Mapping genetic determinants of host susceptibility to Pseudomonas aeruginosa lung infection in mice

Identification of potential immune/diagnosis related gene-immunocyte subtype networks in extracellular immune response to respiratory syncytial virus infection

INTRODUCTION

Respiratory syncytial virus (RSV) is one of the important pathogenic agents of pediatric respiratory tract infection. Weighted gene co-expression network analysis (WGCNA) is used to study autoimmune diseases, which can find potential hub genes. The diagnostic model based on hub genes and machine learning makes it possible to diagnose the extracellular immune response to RSV infection early.

OBJECTIVE

The aim of the present study was to identify potential immune, diagnose and treatment related genes expressed in RSV-infected cells.

METHODS

Firstly, gene expression data were downloaded from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). Secondly, WGCNA was performed based on DEGs to obtain hub genes related to immunity score. Thirdly, protein-protein interaction (PPI) and the immune infiltration analysis of hub immune related genes were performed. Finally, diagnostic and immune related genes were identified by machine learning, followed by functional analysis.

RESULTS

Totally, 2063 DEGs were identified in the extracellular immune response to RSV infection. Among which, 10 key immune and diagnosis related genes were identified, including ITGA2B, GP9, ITGB3, SELP, PPBP, MPL, CXCL8, NFE2, PTGS1 and LY6G6F. Several immune/diagnosis related gene-immunocyte subtype networks were identified, such as CXCL8-Type 17 T helper cell, LY6G6F-CD56 bright natural killer cell, PPBP-activated CD4 T cell/T follicular helper cell, NFE2/PTGS1/SELP-activated dendritic cell, GP9/ITGA2B/MPL-activated CD8 T cell. ITGB3, MPL and PTGS1 could be considered as therapeutic targets. Some significantly enriched signaling pathways were identified, including hematopoietic cell lineage (involving GP9 and ITGA2B), cytokine-cytokine receptor interaction (involving MPL), chemokine signaling pathway (involving PPBP) and arachidonic acid metabolism (involving PTGS1).

CONCLUSIONS

The 10-immune related gene signature may be used as potential diagnostic markers for the extracellular immune response to RSV infection, which may provide a new field in searching for diagnostic and therapeutic molecules in the extracellular immune response to RSV infection.

Langerin-expressing dendritic cells in pulmonary immune-related diseases

Dendritic cells (DCs) are “frontline” immune cells dedicated to antigen presentation. They serve as an important bridge connecting innate and adaptive immunity, and express various receptors for antigen capture. DCs are divided into various subclasses according to their differential expression of cell surface receptors and different subclasses of DCs exhibit specific immunological characteristics. Exploring the common features of each sub-category has became the focus of many studies. There are certain amounts of DCs expressing langerin in airways and peripheral lungs while the precise mechanism by which langerin⁺ DCs drive pulmonary disease is unclear. Langerin-expressing DCs can be further subdivided into numerous subtypes based on the co-expressed receptors, but here, we identify commonalities across these subtypes that point to the major role of langerin. Better understanding is required to clarify key disease pathways and determine potential new therapeutic approaches.

Glucose-Potentiated Amikacin Killing of Cefoperazone/Sulbactam Resistant Pseudomonas aeruginosa

Multidrug-resistant Pseudomonas aeruginosa has become one of global threat pathogens for human health due to insensitivity to antibiotics. Recently developed reprogramming metabolomics can identify biomarkers, and then, the biomarkers were used to revert the insensitivity and elevate antibiotic-mediated killing. Here, the methodology was used to study cefoperazone/sulbactam (SCF)-resistant P. aeruginosa (PA-R_SCF) and identified reduced glycolysis and pyruvate cycle, a recent clarified cycle providing respiratory energy in bacteria, as the most key enriched pathways and the depressed glucose as one of the most crucial biomarkers. Further experiments showed that the depression of glucose was attributed to reduction of glucose transport. However, exogenous glucose reverted the reduction to elevate intracellular glucose via activating glucose transport. The elevated glucose fluxed to the glycolysis, pyruvate cycle, and electron transport chain to promote downstream proton motive force (PMF). Consistently, exogenous glucose did not promote SCF-mediated elimination but potentiated aminoglycosides-mediated killing since aminoglycosides uptake is PMF-dependent, where amikacin was the best one. The glucose-potentiated amikacin-mediated killing was effective to both lab-evolved PA-R_SCF and clinical multidrug-resistant P. aeruginosa. These results reveal the depressed glucose uptake causes the reduced intracellular glucose and expand the application of metabolome-reprogramming on selecting conventional antibiotics to achieve the best killing efficacy.

Extract From Tetrastigma hemsleyanum Leaf Alleviates Pseudomonas aeruginosa Lung Infection: Network Pharmacology Analysis and Experimental Evidence

Tetrastigma hemsleyanum Diels & Gilg (T. hemsleyanum) has attracted much attention due to its ability on pneumonia, bronchitis, and immune-related diseases, while its functional components and underlying mechanism of action on pneumonia have not been fully elucidated. Herein, we used a systematic network pharmacology approach to explore the action mechanism of T. hemsleyanum leaf in the treatment of pneumonia. In this study, the results of network pharmacology demonstrated that there were 34 active components and 80 drug-disease targets in T. hemsleyanum leaf, which were strongly in connection with signal transduction, inflammatory response, and the oxidation-reduction process. Subsequently, a mouse model of pneumonia induced by Pseudomonas aeruginosa (P. aeruginosa) was established to validate the predicted results of network pharmacology. In the animal experiments, aqueous extract of T. hemsleyanum leaf (EFT) significantly attenuated the histopathological changes of lung tissue in P. aeruginosa-induced mice and reduced the number of bacterial colonies in BALFs by 96.84% (p < 0.01). Moreover, EFT treatment suppressed the increase of pro-inflammatory cytokines IL-17, IL-6, and TNF-α in lung tissues triggered by P. aeruginosa, which led to the increase of Th17 cells (p < 0.05). High concentration of EFT treatment (2.0 g/kg) obviously increased the anti-inflammatory cytokine levels, accompanied by the enhancement of Treg proportion in a dose-dependent manner and a notable reversal of transcription factor RORγt expression. These findings demonstrated that network pharmacology was a useful tool for TCM research, and the anti-inflammatory effect of EFT was achieved by maintaining Th17/Treg immune homeostasis and thereby suppressing the inflammatory immune response.

Collaborative Cross Mice Yield Genetic Modifiers for Pseudomonas aeruginosa Infection in Human Lung Disease

Respiratory infection caused by P. aeruginosa is one of the most critical health burdens worldwide. People affected by P. aeruginosa infection include patients with a weakened immune system, such as those with cystic fibrosis (CF) genetic disease or non-CF bronchiectasis. Disease outcomes range from fatal pneumonia to chronic life-threatening infection and inflammation leading to the progressive deterioration of pulmonary function. The development of these respiratory infections is mediated by multiple causes. However, the genetic factors underlying infection susceptibility are poorly known and difficult to predict. Our study employed novel approaches and improved mouse disease models to identify genetic modifiers that affect the severity of P. aeruginosa lung infection. We identified candidate genes to enhance our understanding of P. aeruginosa infection in humans and provide a proof of concept that could be exploited for other human pathologies mediated by bacterial infection.

Human genetics influence a range of pathological and clinical phenotypes in respiratory infections; however, the contributions of disease modifiers remain underappreciated. We exploited the Collaborative Cross (CC) mouse genetic-reference population to map genetic modifiers that affect the severity of Pseudomonas aeruginosa lung infection. Screening for P. aeruginosa respiratory infection in a cohort of 39 CC lines exhibits distinct disease phenotypes ranging from complete resistance to lethal disease. Based on major changes in the survival times, a quantitative-trait locus (QTL) was mapped on murine chromosome 3 to the genomic interval of Mb 110.4 to 120.5. Within this locus, composed of 31 protein-coding genes, two candidate genes, namely, dihydropyrimidine dehydrogenase (Dpyd) and sphingosine-1-phosphate receptor 1 (S1pr1), were identified according to the level of genome-wide significance and disease gene prioritization. Functional validation of the S1pr1 gene by pharmacological targeting in C57BL/6NCrl mice confirmed its relevance in P. aeruginosa pathophysiology. However, in a cohort of Canadian patients with cystic fibrosis (CF) disease, regional genetic-association analysis of the syntenic human locus on chromosome 1 (Mb 97.0 to 105.0) identified two single-nucleotide polymorphisms (rs10875080 and rs11582736) annotated to the Dpyd gene that were significantly associated with age at first P. aeruginosa infection. Thus, there is evidence that both genes might be implicated in this disease. Our results demonstrate that the discovery of murine modifier loci may generate information that is relevant to human disease progression.

Docking protein-1 promotes inflammatory macrophage signaling in gastric cancer

Docking protein-1 (DOK1) is a tumor suppressor frequently lost in malignant cells, however, it retains the ability to control activities of immune receptors in adjacent stroma cells of the tumor microenvironment. We therefore hypothesized that addressing DOK1 may be useful for cancer immunotherapy. DOK1 mRNA and DOK1 protein expression were downregulated in tumor cells of gastric cancer patients (n = 249). Conversely, its expression was up-regulated in cases positive for Epstein Barr Virus (EBV+) together with genes related to macrophage biology and targets of clinical immunotherapy such as programmed-cell-death-ligand-1 (PD-L1). Notably, high DOK1 positivity in stroma cells conferred poor prognosis in patients and correlated with high levels of inducible nitric oxide synthase in CD68+ tumor-associated macrophages. In macrophages derived from human monocytic leukemia cell lines, DOK1 (i) was inducible by agonists of the anti-diabetic transcription factor peroxisome proliferator-activated receptor-gamma (PPARγ), (ii) increased polarization towards an inflammatory phenotype, (iii) augmented nuclear factor-κB-dependent transcription of pro-inflammatory cytokines and (iv) reduced PD-L1 expression. These properties empowered DOK1+ macrophages to decrease the viability of human gastric cancer cells in contact-dependent co-cultures. DOK1 also reduced PD-L1 expression in human primary blood monocytes. Our data propose that the drugability of DOK1 may be exploited to reprogram myeloid cells and enforce the innate immune response against EBV+ human gastric cancer.

Mapping novel genetic loci associated with female liver weight variations using Collaborative Cross mice

BACKGROUND

Liver weight is a complex trait, controlled by polygenic factors and differs within populations. Dissecting the genetic architecture underlying these variations will facilitate the search for key role candidate genes involved directly in the hepatomegaly process and indirectly involved in related diseases etiology.

METHODS

Liver weight of 506 mice generated from 39 different Collaborative Cross (CC) lines with both sexes at age 20 weeks old was determined using an electronic balance. Genomic DNA of the CC lines was genotyped with high-density single nucleotide polymorphic markers.

RESULTS

Statistical analysis revealed a significant (P < 0.05) variation of liver weight between the CC lines, with broad sense heritability (H 2) of 0.32 and genetic coefficient of variation (CVG) of 0.28. Subsequently, quantitative trait locus (QTL) mapping was performed, and results showed a significant QTL only for females on chromosome 8 at genomic interval 88.61-93.38 Mb (4.77 Mb). Three suggestive QTL were mapped at chromosomes 4, 12 and 13. The four QTL were designated as LWL1-LWL4 referring to liver weight loci 1-4 on chromosomes 8, 4, 12 and 13, respectively.

CONCLUSION

To our knowledge, this report presents, for the first time, the utilization of the CC for mapping QTL associated with baseline liver weight in mice. Our findings demonstrate that liver weight is a complex trait controlled by multiple genetic factors that differ significantly between sexes.

The Collaborative Cross mouse model for dissecting genetic susceptibility to infectious diseases

Infectious diseases, also known as communicable diseases, refer to a full range of maladies caused by pathogen invasion to the host body. Host response towards an infectious pathogen varies between individuals, and can be defined by responses from asymptomatic to lethal. Host response to infectious pathogens is considered as a complex trait controlled by gene-gene (host-pathogen) and gene-environment interactions, leading to the extensive phenotypic variations between individuals. With the advancement of the human genome mapping approaches and tools, various genome-wide association studies (GWAS) were performed, aimed at mapping the genetic basis underlying host susceptibility towards infectious pathogens. In parallel, immense efforts were invested in enhancing the genetic mapping resolution and gene-cloning efficacy, using advanced mouse models including advanced intercross lines; outbred populations; consomic, congenic; and recombinant inbred lines. Notwithstanding the evident advances achieved using these mouse models, the genetic diversity was low and quantitative trait loci (QTL) mapping resolution was inadequate. Consequently, the Collaborative Cross (CC) mouse model was established by full-reciprocal mating of eight divergent founder strains of mice (A/J, C57BL/6J, 129S1/SvImJ, NOD/LtJ, NZO/HiLtJ, CAST/Ei, PWK/PhJ, and WSB/EiJ) generating a next-generation mouse genetic reference population (CC lines). Presently, the CC mouse model population comprises a set of about 200 recombinant inbred CC lines exhibiting a unique high genetic diversity and which are accessible for multidisciplinary studies. The CC mouse model efficacy was validated by various studies in our lab and others, accomplishing high-resolution (< 1 MB) QTL genomic mapping for a variety of complex traits, using about 50 CC lines (3-4 mice per line). Herein, we present a number of studies demonstrating the power of the CC mouse model, which has been utilized in our lab for mapping the genetic basis of host susceptibility to various infectious pathogens. These include Aspergillus fumigatus, Klebsiella pneumoniae, Porphyromonas gingivalis and Fusobacterium nucleatum (causing oral mixed infection), Pseudomonas aeruginosa, and the bacterial toxins Lipopolysaccharide and Lipoteichoic acid.

The impact of host genetic background in the Pseudomonas aeruginosa respiratory infections

Understanding the significance of human genetic diversity in modulating host susceptibility to opportunistic infections is an emerging challenge in the field of respiratory illnesses. While it is recognized that diverse bacterial strains account for differential disease manifestations, emerging data indicate that host genetic diversity is an important determinant factor that influences the severity of opportunistic infections. With particular regard to respiratory illnesses mediated by the gram-negative bacterium Pseudomonas aeruginosa, diverse genetic background is also emerging as a key contributor. Human-genome-wide association studies are a common approach for determining the inter-individual genetic variation associated with variability of the pulmonary infections. Historically, diverse murine inbred mouse strains and ex-vivo cellular models were considered complementary to human studies for establishing the contribution of genetic background to P. aeruginosa respiratory infections. More recently, the development of a new mouse model of infection, mirroring human airway diseases, combined with innovative murine resource populations, modelling human genetic variation, provides additional insights into the mechanisms of genetic susceptibility. In this review, we cover the recent state of the art of human and animal studies and we discuss future potential challenges in the field of P. aeruginosa respiratory infections.