| ObjectiveFungi are widely distributed in nature. Up to now, there are about 100,000 kinds of fungi, 300 species of which are pathogenic to humans. Besides, the growth characteristics, clinical features and drug-resistance among different fungi are distinct. In recent years, pathogenic infections caused by fungi become the key cause of death for immunocompromised patients, due to the widespread use of broad-spectrum antimicrobial drugs, radiotherapy and chemotherapy in cancer patients, organ transplantation, and to carry out invasive technical operations. In addition, patients with liver disease are susceptible to fungal infections as a result of hypoalbuminemia, monocyte-macrophage system function severely impaired, leukocyte adhesion and chemotaxis phagocytosis in the intestine and other reasons. Meanwhile, with a large number of antifungal drug used, the drug-resistance of fungi presents a challenge in clinic. Therefore, the accurate identification of fungal infection and drug-resistance is important to clinical treatment.Fungus is characterized by slow growth, and the traditional culture and identification method required a longer time, usually 3-7 days. Besides, the diversity of fungi makes identification difficult, which restricts the early diagnosis and targeted therapies. Matrix-Assisted Laser-Desorption/Ionization Time of Flight Mass Spectrometry(MALDI-TOF MS) is an emerging diagnostic technology in recent years, which can identify viruses, bacteria, mycobacteria and so on through direct detection of biomarkers. It is simple, fast, high accuracy and low cost. However, the accuracy of identification for fungi by MS is controversial, mainly due to the thickness of fungal cell wall and pretreatment methods.The present study compares the results of fungi identified by MS with biochemical method and molecular biology to estimates the ability of identification by MS. It could provide a reliable basis for the rapid diagnosis of clinical fungal infections. In addition, we collected the data of fungal infection in patients with liver disease to find the feature of etiology composition and growth trends of pathogenic fungal infections in patients with liver disease; we also analyzed the drug-resistance to different types of antifungal drugs to guide application of antifungal drug. MethodsFungi strains were isolated from 2236 hospitalized patients with liver disease in our hospital between 2011 and 2014, and the clinical data were also collected(the fungus isolated from the same part of the same patient within 7 days were without double counting). We analysis its vulnerable populations, the site of infection and bacterial distribution Features and so on. The K-B method was performed for 2236 of fungi with fluconazole, amphotericin B, itraconazole, voriconazole to find the drug-resistance. And 327 fungal strains were identified by mass spectrometer(Bruker’s Microflex), then compared the results with that of VITEK-2(yeast-like fungus) and microscope(filamentous fungi). Molecular biology methods were used to confirm the identification. ResultsThe results showed that fungal infections were mainly in male patients, and the ratio(male/female) was 1.73:1. The average age was 54 ± 15 years. Fungal infections were more often in patients with liver cirrhosis decompensation, liver and severe hepatitis patients. The proportion of patients with decompensated cirrhosis was 69.65%, while liver cancer patients accounted for 16.97%. Number of fungi isolated increased from 61 in 2011 to 1222 in 2014, an increase of 19.03 times. The total number of fungi isolated was 2236, and the number of yeast-like fungi was 1889(84.48%), while the number of filamentous fungi was 347(15.52%). Yeast-like fungi was dominant in all isolations, the rate was 63.93%, 85.42%, 84.92%, 85.02%, respectively in the year of 2011, 2012, 2013, 2014. The kinds of fungal isolated were also increased from 15 species to 30 species. Among fungal species, topped as Candida Albicans(52.64%), followed by Candida tropicalis(13.86%) and Aspergillus fumigatus(12.03%). Infection was more often in the respiratory tract, accounting for 66.41%, and yeast-like fungi accounted for 52.24% while filamentous fungi accounted for 14.18%. Candida Albicans was the main species isolated, accounting for 35.15%, followed by Aspergillus fumigatus accounted for 11.09 %. Fungal infections are characterized by Ascites and drainage infections in patients with liver disease, the separation was 13.91%, with Candida Albicans species dominated(8.32%). Besides, the drug-resistance rates of filamentous fungi are generally higher than yeast-like fungi during the last four years in our hospital(p<0.05). The drug-resistance rates of yeast-like fungi to fluconazole, amphotericin, itraconazole and voriconazole were 11.96%, 2.54%, 1.96% and 0.69%, respectively, while the drug-resistance rates of filamentous fungi were 95.97%, 17.29%, 6.05% and 4.61%.The results of 327 fungi identified by MS showed that identification of Candida at species level(score> 2.0) was 90.31%, and the genus level(score> 1.7) was 98.68% according to their score. Identification rate of Filamentous fungi by MS at species level were 74%, while that was 94% at the genus level. The accuracy of identification of Aspergillus could reach to 96.74%.Fungi could be identified by MS at species level and be divided into subgroup. For example, Candida parapsilosis, Candida metapsilosis and Candida orthopsilosis could be distinguished. For the culture bottles containing only one type of fungal, the result of direct protein identification was the same with identification of cultivation of bacteria colonies. Besides, we found that identification of fungal by mass spectrometry just needs 20 min. In addition, MS could simultaneously detect multiple strains of bacteria, so it is considered as the best method for the identification of fungus. ConclusionsIn recent years, pathogenic infections caused by fungi are increasing in the patients with liver disease. Therefore, we should pay attention to the infection in the patients with drainage and other sterile body fluids, and focus on indwelling tube or the invasive treatment. The Clinical antifungal therapy should be based on the results of species identification and susceptibility in microbiology laboratory, taking into account of the toxicity of the liver. Fungal species could be well identified by MS, especially in identification of yeasts and Aspergillus. This method lowers the subjectivity of microscopy, and fully meets the needs of clinical microbiology laboratories. MS has a broad clinical application in the diagnosis of fungal infections. For unusual fungi, we could construct the personalized database according to the characteristics of fungal infections in our hospital, which improve timeliness and accuracy of detection of the fungus. It may give clinic a better guidance to control of fungal infections effectively. |
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