Switchgrass (Panicum virgatum L.) polyubiquitin gene (PvUbi1 and PvUbi2) promoters for use in plant transformation

<p>Abstract</p> <p>Background</p> <p>The ubiquitin protein is present in all eukaryotic cells and promoters from ubiquitin genes are good candidates to regulate the constitutive expression of transgenes in plants. Therefore, two switchgrass (<it>Panicum virgatum </it>L.) ubiquitin genes (<it>PvUbi1 </it>and <it>PvUbi2</it>) were cloned and characterized. Reporter constructs were produced containing the isolated 5' upstream regulatory regions of the coding sequences (i.e. <it>PvUbi1 </it>and <it>PvUbi2 </it>promoters) fused to the <it>uidA </it>coding region (<it>GUS</it>) and tested for transient and stable expression in a variety of plant species and tissues.</p> <p>Results</p> <p><it>PvUbi1 </it>consists of 607 bp containing <it>cis</it>-acting regulatory elements, a 5' untranslated region (UTR) containing a 93 bp non-coding exon and a 1291 bp intron, and a 918 bp open reading frame (ORF) that encodes four tandem, head -to-tail ubiquitin monomer repeats followed by a 191 bp 3' UTR. <it>PvUbi2 </it>consists of 692 bp containing <it>cis</it>-acting regulatory elements, a 5' UTR containing a 97 bp non-coding exon and a 1072 bp intron, a 1146 bp ORF that encodes five tandem ubiquitin monomer repeats and a 183 bp 3' UTR. <it>PvUbi1 </it>and <it>PvUbi2 </it>were expressed in all examined switchgrass tissues as measured by qRT-PCR. Using biolistic bombardment, <it>PvUbi1 </it>and <it>PvUbi2 </it>promoters showed strong expression in switchgrass and rice callus, equaling or surpassing the expression levels of the CaMV <it>35S, 2x35S, ZmUbi1</it>, and <it>OsAct1 </it>promoters. GUS staining following stable transformation in rice demonstrated that the <it>PvUbi1 </it>and <it>PvUbi2 </it>promoters drove expression in all examined tissues. When stably transformed into tobacco (<it>Nicotiana tabacum</it>), the <it>PvUbi2+3 </it>and <it>PvUbi2+9 </it>promoter fusion variants showed expression in vascular and reproductive tissues.</p> <p>Conclusions</p> <p>The <it>PvUbi1 </it>and <it>PvUbi2 </it>promoters drive expression in switchgrass, rice and tobacco and are strong constitutive promoter candidates that will be useful in genetic transformation of monocots and dicots.</p

What scans we will read: imaging instrumentation trends in clinical oncology

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non- invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/ CT), advanced MRI, optical or ultrasound imaging. This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now. Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by progress in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as “data”, and – through the wider adoption of advanced analysis, including machine learning approaches and a “big data” concept – move to the next stage of non-invasive tumor phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi- dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging