Diagnosis and Surveillance of Neonatal Infections by Metagenomic Next-Generation Sequencing

Case Report: Taking action or standing by: managing a preterm neonate at the risk of neonatal varicella by metagenomic next-generation sequencing

Neonatal varicella is indeed a rare condition, and most infants born to mothers with varicella have a good prognosis. However, in exceptional cases, neonatal varicella can be life-threatening, particularly for preterm infants. Therefore, it is vital to make an early diagnosis or predict the risk of neonatal varicella to ensure prompt treatment and improve prognosis. This report made an effort to early predict neonatal vericalla by using metagenomic next-generation sequencing (mNGS) in a preterm infant who was at risk for vericalla infection. A preterm infant born from a mother with varicella with symptom onset at 8 days before delivery, putting the infant at risk for varicella infection. Importantly, the patient develop pneumonia and pneumothorax, and neonatal vericella was suspected. Fortunately, the use of mNGS for testing the varicella gene in the serum promptly ruled out varicella zoster virus (VZV) infection in the patient, as indicated by a negative mNGS result. Subsequent follow-up, which included a 14-day stay in the hospital followed by an additional 7 days at home, confirmed this finding. Throughout this period, the patient did not exhibit any rash or other symptoms associated with varicella. Therefore, the novel approach of using mNGS allows neonatologists to predict and promptly address potential neonatal infections. This early detection is crucial, as delayed diagnosis or treatment could pose life-threatening risks, as exemplified by the case of neonatal varicella. In such cases, neonatologists can take proactive measures instead of standing by for at-risk neonates. Furthermore, given the severity of neonatal varicella as a life-threatening condition, the early exclusion of subsequent varicella infection by mNGS can offer reassurance to both family members and healthcare professionals.

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.

Tracheal microbiome and metabolome profiling in iatrogenic subglottic tracheal stenosis

BACKGROUND

To study the role of microecology and metabolism in iatrogenic tracheal injury and cicatricial stenosis, we investigated the tracheal microbiome and metabolome in patients with tracheal stenosis after endotracheal intubation.

METHODS

We collected 16 protected specimen brush (PSB) and 8 broncho-alveolar lavage (BAL) samples from 8 iatrogenic subglottic tracheal stenosis patients, including 8 PSB samples from tracheal scar sites, 8 PSB samples from scar-free sites and 8 BAL samples, by lavaging the subsegmental bronchi of the right-middle lobe. Metagenomic sequencing was performed to characterize the microbiome profiling of 16 PSB and 8 BAL samples. Untargeted metabolomics was performed in 6 PSB samples (3 from tracheal scar PSB and 3 from tracheal scar-free PSB) using high-performance liquid chromatography‒mass spectrometry (LC‒MS).

RESULTS

At the species level, the top four bacterial species were Neisseria subflava, Streptococcus oralis, Capnocytophaga gingivals, and Haemophilus aegyptius. The alpha and beta diversity among tracheal scar PSB, scar-free PSB and BAL samples were compared, and no significant differences were found. Untargeted metabolomics was performed in 6 PSB samples using LC‒MS, and only one statistically significant metabolite, carnitine, was identified. Pathway enrichment analysis of carnitine revealed significant enrichment in fatty acid oxidation.

CONCLUSION

Our study found that carnitine levels in tracheal scar tissue were significantly lower than those in scar-free tissue, which might be a new target for the prevention and treatment of iatrogenic tracheal stenosis in the future.

Microbial Community Characterization and Molecular Resistance Monitoring in Geriatric Intensive Care Units in China Using mNGS

Background

Surface pathogens in the ICU pose a global public health threat, especially to elderly patients who are immunocompromised. To detect these pathogens, unbiased methods such as metagenomic next-generation sequencing (mNGS) are increasingly utilized for environmental microbiological surveillance.

Methods

In a six-month study from January to July 2022, we investigated microbial communities in Chinese geriatric ICUs by regularly monitoring multiple surfaces at three-month intervals. Using mNGS sequencing, we analyzed microorganisms present at eight specific locations within the ICU. Additionally, we compared pathogen profiles and drug resistance genes between patient cultures and environmental samples collected during the same period.

Results

The microbial composition remained relatively stable over time, but significant differences in alpha diversities were observed among various surfaces such as floors, hands, pumps, trolleys, and ventilator inlets/outlets. Surfaces with high contact frequency for healthcare workers, including workstations, ventilator panels, trolleys, pumps, and beds, harbored pathogenic microorganisms such as Acinetobacter baumannii, Cutibacterium acnes, Staphylococcus haemolyticus, Pseudomonas aeruginosa, and Enterococcus faecium. Acinetobacter baumannii, particularly the carbapenem-resistant strain (CRAB), was the most frequently identified pathogen in geriatric ICU patients regardless of testing method used. The mNGS approach enabled detection of viruses, fungi, and parasites that are challenging to culture. Additionally, an abundance of drug resistance genes was found in almost all environmental samples.

Conclusion

The microbial composition and abundance in the ICU remained relatively constant over time. The floor exhibited the highest microbial diversity and abundance in the ICU environment. Drug-resistant genes in the ICU environment may migrate between patients. Overall, mNGS is an emerging and powerful tool for microbiological monitoring of the hospital environment.

Comparison of quality/quantity mNGS and usual mNGS for pathogen detection in suspected pulmonary infections

Improved metagenomic next-generation sequencing (mNGS), for example, quality/quantity mNGS (QmNGS), is being used in the diagnosis of pulmonary pathogens. There are differences between QmNGS and the usual mNGS (UmNGS), but reports that compare their detection performances are rare. In this prospective study of patients enrolled between December 2021 and March 2022, the bronchoalveolar lavage fluid of thirty-six patients with suspected pulmonary infection was assessed using UmNGS and QmNGS. The sensitivity of QmNGS was similar to that of UmNGS. The specificity of QmNGS was higher than that of UmNGS; however, the difference was not statistically significant. The positive likelihood ratios (+LR) of QmNGS and UmNGS were 3.956 and 1.394, respectively, and the negative likelihood ratios (-LR) were 0.342 and 0.527, respectively. For the co-detection of pathogens, the depth and coverage of the QmNGS sequencing were lower than those of UmNGS, while for the detection of pathogens isolated from patients with pulmonary infection, the concordance rate was 77.2%. In the eleven patients with nonpulmonary infection, only viruses were detected using QmNGS, while UmNGS detected not only viruses but also bacteria and fungi. This study provides a basis for the selection of mNGS for the diagnosis of suspected pulmonary infection.

Clinical and Laboratory Diagnosis of Legionella Pneumonia

Legionella pneumonia is a relatively rare but extremely progressive pulmonary infection with high mortality. Traditional cultural isolation remains the gold standard for the diagnosis of Legionella pneumonia. However, its harsh culture conditions, long turnaround time, and suboptimal sensitivity do not meet the clinical need for rapid and accurate diagnosis, especially for critically ill patients. So far, pathogenic detection techniques including serological assays, urinary antigen tests, and mass spectrometry, as well as nucleic acid amplification technique, have been developed, and each has its own advantages and limitations. This review summarizes the clinical characteristics and imaging findings of Legionella pneumonia, then discusses the advances, advantages, and limitations of the various pathogenetic detection techniques used for Legionella pneumonia diagnosis. The aim is to provide rapid and accurate guiding options for early identification and diagnosis of Legionella pneumonia in clinical practice, further easing healthcare burden.

Combination of Whole Genome Sequencing and Metagenomics for Microbiological Diagnostics

Whole genome sequencing (WGS) provides the highest resolution for genome-based species identification and can provide insight into the antimicrobial resistance and virulence potential of a single microbiological isolate during the diagnostic process. In contrast, metagenomic sequencing allows the analysis of DNA segments from multiple microorganisms within a community, either using an amplicon- or shotgun-based approach. However, WGS and shotgun metagenomic data are rarely combined, although such an approach may generate additive or synergistic information, critical for, e.g., patient management, infection control, and pathogen surveillance. To produce a combined workflow with actionable outputs, we need to understand the pre-to-post analytical process of both technologies. This will require specific databases storing interlinked sequencing and metadata, and also involves customized bioinformatic analytical pipelines. This review article will provide an overview of the critical steps and potential clinical application of combining WGS and metagenomics together for microbiological diagnosis.

Diagnostic Value and Clinical Application of mNGS for Post-Liver Transplantation Infection: A Cross-Sectional Study With Case Reports

Liver transplantation is widely acknowledged as the only effective treatment for end-stage liver disease, and infection is reportedly an important cause of postoperative death. Clinical use of metagenomic next-generation sequencing (mNGS) to diagnose postoperative infection and successfully guide drug therapy remains rare. This study included patients with infectious complications after liver transplantation from July 2019 to December 2020 and was divided into three groups: pneumonia, unknown fever, and others (including hepatic failure, kidney failure, cirrhosis after LT, and other postoperative complications that predispose to infection). The mNGS sequencing was used to detect microorganisms, and the results were compared with traditional culture. We found that mNGS yielded improved sensitivity over culture (85.19 vs. 22.22%; p<0.0001) but lower specificity (35.71 vs. 89.28%; p<0.0001). Among the 48 kinds of pathogens detected, the Torque teno virus 22 (15/122) was the most common, followed by Primate erythroparvovirus 1 (13/122). The top four bacteria included Klebsiella pneumoniae (n = 8), Enterococcus faecium (n = 5), Stenotrophomonas maltophilia (n = 4), and Escherichia coli (n = 4). Aspergillus fumigatus was the most common fungus. The bronchoalveolar lavage fluid (BALF) exhibited the highest proportion of positive findings among sample types, with viral, fungal, and bacterial mixed infection being the most common (n = 6, 19.35%). Besides, using mNGS for early diagnosis of infection after liver transplantation may effectively prolong patient survival. This is the first study to explore the application value of mNGS and its comparison with traditional culture in pneumonia and other infections in post-liver transplantation patients. The simultaneous application of these two methods suggested that the Torque teno virus 22, Klebsiella pneumoniae, and the Aspergillus fumigatus are the most common pathogens of viruses, bacteria, and fungi after LT, suggesting that these pathogens may be associated with postoperative pathogen infection and patient prognosis. The mNGS technique showed distinct advantages in detecting mixed, viral, and parasitic infections in this patient population. Further studies are warranted to systematically elucidate the dynamic evolution and molecular characteristics of infection after liver transplantation.