Claudia Colabella

FTIR Metabolomic Fingerprint Reveals Different Modes of Action Exerted by Structural Variants of N-Alkyltropinium Bromide Surfactants on Escherichia coli and Listeria innocua Cells

Surfactants are extremely important agents to clean and sanitize various environments. Their biocidal activity is a key factor determined by the interactions between amphiphile structure and the target microbial cells. The object of this study was to analyze the interactions between four structural variants of N-alkyltropinium bromide surfactants with the Gram negative Escherichia coli and the Gram positive Listeria innocua bacteria. Microbiological and conductometric methods with a previously described FTIR bioassay were used to assess the metabolomic damage exerted by these compounds. All surfactants tested showed more biocidal activity in L. innocua than in E. coli. N-tetradecyltropinium bromide was the most effective compound against both species, while all the other variants had a reduced efficacy as biocides, mainly against E. coli cells. In general, the most prominent metabolomic response was observed for the constituents of the cell envelope in the fatty acids (W1) and amides (W2) regions and at the wavenumbers referred to peptidoglycan (W2 and W3 regions). This response was particularly strong and negative in L. innocua, when cells were challenged by N-tetradecyltropinium bromide, and by the variant with a smaller head and a 12C tail (N-dodecylquinuclidinium bromide). Tail length was critical for microbial inhibition especially when acting against E. coli, maybe due the complex nature of Gram negative cell envelope. Statistical analysis allowed us to correlate the induced mortality with the metabolomic cell response, highlighting two different modes of action. In general, gaining insights in the interactions between fine structural properties of surfactants and the microbial diversity can allow tailoring these compounds for the various operative conditions.

Phenotypic and molecular diversity of Meyerozyma guilliermondii strains isolated from food and other environmental niches, hints for an incipient speciation

Meyerozyma guilliermondii is a yeast species widely isolated from several natural environments and from fruit; in medical microbiology it is known as the teleomorph of the opportunistic pathogen Candida guilliermondii, which causes about 2% of the human blood infections. This yeast is also promising in a variety of biotechnological applications as vitamins production and post-harvest control. The question if isolates from different sources are physiologically and genetically similar, or if the various environments induced significant differences, is crucial for the understanding of this species structure and to select strains appropriate for each application. This question was addressed using LSU and ITS sequencing for taxonomic assignment, i-SSR (GACA4) for the molecular characterization and FTIR for the metabolomic fingerprint. All data showed that fruit and environmental isolates cluster separately with a general good agreement between metabolomics and molecular analysis. An additional RAPD analysis was able to discriminate strains according to the isolation position within the pineapple fruit. Although all strains are members of the M. guilliermondii species according to the current standards, the distribution of large variability detected suggests that some specialization occurred in the niches inhabited by this yeast and that food related strains can be differentiated from the medical isolates.

Ionic Conductivity as a Tool To Study Biocidal Activity of Sulfobetaine Micelles against Saccharomyces cerevisiae Model Cells

Zwitterionic sulfobetaine surfactants are used in pharmaceutical or biomedical applications for the solubilization and delivery of hydrophobic molecules in aqueous medium or in biological environments. In a screening on the biocidal activity of synthetic surfactants on microbial cells, remarkable results have emerged with sulfobetaine amphiphiles. The interaction between eight zwitterionic sulfobetaine amphiphiles and Saccharomyces cerevisiae model cells was therefore analyzed. S. cerevisiae yeast cells were chosen, as they are a widely used unicellular eukaryotic model organism in cell biology. Conductivity measurements were used to investigate the interaction between surfactant solution and cells. Viable counts measurements were performed, and the mortality data correlated with the conductivity profiles very well, in terms of the inflection points (IPs) observed in the curves and in terms of supramolecular properties of the aggregates. A Fourier transform infrared (FTIR)-based bioassay was then performed to determine the metabolomic stress-response of the cells subjected to the action of zwitterionic surfactants. The surfactants showed nodal concentration (IPs) with all the techniques in their activities, corresponding to the critical micellar concentrations of the amphiphiles. This is due to the pseudocationic behavior of sulfobetaine micelles, because of their charge distribution and charge densities. This behavior permits the interaction of the micellar aggregates with the cells, and the structure of the surfactant monomers has impact on the mortality and the metabolomic response data observed. On the other hand, the concentrations that are necessary to provoke a biocidal activity do not promote these amphiphiles as potential antimicrobial agents. In fact, they are much higher than the ones of cationic surfactants.

A novel, rapid and automated conductometric method to evaluate surfactant–cells interactions by means of critical micellar concentration analysis

Conductometry is widely used to determine critical micellar concentration and micellar aggregates surface properties of amphiphiles. Current conductivity experiments of surfactant solutions are typically carried out by manual pipetting, yielding some tens reading points within a couple of hours. In order to study the properties of surfactant-cells interactions, each amphiphile must be tested in different conditions against several types of cells. This calls for complex experimental designs making the application of current methods seriously time consuming, especially because long experiments risk to determine alterations of cells, independently of the surfactant action. In this paper we present a novel, accurate and rapid automated procedure to obtain conductometric curves with several hundreds reading points within tens of minutes. The method was validated with surfactant solutions alone and in combination with Saccharomyces cerevisiae cells. An easy-to use R script, calculates conductometric parameters and their statistical significance with a graphic interface to visualize data and results. The validations showed that indeed the procedure works in the same manner with surfactant alone or in combination with cells, yielding around 1000 reading points within 20 min and with high accuracy, as determined by the regression analysis.

Exploring ecological modelling to investigate factors governing the colonization success in nosocomial environment of Candida albicans and other pathogenic yeasts.

Two hundred seventy seven strains from eleven opportunistic species of the genus Candida, isolated from two Italian hospitals, were identified and analyzed for their ability to form biofilm in laboratory conditions. The majority of Candida albicans strains formed biofilm while among the NCAC species there were different level of biofilm forming ability, in accordance with the current literature. The relation between the variables considered, i.e. the departments and the hospitals or the species and their ability to form biofilm, was tested with the assessment of the probability associated to each combination. Species and biofilm forming ability appeared to be distributed almost randomly, although some combinations suggest a potential preference of some species or of biofilm forming strains for specific wards. On the contrary, the relation between biofilm formation and species isolation frequency was highly significant (R2 around 0.98). Interestingly, the regression analyses carried out on the data of the two hospitals separately were rather different and the analysis on the data merged together gave a much lower correlation. These findings suggest that, harsh environments shape the composition of microbial species significantly and that each environment should be considered per se to avoid less significant statistical treatments.

NGS barcode sequencing in taxonomy and diagnostics, an application in "Candida" pathogenic yeasts with a metagenomic perspective

Species identification of yeasts and other Fungi is currently carried out with Sanger sequences of selected molecular markers, mainly from the ribosomal DNA operon, characterized by hundreds of tandem repeats of the 18S, ITS1, 5.8S, ITS2 and LSU loci. The ITS region has been recently proposed as a primary barcode marker making this region the most used one in taxonomy, phylogeny and diagnostics. The introduction of NGS is providing tools of high efficacy and relatively low cost to amplify two or more markers simultaneously with great sequencing depth. However, the presence of intra-genomic variability between the repeats requires specific analytical procedures and pipelines. In this study, 286 strains belonging to 11 pathogenic yeasts species were analysed with NGS of the region spanning from ITS1 to the D1/D2 domain of the LSU encoding ribosomal DNA. Results showed that relatively high heterogeneity can hamper the use of these sequences for the identification of single strains and even more of complex microbial mixtures. These observations point out that the metagenomics studies could be affected by species inflection at levels higher than currently expected.

Early Ongoing Speciation of Ogataea uvarum Sp. Nov. Within the Grape Ecosystem Revealed by the Internal Variability Among the rDNA Operon Repeats

A yeast strain was isolated during a study on vineyard-associated yeast strains from Apulia in Southern Italy. ITS and LSU D1/D2 rDNA sequences showed this strain not to belong to any known species and was described as the type strain of Ogataea uvarum sp. nov., a close relative of O. philodendri. Several secondary peaks appeared in the sequences, suggesting internal heterogeneity among the copies of the rDNA. This hypothesis was tested by sequencing single clones of the marker region. The analyses showed different levels of variability throughout the operon with differences between the rRNA encoding genes and the internally transcribed regions. O. uvarum and O. philodendri share high frequency variants, i.e., variants frequently found in many clones, whereas there is a large variability of the low frequency polymorphisms, suggesting that the mechanism of homogenization is more active with the former than with the latter type of variation. These findings indicate that low frequency variants are detected in Sanger sequencing as secondary peaks whereas in Next Generation Sequencing (NGS) of metagenomics DNA would lead to an overestimate of the alpha diversity. For the first time in our knowledge, this investigation shed light on the variation of the copy number of the rDNA cistron during the yeast speciation process. These polymorphisms can be used to investigate on the processes occurring in these taxonomic markers during the separation of fungal species, it being a genetic process highly frequent in the complex microbial ecosystem existing in grape, must and wine.

Merging FT-IR and NGS for simultaneous phenotypic and genotypic identification of pathogenic Candida species

The rapid and accurate identification of pathogen yeast species is crucial for clinical diagnosis due to the high level of mortality and morbidity induced, even after antifungal therapy. For this purpose, new rapid, high-throughput and reliable identification methods are required. In this work we described a combined approach based on two high-throughput techniques in order to improve the identification of pathogenic yeast strains. Next Generation Sequencing (NGS) of ITS and D1/D2 LSU marker regions together with FTIR spectroscopy were applied to identify 256 strains belonging to Candida genus isolated in nosocomial environments. Multivariate data analysis (MVA) was carried out on NGS and FT-IR data-sets, separately. Strains of Candida albicans, C. parapsilosis, C. glabrata and C. tropicalis, were identified with high-throughput NGS sequencing of ITS and LSU markers and then with FTIR. Inter- and intra-species variability was investigated by consensus principal component analysis (CPCA) which combines high-dimensional data of the two complementary analytical approaches in concatenated PCA blocks normalized to the same weight. The total percentage of correct identification reached around 97.4% for C. albicans and 74% for C. parapsilosis while the other two species showed lower identification rates. Results suggested that the identification success increases with the increasing number of strains actually used in the PLS analysis. The absence of reliable FT-IR libraries in the current scenario is the major limitation in FTIR-based identification of strains, although this metabolomics fingerprint represents a valid and affordable aid to rapid and high-throughput to clinical diagnosis. According to our data, FT-IR libraries should include some tens of certified strains per species, possibly over 50, deriving from diverse sources and collected over an extensive time period. This implies a multidisciplinary effort of specialists working in strain isolation and maintenance, molecular taxonomy, FT-IR technique and chemo-metrics, data management and data basing.

A novel FTIR-based approach to evaluate the interactions between lignocellulosic inhibitory compounds and their effect on yeast metabolism

Inhibitors commonly found in lignocellulosic hydrolysates impair yeast metabolism and growth, reducing the productivity of the overall bioethanol production process. FTIR spectroscopy was used to analyze the metabolomic alterations induced by acetic and formic acid, furfural and 5-hydroxymethyl-2-furaldehyde (HMF) on yeast metabolism, using three Saccharomyces cerevisiae strains with different sensitivities. IR spectrum alterations were summarized with synthetic descriptors to rapidly visualize the kinds of molecules displaying the more intense reactions and to evaluate the type of interaction between inhibitors in a mixture, at concentrations close to those found at the industrial scale. The four inhibitors induced different levels of mortality and metabolomic changes. The metabolomic response was proportional to the different strain resistance level, further supporting their original classification. Inhibitor mixtures severely hindered the cell viability with the exception of the lowest concentration tested, which was partially biocidal. Furthermore, for the first time, this study revealed antagonistic interactions exerted by inhibitor mixtures on microbial metabolism, closely strain- and dose-dependent. This confirms that yeast strain resistance to single inhibitors cannot be used to predict behaviour on exposure to mixtures. This finding is worth further studies to explain the underlying antagonistic mechanism and to support the selection of highly tolerant strains.