Massively parallel digital high resolution melt for rapid and absolutely quantitative sequence profiling.
In clinical diagnostics and pathogen detection, profiling of complex samples for low-level genotypes represents a significant challenge. Advances in speed, sensitivity, and extent of multiplexing of molecular pathogen detection assays are needed to improve patient care. We report the development of an integrated platform enabling the identification of bacterial pathogen DNA sequences in complex samples in less than four hours. The system incorporates a microfluidic chip and instrumentation to accomplish universal PCR amplification, High Resolution Melting (HRM), and machine learning within 20,000 picoliter scale reactions, simultaneously. Clinically relevant concentrations of bacterial DNA molecules are separated by digitization across 20,000 reactions and amplified with universal primers targeting the bacterial 16S gene. Amplification is followed by HRM sequence fingerprinting in all reactions, simultaneously. The resulting bacteria-specific melt curves are identified by Support Vector Machine learning, and individual pathogen loads are quantified. The platform reduces reaction volumes by 99.995% and achieves a greater than 200-fold increase in dynamic range of detection compared to traditional PCR HRM approaches. Type I and II error rates are reduced by 99% and 100% respectively, compared to intercalating dye-based digital PCR (dPCR) methods. This technology could impact a number of quantitative profiling applications, especially infectious disease diagnostics.
Bioengineering Department, University of California San Diego, 92093, USA.
Daniel Ortiz
DO
Velez
Bioengineering Department, University of California San Diego, 92093, USA.
Hannah
H
Mack
Bioengineering Department, University of California San Diego, 92093, USA.
Julietta
J
Jupe
Bioengineering Department, University of California San Diego, 92093, USA.
Sinead
S
Hawker
Electrical and Computer Engineering, University of California San Diego, 92093, USA.
Ninad
N
Kulkarni
Electrical and Computer Engineering, University of California San Diego, 92093, USA.
Behnam
B
Hedayatnia
Bioengineering Department, University of California San Diego, 92093, USA.
Yang
Y
Zhang
Department of Pediatrics, Division of Neonatal-Perinatal Medicine, University of California San Diego and Rady Children's Hospital of San Diego, 92093, USA.
Shelley
S
Lawrence
Bioengineering Department, University of California San Diego, 92093, USA.
Stephanie I
SI
Fraley
D004269:DNA, Bacterial / Q000235:genetics; D023281:Genomics; D006801:Humans; D008089:Listeria monocytogenes / Q000235:genetics; D009691:Nucleic Acid Denaturation / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D016133:Polymerase Chain Reaction; D017422:Sequence Analysis, DNA / Q000379:methods*; D013296:Streptococcus pneumoniae / Q000235:genetics; D060388:Support Vector Machine
D004269:DNA, Bacterial