Comparative Analysis of Quorum Sensing-Dependent Transcriptomic Responses in Phytopathogenic Burkholderia spp.

A Strategy for Antagonizing Quorum Sensing

The techniques of DNA microarray and bioinformatic analysis have exhibited efficiency in identifying dysregulated gene expression in human cancers. In this study, we used integrated bioinformatics analysis to improve our understanding of the pathogenesis of papillary thyroid cancer (PTC). In this study, we integrated four Gene Expression Omnibus (GEO) datasets, GSE33630, GSE35570, GSE60542 and GSE29265, including 136 normal samples and 157 PTC specimens. The contents of the four datasets are based on GPL570, an Affymetrix Human Genome U133 Plus 2.0 array. Gene ontology (GO) analysis was used to identify characteristic the biological attributes of differentially expressed genes (DEGs) between PTC and normal samples. GO annotation was performed on the DEGs obtained, and the process relied on the DAVID online tool. Kyoto Encyclopedia of Genes and Genomes (KEGG) approach enrichment analyses were adopted to obtain the basic functions of the DEGs. The KOBAS online analysis database was used to complete DEG KEGG pathway comparison and analysis. The search tool (STRING) database was mainly used to search for interacting genes and complete the construction of protein-protein interaction (PPI) networks. Five hundred-ninety DEGs were consistently expressed in the four datasets; 327 of them were upregulated, while 263 were downregulated. Ten DEGs, including five upregulated (ENTPD1, THRSP, KLK10, ADAMTS9, MIR31HG) and five downregulated (SCARA5, EPHB1, CHRDL1, LOC440934, FOXP2) genes, were randomly selected for q-PCR in our own tissue samples to validate the integrated data. The most highly enriched GO terms were extracellular exosome (GO:0070062), cell adhesion (GO:0070062), positive regulation of gene expression (GO:0010628), and extracellular matrix (ECM) organization (GO:0030198). KEGG pathway analysis was performed, and it was found that abnormally expressed genes effectively participated in pathways such as tyrosine metabolism, complement and coagulation cascades, cell adhesion molecules (CAMs), transcriptional misregulation and ECM-receptor interaction pathways. Five hundred-ninety DEGs were identified in PTC by integrated microarray analysis. The GO and KEGG analyses presented here suggest that the DEGs were enriched in extracellular exosome, tyrosine metabolism, CAMs, complement and coagulation cascades, transcriptional misregulation and ECM-receptor interaction pathways. Functional studies of PTC should focus on these pathways.

A review: Quorum sensing in Bradyrhizobium

BackgroundBacterial communication through quorum sensing (QS) systems has been reported to be important in coordinating several traits such as biofilm formation. In Aliivibrio salmonicida two QS systems the LuxI/R and AinS/R, have been shown to be responsible for the production of eight acyl-homoserine lactones (AHLs) in a cell density dependent manner. We have previously demonstrated that inactivation of LitR, the master regulator of the QS system resulted in biofilm formation, similar to the biofilm formed by the AHL deficient mutant ΔainSluxI−. In this study, we aimed to investigate the global gene expression patterns of luxI and ainS autoinducer synthases mutants using transcriptomic profiling. In addition, we examined the influence of the different AHLs on biofilm formation.ResultsThe transcriptome profiling of ΔainS and luxI− mutants allowed us to identify genes and gene clusters regulated by QS in A. salmonicida. Relative to the wild type, the ΔainS and luxI− mutants revealed 29 and 500 differentially expressed genes (DEGs), respectively. The functional analysis demonstrated that the most pronounced DEGs were involved in bacterial motility and chemotaxis, exopolysaccharide production, and surface structures related to adhesion. Inactivation of luxI, but not ainS genes resulted in wrinkled colony morphology. While inactivation of both genes (ΔainSluxI−) resulted in strains able to form wrinkled colonies and mushroom structured biofilm. Moreover, when the ΔainSluxI− mutant was supplemented with N-3-oxo-hexanoyl-L-homoserine lactone (3OC6-HSL) or N-3-hydroxy-decanoyl-L-homoserine lactone (3OHC10-HSL), the biofilm did not develop. We also show that LuxI is needed for motility and for repression of EPS production, where repression of EPS is likely operated through the RpoQ-sigma factor.ConclusionThese findings imply that the LuxI and AinS autoinducer synthases play a critical role in the regulation of biofilm formation, EPS production, and motility.

Previous studies have shown that asthma is a risk factor for lung cancer, while the mechanisms involved remain unclear. We attempted to further explore the association between asthma and non-small cell lung cancer (NSCLC) via bioinformatics analysis. We obtained GSE143303 and GSE18842 from the GEO database. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) groups were downloaded from the TCGA database. Based on the results of differentially expressed genes (DEGs) between asthma and NSCLC, we determined common DEGs by constructing a Venn diagram. Enrichment analysis was used to explore the common pathways of asthma and NSCLC. A protein-protein interaction (PPI) network was constructed to screen hub genes. KM survival analysis was performed to screen prognostic genes in the LUAD and LUSC groups. A Cox model was constructed based on hub genes and validated internally and externally. Tumor Immune Estimation Resource (TIMER) was used to evaluate the association of prognostic gene models with the tumor microenvironment (TME) and immune cell infiltration. Nomogram model was constructed by combining prognostic genes and clinical features. 114 common DEGs were obtained based on asthma and NSCLC data, and enrichment analysis showed that significant enrichment pathways mainly focused on inflammatory pathways. Screening of 5 hub genes as a key prognostic gene model for asthma progression to LUAD, and internal and external validation led to consistent conclusions. In addition, the risk score of the 5 hub genes could be used as a tool to assess the TME and immune cell infiltration. The nomogram model constructed by combining the 5 hub genes with clinical features was accurate for LUAD. Five-hub genes enrich our understanding of the potential mechanisms by which asthma contributes to the increased risk of lung cancer.

Quorum sensing (QS) is a complex bacterial intra and interspecific communication system that is regulated by signaling molecules produced by cell density-dependent mechanisms. QS may regulate different phenotypes such as virulence, motility and biofilm production. The aim of this research was to investigate the existence of a QS system in Pseudomonas syringae pv. actinidiae (Psa). Psa lacks the canonical QS system based on N-acyl homoserine lactone (AHL) production and detection. However, at least three signal receptors (PsaR1, PsaR2, PsaR3) were recently identified. The present study was conducted in order to clarify the effects of different cell densities on the intraspecific communication in Psa cultures, and the interspecific interaction between Psa and other bacteria associated with the plant host (i.e. in the phyllosphere) or known to have an active QS system. A bioinformatic research was conducted for the identification of genes putatively involved in Psa QS system. About 30 genes were selected due to their involvement in influencing specific phenotypes such as virulence, density perception, biofilm formation and motility. Motility and biofilm formation are crucial phenotypes in the early stages of host colonization under the control of QS circuitries. The experiments conducted demonstrated Psa ability to produce biofilm in LB liquid media depending on population density. Psa motility resulted particularly enhanced in the supernatants of bacteria with a AHL-based QS system, such as Pseudomonas fluorescens, or an AHL-overproducing strain of Pseudomonas putida. Quantitative expression of QS-related genes was analyzed by qPCR. In conclusion, from our preliminary studies we observed that QS-phenotypes seem to be influenced not only by the cell density, but also by the microbial community that may share the same environment with Psa. Presumably, only by considering the multiple interactions with both the plant host and other bacterial species, the functionality of Psa QS-system will be fully elucidated.

The most common quorum sensing (QS) system in Gram-negative bacteria employs N-acyl homoserine lactones (AHLs) as signal molecule. AHLs allow bacteria to monitor their cell density being commonly used to synchronize/coordinate the expression of virulence-associated factors in a community. An AHL QS system is most commonly mediated by two proteins belonging to the LuxI-AHL synthase and to LuxR-AHL response regulator protein families. AHLs interact directly at quorum concentration with the cognate LuxR-type protein which then binds at QS target gene promoters affecting their transcription. The purpose of this thesis was to investigate the QS systems based on AHL signal molecules in two important bacterial rice pathogens: Xanthomonas oryzae pv. oryzae (Xoo) and Pseudomonas fuscovaginae. Studies revealed that Xoo does not produce AHLs and does not possess a luxI AHL synthase gene; it does have however an unpaired luxR-homolog gene closely related to QS luxR family genes which was designated oryR. OryR was demonstrated to be involved in inter-kingdom signalling by binding an unknown rice signal molecule (RSM) and affecting bacterial gene expression. The concentration of the RSM increases in rice when it is infected with Xoo possibly meaning that it is involved in a response to pathogen attack. RSM does not bind canonical LuxR-family proteins and is not related to AHLs. It was concluded that OryR is not involved in bacterial QS but in inter-kingdom signalling by recognizing and responding to a molecule present in rice. Studies in P. fuscovaginae revealed that it possesses a typical AHL QS system, designated Pfvl/R, highly conserved within the species and highly similar to the Lasl/R and Ppul/R QS systems present in Pseudomonas aeruginosa and Pseudomonas putida respectively. The Pfvl/R QS system was shown to be involved in virulence, to be important for the hypersensitivity response in non-host plants and for bacterial motility.

Quorum sensing (QS) is a widely conserved bacterial regulatory mechanism that relies on production and perception of autoinducing chemical signals to coordinate diverse cooperative activities, such as virulence, exoenzyme secretion, and biofilm formation. In Ralstonia solanacearum, a phytopathogen causing severe bacterial wilt diseases in many plant species, previous studies identified the PhcBSR QS system, which plays a key role in regulation of its physiology and virulence. In this study, we found that R. solanacearum strain EP1 contains the genes encoding uncharacterized LuxI/LuxR (LuxI/R) QS homologues (RasI/RasR [designated RasI/R here]). To determine the roles of the RasI/R system in strain EP1, we constructed a specific reporter for the signals catalyzed by RasI. Chromatography separation and structural analysis showed that RasI synthesized primarily N-(3-hydroxydodecanoyl)-homoserine lactone (3-OH-C12-HSL). In addition, we showed that the transcriptional expression of rasI is regulated by RasR in response to 3-OH-C12-HSL. Phenotype analysis unveiled that the RasI/R system plays a critical role in modulation of cellulase production, motility, biofilm formation, oxidative stress response, and virulence of R. solanacearum EP1. We then further characterized this system by determining the RasI/R regulon using transcriptome sequencing (RNA-seq) analysis, which showed that this newly identified QS system regulates the transcriptional expression of over 154 genes associated with bacterial physiology and pathogenic properties. Taken together, the findings from this study present an essential new QS system in regulation of R. solanacearum physiology and virulence and provide new insight into the complicated regulatory mechanisms and networks in this important plant pathogen. IMPORTANCE Quorum sensing (QS) is a key regulator of virulence factors in many plant-pathogenic bacteria. Previous studies unveiled two QS systems (i.e., PhcBSR and SolI/R) in several R. solanacearum strains. The PhcBSR QS system is known for its key roles in regulation of bacterial virulence, and the LuxI/LuxR (SolI/R) QS system appears dispensable for pathogenicity in a number of R. solanacearum strains. In this study, a new functional QS system (i.e., RasI/R) was identified and characterized in R. solanacearum strain EP1 isolated from infected eggplants. Phenotype analyses showed that the RasI/R system plays an important role in regulation of a range of biological activities associated with bacterial virulence. This QS system produces and responds to the QS signal 3-OH-C12-HSL and hence regulates critical bacterial abilities in survival and infection. To date, multiple QS signaling circuits in R. solanacearum strains are still not well understood. Our findings from this study provide new insight into the complicated QS regulatory networks that govern the physiology and virulence of R. solanacearum and present a valid target and clues for the control and prevention of bacterial wilt diseases.

AIMTo identify and predict the competing endogenous RNA (ceRNA) networks in colorectal cancer (CRC) by bioinformatics analysis.METHODSIn the present study, we obtained CRC tissue and normal tissue gene expression profiles from The Cancer Genome Atlas project. Differentially expressed (DE) genes (DEGs) were identified. Then, upregulated and downregulated miRNA-centered ceRNA networks were constructed by analyzing the DEGs using multiple bioinformatics approaches. DEmRNAs in the ceRNA networks were identified in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways using KEGG Orthology Based Annotation System 3.0. The interactions between proteins were analyzed using the STRING database. Kaplan-Meier survival analysis was conducted for DEGs and real time quantitative polymerase chain reaction (RT-qPCR) was also performed to validate the prognosis-associated lncRNAs in CRC cell lines.RESULTSEighty-one DElncRNAs, 20 DEmiRNAs, and 54 DEmRNAs were identified to construct the ceRNA networks of CRC. The KEGG pathway analysis indicated that nine out of top ten pathways were related with cancer and the most significant pathway was “colorectal cancer”. Kaplan-Meier survival analysis showed that the overall survival was positively associated with five DEGs (IGF2-AS, POU6F2-AS2, hsa-miR-32, hsa-miR-141, and SERPINE1) and it was negatively related to three DEGs (LINC00488, hsa-miR-375, and PHLPP2). Based on the STRING protein database, it was found that SERPINE1 and PHLPP2 interact with AKT1. Besides, SERPINE1 can interact with VEGFA, VTN, TGFB1, PLAU, PLAUR, PLG, and PLAT. PHLPP2 can interact with AKT2 and AKT3. RT-qPCR revealed that the expression of IGF2-AS, POU6F2-AS2, and LINC00488 in CRC cell lines was consistent with the in silico results.CONCLUSIONCeRNA networks play an important role in CRC. Multiple DEGs are related with clinical prognosis, suggesting that they may be potential targets in tumor diagnosis and treatment.

The present study aimed to identify differentially regulated genes between the peritumoral brain zone (PBZ) and tumor core (TC) of glioblastoma (GBM), to elucidate the underlying molecular mechanisms and provide a target for the treatment of tumors. The GSE13276 and GSE116520 datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) for the PBZ and TC were obtained using the GEO2R tool. The bioinformatics and evolutionary genomics online tool Venn was used to identify common DEGs between the two datasets. The Database for Annotation, Visualization, and Integrated Discovery online tool was used to analyze enriched pathways of the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The Search Tool for the Retrieval of Interacting Genes/Proteins online tool was used to construct a protein-protein interaction (PPI) network of DEGs. Hub genes were identified using Cytohubba, a plug-in for Cytoscape. The Gene Expression Profiling Interactive Analysis (GEPIA) database was utilized to perform survival analysis. In total, 75 DEGs, including 12 upregulated and 63 downregulated genes, were identified. In the GO term analysis, these DEGs were mainly enriched in ‘regulation of angiogenesis’ and ‘central nervous system development’. Furthermore, in the KEGG pathway analysis, the DEGs were mainly enriched in ‘bladder cancer’ and ‘endocytosis’. When filtering the results of the PPI network analysis using Cytohubba, a total of 10 hub genes, including proteolipid protein 1, myelin associated oligodendrocyte basic protein, contactin 2, myelin oligodendrocyte glycoprotein, myelin basic protein, myelin associated glycoprotein, SRY-box transcription factor 10, C-X-C motif chemokine ligand 8 (CXCL8), vascular endothelial growth factor A (VEGFA) and plasmolipin, were identified. These hub genes were further subjected to GO term and KEGG pathway analysis, and were revealed to be enriched in ‘central nervous system development’, ‘bladder cancer’ and ‘rheumatoid arthritis’. These hub genes were used to perform survival analysis using the GEPIA database, and it was determined that VEGFA and CXCL8 were significantly associated with a reduction in the overall survival of patients with GBM. In conclusion, the results suggest that the recurrence of GBM is associated with high gene expression levels VEGFA and CXCL8, and the development of the central nervous system.

Acyl homoserine lactones (AHL) are a class of mediator molecules coordinating cell activity in the gram-negative bacteria population. AHLs synchronize individual genomes due to which bacterial populations function as a multicellular organism. AHLs provide a remote signaling between bacteria colonizing the phytosphere that enables the bacterial population to respond to external influences and establish symbiotic or antagonistic relationships with the host plant (A.R. Stacy et al., 2018; A. Shrestha et al., 2020). Autoreception of quantitative parameters of the bacterial population is called quorum sensing (QS) (R.G. Abisado et al., 2018). QS systems form autoinducer signaling molecules that easily penetrate from cells into the environment and back into the cell (M.B. Miller et al., 2001; B. Bassler, 2002). QS systems play a key role in the regulation of metabolic and physiological processes in a bacterial cell (M. Frederix et al., 2011; M. Whiteley et al., 2017). Bacterial signaling is perceived by eukaryotes, which form a symbiosis with microbial communities (A. Schenk et al., 2015; L.M. Babenko et al., 2016, 2017). Plant growth and development, nutrients assimilation, and stress resistance are largely determined by the pattern of this interaction (H.P. Bais et al., 2006; R. Ortíz-Castro et al., 2009; S. Basu et al., 2017). In the plant, bacterial signaling is controlled by the quorum quenching (QQ) system (N. Calatrava-Morales et al., 2018), whose mechanism of action is to suppress AHL synthesis by plant metabolites, compete with AHL for binding to receptor proteins, and repression of QS-controlled genes (H. Zhu et al., 2008; R. Sarkar et al., 2015). However, to date, the molecular mechanisms by which plants respond to bacterial signaling are not fully understood. Individual metabolites of AHL signaling have been characterized, but their role in the chemical interaction of partners in most cases requires further study. It has been shown that the QS phenomenon and its participants are involved in the regulation of prokaryotic-eukaryotic interactions, including the formation of biofilms, the synthesis of phytohormones, the transfer of plasmids, the production of virulence factors, bioluminescence, sporulation, and the formation of nodules (L.M. Babenko et al., 2017). Differences in the structure of molecules ensure that bacteria recognize their own AHL and separate foreign ones. The transfer of AHL from a bacterium to a host plant is carried out by means of membrane vesicles (M. Toyofuku, 2019). In recent years, there has been an active study of genetics, genomics, biochemistry, and signaling diversity of QS molecules. The regulation of the functions of the rhizosphere, the most dynamic site of interaction between the plant and the associated microflora with the participation of AHL, is of particular importance in the development of new biotechnological approaches aimed at increasing the yield and stress resistance of agricultural crops. One of the effective technologies for increasing resistance to biotic and abiotic stresses is pre-sowing treatment (priming) of seeds (A. Shrestha et al., 2020). Both direct (on plants) and indirect (on rhizosphere microflora) effects of AHL priming was established (O.V. Moshynets et al., 2019). AHL induce an increase of growth, of photosynthetic pigments content, as well as cause changes in the ratio of phytohormones in organs and tissues, affect the formation of defense mechanisms, which increases the productivity of agricultural crops (A. Schikora, S.T. Schenk, 2016; A. Shrestha et al., 2020). AHL meet the requirements of intensive organic farming, they are considered as promising ecological phytostimulants and phytomodulators capable of safely increasing the quantity and quality of agricultural products.

Acyl homoserine lactones (AHL) are a class of mediator molecules coordinating cell activity in the gram-negative bacteria population. AHLs synchronize individual genomes due to which bacterial populations function as a multicellular organism. AHLs provide a remote signaling between bacteria colonizing the phytosphere that enables the bacterial population to respond to external influences and establish symbiotic or antagonistic relationships with the host plant (A.R. Stacy et al., 2018; A. Shrestha et al., 2020). Autoreception of quantitative parameters of the bacterial population is called quorum sensing (QS) (R.G. Abisado et al., 2018). QS systems form autoinducer signaling molecules that easily penetrate from cells into the environment and back into the cell (M.B. Miller et al., 2001; B. Bassler, 2002). QS systems play a key role in the regulation of metabolic and physiological processes in a bacterial cell (M. Frederix et al., 2011; M. Whiteley et al., 2017). Bacterial signaling is perceived by eukaryotes, which form a symbiosis with microbial communities (A. Schenk et al., 2015; L.M. Babenko et al., 2016, 2017). Plant growth and development, nutrients assimilation, and stress resistance are largely determined by the pattern of this interaction (H.P. Bais et al., 2006; R. Ortíz-Castro et al., 2009; S. Basu et al., 2017). In the plant, bacterial signaling is controlled by the quorum quenching (QQ) system (N. Calatrava-Morales et al., 2018), whose mechanism of action is to suppress AHL synthesis by plant metabolites, compete with AHL for binding to receptor proteins, and repression of QS-controlled genes (H. Zhu et al., 2008; R. Sarkar et al., 2015). However, to date, the molecular mechanisms by which plants respond to bacterial signaling are not fully understood. Individual metabolites of AHL signaling have been characterized, but their role in the chemical interaction of partners in most cases requires further study. It has been shown that the QS phenomenon and its participants are involved in the regulation of prokaryotic-eukaryotic interactions, including the formation of biofilms, the synthesis of phytohormones, the transfer of plasmids, the production of virulence factors, bioluminescence, sporulation, and the formation of nodules (L.M. Babenko et al., 2017). Differences in the structure of molecules ensure that bacteria recognize their own AHL and separate foreign ones. The transfer of AHL from a bacterium to a host plant is carried out by means of membrane vesicles (M. Toyofuku, 2019). In recent years, there has been an active study of genetics, genomics, biochemistry, and signaling diversity of QS molecules. The regulation of the functions of the rhizosphere, the most dynamic site of interaction between the plant and the associated microflora with the participation of AHL, is of particular importance in the development of new biotechnological approaches aimed at increasing the yield and stress resistance of agricultural crops. One of the effective technologies for increasing resistance to biotic and abiotic stresses is pre-sowing treatment (priming) of seeds (A. Shrestha et al., 2020). Both direct (on plants) and indirect (on rhizosphere microflora) effects of AHL priming was established (O.V. Moshynets et al., 2019). AHL induce an increase of growth, of photosynthetic pigments content, as well as cause changes in the ratio of phytohormones in organs and tissues, affect the formation of defense mechanisms, which increases the productivity of agricultural crops (A. Schikora, S.T. Schenk, 2016; A. Shrestha et al., 2020). AHL meet the requirements of intensive organic farming, they are considered as promising ecological phytostimulants and phytomodulators capable of safely increasing the quantity and quality of agricultural products.

Species from the Burkholderia cepacia complex (Bcc) share a canonical LuxI/LuxR quorum sensing (QS) regulation system named CepI/CepR, which mainly relies on the acyl-homoserine lactone (AHL), octanoyl-homoserine lactone (C8-HSL) as signaling molecule. Burkholderia ambifaria is one of the least virulent Bcc species, more often isolated from rhizospheres where it exerts a plant growth-promoting activity. However, clinical strains of B. ambifaria display distinct features, such as phase variation and higher virulence properties. Notably, we previously reported that under laboratory conditions, only clinical strains of the B. ambifaria species produced 4-hydroxy-3-methyl-2-alkylquinolines (HMAQs) via expression of the hmqABCDEFG operon. HMAQs are the methylated counterparts of the 4-hydroxy-2-alkylquinolines (HAQs) produced by the opportunistic human pathogen Pseudomonas aeruginosa, in which they globally contribute to the bacterial virulence and survival. We have found that unlike P. aeruginosa’s HAQs, HMAQs do not induce their own production. However, they indirectly regulate the expression of the hmqABCDEFG operon. In B. ambifaria, a strong link between CepI/CepR-based QS and HMAQs is proposed, as we have previously reported an increased production of C8-HSL in HMAQ-negative mutants. Here, we report the identification of all AHLs produced by the clinical B. ambifaria strain HSJ1, namely C6-HSL, C8-HSL, C10-HSL, 3OHC8-HSL, 3OHC10-HSL, and 3OHC12-HSL. Production of significant levels of hydroxylated AHLs prompted the identification of a second complete LuxI/LuxR-type QS system relying on 3OHC10-HSL and 3OHC12-HSL, that we have named CepI2/CepR2. The connection between these two QS systems and the hmqABCDEFG operon, responsible for HMAQs biosynthesis, was investigated. The CepI/CepR system strongly induced the operon, while the second system appears moderately involved. On the other hand, a HMAQ-negative mutant overproduces AHLs from both QS systems. Even if HMAQs are not classical QS signals, their effect on AHL-based QS system still gives them a part to play in the QS circuitry in B. ambifaria and thus, on regulation of various phenotypes.

Objective To preliminarily explore potential genes related to radiation resistance in colorectal cancer at the molecular level, we employed bioinformatics to screen different expression genes for radiation resistance in colorectal cancer cells. Methods The comparison between the gene expression levels of radiation resistance colorectal cancer cell lines and parental cell lines was downloaded from the Gene Expression Omnibus(GEO) database. The differentially expressed genes(DEGs) were screened by using the R Programming Language and were analyzed through Gene Ontology(GO) functional enrichment analysis and kyoto encyclopedia of genes and genomes(KEGG) pathway analysis and by using protein-protein interaction(PPI) networks. The hub genes were obtained on the basis of a PPI network. The mRNA relative expression level of the hub genes was verified via quantitative real-time polymerase chain reaction in HCT116 after radiation. The statistical significance of the results was analyzed via student t-test. Results A total of 101 DEGs were found in GSE43206, including 67 upregulated genes and 34 downregulated genes. The GO enrichment analysis suggested that these DEGs are enriched in biological processes, including cell migration and DNA replication. KEGG pathway analysis indicated that these DEGs were mainly enriched in the hypoxia inducible factor-1 signaling pathway. Six radiation resistance genes with high connectivity were identified on the basis of the PPI networks, including NDRG1, PAG1, LRP1, PIM1, LDLR, and PLAUR. Quantitative real-time polymerase chain reation verified that the expression levels of hub genes were markedly up-regulated in HCT116 after radiation, including NDRG1、PAG1、LRP1、PIM1、LDLR and PLAUR (t=49.981, P<0.01; t= 26.420, 28.698, 21.358, 23.545, all P<0.05; t=50.601, P<0.01). Conclusions The use of bioinformatics enabled effectively screening radiation resistance genes in colorectal cancer, which can be used for further researches. The molecular biology experiments confirmed the differential expression of potential genes after irradiation in colorectal cancer cell HCT116. Key words: Colorectal neoplasms; Radiation resistance; Different expression genes; Bioinformatics

Traditional treatment of bacterial infections relies heavily on the use of antibacterial compounds that either kill bacteria (bactericidal) or inhibit their growth (bacteriostatic). Typically, the targets for the main conventional antibiotics are essential cellular processes such as bacterial cell wall biosynthesis, bacterial protein synthesis, and bacterial DNA replication and repair. However, resistance to these drugs arises and spreads very rapidly, even to such an extent that bacteria have been identified that are simultaneously resistant to all available antibiotics [1]. The increasing occurrence of resistant bacteria gradually renders antibiotics ineffective in treating infections and has enormous human and economic consequences worldwide. As a result, the identification of novel drug targets and the development of novel therapeutics constitute an important area of current scientific research. An alternative to killing or inhibiting growth of pathogenic bacteria is the specific attenuation of bacterial virulence, which can be attained by targeting key regulatory systems that mediate the expression of virulence factors. One of the target regulatory systems is quorum sensing (QS), or bacterial cell-to-cell communication. QS is a mechanism of gene regulation in which bacteria coordinate the expression of certain genes in response to the presence or absence of small signal molecules (Figure 1). Figure 1 General scheme of a quorum sensing system. Quorum Sensing: Bacterial Cell-to-Cell Communication QS was first discovered in the marine bacterium Vibrio fischeri and was thought to be restricted to only a limited series of species. Later on, similar systems were found to be present in many other Gram-negative bacteria. These Gram-negative bacteria use acylated homoserine lactones (AHLs) as signal molecules (for a review see [2]). AHLs are typically produced by a homolog of V. fischeri LuxI and detected by a homolog of V. fischeri LuxR. In addition to the AHL-mediated systems in Gram-negative bacteria, some Gram-positive bacteria also regulate a variety of processes by QS. The QS systems of Streptococcus pneumoniae, Bacillus subtilis, and Staphylococcus aureus, for instance, have been extensively studied (for a review see [3]). A different kind of QS system is found in vibrios. These bacteria use multichannel QS systems in which different types of signal molecules are produced. The signal molecules are detected at the cell surface by membrane-bound, two-component receptor proteins that feed a common phosphorylation/dephosphorylation signal transduction cascade (for a review on QS in vibrios, see [4]). One of the signals produced by vibrios is the so-called autoinducer 2 (AI-2), a furanosyl borate diester [5]. AI-2 activity has been detected in many different species (Gram-negative as well as Gram-positive), although its function as a signal is not generally accepted for all species (for a detailed discussion see [6]). The language of bacteria seems to be even more diversified as new QS systems, using different types of signal molecules, are still being discovered [7].