Metagenomic Next-Generation Sequencing for the Diagnosis of Neonatal Infectious Diseases

Microbial cell-free DNA-sequencing as an addition to conventional diagnostics in neonatal sepsis

BACKGROUND

Bloodstream infections remain a challenge for neonatologists, as traditional culture-based methods are time-consuming and rely on adequate blood volume. Next-generation sequencing (NGS) offers an alternative, as it can identify microbial cell-free DNA (mcfDNA) in a small blood sample, providing rapid pathogen detection. This study aimed to assess the diagnostic performance of DISQVER®-NGS compared to blood cultures in neonatal patients with suspected sepsis.

METHODS

In neonates with suspected sepsis, blood cultures and samples for NGS were prospectively collected. Patients were divided into four categories: 1) sepsis, blood culture positive, 2) clinical sepsis, culture negative, 3) suspected sepsis, 4) validation cohort.

RESULTS

NGS detected bacterial, viral or fungal mcfDNA in 24 of 82 samples. Blood cultures were collected in 46 of 84 patients (15/46 positive). DISQVER® correctly identified pathogens in 9/15 patients with a positive blood culture, two with intrinsic resistance to their antibiotic regimen. In seven samples NGS reported the mcfDNA of bacteria that could have theoretically grown in culture but did not.

CONCLUSIONS

NGS may enhance sensitivity in sepsis diagnostics by detecting mcfDNA in neonates with suspected sepsis. Interpreting NGS results requires correlation with clinical data, laboratory values, and routine microbiological tests for a comprehensive understanding of the patient's condition.

IMPACT

Conventional blood culture methods have limitations in accuracy and turnaround time. The study aimed to investigate the diagnostic performance of the Next-Generation Sequencing method DISQVER® compared to traditional blood cultures in neonatal patients with suspected sepsis. Our findings suggest that NGS has the potential to augment the precision of conventional diagnostic techniques, can lead to improved detection of pathogens and targeted treatment approaches in neonatal sepsis. It is emphasized that further validation and integration with clinical and microbiological data are required to ensure optimal clinical utility.

The effects of sequencing strategies on Metagenomic pathogen detection using bronchoalveolar lavage fluid samples

Objectives

Metagenomic next-generation sequencing (mNGS) is a powerful tool for pathogen detection. The accuracy depends on both wet lab and dry lab procedures. The objective of our study was to assess the influence of read length and dataset size on pathogen detection.

Methods

In this study, 43 clinical BALF samples, which tested positive via clinical mNGS and were consistent with the diagnosis, were subjected to re-sequencing on the Illumina NovaSeq 6000 platform. The raw re-sequencing data, consisting of 100 million (M) paired-end 150 bp (PE150) reads, were divided into simulated datasets with eight different data sizes (5 M, 10 M, 15 M, 20 M, 30 M, 50 M, 75 M, 100 M) and five different read lengths (single-end 50 bp (SE50), SE75, SE100, PE100, and PE150). Both Kraken2 and IDseq bioinformatics pipelines were employed to analyze the previously diagnosed pathogens in the simulated data. Detection of pathogens was based on read counts ranging from 1 to 10 and RPM values ranging from 0.2 to 2.

Results

Our results revealed that increasing dataset sizes and read lengths can enhance the performance of mNGS in pathogen detection. However, a larger data sizes for mNGS require higher economic costs and longer turnaround time for data analysis. Our findings indicate 20 M reads being sufficient for SE75 mode to achieve high recall rates. Additionally, high nucleic acid loads in samples can lead to increased stability in pathogen detection efficiency, reducing the impact of sequencing strategies. The choice of bioinformatics pipelines had a significant impact on recall rates achieved in pathogen detection.

Conclusions

Increasing dataset sizes and read lengths can enhance the performance of mNGS in pathogen detection but increase the economic and time costs of sequencing and data analysis. Currently, the 20 M reads in SE75 mode may be the best sequencing option.

Metagenomic Next-generation Sequencing for Pathogen Identification in Bronchoalveolar Lavage Fluid From Neonates Receiving Extracorporeal Membrane Oxygenation

BACKGROUND

Neonates on extracorporeal membrane oxygenation (ECMO) are at high risk of infection. Rapid and accurate identification of pathogens is essential to improve the prognosis of children on ECMO. Metagenome next-generation sequencing (mNGS) has been used in recent years to detect pathogenic bacteria, but evidence for its use in neonates on ECMO is lacking.

METHODS

This retrospective study was conducted using an electronic medical record system. We analyzed the results of mNGS and conventional microbiological tests (CMTs) in bronchoalveolar lavage fluid of neonates receiving ECMO support with pulmonary infections in our hospital from July 2021 to January 2023.

RESULTS

We screened 18 ECMO-supported neonates with pneumonia for inclusion in the study. The median age of the included children was 2 (1-4) days, the median gestational age was 38.3 (33-40 +4 ) weeks, and the median weight was 3.3 (2.2-4.8) kg. The detection rate of mNGS was 77.8% (14/18), higher than the 44.4% (8/18) of CMT ( P = 0.04). A total of 20 pathogens were detected in mNGS, with the top 3 most common pathogens being Klebsiella pneumoniae , Acinetobacter baumannii and Escherichia coli . Mixed infections were found in 14 cases (77.8%), including 13 cases (72.2%) with mixed infections detected by mNGS and 7 cases (27.8%) with mixed infections detected by CMT. A total of 9 children underwent treatment changes based on mNGS results and all of them experienced relief of symptoms.

CONCLUSION

Compared with CMT, mNGS can detect pathogens earlier and more sensitively, and may play an important role in ECMO-supported neonatal pneumonia pathogen detection and optimization of antibiotic therapy.

Combination of metagenomic next-generation sequencing and conventional tests unraveled pathogen profiles in infected patients undergoing allogeneic hematopoietic stem cell transplantation in Jilin Province of China

Background

Infection is the main cause of death for patients after allogeneic hematopoietic stem cell transplantation (HSCT). However, pathogen profiles still have not been reported in detail due to their heterogeneity caused by geographic region.

Objective

To evaluate the performance of metagenomic next-generation sequencing (mNGS) and summarize regional pathogen profiles of infected patients after HSCT.

Methods

From February 2021 to August 2022, 64 patients, admitted to the Department of Hematology of The First Hospital of Jilin University for HSCT and diagnosed as suspected infections, were retrospectively enrolled.

Results

A total of 38 patients were diagnosed as having infections, including bloodstream (n =17), pulmonary (n =16), central nervous system (CNS) (n =4), and chest (n =1) infections. Human betaherpesvirus 5 (CMV) was the most common pathogen in both bloodstream (n =10) and pulmonary (n =8) infections, while CNS (n =2) and chest (n =1) infections were mainly caused by Human gammaherpesvirus 4 (EBV). For bloodstream infection, Mycobacterium tuberculosis complex (n =3), Staphylococcus epidermidis (n =1), and Candida tropicalis (n =1) were also diagnosed as causative pathogens. Furthermore, mNGS combined with conventional tests can identify more causative pathogens with high sensitivity of 82.9% (95% CI 70.4-95.3%), and the total coincidence rate can reach up to 76.7% (95% CI 64.1-89.4%).

Conclusions

Our findings emphasized the importance of mNGS in diagnosing, managing, and ruling out infections, and an era of more rapid, independent, and impartial diagnosis of infections after HSCT can be expected.

Diagnostic performance of metagenomic next-generation sequencing for the detection of pathogens in cerebrospinal fluid in pediatric patients with central nervous system infection: a systematic review and meta-analysis

BACKGROUND

Detecting pathogens in pediatric central nervous system infection (CNSI) is still a major challenge in medicine. In addition to conventional diagnostic patterns, metagenomic next-generation sequencing (mNGS) shows great potential in pathogen detection. Therefore, we systematically evaluated the diagnostic performance of mNGS in cerebrospinal fluid (CSF) in pediatric patients with CNSI.

METHODS

Related literature was searched in the Web of Science, PubMed, Embase, and Cochrane Library. We screened the literature and extracted the data according to the selection criteria. The quality of included studies was assessed by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool and the certainty of the evidence was measured by the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) score system. Then, the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odd's ratio (DOR), and area under the curve (AUC) of the summary receiver operating characteristic curve (sROC) were estimated in Stata Software and MetaDisc. Subgroup analyses were performed to investigate the potential factors that influence the diagnostic performance.

RESULTS

A total of 10 studies were included in the meta-analysis. The combined sensitivity was 0.68 (95% confidence interval [CI]: 0.59 to 0.76, I2 = 66.77%, p < 0.001), and the combined specificity was 0.89 (95% CI: 0.80 to 0.95, I2 = 83.37%, p < 0.001). The AUC of sROC was 0.85 (95% CI, 0.81 to 0.87). The quality level of evidence elevated by the GRADE score system was low.

CONCLUSIONS

Current evidence shows that mNGS presents a good diagnostic performance in pediatric CNSI. Due to the limited quality and quantity of the included studies, more high-quality studies are needed to verify the above conclusion.

Performance of clinical metagenomics in France: a prospective observational study

BACKGROUND

Metagenomic next-generation sequencing (mNGS) allows untargeted identification of a broad range of pathogens, including rare or novel microorganisms. Despite the recognition of mNGS as a valuable diagnostic tool for infections, the most relevant indications for this innovative strategy remain poorly defined. We aimed to assess the determinants of positivity and clinical utility of mNGS.

METHODS

In this observational study, we prospectively performed short-read shotgun metagenomics analysis as a second-line test (in cases of negative first-line test or when the symptoms were not fully explained by initial positive results) or as a first-line test in life-threatening situations requiring urgent non-targeted pathogen identification at the Necker-Enfants Malades Hospital (Paris, France). All sample types, clinical indications, and patient populations were included. Samples were accompanied by a mandatory form completed by the senior clinician or pathologist, on which the clinical level of suspected infection (defined as high or low) was indicated. We assessed the variables (gender, age, immune status, initial suspicion of infection, indication, and sample type) associated with mNGS pathogen detection using odds ratios (ORs) from multivariate logistic regression. Additional investigations were carried out using specific PCR or culture techniques, to confirm positive mNGS results, or when infectious suspicion was particularly high despite a negative mNGS result.

FINDINGS

Between Oct 29, 2019, and Nov 7, 2022, we analysed 742 samples collected from 523 patients. The initial suspicion of infection was either high (n=470, 63%) or low (n=272, 37%). Causative or possibly causative pathogens were detected in 117 (25%) samples from patients with high initial suspicion of infection, versus nine (3%) samples analysed to rule out infection (OR 9·1, 95% CI 4·6-20·4; p<0·0001). We showed that mNGS had higher odds of detecting a causative or possibly causative pathogenic virus on CNS biopsies than CSF samples (4·1, 1·7-10·7; p=0·0025) and in samples from immunodeficient compared with immunocompetent individuals (2·4, 1·4-4·1; p=0·0013). Concordance with conventional confirmatory tests results was 103 (97%) of 106, when mNGS detected causative or possibly causative pathogens. Altogether, among 231 samples investigated by both mNGS and subsequent specific tests, discordant results were found in 69 (30%) samples, of which 58 (84%) were mNGS positive and specific tests negative, and 11 (16%) mNGS negative and specific tests positive.

INTERPRETATION

Major determinants of pathogen detection by mNGS are immune status and initial level of suspicion of infection. These findings will contribute, along with future studies, to refining the positioning of mNGS in diagnostic and treatment decision-making algorithms.

FUNDING

Necker-Enfants Malades Hospital and Institut Pasteur.

TRANSLATION

For the French translation of the abstract see Supplementary Materials section.

Cryptosporidiosis diagnosed using metagenomic next-generation sequencing in a healthy child admitted to pediatric intensive care unit: a case report

Background

Cryptosporidium infections in humans typically result in symptoms such as abdominal pain and diarrhea. When the diarrhea is severe, it can cause serious complications and even be life-threatening, especially in patients with compromised immune systems.

Case presentation

Here, we reported the use of metagenomic next-generation sequencing (mNGS) to assist in the diagnosis and treatment of a 10-year-old boy with severe Cryptosporidium infection. Despite the absence of any history of immunocompromise, the infection still resulted in severe symptoms, including shock, as well as damage to his pancreas and kidneys. The mNGS tests detected the presence of Cryptosporidium parvum when conventional methods failed. The patient received anti-parasite treatment along with supportive care to manage the condition. With disease surveillance based on regular clinical tests and sequential mNGS tests, the child recovered from the severe conditions.

Conclusion

Our study emphasized the importance of recognizing the potential severity of Cryptosporidium infection, even among individuals with normal immune systems. Timely diagnosis and ongoing monitoring are essential for patient prognosis.

High specificity of metagenomic next-generation sequencing using protected bronchial brushing sample in diagnosing pneumonia in children

Background

Lower respiratory tract infections are the leading cause of morbidity and mortality in children worldwide. Timely and accurate pathogen detection is crucial for proper clinical diagnosis and therapeutic strategies. The low detection efficiency of conventional methods and low specificity using respiratory samples seriously hindered the accurate detection of pathogens.

Methods

In this study, we retrospectively enrolled 1,032 children to evaluate the performance of metagenomics next-generation sequencing (mNGS) using bronchoalveolar lavage fluid (BALF) sample and protected bronchial brushing (BB) sample in diagnosing pneumonia in children. In addition, conventional tests (CTs) were also performed.

Results

The specificity of BB mNGS [67.3% (95% CI 58.6%-75.9%)] was significantly higher than that of BALF mNGS [38.5% (95% CI 12.0%-64.9%)]. The total coincidence rate of BB mNGS [77.6% (95% CI 74.8%-80.5%)] was slightly higher than that of BALF mNGS [76.5% (95% CI 68.8%-84.1%)] and CTs [38.5% (95% CI 35.2%-41.9%)]. During the epidemics of Mycoplasma pneumoniae, the detection rate of M. pneumoniae in the >6-year group (81.8%) was higher than that in the 3-6-year (78.9%) and <3-year groups (21.5%). The highest detection rates of bacteria, fungi, and viruses were found in the <3-year, >6-year, and 3-6-year groups, respectively. mNGS detection should be performed at the duration of 5-7 days after the start of continuous anti-microbial therapy or at the duration of 6-9 days from onset to mNGS test.

Conclusions

This is the first report to evaluate the performance of BB mNGS in diagnosing pulmonary infections in children on a large scale. Based on our findings, extensive application of BB mNGS could be expected.

Metagenomic-based pathogen surveillance for children with severe pneumonia in pediatric intensive care unit

Background

Pneumonia is a significant cause of morbidity and mortality in children. Metagenomic next-generation sequencing (mNGS) has the potential to assess the landscape of pathogens responsible for severe pulmonary infection.

Methods

Bronchoalveolar lavage fluid (BALF) samples of 262 children with suspected pulmonary infections were collected from April 2019 to October 2021 in the Pediatric Intensive Care Unit (PICU) of Guangdong Women and Children Hospital. Both mNGS and conventional tests were utilized for pathogen detection.

Results

A total of 80 underlying pathogens were identified using both mNGS and conventional tests. Respiratory syncytial virus (RSV), Staphylococcus aureus and rhinovirus were the most frequently detected pathogens in this cohort. The incidence rate of co-infection was high (58.96%, 148/251), with bacterial-viral agents most co-detected. RSV was the main pathogen in children younger than 6 months of age, and was also commonly found in older pediatric patients. Rhinovirus was prevalent in children older than 6 months. Adenovirus and Mycoplasma pneumoniae were more prevalent in children older than 3 years than in other age groups. Pneumocystis jirovecii was detected in nearly 15% of children younger than 6 months. Besides, influenza virus and adenovirus were rarely found in 2020 and 2021.

Conclusions

Our study highlights the importance of using advanced diagnostic techniques like mNGS to improve our understanding of the microbial epidemiology of severe pneumonia in pediatric patients.