Genome-based surveillance offers new hope in the fight against healthcare-associated infections

By Dr. Priyom Bose, Ph.D.Reviewed by Benedette Cuffari, M.Sc.May 2 2023

Large volumes of high-quality data can be created by high-throughput bacterial genomic sequencing. Simultaneous developments in sequencing technology and bioinformatics have made it easier to use genomics to analyze outbreaks and conduct broader public health surveillance. 

A recent Microbial Genomics study considers major healthcare-associated pathogens and discusses both current and future public health priorities related to these microorganisms. The researchers also discuss the challenges associated with surveilling healthcare-associated infections (HAIs) and how technology could be used to mitigate the public health burden caused by HAIs.

Study: Taking hospital pathogen surveillance to the next level. Image Credit: janews / Shutterstock.com

The landscape of pathogen surveillance

The introduction of a highly reliable, affordable, fast, and standardizable genome-based typing method revolutionized pathogen surveillance. Genome sequencing and data analyses have become more scalable and enable hypothesis-free data evaluation. High-throughput genomic sequencing can elucidate transmission pathways from prospective, large, and transversal isolate collections. 

Globally, interdisciplinary working groups such as the European Center for Disease Prevention and Control (ECDC) and the United States Food and Drug Administration (FDA) have published papers demonstrating the scaling up of disease and genomic pathogen surveillance using high-throughput genomic sequencing technology.

Nevertheless, there are some challenges associated with whole-genome sequencing (WGS), many of which are due to the analytical and technical skills required to process and evaluate these samples.

Recent studies have endeavored to establish and build capacity for genomic surveillance. In addition, novel technological approaches, such as machine learning for antimicrobial resistance (AMR) prediction, have been developed.

The coronavirus disease 2019 (COVID-19) pandemic further highlighted the public health value of genomic epidemiology. Subsequently, large-scale international investments have been made in sequencing capacity and the digitalization of surveillance infrastructures.

Long-standing training collaborative networks in Africa and South America have also come to fruition, as evidenced by the sequencing data produced in these countries during the pandemic.

Short- and long-read sequencing

Public health-oriented surveillance of healthcare pathogens mainly involves surveillance of their antimicrobial resistance (AMR), which may spread horizontally or clonally. Genomic surveillance efforts must monitor both dissemination pathways.

AMR determinants are generally plasmid-borne and flanked by highly repetitive sequences that cannot be easily assembled by short-read sequencing data only. Mobile genetic elements (MGEs) and antibiotic resistance plasmids are complex structures that are difficult to reconstruct using short-read sequencing data. Long-read sequencing can overcome this limitation; however, it is associated with higher costs and greater computational demands.

Post-sequencing data analysis

It is imperative that the data produced by genomic sequencing be evaluated for quality before being used in any downstream analyses. Numeros workflows are currently available, including commercial solutions such as EPISEQ and AREScloud.

However, these commercial solutions, despite being user-friendly, are not suitable for all applications, as they are typically geared towards specific applications. Therefore, open-access streamlined reporting workflows can significantly boost genomic surveillance.

In addition to software, the training of laboratory microbiologists and standardization of tools is essential, as users must be able to conduct intuitive inference based on their results. Large research consortia like COMPARE offer various practical and educational activities on applications of high-throughput sequencing for a larger user community. 

Dedicated platforms that would enable the uploading of raw data and relevant metadata are also needed. This is particularly important considering the large amount of data being generated at local and regional levels.

Strain and active sharing should also be promoted in accordance with open science principles. Examples of existing platforms are BIGSdb, Pathogenwatch, and Enterobase.

The COVID-19 pandemic demonstrated the utility of this approach for understanding whether some variants were locally restricted or formed a part of a larger transmission network. This informed intervention strategies aimed at mitigating the spread of the virus.

In addition to the generation and analysis of data, long-term data storage needs to be carefully considered. One potential solution to the data storage issue could be the deposition of raw reads and associated metadata in public repositories that could subsequently be used for broad population-based analyses.

Conclusions

In the last decade, several efforts have been made to develop genome-based surveillance globally. The COVID-19 pandemic prompted the rapid generation and dissemination of analyses across countries to inform real-time political decision-making.

Pathogen or AMR dissemination could prevail for years if they went unnoticed or prevention and control strategies were less effective. From a public health perspective, the focus of hospital pathogen surveillance is, to a large extent, AMR surveillance, which needs a greater adoption of long-read sequencing.

In the future, the challenge for genome-based surveillance will be to transition from descriptive studies to real-time and predictive pathogen surveillance.