Biology subjects

Cui, Y.

Publications and source records attributed to Cui, Y..

At least 217 records · Page 12Linked to original sources

bioRxiv2020

Transfer learning for reducing health disparity arising from data inequality

As artificial intelligence (AI) is increasingly applied to biomedical research and clinical decisions, developing unbiased AI models that work equally well for all racial and ethnic groups is of crucial importance to health disparity prevention and reduction. However, the biomedical data inequality between different racial and ethnic groups is set to generate new health care disparities through data-driven, algorithm-based biomedical research and clinical decisions. Using an extensive set of machine learning experiments on cancer omics data, we found that current prevalent schemes of multiethnic machine learning are prone to generating significant model performance disparities between racial groups. We showed that these performance disparities are caused by data inequality and data distribution discrepancies between racial groups. We also found that transfer learning can improve machine learning model performance for data-disadvantaged racial groups, and thus provides a novel approach to reduce health care disparities arising from data inequality among racial groups.

bioinformatics↗

bioRxiv2019

Enhanced emotional memory retrieval by chemogenetic activation of locus coeruleus norepinephrine neurons

The ability to retrieve memory store in response to the environment is essential for animal behavioral adaptation. Norepinephrine (NE)-containing neurons in the brain play a key role in the modulation of synaptic plasticity underlying various processes of memory formation. However, the role of the central NE system in memory retrieval remains unclear. In this study, we developed a neural chemogenetic activation strategy using insect olfactory Ionotropic Receptors (IRs), and used it for selective stimulation of NE neurons in the locus coeruleus (LC) in transgenic mice. Ligand-induced activation of LC NE neurons resulted in enhancement of the retrieval process of conditioned taste aversion, which was mediated through at least partly adrenergic receptors in the amygdala. Pharmacological blockade of LC activity confirmed the facilitative role of these neurons in memory retrieval. Our findings indicate that the LC-amygdalar pathway is required and sufficient for enhancing the recall of taste associative memory.

neuroscience↗

bioRxiv2019

Deep convolutional neural network and attention mechanism based pan-specific model for interpretable MHC-I peptide binding prediction

Accurate prediction of peptide binding affinity to the major histocompatibility complex (MHC) proteins has the potential to design better therapeutic vaccines. Previous work has shown that pan-specific prediction algorithms can achieve better prediction performance than other approaches. However, most of the top algorithms are neural networks based black box models. Here, we propose DeepAttentionPan, an improved pan-specific model, based on convolutional neural networks and attention mechanisms for more flexible, stable and interpretable MHC-I binding prediction. With the attention mechanism, our ensemble model consisting of 20 trained networks achieves high and more stabilized prediction performance. Extensive tests on IEDBs weekly benchmark dataset show that our method achieves state-of-the-art prediction performance on 21 test allele datasets. Analysis of the peptide positional attention weights learned by our model demonstrates its capability to capture critical binding positions of the peptides, which leads to mechanistic understanding of MHC-peptide binding with high alignment with experimentally verified results. Furthermore, we show that with transfer learning, our pan model can be fine-tuned for alleles with few samples to achieve additional performance improvement. DeepAttentionPan is freely available as an open source software at https://github.com/jjin49/DeepAttentionPan.\n\nAuthor summaryHuman leukocyte antigen (HLA) proteins are classes of proteins that are responsible for immune system regulation in humans. The peptides are short chains of amino acids. HLA class I group present peptides from inside the cell to the cell surface for scrutiny by T cell receptors. For instance, if the cell is infected by a virus, the HLA system will bind to the peptides derived from viral proteins and bring them to the surface of the cell so that the cell can be destroyed by the immune system. Since the HLA genes exhibit extensive polymorphism, there are many HLA alleles binding to different peptides. And this diversity represents challenges in predicting binders for different HLA alleles, which are important in vaccine designs and characterization of immune responses. Before computational algorithms are used to predict the binding relationships of HLA-peptide pairs, scientists need to conduct costly biological experiments to do preliminary screening among a number of peptides and need to use mutant experiments to identify key peptide positions that contribute to the binding. While previous computational methods have been proposed to predict the binding affinity, identifying the binding anchors is not well addressed. Here we developed a deep neural network models with the attention mechanism to learn the binding relationships automatically in an end-to-end way. Our models are able to identify the important binding positions of the peptide sequence by learning the positional importance distribution, which used to be studied a lot only through costly experimental methods. Our model thus not only improves the performance of binding affinity prediction but also allows us to gain biological insight of binding motifs of different alleles via interpreting the learned deep neural network models.

bioinformatics↗

bioRxiv2019

DeepSeqPanII: an interpretable recurrent neural network model with attention mechanism for peptide-HLA class II binding prediction

Human leukocyte antigen (HLA) complex molecules play an essential role in immune interactions by presenting peptides on the cell surface to T cells. With significant progress in deep learning, a series of neural network based models have been proposed and demonstrated with their good performances for peptide-HLA class I binding prediction. However, there still lack effective binding prediction models for HLA class II protein binding with peptides due to its inherent challenges. In this work, we present a novel sequence-based pan-specific neural network structure, DeepSeaPanII, for peptide-HLA class II binding prediction. Compared with existing pan-specific models, our model is an end-to-end neural network model without the need for pre- or post-processing on input samples. Besides state-of-the-art peformance in binding affinity prediction, DeepSeqPanII can also extract biological insight on the binding mechanism over the peptide and HLA sequences by its attention mechanism based binding core prediction capability. The leave-one-allele-out cross validation and benchmark evaluation results show that our proposed network model achieved state-of-the-art performance in HLA-II peptide binding. The source code and trained models are freely available at https://github.com/pcpLiu/DeepSeqPanII.

bioinformatics↗

bioRxiv2019

Diagnostic value of circulating tumor DNA as an effective biomarker in cervical cancer: a meta-analysis

The applications of liquid biopsy have attracted much attention in biomedical research in recent years. Circulating cell-free DNA (cfDNA) in the serum may serve as a unique tumor marker in various types of cancer. Circulating tumor DNA (ctDNA) is a type of serum cfDNA found in patients with cancer and contains abundant information regarding tumor characteristics, highlighting its potential diagnostic value in the clinical setting. However, the diagnostic value of cfDNA as a biomarker in cervical cancer remains unclear. Here, we performed a meta-analysis to evaluate the applications of ctDNA as a biomarker in cervical cancer. A systematic literature search was performed using PubMed, Embase, and WANFANG MED ONLINE databases up to March 18, 2019. All literature was analyzed using Meta Disc 1.4 and STATA 14.0 software. Diagnostic measures of accuracy of ctDNA in cervical cancer were pooled and investigated. Fifteen studies comprising 1109 patients with cervical cancer met our inclusion criteria and were subjected to analysis. The pooled sensitivity and specificity were 0.52 (95% confidence interval [CI], 0.33-0.71) and 0.97 (95% CI, 0.91-0.99), respectively. The pooled positive likelihood ratio and negative likelihood ratio were 16.0 (95% CI, 5.5-46.4) and 0.50 (95% CI, 0.33-0.75), respectively. The diagnostic odds ratio was 32 (95% CI, 10-108), and the area under the summary receiver operating characteristic curve was 0.92 (95% CI, 0.90- 0.94). There was no significant publication bias observed. In the included studies, ctDNA showed clear diagnostic value for diagnosing and monitoring cervical cancer. Our meta-analysis suggested that detection of human papilloma virus ctDNA in patients with cervical cancer could be used as a noninvasive early dynamic biomarker of tumors, with high specificity and moderate sensitivity. Further large-scale prospective studies are required to validate the factors that may influence the accuracy of cervical cancer diagnosis and monitoring.

bioinformatics↗

bioRxiv2019

Computational redesign of PETase for plastic biodegradation by GRAPE strategy

The excessive use of plastics has been accompanied by severe ecologically damaging effects. The recent discovery of a PETase from Ideonella sakaiensis that decomposes poly(ethylene terephthalate) (PET) under mild conditions provides an attractive avenue for the biodegradation of plastics. However, the inherent instability of the enzyme limits its practical utilization. Here, we devised a novel computational strategy (greedy accumulated strategy for protein engineering, GRAPE). A systematic clustering analysis combined with greedy accumulation of beneficial mutations in a computationally derived library enabled the design of a variant, DuraPETase, which exhibits an apparent melting temperature that is drastically elevated by 31 {degrees}C and strikingly enhanced degradation performance toward semicrystalline PET films (23%) at mild temperatures (over two orders of magnitude improvement). The mechanism underlying the robust promotion of enzyme performance has been demonstrated via a crystal structure and molecular dynamics simulations. This work shows the capabilities of computational enzyme design to circumvent antagonistic epistatic effects and provides a valuable tool for further understanding and advancing polyester hydrolysis in the natural environment.

synthetic biology↗

bioRxiv2019

A Ponceau Staining based Dot-Blot Assay for reliable and cost-effective Protein Quantification

Reliable quantification of protein extracts from tissues can be a challenge e.g. due to interference of the high fat content in tissues of the nervous system. Further problems like under- or overerstimation of protein concentrations in protein quantification kits like the bicinchoninic acid (BCA) assay can occur. In addition, common lysis buffers such as RIPA buffer are known to be unable to solubilize a large amount of proteins (~10-30%) leading to unsatisfactory and unreliable experimental results with techniques such as immunoblotting. In this work, we have developed a Ponceau S staining based protein quantification assay. This assay is compatible with tissues or cells directly lysed in 2x SDS gel loading buffer, containing bromophenolblue, leading to more complete protein extraction. Protein concentrations of several samples can be determined in a fast and cost-effective manner and subsequent experiments (e.g. Western blot) can be performed without loss of proteins. The presented protein quantification method is highly reliable, fast and economical. Using this method, it is possible to save between 2300 to 3200{euro} per 1000 lysates as compared to the costs of a commercial BCA kit.

biochemistry↗

bioRxiv2019

Multiple Myeloma DREAM Challenge Reveals Epigenetic Regulator PHF19 As Marker of Aggressive Disease

While the past decade has seen meaningful improvements in clinical outcomes for multiple myeloma patients, a subset of patients do not benefit from current therapeutics for unclear reasons. Many gene expression-based models of risk have been developed, but each model uses a different combination of genes and often involve assaying many genes making them difficult to implement. We organized the Multiple Myeloma DREAM Challenge, a crowdsourced effort to develop models of rapid progression in newly diagnosed myeloma patients and to benchmark these against previously published models. This effort lead to more robust predictors and found that incorporating specific demographic and clinical features improved gene expression-based models of high risk. Furthermore, post challenge analysis identified a novel expression-based risk marker and histone modifier, PHF19, which featured prominently in several independent models. Lastly, we show that a simple four feature predictor composed of age, International Staging System stage (ISS), and expression of PHF19 and MMSET performs similarly to more complex models with many more gene expression features included.\n\nKey pointsO_LIMost comprehensive and unbiased assessment of prognostic biomarkers in MM resulting in a robust and parsimonious model.\nC_LIO_LIIdentification of PHF19 as the expression based biomarker most strongly associated with rapid progression in MM patients.\nC_LI

cancer biology↗

bioRxiv2019

NbCycB2 represses Nbwo activity via a negative feedback loop in the tobacco trichome developmemt

The wo protein and its downstream gene, SlCycB2 have been demonstrated to regulate the trichome development in tomato. It was shown that only gain-of-function mutant form of wo, Wov (wo woolly motif mutant allele) could induce the increase of trichome density. However, it is still unclear the relationships between wo, Wov and SlCycB2 in trichome regulation. In this study, we demonstrated Nbwo (NbWov) directly regulated the expressions NbCycB2 by binding to the promoter of NbCycB2 and its genomic sequences. As a feedback regulation, NbCycB2 negatively regulates the trichome formation by repressing Nbwo activity at protein level. We further found that the mutations of Nbwo woolly motif could prevent repression of NbWov by NbCycB2, which results in the significant increase of active Nbwo proteins, trichome density and branches. Our results revealed a novel reciprocal mechanism between NbCycB2 and Nbwo during the trichome formation in Nicotiana benthamiana.\n\nHighlightNbCycB2 is specifically expressed in trichomes of Nicotiana benthamiana and represses the Nbwo activity via a negative feedback loop in tobacco trichome developmemt.

plant biology↗

bioRxiv2019

CD155/CD96 promotes immunosuppression in lung adenocarcinoma (LUAD)

Lung adenocarcinoma (LUAD) remains one of the leading causes of death in patients with cancer. The association of CD155 with CD96 transmits an inhibitory signal and suppresses antitumor immune response. This study investigates the effect of CD155/CD96 on immune suppression in LUAD. We demonstrate that LUAD patients with high CD155 expression suffer from immune suppression and experience a poor prognosis, which coincides with an inhibited AKT-mTOR signaling pathway in CD8 T cells and subsequently up-regulated CD96 expression. Moreover, the inhibition effect can be reversed by CD96 blocking antibody. High CD155 expression inhibited the release of IFN{gamma} from CD8 cells. Moreover, Blocking CD96 restored IFN{gamma} production in CD8 T cells and neutralized the inhibition of IFN{gamma} production in CD8 T cells mediated by CD155. Animal experiments showed that CD155-mediated LUAD growth might depend on its suppression antitumor immune response in the tumor microenvironment in PDX mice. In conclusion, our results suggest that LUAD cells suppress antitumor immune response in the tumor microenvironment through CD155/CD96. CD155/CD96 could be a potential therapeutic target for LUAD patients.\n\nAbbreviationsLUAD: lung adenocarcinoma; IFN{gamma}: interferon gamma; PDX: patient-derived xenograft; NSCLC: non-small cell lung cancer; PRR: poliovirus receptor-related; MDSCs: myeloid-derived suppressor cells; PRR: poliovirus receptor-related; STR: short tandem repeat; IRS: immunoreactive score; SI: staining intensity; PP: percentage of positive cells; RT-PCR: reverse transcription-polymerase chain reaction; PBS: phosphate-buffered saline; PBMCs: peripheral blood mononuclear cells; SDS-PAGE: sodium dodecyl sulfate-polyacrylamide gel electrophoresis; rCD155: recombinant human CD155; LUAD cells: lung adenocarcinoma cells; TILs: tumor-infiltrating lymphocytes; GzmB: granzyme B; IL-2 (Interleukin-2); TNF- : tumor necrosis factor-alpha; PI: propidium Iodide; PDX: patient-derived xenograft; TIGIT: T cell immunoreceptor with Igand ITIM domains; WBC: white blood cells; MFI: mean fluorescence intensity; HPF: high power field

cancer biology↗

bioRxiv2019

Precision Genome Editing Using Bacteriophage-derived Peptides

BackgroundCRISPR-Cas9 has been developed as a therapeutic agent for various infectious and genetic diseases. In many clinically relevant applications, constitutively active CRISPR-Cas9 is delivered into human cells without a temporal control system. Excessive and prolonged expression CRISPR-Cas9 can lead to elevated off-target cleavage. The need for modulating CRISPR-Cas9 activity over the dimensions of time and dose has created the demand of developing CRISPR-Cas off-switches. Protein and small molecule-based CRISPR-Cas inhibitors have been reported in previous studies. ResultsWe report the discovery of Cas9-inhibiting peptides from inoviridae bacteriophages. These peptides, derived from the periplasmic domain of phage major coat protein G8P (G8PPD), can inhibit the in vitro activity of Streptococcus pyogenes Cas9 (SpCas9) proteins in an allosteric manner. Importantly, the inhibitory activity of G8PPD on SpCas9 is dependent on the order of guide RNA addition. Ectopic expression of full-length G8P (G8PFL) or G8PPD in human cells can inactivate the genome-editing activity of SpCas9 with minimum alterations of the mutation patterns. Furthermore, unlike the anti-CRISPR protein AcrII4A that completely abolishes the cellular activity of CRISPR-Cas9, G8P co-transfection can reduce the off-target activity of co-transfected SpCas9 while retaining its on-target activity. ConclusionG8Ps discovered in the current study represent the first anti-CRISPR peptides that can allosterically inactivate CRISPR-Cas9. This finding may provide insights into developing next-generation CRISPR-Cas inhibitors for precision genome engineering.

genomics↗

bioRxiv2019

Global analysis of epigenetic heterogeneity identifies divergent drivers of esophageal squamous cell carcinoma

Epigenetic landscapes can shape physiologic and disease phenotypes. We used integrative, high resolution multi-omics methods to characterize the oncogenic drivers of esophageal squamous cell carcinoma (ESCC). We found 98% of CpGs are hypomethylated across the ESCC genome and two-thirds occur in long non-coding (lnc)RNA regions. DNA methylation and epigenetic heterogeneity both coincide with chromosomal topological alterations. Gene body methylation, polycomb repressive complex occupancy, and CTCF binding sites associate with cancer-specific gene regulation. Epigenetically-mediated activation of non-canonical WNT signaling and the lncRNA ESCCAL-1 were validated as potential ESCC driver alterations. Gene-specific cancer driver roles of epigenetic alterations and heterogeneity are identified.

cell biology↗

bioRxiv2019

A Network of Phosphatidylinositol 4,5-bisphosphate Binding Sites Regulate Gating of the Ca2+-activated Cl- Channel ANO1 (TMEM16A)

ANO1 (TMEM16A) is a Ca2+-activated Cl- channel that regulates diverse cellular functions including fluid secretion, neuronal excitability, and smooth muscle contraction. ANO1 is activated by elevation of cytosolic Ca2+ and modulated by phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2). Here we describe a closely concerted experimental and computational study, including electrophysiology, mutagenesis, functional assays, and extended sampling of lipid-protein interactions with molecular dynamics (MD) to characterize PI(4,5)P2 binding modes and sites on ANO1. ANO1 currents in excised inside-out patches activated by 270 nM Ca2+ at +100 mV are increased by exogenous PI(4,5)P2 with an EC50 = 1.24 {micro}M. The effect of PI(4,5)P2 is dependent on membrane voltage and Ca2+ and is explained by a stabilization of the ANO1 Ca2+-bound open state. Unbiased atomistic MD simulations with 1.4 mol% PI(4,5)P2 in a phosphatidylcholine bilayer identified 8 binding sites with significant probability of binding PI(4,5)P2. Three of these sites captured 85% of all ANO1 - PI(4,5)P2 interactions. Mutagenesis of basic amino acids near the membrane-cytosol interface found three regions of ANO1 critical for PI(4,5)P2 regulation that correspond to the same three sites identified by MD. PI(4,5)P2 is stabilized by hydrogen bonding between amino acid sidechains and phosphate/hydroxyl groups on PI(4,5)P2. Binding of PI(4,5)P2 alters the position of the cytoplasmic extension of TM6, which plays a crucial role in ANO1 channel gating, and increases the accessibility of the inner vestibule to Cl-ions. We propose a model consisting of a network of three PI(4,5)P2 binding sites at the cytoplasmic face of the membrane allosterically regulating ANO1 channel gating.\n\nSignificance statementMembrane proteins dwell in a sea of phospholipids that not only structurally stabilize the proteins by providing a hydrophobic environment for their transmembrane segments, but also dynamically regulate protein function. While many cation channels are known to be regulated by phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2), relatively little is known about anion channel regulation by phosphoinositides. Using a combination of patch clamp electrophysiology and atomistic molecular dynamics simulations, we have identified several PI(4,5)P2 binding sites in ANO1 (TMEM16A), a Cl- channel that performs myriad physiological functions from epithelial fluid secretion to regulation of electrical excitability. These binding sites form a band at the cytosolic interface of the membrane that we propose constitute a network to dynamically regulate this highly allosteric protein.

biophysics↗

bioRxiv2019

Differential gene expression analysis reveals novel genes and pathways in pediatric septic shock patients

Septic shock is a severe health condition caused by uncontrolled sepsis. Advancements in the high-throughput sequencing techniques have risen the number of potential genetic biomarkers under review. Multiple genetic markers and functional pathways play a part in the development and progression of pediatric septic shock. Fifty-four differentially expressed pediatric septic shock gene biomarkers were identified using gene expression data from 181 pediatric intensive care unit (PICU) patients within the first 24 hours of admission. The gene expression signatures discovered showed discriminatory power between pediatric septic shock survivors and nonsurvivors types. Using functional enrichment analysis of differentially expressed genes (DEGs), the known genes and pathways in septic shock were validated, and unexplored septic shock-related genes and functional groups were identified. Septic shock survivors were distinguished from septic shock non-survivors by differential expression of genes involved in the immune response, chemokine-mediated signaling, neutrophil chemotaxis, and chemokine activity. The identification of the septic shock gene biomarkers may facilitate in septic shock diagnosis, treatment, and prognosis.

bioinformatics↗

bioRxiv2019

Treatment of Murine Lupus with TIGIT-Ig

The TIGIT (T cell immunoreceptor with Ig and ITIM domains) protein is a co-inhibitory receptor that has been reported to suppress autoreactive T and B cells to trigger immunological tolerance. We generated a new recombinant protein by connecting the extracellular domain of murine TIGIT to the Fc region of the rat immunoglobulin IgG2a. The fusion protein was then characterized. The results suggested that among mice with lupus that were treated with the TIGIT-Ig fusion protein, the onset of proteinuria was delayed, serum concentrations of autoantibodies, such as antinuclear antibodies, were reduced without a decrease in the total IgG concentrations, and the survival rate was significantly increased compared to those of the controls. In conclusion, TIGIT-Ig administration showed promising results for both the prevention and treatment of autoimmune diseases in mice. This indicates that treatment with recombinant human TIGIT-Ig shows promise as an effective way to treat human autoimmune diseases.

immunology↗

bioRxiv2019

Fexofenadine inhibits TNF signaling through targeting to cytosolic phospholipase A2 and is therapeutic against autoimmune diseases

TNF- signaling plays a central role in the pathogenesis of various diseases, particularly autoimmune diseases. Screening of a library composed of FDA approved drugs led to the identification of Terfenadine and its active metabolite Fexofenadine as inhibitors of TNF- signaling. Both Fexofenadine and Terfenadine inhibited TNF/NF-{kappa}B signaling in vitro and in vivo, and ameliorated disease symptoms in various autoimmune disease models, including TNF- transgenic mice, collagen-induced arthritis, and inflammatory bowel disease. Subsequent studies identified cytosolic phospholipase A2 (cPLA2) as a novel target of Fexofenadine. Fexofenadine blocked TNF-stimulated cPLA2 activity and arachidonic acid production through binding to catalytic domain 2 of cPLA2 and inhibition of its phosphorylation on Ser-505. Further, deletion of cPLA2 abolished Fexofenadines anti-TNF activity. Collectively, these findings not only provide new insights into the understanding of Fexofenadine action and underlying mechanism, but also provide new therapeutic interventions for various TNF- and cPLA2-associated pathologies and conditions, particularly autoimmune diseases.

molecular biology↗

bioRxiv2019

Biochemical and structural characterization of a highly active branched-chain amino acid aminotransferase from Pseudomonas sp. for efficient biosynthesis of chiral amino acids

Aminotransferases (ATs) are important biocatalysts for the synthesis of chiral amines because of their capability of introducing amino group into ketones or keto acids as well as their high enantioselectivity, high regioselectivity and no requirement of external addition of cofactor. Among all ATs, branched-chain amino acid aminotransferase (BCAT) can reversibly catalyse branched-chain amino acids (BCAAs), including L-valine, L-leucine, and L-isoleucine, with -ketoglutaric acid to form the corresponding ketonic acids and L-glutamic acid. Alternatively, BCATs have been used for the biosynthesis of unnatural amino acids, such as L-tert-leucine. In the present study, the BCAT from Pseudomonas sp. (PsBCAT) was cloned and expressed in Escherichia coli for biochemical and structural analyses. The optimal reaction temperature and pH of PsBCAT were 40 {degrees}C and 8.5, respectively. PsBCAT exhibited a comparatively broader substrate spectrum, and showed remarkably high activity with L-leucine, L-valine, L-isoleucine and L-methionine with activities of 105 U/mg, 127 U/mg, 115 U/mg and 98 U/mg, respectively. Additionally, PsBCAT had activities with aromatic L-amino acids, L-histidine, L-lysine, and L-threonine. To analyse the catalytic mechanism of PsBCAT with the broad substrate spectrum, the crystal structure of PsBCAT was also determined. Finally, conjugated with the ornithine aminotransferase (OrnAT) from Bacillus subtilis, the coupled system was applied to the preparation of L-tert-leucine with 83% conversion, which provided an approximately 2.7-fold higher yield than the single BCAT reaction. IMPORTANCEDespite the enormous potential of BCATs, the vast majority of enzymes still lack suitably broad substrate scope and activity, thus new sources and novel enzymes are currently being investigated. Here, we described a previously uncharacterized PsBCAT, which showed a surprisingly wide substrate range and was more active towards BCAAs. This substrate promiscuity is unique for the BCAT family and could prove useful in industrial applications. Based on the determined crystal structure, we found some differences in the organization of the substrate binding cavity, which may influence the substrate specificity of the enzyme. Moreover, we demonstrated efficient biocatalytic asymmetric synthesis of L-tert-leucine using a coupling system, which can be used to remove the inhibitory by-product, and to shift the reaction equilibrium towards the product formation. In summary, the structural and functional characteristics of PsBCAT were analysed in detail, and this information will play an important role in the synthesis of chiral amino acids and will be conducive to industrial production of enantiopure chiral amines by aminotransferase.

biochemistry↗

bioRxiv2019

QTL and genetic analysis controlling fiber quality traits using paternal backcross population in Upland cotton

In present study, F14 recombinant inbred line (RIL) population was backcrossed to paternal parent for a paternal backcross (BC/P) population, deriving from one Upland cotton hybrid. Three repetitive BC/P field trials and one BC/M field trial were performed including both two BC populations and the original RIL population. Totally, for fiber quality traits, 24 novel QTLs were detected and 13 QTLs validated previous results. And 19 quantitative trait loci (QTL) in BC/P populations explained 5.01% - 22.09% of phenotype variation (PV). Among the 19 QTLs, three QTLs were detected simultaneously in BC/M population. The present study provided novel alleles of male parent for fiber quality traits with positive genetic effects. Particularly, qFS-Chr3-1 controlling fiber strength explained 22.09% of PV in BC/P population, which increased 0.48 cN/tex for fiber strength. A total of seven, two, eight, two and six QTLs explained over 10.00% of PV for fiber length, fiber uniformity, fiber strength, fiber elongation and fiber micronaire, respectively. In the RIL population, six common QTLs detected in more than one environment such as qFL-Chr1-2, qFS-Chr5-1, qFS-Chr9-1, qFS-Chr21-1, qFM-Chr9-1 and qFM-Chr9-2. Two common QTLs of qFE-Chr2-2 (TMB2386-SWU12343) and qFM-Chr9-1 (NAU2873-CGR6771) explained 22.42% and 21.91% of PV. In addition, a total of 142 and 46 epistatic QTLs and QTL x environments (E-QTLs and QQEs) were identified in RIL-P and BC/P populations, respectively.

plant biology↗