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Sequential extracellular matrix-focused and baited-global cluster analysis of serial transcriptomic profiles identifies candidate modulators of renal tubulointerstitial fibrosis in murine adriamycin-induced nephropathy.

Transcriptome analysis using microarray technology represents a powerful unbiased approach for delineating pathogenic mechanisms in disease. Here molecular mechanisms of renal tubulointerstitial fibrosis (TIF) were probed by monitoring changes in the renal transcriptome in a glomerular disease-dependent model of TIF (adriamycin nephropathy) using Affymetrix (mu74av2) microarray coupled with sequential primary biological function-focused and secondary "baited"-global cluster analysis of gene expression profiles. Primary cluster analysis focused on mRNAs encoding matrix proteins and modulators of matrix turnover as classified by Onto-Compare and Gene Ontology and identified both molecules and pathways already implicated in the pathogenesis of TIF (e.g. transforming growth factor beta1-CTGF-fibronectin-1 pathway) and novel TIF-associated genes (e.g. SPARC and Matrilin-2). Specific gene expression patterns identified by primary extracellular matrix-focused cluster analysis were then used as bioinformatic bait in secondary global clustering, with which to search the renal transcriptome for novel modulators of TIF. Among the genes clustering with ECM proteins in the latter analysis were endoglin, clusterin, and gelsolin. In several notable cases (e.g. claudin-1 and meprin-1beta) the pattern of gene expression identified in adriamycin nephropathy in vivo was replicated during transdifferentiation of renal tubule epithelial cells to a fibroblast-like phenotype in vitro on exposure to transforming growth factor-beta and epidermal growth factor suggesting a role in fibrogenesis. The further exploration of these complex gene networks should shed light on the core molecular pathways that underpin TIF in renal disease.

Animals↗

Global gene expression in Escherichia coli K-12 during short-term and long-term adaptation to glucose-limited continuous culture conditions.

Microarray technology was used to study the cellular events that take place at the transcription level during short-term (physiological) and long-term (genetic) adaptation of the faecal indicator bacterium Escherichia coli K-12 to slow growth under limited nutrient supply. Short-term and long-term adaptation were assessed by comparing the mRNA levels isolated after 40 or 500 h of glucose-limited continuous culture at a dilution rate of 0.3 h(-1) with those from batch culture with glucose excess. A large number of genes encoding periplasmic binding proteins were upregulated, indicating that the cells are prepared for high-affinity uptake of all types of carbon sources during glucose-limited growth in continuous culture. All the genes belonging to the maltose (mal/lamB) and galactose (mgl/gal) operons were upregulated. A similar transcription pattern was observed for long-term cultures except that the expression factors were lower than in the short-term adaptation. The patterns of upregulation were confirmed by real-time RT-PCR. A switch from a fully operational citric acid cycle to the PEP-glyoxylate cycle was clearly observed in cells grown in glucose-limited continuous culture when compared to batch-grown cells and this was confirmed by transcriptome analysis. This transcriptome analysis confirms and extends the observations from previous proteome and catabolome studies in the authors' laboratory.

Adaptation, Physiological↗

Comparative analysis of histological and transcriptomic characteristics in caudal muscles of nile crocodiles (Crocodylus niloticus), siamese crocodiles (Crocodylus siamensis), and their hybrids.

Crocodylus niloticus and Crocodylus siamensis are high-value aquaculture species. C. niloticus is large-bodied but less abundant, while C. siamensis grows fast but is small-sized. Their hybrids combine parental advantages, yet relevant research is scarce. This study compared the histological and transcriptomic characteristics of the caudal muscle across the three taxa. HE staining indicated that C. niloticus had significantly larger myofiber diameters (p&#xa0;<&#xa0;0.05); C. siamensis had the smallest, and the myofiber density of hybrids was much closer to that of C. siamensis. Masson's trichrome staining indicated that C. niloticus had the thickest collagen fibers (p&#xa0;<&#xa0;0.05), C. siamensis the thinnest, and hybrids exhibited highly similar histological traits to C. siamensis. C. niloticus had higher LDH and SDH activities in caudal muscles, whereas the hybrid crocodile indicated the highest CK activity. Transcriptomic analysis identified numerous differentially expressed genes (DEGs), which were enriched in growth, muscle metabolism, and energy allocation pathways via GO/KEGG annotations. PPI analysis screened 24 hub genes related to energy metabolism. This study systematically reveals caudal muscle differences, providing insights into growth-related molecular mechanisms and theoretical support for crocodile artificial breeding.

Animals↗

Comprehensive Profiling of Claudin 18.2 Immunohistochemical Expression in 564 Surgically Resected Gastric and Gastroesophageal Junction Adenocarcinomas.

Claudin 18 isoform 2 (CLDN18.2) is a novel therapeutic target for advanced, HER2-negative gastric/gastroesophageal junction (GEJ) adenocarcinoma positive for CLDN18.2 immunohistochemical (IHC) expression, defined as &#x2265;75% tumor cells with moderate-to-strong membranous staining. Clinical studies for emerging CLDN18.2-targeted therapeutics have used less stringent enrollment criteria to test the efficacy of such therapies in patients with moderate-to-low CLDN18.2 IHC expression. Anticipating the advent of such treatments, this study aimed to provide a comprehensive survey of CLDN18.2 expression using a clinical trial-validated CLDN18.2 monoclonal antibody in surgically resected gastric/GEJ adenocarcinomas and characterize CLDN18.2-positive carcinomas using both high- and low-expression thresholds. Crisp membranous CLDN18.2 staining was detected in 59% (335/564) carcinomas, including 57% (164/286) of gastric and 62% (171/278) of GEJ adenocarcinomas. Most gastric (147/164, 90%) and GEJ (166/171, 97%) adenocarcinomas with staining demonstrated moderate or strong staining intensity. Using the high-expression threshold (&#x2265;75% tumor cells with moderate-to-strong staining), positive CLDN18.2 expression was observed in 20% (57/286) of gastric and 27% (75/278) of GEJ adenocarcinomas and was associated with Epstein-Barr virus status (P < .001) and stage I gastric adenocarcinomas (P = .02) but stage IV GEJ adenocarcinomas (P = .03). Using a low-expression threshold (&#x2265;10% tumor cells with membranous staining), positive CLDN18.2 remained significantly associated with stage I (P = .004) and showed an unadjusted association with improved disease-specific survival in gastric adenocarcinomas (P = .045), which was not retained in multivariable analysis. Whole transcriptomic analysis showed concordance between IHC and CLDN18 messenger RNA expression. Transcriptomic alterations in CLDN18.2 IHC-positive gastric adenocarcinomas included pathways in drug resistance and tumor invasion. In summary, our study presents a detailed characterization of the prevalence and distribution of CLDN18.2 IHC expression patterns. Our results showed that 59% surgically resected gastric/GEJ adenocarcinomas exhibited CLDN18.2 staining. CLDN18.2 IHC positivity defined by both high- and low-expression thresholds may be associated with early-stage gastric adenocarcinoma. These findings expand our recognition of patients who may benefit from CLDN18.2-targeted therapy.

CLDN18.2↗

Transcriptome-Proteome Analysis of Human Naive and Memory B Cell Subsets Reveals Isotype and Subclass-Specific Phenotypes.

Antibodies produced by B cells aid in the recognition and clearance of pathogens and are the cornerstone of vaccination strategies. Humans produce nine different antibody isotypes, and their effector functions differ according to the type of antigen and route of exposure. Phenotypic variation between isotype-switched B cell subsets is expected but not studied in detail. To obtain a molecular definition of isotype-defined cell identity, we performed proteomics and transcriptomics on isotype-defined populations of human naive and memory B cells (MBCs): CD27-IgM+IgD+, CD27+CD38lo/-IgM+IgD+, CD27+CD38lo/-IgM+IgD-, and IgA1, IgA2, IgG1, IgG2, IgG3, and IgG4 MBCs (CD27+CD38lo/-Ig+). Combined proteome and transcriptome analysis revealed that mRNA and protein expression profiles separate isotype-defined B cell subsets according to their differentiation status. mRNA and protein expression levels correlated reasonably well for many genes. IgG4-switched B cells were most distinct from naive B cells in terms of mRNA as well as protein expression profiles. Besides a distinct expression profile of cytokine and Fc receptors, we identified a high expression of IgE-coding mRNA in IgG4-switched B cells. SDR16C5 was identified as uniquely upregulated in IgG4-switched B cells. Taken together, this study highlights the distinct phenotypic profile of IgG4-switched B cells.

Humans↗

Proteome and transcriptome based analysis of Bacillus subtilis cells overproducing an insoluble heterologous protein.

Bacillus subtilis and related Bacillus species are frequently used as hosts for the industrial production of recombinant proteins. In this study the cellular response of B. subtilis to the overproduction of an insoluble heterologous protein was investigated. For this purpose PorA, an outer membrane protein from Neisseria meningitidis, which accumulates after overexpression in the cytoplasm of B. subtilis mainly in the form of inclusion bodies, was used. The molecular response to overexpression of porA has been analysed at the transcriptional level using the DNA macro array technique and at the translational level by two-dimensional polyacrylamide gel electrophoresis. It was found that the expression of the heat shock genes of class I (dnaK, groEL and grpE) and class III (clpP and clpC) are increased under overproducing conditions. Furthermore, the protein levels of the two ribosomal proteins RpsB and RplJ are increased in the PorA overproducing cells. The transcriptome analysis indicated that mRNA levels of genes encoding pyrimidine and purine synthesis enzymes but also from ribosomal protein genes have elevated levels under overproducing conditions. Finally, the association of the protease ClpP and its ATPase subunits ClpC and ClpX with the PorA inclusion bodies was demonstrated by means of the immunogold labelling technique.

Adenosine Triphosphatases↗

Mycosis Fungoides-Like Atopic Dermatitis Represents a Th22-Dominant Inflammatory Endotype.

BACKGROUND: Early-stage mycosis fungoides (MF) often presents diagnostic challenges because of its clinical overlap with atopic dermatitis (AD). In clinical practice, we encountered a subset of patients with severe AD who fulfilled the MF diagnostic criteria yet remained clinically indistinguishable from AD and presented refractoriness to advanced therapies. We termed this ambiguous entity "mycosis fungoides-like AD" (mfAD) and sought to determine whether it represents malignant transformation or a distinct inflammatory endotype of AD. METHODS: Skin biopsies were obtained from 7 patients with AD and 11 patients with mfAD. We performed paired single-cell RNA sequencing and single-cell T-cell receptor sequencing analyses. Publicly available MF and AD datasets were integrated for comparative analysis. Spatial transcriptomic profiling was used to contextualize single-cell findings within the tissue architecture. RESULTS: Comparative transcriptomic analysis revealed that T cells in mfAD were aligned with those in AD and lacked genomic instability. High-resolution profiling showed that mfAD was characterized by oligoclonal Th22 expansion rather than a single dominant malignant clone. Notably, all patients with mfAD achieved rapid clinical remission with selective JAK1 inhibition, indicating the therapeutic response characteristics of inflammatory dermatoses. CONCLUSION: Our findings demonstrate that mfAD is not a true malignancy, but rather a Th22-driven inflammatory endotype of AD. These results redefine mfAD as an inflammatory subtype within the AD spectrum, providing a mechanistic explanation for both the "pseudo-monoclonality" that leads to MF misdiagnosis and the failure of dupilumab. This study establishes a rationale for the use of JAK inhibitors in precision medicine for this patient population.

JAK inhibitor↗

Gene identification signature (GIS) analysis for transcriptome characterization and genome annotation.

We have developed a DNA tag sequencing and mapping strategy called gene identification signature (GIS) analysis, in which 5' and 3' signatures of full-length cDNAs are accurately extracted into paired-end ditags (PETs) that are concatenated for efficient sequencing and mapped to genome sequences to demarcate the transcription boundaries of every gene. GIS analysis is potentially 30-fold more efficient than standard cDNA sequencing approaches for transcriptome characterization. We demonstrated this approach with 116,252 PET sequences derived from mouse embryonic stem cells. Initial analysis of this dataset identified hundreds of previously uncharacterized transcripts, including alternative transcripts of known genes. We also uncovered several intergenically spliced and unusual fusion transcripts, one of which was confirmed as a trans-splicing event and was differentially expressed. The concept of paired-end ditagging described here for transcriptome analysis can also be applied to whole-genome analysis of cis-regulatory and other DNA elements and represents an important technological advance for genome annotation.

5' Flanking Region↗

The difficult interpretation of transcriptome data: the case of the GATC regulatory network.

Genomic analyses on part of Escherichia coli's chromosome had suggested the existence of a GATC regulated network. This has recently been confirmed through a transcriptome analysis. Two hypotheses about the molecular control mechanism have been proposed-(i) the GATC network regulation is caused by the presence of GATC clusters within the coding sequences; the regulation is the direct consequence of the clusters' hemi-methylation and therefore their elevated melting temperature, (ii) the regulation is caused by the presence of GATCs in the non-coding 500 bp upstream regions of the affected genes; it is the consequence of an interaction with a regulatory protein like Fnr or CAP. An analysis of the transcriptome data has not allowed us to decide between the two hypotheses. We have therefore taken a classic genomic approach, analyzing the statistical distribution of GATC along the chromosome, using a realistic model of the chromosome as theoretical reference. We observe no particular distribution of GATC in the non-coding upstream regions; however, we confirm the presence of GATC clusters within the genes. In order to verify that the particular distribution observed in E. coli is not a statistical artefact, but has a physiological role, we have carried out the same analysis on Salmonella, making the hypothesis that the genes containing a GATC clusters should be largely the same in the two bacteria. This has been indeed observed, showing that the genes containing a GATC cluster are part of a regulation network. The present is a case study, which demonstrates that the analysis of transcriptome data does not always permit to identify the primary cause of a phenomenon observed; on the other hand, a classic genomic approach linked with a comparative study of related genomes may allow this identification.

Computational Biology↗

Endosperm-preferred expression of maize genes as revealed by transcriptome-wide analysis of expressed sequence tags.

The transcriptome-wide endosperm-preferred expression of maize genes was addressed by analyzing a large database of expressed sequence tags (ESTs). We generated 30,531 high quality sequence-reads from the 5'-ends of cDNA libraries from maize endosperm harvested at 10, 15, and 20 days after pollination. A further 196,900 maize sequence-reads retrieved from public databases were added to this endosperm collection to generate MAIZEST, a database with tools for data storage and analysis. MAIZEST contains 227,431 ESTs, one third of which represents developing endosperm and the remaining two-thirds represent transcripts from 49 cDNA libraries constructed from different organs and tissues. Assembling the MAIZEST ESTs generated 29,206 putative transcripts, of which a set of 4032 assembled sequences was composed exclusively of sequences derived from endosperm cDNA libraries. After sequence analysis using overlapping parameters, a sub-set of 2403 assembled sequences was functionally annotated and revealed a wide variety of putative new genes involved in endosperm development and metabolism.

Expressed Sequence Tags↗

Genetic dissection of cardiac iron regulation using transcriptome network analysis and systems genetics in BXD mice.

Cardiac iron homeostasis is essential for myocardial energy metabolism and contractile function, yet the genetic and molecular mechanisms governing iron levels within the heart remain poorly understood. We used a systems genetics approach to dissect the transcriptional regulation of cardiac iron homeostasis. Myocardial iron level varies substantially across BXD strains (40-112 &#x3bc;g/g) and is under heritable genetic control (H2 = 0.38). Elevated cardiac iron is associated with reduced ventricular mass, increased ventricular ectopy, and prolonged atrioventricular conduction in the BXD population. Weighted gene co-expression network analysis of the BXD heart transcriptome identified a co-expression module that was significantly and negatively correlated with cardiac iron levels in both young and old BXD mice and enriched for pathways related to metabolic regulation, cyclic AMP (cAMP) signaling, circadian entrainment, and cardiovascular physiology. The module showed substantial overlap with a curated cardiac iron gene set, and cross-species enrichment analysis confirmed its conservation in human cardiomyopathy differentially expressed genes (enrichment ratio = 1.49; false discovery rate [FDR] = 0.0342). Quantitative trait locus (QTL) mapping of the first principal component of the overlapping module iron genes (n = 38), corroborated by individual gene mapping, identified trans-eQTL hotspots on multiple chromosomes, implicating Fcho2, Gcc2, and Rmdn1 as candidate upstream regulators operating through sequential steps of intracellular iron trafficking. Together, these findings establish a systems-level map of cardiac iron gene regulation, identify candidate genetic regulators, and provide a molecular framework linking disruption of iron-related transcriptional networks to structural and electrical cardiac dysfunction with implications for iron-related heart diseases.

BXD mouse population↗

Potential Involvement of the IL-6/STAT3/MMP12 Signaling Axis in DMSO-Mediated Anti-Fibrotic Effects in Experimental Silicosis.

This study aims to investigate the anti-inflammatory and anti-fibrotic effects of dimethyl sulfoxide (DMSO) in a mouse model of silicosis, thereby exploring its potential therapeutic value. A mouse model of silicosis was established by intranasal instillation, and DMSO treatment was administered via intraperitoneal injection. The experiment was conducted over a period of 1 month. Lung tissues were collected from all mice; a subset was subjected to transcriptomic analysis, and differentially expressed genes were identified using the limma package. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were conducted using ClusterProfiler to investigate gene functions and associated pathways. The remaining samples were subjected to histopathological assessment by hematoxylin and eosin staining (HE) and Masson's trichrome staining, while Western blot analysis was performed to validate transcriptomic results. This study suggests that DMSO may alleviate the fibrotic process in silicosis by modulating the IL-6/STAT3-MMP12 signaling axis. In the silica-induced silicosis mouse model, DMSO attenuated disease-associated weight loss and reduced collagen deposition. Transcriptomic analysis indicated that DMSO suppressed the activity of multiple fibrosis-related pathways and identified 51 key genes, including MMP12, which was significantly downregulated. Western blot analysis further confirmed reduced MMP12 expression, accompanied by markedly decreased levels of IL-6 and p-STAT3, suggesting the IL-6/STAT3 pathway may play a crucial role in regulating MMP12 expression. DMSO may attenuate inflammatory responses and pulmonary fibrosis in silicosis by inhibiting activation of the IL-6/STAT3 signaling pathway, thereby reducing MMP12 expression.

Animals↗

Genome-wide transcriptome mapping analysis identifies organ-specific gene expression patterns along human chromosomes.

The Human Genome Project has revealed that there about 32,000 protein-encoding genes, which are distributed throughout the genome. It is unclear, however, whether genes are distributed on the chromosomes according to patterns linked to organ specificity. To explore the relationship between genes actively transcribed in normal tissues and their chromosomal locations, we analyzed serial analysis of gene expression libraries of normal human liver, brain, breast, and colon tissues. Transcriptome mapping analysis revealed that transcriptional activity in each tissue varied according to the chromosomal domains, and a weak positive correlation was observed between transcription density and gene density. We identified six liver-related and five colon-related chromosomal domains highly transcribed in each tissue, whereas no brain-related or breast-related chromosomal domains were identified. Representative genes located on these chromosomal domains were associated with the function of each organ and were highly conserved in both mouse and rat genomes. These data revealed that the transcriptional activities of normal human tissues are well orchestrated at chromosomal levels, suggesting that highly expressed genes may share physical proximity.

Chromosome Mapping↗

A Practical Workflow for Spatial Transcriptomics Data Analysis: From Data Acquisition to Advanced Analyses.

Spatial transcriptomics (ST) profiles genome-wide gene expression while preserving the two-dimensional spatial context of mRNA molecules within tissue sections, enabling studies of tissue architecture and microenvironment-associated biology. However, ST analysis remains challenging because data import, quality control, integration, deconvolution, spatial statistics, and visualization often require multiple software environments and reproducible parameter choices. This protocol presents a practical computational workflow for public ST datasets in R, beginning with data acquisition and software setup and proceeding through Seurat-based data loading, quality control, normalization, multi-sample integration, clustering, and spatially variable gene analysis. The workflow then applies complementary deconvolution strategies, including reference-guided SPOTlight analysis and unsupervised STdeconvolve topic modeling, followed by Giotto-based spatial cell-cell communication analysis and interactive region-of-interest (ROI) selection using a custom Python Dash application. By emphasizing script-based execution, explicit parameter rationales, expected outputs, and troubleshooting checkpoints, the protocol provides an adaptable framework for standard array-based ST datasets and related platforms after dataset- and platform-specific parameter evaluation.

Spatial Transcriptomics↗

Uncovering hub genes and key pathways responsive to drought stress in rice via meta-analysis of transcriptomic data.

Drought stress presents a formidable threat to global rice cultivation, triggering complex molecular responses that impact plant growth and productivity. To decipher the underlying gene expression dynamics, we performed a comprehensive meta-analysis of transcriptomic datasets derived from drought-tolerant rice genotypes. Via microarray data from three independent studies, we identified a set of consistently expressed differentially expressed genes (DEGs) under drought conditions. Integration of functional annotation tools, including GO and KEGG pathway enrichment, revealed key biological processes and signaling cascades involved in stress mitigation, such as ABA signaling, protein folding, and photosynthesis suppression. Protein-protein interaction (PPI) network construction, followed by hub gene identification via maximal clique centrality (MCC), highlighted pivotal regulators including LEA proteins, dehydrins, HSP70, and several transcription factors. Machine learning approaches further prioritize potential biomarkers, with Random Forest models achieving high classification accuracy and pinpointing key predictive genes. Chromosomal localization analysis provided spatial insights into the distribution of these hub genes, whose expression patterns were further compared against qRT-PCR data from previously published studies. This integrative approach identifies candidate genomic markers and mechanistic insights that may support future breeding strategies for drought-tolerant rice, pending experimental validation.

Cytoscape↗

transFusion: a novel comprehensive platform for integration analysis of single-cell and spatial transcriptomics.

MOTIVATION: Understanding spatial organization, intercellular interactions, and regulatory networks within the spatial context of tissues is crucial for uncovering complex biological processes and disease mechanisms. Spatial transcriptomics technologies have revolutionized this field by enabling the spatially resolved profiling of gene expression. 10&#xd7; Visium has emerged as the predominant spatial technology, but its low resolution and the complexity of integrating multimodal datasets present significant analytical challenges, particularly for researchers with limited computational and statistical expertise. Current spatial transcriptomics analysis platforms generally fall short of effectively integrating multimodal data and maximizing the utility of spatial information-such as uncovering complex cellular spatial dependencies, multimodal gradient patterns, and spatial coexpression of ligand-receptor pairs and regulatory networks related to disease or biological states-thereby limiting their ability to provide comprehensive end-to-end analytical workflows when analyzing 10&#xd7; Visium data. RESULTS: To address these limitations, we developed transFusion, a novel, advanced web-based platform specializing in the most comprehensive and effective integration analysis of scRNA-seq and 10&#xd7; Visium spatial transcriptomics data. transFusion offers 12 key functions, from basic visualization to advanced analyses, including intercellular dependency analysis, ligand-receptor coexpression identification and visualization, and spatial multimodal gradient variation patterns. Two case studies were used to demonstrate transFusion's capabilities in exploring tissue architecture, intercellular communication, dependency networks, and multimodal gradient variation patterns with minimal computational skills and statistical expertise. transFusion provides a flexible and powerful framework for multimodal data integration analysis. AVAILABILITY AND IMPLEMENTATION: transFusion is freely available at https://github.com/WQLin8/transFusion.

Spatial Transcriptomics↗

Initial transcriptome and proteome analyses of low culture temperature-induced expression in CHO cells producing erythropoietin.

Low culture temperature is known to enhance the specific productivity of Chinese hamster ovary (CHO) cells expressing erythropoietin (EPO) (LGE10-9-27). Genomic and proteomic approaches were taken to better understand the intracellular responses of these CHO cells resulting from use of low culture temperature (33 degrees C). For transcriptome analysis, commercially available rat and mouse cDNA microarrays were used. The data obtained from the rat and mouse cDNA chips were only somewhat informative in understanding the gene expression profile of CHO cells because of their different sequence homologies with CHO transcriptomes. Overall, transcriptome analysis revealed that low culture temperature could lead to changes in gene expression in various cellular processes such as metabolism, transport, and signaling pathways. Proteome analysis was carried out using 2-D PAGE. Based on spot intensity, 60 high intensity protein spots, from a total of more than 800, were chosen for MS analysis. Forty of the 60 protein spots, which represent 26 different kinds of proteins, were identified by MALDI-TOF-MS and validated by MS/MS. Compared to the reference temperature (37 degrees C), the expression levels of seven proteins (PDI, vimentin, NDK B, ERp57, RIKEN cDNA, phosphoglycerate kinase, and heat shock cognate 71 kDa protein) were increased over twofold at 33 degrees C and those of two proteins (HSP90-beta and EF2) were decreased over twofold at 33 degrees C. Taken together, the results demonstrate the potential of combined analysis of transcriptome and proteome analyses as a tool for the systematic comprehension of cellular mechanisms in CHO cells.

Animals↗

Plasticity of mouse renal collecting duct in response to potassium depletion.

Plasticity of mouse renal collecting duct in response to potassium depletion.--Renal collecting ducts are the main sites for regulation of whole body potassium balance. Changes in dietary intake of potassium induce pleiotropic adaptations of collecting duct cells, which include alterations of ion and water transport properties along with an hypertrophic response. To study the pleiotropic adaptation of the outer medullary collecting duct (OMCD) to dietary potassium depletion, we combined functional studies of renal function (ion, water, and acid/base handling), analysis of OMCD hypertrophy (electron microscopy) and hyperplasia (PCNA labeling), and large scale analysis of gene expression (transcriptome analysis). The transcriptome of OMCD was compared in mice fed either a normal or a potassium-depleted diet for 3 days using serial analysis of gene expression (SAGE) adapted for downsized extracts. SAGE is based on the generation of transcript-specific tag libraries. Approximately 20,000 tags corresponding to 10,000 different molecular species were sequenced in each library. Among the 186 tags differentially expressed (P < 0.05) between the two libraries, 120 were overexpressed and 66 were downregulated. The SAGE expression profile obtained in the control library was representative of different functional classes of proteins and of the two cell types (principal and alpha-intercalated cells) constituting the OMCD. Combined with gene expression analysis, results of functional and morphological studies allowed us to identify candidate genes for distinct physiological processes modified by potassium depletion: sodium, potassium, and water handling, hyperplasia and hypertrophy. Finally, comparison of mouse and human OMCD transcriptomes allowed us to address the question of the relevance of the mouse as a model for human physiology and pathophysiology.

Acid-Base Equilibrium↗