A Novel System of Cytoskeletal Elements in the Human Pathogen Helicobacter pylori

Pathogenicity of the human pathogen Helicobacter pylori relies upon its capacity to adapt to a hostile environment and to escape from the host response. Therefore, cell shape, motility, and pH homeostasis of these bacteria are specifically adapted to the gastric mucus. We have found that the helical shape of H. pylori depends on coiled coil rich proteins (Ccrp), which form extended filamentous structures in vitro and in vivo, and are differentially required for the maintenance of cell morphology. We have developed an in vivo localization system for this pathogen. Consistent with a cytoskeleton-like structure, Ccrp proteins localized in a regular punctuate and static pattern within H. pylori cells. Ccrp genes show a high degree of sequence variation, which could be the reason for the morphological diversity between H. pylori strains. In contrast to other bacteria, the actin-like MreB protein is dispensable for viability in H. pylori, and does not affect cell shape, but cell length and chromosome segregation. In addition, mreB mutant cells displayed significantly reduced urease activity, and thus compromise a major pathogenicity factor of H. pylori. Our findings reveal that Ccrp proteins, but not MreB, affect cell morphology, while both cytoskeletal components affect the development of pathogenicity factors and/or cell cycle progression

Fitness of Escherichia coli during Urinary Tract Infection Requires Gluconeogenesis and the TCA Cycle

Microbial pathogenesis studies traditionally encompass dissection of virulence properties such as the bacterium's ability to elaborate toxins, adhere to and invade host cells, cause tissue damage, or otherwise disrupt normal host immune and cellular functions. In contrast, bacterial metabolism during infection has only been recently appreciated to contribute to persistence as much as their virulence properties. In this study, we used comparative proteomics to investigate the expression of uropathogenic Escherichia coli (UPEC) cytoplasmic proteins during growth in the urinary tract environment and systematic disruption of central metabolic pathways to better understand bacterial metabolism during infection. Using two-dimensional fluorescence difference in gel electrophoresis (2D-DIGE) and tandem mass spectrometry, it was found that UPEC differentially expresses 84 cytoplasmic proteins between growth in LB medium and growth in human urine (P<0.005). Proteins induced during growth in urine included those involved in the import of short peptides and enzymes required for the transport and catabolism of sialic acid, gluconate, and the pentose sugars xylose and arabinose. Proteins required for the biosynthesis of arginine and serine along with the enzyme agmatinase that is used to produce the polyamine putrescine were also up-regulated in urine. To complement these data, we constructed mutants in these genes and created mutants defective in each central metabolic pathway and tested the relative fitness of these UPEC mutants in vivo in an infection model. Import of peptides, gluconeogenesis, and the tricarboxylic acid cycle are required for E. coli fitness during urinary tract infection while glycolysis, both the non-oxidative and oxidative branches of the pentose phosphate pathway, and the Entner-Doudoroff pathway were dispensable in vivo. These findings suggest that peptides and amino acids are the primary carbon source for E. coli during infection of the urinary tract. Because anaplerosis, or using central pathways to replenish metabolic intermediates, is required for UPEC fitness in vivo, we propose that central metabolic pathways of bacteria could be considered critical components of virulence for pathogenic microbes

The modular systems biology approach to investigate the control of apoptosis in Alzheimer's disease neurodegeneration

Apoptosis is a programmed cell death that plays a critical role during the development of the nervous system and in many chronic neurodegenerative diseases, including Alzheimer's disease (AD). This pathology, characterized by a progressive degeneration of cholinergic function resulting in a remarkable cognitive decline, is the most common form of dementia with high social and economic impact. Current therapies of AD are only symptomatic, therefore the need to elucidate the mechanisms underlying the onset and progression of the disease is surely needed in order to develop effective pharmacological therapies. Because of its pivotal role in neuronal cell death, apoptosis has been considered one of the most appealing therapeutic targets, however, due to the complexity of the molecular mechanisms involving the various triggering events and the many signaling cascades leading to cell death, a comprehensive understanding of this process is still lacking. Modular systems biology is a very effective strategy in organizing information about complex biological processes and deriving modular and mathematical models that greatly simplify the identification of key steps of a given process. This review aims at describing the main steps underlying the strategy of modular systems biology and briefly summarizes how this approach has been successfully applied for cell cycle studies. Moreover, after giving an overview of the many molecular mechanisms underlying apoptosis in AD, we present both a modular and a molecular model of neuronal apoptosis that suggest new insights on neuroprotection for this disease

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases