Metagenomic Next-Generation Sequencing Reveals the Profile of Fungal Infections in Kidney Transplant Recipients: a retrosective study

Metagenomic Next-Generation Sequencing Reveals the Profile of Fungal Infections in Kidney Transplant Recipients: a retrosective study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Metagenomic Next-Generation Sequencing Reveals the Profile of Fungal Infections in Kidney Transplant Recipients: a retrosective study Qin Wang, Handong Ding, Yazi Zhao, Zongyao Hao, Guiyi Liao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5380360/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Infection is an important cause of death after kidney transplant surgery. Although fungal infections are relatively rare, they have low detection rates and high mortality rates. The value of metagenomic next-generation sequencing (mNGS) in kidney transplant patients with fungal infections remains to be studied, especially in diagnosis and to guide the use of antibiotics. Methods From September 2021 to August 2023, a total of 234 patients after kidney transplantation were enrolled, and data of 66 patients with suspected fungal infections were collected. The pathogen detection performance of mNGS and conventional microbiological tests (CMTs) were compared. The impacts of mNGS and CMTs on treatment adjustment were also assessed. Finally, we explored the value of mNGS in donor-derived infections. Results A total of 21 fungal species were detected in the 66 patients, of which 18 species of fungus were detected by mNGS and 10 species of fungus were detected by CMTs. mNGS was significantly higher than culture in total positive rate (90.67% vs. 26.67%), especially for multiple fungal infections (9vs0). mNGS identified more candida (26vs12), pneumocystis jirovecii (14vs0), aspergillus (10vs4), mucor (6vs2) organisms compared with CMTs. Fungi from donors were identified in 11(6.7%) patients, including 10 cases of Candida spp. and 1 case of Mucor spp. The anti-infection therapies were adjusted in 28 (24.4%) cases by mNGS. Conclusion The mNGS technique showed distinct advantages in detecting fungal infections in kidney transplant patients, which can guide anti-infection strategies and protect grafts. In addition, it has a good identification value for fungal infections from donor sources. metagenomic next-generation sequencing (mNGS) fungal infections kidney transplantation donor-derived infection antibiotic Treatment Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION After kidney transplantation, patients need long-term and extensive use of immunosuppressants, and their immune function is impaired, which increases the risk of infection. There are three stages of infection after transplantation: (1) a phase up to 1 month characterized by nosocomial infections and donor-derived infections; (2) a phase of profound immunosuppression for up to 6 months associated with opportunistic infections; and (3) a phase of reduced immunosuppression with community-acquired and rare infectious agents. Infectious diseases are a major cause of morbidity and mortality after kidney transplantation [ 1 , 2 ]. Fungal infections account for less than 5% of all renal transplant infections. The common fungi in kidney transplant patients were Candida and Aspergillus [ 3 , 4 ]. The mortality rate of invasive aspergillosis is reported to be approximately 22% [ 5 , 6 ]. The overall mortality of invasive candidiasis at 12 months is reported to be 34% [ 7 ]. Donor-derived infection (DDI) is rare but causes significant morbidity and mortality. However, graft loss or death occurred in about one-third of recipients with DDI, with higher rates associated with fungal diseases [ 8 ]. The reported incidence of DDI is approximately 0.2% in all deceased donor organ transplantations [ 9 ]. Fungal infections account for approximately 15.5% of DDI [ 10 ]. However, many questions regarding the prevention and early diagnosis of infections remain unanswered, and more research is needed in this area. The gold standard for the detection of invasive fungal infections is histopathological diagnosis or culture obtained by a sterile procedure. Unfortunately, histopathological testing is rarely available in a timely manner, whereas culture methods are insensitive and time-consuming. Although microscopic smears can identify Aspergillus hyphae faster than culture, it requires a large number of pathogens and experienced microbiologists, making it less feasible. Galactomannan (GM) test and Beta-D-Glucan (BDG) have been widely used for the diagnosis of fungal diseases, but their diagnostic ability is limited due to low fungal load in lesions, low probability of antigen appearance in blood, unstandardized sampling in different samples, antimicrobial treatment before sampling, and various other factors. Metagenomic next generation sequencing (mNGS) makes up for the limitations of current diagnosis and is applied to pathogen detection in clinical practice. It can detect pathogens faster and more accurately, and is not affected by antibiotic exposure prior to detection. The results of studies on the diagnosis of fungal infections are controversial. Some studies showed that mNGS can improve the sensitivity of fungal infection and are less affected by antibiotic exposure prior to detection [ 11 , 12 ]. In contrast, identification of filamentous molds, such as Aspergillus , by mNGS remains challenging due to the difficulty of extracting DNA from thicker polysaccharide cell walls and the relatively low fungal load in BALF [ 13 , 14 ]. However, few studies have investigated the use of mNGS in fungal infection in renal transplant patients, especially in DDI. We used the mNGS technique to identify pathogens from multiple samples of patients with possible fungal infection, evaluated the type and prevalence of pathogens found, and compared the results to those obtained with conventional methods. Moreover, we reported cases where mNGS assisted medication to improve the patient's condition. MATERIALS AND METHODS Patients and Study Design This is a retrospective study conducted in renal transplant recipients in the First Affiliated Hospital of Anhui Medical University between September 2021 and August 2023. Deceased donors are usually hospitalized in the intensive care unit (ICU) for long periods of time and have a high risk of infection, all organ preservation fluids from donors need to be both conventionally cultured and submitted to next-generation sequencing. A total of 395 samples from 234 patients were initially enrolled in this study. Patients were included if they met all the following criteria: (1) having smear, culture, and mNGS results; (2) mNGS or conventional microbiological tests (CMTs) identified the fungus. The following exclusion criteria were used: (1) mNGS and CMTs were not paired (i.e., not conducted simultaneously or on the same day); (2) the medical record was incomplete. Among these patients, a total of 75 samples from 66 patients were investigated in this study. This study was approved by the research ethics committee of the First Affiliated Hospital of Anhui Medical University. Individual consent for this retrospective analysis was waived. Samples from patients were collected according to standard operating procedures. All the collected initial specimens were divided into two parts: one was used for subsequent mNGS sequencing, and the other was used for traditional culture. Patients with suspected fungal infections underwent serum (1,3)-β-D Glucan (BDG) and serum galactomannan testing. The standards and methods were implemented according to the routine microbial culture process, which was completed by the Clinical Laboratory of the First Affiliated Hospital of Anhui Medical University. Microbiologic Methods Using conventional microbiologic methods, samples (blood, BALF, organ preservation solutions, drainage fluid, sputum) were examined by routine laboratory staining and cultures. Serum BDG was detected according to the manufacturer’s instructions. Both BALF and serum galactomannan detection were performed using a double-sandwich ELISA according to the manufacturer’s instructions. Clinical Data Collection Data, including demographics, laboratory test results, diagnosis, treatment, and clinical outcomes, were collected from the electronic medical records of the First Affiliated Hospital of Anhui Medical University through a standardized data collection form. Information of initial antibiotic and later adjustment based on mNGS results was also collected. Metagenomic Next-Generation Sequencing and Analysis Seventy-five samples were collected from different tissues, including 23 BALF samples, 23 drainage fluid samples, 13 blood samples, 15 organ preservation culture samples, and 1 sputum sample, and DNA alone or combined DNA and RNA sequencing was performed. The samples for mNGS were sent to testing companies for nucleic acid extraction, library construction, high-throughput sequencing, result presentation, and pathogen data interpretation. The samples were sealed aseptically and stored at -20 ℃ or transported on dry ice to Hugobiotech Co., Ltd., (Beijing, China) to perform mNGS detection immediately. The DNA was extracted and purified according to the instructions of QIAamp DNA Micro Kit (QIAGEN, Hilden, Germany). DNA concentration and quality were checked through Qubit 3.0 Fluoremeter (Invitrogen, Q33216) and agarose gel electrophoresis (Major Science, UVC1-1100). DNA library construction was performed according to the Qiagen library construction kit (QIAseq Ultralow Input Library Kit) operating instructions. Library quality control was performed by Qubit 3.0 Fluoremeter (Invitrogen, Q33216) and Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, USA). Qualified DNA libraries with different barcode tags were pooled and then sequenced using the Illumina Nextseq 550 sequencing platform (Illumina, San Diego, USA) and a SE75bp sequencing strategy. After obtaining the sequencing data, high quality data was generated by filtering out connectors, low quality, low complexity and shorter sequences. Next human-derived sequences matching to the human reference database (hg38) were removed by using SNAP software. The remaining data were then aligned to the microbial genome database using Burrow-Wheeler Alignment. This database contains a large collection of microbial genomes from NCBI containing more than 30,000 microorganisms, including 17,748 species of bacteria, 11,058 species of viruses, 1,134 species of fungi, and 308 species of parasites. Criteria for a Positive mNGS Result (1) For bacteria other than TB, fungi other than Cryptococcus and parasites: sequencing coverage in the top 10 of all pathogens detected and not detected in the negative control (NTC); or sample/NTC with an RPM (reads per million mapped reads) ratio greater than 10. (2) For viruses, tuberculosis and cryptococci: at least 1 specific sequence was detected and not detected in the NTC; or the RPM ratio of sample/NTC was greater than 5. Statistical Analysis Continuous data conforming to a normal distribution were reported as the mean ± standard deviation value; continuous data outside the normal distribution were presented as median and interquartile range (IQR). Categorical data were presented as the number of cases and percentage (%). Statistical analyses were performed using SPSS version 20.0 (IBM Corporation, Armonk, NY, USA). A p -value less than 0.05 was considered statistically significant. RESULTS 1. Sample and Patient Characteristics Between September 2021 and August 2023, a total of 75 samples from 66 patients with suspected fungal infections were enrolled in this study. All patients underwent mNGS and CMTs. The patient average age was 43.7 ± 9.6 years, and 39 (59.09%) patients were male. The most common comorbidity was anemia (53.03%, 35/66), followed by hypertension (40.91%, 27/66), agranulocytosis (16.67%, 11/66), chronic digestive system disease (11.4%, 16/140), and diabetes (15.15%, 10/66). Some patients are complicated with various comorbidities. The median length of hospital stay was 28.5 (20–55) days. Additionally, 18 (27.27%) patients were admitted to the intensive care unit (ICU), and their median length of stay in ICU was 3.5 (1–7) ( Table 2 ) . The overall mortality rate was 15.15% (10/66). Among these 10 deceased patients, seven had fungal blood stream infection, and the other 3 patients died of Acinetobacter baumannii infection and myocardial infarction, Pseudomonas aeruginosa bloodstream infection, and septic shock caused by COVID-19, respectively ( Table 1 ) . The characteristics of the 10 deceased patients are shown in Table 1 . There were 16 patients with fever before treatment, and 6 patients still had fever after treatment ( Table 2 ) . Overall, the sample types consisted of drainage fluid [n = 23 (30.67%)], followed by BALF [n = 23 (30.67%)], organ preservation cultures [n = 15 (20.00%)], blood [n = 13 (17.33%)], and sputum [n = 1 (1.33%)] ( Fig. 1 ) . Table 1 The characteristics of died patients NO. sex years Hospital length of stay (days) ICU length of stay (days) Cause of death Source of fungal Pathogen 1 Male 29 17 0 Acinetobacter baumannii infection, Myocardial infarction Drainage fluid Candida glabrata 2 Female 47 67 10 COVID-19, septic shock Blood, Drainage fluid, Organ preservation cultures Rhizomucor pusillus 3 Male 33 13 6 Infectious Blood Rhizomucor pusillus, Aspergillus flavus 4 Male 44 25 0 Septic shock Blood Lichtheimia ramasa 5 Male 46 22 2 Cerebral infarction, Infectious BALF Aspergillus flavus, Lichtheimia corymbifera, Rhizomucor pusillus Blood Lichtheimia corymbifera 6 Female 46 86 4 COVID-19, Pseudomonas aeruginosa infectious Organ preservation cultures Aspergillus niger 7 Female 24 21 15 COVID-19, Infectious Blood Pneumocystis jirovecii 8 Female 63 9 7 COVID-19, Infectious Blood Pneumocystis jirovecii 9 Female 53 80 7 Septic shock, COVID-19 Blood Candida parapsilosis 10 Female 43 121 0 Septic shock, COVID-19 BALF Candida parapsilosis Table 2 Patient Characteristics Characteristics Cases (n = 66) Gender, n (%) Male 39 Female 27 Age (years) 40.7 ± 9.6 Comorbidity Hypertension 27 (40.91%) Diabetes 10 (15.15%) Anemia 35 (53.03%) Agranulocytosis 11 (16.67%) Outcomes Hospital LOS (days), median (IQR) 28.5 (20, 55) ICU admission rate, n (%) 18(27.27%) ICU LOS (days), median (IQR) 3.5 (1, 7) Mortality, n (%) 10(15.15%) Body temperature Before After Normal X 50 60 ≥ 37.3◦C 16 6 ICU( intensive care unit); LOS: length of stay 2. Distribution of Fungal Species Detected by mNGS and CMTs A total of 21 fungal species were detected in the 66 patients, of which 17 species of fungus were detected by mNGS ( Fig. 2 ). The most common pathogens detected by mNGS were Pneumocystis (14), Candida albicans (12), and Candida parapsilosis (6). A total of 26 cases of Candida spp., 10 cases of Aspergillus spp., and 6 cases of Mucor spp. were detected by mNGS. Among them, nine patients were infected with multiple fungus. The pathogens of multiple fungal infections were derived from BALF and blood in 7 cases and drainage fluid in 2 cases. The specific characteristics of the patients are shown in Table 3 . For CMTs, eleven species of fungus were cultured, with Candida albicans and Candida glabrata being the most common. Only one patient was infected with multiple fungus ( Fig. 3 ) . CMTs identified 12 cases of Candida spp., 6 cases of Aspergillus spp., and 1 case of Aspergillus spp.. Table 3 The patients with multiple fungus. Sex Years Hospital length of stay (days) ICU length of stay (days) outcomes Source of fungal Pathogen Male 31 30 0 Improved Drainage fluid Candida glabrata, Candida tropicalis Female 34 186 0 Improved BALF Rhizomucor pusillus, aspergillus fumigatus Male 33 13 6 died Blood Rhizomucor pusillus, Aspergillus flavus Male 38 22 0 Improved Blood Candida parapsilosis, Candida tropicalis Female 44 192 0 Improved BALF Aspergillus fumigatus, Aspergillus flavus, Candida albicans Male 28 29 0 Improved BALF Aspergillus flavus, Aspergillus fumigatus, rhizopus oryzae, Rhizopusdelemar, Pneumocystis jirovecii Male 46 22 2 died BALF Aspergillus flavus, Lichtheimia corymbifera, Rhizomucor pusillus Male 42 109 0 Improved BALF Aspergillus flavus, aspergillus terreus, aspergillus niger Male 28 25 0 Improved Drainage fluid Candida glabrata, Candida albicans DDI can result in significant morbidity and mortality. Pathogens in organ preservation fluid and drainage fluids may indicate donor-derived infection and reduce the risk of donor-derived fungal infection. Therefore, thirty-eight samples from organ preservation and drainage fluids were further analyzed. A total of 12 different fungal species were identified from 31 fungal strains using NGS, of which the most common was Candida spp. , accounting for 70.97% (22/31) of all strains. Two of the patients were infected with multiple fungal species ( Fig. 4 ) . For traditional cultures, sixteen cases of fungus were cultured, of which Candida spp. accounted for 81.25% (13/16). Only one patient was infected with multiple fungus (Fig. 5) . 3. Mixed Infections Detected by mNGS Mixed infection was defined when two or more infectious pathogens were detected. Mixed infection were detected in 57 samples by mNGS. The most frequent pattern of mixed infection was fungi and bacteria mixed infection (21/75, 28%), followed by bacteria, virus and fungi mixed infection (19/75, 25.33%). Fungal and viral co-infection was detected in 14 samples (14/75, 18.67%); eleven patients were diagnosed as fungi infection (11/75, 14.67%); the other three patients had mixed infections with Mycobacterium tuberculosis or atypical pathogens. Notably, twenty seven mixed infection were detected in organ preservation cultures and drainage fluid. The most frequent pattern of mixed infection was bacteria and fungi (17/38, 44.74%), followed by bacteria, virus and fungi mixed infection (8/38, 21.05%). Nine samples were dentified two or more fungal species, among which 3 patients were infected with two kinds of Candida spp., four patients were infected with Aspergillus spp., Mucor spp., one patient was infected with a variety of Aspergillus spp. and one patient was infected with Aspergillus spp. and Candida spp.. The samples of 9 cases were from 5 alveolar lavage fluid, 2 cases from blood, and 2 cases from drainage fluid. Among them, two cases resulted in death: one due to a mixed infection of mucormycosis and aspergillosis, and the other due to multiple mucormycosis infections ( Table 3 ) . 4. Comparison of the Diagnostic Performance of mNGS and CMTs All samples underwent both mNGS and CMTs. In this study, the mNGS results for 68 of 75 (90.67%) patients were positive for fungus, which was much superior to the CMTs of 26.67% (20/75). A comparison of the diagnostic results from mNGS with CMTs is shown in Fig. 2 , 3 . In our study, the results of mNGS and CMTs were both positive in 13 (13/75, 13.33%) cases. A total of 55 (55/75, 73.33%) cases were positive by mNGS only, but 7 (7/75, 9.33%) cases were positive by CMTs only. Additionally, for 13 double-positive cases, the results between mNGS and CMTs were consistent in 7 (7/75, 9.33%), partially consistent in 3 (3/75, 4%), and completely inconsistent in 3 (3/75, 4%) ( Figure. 6 ). Overall, mNGS identified more candida (26 vs 12), aspergillus (10 vs 4), and mucor (6 vs 2) organisms compared with CMTs. The pathogens missed by conventional culture were pneumocystis jirovecii (14), candida guilliermondii (1), aspergillus niger (1), rhizopusdelemar (1), lichtheimia ramasa (1), lichtheimia corymbifera (1), cryptococcus albidus (1), talaromyces marneffei (1), talaromyces marneffei (1), alternaria alternata (1), rhizopus oryzae (1), and aspergillus terreus (1). On the contrary, the pathogens missed by mNGS included yeast (1), aspergillus sydowii (1), and aspergillus versicolor (1). In summary, mNGS identified pathogens which were relatively complex or undetectable under culture conditions. 5. Donor-derived Fungal Infections From September 2021 to August 2023, there were 146 patients who underwent kidney transplantation from donors after cardiac death. Organ preservation fluid and/or drainage fluid from all patients underwent mNGS and CMTs. A total of 248 samples of organ preservation fluid and drainage fluid were collected, with fungi detected in 41 samples from 35 patients. Fungi from donors were identified in 11 (11/146, 7.5%) patients, including 10 cases of Candida spp. and 1 case of Mucor spp.. Among these 11 patients, two cases resulted in death: one due to bacterial infection and the other due to disseminated mucormycosis. No deaths due to Candida infection were observed in the patients. Detection methods included reliance on mNGS in 4 cases, CMTs in 4 cases, and both mNGS and CMTs in the remaining 3 cases ( Table 4 ) . Table 4 The characteristics of donor-derived infections NO. Sex Years Hospital length of stay (days) outcomes Pathogen Detection method 1 Male 29 17 Deid Candida glabrata NGS, CMTs 2 Male 31 30 Improved Candida glabrata NGS, CMTs 3 Female 37 24 Improved Candida tropicalis CMTs 4 Male 38 51 Improved Candida glabrata NGS, CMTs 5 Male 38 30 Improved Candida glabrata CMTs 6 Female 47 67 Deid Rhizomucor pusillus NGS 7 Female 35 57 Improved Candida albicans NGS 8 Female 44 85 Improved Candida albicans NGS 9 Male 39 27 Improved Candida albicans NGS 10 Male 28 25 Improved Candida glabrata CMTs 11 Female 55 21 Improved Candida albicans CMTs 6. Impacts of mNGS on the Application of Antibiotic Treatment Table 5 shows records of antimicrobial treatment of 66 patients with mycosis during hospitalization. We evaluated the impact of mNGS on antimicrobial therapy. Nine patients were not initially treated with antifungal agents, and the other patients were initially treated with different antifungal agents empirically. Antifungal therapy was changed in 42.4% (28/66) of patients based on mNGS results. In most of the cases without adjustment, treatment was not adjusted due to previous empirical caspofungin covering the pathogens detected. For patients mNGS provided positive identification of aspergillus in 10 cases, leading to the addition of voriconazole in these patients. For patients with Pneumocystis jirovecii confirmed by mNGS, therapeutic doses of compound sulfamethoxazole were added in 10 patients. As we observed, 13 patients discontinued caspofungin according to mNGS. Table 5 Adjustment of antibiotic treatment according to mNGS results Antimicrobials Pre-mNGS After-mNGS Reduce fungal agents Increase fungal agents Voriconazole 6 3 10 posaconazole 0 0 6 isavuconazole 0 0 1 Caspofungin 51 13 5 Amphotericin B 0 0 2 TMP-SMZ (therapeutic dose) 5 2 10 No change 38 DISCUSSION Effective management of post-transplant infection relies on prevention, early diagnosis, and specific therapy. In the field of organ transplantation, fungal infections, although less common than bacterial infections, have a higher mortality rate [ 15 , 16 ]. The incidence of invasive fungal infections (IFIs) varies across different types of organ transplants, ranging from 1.3–11.6% [ 7 ]. Some studies reported that the overall mortality rate for kidney transplant recipients with fungal infections ranged between 15% and 50% [ 17 ]. Despite numerous studies investigating one or more pathogenic infections following renal transplantation, there is a lack of research revealing fungal infections in renal transplant patients using mNGS techniques. For this, detailed information on the incidence, microbial etiology, and timeline of infections is crucial. In this study, we performed a comprehensive and systematic analysis of fungal infections after kidney transplantation using mNGS and compared them with CMTs. This study included 395 NGS samples collected over the past two years, covering kidney transplants from related donors and DCD donors. Our study revealed differences between mNGS and CMTs in fungal detection and highlighted the potential advantages of mNGS in clinical applications. We analyzed the detected fungal species, mixed infections, fungal infections from donor sources, and the impact of mNGS on fungal treatment. Thus far, fungal smear and culture, serum (1,3)-b-D-glucan (G) or galactomannan (GM) tests, and PCR are used in the microbiological analysis of fungi. Compared with other tests, traditional culture methods can provide information on drug susceptibility. However, these methods have certain limitations, such as low positive rates, low sensitivity, high false-positive rates, and long processing times. Kidney transplant patients often use multiple medications, which may affect the accuracy of the aforementioned diagnostic methods. Conventional blood cultures may fail to diagnose candidiasis in up to 25–50% of cases [ 18 ]. mNGS, with the characteristics of fast detection speed, high sensitivity, and broad coverage, can effectively compensate for traditional methods. Currently, the most reported tests were mNGS on blood, alveolar lavage fluid, and cerebrospinal fluid, which can rapidly and accurately identify microbial species, improve clinical diagnosis, and guide effective clinical treatment. A retrospective cohort study found that mNGS had a higher positivity rate than blood cultures (58.5% vs. 21.9%) and was able to identify multiple species, including bacteria, fungi, and viruses, in a cohort of ICU patients [ 19 ]. A study involving patients with lower respiratory tract infections demonstrated that mNGS identified pathogens in 65% of cases, significantly higher than the 20% detection rate of CMTs [ 20 ]. In cases of invasive pulmonary fungal infection and early postoperative pulmonary infection following lung transplantation, the diagnostic performance of mNGS surpasses CMTs [ 21 ]. For bloodstream fungal infections, whether in liver transplant patients or those with sepsis, the use of mNGS significantly improves the detection rate compared to CMTs [ 22 , 23 ]. These studies all indicate that mNGS has clear advantages in the diagnosis of fungal infections. Our study also showed that the fungal detection rate of mNGS in kidney transplant patients was significantly higher than that of CMTs (90.67% vs. 26.67%). Research suggested that mNGS exhibited better performance than culture with regard to fungal detection, but the difference was not significant in Aspergillus detection [ 24 ]. Peng et al. concluded that CMTs were more effective than mNGS for fungal infections in the lung [ 25 ]. Therefore, the diagnostic value of mNGS in fungal infections remains controversial. mNGS can detect rare and opportunistic fungi that might be missed by traditional methods, such as Pneumocystis . This capability is particularly important in immunocompromised patients, where infections with uncommon fungi can occur. Wang et al. reported that the most commonly fungi detected by mNGS in pulmonary fungal infections were Candida albicans , Aspergillus fumigatus and Pneumocystis [ 21 ]. Another study showed that the most commonly isolated fungi species were Aspergillus , Pneumocystis , and Rhizopus detected by mNGS in pulmonary fungal infections [ 26 ]. In our study, the most common pathogens detected by mNGS were Pneumocystis (14/75, 18.67%), Candida spp. (26/75, 34.67%), Aspergillus spp. (10/75, 13.33%), and Mucormyces spp. (6/75, 8%). Additionally, among patients with multiple fungal infections, mixed infections involving Candida , Aspergillus , and Mucor species were predominant. Overall, these studies indicate that mNGS detects more Candida , Pneumocystis , Aspergillus , and Mucorales compared to CMTs. In particular, Pneumocystis cannot be detected by CMTs, one of the important infections in renal transplant patients. In our study, Pneumocystis jirovecii , Aspergillus spp. , and Mucor spp. were predominantly isolated from pulmonary infections. As a new pathogen detection strategy, mNGS reached a sensitivity rate of 100% in the diagnosis of Pneumocystis jirovecii , according to a study of HIV-negative immunocompromised patients [ 27 ]. Other studies have also demonstrated that NGS exhibits higher sensitivity and specificity in detecting Pneumocystis jirovecii compared to GMS and BDG [ 28 – 30 ]. Candida spp. is the most frequent fungal pathogen in nearly all solid organ transplants. Generally, the onset of invasive candidiasis occurs earlier than other invasive fungal infections, typically within the first few months post-transplantation. Approximately 50% of the isolates involve Candida albicans , while Candida glabrata is the most common non- albican Candida species [ 31 ]. The findings of our study are consistent with previous research, regardless of whether CMTs or mNGS were used. Invasive aspergillosis is one of the most relevant fungal infections in solid organ transplantation recipients. It occurs in 1–15% of the SOT patients, and currently reported mortality rates of invasive aspergillosis are approximately 22% despite novel treatment modalities. In lung transplant recipients, invasive pulmonary disease has an even higher mortality rate of 67–82% [ 5 ]. In recent years, studies have demonstrated that mNGS exhibits superior diagnostic performance for Aspergillus infections compared to traditional methods, particularly in immunosuppressed patients [ 11 , 32 – 34 ]. Our study also indicates that the detection rate of aspergillosis using mNGS is superior to that of CMTs (10 vs 3). Furthermore, mNGS performed well in identifying fungal species and co-pathogens, indicating that mNGS may have a valuable role in guiding antimicrobial therapy. Numerous studies have confirmed that mNGS has obvious advantages in detecting mixed pathogen infections [ 35 , 36 ]. And we also found that mixed infections were detected in 57 samples by mNGS. Additionally, NGS identified multiple fungal infections in 9 samples, whereas CMTs detected only one case. The comprehensive fungal profile obtained through mNGS offers valuable insights into the epidemiology of fungal infections in transplant recipients. The effect of antibacterial drugs on mNGS is less than CMTs, and the treatment strategies can be adjusted according to these results. As is well known, accurate identification of strains is crucial for guiding antifungal treatment. A study on lower respiratory tract infections demonstrated that mNGS could alter the treatment regimen in 39.3% of patients [ 35 ]. According to another study, antibiotics were adjusted in 45.1% of patients based on mNGS [ 36 ]. Yan Shi et al. highlighted the favorable prognosis resulting from antifungal drug changes based on mNGS results [ 11 ]. Our study showed that antifungal therapy was changed in 42.4% (28/66) of patients based on mNGS results. The primary medication adjustments are as follows: reduction of caspofungin, increase of voriconazole, and adjustment of the trimethoprim-sulfamethoxazole dosage. The rapid results of mNGS can provide evidence for the next step in treatment, especially to avoid overuse of antibiotics and improve patient outcomes. Compared to bacterial and viral infections, donor-derived fungal infections are less common but often more severe and potentially life-threatening when they occur. The overall incidence of DDI was 0.14%. Donor-derived fungal infections accounted for 22%, which is lower than bacterial infections (30%) and viral infections (approximately 31%). The overall DDI-associated mortality was 15% [ 8 ]. Blood and urine cultures are recommended for all deceased donors. The guidelines generally do not recommend culturing preservation fluid. If Candida is detected in the kidney, liver, or pancreas, consider adding fungal cultures of the recipient's urine (kidney recipient), blood, and drainage fluid [ 37 , 38 ]. In our study, culture results for donors were not provided, but both NGS and CMTs were performed on kidney lavage fluid and drainage fluid, while CMTs were also conducted on the recipient's blood and urine. A comprehensive systematic review and meta-analysis previously reported an overall organ preservation fluids culture positivity rate of 37%. The positivity of organ preservation fluid cultures was not a strong indicator of transmission, regardless of the allograft type, with an overall incidence of organ preservation fluid-related DDI of 4% [ 39 ]. In our study, the positivity rate of organ preservation fluid fungi was 8.9% (13/146). Fungi from donors were identified in 11 (11/146, 7.5%) patients. The donor-derived fungal infection rate we observed is higher than previously reported rates, which may be attributed to our use of both NGS and CMTs for detection. Previous studies have shown that the most common fungal infections originating from donors are caused by Candida (24%), followed by Cryptococcus (20%) and Aspergillus (13%), with mucormycosis being relatively rare [ 8 ]. Our study identified 11 cases (7.5%) of donor-derived fungal infections, of which 10 were due to Candida and 1 was due to mucormycosis . Additionally, previous studies have reported mortality rates for donor-derived fungal infections as follows: Candida at 10.0%, Aspergillus at 33.3%, and Cryptococcus at 7.7% [ 8 ]. In our study, ten patients did not die from Candida infections, and one patient died due to mucormycosis . No cases of donor-derived Aspergillus or Cryptococcus infections were observed in our study, likely because lung transplants are more prone to spreading these infections, whereas our study focused on kidney transplants. The most common donor-derived fungal infection in our study was Candida (6.8%), consistent with previous research findings. Previously, nephrectomy was recommended for patients with lavage fluid positive for Candida species. However, recent data suggest that recipients of organs from Candida culture-positive donors require aggressive treatment. Current guidelines recommend 14 days of aggressive treatment with fluconazole or echinocandin in cases of unknown species or suspected azole resistance [ 38 ]. At our transplant center, for kidneys obtained from donation after circulatory death, recipients routinely receive caspofungin postoperatively for fungal prophylaxis. Subsequent adjustments to antimicrobial therapy will be based on etiological evidence. LIMITATION The present study had several limitations. First, in our study, traditional detection methods were not comprehensive, such as the G test, GM test, cryptococcal capsular polysaccharide antigen test, and Grocott methenamine silver stain. Fungi like Mucor and Pneumocystis jirovecii are difficult to culture, and these detection methods help diagnose these fungi. Therefore, it is impossible to compare the diagnostic performance of mNGS with these methods. Second, mNGS cannot distinguish between infection and colonization, and it is necessary to consider the patient's clinical features, imaging characteristics, and other testing methods comprehensively. Third, mNGS does not provide susceptibility results, although fungal resistance is not as complex as bacterial resistance. Fourth, the cell wall of Aspergillus is thick, and nucleic acids are difficult to release, which causes a false-negative result. Finally, this study is retrospective, and the diagnostic value of mNGS in fungal infections among kidney transplant patients has not been fully studied. Further multicenter prospective studies with large sample sizes are needed. In summary, although NGS offers advantages such as rapid and sensitive detection of fungal infections in kidney transplant patients, particularly for pathogens that cannot be cultured using traditional methods, it also has several unavoidable drawbacks. Standardizing its indications, optimal timing of use, and the diagnostic approach for various pathogens may need to be tailored to the specific circumstances of each patient. Declarations ACKNOWLEDGMENTS This research was supported by National Natural Science Foundation of China (82470783). The authors declare that they have no competing interest. AUTHOR CONTRIBUTIONS WQ, DHD and LGY are responsible for the conception and design, development of methodology, data analysis and interpretation, writing, review, and revision of the manuscript. HZY contributed to the study concept and design, interpretation of the data and revision of the manuscript. ZYZ contributed to conception, design and data analysis. All authors have read and approved the final manuscript. References Fishman JA: Infection in Organ Transplantation. American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons 2017, 17(4):856-879. Fiorentino M, Pesce F, Schena A, Simone S, Castellano G, Gesualdo L: Updates on urinary tract infections in kidney transplantation. Journal of nephrology 2019, 32(5):751-761. Sommerer C, Schroter I, Gruneberg K, Schindler D, Behnisch R, Morath C, Renders L, Heemann U, Schnitzler P, Melk A et al: Incidences of Infectious Events in a Renal Transplant Cohort of the German Center of Infectious Diseases (DZIF). Open forum infectious diseases 2022, 9(7):ofac243. Anastasopoulos NA, Duni A, Peschos D, Agnantis N, Dounousi E: The Spectrum of Infectious Diseases in Kidney Transplantation: A Review of the Classification, Pathogens and Clinical Manifestations. In vivo 2015, 29(4):415-422. Singh N, Husain S, Practice ASTIDCo: Aspergillosis in solid organ transplantation. American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons 2013, 13 Suppl 4:228-241. Silva JT, Torre-Cisneros J, Aguado JM: Invasive aspergillosis in solid organ transplantation. Revista iberoamericana de micologia 2018, 35(4):206-209. 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Wu K, Annambhotla P, Free RJ, Ritter JM, Leitgeb B, Jackson BR, Toda M, Basavaraju SV, Gold JAW: Fatal Invasive Mold Infections after Transplantation of Organs Recovered from Drowned Donors, United States, 2011-2021. Emerging infectious diseases 2023, 29(7):1455-1458. Seok H, Huh K, Cho SY, Kang CI, Chung DR, Huh WS, Park JB, Peck KR: Invasive Fungal Diseases in Kidney Transplant Recipients: Risk Factors for Mortality. Journal of clinical medicine 2020, 9(6). Bassetti M, Peghin M, Timsit JF: The current treatment landscape: candidiasis. The Journal of antimicrobial chemotherapy 2016, 71(suppl 2):ii13-ii22. Overbeek R, Leitl CJ, Stoll SE, Wetsch WA, Kammerer T, Mathes A, Bottiger BW, Seifert H, Hart D, Dusse F: The Value of Next-Generation Sequencing in Diagnosis and Therapy of Critically Ill Patients with Suspected Bloodstream Infections: A Retrospective Cohort Study. Journal of clinical medicine 2024, 13(2). Chen H, Yin Y, Gao H, Guo Y, Dong Z, Wang X, Zhang Y, Yang S, Peng Q, Liu Y et al: Clinical Utility of In-house Metagenomic Next-generation Sequencing for the Diagnosis of Lower Respiratory Tract Infections and Analysis of the Host Immune Response. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 2020, 71(Suppl 4):S416-S426. Wang C, You Z, Fu J, Chen S, Bai D, Zhao H, Song P, Jia X, Yuan X, Xu W et al: Application of metagenomic next-generation sequencing in the diagnosis of pulmonary invasive fungal disease. Frontiers in cellular and infection microbiology 2022, 12:949505. Decker SO, Kruger A, Wilk H, Grumaz S, Vainshtein Y, Schmitt FCF, Uhle F, Bruckner T, Zimmermann S, Mehrabi A et al: New approaches for the detection of invasive fungal diseases in patients following liver transplantation-results of an observational clinical pilot study. Langenbeck's archives of surgery 2019, 404(3):309-325. Chien JY, Yu CJ, Hsueh PR: Utility of Metagenomic Next-Generation Sequencing for Etiological Diagnosis of Patients with Sepsis in Intensive Care Units. Microbiology spectrum 2022, 10(4):e0074622. Miao Q, Ma Y, Wang Q, Pan J, Zhang Y, Jin W, Yao Y, Su Y, Huang Y, Wang M et al: Microbiological Diagnostic Performance of Metagenomic Next-generation Sequencing When Applied to Clinical Practice. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 2018, 67(suppl_2):S231-S240. Peng JM, Du B, Qin HY, Wang Q, Shi Y: Metagenomic next-generation sequencing for the diagnosis of suspected pneumonia in immunocompromised patients. The Journal of infection 2021, 82(4):22-27. Zhao Z, Song J, Yang C, Yang L, Chen J, Li X, Wang Y, Feng J: Prevalence of Fungal and Bacterial Co-Infection in Pulmonary Fungal Infections: A Metagenomic Next Generation Sequencing-Based Study. Frontiers in cellular and infection microbiology 2021, 11:749905. Jiang J, Bai L, Yang W, Peng W, An J, Wu Y, Pan P, Li Y: Metagenomic Next-Generation Sequencing for the Diagnosis of Pneumocystis jirovecii Pneumonia in Non-HIV-Infected Patients: A Retrospective Study. Infectious diseases and therapy 2021, 10(3):1733-1745. Xu J, Yu Y, Lv J, Yang S, Wu J, Chen J, Peng W: Application of Metagenomic Next-Generation Sequencing to Diagnose Pneumocystis jirovecii Pneumonia in Kidney Transplantation Recipients. Annals of transplantation 2021, 26:e931059. Sun H, Wang F, Zhang M, Xu X, Li M, Gao W, Wu X, Han H, Wang Q, Yao G et al: Diagnostic Value of Bronchoalveolar Lavage Fluid Metagenomic Next-Generation Sequencing in Pneumocystis jirovecii Pneumonia in Non-HIV Immunosuppressed Patients. Frontiers in cellular and infection microbiology 2022, 12:872813. Duan J, Gao J, Liu Q, Sun M, Liu Y, Tan Y, Xing L: Characteristics and Prognostic Factors of Non-HIV Immunocompromised Patients With Pneumocystis Pneumonia Diagnosed by Metagenomics Next-Generation Sequencing. Frontiers in medicine 2022, 9:812698. Anesi JA, Baddley JW: Approach to the Solid Organ Transplant Patient with Suspected Fungal Infection. Infectious disease clinics of North America 2016, 30(1):277-296. Hoenigl M, Egger M, Price J, Krause R, Prattes J, White PL: Metagenomic Next-Generation Sequencing of Plasma for Diagnosis of COVID-19-Associated Pulmonary Aspergillosis. Journal of clinical microbiology 2023, 61(3):e0185922. Zhan W, Liu Q, Yang C, Zhao Z, Yang L, Wang Y, Feng J: Evaluation of metagenomic next-generation sequencing diagnosis for invasive pulmonary aspergillosis in immunocompromised and immunocompetent patients. Mycoses 2023, 66(4):331-337. Niu S, Liu D, Yang Y, Zhao L: Clinical utility of metagenomic next-generation sequencing in the diagnosis of invasive pulmonary aspergillosis in acute exacerbation of chronic obstructive pulmonary disease patients in the intensive care unit. Frontiers in cellular and infection microbiology 2024, 14:1397733. Liang M, Fan Y, Zhang D, Yang L, Wang X, Wang S, Xu J, Zhang J: Metagenomic next-generation sequencing for accurate diagnosis and management of lower respiratory tract infections. International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases 2022, 122:921-929. Zhang M, Wang Z, Wang J, Lv H, Xiao X, Lu W, Jin X, Meng J, Pu Y, Zhao M: The Value of Metagenomic Next-Generation Sequencing in Hematological Malignancy Patients with Febrile Neutropenia After Empiric Antibiotic Treatment Failure. Infection and drug resistance 2022, 15:3549-3559. Malinis M, Boucher HW, Practice ASTIDCo: Screening of donor and candidate prior to solid organ transplantation-Guidelines from the American Society of Transplantation Infectious Diseases Community of Practice. Clinical transplantation 2019, 33(9):e13548. Singh N, Huprikar S, Burdette SD, Morris MI, Blair JE, Wheat LJ, American Society of Transplantation IDCoPD-DFIWG: Donor-derived fungal infections in organ transplant recipients: guidelines of the American Society of Transplantation, infectious diseases community of practice. American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons 2012, 12(9):2414-2428. Oriol I, Sabe N, Tebe C, Veroux M, Boin I, Carratala J: Clinical impact of culture-positive preservation fluid on solid organ transplantation: A systematic review and meta-analysis. Transplantation reviews 2018, 32(2):85-91. Additional Declarations No competing interests reported. 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03:38:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5380360/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5380360/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70385468,"identity":"053aafe8-13e3-4664-8efb-964789726564","added_by":"auto","created_at":"2024-12-02 17:12:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":49988,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of sample types\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5380360/v1/1a5d18438b59e4ad1db08fd2.png"},{"id":70385592,"identity":"7e0852db-8caf-4970-bde1-8c3fd5fe1133","added_by":"auto","created_at":"2024-12-02 17:13:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81406,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of fungi detected by mNGS\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5380360/v1/d03f7fae28453669219d0110.png"},{"id":70385756,"identity":"5c0ae620-e183-4a28-914f-92bb2f0a550a","added_by":"auto","created_at":"2024-12-02 17:15:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":62578,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of fungi detected by CMTs\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5380360/v1/f58fcc537f8de7781ac5b89a.png"},{"id":70385449,"identity":"ab7fcf15-935e-450f-be73-5c920599a4dd","added_by":"auto","created_at":"2024-12-02 17:10:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":75628,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of fungi detected in drainage fluid and organ preservation fluids by mNGS\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5380360/v1/784732bf226527fd5494b873.png"},{"id":70385547,"identity":"57e63e9c-a43c-451d-8a24-5e5f13be6c67","added_by":"auto","created_at":"2024-12-02 17:13:13","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":54571,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5380360/v1/823164bd7edfc98a51f0fd00.png"},{"id":70385576,"identity":"e2e1ab23-79a1-45c9-a327-65bceff2f026","added_by":"auto","created_at":"2024-12-02 17:13:38","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":81954,"visible":true,"origin":"","legend":"\u003cp\u003eConsistency of mNGS and CMTs in fungal infections.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5380360/v1/e5568fee0a767a24cb33a4e0.png"},{"id":71916248,"identity":"9db03164-78d8-4c97-a09c-590d09c9147c","added_by":"auto","created_at":"2024-12-19 16:32:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1149152,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5380360/v1/715be9ff-1b59-4cc7-b00d-f9cae5b06748.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Metagenomic Next-Generation Sequencing Reveals the Profile of Fungal Infections in Kidney Transplant Recipients: a retrosective study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAfter kidney transplantation, patients need long-term and extensive use of immunosuppressants, and their immune function is impaired, which increases the risk of infection. There are three stages of infection after transplantation: (1) a phase up to 1 month characterized by nosocomial infections and donor-derived infections; (2) a phase of profound immunosuppression for up to 6 months associated with opportunistic infections; and (3) a phase of reduced immunosuppression with community-acquired and rare infectious agents. Infectious diseases are a major cause of morbidity and mortality after kidney transplantation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Fungal infections account for less than 5% of all renal transplant infections. The common fungi in kidney transplant patients were \u003cem\u003eCandida\u003c/em\u003e and \u003cem\u003eAspergillus\u003c/em\u003e [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The mortality rate of invasive aspergillosis is reported to be approximately 22% [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The overall mortality of invasive candidiasis at 12 months is reported to be 34% [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Donor-derived infection (DDI) is rare but causes significant morbidity and mortality. However, graft loss or death occurred in about one-third of recipients with DDI, with higher rates associated with fungal diseases [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The reported incidence of DDI is approximately 0.2% in all deceased donor organ transplantations [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Fungal infections account for approximately 15.5% of DDI [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, many questions regarding the prevention and early diagnosis of infections remain unanswered, and more research is needed in this area. The gold standard for the detection of invasive fungal infections is histopathological diagnosis or culture obtained by a sterile procedure. Unfortunately, histopathological testing is rarely available in a timely manner, whereas culture methods are insensitive and time-consuming. Although microscopic smears can identify Aspergillus hyphae faster than culture, it requires a large number of pathogens and experienced microbiologists, making it less feasible. Galactomannan (GM) test and Beta-D-Glucan (BDG) have been widely used for the diagnosis of fungal diseases, but their diagnostic ability is limited due to low fungal load in lesions, low probability of antigen appearance in blood, unstandardized sampling in different samples, antimicrobial treatment before sampling, and various other factors.\u003c/p\u003e \u003cp\u003eMetagenomic next generation sequencing (mNGS) makes up for the limitations of current diagnosis and is applied to pathogen detection in clinical practice. It can detect pathogens faster and more accurately, and is not affected by antibiotic exposure prior to detection. The results of studies on the diagnosis of fungal infections are controversial. Some studies showed that mNGS can improve the sensitivity of fungal infection and are less affected by antibiotic exposure prior to detection [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In contrast, identification of filamentous molds, such as \u003cem\u003eAspergillus\u003c/em\u003e, by mNGS remains challenging due to the difficulty of extracting DNA from thicker polysaccharide cell walls and the relatively low fungal load in BALF [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, few studies have investigated the use of mNGS in fungal infection in renal transplant patients, especially in DDI. We used the mNGS technique to identify pathogens from multiple samples of patients with possible fungal infection, evaluated the type and prevalence of pathogens found, and compared the results to those obtained with conventional methods. Moreover, we reported cases where mNGS assisted medication to improve the patient's condition.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients and Study Design\u003c/h2\u003e \u003cp\u003eThis is a retrospective study conducted in renal transplant recipients in the First Affiliated Hospital of Anhui Medical University between September 2021 and August 2023. Deceased donors are usually hospitalized in the intensive care unit (ICU) for long periods of time and have a high risk of infection, all organ preservation fluids from donors need to be both conventionally cultured and submitted to next-generation sequencing. A total of 395 samples from 234 patients were initially enrolled in this study. Patients were included if they met all the following criteria: (1) having smear, culture, and mNGS results; (2) mNGS or conventional microbiological tests (CMTs) identified the fungus. The following exclusion criteria were used: (1) mNGS and CMTs were not paired (i.e., not conducted simultaneously or on the same day); (2) the medical record was incomplete. Among these patients, a total of 75 samples from 66 patients were investigated in this study. This study was approved by the research ethics committee of the First Affiliated Hospital of Anhui Medical University. Individual consent for this retrospective analysis was waived.\u003c/p\u003e \u003cp\u003eSamples from patients were collected according to standard operating procedures. All the collected initial specimens were divided into two parts: one was used for subsequent mNGS sequencing, and the other was used for traditional culture. Patients with suspected fungal infections underwent serum (1,3)-β-D Glucan (BDG) and serum galactomannan testing. The standards and methods were implemented according to the routine microbial culture process, which was completed by the Clinical Laboratory of the First Affiliated Hospital of Anhui Medical University.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMicrobiologic Methods\u003c/h3\u003e\n\u003cp\u003eUsing conventional microbiologic methods, samples (blood, BALF, organ preservation solutions, drainage fluid, sputum) were examined by routine laboratory staining and cultures. Serum BDG was detected according to the manufacturer\u0026rsquo;s instructions. Both BALF and serum galactomannan detection were performed using a double-sandwich ELISA according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\n\u003ch3\u003eClinical Data Collection\u003c/h3\u003e\n\u003cp\u003eData, including demographics, laboratory test results, diagnosis, treatment, and clinical outcomes, were collected from the electronic medical records of the First Affiliated Hospital of Anhui Medical University through a standardized data collection form. Information of initial antibiotic and later adjustment based on mNGS results was also collected.\u003c/p\u003e\n\u003ch3\u003eMetagenomic Next-Generation Sequencing and Analysis\u003c/h3\u003e\n\u003cp\u003eSeventy-five samples were collected from different tissues, including 23 BALF samples, 23 drainage fluid samples, 13 blood samples, 15 organ preservation culture samples, and 1 sputum sample, and DNA alone or combined DNA and RNA sequencing was performed. The samples for mNGS were sent to testing companies for nucleic acid extraction, library construction, high-throughput sequencing, result presentation, and pathogen data interpretation.\u003c/p\u003e \u003cp\u003eThe samples were sealed aseptically and stored at -20 ℃ or transported on dry ice to Hugobiotech Co., Ltd., (Beijing, China) to perform mNGS detection immediately. The DNA was extracted and purified according to the instructions of QIAamp DNA Micro Kit (QIAGEN, Hilden, Germany). DNA concentration and quality were checked through Qubit 3.0 Fluoremeter (Invitrogen, Q33216) and agarose gel electrophoresis (Major Science, UVC1-1100).\u003c/p\u003e \u003cp\u003eDNA library construction was performed according to the Qiagen library construction kit (QIAseq Ultralow Input Library Kit) operating instructions. Library quality control was performed by Qubit 3.0 Fluoremeter (Invitrogen, Q33216) and Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, USA). Qualified DNA libraries with different barcode tags were pooled and then sequenced using the Illumina Nextseq 550 sequencing platform (Illumina, San Diego, USA) and a SE75bp sequencing strategy.\u003c/p\u003e \u003cp\u003eAfter obtaining the sequencing data, high quality data was generated by filtering out connectors, low quality, low complexity and shorter sequences. Next human-derived sequences matching to the human reference database (hg38) were removed by using SNAP software. The remaining data were then aligned to the microbial genome database using Burrow-Wheeler Alignment. This database contains a large collection of microbial genomes from NCBI containing more than 30,000 microorganisms, including 17,748 species of bacteria, 11,058 species of viruses, 1,134 species of fungi, and 308 species of parasites.\u003c/p\u003e\n\u003ch3\u003eCriteria for a Positive mNGS Result\u003c/h3\u003e\n\u003cp\u003e (1) For bacteria other than TB, fungi other than Cryptococcus and parasites: sequencing coverage in the top 10 of all pathogens detected and not detected in the negative control (NTC); or sample/NTC with an RPM (reads per million mapped reads) ratio greater than 10.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e(2) For viruses, tuberculosis and cryptococci: at least 1 specific sequence was detected and not detected in the NTC; or the RPM ratio of sample/NTC was greater than 5.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eContinuous data conforming to a normal distribution were reported as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation value; continuous data outside the normal distribution were presented as median and interquartile range (IQR). Categorical data were presented as the number of cases and percentage (%). Statistical analyses were performed using SPSS version 20.0 (IBM Corporation, Armonk, NY, USA). A \u003cem\u003ep\u003c/em\u003e-value less than 0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e1. Sample and Patient Characteristics\u003c/h2\u003e \u003cp\u003eBetween September 2021 and August 2023, a total of 75 samples from 66 patients with suspected fungal infections were enrolled in this study. All patients underwent mNGS and CMTs. The patient average age was 43.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6 years, and 39 (59.09%) patients were male. The most common comorbidity was anemia (53.03%, 35/66), followed by hypertension (40.91%, 27/66), agranulocytosis (16.67%, 11/66), chronic digestive system disease (11.4%, 16/140), and diabetes (15.15%, 10/66). Some patients are complicated with various comorbidities. The median length of hospital stay was 28.5 (20\u0026ndash;55) days. Additionally, 18 (27.27%) patients were admitted to the intensive care unit (ICU), and their median length of stay in ICU was 3.5 (1\u0026ndash;7) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The overall mortality rate was 15.15% (10/66). Among these 10 deceased patients, seven had fungal blood stream infection, and the other 3 patients died of \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e infection and myocardial infarction, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e bloodstream infection, and septic shock caused by COVID-19, respectively \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The characteristics of the 10 deceased patients are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. There were 16 patients with fever before treatment, and 6 patients still had fever after treatment \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Overall, the sample types consisted of drainage fluid [n\u0026thinsp;=\u0026thinsp;23 (30.67%)], followed by BALF [n\u0026thinsp;=\u0026thinsp;23 (30.67%)], organ preservation cultures [n\u0026thinsp;=\u0026thinsp;15 (20.00%)], blood [n\u0026thinsp;=\u0026thinsp;13 (17.33%)], and sputum [n\u0026thinsp;=\u0026thinsp;1 (1.33%)] \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe characteristics of died patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003esex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eyears\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHospital length of stay (days)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eICU length of stay (days)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCause of death\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSource of fungal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePathogen\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eAcinetobacter baumannii\u003c/em\u003e infection, Myocardial infarction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDrainage fluid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eCandida glabrata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCOVID-19, septic shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBlood, Drainage fluid, Organ preservation cultures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eRhizomucor pusillus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eInfectious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eRhizomucor pusillus, Aspergillus flavus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSeptic shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLichtheimia ramasa\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCerebral infarction, Infectious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBALF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eAspergillus flavus, Lichtheimia corymbifera, Rhizomucor pusillus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eLichtheimia corymbifera\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCOVID-19, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e infectious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOrgan preservation cultures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eAspergillus niger\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCOVID-19, Infectious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ePneumocystis jirovecii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCOVID-19, Infectious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ePneumocystis jirovecii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSeptic shock, COVID-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eCandida parapsilosis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSeptic shock, COVID-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBALF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eCandida parapsilosis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCases (n\u0026thinsp;=\u0026thinsp;66)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (40.91%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (15.15%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnemia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (53.03%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAgranulocytosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (16.67%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOutcomes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital LOS (days), median (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.5 (20, 55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eICU admission rate, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(27.27%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eICU LOS (days), median (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5 (1, 7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMortality, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(15.15%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody temperature\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eBefore\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eAfter\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNormal X\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e\u0026ge;\u0026thinsp;37.3◦C\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eICU( intensive care unit); LOS: length of stay\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2. Distribution of Fungal Species Detected by mNGS and CMTs\u003c/h2\u003e \u003cp\u003eA total of 21 fungal species were detected in the 66 patients, of which 17 species of fungus were detected by mNGS \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e The most common pathogens detected by mNGS were \u003cem\u003ePneumocystis\u003c/em\u003e (14), \u003cem\u003eCandida albicans\u003c/em\u003e (12), and \u003cem\u003eCandida parapsilosis\u003c/em\u003e (6). A total of 26 cases of \u003cem\u003eCandida\u003c/em\u003e spp., 10 cases of \u003cem\u003eAspergillus\u003c/em\u003e spp., and 6 cases of \u003cem\u003eMucor\u003c/em\u003e spp. were detected by mNGS. Among them, nine patients were infected with multiple fungus. The pathogens of multiple fungal infections were derived from BALF and blood in 7 cases and drainage fluid in 2 cases. The specific characteristics of the patients are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. For CMTs, eleven species of fungus were cultured, with \u003cem\u003eCandida albicans\u003c/em\u003e and \u003cem\u003eCandida glabrata\u003c/em\u003e being the most common. Only one patient was infected with multiple fungus \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. CMTs identified 12 cases of \u003cem\u003eCandida\u003c/em\u003e spp., 6 cases of \u003cem\u003eAspergillus\u003c/em\u003e spp., and 1 case of \u003cem\u003eAspergillus\u003c/em\u003e spp..\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe patients with multiple fungus.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYears\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHospital length of stay (days)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eICU length of stay (days)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eoutcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eSource of fungal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePathogen\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eDrainage fluid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003eCandida glabrata, Candida tropicalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eBALF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003eRhizomucor pusillus, aspergillus fumigatus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003edied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003eRhizomucor pusillus, Aspergillus flavus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003eCandida parapsilosis, Candida tropicalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eBALF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003eAspergillus fumigatus, Aspergillus flavus, Candida albicans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eBALF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003eAspergillus flavus, Aspergillus fumigatus, rhizopus oryzae, Rhizopusdelemar, Pneumocystis jirovecii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003edied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eBALF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003eAspergillus flavus, Lichtheimia corymbifera, Rhizomucor pusillus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eBALF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003eAspergillus flavus, aspergillus terreus, aspergillus niger\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eDrainage fluid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003eCandida glabrata, Candida albicans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDDI can result in significant morbidity and mortality. Pathogens in organ preservation fluid and drainage fluids may indicate donor-derived infection and reduce the risk of donor-derived fungal infection. Therefore, thirty-eight samples from organ preservation and drainage fluids were further analyzed. A total of 12 different fungal species were identified from 31 fungal strains using NGS, of which the most common was \u003cem\u003eCandida spp.\u003c/em\u003e, accounting for 70.97% (22/31) of all strains. Two of the patients were infected with multiple fungal species \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. For traditional cultures, sixteen cases of fungus were cultured, of which \u003cem\u003eCandida spp.\u003c/em\u003e accounted for 81.25% (13/16). Only one patient was infected with multiple fungus \u003cb\u003e(Fig.\u0026nbsp;5)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3. Mixed Infections Detected by mNGS\u003c/h2\u003e \u003cp\u003eMixed infection was defined when two or more infectious pathogens were detected. Mixed infection were detected in 57 samples by mNGS. The most frequent pattern of mixed infection was fungi and bacteria mixed infection (21/75, 28%), followed by bacteria, virus and fungi mixed infection (19/75, 25.33%). Fungal and viral co-infection was detected in 14 samples (14/75, 18.67%); eleven patients were diagnosed as fungi infection (11/75, 14.67%); the other three patients had mixed infections with \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e or atypical pathogens.\u003c/p\u003e \u003cp\u003eNotably, twenty seven mixed infection were detected in organ preservation cultures and drainage fluid. The most frequent pattern of mixed infection was bacteria and fungi (17/38, 44.74%), followed by bacteria, virus and fungi mixed infection (8/38, 21.05%). Nine samples were dentified two or more fungal species, among which 3 patients were infected with two kinds of \u003cem\u003eCandida\u003c/em\u003e spp., four patients were infected with \u003cem\u003eAspergillus\u003c/em\u003e spp., \u003cem\u003eMucor\u003c/em\u003e spp., one patient was infected with a variety of \u003cem\u003eAspergillus\u003c/em\u003e spp. and one patient was infected with \u003cem\u003eAspergillus\u003c/em\u003e spp. and \u003cem\u003eCandida\u003c/em\u003e spp.. The samples of 9 cases were from 5 alveolar lavage fluid, 2 cases from blood, and 2 cases from drainage fluid. Among them, two cases resulted in death: one due to a mixed infection of mucormycosis and aspergillosis, and the other due to multiple mucormycosis infections \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4. Comparison of the Diagnostic Performance of mNGS and CMTs\u003c/h2\u003e \u003cp\u003eAll samples underwent both mNGS and CMTs. In this study, the mNGS results for 68 of 75 (90.67%) patients were positive for fungus, which was much superior to the CMTs of 26.67% (20/75). A comparison of the diagnostic results from mNGS with CMTs is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In our study, the results of mNGS and CMTs were both positive in 13 (13/75, 13.33%) cases. A total of 55 (55/75, 73.33%) cases were positive by mNGS only, but 7 (7/75, 9.33%) cases were positive by CMTs only. Additionally, for 13 double-positive cases, the results between mNGS and CMTs were consistent in 7 (7/75, 9.33%), partially consistent in 3 (3/75, 4%), and completely inconsistent in 3 (3/75, 4%) (\u003cb\u003eFigure. 6\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eOverall, mNGS identified more candida (26 vs 12), aspergillus (10 vs 4), and mucor (6 vs 2) organisms compared with CMTs. The pathogens missed by conventional culture were \u003cem\u003epneumocystis jirovecii\u003c/em\u003e (14), \u003cem\u003ecandida guilliermondii\u003c/em\u003e (1), \u003cem\u003easpergillus niger\u003c/em\u003e (1), \u003cem\u003erhizopusdelemar\u003c/em\u003e (1), \u003cem\u003elichtheimia ramasa\u003c/em\u003e (1), \u003cem\u003elichtheimia corymbifera\u003c/em\u003e (1), \u003cem\u003ecryptococcus albidus\u003c/em\u003e (1), \u003cem\u003etalaromyces marneffei\u003c/em\u003e (1), \u003cem\u003etalaromyces marneffei\u003c/em\u003e (1), \u003cem\u003ealternaria alternata\u003c/em\u003e (1), \u003cem\u003erhizopus oryzae\u003c/em\u003e (1), and \u003cem\u003easpergillus terreus\u003c/em\u003e (1). On the contrary, the pathogens missed by mNGS included yeast (1), \u003cem\u003easpergillus sydowii\u003c/em\u003e (1), and \u003cem\u003easpergillus versicolor\u003c/em\u003e (1). In summary, mNGS identified pathogens which were relatively complex or undetectable under culture conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e5. Donor-derived Fungal Infections\u003c/h2\u003e \u003cp\u003eFrom September 2021 to August 2023, there were 146 patients who underwent kidney transplantation from donors after cardiac death. Organ preservation fluid and/or drainage fluid from all patients underwent mNGS and CMTs. A total of 248 samples of organ preservation fluid and drainage fluid were collected, with fungi detected in 41 samples from 35 patients. Fungi from donors were identified in 11 (11/146, 7.5%) patients, including 10 cases of \u003cem\u003eCandida spp.\u003c/em\u003e and 1 case of \u003cem\u003eMucor\u003c/em\u003e spp.. Among these 11 patients, two cases resulted in death: one due to bacterial infection and the other due to disseminated mucormycosis. No deaths due to \u003cem\u003eCandida\u003c/em\u003e infection were observed in the patients. Detection methods included reliance on mNGS in 4 cases, CMTs in 4 cases, and both mNGS and CMTs in the remaining 3 cases \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe characteristics of donor-derived infections\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYears\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHospital length of stay (days)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eoutcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePathogen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDetection method\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDeid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCandida glabrata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNGS, CMTs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCandida glabrata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNGS, CMTs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCandida tropicalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCMTs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCandida glabrata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNGS, CMTs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCandida glabrata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCMTs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDeid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eRhizomucor pusillus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNGS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCandida albicans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNGS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCandida albicans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNGS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCandida albicans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNGS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCandida glabrata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCMTs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eCandida albicans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCMTs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e6. Impacts of mNGS on the Application of Antibiotic Treatment\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows records of antimicrobial treatment of 66 patients with mycosis during hospitalization. We evaluated the impact of mNGS on antimicrobial therapy. Nine patients were not initially treated with antifungal agents, and the other patients were initially treated with different antifungal agents empirically. Antifungal therapy was changed in 42.4% (28/66) of patients based on mNGS results. In most of the cases without adjustment, treatment was not adjusted due to previous empirical caspofungin covering the pathogens detected. For patients mNGS provided positive identification of \u003cem\u003easpergillus in\u003c/em\u003e 10 cases, leading to the addition of voriconazole in these patients. For patients with \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e confirmed by mNGS, therapeutic doses of compound sulfamethoxazole were added in 10 patients. As we observed, 13 patients discontinued caspofungin according to mNGS.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAdjustment of antibiotic treatment according to mNGS results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAntimicrobials\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePre-mNGS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eAfter-mNGS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReduce fungal agents\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIncrease fungal agents\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVoriconazole\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eposaconazole\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eisavuconazole\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCaspofungin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAmphotericin B\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTMP-SMZ\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(therapeutic dose)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo change\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eEffective management of post-transplant infection relies on prevention, early diagnosis, and specific therapy. In the field of organ transplantation, fungal infections, although less common than bacterial infections, have a higher mortality rate [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The incidence of invasive fungal infections (IFIs) varies across different types of organ transplants, ranging from 1.3\u0026ndash;11.6% [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Some studies reported that the overall mortality rate for kidney transplant recipients with fungal infections ranged between 15% and 50% [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Despite numerous studies investigating one or more pathogenic infections following renal transplantation, there is a lack of research revealing fungal infections in renal transplant patients using mNGS techniques. For this, detailed information on the incidence, microbial etiology, and timeline of infections is crucial. In this study, we performed a comprehensive and systematic analysis of fungal infections after kidney transplantation using mNGS and compared them with CMTs. This study included 395 NGS samples collected over the past two years, covering kidney transplants from related donors and DCD donors. Our study revealed differences between mNGS and CMTs in fungal detection and highlighted the potential advantages of mNGS in clinical applications. We analyzed the detected fungal species, mixed infections, fungal infections from donor sources, and the impact of mNGS on fungal treatment.\u003c/p\u003e \u003cp\u003eThus far, fungal smear and culture, serum (1,3)-b-D-glucan (G) or galactomannan (GM) tests, and PCR are used in the microbiological analysis of fungi. Compared with other tests, traditional culture methods can provide information on drug susceptibility. However, these methods have certain limitations, such as low positive rates, low sensitivity, high false-positive rates, and long processing times. Kidney transplant patients often use multiple medications, which may affect the accuracy of the aforementioned diagnostic methods. Conventional blood cultures may fail to diagnose candidiasis in up to 25\u0026ndash;50% of cases [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. mNGS, with the characteristics of fast detection speed, high sensitivity, and broad coverage, can effectively compensate for traditional methods.\u003c/p\u003e \u003cp\u003eCurrently, the most reported tests were mNGS on blood, alveolar lavage fluid, and cerebrospinal fluid, which can rapidly and accurately identify microbial species, improve clinical diagnosis, and guide effective clinical treatment. A retrospective cohort study found that mNGS had a higher positivity rate than blood cultures (58.5% vs. 21.9%) and was able to identify multiple species, including bacteria, fungi, and viruses, in a cohort of ICU patients [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. A study involving patients with lower respiratory tract infections demonstrated that mNGS identified pathogens in 65% of cases, significantly higher than the 20% detection rate of CMTs [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In cases of invasive pulmonary fungal infection and early postoperative pulmonary infection following lung transplantation, the diagnostic performance of mNGS surpasses CMTs [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. For bloodstream fungal infections, whether in liver transplant patients or those with sepsis, the use of mNGS significantly improves the detection rate compared to CMTs [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These studies all indicate that mNGS has clear advantages in the diagnosis of fungal infections. Our study also showed that the fungal detection rate of mNGS in kidney transplant patients was significantly higher than that of CMTs (90.67% vs. 26.67%). Research suggested that mNGS exhibited better performance than culture with regard to fungal detection, but the difference was not significant in Aspergillus detection [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Peng et al. concluded that CMTs were more effective than mNGS for fungal infections in the lung [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Therefore, the diagnostic value of mNGS in fungal infections remains controversial.\u003c/p\u003e \u003cp\u003emNGS can detect rare and opportunistic fungi that might be missed by traditional methods, such as \u003cem\u003ePneumocystis\u003c/em\u003e. This capability is particularly important in immunocompromised patients, where infections with uncommon fungi can occur. Wang et al. reported that the most commonly fungi detected by mNGS in pulmonary fungal infections were \u003cem\u003eCandida albicans\u003c/em\u003e, \u003cem\u003eAspergillus fumigatus\u003c/em\u003e and \u003cem\u003ePneumocystis\u003c/em\u003e [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Another study showed that the most commonly isolated fungi species were \u003cem\u003eAspergillus\u003c/em\u003e, \u003cem\u003ePneumocystis\u003c/em\u003e, and \u003cem\u003eRhizopus\u003c/em\u003e detected by mNGS in pulmonary fungal infections [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In our study, the most common pathogens detected by mNGS were \u003cem\u003ePneumocystis\u003c/em\u003e (14/75, 18.67%), \u003cem\u003eCandida spp.\u003c/em\u003e (26/75, 34.67%), \u003cem\u003eAspergillus spp.\u003c/em\u003e (10/75, 13.33%), and \u003cem\u003eMucormyces spp.\u003c/em\u003e (6/75, 8%). Additionally, among patients with multiple fungal infections, mixed infections involving \u003cem\u003eCandida\u003c/em\u003e, \u003cem\u003eAspergillus\u003c/em\u003e, and \u003cem\u003eMucor\u003c/em\u003e species were predominant. Overall, these studies indicate that mNGS detects more \u003cem\u003eCandida\u003c/em\u003e, \u003cem\u003ePneumocystis\u003c/em\u003e, \u003cem\u003eAspergillus\u003c/em\u003e, and \u003cem\u003eMucorales\u003c/em\u003e compared to CMTs. In particular, \u003cem\u003ePneumocystis\u003c/em\u003e cannot be detected by CMTs, one of the important infections in renal transplant patients. In our study, \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e, \u003cem\u003eAspergillus spp.\u003c/em\u003e, and \u003cem\u003eMucor spp.\u003c/em\u003e were predominantly isolated from pulmonary infections. As a new pathogen detection strategy, mNGS reached a sensitivity rate of 100% in the diagnosis of \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e, according to a study of HIV-negative immunocompromised patients [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Other studies have also demonstrated that NGS exhibits higher sensitivity and specificity in detecting \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e compared to GMS and BDG [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. \u003cem\u003eCandida spp.\u003c/em\u003e is the most frequent fungal pathogen in nearly all solid organ transplants. Generally, the onset of invasive candidiasis occurs earlier than other invasive fungal infections, typically within the first few months post-transplantation. Approximately 50% of the isolates involve \u003cem\u003eCandida albicans\u003c/em\u003e, while \u003cem\u003eCandida glabrata\u003c/em\u003e is the most common non-\u003cem\u003ealbican Candida\u003c/em\u003e species [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The findings of our study are consistent with previous research, regardless of whether CMTs or mNGS were used. Invasive \u003cem\u003easpergillosis\u003c/em\u003e is one of the most relevant fungal infections in solid organ transplantation recipients. It occurs in 1\u0026ndash;15% of the SOT patients, and currently reported mortality rates of invasive aspergillosis are approximately 22% despite novel treatment modalities. In lung transplant recipients, invasive pulmonary disease has an even higher mortality rate of 67\u0026ndash;82% [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In recent years, studies have demonstrated that mNGS exhibits superior diagnostic performance for \u003cem\u003eAspergillus\u003c/em\u003e infections compared to traditional methods, particularly in immunosuppressed patients [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Our study also indicates that the detection rate of aspergillosis using mNGS is superior to that of CMTs (10 vs 3).\u003c/p\u003e \u003cp\u003eFurthermore, mNGS performed well in identifying fungal species and co-pathogens, indicating that mNGS may have a valuable role in guiding antimicrobial therapy. Numerous studies have confirmed that mNGS has obvious advantages in detecting mixed pathogen infections [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. And we also found that mixed infections were detected in 57 samples by mNGS. Additionally, NGS identified multiple fungal infections in 9 samples, whereas CMTs detected only one case. The comprehensive fungal profile obtained through mNGS offers valuable insights into the epidemiology of fungal infections in transplant recipients.\u003c/p\u003e \u003cp\u003eThe effect of antibacterial drugs on mNGS is less than CMTs, and the treatment strategies can be adjusted according to these results. As is well known, accurate identification of strains is crucial for guiding antifungal treatment. A study on lower respiratory tract infections demonstrated that mNGS could alter the treatment regimen in 39.3% of patients [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. According to another study, antibiotics were adjusted in 45.1% of patients based on mNGS [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Yan Shi et al. highlighted the favorable prognosis resulting from antifungal drug changes based on mNGS results [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Our study showed that antifungal therapy was changed in 42.4% (28/66) of patients based on mNGS results. The primary medication adjustments are as follows: reduction of caspofungin, increase of voriconazole, and adjustment of the trimethoprim-sulfamethoxazole dosage. The rapid results of mNGS can provide evidence for the next step in treatment, especially to avoid overuse of antibiotics and improve patient outcomes.\u003c/p\u003e \u003cp\u003eCompared to bacterial and viral infections, donor-derived fungal infections are less common but often more severe and potentially life-threatening when they occur. The overall incidence of DDI was 0.14%. Donor-derived fungal infections accounted for 22%, which is lower than bacterial infections (30%) and viral infections (approximately 31%). The overall DDI-associated mortality was 15% [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Blood and urine cultures are recommended for all deceased donors. The guidelines generally do not recommend culturing preservation fluid. If \u003cem\u003eCandida\u003c/em\u003e is detected in the kidney, liver, or pancreas, consider adding fungal cultures of the recipient's urine (kidney recipient), blood, and drainage fluid [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In our study, culture results for donors were not provided, but both NGS and CMTs were performed on kidney lavage fluid and drainage fluid, while CMTs were also conducted on the recipient's blood and urine. A comprehensive systematic review and meta-analysis previously reported an overall organ preservation fluids culture positivity rate of 37%. The positivity of organ preservation fluid cultures was not a strong indicator of transmission, regardless of the allograft type, with an overall incidence of organ preservation fluid-related DDI of 4% [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In our study, the positivity rate of organ preservation fluid fungi was 8.9% (13/146). Fungi from donors were identified in 11 (11/146, 7.5%) patients. The donor-derived fungal infection rate we observed is higher than previously reported rates, which may be attributed to our use of both NGS and CMTs for detection. Previous studies have shown that the most common fungal infections originating from donors are caused by \u003cem\u003eCandida\u003c/em\u003e (24%), followed by \u003cem\u003eCryptococcus\u003c/em\u003e (20%) and \u003cem\u003eAspergillus\u003c/em\u003e (13%), with \u003cem\u003emucormycosis\u003c/em\u003e being relatively rare [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Our study identified 11 cases (7.5%) of donor-derived fungal infections, of which 10 were due to \u003cem\u003eCandida\u003c/em\u003e and 1 was due to \u003cem\u003emucormycosis\u003c/em\u003e. Additionally, previous studies have reported mortality rates for donor-derived fungal infections as follows: \u003cem\u003eCandida\u003c/em\u003e at 10.0%, \u003cem\u003eAspergillus\u003c/em\u003e at 33.3%, and \u003cem\u003eCryptococcus\u003c/em\u003e at 7.7% [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In our study, ten patients did not die from \u003cem\u003eCandida\u003c/em\u003e infections, and one patient died due to \u003cem\u003emucormycosis\u003c/em\u003e. No cases of donor-derived \u003cem\u003eAspergillus\u003c/em\u003e or \u003cem\u003eCryptococcus\u003c/em\u003e infections were observed in our study, likely because lung transplants are more prone to spreading these infections, whereas our study focused on kidney transplants. The most common donor-derived fungal infection in our study was \u003cem\u003eCandida\u003c/em\u003e (6.8%), consistent with previous research findings. Previously, nephrectomy was recommended for patients with lavage fluid positive for \u003cem\u003eCandida\u003c/em\u003e species. However, recent data suggest that recipients of organs from \u003cem\u003eCandida\u003c/em\u003e culture-positive donors require aggressive treatment. Current guidelines recommend 14 days of aggressive treatment with fluconazole or echinocandin in cases of unknown species or suspected azole resistance [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. At our transplant center, for kidneys obtained from donation after circulatory death, recipients routinely receive caspofungin postoperatively for fungal prophylaxis. Subsequent adjustments to antimicrobial therapy will be based on etiological evidence.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eLIMITATION\u003c/h2\u003e \u003cp\u003eThe present study had several limitations. First, in our study, traditional detection methods were not comprehensive, such as the G test, GM test, cryptococcal capsular polysaccharide antigen test, and Grocott methenamine silver stain. Fungi like \u003cem\u003eMucor\u003c/em\u003e and \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e are difficult to culture, and these detection methods help diagnose these fungi. Therefore, it is impossible to compare the diagnostic performance of mNGS with these methods. Second, mNGS cannot distinguish between infection and colonization, and it is necessary to consider the patient's clinical features, imaging characteristics, and other testing methods comprehensively. Third, mNGS does not provide susceptibility results, although fungal resistance is not as complex as bacterial resistance. Fourth, the cell wall of \u003cem\u003eAspergillus\u003c/em\u003e is thick, and nucleic acids are difficult to release, which causes a false-negative result. Finally, this study is retrospective, and the diagnostic value of mNGS in fungal infections among kidney transplant patients has not been fully studied. Further multicenter prospective studies with large sample sizes are needed.\u003c/p\u003e \u003cp\u003eIn summary, although NGS offers advantages such as rapid and sensitive detection of fungal infections in kidney transplant patients, particularly for pathogens that cannot be cultured using traditional methods, it also has several unavoidable drawbacks. Standardizing its indications, optimal timing of use, and the diagnostic approach for various pathogens may need to be tailored to the specific circumstances of each patient.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by National Natural Science Foundation of China (82470783).\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWQ, DHD and LGY are responsible for the conception and design, development of methodology, data analysis and interpretation, writing, review, and revision of the manuscript. HZY contributed to the study concept and design, interpretation of the data and revision of the manuscript. ZYZ contributed to \u0026nbsp;conception, design and data analysis. All authors have read and approved the final manuscript.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFishman JA: Infection in Organ Transplantation. American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons 2017, 17(4):856-879.\u003c/li\u003e\n\u003cli\u003eFiorentino M, Pesce F, Schena A, Simone S, Castellano G, Gesualdo L: Updates on urinary tract infections in kidney transplantation. Journal of nephrology 2019, 32(5):751-761.\u003c/li\u003e\n\u003cli\u003eSommerer C, Schroter I, Gruneberg K, Schindler D, Behnisch R, Morath C, Renders L, Heemann U, Schnitzler P, Melk A et al: Incidences of Infectious Events in a Renal Transplant Cohort of the German Center of Infectious Diseases (DZIF). 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The Journal of antimicrobial chemotherapy 2016, 71(suppl 2):ii13-ii22.\u003c/li\u003e\n\u003cli\u003eOverbeek R, Leitl CJ, Stoll SE, Wetsch WA, Kammerer T, Mathes A, Bottiger BW, Seifert H, Hart D, Dusse F: The Value of Next-Generation Sequencing in Diagnosis and Therapy of Critically Ill Patients with Suspected Bloodstream Infections: A Retrospective Cohort Study. Journal of clinical medicine 2024, 13(2).\u003c/li\u003e\n\u003cli\u003eChen H, Yin Y, Gao H, Guo Y, Dong Z, Wang X, Zhang Y, Yang S, Peng Q, Liu Y et al: Clinical Utility of In-house Metagenomic Next-generation Sequencing for the Diagnosis of Lower Respiratory Tract Infections and Analysis of the Host Immune Response. 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Journal of clinical microbiology 2023, 61(3):e0185922.\u003c/li\u003e\n\u003cli\u003eZhan W, Liu Q, Yang C, Zhao Z, Yang L, Wang Y, Feng J: Evaluation of metagenomic next-generation sequencing diagnosis for invasive pulmonary aspergillosis in immunocompromised and immunocompetent patients. Mycoses 2023, 66(4):331-337.\u003c/li\u003e\n\u003cli\u003eNiu S, Liu D, Yang Y, Zhao L: Clinical utility of metagenomic next-generation sequencing in the diagnosis of invasive pulmonary aspergillosis in acute exacerbation of chronic obstructive pulmonary disease patients in the intensive care unit. Frontiers in cellular and infection microbiology 2024, 14:1397733.\u003c/li\u003e\n\u003cli\u003eLiang M, Fan Y, Zhang D, Yang L, Wang X, Wang S, Xu J, Zhang J: Metagenomic next-generation sequencing for accurate diagnosis and management of lower respiratory tract infections. International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases 2022, 122:921-929.\u003c/li\u003e\n\u003cli\u003eZhang M, Wang Z, Wang J, Lv H, Xiao X, Lu W, Jin X, Meng J, Pu Y, Zhao M: The Value of Metagenomic Next-Generation Sequencing in Hematological Malignancy Patients with Febrile Neutropenia After Empiric Antibiotic Treatment Failure. Infection and drug resistance 2022, 15:3549-3559.\u003c/li\u003e\n\u003cli\u003eMalinis M, Boucher HW, Practice ASTIDCo: Screening of donor and candidate prior to solid organ transplantation-Guidelines from the American Society of Transplantation Infectious Diseases Community of Practice. Clinical transplantation 2019, 33(9):e13548.\u003c/li\u003e\n\u003cli\u003eSingh N, Huprikar S, Burdette SD, Morris MI, Blair JE, Wheat LJ, American Society of Transplantation IDCoPD-DFIWG: Donor-derived fungal infections in organ transplant recipients: guidelines of the American Society of Transplantation, infectious diseases community of practice. American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons 2012, 12(9):2414-2428.\u003c/li\u003e\n\u003cli\u003eOriol I, Sabe N, Tebe C, Veroux M, Boin I, Carratala J: Clinical impact of culture-positive preservation fluid on solid organ transplantation: A systematic review and meta-analysis. Transplantation reviews 2018, 32(2):85-91.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"metagenomic next-generation sequencing (mNGS), fungal infections, kidney transplantation, donor-derived infection, antibiotic Treatment","lastPublishedDoi":"10.21203/rs.3.rs-5380360/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5380360/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eInfection is an important cause of death after kidney transplant surgery. Although fungal infections are relatively rare, they have low detection rates and high mortality rates. The value of metagenomic next-generation sequencing (mNGS) in kidney transplant patients with fungal infections remains to be studied, especially in diagnosis and to guide the use of antibiotics.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eFrom September 2021 to August 2023, a total of 234 patients after kidney transplantation were enrolled, and data of 66 patients with suspected fungal infections were collected. The pathogen detection performance of mNGS and conventional microbiological tests (CMTs) were compared. The impacts of mNGS and CMTs on treatment adjustment were also assessed. Finally, we explored the value of mNGS in donor-derived infections.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 21 fungal species were detected in the 66 patients, of which 18 species of fungus were detected by mNGS and 10 species of fungus were detected by CMTs. mNGS was significantly higher than culture in total positive rate (90.67% vs. 26.67%), especially for multiple fungal infections (9vs0). mNGS identified more \u003cem\u003ecandida\u003c/em\u003e (26vs12), \u003cem\u003epneumocystis jirovecii\u003c/em\u003e (14vs0), \u003cem\u003easpergillus\u003c/em\u003e (10vs4), \u003cem\u003emucor\u003c/em\u003e (6vs2) organisms compared with CMTs. Fungi from donors were identified in 11(6.7%) patients, including 10 cases of \u003cem\u003eCandida spp.\u003c/em\u003e and 1 case of \u003cem\u003eMucor\u003c/em\u003e spp. The anti-infection therapies were adjusted in 28 (24.4%) cases by mNGS.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe mNGS technique showed distinct advantages in detecting fungal infections in kidney transplant patients, which can guide anti-infection strategies and protect grafts. In addition, it has a good identification value for fungal infections from donor sources.\u003c/p\u003e","manuscriptTitle":"Metagenomic Next-Generation Sequencing Reveals the Profile of Fungal Infections in Kidney Transplant Recipients: a retrosective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-02 16:18:40","doi":"10.21203/rs.3.rs-5380360/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"41fc3247-63ae-461c-8dec-b11df7dfd8a2","owner":[],"postedDate":"December 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-19T16:24:17+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-02 16:18:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5380360","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5380360","identity":"rs-5380360","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}