Preface

One of the current challenges in plant biology is the development of quantitative phenotyping approaches to link the genotype and the environment to plant structural, functional, and yield characteristics in order to meet the growing demands for sustainable food, feed, and fuel. The genotype of a plant consists of all of the hereditary information within the individual, whilst the phenotype, which represents the morphological, physiological, anatomical, and developmental characteristics, is the result of the interaction between the genotype and the environment. Understanding this interaction is one of the major challenges in plant sciences. In plant breeding, the ultimate goal is the improvement of traits of agricultural importance related to disease resistance, high yields, and the plant’s ability to grow in unfavourable environmental conditions. Currently, breeding approaches produce an annual yield increase of approximately 1% for major crops, which is below the over 2% increase needed to meet the global demands for food by 2050 (Ray et al., 2013).Rapid developments in plant molecular biology and in molecular-based breeding techniques have resulted in an increasing number of species being sequenced and large collections of mutants, accessions, and recombinant lines allowing detailed analysis of gene functions. High-definition genotyping can now be carried out on thousands of plants in an automated way at continuously decreasing costs, thereby facilitating association genetics and the determination of multi-parental quantitative trait loci (QTLs) (Poland and Rife, 2012). For transcriptomic, proteomic, and metabolomic analyses large, often robotized, platforms are available allowing detailed characterization of the biochemical status of plants at a reasonable cost (Ehrhardt and Frommer, 2012). By contrast, an understanding of the link between genotype and phenotype has progressed more slowly and is the major limiting step i

Synthetic long non-coding RNAs [SINEUPs] rescue defective gene expression in vivo

Non-coding RNAs provide additional regulatory layers to gene expression as well as the potential to being exploited as therapeutic tools. Non-coding RNA-based therapeutic approaches have been attempted in dominant diseases, however their use for treatment of genetic diseases caused by insufficient gene dosage is currently more challenging. SINEUPs are long antisense non-coding RNAs that up-regulate translation in mammalian cells in a gene-specific manner, although, so far evidence of SINEUP efficacy has only been demonstrated in in vitro systems. We now show that synthetic SINEUPs effectively and specifically increase protein levels of a gene of interest in vivo. We demonstrated that SINEUPs rescue haploinsufficient gene dosage in a medakafish model of a human disorder leading to amelioration of the disease phenotype. Our results demonstrate that SINEUPs act through mechanisms conserved among vertebrates and that SINEUP technology can be successfully applied in vivo as a new research and therapeutic tool for gene-specific up-regulation of endogenous functional proteins

Selecting normalization genes for small diagnostic microarrays

BACKGROUND: Normalization of gene expression microarrays carrying thousands of genes is based on assumptions that do not hold for diagnostic microarrays carrying only few genes. Thus, applying standard microarray normalization strategies to diagnostic microarrays causes new normalization problems. RESULTS: In this paper we point out the differences of normalizing large microarrays and small diagnostic microarrays. We suggest to include additional normalization genes on the small diagnostic microarrays and propose two strategies for selecting them from genomewide microarray studies. The first is a data driven univariate selection of normalization genes. The second is multivariate and based on finding a balanced diagnostic signature. Finally, we compare both methods to standard normalization protocols known from large microarrays. CONCLUSION: Not including additional genes for normalization on small microarrays leads to a loss of diagnostic information. Using house keeping genes from the literature for normalization fails to work for certain datasets. While a data driven selection of additional normalization genes works well, the best results were obtained using a balanced signature

Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study

BACKGROUND: Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. RESULTS: The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. CONCLUSIONS: Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens

Wolbachia in the flesh: symbiont intensities in germ-line and somatic tissues challenge the conventional view of Wolbachia transmission routes

Symbionts can substantially affect the evolution and ecology of their hosts. The investigation of the tissue-specific distribution of symbionts (tissue tropism) can provide important insight into host-symbiont interactions. Among other things, it can help to discern the importance of specific transmission routes and potential phenotypic effects. The intracellular bacterial symbiont Wolbachia has been described as the greatest ever panzootic, due to the wide array of arthropods that it infects. Being primarily vertically transmitted, it is expected that the transmission of Wolbachia would be enhanced by focusing infection in the reproductive tissues. In social insect hosts, this tropism would logically extend to reproductive rather than sterile castes, since the latter constitute a dead-end for vertically transmission. Here, we show that Wolbachia are not focused on reproductive tissues of eusocial insects, and that non-reproductive tissues of queens and workers of the ant Acromyrmex echinatior, harbour substantial infections. In particular, the comparatively high intensities of Wolbachia in the haemolymph, fat body, and faeces, suggest potential for horizontal transmission via parasitoids and the faecal-oral route, or a role for Wolbachia modulating the immune response of this host. It may be that somatic tissues and castes are not the evolutionary dead-end for Wolbachia that is commonly thought

Ethylene supports colonization of plant roots by the mutualistic fungus Piriformospora indica

The mutualistic basidiomycete Piriformospora indica colonizes roots of mono- and dicotyledonous plants, and thereby improves plant health and yield. Given the capability of P. indica to colonize a broad range of hosts, it must be anticipated that the fungus has evolved efficient strategies to overcome plant immunity and to establish a proper environment for nutrient acquisition and reproduction. Global gene expression studies in barley identified various ethylene synthesis and signaling components that were differentially regulated in P. indica-colonized roots. Based on these findings we examined the impact of ethylene in the symbiotic association. The data presented here suggest that P. indica induces ethylene synthesis in barley and Arabidopsis roots during colonization. Moreover, impaired ethylene signaling resulted in reduced root colonization, Arabidopsis mutants exhibiting constitutive ethylene signaling, -synthesis or ethylene-related defense were hyper-susceptible to P. indica. Our data suggest that ethylene signaling is required for symbiotic root colonization by P. indica

The alpha 7 nicotinic receptor agonist PHA-543613 hydrochloride inhibits <i>Porphyromonas gingivalis</i>-induced expression of interleukin-8 by oral keratinocytes

Objective: The alpha 7 nicotinic receptor (α7nAChR) is expressed by oral keratinocytes. α7nAChR activation mediates anti-inflammatory responses. The objective of this study was to determine if α7nAChR activation inhibited pathogen-induced interleukin-8 (IL-8) expression by oral keratinocytes.&lt;p&gt;&lt;/p&gt; Materials and methods: Periodontal tissue expression of α7nAChR was determined by real-time PCR. OKF6/TERT-2 oral keratinocytes were exposed to &lt;i&gt;Porphyromonas gingivalis&lt;/i&gt; in the presence and absence of a α7nAChR agonist (PHA-543613 hydrochloride) alone or after pre-exposure to a specific α7nAChR antagonist (α-bungarotoxin). Interleukin-8 (IL-8) expression was measured by ELISA and real-time PCR. Phosphorylation of the NF-κB p65 subunit was determined using an NF-κB p65 profiler assay and STAT-3 activation by STAT-3 in-cell ELISA. The release of ACh from oral keratinocytes in response to &lt;i&gt;P. gingivalis&lt;/i&gt; lipopolysaccharide was determined using a GeneBLAzer M3 CHO-K1-blacell reporter assay.&lt;p&gt;&lt;/p&gt; Results: Expression of α7nAChR mRNA was elevated in diseased periodontal tissue. PHA-543613 hydrochloride inhibited &lt;i&gt;P. Gingivalis&lt;/i&gt;-induced expression of IL-8 at the transcriptional level. This effect was abolished when cells were pre-exposed to a specific α7nAChR antagonist, α-bungarotoxin. PHA-543613 hydrochloride downregulated NF-κB signalling through reduced phosphorylation of the NF-κB p65-subunit. In addition, PHA-543613 hydrochloride promoted STAT-3 signalling by maintenance of phosphorylation. Furthermore, oral keratinocytes upregulated ACh release in response to &lt;i&gt;P. Gingivalis&lt;/i&gt; lipopolysaccharide.&lt;p&gt;&lt;/p&gt; Conclusion: These data suggest that α7nAChR plays a role in regulating the innate immune responses of oral keratinocytes.&lt;p&gt;&lt;/p&gt

TRIB2 confers resistance to anti-cancer therapy by activating the serine/threonine protein kinase AKT.

Intrinsic and acquired resistance to chemotherapy is the fundamental reason for treatment failure for many cancer patients. The identification of molecular mechanisms involved in drug resistance or sensitization is imperative. Here we report that tribbles homologue 2 (TRIB2) ablates forkhead box O activation and disrupts the p53/MDM2 regulatory axis, conferring resistance to various chemotherapeutics. TRIB2 suppression is exerted via direct interaction with AKT a key signalling protein in cell proliferation, survival and metabolism pathways. Ectopic or intrinsic high expression of TRIB2 induces drug resistance by promoting phospho-AKT (at Ser473) via its COP1 domain. TRIB2 expression is significantly increased in tumour tissues from patients correlating with an increased phosphorylation of AKT, FOXO3a, MDM2 and an impaired therapeutic response. This culminates in an extremely poor clinical outcome. Our study reveals a novel regulatory mechanism underlying drug resistance and suggests that TRIB2 functions as a regulatory component of the PI3K network, activating AKT in cancer cells

Urinary MicroRNA Profiling in the Nephropathy of Type 1 Diabetes

Background: Patients with Type 1 Diabetes (T1D) are particularly vulnerable to development of Diabetic nephropathy (DN) leading to End Stage Renal Disease. Hence a better understanding of the factors affecting kidney disease progression in T1D is urgently needed. In recent years microRNAs have emerged as important post-transcriptional regulators of gene expression in many different health conditions. We hypothesized that urinary microRNA profile of patients will differ in the different stages of diabetic renal disease. Methods and Findings: We studied urine microRNA profiles with qPCR in 40 T1D with >20 year follow up 10 who never developed renal disease (N) matched against 10 patients who went on to develop overt nephropathy (DN), 10 patients with intermittent microalbuminuria (IMA) matched against 10 patients with persistent (PMA) microalbuminuria. A Bayesian procedure was used to normalize and convert raw signals to expression ratios. We applied formal statistical techniques to translate fold changes to profiles of microRNA targets which were then used to make inferences about biological pathways in the Gene Ontology and REACTOME structured vocabularies. A total of 27 microRNAs were found to be present at significantly different levels in different stages of untreated nephropathy. These microRNAs mapped to overlapping pathways pertaining to growth factor signaling and renal fibrosis known to be targeted in diabetic kidney disease. Conclusions: Urinary microRNA profiles differ across the different stages of diabetic nephropathy. Previous work using experimental, clinical chemistry or biopsy samples has demonstrated differential expression of many of these microRNAs in a variety of chronic renal conditions and diabetes. Combining expression ratios of microRNAs with formal inferences about their predicted mRNA targets and associated biological pathways may yield useful markers for early diagnosis and risk stratification of DN in T1D by inferring the alteration of renal molecular processes. © 2013 Argyropoulos et al