Concept of Fluorescent Transport Activity Biosensor for the Characterization of the Arabidopsis NPF1.3 Activity of Nitrate.

The NRT1/PTR FAMILY (NPF) in Arabidopsis (Arabidopsis thaliana) plays a major role as a nitrate transporter. The first nitrate transporter activity biosensor NiTrac1 converted the dual-affinity nitrate transceptor NPF6.3 into fluorescence activity sensors. To test whether this approach is transferable to other members of this family, screening for genetically encoded fluorescence transport activity sensor was performed with the member of the NPF family in Arabidopsis. In this study, NPF1.3, an uncharacterized member of NPF in Arabidopsis, was converted into a transporter activity biosensor NiTrac-NPF1.3 that responds specifically to nitrate. The emission ratio change of NiTrac-NPF1.3 triggered by the addition of nitrate reveals the important function of NPF1.3 in nitrate transport in Arabidopsis. A functional analysis of Xenopus laevis oocytes confirmed that NPF1.3 plays a role as a nitrate transporter. This new technology is applicable in plant and medical research.

The Pathomechanism, Antioxidant Biomarkers, and Treatment of Oxidative Stress-Related Eye Diseases.

Oxidative stress is an important pathomechanism found in numerous ocular degenerative diseases. To provide a better understanding of the mechanism and treatment of oxidant/antioxidant imbalance-induced ocular diseases, this article summarizes and provides updates on the relevant research. We review the oxidative damage (e.g., lipid peroxidation, DNA lesions, autophagy, and apoptosis) that occurs in different areas of the eye (e.g., cornea, anterior chamber, lens, retina, and optic nerve). We then introduce the antioxidant mechanisms present in the eye, as well as the ocular diseases that occur as a result of antioxidant imbalances (e.g., keratoconus, cataracts, age-related macular degeneration, and glaucoma), the relevant antioxidant biomarkers, and the potential of predictive diagnostics. Finally, we discuss natural antioxidant therapies for oxidative stress-related ocular diseases.

Feedback inhibition of AMT1 NH4+-transporters mediated by CIPK15 kinase.

BACKGROUND: Ammonium (NH4+), a key nitrogen form, becomes toxic when it accumulates to high levels. Ammonium transporters (AMTs) are the key transporters responsible for NH4+ uptake. AMT activity is under allosteric feedback control, mediated by phosphorylation of a threonine in the cytosolic C-terminus (CCT). However, the kinases responsible for the NH4+-triggered phosphorylation remain unknown. RESULTS: In this study, a functional screen identified protein kinase CBL-Interacting Protein Kinase15 (CIPK15) as a negative regulator of AMT1;1 activity. CIPK15 was able to interact with several AMT1 paralogs at the plasma membrane. Analysis of AmTryoshka, an NH4+ transporter activity sensor for AMT1;3 in yeast, and a two-electrode-voltage-clamp (TEVC) of AMT1;1 in Xenopus oocytes showed that CIPK15 inhibits AMT activity. CIPK15 transcript levels increased when seedlings were exposed to elevated NH4+ levels. Notably, cipk15 knockout mutants showed higher 15NH4+ uptake and accumulated higher amounts of NH4+ compared to the wild-type. Consistently, cipk15 was hypersensitive to both NH4+ and methylammonium but not nitrate (NO3-). CONCLUSION: Taken together, our data indicate that feedback inhibition of AMT1 activity is mediated by the protein kinase CIPK15 via phosphorylation of residues in the CCT to reduce NH4+-accumulation.

Fluorescent Biosensor Imaging of Nitrate in Arabidopsis thaliana.

Nitrate (NO3-) is an essential element and nutrient for plants and animals. Despite extensive studies on the regulation of nitrate uptake and downstream responses in various cells, our knowledge of the distribution of nitrogen forms in different root cell types and their cellular compartments is still limited. Previous physiological models have relied on in vitro biochemistry and metabolite level analysis, which limits the ability to differentiate between cell types and compartments. Here, to address this, we report a nuclear-localized, genetically encoded fluorescent biosensor, which we named nlsNitraMeter3.0, for the quantitative visualization of nitrate concentration and distribution at the cellular level in Arabidopsis thaliana. This biosensor was specifically designed for nitrate measurements, not nitrite. Through genetic engineering to create and select sensors using yeast, Xenopus oocyte, and Arabidopsis expression systems, we developed a reversible and highly specific nitrate sensor. This method, combined with fluorescence imaging systems such as confocal microscopy, allows for the understanding and monitoring of nitrate transporter activity in plant root cells in a minimally invasive manner. Furthermore, this approach enables the functional analysis of nitrate transporters and the measurement of nitrate distribution in plants, providing a valuable tool for plant biology research. In summary, we provide a protocol for sensor development and a biosensor that can be used to monitor nitrate levels in plants. Key features This protocol builds upon the concept of FRET biosensors for in vivo visualization of spatiotemporal nitrate levels at a cellular resolution. Nitrate levels can be quantified utilizing the biosensor in conjunction with either a plate reader or a fluorescence microscope.

CIPK15-mediated inhibition of NH4+ transport protects Arabidopsis from submergence.

Ammonium (NH4+) serves as a vital nitrogen source for plants, but it can turn toxic when it accumulates in excessive amounts. Toxicity is aggravated under hypoxic/anaerobic conditions, e.g., during flooding or submergence, due to a lower assimilation capacity. AMT1; 1 mediates NH4+ uptake into roots. Under conditions of oxygen-deficiency, i.e., submergence, the CBL-interacting protein kinase OsCIPK15 has been shown to trigger SnRK1A signaling, promoting starch mobilization, thereby the increasing availability of ATP, reduction equivalents and acceptors for NH4+ assimilation in rice. Our previous study in Arabidopsis demonstrates that AtCIPK15 phosphorylates AMT1; 1 whose activity is under allosteric feedback control by phosphorylation of T460 in the cytosolic C-terminus. Here we show that submergence cause higher NH4+ accumulation in wild-type, plant but not of nitrate, nor in a quadruple amt knock-out mutant. In addition, submergence triggers rapid accumulation of AtAMT1;1 and AtCIPK15 transcripts as well as AMT1 phosphorylation. Significantly, cipk15 knock-out mutants do not exhibit an increase in AMT1 phosphorylation; however, they do display heightened sensitivity to submergence. These findings suggest that CIPK15 suppresses AMT activity, resulting in decreased NH4+ accumulation during submergence, a period when NH4+ assimilation capacity may be impaired.

In vivo visualization of nitrate dynamics using a genetically encoded fluorescent biosensor.

Nitrate (NO3-) uptake and distribution are critical to plant life. Although the upstream regulation of NO3- uptake and downstream responses to NO3- in a variety of cells have been well studied, it is still not possible to directly visualize the spatial and temporal distribution of NO3- with high resolution at the cellular level. Here, we report a nuclear-localized, genetically encoded fluorescent biosensor, which we named NitraMeter3.0, for the quantitative visualization of NO3- distribution in Arabidopsis thaliana. This biosensor tracked the spatiotemporal distribution of NO3- along the primary root axis and disruptions by genetic mutation of transport (low NO3- uptake) and assimilation (high NO3- accumulation). The developed biosensor effectively monitors NO3- concentrations at the cellular level in real time and spatiotemporal changes during the plant life cycle.

Loss of heterozygosity of FCY2 leading to the development of flucytosine resistance in Candida tropicalis.

As fluconazole resistance becomes an emerging issue for treating infections caused by Candida tropicalis, searching for alternative becomes a prominent task. In the present study, 97 clinical isolates of C. tropicalis were tested for the susceptibilities to flucytosine (5FC) with the Etest method. Although only one isolate was resistant to 5FC, 30 susceptible isolates could produce resistant progeny after exposure to the drug. Interestingly, 22 of these 30 clinical isolates had a heterozygous G/T at the 145th position on FCY2, encoding purine-cytosine permease, whereas their progeny recovered from within the inhibitory ellipses had homozygous T/T, resulting in null alleles for both copies of the gene and produced only truncated proteins, effecting the 5FC resistance. Furthermore, we found that two major fluconazole-resistant clinical clones, diploid sequence type 98 (DST98) and DST140, had a homozygous G/G at the 145th position, and neither was able to produce 5FC-resistant progeny within the inhibitory ellipses. Hence, strains of C. tropicalis containing heterozygous alleles may develop 5FC resistance readily, whereas those with homozygous G/G wild-type alleles can be treated with 5FC. Subsequently, a combination of 5FC and another antifungal drug is applicable for treating infections of C. tropicalis.

Evaluating the Effect of Topical Atropine Use for Myopia Control on Intraocular Pressure by Using Machine Learning.

Atropine is a common treatment used in children with myopia. However, it probably affects intraocular pressure (IOP) under some conditions. Our research aims to analyze clinical data by using machine learning models to evaluate the effect of 19 important factors on intraocular pressure (IOP) in children with myopia treated with topical atropine. The data is collected on 1545 eyes with spherical equivalent (SE) less than -10.0 diopters (D) treated with atropine for myopia control. Four machine learning models, namely multivariate adaptive regression splines (MARS), classification and regression tree (CART), random forest (RF), and eXtreme gradient boosting (XGBoost), were used. Linear regression (LR) was used for benchmarking. The 10-fold cross-validation method was used to estimate the performance of the five methods. The main outcome measure is that the 19 important factors associated with atropine use that may affect IOP are evaluated using machine learning models. Endpoint IOP at the last visit was set as the target variable. The results show that the top five significant variables, including baseline IOP, recruitment duration, age, total duration and previous cumulative dosage, were identified as most significant for evaluating the effect of atropine use for treating myopia on IOP. We can conclude that the use of machine learning methods to evaluate factors that affect IOP in children with myopia treated with topical atropine is promising. XGBoost is the best predictive model, and baseline IOP is the most accurate predictive factor for endpoint IOP among all machine learning approaches.