Tarmo Äijö

Modulation of TET2 expression and 5-methylcytosine oxidation by the CXXC domain protein IDAX

TET (ten-eleven-translocation) proteins are Fe(ii)- and α-ketoglutarate-dependent dioxygenases that modify the methylation status of DNA by successively oxidizing 5-methylcytosine to 5-hydroxymethylcytosine, 5-formylcytosine and 5-carboxycytosine, potential intermediates in the active erasure of DNA-methylation marks. Here we show that IDAX (also known as CXXC4), a reported inhibitor of Wnt signalling that has been implicated in malignant renal cell carcinoma and colonic villous adenoma, regulates TET2 protein expression. IDAX was originally encoded within an ancestral TET2 gene that underwent a chromosomal gene inversion during evolution, thus separating the TET2 CXXC domain from the catalytic domain. The IDAX CXXC domain binds DNA sequences containing unmethylated CpG dinucleotides, localizes to promoters and CpG islands in genomic DNA and interacts directly with the catalytic domain of TET2. Unexpectedly, IDAX expression results in caspase activation and TET2 protein downregulation, in a manner that depends on DNA binding through the IDAX CXXC domain, suggesting that IDAX recruits TET2 to DNA before degradation. IDAX depletion prevents TET2 downregulation in differentiating mouse embryonic stem cells, and short hairpin RNA against IDAX increases TET2 protein expression in the human monocytic cell line U937. Notably, we find that the expression and activity of TET3 is also regulated through its CXXC domain. Taken together, these results establish the separate and linked CXXC domains of TET2 and TET3, respectively, as previously unknown regulators of caspase activation and TET enzymatic activity.

The transcription factor NFAT promotes exhaustion of activated CD8⁺ T cells.

During persistent antigen stimulation, CD8(+) T cells show a gradual decrease in effector function, referred to as exhaustion, which impairs responses in the setting of tumors and infections. Here we demonstrate that the transcription factor NFAT controls the program of T cell exhaustion. When expressed in cells, an engineered form of NFAT1 unable to interact with AP-1 transcription factors diminished T cell receptor (TCR) signaling, increased the expression of inhibitory cell surface receptors, and interfered with the ability of CD8(+) T cells to protect against Listeria infection and attenuate tumor growth in vivo. We defined the genomic regions occupied by endogenous and engineered NFAT1 in primary CD8(+) T cells and showed that genes directly induced by the engineered NFAT1 overlapped with genes expressed in exhausted CD8(+) T cells in vivo. Our data show that NFAT promotes T cell anergy and exhaustion by binding at sites that do not require cooperation with AP-1.

Control of Foxp3 stability through modulation of TET activity

TET2 and TET3 redundantly regulate Foxp3 stability, and their activity can be modulated by vitamin C.

Dissecting the dynamic changes of 5-hydroxymethylcytosine in T-cell development and differentiation

Significance 5-Hydroxymethylcytosine (5hmC) is an epigenetic DNA modification produced through the enzymatic activity of TET proteins. Here we present the first genome-wide mapping of 5hmC in T cells during sequential steps of lineage commitment in the thymus and the periphery (thymic DP, CD4 SP, and CD8 SP cells; peripheral naive CD8 and CD4 T cells; and in vitro-differentiated Th1 and Th2 cells). We show that 5hmC is enriched at gene bodies and cell type-specific enhancers, that its levels in the gene body correlate strongly with gene expression and histone modifications, and that its levels change dynamically during the course of T-cell development and differentiation. Our analysis will facilitate increased understanding of the role of 5hmC in T-cell development and differentiation. The discovery of Ten Eleven Translocation proteins, enzymes that oxidize 5-methylcytosine (5mC) in DNA, has revealed novel mechanisms for the regulation of DNA methylation. We have mapped 5-hydroxymethylcytosine (5hmC) at different stages of T-cell development in the thymus and T-cell differentiation in the periphery. We show that 5hmC is enriched in the gene body of highly expressed genes at all developmental stages and that its presence correlates positively with gene expression. Further emphasizing the connection with gene expression, we find that 5hmC is enriched in active thymus-specific enhancers and that genes encoding key transcriptional regulators display high intragenic 5hmC levels in precursor cells at those developmental stages where they exert a positive effect. Our data constitute a valuable resource that will facilitate detailed analysis of the role of 5hmC in T-cell development and differentiation.

Learning gene regulatory networks from gene expression measurements using non-parametric molecular kinetics

MOTIVATIONnRegulation of gene expression is fundamental to the operation of a cell. Revealing the structure and dynamics of a gene regulatory network (GRN) is of great interest and represents a considerably challenging computational problem. The GRN estimation problem is complicated by the fact that the number of gene expression measurements is typically extremely small when compared with the dimension of the biological system. Further, because the gene regulation process is intrinsically complex, commonly used parametric models can provide too simple description of the underlying phenomena and, thus, can be unreliable. In this article, we propose a novel methodology for the inference of GRNs from time-series and steady-state gene expression measurements. The presented framework is based on the use of Bayesian analysis with ordinary differential equations (ODEs) and non-parametric Gaussian process modeling for the transcriptional-level regulation.nnnRESULTSnThe performance of the proposed structure inference method is evaluated using a recently published in vivo dataset. By comparing the obtained results with those of existing ODE- and Bayesian-based inference methods we demonstrate that the proposed method provides more accurate network structure learning. The predictive capabilities of the method are examined by splitting the dataset into a training set and a test set and by predicting the test set based on the training set.nnnAVAILABILITYnA MATLAB implementation of the method will be available from http://www.cs.tut.fi/~aijo2/gp upon publication.

MicroRNA-directed program of cytotoxic CD8+ T-cell differentiation

Significance Development of cytotoxic T lymphocytes (CTLs) from activated CD8+ T cells is a key step of the antiviral immune response and is marked by the up-regulation of lytic molecules (perforin, granzymes). How this process is regulated at the posttranscriptional level is still largely unknown. Here we report that Dicer and microRNAs (miRNAs) restrict the expression of lytic molecules in mouse and human CTLs, and describe a unique signaling network that controls the expression of perforin, eomesodermin, and the IL-2Rα chain (CD25) downstream of IL-2 and inflammatory signals through miR-139 and miR-150 in differentiating CTLs. Acquisition of effector properties is a key step in the generation of cytotoxic T lymphocytes (CTLs). Here we show that inflammatory signals regulate Dicer expression in CTLs, and that deletion or depletion of Dicer in mouse or human activated CD8+ T cells causes up-regulation of perforin, granzymes, and effector cytokines. Genome-wide analysis of microRNA (miR, miRNA) changes induced by exposure of differentiating CTLs to IL-2 and inflammatory signals identifies miR-139 and miR-150 as components of an miRNA network that controls perforin, eomesodermin, and IL-2Rα expression in differentiating CTLs and whose activity is modulated by IL-2, inflammation, and antigenic stimulation. Overall, our data show that strong IL-2R and inflammatory signals act through Dicer and miRNAs to control the cytolytic program and other aspects of effector CTL differentiation.

Identification of early gene expression changes during human Th17 cell differentiation

Th17 cells play an essential role in the pathogenesis of autoimmune and inflammatory diseases. Most of our current understanding on Th17 cell differentiation relies on studies carried out in mice, whereas the molecular mechanisms controlling human Th17 cell differentiation are less well defined. In this study, we identified gene expression changes characterizing early stages of human Th17 cell differentiation through genome-wide gene expression profiling. CD4(+) cells isolated from umbilical cord blood were used to determine detailed kinetics of gene expression after initiation of Th17 differentiation with IL1β, IL6, and TGFβ. The differential expression of selected candidate genes was further validated at protein level and analyzed for specificity in initiation of Th17 compared with initiation of other Th subsets, namely Th1, Th2, and iTreg. This first genome-wide profiling of transcriptomics during the induction of human Th17 differentiation provides a starting point for defining gene regulatory networks and identifying new candidates regulating Th17 differentiation in humans.

Methods for time series analysis of RNA-seq data with application to human Th17 cell differentiation

Motivation: Gene expression profiling using RNA-seq is a powerful technique for screening RNA species’ landscapes and their dynamics in an unbiased way. While several advanced methods exist for differential expression analysis of RNA-seq data, proper tools to anal.yze RNA-seq time-course have not been proposed. Results: In this study, we use RNA-seq to measure gene expression during the early human T helper 17 (Th17) cell differentiation and T-cell activation (Th0). To quantify Th17-specific gene expression dynamics, we present a novel statistical methodology, DyNB, for analyzing time-course RNA-seq data. We use non-parametric Gaussian processes to model temporal correlation in gene expression and combine that with negative binomial likelihood for the count data. To account for experiment-specific biases in gene expression dynamics, such as differences in cell differentiation efficiencies, we propose a method to rescale the dynamics between replicated measurements. We develop an MCMC sampling method to make inference of differential expression dynamics between conditions. DyNB identifies several known and novel genes involved in Th17 differentiation. Analysis of differentiation efficiencies revealed consistent patterns in gene expression dynamics between different cultures. We use qRT-PCR to validate differential expression and differentiation efficiencies for selected genes. Comparison of the results with those obtained via traditional timepoint-wise analysis shows that time-course analysis together with time rescaling between cultures identifies differentially expressed genes which would not otherwise be detected. Availability: An implementation of the proposed computational methods will be available at http://research.ics.aalto.fi/csb/software/ Contact: tarmo.aijo@aalto.fi or harri.lahdesmaki@aalto.fi Supplementary information: Supplementary data are available at Bioinformatics online.

Heterogeneous nuclear ribonucleoprotein L-like (hnRNPLL) and elongation factor, RNA polymerase II, 2 (ELL2) are regulators of mRNA processing in plasma cells

B cells and plasma cells possess distinct RNA processing environments that respectively promote the expression of membrane-associated Ig by B cells versus the secretion of Ig by plasma cells. Through a combination of transcriptional profiling and screening using a lentiviral short-hairpin RNA interference library, we show that both the splicing factor hnRNPLL and the transcription elongation factor ELL2 modulate the ratio of secreted versus membrane-encoding Ighg2b transcripts in MPC11 plasmacytoma cell lines. hnRNPLL and ELL2 are both highly expressed in primary plasma cells relative to B cells, but hnRNPLL binds Ighg2b mRNA transcripts and promotes an increase in levels of the membrane-encoding Ighg2b isoform at the expense of the secreted Ighg2b isoform, whereas ELL2 counteracts this effect and drives Ig secretion by increasing the frequency of the secreted Ighg2b isoform. As in T cells, hnRNPLL also alters the splicing pattern of mRNA encoding the adhesion receptor CD44, promoting exon inclusion, and decreasing the overall level of CD44 expression. Further characterization of ELL2-dependent transcription by RNA-Seq revealed that ∼12% of transcripts expressed by plasma cells were differentially processed because of the activities of ELL2, including B-cell maturation antigen BCMA, a receptor with a defined role in plasma cell survival. Taken together, our data identify hnRNPLL and ELL2 as regulators of pre-mRNA processing in plasma cells.

The microRNA miR-31 inhibits CD8+ T cell function in chronic viral infection

During infection, antigen-specific T cells undergo tightly regulated developmental transitions controlled by transcriptional and post-transcriptional regulation of gene expression. We found that the microRNA miR-31 was strongly induced by activation of the T cell antigen receptor (TCR) in a pathway involving calcium and activation of the transcription factor NFAT. During chronic infection with lymphocytic choriomeningitis virus (LCMV) clone 13, miR-31-deficent mice recovered from clinical disease, while wild-type mice continued to show signs of disease. This disease phenotype was explained by the presence of larger numbers of cytokine-secreting LCMV-specific CD8+ T cells in miR-31-deficent mice than in wild-type mice. Mechanistically, miR-31 increased the sensitivity of T cells to type I interferons, which interfered with effector T cell function and increased the expression of several proteins related to T cell dysfunction during chronic infection. These studies identify miR-31 as an important regulator of T cell exhaustion in chronic infection.