IV. RESULTS AND DISCUSSION
2.5.2. SDS-‐PAGE of inner membrane proteins
Results and Discussion: Chapter 2
-‐125-‐
The resulting accumulation of abnormal membrane proteins would disturb the membrane structure and function, eventually compromising cellular integrity and viability (Akiyama, 2009).
Inner membrane proteins from all stress samples were extracted and separated in 12% poliacrylamide gels.
As with outer membrane proteins, during stress conditions drastic changes in the protein patterns compared with the optimal conditions were not observed in a range from 250 to 25 kDa; this observation was also repeated during 30 days-‐prolonged stress. However, M8 temperature pattern showed some specific proteins bands different to the control and to the other stress conditons (Figure 28). Proteins bands around 150, 120, 60, and 25 kDa were detected only during temperature stress (black arrows, Fig. 28), whereas a band around 90 kDa was observed in control, anoxia, and dilution patterns, but not in the temperature one. In the same way, a band of 45 kDa was detected in control, anoxia, and temperature patterns but not during dilution stress (dotted arrows, Fig. 28). Moreover, in M31 the main change was observed in the anoxia protein pattern, where two bands of about 65 and 60 kDa detected in the control condition, disappeared. In addition, the same band of 65 kDa was not clearly detected in the dilution and temperature protein patterns (dotted arrows, Fig. 28). As in the OMPs analysis, protein banding differences between strains could be related to the expression of specific-‐strain genes, but also to the the number of related-‐membrane genes present in each strain (Peña et al., 2010). This fact might be also associated to the changes in intensity observed between both strains at low temperature (Fig. 28). These changes, could be related to the increase in the expression of some proteins in M8 (from 60 to 150 kDa), and to the decrease in the expression of all proteins observed in M31 (Fig. 28).
The inner membrane has a more complex protein system than the outer membrane, including transporters, channels, receptors and enzymes involved in the synthesis and metabolism of membrane constituents (Akiyama, 2009). The analysis of inner membrane proteins showed differences of some proteins, expressed during low temperature (M8) whereas during anoxia and dilution stress not significant changes were observed. These not significant changes could be related to the fact that under stress conditions, the production of low molecular weight stress proteins increases (Denich et al. 2003), but due to the used experimental conditions, these kind of proteins could not be detected. In addition, the structural or conformational adaptacion of proteins in response to stress conditions can not be detected by SDS-‐PAGE (Denich et al, 2003). On the other hand, exposure to temperatures above but close to 0 °C is usually associated to an active response by bacteria, typically the synthesis of specific proteins or cold shock proteins (CSPs), leading to a transient metabolic adaptation, statibilizing proteins involved in the structure and function of nucleics acids (Panoff et al., 1998).
Results and Discussion: Chapter 2
-‐126-‐
Specifically, transfers of mesophilic bacteria from the optimal growth temperature to a lower temperature still allows growth but leads to a relatively rapid decrease in the synthesis of ‘‘housekeeping’’ proteins and the synthesis of CSPs , which are low molecular weight (less than 10 kDa) and could not be detected by this study (Jiang et al, 1997;(Panoff et al., 1998)Panoff et al., 1998). Despite this, these results suggested that the stress response of inner membrane in S. ruber might be associated to conformational or functional changes of proteins more than significant changes in the membrane-‐protein composition, so the transmembrane transferring of molecules and other functions of the membrane-‐bound proteins are not affected and cells preserve their viability.
Figure 28: Pattern of inner membrane proteins in S. ruber during optimal and stress conditions (16h). Inner membrane associated-‐proteins fractions of M8 and M31 strains were separated in 12 % SDS–polyacrylamide gels by Tris-‐glycine buffer and stained with Coomassie blue. Arrows indicate the proteins bands that were different (black) and the missing protein bands (dotted) respect to the rest of protein band patterns. M: molecular weight standard; C: control or optimal condition; O: oxygen depletion; D: dilution; T: temperature.
2.6. Lipopolysaccharide (LPS) analysis of strains during stress conditions
As mentioned before, the cell envelope is the initial target of physical (e.g., hyperthermia, osmolarity), chemical (e.g., ethanol, pH, detergent) or biological (e.g., adhesion, infection) stresses. These stresses may alter envelope components by inducing numerous alterations, each of which may be perceived by different pathways of stress response, and may contribute to adapt the cell to different aspects of the stress damage.
Results and Discussion: Chapter 2
-‐127-‐
Lipopolysaccharides (LPS) are amphiphilic macromolecules composed of a hydrophilic heteropolysaccharide (formed by core oligosaccharide and O-‐specific polysaccharide or O-‐chain) covalently linked to a lipophilic moiety termed lipid A which anchors these macromolecules to the outer membrane (Silipo et al., 2005). LPS is the major component of the outer membrane of Gram-‐negative bacteria, contributing greatly to the structural integrity of the bacteria, and protecting the membrane from certain kinds of chemical attack (Ghuysen & Hakenbeck, 1994).
To supplement the metabolomic observations, and considering the contribution of LPS in the membrane integrity, changes in the LPS pattern of S. ruber strains during stress conditions were also analyzed in the different cultures by a modification of the method described by Hitchcock and Brown (Hitchcock & Brown, 1983), and by the Busse method (Busse et al., 1989). LPS was checked using SDS-‐PAGE (12%) visualizing gels with silver staining according to Tsai and Frasch (Tsai & Frasch, 1982).
Unfortunately, none of the used methods yielded good results and LPS patterns never had the good resolution for suggesting a specific response under stress conditions. Metagenomic analyses in hyper-‐
halophiles, showed that genomics islands (related to the biosynthesis of polysaccharide compounds wall cell) shared a number of similarities with gene clusters of pathogenic Gram negative bacteria (Pašic et al., 2009).
Based on this information, standard protocols described for Salmonella (Hitchcock & Brown, 1983) and Pseudomonas (Busse et al., 1989) were used, but perhaps due to the halophilic characteristics of S. ruber, they were unsuccessful. LPS studies in halophilic marine bacteria have been carried out using acetone-‐dried cells, where the LPS is extracted with a mixture of phenol/ chloroform/petroleum eter (2:5:8 v/v/v) and then liofilized to be analyzed by electrophoresis (Silipo et al., 2005).
Although LPS are the major components of their outer leaflet, very little is known about the role of these molecules in the adaptation mechanisms of extremophiles, and LPS from halophilic bacteria frequently show unusual chemical features most likely due to their external environment (Pieretti et al., 2010; Silipo et al., 2005). Thus, even though a metagenomic study has shown that genomic islands shared a number of similarities with O-‐polysaccharide gene clusters of pathogenic Gram negative bacteria, S ruber lacks core LPS genes which would indicate that these external polysaccharides might be anchored by a non-‐canonical structure (Pašic et al., 2009) and it is possible that standard protocols used in this work are not the most indicated to their detection.
Due to the complexity of a specific protocol for the study of LPS in certain microorganisms, we could not find the right procedure during this work. Nonetheless, it would be useful to standarize a specific protocol to study membrane compounds, as LPS, in halophilic or other extreme microorganisms.
Results and Discussion: Chapter 2
-‐128-‐
2.7. Matrix assisted laser desorption/ionization-‐time-‐of-‐flight mass spectrometry analysis of strains during stress
Matrix assisted laser desorption/ionization-‐time-‐of-‐flight mass spectrometry (MALDI-‐TOF MS), is a fast, reliable and cost-‐effective technique that has the potential to replace and/or complement conventional phenotypic identification for most bacterial strains (Sauer & Kliem, 2010). The great advantage of the method is that the analyses can be done using a minute amount of biomass from a given colony, mixed with the matrix solution and transferred to the MALDI-‐TOF mass spectrometer, without previous treatments or time-‐consuming extractions (Muñoz et al., 2011). The MS profiles, in part, reflecting the heterogeneity of cell ribosomal proteins, produce stable phenotypic characterizations that have been used previously to identify clinical microorganisms (Seng et al., 2010), environmental strains (Ruelle et al., 2004), and moderately halophilic microorganisms (Munoz et al., 2011). This technique was used to study the main phenotypical changes of strains under the different stress conditions from the whole cell and to evaluate whether these were consistent with the results previously obtained by other techniques. In order to extract the main patterns of variation, to identify groups or clusters of samples, two different multivariate exploratory techniques were applied: partial least square discriminative analysis (PLS-‐DA) and cluster analysis (Ramette, 2007b) that were used to explore whether the different stress conditions involve changes in the whole protein pattern of each strain.
2.7.1.Statistical analysis
All pure culture samples were submitted to whole-‐cell MALDI-‐TOF MS analysis. Each sample was measured twice in order to confirm the reproducibility of the individual profiles. From all obtained spectra, the averaged value of masses was calculated for each sample, which finally yielded a matrix composed by 341 masses. In order to test for significant differences between different stress conditions PLS-‐DA models with Orthogonal Signal Correction (OSC) were first applied to analyze this group of masses and evaluate whether any of the variables (time or stress conditions) was related to the intensity of masses detected in each sample. The inspection of this model showed a dependence of intensity with time (Figure 29) where stress samples at 16 and 40 h were those that presented more differences respect to the control masses. However, protein intensity patterns obtained from temperature stress at 16 and 40 h in M8 were less significant and more similar to control patterns than in M31 strain (Fig.29). Differences in the protein patterns between strains had already been observed in the previous sections when analyzing membrane proteins.
Results and Discussion: Chapter 2
-‐129-‐
Again, these differences could be explained by the genomic differences existing between them, but also by the different metabolic stress response observed in the metabolomic analysis, where metabolomic composition of M31 were less related to the control condition than the M8 metabolome (see Fig. 24).
Differences of intensities in the ”proteome” under stress conditions is not trivial due to the response to imposed stress in bacteria is accomplished by changes in the patterns of gene expression which is directly related to the protein expression (Marles-‐Wright & Lewis, 2007). Thereby, osmotic stress in some halophilic organisms could involve an inhibition in the protein synthesis and amino acid uptake during initial phase of adaptation to the new conditions, whereas during the adaptation period, changes in the patterns of proteins coulb be observed (Ventosa et al., 1998), which may explain the higher intensity differences of the masses observed at 40 h during all stress conditions (Fig.29). Consequently bacteria have developed sophisticated responses, modulated by the re-‐modelling of protein complexes and by phophorylation-‐dependent signal transduction systems, to adapt to and to survival a variety of adverse changes (Marles-‐Wright & Lewis, 2007).
Figure 29: Orthogonal PLS model from all stress and control samples analyzed by MALDI-‐TOF MS The model shows a dependence on the intensity of masses with the time of stress (with Q2(cum)=0.2; R2Y(cum)=0.52), being higher at 40 h and well differentiated respect to the control condition under all stress conditions which are indicated as O (Oxygen),D (Dilution), and T (Temperature) in M8 and M31 strains. Control conditions are labelled in yellow whereas different times are labelled in red (2h), orange (16h) and brown (40h).
Results and Discussion: Chapter 2
-‐130-‐