. To understand whether degeneration in motor neurons shares axonal dysregulation, the authors compared a previously published motor neuron axon dataset in spinal muscular atrophy  and identified dysregulated Neuropilin 1 (Nrp1) also in spinal muscular atrophy motor axons.
In short, this preprint introduced Axon-seq, a sensitive method to profile the axon transcriptome with high purity and revealed axon transcripts that are either cell-type specific or disease-relevant.
Why I like these preprints
Though researchers have long sought to understand the source of selective vulnerability by comparing involved and not-involved neurons, our knowledge of the underlying mechanism remains sparse and sometimes paradoxical. One major challenge of this approach is the robust nature of biological processes, in which cells and tissues would respond to better tolerate pathological disruptions. It is thus difficult to distinguish detrimental disease processes from compensatory responses, and some critical dysregulation might even be masked. To overcome this, I believe the development of high-throughput techniques with temporal and subcellular precision is a critical step.
These two preprints characterized transcriptomic changes in somatic motor neurons across cell types, time points, and subcellular compartments, and suggested dysregulations previously masked in bulk profiling. All this information is invaluable because if they are properly integrated with our prior knowledge, they can give us a better chance to identify compensation versus dysregulation and even to infer causality from a temporal profile.
Beyond a disease prospective, this powerful and scalable cellular model to investigate the transcriptome specifically in axons introduced by Nijssen et al. could also help us understand how different neurons find their way to their targets and wire accurately.
- The authors suggested that in resistant somatic motor neurons, the compensatory transcriptional response is highly coordinated. It is thus tempting to imagine that this coordinated response is regulated by one or few transcription factors. Would it be possible to identify these coordinators from earlier- or pre-symptomatic samples?
- The analysis that discovered protective responses focused mainly on the late-symptomatic stage after significant motor neuron loss , which is not uniform across subtypes of spinal motor neurons . When spinal motor neurons are treated as a whole to perform differential expression analysis, would it be possible to tell whether differential expression reflects changes in transcription activity or in composition of collected cells?
- Control of local translation is known to be important in axons, and in this preprint, transcripts regulating local translation are enriched in Axon-seq. It will be very intriguing to see what kind of post-transcriptional regulation is present in axons to allow axon terminals or neuromuscular junctions to properly adapt and respond to environmental changes.
- Simon, C. M. et al. Converging Mechanisms of p53 Activation Drive Motor Neuron Degeneration in Spinal Muscular Atrophy. Cell Rep. 21, 3767–3780 (2017).
- Saal L, Briese M, Kneitz S, Glinka M, Sendtner M. Subcellular transcriptome alterations in a cell culture model of spinal muscular atrophy point to widespread defects in axonal growth and presynaptic differentiation. RNA. 2014;20(11):1789-1802.
- Le, T. T. et al. SMNΔ7, the major product of the centromeric survival motor neuron (SMN2) gene, extends survival in mice with spinal muscular atrophy and associates with full-length SMN. Hum. Mol. Genet. 14, 845–857 (2005).
- Murray, L. M., Beauvais, A., Gibeault, S., Courtney, N. L. & Kothary, R. Transcriptional profiling of differentially vulnerable motor neurons at pre-symptomatic stage in the Smn (2b/-) mouse model of spinal muscular atrophy. Acta Neuropathol. Commun. 3, 55 (2015).
Posted on: 12th September 2018 , updated on: 13th September 2018