Biology subjects

Huang, Y.

Publications and source records attributed to Huang, Y..

At least 973 records · Page 54Linked to original sources

bioRxiv2018

Global Quantitative Mapping of Enhancers in Rice Genome by STARR-seq

Identification of enhancers has been a challenge in plants. STARR-seq measures enhancer activity of millions fragments in parallel. Here we present a global map of rice enhancers quantitatively determined using STARR-seq. Most enhancers are mapped within genes, especially at the 5 untranslated regions (5 UTR) and the coding sequences. Silent and low expressed genes in genomic regions enriched with transposable elements (TEs) are frequently found containing proximal enhancers. Analysis of enhancer epigenetic features at their endogenous loci revealed that most enhancers do not co-localize with DNase I hypersensitive sites (DHSs) and are lack of H3K4me1. Clustering enhancers by their epigenetic modifications revealed that about 40% of identified enhancers carry one or more epigenetic marks. Repressive H3K27me3 is frequently enriched with positive marks of H3K4m3 and/or H3K27ac, which together may bookmark poised enhancers. Intergenic enhancers were predicted based on the location of DHS relative to genes, which overlap poorly with functionally identified enhancers. In summary, enhancers were quantitatively identified by functional analysis in a model plant genome, which provides a valuable resource for further mechanistic studies in different biological contexts.

genomics↗

bioRxiv2018

Accurate loop calling for 3D genomic data with cLoops

Sequencing-based 3D genome mapping technologies can identify loops formed by interactions between regulatory elements hundreds of kilobases apart. Existing loop-calling tools are mostly restricted to a single data type, with accuracy dependent on a pre-defined resolution contact matrix or called peaks, and can have prohibitive hardware costs. Here we introduce cLoops ( see loops) to address these limitations. cLoops is based on the clustering algorithm cDBSCAN that directly analyzes the paired-end tags (PETs) to find candidate loops and uses a permuted local background to estimate statistical significance. These two data-type-independent processes enable loops to be reliably identified for both sharp and broad peak data, including but not limited to ChIA-PET, Hi-C, HiChIP and Trac-looping data. Loops identified by cLoops showed much less distance-dependent bias and higher enrichment relative to local regions than existing tools. Altogether, cLoops improves accuracy of detecting of 3D-genomic loops from sequencing data, is versatile, flexible, efficient, and has modest hardware requirements, and is freely available at: https://github.com/YaqiangCao/cLoops.

bioinformatics↗

bioRxiv2018

Global analysis of N6-methyladenosine functions and its disease association using deep learning and network-based methods

N6-methyladenosine (m6A) is the most abundant methylation, existing in >25% of human mRNAs. Exciting recent discoveries indicate the close involvement of m6A in regulating many different aspects of mRNA metabolism and diseases like cancer. However, our current knowledge about how m6A levels are controlled and whether and how regulation of m6A levels of a specific gene can play a role in cancer and other diseases is mostly elusive. We propose in this paper a computational scheme for predicting m6A-regulated genes and m6A-associated disease, which includes Deep-m6A, the first model for detecting condition-specific m6A sites from MeRIP-Seq data with a single base resolution using deep learning and a new network-based pipeline that prioritizes functional significant m6A genes and its associated diseases using the Protein-Protein Interaction (PPI) and gene-disease heterogeneous networks. We applied Deep-m6A and this pipeline to 75 MeRIP-seq human samples, which produced a compact set of 709 functionally significant m6A-regulated genes and nine functionally enriched subnetworks. The functional enrichment analysis of these genes and networks reveal that m6A targets key genes of many critical biological processes including transcription, cell organization and transport, and cell proliferation and cancer-related pathways such as Wnt pathway. The m6A-associated disease analysis prioritized five significantly associated diseases including leukemia and renal cell carcinoma. These results demonstrate the power of our proposed computational scheme and provide new leads for understanding m6A regulatory functions and its roles in diseases.\n\nAuthor summaryThe goal of this work is to identify functional significant m6A-regulated genes and m6A-associated diseases from analyzing an extensive collection of MeRIP-seq data. To achieve this, we first developed Deep-m6A, a CNN model for single-base m6A prediction. To our knowledge, this is the first condition-specific single-base m6A site prediction model that combines mRNA sequence feature and MeRIP-Seq data. The 10-fold cross-validation and test on an independent dataset showthat Deep-m6A outperformed two sequence-based models. We applied Deep-m6A followed by network-based analysis using HotNet2 and RWRH to 75 human MeRIP-Seq samples from various cells and tissue under different conditions to globally detect m6A-regulated genes and further predict m6A mediated functions and associated diseases. This is also to our knowledge the first attempt to predict m6A functions and associated diseases using only computational methods in a global manner on a large number of human MeRIP-Seq samples. The predicted functions and diseases show considerable consistent with those reported in the literature, which demonstrated the power of our proposed pipeline to predict potential m6A mediated functions and associated diseases.

bioinformatics↗

bioRxiv2018

Decoding voluntary movements and postural tremor based on thalamic LFPs for closed-loop stimulation for essential tremor

High frequency deep brain stimulation (DBS) targeting motor thalamus is an effective therapy for essential tremor (ET). However, conventional continuous stimulation may deliver unnecessary current to the brain since tremor mainly affects voluntary movements and sustained postures in ET. We recorded LFPs from the motor thalamus, surface electromyographic (EMG) signals and/or behavioural measurements in seven ET patients during temporary lead externalization after the first surgery for DBS when they performed different voluntary upper limb movements and in nine more patients during the surgery, when they were asked to lift their arms to trigger postural tremor. We show that both voluntary movements and postural tremor can be decoded based on features extracted from thalamic LFPs using a machine learning based binary classifier. This information can be used to close the loop for DBS so that stimulation could be delivered on demand, without the need for peripheral sensors or additional invasive electrodes.

neuroscience↗

bioRxiv2018

Changes in pregnancy-related serum biomarkers early in gestation are associated with later development of preeclampsia

BackgroundPlacental protein expression plays a crucial biological role during normal and complicated pregnancies. We hypothesized that: (1) circulating pregnancy-associated, placenta-related protein levels throughout gestation reflect the uncomplicated, full-term temporal progression of human gestation, and effectively estimates gestational ages (GAs); (2) pregnancies with underlying placental pathology, such as preeclampsia (PE), are associated with disruptions in this GA estimation in early gestation; (3) malfunctions of this GA estimation can be employed to identify impending PE. In addition, to explore the underlying biology and PE etiology, we set to compare protein gestational patterns of human and mouse, using pregnant heme oxygenase-1 (HO-1) heterozygote (Het) mice, a mouse model reflecting PE-like symptoms.\n\nMethodsSerum levels of circulating placenta-related proteins - leptin (LEP), chorionic somatomammotropin hormone like 1 (CSHL1), elabela (ELA), activin A, soluble fms-like tyrosine kinase 1 (sFlt-1), and placental growth factor (PlGF)- were quantified by ELISA in blood serially collected throughout human pregnancies (20 normal subjects with 66 samples, and 20 PE subjects with 61 samples). Linear multivariate analysis of the targeted serological protein levels was performed to estimate the normal GA. Logarithmic transformed mean-squared errors of GA estimations were used to identify impending PE. Then the human gestational protein patterns were compared to those in the pregnant HO-1 mice.\n\nResultsAn elastic net (EN)-based gestational dating model was developed (R2 = 0.76) and validated (R2 = 0.61) using the serum levels of the 6 proteins at various GAs from women with normal uncomplicated pregnancies (n = 10 for training and n = 6 for validation). In pregnancies complicated by PE (n = 14), the EN model was not (R2 = -0.17) associated with GA at sampling in PE. Statistically significant deviations from the normal GA EN model estimations were observed in PE-associated pregnancies between GAs of 16-30 weeks (P = 0.01). The EN model developed with 5 proteins (ELA excluded due to the lack of robustness of the mouse ELA essay) performed similarly on normal human (R2 = 0.68) and WT mouse (R2 = 0.85) pregnancies. Disruptions of this model were observed in both human PE-associated (human: R2 = 0.27) and mouse HO-1 Het (mouse: R2 = 0.30) pregnancies. LEP out performed sFlt-1 and PlGF in differentiating impending PE at early human and late mouse gestations.\n\nConclusionsAs revealed in both human and mouse GA EN analyses, temporal serological placenta-related protein patterns are tightly regulated throughout normal human pregnancies and can be significantly disrupted in pathologic PE states. LEP changes earlier during gestation than the well-established late GA PE biomarkers (sFlt-1 and PlGF). Our HO-1 Het mouse analysis provides direct evidence of the causative action of HO-1 deficiency in LEP upregulation in a PE-like murine model. Therefore, longitudinal analyses of pregnancy-related protein patterns in sera, may not only help in the exploration of underlying PE pathophysiology but also provide better clinical utility in PE assessment.

molecular biology↗

bioRxiv2018

Adopting Literature-based Discovery on Rehabilitation Therapy Repositioning for Stroke

Stroke is a common disabling disease severely affecting the daily life of the patients. There is evidence that rehabilitation therapy can improve the movement function. However, there are no clear guidelines that identify specific, effective rehabilitation therapy schemes, and the development of new rehabilitation techniques has been fairly slow. One informatics translational approach, called ABC model in Literature-based Discovery, was used to mine an existing rehabilitation candidate which is most likely to be repositioned for stroke. As in the classic ABC model originated from Don Swanson, we built the internal links of stroke (A), assessment scales (B), rehabilitation therapies (C) in PubMed relating to upper limb function measurements for stroke patients. In the first step, with E-utility we retrieved both stroke related assessment scales and rehabilitation therapies records, and complied two datasets called Stroke_Scales and Stroke_Therapies, respectively. In the next step, we crawled all rehabilitation therapies co-occurred with the Stroke_Theapies, named as All_Therapies. Therapies that were already included in Stroke_Therapies were deleted from All_Therapies, so that the remaining therapies were the potential rehabilitation therapies, which could be repositioned for stroke after subsequent filtration by manual check. We identified the top ranked repositioning rehabilitation therapy following by subsequent clinical validation. Hand-arm bimanual intensive training (HABIT) ranked the first in our repositioning rehabilitation therapies list, with the most interaction links with Stroke_Scales. HABIT showed a significant improvement in clinical scores on assessment scales of Fugl-Meyer Assessment and Action Research Arm Test in the clinical validation on upper limb function for acute stroke patients. Based on the ABC model and clinical validation of the results, we put forward that HABIT as a promising rehabilitation therapy for stroke, which shows that the ABC model is an effective text mining approach for rehabilitation therapy repositioning. The results seem to be promoted in clinical knowledge discovery.\n\nAuthor SummaryIn the present study, we proposed a text mining approach to mining terms related to disease, rehabilitation therapy, and assessment scale from literature, with a subsequent ABC inference analysis to identify relationships of these terms across publications. The clinical validation demonstrated that our approach can be used to identify potential repositioning rehabilitation therapy strategies for stroke. Specifically, we identified a promising rehabilitation method called HABIT previously used in pediatric congenital hemiplegia. A subsequent clinical trial confirmed this as a highly promising rehabilitation therapy for stroke.

bioinformatics↗

bioRxiv2018

Cardelino: Integrating whole exomes and single-cell transcriptomes to reveal phenotypic impact of somatic variants

Decoding the clonal substructures of somatic tissues sheds light on cell growth, development and differentiation in health, ageing and disease. DNA-sequencing, either using bulk or using single-cell assays, has enabled the reconstruction of clonal trees from frequency and co-occurrence patterns of somatic variants. However, approaches to systematically characterize phenotypic and functional variations between individual clones are not established. Here we present cardelino (https://github.com/PMBio/cardelino), a computational method for inferring the clone of origin of individual cells that have been assayed using single-cell RNA-seq (scRNA-seq). After validating our model using simulations, we apply cardelino to matched scRNA-seq and exome sequencing data from 32 human dermal fibroblast lines, identifying hundreds of differentially expressed genes between cells from different somatic clones. These genes are frequently enriched for cell cycle and proliferation pathways, indicating a key role for cell division genes in non-neutral somatic evolution.\n\nKey findingsO_LIA novel approach for integrating DNA-seq and single-cell RNA-seq data to reconstruct clonal substructure for single-cell transcriptomes.\nC_LIO_LIEvidence for non-neutral evolution of clonal populations in human fibroblasts.\nC_LIO_LIProliferation and cell cycle pathways are commonly distorted in mutated clonal populations.\nC_LI

genomics↗

bioRxiv2018

The Histone Demethylase KDM4D Promotes Hepatic Fibrogenesis by Modulating Toll-Like Receptor 4 Signaling Pathway

Accumulating evidence has revealed the pivotal role of epigenetic regulation in the pathogenesis of liver disease. However, the epigenetic mechanism that accounts for hepatic stellate cells (HSCs) activation in liver fibrosis remains largely unknown. In this study, primary HSCs were used to screen the differentially expressed histone H3 lysine methyltransferases and demethylases during HSC activation. KDM4D was identified as a remarkable up-regulated histone H3 demethylase during HSC activation. The overexpression profile of KDM4D was further confirmed in three fibrosis animal models and human fibrotic liver tissues. In vitro genetic silencing of Kdm4d impaired the collagen gel contraction and migration capacity of primary HSCs. In established CCl4-induced mice model, Kdm4d knockdown inhibited fibrosis progression, and promoted fibrosis reversal, with enhanced thinning and splitting of fibrotic septa, as well as a dramatic decrease in collagen area. Whole gene transcriptome analysis showed the regulatory role of KDM4D in Toll-Like Receptor (TLR) signaling pathway. Mechanistically, KDM4D catalyzed histone 3 on lysine 9 (H3K9) di-, and tri-demethylation, which promoted TLR4 expression, and subsequently prompted liver fibrogenesis by activating NF-{kappa}B signaling pathways. KDM4D facilitates TLR4 transcription through demethylation of H3K9, thus activating TLR4/NF-{kappa}B signaling pathways in HSCs, contributing to HSC activation and collagen crosslinking, further, hepatic fibrosis progression.

cell biology↗

bioRxiv2018

Genome-wide selection footprints and deleterious variations in young Asian allotetraploid rapeseed

Brassica napus (AACC, 2n=38), is an important oilseed crop grown worldwide. However, little is known about the population evolution of this species, the genomic difference between its major genetic clusters, such as European and Asian rapeseed, and impacts of historical large-sale introgression events in this young tetraploid. In this study, we reported the de novo assembly of the genome sequences of an Asian rapeseed (B. napus), Ningyou 7 and its four progenitors and carried out de novo assembly-based comparison, pedigree and population analysis with other available genomic data from diverse European and Asian cultivars. Our results showed that Asian rapeseed originally derived from European rapeseed, but it had subsequently significantly diverged, with rapid genome differentiation after intensive local breeding selection. The first historical introgression of B. rapa dramatically broadened the allelic pool of Asian B. napus, but decreased their deleterious variations. The secondary historical introgression of European rapeseed (canola-quality) has reshaped Asian rapeseed into two groups, accompanied by an increase in genetic load. This study demonstrates distinctive genomic footprints by recent intra- and inter-species introgression events for local adaptation, and provide novel insights for understanding the rapid genome evolution of a young allopolyploid crop.

genomics↗

bioRxiv2018

Dynamic 3D tissue architecture directs BMP morphogen signaling during Drosophila wing morphogenesis

At the level of organ formation, tissue morphogenesis drives developmental processes in animals, often involving the rearrangement of two-dimensional (2D) structures into more complex three-dimensional (3D) tissues. These processes can be directed by growth factor signaling pathways. However, little is known about how such morphological changes affect the spatiotemporal distribution of growth factor signaling. Here, using the Drosophila pupal wing, we address how Decapentaplegic (Dpp) / Bone Morphogenetic Protein (BMP) signaling and 3D wing morphogenesis are coupled. Dpp, expressed in the longitudinal veins (LVs) of the pupal wing, initially diffuses laterally during the inflation stage to regulate cell proliferation. Dpp localization is then refined to the LVs within each epithelial plane, but with active interplanar signaling for vein patterning, as the two epithelia appose. Our data further suggest that the 3D architecture of the wing epithelia directs the spatial distribution of BMP signaling, revealing how 3D morphogenesis is an emergent property of the interactions between extracellular signaling and tissue shape changes.

developmental biology↗

bioRxiv2018

The Pemphigus Vulgaris antigen desmoglein-3 suppresses p53 function via the YAP-Hippo pathway

Desmoglein-3 (Dsg3), the Pemphigus Vulgaris (PV) antigen (PVA), plays an essential role in keratinocyte cell-cell adhesion and regulates various signaling pathways implicated in the pathogenesis the PV blistering disease. We show here that expression of Dsg3 may directly influence p53, a key transcription factor governing the response to cellular stress. Dsg3 depletion caused increased p53 and apoptosis, an effect that was further enhanced by UV and mechanical strain and reversed by Dsg3 gain-of-function studies. Analysis in Dsg3-/- mouse skin confirmed increased p53/p21/caspase-3 compared to Dsg3+/- control in vivo. This Dsg3-p53 pathway involved YAP since Dsg3 forms a complex with YAP and regulates its expression and localization. Analysis of PV patient samples detected increased p53/YAP with diffuse cytoplasmic and/or nuclear staining in cells surrounding blisters. Treatment of keratinocytes with PV sera evoked pronounced p53/YAP expression. Collectively, our findings establish a novel role for Dsg3 as an anti-stress protein, via suppression of p53 function, suggesting that this pathway, involving YAP-Hippo control of skin homeostasis, is disrupted in PV.

cell biology↗

bioRxiv2018

AnatomyNet: Deep 3D Squeeze-and-excitation U-Nets for fast and fully automated whole-volume anatomical segmentation

PurposeRadiation therapy (RT) is a common treatment for head and neck (HaN) cancer where therapists are often required to manually delineate boundaries of the organs-at-risks (OARs). The radiation therapy planning is time-consuming as each computed tomography (CT) volumetric data set typically consists of hundreds to thousands of slices and needs to be individually inspected. Automated head and neck anatomical segmentation provides a way to speed up and improve the reproducibility of radiation therapy planning. Previous work on anatomical segmentation is primarily based on atlas registrations, which takes up to hours for one patient and requires sophisticated atlas creation. In this work, we propose the AnatomyNet, an end-to-end and atlas-free three dimensional squeeze-and-excitation U-Net (3D SE U-Net), for fast and fully automated whole-volume HaN anatomical segmentation.\n\nMethodsThere are two main challenges for fully automated HaN OARs segmentation: 1) challenge in segmenting small anatomies (i.e., optic chiasm and optic nerves) occupying only a few slices, and 2) training model with inconsistent data annotations with missing ground truth for some anatomical structures because of different RT planning. We propose the AnatomyNet that has one down-sampling layer with the trade-off between GPU memory and feature representation capacity, and 3D SE residual blocks for effective feature learning to alleviate these challenges. Moreover, we design a hybrid loss function with the Dice loss and the focal loss. The Dice loss is a class level distribution loss that depends less on the number of voxels in the anatomy, and the focal loss is designed to deal with highly unbalanced segmentation. For missing annotations, we propose masked loss and weighted loss for accurate and balanced weights updating in the learning of the AnatomyNet.\n\nResultsWe collect 261 HaN CT images to train the AnatomyNet, and use MICCAI Head and Neck Auto Segmentation Challenge 2015 as the benchmark dataset to evaluate the performance of the AnatomyNet. The objective is to segment nine anatomies: brain stem, chiasm, mandible, optic nerve left, optic nerve right, parotid gland left, parotid gland right, submandibular gland left, and submandibular gland right. Compared to previous state-of-the-art methods for each anatomy from the MICCAI 2015 competition, the AnatomyNet increases Dice similarity coefficient (DSC) by 3.3% on average. The proposed AnatomyNet takes only 0.12 seconds on average to segment a whole-volume HaN CT image of an average dimension of 178 x 302 x 225. All the data and code will be availablea.\n\nConclusion1We propose an end-to-end, fast and fully automated deep convolutional network, AnatomyNet, for accurate and whole-volume HaN anatomical segmentation. The proposed Anato-myNet outperforms previous state-of-the-art methods on the benchmark dataset. Extensive experiments demonstrate the effectiveness and good generalization ability of the components in the AnatomyNet.

bioengineering↗

bioRxiv2018

Can transcranial electric stimulation with multiple electrodes reach deep targets?

To reach a deep target in the brain with transcranial electric stimulation (TES), currents have to pass also through the cortical surface. Thus, it is generally thought that TES cannot achieve focal deep brain stimulation. Recent efforts with interfering waveforms and pulsed stimulation have argued that one can achieve deeper or more intense stimulation in the brain. Here we argue that conventional transcranial stimulation with multiple current sources is just as effective as these new approaches. The conventional multi-electrode approach can be numerically optimized to maximize intensity or focality at a desired target location. Using such optimal electrode configurations we find in a detailed and realistic head model that deep targets may in fact be strongly stimulated, with cerebro-spinal fluid guiding currents deep into the brain.\n\nO_LSTHighlightsC_LSTO_LIDeep targets can be reached with intensities comparable to the cortical surface.\nC_LIO_LIMulti-electrode montages increase intensity with the same current limits per electrode.\nC_LIO_LIHigh-definition and intersectional pulsed stimulation are largely equivalent.\nC_LIO_LIInterferential stimulation is generally weaker than conventional stimulation.\nC_LI

biophysics↗

bioRxiv2018

Human cytomegalovirus RNA2.7 regulates host cell cycle and facilitates viral DNA replication by inhibiting RNA polymerase II phosphorylation

Human cytomegalovirus (HCMV) is a ubiquitous pathogen belongs to the beta herpesvirus family. RNA2.7 is a viral long non-coding RNA accounting for more than 20% of total viral transcripts at early time of infection. By construction of RNA2.7 deleted mutant and genome transcriptomic analysis, RNA2.7 is demonstrated to repress host cellular RNA polymerase II (Pol II)-dependent transcription through inhibiting the phosphorylation of RNA polymerase II (Pol II). Co-immunoprecipitation, RNA immunoprecipitation and RNA electrophoretic mobility shift assay are followed to investigate its mechnism. A 145nt-in-length fragment in RNA2.7 is identified to bind to Pol II and block the interaction between Pol II and phosphorylated cyckin-dependent kinase 9 (phospho-CDK9). By inhibiting Pol II phosphorylation, RNA2.7 decreases the transcription and expression levels of chromatin licensing and DNA replication factor 1 (Cdt1) and cell division cycle gene 6 (Cdc6). Through above way, RNA2.7 prevents the entry of cells into S phase and facilitates viral DNA replication. Our results discover the functions of HCMV RNA2.7 in regulation of Pol II phosphorylation and cell cycle control during infection.\n\nAuthor summaryHuman cytomegalovirus (HCMV) RNA2.7 is a viral lncRNA that is most abundant during infection. Here we show that a 145nt-in-length fragment in RNA2.7 binds to RNA polymerase II (Pol II) and blocks the interaction between Pol II and phosphorylated cyckin-dependent kinase 9 (phospho-CDK9). By inhibiting Pol II phosphorylation, RNA2.7 decreases the transcription and expression levels of chromatin licensing and DNA replication factor 1 (Cdt1) and cell division cycle gene 6 (Cdc6), and blocks host cells entering into S phase. RNA2.7 is confirmed to facilitate viral DNA replication through decreasing Cdt1 and Cdc6. Therefore, our results discover the functions of HCMV RNA2.7 in regulation of Pol II phosphorylation and cell cycle control during infection.

microbiology↗

bioRxiv2018

Radiosensitivity is an acquired vulnerability of PARPi-resistant BRCA1-deficient tumors

The homologous recombination (HR) defect in BRCA1-associated cancers can be therapeutically exploited by the treatment with DNA-damaging agents and poly (ADP-ribose) polymerase (PARP) inhibitors. We and others previously reported that BRCA1-deficient tumors are initially hypersensitive to the inhibition of topoisomerase I/II and PARP, but acquire drug resistance through restoration of HR activity by the loss of end-resection antagonists of the 53BP1/RIF1/REV7/Shieldin/CST pathway. Here, we identified radiotherapy as an acquired vulnerability of 53BP1;BRCA1-deficient cells in vitro and in vivo. In contrast to the radioresistance caused by HR restoration through BRCA1 reconstitution, HR restoration by 53BP1 pathway inactivation further increases radiosensitivity. This highlights the relevance of this pathway for the repair of radiotherapy-induced damage. Moreover, our data show that BRCA1-mutated tumors that acquired drug resistance due to BRCA1-independent HR restoration can be targeted by radiotherapy.\n\nSTATEMENT OF SIGNIFICANCEIn this study, we uncovered radiosensitivity as a novel therapeutically exploitable vulnerability of BRCA1-deficient mouse mammary cells that have acquired drug resistance due to the loss of the 53BP1 pathway.

cancer biology↗

bioRxiv2018

Impact of acetolactate synthase inactivation on 1,3-propanediol fermentation by Klebsiella pneumoniae

1,3-Propanediol (1,3-PDO) is an important compound that is mainly used in industry for polymer production. Fermentation of 1,3-PDO from glycerol by marine Klebsiella pneumoniae is accompanied by formation of 2,3-butanediol (2,3-BDO) as one of the main byproduct. The first step in the formation of 2,3-BDO from pyruvate is catalyzed by acetolactate synthase (ALS), an enzyme that competes with 1,3-PDO oxidoreductase for the cofactor NADH. This study aimed to analyze the impact of engineering the 2,3-BDO formation pathway via inactivation of ALS on 1,3-PDO fermentation by marine K. pneumoniae HSL4. An ALS mutant was generated using Red recombinase assisted gene replacement. The ALS specific activities of K. pneumoniae {Delta}ALS were notably lower than that of the wild-type strain. Fed-batch fermentation of the mutant strain resulted in a 1,3-PDO concentration, productivity and conversion of 72.04 g L-1, 2.25 g L-1 h-1, and 0.41 g g-1, a slightly increase compared with the parent strain. Moreover, inactivation of ALS decreased meso-2,3-BDO formation to trace amounts, significantly increased 2S,3S-BDO and lactate production, and a pronounced redistribution of intracellular metabolic flux was apparent.

microbiology↗

bioRxiv2018

Single-cell transcriptome analysis during cardiogenesis reveals basis for organ level developmental anomalies

Organogenesis involves integration of myriad cell types with reciprocal interactions, each progressing through successive stages of lineage specification and differentiation. Establishment of unique gene networks within each cell dictates fate determination, and mutations of transcription factors that drive such networks can result in birth defects. Congenital heart defects are the most common malformations and are caused by disruption of discrete subsets of progenitors1-3, however, determining the transcriptional changes in individual cells that lead to organ-level defects in the heart, or other organs, has not been tractable. Here, we employed single-cell RNA sequencing to interrogate early cardiac progenitor cells as they become specified during normal and abnormal cardiogenesis, revealing how dysregulation of specific cellular sub-populations can have catastrophic consequences. A network-based computational method for single-cell RNA-sequencing that predicts lineage specifying transcription factors4,5 identified Hand2 as a specifier of outflow tract cells but not right ventricular cells, despite failure of right ventricular formation in Hand2-null mice6. Temporal single-cell transcriptome analysis of Hand2-null embryos revealed failure of outflow tract myocardium specification, whereas right ventricular myocardium differentiated but failed to migrate into the anterior pole of the developing heart. Dysregulation of retinoic acid signaling, responsible for anterior-posterior patterning7, was associated with posteriorization of anterior cardiac progenitors in Hand2-null mutant hearts and ectopic atrial gene expression in outflow tract and right ventricle precursors. This work reveals transcriptional determinants in individual cells that specify cardiac progenitor cell fate and differentiation and exposes mechanisms of disrupted cardiac development at single-cell resolution, providing a framework to investigate congenital heart defects.

developmental biology↗

bioRxiv2018

NudCL2 is an Hsp90 cochaperone to regulate sister chromatid cohesion by stabilizing cohesin subunits

Sister chromatid cohesion plays a key role in ensuring precise chromosome segregation during mitosis, which is mediated by the multisubunit complex cohesin. However, the molecular regulation of cohesin subunits stability remains unclear. Here, we show that NudCL2 (NudC-like protein 2) is essential for the stability of cohesin subunits by regulating Hsp90 ATPase activity in mammalian cells. Depletion of NudCL2 induces mitotic defects and premature sister chromatid separation and destabilizes cohesin subunits that interact with NudCL2. Similar defects are also observed upon inhibition of Hsp90 ATPase activity. Interestingly, ectopic expression of Hsp90 efficiently rescues the protein instability and functional deficiency of cohesin induced by NudCL2 depletion, but not vice versa. Moreover, NudCL2 not only binds to Hsp90, but also significantly modulates Hsp90 ATPase activity and promotes the chaperone function of Hsp90. Taken together, these data suggest that NudCL2 is a previously undescribed Hsp90 cochaperone to modulate sister chromatid cohesion by stabilizing cohesin subunits, providing a hitherto unrecognized mechanism that is crucial for faithful chromosome segregation during mitosis.

cell biology↗