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Simon Rayner joined the FEBS Open Bio Editorial Board in March 2022. Currently, he is Professor of Bioinformatics at Oslo University Hospital and the University of Oslo in Norway. He received a PhD in computational solid‐state physics from the University of East Anglia, in 1991, and served as a Lecturer at the Dept of Physics in the University of Texas before working as a Research Fellow at the McDermott Centre for Human Growth and Development, University of Texas Southwestern Medical Centre at Dallas (UTSW). He went on to become Assistant Professor at the Depts of Biochemistry & Internal Medicine, UTSW before co‐founding BioAutomation Inc. where he developed DNA & RNA synthesis technology and was involved in the Human Genome Project. Simon is a CAS scholar and has also been a Professor of Bioinformatics at the Chinese Agricultural University in Beijing. Here, he tells us about his multi‐disciplinary career transitions, including experience working on three continents, and reflects on implementing open science and fair data.

The presence of human cytomegalovirus (HCMV) in glioblastoma (GBM) and improved outcomes of GBM patients receiving therapies targeting the virus have implicated HCMV in GBM progression. However, a unifying mechanism that accounts for the contribution of HCMV to the malignant phenotype of GBM remains incompletely defined. Here we have identified SOX2, a marker of glioma stem cells (GSCs), as a key determinant of HCMV gene expression in gliomas. Our studies demonstrated that SOX2 downregulated promyelocytic leukemia (PML) and Sp100 and consequently facilitated viral gene expression by decreasing the amount of PML nuclear bodies in HCMV-infected glioma cells. Conversely, the expression of PML antagonized the effects of SOX2 on HCMV gene expression. Furthermore, this regulation of SOX2 on HCMV infection was demonstrated in a neurosphere assay of GSCs and in a murine xenograft model utilizing xenografts from patient-derived glioma tissue. In both cases, SOX2 overexpression facilitated the growth of neurospheres and xenografts implanted in immunodeficient mice. Lastly, the expression of SOX2 and HCMV immediate early 1 (IE1) protein could be correlated in tissues from glioma patients, and interestingly, elevated levels of SOX2 and IE1 were predictive of a worse clinical outcome. These studies argue that HCMV gene expression in gliomas is regulated by SOX2 through its regulation of PML expression and that targeting molecules in this SOX2-PML pathway could identify therapies for glioma treatment.

Focal lesions of articular cartilage give rise to pain and reduced joint function and may, if left untreated, lead to osteoarthritis. Implantation of in vitro generated, scaffold-free autologous cartilage discs may represent the best treatment option. Here we compare articular chondrocytes (ACs) and bone marrow-derived mesenchymal stromal cells (MSCs) for their ability to make scaffold-free cartilage discs. Articular chondrocytes produced more extracellular matrix per seeded cell than mesenchymal stromal cells. Quantitative proteomics analysis showed that articular chondrocyte discs contained more articular cartilage proteins, while mesenchymal stromal cell discs had more proteins associated with cartilage hypertrophy and bone formation. Sequencing analysis revealed more microRNAs associated with normal cartilage in articular chondrocyte discs, and large-scale target predictions, performed for the first time for in vitro chondrogenesis, suggested that differential expression of microRNAs in the two disc types were important mechanisms behind differential synthesis of proteins. We conclude that articular chondrocytes should be preferred over mesenchymal stromal cells for tissue engineering of articular cartilage.

Congenital cytomegalovirus (cCMV) infection is the leading infectious cause of neurodevelopmental disorders. However, the neuropathogenesis remains largely elusive due to a lack of informative animal models. In this study, we developed a congenital murine CMV (cMCMV) infection mouse model with high survival rate and long survival period that allowed long-term follow-up study of neurodevelopmental disorders. This model involves in utero intracranial injection and mimics many reported clinical manifestations of cCMV infection in infants, including growth restriction, hearing loss, and impaired cognitive and learning-memory abilities. We observed that abnormalities in MRI/CT neuroimaging were consistent with brain hemorrhage and loss of brain parenchyma, which was confirmed by pathological analysis. Neuropathological findings included ventriculomegaly and cortical atrophy associated with impaired proliferation and migration of neural progenitor cells in the developing brain at both embryonic and postnatal stages. Robust inflammatory responses during infection were shown by elevated inflammatory cytokine levels, leukocyte infiltration, and activation of microglia and astrocytes in the brain. Pathological analyses and CT neuroimaging revealed brain calcifications induced by cMCMV infection and cell death via pyroptosis. Furthermore, antiviral treatment with ganciclovir significantly improved neurological functions and mitigated brain damage as shown by CT neuroimaging. These results demonstrate that this model is suitable for investigation of mechanisms of infection-induced brain damage and long-term studies of neurodevelopmental disorders, including the development of interventions to limit CNS damage associated with cCMV infection.

BackgroundMethotrexate (MTX) is the first line treatment of rheumatoid arthritis (RA), and methylation changes in bulk T cells have been reported after treatment with MTX. We have investigated cell-type specific DNA methylation changes across the genome in naïve and memory CD4+ T cells before and after MTX treatment of RA patients. DNA methylation profiles of newly diagnosed RA patients (N=9) were assessed by reduced representation bisulfite sequencing.ResultsWe found that MTX treatment significantly influenced DNA methylation levels at multiple CpG sites in both cell populations. Interestingly, we identified differentially methylated sites annotated to two genes; TRIM15 and SORC2, previously reported to predict treatment outcome in RA patients when measured in bulk T cells. Furthermore, several of the genes, including STAT3, annotated to the significant CpG sites are relevant for RA susceptibility or the action of MTX.ConclusionWe detected CpG sites that were associated with MTX treatment in CD4+ naïve and memory T cells isolated from RA patients. Several of these sites overlap genetic regions previously associated with RA risk and MTX treatment outcome.

Rheumatoid arthritis (RA) is a complex disease with a wide range of underlying susceptibility factors. Recently, dysregulation of microRNAs (miRNAs) in RA have been reported in several immune cell types from blood. However, B cells have not been studied in detail yet. Given the autoimmune nature of RA with the presence of autoantibodies, CD19+ B cells are a key cell type in RA pathogenesis and alterations in CD19+ B cell subpopulations have been observed in patient blood. Therefore, we aimed to reveal the global miRNA repertoire and to analyze miRNA expression profile differences in homogenous RA patient phenotypes in blood-derived CD19+ B cells. Small RNA sequencing was performed on CD19+ B cells of newly diagnosed untreated RA patients (n=10), successfully methotrexate (MTX) treated RA patients in remission (MTX treated RA patients, n=18) and healthy controls (n=9). The majority of miRNAs was detected across all phenotypes. However, significant expression differences between MTX treated RA patients and controls were observed for 27 miRNAs, while no significant differences were seen between the newly diagnosed patients and controls. Several of the differentially expressed miRNAs were previously found to be dysregulated in RA including miR-223-3p, miR-486-3p and miR-23a-3p. MiRNA target enrichment analysis, using the differentially expressed miRNAs and miRNA-target interactions from miRTarBase as input, revealed enriched target genes known to play important roles in B cell activation, differentiation and B cell receptor signaling, such as STAT3, PRDM1 and PTEN. Interestingly, many of those genes showed a high degree of correlated expression in CD19+ B cells in contrast to other immune cell types. Our results suggest important regulatory functions of miRNAs in blood-derived CD19+ B cells of MTX treated RA patients and motivate for future studies investigating the interactive mechanisms between miRNA and gene targets, as well as the possible predictive power of miRNAs for RA treatment response.

Background: Differences in DNA methylation have been reported in B and T lymphocyte populations, including CD4+ T cells, isolated from rheumatoid arthritis (RA) patients when compared to healthy controls. CD4+ T cells are a heterogeneous cell type with subpopulations displaying distinct DNA methylation patterns. In this study, we investigated DNA methylation using reduced representation bisulfite sequencing in two CD4+ T cell populations (CD4+ memory and naïve cells) in three groups: newly diagnosed, disease modifying antirheumatic drugs (DMARD) naïve RA patients (N = 11), methotrexate (MTX) treated RA patients (N = 18), and healthy controls (N = 9) matched for age, gender and smoking status.Results: Analyses of these data revealed significantly more differentially methylated positions (DMPs) in CD4+ memory than in CD4+ naïve T cells (904 vs. 19 DMPs) in RA patients compared to controls. The majority of DMPs (72%) identified in newly diagnosed and DMARD naïve RA patients with active disease showed increased DNA methylation (39 DMPs), whereas most DMPs (80%) identified in the MTX treated RA patients in remission displayed decreased DNA methylation (694 DMPs). Interestingly, we also found that about one third of the 101 known RA risk loci overlapped (±500 kb) with the DMPs. Notably, introns of the UBASH3A gene harbor both the lead RA risk SNP and two DMPs in CD4+ memory T cells.Conclusion: Our results suggest that RA associated DNA methylation differences vary between the two T cell subsets, but are also influenced by RA characteristics such as disease activity, disease duration and/or MTX treatment.

It has been reported that several aspects of human health could be disturbed during a long-term isolated environment (for instance, the Mars-500 mission), including psychiatric disorders, circadian disruption, temporal dynamics of gut microbiota, immune responses, and physical-activity-related neuromuscular performance. Nevertheless, the mechanisms underlying these disturbances and the interactions among different aspects of human adaptation to extreme environments remain to be elucidated. Epigenetic features, like DNA methylation, might be a linking mechanism that explains the involvement of environmental factors between the human genome and the outcome of health. We conducted an exploration of personalized longitudinal DNA methylation patterns of the peripheral whole blood cells, profiling six subjects across six sampling points in the Mars-500 mission. Specifically, we developed a Personalized Epigenetic-Phenotype Synchronization Analysis (PeSa) algorithm to explore glucose- and mood-state-synchronized DNA methylation sites, focusing on finding the dynamic associations between epigenetic patterns and phenotypes in each individual, and exploring the underling epigenetic connections between glucose and mood-state disturbance. Results showed that DMPs (differentially methylated-probes) were significantly enriched in pathways related to glucose metabolism (Type II diabetes mellitus pathway), mood state (Long-term depression) and circadian rhythm (Circadian entrainment pathway) during the mission. Furthermore, our data revealed individualized glucose-synchronized and mood-state-synchronized DNA methylation sites, and PTPRN2 was found to be associated with both glucose and mood state disturbances across all six subjects. Our findings suggest that personalized phenotype-synchronized epigenetic features could reflect the effects on the human body, including the disturbances of glucose and mood-states. The association analysis of DNA methylation and phenotypes, like the PeSa analysis, could provide new possibilities in understanding the intrinsic relationship between phenotypic changes of the human body adapting to long-term isolation environmental factors.

In the original publication the email addresses of corresponding authors have not been displayed. The correct email addresses of corresponding authors are provided in this correction. Fang-Cheng Li (sjwklfc@126.com), Fei Hu (neuron111@163.com), Min-Hua Luo (luomh@wh.iov.cn).

Coordinated surveillance, vaccination and public information efforts have brought the Chinese rabies epizootic under control, but significant numbers of fatalities are still reported annually with some cases occurring in previously rabies free regions. Tibet has remained virtually rabies free for 16 years, but since 2015 one human rabies case has been reported each year. To better understand the origins of these cases, we sequenced three human samples and an additional sample isolated from a dog in 2012. Three genomes were sequenced from brain samples: human case 1 (reported in 2015), human case 3 (2017), and the 2012 dog case. For human case 2 (2016), the rabies N gene was sequenced from a limited saliva sample. Phylogenetic analysis shows that Case 1 (CXZ1501H) and the dog case (CXZ1201D) belong to China IV lineage (equivalent to Arctic-like-2 in global rabies), suggesting an association with a wildlife spillover event. However, Case 2 (CXZ1601H) is placed within the dominant lineage China I, and was most similar with recent strains from neighboring Yunnan province, indicating the current epizootic has finally reached Tibet. Most surprisingly however, was the finding that Case 3 (CXZ1704H) is distinct from other Chinese isolates. This isolate is placed in the Indian Subcontinent clade, similar to recent Nepal strains, indicating that cross-border transmission is a new source for rabies infections. Thus, the complex mixture of the rabies epizootic in Tibet represents a major new challenge for Tibet and national rabies control.

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression by binding to partially complementary regions within the 3'UTR of their target genes. Computational methods play an important role in target prediction and assume that the miRNA "seed region" (nt 2 to 8) is required for functional targeting, but typically only identify ∼80% of known bindings. Recent studies have highlighted a role for the entire miRNA, suggesting that a more flexible methodology is needed. We present a novel approach for miRNA target prediction based on Deep Learning (DL) which, rather than incorporating any knowledge (such as seed regions), investigates the entire miRNA and 3'TR mRNA nucleotides to learn a uninhibited set of feature descriptors related to the targeting process. We collected more than 150,000 experimentally validated homo sapiens miRNA:gene targets and cross referenced them with different CLIP-Seq, CLASH and iPAR-CLIP datasets to obtain ∼20,000 validated miRNA:gene exact target sites. Using this data, we implemented and trained a deep neural network-composed of autoencoders and a feed-forward network-able to automatically learn features describing miRNA-mRNA interactions and assess functionality. Predictions were then refined using information such as site location or site accessibility energy. In a comparison using independent datasets, our DL approach consistently outperformed existing prediction methods, recognizing the seed region as a common feature in the targeting process, but also identifying the role of pairings outside this region. Thermodynamic analysis also suggests that site accessibility plays a role in targeting but that it cannot be used as a sole indicator for functionality. Data and source code available at: https://bitbucket.org/account/user/bipous/projects/MIRAW.

Zika virus (ZIKV) infection is associated with severe neurological defects in fetuses and newborns, such as microcephaly. However, the underlying mechanisms remain to be elucidated. In this study, proteomic analysis on ZIKV-infected primary human fetal neural progenitor cells (NPCs) revealed that virus infection altered levels of cellular proteins involved in NPC proliferation, differentiation and migration. The transcriptional levels of some of the altered targets were also confirmed by qRT-PCR. Among the altered proteins, doublecortin (DCX) plays an important role in NPC differentiation and migration. Results showed that ZIKV infection downregulated DCX, at both mRNA and protein levels, as early as 1 day post infection (1 dpi), and lasted throughout the virus replication cycle (4 days). The downregulation of DCX was also observed in a ZIKV-infected fetal mouse brain model, which displayed decreased body weight, brain size and weight, as well as defective cortex structure. By screening the ten viral proteins of ZIKV, we found that both the expression of NS4A and NS5 were correlated with the downregulation of both mRNA and protein levels of DCX in NPCs. These data suggest that DCX is modulated following infection of the brain by ZIKV. How these observed changes of DCX expression translate in the pathological consequences of ZIKV infection and if other cellular proteins are equally involved remains to be investigated.

Congenital human cytomegalovirus (HCMV) infection is the leading cause of neurological disabilities in children worldwide, but the mechanisms underlying these disorders are far from well-defined. HCMV infection has been shown to dysregulate the Notch signaling pathway in human neural progenitor cells (NPCs). As an important downstream effector of Notch signaling, the transcriptional regulator Hairy and Enhancer of Split 1 (Hes1) is essential for governing NPC fate and fetal brain development. In the present study, we report that HCMV infection downregulates Hes1 protein levels in infected NPCs. The HCMV 72-kDa immediate-early 1 protein (IE1) is involved in Hes1 degradation by assembling a ubiquitination complex and promoting Hes1 ubiquitination as a potential E3 ubiquitin ligase, followed by proteasomal degradation of Hes1. Sp100A, an important component of PML nuclear bodies, is identified to be another target of IE1-mediated ubiquitination. A C-terminal acidic region in IE1, spanning amino acids 451 to 475, is required for IE1/Hes1 physical interaction and IE1-mediated Hes1 ubiquitination, but is dispensable for IE1/Sp100A interaction and ubiquitination. Our study suggests a novel mechanism linking downregulation of Hes1 protein to neurodevelopmental disorders caused by HCMV infection. Our findings also complement the current knowledge of herpesviruses by identifying IE1 as the first potential HCMV-encoded E3 ubiquitin ligase.

A necessary pre-processing data analysis step is the removal of adapter sequences from the raw reads. While most adapter trimming tools require adapter sequence as an essential input, adapter information is often incomplete or missing. This can impact quantification of features, reproducibility of the study and might even lead to erroneous conclusions. Here, we provide examples to highlight the importance of specifying the adapter sequence by demonstrating the effect of using similar but different adapter sequences and identify additional potential sources of errors in the adapter trimming step. Finally, we propose solutions by which users can ensure their small RNA-seq data is fully annotated with adapter information.

Cancer is a disease associated with the deregulation of multiple gene networks. Microarray data has permitted researchers to identify gene panel markers for diagnosis or prognosis of cancer but these are not sufficient to make specific mechanistic assertions about phenotype switches. We propose a strategy to identify putative mechanisms of cancer phenotypes by protein-protein interactions (PPI). We first extracted the logic status of a PPI via the relative expression of the corresponding gene pair. The joint association of a gene pair on a cancer phenotype was calculated by entropy minimization and assessed using a support vector machine. A typical predictor is “If Src high-expression, and Cav-1 low-expression, then cancer.” We achieved 90% accuracy on test data with a majority of predictions associated with the MAPK pathway, focal adhesion, apoptosis and cell cycle. Our results can aid in the development of phenotype discrimination biomarkers and identification of putative therapeutic interference targets for drug development.

In China, rabies remains an ongoing threat to public health. Although control efforts have been effective in reducing the number of annual cases, the virus continues to spread into new areas. Tibet, Qinghai, Gansu and Ningxia in western China have, until recently, reported only a handful of events. However, since 2011, there have been increasing numbers of cases recorded in these areas. In this study, we report the collection and analysis of samples collected from these regions. We find that cases originate from two different sources. Strains collected from Gansu and Ningxia are closely related to the primary lineage associated with the current epizootic, whereas those from Tibet and Qinghai are related to the Arctic-like-2 lineage that is most commonly associated with wildlife cases in China. Thus, it appears that while the epizootic is beginning to encroach into Gansu and Ningxia, Tibet and Qinghai a significant number of rabies cases originate from wildlife.

Identifying patients most responsive to specific chemotherapy agents in neoadjuvant settings can help to maximize the benefits of treatment and minimize unnecessary side effects. Metagene approaches that predict response based on gene expression signatures derived from an associative analysis of clinical data can identify chance associations caused by the heterogeneity of a tumor, leading to reproducibility issues in independent validations. In this study, to incorporate information from drug mechanisms of action, we explore the potential of microRNA regulation networks as a new feature space for identifying predictive markers. We introduce a measure we term the CoMi (Context-specific-miRNA-regulation) pattern to represent a descriptive feature of the miRNA regulation network in the transcriptome. We examine whether the modifications to the CoMi pattern on specific biological processes are a useful representation of drug action by predicting the response to neoadjuvant Paclitaxel treatment in breast cancer and show that the drug counteracts the CoMi network dysregulation induced by tumorigenesis. We then generate a quantitative testbed to investigate the ability of the CoMi pattern to distinguish FDA approved breast cancer drugs from other FDA approved drugs not related to breast cancer. We also compare the ability of the CoMi and metagene methods to predict response to neoadjuvant Paclitaxel treatment in clinical cohorts. We find the CoMi method outperforms the metagene method, achieving area under curve (AUC) values of 0.78 and 0.66 respectively. Furthermore, several of the predicted CoMi features highlight the network-based mechanism of drug resistance. Thus, our study suggests that explicitly modeling the drug action using network biology provides a promising approach for predictive marker discovery.

China has seen a massive resurgence of rabies cases in the last 15 years with more than 25,000 human fatalities. Initial cases were reported in the southwest but are now reported in almost every province. There have been several phylogenetic investigations into the origin and spread of the virus within China but few reports investigating the impact of the epidemic on neighboring countries. We therefore collected nucleoprotein sequences from China and South East Asia and investigated their phylogenetic and phylogeographic relationship. Our results indicate that within South East Asia, isolates mainly cluster according to their geographic origin. We found evidence of sporadic exchange of strains between neighboring countries, but it appears that the major strain responsible for the current Chinese epidemic has not been exported. This suggests that national geographical boundaries and border controls are effective at halting the spread of rabies from China into adjacent regions. We further investigated the geographic structure of Chinese sequences and found that the current epidemic is dominated by variant strains that were likely present at low levels in previous domestic epidemics. We also identified epidemiological linkages between high incidence provinces consistent with observations based on surveillance data from human rabies cases.

Rabies remains a serious problem in China with three epidemics since 1949 and the country in the midst of the third epidemic. Significantly, the control of each outbreak has been followed by a rapid reemergence of the disease. In 2005, the government implemented a rabies national surveillance program that included the collection and screening of almost 8,000 samples. In this work, we analyzed a Chinese dataset comprising 320 glycoprotein sequences covering 23 provinces and eight species, spanning the second and third epidemics. Specifically, we investigated whether the three epidemics are associated with a single reemerging lineage or a different lineage was responsible for each epidemic. Consistent with previous results, phylogenetic analysis identified six lineages, China I to VI. Analysis of the geographical composition of these lineages revealed they are consistent with human case data and reflect the gradual emergence of China I in the third epidemic. Initially, China I was restricted to south China and China II was dominant. However, as the epidemic began to spread into new areas, China I began to emerge, whereas China II remained confined to south China. By the latter part of the surveillance period, almost all isolates were China I and contributions from the remaining lineages were minimal. The prevalence of China II in the early stages of the third epidemic and its established presence in wildlife suggests that it too replaced a previously dominant lineage during the second epidemic. This lineage replacement may be a consequence of control programs that were dominated by dog culling efforts as the primary control method in the first two epidemics. This had the effect of reducing dominant strains to levels comparable with other localized background stains. Our results indicate the importance of effective control strategies for long term control of the disease.

INTRODUCTION: The Hepatitis B Virus (HBV) genome contains four ORFs, S (surface), P (polymerase), C (core) and X. S is completely overlapped by P and as a consequence the overlapping region is subject to distinctive evolutionary constraints compared to the remainder of the genome. Specifically, a non-synonymous substitution in one coding frame may produce a synonymous substitution in the alternative frame, suggesting a possible conflict between requirements for diversifying and purifying forces. To examine how these contrasting requirements are balanced within this region, we investigated the relationship amongst positive selection sites, conserved regions, epitopes and elements of protein structure to consider how HBV balances the contrasting evolutionary pressures. METHODOLOGY/RESULTS: 323 HBV genotype D genome sequences were collected and analyzed to identify sites under positive selection and highly conserved regions. Epitopes sequences were retrieved from previously published experimental studies stored in the Immune Epitope Database. Predicted secondary structures were used to investigate the association between structure and conservation. Entropy was used as a measure of conservation and bivariate logistic regression was used to investigate the relationship between positive selection/conserved sites and epitope/secondary structure regions. Our results indicate: (i) conservation in S is primarily dictated by α-helix elements in the protein structure, (ii) variable residues are mainly located in PreS, the major hydrophilic region (MHR) and the C-terminus, (iii) epitopes in S, which are directly targeted by the host immune system, are significantly associated with sites under positive selection. CONCLUSIONS: The highly variable spacer domain in P, which corresponds to PreS in S, appears to act as a harbor for the accumulation of mutations that can provide flexibility for conformational changes and responding to immune pressure.

Background and objectivesRecent years have seen a rapid increase in the number of rabies cases in China and an expansion in the geographic distribution of the virus. In spite of the seriousness of the outbreak and increasing number of fatalities, little is known about the phylogeography of the disease in China. In this study, we report an analysis of a set of Nucleocapsid sequences consisting of samples collected through the trial Chinese National Surveillance System as well as publicly available sequences. This sequence set represents the most comprehensive dataset from China to date, comprising 210 sequences (including 57 new samples) from 15 provinces and covering all epidemic regions. Using this dataset we investigated genetic diversity, patterns of distribution, and evolutionary history.ResultsOur analysis indicates that the rabies virus in China is primarily defined by two clades that exhibit distinct population subdivision and translocation patterns and that contributed to the epidemic in different ways. The younger clade originated around 1992 and has properties that closely match the observed spread of the recent epidemic. The older clade originated around 1960 and has a dispersion pattern that suggests it represents a strain associated with a previous outbreak that remained at low levels throughout the country and reemerged in the current epidemic.ConclusionsOur findings provide new insight into factors associated with the recent epidemic and are relevant to determining an effective policy for controlling the virus.

BACKGROUND: The family Tymoviridae comprises three plant virus genera, including Tymovirus, Marafivirus, and Maculavirus, which are found in most parts of the world and cause severe agricultural losses. We describe a putatively novel member of the family Tymoviridae, which is isolated from mosquitoes (Culex spp.), referred to as CuTLV. METHODS AND RESULTS: The CuTLV was isolated by cell culture, which replicates and causes cytopathic effects in Aedes albopictus C6/36 cells, but not in mammalian BHK-21 or Vero cells. The complete 6471 nucleotide sequence of CuTLV was determined. The genome of CuTLV is predicted to contain three open reading frames (ORFs). The largest ORF1 is 5307 nucleotides (nt) in length and encodes a putative polypeptide of 1769 amino acids (aa), which contains the conserved motifs for the methyltransferase (MTR), Tymovirus endopeptidase (PRO), helicase (HEL), and RNA-dependent RNA polymerase (RdRp) of the replication-associated proteins (RPs) of positive-stranded RNA viruses. In contrast, the ORF1 sequence does not contain the so-called "tymobox" or "marafibox", the conserved subgenomic RNA promoter present in all tymoviruses or marafiviruses, respectively. ORF2 and ORF3 putatively encode a 248-aa coat protein (CP) and a proline-rich 149-aa polypeptide. The whole genomic nucleotide identity of CuTLV with other members of family Tymoviridae ranged from 46.2% (ChiYMV) to 52.4% (GFkV). Phylogenetic analysis based on the putative RP and CP genes of CuTLV demonstrated that the virus is most closely related to viruses in the genus Maculavirus. CONCLUSIONS: The CuTLV is a novel virus related to members of the family Tymoviridae, with molecular characters that are distinct from those of tymoviruses, marafiviruses, and other maculaviruses or macula-like viruses. This is the first report of the isolation of a Tymoviridae-like virus from mosquitoes. Further investigations are required to clarify the origin, replication strategy, and the public health or agricultural importance of the CuTLV.

Direct cloning of PCR fragments by TA cloning or blunt end ligation are two simple methods which would greatly benefit high-throughput (HTP) cloning constructions if the efficiency can be improved. In this study, we have developed a ribosomal binding site (RBS) switching strategy for direct cloning of PCR fragments. RBS is an A/G rich region upstream of the translational start codon and is essential for gene expression. Change from A/G to T/C in the RBS blocks its activity and thereby abolishes gene expression. Based on this property, we introduced an inactive RBS upstream of a selectable marker gene, and designed a fragment insertion site within this inactive RBS. Forward and reverse insertions of specifically tailed fragments will respectively form an active and inactive RBS, thus all background from vector self-ligation and fragment reverse insertions will be eliminated due to the non-expression of the marker gene. The effectiveness of our strategy for TA cloning and blunt end ligation are confirmed. Application of this strategy to gene over-expression, a bacterial two-hybrid system, a bacterial one-hybrid system, and promoter bank construction are also verified. The advantages of this simple procedure, together with its low cost and high efficiency, makes our strategy extremely useful in HTP cloning constructions.

The high rates of failure in oncology drug clinical trials highlight the problems of using pre-clinical data to predict the clinical effects of drugs. Patient population heterogeneity and unpredictable physiology complicate pre-clinical cancer modeling efforts. We hypothesize that gene networks associated with cancer outcome in heterogeneous patient populations could serve as a reference for identifying drug effects. Here we propose a novel in vivo genetic interaction which we call 'synergistic outcome determination' (SOD), a concept similar to 'Synthetic Lethality'. SOD is defined as the synergy of a gene pair with respect to cancer patients' outcome, whose correlation with outcome is due to cooperative, rather than independent, contributions of genes. The method combines microarray gene expression data with cancer prognostic information to identify synergistic gene-gene interactions that are then used to construct interaction networks based on gene modules (a group of genes which share similar function). In this way, we identified a cluster of important epigenetically regulated gene modules. By projecting drug sensitivity-associated genes on to the cancer-specific inter-module network, we defined a perturbation index for each drug based upon its characteristic perturbation pattern on the inter-module network. Finally, by calculating this index for compounds in the NCI Standard Agent Database, we significantly discriminated successful drugs from a broad set of test compounds, and further revealed the mechanisms of drug combinations. Thus, prognosis-guided synergistic gene-gene interaction networks could serve as an efficient in silico tool for pre-clinical drug prioritization and rational design of combinatorial therapies.

BACKGROUND: Plant infection models provide certain advantages over animal models in the study of pathogenesis. However, current plant models face some limitations, e.g., plant and pathogen cannot co-culture in a contained environment. Development of such a plant model is needed to better illustrate host-pathogen interactions. METHODOLOGY/PRINCIPAL FINDINGS: We describe a novel model plant system for the study of human pathogenic bacterial infection on a large scale. This system was initiated by co-cultivation of axenic duckweed (Lemna minor) plants with pathogenic bacteria in 24-well polystyrene cell culture plate. Pathogenesis of bacteria to duckweed was demonstrated with Pseudomonas aeruginosa and Staphylococcus aureus as two model pathogens. P. aeruginosa PAO1 caused severe detriment to duckweed as judged from inhibition to frond multiplication and chlorophyll formation. Using a GFP-marked PAO1 strain, we demonstrated that bacteria colonized on both fronds and roots and formed biofilms. Virulence of PAO1 to duckweed was attenuated in its quorum sensing (QS) mutants and in recombinant strains overexpressing the QS quenching enzymes. RN4220, a virulent strain of S. aureus, caused severe toxicity to duckweed while an avirulent strain showed little effect. Using this system for antimicrobial chemical selection, green tea polyphenols exhibited inhibitory activity against S. aureus virulence. This system was further confirmed to be effective as a pathogenesis model using a number of pathogenic bacterial species. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that duckweed can be used as a fast, inexpensive and reproducible model plant system for the study of host-pathogen interactions, could serve as an alternative choice for the study of some virulence factors, and could also potentially be used in large-scale screening for the discovery of antimicrobial chemicals.