16 research outputs found
Advanced abdominal imaging with dual energy CT is feasible without increasing radiation dose
Mechanism of Disruption of the Amt-GlnK Complex by PII-Mediated Sensing of 2-Oxoglutarate
GlnK proteins regulate the active uptake of ammonium by Amt transport proteins by inserting their regulatory T-loops into the transport channels of the Amt trimer and physically blocking substrate passage. They sense the cellular nitrogen status through 2-oxoglutarate, and the energy level of the cell by binding both ATP and ADP with different affinities. The hyperthermophilic euryarchaeon Archaeoglobus fulgidus possesses three Amt proteins, each encoded in an operon with a GlnK ortholog. One of these proteins, GlnK2 was recently found to be incapable of binding 2-OG, and in order to understand the implications of this finding we conducted a detailed structural and functional analysis of a second GlnK protein from A. fulgidus, GlnK3. Contrary to Af-GlnK2 this protein was able to bind both ATP/2-OG and ADP to yield inactive and functional states, respectively. Due to the thermostable nature of the protein we could observe the exact positioning of the notoriously flexible T-loops and explain the binding behavior of GlnK proteins to their interaction partner, the Amt proteins. A thermodynamic analysis of these binding events using microcalorimetry evaluated by microstate modeling revealed significant differences in binding cooperativity compared to other characterized PII proteins, underlining the diversity and adaptability of this class of regulatory signaling proteins
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An integrated omics analysis reveals molecular mechanisms that are associated with differences in seed oil content between Glycine max and Brassica napus
Abstract
Background: Rapeseed (Brassica napus L.) and soybean (Glycine max L.) seeds are rich in both protein and oil, which
are major sources of biofuels and nutrition. Although the difference in seed oil content between soybean (~ 20%) and
rapeseed (~ 40%) exists, little is known about its underlying molecular mechanism.
Results: An integrated omics analysis was performed in soybean, rapeseed, Arabidopsis (Arabidopsis thaliana L. Heynh),
and sesame (Sesamum indicum L.), based on Arabidopsis acyl-lipid metabolism- and carbon metabolism-related genes.
As a result, candidate genes and their transcription factors and microRNAs, along with phylogenetic analysis and
co-expression network analysis of the PEPC gene family, were found to be largely associated with the difference
between the two species. First, three soybean genes (Glyma.13G148600, Glyma.13G207900 and Glyma.12G122900)
co-expressed with GmPEPC1 are specifically enriched during seed storage protein accumulation stages, while the
expression of BnPEPC1 is putatively inhibited by bna-miR169, and two genes BnSTKA and BnCKII are co-expressed
with BnPEPC1 and are specifically associated with plant circadian rhythm, which are related to seed oil biosynthesis. Then,
in de novo fatty acid synthesis there are rapeseed-specific genes encoding subunits β-CT (BnaC05g37990D) and BCCP1
(BnaA03g06000D) of heterogeneous ACCase, which could interfere with synthesis rate, and β-CT is positively regulated by
four transcription factors (BnaA01g37250D, BnaA02g26190D, BnaC01g01040D and BnaC07g21470D). In triglyceride synthesis,
GmLPAAT2 is putatively inhibited by three miRNAs (gma-miR171, gma-miR1516 and gma-miR5775). Finally, in rapeseed
there was evidence for the expansion of gene families, CALO, OBO and STERO, related to lipid storage, and
the contraction of gene families, LOX, LAH and HSI2, related to oil degradation.
Conclusions: The molecular mechanisms associated with differences in seed oil content provide the basis for
future breeding efforts to improve seed oil content
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
Science forum: vision, challenges and opportunities for a Plant Cell Atlas
With growing populations and pressing environmental problems, future economies will be increasingly plant-based. Now is the time to reimagine plant science as a critical component of fundamental science, agriculture, environmental stewardship, energy, technology and healthcare. This effort requires a conceptual and technological framework to identify and map all cell types, and to comprehensively annotate the localization and organization of molecules at cellular and tissue levels. This framework, called the Plant Cell Atlas (PCA), will be critical for understanding and engineering plant development, physiology and environmental responses. A workshop was convened to discuss the purpose and utility of such an initiative, resulting in a roadmap that acknowledges the current knowledge gaps and technical challenges, and underscores how the PCA initiative can help to overcome them