Bacteriophage Analysis Technique Reveals Details of COVID-19’s Impact on the Immune System
By LabMedica International staff writers Posted on 06 Oct 2020 |
Image: This illustration reveals the ultrastructural morphology exhibited by coronaviruses. Note the protein spikes that adorn the outer surface of the virus, which impart the look of a corona surrounding the virion, when viewed through an electron microscope (Photo courtesy of [U.S.] Centers for Disease Control and Prevention)
An analytical technique that can determine which of more than 1,000 different viruses have infected a person, has been utilized for a detailed study of the SARS-CoV-2 (COVID-19) virus and its impact on the immune system.
Investigators at Harvard Medical School (Boston, MA, USA) worked with VirScan, a technology in which peptide-displaying bacteriophages were incubated with a single drop of patient’s blood. Antiviral antibodies in the blood bound to their target epitopes on the bacteriophages. Antibody bound bacteriophages were then captured. DNA sequencing of these bacteriophages indicated which viral peptides were bound to antibodies. In this way, an individual’s complete viral serological history, including both vaccination and infection, could be determined.
For the current study, the investigators used VirScan to analyze blood samples from 232 COVID-19 patients and 190 pre-COVID-19 era controls.
Results revealed over 800 epitopes (sites recognized by the immune system) in the SARS-CoV-2 proteome, including 10 epitopes likely recognized by neutralizing antibodies. Pre-existing antibodies in control samples recognized SARS-CoV-2 ORF1, while only COVID-19 patients primarily recognized spike and nucleoprotein. A machine learning model trained on VirScan data predicted SARS-CoV-2 exposure history with 99% sensitivity and 98% specificity.
Individuals with more severe COVID-19 exhibited stronger and broader SARS-CoV-2 responses, weaker antibody responses to prior infections, and higher incidence of CMV (Cytomegalovirus) and HSV-1 (Herpes simplex virus 1). Among hospitalized patients, males had greater SARS-CoV-2 antibody responses than females.
"This may be the deepest serological analysis of any virus in terms of resolution," said senior author Dr. Stephen Elledge, professor of genetics at Harvard Medical School. "We now understand much, much more about the antibodies generated in response to SARS-CoV-2 and how frequently they are made. The next question is, what do those antibodies do? We need to identify which antibodies have an inhibitory capacity or which, if any, may promote the virus and actually help it enter into immune cells."
"Our paper illuminates the landscape of antibody responses in COVID-19 patients," said Dr. Elledge. "Next, we need to identify the antibodies that bind these recurrently recognized epitopes to determine whether they are neutralizing antibodies or antibodies that might exacerbate patient outcomes. This could inform the production of improved diagnostics and vaccines for SARS-CoV-2."
The VirScan analysis of COVID-19 was published in the September 29, 2020, online edition of the journal Science.
Related Links:
Harvard Medical School
Investigators at Harvard Medical School (Boston, MA, USA) worked with VirScan, a technology in which peptide-displaying bacteriophages were incubated with a single drop of patient’s blood. Antiviral antibodies in the blood bound to their target epitopes on the bacteriophages. Antibody bound bacteriophages were then captured. DNA sequencing of these bacteriophages indicated which viral peptides were bound to antibodies. In this way, an individual’s complete viral serological history, including both vaccination and infection, could be determined.
For the current study, the investigators used VirScan to analyze blood samples from 232 COVID-19 patients and 190 pre-COVID-19 era controls.
Results revealed over 800 epitopes (sites recognized by the immune system) in the SARS-CoV-2 proteome, including 10 epitopes likely recognized by neutralizing antibodies. Pre-existing antibodies in control samples recognized SARS-CoV-2 ORF1, while only COVID-19 patients primarily recognized spike and nucleoprotein. A machine learning model trained on VirScan data predicted SARS-CoV-2 exposure history with 99% sensitivity and 98% specificity.
Individuals with more severe COVID-19 exhibited stronger and broader SARS-CoV-2 responses, weaker antibody responses to prior infections, and higher incidence of CMV (Cytomegalovirus) and HSV-1 (Herpes simplex virus 1). Among hospitalized patients, males had greater SARS-CoV-2 antibody responses than females.
"This may be the deepest serological analysis of any virus in terms of resolution," said senior author Dr. Stephen Elledge, professor of genetics at Harvard Medical School. "We now understand much, much more about the antibodies generated in response to SARS-CoV-2 and how frequently they are made. The next question is, what do those antibodies do? We need to identify which antibodies have an inhibitory capacity or which, if any, may promote the virus and actually help it enter into immune cells."
"Our paper illuminates the landscape of antibody responses in COVID-19 patients," said Dr. Elledge. "Next, we need to identify the antibodies that bind these recurrently recognized epitopes to determine whether they are neutralizing antibodies or antibodies that might exacerbate patient outcomes. This could inform the production of improved diagnostics and vaccines for SARS-CoV-2."
The VirScan analysis of COVID-19 was published in the September 29, 2020, online edition of the journal Science.
Related Links:
Harvard Medical School
Latest Molecular Diagnostics News
- Urine Test to Revolutionize Lyme Disease Testing
- Simple Blood Test Could Enable First Quantitative Assessments for Future Cerebrovascular Disease
- New Genetic Testing Procedure Combined With Ultrasound Detects High Cardiovascular Risk
- Blood Samples Enhance B-Cell Lymphoma Diagnostics and Prognosis
- Blood Test Predicts Knee Osteoarthritis Eight Years Before Signs Appears On X-Rays
- Blood Test Accurately Predicts Lung Cancer Risk and Reduces Need for Scans
- Unique Autoantibody Signature to Help Diagnose Multiple Sclerosis Years before Symptom Onset
- Blood Test Could Detect HPV-Associated Cancers 10 Years before Clinical Diagnosis
- Low-Cost Point-Of-Care Diagnostic to Expand Access to STI Testing
- 18-Gene Urine Test for Prostate Cancer to Help Avoid Unnecessary Biopsies
- Urine-Based Test Detects Head and Neck Cancer
- Blood-Based Test Detects and Monitors Aggressive Small Cell Lung Cancer
- Blood-Based Machine Learning Assay Noninvasively Detects Ovarian Cancer
- Simple PCR Assay Accurately Differentiates Between Small Cell Lung Cancer Subtypes
- Revolutionary T-Cell Analysis Approach Enables Cancer Early Detection
- Single Genetic Test to Accelerate Diagnoses for Rare Developmental Disorders