(1) Background: Little is known about the impact of urinary microflora, in particular, its effects on side effects after radiotherapy. The use of mass spectrometry identification method (MALDI) may bring a new look at the issue of the composition and significance of the urinary microbiome. This study aimed to use the mass spectrometry identification method (MALDI) to identify the microbiome of urine samples collected from 50 irradiated prostate cancer patients. (2) Methods: Blood and urine samples were collected before gold marker implantation, at the start and last day of radiotherapy, 1, 4 months after. Patients do not always collect the urine from the midstream; therefore, samples were collected from the first void and midstream in 12 patients for MALDI analysis; in the remaining 38 patients—from the midstream void for MALDI and biochemical analysis. (3) Results: Microorganisms were present in 140/181 urine samples. We found 33 different species 3G(−) and 30G(+). The most frequently isolated strains were: Staphylococcus haemolyticus, Staphylococcus epidermidis, Staphylococcus hominis, Enterococcus faecalis, and Micrococcus luteus. When comparing the type of urine samples, bacteria were more common in samples from the first-void urine than from the midstream one. The absence of bacteria was found in 12.2% of samples from the first-void urine and in 24.7% from the midstream. There was no difference in the total incidence of species between streams (p = 0.85). Before fiducial implantation, the total number of detected bacterial species was significantly higher in comparison to the end of radiotherapy (p = 0.038), indicating that the administered therapy resulted in depleting the local microbiome. One month after radiotherapy, an increase in the number of isolated bacteria was observed. The number of bacterial species in urine did not correlate with blood parameters. The presence of leukocytes (p = 0.013) and proteins (p = 0.004) in urine was related to a greater variety of bacteria found in urine specimens. (4) Conclusions: We obtained a similar spectrum of bacteria from the initial and middle urine streams. We also showed that there is a change in bacteria species affected by the treatment of prostate cancer patients, with both antibiotics before gold fiducial implantation and radiotherapy.
The present study attempted to apply the capillary electrophoresis technique for the fractionation and separation of S. Staphylococcus hominis and Escherichia coli bacteria isolated from urine samples and the detection of migrated fraction with spectrometric method. This involved the selection of suitable conditions for separation as well as the identification of pathogens. The result of the research was the separation of Gram‐negative and Gram‐positive bacteria, as well as their subsequent identification by matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry using two different approaches (culture of fractions on an agar plate and direct analysis of the collected fractions). The preliminary results provide a solid basis for further research on the use of electromigration techniques with LDI detection to identify pathogens such as bacteria and viruses in biological samples.
In the present research, the MALDI-TOF MS technique was applied as a tool to rapidly identify the salivary microbiome. In this fact, it has been monitored the changes occurred in molecular profiles under different antibiotic therapy. Significant changes in the composition of the salivary microbiota were noticed not only in relation to the non antibiotic (non-AT) and antibiotic treatment (AT) groups, but also to the used media, the antibiotic therapy and co-existed microbiota. Each antibiotic generates specific changes in molecular profiles. The highest number of bacterial species was isolated in the universal culture medium (72%) followed by the selective medium (48% and 38%). In the case of non-AT patients, the prevalence of Streptococcus salivarius (25%), Streptococcus vestibularis (19%), Streptococcus oralis (13%), and Staphylococcus aureus (6%) was identified while in the case of AT, Streptococcus salivarius (11%), Streptococcus parasanguinis (11%), Staphylococcus epidermidis (12%), Enterococcus faecalis (9%), Staphylococcus hominis (8%), and Candida albicans (6%) were identified. Notable to specified that the Candida albicans was noticed only in AT samples, indicating a negative impact on the antibiotic therapy. The accuracy of the MALDI-TOF MS technique was performed by the 16S rRNA gene sequencing analysis—as a reference method. Conclusively, such an approach highlighted in the present study can help in developing the methods enabling a faster diagnosis of disease changes at the cellular level before clinical changes occur. Once the MALDI tool allows for the distinguishing of the microbiota of non-AT and AT, it may enable to monitor the diseases treatment and develop a treatment regimen for individual patients in relation to each antibiotic. Key points The salivary microbiota of antibiotic-treated patients was more bacteria variety MALDI-TOF MS is a promising tool for recording of reproducible molecular profiles Our data can allow to monitor the treatment of bacterial diseases for patients
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