Magdalena Hernández

Interspecies competition triggers virulence and mutability in Candida albicans-Pseudomonas aeruginosa mixed biofilms.

Inter-kingdom and interspecies interactions are ubiquitous in nature and are important for the survival of species and ecological balance. The investigation of microbe-microbe interactions is essential for understanding the in vivo activities of commensal and pathogenic microorganisms. Candida albicans, a polymorphic fungus, and Pseudomonas aeruginosa, a Gram-negative bacterium, are two opportunistic pathogens that interact in various polymicrobial infections in humans. To determine how P. aeruginosa affects the physiology of C. albicans and vice versa, we compared the proteomes of each species in mixed biofilms versus single-species biofilms. In addition, extracellular proteins were analyzed. We observed that, in mixed biofilms, both species showed differential expression of virulence proteins, multidrug resistance-associated proteins, proteases and cell defense, stress and iron-regulated proteins. Furthermore, in mixed biofilms, both species displayed an increase in mutability compared with monospecific biofilms. This characteristic was correlated with the downregulation of enzymes conferring protection against DNA oxidation. In mixed biofilms, P. aeruginosa regulates its production of various molecules involved in quorum sensing and induces the production of virulence factors (pyoverdine, rhamnolipids and pyocyanin), which are major contributors to the ability of this bacterium to cause disease. Overall, our results indicate that interspecies competition between these opportunistic pathogens enhances the production of virulence factors and increases mutability and thus can alter the course of host-pathogen interactions in polymicrobial infections.

Comparative proteomics using 2-D gel electrophoresis and mass spectrometry as tools to dissect stimulons and regulons in bacteria with sequenced or partially sequenced genomes

We propose two-dimensional gel electrophoresis (2-DE) and mass spectrometry to define the protein components of regulons and stimulons in bacteria, including those organisms where genome sequencing is still in progress. The basic 2-DE protocol allows high resolution and reproducibility and enables the direct comparison of hundreds or even thousands of proteins simultaneously. To identify proteins that comprise stimulons and regulons, peptide mass fingerprint (PMF) with matrix-assisted laser desorption ionization/time-of-flight mass spectrometry (MALDI-TOF-MS) analysis is the first option and, if results from this tool are insufficient, complementary data obtained with electrospray ionization tandem-MS (ESI-MS/MS) may permit successful protein identification. ESI-MS/MS and MALDI-TOF-MS provide complementary data sets, and so a more comprehensive coverage of a proteome can be obtained using both techniques with the same sample, especially when few sequenced proteins of a particular organism exist or genome sequencing is still in progress.

Systems biology of bacterial nitrogen fixation: High-throughput technology and its integrative description with constraint-based modeling

BackgroundBacterial nitrogen fixation is the biological process by which atmospheric nitrogen is uptaken by bacteroids located in plant root nodules and converted into ammonium through the enzymatic activity of nitrogenase. In practice, this biological process serves as a natural form of fertilization and its optimization has significant implications in sustainable agricultural programs. Currently, the advent of high-throughput technology supplies with valuable data that contribute to understanding the metabolic activity during bacterial nitrogen fixation. This undertaking is not trivial, and the development of computational methods useful in accomplishing an integrative, descriptive and predictive framework is a crucial issue to decoding the principles that regulated the metabolic activity of this biological process.ResultsIn this work we present a systems biology description of the metabolic activity in bacterial nitrogen fixation. This was accomplished by an integrative analysis involving high-throughput data and constraint-based modeling to characterize the metabolic activity in Rhizobium etli bacteroids located at the root nodules of Phaseolus vulgaris ( bean plant). Proteome and transcriptome technologies led us to identify 415 proteins and 689 up-regulated genes that orchestrate this biological process. Taking into account these data, we: 1) extended the metabolic reconstruction reported for R. etli; 2) simulated the metabolic activity during symbiotic nitrogen fixation; and 3) evaluated the in silico results in terms of bacteria phenotype. Notably, constraint-based modeling simulated nitrogen fixation activity in such a way that 76.83% of the enzymes and 69.48% of the genes were experimentally justified. Finally, to further assess the predictive scope of the computational model, gene deletion analysis was carried out on nine metabolic enzymes. Our model concluded that an altered metabolic activity on these enzymes induced different effects in nitrogen fixation, all of these in qualitative agreement with observations made in R. etli and other Rhizobiaceas.ConclusionsIn this work we present a genome scale study of the metabolic activity in bacterial nitrogen fixation. This approach leads us to construct a computational model that serves as a guide for 1) integrating high-throughput data, 2) describing and predicting metabolic activity, and 3) designing experiments to explore the genotype-phenotype relationship in bacterial nitrogen fixation.

Cell-Wall Proteins Induced by Water Deficit in Bean (Phaseolus vulgaris L.) Seedlings.

In the last few years, much attention has been given to the role of proteins that accumulate during water deficit. In this work, we analyzed the electrophoretic patterns of basic protein extracts, enriched for a number of cell-wall proteins, from bean (Phaseolus vulgaris L.) seedlings and 21-d-old plants subjected to water deficit. Three major basic proteins accumulated in bean seedlings exposed to low water potentials, with apparent molecular masses of 36, 33, and 22 kD, which we refer to as p36, p33, and p22, respectively. Leaves and roots of 21-d-old plants grown under low-water-availability conditions accumulated only p36 and p33 proteins. In 21-d-old plants subjected to a fast rate of water loss, both p33 and p36 accumulated to approximately the same levels, whereas if the plants were subjected to a gradual loss of water, p33 accumulated to higher levels. Both p36 and p33 were glycosylated and were found in the cell-wall fraction. In contrast, p22 was not glycosylated and was found in the soluble fraction. The accumulation of these proteins was also induced by abscisic acid (0.1–1.0 mM) treatment but not by wounding or by jasmonate treatment.

Functional Modules, Structural Topology, and Optimal Activity in Metabolic Networks

Modular organization in biological networks has been suggested as a natural mechanism by which a cell coordinates its metabolic strategies for evolving and responding to environmental perturbations. To understand how this occurs, there is a need for developing computational schemes that contribute to integration of genomic-scale information and assist investigators in formulating biological hypotheses in a quantitative and systematic fashion. In this work, we combined metabolome data and constraint-based modeling to elucidate the relationships among structural modules, functional organization, and the optimal metabolic phenotype of Rhizobium etli, a bacterium that fixes nitrogen in symbiosis with Phaseolus vulgaris. To experimentally characterize the metabolic phenotype of this microorganism, we obtained the metabolic profile of 220 metabolites at two physiological stages: under free-living conditions, and during nitrogen fixation with P. vulgaris. By integrating these data into a constraint-based model, we built a refined computational platform with the capability to survey the metabolic activity underlying nitrogen fixation in R. etli. Topological analysis of the metabolic reconstruction led us to identify modular structures with functional activities. Consistent with modular activity in metabolism, we found that most of the metabolites experimentally detected in each module simultaneously increased their relative abundances during nitrogen fixation. In this work, we explore the relationships among topology, biological function, and optimal activity in the metabolism of R. etli through an integrative analysis based on modeling and metabolome data. Our findings suggest that the metabolic activity during nitrogen fixation is supported by interacting structural modules that correlate with three functional classifications: nucleic acids, peptides, and lipids. More fundamentally, we supply evidence that such modular organization during functional nitrogen fixation is a robust property under different environmental conditions.

Displacers improve the selectivity of phosphopeptide enrichment by metal oxide affinity chromatography

BACKGROUND A key process in cell regulation is protein phosphorylation, which is catalyzed by protein kinases and phosphatases. However, phosphoproteomics studies are difficult because of the complexity of protein phosphorylation and the number of phosphorylation sites. METHODS We describe an efficient approach analyzing phosphopeptides in single, separated protein by two-dimensional gel electrophoresis. In this method, a titanium oxide (TiO2)-packed NuTip is used as a phosphopeptide trap, together with displacers as lactic acid in the loading buffer to increase the efficiency of the interaction between TiO2 and phosphorylated peptides. RESULTS The results were obtained from the comparison of mass spectra of proteolytic peptides of proteins with a matrix-assisted laser desorption-ionization-time of flight (MALDI-TOF) instrument. CONCLUSIONS This method has been applied to identifying phosphoproteins involved in the symbiosis Rhizobium etli-Phaseolus vulgaris.

Proteomic and Transcriptomic Approaches to Study Global Genome Expression in Rhizobium etli and Sinorhizobium meliloti

Two global approaches have been used to study the free-living state of the symbiotic species, Rhizobium etli and Sinorhizobium meliloti, as well as the R. etli-Phaseolus vulgaris interaction. The proteome of R. etli was examined to determine the enzymatic reactions and cell processes that occur in the free-living state (fermentative, aerobic metabolism, and symbiosis with legume plants). All the detectable protein spots on the two-dimensional (2-D) gels between pH 3–10 were analyzed. In total, we identified 1,518 proteins. Using a combination of 2-D gel electrophoresis, peptide mass fingerprinting, and bioinformatics, our goal is to identify: (i) biofilm-, aerobicand fermentative metabolism-, symbiosisand stress-specific proteins; and (ii) the biochemical pathways active under different conditions tested. Using the databases of the genome sequences from R. etli and S. meliloti genomes and the software “Pathway tools”, we constructed in silico the pathways and metabolic reactions potentially functional in both bacteria. We called these databases Sinocyc (S. meliloti) and Rhizocyc (R. etli). Using this definition, 46 pathways involved in many common anabolic and catabolic cellular processes of small molecule metabolism can be considered active in R. etli under the conditions examined.