US 12,473,597 B2
Methods and systems for processing a nucleic acid sample
Ephraim L. Tsalik, Cary, NC (US); Ricardo Henao Giraldo, Durham, NC (US); Thomas W. Burke, Durham, NC (US); Geoffrey S. Ginsburg, Durham, NC (US); Christopher W. Woods, Durham, NC (US); and Micah T. McClain, Durham, NC (US)
Assigned to Duke University, Durham, NC (US)
Filed by Duke University, Durham, NC (US)
Filed on May 26, 2023, as Appl. No. 18/324,445.
Application 18/324,445 is a continuation of application No. 15/738,339, abandoned, previously published as PCT/US2016/040437, filed on Jun. 30, 2016.
Claims priority of provisional application 62/257,406, filed on Nov. 19, 2015.
Claims priority of provisional application 62/187,683, filed on Jul. 1, 2015.
Prior Publication US 2024/0401107 A1, Dec. 5, 2024
Int. Cl. C12Q 1/6883 (2018.01); A61K 31/00 (2006.01); A61K 39/00 (2006.01); C12Q 1/6806 (2018.01); C12Q 1/6844 (2018.01); C12Q 1/689 (2018.01); C12Q 1/70 (2006.01); G01N 21/64 (2006.01)
CPC C12Q 1/6883 (2013.01) [A61K 31/00 (2013.01); A61K 39/00 (2013.01); C12Q 1/6806 (2013.01); C12Q 1/6846 (2013.01); C12Q 1/689 (2013.01); C12Q 1/70 (2013.01); G01N 21/6428 (2013.01); G01N 21/6486 (2013.01); C12Q 2600/106 (2013.01); C12Q 2600/118 (2013.01); C12Q 2600/158 (2013.01); G01N 2021/6439 (2013.01)] 32 Claims
OG exemplary drawing
 
1. A method of processing a blood sample of a subject, comprising:
(a) providing said blood sample of said subject having or suspected of having a viral or bacterial infection, wherein said blood sample comprises a plurality of host messenger ribonucleic acid (mRNA) molecules from said subject;
(b) subjecting said plurality of host mRNA molecules to reverse transcription to generate a plurality of complementary deoxyribonucleic acid (cDNA) molecules;
(c) optically detecting said plurality of cDNA molecules or derivative thereof, wherein optically detecting comprises measuring expression levels of said plurality of host mRNA molecules;
(d) processing said expression levels or a derivative of said expression levels using a classifier to detect a presence of said viral infection or said bacterial infection in said subject,
wherein said classifier comprises an algorithm trained using data from a first set of subjects known to have said viral infection, a second set of subjects known to have said bacterial infection, and a third set of uninfected subjects displaying symptoms of a non-infectious illness, wherein said data comprises expression levels of host mRNA molecules from samples from said first set of subjects known to have said viral infection, said second set of subjects known to have said bacterial infection, and said third set of uninfected subjects displaying symptoms of said non-infectious illness,
wherein said symptoms of said non-infectious illness include two or more systemic inflammatory response syndrome (SIRS) criteria selected from the group consisting of (i) temperature <36° or >38° C., (ii) heart rate >90 beats per minute, (iii) respiratory rate >20 breaths per minute or arterial partial pressure of CO2<32 mmHg, and (iv) white blood cell count <4000 or >12,000 cells/mm3 or >10% band form neutrophils,
wherein said classifier is capable of differentiating (i) said bacterial infection from said viral infection or said non-infectious illness, (ii) said viral infection from said bacterial infection or said non-infectious illness, and (iii) said non-infectious illness from said bacterial infection or said viral infection, and wherein said classifier is generated by a method comprising:
(A) obtaining said host mRNA molecules from said samples from said first set of subjects known to have said viral infection, said second set of subjects known to have said bacterial infection, and said third set of uninfected subjects displaying symptoms of said non-infectious illness:
(B) subjecting said host mRNA molecules of (A) to reverse transcription to generate cDNA molecules;
(C) optically detecting said cDNA molecules of (B) or derivative thereof to measure expression levels of said host mRNA molecules of (A);
(D) based on said expression levels of (C), generating a bacterial classifier by estimating a probability of said bacterial infection versus said viral infection and said non-infectious illness, a viral classifier by estimating a probability of said viral infection versus said bacterial infection and said non-infectious illness, and a non-infectious illness classifier by estimating a probability of said non-infectious illness versus said bacterial infection and said viral infection; and
(E) combining said bacterial classifier, said viral classifier and said non-infectious illness classifier into a single decision model, thereby generating said classifier; and
(e) upon detecting said presence of said bacterial infection or said viral infection in (d), administering to said subject a therapeutically effective amount of an antibiotic treatment for said bacterial infection or a therapeutically effective amount of an antiviral treatment for said viral infection.