Cerebral transcriptome analysis reveals age-dependent progression of neuroinflammation in P301S mutant tau transgenic male mice

The reverse transcriptase inhibitor 3TC modulates hippocampal transcriptome signatures of inflammation in tauopathy model mice

Reducing neuroinflammation, a key contributor to brain aging and neurodegenerative diseases, is a promising strategy for improving cognitive function in these settings. The FDA-approved nucleoside reverse transcriptase inhibitor 3TC (Lamivudine) has been reported to improve cognitive function in old wild-type mice and multiple mouse models of neurodegenerative disease, but its effects on the brain have not been comprehensively investigated. In the current study, we used transcriptomics to broadly characterize the effects of long-term supplementation with a human-equivalent therapeutic dose of 3TC on the hippocampal transcriptome in male and female rTg4510 mice (a commonly studied model of tauopathy-associated neurodegeneration). We found that tauopathy increased hippocampal transcriptomic signatures of neuroinflammation/immune activation, but 3TC treatment reversed some of these effects. We also found that 3TC mitigated tauopathy-associated activation of key transcription factors that contribute to neuroinflammation and immune activation, and these changes were related to improved recognition memory performance. Collectively, our findings suggest that 3TC exerts protective effects against tauopathy in the hippocampus by modulating inflammation and immune activation, and they may provide helpful insight for ongoing clinical efforts to determine if 3TC and/or related therapeutics hold promise for treating neurodegeneration.

Cholesterol 25-hydroxylase mediates neuroinflammation and neurodegeneration in a mouse model of tauopathy

Alzheimer's disease (AD) is characterized by amyloid plaques and neurofibrillary tangles, in addition to neuroinflammation and changes in brain lipid metabolism. 25-Hydroxycholesterol (25-HC), a known modulator of both inflammation and lipid metabolism, is produced by cholesterol 25-hydroxylase encoded by Ch25h expressed as a "disease-associated microglia" signature gene. However, whether Ch25h influences tau-mediated neuroinflammation and neurodegeneration is unknown. Here, we show that in the absence of Ch25h and the resultant reduction in 25-HC, there is strikingly reduced age-dependent neurodegeneration and neuroinflammation in the hippocampus and entorhinal/piriform cortex of PS19 mice, which express the P301S mutant human tau transgene. Transcriptomic analyses of bulk hippocampal tissue and single nuclei revealed that Ch25h deficiency in PS19 mice strongly suppressed proinflammatory signaling in microglia. Our results suggest a key role for Ch25h/25-HC in potentiating proinflammatory signaling to promote tau-mediated neurodegeneration. Ch25h may represent a novel therapeutic target for primary tauopathies, AD, and other neuroinflammatory diseases.

Antisense Oligonucleotide-Mediated Reduction of HDAC6 Does Not Reduce Tau Pathology in P301S Tau Transgenic Mice

Acetylation of tau protein is dysregulated in Alzheimer's Disease (AD). It has been proposed that acetylation of specific sites in the KXGS motif of tau can regulate phosphorylation of nearby residues and reduce the propensity of tau to aggregate. Histone deacetylase 6 (HDAC6) is a cytoplasmic enzyme involved in deacetylation of multiple targets, including tau, and it has been suggested that inhibition of HDAC6 would increase tau acetylation at the KXGS motifs and thus may present a viable therapeutic approach to treat AD. To directly test the contribution of HDAC6 to tau pathology, we intracerebroventricularly injected an antisense oligonucleotide (ASO) directed against HDAC6 mRNA into brains of P301S tau mice (PS19 model), which resulted in a 70% knockdown of HDAC6 protein in the brain. Despite a robust decrease in levels of HDAC6, no increase in tau acetylation was observed. Additionally, no change of tau phosphorylation or tau aggregation was detected upon the knockdown of HDAC6. We conclude that HDAC6 does not impact tau pathology in PS19 mice.

Melatonin and Melatonergic Influence on Neuronal Transcription Factors: Implications for the Development of Novel Therapies for Neurodegenerative Disorders

Melatonin is a multifunctional signalling molecule that is secreted by the mammalian pineal gland, and also found in a number of organisms including plants and bacteria. Research has continued to uncover an ever-increasing number of processes in which melatonin is known to play crucial roles in mammals. Amongst these functions is its contribution to cell multiplication, differentiation and survival in the brain. Experimental studies show that melatonin can achieve these functions by influencing transcription factors which control neuronal and glial gene expression. Since neuronal survival and differentiation are processes that are important determinants of the pathogenesis, course and outcome of neurodegenerative disorders; the known and potential influences of melatonin on neuronal and glial transcription factors are worthy of constant examination. In this review, relevant scientific literature on the role of melatonin in preventing or altering the course and outcome of neurodegenerative disorders, by focusing on melatonin's influence on transcription factors is examined. A number of transcription factors whose functions can be influenced by melatonin in neurodegenerative disease models have also been highlighted. Finally, the therapeutic implications of melatonin's influences have also been discussed and the potential limitations to its applications have been highlighted.

Integrated analysis of the aging brain transcriptome and proteome in tauopathy

Background

Tau neurofibrillary tangle pathology characterizes Alzheimer’s disease and other neurodegenerative tauopathies. Brain gene expression profiles can reveal mechanisms; however, few studies have systematically examined both the transcriptome and proteome or differentiated Tau- versus age-dependent changes.

Methods

Paired, longitudinal RNA-sequencing and mass-spectrometry were performed in a Drosophila model of tauopathy, based on pan-neuronal expression of human wildtype Tau (Tau^WT) or a mutant form causing frontotemporal dementia (Tau^R406W). Tau-induced, differentially expressed transcripts and proteins were examined cross-sectionally or using linear regression and adjusting for age. Hierarchical clustering was performed to highlight network perturbations, and we examined overlaps with human brain gene expression profiles in tauopathy.

Results

Tau^WT induced 1514 and 213 differentially expressed transcripts and proteins, respectively. Tau^R406W had a substantially greater impact, causing changes in 5494 transcripts and 697 proteins. There was a ~ 70% overlap between age- and Tau-induced changes and our analyses reveal pervasive bi-directional interactions. Strikingly, 42% of Tau-induced transcripts were discordant in the proteome, showing opposite direction of change. Tau-responsive gene expression networks strongly implicate innate immune activation. Cross-species analyses pinpoint human brain gene perturbations specifically triggered by Tau pathology and/or aging, and further differentiate between disease amplifying and protective changes.

Conclusions

Our results comprise a powerful, cross-species functional genomics resource for tauopathy, revealing Tau-mediated disruption of gene expression, including dynamic, age-dependent interactions between the brain transcriptome and proteome.

Transcriptomic analysis highlights cochlear inflammation associated with age-related hearing loss in C57BL/6 mice using next generation sequencing

Background

In our aging society, age-related hearing loss (AHL) is the most common sensory disorder in old people. Much progress has been made in understanding the pathological process of AHL over the past few decades. However, the mechanism of cochlear degeneration during aging is still not fully understood.

Methods

Next generation sequencing technique was used to sequence the whole transcriptome of the cochlea of C57BL/6 mice, a mouse model of AHL. Differentially expressed genes (DEGs) were identified using the Cuffdiff software. GO and KEGG pathway enrichment analyses of the DEGs were implemented by using the GOseq R package and KOBAS software, respectively.

Results

A total of 731 genes (379 up- and 352 down-regulated) were revealed to be differentially expressed in the cochlea of aged mice compared to the young. Many genes associated with aging, apoptosis, necroptosis and particularly, inflammation were identified as being significantly modulated in the aged cochlea. GO and KEGG analyses of the upregulated DEGs revealed that the most enriched terms were associated with immune responses and inflammatory pathways, whereas many of the downregulated genes are involved in ion channel function and neuronal signaling. Real-time qPCR showed that H₂O₂ treatment significantly induced the expression of multiple inflammation and necroptosis-related genes in HEI-OC1 cells.

Conclusion

Using next generation sequencing, our transcriptomic analysis revealed the differences of gene expression pattern with age in the cochlea of C57BL/6 mice. Our study also revealed multiple immune and inflammatory transcriptomic changes during cochlear aging and provides new insights into the molecular mechanisms underlying cochlear inflammation in AHL.

A practical application of generative adversarial networks for RNA-seq analysis to predict the molecular progress of Alzheimer's disease

Next-generation sequencing (NGS) technology has become a powerful tool for dissecting the molecular and pathological signatures of a variety of human diseases. However, the limited availability of biological samples from different disease stages is a major hurdle in studying disease progressions and identifying early pathological changes. Deep learning techniques have recently begun to be applied to analyze NGS data and thereby predict the progression of biological processes. In this study, we applied a deep learning technique called generative adversarial networks (GANs) to predict the molecular progress of Alzheimer's disease (AD). We successfully applied GANs to analyze RNA-seq data from a 5xFAD mouse model of AD, which recapitulates major AD features of massive amyloid-β (Aβ) accumulation in the brain. We examined how the generator is featured to have specific-sample generation and biological gene association. Based on the above observations, we suggested virtual disease progress by latent space interpolation to yield the transition curves of various genes with pathological changes from normal to AD state. By performing pathway analysis based on the transition curve patterns, we identified several pathological processes with progressive changes, such as inflammatory systems and synapse functions, which have previously been demonstrated to be involved in the pathogenesis of AD. Interestingly, our analysis indicates that alteration of cholesterol biosynthesis begins at a very early stage of AD, suggesting that it is the first effect to mediate the cholesterol metabolism of AD downstream of Aβ accumulation. Here, we suggest that GANs are a useful tool to study disease progression, leading to the identification of early pathological signatures.