High sensitivity pathogen detection assays from crude samples

Mostafa, Ariana

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https://hdl.handle.net/2142/110786 Copy

Description

Title

High sensitivity pathogen detection assays from crude samples

Author(s)

Mostafa, Ariana

Issue Date

2021-04-05

Director of Research (if dissertation) or Advisor (if thesis)

Bashir, Rashid

Doctoral Committee Chair(s)

Bashir, Rashid

Committee Member(s)

• Cunningham, Brian
• Irudayaraj, Joseph
• Timperman, Aaron

Department of Study

Bioengineering

Discipline

Bioengineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Detection
• Pathogens
• Crude Samples
• LAMP
• Diagnostic

Abstract

Detection of pathogens for diagnosis of disease is very important for advancing healthcare, especially in resource-scarce settings with minimal access to laboratory equipment or techniques. Culture being the gold standard for bacterial and fungal detection and immunoassay or nucleic acid-based testing for viral detection, these approaches are time-consuming, expensive, and require extensive resources and time for the identification of pathogen. Standard protocols for nucleic acid-based detection for pathogens require intricate pretreatment processes including pathogen lysis, isolation, and purification processes to separate the inhibiting factors from crude samples (such as whole blood, nasal swabs, saliva, and even food/environmental samples) before nucleic acid-based tests are performed. These laboratory-based procedures involve multiple steps, skilled technicians, and specific instruments, which all add to the limitations of current nucleic acid-based point of care testing. Therefore, there is a need for diagnostics with quick and direct detection of pathogenic nucleic acids from unpurified samples. In this thesis, we present a “Biphasic” LAMP based platform for detection of bacterial and fungal pathogens from whole blood with minimal blood processing and sensitive results obtained within 2.5 hours of blood collection. Termed as the “Biphasic” approach, we provide an alternative to blood processing where we rapidly dry the whole blood with pathogens to generate a dried blood matrix. Through a thermal lysis step, we generate a physical micro and nano fluidic network inside the dried blood matrix for polymerase to access the DNA and initiate amplification. In our platform, the dried blood does not take part in or mix with the reaction and acts as a substrate during the reaction where the inhibitory elements such as platelets, cells, and proteins are locked and remain as part of the substrate. This allows the fluorescent amplicons post-amplification to be concentrated in the clear supernatant phase, giving an extraordinary signal-to-noise and fluorescence change. When this biphasic approach is coupled with mechanical bead lysis for effective pathogen lysis, the limit of detection for detecting MRSA, E. coli, Candida ablicans in our platform was found to be 1.2cfu/ml. This biphasic concept was further translated to detect bacterial pathogens in complex food matrices such as ground beef where high amounts of protein, fats, and other inhibitors affect the sensitivity of the assay. Our biphasic approach allowed us to detection E. coli with an LOD of 33 cfu/g within 2.5 hours of sample collection without complicated instruments except for a heater and optical reader. Furthermore, with the COVID19 pandemic in hand, we utilized our understanding of LAMP reactions on crude sample detecting SARS-CoV-2 viruses in crude nasopharyngeal swabs and saliva samples. Starting with primer design, we developed highly sensitive RT-LAMP based assays that can detect low copies of SARS-CoV-2 pathogen. We challenged ourselves to demonstrate even single-molecule detection of SARS-CoV-2 using a modified 2-step RT-LAMP process where only 2 primers are added during cDNA synthesis such that primer-dimer attachment is avoided and leads to single-molecule sensitivity. We have demonstrated our assays with clinical samples from OSF and Carle Hospital with high accuracy.

Graduation Semester

2021-05

Type of Resource

Thesis

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http://hdl.handle.net/2142/110786

Copyright and License Information

Copyright 2021 Ariana Mostafa

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