Distribution of PCP4 protein in the forebrain of adult mice

Multi-omic analysis of Huntington's disease reveals a compensatory astrocyte state

The mechanisms underlying the selective regional vulnerability to neurodegeneration in Huntington's disease (HD) have not been fully defined. To explore the role of astrocytes in this phenomenon, we used single-nucleus and bulk RNAseq, lipidomics, HTT gene CAG repeat-length measurements, and multiplexed immunofluorescence on HD and control post-mortem brains. We identified genes that correlated with CAG repeat length, which were enriched in astrocyte genes, and lipidomic signatures that implicated poly-unsaturated fatty acids in sensitizing neurons to cell death. Because astrocytes play essential roles in lipid metabolism, we explored the heterogeneity of astrocytic states in both protoplasmic and fibrous-like (CD44+) astrocytes. Significantly, one protoplasmic astrocyte state showed high levels of metallothioneins and was correlated with the selective vulnerability of distinct striatal neuronal populations. When modeled in vitro, this state improved the viability of HD-patient-derived spiny projection neurons. Our findings uncover key roles of astrocytic states in protecting against neurodegeneration in HD.

Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics

Spatially resolved transcriptomics (SRT) has emerged as a powerful tool for investigating gene expression in spatial contexts, providing insights into the molecular mechanisms underlying organ development and disease pathology. However, the expression sparsity poses a computational challenge to integrate other modalities (e.g. histological images and spatial locations) that are simultaneously captured in SRT datasets for spatial clustering and variation analyses. In this study, to meet such a challenge, we propose multi-modal domain adaption for spatial transcriptomics (stMDA), a novel multi-modal unsupervised domain adaptation method, which integrates gene expression and other modalities to reveal the spatial functional landscape. Specifically, stMDA first learns the modality-specific representations from spatial multi-modal data using multiple neural network architectures and then aligns the spatial distributions across modal representations to integrate these multi-modal representations, thus facilitating the integration of global and spatially local information and improving the consistency of clustering assignments. Our results demonstrate that stMDA outperforms existing methods in identifying spatial domains across diverse platforms and species. Furthermore, stMDA excels in identifying spatially variable genes with high prognostic potential in cancer tissues. In conclusion, stMDA as a new tool of multi-modal data integration provides a powerful and flexible framework for analyzing SRT datasets, thereby advancing our understanding of intricate biological systems.

Immunohistochemical field parcellation of the human hippocampus along its antero-posterior axis

The primate hippocampus includes the dentate gyrus, cornu ammonis (CA), and subiculum. CA is subdivided into four fields (CA1-CA3, plus CA3h/hilus of the dentate gyrus) with specific pyramidal cell morphology and connections. Work in non-human mammals has shown that hippocampal connectivity is precisely patterned both in the laminar and longitudinal axes. One of the main handicaps in the study of neuropathological semiology in the human hippocampus is the lack of clear laminar and longitudinal borders. The aim of this study was to explore a histochemical segmentation of the adult human hippocampus, integrating field (medio-lateral), laminar, and anteroposterior longitudinal patterning. We provide criteria for head-body-tail field and subfield parcellation of the human hippocampus based on immunodetection of Rabphilin3a (Rph3a), Purkinje-cell protein 4 (PCP4), Chromogranin A and Regulation of G protein signaling-14 (RGS-14). Notably, Rph3a and PCP4 allow to identify the border between CA3 and CA2, while Chromogranin A and RGS-14 give specific staining of CA2. We also provide novel histological data about the composition of human-specific regions of the anterior and posterior hippocampus. The data are given with stereotaxic coordinates along the longitudinal axis. This study provides novel insights for a detailed region-specific parcellation of the human hippocampus useful for human brain imaging and neuropathology.

Integrating multi-modal information to detect spatial domains of spatial transcriptomics by graph attention network

Recent advances in spatially resolved transcriptomic technologies have enabled unprecedented opportunities to elucidate tissue architecture and function in situ. Spatial transcriptomics can provide multimodal and complementary information simultaneously, including gene expression profiles, spatial locations, and histology images. However, most existing methods have limitations in efficiently utilizing spatial information and matched high-resolution histology images. To fully leverage the multi-modal information, we propose a SPAtially embedded Deep Attentional graph Clustering (SpaDAC) method to identify spatial domains while reconstructing denoised gene expression profiles. This method can efficiently learn the low-dimensional embeddings for spatial transcriptomics data by constructing multi-view graph modules to capture both spatial location connectives and morphological connectives. Benchmark results demonstrate that SpaDAC outperforms other algorithms on several recent spatial transcriptomics datasets. SpaDAC is a valuable tool for spatial domain detection, facilitating the comprehension of tissue architecture and cellular microenvironment. The source code of SpaDAC is freely available at Github (https://github.com/huoyuying/SpaDAC.git).

Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification

Spatially resolved transcriptomics (SRT) enable the comprehensive characterization of transcriptomic profiles in the context of tissue microenvironments. Unveiling spatial transcriptional heterogeneity needs to effectively incorporate spatial information accounting for the substantial spatial correlation of expression measurements. Here, we develop a computational method, SpaSRL (spatially aware self-representation learning), which flexibly enhances and decodes spatial transcriptional signals to simultaneously achieve spatial domain detection and spatial functional genes identification. This novel tunable spatially aware strategy of SpaSRL not only balances spatial and transcriptional coherence for the two tasks, but also can transfer spatial correlation constraint between them based on a unified model. In addition, this joint analysis by SpaSRL deciphers accurate and fine-grained tissue structures and ensures the effective extraction of biologically informative genes underlying spatial architecture. We verified the superiority of SpaSRL on spatial domain detection, spatial functional genes identification and data denoising using multiple SRT datasets obtained by different platforms and tissue sections. Our results illustrate SpaSRL's utility in flexible integration of spatial information and novel discovery of biological insights from spatial transcriptomic datasets.

PCP4 Promotes Alzheimer's Disease Pathogenesis by Affecting Amyloid-β Protein Precursor Processing

BACKGROUND

Down syndrome (DS) is caused by an extra copy of all or part of chromosome 21. The patients with DS develop typical Alzheimer's disease (AD) neuropathology, indicating the role of genes on human chromosome 21 (HSA21) in the pathogenesis of AD. Purkinje cell protein 4 (PCP4), also known as brain-specific protein 19, is a critical gene located on HSA21. However, the role of PCP4 in DS and AD pathogenesis is not clear.

OBJECTIVE

To explore the role of PCP4 in amyloid-β protein precursor (AβPP) processing in AD.

METHODS

In this study, we investigated the role of PCP4 in AD progression in vitro and in vivo. In vitro experiments, we overexpressed PCP4 in human Swedish mutant AβPP stable expression or neural cell lines. In vitro experiments, APP23/PS45 double transgenic mice were selected and treated with AAV-PCP4. Multiple topics were detected by western blot, RT-PCR, immunohistochemical and behavioral test.

RESULTS

We found that PCP4 expression was altered in AD. PCP4 was overexpressed in APP23/PS45 transgenic mice and PCP4 affected the processing of AβPP. The production of amyloid-β protein (Aβ) was also promoted by PCP4. The upregulation of endogenous AβPP expression and the downregulation of ADAM10 were due to the transcriptional regulation of PCP4. In addition, PCP4 increased Aβ deposition and neural plaque formation in the brain, and exuberated learning and memory impairment in transgenic AD model mice.

CONCLUSION

Our finding reveals that PCP4 contributes to the pathogenesis of AD by affecting AβPP processing and suggests PCP4 as a novel therapeutic target for AD by targeting Aβ pathology.

Transcriptomes of Clusterin- and S100B-transfected neuronal cells elucidate protective mechanisms against hypoxia and oxidative stress in the hooded seal (Cystophora cristata) brain

BACKGROUND

The hooded seal (Cystophora cristata) exhibits impressive diving skills and can tolerate extended durations of asphyxia, hypoxia and oxidative stress, without suffering from irreversible neuronal damage. Thus, when exposed to hypoxia in vitro, neurons of fresh cortical and hippocampal tissue from hooded seals maintained their membrane potential 4-5 times longer than neurons of mice. We aimed to identify the molecular mechanisms underlying the intrinsic neuronal hypoxia tolerance. Previous comparative transcriptomics of the visual cortex have revealed that S100B and clusterin (apolipoprotein J), two stress proteins that are involved in neurological disorders characterized by hypoxic conditions, have a remarkably high expression in hooded seals compared to ferrets. When overexpressed in murine neuronal cells (HN33), S100B and clusterin had neuroprotective effects when cells were exposed to hypoxia. However, their specific roles in hypoxia have remained largely unknown.

METHODS

In order to shed light on potential molecular pathways or interaction partners, we exposed HN33 cells transfected with either S100B, soluble clusterin (sCLU) or nuclear clusterin (nCLU) to normoxia, hypoxia and oxidative stress for 24 h. We then determined cell viability and compared the transcriptomes of transfected cells to control cells. Potential pathways and upstream regulators were identified via Gene Ontology (GO) and Ingenuity Pathway Analysis (IPA).

RESULTS

HN33 cells transfected with sCLU and S100B demonstrated improved glycolytic capacity and reduced aerobic respiration at normoxic conditions. Additionally, sCLU appeared to enhance pathways for cellular homeostasis to counteract stress-induced aggregation of proteins. S100B-transfected cells sustained lowered energy-intensive synaptic signaling. In response to hypoxia, hypoxia-inducible factor (HIF) pathways were considerably elevated in nCLU- and sCLU-transfected cells. In a previous study, S100B and sCLU decreased the amount of reactive oxygen species and lipid peroxidation in HN33 cells in response to oxidative stress, but in the present study, these functional effects were not mirrored in gene expression changes.

CONCLUSIONS

sCLU and S100B overexpression increased neuronal survival by decreasing aerobic metabolism and synaptic signaling in advance to hypoxia and oxidative stress conditions, possibly to reduce energy expenditure and the build-up of deleterious reactive oxygen species (ROS). Thus, a high expression of CLU isoforms and S100B is likely beneficial during hypoxic conditions.

Assessing equivalent and inverse change in genes between diverse experiments

Background: It is important to identify when two exposures impact a molecular marker (e.g., a gene's expression) in similar ways, for example, to learn that a new drug has a similar effect to an existing drug. Currently, statistically robust approaches for making comparisons of equivalence of effect sizes obtained from two independently run treatment vs. control comparisons have not been developed. Results: Here, we propose two approaches for evaluating the question of equivalence between effect sizes of two independent studies: a bootstrap test of the Equivalent Change Index (ECI), which we previously developed, and performing Two One-Sided t-Tests (TOST) on the difference in log-fold changes directly. The ECI of a gene is computed by taking the ratio of the effect size estimates obtained from the two different studies, weighted by the maximum of the two p-values and giving it a sign indicating if the effects are in the same or opposite directions, whereas TOST is a test of whether the difference in log-fold changes lies outside a region of equivalence. We used a series of simulation studies to compare the two tests on the basis of sensitivity, specificity, balanced accuracy, and F1-score. We found that TOST is not efficient for identifying equivalently changed gene expression values (F1-score = 0) because it is too conservative, while the ECI bootstrap test shows good performance (F1-score = 0.95). Furthermore, applying the ECI bootstrap test and TOST to publicly available microarray expression data from pancreatic cancer showed that, while TOST was not able to identify any equivalently or inversely changed genes, the ECI bootstrap test identified genes associated with pancreatic cancer. Additionally, when investigating publicly available RNAseq data of smoking vs. vaping, no equivalently changed genes were identified by TOST, but ECI bootstrap test identified genes associated with smoking. Conclusion: A bootstrap test of the ECI is a promising new statistical approach for determining if two diverse studies show similarity in the differential expression of genes and can help to identify genes which are similarly influenced by a specific treatment or exposure. The R package for the ECI bootstrap test is available at https://github.com/Hecate08/ECIbootstrap.

Postnatal Developmental Expression Profile Classifies the Indusium Griseum as a Distinct Subfield of the Hippocampal Formation

The indusium griseum (IG) is a cortical structure overlying the corpus callosum along its anterior–posterior extent. It has been classified either as a vestige of the hippocampus or as an extension of the dentate gyrus via the fasciola cinerea, but its attribution to a specific hippocampal subregion is still under debate. To specify the identity of IG neurons more precisely, we investigated the spatiotemporal expression of calbindin, secretagogin, Necab2, PCP4, and Prox1 in the postnatal mouse IG, fasciola cinerea, and hippocampus. We identified the calcium-binding protein Necab2 as a first reliable marker for the IG and fasciola cinerea throughout postnatal development into adulthood. In contrast, calbindin, secretagogin, and PCP4 were expressed each with a different individual time course during maturation, and at no time point, IG or fasciola cinerea principal neurons expressed Prox1, a transcription factor known to define dentate granule cell fate. Concordantly, in a transgenic mouse line expressing enhanced green fluorescent protein (eGFP) in dentate granule cells, neurons of IG and fasciola cinerea were eGFP-negative. Our findings preclude that IG neurons represent dentate granule cells, as earlier hypothesized, and strongly support the view that the IG is an own hippocampal subfield composed of a distinct neuronal population.

GNG13 Is a Potential Marker of the State of Health of Alzheimer's Disease Patients' Cerebellum

Brain regions such as the cerebellum (CB) have been neglected for a long time in the study of Alzheimer's disease (AD) pathogenesis. In reference to a new emerging hypothesis according to which there is an altered cerebellar synaptic processing in AD, we verified the possible role played by new biomarkers in the CB of AD patients compared with not-demented healthy control subjects (NDHS). Using a bioinformatics approach, we have collected several microarray datasets and obtained 626 cerebella sample biopsies belonging to subjects who did not die from causes related to neurological diseases and 199 cerebella belonging to AD. The analysis of logical relations between the transcriptome dataset highlighted guanine nucleotide-binding protein (G protein) gamma 13 (GNG13) as a potential new biomarker for Purkinje cells (PCs). We have correlated GNG13 expression levels with already widely existing bibliography of PC marker genes, such as Purkinje cell protein 2 (PCP2), Purkinje cell protein 4 (PCP4), and cerebellin 3 (CBLN3). We showed that expression levels of GNG13 and PCP2, PCP4, and CBLN3 were significantly correlated with each other in NDHS and in AD and significantly reduced in AD patients compared with NDHS subjects. In addition, we highlighted a negative correlation between the expression levels of PC biomarkers and age. From the outcome of our investigation, it is possible to conclude that the identification of GNG13 as a potentially biomarker in PCs represents also a state of health of CB, in association with the expression of PCP2, PCP4, and CBLN3.

Inferring spatial and signaling relationships between cells from single cell transcriptomic data

Single-cell RNA sequencing (scRNA-seq) provides details for individual cells; however, crucial spatial information is often lost. We present SpaOTsc, a method relying on structured optimal transport to recover spatial properties of scRNA-seq data by utilizing spatial measurements of a relatively small number of genes. A spatial metric for individual cells in scRNA-seq data is first established based on a map connecting it with the spatial measurements. The cell-cell communications are then obtained by "optimally transporting" signal senders to target signal receivers in space. Using partial information decomposition, we next compute the intercellular gene-gene information flow to estimate the spatial regulations between genes across cells. Four datasets are employed for cross-validation of spatial gene expression prediction and comparison to known cell-cell communications. SpaOTsc has broader applications, both in integrating non-spatial single-cell measurements with spatial data, and directly in spatial single-cell transcriptomics data to reconstruct spatial cellular dynamics in tissues.

Loss of Dmrt5 Affects the Formation of the Subplate and Early Corticogenesis

Dmrt5 (Dmrta2) and Dmrt3 are key regulators of cortical patterning and progenitor proliferation and differentiation. In this study, we show an altered apical to intermediate progenitor transition, with a delay in SP neurogenesis and premature birth of Ctip2⁺ cortical neurons in Dmrt5^−/− mice. In addition to the cortical progenitors, DMRT5 protein appears present in postmitotic subplate (SP) and marginal zone neurons together with some migrating cortical neurons. We observed the altered split of preplate and the reduced SP and disturbed radial migration of cortical neurons into cortical plate in Dmrt5^−/− brains and demonstrated an increase in the proportion of multipolar cells in primary neuronal cultures from Dmrt5^−/− embryonic brains. Dmrt5 affects cortical development with specific time sensitivity that we described in two conditional mice with slightly different deletion time. We only observed a transient SP phenotype at E15.5, but not by E18.5 after early (Dmrt5^lox/lox;Emx1^Cre), but not late (Dmrt5^lox/lox;Nestin^Cre) deletion of Dmrt5. SP was less disturbed in Dmrt5^lox/lox;Emx1^Cre and Dmrt3^−/− brains than in Dmrt5^−/− and affects dorsomedial cortex more than lateral and caudal cortex. Our study demonstrates a novel function of Dmrt5 in the regulation of early SP formation and radial cortical neuron migration.

Summary Statement

Our study demonstrates a novel function of Dmrt5 in regulating marginal zone and subplate formation and migration of cortical neurons to cortical plate.

Genetic and epigenetic pathways in Down syndrome: Insights to the brain and immune system from humans and mouse models

The presence of an extra copy of human chromosome 21 (Hsa21) leads to a constellation of phenotypic manifestations in Down syndrome (DS), including prominent effects on the brain and immune system. Intensive efforts to unravel the molecular mechanisms underlying these phenotypes may help developing effective therapies, both in DS and in the general population. Here we review recent progress in genetic and epigenetic analysis of trisomy 21 (Ts21). New mouse models of DS based on syntenic conservation of segments of the mouse and human chromosomes are starting to clarify the contributions of chromosomal subregions and orthologous genes to specific phenotypes in DS. The expression of genes on Hsa21 is regulated by epigenetic mechanisms, and with recent findings of highly recurrent gene-specific changes in DNA methylation patterns in brain and immune system cells with Ts21, the epigenomics of DS has become an active research area. Here we highlight the value of combining human studies with mouse models for defining DS critical genes and understanding the trans-acting effects of a simple chromosomal aneuploidy on genome-wide epigenetic patterning. These genetic and epigenetic studies are starting to uncover fundamental biological mechanisms, leading to insights that may soon become therapeutically relevant.

Genetic dissection of the Down syndrome critical region

Down syndrome (DS), caused by trisomy 21, is the most common chromosomal disorder associated with developmental cognitive deficits. Despite intensive efforts, the genetic mechanisms underlying developmental cognitive deficits remain poorly understood, and no treatment has been proven effective. The previous mouse-based experiments suggest that the so-called Down syndrome critical region of human chromosome 21 is an important region for this phenotype, which is demarcated by Setd4/Cbr1 and Fam3b/Mx2. We first confirmed the importance of the Cbr1-Fam3b region using compound mutant mice, which carry a duplication spanning the entire human chromosome 21 orthologous region on mouse chromosome 16 [Dp(16)1Yey] and Ms1Rhr. By dividing the Setd4-Mx2 region into complementary Setd4-Kcnj6 and Kcnj15-Mx2 intervals, we started an unbiased dissection through generating and analyzing Dp(16)1Yey/Df(16Setd4-Kcnj6)Yey and Dp(16)1Yey/Df(16Kcnj15-Mx2)Yey mice. Surprisingly, the Dp(16)1Yey-associated cognitive phenotypes were not rescued by either deletion in the compound mutants, suggesting the possible presence of at least one causative gene in each of the two regions. The partial rescue by a Dyrk1a mutation in a compound mutant carrying Dp(16)1Yey and the Dyrk1a mutation confirmed the causative role of Dyrk1a, whereas the absence of a similar rescue by Df(16Dyrk1a-Kcnj6)Yey in Dp(16)1Yey/Df(16Dyrk1a-Kcnj6)Yey mice demonstrated the importance of Kcnj6. Our results revealed the high levels of complexities of gene actions and interactions associated with the Setd4/Cbr1-Fam3b/Mx2 region as well as their relationship with developmental cognitive deficits in DS.