LOMA: a fast method to generate efficient tagged-random primers despite amplification bias of random PCR on pathogens

Recent advances and application of whole genome amplification in molecular diagnosis and medicine

Whole genome amplification (WGA) is a technology for non-selective amplification of the whole genome sequence, first appearing in 1992. Its primary purpose is to amplify and reflect the whole genome of trace tissues and single cells without sequence bias and to provide sufficient DNA template for subsequent multigene and multilocus analysis, along with comprehensive genome research. WGA provides a method to obtain a large amount of genetic information from a small amount of DNA and provides a valuable tool for preserving limited samples in molecular biology. WGA technology is especially suitable for forensic identification and genetic disease research, along with new technologies such as next-generation sequencing (NGS). In addition, WGA is also widely used in single-cell sequencing. Due to the small amount of DNA in a single cell, it is often unable to meet the amount of samples needed for sequencing, so WGA is generally used to achieve the amplification of trace samples. This paper reviews WGA methods based on different principles, summarizes both amplification principle and amplification quality, and discusses the application prospects and challenges of WGA technology in molecular diagnosis and medicine.

Comparison of microarray-predicted closest genomes to sequencing for poliovirus vaccine strain similarity and influenza A phylogeny

We evaluate sequence data from the PathChip high-density hybridization array for epidemiological interpretation of detected pathogens. For influenza A, we derive similar relative outbreak clustering in phylogenetic trees from PathChip-derived compared to classical Sanger-derived sequences. For a positive polio detection, recent infection could be excluded based on vaccine strain similarity.

Pathogen chip for respiratory tract infections

Determining the viral etiology of respiratory tract infections (RTI) has been limited for the most part to specific primer PCR-based methods due to their increased sensitivity and specificity compared to other methods, such as tissue culture. However, specific primer approaches have limited the ability to fully understand the diversity of infecting pathogens. A pathogen chip system (PathChip), developed at the Genome Institute of Singapore (GIS), using a random-tagged PCR coupled to a chip with over 170,000 probes, has the potential to recognize all known human viral pathogens. We tested 290 nasal wash specimens from Filipino children <2 years of age with respiratory tract infections using culture and 3 PCR methods-EraGen, Luminex, and the GIS PathChip. The PathChip had good diagnostic accuracy, ranging from 85.9% (95% confidence interval [CI], 81.3 to 89.7%) for rhinovirus/enteroviruses to 98.6% (95% CI, 96.5 to 99.6%) for PIV 2, compared to the other methods and additionally identified a number of viruses not detected by these methods.

Expecting the unexpected: nucleic acid-based diagnosis and discovery of emerging viruses

Extrapolation from recent disease history suggests that changes in the global environment, including virus, vector and human behavior, will continue to influence the spectrum of viruses to which humans are exposed. In this article, these environmental changes will be enumerated, and their potential impact on target-focused, nucleic acid-based diagnostic tests will be considered, followed by a presentation of some emerging technological responses.

Large-scale evolutionary surveillance of the 2009 H1N1 influenza A virus using resequencing arrays

In April 2009, a new influenza A (H1N1 2009) virus emerged that rapidly spread around the world. While current variants of this virus have caused widespread disease, particularly in vulnerable groups, there remains the possibility that future variants may cause increased virulence, drug resistance or vaccine escape. Early detection of these virus variants may offer the chance for increased containment and potentially prevention of the virus spread. We have developed and field-tested a resequencing kit that is capable of interrogating all eight segments of the 2009 influenza A(H1N1) virus genome and its variants, with added focus on critical regions such as drug-binding sites, structural components and mutation hotspots. The accompanying base-calling software (EvolSTAR) introduces novel methods that utilize neighbourhood hybridization intensity profiles and substitution bias of probes on the microarray for mutation confirmation and recovery of ambiguous base queries. Our results demonstrate that EvolSTAR is highly accurate and has a much improved call rate. The high throughput and short turn-around time from sample to sequence and analysis results (30 h for 24 samples) makes this kit an efficient large-scale evolutionary biosurveillance tool.