Molecular Cloning, Characterization and Expression Analysis of Two Members of the Pht1 Family of Phosphate Transporters in Glycine max

BACKGROUND: Phosphorus is one of the macronutrients essential for plant growth and development. The acquisition and translocation of phosphate are pivotal processes of plant growth. In a large number of plants, phosphate uptake by roots and translocation within the plant are presumed to occur via a phosphate/proton cotransport mechanism. PRINCIPAL FINDINGS: We cloned two cDNAs from soybean (Glycine max), GmPT1 and GmPT2, which show homology to the phosphate/proton cotransporter PHO84 from the budding yeast Saccharomyces cerevisiae. The amino acid sequence of the products predicted from GmPT1 and GmPT2 share 61% and 63% identity, respectively, with the PHO84 in amino acid sequence. The deduced structure of the encoded proteins revealed 12 membrane-spanning domains with a central hydrophilic region. The molecular mass values are ∼58.7 kDa for GmPT1 and ∼58.6 kDa for GmPT2. Transiently expressed GFP-protein fusions provide direct evidence that the two Pi transporters are located in the plasma membrane. Uptake of radioactive orthophosphate by the yeast mutant MB192 showed that GmPT1 and GmPT2 are dependent on pH and uptake is reduced by the addition of uncouplers of oxidative phosphorylation. The K(m) for phosphate uptake by GmPT1 and GmPT2 is 6.65 mM and 6.63 mM, respectively. A quantitative real time RT-PCR assay indicated that these two genes are expressed in the roots and shoots of seedlings whether they are phosphate-deficient or not. Deficiency of phosphorus caused a slight change of the expression levels of GmPT1 and GmPT2. CONCLUSIONS: The results of our experiments show that the two phosphate transporters have low affinity and the corresponding genes are constitutively expressed. Thereby, the two phosphate transporters can perform translocation of phosphate within the plant

Comparative molecular biological analysis of membrane transport genes in organisms

Comparative analyses of membrane transport genes revealed many differences in the features of transport homeostasis in eight diverse organisms, ranging from bacteria to animals and plants. In bacteria, membrane-transport systems depend mainly on single genes encoding proteins involved in an ATP-dependent pump and secondary transport proteins that use H+ as a co-transport molecule. Animals are especially divergent in their channel genes, and plants have larger numbers of P-type ATPase and secondary active transporters than do other organisms. The secondary transporter genes have diverged evolutionarily in both animals and plants for different co-transporter molecules. Animals use Na+ ions for the formation of concentration gradients across plasma membranes, dependent on secondary active transporters and on membrane voltages that in turn are dependent on ion transport regulation systems. Plants use H+ ions pooled in vacuoles and the apoplast to transport various substances; these proton gradients are also dependent on secondary active transporters. We also compared the numbers of membrane transporter genes in Arabidopsis and rice. Although many transporter genes are similar in these plants, Arabidopsis has a more diverse array of genes for multi-efflux transport and for response to stress signals, and rice has more secondary transporter genes for carbohydrate and nutrient transport

A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems

Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks encountered by the deployed systems will not be limited to the original training context, and systems will instead need to adapt to novel distributions and tasks while deployed. This critical gap may be addressed through the development of "Lifelong Learning" systems that are capable of 1) Continuous Learning, 2) Transfer and Adaptation, and 3) Scalability. Unfortunately, efforts to improve these capabilities are typically treated as distinct areas of research that are assessed independently, without regard to the impact of each separate capability on other aspects of the system. We instead propose a holistic approach, using a suite of metrics and an evaluation framework to assess Lifelong Learning in a principled way that is agnostic to specific domains or system techniques. Through five case studies, we show that this suite of metrics can inform the development of varied and complex Lifelong Learning systems. We highlight how the proposed suite of metrics quantifies performance trade-offs present during Lifelong Learning system development - both the widely discussed Stability-Plasticity dilemma and the newly proposed relationship between Sample Efficient and Robust Learning. Further, we make recommendations for the formulation and use of metrics to guide the continuing development of Lifelong Learning systems and assess their progress in the future.Comment: To appear in Neural Network

Sensitivity of jarrah (Eucalyptus marginata) to phosphate, phosphite, and arsenate pulses as influenced by fungal symbiotic associations

Many plant species adapted to P-impoverished soils, including jarrah (Eucalyptus marginata), develop toxicity symptoms when exposed to high doses of phosphate (Pi) and its analogs such as phosphite (Phi) and arsenate (AsV). The present study was undertaken to investigate the effects of fungal symbionts Scutellospora calospora, Scleroderma sp., and Austroboletus occidentalis on the response of jarrah to highly toxic pulses (1.5 mmol kg−1 soil) of Pi, Phi, and AsV. S. calospora formed an arbuscular mycorrhizal (AM) symbiosis while both Scleroderma sp. and A. occidentalis established a non-colonizing symbiosis with jarrah plants. All these interactions significantly improved jarrah growth and Pi uptake under P-limiting conditions. The AM fungal colonization naturally declines in AM-eucalypt symbioses after 2–3 months; however, in the present study, the high Pi pulse inhibited the decline of AM fungal colonization in jarrah. Four weeks after exposure to the Pi pulse, plants inoculated with S. calospora had significantly lower toxicity symptoms compared to non-mycorrhizal (NM) plants, and all fungal treatments induced tolerance against Phi toxicity in jarrah. However, no tolerance was observed for AsV-treated plants even though all inoculated plants had significantly lower shoot As concentrations than the NM plants. The transcript profile of five jarrah high-affinity phosphate transporter (PHT1 family) genes in roots was not altered in response to any of the fungal species tested. Interestingly, plants exposed to high Pi supplies for 1 day did not have reduced transcript levels for any of the five PHT1 genes in roots, and transcript abundance of four PHT1 genes actually increased. It is therefore suggested that jarrah, and perhaps other P-sensitive perennial species, respond positively to Pi available in the soil solution through increasing rather than decreasing the expression of selected PHT1 genes. Furthermore, Scleroderma sp. can be considered as a fungus with dual functional capacity capable of forming both ectomycorrhizal and non-colonizing associations, where both pathways are always accompanied by evident growth and nutritional benefits

NeuroBench:A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems

Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research field currently lacks standardized benchmarks, making it difficult to accurately measure technological advancements, compare performance with conventional methods, and identify promising future research directions. Prior neuromorphic computing benchmark efforts have not seen widespread adoption due to a lack of inclusive, actionable, and iterative benchmark design and guidelines. To address these shortcomings, we present NeuroBench: a benchmark framework for neuromorphic computing algorithms and systems. NeuroBench is a collaboratively-designed effort from an open community of nearly 100 co-authors across over 50 institutions in industry and academia, aiming to provide a representative structure for standardizing the evaluation of neuromorphic approaches. The NeuroBench framework introduces a common set of tools and systematic methodology for inclusive benchmark measurement, delivering an objective reference framework for quantifying neuromorphic approaches in both hardware-independent (algorithm track) and hardware-dependent (system track) settings. In this article, we present initial performance baselines across various model architectures on the algorithm track and outline the system track benchmark tasks and guidelines. NeuroBench is intended to continually expand its benchmarks and features to foster and track the progress made by the research community