MATRIN3 deficiency triggers autoinflammation via cGAS-STING activation.

Interferon-stimulated genes (ISGs) comprise a program of immune effectors important for host immune defense. When uncontrolled, ISGs play a central role in interferonopathies and other inflammatory diseases. The mechanisms responsible for turning on ISGs are not completely known. By investigating MATRIN3 (MATR3), a nuclear RNA-binding protein mutated in familial ALS, we found that perturbing MATR3 results in elevated expression of ISGs. Using an integrative approach, we elucidate a pathway that leads to activation of cGAS-STING. This outlines a plausible mechanism for pathogenesis in a subset of ALS, and suggests new diagnostic and therapeutic approaches for this fatal disease.

Regulatory T cell differentiation is controlled by αKG-induced alterations in mitochondrial metabolism and lipid homeostasis.

Suppressive regulatory T cell (Treg) differentiation is controlled by diverse immunometabolic signaling pathways and intracellular metabolites. Here we show that cell-permeable α-ketoglutarate (αKG) alters the DNA methylation profile of naive CD4 T cells activated under Treg polarizing conditions, markedly attenuating FoxP3+ Treg differentiation and increasing inflammatory cytokines. Adoptive transfer of these T cells into tumor-bearing mice results in enhanced tumor infiltration, decreased FoxP3 expression, and delayed tumor growth. Mechanistically, αKG leads to an energetic state that is reprogrammed toward a mitochondrial metabolism, with increased oxidative phosphorylation and expression of mitochondrial complex enzymes. Furthermore, carbons from ectopic αKG are directly utilized in the generation of fatty acids, associated with lipidome remodeling and increased triacylglyceride stores. Notably, inhibition of either mitochondrial complex II or DGAT2-mediated triacylglyceride synthesis restores Treg differentiation and decreases the αKG-induced inflammatory phenotype. Thus, we identify a crosstalk between αKG, mitochondrial metabolism and triacylglyceride synthesis that controls Treg fate.

Posttranscriptional regulation of human endogenous retroviruses by RNA-binding motif protein 4, RBM4.

The human genome encodes for over 1,500 RNA-binding proteins (RBPs), which coordinate regulatory events on RNA transcripts. Most studies of RBPs have concentrated on their action on host protein-encoding mRNAs, which constitute a minority of the transcriptome. A widely neglected subset of our transcriptome derives from integrated retroviral elements, termed endogenous retroviruses (ERVs), that comprise ∼8% of the human genome. Some ERVs have been shown to be transcribed under physiological and pathological conditions, suggesting that sophisticated regulatory mechanisms to coordinate and prevent their ectopic expression exist. However, it is unknown how broadly RBPs and ERV transcripts directly interact to provide a posttranscriptional layer of regulation. Here, we implemented a computational pipeline to determine the correlation of expression between individual RBPs and ERVs from single-cell or bulk RNA-sequencing data. One of our top candidates for an RBP negatively regulating ERV expression was RNA-binding motif protein 4 (RBM4). We used photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation to demonstrate that RBM4 indeed bound ERV transcripts at CGG consensus elements. Loss of RBM4 resulted in an elevated transcript level of bound ERVs of the HERV-K and -H families, as well as increased expression of HERV-K envelope protein. We pinpointed RBM4 regulation of HERV-K to a CGG-containing element that is conserved in the LTRs of HERV-K-10, -K-11, and -K-20, and validated the functionality of this site using reporter assays. In summary, we systematically identified RBPs that may regulate ERV function and demonstrate a role for RBM4 in controlling ERV expression.

Enhancement of LIN28B-induced hematopoietic reprogramming by IGF2BP3.

Fetal hematopoietic stem and progenitor cells (HSPCs) hold promise to cure a wide array of hematological diseases, and we previously found a role for the RNA-binding protein (RBP) Lin28b in respecifying adult HSPCs to resemble their fetal counterparts. Here we show by single-cell RNA sequencing that Lin28b alone was insufficient for complete reprogramming of gene expression from the adult toward the fetal pattern. Using proteomics and in situ analyses, we found that Lin28b (and its closely related paralog, Lin28a) directly interacted with Igf2bp3, another RBP, and their enforced co-expression in adult HSPCs reactivated fetal-like B-cell development in vivo more efficiently than either factor alone. In B-cell progenitors, Lin28b and Igf2bp3 jointly stabilized thousands of mRNAs by binding at the same sites, including those of the B-cell regulators Pax5 and Arid3a as well as Igf2bp3 mRNA itself, forming an autoregulatory loop. Our results suggest that Lin28b and Igf2bp3 are at the center of a gene regulatory network that mediates the fetal-adult hematopoietic switch. A method to efficiently generate induced fetal-like hematopoietic stem cells (ifHSCs) will facilitate basic studies of their biology and possibly pave a path toward their clinical application.

C3HeB/FeJ Mice mimic many aspects of gene expression and pathobiological features of human hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) remains a deadly cancer, underscoring the need for relevant preclinical models. Male C3HeB/FeJ mice model spontaneous HCC with some hepatocarcinogenesis susceptibility loci corresponding to syntenic regions of human chromosomes altered in HCC. We tested other properties of C3HeB/FeJ tumors for similarity to human HCC. C3HeB/FeJ tumors were grossly visible at 4 months of age, with prevalence and size increasing until about 11 months of age. Histologic features shared with human HCC include hepatosteatosis, tumor progression from dysplasia to poorly differentiated, vascular invasion, and trabecular, oncocytic, vacuolar, and clear cell variants. More tumor cells displayed cytoplasmic APE1 staining versus normal liver. Ultrasound effectively detected and monitored tumors, with 85.7% sensitivity. Over 5000 genes were differentially expressed based on the GSE62232 and GSE63898 human HCC datasets. Of these, 158 and 198 genes, respectively, were also differentially expressed in C3HeB/FeJ. Common cancer pathways, cell cycle, p53 signaling and other molecular aspects, were shared between human and mouse differentially expressed genes. We established eigengenes that distinguish HCC from normal liver in the C3HeB/FeJ model and a subset of human HCC. These features extend the relevance and improve the utility of the C3HeB/FeJ line for HCC studies.

Applications of Bayesian network models in predicting types of hematological malignancies.

Network analysis is the preferred approach for the detection of subtle but coordinated changes in expression of an interacting and related set of genes. We introduce a novel method based on the analyses of coexpression networks and Bayesian networks, and we use this new method to classify two types of hematological malignancies; namely, acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). Our classifier has an accuracy of 93%, a precision of 98%, and a recall of 90% on the training dataset (n = 366); which outperforms the results reported by other scholars on the same dataset. Although our training dataset consists of microarray data, our model has a remarkable performance on the RNA-Seq test dataset (n = 74, accuracy = 89%, precision = 88%, recall = 98%), which confirms that eigengenes are robust with respect to expression profiling technology. These signatures are useful in classification and correctly predicting the diagnosis. They might also provide valuable information about the underlying biology of diseases. Our network analysis approach is generalizable and can be useful for classifying other diseases based on gene expression profiles. Our previously published Pigengene package is publicly available through Bioconductor, which can be used to conveniently fit a Bayesian network to gene expression data.

Large-scale gene network analysis reveals the significance of extracellular matrix pathway and homeobox genes in acute myeloid leukemia: an introduction to the Pigengene package and its applications.

BACKGROUND: The distinct types of hematological malignancies have different biological mechanisms and prognoses. For instance, myelodysplastic syndrome (MDS) is generally indolent and low risk; however, it may transform into acute myeloid leukemia (AML), which is much more aggressive. METHODS: We develop a novel network analysis approach that uses expression of eigengenes to delineate the biological differences between these two diseases. RESULTS: We find that specific genes in the extracellular matrix pathway are underexpressed in AML. We validate this finding in three ways: (a) We train our model on a microarray dataset of 364 cases and test it on an RNA Seq dataset of 74 cases. Our model showed 95% sensitivity and 86% specificity in the training dataset and showed 98% sensitivity and 91% specificity in the test dataset. This confirms that the identified biological signatures are independent from the expression profiling technology and independent from the training dataset. (b) Immunocytochemistry confirms that MMP9, an exemplar protein in the extracellular matrix, is underexpressed in AML. (c) MMP9 is hypermethylated in the majority of AML cases (n=194, Welch's t-test p-value <10-138), which complies with its low expression in AML. Our novel network analysis approach is generalizable and useful in studying other complex diseases (e.g., breast cancer prognosis). We implement our methodology in the Pigengene software package, which is publicly available through Bioconductor. CONCLUSIONS: Eigengenes define informative biological signatures that are robust with respect to expression profiling technology. These signatures provide valuable information about the underlying biology of diseases, and they are useful in predicting diagnosis and prognosis.

Profiling microRNA expression in bovine alveolar macrophages using RNA-seq.

MicroRNAs (miRNAs) are important regulators of gene expression and are known to play a key role in regulating both adaptive and innate immunity. Bovine alveolar macrophages (BAMs) help maintain lung homeostasis and constitute the front line of host defense against several infectious respiratory diseases, such as bovine tuberculosis. Little is known, however, about the role miRNAs play in these cells. In this study, we used a high-throughput sequencing approach, RNA-seq, to determine the expression levels of known and novel miRNAs in unchallenged BAMs isolated from lung lavages of eight different healthy Holstein-Friesian male calves. Approximately 80 million sequence reads were generated from eight BAM miRNA Illumina sequencing libraries, and 80 miRNAs were identified as being expressed in BAMs at a threshold of at least 100 reads per million (RPM). The expression levels of miRNAs varied over a large dynamic range, with a few miRNAs expressed at very high levels (up to 800,000RPM), and the majority lowly expressed. Notably, many of the most highly expressed miRNAs in BAMs have known roles in regulating immunity in other species (e.g. bta-let-7i, bta-miR-21, bta-miR-27, bta-miR-99b, bta-miR-146, bta-miR-147, bta-miR-155 and bta-miR-223). The most highly expressed miRNA in BAMs was miR-21, which has been shown to regulate the expression of antimicrobial peptides in Mycobacterium leprae-infected human monocytes. Furthermore, the predicted target genes of BAM-expressed miRNAs were found to be statistically enriched for roles in innate immunity. In addition to profiling the expression of known miRNAs, the RNA-seq data was also analysed to identify potentially novel bovine miRNAs. One putatively novel bovine miRNA was identified. To the best of our knowledge, this is the first RNA-seq study to profile miRNA expression in BAMs and provides an important reference dataset for investigating the regulatory roles miRNAs play in this important immune cell type.

Next generation sequencing reveals the expression of a unique miRNA profile in response to a gram-positive bacterial infection.

MicroRNAs (miRNAs) are short, non-coding RNAs, which post-transcriptionally regulate gene expression and are proposed to play a key role in the regulation of innate and adaptive immunity. Here, we report a next generation sequencing (NGS) approach profiling the expression of miRNAs in primary bovine mammary epithelial cells (BMEs) at 1, 2, 4 and 6 hours post-infection with Streptococcus uberis, a causative agent of bovine mastitis. Analysing over 450 million sequencing reads, we found that 20% of the approximately 1,300 currently known bovine miRNAs are expressed in unchallenged BMEs. We also identified the expression of more than 20 potentially novel bovine miRNAs. There is, however, a significant dynamic range in the expression of known miRNAs. The top 10 highly expressed miRNAs account for >80% of all aligned reads, with the remaining miRNAs showing much lower expression. Twenty-one miRNAs were identified as significantly differentially expressed post-infection with S. uberis. Several of these miRNAs have characterised roles in the immune systems of other species. This miRNA response to the Gram-positive S. uberis is markedly different, however, to lipopolysaccharide (LPS) induced miRNA expression. Of 145 miRNAs identified in the literature as being LPS responsive, only 9 were also differentially expressed in response to S. uberis. Computational analysis has also revealed that the predicted target genes of miRNAs, which are down-regulated in BMEs following S. uberis infection, are statistically enriched for roles in innate immunity. This suggests that miRNAs, which potentially act as central regulators of gene expression responses to a Gram-positive bacterial infection, may significantly regulate the sentinel capacity of mammary epithelial cells to mobilise the innate immune system.

InnateDB: systems biology of innate immunity and beyond--recent updates and continuing curation.

InnateDB (http://www.innatedb.com) is an integrated analysis platform that has been specifically designed to facilitate systems-level analyses of mammalian innate immunity networks, pathways and genes. In this article, we provide details of recent updates and improvements to the database. InnateDB now contains >196 000 human, mouse and bovine experimentally validated molecular interactions and 3000 pathway annotations of relevance to all mammalian cellular systems (i.e. not just immune relevant pathways and interactions). In addition, the InnateDB team has, to date, manually curated in excess of 18 000 molecular interactions of relevance to innate immunity, providing unprecedented insight into innate immunity networks, pathways and their component molecules. More recently, InnateDB has also initiated the curation of allergy- and asthma-related interactions. Furthermore, we report a range of improvements to our integrated bioinformatics solutions including web service access to InnateDB interaction data using Proteomics Standards Initiative Common Query Interface, enhanced Gene Ontology analysis for innate immunity, and the availability of new network visualizations tools. Finally, the recent integration of bovine data makes InnateDB the first integrated network analysis platform for this agriculturally important model organism.

Pathway-GPS and SIGORA: identifying relevant pathways based on the over-representation of their gene-pair signatures.

Motivation. Predominant pathway analysis approaches treat pathways as collections of individual genes and consider all pathway members as equally informative. As a result, at times spurious and misleading pathways are inappropriately identified as statistically significant, solely due to components that they share with the more relevant pathways. Results. We introduce the concept of Pathway Gene-Pair Signatures (Pathway-GPS) as pairs of genes that, as a combination, are specific to a single pathway. We devised and implemented a novel approach to pathway analysis, Signature Over-representation Analysis (SIGORA), which focuses on the statistically significant enrichment of Pathway-GPS in a user-specified gene list of interest. In a comparative evaluation of several published datasets, SIGORA outperformed traditional methods by delivering biologically more plausible and relevant results. Availability. An efficient implementation of SIGORA, as an R package with precompiled GPS data for several human and mouse pathway repositories is available for download from http://sigora.googlecode.com/svn/.

Curating the innate immunity interactome.

BACKGROUND: The innate immune response is the first line of defence against invading pathogens and is regulated by complex signalling and transcriptional networks. Systems biology approaches promise to shed new light on the regulation of innate immunity through the analysis and modelling of these networks. A key initial step in this process is the contextual cataloguing of the components of this system and the molecular interactions that comprise these networks. InnateDB (http://www.innatedb.com) is a molecular interaction and pathway database developed to facilitate systems-level analyses of innate immunity. RESULTS: Here, we describe the InnateDB curation project, which is manually annotating the human and mouse innate immunity interactome in rich contextual detail, and present our novel curation software system, which has been developed to ensure interactions are curated in a highly accurate and data-standards compliant manner. To date, over 13,000 interactions (protein, DNA and RNA) have been curated from the biomedical literature. Here, we present data, illustrating how InnateDB curation of the innate immunity interactome has greatly enhanced network and pathway annotation available for systems-level analysis and discuss the challenges that face such curation efforts. Significantly, we provide several lines of evidence that analysis of the innate immunity interactome has the potential to identify novel signalling, transcriptional and post-transcriptional regulators of innate immunity. Additionally, these analyses also provide insight into the cross-talk between innate immunity pathways and other biological processes, such as adaptive immunity, cancer and diabetes, and intriguingly, suggests links to other pathways, which as yet, have not been implicated in the innate immune response. CONCLUSIONS: In summary, curation of the InnateDB interactome provides a wealth of information to enable systems-level analysis of innate immunity.