5,537 research outputs found
Unexpected interfarm transmission dynamics during a highly pathogenic avian influenza epidemic
Next-generation sequencing technology is now being increasingly applied to study the within- and between-host population dynamics of viruses. However, information on avian influenza virus evolution and transmission during a naturally occurring epidemic is still limited. Here, we use deep-sequencing data obtained from clinical samples collected from five industrial holdings and a backyard farm infected during the 2013 highly pathogenic avian influenza (HPAI) H7N7 epidemic in Italy to unravel (i) the epidemic virus population diversity, (ii) the evolution of virus pathogenicity, and (iii) the pathways of viral transmission between different holdings and sheds. We show a high level of genetic diversity of the HPAI H7N7 viruses within a single farm as a consequence of separate bottlenecks and founder effects. In particular, we identified the cocirculation in the index case of two viral strains showing a different insertion at the hemagglutinin cleavage site, as well as nine nucleotide differences at the consensus level and 92 minority variants. To assess interfarm transmission, we combined epidemiological and genetic data and identified the index case as the major source of the virus, suggesting the spread of different viral haplotypes from the index farm to the other industrial holdings, probably at different time points. Our results revealed interfarm transmission dynamics that the epidemiological data alone could not unravel and demonstrated that delay in the disease detection and stamping out was the major cause of the emergence and the spread of the HPAI strain
Evolution of experimental design and research techniques in HIV-1 reservoir studies : a systematic review
Although HIV-1 has evolved from a deadly to a chronic disease over the past 20 years, an HIV-1 cure is still lacking due to the presence of persisting cellular viral reservoirs which are spread throughout the body in different anatomical compartments. Hence, the identification and characterization of these HIV-1 reservoirs were the focus of many studies during the past decades. In this review, a systematic literature screening and text mining approach were implemented to assess the evolution in experimental design of these HIV-1 reservoir studies. For this purpose. the online databases PubMed, Web of Science. and ClinicalTrials.gov were consulted and 1768 articles were identified, of which 106 are included in this review. We observed several evolutions that indicate a more structured approach of recent HIV-1 reservoir studies. This includes the use of well-characterized patient cohorts, tissue sampling at several time points and anatomical compartments, the inclusion of patients with different treatment status (on and off antiretroviral therapy), and the implementation of state-of-the-art research techniques such as single genome sequencing. In addition, there is an increased interest and sampling of lymphoid tissues and cerebrospinal fluid together with methods to investigate cellular subsets and HIV-1 sequences. Overall, this review describes an observed shift from detecting and quantifying HIV-1 toward a qualitative in-depth assessment of anatomical reservoirs and cellular subsets playing a role in H1V-1 persistence/latency. These trends coincide with the evolution in focus from controlling HIV-1 replication by currently available antiretroviral therapy toward HIV-1 curative strategies
Gut microbiota in HIV-pneumonia patients is related to peripheral CD4 counts, lung microbiota, and in vitro macrophage dysfunction.
Pneumonia is common and frequently fatal in HIV-infected patients, due to rampant, systemic inflammation and failure to control microbial infection. While airway microbiota composition is related to local inflammatory response, gut microbiota has been shown to correlate with the degree of peripheral immune activation (IL6 and IP10 expression) in HIV-infected patients. We thus hypothesized that both airway and gut microbiota are perturbed in HIV-infected pneumonia patients, that the gut microbiota is related to peripheral CD4+ cell counts, and that its associated products differentially program immune cell populations necessary for controlling microbial infection in CD4-high and CD4-low patients. To assess these relationships, paired bronchoalveolar lavage and stool microbiota (bacterial and fungal) from a large cohort of Ugandan, HIV-infected patients with pneumonia were examined, and in vitro tests of the effect of gut microbiome products on macrophage effector phenotypes performed. While lower airway microbiota stratified into three compositionally distinct microbiota as previously described, these were not related to peripheral CD4 cell count. In contrast, variation in gut microbiota composition significantly related to CD4 cell count, lung microbiota composition, and patient mortality. Compared with patients with high CD4+ cell counts, those with low counts possessed more compositionally similar airway and gut microbiota, evidence of microbial translocation, and their associated gut microbiome products reduced macrophage activation and IL-10 expression and increased IL-1β expression in vitro. These findings suggest that the gut microbiome is related to CD4 status and plays a key role in modulating macrophage function, critical to microbial control in HIV-infected patients with pneumonia
Computational pan-genomics: status, promises and challenges
International audienceMany disciplines, from human genetics and oncology to plant breeding, microbiology and virology, commonly face the challenge of analyzing rapidly increasing numbers of genomes. In case of Homo sapiens, the number of sequenced genomes will approach hundreds of thousands in the next few years. Simply scaling up established bioinformatics pipelines will not be sufficient for leveraging the full potential of such rich genomic data sets. Instead, novel, qualitatively different computational methods and paradigms are needed. We will witness the rapid extension of computational pan-genomics, a new sub-area of research in computational biology. In this article, we generalize existing definitions and understand a pan-genome as any collection of genomic sequences to be analyzed jointly or to be used as a reference. We examine already available approaches to construct and use pan-genomes, discuss the potential benefits of future technologies and methodologies and review open challenges from the vantage point of the above-mentioned biological disciplines. As a prominent example for a computational paradigm shift, we particularly highlight the transition from the representation of reference genomes as strings to representations as graphs. We outline how this and other challenges from different application domains translate into common computational problems, point out relevant bioinformatics techniques and identify open problems in computer science. With this review, we aim to increase awareness that a joint approach to computational pan-genomics can help address many of the problems currently faced in various domains
N Engl J Med
Rapid advances in DNA sequencing technology ("next-generation sequencing") have inspired optimism about the potential of human genomics for "precision medicine." Meanwhile, pathogen genomics is already delivering "precision public health" through more effective investigations of outbreaks of foodborne illnesses, better-targeted tuberculosis control, and more timely and granular influenza surveillance to inform the selection of vaccine strains. In this article, we describe how public health agencies have been adopting pathogen genomics to improve their effectiveness in almost all domains of infectious disease. This momentum is likely to continue, given the ongoing development in sequencing and sequencing-related technologies.CC999999/ImCDC/Intramural CDC HHS/United States2020-02-10T00:00:00Z31881145PMC7008580719
DOES THE GUT MICROBIOTA INFLUENCE THE IMMUNE RESPONSE TO INFLUENZA VACCINATION IN OBESE POPULATIONS?
In the United States and globally, rates of obesity have greatly increased and prevalence is continuing to grow. As of 2014, 35.0% of adult males and 40.4% of adult females in the U.S. were obese, according to the National Health and Nutrition Examination Survey (NHANES).1 Previous research in the Beck lab has demonstrated that vaccinated obese individuals have twice the likelihood of developing influenza or “flu-like-illness” when compared to healthy weight individuals, despite antibody levels above the threshold of protection.2 This is concerning because the influenza vaccination is the single most effective method of protection. What is not understood is the mechanisms underlying this difference in obese individuals. Previous work in the Beck Lab has found that antibody response is not significantly different between obese and lean individuals 30 days post vaccination, but falters between that time and one-year post vaccination. We have also found that there is a difference in the metabolism and function of T cells in the response to the influenza vaccination. With the goal of discovering new research directions that might aid in the discovery of molecular mechanisms underlying this phenomenon, I conducted a study using a bioinformatics approach to analyze the gut microbiota as a potential mediator. Strong preliminary evidence was found linking BMI, Firmicutes, and the antibody response to the 2014-2015 TIV immunization.Master of Scienc
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