Weighted Gene Co-Expression Network Analysis Identifies Key Modules and Hub Genes Associated with Mycobacterial Infection of Human Macrophages (original) (raw)
Related papers
Transcriptional landscape of Mycobacterium tuberculosis infection in macrophages
Scientific reports, 2018
Mycobacterium tuberculosis (Mtb) infection reveals complex and dynamic host-pathogen interactions, leading to host protection or pathogenesis. Using a unique transcriptome technology (CAGE), we investigated the promoter-based transcriptional landscape of IFNγ (M1) or IL-4/IL-13 (M2) stimulated macrophages during Mtb infection in a time-kinetic manner. Mtb infection widely and drastically altered macrophage-specific gene expression, which is far larger than that of M1 or M2 activations. Gene Ontology enrichment analysis for Mtb-induced differentially expressed genes revealed various terms, related to host-protection and inflammation, enriched in up-regulated genes. On the other hand, terms related to dis-regulation of cellular functions were enriched in down-regulated genes. Differential expression analysis revealed known as well as novel transcription factor genes in Mtb infection, many of them significantly down-regulated. IFNγ or IL-4/IL-13 pre-stimulation induce additional differ...
bioRxiv (Cold Spring Harbor Laboratory), 2023
Mycobacterium tuberculosis, the causative agent of human tuberculosis (hTB), is currently classed as the thirteenth leading cause of death worldwide. Mycobacterium bovis, a close evolutionary relative of M. tuberculosis, causes bovine tuberculosis (bTB) and is one of the most damaging infectious diseases to livestock agriculture. Previous studies have shown that the pathogenesis of bTB disease is comparable to hTB disease, and that the bovine and human alveolar macrophage (bAM and hAM, respectively) transcriptomes are extensively reprogrammed in response to infection with these intracellular mycobacterial pathogens. However, although M. bovis and M. tuberculosis share over 99% identity at the genome level, the innate immune responses to these pathogens have been shown to be different in human or cattle hosts. In this study, a multi-omics integrative approach was applied to encompass functional genomics and GWAS data sets across the two primary hosts (Bos taurus and Homo sapiens) and both pathogens (M. bovis and M. tuberculosis). Four different experimental infection groups were used, each with parallel non-infected control cells: 1) bAM infected with M. bovis, 2) bAM infected with M. tuberculosis, 3) hAM infected with M. tuberculosis, and 4) human monocyte-derived macrophages (hMDM) infected with M. tuberculosis. RNA-seq data from these experiments 24 hours postinfection (24 hpi) was analysed using three separate computational pipelines: 1) differentially expressed genes, 2) differential gene expression interaction networks, and 3) combined pathway analysis. The results of these analyses were then integrated with high-resolution bovine and human GWAS data sets to detect novel quantitative trait loci (QTLs) for resistance to mycobacterial infection and resilience to disease. Results from this study revealed common and unique response macrophage pathways for both pathogens and identified 32 genes (12 bovine and 20 human) significantly enriched for SNPs associated with disease resistance, the majority of which encode key components of the NF-κB signalling pathway and that also drive formation of the granuloma.
Immunology, 2006
Macrophages play an essential role in the immune response to Mycobacterium tuberculosis (Mtb). Previous transcriptome surveys, by means of micro- and macroarrays, investigated the cellular gene expression profile during the early phases of infection (within 48 hr). However, Mtb remains within the host macrophages for a longer period, continuing to influence the macrophage gene expression and, consequently, the environment in which it persists. Therefore, we studied the transcription patterns of human macrophages for up to 7 days after infection with Mtb. We used a macroarray approach to study 858 human genes involved in immunoregulation, and we confirmed by quantitative real-time reverse transcriptase polymerase chain reaction (q-rt RT-PCR) and by enzyme-linked immunosorbent assay the most relevant modulations. We constantly observed the up-regulation in infected macrophages versus uninfected, of the following genes: interleukin-1β and interleukin-8, macrophage inflammatory protein-1α, growth-related oncogene-β, epithelial cell-derived neutrophil-activating peptide-78, macrophage-derived chemokine, and matrix metalloproteinase-7; whereas macrophage colony-stimulating factor-receptor and CD4 were down-regulated in infected macrophages. Mtb is able to withstand this intense cytokine microenvironment and to survive inside the human macrophage. Therefore we simultaneously investigated by q-rt RT-PCR the modulation of five mycobacterial genes: the alternative sigma factors sigA, sigE and sigG, the α-crystallin (acr) and the superoxide dismutase C (sodC) involved in survival mechanisms. The identified host and mycobacterial genes that were expressed until 7 days after infection, could have a role in the interplay between the host immune defences and the bacterial escape mechanisms.
Frontiers in Immunology, 2014
Mycobacterium bovis is an intracellular pathogen that causes tuberculosis in cattle. Following infection, the pathogen resides and persists inside host macrophages by subverting host immune responses via a diverse range of mechanisms. Here, a high-density bovine microarray platform was used to examine the bovine monocyte-derived macrophage transcriptome response to M. bovis infection relative to infection with the attenuated vaccine strain, M. bovis Bacille Calmette-Guérin. Differentially expressed genes were identified (adjusted P -value ≤0.01) and interaction networks generated across an infection time course of 2, 6, and 24 h. The largest number of biological interactions was observed in the 24-h network, which exhibited scale-free network properties. The 24-h network featured a small number of key hub and bottleneck gene nodes, including IKBKE, MYC, NFKB1, and EGR1 that differentiated the macrophage response to virulent and attenuated M. bovis strains, possibly via the modulation of host cell death mechanisms. These hub and bottleneck genes represent possible targets for immuno-modulation of host macrophages by virulent mycobacterial species that enable their survival within a hostile environment.
Identification of Tuberculosis Susceptibility Genes with Human Macrophage Gene Expression Profiles
PLOS Pathogens, 2008
Although host genetics influences susceptibility to tuberculosis (TB), few genes determining disease outcome have been identified. We hypothesized that macrophages from individuals with different clinical manifestations of Mycobacterium tuberculosis (Mtb) infection would have distinct gene expression profiles and that polymorphisms in these genes may also be associated with susceptibility to TB. We measured gene expression levels of .38,500 genes from ex vivo Mtb-stimulated macrophages in 12 subjects with 3 clinical phenotypes: latent, pulmonary, and meningeal TB (n = 4 per group). After identifying differentially expressed genes, we confirmed these results in 34 additional subjects by real-time PCR. We also used a case-control study design to examine whether polymorphisms in differentially regulated genes were associated with susceptibility to these different clinical forms of TB. We compared gene expression profiles in Mtb-stimulated and unstimulated macrophages and identified 1,608 and 199 genes that were differentially expressed by .2and .5-fold, respectively. In an independent sample set of 34 individuals and a subset of highly regulated genes, 90% of the microarray results were confirmed by RT-PCR, including expression levels of CCL1, which distinguished the 3 clinical groups. Furthermore, 6 single nucleotide polymorphisms (SNPs) in CCL1 were found to be associated with TB in a case-control genetic association study with 273 TB cases and 188 controls. To our knowledge, this is the first identification of CCL1 as a gene involved in host susceptibility to TB and the first study to combine microarray and DNA polymorphism studies to identify genes associated with TB susceptibility. These results suggest that genome-wide studies can provide an unbiased method to identify critical macrophage response genes that are associated with different clinical outcomes and that variation in innate immune response genes regulate susceptibility to TB.
PloS one, 2018
Human alveolar macrophages (HAM) are primary bacterial niche and immune response cells during Mycobacterium tuberculosis (M.tb) infection, and human blood monocyte-derived macrophages (MDM) are a model for investigating M.tb-macrophage interactions. Here, we use a targeted RNA-Seq method to measure transcriptome-wide changes in RNA expression patterns of freshly obtained HAM (used within 6 h) and 6 day cultured MDM upon M.tb infection over time (2, 24 and 72 h), in both uninfected and infected cells from three donors each. The Ion AmpliSeq™ Transcriptome Human Gene Expression Kit (AmpliSeq) uses primers targeting 18,574 mRNAs and 2,228 non-coding RNAs (ncRNAs) for a total of 20,802 transcripts. AmpliSeqTM yields highly precise and reproducible gene expression profiles (R2 >0.99). Taking advantage of AmpliSeq's reproducibility, we establish well-defined quantitative RNA expression patterns of HAM versus MDM, including significant M.tb-inducible genes, in networks and pathways ...
Mycobacterium tuberculosis owes its high pathogenic potential to its ability to evade host immune responses and thrive inside the macrophage. The outcome of infection is largely determined by the cellular response comprising a multitude of molecular events. The complexity and inter-relatedness in the processes makes it essential to adopt systems approaches to study them. In this work, we construct a comprehensive network of infection-related processes in a human macrophage comprising 1888 proteins and 14,016 interactions. We then compute response networks based on available gene expression profiles corresponding to states of health, disease and drug treatment. We use a novel formulation for mining response networks that has led to identifying highest activities in the cell. Highest activity paths provide mechanistic insights into pathogenesis and response to treatment. The approach used here serves as a generic framework for mining dynamic changes in genome-scale protein interaction networks.
Molecular Microbiology
A whole genome co-expression network was created using Mycobacterium tuberculosis transcriptomic data from publicly available RNA-sequencing experiments covering a wide variety of experimental conditions. The network includes expressed regions with no formal annotation, including putative short RNAs and untranslated regions of expressed transcripts, along with the protein-coding genes. These unannotated expressed transcripts were among the best-connected members of the module sub-networks, making up more than half of the 'hub' elements in modules that include protein-coding genes known to be part of regulatory systems involved in stress response and host adaptation. This dataset provides a valuable resource for investigating the role of non-coding RNA, and conserved hypothetical proteins, in transcriptomic remodelling. Based on their connections to genes with known functional groupings and correlations with replicated host conditions, predicted expressed transcripts can be screened as suitable candidates for further experimental validation. Non-coding RNA prediction and quantification Each dataset was run through the R-package, baerhunter (Ozuna et al., 2019), using the 'feature_file_editor' function optimised to the most appropriate parameters for the sequencing depth (https://doi.org/10.5281/zenodo.7709329). 'Count_features' and 'tpm_norm_flagging' functions were used for transcript quantification and to identify low