Genome-wide Dissection of Co-selected UV-B Responsive Pathways in the UV-B Adaptation of Qingke

Qingke (Tibetan hulless barley) has long been cultivated and exposed to long-term and strong UV-B radiation on the Tibetan Plateau, which renders it an ideal species for elucidating novel UV-B responsive mechanisms in plants. Here we report a comprehensive metabolite profiling and metabolite-based genome-wide association study (mGWAS) using 196 diverse qingke and barley accessions. Our results demonstrated both constitutive and induced accumulation, and common genetic regulation, of metabolites from different branches of the phenylpropanoid pathway that are involved in UV-B protection. A total of 90 significant mGWAS loci for these metabolites were identified in barley-qingke differentiation regions, and a number of high-level metabolite trait alleles were found to be significantly enriched in qingke, suggesting co-selection of various phenylpropanoids. Upon dissecting the entire phenylpropanoid pathway, we identified some key determinants controlling natural variation of phenylpropanoid content, including three novel proteins, a flavone C-pentosyltransferase, a tyramine hydroxycinnamoyl acyltransferase, and a MYB transcription factor. Our study, furthermore, demonstrated co-selection of both constitutive and induced phenylpropanoids for UV-B protection in qingke.

SARS-CoV-2 infection causes immunodeficiency in recovered patients by downregulating CD19 expression in B cells via enhancing B-cell metabolism

The SARS-CoV-2 infection causes severe immune disruption.However,it is unclear if disrupted immune regulation still exists and pertains in recovered COVID-19 patients.In our study,we have characterized the immunephe no type of B cells from 15 recovered COVID-19 patients,and found that healthy controls and recovered patients had similar B-cell populations before and after BCR stimulation,but the frequencies of PBC in patients were significantly increased when compared to healthy controls before stimulation.However,the percentage of unswitched memory B cells was decreased in recovered patients but not changed in healthy controls upon BCR stimulation.Interestingly,we found that CD19 expression was significantly reduced in almost all the B-cell subsets in recovered patients.Moreover,the BCR signaling and early B-cell response were disrupted upon BCR stimulation.Mechanistically,we found that the reduced CD19 expression was caused by the dysregulation of cell metabolism.In conclusion,we found that SARS-CoV-2 infection causes immunodeficiency in recovered patients by downregulating CD19 expression in B cells via enhandng B-cell metabolism,which may provide a new intervention target to cure COVID-19.

Metabolome profiling by widely-targeted metabolomics and biomarker panel selection using machine-learning for patients in different stages of chronic kidney disease

Chronic kidney disease(CKD)is an increasingly prevalent medical condition associated with high mortality and cardiovascular complications.The intricate interplay between kidney dysfunction and subsequent metabolic disturbances may provide insights into the underlying mechanisms driving CKD onset and progression.Herein,we proposed a large-scale plasma metabolite identification and quantification system that combines the strengths of targeted and untargeted metabolomics technologies,i.e.,widely-targeted metabolomics(WT-Met)approach.WT-Met method enables large-scale identification and accurate quantification of thousands of metabolites.We collected plasma samples from 21 healthy controls and 62CKD patients,categorized into different stages(22 in stages 1-3,20 in stage 4,and 20 in stage 5).Using LC-MS-based WT-Met approach,we were able to effectively annotate and quantify a total of 1431metabolites from the plasma samples.Focusing on the 539 endogenous metabolites,we identified 399significantly altered metabolites and depicted their changing patterns from healthy controls to end-stage CKD.Furthermore,we employed machine-learning to identify the optimal combination of metabolites for predicting different stages of CKD.We generated a multiclass classifier consisting of 7 metabolites by machine-learning,which exhibited an average AUC of 0.99 for the test set.In general,amino acids,nucleotides,organic acids,and their metabolites emerged as the most significantly altered metabolites.However,their patterns of change varied across different stages of CKD.The 7-metabolite panel demonstrates promising potential as biomarker candidates for CKD.Further exploration of these metabolites can provide valuable insights into their roles in the etiology and progression of CKD.

COVID-19 induces new-onset insulin resistance and lipid metabolic dysregulation via regulation of secreted metabolic factors

Abnormal glucose and lipid metabolism in COVID-19 patients were recently reported with unclear mechanism.In this study,we retrospectively investigated a cohort of COVID-19 patients without pre-existing metabolic-related diseases,and found new-onset in suli n resista nee,hyperglycemia,and decreased HDL-C in these patie nts.Mecha nistically,SARS-CoV-2 infecti on in creased the expression of RE1-silencing transcription factor(REST),which modulated the expression of secreted metabolic factors including myeloperoxidase,apelin,and myostatin at the transcriptional level,resulting in the perturbation of glucose and lipid metabolism.Furthermore,several lipids,including(±)5-HETE,(±)12-HETE,propionic acid,and isobutyric acid were identified as the potential biomarkers of COVID-19-induced metabolic dysregulation,especially in insulin resistance.Taken together,our study revealed insulin resistance as the direct cause of hyperglycemia upon COVID-19,and further illustrated the underlying mechanisms,providing potential therapeutic targets for COVID-19-induced metabolic complications.

Watermelon domestication was shaped by stepwise selection and regulation of the metabolome

Although crop domestication has greatly aided human civilization,the sequential domestication and regulation of most quality traits remain poorly understood.Here,we report the stepwise selection and regulation of major fruit quality traits that occurred during watermelon evolution.The levels of fruit cucurbitacins and flavonoids were negatively selected during speciation,whereas sugar and carotenoid contents were positively selected during domestication.Interestingly,fruit malic acid and citric acid showed the opposite selection trends during the improvement.We identified a novel gene cluster(CGC1,cucurbitacin gene cluster on chromosome 1)containing both regulatory and structural genes involved in cucurbitacin biosynthesis,which revealed a cascade of transcriptional regulation operating mechanisms.In the CGC1,an allele caused a single nucleotide change in Cl ERF1 binding sites(GCC-box)in the promoter of Cl Bh1,which resulted in reduced expression of Cl Bh1 and inhibition of cucurbitacin synthesis in cultivated watermelon.Functional analysis revealed that a rare insertion of 244 amino acids,which arose in C.amarus and became fixed in sweet watermelon,in Cl OSC(oxidosqualene cyclase)was critical for the negative selection of cucurbitacins during watermelon evolution.This research provides an important resource for metabolomics-assisted breeding in watermelon and for exploring metabolic pathway regulation mechanisms.