Correction: Identification and replication of RNA-Seq gene network modules associated with depression severity.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Identification and replication of RNA-Seq gene network modules associated with depression severity.

Genomic variation underlying major depressive disorder (MDD) likely involves the interaction and regulation of multiple genes in a network. Data-driven co-expression network module inference has the potential to account for variation within regulatory networks, reduce the dimensionality of RNA-Seq data, and detect significant gene-expression modules associated with depression severity. We performed an RNA-Seq gene co-expression network analysis of mRNA data obtained from the peripheral blood mononuclear cells of unmedicated MDD (n = 78) and healthy control (n = 79) subjects. Across the combined MDD and HC groups, we assigned genes into modules using hierarchical clustering with a dynamic tree cut method and projected the expression data onto a lower-dimensional module space by computing the single-sample gene set enrichment score of each module. We tested the single-sample scores of each module for association with levels of depression severity measured by the Montgomery-Åsberg Depression Scale (MADRS). Independent of MDD status, we identified 23 gene modules from the co-expression network. Two modules were significantly associated with the MADRS score after multiple comparison adjustment (adjusted p = 0.009, 0.028 at 0.05 FDR threshold), and one of these modules replicated in a previous RNA-Seq study of MDD (p = 0.03). The two MADRS-associated modules contain genes previously implicated in mood disorders and show enrichment of apoptosis and B cell receptor signaling. The genes in these modules show a correlation between network centrality and univariate association with depression, suggesting that intramodular hub genes are more likely to be related to MDD compared to other genes in a module.

IL-18 acts in synergy with IL-7 to promote ex vivo expansion of T lymphoid progenitor cells.

Although IL-18 has not previously been shown to promote T lymphopoiesis, results obtained via a novel data mining algorithm (global microarray meta-analysis) led us to explore a predicted role for this cytokine in T cell development. IL-18 is a member of the IL-1 cytokine family that has been extensively characterized as a mediator of inflammatory immune responses. To assess a potential role for IL-18 in T cell development, we sort-purified mouse bone marrow-derived common lymphoid progenitor cells, early thymic progenitors (ETPs), and double-negative 2 thymocytes and cultured these populations on OP9-Delta-like 4 stromal layers in the presence or absence of IL-18 and/or IL-7. After 1 wk of culture, IL-18 promoted proliferation and accelerated differentiation of ETPs to the double-negative 3 stage, similar in efficiency to IL-7. IL-18 showed synergy with IL-7 and enhanced proliferation of both the thymus-derived progenitor cells and the bone marrow-derived common lymphoid progenitor cells. The synergistic effect on the ETP population was further characterized and found to correlate with increased surface expression of c-Kit and IL-7 receptors on the IL-18-treated cells. In summary, we successfully validated the global microarray meta-analysis prediction that IL-18 affects T lymphopoiesis and demonstrated that IL-18 can positively impact bone marrow lymphopoiesis and T cell development, presumably via interaction with the c-Kit and IL-7 signaling axis.

Inflammation and neurological disease-related genes are differentially expressed in depressed patients with mood disorders and correlate with morphometric and functional imaging abnormalities.

Depressed patients show evidence of both proinflammatory changes and neurophysiological abnormalities such as increased amygdala reactivity and volumetric decreases of the hippocampus and ventromedial prefrontal cortex (vmPFC). However, very little is known about the relationship between inflammation and neuroimaging abnormalities in mood disorders. A whole genome expression analysis of peripheral blood mononuclear cells yielded 12 protein-coding genes (ADM, APBB3, CD160, CFD, CITED2, CTSZ, IER5, NFKBIZ, NR4A2, NUCKS1, SERTAD1, TNF) that were differentially expressed between 29 unmedicated depressed patients with a mood disorder (8 bipolar disorder, 21 major depressive disorder) and 24 healthy controls (HCs). Several of these genes have been implicated in neurological disorders and/or apoptosis. Ingenuity Pathway Analysis yielded two genes networks, one centered around TNF with NFKß, TGFß, and ERK as connecting hubs, and the second network indicating cell cycle and/or kinase signaling anomalies. fMRI scanning was conducted using a backward-masking task in which subjects were presented with emotionally-valenced faces. Compared with HCs, the depressed subjects displayed a greater hemodynamic response in the right amygdala, left hippocampus, and the ventromedial prefrontal cortex to masked sad versus happy faces. The mRNA levels of several genes were significantly correlated with the hemodynamic response of the amygdala, vmPFC and hippocampus to masked sad versus happy faces. Differentially-expressed transcripts were significantly correlated with thickness of the left subgenual ACC, and volume of the hippocampus and caudate. Our results raise the possibility that molecular-level immune dysfunction can be mapped onto macro-level neuroimaging abnormalities, potentially elucidating a mechanism by which inflammation leads to depression.

Ten-color flow cytometry reveals distinct patterns of expression of CD124 and CD126 by developing thymocytes.

BACKGROUND: We have developed a 12-parameter/10-color flow cytometric staining method for the simultaneous detection and characterization of 21 mouse thymocyte subpopulations that represent discreet stages of T cell development. To demonstrate the utility of this method, we assessed cytokine receptor expression on mouse thymocyte subsets. These experiments revealed distinct patterns of surface expression of receptors for the cytokines IL-4 and IL-6. RESULTS: The IL-4 receptor α chain (CD124) was highly expressed on the earliest thymocyte subsets, then downregulated prior to T cell receptor ß-selection and finally upregulated in the CD4/CD8 double positive cells prior to positive selection. The IL-6 receptor α chain (CD126) showed a different pattern of expression. It was expressed on the most mature subsets within the CD4 and CD8 single positive (SP) compartments and was absent on all other thymocytes with the exception of a very small cKit-CD4-CD8- population. Intracellular staining of SP thymocytes for phosphorylated STAT-1 demonstrated that IL-6 signaling was confined to the most mature SP subsets. CONCLUSIONS: This 12-parameter staining methodology uses only commercially available fluorochrome-coupled monoclonal antibodies and therefore could be employed by any investigator with access to a 4-laser flow cytometer. This novel staining scheme allowed us to easily phenotype thymocyte subpopulations that span across development, from the early thymic progenitors (ETPs) to the most mature subsets of the CD4 and CD8 single positive populations.

CD28 expression redefines thymocyte development during the pre-T to DP transition.

CD27 and CD28 have emerged as indicators demarcating the transition of thymocytes through beta-selection. We found that CD28 exhibits a greater dynamic range of expression during this phase, thus it was employed to further parse the DN/CD44(-) compartment in order to assess IL-7 signaling during the beta-selection process. Plotting CD28 versus CD25 expression revealed six DN/CD44(-) populations. OP9-DL1 stromal cell co-culture was used to demonstrate a developmental linkage from DN3a (CD25(+)CD28(-/lo)) to DN3b (CD25(+)CD28(+)) to DN3c (CD25(int)CD28(+)) to DN4a (CD25(-)CD28(+)) to double positive (DP) and showed the DN4b (CD25(-)CD28(hi)) and DN4c (CD25(-)CD28(-/lo)) populations to be inefficient in producing DP cells. Using CD69 as an additional marker to further parse the DN4a population, we found the pre-DP cells to be the CD44(-)CD25(-)CD28(int)CD69(-)CD4(-/lo)CD8(-/lo) subset. Using this refined developmental scheme, IL-7R alpha expression was found to be transiently up-regulated post-beta-selection in the DN3b and DN3c subsets; however, this increase did not confer enhanced responsiveness over that observed in the DN3a population. CD28 messenger RNA expression was up-regulated in post-beta-selected cells, whereas transcripts for CD27, IL-7R alpha and Bcl-2 were lower than that observed in the DN3a population. This study refines the current thymocyte differentiation scheme to allow for more detailed evaluation of events controlling early T-cell development, specifically surrounding the beta-selection checkpoint.

Differential IL-7 responses in developing human thymocytes.

Interleukin (IL)-7 is a factor essential for mouse and human thymopoiesis. Mouse thymocytes have altered sensitivities to IL-7 at different developmental stages. CD4/CD8 double positive (DP) mouse thymocytes are shielded from the influence of IL-7 because of loss of CD127 (IL-7Ralpha). In this study, we assessed IL-7 receptor expression and IL-7 signaling in human thymocytes. We found human DP cells to be severely limited in their ability to phosphorylate STAT-5 in response to IL-7. The relative expression levels of the IL-7-inducible proteins Bcl-2 and Mcl-1 were also lower in human DP cells, consistent with a stage-specific decrease in IL-7 responsiveness. IL-7 responses were restored in a subset of cells that matured past the DP stage. Unlike the regulation of IL-7 signaling in mouse thymocytes, loss of IL-7 signaling in human DP cells was not due to absence of CD127, but instead correlated with downregulation of CD132 (common gamma chain).

Disruption of thymopoiesis in ST6Gal I-deficient mice.

Thymocyte development is accompanied by sequential changes in cell surface glycosylation. For example, medullary thymocytes have increased levels of alpha2,3-linked sialic acid and a loss of asialo core 1 O-glycans as compared to cortical thymocytes. Some of these changes have been linked to fine tuning of the T cell receptor avidity. We analyzed ST6Gal I transcript abundance and levels of alpha2,6-linked sialic acid across thymocyte subsets. We found that ST6Gal I transcript levels increased following T cell receptor beta-selection suggesting that this sialyltransferase may influence the development of early thymocyte populations. Indeed, low levels of alpha2,6-linked sialic acid were found in the earliest T lineage cells, and then increased in T cell receptor beta-selected cells. To determine whether ST6Gal I influences T cell development, we analyzed ST6Gal I-deficient mice for disruptions in thymocyte populations. We found reduced thymic cellularity in the ST6Gal I-deficient mice starting in the early thymocyte compartments.

Impaired thymopoiesis in interleukin-7 receptor transgenic mice is not corrected by Bcl-2.

Murine thymocytes down-regulate IL-7 responsiveness following beta-selection and reacquire sensitivity after positive selection. To assess the potential consequences of IL-7 signaling during this phase of development, transgenic IL-7 receptor alpha (IL-7Ralpha) mice were evaluated for IL-7 responsiveness as gauged by STAT-5 phosphorylation. Transgenic IL-7Ralpha expression increased the percentage of thymocytes responsive to IL-7 yet resulted in a decrease in total thymic cellularity. Aberrant thymocyte development in transgenic mice was first manifested by a reduction of DN3 thymocytes that correlated with lower Bcl-2 expression. Surprisingly, transgenic restoration of Bcl-2 expression did not correct thymic hypocellularity induced by IL-7Ralpha overexpression. These findings demonstrate that failure to appropriately downregulate IL-7Ralpha expression interferes with thymocyte development past the pro-T stage resulting in significantly lower levels of mature thymocytes.

Attenuation of cytokine responsiveness during T cell development and differentiation.

Cytokines play critical roles during T cell development; however, it is unclear to what extent development is altered by the high levels of cytokines produced during immune responses. A potential mechanism to shield developing cells from cytokine influence is attenuation of cytokine signaling. Using intracellular staining and flow cytometry to detect cytokine-induced Stat phosphorylation, we analyzed the cytokine responsiveness of developmentally defined mouse T cells. We assessed CD4(-)CD8(-) (DN), CD4(+)CD8(+) (DP), CD4(+)CD8(-) (SP4), and CD4(-)CD8(+) (SP8) in the thymus, and CD4(+)CD44(lo) (naive), CD4(+)CD44(hi) (memory), CD8(+)CD44(lo) (naive), and CD8(+)CD44(hi) (memory) in the periphery for responsiveness to interleukin-2 (IL-2), IL-4, IL-6, IL-7, IL- 10, IL-15, interferon-alpha (IFN-alpha), and IFN-gamma. SP thymocytes responded to a wider range of cytokines than did the less mature DN and DP subpopulations. DP thymocytes were nonresponsive to all cytokines tested except for modest responses to IL-4 and IFN-alpha. Peripheral naive and memory T cells also displayed differential cytokine sensitivity. Memory T cells were less responsive to the proinflammatory cytokines IL-6 and IFN-gamma when compared with naive T cells, and the memory CD4(+) subset was less responsive to IL-4. In summary, developing thymocytes and memory T cells appear to be resistant to the influences of numerous cytokines produced during immune responses.

Sialyltransferase mRNA abundances in B cells are strictly controlled, correlated with cognate lectin binding, and differentially responsive to immune signaling in vitro.

Mouse gene knockout studies have provided unimpeachable evidence of immune-relevant functions for several sialyltransferase enzymes including ST6Gal I, ST3Gal I, and ST3Gal IV. Such studies cannot, however, identify cellular mechanisms for regulating such activities. In this article we provide evidence that murine B lymphocytes respond to specific immune signals in vitro with tightly regulated changes in the sialic acid composition of the cell surface glycocalyx. These changes are both quantitative and qualitative in nature and are apparently regulated at both the transcriptional and posttranscriptional levels. We used lectin binding and flow cytometry combined with relative real-time PCR to show that MAH and PNA binding are tightly correlated with the abundance of ST3Gal IV and ST3Gal I mRNA, respectively, under several different conditions of B cell stimulation. Finally, we show that although SNA binding and the expression of ST6Gal I coding sequence are not tightly correlated, there is a clear differential control of 5'UTR exon usage in response to different immune signals.

Loss of interferon-induced Stat1 phosphorylation in activated T cells.

Modulation of cytokine responsiveness following T cell activation represents an important mechanism that shapes the fate of T cells after encounters with antigens. We activated T cells in mice with superantigen and assessed their ability to phosphorylate Stat1 in response to interferon-gamma (IFN-gamma) and IFN-alpha. After 4 h of activation in vivo, T cells became deficient in their ability to phosphorylate Stat1 in response to either cytokine. The loss of IFN sensitivity was accompanied by increased mRNA transcription for multiple suppressors of cytokine signaling (SOCS) genes (SOCS1, SOCS3, and SOCS7). The transcript levels of these SOCS were elevated only during the early hours after activation and were at or below normal levels by 60 h. Likewise, the activation-induced inhibition of IFN-alpha signaling was transient, and sensitivity was restored by 3 days postactivation. The loss of sensitivity to IFN-gamma persisted, however, and was still evident at 3 days. These data suggest that SOCS-independent mechanisms specific for inhibition of IFN-gamma signaling may be present at later stages of the T cell response. The loss of Stat1 signaling may be a factor in differentiation of T cells during and after activation, and it could also represent a protective mechanism against the toxic effects of IFN-gamma during immune responses.

Thymocytes between the beta-selection and positive selection checkpoints are nonresponsive to IL-7 as assessed by STAT-5 phosphorylation.

Interleukin-7 is widely accepted as a major homeostatic factor involved in T cell development. To assess the IL-7 responsiveness of thymocytes involved in selection processes, we used a new sensitive flow cytometry-based assay to detect intracellular phosphorylation of STAT-5 induced by IL-7 in defined mouse thymocyte subsets. Using this method, we found the earliest thymocyte subset (CD4(-)CD8(-)CD25(-)CD44(+)) to contain both IL-7-responsive and nonresponsive cells. Transition through the next stages of development (CD4(-)CD8(-)CD25(+)CD44(+ and -)) was associated with responsiveness of all thymocytes within these populations. Passage of thymocytes through beta-selection resulted in a significant reduction in IL-7 sensitivity. In the next phases of development (TCR(-) and TCR(low)CD69(-)), thymocytes were completely insensitive to the effects of IL-7. STAT-5 phosphorylation in response to IL-7 was again observed, however, in thymocytes involved in the positive selection process (TCR(low)CD69(+) and TCR(intermediate)). As expected, CD4 and CD8 single-positive thymocytes were responsive to IL-7. These findings delineate an IL-7-insensitive population between the beta-selection and positive selection checkpoints encompassing thymocytes predicted to die by neglect due to failure of positive selection. This pattern of sensitivity suggests a two-signal mechanism by which survival of thymocytes at these checkpoints is governed.

Accurate and statistically verified quantification of relative mRNA abundances using SYBR Green I and real-time RT-PCR.

Among the many methods currently available for quantifying mRNA transcript abundance, reverse transcription-polymerase chain reaction (RT-PCR) has proved to be the most sensitive. Recently, several protocols for real-time relative RT-PCR using the reporter dye SYBR Green I have appeared in the literature. In these methods, sample and control mRNA abundance is quantified relative to an internal reference RNA whose abundance is known not to change under the differing experimental conditions. We have developed new data analysis procedures for the two most promising of these methodologies and generated data appropriate to assess both the accuracy and precision of the two protocols. We demonstrate that while both methods produce results that are precise when 18S rRNA is used as an internal reference, only one of these methods produces consistently accurate results. We have used this latter system to show that mRNA abundances can be accurately measured and strongly correlate with cell surface protein and carbohydrate expression as assessed by flow cytometry under different conditions of B cell activation.