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Liu, D.

Publications and source records attributed to Liu, D..

At least 271 records · Page 15Linked to original sources

The viral packaging motor potentiates late gene expression in Kaposi's sarcoma-associated herpesvirus

{beta}- and {gamma}-herpesviruses transcribe their late genes in a manner distinct from host transcription. This process is directed by a complex of viral transcriptional activator proteins that hijack cellular RNA polymerase II and an unknown set of additional factors. We employed proximity labeling coupled with mass spectrometry, followed by CRISPR and siRNA screening to identify proteins functionally associated with the Kaposis sarcoma-associated herpesvirus (KSHV) late gene transcriptional complex. These data revealed that the catalytic subunit of the viral DNA packaging motor, ORF29, is both dynamically associated with the viral transcriptional activator complex and potentiates late gene expression. Through genetic mutation and deletion of ORF29, we establish that its catalytic activity potentiates viral transcription and is required for robust accumulation of essential late proteins during infection. Thus, we propose an expanded role for ORF29 that encompasses its established function in viral packaging and its newly discovered contributions to viral transcription and late gene expression in KSHV. Author summary{beta}- and {gamma}-herpesviruses express a class of genes essential for completion of the viral life cycle late during infection. A specialized complex of viral transcriptional activator proteins drives expression of these late genes in a manner dependent on viral genome replication, although the mechanisms and regulation of this process are largely unknown. Here, we identified factors that physically and functionally associate with the late gene transcription complex and unexpectedly found that the viral DNA packaging motor in Kaposis sarcoma-associated herpesvirus (KSHV) contributes to late gene expression. We show that the catalytic activity of this protein is not only required for genomic packaging but also for the robust expression of late genes to ensure the successful production of progeny virions. Thus, late gene transcription is mechanistically linked to the conserved processes of viral genome replication and packaging.

molecular biology↗

Endothelial vacuole membrane enriched aquaporins regulate microvascular lumenization in development and hyperglycemia

BackgroundIn patients with diabetic microvascular complications, decreased perfusion or vascular occlusion, caused by reduced vascular diameter, is a common characteristic that will lead to insufficient blood supply. However, the regulatory mechanism remains undetermined and the treatment approach is lacking. MethodsGene expression of Aquaporin 1 (AQP1) was compared between diabetic and non-diabetic human retina samples. Confocal live imaging analysis of zebrafish was utilized to investigate the hyperglycemia-induced alterations in vascular morphology. Transcriptomic and single-cell RNA sequencing, in situ hybridization, and quantitative PCR were used to analyze gene expressions. Gene knock-out zebrafish and stable transgenic lines were established for functional analysis. Human embryonic stem cells (H1 line), H1-derived endothelial cells (ECs), human umbilical vein endothelial cells (HUVECs), and human retinal microvascular endothelial cells (HRMECs) were used for functional analysis. ResultsFirstly, we found that the expression of human AQP1 was downregulated in diabetic human retina samples (49 healthy vs. 54 diabetic samples) and high-glucose-treated human retinal microvascular endothelial cells. Then, we observed the reduction of vascular diameter and compromised perfusion in high glucose-treated zebrafish embryos. Two aquaporins (aqp1a.1 and aqp8a.1), highly enriched in ECs, were significantly down-regulated under hyperglycemic conditions. Aqp1a.1 and/or aqp8a.1 loss-of-function leaded to reduction in intersegmental vessel diameters, recapitulating the phenotype of the hyperglycemic zebrafish model. Overexpressing aqp1a.1/aqp8a.1 in zebrafish ECs promoted the enlargement of microvascular diameters. Moreover, the reduced vessel diameters induced by high-glucose treatment was rescued by aquaporin overexpression. In addition, both aqp1a.1 and apq8a.1 were localized in the intracellular vacuoles in cultured ECs as well as the ECs of sprouting ISVs, and loss of Aqps caused the reduction of those vacuoles, which was required for lumenization. Loss of AQP1 had no influence on EC differentiation from human stem cells but strongly inhibited the vascular tube formation of differentiated ECs. ConclusionsEC-enriched aquaporins regulate intracellular vacuole-mediated blood vessel diameter hyperglycemia. All of these suggest that EC-expressed aquaporins might be potential targets for gene therapy to cure diabetes-related vascular perfusion defects.

cell biology↗

Single-cell RNA sequencing reveals aortic cellular heterogeneity in MSC_ITGB3-treated ApoE-/- mice on a high-fat diet

The aorta contains various cell types that are involved in the development of vascular inflammation and atherosclerosis. However, the cellular atlas of heterogeneous aorta cells, cellular responses, and intercellular communication has not been investigated in the background of a high-fat diet (HFD) and treatment with integrin beta 3-modified mesenchymal stem cells (MSC_ITGB3). In this study, 33,782 individual cells from mouse aortas under HFD with or without MSC_ITGB3 treatment were subjected to single-cell RNA sequencing as an unbiased analysis strategy. We generated a compendium of 30 different clusters, mainly smooth muscle cells (SMCs), endothelial cells, and immune cells. The proportion of the different cell types was considerably influenced by HFD and MSC_ITGB3. In the HFD group, genes associated with proliferation, migration, and collagen were highly expressed in the major SMC subpopulations. However, the expression of contraction-related genes in SMC subpopulations was significantly higher in the MSC_ITGB3 group than in the HFD group. After HFD consumption, subpopulations of ECs with active PI3K-Akt signaling pathway, ECM-receptor interaction, and contraction-related genes were significantly enriched. In the MSC_ITGB3 group, the number of dendritic cells (DCs), which are positively correlated with atherosclerotic lesion progression and contribute to lipid accumulation, and levels of inflammatory factors notably decreased. Our findings provide data on the composition, signaling pathways, and cellular communication of the aorta cells following stem cell treatment as well as on the evolution and progression of atherosclerotic disease. The findings may help in improving the treatment of atherosclerosis.

bioinformatics↗

GraphGPSM: a global scoring model for protein structure using graph neural networks

The scoring models used for protein structure modeling and ranking are mainly divided into unified field and protein-specific scoring functions. Although protein structure prediction has made tremendous progress since CASP14, the modeling accuracy still cannot meet the requirements to a certain extent. Especially, accurate modeling of multi-domain and orphan proteins remains a challenge. Therefore, an accurate and efficient protein scoring model should be developed urgently to guide the protein structure folding or ranking through deep learning. In this work, we propose a protein structure global scoring model based on equivariant graph neural network (EGNN), named GraphGPSM, to guide protein structure modeling and ranking. We construct an EGNN architecture, and a message passing mechanism is designed to update and transmit information between nodes and edges of the graph. Finally, the global score of the protein model is output through a multilayer perceptron. Residue-level ultrafast shape recognition is used to describe the relationship between residues and the overall structure topology, and distance and direction encoded by Gaussian radial basis functions are designed to represent the overall topology of the protein backbone. These two features are combined with Rosetta energy terms, backbone dihedral angles, and inter-residue distance and orientations to represent the protein model and embedded into the nodes and edges of the graph neural network. The experimental results on the CASP13, CASP14, and CAMEO test sets show that the scores of our developed GraphGPSM have a strong correlation with the TM-score of the models, which are significantly better than those of the unified field score function REF2015 and the state-of-the-art local lDDT-based scoring models ModFOLD8, ProQ3D, and DeepAccNet etc. The modeling experimental results on 484 test proteins demonstrate that GraphGPSM can greatly improve the modeling accuracy. GraphGPSM is further used to model 35 orphan proteins and 57 multi-domain proteins. The results show that the average TM-score of the models predicted by GraphGPSM is 13.2% and 7.1% higher than that of the models predicted by AlphaFold2. GraphGPSM also participates in CASP15 and achieves competitive performance in global accuracy estimation.

bioinformatics↗

BnIR: a multi-omics collaborative resource and tool platform for Brassica napus biological study

In the post-GWAS era, multi-omics techniques have shown great power and potential for candidate gene mining and functional genomics research. However, due to the lack of effective data integration and multi-omics analysis platforms, such techniques have not still been applied widely in rapeseed, an important oil crop worldwide. Here, we constructed a rapeseed multi-omics database (BnIR; http://yanglab.hzau.edu.cn/BnIR), which provides datasets of six omics including genomics, transcriptomics, variomics, epigenetics, phenomics and metabolomics, as well as numerous "variation-gene expression-phenotype" associations by using multiple statistical methods. In addition, a series of multi-omics search and analysis tools are integrated to facilitate the browsing and application of these datasets. BnIR is the most comprehensive multi-omics database for rapeseed so far, and two case studies demonstrated its power to mine candidate genes associated with specific traits and analyze their potential regulatory mechanisms. Short SummaryIn this study, we developed BnIR (http://yanglab.hzau.edu.cn/BnIR), a multi-omics database for rapeseed that integrates six omics datasets and "variation-gene expression-phenotype" associations. The database is equipped with a range of multi-omics tools for streamlined browsing and analysis. Through multiple case studies, we demonstrated BnIRs potential to identify candidate genes associated with specific traits and investigate their regulatory mechanisms.

bioinformatics↗

The genomic diversity of Taiwanese Austronesian groups: implications for the "Into and Out of Taiwan" models

The origin and dispersal of the Austronesian language family, one of the largest and most widespread in the world, have long attracted the attention of linguists, archaeologists, and geneticists. Even though there is a growing consensus that Taiwan is the source of the spread of Austronesian languages, little is known about the migration patterns of the early Austronesians who settled in and left Taiwan, i.e., the "Into-Taiwan" and "Out-of-Taiwan" events. In particular, the genetic diversity/structure within Taiwan and how this relates to the Into/Out-of-Taiwan events is largely unexplored, because most genomic studies have largely utilized data from just two of the 16 recognized highland Austronesian groups in Taiwan. In this study, we generated the largest genome-wide dataset for Taiwanese Austronesians to date, including six highland groups and one lowland group from across the island, and two Taiwanese Han groups. We identified fine scale genomic structure in Taiwan, inferred the ancestry profile of the ancestors of Austronesians, and found that the southern Taiwanese Austronesians show excess genetic affinities toward the Austronesians outside of Taiwan. Our findings thus shed new light on the Into and Out-of-Taiwan dispersals.

genomics↗

IL-15 enhances functional properties and responses of CD28-negative CD4+ cytotoxic T cells expanded in Systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disorder that results in an attack by bodys immune system of its own tissues, causing chronic inflammation and tissue damage. T cells play a key role in the pathogenesis of SLE, as they secrete pro-inflammatory cytokines as well as mediate direct effects on target tissues. Recently, CD4-positive T cells with cytotoxic potential were showed to be involved in autoimmune disease progression and tissue damage. However, whether this cell type expands and plays effector functions in SLE patients remain to be elucidated. Analyzing single-cell RNA sequencing (scRNA-Seq) data and flow cytometry data, we find that cytotoxic CD4+CD28- T cells are present in SLE patients. We also show that these cells expand most prominently in patients affected by lupus nephritis, and they exhibit cytotoxic activity against human renal glomerular endothelial cells in vitro. In addition, our study suggests that Interleukin-15 (IL-15) promotes the expansion, proliferation and cytotoxic function of CD4+CD28- T cells in SLE patients. Tofacitinib, a selective JAK3 inhibitor, inhibits the effect of IL-15 on CD4+CD28- T cells. Together, our study clearly demonstrated that CD4+ CD28- T cells characterized by proinflammatory properties and cytolytic function expand in SLE patients. The pathogenic potential of these CD4+ CD28- T cells is driven by IL-15/IL-15R/JAK3/STAT5 signaling pathway, which may open new avenues for therapeutic intervention to prevent progression of SLE patients.

immunology↗

mRNA delivery of dimeric human IgA protects mucosal tissues from bacterial infection

Monoclonal antibody (mAb) therapy is a promising infectious disease intervention strategy but is limited to IgG1 isotypes that have restricted access to mucosal sites. IgA is well-established as the predominant antibody isotype in mucosal secretions but is clinically underutilized. To enable development of IgA-based mAbs, we exploited mRNA platform technology and demonstrated expression of functional, antigen-specific IgA (IgAmRNA) that can limit bacterial invasion in the intestine and prevent colonization in the lung. Moreover, in vivo IgAmRNA had enhanced serum half-life and a greater degree of sialylation than a recombinantly produced IgA. The results underscore the potential of mRNA-based platforms to deliver protective human mAbs to mucosal surfaces and open new avenues to combat infectious diseases in the face of pervasive antibiotic resistance. One Sentence SummarymRNA-encoded human monoclonal IgA traffics to mucosal tissues and provides protection against bacterial challenge

immunology↗

A versatile semiautomated image analysis workflow for time-lapsed camera trap image classification.

O_LICamera trap arrays can generate thousands to millions of images that require exorbitant time and effort to classify and annotate by trained observers. Computer vision has evolved as an automated alternative to manual classification. The most popular computer vision solution is the supervised Machine Learning technique, which uses labeled images to train automated classification algorithms. C_LIO_LIWe propose a multi-step semi-automated workflow that consists of (1) identifying and separating bad-from good-quality images, (2) parsing good images into animals, humans, vehicles, and empty, and (3) cropping animals from images and classifying them into species for manual inspection. We trained, validated, and evaluated this approach using 548,627 images from 46 cameras in two regions of the Arctic (northeastern Norway, and Yamal Peninsula, Russia). C_LIO_LIWe obtained an accuracy of 0.959 for all three steps combined with the complete year test data set at Varanger and 0.922 at Yamal, reducing the number of images that required manual inspection to 7.9% of the original set from Varanger and 3.2% from Yamal. C_LIO_LIResearchers can modify this multi-step process to meet their specific needs for monitoring and surveying wildlife, providing greater flexibility than current options available for image classification. C_LI

ecology↗

Best: A Tool for Characterizing Sequencing Errors

SummaryPlatform-dependent sequencing errors must be understood to develop accurate sequencing technologies. We propose a new tool, best (Bam Error Stats Tool), for efficiently quantifying and summarizing error types in sequenced reads. best ingests reads aligned to a high-quality reference assembly and produces per-read metrics, summary statistics, and stratified metrics across genomic intervals. We show that best is 16 times faster than a prior method. In addition to being useful to support development that improves the accuracy of sequencing platforms, best can also be applied to evaluate and improve other experimental factors such as library preparation and error correction methods. Availability and implementationbest is an open-source command-line utility available on Github (github.com/google/best) under an MIT license. Contactdanielecook@google.com

bioinformatics↗

GeneSegNet: A deep learning framework for cell segmentation by integrating gene expression and imaging

When analyzing data from in situ RNA detection technologies, cell segmentation is an essential step in identifying cell boundaries, assigning RNA reads to cells, and studying the gene expression and morphological features of cells. We developed a deep-learning-based method, GeneSegNet, that integrates both gene expression and imaging information to perform cell segmentation. GeneSegNet also employs a recursive training strategy to deal with noisy training labels. We show that GeneSegNet significantly improves cell segmentation performances over existing methods that either ignore gene expression information or underutilize imaging information.

bioinformatics↗

Genomic heterogeneity and ploidy identify patients with intrinsic resistance to PD-1 blockade in metastatic melanoma

While the introduction of immune checkpoint blockade (ICB) has dramatically improved clinical outcomes for patients with advanced melanoma, a significant proportion of patients develop resistance to therapy, and mechanisms of resistance are poorly elucidated in most cases. Further, while combination ICB has higher response rates and improved progression free survival compared to single agent therapy in the front line setting, there is significantly increased toxicity with combination ICB, and biomarkers to identify patients who would disproportionately benefit from combination therapy vs aPD-1 ICB are poorly characterized. To understand resistance mechanisms to single vs combination ICB therapy, we analyze whole-exome-sequencing (WES) of pre-treatment tumor and matched normals of 4 cohorts (n=140) of previously ICB-naive aPD-1 ICB treated patients. We find that high intratumoral genomic heterogeneity and low ploidy identify patients with intrinsic resistance to aPD-1 ICB. Comparing to a melanoma cohort from a pre-targeted therapy and ICB time period ("untreated" cohort), we find that genomic heterogeneity specifically predicts response and survival in the ICB treated cohorts, but not in the untreated cohort, while ploidy is also prognostic of overall survival in the "untreated" (by targeted therapy or ICB) group. To establish clinically actionable predictions, we optimize a simple decision tree using genomic ploidy and heterogeneity to identify with high confidence (90% PPV) a subset of patients with intrinsic resistance to and significantly worse survival on aPD1 ICB treatment. We then validate this model in independent cohorts, and further show that a significant proportion of patients predicted to have intrinsic resistance to single agent aPD-1 ICB respond to combination ICB, which suggests that nominated patients may benefit disproportionately from combination ICB. We further show that the features and predictions of the model are independent of known clinical features and previously nominated molecular biomarkers. These findings highlight the clinical and biological importance of genomic heterogeneity and ploidy, and sets a concrete framework towards clinical actionability, broadly advancing precision medicine in oncology.

cancer biology↗

Assigning functionality to cysteines by base editing of cancer dependency genes

Chemical probes are lacking for most human proteins. Covalent chemistry represents an attractive strategy for expanding the ligandability of the proteome, and chemical proteomics has revealed numerous electrophile-reactive cysteines on diverse proteins. Determining which of these covalent binding events impact protein function, however, remains challenging. Here, we describe a base-editing strategy to infer the functionality of cysteines by quantifying the impact of their missense mutation on cell proliferation. We show that the resulting atlas, which covers >13,800 cysteines on >1,750 cancer dependency proteins, correctly predicts the essentiality of cysteines targeted by cancer therapeutics and, when integrated with chemical proteomic data, identifies essential, ligandable cysteines on >110 cancer dependency proteins. We further demonstrate how measurements of reactivity in native versus denatured proteomes can discriminate essential cysteines amenable to chemical modification from those buried in protein structures, providing a valuable resource to prioritize the pursuit of small-molecule probes with high function-perturbing potential.

systems biology↗

Subscaling of a cytosolic RNA binding protein governs cell size homeostasis in the multiple fission alga Chlamydomonas

Coordination of growth and division in eukaryotic cells is essential for populations of proliferating cells to maintain size homeostasis, but the underlying mechanisms that govern cell size have only been investigated in a few taxa. The green alga Chlamydomonas reinhardtii (Chlamydomonas) proliferates using a multiple fission cell cycle that involves a long G1 phase followed by a rapid series of successive S and M phases (S/M) that produces 2n daughter cells. Two control points show cell-size dependence: Commitment in mid-G1 phase requires attainment of a minimum size to enable at least one mitotic division during S/M, and the S/M control point where mother cell size governs cell division number (n), ensuring that daughter distributions are uniform. tny1 mutants pass Commitment at a smaller size than wild type and undergo extra divisions during S/M phase to produce small daughters, indicating that TNY1 functions to inhibit size-dependent cell cycle progression. TNY1 encodes a cytosolic hnRNP A- related RNA binding protein and is produced once per cell cycle during S/M phase where it is apportioned to daughter cells, and then remains at constant absolute abundance as cells grow, a property known as subscaling (1). Altering the dosage of TNY1 in heterozygous diploids or through overexpression increased Commitment cell size and daughter cell size, indicating that TNY1 is a limiting factor for both size control checkpoints. Epistasis placed TNY1 function upstream of the retinoblastoma tumor suppressor complex (RBC) and one of its regulators, Cyclin-Dependent Kinase G1 (CDKG1) (2). Moreover, CDKG1 protein and mRNA were found to over-accumulate in tny1 cells suggesting that CDKG1 may be a direct target of repression by TNY1. Our data expand the potential roles of subscaling proteins outside the nucleus and imply a control mechanism that ties TNY1 accumulation to pre-division mother cell size. Author SummarySize control is a fundamental property of cells which requires balancing cell growth with cell division, but the mechanisms used by cells to achieve this balance are only partly understood. The best-characterized mechanisms for size control to date involve fixed amounts of nuclear- DNA-bound inhibitory factors which repress cell division until cells grow past a minimum size threshold to overcome the inhibition. The unicellular green alga Chlamydomonas and many other algae and protists use a non-canonical cell cycle where cells can grow by many-fold in size before dividing, and then undergo multiple fission which involves successive rapid divisions to produce a uniform-sized population of daughters. In Chlamydomonas an unknown size homeostasis mechanism couples mother cell size to division number such that larger mother cells divide more times than smaller mother cells. Here, we identified and characterized a key factor governing size control in Chlamydomonas, a cytoplasmic RNA-binding protein and division inhibitor, TNY1, that is produced in a fixed amount in daughter cells and does not increase with cell growth, a property called sub-scaling. We found that TNY1 represses production of a cell cycle activator, CDKG1, during multiple fission to control daughter cell size. TNY1 is the first example of a cytosolic cell cycle inhibitor that does not depend on nuclear DNA binding to govern sub-scaling.

cell biology↗

Whole Human-Brain Mapping of Single Cortical Neurons for Profiling Morphological Diversity and Stereotypy

Quantification of individual cells morphology and their distribution at the whole brain scale is essential to understand the structure and diversity of cell types. Despite recent technological advances, especially single cell labeling and whole brain imaging, for many prevailing animal models, it is exceedingly challenging to reuse similar technologies to study human brains. Here we propose Adaptive Cell Tomography (ACTomography), a low-cost, high-throughput, high-efficacy tomography approach, based on adaptive targeting of individual cells suitable for human-brain scale modeling of single neurons to characterize their 3-D structures, statistical distributions, and extensible for other cellular features. Specifically, we established a platform to inject dyes into cortical neurons in surgical tissues of 18 patients with brain tumors or other conditions and 1 donated fresh postmortem brain. We collected 3-D images of 1746 cortical neurons, of which 852 neurons were subsequentially reconstructed to quantify their local dendritic morphology, and mapped to standard atlases both computationally and semantically. In our data, human neurons are more diverse across brain regions than by subject age or gender. The strong stereotypy within cohorts of brain regions allows generating a statistical tensor-field of neuron morphology to characterize 3-D anatomical modularity of a human brain.

neuroscience↗

Salt-inducible kinase inhibition promotes the adipocyte thermogenic program and adipose tissue browning

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC="FIGDIR/small/514130v2_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@ce743org.highwire.dtl.DTLVardef@122f339org.highwire.dtl.DTLVardef@18e3013org.highwire.dtl.DTLVardef@1f65311_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractsC_FLOATNO C_FIG ObjectiveNorepinephrine stimulates the adipose tissue thermogenic program through a {beta}-adrenergic receptor ({beta}AR) - cyclic adenosine monophosphate (cAMP) - protein kinase A (PKA) signaling cascade. We discovered that a noncanonical activation of the mechanistic target of rapamycin complex 1 (mTORC1) by PKA is required for the {beta}AR-stimulation of adipose tissue browning. However, the downstream events triggered by PKA-phosphorylated mTORC1 activation that drive this thermogenic response are not well understood. MethodsWe used a proteomic approach of Stable Isotope Labeling by/with Amino acids in Cell culture (SILAC) to characterize the global protein phosphorylation profile in brown adipocytes treated with the {beta}AR agonist. We identified salt-inducible kinase 3 (SIK3) as a candidate mTORC1 substrate and further tested the effect of SIK3 deficiency or SIK inhibition on the thermogenic gene expression program in brown adipocytes and in mouse adipose tissue. ResultsSIK3 interacts with RAPTOR, the defining component of the mTORC1 complex, and is phosphorylated at Ser884 in a rapamycin-sensitive manner. Pharmacological SIK inhibition by a pan-SIK inhibitor (HG-9-91-01) in brown adipocytes increases basal Ucp1 gene expression and restores its expression upon blockade of either mTORC1 or PKA. Short-hairpin RNA (shRNA) knockdown of Sik3 augments, while overexpression of SIK3 suppresses, Ucp1 gene expression in brown adipocytes. The regulatory PKA phosphorylation domain of SIK3 is essential for its inhibition. CRISPR-mediated Sik3 deletion in brown adipocytes increases type IIa histone deacetylase (HDAC) activity and enhances the expression of genes involved in thermogenesis such as Ucp1, Pgc1, and mitochondrial OXPHOS complex protein. We further show that HDAC4 interacts with PGC1 after {beta}AR stimulation and reduces lysine acetylation in PGC1. Finally, a SIK inhibitor well-tolerated in vivo (YKL-05-099) can stimulate the expression of thermogenesis-related genes and browning of mouse subcutaneous adipose tissue. ConclusionsTaken together, our data reveal that SIK3, with the possible contribution of other SIKs, functions as a phosphorylation switch for {beta}-adrenergic activation to drive the adipose tissue thermogenic program and indicates that more work to understand the role of the SIKs is warranted. Our findings also suggest that maneuvers targeting SIKs could be beneficial for obesity and related cardiometabolic disease.

physiology↗

Intrathecal administration of bone marrow stromal cells and TGF-β1 alleviate chemotherapy-induced neuropathic pain in male mice

Chemotherapy-induced peripheral neuropathy (CIPN) is the de facto clinical side effect that limits the administration of anti-cancer treatments. Recently, we reported that intrathecally injected bone marrow stromal cells (BMSCs) reduced nerve trauma-induced neuropathic pain in male mice via TGF-{beta}1 signaling. In this study, we examined sex-dependent pain relief mediated by intrathecally delivered BMSCs and TGF-{beta}1 in paclitaxel (PTX)-induced CIPN. BMSCs were prepared from primary cultures of male or female mice separately. A single intrathecal injection of BMSCs, prepared from male donors, completely prevented the development of PTX-evoked mechanical allodynia in male mice. However, female mice showed no analgesic response to either male or female BMSCs. Additionally, male mice did not demonstrate an analgesic response to BMSCs from female donors. Intrathecal injection of TGF-{beta}1 neutralizing antibody reversed the analgesic action of BMSCs. Interestingly, spinal administration of TGF-{beta}1 reduced mechanical allodynia in male mice but not in female mice. Ex vivo patch-clamp recordings in spinal cord slices revealed that TGF-{beta}1 inhibited PTX-induced synaptic plasticity, i.e. increase in spontaneous excitatory synaptic currents (sEPsCs), in spinal cord neurons from male mice only. Intrathecal TGF-{beta}1 increased the paw withdrawal threshold in von Frey testing in naive mice of males but not females, and the antinociceptive effect of TGF-{beta}1 in males was blocked by orchiectomy-induced androgen deficiency. Together, these findings reveal sex dimorphism in BMSC control of mechanical pain through spinal TGF-{beta}1 signaling.

neuroscience↗

Hybrid Synthesis of bioplastics polyhydroxybutyrate from carbon dioxide

The accelerating environmental crisis has intensified the demand for switching from traditional economy to a renewable one with a reduced carbon footprint. Here we reported a hybrid system, coupling chemical process of CO2 hydrogen reduction and biological process for polyhydroxybutyrate (PHB) synthesis, that utilized CO2 as a raw material to produce PHB in vitro. The synthetic pathway of PHB was optimized by screening more efficient methanol oxidases, high activity mutants of glycolaldehyde synthase and coordinating enzyme dosages in the pathway, which achieved the carbon yield of 93.6% for producing PHB from methanol. Finally, by combining with the chemical process from CO2 to methanol, a scaling-up bio-system was performed to convert CO2 into PHB, yielding 5.8 g/L with the productivity of 1.06 g-1L-1h-1. This approach represents a promising carbon-neutral way to produce biodegradable plastics.

synthetic biology↗