With recent emergences in new infectious diseases and their variants, there is a need to develop faster and more specific analytical tools to detect different respiratory infectious diseases such as SARS-CoV-2 or influenza viruses. Not only are their initial symptoms similar, but they are also both enveloped viruses with several common biological properties, often leading to challenges in disease identification. Although polymerase chain reaction (PCR) is a valuable tool in infectious disease testing, the recent pandemic demonstrated the need to develop analogous testing methods that utilize different consumables.

Infectious disease particles contain proteins that are biomarkers of infection. One approach capable of detecting such proteins is bottom-up mass spectrometry (MS). Proteolytic digestion of proteins generates peptides, which can be separated by liquid chromatography (LC) and detected by MS. Targeting multiple signature peptides of different proteins has been demonstrated to simultaneously detect peptides from five common respiratory infectious disease biomarkers; SARS-CoV-2, influenza virus A and B, respiratory syncytial virus, and human coronavirus (HCoV-229E).

In this talk, multiple workflows for infectious disease detection by LC-MS will be discussed. These workflows contain different sample preparation techniques, such as peptide enrichment via stable isotope-labelled standard and capture by anti-peptide antibodies (SISCAPA), immunoprecipitation of target proteins via antibody-coupled Dynabeads and a minimal sample preparation technique involving protein precipitation.

Learning Objectives:

1. Determine why peptide enrichment provides better sensitivity and selectivity of target peptides.

2. Elaborate how you can simultaneously detect a panel of infectious disease.

3. List the steps in quantifying proteins in biological matrices from sample to reporting.

Severe acute respiratory syndrome coronavirus (SARS-CoV-2) is a novel virus that causes COVID-19 and has considerable variability in clinical outcomes among infected patients. The GENCOV study links laboratory data (including genetic, immunology, biochemistry, microbiology and hematology) and patient characteristics to provide a comprehensive understanding of factors that contribute to variability in COVID-19 patient outcomes. GENCOV includes 25 co-investigators and collaborators across 6 hospital sites in Ontario to study 1,500 Covid-19 patients over a 12-month period. This lecture will describe the GENCOV study protocol and the clinical characteristics of Covid-19 infected patients that increase odds of hospitalization, including age, ethnicity, BMI, viral variant and presence of hypertension. Surveys results that relate to participants understanding of Covid-19 serological testing will be described. To our knowledge, GENCOV is the first study to assess public knowledge of SARS-CoV-2 antibodies and serological testing. Our findings indicate that age, household income and level of education play a role in understanding information related to Covid-19 serology. Lastly, serial antibody titer levels, antigen target and viral neutralization are longitudinally assessed using an in-house developed immunoassay and the Health Canada approved Roche Elecsys® SARS-CoV-2 immunoassay. Our findings show that unvaccinated inpatients 1-month post-infection have significantly greater IgG antibody levels against all antigen targets (spike, receptor binding domain or nucleocapsid) when compared to unvaccinated outpatients. Patients with breakthrough or hybrid infections show higher antibody levels at 1 and 6 months post infection in comparison to those who are infected without vaccination. Understanding the basis for the variation in immune response and how this correlates to patient outcomes will help to better characterize future vaccine development and roll out plans.

Learning Objectives:

1. Describe how laboratory and clinical characteristics can be linked to provide a comprehensive understanding of factors that contribute to variability in COVID-19 patient outcomes.

2. Describe short and long-term COVID-19 serological findings in vaccinated and unvaccinated individuals.

3. Identify populations at risk of knowledge gaps related to COVID-19 serology.

Rapid genomic surveillance of pathogens can provide valuable insights, in order to guide public health interventions. Novel workflows using nanopore technology enables for real-time sequencing of clinical samples. However, current library preparation workflows are limited and can take up to 5 hours whereby PCR takes around 3,5 hours. 

By using NextGenPCR technology it is possible to decrease the PCR library preparation to 27 minutes for the SARS-CoV-2 Midnight protocol from Nikkie Freed et al. While optimizing this SARS-CoV-2 PCR tiling, the world faced a monkeypox pandemic. At the beginning of the pandemic, public health institutes were limited to metagenomics approaches. Using this method, the coverage depth becomes the limiting factor that prevents to multiplex multiple samples on a single flowcell, making sequencing very costly.

A collaboration between AmsterdamUMC (Netherlands), Rigshospitalet Copenhagen (Denmark), and Molecular Biology Systems (Netherlands) resulted in a successful optimalisation and validation of an amplicon-based sequencing approach, inspired by SARS-CoV-2 Midnight protocol and the ARTIC network. This allows labs to increase depth of coverage and multiplex up to 20 samples per flowcell. 

Using this fast developed sequencing workflow, we were able to get fast insights of the spread of monkeypox in the region of Amsterdam, which resulted in a publication in Eurosurveillance about the first pediatric case in the Netherlands. 

Learning Objectives:

1. Discuss the benefits of having faster Next Generation sequencing data in outbreak settings.

2. Discuss the use of PCR tiling for Monkeypox sequencing.

3. Explain the potential of PCR tiling methodologies for other applications.