The novel potential multidrug-resistance biomarkers for Pseudomonas aeruginosa lung infections using transcriptomics data analysis

Development of multidrug resistance is the main obstacle for treating infections of Pseudomonas aeruginosa, an opportunistic pathogen responsible for a wide range of persistent infections throughout the body. Hence, identifying the major genes contributing to the development of multidrug resistance in Pseudomonas aeruginosa could help to introduce new efficient drugs to prevent resistance development. Here we conducted a differential gene expression analysis and a series of systems biology investigations on a RNASeq data set of multidrug resistant Pseudomonas aeruginosa isolates obtained from the patientsâ�� airways and wild-type, drug-sensitive strains. Respectively 67 and 178 up- and down-regulated genes were detected, including several genes of unknown functions that their functional characterization will help to elucidate the hidden mechanisms for multidrug resistance development in Pseudomonas aeruginosa. By inspecting the constructed gene regulatory network, two cases of feed forward loops were identified which in the case of establishing the type of regulatory interactions between transcription factors and their target genes, as activatory or inhibitory, their true contribution to multidrug resistance will be better understood. Inspecting the constructed gene co-expression network revealed co-expression between four deregulated genes including PA1432830, PA1403380, fpvA and PA14₁₅₆₁₀ and four already known drug resistance biomarkers. Functional characterization of these four co-expressed genes, will elucidate their possible roles in the process of multidrug resistance development in Pseudomonas aeruginosa. These findings will suggest new potential multidrug resistance biomarkers that following confirmation by larger number of samples, can be considered as new promising drug targets. © 2021 The Author

Genome-scale co-expression network comparison across escherichia coli and salmonella enterica serovar typhimurium reveals significant conservation at the regulon level of local regulators despite their dissimilar lifestyles

Availability of genome-wide gene expression datasets provides the opportunity to study gene expression across different organisms under a plethora of experimental conditions. In our previous work, we developed an algorithm called COMODO (COnserved MODules across Organisms) that identifies conserved expression modules between two species. In the present study, we expanded COMODO to detect the co-expression conservation across three organisms by adapting the statistics behind it. We applied COMODO to study expression conservation/divergence between Escherichia coli, Salmonella enterica, and Bacillus subtilis. We observed that some parts of the regulatory interaction networks were conserved between E. coli and S. enterica especially in the regulon of local regulators. However, such conservation was not observed between the regulatory interaction networks of B. subtilis and the two other species. We found co-expression conservation on a number of genes involved in quorum sensing, but almost no conservation for genes involved in pathogenicity across E. coli and S. enterica which could partially explain their different lifestyles. We concluded that despite their different lifestyles, no significant rewiring have occurred at the level of local regulons involved for instance, and notable conservation can be detected in signaling pathways and stress sensing in the phylogenetically close species S. enterica and E. coli. Moreover, conservation of local regulons seems to depend on the evolutionary time of divergence across species disappearing at larger distances as shown by the comparison with B. subtilis. Global regulons follow a different trend and show major rewiring even at the limited evolutionary distance that separates E. coli and S. enterica

Differential miRNAs expression pattern of irradiated breast cancer cell lines is correlated with radiation sensitivity

Radiotherapy is a fundamental step in the treatment of breast cancer patients. The treatment efficiency is however reduced by the possible onset of radiation resistance. In order to develop the effective treatment approach, it is important to understand molecular basis of radiosensitivity in breast cancer. The purpose of the present study was to investigate different radiation response of breast cancer cell lines, and find out if this response may be related to change in the microRNAs expression profile. MDA-MB-231 and T47D cells were subjected to different doses of radiation, then MTT and clonogenic assays were performed to assess radiation sensitivity. Cytofluorometric and western blot analysis were performed to gain insight into cell cycle distribution and protein expression. MicroRNA sequencing and bioinformatics prediction methods were used to identify the difference in microRNAs expression between two breast cancer cells and the related genes and pathways. T47D cells were more sensitive to radiation respect to MDA-MB-231 cells as demonstrated by a remarkable G2 cell cycle arrest followed by a greater reduction in cell viability and colony forming ability. Accordingly, T47D cells showed higher increase in the phosphorylation of ATM, TP53 and CDK1 (markers of radiation response) and faster and more pronounced increase in RAD51 and γH2AX expression (markers of DNA damage), when compared to MDA-MB-231 cells. The two cell lines had different microRNAs expression profiles with a confirmed significant differential expression of miR-16-5p, which targets cell cycle related genes and predicts longer overall survival of breast cancer patients, as determined by bioinformatics analysis. These results suggest a possible role for miR-16-5p as radiation sensitizing microRNA and as prognostic/predictive biomarker in breast cancer. © 2020, The Author(s)

Comprehensive transcriptomic analysis of papillary thyroid cancer: potential biomarkers associated with tumor progression

Purpose: Identification of stage-specific prognostic/predictive biomarkers in papillary thyroid carcinoma (PTC) could lead to its more efficient clinical management. The main objective of this study was to characterize the stage-specific deregulation in genes and miRNA expression in PTC to identify potential prognostic biomarkers. Methods: 495 RNASeq and 499 miRNASeq PTC samples (stage I�IV) as well as, respectively, 56 and 57 normal samples were retrieved from The Cancer Genome Atlas (TCGA). Differential expression analysis was performed using DESeq 2 to identify deregulation of genes and miRNAs between sequential stages. To identify the minority of patients who progress to higher stages, we performed clustering analysis on stage I RNASeq data. An independent PTC RNASeq data set (BioProject accession PRJEB11591) was also used for the validation of the results. Results: LTF and PLA2R1 were identified as two promising biomarkers down-regulated in a subgroup of stage I (both in TCGA and in the validation data set) and in the majority of stage IV of PTC (in TCGA data set). hsa-miR-205, hsa-miR-509-2, hsa-miR-514-1 and hsa-miR-514-2 were also detected as up-regulated miRNAs in both PTC patients with stage I and stage III. Hierarchical clustering of stage I samples showed substantial heterogeneity in the expression pattern of PTC indicating the necessity of categorizing stage I patients based on the expressional alterations of specific biomarkers. Conclusion: Stage I PTC patients showed large amount of expressional heterogeneity. Therefore, risk stratification based on the expressional alterations of candidate biomarkers could be an important step toward personalized management of these patients. © 2020, Italian Society of Endocrinology (SIE)

Large contribution of copy number alterations in early stage of Papillary Thyroid Carcinoma

Papillary Thyroid Carcinoma (PTC) accounts for approximately 85 of patients with thyroid cancer. Despite its indolent nature, progression to higher stages is expected in a subgroup of patients. Hence, genomic characterization of the early stages of PTC may help to identify this subgroup, leading to better clinical management. Here, we conducted a comprehensive mutational and somatic copy number alteration (SCNA) investigation on 277 stage one PTC from TCGA. SCNA analysis revealed amplification and deletion of several cancer related genes. We found amplification of 60 oncogenes (Oncs), from which 15 were recurrently observed. Deletion of 58 tumor suppressors (TSs) was also detected. MAPK, PI3K-Akt, Rap1 and Ras were the signaling pathways with large numbers of amplified Oncs. On the other hand, deleted TSs belonged mostly to cell cycle, PI3K-Akt, mTOR and cellular senescence pathways. This suggests that despite heterogeneity in SCNA events, the final results would be the activation/deactivation of a few cancer signaling pathways. Of note, despite large amounts of heterogeneity in stage one PTC, recurrent broad deletion on Chr22 was detected in 21 individuals, leading to deletion of several tumor suppressors. In parallel, the oncogenic/pathogenic mutations in the RTK-RAS and PI3k-Akt pathways were detected. However, no pathogenic mutation was identified in known tumor suppressor genes. In order to identify a potential subgroup of BRAF (V600E) positive patients, who might progress to higher stages, low frequency mutations accompanying BRAF (V600E) were also identified. In conclusion, our findings imply that SCNA have a substantial contribution to early stages of PTC. Experimental validation of the observed genomic alterations could help to stratify patients at the time of diagnosis, and to move toward precision medicine in PTC. © 202

Impact of human rhinoviruses on gene expression in pediatric patients with severe acute respiratory infection

Human rhinovirus (HRV) is one of the most common viruses, causing mild to severe respiratory tract infections in children and adults. Moreover, it can lead to patients� hospitalization. Nowadays, evaluation of gene expression alterations in host cells due to viral respiratory infections considered essential to understand the viral effects on cells. Objective: In this study, we aimed to find important differentially expressed genes (DEGs) related to rhinitis and asthma exacerbation stimulated with Poly (I: C) and then to validate their expression in clinical samples of children how were less than 5 years old, hospitalized with severe acute respiratory infection (SARI) due to HRV infection in comparison with healthy cases. Methods: Eight candidate genes involved in immunity, viral defense, inflammation, P53 pathway, and viral release processes were selected based on the analysis of a gene expression data set (GSE51392) and gene enrichment analysis. Then quantitative real-time PCR on cDNAs was performed for selected genes. The results were analyzed by Livak method and visualized by GraphPad prism software (8.4.3). Result: CXCL10, CMPK2, RSAD2, SERPINA3, TNFAIP6, CXCL14, IVNS1AB, and ZMAT3 were selected based on the enrichment and topological analysis of the constructed protein-protein interaction (PPI) network. Laboratory validation by real-time PCR showed CXCL10, CMPK2, RSAD2, SERPINA3, and TNFAIP6 (belonged to immunity, inflammatory responses and viral defense) were up-regulated, whereas CXCL14 (related to immunity) and IVNS1AB, ZMAT3 (associated to Influenza and P53 pathway) were down-regulated. Conclusion: Our results showed, that in children less than 5 years old affected by HRV and hospitalized with SARI, the inflammatory responses, antiviral defense, and type 1 interferon-signaling pathway have significantly affected by viral infection. © 202

Dysregulation of Key Proteinases in Aspergillus fumigatus Induced by Blood Platelets

Background: Aspergillus fumigatus is the most common species causing invasive aspergillosis (IA), a life- threatening infection with more than 80 mortality. Interactions between A. fumigatus and human blood platelets lead to intravascular thrombosis and localized infarcts. To better understand A. fumigatus pathogenesis, we aimed to analyze the genetic basis of interactions between the pathogen and blood platelets.Methods: A bioinformatic pipeline on microarray gene expression dataset, including analysis of differentially expressed genes (DEGs) using Limma R package and their molecular function, as well as biological pathways identification, was conducted to find the effective genes involved in IA. In the wet phase, the gene expression patterns following fungal exposure to blood platelets at 15, 30, 60, and 180 min were evaluated by quantitative reverse transcriptase-PCR analysis.Results: Three genes encoding aspartic endopeptidases including (Pep1), (Asp f 13), and (P-glucanase) were the standing candidates. The invasion-promoting fungal proteinase-encoding genes were down- regulated after 30 min of hyphal incubation with blood platelets, and then up-regulated at 60 and 180 min, although only Pep1 was greater than the control at the 60and 180 min time points. Also, the same genes were downregulated in more the clinical isolates relative to the standard strain CBS 144.89.Conclusions: Our findings delineate the possible induction of fungal-encoded proteinases by blood platelets. This provides a new research line into A. fumigatus � molecular pathogenesis. Such insight into IA pathogenesis might also guide researchers toward novel platelet-based therapies that involve molecular interventions, especially in IA patients. © 2021, Reports of Biochemistry & Molecular Biology .All Rights Reserved