Direct Detection and Identification of Prosthetic Joint Infection Pathogens in Synovial Fluid by Metagenomic Shotgun Sequencing

Performance of Sequencing Assays in Diagnosis of Prosthetic Joint Infection: A Systematic Review and Meta-Analysis

BACKGROUND

A prompt, accurate diagnosis of prosthetic joint infection (PJI) allows early treatment, and with identification of the causative organism, sensitive antibiotics could be applied. However, routine methods cannot identify the causative organism under certain circumstances. Gene sequencing assays have unique superiority in promptness and broad coverage of pathogens, but evidence of its accuracy is quite limited.

METHODS

Of 247 citations identified for screening, 12 studies with 1965 patients in total were included. The diagnostic value of sequencing assays in PJI was systematically reviewed. Subgroup analysis was conducted to explore the source of heterogeneity.

RESULTS

Pooled sensitivity was 0.81 (95% confidence interval [CI], 0.73-0.87); pooled specificity was 0.94 (95% CI, 0.91-0.97); positive likelihood ratio was 14.2 (95% CI, 8.7-23.4); negative likelihood ratio was 0.20 (95% CI, 0.14-0.29); and the area under the curve was 0.94 (95% CI, 0.18-1.00). The results of subgroup analysis revealed that antibiotics reduced the sensitivity of sequencing-based diagnosis compared with withholding antibiotics before sampling (0.71 vs 0.94). In another subgroup analysis, sequencing by synthesis (Illumina sequencing) had better specificity than other next-generation sequencing methods (0.963 vs 0.829) and specificity similar to time-consuming and laborious Sanger sequencing (0.963 vs 0.967).

CONCLUSION

Sequencing assays had favorable diagnostic accuracy of PJI. When sequencing assays were applied to diagnosing PJI, an antibiotic-free interval before sampling may enhance the ability to detect the causative organism and, among next-generation sequencing methods, sequencing by synthesis seemed to have advantages over other methods in specificity.

The World Association against Infection in Orthopaedics and Trauma (WAIOT) procedures for Microbiological Sampling and Processing for Periprosthetic Joint Infections (PJIs) and other Implant-Related Infections

While implant-related infections continue to play a relevant role in failure of implantable biomaterials in orthopaedic and trauma there is a lack of standardised microbiological procedures to identify the pathogen(s). The microbiological diagnosis of implant-related infections is challenging due to the following factors: the presence of bacterial biofilm(s), often associated with slow-growing microorganisms, low bacterial loads, previous antibiotic treatments and, possible intra-operative contamination. Therefore, diagnosis requires a specific set of procedures. Based on the Guidelines of the Italian Association of the Clinical Microbiologists (AMCLI), the World Association against Infection in Orthopaedics and Trauma has drafted the present document. This document includes guidance on the basic principles for sampling and processing for implant-related infections based on the most relevant literature. These procedures outline the main microbiological approaches, including sampling and processing methodologies for diagnostic assessment and confirmation of implant-related infections. Biofilm dislodgement techniques, incubation time and the role of molecular approaches are addressed in specific sections. The aim of this paper is to ensure a standardised approach to the main microbiological methods for implant-related infections, as well as to promote multidisciplinary collaboration between clinicians and microbiologists.

Clinical metagenomics

Clinical metagenomic next-generation sequencing (mNGS), the comprehensive analysis of microbial and host genetic material (DNA and RNA) in samples from patients, is rapidly moving from research to clinical laboratories. This emerging approach is changing how physicians diagnose and treat infectious disease, with applications spanning a wide range of areas, including antimicrobial resistance, the microbiome, human host gene expression (transcriptomics) and oncology. Here, we focus on the challenges of implementing mNGS in the clinical laboratory and address potential solutions for maximizing its impact on patient care and public health.

Detection of respiratory pathogens in clinical samples using metagenomic shotgun sequencing

PURPOSE

In this pilot study, we used shotgun metagenome sequencing (SMS) strategy on bronchoalveolar lavage (BAL) samples from hospitalized patients with suspected ventilate-associated pneumonia (VAP) in order to explore its potential for improving detection of ventilator-associated-pneumonia (VAP) etiology.

METHODOLOGY

In total, 67BAL samples from patients with VAP were tested with SMS strategy for detection of respiratory pathogens. Results of SMS and routine respiratory culture were compared.

RESULTS

SMS detected all pathogens recovered by cultivation approaches. In addition, putative pathogens other than the organisms recovered by culture were detected by SMS in culture-positive samples. In 40 of 45 (89  %) culture-negative samples, a potential pathogen was detected by SMS.

CONCLUSION

This proof-of-concept study demonstrates that SMS is able to detect bacterial, fungal and viral organisms in BAL, including culture-negative cases.

A Practical Guide to the Role of Ancillary Techniques in the Diagnosis of Infectious Agents in Fine Needle Aspiration Samples

Fine needle aspiration samples and small biopsies provide a minimally invasive diagnostic modality for mass lesions. When an infectious process is suspected based on initial evaluation, ancillary techniques can assist in making a specific diagnosis. Here we review the cytopathology that should prompt additional testing and review the availability and interpretation of special stains, immunohistochemistry, and in situ hybridization. In addition, this review addresses when special cultures may be necessary and the use of newer molecular techniques for pathogen identification.

Evaluation of the CosmosID Bioinformatics Platform for Prosthetic Joint-Associated Sonicate Fluid Shotgun Metagenomic Data Analysis

We previously demonstrated that shotgun metagenomic sequencing can detect bacteria in sonicate fluid, providing a diagnosis of prosthetic joint infection (PJI). A limitation of the approach that we used is that data analysis was time-consuming and specialized bioinformatics expertise was required, both of which are barriers to routine clinical use. Fortunately, automated commercial analytic platforms that can interpret shotgun metagenomic data are emerging. In this study, we evaluated the CosmosID bioinformatics platform using shotgun metagenomic sequencing data derived from 408 sonicate fluid samples from our prior study with the goal of evaluating the platform vis-à-vis bacterial detection and antibiotic resistance gene detection for predicting staphylococcal antibacterial susceptibility. Samples were divided into a derivation set and a validation set, each consisting of 204 samples; results from the derivation set were used to establish cutoffs, which were then tested in the validation set for identifying pathogens and predicting staphylococcal antibacterial resistance. Metagenomic analysis detected bacteria in 94.8% (109/115) of sonicate fluid culture-positive PJIs and 37.8% (37/98) of sonicate fluid culture-negative PJIs. Metagenomic analysis showed sensitivities ranging from 65.7 to 85.0% for predicting staphylococcal antibacterial resistance. In conclusion, the CosmosID platform has the potential to provide fast, reliable bacterial detection and identification from metagenomic shotgun sequencing data derived from sonicate fluid for the diagnosis of PJI. Strategies for metagenomic detection of antibiotic resistance genes for predicting staphylococcal antibacterial resistance need further development.

Metagenomic next-generation sequencing contribution in identifying prosthetic joint infection due to Parvimonas micra: a case report

Identifying fastidious pathogens in patients with prosthetic joint infection (PJI) by culture is challenging. Metagenomic next-generation sequencing (mNGS) is a novel culture-independent approach that is associated with a higher likelihood for identifying pathogens. We present a case where mNGS was implemented to identify Parvimonas micra, a rarely reported and difficult-to-culture PJI pathogen.

Eighty Years of Mycopathologia: A Retrospective Analysis of Progress Made in Understanding Human and Animal Fungal Pathogens

Mycopathologia was founded in 1938 to 'diffuse the understanding of fungal diseases in man and animals among mycologists.' This was an important mission considering that pathogenic fungi for humans and animals represent a tiny minority of the estimated 1.5-5 million fungal inhabitants on Earth. These pathogens have diverged from the usual saprotrophic lifestyles of most fungi to colonize and infect humans and animals. Medical and veterinary mycology is the subdiscipline of microbiology that dwells into the mysteries of parasitic, fungal lifestyles. Among the oldest continuing scientific publications on the subject, Mycopathologia had its share of 'classic papers' since the first issue was published in 1938. An analysis of the eight decades of notable contributions reveals many facets of host-pathogen interactions among 183 volumes comprising about 6885 articles. We have analyzed the impact and relevance of this body of work using a combination of citation tools (Google Scholar and Scopus) since no single citation metric gives an inclusive perspective. Among the highly cited Mycopathologia publications, those on experimental mycology accounted for the major part of the articles (36%), followed by diagnostic mycology (16%), ecology and epidemiology (15%), clinical mycology (14%), taxonomy and classification (10%), and veterinary mycology (9%). The first classic publication, collecting nearly 200 citations, appeared in 1957, while two articles published in 2010 received nearly 150 citations each, which is notable for a journal covering a highly specialized field of study. An empirical analysis of the publication trends suggests continuing interests in novel diagnostics, fungal pathogenesis, review of clinical diseases especially with relevance to the laboratory scientists, taxonomy and classification of fungal pathogens, fungal infections and carriage in pets and wildlife, and changing ecology and epidemiology of fungal diseases around the globe. We anticipate that emerging and re-emerging fungal pathogens will continue to cause significant health burden in the coming decades. It remains vital that scientists and physicians continue to collaborate by learning each other's language for the study of fungal diseases, and Mycopathologia will strive to be their partner in this increasingly important endeavor to its 100th anniversary in 2038 and beyond.

Metagenomics for Clinical Infectious Disease Diagnostics Steps Closer to Reality

Metagenomics approaches based on shotgun next-generation sequencing hold promise for infectious disease diagnostics. Despite substantial challenges that remain, work done over the past few years justifies excitement about the potential for these approaches to transform how clinical pathogen identification and analysis are performed. In an article in this issue of the Journal of Clinical Microbiology, M. I. Ivy et al. (J Clin Microbiol 56:e00402-18, 2018, https://doi.org/10.1128/JCM.00402-18) have applied a shotgun metagenomics approach to the diagnosis of prosthetic joint infections directly from synovial fluid. The results from this work demonstrate both the potentials and challenges of this approach applied in the clinical microbiology laboratory.