<i>In silico</i> structural analysis of secretory clusterin to assess pathogenicity of mutations identified in the evolutionarily conserved regions

Clusterin (CLU) is a secreted glycoprotein, heterodimeric in nature, and is expressed in a wide variety of tissues and body fluids such as serum and plasma. CLU has also been known to be a promising biomarker for cell death, malignancy, cancer progression, and resistance development. However, the lack of a CLU crystal structure obstructs understanding the possible role of reported mutations on the structure, and the subsequent effects on downstream signaling pathways and cancer progression. Considering the importance of crystal structure, a model structure of the pre-secretory isoform of CLU was built to predict the effect of mutations at the molecular level. Ab initio model was built using RaptorX, and loop refinement and energy minimization were carried out with ModLoop, ModRefiner, and GalaxyWeb servers. The cancer associated mutational spectra of CLU was retrieved from the cBioPortal server and 117 unique missense mutations were identified. Evolutionarily conserved regions and pathogenicity of mutations identified in CLU were analyzed using ConSurf and Rhapsody, respectively. Furthermore, sequence and structure-based mutational analysis were carried out with iSTABLE, DynaMut and PremPS servers. Molecular dynamics simulations were carried out with GROMACS for 50 ns to determine the stability of the wild type and mutant protein structures. A dynamically stable model structure of pre-secretory CLU (psCLU) which has high concurrence with the sequence based secondary structure predictions has been explored. Changes in the intra-atomic interactions and folding pattern between wild type and mutant structures were observed. To our conclusion, eleven mutations with the highest structural and functional significance have been predicted to have pathogenic and deleterious effects. Communicated by Ramaswamy H. Sarma</p

Additional file 1: Table S2. of Non-typhoidal Salmonella DNA traces in gallbladder cancer

Primer sequences used for detection of Salmonella (PDF 122 kb

Additional file 3: Table S1. of Non-typhoidal Salmonella DNA traces in gallbladder cancer

Detailed annotation table of read sequences of different Salmonella species identified across gallbladder cancer patient samples. (PDF 348 kb

Additional file 5: Figure S3. of Non-typhoidal Salmonella DNA traces in gallbladder cancer

Sanger validation of Salmonella read sequences in gall bladder cancer samples Individual read sequences were PCR amplified and Sanger sequencing trace of individual read sequence with their blast output is represented in the figure. (PDF 1437 kb

Additional file 4: Figure S2. of Non-typhoidal Salmonella DNA traces in gallbladder cancer

Specificity and Sensitivity for detection of Salmonella reads in whole exome sequence of gallbladder samples. (A) Specificity for detection of Salmonella reads in whole exome sequence of gallbladder samples. Exome sequenced reads were reversed (not complement) to maintain the genome complexity and used an input file to detect random Salmonella reads. No Salmonella reads were found in the samples with reversed whole exome sequence. (B) Sensitivity for detection of Salmonella reads in gallbladder samples as a function of increasing genome sequence coverage. Gallbladder tumour sample 16 T with highest number of Salmonella reads was down-sampled to 1x, 5x, 10x, 15x, 25x, 50x, 75x and 100x. Salmonella reads were counted (black line) and plotted against increasing coverage of the genome on x-axis. (PDF 5395 kb

Additional file 2 of Progesterone modulates the DSCAM-AS1/miR-130a/ESR1 axis to suppress cell invasion and migration in breast cancer

Additional file 2.Table S1. List of primer sequences. Table S2. Differentially expressed genes upon progesterone treatment to breast primary tumors. Table S3. Differentially expressed genes upon progesterone treatment to T47D (PR+/ER+/Her2-) cell line. Table S4. Differentially expressed genes upon progesterone treatment to MDA-MB-231 (PR-/ER-/Her2-) cell line. Table S5. List of miRNAs binding to DSCAM-AS1. Table S6. List of miRNAs targeting 3'-UTR-ESR1

Additional file 1 of Progesterone modulates the DSCAM-AS1/miR-130a/ESR1 axis to suppress cell invasion and migration in breast cancer

Additional file 1.Fig. S1. Differentially expressed genes upon progesterone treatment in breast cancer cell lines (A, B) Volcano plot depicting differentially expressed genes upon progesterone treatment in (A) T47-D and (B) MDA-MB-231 breast cancer cell lines, identified in RNA-sequencing data. X- and Y-axes represent log2(fold change) and -log10(p-value), respectively. Each dot represents expression fold change for an individual gene. All genes above the horizontal red line and outside central blue quadrant are significantly deregulated upon progesterone treatment. The total number of significantly up-regulated and down-regulated genes are represented on the top right and top left of the plot respectively. Fig. S2. DSCAM-AS1 expression in progesterone-treated and -untreated primary breast tumor samples. Gene expression normalization was performed using median of ratios method (DESeq2). The normalized values are plot on Y-axis. X-axis indicates breast cancer patient samples (samples #1 to #30). Median DSCAM-AS1 expression in each group is indicated. Fig. S3. Real time PCR analysis of differentially expressed lncRNAs in MCF7 cells treated with progesterone. Data are normalized with expression of GAPDH and relative fold changes with respect to vehicle control are plotted on Y-axis. Changes in the normalized expression of lncRNAs upon treatment are plotted as relative fold change (2-ΔΔCT) with respect to expression in vehicle control for the same cell line. This consist of data from three biological replicates. The horizontal black line represents normalized expression of lncRNAs in vehicle-treated cells. SGK1, a progesterone-responsive gene, is used as a positive control. p-value calculated using Student’s t-test. *, p0.05. Fig. S7. Transient overexpression of DSCAM-AS1 reduces miR-130a and increases ESR1 levels in PR-positive breast cancer cells (A-C) Real-time PCR analysis indicating expression of (A) DSCAM-AS1, (B) ESR1, and (C) miR-130a in T47-D cells upon transient overexpression of DSCAM-AS1. Relative fold change of expression of gene/lncRNA and miR130a with respect to that of ACTB and U6, respectively, is plotted. p-value calculated using Student’s t-test. *, p<0.05; **,p<0.01; ***,p<0.001; ****,p<0.0001; ns, non-significant. Fig. S8. Expression of miR-130a is inversely correlated with DSCAM-AS1 and ESR1 expression in the TCGA breast cancer RNA-seq dataset (A, B) Expression plot for miR-130a in the TCGA breast cancer samples expressing high and low levels of (A) DSCAM-AS1 and (B) ESR1 high and low TCGA breast cancer samples. Upper and lower quartile patient groups in terms of DSCAM-AS1 or ESR1 expression are included in the analysis. Normalized expression of miR-130a is plotted on Y-axis

Additional file 2: Figure S1. of Non-typhoidal Salmonella DNA traces in gallbladder cancer

Abundance and annotation of Salmonella reads found across the 16 of 26 gall bladder cancer samples. Heat map representation of individual Salmonella reads (in rows) identified from 6 different isolates found across the 16 gall bladder cancer samples (in column) is shown. Variable length and number of overlapping reads, each of 150 bp obtained from paired end Illumina sequence for each isolate, were assembled into contigs based on Clustal X2 multiple alignment. The unique total length of contigs generated is shown in second column reflecting the total length of the gene covered in the study. The contigs generated were annotated based on gene annotation database of Salmonella isolates from NCBI database. A representative general class for all genes identified is shown in the third column. (PDF 11190 kb

Patient Demographics.

<p>Patient Demographics.</p

Molecular Epidemiological status of EGFR mutation (adapted [15]).

<p>Molecular Epidemiological status of EGFR mutation (adapted <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076164#pone.0076164-PanChyrYang1" target="_blank">[15]</a>).</p