Rapid and reliable identification of waterborne Legionella species by MALDI-TOF mass spectrometry

Water Safety Plan, Monochloramine Disinfection and Extensive Environmental Sampling Effectively Control Legionella and Other Waterborne Pathogens in Nosocomial Settings: The Ten-Year Experience of an Italian Hospital

Legionella contamination control is crucial in healthcare settings where patients suffer an increased risk of disease and fatal outcome. To ensure an effective management of this health hazard, the accurate application of a hospital-specific Water Safety Plan (WSP), the choice of a suitable water disinfection system and an extensive monitoring program are required. Here, the ten-year experience of an Italian hospital is reported: since its commissioning, Legionellosis risk management has been entrusted to a multi-disciplinary Working Group, applying the principles of the World Health Organization's WSP. The disinfection strategy to prevent Legionella and other waterborne pathogens relies on the treatment of domestic hot water with a system ensuring the in situ production and dosage of monochloramine. An average of 250 samples/year were collected and analyzed to allow an accurate assessment of the microbiological status of water network. With the aim of increasing the monitoring sensitivity, in addition to the standard culture method, an optimized MALDI-ToF MS-based strategy was applied, allowing the identification of Legionella species and other relevant opportunistic pathogens. Data collected so far confirmed the effectiveness of this multidisciplinary approach: the fraction of positive samples never overcame 1% on a yearly basis and Legionnaires' Disease cases never occurred.

Legionella anisa or Legionella bozemanii? Traditional and molecular techniques as support in the environmental surveillance of a hospital water network

Understanding the actual distribution of different Legionella species in water networks would help prevent outbreaks. Culture investigations followed by serological agglutination tests, with poly/monovalent antisera, still represent the gold standard for isolation and identification of Legionella strains. However, also MALDI-TOF and mip-gene sequencing are currently used. This study was conducted to genetically correlate strains of Legionella non pneumophila (L-np) isolated during environmental surveillance comparing different molecular techniques. Overall, 346 water samples were collected from the water system of four pavilions located in a hospital of the Apulia Region of Italy. Strains isolated from the samples were then identified by serological tests, MALDI-TOF, and mip-gene sequencing. Overall, 24.9% of water samples were positive for Legionella, among which the majority were Legionella pneumophila (Lpn) 1 (52.3%), followed by Lpn2-15 (20.9%), L-np (17.4%), Lpn1 + Lpn2-15 (7.1%), and L-np + Lpn1 (2.3%). Initially, L-np strains were identified as L. bozemanii by monovalent antiserum, while MALDI-TOF and mip-gene sequencing assigned them to L. anisa. More cold water than hot water samples were contaminated by L. anisa (p < 0.001). PFGE, RAPD, Rep-PCR, and SAU-PCR were performed to correlate L. anisa strains. Eleven out of 14 strains identified in all four pavilions showed 100% of similarity upon PFGE analysis. RAPD, Rep-PCR, and SAU-PCR showed greater discriminative power than PFGE.

A multi-center validation study on the discrimination of Legionella pneumophila sg.1, Legionella pneumophila sg. 2-15 and Legionella non-pneumophila isolates from water by FT-IR spectroscopy

This study developed and validated a method, based on the coupling of Fourier-transform infrared spectroscopy (FT-IR) and machine learning, for the automated serotyping of Legionella pneumophila serogroup 1, Legionella pneumophila serogroups 2-15 as well as their successful discrimination from Legionella non-pneumophila. As Legionella presents significant intra- and inter-species heterogeneities, careful data validation strategies were applied to minimize late-stage performance variations of the method across a large microbial population. A total of 244 isolates were analyzed. In details, the method was validated with a multi-centric approach with isolates from Italian thermal and drinking water (n = 82) as well as with samples from German, Italian, French, and British collections (n = 162). Specifically, robustness of the method was verified over the time-span of 1 year with multiple operators and two different FT-IR instruments located in Italy and Germany. Moreover, different production procedures for the solid culture medium (in-house or commercial) and different culture conditions (with and without 2.5% CO₂) were tested. The method achieved an overall accuracy of 100, 98.5, and 93.9% on the Italian test set of Legionella, an independent batch of Legionella from multiple European culture collections, and an extra set of rare Legionella non-pneumophila, respectively.

Polymer Brushes on GaAs and GaAs/AlGaAs Nanoheterostructures: A Promising Platform for Attractive Detection of Legionella pneumophila

This work reports on the potential of polymer brushes (PBs) grown on GaAs substrates (PB-GaAs) as a promising platform for the detection of Legionella pneumophila (Lp). Three functionalization approaches of the GaAs surface were used, and their compatibility with antibodies against Lp was evaluated using Fourier transform infrared spectroscopy and fluorescence microscopy. The incorporation of PBs on GaAs has allowed a significant improvement of the antibody immobilization by increased surface coverage. Bacterial capture experiments demonstrated the promising potential for enhanced immobilization of Lp in comparison with the conventional alkanethiol self-assembled monolayer-based biosensing architectures. Consistent with an eightfold improved capture of bacteria on the surface of a PB-functionalized GaAs/AlGaAs digital photocorrosion biosensor, we report the attractive detection of Lp at 500 CFU/mL.

Assessing direct analysis in real-time mass spectrometry for the identification and serotyping of Legionella pneumophila

AIMS

The efficacy of ambient mass spectrometry to identify and serotype Legionella pneumophila was assessed. To this aim, isolated waterborne colonies were submitted to a rapid extraction method and analysed by direct analysis in real-time mass spectrometry (DART-HRMS).

METHODS AND RESULTS

The DART-HRMS profiles, coupled with partial least squares discriminant analysis (PLS-DA), were first evaluated for their ability to differentiate Legionella spp. from other bacteria. The resultant classification model achieved an accuracy of 98.1% on validation. Capitalising on these encouraging results, DART-HRMS profiling was explored as an alternative approach for the identification of L. pneumophila sg. 1, L. pneumophila sg. 2-15 and L. non-pneumophila; therefore, a different PLS-DA classifier was built. When tested on a validation set, this second classifier reached an overall accuracy of 95.93%. It identified the harmful L. pneumophila sg. 1 with an impressive specificity (100%) and slightly lower sensitivity (91.7%), and similar performances were reached in the classification of L. pneumophila sg. 2-15 and L. non-pneumophila.

CONCLUSIONS

The results of this study show the DART-HMRS method has good accuracy, and it is an effective method for Legionella serogroup profiling.

SIGNIFICANCE AND IMPACT OF THE STUDY

These preliminary findings could open a new avenue for the rapid identification and quick epidemiologic tracing of L. pneumophila, with a consequent improvement to risk assessment.

Advances in Environmental Detection and Clinical Diagnostic Tests for Legionella Species

Legionella is a fastidious organism that is difficult to culture in the lab but is widely distributed in environmental, domestic, and hospital settings. The clinical manifestations due to Legionella infections range from mild fever to fatal pneumonia and multiorgan pathologies. Legionella outbreaks though prevalent globally are not reported in developing countries due to difficulties in isolating this organism and the lack of simple diagnostic protocols. Here, we review the literature from across countries to present various methods used to detect Legionella from environmental and clinical samples. We compare the sensitivity and the specificity of the conventional culture-based assays with the recent methods and discuss approaches to develop better detection and diagnostic tests. With better cost-effective detection techniques and regular monitoring of the susceptible sites, which may harbor Legionella colonies, most of the Legionella infections can be prevented. As a result, considerable burden, caused by Legionella infections, on the healthcare system, in especially economically weaker countries, can be mitigated.

Modern Analytical Techniques for Detection of Bacteria in Surface and Wastewaters

Contamination of surface waters with pathogens as well as all diseases associated with such events are a significant concern worldwide. In recent decades, there has been a growing interest in developing analytical methods with good performance for the detection of this category of contaminants. The most important analytical methods applied for the determination of bacteria in waters are traditional ones (such as bacterial culturing methods, enzyme-linked immunoassay, polymerase chain reaction, and loop-mediated isothermal amplification) and advanced alternative methods (such as spectrometry, chromatography, capillary electrophoresis, surface-enhanced Raman scattering, and magnetic field-assisted and hyphenated techniques). In addition, optical and electrochemical sensors have gained much attention as essential alternatives for the conventional detection of bacteria. The large number of available methods have been materialized by many publications in this field aimed to ensure the control of water quality in water resources. This study represents a critical synthesis of the literature regarding the latest analytical methods covering comparative aspects of pathogen contamination of water resources. All these aspects are presented as representative examples, focusing on two important bacteria with essential implications on the health of the population, namely Pseudomonas aeruginosa and Escherichia coli.

Quantification of Legionella pneumophila by qPCR and culture in tap water with different concentrations of residual disinfectants and heterotrophic bacteria

Legionellosis prevalence is increasing in the United States. This disease is caused primarily by the bacterium Legionella pneumophila found in water and transmitted by aerosol inhalation. This pathogen has a slow growth rate and can "hide" in amoeba, making it difficult to monitor by the traditional culture method on selective media. Tap water samples (n = 358) collected across the United States were tested for L. pneumophila by both culture and quantitative Polymerase Chain Reaction (qPCR). The presence of other bacteria was quantified by heterotrophic plate counts (HPC). Residual disinfectant concentrations (free chlorine or monochloramine) were measured in all samples. Legionella pneumophila had the highest prevalence and concentration in the chlorinated water samples that had a free‑chlorine value of less than 0.2 mg Cl₂/L. In total, 24% (87/358) of the samples were positive for L. pneumophila either by qPCR or 3% (11/358) were positive by culture. In chloramine-treated samples, L. pneumophila was detected by qPCR in 21% (31/148) and 1% (2/148) by culture, despite a high monochloramine residual >1 mg Cl₂/L. Despite the presence of a high disinfectant residual (>1 mg Cl₂/L), HPC counts were substantial. This study indicates that both culture and qPCR methods have limitations when predicting a potential risk for disease associated with L. pneumophila in tap water. Measuring disinfectant residuals and quantifying HPC in water samples may be useful adjunct parameters for reducing Legionellosis' risk from public water supplies at high-risk locations.

Efficient cooling tower operation at alkaline pH for the control of Legionella pneumophila and other pathogenic genera

Efficient control of pathogenic bacteria, specifically Legionella pneumophila, is one of the main concerns when operating industrial cooling towers. Common practices to limit proliferation involves use of disinfectants, leading to formation of disinfection by-product and increase in water corrosiveness. A disinfectant-free Legionella control method would make the industry more environmentally friendly. A pilot-scale cooling tower (1 m³/h) operated with demineralized water was used to investigate the potential of high-pH conditioning as a disinfectant-free alternative for control of L. pneumophila and other pathogens. One control experiment was performed under standard full-scale operation involving sodium hypochlorite dosage. Thereafter 3 alkaline pHs of the cooling water were tested: 9.0, 9.4 and 9.6. The tests lasted between 25 and 35 days. The cooling water from the basins were analysed for total cell count by flow cytometry, L. pneumophila concentration by plate count and occasional qPCR analyses targeting the mip-gene, bacterial and eukaryotic community analyses with 16S and 18S rRNA gene amplicon sequencing, relative abundance of eukaryotic to prokaryotic DNA by qPCR of the 16S and 18S rRNA gene. The L. pneumophila analyses showed considerable growth at pH 9.0 and pH 9.4 but was maintained below detection limit (< 100 CFU/L) at pH 9.6 without disinfection. Interestingly, the results correlated with the overall abundance of protozoa in the water samples but not directly with the relative abundance of specific reported protozoan hosts of Legionella. The pathogenicity based on 16S rRNA gene amplicon sequencing of the cooling water DNA decreased with increasing pH with a strong decline between pH 9.0 and pH 9.4, from 7.1% to 1.6% of relative abundance of pathogenic genera respectively. A strong shift in microbiome was observed between each tested pH and reproducibility of the experiment at pH 9.6 was confirmed with a duplicate test lasting 80 days. High-pH conditioning ≥ 9.6 is therefore considered as an efficient disinfectant-free cooling tower operation for control of pathogenicity, including L. pneumophila.

Evaluation of MALDI-TOF Mass Spectrometry in Diagnostic and Environmental Surveillance of Legionella Species: A Comparison With Culture and Mip-Gene Sequencing Technique

Legionella spp. are widespread bacteria in aquatic environments with a growing impact on human health. Between the 61 species, Legionella pneumophila is the most prevalent in human diseases; on the contrary, Legionella non-pneumophila species are less detected in clinical diagnosis or during environmental surveillance due to their slow growth in culture and the absence of specific and rapid diagnostic/analytical tools. Reliable and rapid isolate identification is essential to estimate the source of infection, to undertake containment measures, and to determine clinical treatment. Matrix-assisted laser desorption ionization–time-of-flight mass spectrometry (MALDI–TOF MS), since its introduction into the routine diagnostics of laboratories, represents a widely accepted method for the identification of different bacteria species, described in a few studies on the Legionella clinical and environmental surveillance. The focus of this study was the improvement of MALDI–TOF MS on Legionella non-pneumophila species collected during Legionella nosocomial and community surveillance. Comparative analysis with cultural and mip-gene sequencing results was performed. Moreover, a phylogenetic analysis was carried out to estimate the correlations amongst isolates. MALDI–TOF MS achieved correct species-level identification for 45.0% of the isolates belonging to the Legionella anisa, Legionella rubrilucens, Legionella feeleii, and Legionella jordanis species, displaying a high concordance with the mip-gene sequencing results. In contrast, less reliable identification was found for the remaining 55.0% of the isolates, corresponding to the samples belonging to species not yet included in the database. The phylogenetic analysis showed relevant differences inside the species, regruped in three main clades; among the Legionella anisa clade, a subclade with a divergence of 3.3% from the main clade was observed. Moreover, one isolate, identified as Legionella quinlivanii, displayed a divergence of 3.8% from the corresponding reference strain. However, these findings require supplementary investigation. The results encourage the implementation of MALDI–TOF MS in routine diagnostics and environmental Legionella surveillance, as it displays a reliable and faster identification at the species level, as well as the potential to identify species that are not yet included in the database. Moreover, phylogenetic analysis is a relevant approach to correlate the isolates and to track their spread, especially in unconventional reservoirs, where Legionella prevention is still underestimated.

Effects of cold recovery technology on the microbial drinking water quality in unchlorinated distribution systems

Drinking water distribution systems (DWDSs) are used to supply hygienically safe and biologically stable water for human consumption. The potential of thermal energy recovery from drinking water has been explored recently to provide cooling for buildings. Yet, the effects of increased water temperature induced by this "cold recovery" on the water quality in DWDSs are not known. The objective of this study was to investigate the impact of cold recovery from DWDSs on the microbiological quality of drinking water. For this purpose, three pilot distribution systems were operated in parallel for 38 weeks. System 1 has an operational heat exchanger, mimicking the cold recovery system by maintaining the water temperature at 25 °C; system 2 operated with a non-operational heat exchanger and system 3 run without heat exchanger. The results showed no significant effects on drinking water quality: cell numbers and ATP concentrations remained around 3.5 × 10⁵ cells/ml and 4 ng ATP/l, comparable observed operational taxonomic units (OTUs) (~470-490) and similar Shannon indices (7.7-8.9). In the system with cold recovery, a higher relative abundance of Pseudomonas spp. and Chryseobacterium spp. was observed in the drinking water microbial community, but only when the cold recovery induced temperature difference (ΔT) was higher than 9 °C. In the 38 weeks' old biofilm, higher ATP concentration (475 vs. 89 pg/cm²), lower diversity (observed OTUs: 88 vs. ≥200) and a different bacterial community composition (e.g. higher relative abundance of Novosphingobium spp.) were detected, which did not influence water quality. No impacts were observed for the selected opportunisitic pathogens after introducing cold recovery. It is concluded that cold recovery does not affect bacterial water quality. Further investigation for a longer period is commended to understand the dynamic responses of biofilm to the increased temperature caused by cold recovery.

Comparisons of protective effects between two sea cucumber hydrolysates against diet induced hyperuricemia and renal inflammation in mice

Differences in the anti-hyperuricemic and anti-inflammation effects between two sea cucumber hydrolysates in diet induced hyperuricemic mice.

Fast and Accurate Bacterial Species Identification in Urine Specimens Using LC-MS/MS Mass Spectrometry and Machine Learning

Fast identification of microbial species in clinical samples is essential to provide an appropriate antibiotherapy to the patient and reduce the prescription of broad-spectrum antimicrobials leading to antibioresistances. MALDI-TOF-MS technology has become a tool of choice for microbial identification but has several drawbacks: it requires a long step of bacterial culture before analysis (≥24 h), has a low specificity and is not quantitative. We developed a new strategy for identifying bacterial species in urine using specific LC-MS/MS peptidic signatures. In the first training step, libraries of peptides are obtained on pure bacterial colonies in DDA mode, their detection in urine is then verified in DIA mode, followed by the use of machine learning classifiers (NaiveBayes, BayesNet and Hoeffding tree) to define a peptidic signature to distinguish each bacterial species from the others. Then, in the second step, this signature is monitored in unknown urine samples using targeted proteomics. This method, allowing bacterial identification in less than 4 h, has been applied to fifteen species representing 84% of all Urinary Tract Infections. More than 31,000 peptides in 190 samples were quantified by DIA and classified by machine learning to determine an 82 peptides signature and build a prediction model. This signature was validated for its use in routine using Parallel Reaction Monitoring on two different instruments. Linearity and reproducibility of the method were demonstrated as well as its accuracy on donor specimens. Within 4h and without bacterial culture, our method was able to predict the predominant bacteria infecting a sample in 97% of cases and 100% above the standard threshold. This work demonstrates the efficiency of our method for the rapid and specific identification of the bacterial species causing UTI and could be extended in the future to other biological specimens and to bacteria having specific virulence or resistance factors.

Temporal influence of different antibiotics onto the inhibition of Escherichia coli bacterium grown in different media

Escherichia coli (E. coli) is a Gram-negative bacterium commonly found in the lower intestine of warm-blooded organisms, including humans. Although the majority of the strains are considerably harmless, some serotypes are pathogenic, frequently causing diarrhea and other illnesses outside the intestinal tract. The standard antidote against bacteria is the use of antibiotics. Depending on their type, the antibiotics have various mechanisms of action on bacteria. Moreover, in case of in-vitro cultivation of bacteria, the used growth media plays a crucial role, since it influences bacterial inhibition as well. In the present study, we emphasize the importance of cultivability in bacterial inhibition under the treatment with five different antibiotics belonging to different classes. Consequently, E. coli was cultivated in three different growth media: trypcase soy broth (TSB), Mueller Hinton (MH), and minimal salts (M9) enriched with glucose, respectively. MALDI-TOF MS (matrix-assisted laser desorption ionization time-of-flight mass spectrometry) analyses, that were used for fast characterization of changes that occur in ribosomal protein profiles, revealed differentiation and similarities between investigated cases, while flow cytometry (FCM) tests better explained the given changes that occurred in the analyzed samples after 3, 24 and 48 h of experimental campaign.

In silico analysis and in vivo tests of the tuna dark muscle hydrolysate anti-oxidation effect

Hydrolysate is a mixture of various peptides with specific functions. However, functional identification of hydrolysate with high throughput is still a difficult task. Furthermore, using in vivo tests via animal or cell experiments is time and labor-intensive. In this study, the peptides component of hydrolysate derived from the tuna dark muscle was measured via MALDI-TOF/TOF-MS, and the functions of the KEFT (Lys-Glu-Phe-Thr), EEASA (Glu-Glu-Ala-Ser-Ala) and RYDD (Arg-Tyr-Asp-Asp) peptides, which were found with the highest proportion, were predicted via Discovery Studio 2016 software. All three peptides were predicted to bind to the Keap1 protein with the highest fit-value and to affect the activity of Keap1, which is involved in anti-oxidation pathways. Subsequently, mice experiments showed that administration of tuna dark muscle hydrolysate increased the levels of superoxide dismutase and glutathione peroxidase in the serum and liver (P < 0.05) and decreased the malondialdehyde level (P < 0.05) as well as transcription of Keap1 (P > 0.05), which are consistent with the in silico analysis results using Discovery Studio 2016 software. The combination of in silico analysis and in vivo tests provided an alternative strategy for identifying hydrolysate function and provided insight into high-value utilization of protein hydrolysate.

In silico prediction and in vivo confirmation of anti-oxidation effect.

MALDI-TOF MS analysis as a useful tool for an identification of Legionella pneumophila, a facultatively pathogenic bacterium interacting with free-living amoebae: A case study from water supply system of hospitals in Bratislava (Slovakia)

Legionellae, i.e. Legionella pneumophila, are human bacterial hydrophilic facultative pathogens causing pneumonia (Legionnaires' disease). Free-living amoebae (FLA) can serve as natural hosts and thus as reservoirs of many amoebae-resistant bacteria. An encysted amoeba can contribute to the resistance of intracellular L. pneumophila to various chemical and physical treatments. Humans can be infected by droplets containing bacteria from an environmental source or human-made devices such as shower heads, bathtubs, air-conditioning units or whirlpools. In this study, we were investigating the presence of FLA and L. pneumophila in plumbing systems of healthcare facilities in Bratislava (Slovakia) by standard diagnostic methods, while the presence of L. pneumophila was verified also by MALDI-TOF MS (matrix-assisted laser desorption/ionization time-of-flight mass spectrometry) analysis. The results showed the occurrence of L. pneumophila and FLA in 62.26% and 66.4% of samples taken from four paediatric clinics, respectively. Both standard methods and MALDI-TOF MS showed comparable results and they can be successfully applied for the identification of L. pneumophila strains in environmental samples. Our approach could be useful for further monitoring, prevention and decreasing risk of Legionella infection also in other hospitals.

Mass spectrometric techniques for the analysis of volatile organic compounds emitted from bacteria

Bacteria are the main cause of many human diseases. Typical bacterial identification methods, for example culture-based, serological and genetic methods, are time-consuming, delaying the potential for an early and accurate diagnosis and the appropriate subsequent treatment. Nevertheless, there is a stringent need for in situ tests that are rapid, noninvasive and sensitive, which will greatly facilitate timely treatment of the patients. This review article presents volatile organic metabolites emitted from various micro-organism strains responsible for common bacterial infections in humans. Additionally, the manuscript shows the application of different analytical techniques for fast bacterial identification. Details of these techniques are given, which focuses on their advantages and drawbacks in using for volatile organic components analysis.