Voxelation and gene expression tomography for the acquisition of 3-D gene expression maps in the brain

Effect of Enterococcus faecalis 2001 on colitis and depressive-like behavior in dextran sulfate sodium-treated mice: involvement of the brain-gut axis

BACKGROUND

Patients with inflammatory bowel disease (IBD), including those with ulcerative colitis and Crohn's disease, have higher rates of psychiatric disorders, such as depression and anxiety; however, the mechanism of psychiatric disorder development remains unclear. Mice with IBD induced by dextran sulfate sodium (DSS) in drinking water exhibit depressive-like behavior. The presence of Lactobacillus in the gut microbiota is associated with major depressive disorder. Therefore, we examined whether Enterococcus faecalis 2001 (EF-2001), a biogenic lactic acid bacterium, prevents DSS-induced depressive-like behavior and changes in peripheral symptoms.

METHODS

We evaluated colon inflammation and used the tail suspension test to examine whether EF-2001 prevents IBD-like symptoms and depressive-like behavior in DSS-treated mice. The protein expression of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), X-linked inhibitor of apoptosis protein (XIAP), and cleaved caspase-3 in the rectum and hippocampus was assessed by western blotting. Hippocampal neurogenesis, altered nuclear factor-kappa B (NFκB) p65 morphometry, and the localization of activated NFκB p65 and XIAP were examined by immunohistochemistry.

RESULTS

Treatment with 1.5% DSS for 7 days induced IBD-like pathology and depressive-like behavior, increased TNF-α and IL-6 expression in the rectum and hippocampus, activated caspase-3 in the hippocampus, and decreased hippocampal neurogenesis. Interestingly, these changes were reversed by 20-day administration of EF-2001. Further, EF-2001 administration enhanced NFκB p65 expression in the microglial cells and XIAP expression in the hippocampus of DSS-treated mice.

CONCLUSION

EF-2001 prevented IBD-like pathology and depressive-like behavior via decreased rectal and hippocampal inflammatory cytokines and facilitated the NFκB p65/XIAP pathway in the hippocampus. Our findings suggest a close relationship between IBD and depression.

Mechanisms underpinning AMP-activated protein kinase-related effects on behavior and hippocampal neurogenesis in an animal model of depression

Adenosine monophosphate-activated protein kinase (AMPK) is critical for whole-body energy metabolism regulation. Recent studies have suggested that physical exercise ameliorates depressive-like behaviors via AMPK activation; however, the underlying mechanism is unclear. Here, we examined the effects and underlying mechanisms of AMPK activation on depressive-like behavior in olfactory bulbectomized (OBX) mice. We treated OBX mice with the AMPK activator, 5-aminoimidazole-4-carboxamide-1-β-d-ribonucleotide (AICAR) on the 7th or 14th day after bilateral bulbectomy and evaluated depressive-like behavior using the tail-suspension test (TST) and forced swimming test (FST) on the 21st day. The expression of phosphorylated AMPK, protein kinase C ζ (PKCζ), nuclear factor-kappa B (NF-κB), brain-derived neurotrophic factor (BDNF), and cAMP response element-binding protein (CREB) in the hippocampus was assessed by western blotting. Hippocampal neurogenesis and localization of AMPK and phosphorylated NF-κB were examined by immunohistochemistry. Chronic AICAR treatment suppressed the prolonged immobility of OBX mice in the TST and FST, and increased the levels of phosphorylated AMPK, PKCζ, NF-κB, CREB, and BDNF. Hippocampal neurogenesis in OBX mice was promoted by chronic AICAR treatment. Co-administration of AICAR with the PKCζ inhibitor or the neurotrophic tyrosine kinase receptor type 2 (TrkB) antagonist, ANA-12, inhibited these effects. Phosphorylated AMPK was detected in mature and immature hippocampal neurons and microglia, while phosphorylated NF-κB was detected only in neurons in AICAR-treated OBX mice. These data indicate that AMPK activation produces anti-depressant effects, which are mediated by elevated hippocampal neurogenesis potentially via PKCζ/NF-κB/BDNF/TrkB/CREB signaling in neurons.

Learning pair-wise gene functional similarity by multiplex gene expression maps

Background

The relationships between the gene functional similarity and gene expression profile, and between gene function annotation and gene sequence have been studied extensively. However, not much work has considered the connection between gene functions and location of a gene's expression in the mammalian tissues. On the other hand, although unsupervised learning methods have been commonly used in functional genomics, supervised learning cannot be directly applied to a set of normal genes without having a target (class) attribute.

Results

Here, we propose a supervised learning methodology to predict pair-wise gene functional similarity from multiplex gene expression maps that provide information about the location of gene expression. The features are extracted from expression maps and the labels denote the functional similarities of pairs of genes. We make use of wavelet features, original expression values, difference and average values of neighboring voxels and other features to perform boosting analysis. The experimental results show that with increasing similarities of gene expression maps, the functional similarities are increased too. The model predicts the functional similarities between genes to a certain degree. The weights of the features in the model indicate the features that are more significant for this prediction.

Conclusions

By considering pairs of genes, we propose a supervised learning methodology to predict pair-wise gene functional similarity from multiplex gene expression maps. We also explore the relationship between similarities of gene maps and gene functions. By using AdaBoost coupled with our proposed weak classifier we analyze a large-scale gene expression dataset and predict gene functional similarities. We also detect the most significant single voxels and pairs of neighboring voxels and visualize them in the expression map image of a mouse brain. This work is very important for predicting functions of unknown genes. It also has broader applicability since the methodology can be applied to analyze any large-scale dataset without a target attribute and is not restricted to gene expressions.

Development of a New Tool for 3D Modeling for Regenerative Medicine

The effectiveness of therapeutic treatment based on regenerative medicine for degenerative diseases (i.e., neurodegenerative or cardiac diseases) requires tools allowing the visualization and analysis of the three-dimensional (3D) distribution of target drugs within the tissue. Here, we present a new computational procedure able to overcome the limitations of visual analysis emerging by the examination of a molecular signal within images of serial tissue/organ sections by using the conventional techniques. Together with the 3D anatomical reconstitution of the tissue/organ, our framework allows the detection of signals of different origins (e.g., marked generic molecules, colorimetric, or fluorimetric substrates for enzymes; microRNA; recombinant protein). Remarkably, the application does not require the employment of specific tracking reagents for the imaging analysis. We report two different representative applications: the first shows the reconstruction of a 3D model of mouse brain with the analysis of the distribution of theβ-Galactosidase, the second shows the reconstruction of a 3D mouse heart with the measurement of the cardiac volume.

Mapping protein abundance patterns in the brain using voxelation combined with liquid chromatography and mass spectrometry

Voxelation creates expression atlases by high-throughput analysis of spatially registered cubes or voxels harvested from the brain. The modality independence of voxelation allows a variety of bioanalytical techniques to be used to map abundance. Protein expression patterns in the brain can be obtained using liquid chromatography (LC) combined with mass spectrometry (MS). Here we describe the methodology of voxelation as it pertains particularly to LC-MS proteomic analysis: sample preparation, instrumental set up and analysis, peptide identification and protein relative abundance quantitation. We also briefly describe some of the advantages, limitations and insights into the brain that can be obtained using combined proteomic and transcriptomic maps.

Analysis of multiplex gene expression maps obtained by voxelation

BACKGROUND

Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions.

RESULTS

To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in cortex and corpus callosum.

CONCLUSION

The experimental results confirm the hypothesis that genes with similar gene expression maps might have similar gene functions. The voxelation data takes into account the location information of gene expression level in mouse brain, which is novel in related research. The proposed approach can potentially be used to predict gene functions and provide helpful suggestions to biologists.

Spatial mapping of protein abundances in the mouse brain by voxelation integrated with high-throughput liquid chromatography-mass spectrometry

Temporally and spatially resolved mapping of protein abundance patterns within the mammalian brain is of significant interest for understanding brain function and molecular etiologies of neurodegenerative diseases; however, such imaging efforts have been greatly challenged by complexity of the proteome, throughput and sensitivity of applied analytical methodologies, and accurate quantitation of protein abundances across the brain. Here, we describe a methodology for comprehensive spatial proteome mapping that addresses these challenges by employing voxelation integrated with automated microscale sample processing, high-throughput liquid chromatography (LC) system coupled with high-resolution Fourier transform ion cyclotron resonance (FTICR) mass spectrometer, and a "universal" stable isotope labeled reference sample approach for robust quantitation. We applied this methodology as a proof-of-concept trial for the analysis of protein distribution within a single coronal slice of a C57BL/6J mouse brain. For relative quantitation of the protein abundances across the slice, an 18O-isotopically labeled reference sample, derived from a whole control coronal slice from another mouse, was spiked into each voxel sample, and stable isotopic intensity ratios were used to obtain measures of relative protein abundances. In total, we generated maps of protein abundance patterns for 1028 proteins. The significant agreement of the protein distributions with previously reported data supports the validity of this methodology, which opens new opportunities for studying the spatial brain proteome and its dynamics during the course of disease progression and other important biological and associated health aspects in a discovery-driven fashion.

Investigation of different transcript quantitation tools for high-throughput mapping of brain gene expression using voxelation

Voxelation is a new approach for genome scale acquisition of brain gene expression patterns. The method employs high-throughput analysis of spatially registered voxels (cubes) to create multiple volumetric images of brain gene expression, similar to those obtained from biomedical imaging systems. The spatial resolution of voxelation depends on voxel size, with smaller voxels giving higher resolution. An important question is the applicability of different transcript profiling tools for the various levels of resolution that can be employed. Here, we describe the use of three methods to analyze voxel transcript abundance: real-time PCR, microarray analysis and linear amplification coupled with microarrays. We show statistically significant concordance between real-time PCR and microarray analysis for the myelin basic protein gene in human brain specimens at differing levels of spatial resolution. In addition, we also demonstrate the feasibility of using linear amplification coupled with microarray analysis to create voxelation maps from the mouse brain at high resolution, 1 microl. These data indicate the suitability of a number of transcript profiling tools for various levels of spatial resolution in voxelation.

Anatomical methods for voxelation of the mammalian brain

Voxelation allows high-throughput acquisition of three-dimensional gene expression patterns in the brain through analysis of spatially registered voxels (cubes). The method results in multiple volumetric maps of gene expression analogous to the images reconstructed in biomedical imaging techniques. An important issue for voxelation is the development of approaches to anchor correctly harvested voxels to the underlying anatomy. Here, we describe experiments to identify fixation and cryopreservation protocols for improved registration of harvested voxels with neuroanatomical structures. Paraformaldehyde fixation greatly reduced RNA recovery as judged by ribosomal RNA abundance. However, gene expression signals from paraformaldehyde-fixed samples were not appreciably diminished as judged by average signal-noise ratios from microarrays, highlighting the difficulties of accurate quantitation of cross-linked RNA. Additional use of cryoprotection helped to improve further RNA recovery and signal from fixed tissue. It appears that the best protocol to provide the necessary resolution of neuroanatomical information in voxelation entails a controlled dose of fixation and thorough cryoprotection, complemented by histological staining.