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Developing a Standardized PanGIA Workflow

General Global Health Surveillance

Rapid, Unbiased, Field-Forward Detection of Bacterial and Viral Pathogens in Under 24 Hours

Their names are familiar to most. Marburg, Ebola, E. coli, Mpox, Staphylococcus aureus (staph), and most devastatingly SARS-CoV-2, the coronavirus that causes COVID-19. These and other diseases make news headlines, permeate daily conversations, and have come to change our lives in profound ways.

As we’ve all been starkly reminded these past few years, the prevalence of infectious viral and bacterial diseases impact not only public health, but also have the potential to upend global economies and political systems. 

Importantly, progress has been made toward the eradication of some diseases, such as polio and malaria, though the latter is still endemic and devastating in some parts of Africa. There has also been a reduction in the number of annual deaths associated with these and many other diseases. However, emerging infectious diseases and the threat of bioterrorism agents pose challenges to further reducing their global burden. As a result, identifying and characterizing both these known and unknown infectious diseases remains a crucial aspect of the global response and critical to ensuring public health. By developing a standardized PanGIA workflow, we can improve this process. 

The Limitations of Traditional Detection Methods

Traditionally, infectious disease detection has relied on culture-based methods for identifying bacterial, viral, and fungal pathogens. However, the utility of culture-based methods can be limited with slow-growing organisms, have fastidious growth conditions, and pose a biohazard risk to laboratory workers. Additionally, the positive predictive value of culture methods varies according to the organism, complicating the determination of a true hazard versus what may be a contaminated sample. 

Alternative methods, which are often used in concert with pathogen detection, include the use of microscopy, serology, and a variety of molecular methods. This includes technological advancements like molecular diagnostic tools, direct detection from a clinical or environmental sample, and the ability to provide high-confidence detection. Most molecular diagnostic tools utilize nucleic acid amplification tests (NAATs) for pathogen identification based on detecting specific nucleic acid sequences. Despite the rapid turnaround time and ease of use associated with these technologies, they are limited to the detection of up to only 30 pathogens, with the majority targeting a single pathogen. In addition, NAATs often fail to detect new pathogen variants that have evolved due to mutations in the genome or acquisition of new genetic elements through horizontal gene transfer. This can be a significant limitation and hinderance to accurate detection when encountered with a host of emerging infectious diseases from around the world. 

Improving Next-Generation Sequencing

Next-generation sequencing (NGS) can allow pathogen detection in scenarios where traditional methods have generated negative or inconclusive results. The ability of NGS to sequence millions of DNA fragments in parallel, with greater depth, is a significant improvement over traditional technologies. Targeted NGS utilizes amplicons or hybridization capture techniques to query specific target sequences, which offers increased pathogen detection, but is also limited by the ability to detect only the targeted pathogens. 

An advancement, metagenomic NGS offers the ability for less biased pathogen detection and characterization. Despite the many advantages NGS offers, this technology is not routinely utilized in clinical laboratories due to a lack of standardized protocols, clinical guidelines for optimal use and appropriate result interpretation, and the challenges associated with analyzing complex genomic data

The development of a non-targeted, metagenomics-based pathogen detection system that meets the four following operational requirements could better address the needs for the biosurveillance community: 

  • Compatible with mobile laboratories, standardized operating procedures (SOPs), and utilization of commercial off-the-shelf (COTS) reagents; 
  • Sample-to-answer, including data analysis, within 24 hours; 
  • Universal sample preparation workflow to enable detection of all pathogen types, including bacteria and viruses; and,
  • Development of a straightforward, “push-button” bioinformatics workflow using commodity hardware. 

Each of these requirements was taken into consideration in developing a standardized PanGIA (Pan-Genomics for Infectious Agents) workflow, with the goals of being standardized, rapid, detecting pathogens broadly, and ensuring ease-of-use. 

Solutions for Pathogen Detection

Developing a standardized PanGIA workflow that meets these requirements presents challenges. The optimization of sample preparation techniques is crucial for generating high-quality nucleic acids for sequencing. As such, specific considerations are necessary for different sample types. For example, clinical samples often have low-titer pathogen concentrations that are difficult to detect in a high background of human cells and nucleic acids. Environmental samples often comprise diverse microbial populations and contain components that interfere with sample processing and sequencing library preparation. Additionally, bioinformatics analysis needs to balance the use of inexpensive, lightweight commercially available hardware with the need for speed, accuracy, and high information content.

To address these challenges, we adopted a “best-of-breed” approach to identify, evaluate, and select commercial-off-the-shelf (COTS) technologies and products to use developing a standardized PanGIA workflow. To do this, we evaluated 79 technologies for the proposed workflow, encompassing sample pre-processing, pathogen concentration, pre-lysis host depletion, total nucleic acid purification, total nucleic acid concentration, whole transcriptome amplification, post-purification host depletion, library generation, next-generation sequencing, and bioinformatics analysis. 

Selecting Our Technologies and Methods

To develop an unbiased, sample-to-sequence workflow, we performed this approach to understand what technologies and methods are best suited for system integration. This analysis included identifying, evaluating, and down-selecting candidate technologies for each workflow component that supported the program requirements. Notably, the final workflow had to be compatible with gram positive and gram-negative bacteria, DNA virus, and RNA viruses. The process also included literature reviews, end-user feedback, and wet-lab experiments. 

Following evaluation, testing, and optimization of commercially available technologies, we developed and optimized standardized workflows for unbiased, metagenomic analysis of samples using NGS and an optimized bioinformatics pipeline for detection of human pathogens from clinical (including whole blood, plasma, serum, and saliva) and environmental samples (such as swabs, soil, and wastewater) – the PanGIA Clinical Workflow and the PanGIA Environmental Workflow. 

To the best of our knowledge, this is the first standardized NGS-based, end-to-end solution for the unbiased detection of bacterial and viral pathogens from clinical or environmental samples in under 24 hours. 

Adoption of Metagenomic Biosurveillance Capabilities

The development of a universal method for pathogen detection from sample-to-answer requires overcoming several challenges that include addressing bacterial versus viral extraction methods, purification of both DNA and RNA, reduction in host nucleic acids, and concentration of low-level pathogens. Our work offers a standardized solution toward addressing these needs for infectious disease pathogen detection and discovery. The PanGIA workflows were optimized to increase end users’ ease-of-use, while minimizing hands-on processing time to allow for a 24-hour turnaround from sample-to-answer. The workflow incorporates novel processes for dehosting and simultaneous sequencing of RNA and DNA targets. We have developed standardized operating procedures that will be open access for end users to integrate into their pathogen detection protocols, decreasing the barrier of entry for laboratories looking to adopt metagenomic biosurveillance capabilities into their routine work.

Continued Development for the Future

Future work will focus on improving the efficiency and sensitivity of the PanGIA workflows through continued gap analysis to identify and evaluate new technologies as they become available. In addition, we will continue efforts to expand the workflows to include other relevant clinical and environmental matrices, such as serum, nasopharyngeal swabs, mosquitoes, and others, as well as additional classes of pathogens, including eukaryotic pathogens and parasites. Finally, future work will include optimization for sample analysis in austere conditions, such as mobile laboratories or other field-forward settings. This capability will allow the workflows to be used to their full potential, providing unbiased pathogen detection, in less than 24 hours, in settings where traditional methods are not currently feasible or sufficient.

The complete results of this work were published as “Development and Optimization of an Unbiased, Metagenomics-Based Pathogen Detection Workflow for Infectious Disease and Biosurveillance Applications” on Feb. 15, 2023 by Tropical Medicine and Infectious Disease, which is an international, scientific, peer-reviewed, open access journal of tropical medicine and infectious disease published monthly online by MDPI.

GETTING STARTED AT MRIGLOBAL

Contact MRIGlobal to further understand our work in infectious diseases. We offer a broad portfolio of infectious disease testing assays and capabilities across diagnostic disciplines, from screening and diagnosis to genotyping, therapy, and monitoring. Those seeking analysis of infectious disease tests can trust in our breadth of experience and knowledge – not just on the subject matter, but FDA protocols as well. 

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