Kirsten St. George

Bio: Kirsten St. George is an academic researcher from New York State Department of Health. The author has contributed to research in topics: Influenza A virus & Virus. The author has an hindex of 38, co-authored 104 publications receiving 8006 citations. Previous affiliations of Kirsten St. George include University of Pittsburgh & Wadsworth Center.

Antigenic and Genetic Characteristics of Swine-Origin 2009 A(H1N1) Influenza Viruses Circulating in Humans

Abstract: Since its identification in April 2009, an A(H1N1) virus containing a unique combination of gene segments from both North American and Eurasian swine lineages has continued to circulate in humans. The lack of similarity between the 2009 A(H1N1) virus and its nearest relatives indicates that its gene segments have been circulating undetected for an extended period. Its low genetic diversity suggests that the introduction into humans was a single event or multiple events of similar viruses. Molecular markers predictive of adaptation to humans are not currently present in 2009 A(H1N1) viruses, suggesting that previously unrecognized molecular determinants could be responsible for the transmission among humans. Antigenically the viruses are homogeneous and similar to North American swine A(H1N1) viruses but distinct from seasonal human A(H1N1).

Single-Reaction Genomic Amplification Accelerates Sequencing and Vaccine Production for Classical and Swine Origin Human Influenza A Viruses

Abstract: Pandemic influenza A viruses that emerge from animal reservoirs are inevitable. Therefore, rapid genomic analysis and creation of vaccines are vital. We developed a multisegment reverse transcription-PCR (M-RTPCR) approach that simultaneously amplifies eight genomic RNA segments, irrespective of virus subtype. M-RTPCR amplicons can be used for high-throughput sequencing and/or cloned into modified reverse-genetics plasmids via regions of sequence identity. We used these procedures to rescue a contemporary H3N2 virus and a swine origin H1N1 virus directly from human swab specimens. Together, M-RTPCR and the modified reverse-genetics plasmids that we designed streamline the creation of vaccine seed stocks (9 to 12 days).

Infections With Oseltamivir-Resistant Influenza A(H1N1) Virus in the United States

Abstract: Context During the 2007-2008 influenza season, oseltamivir resistance among influenza A(H1N1) viruses increased significantly for the first time worldwide. Early surveillance data suggest that the prevalence of oseltamivir resistance among A(H1N1) viruses will most likely be higher during the 2008-2009 season. Objectives To describe patients infected with oseltamivir-resistant influenza A(H1N1) virus and to determine whether there were any differences between these patients and patients infected with oseltamivir-susceptible A(H1N1) virus in demographic or epidemiological characteristics, clinical symptoms, severity of illness, or clinical outcomes. Design, Setting, and Patients Influenza A(H1N1) viruses that were identified and submitted to the Centers for Disease Control and Prevention by US public health laboratories between September 30, 2007, and May 17, 2008, and between September 28, 2008, and February 19, 2009, were tested as part of ongoing surveillance. Oseltamivir resistance was determined by neuraminidase inhibition assay and pyrosequencing analysis. Information was collected using a standardized case form from patients with oseltamivir-resistant A(H1N1) infections and a comparison group of patients with oseltamivir-susceptible A(H1N1) infections during 2007-2008. Main Outcome Measures Demographic and epidemiological information as well as clinical information, including symptoms, severity of illness, and clinical outcomes. Results During the 2007-2008 season, influenza A(H1N1) accounted for an estimated 19% of circulating influenza viruses in the United States. Among 1155 influenza A(H1N1) viruses tested from 45 states, 142 (12.3%) from 24 states were resistant to oseltamivir. Data were available for 99 oseltamivir-resistant cases and 182 oseltamivir-susceptible cases from this period. Among resistant cases, median age was 19 years (range, 1 month to 62 years), 5 patients (5%) were hospitalized, and 4 patients (4%) died. None reported oseltamivir exposure before influenza diagnostic sample collection. No significant differences were found between cases of oseltamivir-resistant and oseltamivir-susceptible influenza in demographic characteristics, underlying medical illness, or clinical symptoms. Preliminary data from the 2008-2009 influenza season identified resistance to oseltamivir among 264 of 268 influenza A(H1N1) viruses (98.5%) tested. Conclusions Oseltamivir-resistant A(H1N1) viruses circulated widely in the United States during the 2007-2008 influenza season, appeared to be unrelated to oseltamivir use, and appeared to cause illness similar to oseltamivir-susceptible A(H1N1) viruses. Circulation of oseltamivir-resistant A(H1N1) viruses will continue, with a higher prevalence of resistance, during the 2008-2009 season.Published online March 2, 2009 (doi:10.1001/jama.2009.294).

Large-scale sequencing of human influenza reveals the dynamic nature of viral genome evolution

Abstract: Influenza viruses are remarkably adept at surviving in the human population over a long timescale. The human influenza A virus continues to thrive even among populations with widespread access to vaccines, and continues to be a major cause of morbidity and mortality. The virus mutates from year to year, making the existing vaccines ineffective on a regular basis, and requiring that new strains be chosen for a new vaccine. Less-frequent major changes, known as antigenic shift, create new strains against which the human population has little protective immunity, thereby causing worldwide pandemics. The most recent pandemics include the 1918 'Spanish' flu, one of the most deadly outbreaks in recorded history, which killed 30-50 million people worldwide, the 1957 'Asian' flu, and the 1968 'Hong Kong' flu. Motivated by the need for a better understanding of influenza evolution, we have developed flexible protocols that make it possible to apply large-scale sequencing techniques to the highly variable influenza genome. Here we report the results of sequencing 209 complete genomes of the human influenza A virus, encompassing a total of 2,821,103 nucleotides. In addition to increasing markedly the number of publicly available, complete influenza virus genomes, we have discovered several anomalies in these first 209 genomes that demonstrate the dynamic nature of influenza transmission and evolution. This new, large-scale sequencing effort promises to provide a more comprehensive picture of the evolution of influenza viruses and of their pattern of transmission through human and animal populations. All data from this project are being deposited, without delay, in public archives.

Whole-Genome Analysis of Human Influenza A Virus Reveals Multiple Persistent Lineages and Reassortment among Recent H3N2 Viruses

Abstract: Understanding the evolution of influenza A viruses in humans is important for surveillance and vaccine strain selection. We performed a phylogenetic analysis of 156 complete genomes of human H3N2 influenza A viruses collected between 1999 and 2004 from New York State, United States, and observed multiple co-circulating clades with different population frequencies. Strikingly, phylogenies inferred for individual gene segments revealed that multiple reassortment events had occurred among these clades, such that one clade of H3N2 viruses present at least since 2000 had provided the hemagglutinin gene for all those H3N2 viruses sampled after the 2002–2003 influenza season. This reassortment event was the likely progenitor of the antigenically variant influenza strains that caused the A/Fujian/411/2002-like epidemic of the 2003–2004 influenza season. However, despite sharing the same hemagglutinin, these phylogenetically distinct lineages of viruses continue to co-circulate in the same population. These data, derived from the first large-scale analysis of H3N2 viruses, convincingly demonstrate that multiple lineages can co-circulate, persist, and reassort in epidemiologically significant ways, and underscore the importance of genomic analyses for future influenza surveillance.

Database resources of the National Center for Biotechnology Information

Abstract: In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's website. NCBI resources include Entrez, PubMed, PubMed Central, LocusLink, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, SARS Coronavirus Resource, SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD) and the Conserved Domain Architecture Retrieval Tool (CDART). Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.gov.

“Bioinformatics” 특집을 내면서

Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

Discriminant analysis of principal components: a new method for the analysis of genetically structured populations

Abstract: The dramatic progress in sequencing technologies offers unprecedented prospects for deciphering the organization of natural populations in space and time. However, the size of the datasets generated also poses some daunting challenges. In particular, Bayesian clustering algorithms based on pre-defined population genetics models such as the STRUCTURE or BAPS software may not be able to cope with this unprecedented amount of data. Thus, there is a need for less computer-intensive approaches. Multivariate analyses seem particularly appealing as they are specifically devoted to extracting information from large datasets. Unfortunately, currently available multivariate methods still lack some essential features needed to study the genetic structure of natural populations. We introduce the Discriminant Analysis of Principal Components (DAPC), a multivariate method designed to identify and describe clusters of genetically related individuals. When group priors are lacking, DAPC uses sequential K-means and model selection to infer genetic clusters. Our approach allows extracting rich information from genetic data, providing assignment of individuals to groups, a visual assessment of between-population differentiation, and contribution of individual alleles to population structuring. We evaluate the performance of our method using simulated data, which were also analyzed using STRUCTURE as a benchmark. Additionally, we illustrate the method by analyzing microsatellite polymorphism in worldwide human populations and hemagglutinin gene sequence variation in seasonal influenza. Analysis of simulated data revealed that our approach performs generally better than STRUCTURE at characterizing population subdivision. The tools implemented in DAPC for the identification of clusters and graphical representation of between-group structures allow to unravel complex population structures. Our approach is also faster than Bayesian clustering algorithms by several orders of magnitude, and may be applicable to a wider range of datasets.

Origins and evolutionary genomics of the 2009 swine-origin H1N1 influenza A epidemic.

Abstract: In March and early April 2009, a new swine-origin influenza A (H1N1) virus (S-OIV) emerged in Mexico and the United States. During the first few weeks of surveillance, the virus spread worldwide to 30 countries (as of May 11) by human-to-human transmission, causing the World Health Organization to raise its pandemic alert to level 5 of 6. This virus has the potential to develop into the first influenza pandemic of the twenty-first century. Here we use evolutionary analysis to estimate the timescale of the origins and the early development of the S-OIV epidemic. We show that it was derived from several viruses circulating in swine, and that the initial transmission to humans occurred several months before recognition of the outbreak. A phylogenetic estimate of the gaps in genetic surveillance indicates a long period of unsampled ancestry before the S-OIV outbreak, suggesting that the reassortment of swine lineages may have occurred years before emergence in humans, and that the multiple genetic ancestry of S-OIV is not indicative of an artificial origin. Furthermore, the unsampled history of the epidemic means that the nature and location of the genetically closest swine viruses reveal little about the immediate origin of the epidemic, despite the fact that we included a panel of closely related and previously unpublished swine influenza isolates. Our results highlight the need for systematic surveillance of influenza in swine, and provide evidence that the mixing of new genetic elements in swine can result in the emergence of viruses with pandemic potential in humans.