The evolutionary-developmental analysis of plant microRNAs

MicroRNAs (miRNAs) control many important aspects of plant development, suggesting these molecules may also have played key roles in the evolution of developmental processes in plants. However, evolutionary-developmental (evo-devo) studies of miRNAs have been held back by technical difficulties in gene identification. To help solve this problem, we have developed a two-step procedure for the efficient identification of miRNA genes in any plant species. As a test case, we have studied the evolution of the MIR164 family in the angiosperms. We have identified novel MIR164 genes in three species occupying key phylogenetic positions and used these, together with published sequence data, to partially reconstruct the evolution of the MIR164 family since the last common ancestor of the extant flowering plants. We use our evolutionary reconstruction to discuss potential roles for MIR164 genes in the evolution of leaf shape and carpel closure in the angiosperms. The techniques we describe may be applied to any miRNA family and should thus enable plant evo-devo to begin to investigate the contributions miRNAs have made to the evolution of plant development.     

Dissection of a metastatic gene expression signature into distinct components

Background

Metastasis, the process whereby cancer cells spread, is in part caused by an incompletely understood interplay between cancer cells and the surrounding stroma. Gene expression studies typically analyze samples containing tumor cells and stroma. Samples with less than 50% tumor cells are generally excluded, thereby reducing the number of patients that can benefit from clinically relevant signatures.

Results

For a head-neck squamous cell carcinoma (HNSCC) primary tumor expression signature that predicts the presence of lymph node metastasis, we first show that reduced proportions of tumor cells results in decreased predictive accuracy. To determine the influence of stroma on the predictive signature and to investigate the interaction between tumor cells and the surrounding microenvironment, we used laser capture microdissection to divide the metastatic signature into six distinct components based on tumor versus stroma expression and on association with the metastatic phenotype. A strikingly skewed distribution of metastasis associated genes is revealed.

Conclusion

Dissection of predictive signatures into different components has implications for design of expression signatures and for our understanding of the metastatic process. Compared to primary tumors that have not formed metastases, primary HNSCC tumors that have metastasized are characterized by predominant down-regulation of tumor cell specific genes and exclusive up-regulation of stromal cell specific genes. The skewed distribution agrees with poor signature performance on samples that contain less than 50% tumor cells. Methods for reducing tumor composition bias that lead to greater predictive accuracy and an increase in the types of samples that can be included are presented.     

Current trends and future directions in flower development research

Flowers, the reproductive structures of the approximately 400 000 extant species of flowering plants, exist in a tremendous range of forms and sizes, mainly due to developmental differences involving the number, arrangement, size and form of the floral organs of which they consist. However, this tremendous diversity is underpinned by a surprisingly robust basic floral structure in which a central group of carpels forms on an axis of determinate growth, almost invariably surrounded by two successive zones containing stamens and perianth organs, respectively. Over the last 25 years, remarkable progress has been achieved in describing the molecular mechanisms that control almost all aspects of flower development, from the phase change that initiates flowering to the final production of fruits and seeds. However, this work has been performed almost exclusively in a small number of eudicot model species, chief among which is Arabidopsis thaliana. Studies of flower development must now be extended to a much wider phylogenetic range of flowering plants and, indeed, to their closest living relatives, the gymnosperms. Studies of further, more wide-ranging models should provide insights that, for various reasons, cannot be obtained by studying the major existing models alone. The use of further models should also help to explain how the first flowering plants evolved from an unknown, although presumably gymnosperm-like ancestor, and rapidly diversified to become the largest major plant group and to dominate the terrestrial flora. The benefits for society of a thorough understanding of flower development are self-evident, as human life depends to a large extent on flowering plants and on the fruits and seeds they produce. In this preface to the Special Issue, we introduce eleven articles on flower development, representing work in both established and further models, including gymnosperms. We also present some of our own views on current trends and future directions of the flower development field.     

An Integrated Mass-Spectrometry Pipeline Identifies Novel Protein Coding-Regions in the Human Genome

Background

Most protein mass spectrometry (MS) experiments rely on searches against a database of known or predicted proteins, limiting their ability as a gene discovery tool.

Results

Using a search against an in silico translation of the entire human genome, combined with a series of annotation filters, we identified 346 putative novel peptides [False Discovery Rate (FDR)<5%] in a MS dataset derived from two human breast epithelial cell lines. A subset of these were then successfully validated by a different MS technique. Two of these correspond to novel isoforms of Heterogeneous Ribonuclear Proteins, while the rest correspond to novel loci.

Conclusions

MS technology can be used for ab initio gene discovery in human data, which, since it is based on different underlying assumptions, identifies protein-coding genes not found by other techniques. As MS technology continues to evolve, such approaches will become increasingly powerful.     

Development and Validation of a Risk Model for Predicting Adverse Drug Reactions in Older People during Hospital Stay: Brighton Adverse Drug Reactions Risk (BADRI) Model

Background

Older patients are at an increased risk of developing adverse drug reactions (ADR). Of particular concern are the oldest old, which constitute an increasingly growing population. Having a validated clinical tool to identify those older patients at risk of developing an ADR during hospital stay would enable healthcare staff to put measures in place to reduce the risk of such an event developing. The current study aimed to (1) develop and (2) validate an ADR risk prediction model.

Methods

We used a combination of univariate analysis and multivariate binary logistic regression to identify clinical risk factors for developing an ADR in a population of older people from a UK teaching hospital. The final ADR risk model was then validated in a European population (European dataset).

Results

Six-hundred-ninety patients (median age 85 years) were enrolled in the development stage of the study. Ninety-five reports of ADR were confirmed by independent review in these patients. Five clinical variables were identified through multivariate analysis and included in our final model; each variable was attributed a score of 1. Internal validation produced an AUROC of 0.74, a sensitivity of 80%, and specificity of 55%. During the external validation stage the AUROC was 0.73, with sensitivity and specificity values of 84% and 43% respectively.

Conclusions

We have developed and successfully validated a simple model to use ADR risk score in a population of patients with a median age of 85, i.e. the oldest old. The model is based on 5 clinical variables (≥8 drugs, hyperlipidaemia, raised white cell count, use of anti-diabetic agents, length of stay ≥12 days), some of which have not been previously reported.     

New perspectives in the differentiation of bone-forming cells.

Bone formation comprises a complex but ordered sequence of events which involves the proliferation and differentiation of chondrogenic and osteoblastic precursor cells ultimately leading to the formation of a calcified extracellular matrix. This process can be observed in vivo but under these conditions is difficult to study at the molecular level. A number of in vitro models have been developed which recapitulate discrete elements of this process. Using these models, detailed information has been obtained regarding the differentiation of bone forming cells and the molecular biology of the mineralization process. It has been shown that, in vitro, osteoblastic precursor cells can form a mineralized matrix similar to that seen in vivo. This calcification process was shown to consist of three interdependent phases: proliferation, matrix maturation and mineralization. Each of these phases was characterized by the expression of particular genes. Osteoblast precursors have been cloned and consequently shown to be able to differentiate in vitro into a number of other mesenchymal cells, supporting the theory that osteoblasts are derived from multipotent mesenchymal cells. It is possible that markers derived from these models could be used in the future to extend our knowledge of bone formation in vivo.     

Herbicidal aryldiones incorporating a 5-methoxy-[1,2,5]triazepane ring

Novel 2-aryl-cyclic-1,3-diones containing a 5-methoxy-[1,2,5]triazepane unit were explored towards an effective and wheat safe control of grass weeds. Their preparation builds on the ease of synthetic access to 7-membered heterocyclic [1,2,5]triazepane building blocks. Substitution and pattern hopping in the phenyl moiety revealed structure–activity relationships in good agreement with previously disclosed observations amongst the pinoxaden family of acetyl-CoA carboxylase inhibitors. In light of basic physicochemical, enzyme inhibitory and binding site properties, the N-methoxy functionality effectively acts as a bioisostere of the ether group in the seven-membered hydrazine ring.     

Impact of Ramadan intermittent fasting on cognitive function in trained cyclists: a pilot study

This study assessed selected measures of cognitive function in trained cyclists who observed daylight fasting during Ramadan. Eleven cyclists volunteered to participate (age: 21.6±4.8 years, VO₂max: 57.7±5.6 ml kg⁻¹·min⁻¹) and were followed for 2 months. Cognitive function (Cambridge Neuropsychological Test Automated Battery (CANTAB), Reaction Time index (RTI) and Rapid Visual Information Processing (RVP) tests) and sleep architecture (ambulatory EEG) were assessed: before Ramadan (BR), in the 1st week (RA1) and 4th week of Ramadan (RA4), and 2 weeks post-Ramadan (PR). Both cognitive tests were performed twice per day: before and after Ramadan at 8-10 a.m. and 4-6 p.m., and during Ramadan at 4-6 p.m. and 0-2 a.m., respectively. Training load (TL) by the rating of perceived exertion (RPE) method and wellness (Hooper index) were measured daily. If the TL increased over the study period, this variable was stable during Ramadan. The perceived fatigue and delayed onset muscle soreness (DOMS) increased at RA4. Sleep patterns and architecture showed clear disturbances, with significant increases in the number of awakenings and light sleep durations during Ramadan (RA1 and RA4), together with decreased durations of deep and REM sleep stages at PR. RTI (simple and multiple reaction index) reaction and movement times did not vary over the study period. The RVP test showed reduced false alarms during Ramadan, suggesting reduced impulsivity. Overall accuracy significantly increased at RA1, RA4 and PR compared to baseline. At RA4, the accuracy was higher at 0-2 a.m. compared to 4-6 p.m. Despite the observed disturbances in sleep architecture, Ramadan fasting did not negatively impact the cognitive performance of trained cyclists from the Middle East.