FilmArray, an Automated Nested Multiplex PCR System for Multi-Pathogen Detection: Development and Application to Respiratory Tract Infection

The ideal clinical diagnostic system should deliver rapid, sensitive, specific and reproducible results while minimizing the requirements for specialized laboratory facilities and skilled technicians. We describe an integrated diagnostic platform, the “FilmArray”, which fully automates the detection and identification of multiple organisms from a single sample in about one hour. An unprocessed biologic/clinical sample is subjected to nucleic acid purification, reverse transcription, a high-order nested multiplex polymerase chain reaction and amplicon melt curve analysis. Biochemical reactions are enclosed in a disposable pouch, minimizing the PCR contamination risk. FilmArray has the potential to detect greater than 100 different nucleic acid targets at one time. These features make the system well-suited for molecular detection of infectious agents. Validation of the FilmArray technology was achieved through development of a panel of assays capable of identifying 21 common viral and bacterial respiratory pathogens. Initial testing of the system using both cultured organisms and clinical nasal aspirates obtained from children demonstrated an analytical and clinical sensitivity and specificity comparable to existing diagnostic platforms. We demonstrate that automated identification of pathogens from their corresponding target amplicon(s) can be accomplished by analysis of the DNA melting curve of the amplicon

Visualizing variation within global pneumococcal sequence clusters (GPSCS) and country population snapshots to contextualize pneumococcal isolates

Knowledge of pneumococcal lineages, their geographic distribution and antibiotic resistance patterns, can give insights into global pneumococcal disease. We provide interactive bioinformatic outputs to explore such topics, aiming to increase dissemi-nation of genomic insights to the wider community, without the need for specialist training. We prepared 12 country-specific phylogenetic snapshots, and international phylogenetic snapshots of 73 common Global Pneumococcal Sequence Clusters (GPSCs) previously defined using PopPUNK, and present them in Microreact. Gene presence and absence defined using Roary, and recombination profiles derived from Gubbins are presented in Phandango for each GPSC. Temporal phylogenetic signal was assessed for each GPSC using BactDating. We provide examples of how such resources can be used. In our example use of a country-specific phylogenetic snapshot we determined that serotype 14 was observed in nine unrelated genetic backgrounds in South Africa. The international phylogenetic snapshot of GPSC9, in which most serotype 14 isolates from South Africa were observed, highlights that there were three independent sub-clusters represented by South African serotype 14 isolates. We estimated from the GPSC9-dated tree that the sub-clusters were each established in South Africa during the 1980s. We show how recombination plots allowed the identification of a 20 kb recombination spanning the capsular polysaccharide locus within GPSC97. This was consistent with a switch from serotype 6A to 19A estimated to have occured in the 1990s from the GPSC97-dated tree. Plots of gene presence/absence of resistance genes (tet, erm, cat) across the GPSC23 phylogeny were consistent with acquisition of a composite transposon. We estimated from the GPSC23-dated tree that the acquisition occurred between 1953 and 1975. Finally, we demonstrate the assignment of GPSC31 to 17 externally generated pneumococcal serotype 1 assemblies from Utah via Pathogenwatch. Most of the Utah isolates clustered within GPSC31 in a USA-specific clade with the most recent common ancestor estimated between 1958 and 1981. The resources we have provided can be used to explore to data, test hypothesis and generate new hypotheses. The accessible assignment of GPSCs allows others to contextualize their own collections beyond the data presented here.Fil: Gladstone, Rebecca A.. Wellcome Sanger Institute; Reino UnidoFil: Lo, Stephanie W.. Wellcome Sanger Institute; Reino UnidoFil: Goater, Richard. Wellcome Sanger Institute; Reino Unido. University of Oxford; Reino UnidoFil: Yeats, Corin. Wellcome Sanger Institute; Reino Unido. University of Oxford; Reino UnidoFil: Taylor, Ben. Wellcome Sanger Institute; Reino Unido. University of Oxford; Reino UnidoFil: Hadfield, James. Fred Hutchinson Cancer Research Center; Estados UnidosFil: Lees, John A.. Imperial College London; Reino UnidoFil: Croucher, Nicholas J.. Imperial College London; Reino UnidoFil: van Tonder, Andries. Wellcome Sanger Institute; Reino Unido. University of Cambridge; Estados UnidosFil: Bentley, Leon J.. Wellcome Sanger Institute; Reino UnidoFil: Quah, Fu Xiang. Wellcome Sanger Institute; Reino UnidoFil: Blaschke, Anne J.. University of Utah; Estados UnidosFil: Pershing, Nicole L.. University of Utah; Estados UnidosFil: Byington, Carrie L.. University of California; Estados UnidosFil: Balaji, Veeraraghavan. Christian Medical College; IndiaFil: Hryniewicz, Waleria. National Medicines Institute; PoloniaFil: Sigauque, Betuel. Instituto Nacional de Saude Maputo; MozambiqueFil: Ravikumar, K. L.. Kempegowda Institute Of Medical Sciences; IndiaFil: Grassi Almeida, Samanta Cristine. Adolfo Lutz Institute; BrasilFil: Ochoa, Theresa J.. Universidad Peruana Cayetano Heredia; PerúFil: Ho, Pak Leung. The University Of Hong Kong; Hong KongFil: du Plessis, Mignon. National Institute for Communicable Diseases; SudáfricaFil: Ndlangisa, Kedibone M.. National Institute for Communicable Diseases; SudáfricaFil: Cornick, Jennifer. Malawi liverpool wellcome Trust Clinical Research Programme; MalauiFil: Kwambana Adams, Brenda. Colegio Universitario de Londres; Reino Unido. Medical Research Council Unit The Gambia at The London School of Hygiene & Tropical Medicine; GambiaFil: Benisty, Rachel. Ben Gurion University of the Negev; IsraelFil: Nzenze, Susan A.. University of the Witwatersrand; SudáfricaFil: Madhi, Shabir A.. University of the Witwatersrand; SudáfricaFil: Hawkins, Paulina A.. Emory University; Estados UnidosFil: Faccone, Diego Francisco. Dirección Nacional de Institutos de Investigación. Administración Nacional de Laboratorios e Institutos de Salud. Instituto Nacional de Enfermedades Infecciosas. Área de Antimicrobianos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Visualizing variation within Global Pneumococcal Sequence Clusters (GPSCs) and country population snapshots to contextualize pneumococcal isolates.

Knowledge of pneumococcal lineages, their geographic distribution and antibiotic resistance patterns, can give insights into global pneumococcal disease. We provide interactive bioinformatic outputs to explore such topics, aiming to increase dissemination of genomic insights to the wider community, without the need for specialist training. We prepared 12 country-specific phylogenetic snapshots, and international phylogenetic snapshots of 73 common Global Pneumococcal Sequence Clusters (GPSCs) previously defined using PopPUNK, and present them in Microreact. Gene presence and absence defined using Roary, and recombination profiles derived from Gubbins are presented in Phandango for each GPSC. Temporal phylogenetic signal was assessed for each GPSC using BactDating. We provide examples of how such resources can be used. In our example use of a country-specific phylogenetic snapshot we determined that serotype 14 was observed in nine unrelated genetic backgrounds in South Africa. The international phylogenetic snapshot of GPSC9, in which most serotype 14 isolates from South Africa were observed, highlights that there were three independent sub-clusters represented by South African serotype 14 isolates. We estimated from the GPSC9-dated tree that the sub-clusters were each established in South Africa during the 1980s. We show how recombination plots allowed the identification of a 20 kb recombination spanning the capsular polysaccharide locus within GPSC97. This was consistent with a switch from serotype 6A to 19A estimated to have occured in the 1990s from the GPSC97-dated tree. Plots of gene presence/absence of resistance genes (tet, erm, cat) across the GPSC23 phylogeny were consistent with acquisition of a composite transposon. We estimated from the GPSC23-dated tree that the acquisition occurred between 1953 and 1975. Finally, we demonstrate the assignment of GPSC31 to 17 externally generated pneumococcal serotype 1 assemblies from Utah via Pathogenwatch. Most of the Utah isolates clustered within GPSC31 in a USA-specific clade with the most recent common ancestor estimated between 1958 and 1981. The resources we have provided can be used to explore to data, test hypothesis and generate new hypotheses. The accessible assignment of GPSCs allows others to contextualize their own collections beyond the data presented here

Transmission of rhinovirus in the Utah BIG-LoVE families: Consequences of age and household structure.

BACKGROUND:Common cold viruses create significant health and financial burdens, and understanding key loci of transmission would help focus control strategies. This study (1) examines factors that influence when individuals transition from a negative to positive test (acquisition) or a positive to negative test (loss) of rhinovirus (HRV) and other respiratory tract viruses in 26 households followed weekly for one year, (2) investigates evidence for intrahousehold and interhousehold transmission and the characteristics of individuals implicated in transmission, and (3) builds data-based simulation models to identify factors that most strongly affect patterns of prevalence. METHODS:We detected HRV, coronavirus, paramyxovirus, influenza and bocavirus with the FilmArray polymerase chain reaction (PCR) platform (BioFire Diagnostics, LLC). We used logistic regression to find covariates affecting acquisition or loss of HRV including demographic characteristics of individuals, their household, their current infection status, and prevalence within their household and across the population. We apply generalized linear mixed models to test robustness of results. RESULTS:Acquisition of HRV was less probable in older individuals and those infected with a coronavirus, and higher with a higher proportion of other household members infected. Loss of HRV is reduced with a higher proportion of other household members infected. Within households, only children and symptomatic individuals show evidence for transmission, while between households only a higher number of infected older children (ages 5-19) increases the probability of acquisition. Coronaviruses, paramyxoviruses and bocavirus also show evidence of intrahousehold transmission. Simulations show that age-dependent susceptibility and transmission have the largest effects on mean HRV prevalence. CONCLUSIONS:Children are most likely to acquire and most likely to transmit HRV both within and between households, with infectiousness concentrated in symptomatic children. Simulations predict that the spread of HRV and other respiratory tract viruses can be reduced but not eliminated by practices within the home

Invasive Meningococcal Disease, Utah, 1995–2005

Trends in invasive meningococcal disease in Utah during 1995–2005 have differed substantially from US trends in incidence rate and serogroup and age distributions. Regional surveillance is essential to identify high-risk populations that might benefit from targeted immunization efforts