scholarly journals The Lrp/AsnC-Type Regulator PA2577 Controls the EamA-like Transporter Gene PA2576 in Pseudomonas aeruginosa

2021 ◽  
Vol 22 (24) ◽  
pp. 13340
Author(s):  
Magdalena Modrzejewska ◽  
Adam Kawalek ◽  
Aneta Agnieszka Bartosik
Keyword(s):  
Gene Expression ◽  
Pseudomonas Aeruginosa ◽  
Cellular Response ◽  
Mrna Level ◽  
Transcriptional Regulators ◽  
Polymyxin B ◽  
Transport Processes ◽  
Strong Interactions ◽  
Phenotype Microarray ◽  
Metabolism Regulation

The regulatory network of gene expression in Pseudomonas aeruginosa, an opportunistic human pathogen, is very complex. In the PAO1 reference strain, about 10% of genes encode transcriptional regulators, many of which have undefined regulons and unknown functions. The aim of this study is the characterization of PA2577 protein, a representative of the Lrp/AsnC family of transcriptional regulators. This family encompasses proteins involved in the amino acid metabolism, regulation of transport processes or cell morphogenesis. The transcriptome profiling of P. aeruginosa cells with mild PA2577 overproduction revealed a decreased expression of the PA2576 gene oriented divergently to PA2577 and encoding an EamA-like transporter. A gene expression analysis showed a higher mRNA level of PA2576 in P. aeruginosa ΔPA2577, indicating that PA2577 acts as a repressor. Concomitantly, ChIP-seq and EMSA assays confirmed strong interactions of PA2577 with the PA2577/PA2576 intergenic region. Additionally, phenotype microarray analyses indicated an impaired metabolism of ΔPA2576 and ΔPA2577 mutants in the presence of polymyxin B, which suggests disturbances of membrane functions in these mutants. We show that PA2576 interacts with two proteins, PA5006 and PA3694, with a predicted role in lipopolysaccharide (LPS) and membrane biogenesis. Overall, our results indicate that PA2577 acts as a repressor of the PA2576 gene coding for the EamA-like transporter and may play a role in the modulation of the cellular response to stress conditions, including antimicrobial peptides, e.g., polymyxin B.

scholarly journals The MarR-Type Regulator PA3458 Is Involved in Osmoadaptation Control in Pseudomonas aeruginosa

2021 ◽  
Vol 22 (8) ◽  
pp. 3982
Author(s):  
Karolina Kotecka ◽  
Adam Kawalek ◽  
Kamil Kobylecki ◽  
Aneta Agnieszka Bartosik
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Binding Sites ◽  
Transcriptional Profiling ◽  
Mrna Level ◽  
Transcriptional Regulators ◽  
Resistance Mechanisms ◽  
Chronic Infections ◽  
Environmental Signals ◽  
Regulatory Systems

Pseudomonas aeruginosa is a facultative human pathogen, causing acute and chronic infections that are especially dangerous for immunocompromised patients. The eradication of P. aeruginosa is difficult due to its intrinsic antibiotic resistance mechanisms, high adaptability, and genetic plasticity. The bacterium possesses multilevel regulatory systems engaging a huge repertoire of transcriptional regulators (TRs). Among these, the MarR family encompasses a number of proteins, mainly acting as repressors, which are involved in response to various environmental signals. In this work, we aimed to decipher the role of PA3458, a putative MarR-type TR from P. aeruginosa. Transcriptional profiling of P. aeruginosa PAO1161 overexpressing PA3458 showed changes in the mRNA level of 133 genes; among them, 100 were down-regulated, suggesting the repressor function of PA3458. Concomitantly, ChIP-seq analysis identified more than 300 PA3458 binding sites in P. aeruginosa. The PA3458 regulon encompasses genes involved in stress response, including the PA3459–PA3461 operon, which is divergent to PA3458. This operon encodes an asparagine synthase, a GNAT-family acetyltransferase, and a glutamyl aminopeptidase engaged in the production of N-acetylglutaminylglutamine amide (NAGGN), which is a potent bacterial osmoprotectant. We showed that PA3458-mediated control of PA3459–PA3461 expression is required for the adaptation of P. aeruginosa growth in high osmolarity. Overall, our data indicate that PA3458 plays a role in osmoadaptation control in P. aeruginosa.

scholarly journals PrtR Homeostasis Contributes to Pseudomonas aeruginosa Pathogenesis and Resistance against Ciprofloxacin

2014 ◽  
Vol 82 (4) ◽  
pp. 1638-1647 ◽  
Author(s):  
Ziyu Sun ◽  
Jing Shi ◽  
Chang Liu ◽  
Yongxin Jin ◽  
Kewei Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pseudomonas Aeruginosa ◽  
Bacterial Colonization ◽  
Mrna Level ◽  
Sos Response ◽  
Opportunistic Pathogen ◽  
Host Cells ◽  
Chronic Infections ◽  
Mobility Shift ◽  
Content Type

ABSTRACTPseudomonas aeruginosais an opportunistic pathogen that causes acute and chronic infections in humans. Pyocins are bacteriocins produced byP. aeruginosathat are usually released through lysis of the producer strains. Expression of pyocin genes is negatively regulated by PrtR, which gets cleaved under SOS response, leading to upregulation of pyocin synthetic genes. Previously, we demonstrated that PrtR is required for the expression of type III secretion system (T3SS), which is an important virulence component ofP. aeruginosa. In this study, we demonstrate that mutation inprtRresults in reduced bacterial colonization in a mouse acute pneumonia model. Examination of bacterial and host cells in the bronchoalveolar lavage fluids from infected mice revealed that expression of PrtR is induced by reactive oxygen species (ROS) released by neutrophils. We further demonstrate that treatment with hydrogen peroxide or ciprofloxacin, known to induce the SOS response and pyocin production, resulted in an elevated PrtR mRNA level. Overexpression of PrtR by atacpromoter repressed the endogenousprtRpromoter activity, and electrophoretic mobility shift assay revealed that PrtR binds to its own promoter, suggesting an autorepressive mechanism of regulation. A high level of PrtR expressed from a plasmid resulted in increased T3SS gene expression during infection and higher resistance against ciprofloxacin. Overall, our results suggest that the autorepression of PrtR contributes to the maintenance of a relatively stable level of PrtR, which is permissive to T3SS gene expression in the presence of ROS while increasing bacterial tolerance to stresses, such as ciprofloxacin, by limiting pyocin production.

scholarly journals Bacterial Two-Hybrid Analysis of Interactions between Region 4 of the ς70 Subunit of RNA Polymerase and the Transcriptional Regulators Rsd from Escherichia coli and AlgQ from Pseudomonas aeruginosa

2001 ◽  
Vol 183 (21) ◽  
pp. 6413-6421 ◽  
Author(s):  
Simon L. Dove ◽  
Ann Hochschild
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Pseudomonas Aeruginosa ◽  
Amino Acid ◽  
Rna Polymerase ◽  
Amino Acid Substitution ◽  
Transcriptional Regulators ◽  
Binding Motif ◽  
E Coli ◽  
Two Hybrid

ABSTRACT A number of transcriptional regulators mediate their effects through direct contact with the ς70 subunit ofEscherichia coli RNA polymerase (RNAP). In particular, several regulators have been shown to contact a C-terminal portion of ς70 that harbors conserved region 4. This region of ς contains a putative helix-turn-helix DNA-binding motif that contacts the −35 element of ς70-dependent promoters directly. Here we report the use of a recently developed bacterial two-hybrid system to study the interaction between the putative anti-ς factor Rsd and the ς70 subunit of E. coli RNAP. Using this system, we found that Rsd can interact with an 86-amino-acid C-terminal fragment of ς70 and also that amino acid substitution R596H, within region 4 of ς70, weakens this interaction. We demonstrated the specificity of this effect by showing that substitution R596H does not weaken the interaction between ς and two other regulators shown previously to contact region 4 of ς70. We also demonstrated that AlgQ, a homolog of Rsd that positively regulates virulence gene expression inPseudomonas aeruginosa, can contact the C-terminal region of the ς70 subunit of RNAP from this organism. We found that amino acid substitution R600H in ς70 fromP. aeruginosa, corresponding to the R596H substitution in E. coli ς70, specifically weakens the interaction between AlgQ and ς70. Taken together, our findings suggest that Rsd and AlgQ contact similar surfaces of RNAP present in region 4 of ς70 and probably regulate gene expression through this contact.

scholarly journals Machine Learning of Pseudomonas aeruginosa transcriptomes identifies independently modulated sets of genes associated with known transcriptional regulators

2021 ◽  
Author(s):  
Akanksha Rajput ◽  
Hannah Tsunemoto ◽  
Anand V Sastry ◽  
Richard Szubin ◽  
Kevin Rychel ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Transcriptional Regulatory Network ◽  
Critical Role ◽  
Gene Clusters ◽  
Transcriptional Regulators ◽  
Critical Conditions ◽  
Future Research ◽  
Secretion Systems ◽  
Metabolism Regulation ◽  
Transcriptional Regulatory

The transcriptional regulatory network (TRN) of Pseudomonas aeruginosa plays a critical role in coordinating numerous cellular processes. We extracted and quality controlled all publicly available RNA-sequencing datasets for P. aeruginosa to find 281 high-quality transcriptomes. We produced 83 new RNAseq data sets under critical conditions to generate a comprehensive compendium of 364 transcriptomes. We used this compendium to reconstruct the TRN of P. aeruginosa using independent component analysis (ICA). We identified 104 independently modulated sets of genes (called iModulons), among which 81 (78%) reflect the effects of known transcriptional regulators. We show that iModulons: 1) play an important role in defining the genomic boundaries of biosynthetic gene clusters (BGCs); 2) show increased expression of the BGCs and associated secretion systems in conditions that emulate cystic fibrosis (CF); 3) show the presence of a novel BGC named RiPP (bacteriocin producer) which might have a role in worsening CF outcomes; 4) exhibit the interplay of amino acid metabolism regulation and central metabolism across carbon sources, and 5) clustered according to their activity changes to define iron and sulfur stimulons. Finally, we compare the iModulons of P. aeruginosa with those of E. coli to observe conserved regulons across two gram negative species. This comprehensive TRN framework covers almost every aspect of the transcriptional regulatory machinery in P. aeruginosa, and thus could prove foundational for future research of its physiological functions.

scholarly journals Transcriptome Analysis of Pseudomonas aeruginosa Growth: Comparison of Gene Expression in Planktonic Cultures and Developing and Mature Biofilms

2005 ◽  
Vol 187 (18) ◽  
pp. 6571-6576 ◽  
Author(s):  
Richard D. Waite ◽  
Anastasia Papakonstantinopoulou ◽  
Eddie Littler ◽  
Michael A. Curtis
Keyword(s):  
Gene Expression ◽  
Pseudomonas Aeruginosa ◽  
Stationary Phase ◽  
Solute Transport ◽  
Transcriptome Analysis ◽  
Transcriptional Regulators ◽  
Transport Proteins ◽  
Stages Of Development ◽  
Novel Genes ◽  
Genes Encoding

ABSTRACT The transcriptomes of logarithmic- and stationary-phase Pseudomonas aeruginosa planktonic cultures and static biofilms of different stages of development were compared. Developing and confluent biofilm transcriptomes were found to be related to those of logarithmic- and stationary-phase planktonic cultures, respectively. In addition, a number of novel genes were up-regulated in developing and confluent biofilms, including genes encoding putative solute transport proteins and transcriptional regulators, respectively.

scholarly journals ADAGE analysis of publicly available gene expression data collections illuminates Pseudomonas aeruginosa-host interactions

2015 ◽  
Author(s):  
Jie Tan ◽  
John H Hammond ◽  
Deborah A Hogan ◽  
Casey S Greene
Keyword(s):  
Gene Expression ◽  
Pseudomonas Aeruginosa ◽  
Gene Expression Data ◽  
Cellular Response ◽  
Bacterial Pathogen ◽  
Positive Control ◽  
Expression Data ◽  
Low Oxygen ◽  
Biological Interpretation ◽  
Data Collections

The growth in genome-scale assays of gene expression for different species in publicly available databases presents new opportunities for computational methods that aid in hypothesis generation and biological interpretation of these data. Here, we present an unsupervised machine-learning approach, ADAGE (Analysis using Denoising Autoencoders of Gene Expression) and apply it to the interpretation of all of the publicly available gene expression data for Pseudomonas aeruginosa, an important opportunistic bacterial pathogen. In post-hoc positive control analyses using curated knowledge, the P. aeruginosa ADAGE model found that co-operonic genes often participated in similar processes and accurately predicted which genes had similar functions. By analyzing newly generated data and previously published microarray and RNA-seq data, the ADAGE model identified gene expression differences between strains, modeled the cellular response to low oxygen, and predicted the involvement of biological processes despite low level expression differences in directly involved genes. Comparison of ADAGE with PCA and ICA revealed that ADAGE extracts distinct signals. We provide the ADAGE model with analysis of all publicly available P. aeruginosa GeneChip experiments, and we provide open source code for use in other species and settings.

scholarly journals The DtxR Regulon of Corynebacterium glutamicum

2006 ◽  
Vol 188 (8) ◽  
pp. 2907-2918 ◽  
Author(s):  
Julia Wennerhold ◽  
Michael Bott
Keyword(s):  
Gene Expression ◽  
Corynebacterium Glutamicum ◽  
Dna Microarrays ◽  
Iron Acquisition ◽  
Mrna Level ◽  
Global Gene Expression ◽  
Transcriptional Regulators ◽  
Mrna Levels ◽  
Computer Based ◽  
Transcriptome Comparison

ABSTRACT Previous studies with Corynebacterium diphtheriae and Mycobacterium species revealed that the transcriptional regulator DtxR and its ortholog IdeR play a central role in the control of iron metabolism. In the present work, we used genome-based approaches to determine the DtxR regulon of Corynebacterium glutamicum, a nonpathogenic relative of C. diphtheriae. First, global gene expression of a dtxR deletion mutant was compared with that of the wild type using DNA microarrays. Second, we used a computer-based approach to identify 117 putative DtxR binding sites in the C. glutamicum genome. In the third step, 74 of the corresponding genome regions were amplified by PCR, 51 of which were shifted by the DtxR protein. Finally, we analyzed which of the genes preceded by a functional DtxR binding site showed altered mRNA levels in the transcriptome comparison. Fifty-one genes organized in 27 putative operons displayed an increased mRNA level in the ΔdtxR mutant and thus are presumably repressed by DtxR. The majority of these genes are obviously involved in iron acquisition, three encode transcriptional regulators, e.g., the recently identified repressor of iron proteins RipA, and the others encode proteins of diverse or unknown functions. Thirteen genes showed a decreased mRNA level in the ΔdtxR mutant and thus might be activated by DtxR. This group included the suf operon, whose products are involved in the formation and repair of iron-sulfur clusters, and several genes for transcriptional regulators. Our results clearly establish DtxR as the master regulator of iron-dependent gene expression in C. glutamicum.

Nanoparticle-plasma Membrane Interactions: Thermodynamics, Toxicity and Cellular Response

2020 ◽  
Vol 27 (20) ◽  
pp. 3330-3345
Author(s):  
Ana G. Rodríguez-Hernández ◽  
Rafael Vazquez-Duhalt ◽  
Alejandro Huerta-Saquero
Keyword(s):  
Gene Expression ◽  
Immune Responses ◽  
Cellular Response ◽  
Cellular Level ◽  
Membrane Interactions ◽  
Daily Lives ◽  
Cellular Physiology ◽  
Associated Proteins ◽  
First Contact ◽  
Insight Into

Nanomaterials have become part of our daily lives, particularly nanoparticles contained in food, water, cosmetics, additives and textiles. Nanoparticles interact with organisms at the cellular level. The cell membrane is the first protective barrier against the potential toxic effect of nanoparticles. This first contact, including the interaction between the cell membranes -and associated proteins- and the nanoparticles is critically reviewed here. Nanoparticles, depending on their toxicity, can cause cellular physiology alterations, such as a disruption in cell signaling or changes in gene expression and they can trigger immune responses and even apoptosis. Additionally, the fundamental thermodynamics behind the nanoparticle-membrane and nanoparticle-proteins-membrane interactions are discussed. The analysis is intended to increase our insight into the mechanisms involved in these interactions. Finally, consequences are reviewed and discussed.

Application of Phenotype Microarray for Profiling Carbon Sources Utilization between Biofilm and Non-Biofilm of Pseudomonas aeruginosa from Clinical Isolates

2020 ◽  
Vol 21 (14) ◽  
pp. 1539-1550
Author(s):  
Nur S. Ismail ◽  
Suresh K. Subbiah ◽  
Niazlin M. Taib
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Carbon Sources ◽  
Anaerobic Respiration ◽  
Regulatory System ◽  
Negative Control ◽  
High Morbidity ◽  
Metabolic Profiles ◽  
Phenotype Microarray ◽  
Diverse Environment ◽  
Phenotype Microarrays

Background: This is the fastest work in obtaining the metabolic profiles of Pseudomonas aeruginosa in order to combat the infection diseases which leads to high morbidity and mortality rates. Pseudomonas aeruginosa is a high versatility of gram-negative bacteria that can undergo aerobic and anaerobic respiration. Capabilities in deploying different carbon sources, energy metabolism and regulatory system, ensure the survival of this microorganism in the diverse environment condition. Determination of differences in carbon sources utilization among biofilm and non-biofilm of Pseudomonas aeruginosa provides a platform in understanding the metabolic activity of the microorganism. Methods: The study was carried out from September 2017 to February 2019. Four archive isolates forming strong and intermediate biofilm and non-biofilms producer were subcultured from archive isolates. ATCC 27853 P. aeruginosa was used as a negative control or non-biofilm producing microorganism. Biofilm formation was confirmed by Crystal Violet Assay (CVA) and Congo Red Agar (CRA). Metabolic profiles of the biofilm and non-biofilms isolates were determined by phenotype microarrays (Biolog Omnilog). Results and Discussion: In this study, Pseudomonas aeruginosa biofilm isolates utilized uridine, L-threonine and L-serine while non-biofilm utilized adenosine, inosine, monomethyl, sorbic acid and succinamic acid. Conclusion: The outcome of this result will be used for future studies to improve detection or inhibit the growth of P. aeruginosa biofilm and non-biofilm respectively.

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