58 research outputs found

    Analysis of the cell surface layer ultrastructure of the oral pathogen Tannerella forsythia

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    The Gram-negative oral pathogen Tannerella forsythia is decorated with a 2D crystalline surface (S-) layer, with two different S-layer glycoprotein species being present. Prompted by the predicted virulence potential of the S-layer, this study focused on the analysis of the arrangement of the individual S-layer glycoproteins by a combination of microscopic, genetic, and biochemical analyses. The two S-layer genes are transcribed into mRNA and expressed into protein in equal amounts. The S-layer was investigated on intact bacterial cells by transmission electron microscopy, by immune fluorescence microscopy, and by atomic force microscopy. The analyses of wild-type cells revealed a distinct square S-layer lattice with an overall lattice constant of 10.1 ± 0.7 nm. In contrast, a blurred lattice with a lattice constant of 9.0 nm was found on S-layer single-mutant cells. This together with in vitro self-assembly studies using purified (glyco)protein species indicated their increased structural flexibility after self-assembly and/or impaired self-assembly capability. In conjunction with TEM analyses of thin-sectioned cells, this study demonstrates the unusual case that two S-layer glycoproteins are co-assembled into a single S-layer. Additionally, flagella and pilus-like structures were observed on T. forsythia cells, which might impact the pathogenicity of this bacterium

    Biogenesis and functions of bacterial S-layers.

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    The outer surface of many archaea and bacteria is coated with a proteinaceous surface layer (known as an S-layer), which is formed by the self-assembly of monomeric proteins into a regularly spaced, two-dimensional array. Bacteria possess dedicated pathways for the secretion and anchoring of the S-layer to the cell wall, and some Gram-positive species have large S-layer-associated gene families. S-layers have important roles in growth and survival, and their many functions include the maintenance of cell integrity, enzyme display and, in pathogens and commensals, interaction with the host and its immune system. In this Review, we discuss our current knowledge of S-layer and related proteins, including their structures, mechanisms of secretion and anchoring and their diverse functions

    Cancer Biomarker Discovery: The Entropic Hallmark

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    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
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