PREPL

Mitochondrial oxidative phosphorylation (OXPHOS) complexes are assembled from proteins encoded by both nuclear and mitochondrial DNA. These dual-origin enzymes pose a complex gene regulatory challenge for cells requiring coordinated gene expression across organelles. To identify genes involved in dual-origin protein complex synthesis, we performed fluorescence-activated cell-sorting-based genome-wide screens analysing mutant cells with unbalanced levels of mitochondrial- and nuclear-encoded subunits of Complex IV. We identified genes involved in OXPHOS biogenesis, including two uncharacterized genes: PREPL and NME6. We found that PREPL specifically impacts Complex IV biogenesis by acting at the intersection of mitochondrial lipid metabolism and protein synthesis, whereas NME6, an uncharacterized nucleoside diphosphate kinase, controls OXPHOS biogenesis through multiple mechanisms reliant on its NDPK domain. Firstly, NME6 forms a complex with RCC1L, which together perform nucleoside diphosphate kinase activity to maintain local mitochondrial pyrimidine triphosphate levels essential for mitochondrial RNA abundance. Secondly, NME6 modulates the activity of mitoribosome regulatory complexes, altering mitoribosome assembly and mitochondrial RNA pseudouridylation. Taken together, we propose that NME6 acts as a link between compartmentalized mitochondrial metabolites and mitochondrial gene expression.

Glucose metabolism plays a crucial role in the progression of Alzheimer's disease (AD). The purpose of this study is to identify genes related to glucose metabolism in AD by bioinformatics, construct an early AD prediction model from the perspective of glucose metabolism, and analyze the characteristics of immune cell infiltration.

AD-related modules and genes were screened by weighted gene co-expression network analysis (WGCNA). The GO and KEEG enrichment analysis were used to explore the potential biological functions of glucose metabolism related genes (GMRGs) in AD. The Least Absolute Shrinkage Selection Operator (LASSO) method was used to construct an early AD prediction model based on GMRGs. Then, the receiver operating characteristic curve (ROC) and nomogram were introduced to evaluate the effectiveness of this model. Finally, CIBERSORT and single-cell analysis were applied for illustrating the immune characteristics in AD patients.

A total of 462 differential expressed genes (DEGs) were obtained between Non-Alzheimer's disease (ND,) and AD groups. The genes in the blue module had the highest correlation with AD by WGCNA analysis. We found 18 intersected genes among DEGs, blue model genes and GMRGs according to the Venn diagram. The GO and KEEG enrichment analysis showed that these 18 genes were mainly involved in the production of metabolites and energy, glycolysis, amino acid biosynthesis and so on. The early AD prediction model including ENO2, TPI1, AEBP1, HERC1, PCSK1, PREPL, SLC25A4, UQCRC2, CHST6, DDIT4, ACSS1 and SUCLA2 was constructed by LASSO analysis. The area under the curve (AUC) of this model in brain tissues was 0.942. Then, we draw the nomogram of this model and the C-index was 0.942. The model was further validated in blood samples and the AUC was 0.644. Immune cell infiltration analysis showed that the proportion of plasma cells, T cells follicular helper and activated NK cells in AD group were significantly lower than ND group, while the proportion of M1 macrophages, neutrophils, T cells CD4 naive and γ-δ T cells was significantly increased when compared with the ND group. Additionally, the specific GMRGs such as ENO2, DDIT4, and SUCLA2 are significantly correlated with certain immune cells such as plasma cells, follicular helper T cells, and M1 macrophages. Single-cell analysis results suggested that the increased macrophages in AD was associated with the up-regulation of AEBP1, DDIT4 and ACSS1.

The diagnosis model based on the twelve GMRGs has strong predictive ability and can be used as early diagnosis biomarkers for AD. In addition, these GMRGs closely associate with AD development by influencing the glucose metabolism of immune cells.

Current treatments for Alzheimer's disease (AD) help reduce symptoms for a limited time but do not treat the underlying pathology. To identify potential therapeutic targets for AD, an integrative network analysis was previously carried out using 364 human postmortem control, mild cognitive impairment and AD brains. This analysis identified proline endopeptidase-like protein (PREPL), an understudied protein, as a down-regulated protein in late-onset AD patients. In this study we investigate the role of PREPL. Analyses of data from human postmortem samples and PREPL knockdown (KD) cells suggest that PREPL expression modulates pathways associated with protein trafficking, synaptic activities, and lipid metabolism. Furthermore, PREPL KD impairs cell proliferation, modulates the structure of vesicles and levels of neuropeptide processing enzymes as well as secretion of neuropeptides. In addition, decrease in PREPL levels leads to changes in the levels of a number of synaptic proteins as well as changes in the levels of secreted Amyloid Beta (Ab) 42 peptide and Tau phosphorylation. Finally, we report that local decrease in PREPL levels in mouse hippocampus attenuates long-term potentiation suggesting a role in synaptic plasticity. Together, our results indicate that PREPL affects neuronal function by modulating protein trafficking and synaptic function, an important mechanism of AD pathogenesis. Significance Statement Integrative network analysis reveals PREPL to be downregulated in human sporadic late-onset Alzheimer's disease brains. Down regulation of PREPL leads to increases in Aβ secretion, Tau phosphorylation and decreases in protein trafficking and in long-term potentiation.