Differential utilization of NF-kappaB RELA and RELB in response to extracellular versus intracellular polyIC stimulation in HT1080 cells

Abstract Background Pattern recognition receptors (PRRs) for double-stranded RNA (dsRNA) are components of innate immunity that recognize the presence of viral infection and initiate efficient defense mechanisms. In addition to previously well-characterized signaling pathways that are mediated by PKR and TLR3, new intracellular dsRNA sensors, that are members of CARD and DExD/H box helicase family, have been identified. However, the molecular mechanisms involved in the signaling pathways mediated by these new dsRNA sensors have not been extensively characterized. Results Here, we studied an intracellular dsRNA pathway in the human fibrosarcoma cell line HT1080, which is distinct from the TLR3-mediated extracellular dsRNA pathway. Particularly, the NF-kB subunits RELA and RELB were differentially utilized by these two dsRNA signaling pathways. In TLR3-mediated dsRNA signaling, siRNA knock-down studies suggested a limited role for RELA on regulation of interferon beta and other cytokines whereas RELB appeared to have a negative regulatory role. By contrast, intracellular dsRNA signaling was dependent on RELA, but not RELB. Conclusions Our study suggests that extracellular and intracellular dsRNA signaling pathways may utilize different NF-kB members, and particularly the differential utilization of RELB may be a key mechanism for powerful inductions of NF-kB regulated genes in the intracellular dsRNA signaling pathway

Exploiting the noise: improving biomarkers with ensembles of data analysis methodologies.

BackgroundThe advent of personalized medicine requires robust, reproducible biomarkers that indicate which treatment will maximize therapeutic benefit while minimizing side effects and costs. Numerous molecular signatures have been developed over the past decade to fill this need, but their validation and up-take into clinical settings has been poor. Here, we investigate the technical reasons underlying reported failures in biomarker validation for non-small cell lung cancer (NSCLC).MethodsWe evaluated two published prognostic multi-gene biomarkers for NSCLC in an independent 442-patient dataset. We then systematically assessed how technical factors influenced validation success.ResultsBoth biomarkers validated successfully (biomarker #1: hazard ratio (HR) 1.63, 95% confidence interval (CI) 1.21 to 2.19, P = 0.001; biomarker #2: HR 1.42, 95% CI 1.03 to 1.96, P = 0.030). Further, despite being underpowered for stage-specific analyses, both biomarkers successfully stratified stage II patients and biomarker #1 also stratified stage IB patients. We then systematically evaluated reasons for reported validation failures and find they can be directly attributed to technical challenges in data analysis. By examining 24 separate pre-processing techniques we show that minor alterations in pre-processing can change a successful prognostic biomarker (HR 1.85, 95% CI 1.37 to 2.50, P < 0.001) into one indistinguishable from random chance (HR 1.15, 95% CI 0.86 to 1.54, P = 0.348). Finally, we develop a new method, based on ensembles of analysis methodologies, to exploit this technical variability to improve biomarker robustness and to provide an independent confidence metric.ConclusionsBiomarkers comprise a fundamental component of personalized medicine. We first validated two NSCLC prognostic biomarkers in an independent patient cohort. Power analyses demonstrate that even this large, 442-patient cohort is under-powered for stage-specific analyses. We then use these results to discover an unexpected sensitivity of validation to subtle data analysis decisions. Finally, we develop a novel algorithmic approach to exploit this sensitivity to improve biomarker robustness

Unravelling the functions of biogenic volatiles in boreal and temperate forest ecosystems

Living trees are the main source of biogenic volatile organic compounds (BVOCs) in forest ecosystems, but substantial emissions originate from leaf and wood litter, the rhizosphere and from microorganisms. This review focuses on temperate and boreal forest ecosystems and the roles of BVOCs in ecosystem function, from the leaf to the forest canopy and from the forest soil to the atmosphere level. Moreover, emphasis is given to the question of how BVOCs will help forests adapt to environmental stress, particularly biotic stress related to climate change. Trees use their vascular system and emissions of BVOCs in internal communication, but emitted BVOCs have extended the communication to tree population and whole community levels and beyond. Future forestry practices should consider the importance of BVOCs in attraction and repulsion of attacking bark beetles, but also take an advantage of herbivore-induced BVOCs to improve the efficiency of natural enemies of herbivores. BVOCs are extensively involved in ecosystem services provided by forests including the positive effects on human health. BVOCs have a key role in ozone formation but also in ozone quenching. Oxidation products form secondary organic aerosols that disperse sunlight deeper into the forest canopy, and affect cloud formation and ultimately the climate. We also discuss the technical side of reliable BVOC sampling of forest trees for future interdisciplinary studies that should bridge the gaps between the forest sciences, health sciences, chemical ecology, conservation biology, tree physiology and atmospheric science

Genomic DNA functions as a universal external standard in quantitative real-time PCR

Real-time quantitative PCR (qPCR) is a powerful tool for quantifying specific DNA target sequences. Although determination of relative quantity is widely accepted as a reliable means of measuring differences between samples, there are advantages to being able to determine the absolute copy numbers of a given target. One approach to absolute quantification relies on construction of an accurate standard curve using appropriate external standards of known concentration. We have validated the use of tissue genomic DNA as a universal external standard to facilitate quantification of any target sequence contained in the genome of a given species, addressing several key technical issues regarding its use. This approach was applied to validate mRNA expression of gene candidates identified from microarray data and to determine gene copies in transgenic mice. A simple method that can assist achieving absolute quantification of gene expression would broadly enhance the uses of real-time qPCR and in particular, augment the evaluation of global gene expression studies

A Concomitant Muscle Injury Does Not Worsen Traumatic Brain Injury Outcomes in Mice

Traumatic brain injury (TBI) often involves multitrauma in which concurrent extracranial injury occurs. We previously demonstrated that a long bone fracture exacerbates neuroinflammation and functional outcomes in mice given a TBI. Whether other forms of concomitant peripheral trauma that are common in the TBI setting, such as skeletal muscle injury, have similar effects is unknown. As such, here we developed a novel mouse multitrauma model by combining a closed-skull TBI with a cardiotoxin (CTX)-induced muscle injury to investigate whether muscle injury affects TBI outcomes. Adult male mice were assigned to four groups: sham-TBI + sham-muscle injury (SHAM); sham-TBI + CTX-muscle injury (CTX); TBI + sham-muscle injury (TBI); TBI + CTX-muscle injury (MULTI). Some mice were euthanized at 24 h post-injury to assess neuroinflammation and cerebral edema. The remaining mice underwent behavioral testing after a 30-day recovery period, and were euthanized at 35 days post-injury for post-mortem analysis. At 24 h post-injury, both TBI and MULTI mice had elevated edema, increased expression of GFAP (i.e., a marker for reactive astrocytes), and increased mRNA levels of inflammatory chemokines. There was also an effect of injury on cytokine levels at 35 days post-injury. However, the TBI and MULTI mice did not significantly differ on any of the measures assessed. These initial findings suggest that a concomitant muscle injury does not significantly affect preclinical TBI outcomes. Future studies should investigate the combination of different injury models, additional outcomes, and other post-injury time points

Needs assessment to strengthen capacity in water and sanitation research in Africa:experiences of the African SNOWS consortium

Despite its contribution to global disease burden, diarrhoeal disease is still a relatively neglected area for research funding, especially in low-income country settings. The SNOWS consortium (Scientists Networked for Outcomes from Water and Sanitation) is funded by the Wellcome Trust under an initiative to build the necessary research skills in Africa. This paper focuses on the research training needs of the consortium as identified during the first three years of the project

CpG Island microarray probe sequences derived from a physical library are representative of CpG Islands annotated on the human genome

An effective tool for the global analysis of both DNA methylation status and protein–chromatin interactions is a microarray constructed with sequences containing regulatory elements. One type of array suited for this purpose takes advantage of the strong association between CpG Islands (CGIs) and gene regulatory regions. We have obtained 20 736 clones from a CGI Library and used these to construct CGI arrays. The utility of this library requires proper annotation and assessment of the clones, including CpG content, genomic origin and proximity to neighboring genes. Alignment of clone sequences to the human genome (UCSC hg17) identified 9595 distinct genomic loci; 64% were defined by a single clone while the remaining 36% were represented by multiple, redundant clones. Approximately 68% of the loci were located near a transcription start site. The distribution of these loci covered all 23 chromosomes, with 63% overlapping a bioinformatically identified CGI. The high representation of genomic CGI in this rich collection of clones supports the utilization of microarrays produced with this library for the study of global epigenetic mechanisms and protein–chromatin interactions. A browsable database is available on-line to facilitate exploration of the CGIs in this library and their association with annotated genes or promoter elements

Sampling strategies to measure the prevalence of common recurrent infections in longitudinal studies

<p>Abstract</p> <p>Background</p> <p>Measuring recurrent infections such as diarrhoea or respiratory infections in epidemiological studies is a methodological challenge. Problems in measuring the incidence of recurrent infections include the episode definition, recall error, and the logistics of close follow up. Longitudinal prevalence (LP), the proportion-of-time-ill estimated by repeated prevalence measurements, is an alternative measure to incidence of recurrent infections. In contrast to incidence which usually requires continuous sampling, LP can be measured at intervals. This study explored how many more participants are needed for infrequent sampling to achieve the same study power as frequent sampling.</p> <p>Methods</p> <p>We developed a set of four empirical simulation models representing low and high risk settings with short or long episode durations. The model was used to evaluate different sampling strategies with different assumptions on recall period and recall error.</p> <p>Results</p> <p>The model identified three major factors that influence sampling strategies: (1) the clustering of episodes in individuals; (2) the duration of episodes; (3) the positive correlation between an individual's disease incidence and episode duration. Intermittent sampling (e.g. 12 times per year) often requires only a slightly larger sample size compared to continuous sampling, especially in cluster-randomized trials. The collection of period prevalence data can lead to highly biased effect estimates if the exposure variable is associated with episode duration. To maximize study power, recall periods of 3 to 7 days may be preferable over shorter periods, even if this leads to inaccuracy in the prevalence estimates.</p> <p>Conclusion</p> <p>Choosing the optimal approach to measure recurrent infections in epidemiological studies depends on the setting, the study objectives, study design and budget constraints. Sampling at intervals can contribute to making epidemiological studies and trials more efficient, valid and cost-effective.</p

CD4+ regulatory T cells require CTLA-4 for the maintenance of systemic tolerance

Cytotoxic T lymphocyte antigen-4 (CTLA-4) plays a critical role in negatively regulating T cell responses and has also been implicated in the development and function of natural FOXP3+ regulatory T cells. CTLA-4–deficient mice develop fatal, early onset lymphoproliferative disease. However, chimeric mice containing both CTLA-4–deficient and –sufficient bone marrow (BM)–derived cells do not develop disease, indicating that CTLA-4 can act in trans to maintain T cell self-tolerance. Using genetically mixed blastocyst and BM chimaeras as well as in vivo T cell transfer systems, we demonstrate that in vivo regulation of Ctla4−/− T cells in trans by CTLA-4–sufficient T cells is a reversible process that requires the persistent presence of FOXP3+ regulatory T cells with a diverse TCR repertoire. Based on gene expression studies, the regulatory T cells do not appear to act directly on T cells, suggesting they may instead modulate the stimulatory activities of antigen-presenting cells. These results demonstrate that CTLA-4 is absolutely required for FOXP3+ regulatory T cell function in vivo