Improving the Diagnosis of Bacterial Infections: Evaluation of 16S rRNA Nanopore Metagenomics in Culture-Negative Samples

Nationwide multicentre study of Nanopore long-read sequencing for 16S rRNA-species identification

PURPOSE

Recent improvements in Nanopore sequencing chemistry has made it a promising platform for long-read 16S rRNA sequencing. This study evaluated its clinical utility in a nationwide collaboration coordinated by Genomic Medicine Sweden.

METHODS

Thirteen mock samples comprised of various bacterial strains and an External Quality Assessment (EQA) panel from QCMD (Quality Control for Molecular Diagnostics) were analysed by 20 microbiological laboratories across Sweden, using the recent v14 chemistry. Most laboratories generated full-length 16S rRNA sequencing libraries using an optimized protocol for the 16S Barcoding Kit 24, while two laboratories employed in-house PCR coupled with the Ligation Sequencing Kit. The commercial 16S bioinformatic pipeline from 1928 Diagnostics (1928-16S) was evaluated and compared with the open-sourced gms_16S pipeline that is based on the EMU classification tool (GMS-16S).

RESULTS

Seventeen out of 20 laboratories successfully sequenced and analysed the samples. Laboratories that used sodium acetate-containing elution buffers faced compatibility issues during library construction, resulting in reduced read count. High bacterial load samples were generally well-characterized, whereas hard-to-lyse bacteria such as Gram-positive strains were detected at lower abundance. The GMS-16S tool provided improved species-level identification compared to the 1928-16S pipeline, particularly for closely related taxa within the Streptococcus and Staphylococcus genera.

CONCLUSION

Nanopore sequencing demonstrated promising potential for bacterial identification in a clinical setting. The results prompt further optimization of the protocol to improve detection of a broader range of species. This multicentre study highlights the feasibility of implementing Nanopore sequencing into clinical microbiological laboratories, for improved national precision diagnostics.

Leveraging innovative diagnostics as a tool to contain superbugs

The evolutionary adaptation of pathogens to biological materials has led to an upsurge in drug-resistant superbugs that significantly threaten public health. Treating most infections is an uphill task, especially those associated with multi-drug-resistant pathogens, biofilm formation, persister cells, and pathogens that have acquired robust colonization and immune evasion mechanisms. Innovative diagnostic solutions are crucial for identifying and understanding these pathogens, initiating efficient treatment regimens, and curtailing their spread. While next-generation sequencing has proven invaluable in diagnosis over the years, the most glaring drawbacks must be addressed quickly. Many promising pathogen-associated and host biomarkers hold promise, but their sensitivity and specificity remain questionable. The integration of CRISPR-Cas9 enrichment with nanopore sequencing shows promise in rapid bacterial diagnosis from blood samples. Moreover, machine learning and artificial intelligence are proving indispensable in diagnosing pathogens. However, despite renewed efforts from all quarters to improve diagnosis, accelerated bacterial diagnosis, especially in Africa, remains a mystery to this day. In this review, we discuss current and emerging diagnostic approaches, pinpointing the limitations and challenges associated with each technique and their potential to help address drug-resistant bacterial threats. We further critically delve into the need for accelerated diagnosis in low- and middle-income countries, which harbor more infectious disease threats. Overall, this review provides an up-to-date overview of the diagnostic approaches needed for a prompt response to imminent or possible bacterial infectious disease outbreaks.

The rapid diagnosis of intraamniotic infection with nanopore sequencing

BACKGROUND

Intraamniotic infection (defined as intraamniotic inflammation with microorganisms) is an important cause of the preterm labor syndrome. Methods for the detection of microorganisms in amniotic fluid are culture and/or polymerase chain reaction assay. However, both methods take time, and the results are rarely available for clinical decision-making. Nanopore sequencing technology offers real-time, long-read sequencing that can produce rapid results.

OBJECTIVE

To determine 1) the diagnostic performance of the 16S rDNA nanopore sequencing method for the identification of microorganisms in patients with intraamniotic inflammation and 2) the relationship between microbial burden and the intensity of the amniotic fluid inflammatory response.

STUDY DESIGN

We performed a prospective cohort study that included singleton pregnancies presenting with symptoms of preterm labor with intact membranes or of preterm prelabor rupture of the membranes. Amniotic fluid samples were obtained for the evaluation of bacteria in the amniotic cavity using cultivation and polymerase chain reaction-based 16S Sanger sequencing methods. Participants were classified into 4 groups according to the results of an amniotic fluid culture, 16S Sanger sequencing, and an amniotic fluid interleukin 6 concentration: 1) no intraamniotic infection and intraamniotic inflammation (interleukin 6 <2.6 ng/mL, and no microorganisms in the amniotic cavity, as determined by culture or 16S Sanger sequencing); 2) microbial invasion of the amniotic cavity without intraamniotic inflammation, defined by the presence of bacteria detected by culture or 16S Sanger sequencing; 3) sterile intraamniotic inflammation (interleukin 6 ≥2.6 ng/mL without microbial invasion of the amniotic cavity); and 4) intraamniotic infection (interkeukin 6 ≥2.6 ng/mL with microbial invasion of the amniotic cavity). Patients who underwent a mid-trimester amniocentesis, had no intraamniotic infection or intraamniotic inflammation, and delivered at term represented the control group. 16S rDNA nanopore sequencing was performed and the diagnostic indices for the identification of intraamniotic infection were determined. Bioinformatic analysis was carried out to identify microorganisms, and a read count of at least 100 or a read count exceeding that of the background species from the control group, along with a relative abundance of no less than 1%, was used.

RESULTS

1) The 16S nanopore sequencing had a sensitivity of 88.9% (8/9), specificity of 95.4% (41/43), positive predictive value of 80.0% (8/10), negative predictive value of 97.6% (41/42), positive likelihood ratio of 19.1 (95% confidence interval, 4.8-75.4), negative likelihood ratio of 0.1 (95% confidence interval, 0.02-0.7), and an accuracy of 94.2% (49/52) for the identification of intraamniotic infection (prevalence, 17% [9/52]); 2) the microbial load determined by the 16S nanopore sequencing had a strong positive correlation with the intensity of an intraamniotic inflammatory response (amniotic fluid interleukin 6 concentration; Spearman's correlation 0.9; P=.002); and 3) a subgroup of patients with intraamniotic inflammation did not have bacteria determined by culture, Sanger sequencing, or nanopore 16S, thus confirming the existence of sterile intraamniotic inflammation.

CONCLUSION

The 16S nanopore sequencing has high diagnostic indices, predictive values, likelihood ratios, and accuracy in the diagnosis of intraamniotic infection.

Clinical performance of real-time nanopore metagenomic sequencing for rapid identification of bacterial pathogens in cerebrospinal fluid: a pilot study

This study aimed to evaluate the usefulness of amplicon-based real-time metagenomic sequencing applied to cerebrospinal fluid (CSF) for identifying the causative agents of bacterial meningitis. We conducted a 16S rRNA amplicon sequencing using a nanopore-based platform, alongside routine polymerase chain reaction (PCR) testing or bacterial culture, to compare its clinical performance in pathogen detection on CSF samples. Among 17 patients, nanopore-based sequencing, multiplex PCR, and bacterial culture detected potential bacterial pathogens in 47.1%, 0%, and 47.1% samples, respectively. Nanopore-based sequencing demonstrated a sensitivity of 50.0%, specificity of 55.6%, positive predictive value of 50.0%, negative predictive value of 55.6%, and overall accuracy of 47.1%, compared to the gold standard method for bacterial culture. In 44.4% (4/9) of culture-negative cases, nanopore-based sequencing detected potentially causative pathogens, whereas four (23.5%) patients were positive only in culture. Using nanopore-based sequencing alongside bacterial culture increased the positivity rate from 47.1 to 70.6%. However, these values may be overestimated due to challenges in distinguishing significant pathogens from background noise. Meanwhile, the bioinformatics module in EPI2ME reduced the turn-around time to 10 min. Nanopore-based metagenomic sequencing is expected to serve as a complementary tool for pathogen detection in CSF samples by facilitating rapid and accurate diagnosis.

Rapid detection of causative bacteria including multiple infections of bovine respiratory disease using 16S rRNA amplicon-based nanopore sequencing

Bovine respiratory disease (BRD) is a multifaceted condition that poses a primary challenge in calf rearing. Viruses and bacteria are etiological agents of BRD. Viral BRD is typically managed symptomatically, whereas bacterial BRD is predominantly managed through the empirical administration of antimicrobials. However, this empirical administration has raised concerns regarding the emergence of antimicrobial-resistant bacteria. Thus, rapid identification of pathogenic bacteria and judicious selection of antimicrobials are required. This study evaluated the usefulness of 16S rRNA analysis through nanopore sequencing for the rapid identification of BRD-causing bacteria. A comparative evaluation of nanopore sequencing and traditional culture method was performed on 100 calf samples detected with BRD. Nanopore sequencing facilitated the identification of bacteria at the species level in bovine nasal swabs, ear swabs, and lung tissue samples within approximately 6 h. Of the 92 samples in which BRD-causing bacteria were identified via nanopore sequencing, 82 (89%) were concordant with the results of culture isolation. In addition, the occurrence of multiple infections exceeded that of singular infections. These results suggest that 16S rRNA sequencing via nanopore technology is effective in reducing analysis time and accurately identifying BRD-causing bacteria. This method is particularly advantageous for the initial detectable screening of BRD.

A prospective multicentre evaluation of BioFire® Joint Infection Panel for the rapid microbiological documentation of acute arthritis

OBJECTIVES

To assess the performance of the rapid syndromic BioFire® Joint Infection Panel (BF-JIP) to detect bacterial and fungal pathogens, as well as antibiotic resistance genes, directly in synovial fluid specimens collected from patients with acute arthritis.

METHODS

The study was conducted in six French bacteriological laboratories. To assess the performances of BF-JIP, results were compared with those of synovial fluid 14-day culture and, in case of discrepancy, with those of complementary molecular methods and intraoperative samples. A total of 308 synovial fluid specimens were tested after collection from 308 adults and children presenting with clinical and biological suspicion of acute arthritis; patients presenting with acute periprosthetic joint infection were included according to the European Bone and Joint Infection Society 2021 criteria.

RESULTS

Only one specimen failed (no result). On the basis of the consolidated data, the BF-JIP was concordant with the 14-day culture in 280 (91.2%) of the 307 specimens finally included in the study. The positive percentage agreement was 84.9% (95% CI, 78.8-89.8%) and the negative percentage agreement was 100% (95% CI, 97.2-100%). The positive predictive value was extremely high (100%; 95% CI, 97.6-100%), whereas the negative predictive value was lower (82.6%; 95% CI, 75.7-88.2%), partially explained by the missing target species in the panel.

DISCUSSION

The BF-JIP showed high performances to detect pathogens involved in acute arthritis.

Implementation of full-length 16S nanopore sequencing for bacterial identification in a clinical diagnostic setting

This study describes the implementation of 16S nanopore sequencing in a diagnostic lab for pathogen identification without prior enrichment. First, the universality of the test and taxonomic resolution was evaluated for 78 clinically relevant bacteria (69 known and 9 unknown bacterial cultures). Next, the diagnostic value of the test was evaluated based on clinical samples. It was shown that 16S sequencing can be used both for identification of unknown cultures and to find bacteria directly in the clinical sample without cultivation. All culture-positive samples (n=11) tested positive with 16S sequencing directly performed on the sample, but bacteria were found as well in 15/30 culture-negative samples. Pathogenic bacteria were found in a background of commensal flora, and even complex polymicrobial infections could be unraveled. This study demonstrates the feasibility of implementing 16S nanopore sequencing in a clinical diagnostic setting and demonstrates its value for the diagnosis of culture-negative and polymicrobial infections.

The clinical utility of Nanopore 16S rRNA gene sequencing for direct bacterial identification in normally sterile body fluids

The prolonged incubation period of traditional culture methods leads to a delay in diagnosing invasive infections. Nanopore 16S rRNA gene sequencing (Nanopore 16S) offers a potential rapid diagnostic approach for directly identifying bacteria in infected body fluids. To evaluate the clinical utility of Nanopore 16S, we conducted a study involving the collection and sequencing of 128 monomicrobial samples, 65 polymicrobial samples, and 20 culture-negative body fluids. To minimize classification bias, taxonomic classification was performed using 3 analysis pipelines: Epi2me, Emu, and NanoCLUST. The result was compared to the culture references. The limit of detection of Nanopore 16S was also determined using simulated bacteremic blood samples. Among the three classifiers, Emu demonstrated the highest concordance with the culture results. It correctly identified the taxon of 125 (97.7%) of the 128 monomicrobial samples, compared to 109 (85.2%) for Epi2me and 102 (79.7%) for NanoCLUST. For the 230 cultured species in the 65 polymicrobial samples, Emu correctly identified 188 (81.7%) cultured species, compared to 174 (75.7%) for Epi2me and 125 (54.3%) for NanoCLUST. Through ROC analysis on the monomicrobial samples, we determined a threshold of relative abundance at 0.058 for distinguishing potential pathogens from background in Nanopore 16S. Applying this threshold resulted in the identification of 107 (83.6%), 117 (91.4%), and 114 (91.2%) correctly detected samples for Epi2me, Emu, and NanoCLUST, respectively, in the monomicrobial samples. Nanopore 16S coupled with Epi2me could provide preliminary results within 6 h. However, the ROC analysis of polymicrobial samples exhibited a random-like performance, making it difficult to establish a threshold. The overall limit of detection for Nanopore 16S was found to be about 90 CFU/ml.

Genomics in the long-read sequencing era

Long-read sequencing (LRS) technologies have provided extremely powerful tools to explore genomes. While in the early years these methods suffered technical limitations, they have recently made significant progress in terms of read length, throughput, and accuracy and bioinformatics tools have strongly improved. Here, we aim to review the current status of LRS technologies, the development of novel methods, and the impact on genomics research. We will explore the most impactful recent findings made possible by these technologies focusing on high-resolution sequencing of genomes and transcriptomes and the direct detection of DNA and RNA modifications. We will also discuss how LRS methods promise a more comprehensive understanding of human genetic variation, transcriptomics, and epigenetics for the coming years.

Utility of Metagenomic Next-Generation Sequencing in Infective Endocarditis: A Systematic Review

Blood cultures have been the gold standard for identifying pathogens in infective endocarditis (IE). Blood culture-negative endocarditis (BCNE), however, occurs in 40% or more of IE cases with the bulk of them due to recent antibiotic exposure prior to obtaining blood cultures. Increasingly, molecular techniques are being used for pathogen identification in cases of BCNE and more recently has included metagenomic next-generation sequencing (mNGS). We therefore performed a literature search on August 31, 2022, that assessed the mNGS in IE and 13 publications were identified and included in a systematic review. Eight (61.5%) of them focused only on IE with mNGS performed on cardiac valve tissue in four studies, plasma in three studies and cardiac implantable electronic devices (CIED) in one study. Gram-positive cocci, including Staphylococcus aureus (n = 31, 8.9%), coagulase-negative staphylococci (n = 61, 17.6%), streptococci (n = 130, 37.5%), and Enterococcus faecalis (n = 23, 6.6%) were the predominant organisms identified by mNGS. Subsequent investigations are needed to further define the utility of mNGS in BCNE and its impact on patient outcomes. Despite some pitfalls, mNGS seems to be of value in pathogen identification in IE cases, particularly in those with BCNE. This study was registered and on the Open Science Framework platform.