The in situ physiology of "Nostocoida limicola" II, a filamentous bacterial morphotype in bulking activated sludge, using fluorescence in situ hybridization and microautoradiography

The in situ physiology of the actinobacterial bulking and foaming filamentous bacterium "Nostocoida limicola" II was studied by fluorescence in situ hybridization/microautoradiography. Substrate assimilation patterns of pure cultures of this bacterium were different to those seen in activated sludge biomass samples. There was no evidence to suggest that "N. limicola" II preferred hydrophobic substrates, but evidence was produced to support the view that it is metabolically active under anaerobic conditions in activated sludge.

An empirical study of neighbourhood decay in Kohonen's self organizing map

In this paper, empirical results are presented which suggest that size and rate of decay of region size plays a much more significant role in the learning, and especially the development, of topographic feature maps. Using these results as a basis, a scheme for decaying region size during SOM training is proposed. The proposed technique provides near optimal training time. This scheme avoids the need for sophisticated learning gain decay schemes, and precludes the need for a priori knowledge of likely training times. This scheme also has some potential uses for continuous learning.

Bacterial membrane vesicles deliver peptidoglycan to NOD1 in epithelial cells

Gram-negative bacterial peptidoglycan is specifically recognized by the host intracellular sensor NOD1, resulting in the generation of innate immune responses. Although epithelial cells are normally refractory to external stimulation with peptidoglycan, these cells have been shown to respond in a NOD1-dependent manner to Gram-negative pathogens that can either invade or secrete factors into host cells. In the present work, we report that Gram-negative bacteria can deliver peptidoglycan to cytosolic NOD1 in host cells via a novel mechanism involving outer membrane vesicles (OMVs). We purified OMVs from the Gram-negative mucosal pathogens: Helicobacter pylori, Pseudomonas aeruginosa and Neisseria gonorrhoea and demonstrated that these peptidoglycan containing OMVs upregulated NF-κB and NOD1-dependent responses in vitro. These OMVs entered epithelial cells through lipid rafts thereby inducing NOD1-dependent responses in vitro. Moreover, OMVs delivered intragastrically to mice-induced innate and adaptive immune responses via a NOD1-dependent but TLR-independent mechanism. Collectively, our findings identify OMVs as a generalized mechanism whereby Gram-negative bacteria deliver peptidoglycan to cytosolic NOD1. We propose that OMVs released by bacteria in vivo may promote inflammation and pathology in infected hosts.

Lipid membrane : a novel target for viral and bacterial pathogens

Abstracts: Lipid rafts are defined as specialized, dynamic microdomains that can be found in plasma membrane, and they are enriched with cholesterol and sphingolipids. Since lipid rafts’ first debut in the mid 1990’s, their existence, function and biological relevance have been a subject of intense scrutiny within the scientific community. Throughout this debate, we have learned a great deal regarding how cargos (both pathogens and cellular factors) are transported into and out of the cell through raft-dependent or raft-independent pathways. It is now apparent that a number of toxins, bacterial-, and viral-pathogens are able to exploit cholesterol and/or lipid rafts to gain a foot hold in their target hosts. The objective of this review is to describe our current appreciation on how selected pathogens utilise cholesterol and/or lipid rafts to support their propagation and to speculate on how some of these observations can be explored for the development of novel strategies that target plasma membrane lipids to control the spread of these viral- and bacterial-pathogens.

A hybrid neural network classifier combining ordered fuzzy ARTMAP and the dynamic decay adjustment algorithm

This paper presents a novel conflict-resolving neural network classifier that combines the ordering algorithm, fuzzy ARTMAP (FAM), and the dynamic decay adjustment (DDA) algorithm, into a unified framework. The hybrid classifier, known as Ordered FAMDDA, applies the DDA algorithm to overcome the limitations of FAM and ordered FAM in achieving a good generalization/performance. Prior to network learning, the ordering algorithm is first used to identify a fixed order of training patterns. The main aim is to reduce and/or avoid the formation of overlapping prototypes of different classes in FAM during learning. However, the effectiveness of the ordering algorithm in resolving overlapping prototypes of different classes is compromised when dealing with complex datasets. Ordered FAMDDA not only is able to determine a fixed order of training patterns for yielding good generalization, but also is able to reduce/resolve overlapping regions of different classes in the feature space for minimizing misclassification during the network learning phase. To illustrate the effectiveness of Ordered FAMDDA, a total of ten benchmark datasets are experimented. The results are analyzed and compared with those from FAM and Ordered FAM. The outcomes demonstrate that Ordered FAMDDA, in general, outperforms FAM and Ordered FAM in tackling pattern classification problems.

In depression, bacterial translocation may drive inflammatory responses, oxidative and nitrosative stress (O&NS) and autoimmune responses directed against O&NS- damaged neoepitopes

Objective: Depression is accompanied by activation of immuno-inflammatory and oxidative and nitrosative stress (IO&NS) pathways, and increased IgM/IgA responses to lipopolysaccharide (LPS) of gram-negative commensal bacteria. The latter suggests that bacterial translocation has caused IgM/IgA responses directed against LPS. Bacterial translocation may drive IO&NS responses.

Method: To examine the associations between IgM/IgA responses to LPS and IO&NS measurements, including plasma/serum interleukin-1 (IL-1), tumor necrosis factor (TNF)α, neopterin, lysozyme, oxidized LDL (oxLDL) antibodies, peroxides, and IgM (auto)immune responses against malondialdehyde (MDA), azelaic acid, phophatidyl inositol (Pi), NO-tryptophan and NO-tyrosine in depressed patients and controls.

Results: We found significant positive associations between IgM/IgA responses to LPS and oxLDL antibodies, IgM responses against MDA, azelaic acid, Pi, NO-tryptophan, and NO-tyrosine. The IgA responses to LPS were correlated with lysozyme. There were no significant positive correlations between the IgM/IgA responses to LPS and IL-1 and neopterin.

Conclusion: The findings show that in depression there is an association between increased bacterial translocation and lysozyme production, an antibacterial compound, O&NS processes, and autoimmune responses directed against O&NS generated neoantigenic determinants. It is suggested that bacterial translocation may drive IO&NS pathways in depression and thus play a role in its pathophysiology.

Bacterial biosensors for measuring availability of environmental pollutants

Biosensors are projected to find many applications due to their high selectivity and sensitivity, rapid reaction, economy and ease of handling in field measurements. Even though biosensors for a wide range of environmental pollutants have been extensively reported in the literature, the decision to develop a suitable biosensing system that can be approved by a regulatory perspective for environmental applications is fraught with technical issues. These issues mainly concern the biological recognition element, the physico-chemical transducer and the interfaces between the biological and the physical components, but also aspects of fluidics, electronics, and software for data processing. This article focused on the development of microbial-based biosensors for environmental applications especially metal contaminants such as arsenic.

Minimum inhibitory and bacterial concentrations of theaflavin and synergistic combinations with epicatechin and quercetin against clinical isolates of Stenotrophomonas Maltophilia

Stenotrophomonas maltophilia is an important nosocomial pathogen with intrinsic resistance to multiple antibiotics. Previous investigations have shown flavanols from black tea to possess antibacterial activity. This study describes the determination of minimum inhibitory concentrations and minimum bactericidal concentration for theaflavin independently and in formulations with the polyphenols epicatechin and quercetin against nine clinical isolates of Stenotrophomonas maltophilia and the control isolate NCTC 130141 via the microtitre assay. The results demonstrate that theaflavin has strong antibacterial activity and also shows significant synergism with epicatechin and quercetin. The minimum inhibitory concentrations of the isolates range between 200-400 g/mL for theaflavin and 100-200 g/mL for both theaflavin:epicatechin and theaflavin:quercetin combinations. The minimum bactericidal concentrations were discovered to be a 2 fold increase on those of the minimum inhibitory concentrations. The research highlights the potential use of polyphenols for the clinical treatment of highly antibiotic resistant bacteria.