miRNome landscape analysis reveals a 30 miRNA core in retinoblastoma.

BACKGROUND: miRNAs exert their effect through a negative regulatory mechanism silencing expression upon hybridizing to their target mRNA, and have a prominent position in the control of many cellular processes including carcinogenesis. Previous miRNA studies on retinoblastoma (Rb) have been limited to specific miRNAs reported in other tumors or to medium density arrays. Here we report expression analysis of the whole miRNome on 12 retinoblastoma tumor samples using a high throughput microarray platform including 2578 mature miRNAs. METHODS: Twelve retinoblastoma tumor samples were analyzed using an Affymetrix platform including 2578 mature miRNAs. We applied RMA analysis to normalize raw data, obtained categorical data from detection call values, and also used signal intensity derived expression data. We used Diana-Tools-microT-CDS to find miRNA targets and ChromDraw to map miRNAs in chromosomes. RESULTS: We discovered a core-cluster of 30 miRNAs that were highly expressed in all the cases and a cluster of 993 miRNAs that were uniformly absent in all cases. Another 1022 miRNA were variably present in the samples reflecting heterogeneity between tumors. We explored mRNA targets, pathways and biological processes affected by some of these miRNAs. We propose that the core-cluster of 30 miRs represent miRNA machinery common to all Rb, and affecting most pathways considered hallmarks of cancer. In this core, we identified miR-3613 as a potential and critical down regulatory hub, because it is highly expressed in all the samples and its potential mRNA targets include at least 36 tumor suppressor genes, including RB1. In the variably expressed miRNA, 36 were differentially expressed between males and females. Some of the potential pathways targeted by these 36 miRNAs were associated with hormonal production. CONCLUSION: These findings indicate that Rb tumor samples share a common miRNA expression profile regardless of tumor heterogeneity, and shed light on potential novel therapeutic targets such as mir-3613 This is the first work to delineate the miRNA landscape in retinoblastoma tumor samples using an unbiased approach.

Fatal Psychrobacter sp. infection in a pediatric patient with meningitis identified by metagenomic next-generation sequencing in cerebrospinal fluid.

The genus Psychrobacter contains environmental, psychrophilic and halotolerant gram-negative bacteria considered rare opportunistic pathogens in humans. Metagenomics was performed on the cerebrospinal fluid (CSF) of a pediatric patient with meningitis. Nucleic acids were extracted, randomly amplified, and sequenced with the 454 GS FLX Titanium next-generation sequencing (NGS) system. Sequencing reads were assembled, and potential virulence genes were predicted. Phylogenomic and phylogenetic studies were performed. Psychrobacter sp. 310 was identified, and several virulence genes characteristic of pathogenic bacteria were found. The phylogenomic study and 16S rRNA gene phylogenetic analysis showed that the closest relative of Psychrobacter sp. 310 was Psychrobacter sanguinis. To our knowledge, this is the first report of a meningitis case associated with Psychrobacter sp. identified by NGS metagenomics in CSF from a pediatric patient. The metagenomic strategy based on NGS was a powerful tool to identify a rare unknown pathogen in a clinical case.

Detection of common chromosomal translocations in small round blue cell pediatric tumors.

BACKGROUND AND AIMS: Recurrent and specific chromosomal translocations have been described in four pediatric sarcomas belonging to the small round blue cell (SRBC) group of tumors. Identification of mRNA chimeras using RT-PCR discriminates among alveolar rhabdomyosarcoma (ARMS), Ewing's sarcoma (ES/pPNET), synovial sarcoma (SS) and desmoplastic small round cell tumor (DSRCT); however, frequencies of these translocations are variable. We present a retrospective study comparing histological examination and occurrence of major chromosomal translocations to validate the diagnosis and to assess the frequency of these molecular markers in a group of 92 small round blue cell (SRBC) tumor samples from Hospital Infantil de Mexico. METHODS: We tested a panel of RT-PCR assays to each RNA tumor sample from formalin-fixed, paraffin-embedded tumors to detect specific mRNA chimeras in 47 ES/pPNET, 19 ARMS, four SS, three DSRCT, and 19 other SRBC tumors. RESULTS: After excluding poor RNA quality samples, we found translocations in 17/31 ES/pPNET (54.8%), 10/19 ARMS (52.6%), 4/4 SS (100%) and 4/4 DSRCT (100%). We found disagreement in only three samples: one ES/pPNET and one embryonal rhabdomyosarcoma harbor a PAX3-FOXO1 translocation (for ARMS), and one neuroepithelioma harboring a EWS-WT1 (for DSRCT). Unsuitable RNA was found in 20/92 samples (21.7%) and was related to necrosis, small amount of tumor tissue, and use of nitric acid in bone biopsies, but was not related to age of the block. CONCLUSIONS: We found a significantly lower occurrence of chromosomal translocations in ES/pPNET compared to reports from other groups. Differences may exist in the frequencies of these molecular markers among different populations.

HOMO: A novel script for data mining of microarrays.

UNLABELLED: HOMO.pl is a perl script that allows extracting important registers from an extensive data table or microarrays results. It is very useful in data mining for microarrays analysis. HOMO works as a homogenizer that converts the initial data table into more specific and manageable data according to a list of important genes or terms. This is very useful when a pathway, a condition, or a GO-Term is studied. The HOMO script has two inputs and one principal output. A table with the microarray data results is used as an input and a list of genes or important terms is used as a second input. The output is an adjusted table from the microarray results that contains only the genes included in the input list. HOMO's principal goal is to simplify the subsequent analyses to the microarray data. AVAILABILITY: HOMO.pl and a suite of example files are available by electronic mail request.

Bacterial classification using genomic fingerprints obtained by virtual hybridization.

In silico genomic fingerprints were produced by virtual hybridization of 191 fully sequenced bacterial genomes using a set of 15,264 13-mer probes specially designed to produce universal whole genome fingerprints. A novel approach for constructing phylogenetic trees, based on comparative analysis of genomic fingerprints, was developed. The resultant bacterial phylogenetic tree had strong similarities to those produced from the alignment of conserved sequences. Notably, the trees derived from the alignment of other conserved COG genes divided the Bacillus and Corynebacterium genera into the same subgroups produced by the novel bacterial tree. A number of discrepancies between both techniques were observed for the grouping of some Lactobacillus species. However, a detailed analysis of the alignment of these genomes using other bioinformatics tools revealed that the grouping of these organisms in the novel tree was more satisfactory than the groupings from previous classifications, which used only a few conserved genes. All these data suggest that the bacterial taxonomy produced by genomic fingerprints is satisfactory, but sometimes different from classical taxonomies. Discrepancies probably arise because the fingerprinting technique analyzes genomic sequences and reveals more information than previously used approaches.