Biology subjects

Guo, Z.

Publications and source records attributed to Guo, Z..

At least 217 records · Page 12Linked to original sources

bioRxiv2021

Mechanically Sensitive HSF1 is a Key Regulator of Left-Right Symmetry Breaking in Zebrafish Embryos

The left-right symmetry breaking of vertebrate embryos requires fluid flow (called nodal flow in zebrafish). However, the molecular mechanisms that mediate the asymmetric gene expression regulation under nodal flow remain elusive. In this paper, we report that heat shock factor 1 (HSF1) is asymmetrically activated in the Kuppfers vesicle at the early stage of zebrafish embryos in the presence of nodal flow. Deficiency in HSF1 expression caused a significant situs inversus and disrupted gene expression asymmetry of nodal signaling proteins in zebrafish embryos. Further studies demonstrated that HSF1 could be immediately activated by fluid shear stress. The mechanical sensation ability of HSF1 is conserved in a variety of mechanical stimuli in different cell types. Moreover, cilia and the Ca2+-Akt signaling axis are essential for the activation of HSF1 under mechanical stress in vitro and in vivo. Considering the conserved expression of HSF1 in organisms, these findings unveil a fundamental mechanism of gene expression regulation triggered by mechanical clues during embryonic development and other physiological and pathological transformations.

developmental biology↗

bioRxiv2021

Improving deep learning-based protein distance prediction in CASP14

Accurate prediction of residue-residue distances is important for protein structure prediction. We developed several protein distance predictors based on a deep learning distance prediction method and blindly tested them in the 14th Critical Assessment of Protein Structure Prediction (CASP14). The prediction method uses deep residual neural networks with the channel-wise attention mechanism to classify the distance between every two residues into multiple distance intervals. The input features for the deep learning method include co-evolutionary features as well as other sequence-based features derived from multiple sequence alignments (MSAs). Three alignment methods are used with multiple protein sequence/profile databases to generate MSAs for input feature generation. Based on different configurations and training strategies of the deep learning method, five MULTICOM distance predictors were created to participate in the CASP14 experiment. Benchmarked on 37 hard CASP14 domains, the best performing MULTICOM predictor is ranked 5th out of 30 automated CASP14 distance prediction servers in terms of precision of top L/5 long-range contact predictions (i.e. classifying distances between two residues into two categories: in contact (< 8 Angstrom) and not in contact otherwise) and performs better than the best CASP13 distance prediction method. The best performing MULTICOM predictor is also ranked 6th among automated server predictors in classifying inter-residue distances into 10 distance intervals defined by CASP14 according to the F1 measure. The results show that the quality and depth of MSAs depend on alignment methods and sequence databases and have a significant impact on the accuracy of distance prediction. Using larger training datasets and multiple complementary features improves prediction accuracy. However, the number of effective sequences in MSAs is only a weak indicator of the quality of MSAs and the accuracy of predicted distance maps. In contrast, there is a strong correlation between the accuracy of contact/distance predictions and the average probability of the predicted contacts, which can therefore be more effectively used to estimate the confidence of distance predictions and select predicted distance maps.

bioinformatics↗

bioRxiv2021

Improving protein tertiary structure prediction by deep learning and distance prediction in CASP14

Substantial progresses in protein structure prediction have been made by utilizing deep-learning and residue-residue distance prediction since CASP13. Inspired by the advances, we improve our CASP14 MULTICOM protein structure prediction system in the three main aspects: (1) a new deep-learning based protein inter-residue distance predictor (DeepDist) to improve template-free (ab initio) tertiary structure prediction, (2) an enhanced template-based tertiary structure prediction method, and (3) distance-based model quality assessment methods empowered by deep learning. In the 2020 CASP14 experiment, MULTICOM predictor was ranked 7th out of 146 predictors in protein tertiary structure prediction and ranked 3rd out of 136 predictors in inter-domain structure prediction. The results of MULTICOM demonstrate that the template-free modeling based on deep learning and residue-residue distance prediction can predict the correct topology for almost all template-based modeling targets and a majority of hard targets (template-free targets or targets whose templates cannot be recognized), which is a significant improvement over the CASP13 MULTICOM predictor. The performance of template-free tertiary structure prediction largely depends on the accuracy of distance predictions that is closely related to the quality of multiple sequence alignments. The structural model quality assessment works reasonably well on targets for which a sufficient number of good models can be predicted, but may perform poorly when only a few good models are predicted for a hard target and the distribution of model quality scores is highly skewed.

bioinformatics↗

bioRxiv2021

Protein model accuracy estimation empowered by deep learning and inter-residue distance prediction in CASP14

The inter-residue contact prediction and deep learning showed the promise to improve the estimation of protein model accuracy (EMA) in the 13th Critical Assessment of Protein Structure Prediction (CASP13). During the 2020 CASP14 experiment, we developed and tested several EMA predictors that used deep learning with the new features based on inter-residue distance/contact predictions as well as the existing model quality features. The average global distance test (GDT-TS) score loss of ranking CASP14 structural models by three multi-model MULTICOM EMA predictors (MULTICOM-CONSTRUCT, MULTICOM-AI, and MULTICOM-CLUSTER) is 0.073, 0.079, and 0.081, respectively, which are ranked first, second, and third places out of 68 CASP14 EMA predictors. The single-model EMA predictor (MULTICOM-DEEP) is ranked 10th place among all the single-model EMA methods in terms of GDT_TS score loss. The results show that deep learning and contact/distance predictions are useful in ranking and selecting protein structural models.

bioinformatics↗

bioRxiv2021

Impact of Prior Infection on Protection and Transmission of SARS-CoV-2 in Golden Hamsters

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused over 100 million confirmed human infections, and 2 million more deaths globally since its emergence in the end of 2019. Several studies have shown that prior infection provided protective immunity against SARS-CoV-2 in non-human primate models. However, the effect of prior infection on blocking SARS-CoV-2 transmission is not clear. Here, we evaluated the impact of prior infection on protection and transmission of the SARS-CoV-2 virus in golden hamsters. Our results showed that prior infection provided protective immunity against SARS-CoV-2 re-challenge, but it was not sterizing immunity. The transmission experiment results showed that SARS-CoV-2 was efficiently transmitted from naive hamsters to prior infected hamsters by direct contact and airborne route, but not by indirect contact. Further, the virus was efficiently transmitted from prior infected hamsters to naive hamsters by direct contact, but not by airborne route and indirect contact. Surprisingly, the virus can be transmitted between prior infected hamsters by direct contact during a short period of early infection. Taken together, our study demonstrated that prior infected hamsters with good immunity can still be naturally re-infected, and the virus can be transmitted between prior infected hamsters and the naive through different transmission routes, implying the potential possibility of human re-infection and the risk of virus transmission between prior infected population and the healthy. Our study will help to calculate the herd immunity threshold more accurately, make more reasonable public health decisions, formulate an optimized population vaccination program, as well as aid the implementation of appropriate public health and social measures to control COVID-19.

microbiology↗

bioRxiv2021

Apolipoprotein M attenuates doxorubicin cardiotoxicity by regulating transcription factor EB

ObjectivesDetermine the role of apolipoprotein M (ApoM) in anthracycline (Dox) cardiotoxicity. BackgroundApoM binds the cardioprotective sphingolipid sphingosine-1-phosphate (S1P). Circulating ApoM is inversely associated with mortality in human heart failure (HF). MethodsIn the Penn HF Study (PHFS), we tested the relationship between ApoM and mortality in a subset with anthracycline-induced cardiomyopathy. We measured ApoM in humans and mice treated with Dox and utilized hepatic ApoM transgenic (ApomTG), ApoM knockout (ApomKO), ApoM knock-in mice with impaired S1P binding, and S1P receptor 3 (S1PR3) knockout mice in Dox cardiotoxicity. We assayed autophagy in left ventricular tissue from anthracycline-induced HF patients versus donor controls. ResultsApoM was inversely associated with mortality in PHFS, and Dox reduced circulating ApoM in mice and breast cancer patients. ApomTG mice were protected from Dox-induced cardiac dysfunction and loss of left ventricular mass. ApomTG attenuated Dox-induced impairment in autophagic flux in vivo and accumulation of insoluble p62, which was also observed in the myocardium of patients with anthracycline-induced HF. In vehicle-treated mice, ApoM negatively regulated transcription factor EB (TFEB), a master regulator of autophagy and lysosomal biogenesis. The effect of ApoM on TFEB required both S1P binding and S1PR3. In the presence of Dox, ApoM preserved TFEB and cardiomyocyte lysosomal abundance assessed as lysosomal associated membrane protein 1 positive structures in vivo, while S1P mimetic pretreatment of cardiomyocytes prevented Dox-induced changes in lysosomal pH. ConclusionsApoM attenuates Dox cardiotoxicity via the autophagy-lysosome pathway. The association between ApoM and reduced mortality may be explained by its role in sustaining autophagy. HighlightsO_LICirculating ApoM is inversely associated with survival in human anthracycline-induced cardiomyopathy C_LIO_LIAnthracycline treatment reduces circulating ApoM in humans and mice C_LIO_LIIncreasing ApoM attenuates doxorubicin cardiotoxicity, lysosomal injury and preserves myocardial autophagic flux, but does not impact doxorubicin anti-neoplastic efficacy C_LIO_LIAutophagic impairment is characteristic of human anthracycline cardiomyopathy C_LI

pharmacology and toxicology↗

bioRxiv2021

Resolving the graft ischemia-reperfusion injury during liver transplantation at the single cell resolution

Ischemia-reperfusion injury (IRI) remains the major reason for impaired donor graft function and increased mortality post-liver transplantation. The mechanism of IRI involves multiple pathophysiological processes and numerous types of cells. However, a systematic and comprehensive single-cell transcriptional profile of intrahepatic cells during liver transplantation is still unclear. We performed a single-cell transcriptome analysis of 14,313 cells from liver tissues collected from pre-procurement, at the end of preservation and 2 h post-reperfusion. We made detailed annotations of mononuclear phagocyte, endothelial cell, NK/T, B and plasma cell clusters, and we described the dynamic changes of the transcriptome of these clusters during IRI and the interaction between mononuclear phagocyte clusters and other cell clusters. In addition, we found that TNFAIP3 interacting protein 3 (TNIP3), specifically and highly expressed in Kupffer cell clusters post-reperfusion, may have a protective effect on IRI. In summary, our study provides the first dynamic transcriptome map of intrahepatic cell clusters during liver transplantation at single-cell resolution.

cell biology↗

bioRxiv2020

Listeria monocytogenes MenI encodes a DHNA-CoA thioesterase necessary for menaquinone biosynthesis, cytosolic survival, and virulence

Listeria monocytogenes is a Gram-positive intracellular pathogen that is highly adapted to invade and replicate in the cytosol of eukaryotic cells. Intermediate metabolites in the menaquinone biosynthesis pathway are essential for the cytosolic survival and virulence of L. monocytogenes, independent of the production of MK and aerobic respiration. Determining which specific intermediate metabolite(s) are essential for cytosolic survival and virulence has been hindered by the lack of an identified DHNA-CoA thioesterase essential for converting DHNA-CoA to DHNA in the MK synthesis pathway. Using the recently identified Escherichia coli DHNA-CoA thioesterase as a query, homology sequence analysis revealed a single homolog in L. monocytogenes, LMRG_02730. Genetic deletion of LMRG_02730 resulted in an ablated membrane potential, indicative of a non-functional electron transport chain (ETC) and an inability to aerobically respire. Biochemical kinetic analysis of LMRG_02730 revealed strong activity towards DHNA-CoA, similar to its E. coli homolog, further demonstrating that LMRG_02730 is a DHNA-CoA thioesterase. Functional analyses in vitro, ex vivo, and in vivo using mutants directly downstream and upstream of LMRG_02730 revealed that DHNA-CoA is sufficient to facilitate in vitro growth in minimal media, intracellular replication, and plaque formation in fibroblasts. In contrast, protection against bacteriolysis in the cytosol of macrophages and tissue specific virulence in vivo requires the production of DHNA. Taken together, these data implicate LMRG_02730 (renamed MenI) as a DHNA-CoA thioesterase and suggest that while DHNA protects the bacteria from killing in the macrophage cytosol, DHNA-CoA is necessary for intracellular bacterial replication.

microbiology↗

bioRxiv2020

3D Genome Contributes to Protein-Protein Interactome

Numerous computational methods have been proposed to predict protein-protein interactions, none of which however, considers the original DNA loci of the interacting proteins in the perspective of 3D genome. Here we retrospect the DNA origins of the interacting proteins in the context of 3D genome and discovered that 1) if a gene pair is more proximate in 3D genome, their corresponding proteins are more likely to interact. 2) signal peptide involvement of PPI affects the corresponding gene-gene proximity in 3D genome space. 3) by incorporating 3D genome information, existing PPI prediction methods can be further improved in terms of accuracy. Combining our previous discoveries, we conjecture the existence of 3D genome driven cellular compartmentalization, meaning the co-localization of DNA elements lead to increased probability of the co-localization of RNA elements and protein elements.

bioinformatics↗

bioRxiv2020

Characterization of LC-MS based urine metabolomics in healthy subjects across the life span

Previous studies reported that gender and age could influence urine metabolomics, which should be considered in biomarker discovery. As a consequence, for the baseline of urine metabolomics characteristics, it becomes critical to avoid confounding effects in clinical cohort studies. In this study, we provided a comprehensive lifespan characterization of urine metabolomics in a cohort of 348 healthy children and 315 adults aged 1 to 70 years using liquid chromatography coupled with high resolution mass spectrometry. Our results suggested that gender-dependent urine metabolites are much greater in adults than in children. The pantothenate and CoA biosynthesis and alanine metabolism pathways were enriched in early life. Androgen and estrogen metabolism showed high activity during adolescence and youth stages. Pyrimidine metabolism was enriched in the old stage. Based on the above analysis, metabolomic characteristics of each age stage were provided. This work could help us understand the baseline of urine metabolism characteristics and contribute to further studies of clinical disease biomarker discovery.

biochemistry↗

bioRxiv2020

Resuscitation of soil microbiota after > 70-years of desiccation

The abundance and diversity of bacteria in 24 historical soil samples under air-dried storage conditions for more than 70 years were assessed by quantification and high-throughput sequencing analysis of 16S rRNA genes. All soils contained a measurable abundance of bacteria varying from 103 to 108 per gram of soil and contrasting community compositions were observed in different background soils, suggesting that the bacteria detected were indigenous to the soil. Following a 4-week soil rewetting event, the bacterial abundance significantly increased in soils, indicating strong adaptation of soil bacteria to extreme osmotic change and high resuscitation potential of some bacteria over long periods of desiccation. Paenibacillus, Cohnella and two unclassified Bacillales genera within the phylum Firmicutes represented the most ubiquitously active taxa, which showed growth in the highest number of soils ([≥]12 soils), while genera Tumebacillus, Alicyclobacillus and Brevibacillus in the phylum Firmicutes displayed the highest growth rates in soils (with >1000-fold average increase) following rewetting. Additionally, some Actinobacteria and Proteobacteria genera showed relatively high activity following rewetting, suggesting that the resilience to long-term desiccation and rewetting is a common trait across phylogenetically divergent microbes. The present study thus demonstrated that diversified groups of microbes are present and potentially active in historically desiccated soils, which might be of importance in the context of microbial ecology.

microbiology↗

bioRxiv2020

Fast 3D printing of large-scale biocompatible hydrogel models

Large scale cell-laden hydrogel models hold great promise for tissue repair and organ transplantation, but their fabrication is faced with challenges in achieving clinically-relevant size and hierarchical structures. 3D bioprinting is an emerging technology, but its application in large, solid hydrogel fabrication has been limited by the slow printing speed that can affect the part quality and the biological activity of the encapsulated cells. Here we present a Fast hydrogeL prOjection stereolithogrAphy Technology (FLOAT) that allows the creation of a centimeter-sized, multiscale solid hydrogel model within minutes. Through precisely controlling the photopolymerization condition, we established low suction force-driven, high-velocity flow of the hydrogel prepolymer that supports the continuous replenishment of the prepolymer solution below the curing part and the nonstop part growth. We showed that this process is unique to the hydrogel prepolymer without externally supplemented oxygen. The rapid printing of centimeter-sized hydrogel models using FLOAT was shown to significantly reduce the part deformation and cellular injury caused by the prolonged exposure to the environmental stresses in layer-by-layer based printing methods. Media perfusion in the printed vessel network was shown to promote cell survival and metabolic function in the deep core of the large-sized hydrogel model over long term. The FLOAT is compatible with multiple photocurable hydrogel materials and the printed scaffold supports the endothelialization of prefabricated vascular channels. Together, these studies demonstrate a rapid 3D hydrogel printing method and highlight the potential of this method in the fabrication of large-sized engineered tissue models.

bioengineering↗

bioRxiv2020

Mining the potential of VRS1-5 gene to raise barley grain yield

VRS1-5 genes determine spike row types during the early stages of spike development in barley (Hordeum vulgare), yet their functions for the determination of grain yield during the late stages of spike development are largely unknown. To assess the role of VRS1-5 genes in determining grain yield components, we sequenced VRS1-5 genes from 894 worldwide barley accessions and measured 19 spike morphology traits in four environments. Single nucleotide polymorphism SNP markers and gene marker-based haplotypes for VRS1-5 displayed close associations with spike morphology traits. We further developed a spatiote-temporal transcriptome atlas (255 samples) at 17 stages and five positions along the spike, that linked spike morphology to spikelet development and expression patterns of VRS1-5 genes. Phenotypic measurements demonstrated that mutations in VRS1-5 suppress the initiation of spikelet primordia and, trigger spikelet abortion by increasing cytokinin content and improving sensitivity of spikelet primordia to cytokinin. Our integrated results illustrate how breeding can globally alter spike morphology through diversity at the VRS1-5 genes, which show great potential in increasing barley grain yield.

developmental biology↗

bioRxiv2020

MicroRNA775 Promotes Intrinsic Leaf Size and Reduces Cell Wall Pectin Level via a Target Galactosyltransferase in Arabidopsis

Plants possess unique primary cell walls made of complex polysaccharides that play critical roles in determining intrinsic cell and organ size. How genes responsible for synthesizing and modifying the polysaccharides are regulated by microRNAs (miRNAs) to control plant size remains largely unexplored. Here we identified 23 putative cell wall related miRNAs, termed CW-miRNAs, in Arabidopsis thaliana and characterized miR775 as an example. We showed that miR775 post-transcriptionally silences GALT9, which encodes an endomembrane-located galactosyltransferase belonging to the glycosyltransferase 31 family. Over-expression of miR775 and deletion of GALT9 significantly enlarged leaf-related organs, primarily owing to increases in cell size. Monosaccharide quantification, confocal Raman imaging, and immunolabelling combined with atomic force microscopy (AFM) revealed that the MIR775A-GALT9 circuit modulates pectin level and elastic modulus of the cell wall. We further showed that MIR775A is directly repressed by the transcription factor ELONGATED HYPOCOTYL 5 (HY5). Genetic analysis confirmed that HY5 is a negative regulator of leaf size and acts through the HY5-MIR775A-GALT9 repression cascade to control pectin level. These results demonstrate that miR775-regulated cell wall remodeling is an integral determinant for intrinsic leaf size in A. thaliana and highlight the need to study other CW-miRNAs for more insights into cell wall biology.

plant biology↗

bioRxiv2020

An Engineered Genetic Circuit for Lactose Intolerance Alleviation Coupled with Gut Microbiota Recovery

BackgroundLactose malabsorption occurs in around 68% of the world populations, causing lactose intolerance (LI) symptoms such as abdominal pain, bloating and diarrhoea. To alleviate LI, previous studies mainly focused on strengthening intestinal {beta}-galactosidase activity but neglected the inconspicuous colon pH drop caused by gut microbes fermentation on non-hydrolysed lactose. The colon pH drop will reduce intestinal {beta}-galactosidase activity and influence the intestinal homeostasis. ResultsHere, we synthesized a tri-stable-switch circuit equipped with high {beta}-galactosidase activity and pH rescue ability. This circuit can switch in functionality between expression of {beta}-galactosidase and expression of l-lactate dehydrogenase in respond to intestinal lactose signal and intestinal pH signal. We confirmed the circuit functionality was efficient using 12-hrs in vitro culture at a range of pH levels, as well as 6-hrs in vivo simulations in mice colon. Moreover, another 21-days mice trial indicated that this circuit can recover lactose-effected gut microbiota of mice to the status (enterotypes) similar to that of mice without lactose intake. ConclusionsTaken together, the tri-stable-switch circuit can serve as a promising prototype for LI symptoms relief, especially by flexibly adapting to environmental variation, stabilizing colon pH and restoring gut microbiota.

bioengineering↗

bioRxiv2020

Combination of deep neural network with attention mechanism enhances the explainability of protein contact prediction

Deep learning has emerged as a revolutionary technology for protein residue-residue contact prediction since the 2012 CASP10 competition. Considerable advancements in the predictive power of the deep learning-based contact predictions have been achieved since then. However, little effort has been put into interpreting the black-box deep learning methods. Algorithms that can interpret the relationship between predicted contact maps and the internal mechanism of the deep learning architectures are needed to explore the essential components of contact inference and improve their explainability. In this study, we present an attention-based convolutional neural network for protein contact prediction, which consists of two attention mechanism-based modules: sequence attention and regional attention. Our benchmark results on the CASP13 free-modeling (FM) targets demonstrate that the two attention modules added on top of existing typical deep learning models exhibit a complementary effect that contributes to predictive improvements. More importantly, the inclusion of the attention mechanism provides interpretable patterns that contain useful insights into the key fold-determining residues in proteins. We expect the attention-based model can provide a reliable and practically interpretable technique that helps break the current bottlenecks in explaining deep neural networks for contact prediction.

bioinformatics↗

bioRxiv2020

The PIF1-MIR408-Plantacyanin Repression Cascade Regulates Light Dependent Seed Germination

Light-sensing seed germination is a vital process for the seed plants. A decisive event in light-induced germination is degradation of the central repressor PHYTOCHROME INTERACTING FACTOR1 (PIF1). It is also known that the balance between gibberellic acid (GA) and abscisic acid (ABA) critically controls germination. But the cellular mechanisms linking PIF1 turnover to hormonal rebalancing remain elusive. Here, employing far-red light-induced Arabidopsis seed germination as the experimental system, we identified Plantacyanin (PLC) as an inhibitor of germination, which is a storage vacuole-associated blue copper protein highly expressed in mature seed and rapidly silenced during germination. Molecular analyses showed that PIF1 directly binds to the MIR408 promoter and represses miR408 accumulation, which in turn post-transcriptionally modulates PLC abundance, thus forming the PIF1-MIR408-PLC repression cascade for translating PIF1 turnover to PLC turnover during early germination. Genetic analysis, RNA-sequencing, and hormone quantification revealed that PLC is necessary and sufficient to maintain the PIF1-mediated seed transcriptome and the low-GA-high-ABA state. Furthermore, we found that PLC domain organization and regulation by miR408 are conserved features in seed plants. These results unraveled a cellular mechanism whereby PIF1-relayed external light signals are converted through PLC-based copper mobilization into internal hormonal profiles for controlling seed germination.

plant biology↗

bioRxiv2020

Active Time-Restricted Feeding Protects the Blood Pressure Circadian Rhythm in Diabetic Mice

The quantity and quality of food intake have been considered crucial for peoples wellness. Only recently has it become appreciated that the timing of food intake, independent of total calorie consumption, is also critical. The involvement and contribution of the timing of food intake in nondipping blood pressure (BP), the most common disruption of the BP circadian rhythm in diabetes, however, remains uncertain. Here, we demonstrate that the loss of diurnal rhythm in food intake coincided with nondipping BP in type 2 diabetic db/db mice, and imposing a food intake diurnal rhythm by active time-restricted feeding (ATRF) remarkably prevented db/db mice from the development of nondipping BP. Moreover, ATRF, independent of calorie restriction, also effectively restored the already disrupted BP circadian rhythm in db/db mice. Mechanistically, ATRF reduced the sympathetic vascular tone and BP during the light phase via fasting, thus protecting the BP circadian rhythm in db/db mice. Moreover, we identified BMAL1, an obligatory core clock gene, as a potentially key molecule that links ATRF, sympathetic vascular tone, and BP circadian rhythm. Collectively, these data reveal an important but previously unrecognized role of the timing of food intake in the onset, prevention, and treatment of nondipping BP in diabetes.

physiology↗