Genome-wide siRNA screen of genes regulating the LPS-induced TNF-α response in human macrophages

Identification of potential crucial genes and biomarkers from neutrophils in sepsis using bioinformatics analysis

Sepsis is a complex series of immune responses to infection and is commonly associated with acquired immunodeficiency. The current study aimed to identify the biomarkers of sepsis. Differential expression analysis and protein-protein interaction analysis were conducted to explore potential biomarkers. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes analysis were performed to explore potential mechanisms. The Immune Cell Abundance Identifier website was utilized to evaluate immune cell infiltration in the whole blood. Receiver operating characteristic curve and area under the curve were applied to compare the prognostic accuracy of hub genes. Six genes were selected via differentially expressed gene analysis and protein-protein interaction analysis. Furthermore, CTSD, GADD45A, MAPK14, MMP9, and VIM were selected via validation analysis of independent datasets. Immune infiltration analysis showed that CTSD, GADD45A, MAPK14, MMP9, and VIM may regulate immune cells via neutrophils. Patients with sepsis had a significantly higher expression of CTSD, GADD45A, MAPK14, MMP9, and VIM than normal health controls. The area under the curve of CTSD, GADD45A, MAPK14, MMP9, and VIM were 0.90 (0.83-0.97), 0.89 (0.81-0.96), 0.91 (0.84-0.87), 0.95 (0.91-1.00), and 0.95 (0.91-1.00), respectively. According to the validation result of RT-PCR, only MAPK14 was significantly upregulated compared with controls, which was concordant with the bioinformatics analysis results. This study identified several potential diagnostic genes including CTSD, GADD45A, MAPK14, MMP9, and VIM. These genes may regulate the expression of immune cells via neutrophils in the development of sepsis.

IFIT1 Exerts Opposing Regulatory Effects on the Inflammatory and Interferon Gene Programs in LPS-Activated Human Macrophages

Activation of the TLR4 signaling pathway by lipopolysaccharide (LPS) leads to induction of both inflammatory and interferon-stimulated genes, but the mechanisms through which these coordinately activated transcriptional programs are balanced to promote an optimal innate immune response remain poorly understood. In a genome-wide small interfering RNA (siRNA) screen of the LPS-induced tumor necrosis factor α (TNF-α) response in macrophages, we identify the interferon-stimulated protein IFIT1 as a negative regulator of the inflammatory gene program. Transcriptional profiling further identifies a positive regulatory role for IFIT1 in type I interferon expression, implicating IFIT1 as a reciprocal modulator of LPS-induced gene classes. We demonstrate that these effects of IFIT1 are mediated through modulation of a Sin3A-HDAC2 transcriptional regulatory complex at LPS-induced gene loci. Beyond the well-studied role of cytosolic IFIT1 in restricting viral replication, our data demonstrate a function for nuclear IFIT1 in differential transcriptional regulation of separate branches of the LPS-induced gene program.

Multi-Omics Strategies Uncover Host-Pathogen Interactions

With the success of the Human Genome Project, large-scale systemic projects became a reality that enabled rapid development of the systems biology field. Systems biology approaches to host-pathogen interactions have been instrumental in the discovery of some specifics of Gram-negative bacterial recognition, host signal transduction, and immune tolerance. However, further research, particularly using multi-omics approaches, is essential to untangle the genetic, immunologic, (post)transcriptional, (post)translational, and metabolic mechanisms underlying progression from infection to clearance of microbes. The key to understanding host-pathogen interactions lies in acquiring, analyzing, and modeling multimodal data obtained through integrative multi-omics experiments. In this article, we will discuss how multi-omics analyses are adding to our understanding of the molecular basis of host-pathogen interactions and systemic maladaptive immune response of the host to microbes and microbial products.

Using a Systems Biology Approach To Study Host-Pathogen Interactions

The rapid development of genomics and other "-omics" approaches has significantly impacted how we have investigated host-pathogen interactions since the turn of the millennium. Technologies such as next-generation sequencing, stem cell biology, and high-throughput proteomics have transformed the scale and sensitivity with which we interrogate biological samples. These approaches are impacting experimental design in the laboratory and transforming clinical management in health care systems. Here, we review this area from the perspective of research on bacterial pathogens.

Mass Spectrometry-based Structural Analysis and Systems Immunoproteomics Strategies for Deciphering the Host Response to Endotoxin

One cause of sepsis is systemic maladaptive immune response of the host to bacteria and specifically, to Gram-negative bacterial outer-membrane glycolipid lipopolysaccharide (LPS). On the host myeloid cell surface, proinflammatory LPS activates the innate immune system via Toll-like receptor-4/myeloid differentiation factor-2 complex. Intracellularly, LPS is also sensed by the noncanonical inflammasome through caspase-11 in mice and 4/5 in humans. The minimal functional determinant for innate immune activation is the membrane anchor of LPS called lipid A. Even subtle modifications to the lipid A scaffold can enable, diminish, or abolish immune activation. Bacteria are known to modify their LPS structure during environmental stress and infection of hosts to alter cellular immune phenotypes. In this review, we describe how mass spectrometry-based structural analysis of endotoxin helped uncover major determinations of molecular pathogenesis. Through characterization of LPS modifications, we now better understand resistance to antibiotics and cationic antimicrobial peptides, as well as how the environment impacts overall endotoxin structure. In addition, mass spectrometry-based systems immunoproteomics approaches can assist in elucidating the immune response against LPS. Many regulatory proteins have been characterized through proteomics and global/targeted analysis of protein modifications, enabling the discovery and characterization of novel endotoxin-mediated protein translational modifications.

Multidimensional pooled shRNA screens in human THP-1 cells identify candidate modulators of macrophage polarization

Macrophages are key cell types of the innate immune system regulating host defense, inflammation, tissue homeostasis and cancer. Within this functional spectrum diverse and often opposing phenotypes are displayed which are dictated by environmental clues and depend on highly plastic transcriptional programs. Among these the 'classical' (M1) and 'alternative' (M2) macrophage polarization phenotypes are the best characterized. Understanding macrophage polarization in humans may reveal novel therapeutic intervention possibilities for chronic inflammation, wound healing and cancer. Systematic loss of function screening in human primary macrophages is limited due to lack of robust gene delivery methods and limited sample availability. To overcome these hurdles we developed cell-autonomous assays using the THP-1 cell line allowing genetic screens for human macrophage phenotypes. We screened 648 chromatin and signaling regulators with a pooled shRNA library for M1 and M2 polarization modulators. Validation experiments confirmed the primary screening results and identified OGT (O-linked N-acetylglucosamine (GlcNAc) transferase) as a novel mediator of M2 polarization in human macrophages. Our approach offers a possible avenue to utilize comprehensive genetic tools to identify novel candidate genes regulating macrophage polarization in humans.

Knocking down the obstacles to functional genomics data sharing

This week, Scientific Data published a collection of eight papers that describe datasets from high-throughput functional genomics screens, primarily utilizing RNA interference (RNAi). The publications explore host-pathogen dependencies, innate immune response, disease pathways, and cell morphology and motility at the genome-level. All data, including raw images from the high content screens, are publically available in PubChem BioAssay, figshare, Harvard Dataverse or the Image Data Resource (IDR). Detailed data descriptors enable use of these data for analysis algorithm design, machine learning, data comparisons, as well as generating new scientific hypotheses.