Comparison of high performance liquid chromatography and spectrophotometry in the determination of chitosan content in water-soluble fertilizers

Different analytical methods for the determination of chitosan content in water-soluble fertilizers by HPLC and spectrophotometry were established, and the hydrolysis conditions of chitosan were systematically studied. The results showed that the hydrolysis effect of 1+1 hydrochloric acid solution at 100℃ for 24h was the best. Linear range of HPLC with 1-phenyl-3-methyl-5-pyrazolone (PMP) as derivatizing agent. The detection limit and spiked recovery are 1~200 mg/l, 0.07 mg/l and 95~101% respectively, and the corresponding indicators of spectrophotometry are respectively 0~100μg, 0.47μg and 94%. Through comparison, the two methods have good consistency in the determination results of water-soluble fertilizer samples, and can meet the analysis requirements of chitosan content in water-soluble fertilizer. Among them, HPLC has fewer interference factors and higher efficiency. In addition, methyl fluorene chloroformate (Fmoc-Cl) was also used as a derivant to derive the hydrolysate of chitosan, and then detected by high performance liquid chromatography. It was found that the measured results were basically consistent with the above two methods, but the high performance liquid chromatography and spectrophotometry established in this study were not suitable for the determination of chitosan content in water-soluble fertilizer containing nitrate

Metabolome and Transcriptome Analyses Unravels Molecular Mechanisms of Leaf Color Variation by Anthocyanidin Biosynthesis in Acer triflorum

Acer triflorum Komarov is an important ornamental tree, and its seasonal change in leaf color is the most striking feature. However, the quantifications of anthocyanin and the mechanisms of leaf color change in this species remain unknown. Here, the combined analysis of metabolome and transcriptome was performed on green, orange, and red leaves. In total, 27 anthocyanin metabolites were detected and cyanidin 3-O-arabinoside, pelargonidin 3-O-glucoside, and peonidin 3-O-gluside were significantly correlated with the color development. Several structural genes in the anthocyanin biosynthesis process, such as chalcone synthase (CHS), flavanone 3-hydroxylase (F3H), and dihydroflavonol 4-reductase (DFR), were highly expressed in red leaves compared to green leaves. Most regulators (MYB, bHLH, and other classes of transcription factors) were also upregulated in red and orange leaves. In addition, 14 AtrMYBs including AtrMYB68, AtrMYB74, and AtrMYB35 showed strong interactions with the genes involved in anthocyanin biosynthesis, and, thus, could be further considered the hub regulators. The findings will facilitate genetic modification or selection for further improvement in ornamental qualities of A. triflorum

Chromosome-Level Genome Assembly for Acer pseudosieboldianum and Highlights to Mechanisms for Leaf Color and Shape Change

Acer pseudosieboldianum (Pax) Komarov is an ornamental plant with prominent potential and is naturally distributed in Northeast China. Here, we obtained a chromosome-scale genome assembly of A. pseudosieboldianum combining HiFi and Hi-C data, and the final assembled genome size was 690.24 Mb and consisted of 287 contigs, with a contig N50 value of 5.7 Mb and a BUSCO complete gene percentage of 98.4%. Genome evolution analysis showed that an ancient duplication occurred in A. pseudosieboldianum. Phylogenetic analyses revealed that Aceraceae family could be incorporated into Sapindaceae, consistent with the present Angiosperm Phylogeny Group system. We further construct a gene-to-metabolite correlation network and identified key genes and metabolites that might be involved in anthocyanin biosynthesis pathways during leaf color change. Additionally, we identified crucial teosinte branched1, cycloidea, and proliferating cell factors (TCP) transcription factors that might be involved in leaf morphology regulation of A. pseudosieboldianum, Acer yangbiense and Acer truncatum. Overall, this reference genome is a valuable resource for evolutionary history studies of A. pseudosieboldianum and lays a fundamental foundation for its molecular breeding

Neuropathic Injury-Induced Plasticity of GABAergic System in Peripheral Sensory Ganglia

GABA is a major inhibitory neurotransmitter in the mammalian central nervous system (CNS). Inhibitory GABAA channel circuits in the dorsal spinal cord are the gatekeepers of the nociceptive input from the periphery to the CNS. Weakening of these spinal inhibitory mechanisms is a hallmark of chronic pain. Yet, recent studies have suggested the existence of an earlier GABAergic “gate” within the peripheral sensory ganglia. In this study, we performed systematic investigation of plastic changes of the GABA-related proteins in the dorsal root ganglion (DRG) in the process of neuropathic pain development. We found that chronic constriction injury (CCI) induced general downregulation of most GABAA channel subunits and the GABA-producing enzyme, glutamate decarboxylase, consistent with the weakening of the GABAergic inhibition at the periphery. Strikingly, the α5 GABAA subunit was consistently upregulated. Knock-down of the α5 subunit in vivo moderately alleviated neuropathic hyperalgesia. Our findings suggest that while the development of neuropathic pain is generally accompanied by weakening of the peripheral GABAergic system, the α5 GABAA subunit may have a unique pro-algesic role and, hence, might represent a new therapeutic target

Recognizing the Continuous Nature of Expression Heterogeneity and Clinical Outcomes in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) has been previously classified into putative discrete prognostic subtypes by gene expression profiling. To investigate the robustness of these proposed subtype classifications, we evaluated 12 public datasets, together with a new dataset of 265 ccRCC gene expression profiles. Consensus clustering showed unstable subtype and principal component analysis (PCA) showed a continuous spectrum both within and between datasets. Considering the lack of discrete delineation and continuous spectrum observed, we developed a continuous quantitative prognosis score (Continuous Linear Enhanced Assessment of RCC, or CLEAR score). Prognostic performance was evaluated in independent cohorts from The Cancer Genome Atlas (TCGA) (n = 414) and EMBL-EBI (n = 53), CLEAR score demonstrated both superior prognostic estimates and inverse correlation with anti-angiogenic tyrosine-kinase inhibition in comparison to previously proposed discrete subtyping classifications. Inverse correlation with high-dose interleukin-2 outcomes was also observed for the CLEAR score. Multiple somatic mutations (VHL, PBRM1, SETD2, KDM5C, TP53, BAP1, PTEN, MTOR) were associated with the CLEAR score. Application of the CLEAR score to independent expression profiling of intratumoral ccRCC regions demonstrated that average intertumoral heterogeneity exceeded intratumoral expression heterogeneity. Wider investigation of cancer biology using continuous approaches may yield insights into tumor heterogeneity; single cell analysis may provide a key foundation for this approach

The Manchurian Walnut Genome: Insights into Juglone and Lipid Biosynthesis

Background Manchurian walnut (Juglans mandshurica Maxim.) is a tree with multiple industrial uses and medicinal properties in the Juglandaceae family (walnuts and hickories). J. mandshurica produces juglone, which is a toxic allelopathic agent and has potential utilization value. Furthermore, the seed of J. mandshurica is rich in various unsaturated fatty acids and has high nutritive value. Findings Here, we present a high-quality chromosome-scale reference genome assembly and annotation for J. mandshurica (n = 16) with a contig N50 of 21.4 Mb by combining PacBio high-fidelity reads with high-throughput chromosome conformation capture data. The assembled genome has an estimated sequence size of 548.7 Mb and consists of 657 contigs, 623 scaffolds, and 40,453 protein-coding genes. In total, 60.99% of the assembled genome consists of repetitive sequences. Sixteen super-scaffolds corresponding to the 16 chromosomes were assembled, with a scaffold N50 length of 33.7 Mb and a BUSCO complete gene percentage of 98.3%. J. mandshurica displays a close sequence relationship with Juglans cathayensis, with a divergence time of 13.8 million years ago. Combining the high-quality genome, transcriptome, and metabolomics data, we constructed a gene-to-metabolite network and identified 566 core and conserved differentially expressed genes, which may be involved in juglone biosynthesis. Five CYP450 genes were found that may contribute to juglone accumulation. NAC, bZip, NF-YA, and NF-YC are positively correlated with the juglone content. Some candidate regulators (e.g., FUS3, ABI3, LEC2, and WRI1 transcription factors) involved in the regulation of lipid biosynthesis were also identified. Conclusions Our genomic data provide new insights into the evolution of the walnut genome and create a new platform for accelerating molecular breeding and improving the comprehensive utilization of these economically important tree species

Recognizing the Continuous Nature of Expression Heterogeneity and Clinical Outcomes in Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) has been previously classified into putative discrete prognostic subtypes by gene expression profiling. To investigate the robustness of these proposed subtype classifications, we evaluated 12 public datasets, together with a new dataset of 265 ccRCC gene expression profiles. Consensus clustering showed unstable subtype and principal component analysis (PCA) showed a continuous spectrum both within and between datasets. Considering the lack of discrete delineation and continuous spectrum observed, we developed a continuous quantitative prognosis score (Continuous Linear Enhanced Assessment of RCC, or CLEAR score). Prognostic performance was evaluated in independent cohorts from The Cancer Genome Atlas (TCGA) (n = 414) and EMBL-EBI (n = 53), CLEAR score demonstrated both superior prognostic estimates and inverse correlation with anti-angiogenic tyrosine-kinase inhibition in comparison to previously proposed discrete subtyping classifications. Inverse correlation with high-dose interleukin-2 outcomes was also observed for the CLEAR score. Multiple somatic mutations (VHL, PBRM1, SETD2, KDM5C, TP53, BAP1, PTEN, MTOR) were associated with the CLEAR score. Application of the CLEAR score to independent expression profiling of intratumoral ccRCC regions demonstrated that average intertumoral heterogeneity exceeded intratumoral expression heterogeneity. Wider investigation of cancer biology using continuous approaches may yield insights into tumor heterogeneity; single cell analysis may provide a key foundation for this approach

Update of TTD: Therapeutic Target Database

Increasing numbers of proteins, nucleic acids and other molecular entities have been explored as therapeutic targets, hundreds of which are targets of approved and clinical trial drugs. Knowledge of these targets and corresponding drugs, particularly those in clinical uses and trials, is highly useful for facilitating drug discovery. Therapeutic Target Database (TTD) has been developed to provide information about therapeutic targets and corresponding drugs. In order to accommodate increasing demand for comprehensive knowledge about the primary targets of the approved, clinical trial and experimental drugs, numerous improvements and updates have been made to TTD. These updates include information about 348 successful, 292 clinical trial and 1254 research targets, 1514 approved, 1212 clinical trial and 2302 experimental drugs linked to their primary targets (3382 small molecule and 649 antisense drugs with available structure and sequence), new ways to access data by drug mode of action, recursive search of related targets or drugs, similarity target and drug searching, customized and whole data download, standardized target ID, and significant increase of data (1894 targets, 560 diseases and 5028 drugs compared with the 433 targets, 125 diseases and 809 drugs in the original release described in previous paper). This database can be accessed at http://bidd.nus.edu.sg/group/cjttd/TTD.asp

Genome-wide studies reveal the essential and opposite roles of ARID1A in controlling human cardiogenesis and neurogenesis from pluripotent stem cells

Background Early human heart and brain development simultaneously occur during embryogenesis. Notably, in human newborns, congenital heart defects strongly associate with neurodevelopmental abnormalities, suggesting a common gene or complex underlying both cardiogenesis and neurogenesis. However, due to lack of in vivo studies, the molecular mechanisms that govern both early human heart and brain development remain elusive. Results Here, we report ARID1A, a DNA-binding subunit of the SWI/SNF epigenetic complex, controls both neurogenesis and cardiogenesis from human embryonic stem cells (hESCs) through distinct mechanisms. Knockout-of-ARID1A (ARID1A−/−) leads to spontaneous differentiation of neural cells together with globally enhanced expression of neurogenic genes in undifferentiated hESCs. Additionally, when compared with WT hESCs, cardiac differentiation from ARID1A −/− hESCs is prominently suppressed, whereas neural differentiation is significantly promoted. Whole genome-wide scRNA-seq, ATAC-seq, and ChIP-seq analyses reveal that ARID1A is required to open chromatin accessibility on promoters of essential cardiogenic genes, and temporally associated with key cardiogenic transcriptional factors T and MEF2C during early cardiac development. However, during early neural development, transcription of most essential neurogenic genes is dependent on ARID1A, which can interact with a known neural restrictive silencer factor REST/NRSF. Conclusions We uncover the opposite roles by ARID1A to govern both early cardiac and neural development from pluripotent stem cells. Global chromatin accessibility on cardiogenic genes is dependent on ARID1A, whereas transcriptional activity of neurogenic genes is under control by ARID1A, possibly through ARID1A-REST/NRSF interaction