Spatial Transcriptomics Reveals Genes Associated with Dysregulated Mitochondrial Functions and Stress Signaling in Alzheimer Disease.
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ABSTRACT:
SUBMITTER: Navarro JF
PROVIDER: S-EPMC7522123 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundChronic obstructive pulmonary disease (COPD) is a progressive lung disease with poor treatment options. However, most mouse models of COPD produce a primarily emphysematous disease not recapitulating clinically meaningful COPD features like chronic bronchitis.MethodsWild-type ferrets (Mustela putorius furo) were divided randomly into two groups: whole body cigarette smoke exposure and air controls. Ferrets were exposed to smoke from 1R6F research cigarettes, twice daily for six months. RNA-sequencing was performed on RNA isolated from lung tissue. Comparative transcriptomics analyses of COPD in ferrets, mice, and humans were done to find the uniquely expressed genes. Further, Real-time PCR was performed to confirmed RNA-Seq data on multiple selected genes.ResultsRNA-sequence analysis identified 420 differentially expressed genes (DEGs) that were associated with the development of COPD in ferrets. By comparative analysis, we identified 25 DEGs that are uniquely expressed in ferrets and humans, but not mice. Among DEGs, a number were related to mucociliary clearance (NEK-6, HAS1, and KL), while others have been correlated with abnormal lung function (IL-18), inflammation (TREM1, CTSB), or oxidative stress (SRX1, AHRR). Multiple cellular pathways were aberrantly altered in the COPD ferret model, including pathways associated with COPD pathogenesis in humans. Validation of these selected unique DEGs using real-time PCR demonstrated > absolute 2-fold changes in mRNA versus air controls, consistent with RNA-seq analysis.ConclusionCigarette smoke-induced COPD in ferrets modulates gene expression consistent with human COPD and suggests that the ferret model may be uniquely well suited for the study of aspects of the disease.
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Project description:Postpartum depression (PPD) is a leading cause of morbidity and mortality among women. Clinically, the administration and withdrawal of supraphysiologic estradiol and progesterone (E2 + P) can cause affective symptom reoccurrence in women with a history of PPD, but not matched controls. To investigate the cellular basis underlying this differential affective response, lymphoblastoid cell lines (LCLs) were derived from women with and without past PPD and compared transcriptomically in hormone conditions mimicking pregnancy and parturition: supraphysiologic E2 + P-addback; supraphysiologic E2 + P-withdrawal; and no added E2 + P (Baseline). RNA-sequencing identified unique differentially expressed genes (DEGs) in all hormone conditions, but the majority tended to be downregulated in PPD and observed in E2 + P-addback. Two of these DEGs were evolutionarily conserved cellular stress regulators: IMPACT, an integrative response protein maintaining translational homeostasis, and WWTR1, a transcriptional coactivator in the 'Hippo' pathway mediating cell proliferation and survival. Correspondingly, significant gene network modules were linked to cell cycle progression, estrogen response, and immune dysregulation, suggesting innate differences in intracellular signaling in PPD. In certain hormone conditions, PPD LCLs displayed increased GATA3 expression (an upstream regulator of IMPACT and WWTR1) and differentially phosphorylated eiF2α (the ultimate downstream target of IMPACT). Taken together, these transcriptomic data primarily implicate innately dysregulated cellular responses as potentially influencing mood and/or escalating PPD risk. Furthermore, the intrinsic downregulation of IMPACT's translation and WWTR1's transcription networks may suggest a novel link between PPD and a compromised ability to maintain homeostasis in the context of cellular stress occurring during pregnancy and parturition.
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Project description:Abnormalities of the arterial valves, including bicuspid aortic valve (BAV) are amongst the most common congenital defects and are a significant cause of morbidity as well as predisposition to disease in later life. Despite this, and compounded by their small size and relative inaccessibility, there is still much to understand about how the arterial valves form and remodel during embryogenesis, both at the morphological and genetic level. Here we set out to address this in human embryos, using Spatial Transcriptomics (ST). We show that ST can be used to investigate the transcriptome of the developing arterial valves, circumventing the problems of accurately dissecting out these tiny structures from the developing embryo. We show that the transcriptome of CS16 and CS19 arterial valves overlap considerably, despite being several days apart in terms of human gestation, and that expression data confirm that the great majority of the most differentially expressed genes are valve-specific. Moreover, we show that the transcriptome of the human arterial valves overlaps with that of mouse atrioventricular valves from a range of gestations, validating our dataset but also highlighting novel genes, including four that are not found in the mouse genome and have not previously been linked to valve development. Importantly, our data suggests that valve transcriptomes are under-represented when using commonly used databases to filter for genes important in cardiac development; this means that causative variants in valve-related genes may be excluded during filtering for genomic data analyses for, for example, BAV. Finally, we highlight "novel" pathways that likely play important roles in arterial valve development, showing that mouse knockouts of RBP1 have arterial valve defects. Thus, this study has confirmed the utility of ST for studies of the developing heart valves and broadens our knowledge of the genes and signalling pathways important in human valve development.
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Project description:BackgroundSpatial transcriptomics (STs) simultaneously obtains the location and amount of gene expression within a tissue section. However, current methods like FindMarkers calculated the differentially expressed genes (DEGs) based on the classical statistics, which should abolish the spatial information.Materials and methodsA new method named spatial analysis of spatial transcriptomics (saSpatial) was developed for both the location and the amount of gene expression. Then saSpatial was applied to detect DEGs in both inter- and intra-cross sections. DEGs detected by saSpatial were compared with those detected by FindMarkers.ResultsSpatial analysis of spatial transcriptomics was founded on the basis of spatial statistics. It was able to detect DEGs in different regions in the normal brain section. As for the brain with ischemic stroke, saSpatial revealed the DEGs for the ischemic core and penumbra. In addition, saSpatial characterized the genetic heterogeneity in the normal and ischemic cortex. Compared to FindMarkers, a larger number of valuable DEGs were found by saSpatial.ConclusionSpatial analysis of spatial transcriptomics was able to effectively detect DEGs in STs data. It was a simple and valuable tool that could help potential researchers to find more valuable genes in the future research.
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Project description:Oxidative and nitrosative stress are widely recognized as critical factors in the pathogenesis and progression of Alzheimer disease (AD) and its earlier stage, amnestic mild cognitive impairment (MCI). A major source of free radicals that lead to oxidative and nitrosative damage is mitochondria. This review paper discusses oxidative and nitrosative stress and markers thereof in the brain, along with redox proteomics, which are techniques that have been pioneered in the Butterfield laboratory. Selected biological alterations in-and oxidative and nitrosative modifications of-mitochondria in AD and MCI and systems of relevance thereof also are presented. The review article concludes with a section on the implications of mitochondrial oxidative and nitrosative stress in MCI and AD with respect to imaging studies in and targeted therapies toward these disorders. Taken together, this review provides support for the notion that brain mitochondrial alterations in AD and MCI are key components of oxidative and nitrosative stress observed in these two disorders, and as such, they provide potentially promising therapeutic targets to slow-and hopefully one day stop-the progression of AD, which is a devastating dementing disorder.
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Project description:In high-throughput spatial transcriptomics (ST) studies, it is of great interest to identify the genes whose level of expression in a tissue covaries with the spatial location of cells/spots. Such genes, also known as spatially variable genes (SVGs), can be crucial to the biological understanding of both structural and functional characteristics of complex tissues. Existing methods for detecting SVGs either suffer from huge computational demand or significantly lack statistical power. We propose a non-parametric method termed SMASH that achieves a balance between the above two problems. We compare SMASH with other existing methods in varying simulation scenarios demonstrating its superior statistical power and robustness. We apply the method to four ST datasets from different platforms revealing interesting biological insights.
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