discovery-metastatic-regulators-using-rapid-quantitative-intravital

Discovery of Metastatic Regulators using a Rapid and Quantitative Intravital Chick Chorioallantoic Membrane Model

Recent advances in cancer research has illustrated the highly complex nature of cancer metastasis. Multiple genes or genes networks have been found to be ...

University of Alberta, Edmonton, Alberta, Canada

Crop plants require nitrogen for key macromolecules, such as DNA, proteins and metabolites, yet they are generally inefficient at acquiring nitrogen from the soil. Crop producers compensate for this low nitrogen utilization efficiency by applying nitrogen fertilizers. However, much of this nitrogen is unavailable to the plants as a result of microbial uptake and environmental loss of nitrogen, causing air, water and soil pollution. We engineered rice over-expressing alanine aminotransferase (AlaAT) under the control of a tissue-specific promoter that showed a strong nitrogen use efficiency phenotype. In this study, we examined the transcriptome response in roots and shoots to the over-expression of AlaAT to provide insights into the nitrogen-use-efficient phenotype of these plants. Transgenic and control rice plants were grown hydroponically and the root and shoot gene expression profiles were analysed using Affymetrix Rice GeneChip microarrays. Transcriptome analysis revealed that there was little impact on the transgenic transcriptome compared with controls, with 0.11% and 0.07% differentially regulated genes in roots and shoots, respectively. The most up-regulated transcripts, a glycine-rich cell wall (GRP) gene and a gene encoding a hypothetical protein (Os8823), were expressed in roots. Another transgenic root-specific up-regulated gene was leucine rich repeat (LRR). Genes induced in the transgenic shoots included GRP, LRR, acireductone dioxygenase (OsARD), SNF2 ATP-translocase and a putative leucine zipper transcription factor. This study provides a genome-wide view of the response to AlaAT over-expression, and elucidates some of the genes that may play a role in the nitrogen-use-efficient phenotype.

Transcriptome analysis of nitrogen-efficient rice over-expressing alanine aminotransferase.

In the past 50 years, the application of synthetic nitrogen (N) fertilizer to farmland resulted in a dramatic increase in crop yields but with considerable negative impacts on the environment. New solutions are therefore needed to simultaneously increase yields while maintaining, or preferably decreasing, applied N to maximize the nitrogen use efficiency (NUE) of crops. In this review, we outline the definition of NUE, the selection and development of NUE crops, and the factors that interact with NUE. In particular, we emphasize the challenges of developing crop plants with enhanced NUE, using more classical genetic approaches based on utilizing existing allelic variation for NUE traits. The challenges of phenotyping, mapping quantitative trait loci (QTLs), and selecting candidate genes for NUE improvement are described. In addition, we highlight the importance of different factors that lead to changes in the NUE components of nitrogen uptake efficiency (NUpE) and nitrogen utilization efficiency (NUtE). 

The Genetics of Nitrogen Use Efficiency in Crop Plants.

A comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE) in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms that affect NUE in agricultural settings. However, an exciting collection of computational and experimental approaches has begun to elucidate whole-plant nitrogen usage and provides an avenue for connecting nitrogen-related phenotypes to genes. Herein, we describe how metabolomics, computational models of metabolism, and flux balance analysis have been harnessed to advance our understanding of plant nitrogen metabolism. We introduce a model describing the complex flow of nitrogen through crops in a real-world agricultural setting and describe how experimental metabolomics data, such as isotope labeling rates and analyses of nutrient uptake, can be used to refine these models. In summary, the metabolomics/computational approach offers an exciting mechanism for understanding NUE that may ultimately lead to more effective crop management and engineered plants with higher yields.

Article	Year
Transcriptome analysis of nitrogen-efficient rice over-expressing alanine aminotransferase. Plant biotechnology journal\| PubMed ID: 19508275	2009
The Genetics of Nitrogen Use Efficiency in Crop Plants. Annual review of genetics\| PubMed ID: 26421509	2015
Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches. Plants (Basel, Switzerland)\| PubMed ID: 27735856	2016

Perrin H. Beatty

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