Biology subjects

Hu, H.

Publications and source records attributed to Hu, H..

At least 181 records · Page 10Linked to original sources

bioRxiv2022

Social Regulation of Egg Size Plasticity in the Honey Bee is Mediated by Cytoskeleton Organizer Rho1

Egg size plasticity represents an adaptive reproductive strategy in numerous organisms, including the honey bee, Apis mellifera. However, the proximate causation of this plasticity and egg size in general is unknown. We show that honey bee queens predictably and reversibly adjust egg size in response to their colony size and that this plasticity is an active response to the queens perception of colony size instead of a consequence of egg laying rate. The egg size increase involves changes of 290 ovarian proteins, mostly related to increased energy metabolism, protein transport, and cytoskeleton functions. Spatio-temporal expression analysis of the small GTPase Rho1 indicates its central role in egg size regulation, which we confirm by RNAi-mediated gene knock-down and expression analyses. The molecular adjustments that promote maternal investment of honey bee queens in response to their social environment thus reveal a novel mechanism of egg size regulation.

evolutionary biology↗

bioRxiv2022

INSISTC: Incorporating Network Structure Information for Single-Cell Type Classification

MotivationUncovering gene regulatory mechanisms in individual cells can provide insight into cell heterogeneity and function. Recent accumulated single-cell RNA sequencing data have made it possible to analyze gene regulation at single-cell resolution. On the other hand, understanding cell-type-specific gene regulation can also assist in more accurate cell type and state identification. Computational approaches utilizing gene regulatory relationships for single-cell type classification are under development. Methods pioneering in integrating gene regulatory mechanism discovery with cell-type classification encounter challenges such as how to accurately determine gene regulatory relation-ships and how to incorporate gene regulatory network structure into consideration. ResultsWe developed a computational method to incorporate gene regulatory network structure information for single-cell type classification (INSISTC). INSISTC is capable of identifying cell-type-specific gene regulatory mechanisms while performing single cell type classification. Tested on three mouse scRNA-Seq datasets, including thousands of single-cell samples, INSISTC demonstrated its accuracy in cell type classification and its potential for providing insight into molecular mechanisms specific to individual cells. In comparison with the alternative methods, INSISTC demonstrated its complementary performance for gene regulation interpretation. Availabilityhttps://hulab.ucf.edu/research/projects/INSISTC/ Contacthaihu@cs.ucf.edu or xiaoman@mail.ucf.edu Supplementary informationSupplementary data are available at xxxxxx online.

bioinformatics↗

bioRxiv2022

Preclinical evaluation of RQ3013, a broad-spectrum mRNA vaccine against SARS-CoV-2 variants

The global emergence of SARS-CoV-2 variants has led to increasing breakthrough infections in vaccinated populations, calling for an urgent need to develop more effective and broad-spectrum vaccines to combat COVID-19. Here we report the preclinical development of RQ3013, an mRNA vaccine candidate intended to bring broad protection against SARS-CoV-2 variants of concern (VOCs). RQ3013, which contains pseudouridine-modified mRNAs formulated in lipid nanoparticles, encodes the spike(S) protein harboring a combination of mutations responsible for immune evasion of VOCs. Here we characterized the expressed S immunogen and evaluated the immunogenicity, efficacy, and safety of RQ3013 in various animal models. RQ3013 elicited robust immune responses in mice, hamsters, and nonhuman primates (NHP). It can induce high titers of antibodies with broad cross-neutralizing ability against the Wild-type, B.1.1.7, B.1.351, B.1.617.2, and the omicron B.1.1.529 variants. In mice and NHP, two doses of RQ3013 protected the upper and lower respiratory tract against infection by SARS-CoV-2 and its variants. We also proved the safety of RQ3013 in NHP models. Our results provided key support for the evaluation of RQ3013 in clinical trials.

immunology↗

bioRxiv2022

Cardiac patch treatment alleviates ischemic cardiomyopathy correlated with reverting Piezo1/2 expression by unloading left ventricular myocardium

Pathologically elevated mechanical load promotes the adverse remodeling of left ventricle (LV) post myocardial infarction, which results in the progression from ischemic cardiomyopathy to heart failure. Cardiac patches could attenuate adverse LV remodeling by providing mechanical support to infarcted myocardium and border zone tissue. However, the mechanism of the translation from mechanical effects to favorable therapeutic outcome is still not clear. By transcriptome analysis, we found that the myocardial transcription levels of mechanosensitive ion channel proteins Piezo1 and Piezo2 significantly increased in patients with ischemic cardiomyopathy. In vitro tensile tests with local tissue information revealed a significant decrease in local strain and mechanical load in rat infarct. Cardiac function and geometry were preserved compared to non-treated control. Further, in LV myocardium of the patch-treated group, MI induced expression levels of Piezo1/2 were significantly reverted to the similar levels of the Sham group, indicating that cardiac patch beneficial effects were correlated with suppressing mechanosensitive genes, particularly Piezo1/2. These findings demonstrated the potential of cardiac patches in treating ICM patients with remodeling risks, and could provide guidance for improvement in next generation of patch devices.

pathology↗

bioRxiv2022

Allosteric inhibition of PRPS is moderated by filamentous polymerization

Phosphoribosyl pyrophosphate (PRPP) is an important intermediate for the biosynthesis of purine and pyrimidine nucleotides, histidine, tryptophan, and cofactors NAD and NADP. Abnormal regulation of PRPP synthase (PRPS) has been associated with human disorders including Arts syndrome, retinal dystrophy and gouty arthritis. Recent studies have revealed that PRPS can form filamentous cytoophidia in prokaryotes and eukaryotes. Here we resolve two distinct filament structures of E. coli PRPS at near-atomic resolution under Cryo-EM. Formation of two types of filaments is controlled by the binding of different ligands. While the type A filament attenuates the allosteric inhibition of PRPS by ADP, the type B filament enhances the inhibition. In addition, a novel conformation of the regulatory flexible loop of PRPS was found occupying the ATP binding site. AMP/ADP bound at a noncanonical allosteric site interacts with the regulatory flexible loop and facilitates the binding of ATP. Our findings not only reveal molecular mechanisms of the regulation of PRPS with structural basis, but also suggest a distinctive bidirectional regulatory system for PRPP production via PRPS polymerization.

biochemistry↗

bioRxiv2022

A revisit to universal single-copy genes in bacterial genomes

Universal single-copy genes (USCGs) are widely used for species classification and taxonomic profiling. Despite many studies on USCGs, our understanding of USCGs in bacterial genomes might be out of date, especially how different the USCGs are in different studies, how well a set of USCGs can distinguish two bacterial species, whether USCGs can separate different strains of a bacterial species, to name a few. To fill the void, we studied USCGs in the most updated bacterial RefSeq genomes. We showed that different USCG sets are quite different while coming from highly similar functional categories. We also found that although USCGs occur once in almost all bacterial genomes, each USCG does occur multiple times in certain genomes. We demonstrated that USCGs are reliable markers to distinguish different species while they cannot distinguish different strains of most bacterial species. Our study shed new light on the usage and limitations of USCGs, which will facilitate their applications in evolutionary, phylogenomic, and metagenomic studies.

bioinformatics↗

bioRxiv2022

Profiling the size-dependent heterogeneity of membrane proteins in a mixed population of small extracellular vesicle for potential cancer diagnosis

The heterogeneity in small extracellular vesicles (small EVs) introduces an extra level of complexity in small EV-based liquid biopsy for cancer diagnosis. Heterogeneous membrane protein expression is correlated with sizes of small EVs, but accessing this correlative information is limited by the precise isolation of size-dependent subpopulations. Herein, we present a single EV enumeration (SEVEN) approach to profile protein heterogeneity in size-dependent subpopulations, and demonstrate its potential in improving the accuracy of cancer diagnosis. The interferometric plasmonic microscopy (iPM) capable of imaging single biological nanoparticles with the diameter down to 30 nm is employed to detect small EVs at the single-particle level. Small EVs population with mixed sizes are directly imaged, individually sized and digitally counted during their binding onto different aptamer-coated iPM sensor surfaces. The protein expression levels and binding kinetics of three size-dependent subpopulations are analyzed, forming a multidimensional data matrix for cancer diagnosis. Using small EVs derived from different cancer cell lines, highly heterogeneous protein profiles are recorded in the three subpopulations. We further demonstrate that the cancer classification accuracy could be greatly improved by including the subpopulation level heterogeneous protein profiles as compared with conventional ensemble measurement.

biochemistry↗

bioRxiv2022

A Systematic Evaluation of the Computational Tools for Ligand-receptor-based Cell-Cell Interaction Inference

Cell-cell interactions (CCIs) are essential for multicellular organisms to coordinate biological processes and functions. Many molecules and signaling processes can mediate CCIs. One classical type of CCI mediator is the interaction between secreted ligands and cell surface receptors, i.e., ligand-receptor (LR) interaction. With the recent development of single-cell technologies, a large amount of single-cell RNA Sequencing (scRNA-Seq) data has become widely available. This data availability motivated the single-cell-resolution study of CCIs, particularly LR-based CCIs. Dozens of computational methods and tools have been developed to predict CCIs by identifying LR-based CCIs. Many of these tools have been theoretically reviewed. However, there is little study on current LR-based CCI prediction tools regarding their performance and running results on public scRNA-Seq datasets. In this work, to fill this gap, we tested and compared nine of the most recent computational tools for LR-based CCI prediction. We used fifteen mouse scRNA-Seq samples that correspond to nearly 100K single cells under different experimental conditions for testing and comparison. Besides briefing the methodology used in these nine tools, we summarized the similarities and differences of these tools in terms of both LR prediction and CCI inference between cell types. We provided insight into using these tools to make meaningful discoveries in understanding cell communications.

bioinformatics↗

bioRxiv2022

Single-cell multimodal modeling with deep parametric inference

The paired measurement of multiple modalities, known as the multimodal analysis, is an exciting frontier for connecting single-cell genomics with epitopes and functions. Mapping of transcriptomes in single-cells and the integration with cell phenotypes enable a better understanding of cellular states. However, assembling these paired omics into a unified representation of the cellular state remains challenging with the unique technical characteristics of each measurement. In this study, we built a deep parameter inference model (DPI) based on the properties of single-cell multimodal data. DPI is a complete single-cell multimodal omics analysis framework, which has built in multimodal data preprocessing, multimodal data integration, multimodal data reconstruction, reference and query, disturbance prediction and other analysis functions.

bioinformatics↗

bioRxiv2022

A computational modeling of primary-microRNA expression

MicroRNAs (miRNAs) play crucial roles in gene regulation. Most studies so far focus on mature miRNAs, which leaves many gaps in our knowledge in primary miRNAs (pri-miRNA). To fill these gaps, we attempted to model the expression of pri-miRNAs in 1829 primary cell types and tissues in this study. We demonstrated that the expression of their associated mRNAs could model the expression of the pri-miRNAs well. These associated mRNAs are different from their corresponding target mRNAs and are enriched with specific functions. The majority of the associated mRNAs of a miRNA are shared across conditions, although a fraction of the associated mRNAs are condition-specific. Our study shed new light on the understanding of miRNA biogenesis and general gene transcriptional regulation.

bioinformatics↗

bioRxiv2022

A Deep Learning Method for MiRNA/IsomiR Target Detection

MotivationAccurate identification of microRNA (miRNA) targets at base-pair resolution has been an open problem for over a decade. The recent discovery of miRNA isoforms (isomiRs) adds more complexity to this problem. Despite the existence of many methods, none considers isomiRs, and their performance is still suboptimal. We hypothesize that by taking the isomiR-mRNA interaction into account and applying a deep learning model to study miRNA-mRNA interaction features, we may improve the accuracy of miRNA target predictions. ResultsWe developed a deep learning tool called DMISO to capture the intricate features of miRNA/isomiR-mRNA interactions. Based on 10-fold cross-validation, DMISO showed high precision (95%) and recall (90%). Evaluated on three independent datasets, DMISO had superior performance to five tools, including three popular conventional tools and two recently developed deep learning-based tools. By applying two popular feature interpretation strategies, we demonstrated the importance of the miRNA regions other than their seeds and the potential contribution of the RNA-binding motifs within miRNAs/isomiRs and mRNAs to the miRNA/isomiR-mRNA interactions. AvailabilityThe source code and tool are available at http://hulab.ucf.edu/research/projects/DMISO. Contacthaihu@cs.ucf.edu, xiaoman@mail.ucf.edu Supplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2022

Identification of C270 as a novel site for allosteric modulators of SARS-CoV-2 papain-like protease

The papain-like protease (PLpro) in coronavirus is one of key cysteine proteases responsible for the proteolytic processing of viral polyproteins, and plays an important role in dysregulation of host immune response. PLpro is a promising therapeutic target with a major challenge in inhibitor design due to the restricted S1/S2 sites for two consecutive glycine of substrates. Here we reported the discovery of two activators of the SARS-CoV-2 PLpro from a biochemical screening, and the identification of the unique residue, C270, as an allosteric and covalent regulation site for the activators. This site was also specifically modified by glutathione oxidized, resulting in the S-glutathionylation and activation of the protease. Furthermore, one compound was found to allosterically inhibit the protease by covalent binding to this crucial site. Together, these results elucidated an unrevealed molecular mechanism for allosteric modulation of the proteases activity, and provided a new strategy for discovery of allosteric inhibitors of the SARS-CoV-2 PLpro.

molecular biology↗

bioRxiv2022

LOXL2-dependent deacetylation of aldolase A induces metabolic reprogramming and tumor progression

Lysyl-oxidase like-2 (LOXL2) regulates extracellular matrix remodeling and promotes tumor invasion and metastasis. Altered metabolism is a core hallmark of cancer, however, it remains unclear whether and how LOXL2 contributes to tumor metabolism. Here, we found that LOXL2 and its catalytically inactive L2{Delta}13 splice variant also function as novel deacetylases that trigger metabolic reprogramming during malignant transformation. Integrated transcriptomic and metabolomic analysis revealed that L2{Delta}13-overexpressing transgenic mice displayed perturbed glucose and lipid metabolism, which was associated with increased hepatic fibrosis and enhanced formation of precancerous lesions induced by chemical carcinogens, such as carbon tetrachloride and N-nitrosomethylbenzylamine. Furthermore, both LOXL2 and L2{Delta}13 boosted glucose metabolism of esophageal tumor cells, thereby facilitating tumor cell proliferation in vitro and in vivo. Mechanistically, LOXL2 and L2{Delta}13 interacted physically with several glycolic proteins including aldolase A to enhance their enzymatic activities and mobilization from the actin cytoskeleton. Using SILAC followed by proteomic analysis, we identified LOXL2 as a deacetylase targeting metabolic proteins in esophageal cancer. Importantly, both LOXL2 and L2{Delta}13 directly catalyzed the deacetylation of aldolase A at K13, resulting in enhanced glycolysis which subsequently reprogramed tumor metabolism and promoted tumor progression. High level expression of LOXL2/L2{Delta}13 combined with decreased acetylation of aldolase-K13 predicted poor clinical outcome in patients with esophageal cancer. In summary, we have characterized a novel molecular mechanism that mediates the pro-tumorigenic activity of LOXL2 independently of its classical amine oxidase activity. These findings may enable the future development of therapeutic agents targeting the metabolic machinery via LOXL2 or L2{Delta}13.

cell biology↗

bioRxiv2022

Earliest evidence for frugivory and seed dispersal by birds

The Early Cretaceous diversification of birds was a major event in the history of terrestrial ecosystems, occurring during the earliest phase of the Cretaceous Terrestrial Revolution. Frugivorous birds play an important role in seed dispersal today, and may have done so since their origins. However, evidence of this has been lacking. Jeholornis is one of the earliest-diverging birds, only slightly more derived than Archaeopteryx, but its cranial anatomy has been poorly understood, obscuring diet-related functional interpretations. Originally hypothesised to be granivorous based on seeds preserved as gut contents, this interpretation has become controversial. We conducted high-resolution synchrotron tomography on an exquisitely preserved new skull of Jeholornis, revealing remarkable cranial plesiomorphies combined with a specialised rostrum. We use this to provide a near-complete cranial reconstruction of Jeholornis, and exclude the possibility that Jeholornis was granivorous, based on morphometric analyses of the mandible (3D) and cranium (2D), and comparisons with the 3D alimentary contents of extant birds. We show that Jeholornis was at least seasonally frugivorous, providing the earliest evidence for fruit consumption in birds, and indicating that seed dispersal was present from early in the avian radiation. As highly-mobile seed dispersers, early frugivorous birds could expand the scope for biotic dispersal in plants, and may explain, in part, the subsequent evolutionary expansion of fruits, indicating a potential role of bird-plant interactions in the Cretaceous Terrestrial Revolution.

paleontology↗

bioRxiv2022

Structural basis for receptor selectivity and inverse agonism in S1P5 receptors

The bioactive lysophospholipid sphingosine-1-phosphate (S1P) acts via five different subtypes of S1P receptors (S1PR) - S1P1-5. S1P5 is predominantly expressed in nervous and immune systems, regulating the egress of natural killer cells from lymph nodes and playing a role in immune and neurodegenerative disorders, as well as carcinogenesis. Several S1PR therapeutic drugs have been developed to treat these diseases; however, they lack receptor subtype selectivity, which leads to side effects. In this article, we describe a 2.2 [A] resolution room temperature crystal structure of the human S1P5 receptor in complex with a selective inverse agonist determined by serial femtosecond crystallography (SFX) at the Pohang Accelerator Laboratory X-Ray Free Electron Laser (PAL-XFEL) and analyze its structure-activity relationship data. The structure demonstrates a unique ligand-binding mode, involving an allosteric subpocket, which clarifies the receptor subtype selectivity and provides a template for structure-based drug design. Together with previously published S1PR structures in complex with antagonists and agonists, the new S1P5-inverse agonist structure sheds light on the activation mechanism and reveals structural determinants of the inverse agonism in the S1PR-family.

biophysics↗

bioRxiv2022

Wheat Panache - a pangenome graph database representing presence/absence variation across 16 bread wheat genomes

Bread wheat is one of humanitys most important staple crops, characterized by a large and complex genome with a high level of gene presence/absence variation between cultivars, hampering genomic approaches for crop improvement. With the growing global population and the increasing impact of climate change on crop yield, there is an urgent need to apply genomic approaches to accelerate wheat breeding. With recent advances in DNA sequencing technology, a growing number of high-quality reference genomes are becoming available, reflecting the genetic content of a diverse range of cultivars. However, information on the presence or absence of genomic regions has been hard to visualize and interrogate due to the size of these genomes and the lack of suitable bioinformatics tools. To address this limitation, we have produced a wheat pangenome graph maintained within an online database to facilitate interrogation and comparison of wheat cultivar genomes. The database allows users to visualize regions of the pangenome to assess presence/absence variation between bread wheat genomes. Database URL: http://www.appliedbioinformatics.com.au/wheat_panache

bioinformatics↗

bioRxiv2022

A novel intranasal administration adenoviral vector-based platform for rapid COVID-19 vaccine development

The coronavirus SARS-CoV-2 has a severe impact on global public health, and the emerging variants threaten the efficacy of the circulating vaccines. Here, we report that a single vaccination with a non-replicating chimpanzee adenovirus-based vaccine against the SARS-CoV-2 Delta variant (JS1-delta) elicits potent humoral, cellular and mucosal immunity in mice. Additionally, a single intranasal administration of JS1-delta provides effective protection against the Delta (B.1.617.2) variant challenge in mice. This study indicates that chimpanzee adenovirus type 3 (ChAd3) derived vector represents a promising platform for antiviral vaccine development against respiratory infections and JS1-delta is worth further investigation in human clinical trials. HighlightsO_LIA new chimpanzee adenoviral vaccine against the SARS-CoV-2 Delta variant was developed. C_LIO_LIThe vaccine elicited potent humoral, cellular and mucosal immunity in mice. C_LIO_LIThe vaccine protected mice from the Delta variant challenge. C_LI

immunology↗

bioRxiv2022

StrainPanDA: linked reconstruction of strain composition and gene content profiles via pangenome-based decomposition of metagenomic data

BackgroundMicrobial strains of variable functional capacities co-exist in microbiomes. Current bioinformatics methods of strain analysis cannot provide the direct linkage between strain composition and their gene contents from metagenomic data. MethodsHere we present StrainPanDA (Strain-level Pangenome Decomposition Analysis), a novel method that uses the pangenome coverage profile of multiple metagenomic samples to simultaneously reconstruct the composition and gene content variation of co-existing strains in microbial communities. ResultsWe systematically validate the accuracy and robustness of StrainPanDA using synthetic datasets. To demonstrate the power of gene-centric strain profiling, we then apply StrainPanDA to analyze the gut microbiome samples of infants, as well as patients treated with fecal microbiota transplantation. We show that the linked reconstruction of strain composition and gene content profiles is critical for understanding the relationship between microbial adaptation and strain-specific functions (e.g., nutrient utilization, pathogenicity). ConclusionsStrainPanDA can be applied to metagenomic datasets to detect association between molecular functions and microbial/host phenotypes to formulate testable hypotheses and gain novel biological insights at the strain or subspecies level.

bioinformatics↗