Search

Abstract Retroviral integration into germline DNA can result in the formation of a vertically inherited proviral sequence called an endogenous retrovirus (ERV). Over the course of their evolution, vertebrate genomes have accumulated many thousands of ERV loci. These sequences provide useful retrospective information about ancient retroviruses, and have also played an important role in shaping the evolution of vertebrate genomes. There is an immediate need for a unified system of nomenclature for ERV loci, not only to assist genome annotation, but also to facilitate research on ERVs and their impact on genome biology and evolution. In this review, we examine how ERV nomenclatures have developed, and consider the possibilities for the implementation of a systematic approach for naming ERV loci. We propose that such a nomenclature should not only provide unique identifiers for individual loci, but also denote orthologous relationships between ERVs in different species. In addition, we propose that—where possible—mnemonic links to previous, well-established names for ERV loci and groups should be retained. We show how this approach can be applied and integrated into existing taxonomic and nomenclature schemes for retroviruses, ERVs and transposable elements.

Xenotropic murine leukemia virus-related virus (XMRV) was discovered in 2006 in a search for a viral etiology of human prostate cancer (PC). Substantial interest in XMRV as a potentially new pathogenic human retrovirus was driven by reports that XMRV could be detected in a significant percentage of PC samples, and also in tissues from patients with chronic fatigue syndrome (CFS). After considerable controversy, etiologic links between XMRV and these two diseases were disproven. XMRV was determined to have arisen during passage of a human PC tumor in immunocompromised nude mice, by activation and recombination between two endogenous murine leukemia viruses from cells of the mouse. The resulting XMRV had a xentropic host range, which allowed it replicate in the human tumor cells in the xenograft. This review describes the discovery of XMRV, and the molecular and virological events leading to its formation, XMRV infection in animal models and biological effects on infected cells. Lessons from XMRV for other searches of viral etiologies of cancer are discussed, as well as cautions for researchers working on human tumors or cell lines that have been passed through nude mice, includingpotential biohazards associated with XMRV or other similar xenotropic murine leukemia viruses (MLVs).

While virus growth dynamics have been well-characterized in several infections, data are typically collected once the virus population becomes easily detectable. Earlier dynamics, however, remain less understood. We recently reported unusual early dynamics in an experimental system using adenovirus infection of human embryonic kidney (293) cells. Under identical experimental conditions, inoculation at low infection multiplicities resulted in either robust spread, or in limited spread that eventually stalled, with both outcomes occurring with approximately equal frequencies. The reasons underlying these observations have not been understood. Here, we present further experimental data showing that inhibition of interferon-induced antiviral states in cells results in a significant increase in the percentage of robust infections that are observed, implicating a race between virus replication and the spread of the anti-viral state as a central mechanism. Analysis of a variety of computational models, however, reveals that this alone cannot explain the simultaneous occurrence of both viral growth outcomes under identical conditions, and that additional biological mechanisms have to be invoked to explain the data. One such mechanism is the ability of the virus to overcome the antiviral state through multiple infection of cells. If this is included in the model, two outcomes of viral spread are found to be simultaneously stable, depending on initial conditions. In stochastic versions of such models, the system can go by chance to either state from identical initial conditions, with the relative frequency of the outcomes depending on the strength of the interferon-based anti-viral response, consistent with the experiments. This demonstrates considerable complexity during the early phase of the infection that can influence the ability of a virus to become successfully established. Implications for the initial dynamics of oncolytic virus spread through tumors are discussed.

Retroviruses cause cancers in a variety of animals and humans. Research on retroviruses has provided important insights into mechanisms of oncogenesis in humans, including the discovery of viral oncogenes and cellular proto-oncogenes. The subject of this review is the mechanisms by which retroviruses that do not carry oncogenes (non-acute retroviruses) cause cancers. The common theme is that these tumors result from insertional activation of cellular proto-oncogenes by integration of viral DNA. Early research on insertional activation of proto-oncogenes in virus-induced tumors is reviewed. Research on non-acute retroviruses has led to the discovery of new proto-oncogenes through searches for common insertion sites (CISs) in virus-induced tumors. Cooperation between different proto-oncogenes in development of tumors has been elucidated through the study of retrovirus-induced tumors, and retroviral infection of genetically susceptible mice (retroviral tagging) has been used to identify cellular proto-oncogenes active in specific oncogenic pathways. The pace of proto-oncogene discovery has been accelerated by technical advances including PCR cloning of viral integration sites, the availability of the mouse genome sequence, and high throughput DNA sequencing. Insertional activation has proven to be a significant risk in gene therapy trials to correct genetic defects with retroviral vectors. Studies on non-acute retroviral oncogenesis provide insight into the potential risks, and the mechanisms of oncogenesis.

Jaagsiekte sheep retrovirus (JSRV) is the causative agent of a lung cancer in sheep known as ovine pulmonary adenocarcinoma (OPA). The disease has been identified around the world in several breeds of sheep and goats, and JSRV infection typically has a serious impact on affected flocks. In addition, studies on OPA are an excellent model for human lung carcinogenesis. A unique feature of JSRV is that its envelope (Env) protein functions as an oncogene. The JSRV Env-induced transformation or oncogenesis has been studied in a variety of cell systems and in animal models. Moreover, JSRV studies have provided insights into retroviral genomic RNA export/expression mechanisms. JSRV encodes a trans-acting factor (Rej) within the env gene necessary for the synthesis of Gag protein from unspliced viral RNA. This review summarizes research pertaining to JSRV‑induced pathogenesis, Env transformation, and other aspects of JSRV biology.

Studies of oncogenic viruses have made seminal contributions to the molecular biology of cancer. Key discoveries include the identification of viral oncogenes and cellular proto-oncogenes, elucidation of signal transduction pathways, and identification of tumor suppressor genes. The origins of cancer virology began almost exactly one hundred years ago with the discovery of avian sarcoma and acute leukemia viruses—RNA-containing viruses of the retrovirus family. The study of animal cancer viruses accelerated beginning in the late 1960s and early 1970s, with the discovery of DNA viruses that could transform cells in culture, and the development of quantitative assays for transformation by DNA and RNA-containing tumor viruses. The discovery of reverse transcriptase in retroviruses in 1970 also greatly accelerated research on these viruses. Indeed RNA and DNA tumor viruses led the way in cancer molecular biology during this era before molecular cloning. It was possible to physically purify virus particles and generate specific hybridization probes for viral DNA and RNA at a time when it was not possible to analyze cellular genes in the same manner. [...]

Oncolytic viruses replicate selectively in tumor cells and can serve as targeted treatment agents. While promising results have been observed in clinical trials, consistent success of therapy remains elusive. The dynamics of virus spread through tumor cell populations has been studied both experimentally and computationally. However, a basic understanding of the principles underlying virus spread in spatially structured target cell populations has yet to be obtained. This paper studies such dynamics, using a newly constructed recombinant adenovirus type-5 (Ad5) that expresses enhanced jellyfish green fluorescent protein (EGFP), AdEGFPuci, and grows on human 293 embryonic kidney epithelial cells, allowing us to track cell numbers and spatial patterns over time. The cells are arranged in a two-dimensional setting and allow virus spread to occur only to target cells within the local neighborhood. Despite the simplicity of the setup, complex dynamics are observed. Experiments gave rise to three spatial patterns that we call "hollow ring structure", "filled ring structure", and "disperse pattern". An agent-based, stochastic computational model is used to simulate and interpret the experiments. The model can reproduce the experimentally observed patterns, and identifies key parameters that determine which pattern of virus growth arises. The model is further used to study the long-term outcome of the dynamics for the different growth patterns, and to investigate conditions under which the virus population eliminates the target cells. We find that both the filled ring structure and disperse pattern of initial expansion are indicative of treatment failure, where target cells persist in the long run. The hollow ring structure is associated with either target cell extinction or low-level persistence, both of which can be viewed as treatment success. Interestingly, it is found that equilibrium properties of ordinary differential equations describing the dynamics in local neighborhoods in the agent-based model can predict the outcome of the spatial virus-cell dynamics, which has important practical implications. This analysis provides a first step towards understanding spatial oncolytic virus dynamics, upon which more detailed investigations and further complexity can be built.

ABSTRACT Murine leukemia viruses (MuLVs) encode two forms of Gag polyprotein: the precursor for the viral core proteins (Pr65gag for Moloney MuLV [M-MuLV]) and a longer glycosylated form (glyco-gag, or gPr80gag). gPr80gag is translated from the same unspliced viral RNA as Pr65gag, from an upstream in-frame CUG initiation codon. As a result, gPr80gag contains 88 unique N-terminal amino acids that include a signal peptide that conducts gPr80gag into the rough endoplasmic reticulum, where it is glycosylated, exported to the cell surface, and cleaved into two proteins of 55 and 40 kDa. The amino-terminal 55-kDa protein remains cell associated with the 88 unique amino acids exposed to the cytosol. We previously showed that gPr80gag facilitates efficient M-MuLV release through lipid rafts. In this report, we found that the unique N-terminal domain of gPr80gag is sufficient to facilitate enhanced M-MuLV particle release from transfected 293T cells. A search for cellular proteins involved in gPr80gag function led to cellular La protein. Overexpression of mouse or human La enhanced M-MuLV particle release in the absence of glyco-gag, and the released virus had a reduced buoyant density characteristic of increased cholesterol content. Moreover, small interfering RNA (siRNA) knockdown of human La abolished glyco-gag enhancement of M-MuLV release. These results implicate La as a cellular protein involved in M-MuLV glyco-gag function. We also found that overexpression of mouse or human La could enhance HIV-1 release in the absence of gPr80gag. Therefore, M-MuLV and HIV-1 may share a pathway for release through lipid rafts involving La. IMPORTANCE Retroviruses cause diseases such as leukemia and AIDS. An important aspect of viral replication is how viruses are released from infected cells. We previously found that a unique protein encoded by murine leukemia viruses (MuLVs), glyco-gag (or gPr80gag), enhances efficient virus release through cholesterol-rich membrane subdomains called lipid rafts. In this study, we found that the N-terminal domain of gPr80gag is sufficient to enhance viral release. A search for cellular proteins that participate in gPr80gag function led to cellular La protein. Overexpression of La phenocopied glyco-gag in enhancing M-MuLV release, and knockdown of La abolished glyco-gag function. M-MuLV glyco-gag also enhanced release of HIV-1, as did overexpression La in the absence of glyco-gag. Thus, M-MuLV and HIV-1 may share a cellular pathway for release through lipid rafts involving La. These results may also be relevant for other viruses that are released through lipid rafts.

Non-typhoidal Salmonella remains a leading cause of foodborne illness in the United States, with food animal products serving as a key conduit for transmission. The emergence of antimicrobial resistance (AMR) poses an additional public health concern warranting better understanding of its epidemiology. In this study, 958 retail meat samples collected from January to December 2018 in California were tested for Salmonella. From multivariable logistic regression, there was a 6.47 (90% CI 2.29-18.27), 3.81 (90% CI 1.29-11.27), and 3.12 (90% CI 1.03-9.45) higher odds of contamination in samples purchased in the fall, spring, and summer than in winter months, respectively, and a 3.70 (90% CI 1.05-13.07) higher odds in ground turkey compared to pork samples. Fourteen distinct serotypes and 17 multilocus sequence types were identified among the 43 isolates recovered, with S. Kentucky (25.58%), S. Reading (18.60%), S. Infantis (11.63%), and S. Typhimurium (9.30%) comprising the top serotypes. High prevalence of resistance was observed in retail chicken isolates for streptomycin (12/23, 52.17%) and tetracycline (12/23, 52.17%), in ground turkey isolates for ampicillin (8/15, 53.34%), and in ground beef isolates for nalidixic acid (2/3, 66.67%). Fourteen (32.56%) were susceptible to all antimicrobials tested, 11 (25.58%) were resistant to one drug, and 12 (27.91%) were resistant to two drugs. The remaining six isolates (13.95%) were multidrug-resistant (MDR, ≥3 drug classes) S. Infantis (n = 4), S. Reading (n = 1), and S. Kentucky (n = 1). Whole-genome sequencing (WGS) identified 16 AMR genes and 17 plasmid replicons, including bla CTX-M-65 encoding ceftriaxone resistance and a D87Y mutation in gyrA conferring resistance to nalidixic acid and reduced susceptibility to ciprofloxacin. The IncFIB(pN55391) replicon previously identified in connection to the worldwide dissemination of pESI-like mega plasmid carriage in an emerged S. Infantis clone was detected in four of the six MDR isolates. Genotypes from WGS showed high concordance with phenotype with overall sensitivity and specificity of 95.31% and 100%, respectively. This study provides insight into the AMR profiles of a diversity of Salmonella serotypes isolated from retail meat products in California and highlights the value of routine retail food surveillance for the detection and characterization of AMR in foodborne pathogens.

There is increasing evidence that retail food may serve as a source of Escherichia coli that causes community-acquired urinary tract infections, but the impact of this source in a community is not known. We conducted a prospective, population-based study in one community to examine the frequency of recovery of uropathogenic E. coli genotypes from retail meat samples. We analyzed E. coli isolates from consecutively collected urine samples of patients suspected to have urinary tract infections (UTIs) at a university-affiliated health service and retail meat samples from the same geographic region. We genotyped all E. coli isolates by multilocus sequence typing (MLST) and tested them for antimicrobial susceptibility. From 2016 to 2017, we cultured 233 E. coli isolates from 230 (21%) of 1,087 urine samples and 177 E. coli isolates from 120 (28%) of 427 retail meat samples. Urine samples contained 61 sequence types (STs), and meat samples had 95 STs; 12 STs (ST10, ST38, ST69, ST80, ST88, ST101, ST117, ST131, ST569, ST906, ST1844, and ST2562) were common to both. Thirty-five (81%) of 43 meat isolates among the 12 STs were from poultry. Among 94 isolates in the 12 STs, 26 (60%) of 43 retail meat isolates and 15 (29%) of 51 human isolates were pan-susceptible (P < 0.005). We found that 21% of E. coli isolates from suspected cases of UTIs belonged to STs found in poultry. Poultry may serve as a possible reservoir of uropathogenic E. coli (UPEC). Additional studies are needed to demonstrate transmission pathways of these UPEC genotypes and their food sources.IMPORTANCE Community-acquired urinary tract infection caused by Escherichia coli is one of the most common infectious diseases in the United States, affecting approximately seven million women and costing approximately 11.6 billion dollars annually. In addition, antibiotic resistance among E. coli bacteria causing urinary tract infection continues to increase, which greatly complicates treatment. Identifying sources of uropathogenic E. coli and implementing prevention measures are essential. However, the reservoirs of uropathogenic E. coli have not been well defined. This study demonstrated that poultry sold in retail stores may serve as one possible source of uropathogenic E. coli This finding adds to a growing body of evidence that suggests that urinary tract infection may be a food-borne disease. More research in this area can lead to the development of preventive strategies to control this common and costly infectious disease.

Background: Dynamic susceptibility contrast (DSC) MR perfusion is a frequently-used technique for neurovascular imaging. The progress of a bolus of contrast agent through the tissue of the brain is imaged via a series of T2*-weighted MRI scans. Clinically relevant parameters such as blood flow and Tmax can be calculated by deconvolving the contrast-time curves with the bolus shape (arterial input function). In acute stroke, for instance, these parameters may help distinguish between the likely salvageable tissue and irreversibly damaged infarct core. Deconvolution typically relies on singular value decomposition (SVD): however, studies have shown that these algorithms are very sensitive to noise and artifacts present in the image and therefore may introduce distortions that influence the estimated output parameters. Methods: In this work, we present a machine learning approach to the estimation of perfusion parameters in DSC-MRI. Various machine learning models using as input the raw MR source data were trained to reproduce the output of an FDA approved commercial implementation of the SVD deconvolution algorithm. Experiments were conducted to determine the effect of training set size, optimal patch size, and the effect of using different machine-learning models for regression. Results: Model performance increased with training set size, but after 5,000 samples (voxels) this effect was minimal. Models inferring perfusion maps from a 5 by 5 voxel patch outperformed models able to use the information in a single voxel, but larger patches led to worse performance. Random Forest models produced had the lowest root mean squared error, with neural networks performing second best: however, a phantom study revealed that the random forest was highly susceptible to noise levels, while the neural network was more robust. Conclusion: The machine learning-based approach produces estimates of the perfusion parameters invariant to the noise and artifacts that commonly occur as part of MR acquisition. As a result, better robustness to noise is obtained, when evaluated against the FDA approved software on acute stroke patients and simulated phantom data.

Purpose Circulating tumor cells (CTCs) are known to be associated with late recurrence and poor prognosis in breast cancer (BC). Different CTC enrichment platforms have different CTC cut-off values for poor prognosis. This study aimed to evaluate whether preoperative CTCs could be a prognostic factor for early recurrence of disease in BC patients with resectable tumors, and to ascertain the CTC cut-off value for early recurrence with CytoSorter® CTC system. Methods Thirty-six stage II and III BC patients who had preoperative (pre-op) CTC detection and underwent a mastectomy or lumpectomy for curative intent between January and May 2018 were enrolled in this retrospective study. CTC detection was performed using CytoSorter® CTC system. Correlations of patients’ demographics, clinicopathological characteristics, adjuvant therapies and CTCs with relapse and survival were evaluated. Results CTCs were detected in 32 out of 36 patients before surgery. Nine patients developed relapses during follow-up, and seven of them were distant recurrence. Univariate analysis showed that CTCs were correlated with two-year recurrence free survival (RFS) and distant RFS (D-RFS) (P = 0.013 and 0.029, respectively). Two-year RFS and D-RFS were 85.2% and 88.9%, respectively, for patients with

Purpose Status of epithelial-mesenchymal transition (EMT) varies from tumors to tumors. Epithelial cell adhesion molecule (EpCAM) and cell surface vimentin (CSV) are the most common used targets for isolating epithelial and mesenchymal CTCs, respectively. This study aimed to identify a suitable CTC capturing antibody for CTC enrichment in each solid tumor by comparing CTC detection rates with EpCAM and CSV antibodies in different solid tumors. Methods Treatment-naive patients with confirmed cancer diagnosis and healthy people who have performed CTC detection between April 2017 and May 2018 were included in this study. CTC detection was performed with CytoSorter® CTC system using either EpCAM or CSV antibody. In total, 853 CTC results from 690 cancer patients and 72 healthy people were collected for analysis. The performance of CTC capturing antibody was determined by the CTC detection rate. Results EpCAM has the highest CTC detection rate of 84.09% in CRC, followed by BCa (78.32%). CTC detection rates with EpCAM antibody are less than 40% in HCC (25%), PDAC (32.5%) and OC (33.33%). CSV has the highest CTC detection rate of 90% in sarcoma, followed by BC (85.71%), UC (84.62%), OC (83.33%) and BCa (81.82%). CTC detection rates with CSV antibody are over 60% in all 14 solid tumors. Except for CRC, CSV has better performances than EpCAM in most solid tumors regarding the CTC detection rates. Conclusion EpCAM can be used as a target to isolate CTCs in CRC, LC, GC, BCa, EC, HNSCC, CC and PCa, especially in CRC, while CSV can be used in most solid tumors for isolating CTCs.