Comparison of protists at Xianghai wetland (China) in summer and winter using metagenomic sequencing

To observe the application of alveolar lavage fluid second-generation sequencing in diagnosing and guiding the treatment of patients with severe pneumonia with unidentified pathogenic bacteria and to provide novel ideas and methods for the effective clinical treatment of this disease. The clinical data of 80 patients with severe pneumonia included in our intensive care unit from June 2020 to June 2022 were analyzed and all patients had undergone metagenomic next-generation sequencing and traditional cultures (alveolar lavage fluid culture, sputum culture) to analyze the advantages of metagenomic next-generation sequencing in detecting pathogens in patients with severe pneumonia. The positive rate of metagenomic next-generation sequencing pathogen detection was higher than that of conventional culture. In patients who were negative for conventional culture and positive for metagenomic next-generation sequencing, metagenomic nextgeneration sequencing was able to further identify multiple pathogenic infections. In terms of pathogen distribution, metagenomic next-generation sequencing detected 71 bacterial, 39 fungal and 3 viral strains. In mixed infections, metagenomic next-generation sequencing yielded a higher rate of positive diagnosis. In addition, metagenomic next-generation sequencing had a higher pathogen detection rate in patients with combined underlying diseases and metagenomic next-generation sequencing could identify specific pathogenic infections especially in patients with combined immunocompromised conditions. Metagenomic next-generation sequencing could improve the detection rate of pathogenic microorganisms in patients with severe pneumonia and could be used as a complementary test for patients negative for conventional cultures. Metagenomic next-generation sequencing has advantages in the diagnosis of mixed infections and can identify multiple pathogenic infections simultaneously. Clinically, early application of metagenomic next-generation sequencing in patients with severe pneumonia is recommended for increased clinical benefit.

This study assessed the application of metagenomic next-generation sequencing in pathogen detection of periprosthetic joint infections. A total of 95 cases who previously had undergone hip and knee replacement undergoing revision from January 2018 to January 2021 were included in this study. Specimens of synovial fluid and deep-tissue were collected for culture and metagenomic next-generation sequencing, and patients were retrospectively categorized as infected or aseptic using the Musculoskeletal Infection Society criteria after revision surgery. The sensitivity, specificity, positive and negative predictive values were compared. A total of 36 cases had positive culture results and 59 cases had positive metagenomic next-generation sequencing results. Culture was positive in 34 infected cases (58.6%) and 2 aseptic cases (5.4%). Metagenomic next-generation sequencing was positive in 55 infected cases (94.8%) and 4 aseptic cases (10.8%). Five cases diagnosed with infection had other potential pathogens detected by metagenomic next-generation sequencing. Among the 24 culture-negative periprosthetic joint infections, metagenomic next-generation sequencing was able to identify potential pathogens in 21 cases (87.5%). From sampling to reporting, the average time needed for culture was 5.2 (95% CI 3.1–7.3) days, while that for metagenomic next-generation sequencing was 1.3 (95% CI 0.9–1.7) days. Metagenomic next-generation sequencing is more advantageous in pathogen detection of periprosthetic joint infection after total joint replacement, especially in patients with multiple infections or negative culture results.

Metagenomic next-generation sequencing offers an unbiased approach to identifying viral pathogens in cerebrospinal fluid of patients with meningoencephalitis of unknown etiology. In an 11-month case series, we investigated the use of cerebrospinal fluid metagenomic next-generation sequencing to diagnose viral infections among pediatric hospitalized patients presenting with encephalitis or meningoencephalitis of unknown etiology. Cerebrospinal fluid from patients with known enterovirus meningitis were included as positive controls. Cerebrospinal fluid from patients with primary intracranial hypertension were included to serve as controls without known infections. Cerebrospinal fluid metagenomic next-generation sequencing was performed for 37 patients. Among 27 patients with encephalitis or meningoencephalitis, 4 were later diagnosed with viral encephalitis, 6 had non-central nervous system infections with central nervous system manifestations, 6 had no positive diagnostic tests, and 11 were found to have a noninfectious diagnosis. Metagenomic next-generation sequencing identified West Nile virus (WNV) in the cerebrospinal fluid of 1 immunocompromised patient. Among the 4 patients with known enterovirus meningitis, metagenomic next-generation sequencing correctly identified enteroviruses and characterized the viral genotype. No viral sequences were detected in the cerebrospinal fluid of patients with primary intracranial hypertension. Metagenomic next-generation sequencing also identified sequences of nonpathogenic torque Teno virus in cerebrospinal fluid specimens from 13 patients. Our results showed viral detection by cerebrospinal fluid metagenomic next-generation sequencing only in 1 immunocompromised patient and did not offer a diagnostic advantage over conventional testing. Viral phylogenetic characterization by metagenomic next-generation sequencing could be used in epidemiologic investigations of some viral pathogens, such as enteroviruses. The finding of torque Teno viruses in cerebrospinal fluid by metagenomic next-generation sequencing is of unknown significance but may merit further exploration for a possible association with noninfectious central nervous system disorders.

Metagenomic next-generation sequencing (mNGS) offers an agnostic approach for emerging pathogen detection directly from clinical specimens. In contrast to targeted methods, mNGS also provides valuable information on the composition of the microbiome and might uncover coinfections that may associate with disease progression and impact prognosis. To evaluate the use of mNGS for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and/or other infecting pathogens, we applied direct Oxford Nanopore long-read third-generation metatranscriptomic and metagenomic sequencing. Nasopharyngeal (NP) swab specimens from 50 patients under investigation for CoV disease 2019 (COVID-19) were sequenced, and the data were analyzed by the CosmosID bioinformatics platform. Further, we characterized coinfections and the microbiome associated with a four-point severity index. SARS-CoV-2 was identified in 77.5% (31/40) of samples positive by RT-PCR, correlating with lower cycle threshold (Ct) values and fewer days from symptom onset. At the time of sampling, possible bacterial or viral coinfections were detected in 12.5% of SARS-CoV-2-positive specimens. A decrease in microbial diversity was observed among COVID-19-confirmed patients (Shannon diversity index, P = 0.0082; Chao richness estimate, P = 0.0097; Simpson diversity index, P = 0.018), and differences in microbial communities were linked to disease severity (P = 0.022). Furthermore, statistically significant shifts in the microbiome were identified among SARS-CoV-2-positive and -negative patients, in the latter of whom a higher abundance of Propionibacteriaceae (P = 0.028) and a reduction in the abundance of Corynebacterium accolens (P = 0.025) were observed. Our study corroborates the growing evidence that increased SARS-CoV-2 RNA detection from NP swabs is associated with the early stages rather than the severity of COVID-19. Further, we demonstrate that SARS-CoV-2 causes a significant change in the respiratory microbiome. This work illustrates the utility of mNGS for the detection of SARS-CoV-2, for diagnosing coinfections without viral target enrichment or amplification, and for the analysis of the respiratory microbiome.IMPORTANCE SARS-CoV-2 has presented a rapidly accelerating global public health crisis. The ability to detect and analyze viral RNA from minimally invasive patient specimens is critical to the public health response. Metagenomic next-generation sequencing (mNGS) offers an opportunity to detect SARS-CoV-2 from nasopharyngeal (NP) swabs. This approach also provides information on the composition of the respiratory microbiome and its relationship to coinfections or the presence of other organisms that may impact SARS-CoV-2 disease progression and prognosis. Here, using direct Oxford Nanopore long-read third-generation metatranscriptomic and metagenomic sequencing of NP swab specimens from 50 patients under investigation for COVID-19, we detected SARS-CoV-2 sequences by applying the CosmosID bioinformatics platform. Further, we characterized coinfections and detected a decrease in the diversity of the microbiomes in these patients. Statistically significant shifts in the microbiome were identified among COVID-19-positive and -negative patients, in the latter of whom a higher abundance of Propionibacteriaceae and a reduction in the abundance of Corynebacterium accolens were observed. Our study also corroborates the growing evidence that increased SARS-CoV-2 RNA detection from NP swabs is associated with the early stages of disease rather than with severity of disease. This work illustrates the utility of mNGS for the detection and analysis of SARS-CoV-2 from NP swabs without viral target enrichment or amplification and for the analysis of the respiratory microbiome.

Clinical management and surveillance of the Enterobacter cloacae complex (ECC) face significant challenges due to inaccurate species identification and prolonged turnaround time for culture-based antimicrobial susceptibility testing (AST). To date, no studies have leveraged whole-genome sequencing (WGS) and metagenomic next-generation sequencing (mNGS) to develop a rapid AST prediction model for ECC. Here, a total of 1,054 ECC strain genomes with AST data were collected from a public database and a local hospital. The results of species identification between the average nucleotide identity (ANI)-based method on culture were compared, and machine learning was employed to identify resistance features for imipenem (IPM), meropenem (MEM), ciprofloxacin (CIP), levofloxacin (LEV), and trimethoprim-sulfamethoxazole (SXT). By referring to ANI-based species classification, culture-based methods showed a 74% misidentification rate for 1,054 ECC isolates. The antimicrobial resistance prediction model demonstrated good performance, with the area under the curve values of 91.25% (IPM), 89.69%, 88.17% (CIP), 91.01% (LEV), and 90.93% (SXT) respectively. Moreover, a combined WGS and mNGS approach was utilized and validated using 104 pediatric sputum specimens. Compared to culture-based AST, the overall accuracy of models exceeded 95%, especially achieving 100% for IPM and 98.80% for MEM, and the detection turnaround time was shortened by 69.64 h. Furthermore, it would enable early escalated therapy in 20.83% of cases, significantly improving patient management. This established WGS and mNGS-based AST prediction model addresses the limitations of traditional methods, offering a rapid, accurate, and clinically applicable tool for managing multidrug-resistant ECC infections.IMPORTANCEThe Enterobacter cloacae complex (ECC) poses a major challenge to clinical management due to difficulties in accurate species identification and the slow turnaround times of conventional culture-based antimicrobial susceptibility testing (AST). Current methods are often inefficient and prone to misidentification, leading to delayed or inappropriate treatment. This study introduces a novel approach that combines whole-genome sequencing (WGS) and metagenomic next-generation sequencing (mNGS) to develop a rapid and accurate AST prediction model for ECC. By leveraging machine learning to analyze WGS data from over 1,000 ECC isolates and validating the model with pediatric clinical specimens. The model achieved over 88% area under the curve accuracy for all antibiotics, demonstrated >95% accuracy in clinical validation, and reduced detection turnaround time by 69.64 h compared to traditional methods. The model has the potential to revolutionize ECC management by facilitating timely, targeted therapies and enhancing patient outcomes, especially in the context of multidrug-resistant infections.

Vibrio cholerae is the causative agent of the human intestinal infectious disease cholera, which includes a variety of serogroups. However, there have been very few cases of hepatic space-occupying lesions associated with this infection. Currently, there are various methods for detecting this pathogen, including metagenomic sequencing, which enables quicker and more accurate identification. In this study, metagenomic sequencing is employed to accurately identify non-O1/O139 Vibrio cholerae infections by analyzing the genetic material present in clinical samples. A 75-year-old man presented with diarrhea and fever after consuming crabs. The initial treatment improved the diarrhea, but a liver abscess developed later. Magnetic resonance imaging (MRI) of the liver revealed a hepatic space-occupying lesion. Upon further investigation, a Gram-negative, rod-shaped bacterium was cultured from the patient's liver puncture fluid, and Vibrio cholerae was detected in the same fluid using metagenomic next-generation sequencing (mNGS). The pathogen was confirmed to be non-O1/non-O139 Vibrio cholerae (NOVC) using polymerase chain reaction (PCR). Following treatment with piperacillin/tazobactam sodium and moxifloxacin, the patient's body temperature returned to normal, the liver abscess improved significantly, and he was subsequently discharged from the hospital. This case study describes an elderly male patient with a hepatic space-occupying lesion. Multiple cultures of specimens failed to identify the underlying cause; however, advanced techniques such as mNGS and PCR confirmed an NOVC infection. This indicates that mNGS can serve as a valuable tool in diagnosing cases of unexplained liver infections. The use of mNGS is significant for detecting and clinically diagnosing infectious pathogens in patients with unexplained space-occupying lesions.

Treponema phagedenis, a human commensal spirochete, has been reported world-wide as a key factor in the pathogenesis of bovine digital dermatitis. Here we report a case of T. phagedenis sequence detection in the cerebrospinal fluid (CSF) of a patient. The patient was diagnosed with neurosyphilis, and T. phagedenis was detected as the only microorganism in his CSF by metagenomic sequencing. The patient went through a round of penicillin therapy previously (2.4 million units of Benzathine Penicillin intramuscularly once a week for three weeks) that did not resolve the symptoms; after the diagnosis of neurosyphilis he was treated with Penicillin G Sodium 4.0 million units q4h intravenous for 14 days then his symptoms resolved. To the best of our knowledge, T. phagedenis has never been reported to be detected in a human’s CSF before. This was also the first time it was detected by metagenomic next-generation sequencing. We propose that more etiological tests should be performed including culture and sequencing for more patients with syphilis, which will contribute to a deeper understanding of the pathogenicity of the spirochete.

BackgroundAlthough pulmonary mucormycosis is rare, it is highly invasive and carries a significant mortality rate. Due to its nonspecific clinical manifestations, it is often misdiagnosed as other invasive fungal diseases. Bronchoalveolar lavage fluid metagenomic next-generation sequencing is a rapid, precise, and comprehensive method for pathogen detection, showing great potential in the early diagnosis of pulmonary mucormycosis in a single-center retrospective series. It provides clinicians with faster and more accurate etiological information, thereby improving patient outcomes and reducing mortality rates.MethodsThis study conducted a retrospective analysis of the clinical data from 14 patients diagnosed with pulmonary mucormycosis between 1/6/2021 and 30/6/2024. Peripheral blood samples were collected to perform a complete blood count, measure C-reactive protein levels, and conduct 1,3-β-D-glucan and Galactomannan tests. Lung tissue samples were sent to the pathology laboratory for histological examination. Bronchoalveolar lavage fluid was subjected to fungal culture and metagenomic next-generation sequencing. Additionally, a three-month follow-up on the patients’ survival status was carried out via telephone.ResultsMales accounted for 57.14% of the cases. Diabetes mellitus was present in 12 patients (85.71%, 12/14), and fever was observed in 12 patients (85.71%, 12/14). The 14 patients were categorized as proven cases (4 cases), probable cases (4 cases), and possible cases (6 cases). Two patients (14.29%, 2/14) were diagnosed with disseminated mucormycosis. Chest Computed Tomography scans revealed cavities in half of the patients (50.00%, 7/14). Fungal hyphae were identified in all the histopathological examinations (100%, 4/4). Metagenomic next-generation sequencing detected Mucorales pathogens in all the (100%, 14/14) cases, which is higher positivity than the positive rates of the 1,3-β-D-glucan test (35.71%, 5/14), Galactomannan test (42.86%, 6/14) and fungal culture (7.14%, 1/14). The turnaround time for metagenomic next-generation sequencing reports is 1–3 days, which is much shorter than the time required to obtain results from fungal culture (2–5 days). Additionally, metagenomic next-generation sequencing identified bacterial and viral co-infections, with 11 patients diagnosed as having mixed infections. All patients were treated with antifungal agents targeting Aspergillus species, such as voriconazole, posaconazole, isavuconazole, or amphotericin B, resulting in 9 patients improving, 2 patients being transferred to higher-level hospitals, and 3 patients discontinuing treatment. The 90-day follow-up revealed a mortality rate of 28.57%.ConclusionMetagenomic next-generation sequencing can serve as an important complement to traditional diagnostic methods, enabling rapid and accurate differentiation of Mucorales from other fungi. This allows patients to receive timely and targeted antifungal therapy, playing a critical role in early intervention and improving prognosis.

Objective To evaluate the value of nanopore targeted sequencing in diagnosing pneumonia pathogens. Methods This large-scale multicentre prospective study performed in 8 hospitals across China from April to October 2022. Hospitalised patients with a diagnosis of pneumonia at admission were included. Complete clinical data were collected, and bronchoalveolar lavage fluid were obtained from each patient. These samples underwent simultaneous testing using conventional microbial testing, metagenomic next-generation sequencing, and nanopore targeted sequencing. Results A total of 218 patients were included. Among the 168 cases of pulmonary infection, 246 strains of pathogens were confirmed. Nanopore targeted sequencing outperformed conventional microbial testing, identifying more pathogens with a sensitivity increase of 47.9% (77.2% vs. 29.3%). Metagenomic next-generation sequencing had a sensitivity of 82.9%. Total of 70.1% patients had consistent results in both metagenomic next-generation sequencing and nanopore targeted sequencing. Nanopore targeted sequencing exhibited significantly higher sensitivity in detecting Pneumocystis jiroveci, cytomegalovirus, Mycobacterium tuberculosis, Nontuberculous mycobacteria, Streptococcus pneumoniae, and Mycoplasma pneumoniae compared to conventional microbial testing. However, metagenomic next-generation sequencing demonstrated higher sensitivity than nanopore targeted sequencing for Aspergillus (88.5% vs. 53.8%). Regarding the detection of co-infections, nanopore targeted sequencing displayed significantly higher sensitivity than conventional microbial testing (76.7% vs. 28.7%) and was on par with metagenomic next-generation sequencing (76.7% vs. 82.9%). Conclusion Nanopore targeted sequencing performs equally well as metagenomic next-generation sequencing in bronchoalveolar lavage fluid for pathogen diagnosis in pneumonia, both methods showing higher sensitivity than conventional microbial testing. Nanopore targeted sequencing can be considered a reliable method for diagnosing pathogens in pneumonia.

IntroductionRapid, sensitive, and specific laboratory assays are critical for the diagnosis and management of central nervous system (CNS) infections. The purpose of this study is to explore the intellectual landscape of research investigating methods for the detection of pathogens in patients with CNS infections and to identify the development trends and research frontier in this field.MethodsA bibliometric study is conducted by analyzing literature retrieved from the Web of Science (WoS) Core Collection Database for the years 2000 to 2021. CiteSpace software is used for bibliometric analysis and network visualization, including co-citation analysis of references, co-occurrence analysis of keywords, and cooperation network analysis of authors, institutions, and countries/regions.ResultsA total of 2,282 publications are eventually screened, with an upward trend in the number of publications per year. The majority of papers are attributed to the disciplines of MICROBIOLOGY, INFECTIOUS DISEASES, IMMUNOLOGY, NEUROSCIENCES & NEUROLOGY, and VIROLOGY. The co-citation analysis of references shows that recent research has focused on the largest cluster “metagenomic next-generation sequencing”; the results of the analysis of the highest-cited publications and the citation burst of publications reveal that there is a strong interest stimulated in metagenomic next-generation sequencing. The co-occurrence analysis of keywords indicates that “infection”, “pathogen”, “diagnosis”, “gene”, “virus”, “polymerase chain reaction”, “cerebrospinal fluid”, “epidemiology”, and “metagenomic next-generation sequencing” are the main research priorities in the field of pathogen detection for CNS infections, and the keyword with the highest strength of burst is “metagenomic next-generation sequencing”. Collaborative network analysis reveals that the USA, the Centers for Disease Control and Prevention of USA, and XIN WANG and JENNIFER DIEN BARD are the most influential country, institution, and researchers, respectively.ConclusionsExploring more advanced laboratory assays to improve the diagnostic accuracy of pathogens is essential for CNS infection research. Metagenomic next-generation sequencing is emerging as a novel useful unbiased approach for diagnosing infectious diseases of the CNS.

Metagenomic next generation sequencing for studying antibiotic resistance genes in the environment.

Patients with severe thermal burns are highly susceptible to invasive fungal infections due to compromised skin integrity, prolonged hospitalization, and immunosuppression. Traditional diagnostic methods, such as cultures and tissue biopsies with histopathology, have limitations. Metagenomic next-generation sequencing (mNGS) of microbial cell-free DNA in plasma is a rapid, noninvasive diagnostic tool for detecting fungal elements in the bloodstream. The aim of this report is to present the utility of this method to aid in ruling out an invasive fungal infection in a patient with burns. This case involves a middle-aged male with extensive thermal burns who developed sepsis, with concerns of invasive fungal infection after fungal elements were detected in wound cultures of skin grafts. However, β-d-glucan and galactomannan assays were negative, and mNGS did not detect fungal DNA in plasma. Histopathological examination of tissue biopsies later confirmed the absence of angioinvasion, and blood cultures showed no evidence of fungemia. As a result, antifungal therapy was safely discontinued without clinical deterioration. While mNGS has shown potential for negative predictive value in immunocompromised patients, its role in patients with burns warrants further investigation. Integrating mNGS with conventional diagnostic methods may improve clinical decision-making, reduce unnecessary empirical antifungal treatment, and enhance patient outcomes.

BackgroundWe diagnosed a clinical case of pulmonary infection involving Mycobacterium tuberculosis and Tropheryma whipplei in a patient with acute respiratory distress syndrome. The diagnosis was assisted by metagenomic next-generation sequencing of bronchoalveolar lavage fluid.Case presentationA 44-year-old Han Chinese inmate was transferred to the emergency department because of dry cough, chest tightness, and shortness of breath. The patient’s body temperature rose to 39.3 °C following empirical cephalosporin treatment for 1 week. The blood CD4+/CD8+ ratio was 0.7, suggesting immunodeficiency. Routine microbiological tests were performed, and tuberculosis interferon gamma release assays were positive. Mycobacterium tuberculosis polymerase chain reaction was also positive. Chest computed tomography scan revealed miliary nodules and ground-glass opacifications, which were in accordance with tuberculosis. To fully examine the etiology, we performed routine laboratory tests and metagenomic sequencing, the results of which indicated the presence of Mycobacterium tuberculosis and Tropheryma whipplei. We administered anti-tuberculosis regimen in combination with trimethoprim/sulfamethoxazole. The patient recovered, with chest computed tomography scan showing absorption of lesions.ConclusionsCompared with traditional diagnostic methods such as culture and serology, metagenomic next-generation sequencing has the advantage of detecting a wide array of microorganisms in a single test and therefore can be used for clinical diagnosis of rare pathogens and microbial coinfections. It is particularly useful for immunocompromised patients as they are more prone to infection by opportunistic microorganisms.

Diagnostic Performance and Clinical Impacts of Metagenomic Sequencing after Allogeneic Hematopoietic Stem Cell Transplantation

The homeostasis of the microbiome in lower respiratory tract is crucial in sustaining normal physiological functions of the lung. Different pulmonary diseases display varying degrees of microbiome imbalance; however, the specific variability and clinical significance of their microbiomes remain largely unexplored. In this study, we delineated the pathogen spectrum and commensal microorganisms in the lower respiratory tract of various pulmonary diseases using metagenomic sequencing. We analyzed the disparities and commonalities of the microbial features and examined their correlation with disease characteristics. We observed distinct pathogen profiles and a diversity in lower airway microbiome in patients diagnosed with cancer, interstitial lung disease, bronchiectasis, common pneumonia, Nontuberculous mycobacteria (NTM) pneumonia, and severe pneumonia. This study illustrates the utility of Metagenomic Next-generation Sequencing (mNGS) in identifying pathogens and analyzing the lower respiratory microbiome, which is important for understanding the microbiological aspect of pulmonary diseases and essential for their early and precise diagnosis.