The TGF-β-inducible miR-23a cluster attenuates IFN-γ levels and antigen-specific cytotoxicity in human CD8+ T cells

Cytokine secretion and degranulation represent key components of CD8(+) T-cell cytotoxicity. While transcriptional blockade of IFN-γ and inhibition of degranulation by TGF-β are well established, we wondered whether TGF-β could also induce immune-regulatory miRNAs in human CD8(+) T cells. We used miRNA microarrays and high-throughput sequencing in combination with qRT-PCR and found that TGF-β promotes expression of the miR-23a cluster in human CD8(+) T cells. Likewise, TGF-β up-regulated expression of the cluster in CD8(+) T cells from wild-type mice, but not in cells from mice with tissue-specific expression of a dominant-negative TGF-β type II receptor. Reporter gene assays including site mutations confirmed that miR-23a specifically targets the 3'UTR of CD107a/LAMP1 mRNA, whereas the further miRNAs expressed in this cluster-namely, miR-27a and -24-target the 3'UTR of IFN-γ mRNA. Upon modulation of the miR-23a cluster by the respective miRNA antagomirs and mimics, we observed significant changes in IFN-γ expression, but only slight effects on CD107a/LAMP1 expression. Still, overexpression of the cluster attenuated the cytotoxic activity of antigen-specific CD8(+) T cells. These functional data thus reveal that the miR-23a cluster not only is induced by TGF-β, but also exerts a suppressive effect on CD8(+) T-cell effector functions, even in the absence of TGF-β signaling.

Chromatin immunoprecipitation (ChIP) methodology and readouts

The identification of direct nuclear hormone receptor gene targets provides clues to their contribution to both development and cancer progression. Until recently, the identification of such direct target genes has relied on a combination of expression analysis and in silico searches for consensus binding motifs in gene promoters. Consensus binding motifs for transcription factors are often defined using in vitro DNA binding strategies. Such in vitro strategies fail to account for the many factors that contribute significantly to target selection by transcription factors in cells beyond the recognition of these short consensus DNA sequences. These factors include DNA methylation, chromatin structure, posttranslational modifications of transcription factors, and the cooperative recruitment of transcription factor complexes. Chromatin immunoprecipitation (ChIP) provides a means of isolating transcription factor complexes in the context of endogenous chromatin, allowing the identification of direct transcription factor targets. ChIP can be combined with site-specific PCR for candidate binding sites or alternatively with cloning, genomic microarrays or more recently direct high throughput sequencing to identify novel genomic targets. The application of ChIP-based approaches has redefined consensus binding motifs for transcription factors and provided important insights into transcription factor biology.

Taxonomic and Functional Diversity of Soil and Hypolithic Microbial Communities in Miers Valley, McMurdo Dry Valleys, Antarctica

The McMurdo Dry Valleys of Antarctica are an extreme polar desert. Mineral soils support subsurface microbial communities and translucent rocks support development of hypolithic communities on ventral surfaces in soil contact. Despite significant research attention, relatively little is known about taxonomic and functional diversity or their inter-relationships. Here we report a combined diversity and functional interrogation for soil and hypoliths of the Miers Valley in the McMurdo Dry Valleys of Antarctica. The study employed 16S rRNA fingerprinting and high throughput sequencing combined with the GeoChip functional microarray. The soil community was revealed as a highly diverse reservoir of bacterial diversity dominated by actinobacteria. Hypolithic communities were less diverse and dominated by cyanobacteria. Major differences in putative functionality were that soil communities displayed greater diversity in stress tolerance and recalcitrant substrate utilization pathways, whilst hypolithic communities supported greater diversity of nutrient limitation adaptation pathways. A relatively high level of functional redundancy in both soil and hypoliths may indicate adaptation of these communities to fluctuating environmental conditions.

Long-range Transcriptome Sequencing Reveals Cancer Cell Growth Regulatory Chimeric mRNA

mRNA chimeras from chromosomal translocations often play a role as transforming oncogenes. However, cancer transcriptomes also contain mRNA chimeras that may play a role in tumor development, which arise as transcriptional or post-transcriptional events. To identify such chimeras, we developed a deterministic screening strategy for long-range sequence analysis. High-throughput, long-read sequencing was then performed on cDNA libraries from major tumor histotypes and corresponding normal tissues. These analyses led to the identification of 378 chimeras, with an unexpectedly high frequency of expression (˜2 x 10(-5) of all mRNA). Functional assays in breast and ovarian cancer cell lines showed that a large fraction of mRNA chimeras regulates cell replication. Strikingly, chimeras were shown to include both positive and negative regulators of cell growth, which functioned as such in a cell-type-specific manner. Replication-controlling chimeras were found to be expressed by most cancers from breast, ovary, colon, uterus, kidney, lung, and stomach, suggesting a widespread role in tumor development.

Next-generation sequencing: a change of paradigm in molecular diagnostic validation

Next-generation sequencing (NGS) is beginning to show its full potential for diagnostic and therapeutic applications. In particular, it is enunciating its capacity to contribute to a molecular taxonomy of cancer, to be used as a standard approach for diagnostic mutation detection, and to open new treatment options that are not exclusively organ-specific. If this is the case, how much validation is necessary and what should be the validation strategy, when bringing NGS into the diagnostic/clinical practice? This validation strategy should address key issues such as: what is the overall extent of the validation? Should essential indicators of test performance such as sensitivity of specificity be calculated for every target or sample type? Should bioinformatic interpretation approaches be validated with the same rigour? What is a competitive clinical turnaround time for a NGS-based test, and when does it become a cost-effective testing proposition? While we address these and other related topics in this commentary, we also suggest that a single set of international guidelines for the validation and use of NGS technology in routine diagnostics may allow us all to make a much more effective use of resources.

The impact of next generation sequencing technologies on haematological research - A review

Next-generation sequencing (NGS) technologies have begun to revolutionize the field of haematological malignancies through the assessment of a patient's genetic makeup with a minimal cost. Significant discoveries have already provided a unique insight into disease initiation, risk stratification and therapeutic intervention. Sequencing analysis will likely form part of the routine diagnostic testing in the future. However, a number of important issues need to be addressed for that to become a reality with regard to result interpretation, laboratory workflow, data storage and ethical issues. In this review we summarize the contribution that NGS has already made to the field of haematological malignancies. Finally, we discuss the challenges that NGS technologies will bring in relation to data storage, ethical and legal issues and laboratory validation. Despite these challenges, we predict that high-throughput DNA sequencing will redefine haematological malignancies based on individualized genomic analysis.

Factors influencing success of clinical genome sequencing across a broad spectrum of disorders

To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges.

SNP discovery using Next Generation Transcriptomic Sequencing in Atlantic herring (Clupea harengus)

The introduction of Next Generation Sequencing (NGS) has revolutionised population genetics, providing studies of non-model species with unprecedented genomic coverage, allowing evolutionary biologists to address questions previously far beyond the reach of available resources. Furthermore, the simple mutation model of Single Nucleotide Polymorphisms (SNPs) permits cost-effective high-throughput genotyping in thousands of individuals simultaneously. Genomic resources are scarce for the Atlantic herring (Clupea harengus), a small pelagic species that sustains high revenue fisheries. This paper details the development of 578 SNPs using a combined NGS and high-throughput genotyping approach. Eight individuals covering the species distribution in the eastern Atlantic were bar-coded and multiplexed into a single cDNA library and sequenced using the 454 GS FLX platform. SNP discovery was performed by de novo sequence clustering and contig assembly, followed by the mapping of reads against consensus contig sequences. Selection of candidate SNPs for genotyping was conducted using an in silico approach. SNP validation and genotyping were performed simultaneously using an Illumina 1,536 GoldenGate assay. Although the conversion rate of candidate SNPs in the genotyping assay cannot be predicted in advance, this approach has the potential to maximise cost and time efficiencies by avoiding expensive and time-consuming laboratory stages of SNP validation. Additionally, the in silico approach leads to lower ascertainment bias in the resulting SNP panel as marker selection is based only on the ability to design primers and the predicted presence of intron-exon boundaries. Consequently SNPs with a wider spectrum of minor allele frequencies (MAFs) will be genotyped in the final panel. The genomic resources presented here represent a valuable multi-purpose resource for developing informative marker panels for population discrimination, microarray development and for population genomic studies in the wild.

Area-efficient high-speed 3D DWT processor architecture

An area-efficient high-throughput architecture based on distributed arithmetic is proposed for 3D discrete wavelet transform (DWT). The 3D DWT processor was designed in VHDL and mapped to a Xilinx Virtex-E FPGA. The processor runs up to 85 MHz, which can process the five-level DWT analysis of a 128 x 128 x 128 fMRI volume image in 20 ms.

Ultra-fast processing of gigapixel Tissue MicroArray images using high performance computing.

BACKGROUND:
tissue MicroArrays (TMAs) are a valuable platform for tissue based translational research and the discovery of tissue biomarkers. The digitised TMA slides or TMA Virtual Slides, are ultra-large digital images, and can contain several hundred samples. The processing of such slides is time-consuming, bottlenecking a potentially high throughput platform.
METHODS:
a High Performance Computing (HPC) platform for the rapid analysis of TMA virtual slides is presented in this study. Using an HP high performance cluster and a centralised dynamic load balancing approach, the simultaneous analysis of multiple tissue-cores were established. This was evaluated on Non-Small Cell Lung Cancer TMAs for complex analysis of tissue pattern and immunohistochemical positivity.
RESULTS:
the automated processing of a single TMA virtual slide containing 230 patient samples can be significantly speeded up by a factor of circa 22, bringing the analysis time to one minute. Over 90 TMAs could also be analysed simultaneously, speeding up multiplex biomarker experiments enormously.
CONCLUSIONS:
the methodologies developed in this paper provide for the first time a genuine high throughput analysis platform for TMA biomarker discovery that will significantly enhance the reliability and speed for biomarker research. This will have widespread implications in translational tissue based research.

Fully hardware based WFQ architecture for high-speed QoS packet scheduling

A full hardware implementation of a Weighted Fair Queuing (WFQ) packet scheduler is proposed. The circuit architecture presented has been implemented using Altera Stratix II FPGA technology, utilizing RLDII and QDRII memory components. The circuit can provide fine granularity Quality of Service (QoS) support at a line throughput rate of 12.8Gb/s in its current implementation. The authors suggest that, due to the flexible and scalable modular circuit design approach used, the current circuit architecture can be targeted for a full ASIC implementation to deliver 50 Gb/s throughput. The circuit itself comprises three main components; a WFQ algorithm computation circuit, a tag/time-stamp sort and retrieval circuit, and a high throughput shared buffer. The circuit targets the support of emerging wireline and wireless network nodes that focus on Service Level Agreements (SLA's) and Quality of Experience.

Systolic building block for high performance recursive filtering

A novel bit level systolic array is presented that can be used as a building block in the construction of recursive digital filters. The circuit accepts bit-parallel input data, is pipelined at the bit level, and exhibits a very high throughput rate. The most important feature of the circuit is that it allows recursive operations to be implemented directly without incurring the large m cycle latency (where m is approximately the word length) normally associated with such systems. The use of this circuit in the construction of both first- and second-order IIR (infinite-impulse-response) filters is described.

Computational cancer biology: education is a natural key to many locks

Background: Oncology is a field that profits tremendously from the genomic data generated by high-throughput technologies, including next-generation sequencing. However, in order to exploit, integrate, visualize and interpret such high-dimensional data efficiently, non-trivial computational and statistical analysis methods are required that need to be developed in a problem-directed manner.

Discussion: For this reason, computational cancer biology aims to fill this gap. Unfortunately, computational cancer biology is not yet fully recognized as a coequal field in oncology, leading to a delay in its maturation and, as an immediate consequence, an under-exploration of high-throughput data for translational research.

Summary: Here we argue that this imbalance, favoring 'wet lab-based activities', will be naturally rectified over time, if the next generation of scientists receives an academic education that provides a fair and competent introduction to computational biology and its manifold capabilities. Furthermore, we discuss a number of local educational provisions that can be implemented on university level to help in facilitating the process of harmonization.

An unbiased genetic screen reveals the polygenic nature of the influenza virus anti-interferon response

UNLABELLED: Influenza A viruses counteract the cellular innate immune response at several steps, including blocking RIG I-dependent activation of interferon (IFN) transcription, interferon (IFN)-dependent upregulation of IFN-stimulated genes (ISGs), and the activity of various ISG products; the multifunctional NS1 protein is responsible for most of these activities. To determine the importance of other viral genes in the interplay between the virus and the host IFN response, we characterized populations and selected mutants of wild-type viruses selected by passage through non-IFN-responsive cells. We reasoned that, by allowing replication to occur in the absence of the selection pressure exerted by IFN, the virus could mutate at positions that would normally be restricted and could thus find new optimal sequence solutions. Deep sequencing of selected virus populations and individual virus mutants indicated that nonsynonymous mutations occurred at many phylogenetically conserved positions in nearly all virus genes. Most individual mutants selected for further characterization induced IFN and ISGs and were unable to counteract the effects of exogenous IFN, yet only one contained a mutation in NS1. The relevance of these mutations for the virus phenotype was verified by reverse genetics. Of note, several virus mutants expressing intact NS1 proteins exhibited alterations in the M1/M2 proteins and accumulated large amounts of deleted genomic RNAs but nonetheless replicated to high titers. This suggests that the overproduction of IFN inducers by these viruses can override NS1-mediated IFN modulation. Altogether, the results suggest that influenza viruses replicating in IFN-competent cells have tuned their complete genomes to evade the cellular innate immune system and that serial replication in non-IFN-responsive cells allows the virus to relax from these constraints and find a new genome consensus within its sequence space.

IMPORTANCE: In natural virus infections, the production of interferons leads to an antiviral state in cells that effectively limits virus replication. The interferon response places considerable selection pressure on viruses, and they have evolved a variety of ways to evade it. Although the influenza virus NS1 protein is a powerful interferon antagonist, the contributions of other viral genes to interferon evasion have not been well characterized. Here, we examined the effects of alleviating the selection pressure exerted by interferon by serially passaging influenza viruses in cells unable to respond to interferon. Viruses that grew to high titers had mutations at many normally conserved positions in nearly all genes and were not restricted to the NS1 gene. Our results demonstrate that influenza viruses have fine-tuned their entire genomes to evade the interferon response, and by removing interferon-mediated constraints, viruses can mutate at genome positions normally restricted by the interferon response.

Comprehensive molecular pathology analysis of small bowel adenocarcinoma reveals novel targets with potential for clinical utility

Small bowel accounts for only 0.5% of cancer cases in the US but incidence rates have been rising at 2.4% per year over the past decade. One-third of these are adenocarcinomas but little is known about their molecular pathology and no molecular markers are available for clinical use. Using a retrospective 28 patient matched normal-tumor cohort, next-generation sequencing, gene expression arrays and CpG methylation arrays were used for molecular profiling. Next-generation sequencing identified novel mutations in IDH1, CDH1, KIT, FGFR2, FLT3, NPM1, PTEN, MET, AKT1, RET, NOTCH1 and ERBB4. Array data revealed 17% of CpGs and 5% of RNA transcripts assayed to be differentially methylated and expressed respectively (p < 0.01). Merging gene expression and DNA methylation data revealed CHN2 as consistently hypermethylated and downregulated in this disease (Spearman -0.71, p < 0.001). Mutations in TP53 which were found in more than half of the cohort (15/28) and Kazald1 hypomethylation were both were indicative of poor survival (p = 0.03, HR = 3.2 and p = 0.01, HR = 4.9 respectively). By integrating high-throughput mutational, gene expression and DNA methylation data, this study reveals for the first time the distinct molecular profile of small bowel adenocarcinoma and highlights potential clinically exploitable markers.