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      Nonalcoholic Steatohepatitis and HCC in a Hyperphagic Mouse Accelerated by Western Diet

      research-article
      1 , 2 , 1 , 1 , 3 , 4 , 1 , 1 , 5 , 1 , 6 , 2 , 7 , 4 , 8 , 9 , 1 , 1 , , 1 ,
      Cellular and Molecular Gastroenterology and Hepatology
      Elsevier
      Nonalcoholic Steatohepatitis, Hepatocellular Carcinoma, NASH Regression, Gut Inflammation, Liver Inflammation, ALT, alanine aminotransferase, APC, Allophycocyanin, CD-HFD, choline-deficient high-fat diet, CKD, chronic kidney disease, CVD, cardiovascular disease, CXCL2, C-X-C motif chemokine ligand 2, DSI, distal small intestine, eWAT, white adipose tissue (epididymal fat), FACS, fluorescence-activated cell sorter, FBS, fetal bovine serum, FITC, fluorescein isothiocyanate, HCC, hepatocellular carcinoma, HSC, hepatic stellate cell, IFN, interferon, IHC, immunohistochemistry, IL, interleukin, ILC, innate lymphoid cell, LBP, lipopolysaccharide binding protein, LPS, lipopolysaccharide, MIP2, Macrophage Inflammatory Protein 2, NAFLD, nonalcoholic fatty liver disease, NASH, nonalcoholic steatohepatitis, PBS, phosphate-buffered saline, PE, Phycoerythrin, qRT-PCR, quantitative reverse-transcription polymerase chain reaction, RPCA, robust principal component analysis, rRNA, ribosomal RNA, SI, small intestine, TNF, tumor necrosis factor, WD, Western diet, WT, wild-type

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          Abstract

          Background & Aims

          How benign liver steatosis progresses to nonalcoholic steatohepatitis (NASH), fibrosis, and hepatocellular carcinoma (HCC) remains elusive. NASH progression entails diverse pathogenic mechanisms and relies on complex cross-talk between multiple tissues such as the gut, adipose tissues, liver, and the brain. Using a hyperphagic mouse fed with a Western diet (WD), we aimed to elucidate the cross-talk and kinetics of hepatic and extrahepatic alterations during NASH–HCC progression, as well as regression.

          Methods

          Hyperphagic mice lacking a functional Alms1 gene ( Foz/Foz) and wild-type littermates were fed WD or standard chow for 12 weeks for NASH/fibrosis and for 24 weeks for HCC development. NASH regression was modeled by switching back to normal chow after NASH development.

          Results

          Foz+WD mice were steatotic within 1 to 2 weeks, developed NASH by 4 weeks, and grade 3 fibrosis by 12 weeks, accompanied by chronic kidney injury. Foz+WD mice that continued on WD progressed to cirrhosis and HCC within 24 weeks and had reduced survival as a result of cardiac dysfunction. However, NASH mice that were switched to normal chow showed NASH regression, improved survival, and did not develop HCC. Transcriptomic and histologic analyses of Foz/Foz NASH liver showed strong concordance with human NASH. NASH was preceded by an early disruption of gut barrier, microbial dysbiosis, lipopolysaccharide leakage, and intestinal inflammation. This led to acute-phase liver inflammation in Foz+WD mice, characterized by neutrophil infiltration and increased levels of several chemokines/cytokines. The liver cytokine/chemokine profile evolved as NASH progressed, with subsequent predominance by monocyte recruitment.

          Conclusions

          The Foz+WD model closely mimics the pathobiology and gene signature of human NASH with fibrosis and subsequent HCC. Foz+WD mice provide a robust and relevant preclinical model of NASH, NASH-associated HCC, chronic kidney injury, and heart failure.

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          Most cited references58

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          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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            Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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              limma powers differential expression analyses for RNA-sequencing and microarray studies

              limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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                Author and article information

                Contributors
                Journal
                Cell Mol Gastroenterol Hepatol
                Cell Mol Gastroenterol Hepatol
                Cellular and Molecular Gastroenterology and Hepatology
                Elsevier
                2352-345X
                2021
                29 May 2021
                : 12
                : 3
                : 891-920
                Affiliations
                [1 ]Department of Medicine, University of California San Diego, La Jolla, California
                [3 ]Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, California
                [4 ]Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, California
                [6 ]Department of Surgery, University of California San Diego, La Jolla, California
                [7 ]Department of Pathology, University of California San Diego, La Jolla, California
                [8 ]Center for Microbiome Innovation, University of California San Diego, La Jolla, California
                [9 ]Department of Pediatrics, University of California San Diego, La Jolla, California
                [2 ]Janssen Research and Development, San Diego, California
                [5 ]Department of Gastroenterology and Hepatology, National Medical Center, Jung-Gu, Seoul, South Korea
                Author notes
                [] Correspondence Address correspondence to: David A. Brenner, MD, or Debanjan Dhar, PhD, Department of Medicine, University of California San Diego, 9500 Gilman Drive, MC0063, La Jolla, California 92093. fax: (858) 246-1788. dbrenner@ 123456health.ucsd.edu ddhar@ 123456health.ucsd.edu
                Article
                S2352-345X(21)00099-0
                10.1016/j.jcmgh.2021.05.010
                8342972
                34062281
                dd1b7a50-053f-4681-b0dc-d22c6e5eed93
                © 2021 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 20 January 2021
                : 15 May 2021
                Categories
                Original Research

                nonalcoholic steatohepatitis,hepatocellular carcinoma,nash regression,gut inflammation,liver inflammation,alt, alanine aminotransferase,apc, allophycocyanin,cd-hfd, choline-deficient high-fat diet,ckd, chronic kidney disease,cvd, cardiovascular disease,cxcl2, c-x-c motif chemokine ligand 2,dsi, distal small intestine,ewat, white adipose tissue (epididymal fat),facs, fluorescence-activated cell sorter,fbs, fetal bovine serum,fitc, fluorescein isothiocyanate,hcc, hepatocellular carcinoma,hsc, hepatic stellate cell,ifn, interferon,ihc, immunohistochemistry,il, interleukin,ilc, innate lymphoid cell,lbp, lipopolysaccharide binding protein,lps, lipopolysaccharide,mip2, macrophage inflammatory protein 2,nafld, nonalcoholic fatty liver disease,nash, nonalcoholic steatohepatitis,pbs, phosphate-buffered saline,pe, phycoerythrin,qrt-pcr, quantitative reverse-transcription polymerase chain reaction,rpca, robust principal component analysis,rrna, ribosomal rna,si, small intestine,tnf, tumor necrosis factor,wd, western diet,wt, wild-type

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