UBASH3A deficiency accelerates type 1 diabetes development and enhances salivary gland inflammation in NOD mice

CD6 Regulates CD4 T Follicular Helper Cell Differentiation and Humoral Immunity During Murine Coronavirus Infection

During activation the T cell transmembrane receptor CD6 becomes incorporated into the T cell immunological synapse where it can exert both co-stimulatory and co-inhibitory functions. Given the ability of CD6 to carry out opposing functions, this study sought to determine how CD6 regulates early T cell activation in response to viral infection. Infection of CD6 deficient mice with a neurotropic murine coronavirus resulted in greater activation and expansion of CD4 T cells in the draining lymph nodes. Further analysis demonstrated that there was also preferential differentiation of CD4 T cells into T follicular helper cells, resulting in accelerated germinal center responses and emergence of high affinity virus specific antibodies. Given that CD6 conversely supports CD4 T cell activation in many autoimmune models, we probed potential mechanisms of CD6 mediated suppression of CD4 T cell activation during viral infection. Analysis of CD6 binding proteins revealed that infection induced upregulation of Ubash3a, a negative regulator of T cell receptor signaling, was hindered in CD6 deficient lymph nodes. Consistent with greater T cell activation and reduced UBASH3a activity, the T cell receptor signal strength was intensified in CD6 deficient CD4 T cells. These results reveal a novel immunoregulatory role for CD6 in limiting CD4 T cell activation and deterring CD4 T follicular helper cell differentiation, thereby attenuating antiviral humoral immunity.

FLI1 induces erythroleukemia through opposing effects on UBASH3A and UBASH3B expression

BACKGROUND

FLI1 is an oncogenic transcription factor that promotes diverse malignancies through mechanisms that are not fully understood. Herein, FLI1 is shown to regulate the expression of Ubiquitin Associated and SH3 Domain Containing A/B (UBASH3A/B) genes. UBASH3B and UBASH3A are found to act as an oncogene and tumor suppressor, respectively, and their combined effect determines erythroleukemia progression downstream of FLI1.

METHODS

Promoter analysis combined with luciferase assays and chromatin immunoprecipitation (ChIP) analysis were applied on the UBASH3A/B promoters. RNAseq analysis combined with bioinformatic was used to determine the effect of knocking-down UBASH3A and UBASH3B in leukemic cells. Downstream targets of UBASH3A/B were inhibited in leukemic cells either via lentivirus-shRNAs or small molecule inhibitors. Western blotting and RT-qPCR were used to determine transcription levels, MTT assays to assess proliferation rate, and flow cytometry to examine apoptotic index.

RESULTS

Knockdown of FLI1 in erythroleukemic cells identified the UBASH3A/B genes as potential downstream targets. Herein, we show that FLI1 directly binds to the UBASH3B promoter, leading to its activation and leukemic cell proliferation. In contrast, FLI1 indirectly inhibits UBASH3A transcription via GATA2, thereby antagonizing leukemic growth. These results suggest oncogenic and tumor suppressor roles for UBASH3B and UBASH3A in erythroleukemia, respectively. Mechanistically, we show that UBASH3B indirectly inhibits AP1 (FOS and JUN) expression, and that its loss leads to inhibition of apoptosis and acceleration of proliferation. UBASH3B also positively regulates the SYK gene expression and its inhibition suppresses leukemia progression. High expression of UBASH3B in diverse tumors was associated with worse prognosis. In contrast, UBASH3A knockdown in erythroleukemic cells increased proliferation; and this was associated with a dramatic induction of the HSP70 gene, HSPA1B. Accordingly, knockdown of HSPA1B in erythroleukemia cells significantly accelerated leukemic cell proliferation. Accordingly, overexpression of UBASH3A in different cancers was predominantly associated with good prognosis. These results suggest for the first time that UBASH3A plays a tumor suppressor role in part through activation of HSPA1B.

CONCLUSIONS

FLI1 promotes erythroleukemia progression in part by modulating expression of the oncogenic UBASH3B and tumor suppressor UBASH3A.

The Ubiquitin-Associated and SH3 Domain-Containing Proteins (UBASH3) Family in Mammalian Development and Immune Response

UBASH3A and UBASH3B are protein families of atypical protein tyrosine phosphatases that function as regulators of various cellular processes during mammalian development. As UBASH3A has only mild phosphatase activity, its regulatory effects are based on the phosphatase-independent mechanisms. On the contrary, UBASH3B has strong phosphatase activity, and the suppression of its receptor signalling is mediated by Syk and Zap-70 kinases. The regulatory functions of UBASH3A and UBASH3B are particularly evident in the lymphoid tissues and kidney development. These tyrosine phosphatases are also known to play key roles in autoimmunity and neoplasms. However, their involvement in mammalian development and its regulatory functions are largely unknown and are discussed in this review.

UBASH3A Interacts with PTPN22 to Regulate IL2 Expression and Risk for Type 1 Diabetes

UBASH3A is a negative regulator of T cell activation and IL-2 production and plays key roles in autoimmunity. Although previous studies revealed the individual effects of UBASH3A on risk for type 1 diabetes (T1D; a common autoimmune disease), the relationship of UBASH3A with other T1D risk factors remains largely unknown. Given that another well-known T1D risk factor, PTPN22, also inhibits T cell activation and IL-2 production, we investigated the relationship between UBASH3A and PTPN22. We found that UBASH3A, via its Src homology 3 (SH3) domain, physically interacts with PTPN22 in T cells, and that this interaction is not altered by the T1D risk coding variant rs2476601 in PTPN22. Furthermore, our analysis of RNA-seq data from T1D cases showed that the amounts of UBASH3A and PTPN22 transcripts exert a cooperative effect on IL2 expression in human primary CD8⁺ T cells. Finally, our genetic association analyses revealed that two independent T1D risk variants, rs11203203 in UBASH3A and rs2476601 in PTPN22, interact statistically, jointly affecting risk for T1D. In summary, our study reveals novel interactions, both biochemical and statistical, between two independent T1D risk loci, and suggests how these interactions may affect T cell function and increase risk for T1D.

Genetic and Molecular Quality Control of Genetically Engineered Mice

Genetically engineered mice are used as avatars to understand mammalian gene function and develop therapies for human disease. During genetic modification, unintended changes can occur, and these changes may result in misassigned gene-phenotype relationships leading to incorrect or incomplete experimental interpretations. The types of unintended changes that may occur depend on the allele type being made and the genetic engineering approach used. Here we broadly categorize allele types as deletions, insertions, base changes, and transgenes derived from engineered embryonic stem (ES) cells or edited mouse embryos. However, the methods we describe can be adapted to other allele types and engineering strategies. We describe the sources and consequ ences of common unintended changes and best practices for detecting both intended and unintended changes by screening and genetic and molecular quality control (QC) of chimeras, founders, and their progeny. Employing these practices, along with careful allele design and good colony management, will increase the chance that investigations using genetically engineered mice will produce high-quality reproducible results, to enable a robust understanding of gene function, human disease etiology, and therapeutic development.

Whole-genome identification and construction of the lncRNA-mRNA co-expression network in patients with actinic keratosis

BACKGROUND

Actinic keratosis (AK) is a common premalignant lesion induced by chronic exposure to ultraviolet radiation and may develop into invasive cutaneous squamous carcinoma (cSCC). The identification of specific biomarkers in AK are still unclear. Long non-coding RNAs (lncRNAs), as transcripts of more than 200 nucleotides, significantly involving in multiple biologic processes, especially in the development of tumors.

METHODS

In our study, we obtained data from RNA-sequencing analysis using two AK lesion tissues and three normal cutaneous tissues to comparatively analyze the differentially expressed (DE) lncRNAs and messenger RNAs (mRNAs). Firstly, we used microarray analyses to identify DE lncRNAs and DE mRNAs. Secondly, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to analyze the primary function and find out significant pathways of these DE mRNA and lncRNAs. Finally, we used the top ten DE lncRNAs to construct a lncRNA-mRNA co-expression network.

RESULTS

Our results showed that there were a total of 2,097 DE lncRNAs and 2,043 DE mRNAs identified. GO and KEGG analysis and the lncRNA-mRNA co-expression network (using the top 10 DE lncRNAs comprises 130 specific co-expressed mRNAs to construct) indicated that lncRNA uc011fnr.2 may negatively regulate SCIMP and Toll-like receptor 4 (TLR4) and play an important role in Janus kinase-signal transducer and activator of transcription 3 (JAK-STAT3) signaling pathway of AK.

CONCLUSIONS

lncRNA uc011fnr.2 may play an important role in JAK-STAT3 signaling pathway of AK by modulating SCIMP, TLR4 and IL-6. Further research is required to validate the value of lncRNA uc011fnr.2 in the progression of AK.

Polygenic autoimmune disease risk alleles impacting B cell tolerance act in concert across shared molecular networks in mouse and in humans

Most B cells produced in the bone marrow have some level of autoreactivity. Despite efforts of central tolerance to eliminate these cells, many escape to periphery, where in healthy individuals, they are rendered functionally non-responsive to restimulation through their antigen receptor via a process termed anergy. Broad repertoire autoreactivity may reflect the chances of generating autoreactivity by stochastic use of germline immunoglobulin gene segments or active mechanisms may select autoreactive cells during egress to the naïve peripheral B cell pool. Likewise, it is unclear why in some individuals autoreactive B cell clones become activated and drive pathophysiologic changes in autoimmune diseases. Both of these remain central questions in the study of the immune system(s). In most individuals, autoimmune diseases arise from complex interplay of genetic risk factors and environmental influences. Advances in genome sequencing and increased statistical power from large autoimmune disease cohorts has led to identification of more than 200 autoimmune disease risk loci. It has been observed that autoantibodies are detectable in the serum years to decades prior to the diagnosis of autoimmune disease. Thus, current models hold that genetic defects in the pathways that control autoreactive B cell tolerance set genetic liability thresholds across multiple autoimmune diseases. Despite the fact these seminal concepts were developed in animal (especially murine) models of autoimmune disease, some perceive a disconnect between human risk alleles and those identified in murine models of autoimmune disease. Here, we synthesize the current state of the art in our understanding of human risk alleles in two prototypical autoimmune diseases – systemic lupus erythematosus (SLE) and type 1 diabetes (T1D) along with spontaneous murine disease models. We compare these risk networks to those reported in murine models of these diseases, focusing on pathways relevant to anergy and central tolerance. We highlight some differences between murine and human environmental and genetic factors that may impact autoimmune disease development and expression and may, in turn, explain some of this discrepancy. Finally, we show that there is substantial overlap between the molecular networks that define these disease states across species. Our synthesis and analysis of the current state of the field are consistent with the idea that the same molecular networks are perturbed in murine and human autoimmune disease. Based on these analyses, we anticipate that murine autoimmune disease models will continue to yield novel insights into how best to diagnose, prognose, prevent and treat human autoimmune diseases.

Integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy

Objectives:

The underlying molecular mechanisms of diabetic nephropathy have yet not been investigated clearly. In this investigation, we aimed to identify key genes involved in the pathogenesis and prognosis of diabetic nephropathy.

Methods:

We downloaded next-generation sequencing data set GSE142025 from Gene Expression Omnibus database having 28 diabetic nephropathy samples and nine normal control samples. The differentially expressed genes between diabetic nephropathy and normal control samples were analyzed. Biological function analysis of the differentially expressed genes was enriched by Gene Ontology and REACTOME pathways. Then, we established the protein–protein interaction network, modules, miRNA-differentially expressed gene regulatory network and transcription factor-differentially expressed gene regulatory network. Hub genes were validated by using receiver operating characteristic curve analysis.

Results:

A total of 549 differentially expressed genes were detected including 275 upregulated and 274 downregulated genes. The biological process analysis of functional enrichment showed that these differentially expressed genes were mainly enriched in cell activation, integral component of plasma membrane, lipid binding, and biological oxidations. Analyzing the protein–protein interaction network, miRNA-differentially expressed gene regulatory network and transcription factor-differentially expressed gene regulatory network, we screened hub genes MDFI, LCK, BTK, IRF4, PRKCB, EGR1, JUN, FOS, ALB, and NR4A1 by the Cytoscape software. The receiver operating characteristic curve analysis confirmed that hub genes were of diagnostic value.

Conclusions:

Taken above, using integrated bioinformatics analysis, we have identified key genes and pathways in diabetic nephropathy, which could improve our understanding of the cause and underlying molecular events, and these key genes and pathways might be therapeutic targets for diabetic nephropathy.

De-coding genetic risk variants in type 1 diabetes

The conceptual basis for a genetic predisposition underlying the risk for developing type 1 diabetes (T1D) predates modern human molecular genetics. Over half of the genetic risk has been attributed to the human leukocyte antigen (HLA) class II gene region and to the insulin (INS) gene locus - both thought to confer direction of autoreactivity and tissue specificity. Notwithstanding, questions still remain regarding the functional contributions of a vast array of minor polygenic risk variants scattered throughout the genome that likely influence disease heterogeneity and clinical outcomes. Herein, we summarize the available literature related to the T1D-associated coding variants defined at the time of this review, for the genes PTPN22, IFIH1, SH2B3, CD226, TYK2, FUT2, SIRPG, CTLA4, CTSH and UBASH3A. Data from genotype-selected human cohorts are summarized, and studies from the non-obese diabetic (NOD) mouse are presented to describe the functional impact of these variants in relation to innate and adaptive immunity as well as to β-cell fragility, with expression profiles in tissues and peripheral blood highlighted. The contribution of each variant to progression through T1D staging, including environmental interactions, are discussed with consideration of how their respective protein products may serve as attractive targets for precision medicine-based therapeutics to prevent or suspend the development of T1D.