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Chen, D.

Publications and source records attributed to Chen, D..

At least 145 records · Page 8Linked to original sources

Deep learning uncovers sequence-specific amplification bias in multi-template PCR

Multi-template polymerase chain reaction is a key step in many amplicon sequencing protocols enabling parallel amplification of diverse DNA molecules sharing common adapters in applications, ranging as wide as quantitative molecular biology and DNA data storage. However, this process results in a skewed amplicon abundance, due to sequence-specific amplification biases. In this study, one-dimensional convolutional neural networks (1D-CNNs) were trained on synthetic DNA pools to learn the PCR amplification efficiency of individual templates. These 1D-CNN models can predict poorly amplifying templates based solely on sequence information, achieving an AUROC/AUPRC of up to 0.88/0.44 with very imbalanced prevalence of 2%, thereby greatly outperforming baseline models relying only on GC content and nucleotide frequency as predictors. A new, general-purpose framework for interpreting deep learning models, termed CluMo provides mechanistic insights into the amplification biases. Most strikingly, specific amplification reactions were identified as suffering from adaptor-template self-priming a mechanism previously disregarded in PCR.

molecular biology↗

Enzymatic Degrading Chlorophenol Wastewater by Mixed Strains of Immobilized White Rot Fungi

To address chlorophenol wastewater pollution, immobilized mixed white rot fungi (WRF) strain microsphere was designed as a solid degradation agent, using lignin peroxidase (LiP), manganese peroxidase (MnP), and laccase (Lac) to degradating the wastewater. Considering the diverse physical and chemical properties of the fungal sphere, the immobilization agent formula is optimized and comprehensive environmental factor design response surface analysis are implemented to determine the delivery conditions. Consequently, the 2,4-DCP treatment rate and extracellular enzyme activity for a 1:1 encapsulation of T. versicolor and P. sajor-caju significantly outperform those of individual strains. Using polyvinyl alcohol (PVA), sodium alginate (SA), and biochar as carriers, with sodium dihydrogen phosphate solution as crosslinker and SiO2/zeolite as additives, immobilizing mixed bacteria yielded a high-quality solid agent. This achieved a 99.33% 2,4-DCP degradation rate over 96 hours, with optimal dosage, pH, and initial 2,4-DCP concentration at 11.5 g/L, 5.5, and 40 mg/L. The degradation of 2,4-DCP by WRF selectively removes adjacent chlorine atoms to produce 4-CP, enhancing the dechlorination efficiency. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/611973v1_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@1653067org.highwire.dtl.DTLVardef@4cc31dorg.highwire.dtl.DTLVardef@19daa33org.highwire.dtl.DTLVardef@1115c5_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

Engineering asymmetric nanoscale lipid vesicles for drug delivery

The delivery of therapeutics to cells enables both the treatment and the prevention of diseases. To protect therapeutics from degradation and enable cell-specific targeting, they are often encapsulated into drug delivery vehicles such as lipid nanoparticles, viral vectors or lipid vesicles. These delivery vehicles have been extremely successful in delivering small molecules, nucleic acids or proteins. However, there is no universal drug delivery vehicle that can deliver therapeutics irrespective of the choice of cargo. Here, we present a method to engineer lipid vesicles with asymmetric leaflets and show that they can deliver mRNA and proteins to cells. We also find that the leaflet asymmetry can increase the lipid vesicle uptake by cells. When we load asymmetric vesicles with mRNA, we observe a 5-fold increase in the transfection efficiency indicative of an improved uptake and release by asymmetric vesicles. Moreover, our findings extend beyond mRNA cargos by showcasing the effectiveness of asymmetric vesicles in delivering a wide range of proteins to cells, including the promising CRISPR/Cas9 gene editing system. Our method and findings expand the parameter space for engineering drug delivery vehicles and demonstrate the pivotal role of leaflet asymmetry in determining the performance of drug delivery vehicles. Consequently, our work leads to many applications, including the formation of more efficient universal drug carriers and the delivery of gene-editing proteins to cells.

biophysics↗

The C2 domain augments Ras GTPase Activating Protein catalytic activity

Regulation of Ras GTPases by GTPase activating proteins (GAP) is essential for their normal signaling. Nine of the ten GAPs for Ras contain a C2 domain immediately proximal to their canonical GAP domain, and in RasGAP (p120GAP, p120RasGAP; RASA1) mutation of this domain is associated with vascular malformations in humans. Here, we show that the C2 domain of RasGAP is required for full catalytic activity towards Ras. Analysis of the RasGAP C2-GAP crystal structure, AlphaFold models, and sequence conservation reveal direct C2 domain interaction with the Ras allosteric lobe. This is achieved by an evolutionarily conserved surface centered around RasGAP residue R707, point mutation of which impairs the catalytic advantage conferred by the C2 domain in vitro. In mice, R707C mutation phenocopies the vascular and signaling defects resulting from constitutive disruption of the RASA1 gene. In SynGAP, mutation of the equivalent conserved C2 domain surface impairs catalytic activity. Our results indicate that the C2 domain is required to achieve full catalytic activity of Ras GTPase activating proteins.

biochemistry↗

Slow-wave sleep and REM sleep differentially contribute to memory representational transformation

Memory transforms over time, gradually becoming less idiosyncratic and more gist-like. While sleep contributes to memory transformation, how different sleep stages and EEG activity influence memory transformation is far from clear. Applying representational similarity analysis to electroencephalogram (EEG) recordings, we examined memory representational transformation at both the idiosyncratic "item-level" and the generic "category-level". Our findings revealed that after an overnight sleep, item-level neural representations for post-sleep remembered items were abolished. In contrast, category-level representations remained prominent, but they became distinctive from pre-sleep. Across participants, more rapid eye movement (REM) sleep relative to slow-wave sleep (SWS) was associated with reduced item-level neural representational strength, increased category-level representational strength, as well as the decreased item-level representational similarity between pre-sleep learning and post-sleep retrieval sessions. Moreover, the theta and beta EEG power during REM sleep, and delta power during SWS differentially supported these representational transformations. These findings suggest that post-learning REM sleep and SWS play differential roles in supporting overnight memory transformation.

neuroscience↗

Genetic evolution of keratinocytes to cutaneous squamous cell carcinoma

We performed multi-omic profiling of epidermal keratinocytes, precancerous actinic keratoses, and squamous cell carcinomas to understand the molecular transitions during skin carcinogenesis. Single-cell mutational analyses of normal skin cells showed that most keratinocytes have remarkably low mutation burdens, despite decades of sun exposure, however keratinocytes with TP53 or NOTCH1 mutations had substantially higher mutation burdens. These observations suggest that wild-type keratinocytes (i.e. without pathogenic mutations) are able to withstand high dosages of cumulative UV radiation, but certain pathogenic mutations break these adaptive mechanisms, priming keratinocytes for transformation by increasing their mutation rate. Mutational profiling of squamous cell carcinomas adjacent to actinic keratoses revealed TERT promoter and CDKN2A mutations emerging in actinic keratoses, whereas additional mutations inactivating ARID2 and activating the MAPK-pathway delineated the transition to squamous cell carcinomas. Surprisingly, actinic keratoses were often not related to their neighboring squamous cell carcinoma, indicating that collisions of unrelated neoplasms are common in the skin. Spatial variation in gene expression patterns was common in both tumor and immune cells, with high expression of checkpoint molecules at the invasive front of tumors. In conclusion, this study catalogues the key events during the evolution of cutaneous squamous cell carcinoma.

genomics↗

A Cost-effective, High-throughput, Highly Accurate Genotyping Method for Outbred Populations

Affordable sequencing and genotyping methods are essential for large scale genome-wide association studies. While genotyping microarrays and reference panels for imputation are available for human subjects, non-human model systems often lack such options. Our lab previously demonstrated an efficient and cost-effective method to genotype heterogeneous stock rats using double-digest genotyping-by-sequencing. However, low-coverage whole-genome sequencing offers an alternative method that has several advantages. Here, we describe a cost-effective, high-throughput, high-accuracy genotyping method for N/NIH heterogeneous stock rats that can use a combination of sequencing data previously generated by double-digest genotyping-by-sequencing and more recently generated by low-coverage whole-genome-sequencing data. Using double-digest genotyping-by-sequencing data from 5,745 heterogeneous stock rats (mean 0.21x coverage) and low-coverage whole-genome-sequencing data from 8,760 heterogeneous stock rats (mean 0.27x coverage), we can impute 7.32 million bi-allelic single-nucleotide polymorphisms with a concordance rate >99.76% compared to high-coverage (mean 33.26x coverage) whole-genome sequencing data for a subset of the same individuals. Our results demonstrate the feasibility of using sequencing data from double-digest genotyping-by-sequencing or low-coverage whole-genome-sequencing for accurate genotyping, and demonstrate techniques that may also be useful for other genetic studies in non-human subjects. Article SummaryHeterogeneous stock rats were derived by interbreeding eight inbred founders in 1984, and have been maintained as an outbred population for more than 100 generations. Heterogeneous stock rats offer a high degree of genetic and phenotypic diversity, and have been extensively used for genetic studies. Here, we describe a cost-effective and high-throughput genotyping method for heterogeneous stock rats. We applied the method to 15,552 heterogeneous stock rats. The resulting genotypes were highly accurate. These techniques may be useful for genetic studies in other non-human subjects.

genetics↗

Genomic evolution reshapes cell type diversification in the amniote brain

Over 320 million years of evolution, amniotes have developed complex brains and cognition through largely unexplored genetic and gene expression mechanisms. We created a comprehensive single-cell atlas of over 1.3 million cells from the telencephalon and cerebellum of turtles, zebra finches, pigeons, mice, and macaques, employing single-cell resolution spatial transcriptomics to validate gene expression patterns across species. Our study revealed significant species-specific variations in cell types, highlighting their conservation and diversification in evolution. We found pronounced differences in telencephalon excitatory neurons (EX) and cerebellar cell types between birds and mammals. Birds predominantly express SLC17A6 in EX, whereas mammals expressed SLC17A7 in neocortex and SLC17A6 elsewhere, possibly due to loss of SLC17A7 function loss in birds. Additionally, we identified a novel bird-specific Purkinje cell subtype (SVIL+), implicating the LSD11/KDM1A pathway in learning and circadian rhythms, and related numerous positively selected genes in birds, suggesting an evolutionary optimization of cerebellar functions for ecological and behavioral adaptation. Our findings elucidate the complex interplay between genetic evolution and environmental adaptation, underscoring the role of genetic diversification in the development of specialized cell types across amniotes.

evolutionary biology↗

Comprehensive mapping and modelling of the rice regulome landscape unveils the regulatory architecture underlying complex traits

Unraveling the regulatory mechanisms that govern complex traits is pivotal for advancing crop improvement. Here we present a comprehensive regulome atlas for rice (Oryza sativa), charting the chromatin accessibility across 23 distinct tissues from three representative varieties. Our study uncovers 117,176 unique open chromatin regions (OCRs), accounting for [~]15% of the rice genome, a notably higher proportion compared to previous reports in plants. Integrating RNA-seq data from matched tissues, we confidently predict 59,075 OCR-to-gene links, with enhancers constituting 69.54% of these associations, including many known enhancer-to-gene links. Leveraging this resource, we re-evaluate genome-wide association study results and discover a previously unknown function of OsbZIP06 in seed germination, which we subsequently confirm through experimental validation. We optimize deep learning models to decode regulatory grammar, achieving robust modeling of tissue-specific chromatin accessibility. This approach allows to predict cross-variety regulatory dynamics from genomic sequences, shedding light on the genetic underpinnings of cis-regulatory divergence and morphological disparities between varieties. Overall, our study establishes a foundational resource for rice functional genomics and precision molecular breeding, providing valuable insights into regulatory mechanisms governing complex traits.

genomics↗

Bacterial metabarcoding reveals plant growth promoting members of the core Brachypodium distachyon root-associated microbiome overlooked by culture dependent techniques

Biofertilisers comprised of plant growth promoting bacteria (PGPB) present a promising sustainable alternative to synthetic fertilisers. Bacteria which consistently colonise roots of specific plants across distinct environments, known as that plants core root microbiome, are particularly promising due to their colonisation competency. However, traditional, culture-based techniques can overlook promising PGPB which do not display commonly screened for plant growth promoting traits. Although numerous studies have isolated beneficial root bacteria, few have combined bacterial metabarcoding with culture-based techniques to identify novel biofertiliser candidates. In a two-pronged approach, 16S rRNA amplicon sequencing was used to define the core root microbiome of the model cereal plant, Brachypodium distachyon, grown in four distinct soils. From 7,042 amplicon sequence variants (ASVs) detected in root fractions, only 40 ASVs were common at a prevalence of 80%. Core ASVs primarily belonged to the class Alphaproteobacteria, with the remainder comprising Actinobacteria, Bacilli, Chloroflexia, Gammaproteobacteria and Negativicutes. Secondly, B. distachyon root-associated bacterial strains were isolated from plants grown in the aforementioned soils. Of 207 root-associated isolates, 10 were identified as members of the core root microbiome, with the majority not displaying commonly screened for plant growth promoting traits. However, in a semi-hydroponic system, a core Bacillus and Rhodococcus strain significantly increased B. distachyon shoot dry weight by 32.8% and 40.0%, respectively. Additionally, two core Bacillus strains significantly increased root dry weight by 79.7 and 52.3%. This study demonstrates the potential of incorporating additional criteria afforded by culture-independent methods to screen for novel biofertiliser candidates typically overlooked by culture-dependent techniques. ImportanceBiofertilisers comprised of plant growth promoting bacteria (PGPB) present a sustainable, environmentally friendly alternative to synthetic fertilisers. The search for PGPB has historically relied on culture dependent methods to shortlist candidates by screening for plant growth promoting traits, such as N fixation or production of the plant hormone indole-3-acetic acid before conducting in planta trials. However, these screens may overlook promising bacterial strains which might promote plant growth via indeterminant mechanisms. Culture independent methods can take a snapshot of an entire microbiome without the need for culturing bacteria, allowing for additional selection criteria to be used when shortlisting PGPB. Our results show that targeting bacterial taxa which consistently colonise the roots of the model grass Brachypodium distachyon allowed for selection of bacterial isolates which were overlooked by culture-based PGPB trait screens. This result highlights the utility of combining traditional, culture-dependent methods with culture-independent techniques when searching for novel biofertiliser candidates.

microbiology↗

Synthetic genomes unveil the effects of synonymous recoding

Engineering the genetic code of an organism provides the basis for (i) making any organism safely resistant to natural viruses and (ii) preventing genetic information flow into and out of genetically modified organisms while (iii) allowing the biosynthesis of genetically encoded unnatural polymers1-4. Achieving these three goals requires the reassignment of multiple of the 64 codons nature uses to encode proteins. However, synonymous codon replacement--recoding--is frequently lethal, and how recoding impacts fitness remains poorly explored. Here, we explore these effects using whole-genome synthesis, multiplexed directed evolution, and genome-transcriptome-translatome-proteome co-profiling on multiple recoded genomes. Using this information, we assemble a synthetic Escherichia coli genome in seven sections using only 57 codons to encode proteins. By discovering the rules responsible for the lethality of synonymous recoding and developing a data-driven multi-omics-based genome construction workflow that troubleshoots synthetic genomes, we overcome the lethal effects of 62,007 synonymous codon swaps and 11,108 additional genomic edits. We show that synonymous recoding induces transcriptional noise including new antisense RNAs, leading to drastic transcriptome and proteome perturbation. As the elimination of select codons from an organisms genetic code results in the widespread appearance of cryptic promoters, we show that synonymous codon choice may naturally evolve to minimize transcriptional noise. Our work provides the first genome-scale description of how synonymous codon changes influence organismal fitness and paves the way for the construction of functional genomes that provide genetic firewalls from natural ecosystems and safely produce biopolymers, drugs, and enzymes with an expanded chemistry.

synthetic biology↗

CTCF regulates global chromatin accessibility and transcription during rod photoreceptor development

Chromatin architecture facilitates accurate transcription at a number of loci, but it remains unclear how much chromatin architecture is involved in global transcriptional regulation. Previous work has shown that rapid depletion of the architectural protein CTCF in cell culture strongly alters chromatin organization but results in surprisingly limited gene expression changes. This discrepancy has also been observed when other architectural proteins are depleted, and one possible explanation is that full transcriptional changes are masked by cellular heterogeneity. We tested this idea by performing multi-omics analyses with sorted post-mitotic mouse rods, which undergo synchronized development, and identified CTCF-dependent regulation of global chromatin accessibility and gene expression. Depletion of CTCF leads to dysregulation of [~]20% of the entire transcriptome (>3,000 genes) and [~]41% of genome accessibility (>26,000 sites), and these regions are strongly enriched in euchromatin. Importantly, these changes are highly enriched for CTCF occupancy, suggesting direct CTCF binding and transcriptional regulation at these active loci. CTCF mainly promotes chromatin accessibility of these direct binding targets, and a large fraction of these sites correspond to promoters. At these sites, CTCF binding frequently promotes accessibility and inhibits expression, and motifs of transcription repressors are found to be significantly enriched. Our findings provide different and often opposite conclusions from previous studies, emphasizing the need to consider cell heterogeneity and cell type specificity when performing multi-omics analyses. We conclude that the architectural protein CTCF binds chromatin and regulates global chromatin accessibility and transcription during rod development.

genomics↗

Pioneer factor ETV2 safeguards endothelial cell specification by recruiting the repressor REST to restrict alternative lineage commitment

Mechanisms of cell fate specification remain a central question for developmental biology and regenerative medicine. The pioneer factor ETV2 is a master regulator for the endothelial cell (EC) lineage specification. Here, we studied mechanisms of ETV2-driven fate specification using a highly efficient system in which ETV2 directs human induced pluripotent stem cell-derived mesodermal progenitors to form ECs over two days. By applying CUT&RUN, single-cell RNA-sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) analyses, we characterized the transcriptomic profiles, chromatin landscapes, dynamic cis-regulatory elements (CREs), and molecular features of EC cell differentiation mediated by ETV2. This defined the scope of ETV2 pioneering activity and identified its direct downstream target genes. Induced ETV2 expression both directed specification of endothelial progenitors and suppressed acquisition of alternative fates. Functional screening and candidate validation revealed cofactors essential for efficient EC specification, including the transcriptional activator GABPA. Surprisingly, the transcriptional repressor REST was also necessary for efficient EC specification. ETV2 recruited REST to occupy and repress non-EC lineage genes. Collectively, our study provides an unparalleled molecular analysis of EC specification at single-cell resolution and identifies the important role of pioneer factors to recruit repressors that suppress commitment to alternative lineages.

cell biology↗

Intracranial neurophysiological correlates of rumination

Rumination is a transdiagnostic psychological process that plays a prominent role in many common psychiatric disorders, albeit its neurophysiological basis remains elusive. Existing neuroimaging studies have highlighted the precuneus and hippocampus as two essential brain regions in ruminations neural underpinnings. Here, we examined the intracranial electroencephalogram (iEEG) recordings from 21 patients with epilepsy during a naturalistic, continuous, active rumination state and measured the slow frequency (1-8 Hz) and high gamma (70-150 Hz) band oscillation powers. We observed enhanced slow frequency power in the precuneus and reduced high gamma power in the hippocampus during the rumination condition compared to the control condition. The hippocampal high gamma power reduction was associated with the self-reported reflection tendency. Our findings provided the first empirical evidence of the neurophysiological underpinnings of rumination and implicated a precuneus-hippocampus coupling across neural oscillation bands during an active rumination state.

neuroscience↗

scCaT: an explainable capsulating architecture for sepsis diagnosis transferring from single-cell RNA sequencing

Sepsis is a life-threatening condition characterized by an exaggerated immune response to pathogens, leading to organ damage and high mortality rates in the intensive care unit. Although deep learning has achieved impressive performance on prediction and classification tasks in medicine, it requires large amounts of data and lacks explainability, which hinder its application to sepsis diagnosis. We introduce a deep learning framework, called scCaT, which blends the capsulating architecture with Transformer to develop a sepsis diagnostic model using single-cell RNA sequencing data and transfers it to bulk RNA data. The capsulating architecture effectively groups genes into capsules based on biological functions, which provides explainability in encoding gene expressions. The Transformer serves as a decoder to classify sepsis patients and controls. Our model achieves high accuracy with an AUROC of 0.93 on the single-cell test set and an average AUROC of 0.98 on seven bulk RNA cohorts. Additionally, the capsules can recognize different cell types and distinguish sepsis from control samples based on their biological pathways. This study presents a novel approach for learning gene modules and transferring the model to other data types, offering potential benefits in diagnosing rare diseases with limited subjects. Author summaryDeep learning models used in disease diagnosis usually suffer from insufficient data for training and the lack of explainability, especially in rare diseases. These shortages hinder their application to sepsis diagnosis. Here we propose a diagnostic framework name scCaT(https://github.com/Kimxbzheng/CaT), which transfers knowledge learned from single-cell RNA-seq, for diseases with insufficient bulk data. The framework uses capsulating architecture to group genes into capsules and provide explainability to the deep learning model for sepsis diagnosis. ScCaT achieves robust and outstanding performance for sepsis diagnosis in both scRNA-seq and bulk RNA datasets. This architecture offers potential approaches in diagnosing rare diseases with limited subjects with explainability.

bioinformatics↗

The Class III peroxidase OsPrx20 is a key regulator of stress response and growth in rice

In plants, reactive oxygen species maintain strictly low intracellular levels that is prerequisite for their function as second messengers. However, abiotic and biotic stresses are also long-term processes, requiring rapid scavenging of excess intracellular ROS. Plant Class III peroxidases, as multifunctional enzymes, are core enzymes in regulating intracellular ROS homeostasis and are key to regulating the complicated signaling network. Here, we found a rice Class III peroxidase OsPrx20 maintains intracellular ROS homeostasis in different conditions. OsPrx20 is a target of Ca2+/calmodulin-dependent protein kinase (OsDMI3) and phosphorylates its Thr-244 site by OsDMI3. Overexpression of OsPrx20 enhances osmotic stress tolerance but reduces blast resistance, while lack of OsPrx20 is opposite, suggesting OsPrx20 positively regulates osmotic stress tolerance but negatively regulates blast resistance in rice. Meanwhile, overexpression of OsPrx20 enlarges spike size and grain fullness, whereas lack of OsPrx20 leads to dwarfism and smaller spike. In ABA signaling, OsPrx20 Thr-244 phosphorylation is specifically dependent on OsDMI3 to reduce the sensitivity of ABA to seed germination and root growth and to enhance osmotic stress tolerance without affecting spike and grain development. Our study reveals an essential regulatory mechanism that directly activates OsPrx20 in ABA signaling, highlighting the multi-functionality of OsPrx20 in different biological processes.

plant biology↗

PAMPHLET: A Robust Toolkit for Precise PAM Prediction and Unveiling PAM Consistency in Highly Co-occurrence CRISPR-Cas Systems

The CRISPR-Cas technology has sparked a new technological revolution, significantly enhancing our ability to understand and engineer organisms. The nuclease that underpins this technology is evolving from the "One Cas9 for all" model to a diverse CRISPR toolbox. Identifying PAM sequences is a critical bottleneck in developing novel Cas proteins. Given the limitations of experimental methods, bioinformatics approaches are essential for predicting PAM sequences of Cas proteins in advance. To date, there are only a few PAM sequence prediction programs, and their accuracy is relatively low due to the limited number of spacers in CRISPR-Cas systems. To overcome this challenge, we have developed a pipeline named PAMPHLET, which innovatively utilizes homology searches of Cas proteins to identify additional spacers. PAMPHLET was tested on 20 CRISPR-Cas systems with known PAMs, increasing the number of spacers by up to 18-fold compared to the original datasets and successfully predicting 18 PAM sequences for protospacers. For rigorous and high-quality wet-lab validation of the predictions made by PAMPHLET, we employed the published DocMF platform. This platform leverages next-generation sequencing chips to profile protein-DNA interactions and can simultaneously screen both 5 and 3 PAMs with high throughput. The PAMPHLET predictions showed high consistency with the DocMF results for four novel Cas proteins. We expect that PAMPHLET will overcome the current limitations in PAM sequence prediction, expedite the discovery of PAM sequences, and help to shorten the development cycle for CRISPR tools. Remarkably, PAMPHLET has revealed an intriguing genomic phenomenon: the C2c9 and C2c10 systems, which lack the canonical adaptation module, possess identical PAM sequences to those found in co-occurring type I systems, suggesting potential shared spacer acquisition mechanisms. This finding highlights the complex evolutionary relationships of CRISPR-Cas systems and propels us toward a deeper understanding of their mechanistic diversity and adaptability.

bioinformatics↗

Hepatitis E virus infection upregulates ING5 expression in vitro and vivo

Hepatitis E virus (HEV) is the major pathogen of viral hepatitis. Immunocompromised individual infected by HEV is prone to chronic hepatitis and increases the risk of hepato-cellular carcinoma (HCC). Inhibitor of growth family member 5 (ING5) is a tumor suppressor gene, is low expressed in cancer tumor or cells. However, the underlying relationship between ING5 and HEV infection is unclear. In the present study acute and chronic HEV animal models were employed to explore the interaction between ING5 and HEV. Notably, the expression of ING5 was significantly increased both in the liver of acute HEV infected BALB/c mice and chronic HEV infected rhesus macaques. In addition, the relationship between HEV infection and ING5 expression was further identified in human hepatoma (HepG-2) cells. In conclusion, HEV infection strongly upregulated ING5 expression in vivo and in vitro, bearing significant implications in further understanding the pathogenic mechanism of HEV infection.

microbiology↗