Detection of respiratory pathogens in clinical samples using metagenomic shotgun sequencing

The microbiological diagnostic performance of metagenomic next-generation sequencing in patients with infectious diseases

OBJECTIVE

Metagenomic next-generation sequencing (mNGS) can be used to detect pathogens in clinical infectious diseases through the sequencing analysis of microbial and host nucleic acids in clinical samples. This study aimed to assess the diagnostic performance of mNGS in patients with infections.

METHODS

In this study, 641 patients with infectious diseases were enrolled. These patients simultaneously underwent pathogen detection by both mNGS and microbial culture. Through statistical analysis, we judged the diagnostic performance of mNGS and microbial culture on different pathogens.

RESULTS

Among 641 patients, 276 cases of bacteria and 95 cases of fungi were detected by mNGS, whereas 108 cases of bacteria and 41 cases of fungi were detected by traditional cultures. Among all mixed infections, combined bacterial and viral infections were the highest (51%, 87/169), followed by combined bacterial with fungal infections (16.57%, 28/169) and mixed bacterial, fungal, and viral infections (13.61%, 23/169). Among all sample types, bronchoalveolar lavage fluid (BALF) samples had the highest positive rate (87.8%, 144/164), followed by sputum (85.4%, 76/89) and blood samples (61.2%, 158/258). For the culture method, sputum samples had the highest positive rate (47.2%, 42/89), followed by BALF (37.2%, 61/164). The positive rate of mNGS was 69.89% (448/641), which was significantly higher than that of traditional cultures (22.31% [143/641]) (P < .05).

CONCLUSIONS

Our results show that mNGS is an effective tool for the rapid diagnosis of infectious diseases. Compared with traditional detection methods, mNGS also showed obvious advantages in mixed infections and infections with uncommon pathogens.

Association between Clinical Characteristics and Microbiota in Bronchiectasis Patients Based on Metagenomic Next-Generation Sequencing Technology

This study aimed to investigate the disparities between metagenomic next-generation sequencing (mNGS) and conventional culture results in patients with bronchiectasis. Additionally, we sought to investigate the correlation between the clinical characteristics of patients and their microbiome profiles. The overarching goal was to enhance the effective management and treatment of bronchiectasis patients, providing a theoretical foundation for healthcare professionals. A retrospective survey was conducted on 67 bronchiectasis patients admitted to The First Hospital of Jiaxing from October 2019 to March 2023. Clinical baseline information, inflammatory indicators, and pathogen detection reports, including mNGS, conventional blood culture, bronchoalveolar lavage fluid (BALF) culture, and sputum culture results, were collected. By comparing the results of mNGS and conventional culture, the differences in pathogen detection rate and pathogen types were explored, and the diagnostic performance of mNGS compared to conventional culture was evaluated. Based on the various pathogens detected by mNGS, the association between clinical characteristics of bronchiectasis patients and mNGS microbiota results was analyzed. The number and types of pathogens detected by mNGS were significantly larger than those detected by conventional culture. The diagnostic efficacy of mNGS was significantly superior to conventional culture for all types of pathogens, particularly in viral detection (p < 0.01). Regarding pathogen detection rate, the bacteria with the highest detection rate were Pseudomonas aeruginosa (17/58) and Haemophilus influenzae (11/58); the fungus with the highest detection rate was Aspergillus fumigatus (10/21), and the virus with the highest detection rate was human herpes virus 4 (4/11). Differences were observed between the positive and negative groups for P. aeruginosa in terms of common scoring systems for bronchiectasis and whether the main symptom of bronchiectasis manifested as thick sputum (p < 0.05). Significant distinctions were also noted between the positive and negative groups for A. fumigatus regarding Reiff score, neutrophil percentage, bronchiectasis etiology, and alterations in treatment plans following mNGS results reporting (p < 0.05). Notably, 70% of patients with positive A. fumigatus infection opted to change their treatment plans. The correlation study between clinical characteristics of bronchiectasis patients and mNGS microbiological results revealed that bacteria, such as P. aeruginosa, and fungi, such as A. fumigatus, were associated with specific clinical features of patients. This underscored the significance of mNGS in guiding personalized treatment approaches. mNGS could identify multiple pathogens in different types of bronchiectasis samples and was a rapid and effective diagnostic tool for pathogen identification. Its use was recommended for diagnosing the causes of infections in bronchiectasis patients.

Lophomonas as a respiratory pathogen-jumping the gun

Human infections with the protozoan Lophomonas have been increasingly reported in the medical literature over the past three decades. Initial reports were based on microscopic identification of the purported pathogen in respiratory specimens. Later, a polymerase chain reaction (PCR) was developed to detect Lophomonas blattarum, following which there has been a significant increase in reports. In this minireview, we thoroughly examine the published reports of Lophomonas infection to evaluate its potential role as a human pathogen. We examined the published images and videos of purported Lophomonas, compared its morphology and motility characteristics with host bronchial ciliated epithelial cells and true L. blattarum derived from cockroaches, analyzed the published PCR that is being used for its diagnosis, and reviewed the clinical data of patients reported in the English and Chinese literature. From our analysis, we conclude that the images and videos from human specimens do not represent true Lophomonas and are predominantly misidentified ciliated epithelial cells. Additionally, we note that there is insufficient clinical evidence to attribute the cases to Lophomonas infection, as the clinical manifestations are non-specific, possibly caused by other infections and comorbidities, and there is no associated tissue pathology attributable to Lophomonas. Finally, our analysis reveals that the published PCR is not specific to Lophomonas and can amplify DNA from commensal trichomonads. Based on this thorough review, we emphasize the need for rigorous scientific scrutiny before a microorganism is acknowledged as a novel human pathogen and discuss the potential harms of misdiagnoses for patient care and scientific literature.

Pneumocystis jirovecii with high probability detected in bronchoalveolar lavage fluid of chemotherapy-related interstitial pneumonia in patients with lymphoma using metagenomic next-generation sequencing technology

BACKGROUND

Previous studies achieved low microbial detection rates in lymphoma patients with interstitial pneumonia (IP) after chemotherapy. However, the metagenomic next-generation sequencing (mNGS) is a comprehensive approach that is expected to improve the pathogen identification rate. Thus far, reports on the use of mNGS in lymphoma patients with chemotherapy-related IP remain scarce. In this study, we summarized the microbial detection outcomes of lymphoma patients with chemotherapy-related IP through mNGS testing of bronchoalveolar lavage fluid (BALF).

METHODS

Fifteen lymphoma patients with chemotherapy-related IP were tested for traditional laboratory microbiology, along with the mNGS of BALF. Then, the results of mNGS and traditional laboratory microbiology were compared.

RESULTS

Of the 15 enrolled patients, 11 received rituximab and 8 were administered doxorubicin hydrochloride liposome. The overall microbial yield was 93.3% (14/15) for mNGS versus 13.3% (2/15) for traditional culture methods (P ≤ 0.05). The most frequently detected pathogens were Pneumocystis jirovecii (12/15, 80%), Cytomegalovirus (4/15, 26.7%), and Epstein-Barr virus (3/15, 20%). Mixed infections were detected in 10 cases. Five patients recovered after the treatment with antibiotics alone without glucocorticoids.

CONCLUSION

Our findings obtained through mNGS testing of BALF suggested a high microbial detection rate in lymphoma patients with IP after chemotherapy. Notably, there was an especially high detection rate of Pneumocystis jirovecii. The application of mNGS in patients with chemotherapy-related IP was more sensitive.

Metagenomic next-generation sequencing of bronchoalveolar lavage fluid from children with severe pneumonia in pediatric intensive care unit

Background

Severe pneumonia due to lower respiratory tract infections (LRTIs) is a significant cause of morbidity and mortality in children. Noninfectious respiratory syndromes resembling LRTIs can complicate the diagnosis and may also make targeted therapy difficult because of the difficulty of identifying LRTI pathogens. In the present study, a highly sensitive metagenomic next-generation sequencing (mNGS) approach was used to characterize the microbiome of bronchoalveolar lavage fluid (BALF) in children with severe lower pneumonia and identify pathogenic microorganisms that may cause severe pneumonia. The purpose of this study was to use mNGS to explore the potential microbiomes of children with severe pneumonia in a PICU.

Methods

We enrolled patients meeting diagnostic criteria for severe pneumonia admitted at PICU of the Children’s Hospital of Fudan University, China, from February 2018 to February 2020. In total, 126 BALF samples were collected, and mNGS was performed at the DNA and/or RNA level. The pathogenic microorganisms in BALF were identified and correlated with serological inflammatory indicators, lymphocyte subtypes, and clinical symptoms.

Results

mNGS of BALF identified potentially pathogenic bacteria in children with severe pneumonia in the PICU. An increased BALF bacterial diversity index was positively correlated with serum inflammatory indicators and lymphocyte subtypes. Children with severe pneumonia in the PICU had the potential for coinfection with viruses including Epstein–Barr virus, Cytomegalovirus, and Human betaherpesvirus 6B, the abundance of which was positively correlated with immunodeficiency and pneumonia severity, suggesting that the virus may be reactivated in children in the PICU. There was also the potential for coinfection with fungal pathogens including Pneumocystis jirovecii and Aspergillus fumigatus in children with severe pneumonia in the PICU, and an increase in potentially pathogenic eukaryotic diversity in BALF was positively associated with the occurrence of death and sepsis.

Conclusions

mNGS can be used for clinical microbiological testing of BALF samples from children in the PICU. Bacterial combined with viral or fungal infections may be present in the BALF of patients with severe pneumonia in the PICU. Viral or fungal infections are associated with greater disease severity and death.

Validation of a Metagenomic Next-Generation Sequencing Assay for Lower Respiratory Pathogen Detection

Lower respiratory infection (LRI) is the most fatal communicable disease, with only a few pathogens identified. Metagenomic next-generation sequencing (mNGS), as an unbiased, hypothesis-free, and culture-independent method, theoretically enables the detection of all pathogens in a single test. In this study, we developed and validated a DNA-based mNGS method for the diagnosis of LRIs from bronchoalveolar lavage fluid (BALF). We prepared simulated in silico data sets and published raw data sets from patients to evaluate the performance of our in-house bioinformatics pipeline and compared it with the popular metagenomics pipeline Kraken2-Bracken. In addition, a series of biological microbial communities were used to comprehensively validate the performance of our mNGS assay. Sixty-nine clinical BALF samples were used for clinical validation to determine the accuracy. The in-house bioinformatics pipeline validation showed a recall of 88.03%, precision of 99.14%, and F1 score of 92.26% via single-genome simulated data. Mock in silico microbial community and clinical metagenomic data showed that the in-house pipeline has a stricter cutoff value than Kraken2-Bracken, which could prevent false-positive detection by the bioinformatics pipeline. The validation for the whole mNGS pipeline revealed that overwhelming human DNA, long-term storage at 4°C, and repeated freezing-thawing reduced the analytical sensitivity of the assay. The mNGS assay showed a sensitivity of 95.18% and specificity of 91.30% for pathogen detection from BALF samples. This study comprehensively demonstrated the analytical performance of this laboratory-developed mNGS assay for pathogen detection from BALF, which contributed to the standardization of this technology. IMPORTANCE To our knowledge, this study is the first to comprehensively validate the mNGS assay for the diagnosis of LRIs from BALF. This study exhibited a ready-made example for clinical laboratories to prepare reference materials and develop comprehensive validation schemes for their in-house mNGS assays, which would accelerate the standardization of mNGS testing.

Functional lower airways genomic profiling of the microbiome to capture active microbial metabolism

BACKGROUND

Microbiome studies of the lower airways based on bacterial 16S rRNA gene sequencing assess microbial community structure but can only infer functional characteristics. Microbial products, such as short-chain fatty acids (SCFAs), in the lower airways have significant impact on the host's immune tone. Thus, functional approaches to the analyses of the microbiome are necessary.

METHODS

Here we used upper and lower airway samples from a research bronchoscopy smoker cohort. In addition, we validated our results in an experimental mouse model. We extended our microbiota characterisation beyond 16S rRNA gene sequencing with the use of whole-genome shotgun (WGS) and RNA metatranscriptome sequencing. SCFAs were also measured in lower airway samples and correlated with each of the sequencing datasets. In the mouse model, 16S rRNA gene and RNA metatranscriptome sequencing were performed.

RESULTS

Functional evaluations of the lower airway microbiota using inferred metagenome, WGS and metatranscriptome data were dissimilar. Comparison with measured levels of SCFAs shows that the inferred metagenome from the 16S rRNA gene sequencing data was poorly correlated, while better correlations were noted when SCFA levels were compared with WGS and metatranscriptome data. Modelling lower airway aspiration with oral commensals in a mouse model showed that the metatranscriptome most efficiently captures transient active microbial metabolism, which was overestimated by 16S rRNA gene sequencing.

CONCLUSIONS

Functional characterisation of the lower airway microbiota through metatranscriptome data identifies metabolically active organisms capable of producing metabolites with immunomodulatory capacity, such as SCFAs.

Precision Pandemic Preparedness: Improving Diagnostics with Metagenomics

The threat posed by novel pandemics in the future remains active. Equipping our routine laboratory with clinical metagenomics to detect unknown threats early on offers a considerable advantage and may be feasible and scalable with the ability to identify complicated infectious diseases in routine care. Though several technical and regulatory challenges still exist, clinical metagenomics may improve individual patient outcomes and provide earlier warning signs to improve pandemic preparedness.

A proof-of-concept study of an automated solution for clinical metagenomic next-generation sequencing

AIMS

Metagenomic next-generation sequencing (mNGS) has been utilized for diagnosing infectious diseases. It is a culture-free and hypothesis-free nucleic acid test for diagnosing all pathogens with known genomic sequences, including bacteria, fungi, viruses and parasites. While this technique greatly expands the clinical capacity of pathogen detection, it is a second-line choice due to lengthy procedures and microbial contaminations introduced from wet-lab processes. As a result, we aimed to reduce the hands-on time and exogenous contaminations in mNGS.

METHODS AND RESULTS

We developed a device (NGSmaster) that automates the wet-lab workflow, including nucleic acid extraction, PCR-free library preparation and purification. It shortens the sample-to-results time to 16 and 18·5 h for DNA and RNA sequencing respectively. We used it to test cultured bacteria for validation of the workflow and bioinformatic pipeline. We also compared PCR-free with PCR-based library prep and discovered no differences in microbial reads. Moreover we analysed results by automation and manual testing and found that automation can significantly reduce microbial contaminations. Finally, we tested artificial and clinical samples and showed mNGS results were concordant with traditional culture.

CONCLUSION

NGSmaster can fulfil the microbiological diagnostic needs in a variety of sample types.

SIGNIFICANCE AND IMPACT OF THE STUDY

This study opens up an opportunity of performing in-house mNGS to reduce turnaround time and workload, instead of transferring potentially contagious specimen to a third-party laboratory.

Nosocomial pneumonia diagnosis revisited

PURPOSE OF REVIEW

Nosocomial pneumonia represents a significant burden even for the most resilient healthcare systems. Timely and reliable diagnosis is critical but remains a deficient field. This review critically revises the latest literature on the diagnosis of nosocomial pneumonia, including advances in imaging techniques, as well as the utility of rapid microbiological tests in establishing the etiological diagnosis.

RECENT FINDINGS

Studies on low radiation computed tomography (CT) and lung ultrasound (LUS) have shown promising results for early nosocomial pneumonia diagnosis; however, further data on their sensitivity and specificity are needed, especially for picking up subtle and nonspecific radiographic findings. Moreover, data supporting their superiority in pneumonia diagnosis is still limited. As for microbiological diagnosis, several culture-independent molecular diagnostic techniques have been developed, identifying both causative microorganisms as well as determinants of antimicrobial resistance, but more studies are needed to delineate their role in nosocomial pneumonia diagnosis.

SUMMARY

The development of nonculture dependent tests has launched a new era in microbiological nosocomial pneumonia diagnosis. These modalities along with the use of LUS and/or low radiation CT might improve the sensitivity and specificity of nosocomial pneumonia diagnosis, enhance early detection and guide the antimicrobial therapy but more studies are needed to further evaluate them and determine their role for the routine clinical practice.

Blood and Bronchoalveolar Lavage Fluid Metagenomic Next-Generation Sequencing in Pneumonia

Background

Metagenomic next-generation sequencing (mNGS) has made a revolution in the mode of pathogen identification. We decided to explore the diagnostic value of blood and bronchoalveolar lavage fluid (BALF) as mNGS samples in pneumonia.

Methods

We retrospectively reviewed 467 mNGS results and assessed the diagnostic performance of paired blood and BALF mNGS in 39 patients with pneumonia.

Results

For bacteria and fungi, 16 patients had culture-confirmed pathogen diagnosis, while 13 patients were culture-negative. BALF mNGS was more sensitive than blood mNGS (81.3% vs. 25.0%, p=0.003), and the specificity in BALF and blood mNGS was not statistically significant different (76.9% vs. 84.6%, p=0.317). For 10 patients without culture test, treatments were changed in 2 patients. For viruses, Epstein-Barr virus was positive in blood mNGS in 9 patients. Human adenovirus was detected in both BALF and blood mNGS in 3 patients.

Conclusion

Our study suggests that BALF mNGS is more sensitive than blood mNGS in detecting bacteria and fungi, but blood also has advantages to identify the pathogens of pneumonia, especially for some viruses.

Metagenomic next-generation sequencing for the clinical diagnosis and prognosis of acute respiratory distress syndrome caused by severe pneumonia: a retrospective study

Background

Metagenome next-generation sequencing (mNGS) is a valuable diagnostic tool that can be used for the identification of early pathogens of acute respiratory distress syndrome (ARDS) in severe pneumonia. Little is known about the use of this technology in clinical application and the evaluation of the prognostic value of ARDS.

Methods

We performed a retrospective cohort study of patients with ARDS caused by severe pneumonia. Samples were collected from patients in the intensive care unit (ICU) of Jiangmen Central Hospital from January 2018 to August 2019. The no-next generation sequencing (NGS) group was composed of patients given conventional microbiological tests to examine sputum, blood, or bronchoalveolar lavage fluid. The NGS group was composed of patients tested using mNGS and conventional microbiological tests. We evaluated the etiological diagnostic effect and clinical prognostic value of mNGS in patients with ARDS caused by severe pneumonia.

Results

The overall positive rate (91.1%) detected by the mNGS method was significantly higher than that of the culture method (62.2%, P = 0.001), and antibody plus polymerase chain reaction (28.9%, P < 0.001). Following adjustment of the treatment plan based on microbial testing results, the Acute Physiology and Chronic Health Evaluation-II (APACHE II) score of the NGS group was lower than that of the no-NGS group 7 days after treatment (P < 0.05). The 28-day mortality rate of the NGS group was significantly lower than that of the no-NGS group (P < 0.05). Longer ICU stay, higher APACHE II score and sequential organ failure assessment score were risk factors for the death of ARDS, and adjusting the medication regimen based on mNGS results was a protective factor. The detection of mNGS can significantly shorten the ICU stay of immunosuppressed patients (P < 0.01), shorten the ventilation time (P < 0.01), and reduce the ICU hospitalization cost (P < 0.05).

Conclusions

Metagenome next-generation sequencing is a valuable tool to determine the etiological value of ARDS caused by severe pneumonia to improve diagnostic accuracy and prognosis for this disease. For immunosuppressed patients, mNGS technology can be used in the early stage to provide more diagnostic evidence and guide medications.

Empirical Anti-MRSA vs Standard Antibiotic Therapy and Risk of 30-Day Mortality in Patients Hospitalized for Pneumonia

IMPORTANCE

Use of empirical broad-spectrum antibiotics for pneumonia has increased owing to concern for resistant organisms, including methicillin-resistant Staphylococcus aureus (MRSA). The association of empirical anti-MRSA therapy with outcomes among patients with pneumonia is unknown, even for high-risk patients.

OBJECTIVE

To compare 30-day mortality among patients hospitalized for pneumonia receiving empirical anti-MRSA therapy vs standard empirical antibiotic regimens.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective multicenter cohort study was conducted of all hospitalizations in which patients received either anti-MRSA or standard therapy for community-onset pneumonia in the Veterans Health Administration health care system from January 1, 2008, to December 31, 2013. Subgroups of patients analyzed were those with initial intensive care unit admission, MRSA risk factors, positive results of a MRSA surveillance test, and positive results of a MRSA admission culture. Primary analysis was an inverse probability of treatment-weighted propensity score analysis using generalized estimating equation regression; secondary analyses included an instrumental variable analysis. Statistical analysis was conducted from June 14 to November 20, 2019.

EXPOSURES

Empirical anti-MRSA therapy plus standard pneumonia therapy vs standard therapy alone within the first day of hospitalization.

MAIN OUTCOMES AND MEASURES

Risk of 30-day all-cause mortality after adjustment for patient comorbidities, vital signs, and laboratory results. Secondary outcomes included the development of kidney injury and secondary infections with Clostridioides difficile, vancomycin-resistant Enterococcus species, or gram-negative bacilli.

RESULTS

Among 88 605 hospitalized patients (86 851 men; median age, 70 years [interquartile range, 62-81 years]), empirical anti-MRSA therapy was administered to 33 632 (38%); 8929 patients (10%) died within 30 days. Compared with standard therapy alone, in weighted propensity score analysis, empirical anti-MRSA therapy plus standard therapy was significantly associated with an increased adjusted risk of death (adjusted risk ratio [aRR], 1.4 [95% CI, 1.3-1.5]), kidney injury (aRR, 1.4 [95% CI, 1.3-1.5]), and secondary C difficile infections (aRR, 1.6 [95% CI, 1.3-1.9]), vancomycin-resistant Enterococcus spp infections (aRR, 1.6 [95% CI, 1.0-2.3]), and secondary gram-negative rod infections (aRR, 1.5 [95% CI, 1.2-1.8]). Similar associations between anti-MRSA therapy use and 30-day mortality were found by instrumental variable analysis (aRR, 1.6 [95% CI, 1.4-1.9]) and among patients admitted to the intensive care unit (aRR, 1.3 [95% CI, 1.2-1.5]), those with a high risk for MRSA (aRR, 1.2 [95% CI, 1.1-1.4]), and those with MRSA detected on surveillance testing (aRR, 1.6 [95% CI, 1.3-1.9]). No significant favorable association was found between empirical anti-MRSA therapy and death among patients with MRSA detected on culture (aRR, 1.1 [95% CI, 0.8-1.4]).

CONCLUSIONS AND RELEVANCE

This study suggests that empirical anti-MRSA therapy was not associated with reduced mortality for any group of patients hospitalized for pneumonia. These results contribute to a growing body of evidence that questions the value of empirical use of anti-MRSA therapy using existing risk approaches.

Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity

Infections are a serious health concern worldwide, particularly in vulnerable populations such as the immunocompromised, elderly, and young. Advances in metagenomic sequencing availability, speed, and decreased cost offer the opportunity to supplement or even replace culture-based identification of pathogens with DNA sequence-based diagnostics. Adopting metagenomic analysis for clinical use requires that all aspects of the workflow are optimized and tested, including data analysis and computational time and resources. We tested the accuracy, sensitivity, and resource requirements of three top metagenomic taxonomic classifiers that use fast k-mer based algorithms: Centrifuge, CLARK, and KrakenUniq. Binary mixtures of bacteria showed all three reliably identified organisms down to 1% relative abundance, while only the relative abundance estimates of Centrifuge and CLARK were accurate. All three classifiers identified the organisms present in their default databases from a mock bacterial community of 20 organisms, but only Centrifuge had no false positives. In addition, Centrifuge required far less computational resources and time for analysis. Centrifuge analysis of metagenomes obtained from samples of VAP, infected DFUs, and FN showed Centrifuge identified pathogenic bacteria and one virus that were corroborated by culture or a clinical PCR assay. Importantly, in both diabetic foot ulcer patients, metagenomic sequencing identified pathogens 4–6 weeks before culture. Finally, we show that Centrifuge results were minimally affected by elimination of time-consuming read quality control and host screening steps.

Currently, the gold standard for identifying pathogens that are causing infection is to attempt growth in culture followed by identification based on physical characteristics such as shape and metabolic profile. However, many organisms do not grow in culture or are overgrown by faster growing organisms that out-compete them. Another method to identify pathogens in infections is to sequence the DNA in the samples and use that DNA sequence to identify the pathogens present—a process called metagenomic sequencing. Analyzing clinical metagenomic data can be difficult given the amount of data generated, high levels of human DNA contamination and a lack of well-defined bioinformatics methods. In this study, three leading software tools were compared for identification and quantitation of microbes in metagenomic data. One tool, called Centrifuge, reliably identified microbes present at just 1% relative abundance while requiring less computer time and resources than the others to which it was compared. Moreover, we found that Centrifuge results changed minimally when time-consuming quality control and host-screening steps were eliminated. We also examined Centrifuge’s performance in real-word clinical data sets showing that Centrifuge identified the same pathogens as culture.