Cost-benefit analysis of introducing next-generation sequencing (metagenomic) pathogen testing in the setting of pyrexia of unknown origin

Considerations for applying emerging technologies in paediatric laboratory medicine

Emerging technology in laboratory medicine can be defined as an analytical method (including biomarkers) or device (software, applications, and algorithms) that by its stage of development, translation into broad routine clinical practice, or geographical adoption and implementation has the potential to add value to clinical diagnostics. Paediatric laboratory medicine itself may be considered an emerging area of specialisation that is established relatively recently following increased appreciation and understanding of the unique physiology and healthcare needs of the children. Through four clinical (neonatal hypoglycaemia, neonatal hyperbilirubinaemia, sickle cell disorder, congenital adrenal hyperplasia) and six technological (microassays, noninvasive testing, alternative matrices, next generation sequencing, exosome analysis, machine learning) illustrations, key takeaways of application of emerging technology for each area are summarised. Additionally, nine key considerations when applying emerging technology in paediatric laboratory medicine setting are discussed.

Lung abscess by Fusobacterium nucleatum and Streptococcus spp. co-infection by mNGS: A case series

A lung abscess is a necrotizing infection caused by microbiomes that lead to the loss of healthy lung tissue. The routine culture is a waste of time and yields false-negative results, and clinicians could only choose empiric therapy or use broad-spectrum antibiotics, which could significantly contribute to the problem of resistance or aggravate the condition. We report three patients with a routine-culture-negative lung abscess. The presenting symptoms included fever, cough, dyspnea, and chest pain, and a computed tomography scan revealed a lesion in the lungs. The bronchoalveolar lavage fluid and pleural fluid were tested for pathogens using metagenome next-generation sequencing (mNGS), and the results revealed Fusobacterium nucleatum and Streptococcus spp. (S. constellatus, S. intermedius) as the most represented microbial pathogens. Our data demonstrated that mNGS could be a promising alternative diagnostic tool for pathogen detection, and the pathogen lists indicate that it will be important to focus on the Streptococcus genus rather than the dominant Streptococcus spp. in terms of co-infection of pathogen determined by shotgun mNGS.

A case for investment in clinical metagenomics in low-income and middle-income countries

Clinical metagenomics is the diagnostic approach with the broadest capacity to detect both known and novel pathogens. Clinical metagenomics is costly to run and requires infrastructure, but the use of next-generation sequencing for SARS-CoV-2 molecular epidemiology in low-income and middle-income countries (LMICs) offers an opportunity to direct this infrastructure to the establishment of clinical metagenomics programmes. Local implementation of clinical metagenomics is important to create relevant systems and evaluate cost-effective methodologies for its use, as well as to ensure that reference databases and result interpretation tools are appropriate to local epidemiology. Rational implementation, based on the needs of LMICs and the available resources, could ultimately improve individual patient care in instances in which available diagnostics are inadequate and supplement emerging infectious disease surveillance systems to ensure the next pandemic pathogen is quickly identified.

Metagenomic Pathogen Sequencing in Resource-Scarce Settings: Lessons Learned and the Road Ahead

Metagenomic next-generation sequencing (mNGS) is the process of sequencing all genetic material in a biological sample. The technique is growing in popularity with myriad applications including outbreak investigation, biosurveillance, and pathogen detection in clinical samples. However, mNGS programs are costly to build and maintain, and additional obstacles faced by low- and middle-income countries (LMICs) may further widen global inequities in mNGS capacity. Over the past two decades, several important infectious disease outbreaks have highlighted the importance of establishing widespread sequencing capacity to support rapid disease detection and containment at the source. Using lessons learned from the COVID-19 pandemic, LMICs can leverage current momentum to design and build sustainable mNGS programs, which would form part of a global surveillance network crucial to the elimination of infectious diseases.

Use of Quantitative Metagenomics Next-Generation Sequencing to Confirm Fever of Unknown Origin and Infectious Disease

A body temperature >38.3°C that lasts ≥3 weeks and lacks a clear diagnosis after 1 week of standard hospital examination and treatment is called "fever of unknown origin" (FUO). The main causes of FUO are infections, hematological diseases, autoimmune diseases, and other non-infectious inflammatory diseases. In recent years, quantitative metagenomics next-generation sequencing (Q-mNGS) has been used widely to detect pathogenic microorganisms, especially in the contribution of rare or new (e.g., severe acute respiratory syndrome-coronavirus-2) pathogens. This review addresses the undetermined cause of fever and its evaluation by Q-mNGS.

Stoichiometric ratios for biotics and xenobiotics capture effective metabolic coupling to re(de)fine biodegradation

Preserving human and environmental health requires anthropogenic pollutants to be biologically degradable. Depending on concentration, both nutrients and pollutants induce and activate metabolic capacity in the endemic bacterial consortium, which in turn aids their degradation. Knowledge on such 'acclimation' is rarely implemented in risk assessment cost-effectively. As a result, an accurate description of the mechanisms and kinetics of biodegradation remains problematic. In this study, we defined a yield 'effectivity', comprising the effectiveness at which a pollutant (substrate) enhances its own degradation by inducing (biomass) cofactors involved therein. Our architecture for calculation represents the interplay between concentration and metabolism via both stoichiometric and thermodynamic concepts. The calculus for yield 'effectivity' is biochemically intuitive, implicitly embeds co-metabolism and distinguishes 'endogenic' from 'exogenic' substances' reflecting various phenomena in biodegradation and bio-transformation studies. We combined data on half-lives of pollutants/nutrients in wastewater and surface water with transition-state rate theory to obtain also experimental values for effective yields. These quantify the state of acclimation: the portion of biodegradation kinetics attributable to (contributed by) 'natural metabolism', in view of similarity to natural substances. Calculated and experimental values showed statistically significant correspondence. Particularly, carbohydrate metabolism and nucleic acid metabolism appeared relevant for acclimation (R² = 0.11-0.42), affecting rates up to 10^4.9(±0.7) times: under steady-state acclimation, a compound stoichiometrically identical to carbohydrates or nucleic acids, is 10^3.2 to 10^4.9 times faster aerobically degraded than a compound marginally similar. Our new method, simulating (contribution by) the state of acclimation, supplements existing structure-biodegradation and kinetic models for predicting biodegradation in wastewater and surface water. The accuracy of prediction may increase when characterizing nutrients/co-metabolites in terms of, e.g., elemental analysis. We discuss strengths and limitations of our approach by comparison to empirical and mechanism-based methods.

Evaluations of Clinical Utilization of Metagenomic Next-Generation Sequencing in Adults With Fever of Unknown Origin

Introduction

The diagnosis of infection-caused fever of unknown origin (FUO) is still challenging, making it difficult for physicians to provide an early effective therapy. Therefore, a novel pathogen detection platform is needed. Metagenomic next-generation sequencing (mNGS) provides an unbiased, comprehensive technique for the sequence-based identification of pathogenic microbes, but the study of the diagnostic values of mNGS in FUO is still limited.

Methods

In a single-center retrospective cohort study, 175 FUO patients were enrolled, and clinical data were recorded and analyzed to compare mNGS with culture or traditional methods including as smears, serological tests, and nucleic acid amplification testing (NAAT) (traditional PCR, Xpert MTB/RIF, and Xpert MTB/RIF Ultra).

Results

The blood mNGS could increase the overall rate of new organisms detected in infection-caused FUO by roughly 22.9% and 19.79% in comparison to culture (22/96 vs. 0/96; OR, ∞; p = 0.000) and conventional methods (19/96 vs. 3/96; OR, 6.333; p = 0.001), respectively. Bloodstream infection was among the largest group of those identified, and the blood mNGS could have a 38% improvement in the diagnosis rate compared to culture (19/50 vs. 0/50; OR, ∞; p = 0.000) and 32.0% compared to conventional methods (16/50 vs. 3/50; OR, 5.333; p = 0.004). Among the non-blood samples in infection-caused FUO, we observed that the overall diagnostic performance of mNGS in infectious disease was better than that of conventional methods by 20% (9/45 vs. 2/45; OR, 4.5; p = 0.065), and expectedly, the use of non-blood mNGS in non-bloodstream infection increased the diagnostic rate by 26.2% (8/32 vs. 0/32; OR, ∞; p = 0.008). According to 175 patients’ clinical decision-making, we found that the use of blood mNGS as the first-line investigation could effectively increase 10.9% of diagnosis rate of FUO compared to culture, and the strategy that the mNGS of suspected parts as the second-line test could further benefit infectious patients, improving the diagnosis rate of concurrent infection by 66.7% and 12.5% in non-bloodstream infection, respectively.

Conclusion

The application of mNGS in the FUO had significantly higher diagnostic efficacy than culture or other conventional methods. In infection-caused FUO patients, application of blood mNGS as the first-line investigation and identification of samples from suspected infection sites as the second-line test could enhance the overall FUO diagnosis rate and serve as a promising optimized diagnostic protocol in the future.

Progress Report: Next-Generation Sequencing (NGS), Multiplex Polymerase Chain Reaction (PCR), and Broad-Range Molecular Assays as Diagnostic Tools for Fever of Unknown Origin (FUO) Investigations in Adults

Even well into the 21st century, infectious diseases still account for most causes of fever of unknown origin (FUO). Advances in molecular technologies, including broad-range PCR of the 16S rRNA gene followed by Sanger sequencing, multiplex PCR assays, and more recently, next-generation sequencing (NGS) applications, have transitioned from research methods to more commonplace in some clinical microbiology laboratories. They have the potential to supplant traditional microbial identification methods and antimicrobial susceptibility testing. Despite the remaining challenges with these technologies, publications in the past decade justify excitement about the potential to transform FUO investigations. We discuss available evidence using these molecular methods for FUO evaluations, including potential cost-benefits and future directions.

High-Throughput Metagenomics for Identification of Pathogens in the Clinical Settings

The application of sequencing technology is shifting from research to clinical laboratories owing to rapid technological developments and substantially reduced costs. However, although thousands of microorganisms are known to infect humans, identification of the etiological agents for many diseases remains challenging as only a small proportion of pathogens are identifiable by the current diagnostic methods. These challenges are compounded by the emergence of new pathogens. Hence, metagenomic next-generation sequencing (mNGS), an agnostic, unbiased, and comprehensive method for detection, and taxonomic characterization of microorganisms, has become an attractive strategy. Although many studies, and cases reports, have confirmed the success of mNGS in improving the diagnosis, treatment, and tracking of infectious diseases, several hurdles must still be overcome. It is, therefore, imperative that practitioners and clinicians understand both the benefits and limitations of mNGS when applying it to clinical practice. Interestingly, the emerging third-generation sequencing technologies may partially offset the disadvantages of mNGS. In this review, mainly: a) the history of sequencing technology; b) various NGS technologies, common platforms, and workflows for clinical applications; c) the application of NGS in pathogen identification; d) the global expert consensus on NGS-related methods in clinical applications; and e) challenges associated with diagnostic metagenomics are described.