Author Correction: Defects in mtDNA replication challenge nuclear genome stability through nucleotide depletion and provide a unifying mechanism for mouse progerias

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Defects in mtDNA replication challenge nuclear genome stability through nucleotide depletion and provide a unifying mechanism for mouse progerias

Mitochondrial DNA (mtDNA) mutagenesis and nuclear DNA repair defects are considered cellular mechanisms of ageing. mtDNA mutator mice with increased mtDNA mutagenesis show signs of premature ageing. However, why patients with mitochondrial diseases, or mice with other forms of mitochondrial dysfunction, do not age prematurely remains unknown. Here, we show that cells from mutator mice display challenged nuclear genome maintenance similar to that observed in progeric cells with defects in nuclear DNA repair. Cells from mutator mice show slow nuclear DNA replication fork progression, cell cycle stalling and chronic DNA replication stress, leading to double-strand DNA breaks in proliferating progenitor or stem cells. The underlying mechanism involves increased mtDNA replication frequency, sequestering of nucleotides to mitochondria, depletion of total cellular nucleotide pools, decreased deoxynucleoside 5'-triphosphate (dNTP) availability for nuclear genome replication and compromised nuclear genome maintenance. Our data indicate that defects in mtDNA replication can challenge nuclear genome stability. We suggest that defects in nuclear genome maintenance, particularly in the stem cell compartment, represent a unified mechanism for mouse progerias. Therefore, through their destabilizing effects on the nuclear genome, mtDNA mutations are indirect contributors to organismal ageing, suggesting that the direct role of mtDNA mutations in driving ageing-like symptoms might need to be revisited.

Lymphatic endothelium stimulates melanoma metastasis and invasion via MMP14-dependent Notch3 and β1-integrin activation

Lymphatic invasion and lymph node metastasis correlate with poor clinical outcome in melanoma. However, the mechanisms of lymphatic dissemination in distant metastasis remain incompletely understood. We show here that exposure of expansively growing human WM852 melanoma cells, but not singly invasive Bowes cells, to lymphatic endothelial cells (LEC) in 3D co-culture facilitates melanoma distant organ metastasis in mice. To dissect the underlying molecular mechanisms, we established LEC co-cultures with different melanoma cells originating from primary tumors or metastases. Notably, the expansively growing metastatic melanoma cells adopted an invasively sprouting phenotype in 3D matrix that was dependent on MMP14, Notch3 and β1-integrin. Unexpectedly, MMP14 was necessary for LEC-induced Notch3 induction and coincident β1-integrin activation. Moreover, MMP14 and Notch3 were required for LEC-mediated metastasis of zebrafish xenografts. This study uncovers a unique mechanism whereby LEC contact promotes melanoma metastasis by inducing a reversible switch from 3D growth to invasively sprouting cell phenotype.

Dynamic visualization of multi-level molecular data: The Director package in R

BACKGROUND AND OBJECTIVE

High-throughput measurement technologies have triggered a rise in large-scale cancer studies containing multiple levels of molecular data. While there are a number of efficient methods to analyze individual data types, there are far less that enhance data interpretation after analysis. We present the R package Director, a dynamic visualization approach to linking and interrogating multiple levels of molecular data after analysis for clinically meaningful, actionable insights.

METHODS

Sankey diagrams are traditionally used to represent quantitative flows through multiple, distinct events. Regulation can be interpreted as a flow of biological information through a series of molecular interactions. Functions in Director introduce novel drawing capabilities to make Sankey diagrams robust to a wide range of quantitative measures and to depict molecular interactions as regulatory cascades. The package streamlines creation of diagrams using as input quantitative measurements identifying nodes as molecules of interest and paths as the interaction strength between two molecules.

RESULTS

Director's utility is demonstrated with quantitative measurements of candidate microRNA-gene networks identified in an ovarian cancer dataset. A recent study reported eight miRNAs as master regulators of signature genes in epithelial-mesenchymal transition (EMT). The Sankey diagrams generated with data from this study furthers interpretation of the miRNAs' roles by revealing potential co-regulatory behavior in the extracellular matrix (ECM). An additional analysis identified 32 genes differentially expressed between good and poor prognosis patients in four significant pathways (FDR  ≤  0.1), three of which support a complementary role of the ECM in ovarian cancer. The resulting diagram created with Director suggest elevated levels of COL11A1, INHBA, and THBS2 - a signature feature of metastasis [1] - and decreased levels of their targeting miRNAs define poor prognosis.

CONCLUSION

We have demonstrated a visualization approach suitable for implementation in an analysis workflow, linking multiple levels of molecular data to gain novel perspective on candidate biomarkers in a complex disease. The diagrams are dynamic, easily replicable, and rendered locally as HTML files to facilitate sharing. The R package Director is simple to use and widely available on all operating systems through Bioconductor (http://bioconductor.org/packages/Director) and GitHub (http://kzouchka.github.io/Director).

MicroRNAs regulate key cell survival pathways and mediate chemosensitivity during progression of diffuse large B-cell lymphoma

Despite better therapeutic options and improved survival of diffuse large B-cell lymphoma (DLBCL), 30–40% of the patients experience relapse or have primary refractory disease with a dismal prognosis. To identify biological correlates for treatment resistance, we profiled microRNAs (miRNAs) of matched primary and relapsed DLBCL by next-generation sequencing. Altogether 492 miRNAs were expressed in the DLBCL samples. Thirteen miRNAs showed significant differential expression between primary and relapse specimen pairs. Integration of the differentially expressed miRNAs with matched mRNA expression profiles identified highly anti-correlated, putative targets, which were significantly enriched in cancer-associated pathways, including phosphatidylinositol (PI)), mitogen-activated protein kinase (MAPK), and B-cell receptor (BCR) signaling. Expression data suggested activation of these pathways during disease progression, and functional analyses validated that miR-370-3p, miR-381-3p, and miR-409-3p downregulate genes on the PI, MAPK, and BCR signaling pathways, and enhance chemosensitivity of DLBCL cells in vitro. High expression of selected target genes, that is, PIP5K1 and IMPA1, was found to be associated with poor survival in two independent cohorts of chemoimmunotherapy-treated patients (n = 92 and n = 233). Taken together, our results demonstrate that differentially expressed miRNAs contribute to disease progression by regulating key cell survival pathways and by mediating chemosensitivity, thus representing potential novel therapeutic targets.

SePIA: RNA and small RNA sequence processing, integration, and analysis

Background

Large-scale sequencing experiments are complex and require a wide spectrum of computational tools to extract and interpret relevant biological information. This is especially true in projects where individual processing and integrated analysis of both small RNA and complementary RNA data is needed. Such studies would benefit from a computational workflow that is easy to implement and standardizes the processing and analysis of both sequenced data types.

Results

We developed SePIA (Sequence Processing, Integration, and Analysis), a comprehensive small RNA and RNA workflow. It provides ready execution for over 20 commonly known RNA-seq tools on top of an established workflow engine and provides dynamic pipeline architecture to manage, individually analyze, and integrate both small RNA and RNA data. Implementation with Docker makes SePIA portable and easy to run. We demonstrate the workflow’s extensive utility with two case studies involving three breast cancer datasets. SePIA is straightforward to configure and organizes results into a perusable HTML report. Furthermore, the underlying pipeline engine supports computational resource management for optimal performance.

Conclusion

SePIA is an open-source workflow introducing standardized processing and analysis of RNA and small RNA data. SePIA’s modular design enables robust customization to a given experiment while maintaining overall workflow structure. It is available at http://anduril.org/sepia.

Electronic supplementary material

The online version of this article (doi:10.1186/s13040-016-0099-z) contains supplementary material, which is available to authorized users.

Selective microRNA-Offset RNA expression in human embryonic stem cells

Small RNA molecules, including microRNAs (miRNAs), play critical roles in regulating pluripotency, proliferation and differentiation of embryonic stem cells. miRNA-offset RNAs (moRNAs) are similar in length to miRNAs, align to miRNA precursor (pre-miRNA) loci and are therefore believed to derive from processing of the pre-miRNA hairpin sequence. Recent next generation sequencing (NGS) studies have reported the presence of moRNAs in human neurons and cancer cells and in several tissues in mouse, including pluripotent stem cells. In order to gain additional knowledge about human moRNAs and their putative development-related expression, we applied NGS of small RNAs in human embryonic stem cells (hESCs) and fibroblasts. We found that certain moRNA isoforms are notably expressed in hESCs from loci coding for stem cell-selective or cancer-related miRNA clusters. In contrast, we observed only sparse moRNAs in fibroblasts. Consistent with earlier findings, most of the observed moRNAs derived from conserved loci and their expression did not appear to correlate with the expression of the adjacent miRNAs. We provide here the first report of moRNAs in hESCs, and their expression profile in comparison to fibroblasts. Moreover, we expand the repertoire of hESC miRNAs. These findings provide an expansion on the known repertoire of small non-coding RNA contents in hESCs.

MicroRNA expression profiling reveals miRNA families regulating specific biological pathways in mouse frontal cortex and hippocampus

MicroRNAs (miRNAs) are small regulatory molecules that cause post-transcriptional gene silencing. Although some miRNAs are known to have region-specific expression patterns in the adult brain, the functional consequences of the region-specificity to the gene regulatory networks of the brain nuclei are not clear. Therefore, we studied miRNA expression patterns by miRNA-Seq and microarrays in two brain regions, frontal cortex (FCx) and hippocampus (HP), which have separate biological functions. We identified 354 miRNAs from FCx and 408 from HP using miRNA-Seq, and 245 from FCx and 238 from HP with microarrays. Several miRNA families and clusters were differentially expressed between FCx and HP, including the miR-8 family, miR-182|miR-96|miR-183 cluster, and miR-212|miR-312 cluster overexpressed in FCx and miR-34 family overexpressed in HP. To visualize the clusters, we developed support for viewing genomic alignments of miRNA-Seq reads in the Chipster genome browser. We carried out pathway analysis of the predicted target genes of differentially expressed miRNA families and clusters to assess their putative biological functions. Interestingly, several miRNAs from the same family/cluster were predicted to regulate specific biological pathways. We have developed a miRNA-Seq approach with a bioinformatic analysis workflow that is suitable for studying miRNA expression patterns from specific brain nuclei. FCx and HP were shown to have distinct miRNA expression patterns which were reflected in the predicted gene regulatory pathways. This methodology can be applied for the identification of brain region-specific and phenotype-specific miRNA-mRNA-regulatory networks from the adult and developing rodent brain.