Biology subjects

Wan, X.

Publications and source records attributed to Wan, X..

At least 73 records · Page 4Linked to original sources

bioRxiv2021

VP-Detector: A 3D convolutional neural network for automated macromolecule localization and classification in cryo-electron tomograms

MotivationCryo-electron tomography (Cryo-ET) with sub-tomogram averaging (STA) is indispensable when studying macromolecule structures and functions in their native environments. However, current tomographic reconstructions suffer the low signal-to-noise (SNR) ratio and the missing wedge artifacts. Hence, automatic and accurate macromolecule localization and classification become the bottleneck problem for structural determination by STA. Here, we propose a 3D multi-scale dense convolutional neural network (MSDNet) for voxel-wise annotations of tomograms. Weighted focal loss is adopted as a loss function to solve the class imbalance. The proposed network combines 3D hybrid dilated convolutions (HDC) and dense connectivity to ensure an accurate performance with relatively few trainable parameters. 3D HDC expands the receptive field without losing resolution or learning extra parameters. Dense connectivity facilitates the re-use of feature maps to generate fewer intermediate feature maps and trainable parameters. Then, we design a 3D MSDNet based approach for fully automatic macromolecule localization and classification, called VP-Detector (Voxel-wise Particle Detector). VP-Detector is efficient because classification performs on the pre-calculated coordinates instead of a sliding window. ResultsWe evaluated the VP-Detector on simulated tomograms. Compared to the state-of-the-art methods, our method achieved a competitive performance on localization with the highest F1-score. We also demonstrated that the weighted focal loss improves the classification of hard classes. We trained the network on a part of training sets to prove the availability of training on relatively small datasets. Moreover, the experiment shows that VP-Detector has a fast particle detection speed, which costs less than 14 minutes on a test tomogram. Contactzsh@amss.ac.cn, xfcui@email.sdu.edu.cn, zhangfa@ict.ac.cn Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2021

Reprogrammed tracrRNAs enable repurposing RNAs as crRNAs and detecting RNAs

In type II CRISPR systems, the guide RNA (gRNA) consists of a CRISPR RNA (crRNA) and a hybridized trans-acting CRISPR RNA (tracrRNA) which interacts directly with Cas9 and is essential to its guided DNA targeting function. Though tracrRNAs are diverse in sequences and structures across type II CRISPR systems, the programmability of crRNA-tracrRNA hybridization for particular Cas9 has not been studied adequately. Here, we revealed the high programmability of crRNA-tracrRNA hybridization for Streptococcus pyogenes Cas9. By reprogramming the crRNA-tracrRNA hybridized sequence, reprogrammed tracrRNAs can repurpose various RNAs as crRNAs to trigger CRISPR function. We showed that the engineered crRNA-tracrRNA pairs enable design of orthogonal cellular computing devices and hijacking of endogenous RNAs as crRNAs. We next designed novel RNA sensors that can monitor the transcriptional activity of specific genes on the host genome and detect SARS-CoV-2 RNA in vitro. The engineering potential of crRNA-tracrRNA interaction has therefore redefined the capabilities of CRISPR/Cas9 system.

synthetic biology↗

bioRxiv2021

Distinct Origins of Two-order Hierarchical Cognitive Abilities in Human Adults

Human cognitive abilities are considerably diverse from basic perceptions to complex social behaviors. All human cognitive functions are principally categorized into a two-order hierarchy. Almost all of the first-order cognitive abilities investigated in behavioral genetics have been found to be dominantly heritable. However, the origins of the human second-order cognitive abilities in metacognition and mentalizing so far remain unclear. We here systematically compared the origins of the first-order and second-order cognitive abilities involved in the metacognition and mentalizing tasks using the classical twin paradigm on human adults. Our results demonstrated a double dissociation of the genetic and environmental contributions to the first-order and second-order cognitive abilities. All the first-order cognitive abilities involved in the metacognition and mentalizing tasks were dominantly heritable. In contrast, the shared environmental effects, rather than the genetic effects, had dominant contributions to the second-order cognitive abilities of metacognition and mentalizing in human adults. Hence, our findings suggest that human adults monitoring sensitivities in metacognition and mentalizing are profoundly sculpted by their social or cultural experiences, but less preconditioned by their biological nature.

neuroscience↗

bioRxiv2021

Noise-Transfer2Clean: Denoising cryo-EM images based on noise modeling and transfer

MotivationCryo-electron microscopy (cryo-EM) is a widely-used technology for ultrastructure determination, which constructs the three-dimensional (3D) structures of protein and macromolecular complex from a set of two-dimensional (2D) micrographs. However, limited by the electron beam dose, the micrographs in cryo-EM generally suffer from extremely low signal-to-noise ratio (SNR), which hampers the efficiency and effectiveness of downstream analysis. Especially, the noise in cryo-EM is not simple additive or multiplicative noise whose statistical characteristics are quite different from the ones in natural image, extremely shackling the performance of conventional denoising methods. ResultsHere, we introduce the Noise-Transfer2Clean (NT2C), a denoising deep neural network (DNN) for cryo-EM to enhance image contrast and restore specimen signal, whose main idea is to improve the denoising performance by correctly discovering the noise model of cryo-EM images and transferring the statistical nature of noise into the denoiser. Especially, to cope with the complex noise model in cryo-EM, we design a contrast-guided noise and signal re-weighted algorithm to achieve clean-noisy data synthesis and data augmentation, making our method authentically achieve signal restoration based on noises true properties. To our knowledge, NT2C is the first denoising method that resolves the complex noise model in cryo-EM images. Comprehensive experimental results on simulated datasets and real datasets show that NT2C achieved a notable improvement in image denoising and specimen signal restoration, comparing with the state-of-art methods. A real-world case study shows that NT2C can improve the recognition rate on hard-to-identify particles by 19% in the particle picking task.

bioinformatics↗

bioRxiv2021

Single cell transcriptome analysis of decidua macrophages in normal and recurrent spontaneous abortion patients

Due to the heterogeneity and different polarization state of decidual macrophages (dM{Phi}), they play an important role during the pregnancy, but their definition and exact function remain elusive. We isolated CD14+CD45+ dM{Phi} from the normal or RSA decidua by flow cytometry, followed by single cell RNA sequencing (scRNA-seq). In total, 23,062 single-cell transcriptomes of macrophage were profiled (12,470 Normal and 10,592 RSA), which were divided into 13 major clusters via T-distributed stochastic neighbor embedding (t-SNE) visualization. We observed that there is higher percentage composition of M1 cells (70.6%) in the normal decidua, and higher percentage composition of M2 cells (68.3%) in the RSA decidua. We identified new markers (M1: S100A8, S100A9, M2: SELENOP, FOLR2, RNASE1) and secreted cytokines (M1: IL1{beta}, TNFSF13B and MMP9; M2: CCL3, CCL4) of the dM{Phi}. We found that cluster 10 as the specific cluster of dM{Phi} highly expressing BAG3 in normal group and cluster 7 specific highly expressing CXCL9/10/11 chemokine. After pseudo-time trajectory analysis, we found that the dM{Phi} formed a continuous "V-shaped" trajectory, with M1 and M2 type cells mainly occupying the two heads. We found that NF{kappa}B1, MYC and TCF12 acted as the key transcription factors of dM{Phi}. Our study redefined the polarization state and physiological characteristic of dM{Phi} in early normal and RSA pregnancy, which suggests a novel view and therapeutic target for spontaneous abortion prevention.

cell biology↗

bioRxiv2021

MR-APSS: a unified approach to Mendelian Randomization accounting for pleiotropy and sample structure using genome-wide summary statistics

Mendelian Randomization (MR) is a valuable tool for inferring causal relationships among a wide range of traits using summary statistics from genome-wide association studies (GWASs). Existing summary-level MR methods often rely on strong assumptions, resulting in many false positive findings. To relax MR assumptions, ongoing research has been primarily focused on accounting for confounding due to pleiotropy. Here we show that sample structure is another major confounding factor, including population stratification, cryptic relatedness, and sample overlap. We propose a unified MR approach, MR-APSS, which (i) accounts for pleiotropy and sample structure simultaneously by leveraging genome-wide information; and (ii) allows to include more genetic variants with moderate effects as instrument variables (IVs) to improve statistical power without inflating type I errors. We first evaluated MR-APSS using comprehensive simulations and negative controls, and then applied MR-APSS to study the causal relationships among a collection of diverse complex traits. The results suggest that MR-APSS can better identify plausible causal relationships with high reliability. In particular, MR-APSS can perform well for highly polygenic traits, where the IV strengths tend to be relatively weak and existing summary-level MR methods for causal inference are vulnerable to confounding effects.

genetics↗

bioRxiv2021

Large portion of essential genes is missed by screening either fly or beetle indicating unexpected diversity of insect gene function

Most gene functions were detected by screens in very few model organisms but it has remained unclear how comprehensive these data are. Here, we expanded our RNAi screen in the red flour beetle Tribolium castaneum to cover more than half of the protein-coding genes and we compared the gene sets involved in several processes between beetle and fly. We find that around 50 % of the gene functions are detected in both species while the rest was found only in fly (~10%) or beetle (~40%) reflecting both technical and biological differences. We conclude that work in complementary model systems is required to gain a comprehensive picture on gene functions documented by the annotation of novel GO terms for 96 genes studied here. The RNAi screening resources developed in this project, the expanding transgenic tool-kit and our large-scale functional data make T. castaneum an excellent model system in that endeavor.

genetics↗

bioRxiv2021

IRGM/Irgm1 Aggravates Progression of Atherosclerosis by Inducing Macrophage Apoptosis

AimsAtherosclerosis underlies most cardiovascular diseases, among which acute coronary syndrome (ACS) caused by plaque rupture (PR) often leads to death. Immune-related GTPases (IRGM/Irgm1) have been extensively studied in inflammatory diseases, but their role in atherosclerosis is unclear. Determining how IRGM/Irgm1 promotes atherosclerotic plaque vulnerability will provide information for new biomarkers and/or therapeutic targets. Methods and resultsWe identified ruptured and unruptured plaques by optical coherence tomography, and found that serum IRGM was highly expressed in patients with ST-segment elevation myocardial infarction in PR. We used ApoE-/-Irgm1+/+, ApoE-/-Irgm1+/- mice and chimeric mice to establish a model of advanced atherosclerosis. The results of pathological experiments showed that Irgm1 caused plaque necrosis. The ratio of neutral lipids and cholesterol crystals increases, while the content of collagen fibers decreases, aggravating the destabilization of atherosclerotic plaques. In vitro, we used multiple approaches to confirm that Irgm1 promotes macrophage apoptosis by promoting the production of reactive oxygen species and activating the MAPK signaling pathway. ConclusionsIRGM may be a potential risk factor for PR. Mechanistic studies have shown that IRGM/Irgm1 contributes to the formation and rupture of fragile plaques. This is partly mediated by the induction of macrophage apoptosis via the MAPK signaling pathway. IRGM may offer new strategies for early treatment of ACS. Translation viewOur findings indicate that IRGM/Irgm1 contributes to formation and rupture of vulnerable plaques. It suggests that IRGM may provide a new target for the early treatment of ACS.

pathology↗

bioRxiv2020

Regulation of lipid accumulation-induced ROS in myeloid-derived suppressor cells via targeting fatty-acid transport protein 2 enhanced anti-PD-L1 tumor immunotherapy

Despite the remarkable success and efficacy of immune checkpoint blockade (ICB) therapy against the PD-1/PD-L1 axis, it induces sustained responses in a sizeable minority of cancer patients due to the activation of immunosuppressive factors such as myeloid-derived suppressor cells (MDSCs). Inhibiting the immunosuppressive function of MDSCs is critical for successful cancer ICB therapy. Interestingly, lipid metabolism is a crucial factor in modulating MDSCs function. Fatty acid transport protein 2 (FATP2) conferred the function of PMN-MDSCs in cancer via the upregulation of arachidonic acid metabolism. However, whether regulating lipid accumulation in MDSCs by targeting FATP2 could block MDSCs reactive oxygen species (ROS) production and enhance PD-L1 blockade-mediated tumor immunotherapy remains unexplored. Here we report that FATP2 regulated lipid accumulation, ROS, and immunosuppressive function of MDSCs in tumor-bearing mice. Tumor cells-derived granulocyte macrophage-colony stimulating factor (GM-CSF) induced FATP2 expression in MDSCs by activation of STAT3 signaling pathway. Pharmaceutical blockade of FATP2 expression in MDSCs by lipofermata decreased lipid accumulation, reduced ROS, blocked immunosuppressive activity, and consequently inhibited tumor growth. More importantly, lipofermata inhibition of FATP2 in MDSCs enhanced anti-PD-L1 tumor immunotherapy via the upregulation of CD107a and reduced PD-L1 expression on tumor-infiltrating CD8+ T-cells. Furthermore, the combination therapy blocked MDSCs suppressive role on T-cells thereby enhanced T-cells ability for the production of IFN-{gamma}. These findings indicate that FATP2 plays a key role in modulating lipid-induced ROS in MDSCs and targeting FATP2 in MDSCs provides a novel therapeutic approach to enhance anti-PD-L1 cancer immunotherapy. Research highlightsO_LIFATP2 inhibition in MDSCs blocked ROS-mediated immunosuppressive function and promoted MDSCs differentiation to immune-stimulatory phenotype. C_LIO_LIGM-CSF mediated FATP2 expression via activation of STAT3 signaling leading to lipid accumulation-induced ROS in MDSCs. C_LIO_LIFATP2 inhibition enhanced anti-PD-L1 tumor immunotherapy by reducing MDSCs immunosuppressive activity in blocking T-cells ability to produce IFN-{gamma}. C_LIO_LICombination of anti-PD-L1 antibody and FATP2 inhibitor decreased MDSCs accumulation and PD-L1 surface expression in the spleens of LLC-bearing mice. C_LIO_LICombined treatment of FATP2 inhibitor and PD-L1 blockade-mediated tumor immunotherapy enhanced tumor-infiltrating CD8+ T cells activation via increased CD107a and reduced PD-L1 surface expression. C_LI

immunology↗

bioRxiv2020

SARS-CoV-2 Quasispecies provides insight into its genetic dynamics during infection

A novel coronavirus disease (COVID-19) caused by SARS-CoV-2 has been pandemic worldwide. The genetic dynamics of quasispecies afford RNA viruses a great fitness on cell tropism and host range. However, no quasispecies data of SARS-CoV-2 have been reported yet. To explore quasispecies haplotypes and its transmission characteristics, we carried out single-molecule real-time (SMRT) sequencing of the full-length of SARS-CoV-2 spike gene within 14 RNA samples from 2 infection clusters, covering first-to third-generation infected-patients. We observed a special quasispecies structure of SARS-CoV-2 (modeled as One-King): one dominant haplotype (mean abundance ~70.15%) followed by numerous minor haplotypes (mean abundance < 0.10%). We not only discovered a novel dominant haplotype of F1040 but also realized that minor quasispecies were also worthy of attention. Notably, some minor haplotypes (like F1040 and currently pandemic one G614) could potentially reveal adaptive and converse into the dominant one. However, minor haplotypes exhibited a high transmission bottleneck (~6% could be stably transmitted), and the new adaptive/dominant haplotypes were likely originated from genetic variations within a host rather than transmission. The evolutionary rate was estimated as 2.68-3.86 x 10-3 per site per year, which was larger than the estimation at consensus genome level. The One-King model and conversion event expanded our understanding of the genetic dynamics of SARS-CoV-2, and explained the incomprehensible phenomenon at the consensus genome level, such as limited cumulative mutations and low evolutionary rate. Moreover, our findings suggested the epidemic strains may be multi-host origin and future traceability would face huge difficulties.

pathology↗

bioRxiv2020

SARS-CoV-2 suppresses mRNA expression of selenoproteins associated with ferroptosis, ER stress and DNA synthesis

A significant, positive association between selenium status and prognosis of SARS-CoV-2 infection has been identified among COVID-19 patients in China. Moreover, a German study revealed a pronounced deficit of serum selenium and SELENOP concentrations in COVID-19 patients, and selenium deficiency was associated with mortality risk from COVID-19. The present study investigated the influence of SARS-CoV-2 on gene expression of host selenoproteins which mediate many beneficial actions of selenium. We found that SARS-CoV-2 suppressed mRNA expression of selenoproteins associated with ferroptosis (GPX4), endoplasmic reticulum stress (SELENOF, SELENOK, SELENOM and SELENOS) and DNA synthesis (TXNRD3), while SARS-CoV-2 increased gene expression of IL-6 (an inflammatory cytokine positively correlated with severity of COVID-19), in Vero cells. These results provide a deeper insight into the connection between selenium and SARS-CoV-2 pathogenesis.

microbiology↗

bioRxiv2020

Valproic Acid-Induced Changes of 4D Nuclear Morphology in Astrocyte Cells

Histone deacetylase inhibitors, such as valproic acid (VPA), have important clinical therapeutic and cellular reprogramming applications. They induce chromatin re-organization that is associated with altered cellular morphology. However, there is a lack of comprehensive characterization of VPA-induced changes of nuclear size and shape. Here, we quantify 3D nuclear morphology of primary human astrocyte cells treated with VPA over time (hence, 4D). We compared volumetric and surface-based representations and identified seven features that jointly discriminate between normal and treated cells with 85% accuracy on day 7. From day 3, treated nuclei were more elongated and flattened and then continued to morphologically diverge from controls over time, becoming larger and more irregular. On day 7, most of the size and shape descriptors demonstrated significant differences between treated and untreated cells, including a 24% increase in volume and 6% reduction in extent (shape regularity) for treated nuclei. Overall, we show that 4D morphometry can capture how chromatin re-organization modulates the size and shape of the nucleus over time. These nuclear structural alterations may serve as a biomarker for histone (de-)acetylation events and provide insights into mechanisms of astrocytes-to-neurons reprogramming.

bioinformatics↗

bioRxiv2020

FIRM: Fast Integration of single-cell RNA-sequencing data across Multiple platforms

Single-cell RNA-sequencing (scRNA-seq) is being used extensively to measure the mRNA expression of individual cells from deconstructed tissues, organs, and even entire organisms to generate cell atlas references, leading to discoveries of novel cell types and deeper insight into biological trajectories. These massive datasets are usually collected from many samples using different scRNA-seq technology platforms, including the popular SMART-Seq2 (SS2) and 10X platforms. Inherent heterogeneities between platforms, tissues, and other batch effects makes scRNA-seq data difficult to compare and integrate, especially in large-scale cell atlas efforts; yet, accurate integration is essential for gaining deeper insights into cell biology. Through comprehensive data exploration, we found that accurate integration is often hampered by differences in cell-type compositions. Herein we describe FIRM, an algorithm that addresses this problem and achieves efficient and accurate integration of heterogeneous scRNA-seq datasets across multiple tissue types, platforms, and experimental batches. We applied FIRM to numerous large-scale scRNA-seq datasets from mouse, mouse lemur, and human, comparing its performance in dataset integration with other state-of-the-art methods. FIRM-integrated datasets show accurate mixing of shared cell type identities and superior preservation of original structure without overcorrection, generating robust integrated datasets for downstream exploration and analysis. It is also a facile way to transfer cell type labels and annotations from one dataset to another, making it a reliable and versatile tool for scRNA-seq analysis, especially for cell atlas data integration.

bioinformatics↗

bioRxiv2020

Lipid Droplet Is an Ancient and Inheritable Organelle in Bacteria

Lipid droplet (LD) is a monolayer phospholipid membrane-bound organelle found in all eukaryotes and several prokaryotes which plays key roles in cellular lipid homeostasis and human health. The origin and evolution of the organelle remains unknown. Here, we report that through screening over 660 bacteria using biophysical and biochemical methods, plus LD isolation and proteomic tool, LDs were identified in most of these microbes, affiliated with five main bacterial phyla. Moreover, LDs were also identified in E. coli overexpressing lipid synthesis enzymes, indicating that bacteria without detectable LDs possessed the ability of LD biogenesis. The similarity of isolated LDs from representative strains and evolutionary analysis of LD major protein PspA demonstrate that LDs were conserved in bacteria. Furthermore, time-lapse imaging revealed that LDs were inheritable accompanying with bacterial growth and division. Finally, a common ancestor of LD-containing bacteria was predicted to originate 3.19 billion years ago by a phylogenetic analysis. Our findings suggest that LD is a widespread and inheritable organelle from an ancient common ancestor.

cell biology↗

bioRxiv2020

Computational target fishing by mining transcriptional data using a novel Siamese spectral-based graph convolutional network

Computational target fishing aims to investigate the mechanism of action or the side effects of bioactive small molecules. Unfortunately, conventional ligand-based computational methods only explore a confined chemical space, and structure-based methods are limited by the availability of crystal structures. Moreover, these methods cannot describe cellular context-dependent effects and are thus not useful for exploring the targets of drugs in specific cells. To address these challenges, we propose a novel Siamese spectral-based graph convolutional network (SSGCN) model for inferring the protein targets of chemical compounds from gene transcriptional profiles. Although the gene signature of a compound perturbation only provides indirect clues of the interacting targets, the SSGCN model was successfully trained to learn from known compound-target pairs by uncovering the hidden correlations between compound perturbation profiles and gene knockdown profiles. Using a benchmark set, the model achieved impressive target inference results compared with previous methods such as Connectivity Map and ProTINA. More importantly, the powerful generalization ability of the model observed with the external LINCS phase II dataset suggests that the model is an efficient target fishing or repositioning tool for bioactive compounds.

bioinformatics↗

bioRxiv2019

An abscisic acid (ABA) homeostasis regulated by its production, catabolism and transport in peanut leaves in response to drought stress

ABA is an important messenger that acts as the signaling mediator for regulating the adaptive response of plants to drought stress. Two production pathways, de novo biosynthesis and hydrolysis of glucose-conjugated ABA by {beta}-glucosidase (BG), increase cellular ABA levels in plants. ABA catabolism via hydroxylation by 8-hydroxylase (CYP707A), or conjugation by uridine diphosphate glucosyltransferase (UGT), decreases cellular ABA levels. The transport of ABA through ATP-binding cassette (ABC)-containing transporter proteins, members of ABC transporter G family (ABCG), across plasma membrane (PM) is another important pathway to regulate cellular ABA levels. In this study, based on our previously constructed transcriptome of peanut leaves in response to drought stress, fourteen candidate genes involved in ABA production (including AhZEP, AhNCED1 and AhNCED3, AhABA2, AhAAO1 and AhAAO2, AhABA3, AhBG11 and AhBG24), catabolism (including AhCYP707A3, AhUGT71K1 and AhUGT73B4) and transport (including AhABCG22-1 and AhABCG22-2), were identified homologously and phylogenetically, and further analyzed at the transcriptional level by real-time RT-PCR, simultaneously determining ABA levels in peanut leaves in response to drought. The high sequence identity and very similar subcellular localization of the proteins deduced from 14 identified genes involved in ABA production, catabolism and transport with the reported corresponding enzymes in databases suggest their similar roles in regulating cellular ABA levels. In response to drought stress, ABA accumulation levels in peanut leaves agree very well with the up-regulated expressions of ABA-producing genes (AhZEP, AhNCED1, AhAAO2, AhABA3, AhBG11 and AhBG24) and PM-localized ABA importer genes (AhABCG22-1 and AhABCG22-2), although the expression of ABA catabolic genes (AhCYP707A3 and AhUGT71K1) was also up-regulated. It is likely that drought-responsive induction of catabolic genes helps not only to maintain ABA levels within a permissible range, but also to prepare the plant for degradation of ABA after removal of the stress. These results suggest that ABA homeostasis in peanut leaves in response to drought may be coordinated by a master regulatory circuit that involves production, catabolism, and as well as transport.

plant biology↗

bioRxiv2019

Compartmentalized Biosynthesis of Mycophenolic Acid

Mycophenolic acid (MPA) from filamentous fungi is the first natural product antibiotic in human history and a first-line immunosuppressive drug for organ transplantations and autoimmune diseases. However, its biosynthetic mechanisms have remained a long-standing mystery. Here, we elucidate the MPA biosynthetic pathway that features both compartmentalized enzymatic steps and unique cooperation between biosynthetic and {beta}-oxidation catabolism machineries based on targeted gene inactivation, feeding experiments in heterologous expression hosts, enzyme functional characterization and kinetic analysis, and microscopic observation of protein subcellular localization. Besides identification of the oxygenase MpaB as the long-sought key enzyme responsible for the oxidative cleavage of sesquiterpene side chain, we reveal the intriguing pattern of compartmentalization for the MPA biosynthetic enzymes, including the cytosolic polyketide synthase MpaC and O-methyltransferase MpaG, the Golgi apparatus-associated prenyltransferase MpaA, the endoplasmic reticulum-bound oxygenase MpaB and P450-hydrolase fusion enzyme MpaDE, and the peroxisomal acyl-CoA hydrolase MpaH. The whole pathway is elegantly co-mediated by these compartmentalized enzymes, together with the peroxisomal {beta}-oxidation machinery. Beyond characterizing the remaining outstanding steps of the MPA biosynthetic pathway, our study highlights the importance of considering subcellular contexts and the broader cellular metabolism in natural product biosynthesis.\n\nSignificance StatementHere we elucidate the full biosynthetic pathway of the fungal natural product mycophenolic acid (MPA), which represents an unsolved mystery for decades. Besides the intriguing enzymatic mechanisms, we reveal that the MPA biosynthetic enzymes are elegantly compartmentalized; and the subcellular localization of the acyl-CoA hydrolase MpaH in peroxisomes is required for the unique cooperation between biosynthetic and {beta}-oxidation catabolism machineries. This work highlights the importance of a cell biology perspective for understanding the unexplored organelle-associated essential catalytic mechanisms in natural product biosynthesis of fungi and other higher organisms. The insights provided by our work will also benefit future efforts for both industrial strain improvement and novel drug development.

biochemistry↗

bioRxiv2018

Physiological and transcriptomic analysis of yellow leaf

As important deciduous tree, Populus deltoides Marsh possesses a high ornamental value for its leaves remaining yellow during the non-dormant period. However, little is known about the regulatory mechanism of leaf coloration in Populus deltoides Marsh. Thus, we analyzed physiological and transcriptional differences of yellow leaves (mutant) and green leaves (wild-type) of Populus deltoides Marsh. Physiological experiments showed that the contents of chlorophyll (Chl) and carotenoid are lower in mutant, the flavonoid content is not differed significantly between mutant and wild-type. Transcriptomic sequencing was further used to identify 153 differentially expressed genes (DEGs). Functional classifications based on Gene Ontology enrichment and Genomes enrichment analysis indicated that the DEGs were involved in Chl biosynthesis and flavonoid biosynthesis pathway. Among these, geranylgeranyl diphosphate (CHLP) genes associated with Chl biosynthesis showed down-regulation, while chlorophyllase (CLH) genes associated with Chl degradation were up-regulated in yellow leaves. The expression levels of these genes were further confirmed using quantitative real-time PCR (RT-qPCR). Furthermore, the measurement of the main precursors of Chl confirmed that CHLP is vital enzymes for the yellow leaf color phenotype. Consequently, the formation of yellow leaf color is due to disruption of Chl synthesis and catabolism rather than flavonoid content. These results contribute to our understanding of mechanisms and regulation of leaf color variation in poplar at the transcriptional level.

bioinformatics↗