Additional file 6: Table S5. of Computational master-regulator search reveals mTOR and PI3K pathways responsible for low sensitivity of NCI-H292 and A427 lung cancer cell lines to cytotoxic action of p53 activator Nutlin-3

List of 62 genes up-regulated in Nutlin-3 insensitive cell lines and matching the disease category “Causal Lung Neoplasms”. This list is used for the promoter analysis. (XLSX 61 kb

Additional file 2: Table S1. of Computational master-regulator search reveals mTOR and PI3K pathways responsible for low sensitivity of NCI-H292 and A427 lung cancer cell lines to cytotoxic action of p53 activator Nutlin-3

Normalized expression values of all genes with detected expression in the studies conditions and mapped to Ensembl. In the tab “Nsen vs Sen” we give the results of Limma analysis of the LogFC between Nutlin-3 insensitive (Nsen) and sensitive cell lines. (XLSX 3291 kb

Additional file 3: Table S2. of Computational master-regulator search reveals mTOR and PI3K pathways responsible for low sensitivity of NCI-H292 and A427 lung cancer cell lines to cytotoxic action of p53 activator Nutlin-3

GO analysis of all 7 sets of genes - Up- and Down- regulated genes upon treatment by Nutlin-3 in two concentrations 5 μM and 30 μM of Nutlin-3 (p-value< 0.05, LogFC> 0.58 (which corresponds to FC > 1.5) for up-regulated and LogFC<− 0.58 for down-regulated genes). Parameter Sum_Logpval sums up logarithms of p-values for one GO term in different conditions of treatment. It allows to sort GO terms according to their total significance in all conditions. (XLSX 334 kb

Additional file 8: Table S7. of Computational master-regulator search reveals mTOR and PI3K pathways responsible for low sensitivity of NCI-H292 and A427 lung cancer cell lines to cytotoxic action of p53 activator Nutlin-3

Results of correlation analysis of gene expression in 52 cancer cell lines and their sensitivity (IC50) value towards Mdm2 inhibitor AMGMDS3. We found 168 genes positively correlated with IC50 (insensitivity to the Mdm2 inhibitor) and 227 genes negatively correlated (p-value < 0.01). (XLSX 2438 kb

Additional file 4: Table S3. of Computational master-regulator search reveals mTOR and PI3K pathways responsible for low sensitivity of NCI-H292 and A427 lung cancer cell lines to cytotoxic action of p53 activator Nutlin-3

Results of gene set enrichment analysis (GSEA) of the obtained three gene expression profiles of differences between sensitive and insensitive lung cancer cell lines. For that we used geneXplain platform and applied the pathways ontology of TRANSPATHŽ database. (XLSX 147 kb

Additional file 9: Table S8. of Computational master-regulator search reveals mTOR and PI3K pathways responsible for low sensitivity of NCI-H292 and A427 lung cancer cell lines to cytotoxic action of p53 activator Nutlin-3

Pathway analysis of the gene expression correlations using GSEA method and TRANSPATH pathway ontology. (XLSX 103 kb

Allelic types and HGDI of <i>B</i>. <i>abortus</i> strains for 16 loci in this study.

<p>Allelic types and HGDI of <i>B</i>. <i>abortus</i> strains for 16 loci in this study.</p

Epidemiology of Brucellosis and Genetic Diversity of <i>Brucella abortus</i> in Kazakhstan

<div><p>Brucellosis is a major zoonotic infection in Kazakhstan. However, there is limited data on its incidence in humans and animals, and the genetic diversity of prevalent strains is virtually unstudied. Additionally, there is no detailed overview of Kazakhstan brucellosis control and eradication programs. Here, we analyzed brucellosis epidemiological data, and assessed the effectiveness of eradication strategies employed over the past 70 years to counteract this infection. We also conducted multiple loci variable-number tandem repeat analysis (MLVA) of <i>Brucella abortus</i> strains found in Kazakhstan. We analyzed official data on the incidence of animal brucellosis in Kazakhstan. The records span more than 70 years of anti-brucellosis campaigns, and contain a brief description of the applied control strategies, their effectiveness, and their impact on the incidence in humans. The MLVA-16 method was used to type 94 strains of <i>B</i>. <i>abortus</i> and serial passages of <i>B</i>. <i>abortus</i> 82, a strain used in vaccines. MLVA-8 and MLVA-11 analyses clustered strains into a total of four and seven genotypes, respectively; it is the first time that four of these genotypes have been described. MLVA-16 analysis divided strains into 28 distinct genotypes having genetic similarity coefficient that varies from 60 to100% and a Hunter & Gaston diversity index of 0.871. MST analysis reconstruction revealed clustering into "Kazakhstani-Chinese (Central Asian)", "European" and "American" lines. Detection of multiple genotypes in a single outbreak confirms that poorly controlled trade of livestock plays a crucial role in the spread of infection. Notably, the MLVA-16 profile of the <i>B</i>. <i>abortus</i> 82 strain was unique and did not change during 33 serial passages. MLVA genotyping may thus be useful for epidemiological monitoring of brucellosis, and for tracking the source(s) of infection. We suggest that countrywide application of MLVA genotyping would improve the control of brucellosis in Kazakhstan.</p></div

Incidence of human brucellosis.

<p>Time in years is on the x-axis, incidence per 100,000 population is on the y-axis.</p

Geographical representation of <i>Brucella abortus</i> sample collection sites.

<p>Geographical representation of <i>Brucella abortus</i> sample collection sites.</p