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wu, l.

Publications and source records attributed to wu, l..

3 recordsLinked to original sources

Single-cell RNA sequencing reveals dysregulation of spinal cord cell types in a several spinal muscular atrophy mouse model

Although spinal muscular atrophy (SMA) is a motor neuron disease caused by the loss of survival of motor neuron (SMN) proteins, there is growing evidence that non-neuronal cells play important roles in SMA pathogenesis. However, transcriptome alterations occurring at the single-cell level in SMA spinal cord remain unknown, preventing us from fully comprehending the role of specific cells. Here, we performed single-cell RNA sequencing of the spinal cord of a severe SMA mouse model, and identified ten cell types as well as their differentially expressed genes. Using CellChat, we found that cellular communication between different cell types in the spinal cord of SMA mice was significantly reduced. A dimensionality reduction analysis revealed 29 cell subtypes and their differentially expressed gene. A subpopulation of vascular fibroblasts showed the most significant change in the SMA spinal cord at the single-cell level. This subpopulation was drastically reduced, possibly causing vascular defects and resulting in widespread protein synthesis and energy metabolism reductions in SMA mice. This study reveals for the first time a single-cell atlas of the spinal cord of mice with severe SMA, and sheds new light on the pathogenesis of SMA.

neuroscience↗

Nrf2 mediated ER-phagy protects against oxidative damage in intervertebral disc degeneration

Intervertebral disc degeneration (IDD) increases the risk of low back pain (LBP). Oxidative stress may induce cellular damage and contribute to various diseases including IDD. Endoplasmic reticulum autophagy (ER-phagy) is a specific type of autophagy, its role in oxidative stress induced damage as well as in IDD is unknown. This study explores the role of ER-phagy in oxidative damage in intervertebral disc nucleus pulposus cells (NPCs), as well as the Nrf2/FAM134B axis in ER-phagy regulation and IDD therapy. We found ER-phagy was decreased in NPCs during oxidative stress; while FAM134B may promote ER-phagy and alleviate oxidative stress induced ER-stress and apoptosis. In addition, the nuclear transcription factor Nrf2 may promote the expression of FAM134B as well as ER-phagy, and suppress ER-stress and apoptosis in NPCs. Furthermore, overexpression of FAM134B and Nrf2 could effectively attenuate the progression of IDD in rats in vivo. These results suggest Nrf2/FAM134B mediated ER-phagy may combat oxidative damage in cells; meanwhile, ER-phagy as well as Nrf2 could be potential therapeutic targets for IDD. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/469451v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@188b390org.highwire.dtl.DTLVardef@1c4e4f6org.highwire.dtl.DTLVardef@193fe77org.highwire.dtl.DTLVardef@12770e2_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

A peptide bond based energy score improve identification of the native structures

Protein structure resolution has lagged far behind sequence determination, as it is often laborious and time-consuming to resolve individual protein structure - more often than not even impossible. For computational prediction, due to the lack of detailed knowledge on the folding driving forces, how to design an energy function is still an open question. Furthermore, an effective criterion to evaluate the performance of the energy function is also lacking. Here we present a novel knowledge-based-energy scoring function, simply considering the interactions of peptide bonds, rather than, as conventionally, the residues or atoms as the most important energy contribution. This energy scoring was evaluated by selecting the X-ray structure from a large number of possibilities. It not only outperforms the best of the previously published statistical potentials, but also has very low computational expense. Besides, we suggest an alternative criterion to evaluate the performance of the energy scoring function, measured by the template modeling score of the selected rank-one. We argue that the comparison should allow for some deviation between the x-ray and predicted structures. Collectively, this accurate and simple energy scoring function, together with the optimized criterion, will significantly advance the computational protein structure prediction.

bioinformatics↗