A statistical method for image-mediated association studies discovers genes and pathways associated with four brain disorders.

Brain imaging and genomics are critical tools enabling characterization of the genetic basis of brain disorders. However, imaging large cohorts is expensive and may be unavailable for legacy datasets used for genome-wide association studies (GWASs). Using an integrated feature selection/aggregation model, we developed an image-mediated association study (IMAS), which utilizes borrowed imaging/genomics data to conduct association mapping in legacy GWAS cohorts. By leveraging the UK Biobank image-derived phenotypes (IDPs), the IMAS discovered genetic bases underlying four neuropsychiatric disorders and verified them by analyzing annotations, pathways, and expression quantitative trait loci (eQTLs). A cerebellar-mediated mechanism was identified to be common to the four disorders. Simulations show that, if the goal is identifying genetic risk, our IMAS is more powerful than a hypothetical protocol in which the imaging results were available in the GWAS dataset. This implies the feasibility of reanalyzing legacy GWAS datasets without conducting additional imaging, yielding cost savings for integrated analysis of genetics and imaging.

The development of brain pericytes requires expression of the transcription factor nkx3.1 in intermediate precursors.

Brain pericytes are one of the critical cell types that regulate endothelial barrier function and activity, thus ensuring adequate blood flow to the brain. The genetic pathways guiding undifferentiated cells into mature pericytes are not well understood. We show here that pericyte precursor populations from both neural crest and head mesoderm of zebrafish express the transcription factor nkx3.1 develop into brain pericytes. We identify the gene signature of these precursors and show that an nkx3.1-, foxf2a-, and cxcl12b-expressing pericyte precursor population is present around the basilar artery prior to artery formation and pericyte recruitment. The precursors later spread throughout the brain and differentiate to express canonical pericyte markers. Cxcl12b-Cxcr4 signaling is required for pericyte attachment and differentiation. Further, both nkx3.1 and cxcl12b are necessary and sufficient in regulating pericyte number as loss inhibits and gain increases pericyte number. Through genetic experiments, we have defined a precursor population for brain pericytes and identified genes critical for their differentiation.

A model approach to show that monocytes can enter microporous ß-TCP ceramics.

ß-TCP ceramics are versatile bone substitute materials and show many interactions with cells of the monocyte-macrophage-lineage. The possibility of monocytes entering microporous ß-TCP ceramics has however not yet been researched. In this study, we used a model approach to investigate whether monocytes might enter ß-TCP, providing a possible explanation for the origin of CD68-positive osteoclast-like giant cells found in earlier works.We used flow chambers to unidirectionally load BC, PRP, or PPP into slice models of either 2 mm or 6 mm ß-TCP. Immunofluorescence for CD68 and live/dead staining was performed after the loading process.Our results show that monocytes were present in a relevant number of PRP and BC slices representing the inside of our 2 mm slice model and also present on the actual inside of our 6 mm model. For PPP, monocytes were not found beyond the surface in either model.Our results indicate the possibility of a new and so far neglected constituent in ß-TCP degradation, perhaps causing the process of ceramic degradation also starting from inside the ceramics as opposed to the current understanding. We also demonstrated flow chambers as a possible new in vitro model for interactions between blood and ß-TCP.

Integrating Multi-Omics Data to Uncover Prostate Tissue DNA Methylation Biomarkers and Target Genes for Prostate Cancer Risk.

Previous studies have indicated that specific CpG sites may be linked to the risk of prostate cancer (PCa) by regulating the expression of PCa target genes. However, most existing studies aim to identify DNA methylation (DNAm) biomarkers through blood tissue genetic instruments, which impedes the identification of relevant biomarkers in prostate tissue. To identify PCa risk-associated CpG sites in prostate tissue, we established genetic prediction models of DNAm levels using data from normal prostate samples in the GTEx (N = 108) and assessed associations between genetically predicted DNAm in prostate and PCa risk by studying 122,188 cases and 604,640 controls. We observed significant associations for 3879 CpG sites, including 926 at novel genomic loci. Among them, DNAm levels of 80 CpG sites located at novel loci are significantly associated with expression levels of 45 neighboring genes in normal prostate tissue. Of these genes, 11 further exhibit significant associations with PCa risk for their predicted expression levels in prostate tissue. Intriguingly, a total of 31 CpG sites demonstrate consistent association patterns across the methylation-gene expression-PCa risk pathway. Our findings suggest that specific CpG sites may be related to PCa risk by modulating the expression of nearby target genes.

Rab11b promotes M1-like macrophage polarization by restraining autophagic degradation of NLRP3 in alcohol-associated liver disease.

Macrophage polarization is vital to mounting a host defense or repairing tissue in various liver diseases. Excessive activation of the NLR family pyrin domain containing 3 (NLRP3) inflammasome is related to the orchestration of inflammation and alcohol-associated liver disease (ALD) pathology. Rab GTPases play critical roles in regulating vesicular transport. In this study we investigated the role of Rab11b in ALD, aiming to identify effective therapeutic targets. Here, we first demonstrated a decreased expression of Rab11b in macrophages from ALD mice. Knockdown of Rab11b by macrophage-specific adeno-associated virus can alleviate alcohol induced liver inflammation, injury and steatosis. We found that LPS and alcohol stimulation promoted Rab11b transferring from the nucleus to the cytoplasm in bone marrow-derived macrophages (BMDM) cells. Rab11b specifically activated the NLRP3 inflammasome in BMDMs and RAW264.7 cells to induce M1 macrophage polarization. Rab11b overexpression in BMDMs inhibited autophagic flux, leading to the suppression of LC3B-mediated NLRP3 degradation. We conclude that impaired Rab11b could alleviate alcohol-induced liver injury via autophagy-mediated NLRP3 degradation.

Power analysis of transcriptome-wide association study: Implications for practical protocol choice.

The transcriptome-wide association study (TWAS) has emerged as one of several promising techniques for integrating multi-scale 'omics' data into traditional genome-wide association studies (GWAS). Unlike GWAS, which associates phenotypic variance directly with genetic variants, TWAS uses a reference dataset to train a predictive model for gene expressions, which allows it to associate phenotype with variants through the mediating effect of expressions. Although effective, this core innovation of TWAS is poorly understood, since the predictive accuracy of the genotype-expression model is generally low and further bounded by expression heritability. This raises the question: to what degree does the accuracy of the expression model affect the power of TWAS? Furthermore, would replacing predictions with actual, experimentally determined expressions improve power? To answer these questions, we compared the power of GWAS, TWAS, and a hypothetical protocol utilizing real expression data. We derived non-centrality parameters (NCPs) for linear mixed models (LMMs) to enable closed-form calculations of statistical power that do not rely on specific protocol implementations. We examined two representative scenarios: causality (genotype contributes to phenotype through expression) and pleiotropy (genotype contributes directly to both phenotype and expression), and also tested the effects of various properties including expression heritability. Our analysis reveals two main outcomes: (1) Under pleiotropy, the use of predicted expressions in TWAS is superior to actual expressions. This explains why TWAS can function with weak expression models, and shows that TWAS remains relevant even when real expressions are available. (2) GWAS outperforms TWAS when expression heritability is below a threshold of 0.04 under causality, or 0.06 under pleiotropy. Analysis of existing publications suggests that TWAS has been misapplied in place of GWAS, in situations where expression heritability is low.

Interaction-integrated linear mixed model reveals 3D-genetic basis underlying Autism.

Genetic interactions play critical roles in genotype-phenotype associations. We developed a novel interaction-integrated linear mixed model (ILMM) that integrates a priori knowledge into linear mixed models. ILMM enables statistical integration of genetic interactions upfront and overcomes the problems of searching for combinations. To demonstrate its utility, with 3D genomic interactions (assessed by Hi-C experiments) as a priori, we applied ILMM to whole-genome sequencing data for Autism Spectrum Disorders (ASD) and brain transcriptome data, revealing the 3D-genetic basis of ASD and 3D-expression quantitative loci (3D-eQTLs) for brain tissues. Notably, we reported a potential mechanism involving distal regulation between FOXP2 and DNMT3A, conferring the risk of ASD.

kTWAS: integrating kernel machine with transcriptome-wide association studies improves statistical power and reveals novel genes.

The power of genotype-phenotype association mapping studies increases greatly when contributions from multiple variants in a focal region are meaningfully aggregated. Currently, there are two popular categories of variant aggregation methods. Transcriptome-wide association studies (TWAS) represent a set of emerging methods that select variants based on their effect on gene expressions, providing pretrained linear combinations of variants for downstream association mapping. In contrast to this, kernel methods such as sequence kernel association test (SKAT) model genotypic and phenotypic variance use various kernel functions that capture genetic similarity between subjects, allowing nonlinear effects to be included. From the perspective of machine learning, these two methods cover two complementary aspects of feature engineering: feature selection/pruning and feature aggregation. Thus far, no thorough comparison has been made between these categories, and no methods exist which incorporate the advantages of TWAS- and kernel-based methods. In this work, we developed a novel method called kernel-based TWAS (kTWAS) that applies TWAS-like feature selection to a SKAT-like kernel association test, combining the strengths of both approaches. Through extensive simulations, we demonstrate that kTWAS has higher power than TWAS and multiple SKAT-based protocols, and we identify novel disease-associated genes in Wellcome Trust Case Control Consortium genotyping array data and MSSNG (Autism) sequence data. The source code for kTWAS and our simulations are available in our GitHub repository (https://github.com/theLongLab/kTWAS).

Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding.

DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or "haplotypes." However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics, and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here, we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.

WgLink: reconstructing whole-genome viral haplotypes using L0+L1-regularization.

SUMMARY: Many tools can reconstruct viral sequences based on next-generation sequencing reads. Although existing tools effectively recover local regions, their accuracy suffers when reconstructing the whole viral genomes (strains). Moreover, they consume significant memory when the sequencing coverage is high or when the genome size is large. We present WgLink to meet this challenge. WgLink takes local reconstructions produced by other tools as input and patches the resulting segments together into coherent whole-genome strains. We accomplish this using an L0+L1-regularized regression, synthesizing variant allele frequency data with physical linkage between multiple variants spanning multiple regions simultaneously. WgLink achieves higher accuracy than existing tools both on simulated and on real datasets while using significantly less memory (RAM) and fewer CPU hours. AVAILABILITY AND IMPLEMENTATION: Source code and binaries are freely available at https://github.com/theLongLab/wglink. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genome-wide association study of SARS-CoV-2 infection in Chinese population.

Coronavirus disease 2019 (COVID-19) is a global public health concern. The purpose of this study was to investigate the association between genetic variants and SARS-CoV-2 infection and the COVID-19 severity in Chinese population. A total of 256 individuals including 87 symptomatic patients (tested positive for SARS-CoV-2), 84 asymptomatic cases, and 85 close contacts of confirmed patients (tested negative for SARS-CoV-2) were recruited from February 2020 to May 2020. We carried out the whole exome genome sequencing between the individuals and conducted a genetic association study for SARS-CoV-2 infection and the COVID-19 severity. In total, we analyzed more than 100,000 single-nucleotide polymorphisms. The genome-wide association study suggested potential correlation between genetic variability in POLR2A, ANKRD27, MAN1A2, and ERAP1 genes and SARS-CoV-2 infection susceptibility. The most significant gene locus associated with SARS-CoV-2 infection was located in POLR2A (p = 5.71 × 10-6). Furthermore, genetic variants in PCNX2, CD200R1L, ZMAT3, PLCL2, NEIL3, and LINC00700 genes (p < 1 × 10-5) were closely associated with the COVID-19 severity in Chinese population. Our study confirmed that new genetic variant loci had significant association with SARS-CoV-2 infection and the COVID-19 severity in Chinese population, which provided new clues for the studies on the susceptibility of SARS-CoV-2 infection and the COVID-19 severity. These findings may give a better understanding on the molecular pathogenesis of COVID-19 and genetic basis of heterogeneous susceptibility, with potential impact on new therapeutic options.

Longitudinal Dynamics of the Neutralizing Antibody Response to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a global pandemic with no licensed vaccine or specific antiviral agents for therapy. Little is known about the longitudinal dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific neutralizing antibodies (NAbs) in patients with COVID-19. METHODS: Blood samples (n = 173) were collected from 30 patients with COVID-19 over a 3-month period after symptom onset and analyzed for SARS-CoV-2-specific NAbs using the lentiviral pseudotype assay, coincident with the levels of IgG and proinflammatory cytokines. RESULTS: SARS-CoV-2-specific NAb titers were low for the first 7-10 days after symptom onset and increased after 2-3 weeks. The median peak time for NAbs was 33 days (interquartile range [IQR], 24-59 days) after symptom onset. NAb titers in 93.3% (28/30) of the patients declined gradually over the 3-month study period, with a median decrease of 34.8% (IQR, 19.6-42.4%). NAb titers increased over time in parallel with the rise in immunoglobulin G (IgG) antibody levels, correlating well at week 3 (r = 0.41, P < .05). The NAb titers also demonstrated a significant positive correlation with levels of plasma proinflammatory cytokines, including stem cell factor (SCF), TNF-related apoptosis-inducing ligand (TRAIL), and macrophage colony-stimulating factor (M-CSF). CONCLUSIONS: These data provide useful information regarding dynamic changes in NAbs in patients with COVID-19 during the acute and convalescent phases.

Dicoumarol, an NQO1 inhibitor, blocks cccDNA transcription by promoting degradation of HBx.

BACKGROUND & AIMS: Current antiviral therapies help keep HBV under control, but they are not curative, as they are unable to eliminate the intracellular viral replication intermediate termed covalently closed circular DNA (cccDNA). Therefore, there remains an urgent need to develop strategies to cure CHB. Functional silencing of cccDNA is a crucial curative strategy that may be achieved by targeting the viral protein HBx. METHODS: We screened 2,000 small-molecule compounds for their ability to inhibit HiBiT-tagged HBx (HiBiT-HBx) expression by using a HiBiT lytic detection system. The antiviral activity of a candidate compound and underlying mechanism of its effect on cccDNA transcription were evaluated in HBV-infected cells and a humanised liver mouse model. RESULTS: Dicoumarol, an inhibitor of NAD(P)H:quinone oxidoreductase 1 (NQO1), significantly reduced HBx expression. Moreover, dicoumarol showed potent antiviral activity against HBV RNAs, HBV DNA, HBsAg and HBc protein in HBV-infected cells and a humanised liver mouse model. Mechanistic studies demonstrated that endogenous NQO1 binds to and protects HBx protein from 20S proteasome-mediated degradation. NQO1 knockdown or dicoumarol treatment significantly reduced the recruitment of HBx to cccDNA and inhibited the transcriptional activity of cccDNA, which was associated with the establishment of a repressive chromatin state. The absence of HBx markedly blocked the antiviral effect induced by NQO1 knockdown or dicoumarol treatment in HBV-infected cells. CONCLUSIONS: Herein, we report on a novel small molecule that targets HBx to combat chronic HBV infection; we also reveal that NQO1 has a role in HBV replication through the regulation of HBx protein stability. LAY SUMMARY: Current antiviral therapies for hepatitis B are not curative because of their inability to eliminate covalently closed circular DNA (cccDNA), which persists in the nuclei of infected cells. HBV X (HBx) protein has an important role in regulating cccDNA transcription. Thus, targeting HBx to silence cccDNA transcription could be an important curative strategy. We identified that the small molecule dicoumarol could block cccDNA transcription by promoting HBx degradation; this is a promising therapeutic strategy for the treatment of chronic hepatitis B.

SIRT7 restricts HBV transcription and replication through catalyzing desuccinylation of histone H3 associated with cccDNA minichromosome.

Chronic hepatitis B virus (HBV) infection is a significant public health burden worldwide. HBV covalently closed circular DNA (cccDNA) organized as a minichromosome in nucleus is responsible for viral persistence and is the key obstacle for a cure of chronic hepatitis B (CHB). Recent studies suggest cccDNA transcription is epigenetically regulated by histone modifications, especially histone acetylation and methylation. In the present study, we identified transcriptionally active histone succinylation (H3K122succ) as a new histone modification on cccDNA minichromosome by using cccDNA ChIP-Seq approach. Silent mating type information regulation 2 homolog 7 (SIRT7), as an NAD+-dependent histone desuccinylase, could bind to cccDNA through interaction with HBV core protein where it catalyzed histone 3 lysine 122 (H3K122) desuccinylation. Moreover, SIRT7 acts cooperatively with histone methyltransferase, suppressor of variegation 3-9 homolog 1 (SUV39H1) and SET domain containing 2 (SETD2) to induce silencing of HBV transcription through modulation of chromatin structure. Our data improved the understanding of histone modifications of the cccDNA minichromosome, thus transcriptional silencing of cccDNA may represent a novel antiviral strategy for the prevention or treatment of HBV infection.

A Peptide-Based Magnetic Chemiluminescence Enzyme Immunoassay for Serological Diagnosis of Coronavirus Disease 2019.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel ß-coronavirus, causes severe pneumonia and has spread throughout the globe rapidly. The disease associated with SARS-CoV-2 infection is named coronavirus disease 2019 (COVID-19). To date, real-time reverse-transcription polymerase chain reaction (RT-PCR) is the only test able to confirm this infection. However, the accuracy of RT-PCR depends on several factors; variations in these factors might significantly lower the sensitivity of detection. METHODS: In this study, we developed a peptide-based luminescent immunoassay that detected immunoglobulin (Ig)G and IgM. The assay cutoff value was determined by evaluating the sera from healthy and infected patients for pathogens other than SARS-CoV-2. RESULTS: To evaluate assay performance, we detected IgG and IgM in the sera from confirmed patients. The positive rate of IgG and IgM was 71.4% and 57.2%, respectively. CONCLUSIONS: Therefore, combining our immunoassay with real-time RT-PCR might enhance the diagnostic accuracy of COVID-19.

PRESM: personalized reference editor for somatic mutation discovery in cancer genomics.

MOTIVATION: Accurate detection of somatic mutations is a crucial step toward understanding cancer. Various tools have been developed to detect somatic mutations from cancer genome sequencing data by mapping reads to a universal reference genome and inferring likelihoods from complex statistical models. However, read mapping is frequently obstructed by mismatches between germline and somatic mutations on a read and the reference genome. Previous attempts to develop personalized genome tools are not compatible with downstream statistical models for somatic mutation detection. RESULTS: We present PRESM, a tool that builds personalized reference genomes by integrating germline mutations into the reference genome. The aforementioned obstacle is circumvented by using a two-step germline substitution procedure, maintaining positional fidelity using an innovative workaround. Reads derived from tumor tissue can be positioned more accurately along a personalized reference than a universal reference due to the reduced genetic distance between the subject (tumor genome) and the target (the personalized genome). Application of PRESM's personalized genome reduced false-positive (FP) somatic mutation calls by as much as 55.5%, and facilitated the discovery of a novel somatic point mutation on a germline insertion in PDE1A, a phosphodiesterase associated with melanoma. Moreover, all improvements in calling accuracy were achieved without parameter optimization, as PRESM itself is parameter-free. Hence, similar increases in read mapping and decreases in the FP rate will persist when PRESM-built genomes are applied to any user-provided dataset. AVAILABILITY AND IMPLEMENTATION: The software is available at https://github.com/precisionomics/PRESM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

COVID-19 patients' clinical characteristics, discharge rate, and fatality rate of meta-analysis.

The aim of this study was to analyze the clinical data, discharge rate, and fatality rate of COVID-19 patients for clinical help. The clinical data of COVID-19 patients from December 2019 to February 2020 were retrieved from four databases. We statistically analyzed the clinical symptoms and laboratory results of COVID-19 patients and explained the discharge rate and fatality rate with a single-arm meta-analysis. The available data of 1994 patients in 10 literatures were included in our study. The main clinical symptoms of COVID-19 patients were fever (88.5%), cough (68.6%), myalgia or fatigue (35.8%), expectoration (28.2%), and dyspnea (21.9%). Minor symptoms include headache or dizziness (12.1%), diarrhea (4.8%), nausea and vomiting (3.9%). The results of the laboratory showed that the lymphocytopenia (64.5%), increase of C-reactive protein (44.3%), increase of lactic dehydrogenase (28.3%), and leukocytopenia (29.4%) were more common. The results of single-arm meta-analysis showed that the male took a larger percentage in the gender distribution of COVID-19 patients 60% (95% CI [0.54, 0.65]), the discharge rate of COVID-19 patients was 52% (95% CI [0.34,0.70]), and the fatality rate was 5% (95% CI [0.01,0.11]).

SimPEL: Simulation-based power estimation for sequencing studies of low-prevalence conditions.

Power estimations are important for optimizing genotype-phenotype association study designs. However, existing frameworks are designed for common disorders, and thus ill-suited for the inherent challenges of studies for low-prevalence conditions such as rare diseases and infrequent adverse drug reactions. These challenges include small sample sizes and the need to leverage genetic annotation resources in association analyses for the purpose of ranking potential causal genes. We present SimPEL, a simulation-based program providing power estimations for the design of low-prevalence condition studies. SimPEL integrates the usage of gene annotation resources for association analyses. Customizable parameters, including the penetrance of the putative causal allele and the employed pathogenic scoring system, allow SimPEL to realistically model a large range of study designs. To demonstrate the effects of various parameters on power, we estimated the power of several simulated designs using SimPEL and captured power trends in agreement with observations from current literature on low-frequency condition studies. SimPEL, as a tool, provides researchers studying low-frequency conditions with an intuitive and highly flexible avenue for statistical power estimation. The platform-independent "batteries included" executable and default input files are available at https://github.com/precisionomics/SimPEL.

SIRT3 restricts hepatitis B virus transcription and replication through epigenetic regulation of covalently closed circular DNA involving suppressor of variegation 3-9 homolog 1 and SET domain containing 1A histone methyltransferases.

Hepatitis B virus (HBV) infection remains a major health problem worldwide. Maintenance of the covalently closed circular DNA (cccDNA), which serves as a template for HBV RNA transcription, is responsible for the failure of eradicating chronic HBV during current antiviral therapy. cccDNA is assembled with cellular histone proteins into chromatin, but little is known about the regulation of HBV chromatin by histone posttranslational modifications. In this study, we identified silent mating type information regulation 2 homolog 3 (SIRT3) as a host factor restricting HBV transcription and replication by screening seven members of the sirtuin family, which is the class III histone deacetylase. Ectopic SIRT3 expression significantly reduced total HBV RNAs, 3.5-kb RNA, as well as replicative intermediate DNA in HBV-infected HepG2-Na+ /taurocholate cotransporting polypeptide cells and primary human hepatocytes. In contrast, gene silencing of SIRT3 promoted HBV transcription and replication. A mechanistic study found that nuclear SIRT3 was recruited to the HBV cccDNA, where it deacetylated histone 3 lysine 9. Importantly, occupancy of SIRT3 on cccDNA could increase the recruitment of histone methyltransferase suppressor of variegation 3-9 homolog 1 to cccDNA and decrease recruitment of SET domain containing 1A, leading to a marked increase of trimethyl-histone H3 (Lys9) and a decrease of trimethyl-histone H3 (Lys4) on cccDNA. Moreover, SIRT3-mediated HBV cccDNA transcriptional repression involved decreased binding of host RNA polymerase II and transcription factor Yin Yang 1 to cccDNA. Finally, hepatitis B viral X protein could relieve SIRT3-mediated cccDNA transcriptional repression by inhibiting both SIRT3 expression and its recruitment to cccDNA. CONCLUSION: SIRT3 is a host factor epigenetically restricting HBV cccDNA transcription by acting cooperatively with histone methyltransferase; these data provide a rationale for the use of SIRT3 activators in the prevention or treatment of HBV infection. (Hepatology 2018).

Development and application of a simple recombinase polymerase amplification assay for rapid point-of-care detection of feline herpesvirus type 1.

Feline herpesvirus type 1 (FHV-1) is a highly contagious pathogen of domestic cats and other members of the family Felidae. Point-of-care diagnosis of persistent infection in cats is essential for control of its spread. A recombinase polymerase amplification (RPA) assay (RPA-LFD-FHV) combined with a lateral flow dipstrip (LFD) was developed that uses human body heat for incubation. Sensitivity was evaluated by testing a serial dilution of a control plasmid, and specificity was evaluated by testing related viruses. Swab samples from cats with suspected infection were tested by RPA-LFD-FHV, and the results were compared to those obtained by PCR to evaluate its clinical performance. The RPA-FLD-FHV assay was carried out successfully within 20 min, using body heat for incubation. The RPA-FLD-FHV had a detection limit of 103 copies of the FHV-1 gD gene, which was lower than that of PCR, which was 104 copies. The assay could detect templates of FHV-1 but not those of other feline and canine viruses. Viruses in boiled samples could be efficiently detected by the RPA-FLD-FHV. Thirty-one out of the 80 samples were positive by the RPA-FLD-FHV assay, whereas only 27 were positive by PCR. DNA sequencing confirmed that the four samples that were positive by RPA-FLD-FHV but negative by PCR were indeed positive. These results indicate that RPA-FLD-FHV is applicable for clinical use. The RPA-FLD-FHV assay is a simple, rapid, and reliable method for point-of-care diagnosis of FHV-1 infection.