An optimized fluorescent biosensor for monitoring long-chain fatty acyl-CoAs metabolism in vivo.

Long-chain fatty acyl-CoAs (LCACoAs) are intermediates in lipid metabolism that exert a wide range of cellular functions. However, our knowledge about the subcellular distribution and regulatory impacts of LCACoAs is limited by a lack of methods for detecting LCACoAs in living cells and tissues. Here, we report our development of LACSerHR, a genetically encoded fluorescent biosensor that enables precise measurement of subtle fluctuations in the levels of endogenous LCACoAs in vivo. LACSerHR significantly improve the fluorescent brightness and analyte affinity, in vitro and in vivo testing showcased LACSerHR's large dynamic range. We demonstrate LACSerHR's capacity for real-time evaluation of LCACoA levels in specific subcellular compartments, for example in response to disruption of ACSL enzyme function in HEK293T cells. Moreover, we show the application of LACSerHR for sensitive measurement of elevated LCACoA levels in the livers of mouse models for two common metabolic diseases (NAFLD and type 2 diabetes). Thus, our LACSerHR sensor is a powerful, broadly applicable tool for studying LCACoAs metabolism and disease.

Monitoring Intracellular IP6 with a Genetically Encoded Fluorescence Biosensor.

Inositol hexakisphosphate (IP6), a naturally occurring metabolite of inositol with specific functions in different organelles or tissues, participates in numerous physiological processes and plays a key role in mammalian metabolic regulation. However, current IP6 detection methods, i.e., high-performance liquid chromatography and gel electrophoresis, require sample destruction and lack spatiotemporal resolution. Here, we construct and characterize a genetically encoded fluorescence biosensor named HIPSer that enables ratiometric quantitative IP6 detection in HEK293T cells and subcellular compartments. We demonstrate that HIPSer has a high sensitivity and relative selectivity for IP6 in vitro. We also provide proof-of-concept evidence that HIPSer can monitor IP6 levels in real time in HEK293T cells and can be targeted for IP6 detection in the nucleus of HEK293T cells. Moreover, HIPSer could also detect changes in IP6 content induced by chemical inhibition of IP6-metabolizing enzymes in HEK293T cells. Thus, HIPSer achieves spatiotemporally precise detection of fluctuations in endogenous IP6 in live cells and provides a versatile tool for mechanistic investigations of inositol phosphate functions in metabolism and signaling.

Multi-Modal Neuroimaging Neural Network-Based Feature Detection for Diagnosis of Alzheimer's Disease.

Alzheimer's disease (AD) is a neurodegenerative brain disease, and it is challenging to mine features that distinguish AD and healthy control (HC) from multiple datasets. Brain network modeling technology in AD using single-modal images often lacks supplementary information regarding multi-source resolution and has poor spatiotemporal sensitivity. In this study, we proposed a novel multi-modal LassoNet framework with a neural network for AD-related feature detection and classification. Specifically, data including two modalities of resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) were adopted for predicting pathological brain areas related to AD. The results of 10 repeated experiments and validation experiments in three groups prove that our proposed framework outperforms well in classification performance, generalization, and reproducibility. Also, we found discriminative brain regions, such as Hippocampus, Frontal_Inf_Orb_L, Parietal_Sup_L, Putamen_L, Fusiform_R, etc. These discoveries provide a novel method for AD research, and the experimental study demonstrates that the framework will further improve our understanding of the mechanisms underlying the development of AD.

Feature Fusion and Detection in Alzheimer's Disease Using a Novel Genetic Multi-Kernel SVM Based on MRI Imaging and Gene Data.

Voxel-based morphometry provides an opportunity to study Alzheimer's disease (AD) at a subtle level. Therefore, identifying the important brain voxels that can classify AD, early mild cognitive impairment (EMCI) and healthy control (HC) and studying the role of these voxels in AD will be crucial to improve our understanding of the neurobiological mechanism of AD. Combining magnetic resonance imaging (MRI) imaging and gene information, we proposed a novel feature construction method and a novel genetic multi-kernel support vector machine (SVM) method to mine important features for AD detection. Specifically, to amplify the differences among AD, EMCI and HC groups, we used the eigenvalues of the top 24 Single Nucleotide Polymorphisms (SNPs) in a p-value matrix of 24 genes associated with AD for feature construction. Furthermore, a genetic multi-kernel SVM was established with the resulting features. The genetic algorithm was used to detect the optimal weights of 3 kernels and the multi-kernel SVM was used after training to explore the significant features. By analyzing the significance of the features, we identified some brain regions affected by AD, such as the right superior frontal gyrus, right inferior temporal gyrus and right superior temporal gyrus. The findings proved the good performance and generalization of the proposed model. Particularly, significant susceptibility genes associated with AD were identified, such as CSMD1, RBFOX1, PTPRD, CDH13 and WWOX. Some significant pathways were further explored, such as the calcium signaling pathway (corrected p-value = 1.35 × 10-6) and cell adhesion molecules (corrected p-value = 5.44 × 10-4). The findings offer new candidate abnormal brain features and demonstrate the contribution of these features to AD.

A Ratiometric Fluorescent Biosensor Reveals Dynamic Regulation of Long-Chain Fatty Acyl-CoA Esters Metabolism.

Despite increasing awareness of the biological impacts of long-chain fatty acyl-CoA esters (LCACoAs), our knowledge about the subcellular distribution and regulatory functions of these acyl-CoA molecules is limited by a lack of methods for detecting LCACoAs in living cells. Here, we report development of a genetically encoded fluorescent sensor that enables ratiometric quantification of LCACoAs in living cells and subcellular compartments. We demonstrate how this FadR-cpYFP fusion "LACSer sensor" undergoes LCACoA-induced conformational changes reflected in easily detectable fluorescence responses, and show proof-of-concept for real-time monitoring of LCACoAs in human cells. Subsequently, we applied LACSer in scientific studies investigating how disruption of ACSL enzymes differentially reduces cytosolic and mitochondrial LCACoA levels, and show how genetic disruption of an acyl-CoA binding protein (ACBP) alters mitochondrial accumulation of LCACoAs.

Promotion of Zinc Tolerance, Acquisition and Translocation of Phosphorus in Mimosa pudica L. Mediated by Arbuscular Mycorrhizal Fungi.

Heavy metal contamination of soil is of increasing concern because of its potential risk to human health. In this study, two AMFs (Rhizophagus intraradices and Funneliformis mosseae) substantially increased the biomass of bashfulgrass in Zn-contaminated soil, even at Zn levels of up to 600 mg kg-1. Zn uptake in R. intraradices- and F. mosseae-mycorrhizal bashfulgrass was increased by 40-fold and 7-fold, respectively, when plants grown in Zn-contaminated (400 mg kg-1) soil. Elemental analysis showed that neither AMF had an effect on Zn concentration in plant tissues, including the roots and shoots. However, a significant increase of phosphorus (P) concentration was observed, suggesting the increased is from the improved use efficiency of soil nutrients by AMFs. Comparing the two AMFs, better growth performance with more biomass occurred with R. intraradices-inoculated bashfulgrass in Zn-contaminated soil. This is consistent with R. intraradices being more tolerant to Zn than F. mosseae, indicated by a higher colonization percentage in bashfulgrass roots. Taken together, our data indicate that AMFs possibly improve acquisition and translocation of P to promote increased biomass. Moreover, mycorrhiza did not enhance Zn accumulation in shoots and roots of bashfulgrass at the same Zn level. In the future, developing AMF (especially R. intraradices) inoculation of plants might be a desirable means of safe production of ornamental plants in metal-polluted soil.

Promotion of growth and phytoextraction of cadmium and lead in Solanum nigrum L. mediated by plant-growth-promoting rhizobacteria.

Plant growth-promoting rhizobacteria (PGPR) are a specific category of microbes that improve plant growth and promote greater tolerance to metal stress through their interactions with plant roots. We evaluated the effects of phytoremediation combining the cadmium accumulator Solanum nigrum L. and two Cd- and Pb-resistant bacteria isolates. To understand the interaction between PGPR and their host plant, we conducted greenhouse experiments with inoculation treatments at Nanjing Agricultural University (Jiangsu Province, China), in June 2018. Two Cd- and Pb-resistant PGPR with various growth-promoting properties were isolated from heavy metal-contaminated soil. 16S rRNA analyses indicated that the two isolates were Bacillus genus, and they were named QX8 and QX13. Pot experiments demonstrated that inoculation may improve the rhizosphere soil environment and promote absorption of Fe and P by plants. Inoculation with QX8 and QX13 also enhanced the dry weight of shoots (1.36- and 1.7-fold, respectively) and roots (1.42- and 1.96-fold) of plants growing in Cd- and Pb-contaminated soil, and significantly increased total Cd (1.28-1.81 fold) and Pb (1.08-1.55 fold) content in aerial organs, compared to non-inoculated controls. We also detected increases of 23% and 22% in the acid phosphatase activity of rhizosphere soils inoculated with QX8 and QX13, respectively. However, we did not detect significant differences between inoculated and non-inoculated treatments in Cd and Pb concentrations in plants and available Cd and Pb content in rhizosphere soils. We demonstrated that PGPR-assisted phytoremediation is a promising technique for remediating heavy metal-contaminated soils, with the potential to enhance phytoremediation efficiency and improve soil quality.