Clinical metagenomics—challenges and future prospects

Abstract

Infections lacking precise diagnosis are often caused by a rare or uncharacterized pathogen, a combination of pathogens, or a known pathogen carrying undocumented or newly acquired genes. Despite medical advances in infectious disease diagnostics, many patients still experience mortality or long-term consequences due to undiagnosed or misdiagnosed infections. Thus, there is a need for an exhaustive and universal diagnostic strategy to reduce the fraction of undocumented infections. Compared to conventional diagnostics, metagenomic next-generation sequencing (mNGS) is a promising, culture-independent sequencing technology that is sensitive to detecting rare, novel, and unexpected pathogens with no preconception. Despite the fact that several studies and case reports have identified the effectiveness of mNGS in improving clinical diagnosis, there are obvious shortcomings in terms of sensitivity, specificity, costs, standardization of bioinformatic pipelines, and interpretation of findings that limit the integration of mNGS into clinical practice. Therefore, physicians must understand the potential benefits and drawbacks of mNGS when applying it to clinical practice. In this review, we will examine the current accomplishments, efficacy, and restrictions of mNGS in relation to conventional diagnostic methods. Furthermore, we will suggest potential approaches to enhance mNGS to its maximum capacity as a clinical diagnostic tool for identifying severe infections.

Hybrid-Capture Target Enrichment in Human Pathogens: Identification, Evolution, Biosurveillance, and Genomic Epidemiology

“…Interestingly, in one sample, EBV sequences (n = 3) were recovered post-HC, which was corroborated using qPCR with a low C T value, but no reads were recovered using unbiased sequencing. The recovery of sequences from multiple pathogens could indicate co-infections, but we echo the authors' sentiment that HTS alone might not be indicative of a causal link, as results may be confounded by factors such as commensals or contamination (see [46,126]). Similarly, in cases of meningoencephalitis, the application of VirCapSeq-VERT managed to identify potential pathogens of interest, including unexpected ones [124], but results remained inconclusive and even failed to detect or identify alternative pathogens (i.e., HPgV) to those confirmed by clinical testing (i.e., VCV, JCV, and HSV-2) [44], albeit in a small sample size (n = 8).…”

“…Overall, CM hold great promise as a tool for pathogen identification, particularly for novel or indeterminate sources of infection. However, there are many challenges to overcome for it to be a proper diagnostic tool [ 4 , 46 , 107 , 126 ]. Currently, HC may complement CM by enriching for potential pathogens of interest; given the flexibility of bait design, multiple sets for different diseases can be designed to improve capture efficacy and reduce costs in the future.…”

Forty-nine metagenomic-assembled genomes from an aquatic virome expand Caudoviricetes by 45 potential new families and the newly uncovered Gossevirus of Bamfordvirae

“…However, these protocols have some limitations, such as a limited detection threshold and a tendency to uncover only fragments that cannot be identified. Additionally, the analysis of sequenced data relies heavily on pre-existing databases and studies [8, 9].…”

Impact of Diagnostic Stewardship on Ordering Trends and Pathogen Yield from mNGS Studies

“…This variable clinical impact is due to the diverse range of patient populations, clinical syndromes, and matrices that can be assessed with this unbiased diagnostic approach. 10,[14][15][16] Interpretation of the results is further complicated by differences in the analytic techniques and databases used to classify nucleic acid sequences 17 .…”