Biology subjects

Jia, C.

Publications and source records attributed to Jia, C..

48 records · Page 3Linked to original sources

bioRxiv2021

Multiomics Interrogation into HBV (Hepatitis B Virus)-Host Interaction Reveals Novel Coding potential in Human Genome, and Identifies Canonical and Non-canonical Proteins as Host Restriction Factors against HBV

Hepatitis B Virus constitutes a major threat to global public health. Current understanding of HBV-host interaction is yet limited. Here, ribosome profiling, quantitative mass spectrometry and RNA-sequencing are conducted on a recently established HBV replication system. We have identified multiomic DEGs (differentially expressed genes) that HBV orchestrated to remodel host proteostasis networks. Our multiomics interrogation revealed that HBV induced significant changes in both transcription and translation of 35 canonical genes including PPP1R15A, PGAM5 and SIRT6, as well as the expression of at least 15 non-canonical ORFs including ncPON2 and ncGRWD1, thus revealing an extra coding potential of human genome. Overexpression of these five genes but not the enzymatically deficient SIRT6 mutants suppressed HBV replication while knockdown SIRT6 had opposite effect. Furthermore, the expression of SIRT6 was down-regulated in patients, cells or animal models of HBV infection. Mechanistic study further indicated that SIRT6 directly binds to mini-chromosome and deacetylates histone H3 lysine 9 (H3K9ac) and histone H3 lysine 56 (H3K56ac), and chemical activation of endogenous SIRT6 with MDL800 suppressed HBV infection in vitro and in vivo. By generating the first multiomics landscape of host-HBV interaction, our work is thus opening a new avenue to facilitate therapeutic development against HBV infection.

microbiology↗

bioRxiv2021

Mechanistic insights into the success of xenobiotic degraders resolved from metagenomes of microbial enrichment cultures

Even though microbial communities can be more effective at degrading xenobiotics than cultured micro-organisms, yet little is known about the microbial strategies that underpin xenobiotic biodegradation by microbial communities. Here, we employ metagenomic community sequencing to explore the mechanisms that drive the development of 49 xenobiotic-degrading microbial communities, which were enriched from 7 contaminated soils or sediments with a range of xenobiotic compounds. We show that multiple microbial strategies likely drive the development of xenobiotic degrading communities, notably (i) presence of genes encoding catabolic enzymes to degrade xenobiotics; (ii) presence of genes encoding efflux pumps; (iii) auxiliary catabolic genes on plasmids; and (iv) positive interactions dominate microbial communities with efficient degradation. Overall, the integrated analyses of microbial ecological strategies advance our understanding of microbial processes driving the biodegradation of xenobiotics and promote the design of bioremediation systems.

microbiology↗

bioRxiv2021

Brassinosteroid signaling component SlBES1 promotes tomato fruit softening through transcriptional repression of PMEU1

Firmness is one of the most important factors that affect postharvest properties of tomato fruit. However, the regulatory mechanism underlying firmness formation in tomato fruit is poorly understood. Here, we report a novel role of SlBES1, a transcriptional factor (TF) mediating brassinosteroid (BR) signaling, in tomato fruit softening. We first found that SlBES1 promotes fruit softening during tomato fruit ripening and postharvest storage. RNA-seq analysis suggested that PMEU1, which encodes a pectin de-methylesterification protein, might participate in SlBES1-mediated fruit softening. Biochemical and immunofluorescence assays in SlBES1 transgenic fruits indicated that SlBES1 inhibited PMEU1-related pectin de-methylesterification. Further molecular and genetic evidence verified that SlBES1 directly binds to the E-box in the promoter of PMEU1 to repress its expression, leading to the softening of the tomato fruits. Loss-of-function SlBES1 mutant generated by CRISPR/cas9 showed firmer fruits and longer shelf life during postharvest storage without the color, size and nutritional quality alteration. Collectively, our results indicated the potential of manipulating SlBES1 to regulate fruit firmness via transcriptional inhibition of PMEU1 without negative consequence on visual and nutrition quality.

plant biology↗

bioRxiv2020

Cell size distribution of lineage data: analytic results and parameter inference

Recent advances in single-cell technologies have enabled time-resolved measurements of the cell size over several cell cycles. This data encodes information on how cells correct size aberrations so that they do not grow abnormally large or small. Here we formulate a piecewise deterministic Markov model describing the evolution of the cell size over many generations, for all three cell size homeostasis strategies (timer, sizer, and adder). The model is solved to obtain an analytical expression for the non-Gaussian cell size distribution in a cell lineage; the theory is used to understand how the shape of the distribution is influenced by the parameters controlling the dynamics of the cell cycle and by the choice of cell tracking protocol. The theoretical cell size distribution is found to provide an excellent match to the experimental cell size distribution of E. coli lineage data collected under various growth conditions.

systems biology↗

bioRxiv2020

Adsorption mechanism of bacteria onto a Na-montmorillonite surface with organic and inorganic calcium

The adsorption of bacteria onto the Na-montmorillonite (Na-MMT) was studied as a function of time, bacterial concentration, temperature and pH with the introduction of the organic and inorganic calcium sources. The results indicated that albeit revealing the same adsorption mechanism, the organic calcium (i.e., Ca(CH3COO)2) proposed in this study is more beneficial and environmentally friendly than the inorganic calcium (i.e., CaCl2) in terms of the adsorption of bacteria onto the Na-MMT surface, which can be ascribed to the formation of the denser aggregates in the Na-MMT with Ca(CH3COO)2. Meanwhile, the adsorption kinetics and isotherms followed the pseudo-second-order kinetic model and Langmuir Equation for both two calcium sources. Meanwhile, the adsorption bands of the water molecules on the minerals were observed to shift significantly after the bacterial adsorption, showing that the hydrogen bonding on the Na-MMT surface played an important role during this process. A value of {Delta}H0 > 0 indicated that the bacterial adsorption was affected by van der Waals force and hydrophobic interaction. Finally, the negative zeta potentials of the Na-MMT increased with the addition of Ca2+ ions, and the experimental data also showed that the adsorption of bacteria onto the Na-MMT was mainly determined by the electrostatic and non-electrostatic forces.

biochemistry↗

bioRxiv2020

Frequency domain analysis of fluctuations of mRNA and protein copy numbers within a cell lineage: theory and experimental validation

The stochasticity of gene expression is manifested in the fluctuations of mRNA and protein copy numbers within a cell lineage over time. While data of this type can be obtained for many generations, most mathematical models are unsuitable to interpret such data since they assume non-growing cells. Here we develop a theoretical approach that quantitatively links the frequency content of lineage data to subcellular dynamics. We elucidate how the position, height, and width of the peaks in the power spectrum provide a distinctive fingerprint that encodes a wealth of information about mechanisms controlling transcription, translation, replication, degradation, bursting, promoter switching, cell cycle duration, cell division, and gene dosage compensation. Predictions are confirmed by analysis of single-cell Escherichia coli data obtained using fluorescence microscopy. Furthermore, by matching the experimental and theoretical power spectra, we infer the temperature-dependent gene expression parameters, without the need of measurements relating fluorescence intensities to molecule numbers.

systems biology↗

bioRxiv2020

Prospective representations in rat orbitofrontal ensembles

The orbitofrontal cortex (OFC) has been proposed to encode expected outcomes, which is thought to be important for outcome-directed behavior. However, such neural encoding can also often be explained by the recall of information about the recent past. To dissociate the retrospective and prospective aspects of encoding in the OFC, we designed a non-spatial, continuous, alternating odor-sequence task that mimicked a continuous T-maze. The task consisted of two alternating sequences of four odor-guided trials (2 sequences x 4 positions). In each trial, rats were asked to make a "go" or "no-go" action based on a fixed odor-reward contingency. Odors at both the first and last positions were distinct across the two sequences, such that they resembled unique paths in the past and future, respectively; odors at positions in between were the same and thus resembled a common path. We trained classifiers using neural activity to distinguish between either sequences or positions and asked whether the neural activity patterns in the common path were more like the ones in the past or the future. We found a proximal prospective code for sequence information as well as a distal prospective code for positional information, the latter of which was closely associated with rats ability to predict future outcomes. This study demonstrates a prospective behaviorally-relevant predictive code in rat OFC.

neuroscience↗

bioRxiv2020

Dynamical phase diagram of an auto-regulating gene in fast switching conditions

While the steady-state behavior of stochastic gene expression with auto-regulation has been extensively studied, its time-dependent behavior has received much less attention. Here, under the assumption of fast promoter switching, we derive and solve a reduced chemical master equation for an auto-regulatory gene circuit with translational bursting and cooperative protein-gene interactions. The analytical expression for the time-dependent probability distribution of protein numbers enables a fast exploration of large swaths of parameter space. For a unimodal initial distribution, we identify three distinct types of stochastic dynamics: (i) the protein distribution remains unimodal at all times; (ii) the protein distribution becomes bimodal at intermediate times and then reverts back to being unimodal at long times (transient bimodality) and (iii) the protein distribution switches to being bimodal at long times. For each of these, the deterministic model predicts either monostable or bistable behaviour and hence there exist six dynamical phases in total. We investigate the relationship of the six phases to the transcription rates, the protein binding and unbinding rates, the mean protein burst size, the degree of cooperativity, the relaxation time to the steady state, the protein mean and the type of feedback loop (positive or negative). We show that transient bimodality is a noise-induced phenomenon that occurs when protein expression is sufficiently bursty and we use theory to estimate the observation time window when it is manifest.

systems biology↗

bioRxiv2019

Kinetic foundation of the zero-inflated negative binomial model for single-cell RNA sequencing data

Single-cell RNA sequencing data have complex features such as dropout events, over-dispersion, and high-magnitude outliers, resulting in complicated probability distributions of mRNA abundances that are statistically characterized in terms of a zero-inflated negative binomial (ZINB) model. Here we provide a mesoscopic kinetic foundation of the widely used ZINB model based on the biochemical reaction kinetics underlying transcription. Using multiscale modeling and simplification techniques, we show that the ZINB distribution of mRNA abundance and the phenomenon of transcriptional bursting naturally emerge from a three-state stochastic transcription model. We further reveal a nontrivial quantitative relation between dropout events and transcriptional bursting, which provides novel insights into how and to what extent the burst size and burst frequency could reduce the dropout rate. Three different biophysical origins of over-dispersion are also clarified at the single-cell level.

systems biology↗

bioRxiv2019

Mechanistic insights into NAD synthase NMNAT chaperoning phosphorylated Tau from pathological aggregation

Tau hyper-phosphorylation and deposition into neurofibrillary tangles have been found in brains of patients with Alzheimers disease (AD) and other tauopathies. Molecular chaperones are involved in regulating the pathological aggregation of phosphorylated Tau (pTau) and modulating disease progression. Here, we report that nicotinamide mononucleotide adenylyltransferase (NMNAT), a well-known NAD synthase, serves as a chaperone of pTau to prevent its amyloid aggregation in vitro as well as mitigate its pathology in a fly tauopathy model. By combining NMR spectroscopy, crystallography, single-molecule and computational approaches, we revealed that NMNAT adopts its enzymatic pocket to specifically bind the phosphorylated sites of pTau, which can be competitively disrupted by the enzymatic substrates of NMNAT. Moreover, we found that NMNAT serves as a co-chaperone of Hsp90 for the specific recognition of pTau over Tau. Our work uncovers a dedicated chaperone of pTau and suggests NMNAT as a key node between NAD metabolism and Tau homeostasis in aging and neurodegeneration.

biochemistry↗

bioRxiv2019

PRISM: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact

Post-translational modifications (PTMs) play very important roles in various cell signalling pathways and biological process. Due to PTMs extremely important roles, many major PTMs have been thoroughly studied, while the functional and mechanical characterization of major PTMs is well-documented in several databases. However, most currently available databases mainly focus on protein sequences, while the real 3D structures of PTMs have been largely ignored. Therefore, studies of PTMs 3D structural signatures have been severely limited by the deficiency of the data. Here, we develop PRISMOID, a novel publicly available and free 3D structure database for a wide range of PTMs. PRISMOID represents an up-to-date and interactive online knowledge base with specific focus on 3D structural contexts of PTMs sites and mutations that occur on PTMs and in the close proximity of PTM sites with functional impact. The first version of PRISMOID encompasses 17,145 non-redundant modification sites on 3,919 related protein 3D structure entries pertaining to 37 different types of PTMs. Our entry web page is organized in a comprehensive manner, including detailed PTM annotation on the 3D structure and biological information in terms of mutations affecting PTMs, secondary structure features and per-residue solvent accessibility features of PTM sites, domain context, predicted natively disordered regions and sequence alignments. In addition, high-definition JavaScript packages are employed to enhance information visualization in PRISMOID. PRISMOID equips a variety of interactive and customizable search options and data browsing functions; these capabilities allow users to access data via keyword, ID, and advanced options combination search in an efficient and user-friendly way. A download page is also provided to enable users to download the SQL file, computational structural features, and PTM sites data. We anticipate PRISMOID will swiftly become an invaluable online resource, assisting both biologists and bioinformaticians to conduct experiments and develop applications supporting discovery efforts in the sequence-structural-functional relationship of PTMs and providing important insight into mutations and PTM sites interaction mechanisms. The PRISMOID database is freely accessible at http://prismoid.erc.monash.edu/. The database and web interface are implemented in MySQL, JSP, JavaScript, and HTML with all major browsers supported.

bioinformatics↗

bioRxiv2017

Accounting For Technical Noise In Single-Cell RNA Sequencing Analysis

Recent technological breakthroughs have made it possible to measure RNA expression at the single-cell level, thus paving the way for exploring expression heterogeneity among individual cells. Current single-cell RNA sequencing (scRNA-seq) protocols are complex and introduce technical biases that vary across cells, which can bias downstream analysis without proper adjustment. To account for cell-to-cell technical differences, we propose a statistical framework, TASC (Toolkit for Analysis of Single Cell RNA-seq), an empirical Bayes approach to reliably model the cell-specific dropout rates and amplification bias by use of external RNA spike-ins. TASC incorporates the technical parameters, which reflect cell-to-cell batch effects, into a hierarchical mixture model to estimate the biological variance of a gene and detect differentially expressed genes. More importantly, TASC is able to adjust for covariates to further eliminate confounding that may originate from cell size and cell cycle differences. In simulation and real scRNA-seq data, TASC achieves accurate Type I error control and displays competitive sensitivity and improved robustness to batch effects in differential expression analysis, compared to existing methods. TASC is programmed to be computationally efficient, taking advantage of multi-threaded parallelization. We believe that TASC will provide a robust platform for researchers to leverage the power of scRNA-seq.

bioinformatics↗