Microbial and Chemical Characterization of Underwater Fresh Water Springs in the Dead Sea

Due to its extreme salinity and high Mg concentration the Dead Sea is characterized by a very low density of cells most of which are Archaea. We discovered several underwater fresh to brackish water springs in the Dead Sea harboring dense microbial communities. We provide the first characterization of these communities, discuss their possible origin, hydrochemical environment, energetic resources and the putative biogeochemical pathways they are mediating. Pyrosequencing of the 16S rRNA gene and community fingerprinting methods showed that the spring community originates from the Dead Sea sediments and not from the aquifer. Furthermore, it suggested that there is a dense Archaeal community in the shoreline pore water of the lake. Sequences of bacterial sulfate reducers, nitrifiers iron oxidizers and iron reducers were identified as well. Analysis of white and green biofilms suggested that sulfide oxidation through chemolitotrophy and phototrophy is highly significant. Hyperspectral analysis showed a tight association between abundant green sulfur bacteria and cyanobacteria in the green biofilms. Together, our findings show that the Dead Sea floor harbors diverse microbial communities, part of which is not known from other hypersaline environments. Analysis of the water’s chemistry shows evidence of microbial activity along the path and suggests that the springs supply nitrogen, phosphorus and organic matter to the microbial communities in the Dead Sea. The underwater springs are a newly recognized water source for the Dead Sea. Their input of microorganisms and nutrients needs to be considered in the assessment of possible impact of dilution events of the lake surface waters, such as those that will occur in the future due to the intended establishment of the Red Sea−Dead Sea water conduit

Small Changes in the Primary Structure of Transportan 10 Alter the Thermodynamics and Kinetics of its Interaction with Phospholipid Vesicles

ABSTRACT: The kinetics and thermodynamics of binding of transportan 10 (tp10) and four of its variants to phospholipid vesicles, and the kinetics of peptide-induced dye efflux, were compared. Tp10 is a 21-residue, amphipathic, cationic, cell-penetrating peptide similar to helical antimicrobial peptides. The tp10 variants examined include amidated and free peptides, and replacements of tyrosine by tryptophan. Carboxy-terminal amidation or substitution of tryptophan for tyrosine enhance binding and activity. The Gibbs energies of peptide binding to membranes determined experimentally and calculated from the interfacial hydrophobicity scale are in good agreement. The Gibbs energy for insertion into the bilayer core was calculated using hydrophobicity scales of residue transfer from water to octanol and to the membrane/ water interface. Peptide-induced efflux becomes faster as the Gibbs energies for binding and insertion of the tp10 variants decrease. If anionic lipids are included, binding and efflux rate increase, as expected because all tp10 variants are cationic and an electrostatic component is added. Whether the most important effect of peptide amidation is the change in charge or an enhancement of helical structure, however, still needs to be established. Nevertheless, it is clear that the changes in efflux rate reflect the differences in the thermodynamics of binding and insertion of the free and amidated peptide groups. We have recently reported a detailed investigation (1) o

The Potential of Antimicrobial Peptides as Biocides

Antimicrobial peptides constitute a diverse class of naturally occurring antimicrobial molecules which have activity against a wide range of pathogenic microorganisms. Antimicrobial peptides are exciting leads in the development of novel biocidal agents at a time when classical antibiotics are under intense pressure from emerging resistance, and the global industry in antibiotic research and development stagnates. This review will examine the potential of antimicrobial peptides, both natural and synthetic, as novel biocidal agents in the battle against multi-drug resistant pathogen infections

Making cheaper labor: Domestic outsourcing and development in the Galilee

Middle Eastern Studie

Flexible Manufacturing Systems: background examples and models

In this paper, we discuss recent innovations in manufacturing technology and their implications on the design and control of manufacturing systems. Recognizing the need to respond properly to rapidly changing market demands, we discuss several types of flexibility that can be incorporated in our production organisation to achieve this goal. We show how the concept of a Flexible Manufacturing System (FMS) naturally arises as an attempt to combine the advantages of traditional Job Shops and dedicated production lines.The main body of the paper is devoted to a classification of FMS problem areas and a review of models developed to understand and solve these problems. For each problem area, a number of important contributions in the literature is indicated. The reader, interested in the applications of Operations Research models but not familiar with the technical background of FMS’s, will find the descriptions of some essential FMS elements useful. Some final remarks and directions for future research conclude the paper.<br/

Computerized Closed Queuing Network Models of Flexible Manufacturing Systems: A Comparative Evaluation

Several closed queueing network models are available for stochastic performance evaluation of Flexible Manufacturing Systems (FMS). These models are particularly useful during the planning and design phases of FMS, since they can be applied to study gross tradeoffs between principal design parameters. This paper reviews and analyzes several computerized models for evaluating complex FMS facilities with respect to the desired allocation of the following key resources: manufacturing centers, transporters, pallets and tools. It focuses on such issues as the structure of the mathematical system models, the variety of performance measures (model outputs), model inputs, accuracy of results and computational effort. In addition, some alternatives to overcome part of the common limitations of the models are suggested and tested empirically