Analytical and clinical validation of a microbial cell-free DNA sequencing test for infectious disease.

Thousands of pathogens are known to infect humans, but only a fraction are readily identifiable using current diagnostic methods. Microbial cell-free DNA sequencing offers the potential to non-invasively identify a wide range of infections throughout the body, but the challenges of clinical-grade metagenomic testing must be addressed. Here we describe the analytical and clinical validation of a next-generation sequencing test that identifies and quantifies microbial cell-free DNA in plasma from 1,250 clinically relevant bacteria, DNA viruses, fungi and eukaryotic parasites. Test accuracy, precision, bias and robustness to a number of metagenomics-specific challenges were determined using a panel of 13 microorganisms that model key determinants of performance in 358 contrived plasma samples, as well as 2,625 infections simulated in silico and 580 clinical study samples. The test showed 93.7% agreement with blood culture in a cohort of 350 patients with a sepsis alert and identified an independently adjudicated cause of the sepsis alert more often than all of the microbiological testing combined (169 aetiological determinations versus 132). Among the 166 samples adjudicated to have no sepsis aetiology identified by any of the tested methods, sequencing identified microbial cell-free DNA in 62, likely derived from commensal organisms and incidental findings unrelated to the sepsis alert. Analysis of the first 2,000 patient samples tested in the CLIA laboratory showed that more than 85% of results were delivered the day after sample receipt, with 53.7% of reports identifying one or more microorganisms.

Probe selection for high-density oligonucleotide arrays.

High-density oligonucleotide microarrays enable simultaneous monitoring of expression levels of tens of thousands of transcripts. For accurate detection and quantitation of transcripts in the presence of cellular mRNA, it is essential to design microarrays whose oligonucleotide probes produce hybridization intensities that accurately reflect the concentration of original mRNA. We present a model-based approach that predicts optimal probes by using sequence and empirical information. We constructed a thermodynamic model for hybridization behavior and determined the influence of empirical factors on the effective fitting parameters. We designed Affymetrix GeneChip probe arrays that contained all 25-mer probes for hundreds of human and yeast transcripts and collected data over a 4,000-fold concentration range. Multiple linear regression models were built to predict hybridization intensities of each probe at given target concentrations, and each intensity profile is summarized by a probe response metric. We selected probe sets to represent each transcript that were optimized with respect to responsiveness, independence (degree to which probe sequences are nonoverlapping), and uniqueness (lack of similarity to sequences in the expressed genomic background). We show that this approach is capable of selecting probes with high sensitivity and specificity for high-density oligonucleotide arrays.

High-density genechip oligonucleotide probe arrays.

High-density DNA probe arrays provide a highly parallel approach to nucleic acid sequence analysis that is transforming gene-based biomedical research. Photolithographic DNA synthesis has enabled the large-scale production of GeneChip probe arrays containing hundreds of thousands of oligonucleotide sequences on a glass "chip" about 1.5 cm2 in size. The manufacturing process integrates solid-phase photochemical oligonucleotide synthesis with lithographic techniques similar to those used in the microelectronics industry. Due to their very high information content, GeneChip probe arrays are finding widespread use in the hybridization-based detection and analysis of mutations and polymorphisms ("genotyping"), and in a wide range of gene expression studies.