Super-delta2: An Enhanced Differential Expression Analysis Procedure for Multi-Group Comparisons of RNA-seq Data

Dual activation of estrogen receptor alpha and glucocorticoid receptor upregulate CRTh2-mediated type 2 inflammation; mechanism driving asthma severity in women?

BACKGROUND

Type 2-high asthma is characterized by elevated levels of circulating Th2 cells and eosinophils, cells that express chemoattractant-homologous receptor expressed on Th2 cells (CRTh2). Severe asthma is more common in women than men; however, the underlying mechanism(s) remain elusive. Here we examined whether the relationship between severe asthma and type 2 inflammation differs by sex and if estrogen influences Th2 cell response to glucocorticoid (GC).

METHODS

Type 2 inflammation and the proportion of blood Th2 cells (CD4⁺ CRTh2⁺ ) were assessed in whole blood from subjects with asthma (n = 66). The effects of GC and estrogen receptor alpha (ERα) agonist on in vitro differentiated Th2 cells were examined. Expression of CRTh2, type 2 cytokines and degree of apoptosis (Annexin V⁺ , 7-AAD) were determined by flow cytometry, qRT-PCR, western blot and ELISA.

RESULTS

In severe asthma, the proportion of circulating Th2 cells and hospitalizations were higher in women than men. Women with severe asthma also had more Th2 cells and serum IL-13 than women with mild/moderate asthma. Th2 cells, eosinophils and CRTh2 mRNA correlated with clinical characteristics associated with asthma control in women but not men. In vitro, GC and ERα agonist treated Th2 cells exhibited less apoptosis, more CRTh2 as well as IL-5 and IL-13 following CRTh2 activation than Th2 cells treated with GC alone.

CONCLUSION

Women with severe asthma had higher levels of circulating Th2 cells than men, which may be due to estrogen modifying the effects of GC, enhancing Th2 cell survival and type 2 cytokine production.

IFIH1/IRF1/STAT1 promotes sepsis associated inflammatory lung injury via activating macrophage M1 polarization

BACKGROUND

A growing body of research has shown that the phenotypic change in macrophages from M0 to M1 is essential for the start of the inflammatory process in septic acute respiratory distress syndrome (ARDS). Potential treatment targets might be identified with more knowledge of the molecular regulation of M1 macrophages in septic ARDS.

METHODS

A multi-microarray interrelated analysis of high-throughput experiments from ARDS patients and macrophage polarization was conducted to identify the hub genes associated with macrophage M1 polarization and septic ARDS. Lipopolysaccharide (LPS) and Poly (I:C) were utilized to stimulate bone marrow-derived macrophages (BMDMs) for M1-polarized macrophage model construction. Knock down of the hub genes on BMDMs via shRNAs was used to screen the genes regulating macrophage M1 polarization in vitro. The cecal ligation and puncture (CLP) mouse model was constructed in knockout (KO) mice and wild-type (WT) mice to explore whether the screened genes regulate macrophage M1 polarization in septic ARDS in vivo. ChIP-seq and further experiments on BMDMs were performed to investigate the molecular mechanism.

RESULTS

The bioinformatics analysis of gene expression profiles from a clinical cohort of 26 ARDS patients and macrophage polarization found that the 5 hub genes (IFIH1, IRF1, STAT1, IFIT3, GBP1) may have a synergistic effect on macrophage M1 polarization in septic ARDS. Further in vivo investigations indicated that IFIH1, STAT1 and IRF1 contribute to macrophage M1 polarization. The histological evaluation and immunohistochemistry of the lungs from the IRF1^-/- and WT mice indicated that knockout of IRF1 markedly alleviated CLP-induced lung injury and M1-polarized infiltration. Moreover, the molecular mechanism investigations indicated that knockdown of IFIH1 markedly promoted IRF1 translocation into the nucleus. Knockout of IRF1 significantly decreases the expression of STAT1. ChIP-seq and PCR further confirmed that IRF1, as a transcription factor of STAT1, binds to the promoter region of STAT1.

CONCLUSION

IRF1 was identified as the key molecule that regulates macrophage M1polarization and septic ARDS development in vivo and in vitro. Moreover, as the adaptor in response to infection mimics irritants, IFIH1 promotes IRF1 (transcription factor) translocation into the nucleus to initiate STAT1 transcription.

FastMix: a versatile data integration pipeline for cell type-specific biomarker inference

MOTIVATION

Flow cytometry (FCM) and transcription profiling are the two widely used assays in translational immunology research. However, there is no data integration pipeline for analyzing these two types of assays together with experiment variables for biomarker inference. Current FCM data analysis mainly relies on subjective manual gating analysis, which is difficult to be directly integrated with other automated computational methods. Existing deconvolutional analysis of bulk transcriptomics relies on predefined marker genes in the transcriptomics data, which are unavailable for novel cell types and does not utilize the FCM data that provide canonical phenotypic definitions of the cell types.

RESULTS

We developed a novel analytics pipeline-FastMix-for computational immunology, which integrates flow cytometry, bulk transcriptomics and clinical covariates for identifying cell type-specific gene expression signatures and biomarker genes. FastMix addresses the 'large p, small n' problem in the gene expression and flow cytometry integration analysis via a linear mixed effects model (LMER) for both cross-sectional and longitudinal studies. Its novel moment-based estimator not only reduces bias in parameter estimation but also is more efficient than iterative optimization. The FastMix pipeline also includes a cutting-edge flow cytometry data analysis method-DAFi-for identifying cell populations of interest and their characteristics. Simulation studies showed that FastMix produced smaller type I/II errors than competing methods. Validation using real data of two vaccine studies showed that FastMix identified a consistent set of signature genes as in independent single-cell RNA-seq analysis, producing additional interesting findings.

AVAILABILITY AND IMPLEMENTATION

Source code of FastMix is publicly available at https://github.com/terrysun0302/FastMix.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Orthodenticle homeobox OTX1 is a potential prognostic biomarker for bladder cancer

Bladder cancer (BC) is one of the most aggressive tumors worldwide. OTX1 (orthodenticle homeobox 1) is an important transcription factor involved in various diseases, such as cancers. The aim of this study was to further investigate the role of OTX1 in BC. In this study, differentially expressed genes (DEGs) were screened from tumor tissues and para-cancerous tissues by bioinformatics. The expression of protein and RNA was separately detected by western blotting and immunohistochemistry (IHC), and quantitative polymerase chain reaction (qPCR); cell viability and cell growth were determined by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and clone formation assays, respectively; cell motility was measured by transwell and wound healing assays; cell cycle was measured by flow cytometry. In this study, 9 DEGs were screened out, and OTX1 was employed as a candidate gene for subsequent study. Results found that OTX1 was highly expressed in BC cells and BC tissues, which was significantly associated with poor prognosis of patients. In addition, OTX1 silencing significantly reduced cell viability, and inhibited cell growth and motility, while OTX1 overexpression got opposite results. Moreover, OTX1 co-expressed genes were enriched in cell cycle-related pathways, suggesting that the role of OTX1 in BC may be related to cell cycle, which was confirmed by flow cytometry analysis. Furthermore, in vivo experiments showed that OTX1 silencing significantly inhibited tumor growth in tumor-bearing mice. Taken together, our findings suggested that OTX1 may play a promotional role in BC progression.