scholarly journals A Protein Important for Antimicrobial Peptide Resistance, YdeI/OmdA, Is in the Periplasm and Interacts with OmpD/NmpC

2009 ◽  
Vol 191 (23) ◽  
pp. 7243-7252 ◽  
Author(s):  
M. Carolina Pilonieta ◽  
Kimberly D. Erickson ◽  
Robert K. Ernst ◽  
Corrella S. Detweiler
Keyword(s):  
Gene Expression ◽  
Antimicrobial Peptide ◽  
Bacterial Resistance ◽  
Cell Types ◽  
Polymyxin B ◽  
Sensor Kinase ◽  
Multiple Cell ◽  
Ob Fold ◽  
Antimicrobial Peptide Resistance ◽  
Multicellular Organisms

ABSTRACT Antimicrobial peptides (AMPs) kill or prevent the growth of microbes. AMPs are made by virtually all single and multicellular organisms and are encountered by bacteria in diverse environments, including within a host. Bacteria use sensor-kinase systems to respond to AMPs or damage caused by AMPs. Salmonella enterica deploys at least three different sensor-kinase systems to modify gene expression in the presence of AMPs: PhoP-PhoQ, PmrA-PmrB, and RcsB-RcsC-RcsD. The ydeI gene is regulated by the RcsB-RcsC-RcsD pathway and encodes a 14-kDa predicted oligosaccharide/oligonucleotide binding-fold (OB-fold) protein important for polymyxin B resistance in broth and also for virulence in mice. We report here that ydeI is additionally regulated by the PhoP-PhoQ and PmrA-PmrB sensor-kinase systems, which confer resistance to cationic AMPs by modifying lipopolysaccharide (LPS). ydeI, however, is not important for known LPS modifications. Two independent biochemical methods found that YdeI copurifies with OmpD/NmpC, a member of the trimeric β-barrel outer membrane general porin family. Genetic analysis indicates that ompD contributes to polymyxin B resistance, and both ydeI and ompD are important for resistance to cathelicidin antimicrobial peptide, a mouse AMP produced by multiple cell types and expressed in the gut. YdeI localizes to the periplasm, where it could interact with OmpD. A second predicted periplasmic OB-fold protein, YgiW, and OmpF, another general porin, also contribute to polymyxin B resistance. Collectively, the data suggest that periplasmic OB-fold proteins can interact with porins to increase bacterial resistance to AMPs.

scholarly journals An iron-regulated LysR-type element mediates antimicrobial peptide resistance and virulence in Yersinia pseudotuberculosis

Microbiology ◽  
2009 ◽  
Vol 155 (7) ◽  
pp. 2168-2181 ◽  
Author(s):  
Sonia Arafah ◽  
Marie-Laure Rosso ◽  
Linda Rehaume ◽  
Robert E. W. Hancock ◽  
Michel Simonet ◽  
...  
Keyword(s):  
Antimicrobial Peptide ◽  
Yersinia Pseudotuberculosis ◽  
Polymyxin B ◽  
Uptake System ◽  
Mesenteric Lymph Nodes ◽  
Iron Starvation ◽  
Iron Deprivation ◽  
Genes Encoding ◽  
Antimicrobial Peptide Resistance

During the course of its infection of the mammalian digestive tract, the entero-invasive, Gram-negative bacterium Yersinia pseudotuberculosis must overcome various hostile living conditions (notably, iron starvation and the presence of antimicrobial compounds produced in situ). We have previously reported that in vitro bacterial growth during iron deprivation raises resistance to the antimicrobial peptide polymyxin B; here, we show that this phenotype is mediated by a chromosomal gene (YPTB0333) encoding a transcriptional regulator from the LysR family. We determined that the product of YPTB0333 is a pleiotropic regulator which controls (in addition to its own expression) genes encoding the Yfe iron-uptake system and polymyxin B resistance. Lastly, by using a mouse model of oral infection, we demonstrated that YPTB0333 is required for colonization of Peyer's patches and mesenteric lymph nodes by Y. pseudotuberculosis.

scholarly journals A systems perspective of heterocellular signaling

2018 ◽  
Vol 62 (4) ◽  
pp. 607-617 ◽  
Author(s):  
Alan Wells ◽  
H. Steven Wiley
Keyword(s):  
Cell Types ◽  
Regulatory Processes ◽  
Technical Developments ◽  
Building Models ◽  
Realistic Description ◽  
Multiple Cell ◽  
Solid Foundation ◽  
And Function ◽  
Multicellular Organisms ◽  
Different Cell Types

Signal exchange between different cell types is essential for development and function of multicellular organisms, and its dysregulation is causal in many diseases. Unfortunately, most cell-signaling work has employed single cell types grown under conditions unrelated to their native context. Recent technical developments have started to provide the tools needed to follow signaling between multiple cell types, but gaps in the information they provide have limited their usefulness in building realistic models of heterocellular signaling. Currently, only targeted assays have the necessary sensitivity, selectivity, and spatial resolution to usefully probe heterocellular signaling processes, but these are best used to test specific, mechanistic models. Decades of systems biology research with monocultures has provided a solid foundation for building models of heterocellular signaling, but current models lack a realistic description of regulated proteolysis and the feedback processes triggered within and between cells. Identification and understanding of key regulatory processes in the extracellular environment and of recursive signaling patterns between cells will be essential to building predictive models of heterocellular systems.

scholarly journals A pitfall for machine learning methods aiming to predict across cell types

2019 ◽  
Author(s):  
Jacob Schreiber ◽  
Ritambhara Singh ◽  
Jeffrey Bilmes ◽  
William Stafford Noble
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Cell Types ◽  
Chromatin Domain ◽  
Genomic Locus ◽  
Enhancer Activity ◽  
Domain Boundaries ◽  
Multiple Cell ◽  
Average Activity ◽  
Predict Gene Expression

AbstractMachine learning models used to predict phenomena such as gene expression, enhancer activity, transcription factor binding, or chromatin conformation are most useful when they can generalize to make accurate predictions across cell types. In this situation, a natural strategy is to train the model on experimental data from some cell types and evaluate performance on one or more held-out cell types. In this work, we show that when the training set contains examples derived from the same genomic loci across multiple cell types, the resulting model can be susceptible to a particular form of bias related to memorizing the average activity associated with each genomic locus. Consequently, the trained model may appear to perform well when evaluated on the genomic loci that it was trained on but tends to perform poorly on loci that it was not trained on. We demonstrate this phenomenon by using epigenomic measurements and nucleotide sequence to predict gene expression and chromatin domain boundaries, and we suggest methods to diagnose and avoid the pitfall. We anticipate that, as more data and computing resources become available, future projects will increasingly risk suffering from this issue.

scholarly journals Integrating Mendelian randomization and multiple-trait colocalization to uncover cell-specific inflammatory drivers of autoimmune and atopic disease

2019 ◽  
Vol 28 (19) ◽  
pp. 3293-3300 ◽  
Author(s):  
Lucy M McGowan ◽  
George Davey Smith ◽  
Tom R Gaunt ◽  
Tom G Richardson
Keyword(s):  
Gene Expression ◽  
Mendelian Randomization ◽  
Inflammatory Responses ◽  
Cell Types ◽  
Atopic Disease ◽  
Analytical Framework ◽  
Causal Variant ◽  
Human Populations ◽  
Multiple Trait ◽  
Multiple Cell

Abstract Immune-mediated diseases (IMDs) arise when tolerance is lost and chronic inflammation is targeted towards healthy tissues. Despite their growing prevalence, therapies to treat IMDs are lacking. Cytokines and their receptors orchestrate inflammatory responses by regulating elaborate signalling networks across multiple cell types making it challenging to pinpoint therapeutically relevant drivers of IMDs. We developed an analytical framework that integrates Mendelian randomization (MR) and multiple-trait colocalization (moloc) analyses to highlight putative cell-specific drivers of IMDs. MR evaluated causal associations between the levels of 10 circulating cytokines and 9 IMDs within human populations. Subsequently, we undertook moloc analyses to assess whether IMD trait, cytokine protein and corresponding gene expression are driven by a shared causal variant. Moreover, we leveraged gene expression data from three separate cell types (monocytes, neutrophils and T cells) to discern whether associations may be attributed to cell type-specific drivers of disease. MR analyses supported a causal role for IL-18 in inflammatory bowel disease (IBD) (P = 1.17 × 10−4) and eczema/dermatitis (P = 2.81 × 10−3), as well as associations between IL-2rα and IL-6R with several other IMDs. Moloc strengthened evidence of a causal association for these results, as well as providing evidence of a monocyte and neutrophil-driven role for IL-18 in IBD pathogenesis. In contrast, IL-2rα and IL-6R associations were found to be T cell specific. Our analytical pipeline can help to elucidate putative molecular pathways in the pathogeneses of IMDs, which could be applied to other disease contexts.

scholarly journals Identification of a Genetic Locus Responsible for Antimicrobial Peptide Resistance inClostridium difficile

2010 ◽  
Vol 79 (1) ◽  
pp. 167-176 ◽  
Author(s):  
Shonna M. McBride ◽  
Abraham L. Sonenshein
Keyword(s):  
Antimicrobial Peptides ◽  
Antimicrobial Peptide ◽  
Abc Transporter ◽  
Genetic Locus ◽  
Polymyxin B ◽  
Transcriptional Analysis ◽  
Cationic Antimicrobial Peptide ◽  
Low Levels ◽  
Antimicrobial Peptide Resistance ◽  
Abc Transporter Genes

ABSTRACTClostridium difficilecauses chronic intestinal disease, yet little is understood about how the bacterium interacts with and survives in the host. To colonize the intestine and cause persistent disease, the bacterium must circumvent killing by host innate immune factors, such as cationic antimicrobial peptides (CAMPs). In this study, we investigated the effect of model CAMPs on growth and found thatC. difficileis not only sensitive to these compounds but also responds to low levels of CAMPs by expressing genes that lead to CAMP resistance. By plating the bacterium on medium containing the CAMP nisin, we isolated a mutant capable of growing in three times the inhibitory concentration of CAMPs. This mutant also showed increased resistance to the CAMPs gallidermin and polymyxin B, demonstrating tolerance to different types of antimicrobial peptides. We identified the mutated gene responsible for the resistance phenotype as CD1352. This gene encodes a putative orphan histidine kinase that lies adjacent to a predicted ABC transporter operon (CD1349 to CD1351). Transcriptional analysis of the ABC transporter genes revealed that this operon was upregulated in the presence of nisin in wild-type cells and was more highly expressed in the CD1352 mutant. The insertional disruption of the CD1349 gene resulted in significant decreases in resistance to the CAMPs nisin and gallidermin but not polymyxin B. Because of their role in cationic antimicrobial peptide resistance, we propose the designationcprABCfor genes CD1349 to CD1351 andcprKfor the CD1352 gene. These results provide the first evidence of aC. difficilegene associated with antimicrobial peptide resistance.

scholarly journals A Synthetic Transcription Platform for Programmable Gene Expression in Mammalian Cells

2020 ◽  
Author(s):  
William C.W. Chen ◽  
Leonid Gaidukov ◽  
Ming-Ru Wu ◽  
Jicong Cao ◽  
Gigi C.G. Choi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Interferon Gamma ◽  
Mammalian Cells ◽  
Cell Types ◽  
Regulatory Elements ◽  
Genetic Circuits ◽  
Control Of Gene Expression ◽  
Transcription System ◽  
Multiple Cell ◽  
Cellular Phenotypes

Precise, scalable, and sustainable control of genetic and cellular activities in mammalian cells is key to developing precision therapeutics and smart biomanufacturing. We created a highly tunable, modular, versatile CRISPR-based synthetic transcription system for the programmable control of gene expression and cellular phenotypes in mammalian cells. Genetic circuits consisting of well-characterized libraries of guide RNAs, binding motifs of synthetic operators, transcriptional activators, and additional genetic regulatory elements expressed mammalian genes in a highly predictable and tunable manner. We demonstrated the programmable control of reporter genes episomally and chromosomally, with up to 25-fold more EF1[alpha]; promoter activity, in multiple cell types. We used these circuits to program secretion of human monoclonal antibodies and to control T cell effector function marked by interferon-[gamma] production. Antibody titers and interferon-[gamma]; concentrations were significantly correlated with synthetic promoter strengths, providing a platform for programming gene expression and cellular function for biological, biomanufacturing, and biomedical applications.

scholarly journals Integrative transcriptomic analysis of SLE reveals IFN-driven cross-talk between immune cells

2020 ◽  
Author(s):  
Bharat Panwar ◽  
Benjamin J. Schmiedel ◽  
Shu Liang ◽  
Brandie White ◽  
Enrique Rodriguez ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Autoimmune Disease ◽  
Cross Talk ◽  
Immune Cell ◽  
Cell Types ◽  
Cell Populations ◽  
Multiple Cell ◽  
Classical Monocytes ◽  
Multiple Immune Cell

ABSTRACTThe systemic lupus erythematosus (SLE) is an incurable autoimmune disease disproportionately affecting women and may lead to damage in multiple different organs. The marked heterogeneity in its clinical manifestations is a major obstacle in finding targeted treatments and involvement of multiple immune cell types further increases this complexity. Thus, identifying molecular subtypes that best correlate with disease heterogeneity and severity as well as deducing molecular cross-talk among major immune cell types that lead to disease progression are critical steps in the development of more informed therapies for SLE. Here we profile and analyze gene expression of six major circulating immune cell types from patients with well-characterized SLE (classical monocytes (n=64), T cells (n=24), neutrophils (n=24), B cells (n=20), conventional (n=20) and plasmacytoid (n=22) dendritic cells) and from healthy control subjects. Our results show that the interferon (IFN) response signature was the major molecular feature that classified SLE patients into two distinct groups: IFN-signature negative (IFNneg) and positive (IFNpos). We show that the gene expression signature of IFN response was consistent (i) across all immune cell types, (ii) all single cells profiled from three IFNpos donors using single-cell RNA-seq, and (iii) longitudinal samples of the same patient. For a better understanding of molecular differences of IFNpos versus IFNneg patients, we combined differential gene expression analysis with differential Weighted Gene Co-expression Network Analysis (WGCNA), which revealed a relatively small list of genes from classical monocytes including two known immune modulators, one the target of an approved therapeutic for SLE (TNFSF13B/BAFF: belimumab) and one itself a therapeutic for Rheumatoid Arthritis (IL1RN: anakinra). For a more integrative understanding of the cross-talk among different cell types and to identify potentially novel gene or pathway connections, we also developed a novel gene co-expression analysis method for joint analysis of multiple cell types named integrated WGNCA (iWGCNA). This method revealed an interesting cross-talk between T and B cells highlighted by a significant enrichment in the expression of known markers of T follicular helper cells (Tfh), which also correlate with disease severity in the context of IFNpos patients. Interestingly, higher expression of BAFF from all myeloid cells also shows a strong correlation with enrichment in the expression of genes in T cells that may mark circulating Tfh cells or related memory cell populations. These cell types have been shown to promote B cell class-switching and antibody production, which are well-characterized in SLE patients. In summary, we generated a large-scale gene expression dataset from sorted immune cell populations and present a novel computational approach to analyze such data in an integrative fashion in the context of an autoimmune disease. Our results reveal the power of a hypothesis-free and data-driven approach to discover drug targets and reveal novel cross-talk among multiple immune cell types specific to a subset of SLE patients. This approach is immediately useful for studying autoimmune diseases and is applicable in other contexts where gene expression profiling is possible from multiple cell types within the same tissue compartment.

scholarly journals Trehalose, an mTOR-Independent Inducer of Autophagy, Inhibits Human Cytomegalovirus Infection in Multiple Cell Types

2015 ◽  
Vol 90 (3) ◽  
pp. 1259-1277 ◽  
Author(s):  
Jean-Philippe Belzile ◽  
Maite Sabalza ◽  
Megan Craig ◽  
Alex E. Clark ◽  
Christopher S. Morello ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Cytomegalovirus ◽  
Hcmv Infection ◽  
Human Fibroblasts ◽  
Cell Types ◽  
Viral Gene ◽  
Neural Cells ◽  
Viral Spread ◽  
Hcmv Disease ◽  
Multiple Cell

ABSTRACT Human cytomegalovirus (HCMV) is the major viral cause of birth defects and a serious problem in immunocompromised individuals and has been associated with atherosclerosis. Previous studies have shown that the induction of autophagy can inhibit the replication of several different types of DNA and RNA viruses. The goal of the work presented here was to determine whether constitutive activation of autophagy would also block replication of HCMV. Most prior studies have used agents that induce autophagy via inhibition of the mTOR pathway. However, since HCMV infection alters the sensitivity of mTOR kinase-containing complexes to inhibitors, we sought an alternative method of inducing autophagy. We chose to use trehalose, a nontoxic naturally occurring disaccharide that is found in plants, insects, microorganisms, and invertebrates but not in mammals and that induces autophagy by an mTOR-independent mechanism. Given the many different cell targets of HCMV, we proceeded to determine whether trehalose would inhibit HCMV infection in human fibroblasts, aortic artery endothelial cells, and neural cells derived from human embryonic stem cells. We found that in all of these cell types, trehalose induces autophagy and inhibits HCMV gene expression and production of cell-free virus. Treatment of HCMV-infected neural cells with trehalose also inhibited production of cell-associated virus and partially blocked the reduction in neurite growth and cytomegaly. These results suggest that activation of autophagy by the natural sugar trehalose or other safe mTOR-independent agents might provide a novel therapeutic approach for treating HCMV disease. IMPORTANCE HCMV infects multiple cell types in vivo, establishes lifelong persistence in the host, and can cause serious health problems for fetuses and immunocompromised individuals. HCMV, like all other persistent pathogens, has to finely tune its interplay with the host cellular machinery to replicate efficiently and evade detection by the immune system. In this study, we investigated whether modulation of autophagy, a host pathway necessary for the recycling of nutrients and removal of protein aggregates, misfolded proteins, and pathogens, could be used to target HCMV. We found that autophagy could be significantly increased by treatment with the nontoxic, natural disaccharide trehalose. Importantly, trehalose had a profound inhibitory effect on viral gene expression and strongly impaired viral spread. These data constitute a proof-of-concept for the use of natural products targeting host pathways rather than the virus itself, thus reducing the risk of the development of resistance to treatment.

scholarly journals Functional dynamic genetic effects on gene regulation are specific to particular cell types and environmental conditions

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Anthony S Findley ◽  
Alan Monziani ◽  
Allison L Richards ◽  
Katherine Rhodes ◽  
Michelle C Ward ◽  
...  
Keyword(s):  
Gene Expression ◽  
Complex Traits ◽  
Induced Pluripotent Stem Cell ◽  
Cell Types ◽  
Cell System ◽  
Genetic Effects ◽  
Evolutionary Features ◽  
Multiple Cell ◽  
Multiple Treatments ◽  
Induced Pluripotent

Genetic effects on gene expression and splicing can be modulated by cellular and environmental factors; yet interactions between genotypes, cell type and treatment have not been comprehensively studied together. We used an induced pluripotent stem cell system to study multiple cell types derived from the same individuals and exposed them to a large panel of treatments. Cellular responses involved different genes and pathways for gene expression and splicing, and were highly variable across contexts. For thousands of genes, we identified variable allelic expression across contexts and characterized different types of gene-environment interactions, many of which are associated with complex traits. Promoter functional and evolutionary features distinguished genes with elevated allelic imbalance mean and variance. On average half of the genes with dynamic regulatory interactions were missed by large eQTL mapping studies, indicating the importance of exploring multiple treatments to reveal previously unrecognized regulatory loci that may be important for disease.

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