Metagenomic prediction of antimicrobial resistance in critically ill patients with lower respiratory tract infections

The clinical application of metagenomic next-generation sequencing in immunocompromised patients with severe respiratory infections in the ICU

BACKGROUND

Early targeted antibiotic therapy is crucial for improving the prognosis of immunocompromised patients with severe respiratory infections (SRIs) in the intensive care unit (ICU). Metagenomic next-generation sequencing (mNGS) has shown significant value in pathogen detection, but research on lower respiratory tract microorganisms remains limited.

METHODS

This study enrolled 234 patients with SRIs in the ICU, and individuals were categorized into immunocompromised and immunocompetent groups. We compared the diagnostic performance of mNGS using bronchoalveolar lavage fluid (BALF) with conventional microbiological tests (CMTs) and analyzed the value of mNGS in immunocompromised patients with SRIs in the ICU.

RESULTS

Among all patients, the pathogenic microorganism detection rate of mNGS was higher than that of CMTs (94.02% vs 66.67%, P < 0.05), both in the immunocompromised group (95.0% vs 58.75%, P < 0.05) and the immunocompetent group (93.51% vs 71.43%, P < 0.05). mNGS detected more pathogens than CMTs did (167 vs 51), identifying 116 organisms that were missed by CMTs. The proportion of antibiotic regimen adjustments based on mNGS results was significantly higher compared to CMTs in both the immunocompromised (70.00% vs 17.50%, P < 0.05) and immunocompetent groups (48.70% vs 15.58%, P < 0.05). In the immunocompromised group, patients who had their antibiotic treatment adjusted on mNGS results had improved prognosis, with significantly lower ICU mortality (8.93% vs 50%, P < 0.05) and 28-day mortality rates (30.36% vs 68.75%, P < 0.05) than CMTs. In the immunocompetent group, no statistically significant differences were observed in ICU mortality or 28-day mortality (20.00% vs 33.33%, P > 0.05; 42.67% vs 45.83%, P > 0.05).

CONCLUSION

mNGS shows significant value in detecting pathogens in immunocompromised patients with SRIs in ICU. For immunocompromised patients who respond poorly to empirical treatment, mNGS can provide an etiological basis, helping adjust antibiotic regimens more precisely and thereby improving patient prognosis.

The Utility of Real-Time PCR, Metagenomic Next-Generation Sequencing, and Culture in Bronchoalveolar Lavage Fluid for Diagnosis of Pulmonary Aspergillosis

Timely detection of Aspergillus infection is crucial given the high mortality rate of pulmonary aspergillosis (PA). Here, the diagnostic performances for PA of mycological culture, Aspergillus real-time PCR, and metagenomic next-generation sequencing (mNGS) assay from bronchoalveolar lavage fluid, were evaluated. In total, 139 patients with suspected fungal pneumonia were enrolled between December 2021 and July 2023, collecting 139 bronchoalveolar lavage fluid samples for real-time PCR and culture, with 87 undergoing mNGS assay. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve with 95% CIs of these assays for PA were as follows: 35.3% (14.2%-61.7%), 100.0% (94.0%-100.0%), 100.0% (54.1%-100.0%), 84.5% (79.3%-88.6%), and 0.676 (0.560-0.779), respectively, for culture; 82.4% (56.6%-96.2%), 98.3% (91.1%-100.0%), 93.3% (66.4%-99.0%), 95.2% (87.6%-98.2%), and 0.903 (0.815-0.959), respectively, for same diagnostic performance of real-time PCR and mNGS; and 94.1% (71.3%-99.9%), 96.7% (88.5%-99.6%), 88.9% (67.1%-96.9%), 98.3% (89.6%-99.7%), and 0.954 (0.880-0.989), respectively, for real-time PCR combining mNGS; real-time PCR, mNGS, and their combination significantly improved in area under the curve values over culture (P < 0.001), but real-time PCR testing and mNGS had no significant difference with each other and their combination. Overall, the performance of culture was limited by low sensitivity; both real-time PCR and mNGS assays as single diagnostic tests are promising compared with culture and combined tests.

PathoTracker: an online analytical metagenomic platform for Klebsiella pneumoniae feature identification and outbreak alerting

Clinical metagenomics (CMg) Nanopore sequencing can facilitate infectious disease diagnosis. In China, sub-lineages ST11-KL64 and ST11-KL47 Carbapenem-resistant Klebsiella pneumoniae (CRKP) are widely prevalent. We propose PathoTracker, a specially compiled database and arranged method for strain feature identification in CMg samples and CRKP traceability. A database targeting high-prevalence horizontal gene transfer in CRKP strains and a ST11-only database for distinguishing two sub-lineages in China were created. To make the database user-friendly, facilitate immediate downstream strain feature identification from raw Nanopore metagenomic data, and avoid the need for phylogenetic analysis from scratch, we developed data analysis methods. The methods included pre-performed phylogenetic analysis, gene-isolate-cluster index and multilevel pan-genome database and reduced storage space by 10-fold and random-access memory by 52-fold compared with normal methods. PathoTracker can provide accurate and fast strain-level analysis for CMg data after 1 h Nanopore sequencing, allowing early warning of outbreaks. A user-friendly page ( http://PathoTracker.pku.edu.cn/ ) was developed to facilitate online analysis, including strain-level feature, species identifications and phylogenetic analyses. PathoTracker proposed in this study will aid in the downstream analysis of CMg.

Rapid inference of antibiotic resistance and susceptibility for Klebsiella pneumoniae by clinical shotgun metagenomic sequencing

OBJECTIVES

The study aimed to develop a genotypic antimicrobial resistance testing method for Klebsiella pneumoniae using metagenomic sequencing data.

METHODS

We utilized Lasso regression on assembled genomes to identify genetic resistance determinants for six antibiotics (Gentamicin, Tobramycin, Imipenem, Meropenem, Ceftazidime, Trimethoprim/Sulfamethoxazole). The genetic features were weighted, grouped into clusters to establish classifier models. Origin species of detected antibiotic resistant gene (ARG) was determined by novel strategy integrating "possible species," "gene copy number calculation" and "species-specific kmers." The performance of the method was evaluated on retrospective case studies.

RESULTS

Our study employed machine learning on 3928 K. pneumoniae isolates, yielding stable models with AUCs > 0.9 for various antibiotics. GenseqAMR, a read-based software, exhibited high accuracy (AUC 0.926-0.956) for short-read datasets. The integration of a species-specific kmer strategy significantly improved ARG-species attribution to an average accuracy of 96.67%. In a retrospective study of 191 K. pneumoniae-positive clinical specimens (0.68-93.39% genome coverage), GenseqAMR predicted 84.23% of AST results on average. It demonstrated 88.76-96.26% accuracy for resistance prediction, offering genotypic AST results with a shorter turnaround time (mean ± SD: 18.34 ± 0.87 hours) than traditional culture-based AST (60.15 ± 21.58 hours). Furthermore, a retrospective clinical case study involving 63 cases showed that GenseqAMR could lead to changes in clinical treatment for 24 (38.10%) cases, with 95.83% (23/24) of these changes deemed beneficial.

CONCLUSIONS

In conclusion, GenseqAMR is a promising tool for quick and accurate AMR prediction in Klebsiella pneumoniae, with the potential to improve patient outcomes through timely adjustments in antibiotic treatment.

Clinical application of targeted next-generation sequencing in severe pneumonia: a retrospective review

BACKGROUND

The precise identification of the underlying causes of infectious diseases, such as severe pneumonia, is essential, and the development of next-generation sequencing (NGS) has enhanced the effectiveness of pathogen detection. However, there is limited information on the systematic assessment of the clinical use of targeted next-generation sequencing (tNGS) in cases of severe pneumonia.

METHODS

A retrospective analysis was conducted on 130 patients with severe pneumonia treated in the ICU from June 2022 to June 2023. The consistency of the results of tNGS, metagenomics next-generation sequencing (mNGS), and culture with the clinical diagnosis was evaluated. Additionally, the results for pathogens detected by tNGS were compared with those of culture, mNGS, and quantitative reverse transcription PCR (RT-qPCR). To evaluate the efficacy of monitoring severe pneumonia, five patients with complicated infections were selected for tNGS microbiological surveillance. The tNGS and culture drug sensitisation results were then compared.

RESULTS

The tNGS results for the analysis of the 130 patients showed a concordance rate of over 70% with clinical diagnostic results. The detection of pathogenic microorganisms using tNGS was in agreement with the results of culture, mNGS, and RT-qPCR. Furthermore, the tNGS results for pathogens in the five patients monitored for complicated infections of severe pneumonia were consistent with the culture and imaging test results during treatment. The tNGS drug resistance results were in line with the drug sensitivity results in approximately 65% of the cases.

CONCLUSIONS

The application of tNGS highlights its promise and significance in assessing the effectiveness of clinical interventions and providing guidance for anti-infection therapies for severe pneumonia.

Scutellaria baicalensis water decoction ameliorates lower respiratory tract infection by modulating respiratory microbiota

BACKGROUND

The pathogenesis of lower respiratory tract infections (LRTIs) has been demonstrated to be strongly associated with dysbiosis of respiratory microbiota. Scutellaria baicalensis, a traditional Chinese medicine, is widely used to treat respiratory infections. However, whether the therapeutic effect of S. baicalensis on LRTIs depends upon respiratory microbiota regulation is largely unclear.

PURPOSE

To investigate the potential effect and mechanism of S. baicalensis on the respiratory microbiota of LRTI mice.

METHODS

A mouse model of LRTI was established using Klebsiella pneumoniae or Streptococcus pneumoniae. Antibiotic treatment was administered, and transplantation of respiratory microbiota was performed to deplete the respiratory microbiota of mice and recover the destroyed microbial community, respectively. High-performance liquid chromatography (HPLC) was used to determine and quantify the chemical components of S. baicalensis water decoction (SBWD). Pathological changes in lung tissues and the expressions of serum inflammatory cytokines, including interleukin-17A (IL-17A), granulocyte-macrophage colony-stimulating factor (GM-CSF), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α), were determined by hematoxylin and eosin (H&E) staining and enzyme-linked immunosorbent assay (ELISA), respectively. Quantitative real-time PCR (qRT-PCR) analysis was performed to detect the mRNA expression of GM-CSF. Metagenomic sequencing was performed to evaluate the effect of SBWD on the composition and function of the respiratory microbiota in LRTI mice.

RESULTS

Seven main components, including scutellarin, baicalin, oroxylin A-7-O-β-d-glucuronide, wogonoside, baicalein, wogonin, and oroxylin A, were identified and their levels in SBWD were quantified. SBWD ameliorated pulmonary pathological injury and inflammatory responses in K. pneumoniae and S. pneumoniae-induced LRTI mice, as evidenced by the dose-dependent reductions in the levels of serum inflammatory cytokines, IL-6 and TNF-α. SBWD may exert a bidirectional regulatory effect on the host innate immune responses in LRTI mice and regulate the expressions of IL-17A and GM-CSF in a microbiota-dependent manner. K. pneumoniae infection but not S. pneumoniae infection led to dysbiosis in the respiratory microbiota, evident through disturbances in the taxonomic composition characterized by bacterial enrichment, including Proteobacteria, Enterobacteriaceae, and Klebsiella. K. pneumoniae and S. pneumoniae infection altered the bacterial functional profile of the respiratory microbiota, as indicated by increases in lipopolysaccharide biosynthesis, metabolic pathways, and carbohydrate metabolism. SBWD had a certain trend on the regulation of compositional disorders in the respiratory flora and modulated partial microbial functions embracing carbohydrate metabolism in K. pneumoniae-induced LRTI mice.

CONCLUSION

SBWD may exert an anti-infection effect on LRTI by targeting IL-17A and GM-CSF through respiratory microbiota regulation. The mechanism of S. baicalensis action on respiratory microbiota in LRTI treatment merits further investigation.

Nanopore sequencing for smear-negative pulmonary tuberculosis-a multicentre prospective study in China

PURPOSE

In this prospective study, the diagnosis accuracy of nanopore sequencing-based Mycobacterium tuberculosis (MTB) detection was determined through examining bronchoalveolar lavage fluid (BALF) samples from pulmonary tuberculosis (PTB) -suspected patients. Compared the diagnostic performance of nanopore sequencing, mycobacterial growth indicator tube (MGIT) culture and Xpert MTB/rifampin resistance (MTB/RIF) assays.

METHODS

Specimens collected from suspected PTB cases across China from September 2021 to April 2022 were tested then assay diagnostic accuracy rates were compared.

RESULTS

Among the 111 suspected PTB cases that were ultimately diagnosed as PTB, the diagnostic rate of nanopore sequencing was statistically significant different from other assays (P < 0.05). Fleiss' kappa values of 0.219 and 0.303 indicated fair consistency levels between MTB detection results obtained using nanopore sequencing versus other assays, respectively. Respective PTB diagnostic sensitivity rates of MGIT culture, Xpert MTB/RIF and nanopore sequencing of 36.11%, 40.28% and 83.33% indicated superior sensitivity of nanopore sequencing. Analysis of area under the curve (AUC), Youden's index and accuracy values and the negative predictive value (NPV) indicated superior MTB detection performance for nanopore sequencing (with Xpert MTB/RIF ranking second), while the PTB diagnostic accuracy rate of nanopore sequencing exceeded corresponding rates of the other methods.

CONCLUSIONS

In comparison with MGIT culture and Xpert MTB/RIF assays, BALF's nanopore sequencing provided superior MTB detection sensitivity and thus is suitable for testing of sputum-scarce suspected PTB cases. However, negative results obtained using these assays should be confirmed based on additional evidence before ruling out a PTB diagnosis.

Molecular rapid diagnostic testing for bloodstream infections: Nanopore targeted sequencing with pathogen-specific primers

BACKGROUND

Nanopore sequencing, known for real-time analysis, shows promise for rapid clinical infection diagnosis but lacks effective assays for bloodstream infections (BSIs).

METHODS

We prospectively assessed the performance of a novel nanopore targeted sequencing (NTS) assay in identifying pathogens and predicting antibiotic resistance in BSIs, analyzing 387 blood samples from December 2021 to April 2023.

RESULTS

The positivity rate for NTS (69.5 %, 269/387) nearly matches that of metagenomic next-generation sequencing (mNGS) (74.7 %, 289/387; p = 0.128) and surpasses the positivity rate of conventional blood culture (BC) (33.9 %, 131/387; p < 0.01). Frequent pathogens detected by NTS included Klebsiella pneumoniae (n = 54), Pseudomonas aeruginosa (n = 36), Escherichia coli (n = 36), Enterococcus faecium(n = 30), Acinetobacter baumannii(n = 26), Staphylococcus aureus(n = 23), and Human cytomegalovirus (n = 37). Against a composite BSI diagnostic standard, NTS demonstrated a sensitivity and specificity of 84.0 % (95 % CI 79.5 %-87.7 %) and 90.1 % (95 % CI 81.7 %-88.5 %), respectively. The concordance between NTS and mNGS results (the percentage of total cases where both either detected BSI-related pathogens or were both negative) was 90.2 % (359/387), whereas the consistency between NTS and BC was only 60.2 % (233/387). In 80.6 % (50/62) of the samples with identical pathogens identified by both NTS tests and BCs, the genotypic resistance identified by NTS correlated with culture-confirmed phenotypic resistance. Using NTS, 95 % of samples can be tested and analyzed in approximately 7 h, allowing for early patient diagnosis.

CONCLUSIONS

NTS is rapid, sensitive, and efficient for detecting BSIs and drug-resistant genes, making it a potential preferred diagnostic tool for early infection identification in critically ill patients.

Antimicrobial resistance prediction by clinical metagenomics in pediatric severe pneumonia patients

BACKGROUND

Antimicrobial resistance (AMR) is a major threat to children's health, particularly in respiratory infections. Accurate identification of pathogens and AMR is crucial for targeted antibiotic treatment. Metagenomic next-generation sequencing (mNGS) shows promise in directly detecting microorganisms and resistance genes in clinical samples. However, the accuracy of AMR prediction through mNGS testing needs further investigation for practical clinical decision-making.

METHODS

We aimed to evaluate the performance of mNGS in predicting AMR for severe pneumonia in pediatric patients. We conducted a retrospective analysis at a tertiary hospital from May 2022 to May 2023. Simultaneous mNGS and culture were performed on bronchoalveolar lavage fluid samples obtained from pediatric patients with severe pneumonia. By comparing the results of mNGS detection of microorganisms and antibiotic resistance genes with those of culture, sensitivity, specificity, positive predictive value, and negative predictive value were calculated.

RESULTS

mNGS detected bacterial in 71.7% cases (86/120), significantly higher than culture (58/120, 48.3%). Compared to culture, mNGS demonstrated a sensitivity of 96.6% and a specificity of 51.6% in detecting pathogenic microorganisms. Phenotypic susceptibility testing (PST) of 19 antibiotics revealed significant variations in antibiotics resistance rates among different bacteria. Sensitivity prediction of mNGS for carbapenem resistance was higher than penicillins and cephalosporin (67.74% vs. 28.57%, 46.15%), while specificity showed no significant difference (85.71%, 75.00%, 75.00%). mNGS also showed a high sensitivity of 94.74% in predicting carbapenem resistance in Acinetobacter baumannii.

CONCLUSIONS

mNGS exhibits variable predictive performance among different pathogens and antibiotics, indicating its potential as a supplementary tool to conventional PST. However, mNGS currently cannot replace conventional PST.

Diagnostic strategy of metagenomic next-generation sequencing for gram negative bacteria in respiratory infections

OBJECTIVE

This study aims to identify the most effective diagnostic method for distinguishing pathogenic and non-pathogenic Gram-negative bacteria (GNB) in suspected pneumonia cases using metagenomic next-generation sequencing (mNGS) on bronchoalveolar lavage fluid (BALF) samples.

METHODS

The effectiveness of mNGS was assessed on BALF samples collected from 583 patients, and the results were compared with those from microbiological culture and final clinical diagnosis. Three interpretational approaches were evaluated for diagnostic accuracy.

RESULTS

mNGS outperformed culture significantly. Among the interpretational approaches, Clinical Interpretation (CI) demonstrated the best diagnostic performance with a sensitivity of 87.3%, specificity of 100%, positive predictive value of 100%, and negative predictive value of 98.3%. CI's specificity was significantly higher than Simple Interpretation (SI) at 37.9%. Additionally, CI excluded some microorganisms identified as putative pathogens by SI, including Haemophilus parainfluenzae, Haemophilus parahaemolyticus, and Klebsiella aerogenes.

CONCLUSION

Proper interpretation of mNGS data is crucial for accurately diagnosing respiratory infections caused by GNB. CI is recommended for this purpose.

Nanopore sequencing of infectious fluid is a promising supplement for gold-standard culture in real-world clinical scenario

Introduction

Infectious diseases are major causes of morbidity and mortality worldwide, necessitating the rapid identification and accurate diagnosis of pathogens. While unbiased metagenomic next-generation sequencing (mNGS) has been extensively utilized in clinical pathogen identification and scientific microbiome detection, there is limited research about the application of nanopore platform-based mNGS in the diagnostic performance of various infectious fluid samples.

Methods

In this study, we collected 297 suspected infectious fluids from 10 clinical centers and detected them with conventional microbiology culture and nanopore platform-based mNGS. The objective was to assess detective and diagnostic performance of nanopore-sequencing technology (NST) in real-world scenarios.

Results

Combined with gold-standard culture and clinical adjudication, nanopore sequencing demonstrated nearly 100% positive predictive agreements in microbial-colonized sites, such as the respiratory and urinary tracts. For samples collected from initially sterile body sites, the detected microorganisms were highly suspected pathogens, and the negative predictive agreements were relatively higher than those in the microbial-colonized sites, particularly with 100% in abscess and 95.7% in cerebrospinal fluid. Furthermore, consistent performance was also observed in the identification of antimicrobial resistance genes and drug susceptibility testing of pathogenic strains of Escherichia coli, Staphylococcus aureus, and Acinetobacter baumannii.

Discussion

Rapid NST is a promising clinical tool to supplement gold-standard culture, and it has the potential improve patient prognosis and facilitate clinical treatment of infectious diseases.

Modeling the limits of detection for antimicrobial resistance genes in agri-food samples: a comparative analysis of bioinformatics tools

BACKGROUND

Although the spread of antimicrobial resistance (AMR) through food and its production poses a significant concern, there is limited research on the prevalence of AMR bacteria in various agri-food products. Sequencing technologies are increasingly being used to track the spread of AMR genes (ARGs) in bacteria, and metagenomics has the potential to bypass some of the limitations of single isolate characterization by allowing simultaneous analysis of the agri-food product microbiome and associated resistome. However, metagenomics may still be hindered by methodological biases, presence of eukaryotic DNA, and difficulties in detecting low abundance targets within an attainable sequence coverage. The goal of this study was to assess whether limits of detection of ARGs in agri-food metagenomes were influenced by sample type and bioinformatic approaches.

RESULTS

We simulated metagenomes containing different proportions of AMR pathogens and analysed them for taxonomic composition and ARGs using several common bioinformatic tools. Kraken2/Bracken estimates of species abundance were closest to expected values. However, analysis by both Kraken2/Bracken indicated presence of organisms not included in the synthetic metagenomes. Metaphlan3/Metaphlan4 analysis of community composition was more specific but with lower sensitivity than the Kraken2/Bracken analysis. Accurate detection of ARGs dropped drastically below 5X isolate genome coverage. However, it was sometimes possible to detect ARGs and closely related alleles at lower coverage levels if using a lower ARG-target coverage cutoff (< 80%). While KMA and CARD-RGI only predicted presence of expected ARG-targets or closely related gene-alleles, SRST2 (which allows read to map to multiple targets) falsely reported presence of distantly related ARGs at all isolate genome coverage levels. The presence of background microbiota in metagenomes influenced the accuracy of ARG detection by KMA, resulting in mcr-1 detection at 0.1X isolate coverage in the lettuce but not in the beef metagenome.

CONCLUSIONS

This study demonstrates accurate detection of ARGs in synthetic metagenomes using various bioinformatic methods, provided that reads from the ARG-encoding organism exceed approximately 5X isolate coverage (i.e. 0.4% of a 40 million read metagenome). While lowering thresholds for target gene detection improved sensitivity, this led to the identification of alternative ARG-alleles, potentially confounding the identification of critical ARGs in the resistome. Further advancements in sequencing technologies providing increased coverage depth or extended read lengths may improve ARG detection in agri-food metagenomic samples, enabling use of this approach for tracking clinically important ARGs in agri-food samples.

The antibiotic resistance reservoir of the lung microbiome expands with age in a population of critically ill patients

Antimicrobial resistant lower respiratory tract infections are an increasing public health threat and an important cause of global mortality. The lung microbiome can influence susceptibility of respiratory tract infections and represents an important reservoir for exchange of antimicrobial resistance genes. Studies of the gut microbiome have found an association between age and increasing antimicrobial resistance gene burden, however, corollary studies in the lung microbiome remain absent. We performed an observational study of children and adults with acute respiratory failure admitted to the intensive care unit. From tracheal aspirate RNA sequencing data, we evaluated age-related differences in detectable antimicrobial resistance gene expression in the lung microbiome. Using a multivariable logistic regression model, we find that detection of antimicrobial resistance gene expression was significantly higher in adults compared with children after adjusting for demographic and clinical characteristics. This association remained significant after additionally adjusting for lung bacterial microbiome characteristics, and when modeling age as a continuous variable. The proportion of adults expressing beta-lactam, aminoglycoside, and tetracycline antimicrobial resistance genes was higher compared to children. Together, these findings shape our understanding of the lung resistome in critically ill patients across the lifespan, which may have implications for clinical management and global public health.

Applicability of Bronchoalveolar Lavage Fluid and Plasma Metagenomic Next-Generation Sequencing Assays in the Diagnosis of Pneumonia

Background

Metagenomic next-generation sequencing (mNGS) provides innovative solutions for predicting complex infections. A comprehensive understanding of its strengths and limitations in real-world clinical settings is necessary to ensure that it is not overused or misinterpreted.

Methods

Two hundred nine cases with suspected pneumonia were recruited to compare the capabilities of 2 available mNGS assays (bronchoalveolar lavage fluid [BALF] mNGS and plasma mNGS) to identify pneumonia-associated DNA/RNA pathogens and predict antibiotic resistance.

Results

Compared to clinical diagnosis, BALF mNGS demonstrated a high positive percent agreement (95.3%) but a low negative percent agreement (63.1%). Plasma mNGS revealed a low proportion of true negatives (30%) in predicting pulmonary infection. BALF mNGS independently diagnosed 65.6% (61/93) of coinfections and had a remarkable advantage in detecting caustic, rare, or atypical pathogens. Pathogens susceptible to invasive infection or bloodstream transmission, such as Aspergillus spp, Rhizopus spp, Chlamydia psittaci, and human herpesviruses, are prone to be detected by plasma mNGS. BALF mNGS tests provided a positive impact on the diagnosis and treatment of 128 (61.2%) patients. Plasma mNGS, on the other hand, turned out to be more suitable for diagnosing patients who received mechanical ventilation, developed severe pneumonia, or developed sepsis (all P < .01). BALF mNGS was able to identify resistance genes that matched the phenotypic resistance of 69.4% (25/36) of multidrug-resistant pathogens.

Conclusions

Our data reveal new insights into the advantages and disadvantages of 2 different sequencing modalities in pathogen identification and antibiotic resistance prediction for patients with suspected pneumonia.

Clinical utility of metagenomic next-generation sequencing in pathogen detection for lower respiratory tract infections and impact on clinical outcomes in southernmost China

Background

Today, metagenomic next-generation sequencing (mNGS) has emerged as a diagnostic tool for infections. However, since Hainan has a complicated pathogen spectrum, the diagnostic value and impact on patient outcomes of mNGS in Hainan are to be explored.

Methods

From April 2020 to October 2021, 266 suspected lower respiratory tract infections (LRTIs) patients in Hainan were enrolled, and specimens were collected before antibiotic treatment. Bronchoalveolar lavage fluid (BALF) samples were subjected to mNGS and culture to compare the diagnostic performance. Other conventional microbiological tests (CMT) were also performed. Patients' treatments and clinical outcomes were recorded, and the antibiotic resistance genes (ARGs) were detected via mNGS workflow.

Results

The positive rate of mNGS outperformed that of culture (87.55% vs. 39.30%, p<0.001) and CMT (87.12% vs. 52.65%, p<0.001). Specifically, mNGS detected more P. aeruginosa (12.03% vs 9.02%, p<0.05), H. influenzae (9.77% vs 2.26%, p<0.001), Aspergillus fumigatus (3.00% vs 0.75%, p<0.05), Candida albicans (26.32% vs 7.52%, p<0.001) and uncommon pathogens. It also demonstrated great diagnostic advantages in Mycobacterium tuberculosis with 80% sensitivity and 97.4% specificity. Over half of the patients (147, 55.26%) had modified empirical treatment according to mNGS results and 89.12% of them responded well. For three deaths with modified treatment, multiple drug resistance was predicted by mNGS and confirmed by antibiotic susceptibility test.

Conclusions

The application of mNGS can benefit clinics in pathogen identification and antimicrobial treatment stewardship. Physicians should be alert to some emerging uncommon pathogens, including Chlamydia Psittaci, Nocardia otitidiscaviarum, and rare NTM.

Rapid Detection of Antimicrobial Resistance Genes in Critically Ill Children Using a Custom TaqMan Array Card

Bacteria are identified in only 22% of critically ill children with respiratory infections treated with antimicrobial therapy. Once an organism is isolated, antimicrobial susceptibility results (phenotypic testing) can take another day. A rapid diagnostic test identifying antimicrobial resistance (AMR) genes could help clinicians make earlier, informed antimicrobial decisions. Here we aimed to validate a custom AMR gene TaqMan Array Card (AMR-TAC) for the first time and assess its feasibility as a screening tool in critically ill children. An AMR-TAC was developed using a combination of commercial and bespoke targets capable of detecting 23 AMR genes. This was validated using isolates with known phenotypic resistance. The card was then tested on lower respiratory tract and faecal samples obtained from mechanically ventilated children in a single-centre observational study of respiratory infection. There were 82 children with samples available, with a median age of 1.2 years. Major comorbidity was present in 29 (35%) children. A bacterial respiratory pathogen was identified in 13/82 (16%) of children, of which 4/13 (31%) had phenotypic AMR. One AMR gene was detected in 49/82 (60%), and multiple AMR genes were detected in 14/82 (17%) children. Most AMR gene detections were not associated with the identification of phenotypic AMR. AMR genes are commonly detected in samples collected from mechanically ventilated children with suspected respiratory infections. AMR-TAC may have a role as an adjunct test in selected children in whom there is a high suspicion of antimicrobial treatment failure.

Development of a portable on-site applicable metagenomic data generation workflow for enhanced pathogen and antimicrobial resistance surveillance

Rapid, accurate and comprehensive diagnostics are essential for outbreak prevention and pathogen surveillance. Real-time, on-site metagenomics on miniaturized devices, such as Oxford Nanopore Technologies MinION sequencing, could provide a promising approach. However, current sample preparation protocols often require substantial equipment and dedicated laboratories, limiting their use. In this study, we developed a rapid on-site applicable DNA extraction and library preparation approach for nanopore sequencing, using portable devices. The optimized method consists of a portable mechanical lysis approach followed by magnetic bead-based DNA purification and automated sequencing library preparation, and resulted in a throughput comparable to a current optimal, laboratory-based protocol using enzymatic digestion to lyse cells. By using spike-in reference communities, we compared the on-site method with other workflows, and demonstrated reliable taxonomic profiling, despite method-specific biases. We also demonstrated the added value of long-read sequencing by recovering reads containing full-length antimicrobial resistance genes, and attributing them to a host species based on the additional genomic information they contain. Our method may provide a rapid, widely-applicable approach for microbial detection and surveillance in a variety of on-site settings.

The antibiotic resistance reservoir of the lung microbiome expands with age

Antimicrobial resistant lower respiratory tract infections (LRTI) are an increasing public health threat, and an important cause of global mortality. The lung microbiome influences LRTI susceptibility and represents an important reservoir for exchange of antimicrobial resistance genes (ARGs). Studies of the gut microbiome have found an association between age and increasing antimicrobial resistance gene (ARG) burden, however corollary studies in the lung microbiome remain absent, despite the respiratory tract representing one of the most clinically significant sites for drug resistant infections. We performed a prospective, multicenter observational study of 261 children and 88 adults with acute respiratory failure, ranging in age from 31 days to ≥ 89 years, admitted to intensive care units in the United States. We performed RNA sequencing on tracheal aspirates collected within 72 hours of intubation, and evaluated age-related differences in detectable ARG expression in the lung microbiome as a primary outcome. Secondary outcomes included number and classes of ARGs detected, proportion of patients with an ARG class, and composition of the lung microbiome. Multivariable logistic regression models (adults vs children) or continuous age (years) were adjusted for sex, race/ethnicity, LRTI status, and days from intubation to specimen collection. Detection of ARGs was significantly higher in adults compared with children after adjusting for sex, race/ethnicity, LRTI diagnosis, and days from intubation to specimen collection (adjusted odds ratio (aOR): 2.16, 95% confidence interval (CI): 1.10-4.22). A greater proportion of adults compared with children had beta-lactam ARGs (31% (CI: 21-41%) vs 13% (CI: 10-18%)), aminoglycoside ARGs (20% (CI: 13-30%) vs 2% (CI: 0.6-4%)), and tetracycline ARGs (14% (CI: 7-23%) vs 3% (CI: 1-5%)). Adults ≥70 years old had the highest proportion of these three ARG classes. The total bacterial abundance of the lung microbiome increased with age, and microbiome alpha diversity varied with age. Taxonomic composition of the lung microbiome, measured by Bray Curtis dissimilarity index, differed between adults and children (p = 0.003). The association between age and increased ARG detection remained significant after additionally including lung microbiome total bacterial abundance and alpha diversity in the multivariable logistic regression model (aOR: 2.38, (CI: 1.25-4.54)). Furthermore, this association remained robust when modeling age as a continuous variable (aOR: 1.02, (CI: 1.01-1.03) per year of age). Taken together, our results demonstrate that age is an independent risk factor for ARG detection in the lower respiratory tract microbiome. These data shape our understanding of the lung resistome in critically ill patients across the lifespan, which may have implications for clinical management and global public health.

Metagenomic sequencing of post-mortem tissue samples for the identification of pathogens associated with neonatal deaths

Postmortem minimally invasive tissue sampling together with the detailed review of clinical records has been shown to be highly successful in determining the cause of neonatal deaths. However, conventional tests including traditional culture methods and nucleic acid amplification tests have periodically proven to be insufficient to detect the causative agent in the infectious deaths. In this study, metagenomic next generation sequencing was used to explore for putative pathogens associated with neonatal deaths in post-mortem blood and lung tissue samples, in Soweto, South Africa. Here we show that the metagenomic sequencing results corroborate the findings using conventional methods of culture and nucleic acid amplifications tests on post-mortem samples in detecting the pathogens attributed in the causal pathway of death in 90% (18/20) of the decedents. Furthermore, metagenomic sequencing detected a putative pathogen, including Acinetobacter baumannii, Klebsiella pneumoniae, Escherichia coli, and Serratia marcescens, in a further nine of 11 (81%) cases where no causative pathogen was identified. The antimicrobial susceptibility profile was also determined by the metagenomic sequencing for all pathogens with numerous multi drug resistant organism identified. In conclusion, metagenomic sequencing is able to successfully identify pathogens contributing to infection associated deaths on postmortem blood and tissue samples.

RAPIDprep: A Simple, Fast Protocol for RNA Metagenomic Sequencing of Clinical Samples

Emerging infectious disease threats require rapid response tools to inform diagnostics, treatment, and outbreak control. RNA-based metagenomics offers this; however, most approaches are time-consuming and laborious. Here, we present a simple and fast protocol, the RAPIDprep assay, with the aim of providing a cause-agnostic laboratory diagnosis of infection within 24 h of sample collection by sequencing ribosomal RNA-depleted total RNA. The method is based on the synthesis and amplification of double-stranded cDNA followed by short-read sequencing, with minimal handling and clean-up steps to improve processing time. The approach was optimized and applied to a range of clinical respiratory samples to demonstrate diagnostic and quantitative performance. Our results showed robust depletion of both human and microbial rRNA, and library amplification across different sample types, qualities, and extraction kits using a single workflow without input nucleic-acid quantification or quality assessment. Furthermore, we demonstrated the genomic yield of both known and undiagnosed pathogens with complete genomes recovered in most cases to inform molecular epidemiological investigations and vaccine design. The RAPIDprep assay is a simple and effective tool, and representative of an important shift toward the integration of modern genomic techniques with infectious disease investigations.

Addressing antibiotic resistance: computational answers to a biological problem?

The increasing prevalence of infections caused by antibiotic-resistant bacteria is a global healthcare crisis. Understanding the spread of resistance is predicated on the surveillance of antibiotic resistance genes within an environment. Bioinformatics and artificial intelligence (AI) methods applied to metagenomic sequencing data offer the capacity to detect known and infer yet-unknown resistance mechanisms, and predict future outbreaks of antibiotic-resistant infections. Machine learning methods, in particular, could revive the waning antibiotic discovery pipeline by helping to predict the molecular structure and function of antibiotic resistance compounds, and optimising their interactions with target proteins. Consequently, AI has the capacity to play a central role in guiding antibiotic stewardship and future clinical decision-making around antibiotic resistance.

Respiratory metagenomics: route to routine service

PURPOSE OF REVIEW

The coronavirus disease 2019 pandemic demonstrated broad utility of pathogen sequencing with rapid methodological progress alongside global distribution of sequencing infrastructure. This review considers implications for now moving clinical metagenomics into routine service, with respiratory metagenomics as the exemplar use-case.

RECENT FINDINGS

Respiratory metagenomic workflows have completed proof-of-concept, providing organism identification and many genotypic antimicrobial resistance determinants from clinical samples in <6 h. This enables rapid escalation or de-escalation of empiric therapy for patient benefit and reducing selection of antimicrobial resistance, with genomic-typing available in the same time-frame. Attention is now focussed on demonstrating clinical, health-economic, accreditation, and regulatory requirements. More fundamentally, pathogen sequencing challenges the traditional culture-orientated time frame of microbiology laboratories, which through automation and centralisation risks becoming increasingly separated from the clinical setting. It presents an alternative future where infection experts are brought together around a single genetic output in an acute timeframe, aligning the microbiology target operating model with the wider human genomic and digital strategy.

SUMMARY

Pathogen sequencing is a transformational proposition for microbiology laboratories and their infectious diseases, infection control, and public health partners. Healthcare systems that link output from routine clinical metagenomic sequencing, with pandemic and antimicrobial resistance surveillance, will create valuable tools for protecting their population against future infectious diseases threats.

Metagenomic Sequencing in the ICU for Precision Diagnosis of Critical Infectious Illnesses

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2023. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2023 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from https://link.springer.com/bookseries/8901 .

Diagnostic value of a nanopore sequencing assay of bronchoalveolar lavage fluid in pulmonary tuberculosis

BACKGROUND

To determine the diagnostic accuracy of a nanopore sequencing assay of PCR products from a M. tuberculosis complex-specific region for testing of bronchoalveolar lavage fluid (BALF) samples or sputum samples from suspected pulmonary tuberculosis (PTB) patients and compare the results to results obtained for MGIT and Xpert assays.

METHODS

Cases with suspected PTB (n = 55) were diagnosed from January 2019 to December 2021 based on results of nanopore sequencing, MGIT culture, and Xpert MTB/RIF testing of BALF and sputum samples collected during hospitalization. Diagnostic accuracies of assays were compared.

RESULTS

Ultimately, data from 29 PTB patients and 26 non-PTB cases were analyzed. PTB diagnostic sensitivities of MGIT, Xpert MTB/RIF, and nanopore sequencing assays were 48.28%, 41.38%, and 75.86%, respectively, thus demonstrating that nanopore sequencing provided greater sensitivity than was provided by MGIT culture and Xpert assays (P < 0.05). PTB diagnostic specificities of the respective assays were 65.38%, 100%, and 80.77%, which corresponded with kappa coefficient (κ) values of 0.14, 0.40, and 0.56, respectively. These results indicate that nanopore sequencing provided superior overall performance as compared to Xpert and MGIT culture assays and provided significantly greater PTB diagnostic accuracy than Xpert and sensitivity comparable to that of the MGIT culture assay.

CONCLUSION

Our findings suggest that improved detection of PTB in suspected cases was achieved using nanopore sequencing-based testing of BALF or sputum samples than was achieved using Xpert and MGIT culture-based assays, and nanopore sequencing results alone cannot be used to rule out PTB.

Utility of metagenomics next-generation sequencing in the diagnosis and treatment of severe infectious diseases in the intensive care unit

BACKGROUND

Metagenomic next-generation sequencing (mNGS) is a new method that combines high-throughput sequencing and bioinformatics analysis. However, it has not become as popular due to the limited testing equipment and high costs and lack of family awareness with not much relevant intensive care unit (ICU) research data.

OBJECTIVE

To explore the clinical use and value of metagenomics next-generation sequencing (mNGS) in patients with sepsis in the ICU.

METHODS

We conducted a retrospective analysis of 102 patients with sepsis admitted to the ICU of Peking University International Hospital from January 2018 to January 2022. Based on whether mNGS was performed, the identified patients were divided into the observation group (n= 51) and the control group (n= 51), respectively. Routine laboratory tests, including routine blood test, C-reactive protein, procalcitonin, and culture of suspicious lesion specimens were performed in both groups within 2 hours after admission to the ICU, while mNGS tests were performed in the observation group. Patients in both groups were routinely given initial anti-infective, anti-shock, and organ support treatment. Antibiotic regimens were optimized in a timely manner according to the etiological results. Relevant clinical data were collected.

RESULTS

The testing cycle of mNGS was shorter than that of the conventional culture (30.79 ± 4.01 h vs. 85.38 ± 9.94 h, P< 0.001), while the positive rate of mNGS was higher than that of the conventional culture (82.35% vs. 45.1%, P< 0.05), with obvious superiority in the detection of viruses and fungus. There were significant differences in the optimal time of antibiotics (48 h vs.100 h) and length of ICU stay (11 d vs. 16 d) between the observation group and control group (P< 0.01) respectively, with no difference in 28-day mortality (33.3% vs. 41.2%, P> 0.05).

CONCLUSION

mNGS is useful in the detection of sepsis-causing pathogens in the ICU with the advantages of short testing time and high positive rate. There was no difference in the 28-day outcome between the two groups, which may be related to other confounding factors such as small sample size. Additional studies with extended sample size are needed.