Biology subjects

Zhang, C.

Publications and source records attributed to Zhang, C..

At least 793 records · Page 44Linked to original sources

bioRxiv2021

Evaluation of different concentrations antibiotics on gut bacteria and growth of Ectropis obliquaProut (Lepidoptera: Geometridae)

The use of antibiotics to remove gut bacteria is a commonly used method to study gut function of insects. We assessed the impact of the artificial diet made from tea powder with different concentrations of antibiotics mixture (containing tetracycline, gentamicin, penicillin, and rifampicin) on Ectropis obliqua Prout (Lepidoptera: Geometridae) survival, growth, and reproduction. Antibiotic-induced bacterial clearance was monitored by Polymerase Chain Reaction (PCR) and by Colony-counting Methods. The results indicated that administration of the antibiotic mixture at a concentration of 200g/ml caused the increase of gut bacteria, while a concentration of 300g/ml was more effective in clearing gut bacteria but the concentration of 400g/ml caused a large number of larval deaths. The concentration of 300g/ml had no significant effect on the growth and development of E. obliqua, but had impact on fecundity. Therefore, we could use 300g/ml concentrations of the antibiotic mixture to obtain sterile E. obliqua to study the function of intestinal microbes.

animal behavior and cognition↗

bioRxiv2021

Altered O-glycosylation Level of SARS-CoV-2 Spike Protein by Host O-glycosyltransferase Strengthens Its Trimeric Structure

The trimeric spike protein (S) mediates host-cell entry and membrane fusion of SARS-CoV-2. S protein is highly glycosylated, whereas its O-glycosylation is still poorly understood. Herein, we site-specifically examine the O-glycosylation of S protein through a mass spectrometric approach with HCD-triggered-ETD model. We identify 15 high-confidence O-glycosites and at least 10 distinct O-glycan structures on S protein. Peptide microarray assays prove that human ppGalNAc-T6 actively participates in O-glycosylation of S protein. Importantly, the upregulation of ppGalNAc-T6 expression can profoundly enhance the O-glycosylation level by generating new O-glycosites and increasing both O-glycan heterogeneity and intensities. Further molecular dynamics simulations reveal that the O-glycosylation on the protomer-interface regions, which are mainly modified by ppGalNAc-T6, can potentially stabilize the trimeric S protein structure. Our work provides deep molecular insights of how viral infection harnesses the host O-glycosyltransferases to dynamically regulate the O-glycosylation level of the viral envelope protein responsible for membrane fusion.

biochemistry↗

bioRxiv2021

CDCA-seq resolve the different chromatin structure on integral circular DNAs

Although extrachromosomal DNA (ecDNA) has been intensively studied for several decades, the mechanisms underlying its tumorigenic effects have been revealed only recently. In the majority of conventional sequencing studies, the high-throughput short-read sequencing largely ignores the epigenetic status of most ecDNA regions except for the junctional areas. Here, we developed the sequencing of enzyme-accessible chromatin in circular DNA (CCDA-seq) method, which uses methylase to label open chromatin without fragmentation and exonuclease to enrich the ecDNA sequencing depth, followed by long-read nanopore sequencing. Using CCDA-seq, we observed significantly different patterns in nucleosome/regulator binding in ecDNA at a single-molecule resolution. These results deepen the understanding of ecDNA regulatory mechanisms.

genomics↗

bioRxiv2021

Identification of regulatory networks associated with anti-HIV/AIDS genes via integrated transcriptome, epigenome and proteome analyses

There are individuals naturally resistant to HIV. To identify anti-HIV genes and regulatory networks that enable the native ability to resist HIV, we reanalyzed the transcriptome of HIV resistant and susceptible individuals based on previous efforts, and performed regulatory network prediction using HIV-infection related DNA methylation, miRNA and Chip-SEQ data. We totally found 25 potential anti-HIV genes and 23 of them are newly identified. They are enriched in pathways of immunity, neurological system and cell signaling. 4 anti-HIV genes show DNA hypermethylation signatures and 4 are possibly bounded by the HIV-1 Trans-Activator of Transcription protein (Tat). We found a potential HIV-resistance correlated miRNA hsa-miR-3074-5p possibly regulating an anti-HIV hub gene JUN. Our findings provide novel insights for AIDS treatments and approaches to HIV vaccine design.

bioinformatics↗

bioRxiv2021

Information-Efficient, Off-Center Sampling Results in Improved Precision in 3D Single Particle Tracking Microscopy

In this work, we present a 3D single-particle tracking system that can apply tailored sampling patterns to selectively extract photons that yield the most information for particle localization. We demonstrate that off-center sampling at locations predicted by Fisher information utilizes photons most efficiently. When performing localization in a single dimension, optimized off-center sampling patterns gave doubled precision compared to uniform sampling. A ~20% increase in precision compared to uniform sampling can be achieved when a similar off-center pattern is used in 3D localization. Here we systematically investigated the photon efficiency of different emission patterns in a diffraction-limited system and achieved higher precision than uniform sampling. The ability to maximize information from the limited number of photons demonstrated here is critical for particle tracking applications in biological samples, where photons may be limited.

biophysics↗

bioRxiv2021

Structural insights into hormone recognition by the human glucose-dependent insulinotropic polypeptide receptor

Glucose-dependent insulinotropic polypeptide (GIP) is a peptide hormone that exerts crucial metabolic functions by binding and activating its cognate receptor, GIPR. As an important therapeutic target, GIPR has been subjected to intensive structural studies without success. Here, we report the cryo-EM structure of the human GIPR in complex with GIP and a Gs heterotrimer at a global resolution of 2.9 [A]. GIP adopts a single straight helix with its N terminus dipped into the receptor transmembrane domain (TMD), while the C-terminus is closely associated with the extracellular domain and extracellular loop 1. GIPR employs conserved residues in the lower half of the TMD pocket to recognize the common segments shared by GIP homologous peptides, while uses non-conserved residues in the upper half of the TMD pocket to interact with residues specific for GIP. These results provide a structural framework of hormone recognition and GIPR activation.

molecular biology↗

bioRxiv2021

BEdeepoff: an in silico tool for off-target prediction of ABE and CBE base editors

Base editors, including adenine base editors (ABEs) and cytosine base editors (CBEs), are valuable tools for introducing point mutations, but they frequently induce unwanted off-target mutations. Here, we performed a high-throughput gRNA-target library screening to measure editing efficiencies at integrated genomic off-targets and obtained datasets of 48,632 and 52,429 off-targets for ABE and CBE, respectively. We used the datasets to train deep learning models, resulting in ABEdeepoff and CBEdeepoff which can predict editing efficiencies at off-targets. These tools are freely accessible via online web server http://www.deephf.com/#/bedeep.

bioinformatics↗

bioRxiv2021

BEdeepon: an in silico tool for prediction of base editor efficiencies and outcomes

Base editors enable direct conversion of one target base into another in a programmable manner, but conversion efficiencies vary dramatically among different targets. Here, we performed a high-throughput gRNA-target library screening to measure conversion efficiencies and outcome product frequencies at integrated genomic targets and obtained datasets of 60,615 and 73,303 targets for ABE and CBE, respectively. We used the datasets to train deep learning models, resulting in ABEdeepon and CBEdeepon which can predict on-target efficiencies and outcome sequence frequencies. The software is freely accessible via online web server http://www.deephf.com/#/bedeep/bedeepon.

bioinformatics↗

bioRxiv2021

Permissive epigenetic landscape facilitates distinct transcriptional signatures of activating transcription factor 6 in the liver

Proteostatic stress initiates a transcriptional response that is unique to the stress condition, yet the regulatory mechanisms underlying the distinct gene expression patterns observed in stressed cells remains unknown. Using a functional genomic approach, we investigated how activating transcription factor 6 (ATF6), a key transcription factor in the unfolded protein response (UPR), regulates target genes. We first designed a computational strategy to define Atf6 target genes based on the evolutionary conservation of predicted ATF6 binding in gene promoters, identifying 652 conserved putative Atf6 target (CPAT) genes. CPATs were overrepresented for genes functioning in the UPR, however, the majority functioned in cellular processes unrelated to proteostasis, including small molecule metabolism and development. Functional studies of stress-independent and toxicant based Atf6 activation in zebrafish livers showed that the pattern of CPAT expression in response to Atf6 overexpression, alcohol and arsenic was unique. Only 34 CPATs were differentially expressed in all conditions, indicating that Atf6 is sufficient to regulate a small subset of CPATs. Blocking Atf6 using Ceapins in zebrafish demonstrated that Atf6 is necessary for activation of these genes in response to arsenic. We investigated CPAT during physiologically mediated hepatocyte stress using liver regeneration in mice as a model. Over half of all CPATs were differentially expressed during this process. This was attributed to the permissive chromatin environment in quiescent livers on the promoters of these genes, characterized by the absence of H3K27me3 and enrichment of H3K4me3. Taken together, these data uncover a complex transcriptional response to Atf6 activation and implicate a permissive epigenome as a mechanism by which distinct transcriptional responses are regulated by Atf6.

genomics↗

bioRxiv2021

Potent neutralizing nanobodies resist convergent circulating variants of SARS-CoV-2 by targeting novel and conserved epitopes

There is an urgent need to develop effective interventions resistant to the evolving variants of SARS-CoV-2. Nanobodies (Nbs) are stable and cost-effective agents that can be delivered by novel aerosolization route to treat SARS-CoV-2 infections efficiently. However, it remains unknown if they possess broadly neutralizing activities against the prevalent circulating strains. We found that potent neutralizing Nbs are highly resistant to the convergent variants of concern that evade a large panel of neutralizing antibodies (Abs) and significantly reduce the activities of convalescent or vaccine-elicited sera. Subsequent determination of 9 high-resolution structures involving 6 potent neutralizing Nbs by cryoelectron microscopy reveals conserved and novel epitopes on virus spike inaccessible to Abs. Systematic structural comparison of neutralizing Abs and Nbs provides critical insights into how Nbs uniquely target the spike to achieve high-affinity and broadly neutralizing activity against the evolving virus. Our study will inform the rational design of novel pan-coronavirus vaccines and therapeutics.

biophysics↗

bioRxiv2021

A Biosensor for Detection of Indole Metabolites

The lack of diverse health-related biosensors limits the progress towards our understanding of how the microbiome metabolism impacts health. Microbially produced indole-3-aldehyde (I3A) has been associated with reducing inflammation in diseases such as ulcerative colitis by stimulating the aryl hydrocarbon receptor (AhR) pathway. We mined the protein database for gut microbiome metabolites sensors and developed a biosensor for I3A. We engineered E. coli embedded with a single plasmid carrying a chimeric two-component system that detects I3A. Our I3A receptor characterization identified residues that contribute to the sensors high specificity in a range of 0.1-10 {micro}M. The I3A biosensor opens the door to sensing indole metabolites produced at the host-microbe interface and provides new parts for synthetic biology applications.

synthetic biology↗

bioRxiv2021

Mako: a graph-based pattern growth approach to detect complex structural variants

Complex structural variants (CSVs) are genomic alterations that have more than two breakpoints and are considered as simultaneous occurrence of simple structural variants. However, detecting the compounded mutational signals of CSVs is challenging through a commonly used model-match strategy. As a result, there has been limited progress for CSV discovery compared with simple structural variants. We systematically analyzed the multi-breakpoint connection feature of CSVs, and proposed Mako, utilizing a bottom-up guided model-free strategy, to detect CSVs from paired-end short-read sequencing. Specifically, we implemented a graph-based pattern growth approach, where the graph depicts potential breakpoint connections and pattern growth enables CSV detection without predefined models. Comprehensive evaluations on both simulated and real datasets revealed that Mako outperformed other algorithms. Notably, validation rates of CSV on real data based on experimental and computational validations as well as manual inspections are around 70%, where the medians of experimental and computational breakpoint shift are 13bp and 26bp, respectively. Moreover, Mako CSV subgraph effectively characterized the breakpoint connections of a CSV event and uncovered a total of 15 CSV types, including two novel types of adjacent segments swap and tandem dispersed duplication. Further analysis of these CSVs also revealed impact of sequence homology in the formation of CSVs. Mako is publicly available at https://github.com/jiadong324/Mako.

bioinformatics↗

bioRxiv2021

Multidimensional molecular differences between artificial and wild Artemisia rupestris L.

Different ecological environments affect the active ingredients and molecular content of medicinal plants. Artemisia rupestris L. is a kind of traditional medicinal plant, and the shortages of the wild resource have led to increased use of artificial varieties. However, there have few investigations referring to molecular differences between them in a systematic manner. In the present study, artificial and wild Artemisia rupestris L. plants were collected in the Altay-Fuyun region, Xinjian, China. Untargeted metabolomics method based on liquid chromatography-mass spectrometry (LC-MS) technology was applied to profile flower, stem, and leaf samples, respectively, and levels of a panel of representative known metabolites in this plant were simultaneously analyzed. The genetic basis of these samples was explored using a de novo transcriptomics approach to investigate differentially expressed genes (DEGs) and their pathway annotations. Results indicated metabolic differences between the two varieties mainly reflected in flavonoids and chlorogenic acid/caffeic acid derivatives. 34 chemical markers (CMs) belonging to these two structural categories were discovered after validation using another batch of samples, including 19 potentially new compounds. After correlation analysis, total of six DEGs in different organs relating to 24 CMs were confirmed using quantitative real-time PCR (qPCR). These findings provided novel insight into the molecular landscape of this medicinal plant through metabolomics-transcriptomics integration strategy, and reference information of its quality control and species identification. ONE SENTENCE SUMMARYA metabolomics-transcriptomics research on Artemisia rupestris L. to discover metabolite differences and the genetic basis between artificial and wild varieties in systematic and novel manner.

systems biology↗

bioRxiv2021

Computational analysis of vertebrate myoglobins reveals aggregation resistance in aquatic birds and higher surface hydrophobicity in fish

Myoglobin is the major oxygen carrying protein of vertebrate muscle, and high myoglobin net charge is known to hold evolutionary significance as a molecular signature of secondarily aquatic diving capacity in mammals. However, the evolution of myoglobins electrostatic properties in non-mammalian vertebrates, such as birds, has not been investigated. Here, we used a new deep learning-based protein folding algorithm to model the tertiary structures of myoglobin from 302 vertebrate species and performed a comparative analysis of their net charge, positively charged solvent-accessible surface area, and negatively charged solvent-accessible surface area. For avian myoglobins, we also calculated selection pressure ({omega}). The results suggest that the myoglobins of diving avians, specifically those of the penguins (Sphenisciformes) and diving ducks (Aythyini), have highly positively charged electrostatic surfaces, which evolved via positive selection to reduce aggregation propensity and allow greater storage of oxygen for extended underwater foraging. In contrast, galliform myoglobins are under high purifying selection. Distribution of charged atoms on myoglobin surface was more indicative of high myoglobin content than net charge. We also found inter-class differences in net charge; bird myoglobins are the most positively charged and reptile and amphibian myoglobins are the most negatively charged, and net charge seems to be negatively associated with herbivory within mammals. Finally, we propose an equation that describes the relationship between myoglobin net charge and concentration better than the previously suggested logarithmic function. Our findings offer novel insights into the diversification of myoglobin in vertebrate clades and highlight the power of computational structural approaches for zoological and evolutionary research.

bioinformatics↗

bioRxiv2021

Withaferin A promotes white adipose browning and prevents obesity through sympathetic nerve-activated Prdm16-FATP1 axis

The increasing prevalence of obesity has resulted in demands for the development of new effective strategies for obesity treatment. The Withaferin A (WA) shows a great potential for prevention of obesity by sensitizing leptin signaling in the hypothalamus. However, the mechanism underlying the weight- and adiposity-reducing effects of WA remains to be elucidated. Here, we report that WA treatment induced white adipose tissue (WAT) browning, elevated energy expenditure (EE), decreased respiratory exchange ratio (RER), and prevented high-fat diet (HFD)-induced obesity. The sympathetic chemical denervation dampened the WAT browning and also impeded the reduction of adiposity in WA-treated mice. WA markedly up-regulated the levels of Prdm16 and FATP1 (Slc27a1) in the inguinal WAT (iWAT), and this was blocked by sympathetic denervation. Prdm16 or FATP1 knockdown in iWAT abrogated the WAT browning-inducing effects of WA, and restored the weight gain and the adiposity in WA-treated mice. Together, these findings suggest that WA induces WAT browning through the sympathetic nerve-adipose axis; and the adipocytic Prdm16-FATP1 pathway mediates the promotive effects of WA on white adipose browning.

physiology↗

bioRxiv2021

Single-cell sequencing characterizes intratumoral profile of immune cells in old mice

It has long been thought that aging is a major risk factor for cancer incidence. However, accumulating evidence indicates increased resistance of old animals to tumor growth. A systematic understanding of how old individuals defend against tumor invasion is currently lacking. Here we investigated the differences of age-associated alterations in tumor-infiltrating immune cells between young and old mice using single-cell RNA analysis. Our results showed that a higher proportion of cytotoxic CD8+ T cells, nTregs, cDC, and M1-type macrophages, while a higher percentage of exhausted CD8+ T cells, iTregs, pDC, and M2-type macrophages were found in young mice. Importantly, TCR diversity analysis showed top 10 TCR clones consisted primarily of exhausted CD8+ T cells in young mice whereas tip clones were predominantly cytotoxic CD8+ T cells in old mice. Consistently, trajectory inference demonstrated that CD8+ T cells preferentially differentiated into cytotoxic cells in old mice in contrast to exhausted cells in young mice. Meanwhile, we confirmed the main distinctions between young and old mice by flow cytometry. Collectively, our data revealed that a significantly higher proportion of effector immune cells in old mice defend against tumor progression, providing a framework for the immunotherapy of elderly patients with tumors.

immunology↗

bioRxiv2021

Combined Metabolic Activators decrease liver steatosis by activating mitochondrial metabolism in a Golden Syrian hamster study

The prevalence of non-alcohol fatty liver disease (NAFLD), defined as the livers excessive fat accumulation, continues to increase dramatically. We have recently revealed the molecular mechanism underlying NAFLD using in-depth multi-omics profiling and identified that combined metabolic activators (CMA) could be administered to decrease the amount of hepatic steatosis (HS) in mouse model and NAFLD patients based on systems analysis. Here, we investigated the effects of a CMA including L-carnitine, N-acetyl-l-cysteine, nicotinamide riboside and betaine on a Golden Syrian hamster NAFLD model fed with HFD, and found that HS was decreased with the administration of CMA. To explore the mechanisms involved in the clearance HS, we generated liver transcriptomics data before and after CMA administration, and integrated these data using liver-specific genome-scale metabolic model of liver tissue. We systemically determined the molecular changes after the supplementation of CMAs and found that it activates mitochondria in the liver tissue by modulating the global fatty acid, amino acids, antioxidant and folate metabolism.

systems biology↗

bioRxiv2021

Jumper Enables Discontinuous Transcript Assembly in Coronaviruses

Genes in SARS-CoV-2 and, more generally, in viruses in the order of Nidovirales are expressed by a process of discontinuous transcription mediated by the viral RNA-dependent RNA polymerase. This process is distinct from alternative splicing in eukaryotes, rendering current transcript assembly methods unsuitable to Nidovirales sequencing samples. Here, we introduce the DO_SCPLOWISCONTINUOUSC_SCPLOW TO_SCPLOWRANSCRIPTC_SCPLOW AO_SCPLOWSSEMBLYC_SCPLOW problem of finding transcripts [Formula] and their abundances c given an alignment [Formula] under a maximum likelihood model that accounts for varying transcript lengths. Underpinning our approach is the concept of a segment graph, a directed acyclic graph that, distinct from the splice graph used to characterize alternative splicing, has a unique Hamiltonian path. We provide a compact characterization of solutions as subsets of non-overlapping edges in this graph, enabling the formulation of an efficient mixed integer linear program. We show using simulations that our method, JO_SCPLOWUMPERC_SCPLOW, drastically outperforms existing methods for classical transcript assembly. On short-read data of SARS-CoV-1 and SARS-CoV-2 samples, we find that JO_SCPLOWUMPERC_SCPLOW not only identifies canonical transcripts that are part of the reference transcriptome, but also predicts expression of non-canonical transcripts that are well supported by direct evidence from long-read data, presence in multiple, independent samples or a conserved core sequence. JO_SCPLOWUMPERC_SCPLOW enables detailed analyses of Nidovirales transcriptomes. Code availabilitySoftware is available at https://github.com/elkebir-group/Jumper

bioinformatics↗