Messages from the third International Conference on Clinical Metagenomics (ICCMg3)

Messages from the Seventh International Conference on Clinical Metagenomics (ICCMg7)

Clinical metagenomics (CMg), referring to the application of metagenomic sequencing of clinical samples to obtain clinically relevant information for the diagnosis and management of infectious diseases, has been rapidly evolving these last years. Following this trend, we held the seventh International Conference on Clinical Metagenomics (ICCMg7) in Geneva in October 2022. During the two-day conference, cutting-edge advances and new discoveries using CMg were presented which we summarize in the present paper. During this ICCMg7, we kept on following the progresses achieved worldwide that cover reproducibility in CMg, the advent of new technologies applied to the field of infectious diseases, innovative research in the field of the gut microbiota, and finally the expansion of CMg in the fields of clinical epidemiology with surveillance studies on emerging and known pathogens, but also on antibiotic resistance genes, in the environment and in the animal reservoirs.

ResFinder 4.0 for predictions of phenotypes from genotypes

Objectives

WGS-based antimicrobial susceptibility testing (AST) is as reliable as phenotypic AST for several antimicrobial/bacterial species combinations. However, routine use of WGS-based AST is hindered by the need for bioinformatics skills and knowledge of antimicrobial resistance (AMR) determinants to operate the vast majority of tools developed to date. By leveraging on ResFinder and PointFinder, two freely accessible tools that can also assist users without bioinformatics skills, we aimed at increasing their speed and providing an easily interpretable antibiogram as output.

Methods

The ResFinder code was re-written to process raw reads and use Kmer-based alignment. The existing ResFinder and PointFinder databases were revised and expanded. Additional databases were developed including a genotype-to-phenotype key associating each AMR determinant with a phenotype at the antimicrobial compound level, and species-specific panels for in silico antibiograms. ResFinder 4.0 was validated using Escherichia coli (n = 584), Salmonella spp. (n = 1081), Campylobacter jejuni (n = 239), Enterococcus faecium (n = 106), Enterococcus faecalis (n = 50) and Staphylococcus aureus (n = 163) exhibiting different AST profiles, and from different human and animal sources and geographical origins.

Results

Genotype–phenotype concordance was ≥95% for 46/51 and 25/32 of the antimicrobial/species combinations evaluated for Gram-negative and Gram-positive bacteria, respectively. When genotype–phenotype concordance was <95%, discrepancies were mainly linked to criteria for interpretation of phenotypic tests and suboptimal sequence quality, and not to ResFinder 4.0 performance.

Conclusions

WGS-based AST using ResFinder 4.0 provides in silico antibiograms as reliable as those obtained by phenotypic AST at least for the bacterial species/antimicrobial agents of major public health relevance considered.

Mini Review: Clinical Routine Microbiology in the Era of Automation and Digital Health

Clinical microbiology laboratories are the first line to combat and handle infectious diseases and antibiotic resistance, including newly emerging ones. Although most clinical laboratories still rely on conventional methods, a cascade of technological changes, driven by digital imaging and high-throughput sequencing, will revolutionize the management of clinical diagnostics for direct detection of bacteria and swift antimicrobial susceptibility testing. Importantly, such technological advancements occur in the golden age of machine learning where computers are no longer acting passively in data mining, but once trained, can also help physicians in making decisions for diagnostics and optimal treatment administration. The further potential of physically integrating new technologies in an automation chain, combined to machine-learning-based software for data analyses, is seducing and would indeed lead to a faster management in infectious diseases. However, if, from one side, technological advancement would achieve a better performance than conventional methods, on the other side, this evolution challenges clinicians in terms of data interpretation and impacts the entire hospital personnel organization and management. In this mini review, we discuss such technological achievements offering practical examples of their operability but also their limitations and potential issues that their implementation could rise in clinical microbiology laboratories.

STROBE-metagenomics: a STROBE extension statement to guide the reporting of metagenomics studies

The term metagenomics refers to the use of sequencing methods to simultaneously identify genomic material from all organisms present in a sample, with the advantage of greater taxonomic resolution than culture or other methods. Applications include pathogen detection and discovery, species characterisation, antimicrobial resistance detection, virulence profiling, and study of the microbiome and microecological factors affecting health. However, metagenomics involves complex and multistep processes and there are important technical and methodological challenges that require careful consideration to support valid inference. We co-ordinated a multidisciplinary, international expert group to establish reporting guidelines that address specimen processing, nucleic acid extraction, sequencing platforms, bioinformatics considerations, quality assurance, limits of detection, power and sample size, confirmatory testing, causality criteria, cost, and ethical issues. The guidance recognises that metagenomics research requires pragmatism and caution in interpretation, and that this field is rapidly evolving.

Two Years of Viral Metagenomics in a Tertiary Diagnostics Unit: Evaluation of the First 105 Cases

Metagenomic next-generation sequencing (mNGS) can capture the full spectrum of viral pathogens in a specimen and has the potential to become an all-in-one solution for virus diagnostics. To date, clinical application is still in an early phase and limitations remain. Here, we evaluated the impact of viral mNGS for cases analyzed over two years in a tertiary diagnostics unit. High throughput mNGS was performed upon request by the treating clinician in cases where the etiology of infection remained unknown or the initial differential diagnosis was very broad. The results were compared to conventional routine testing regarding outcome and workload. In total, 163 specimens from 105 patients were sequenced. The main sample types were cerebrospinal fluid (34%), blood (33%) and throat swabs (10%). In the majority of the cases, viral encephalitis/meningitis or respiratory infection was suspected. In parallel, conventional virus diagnostic tests were performed (mean 18.5 individually probed targets/patients). mNGS detected viruses in 34 cases (32%). While often confirmatory, in multiple cases, the identified viruses were not included in the selected routine diagnostic tests. Two years of mNGS in a tertiary diagnostics unit demonstrated the advantages of a single, untargeted approach for comprehensive, rapid and efficient virus diagnostics, confirming the utility of mNGS in complementing current routine tests.