Characterization of CTX-M and SHV extended-spectrum beta-lactamases and associated resistance genes in Escherichia coli strains of food samples in Tunisia

OBJECTIVES: To assess the occurrence of extended-spectrum beta-lactamases (ESBLs) in Escherichia coli isolates of faecal samples of animals (n = 40) and food samples (n = 38) obtained in Tunisia in 2006, and to characterize the type of ESBLs, their genetic environments and the associated resistance genes. METHODS: Samples were inoculated in supplemented media (2 mg/L cefotaxime) for isolation of broad-spectrum cephalosporin-resistant E. coli isolates (one isolate/sample). ESBLs and their genetic environments as well as integrons and their gene cassette composition were characterized by PCR and sequencing. RESULTS: ESBL-producing E. coli isolates were detected in 10 of the 38 food samples analysed (26%) and in none of the tested animal faecal samples. Genes found were as follows (number of isolates): bla(CTX-M-1) (5), bla(CTX-M-1) + bla(TEM-1b) (1), bla(CTX-M-14) + bla(TEM-1b) (2), bla(CTX-M-8) (1) and bla(SHV-5) (1). All ESBL-positive isolates showed unrelated PFGE patterns. ISEcp1 and IS903 were detected surrounding bla(CTX-M-14), and ISEcp1/IS26 and orf477 surrounding some of the bla(CTX-M-1) genes. Four of the ESBL-positive strains harboured class 1 integrons including different gene cassette combinations. CONCLUSIONS: ESBLs, mainly of the CTX-M class, are detected in E. coli of food origin in Tunisia, being the first time that this mechanism has been detected in food E. coli strains in Africa.     

Synthesis of lipophilic tyrosyl esters derivatives and assessment of their antimicrobial and antileishmania activities

Background  

Preparation of tyrosyl lipophilic derivatives was carried out as a response to the food, cosmetic and pharmaceutical industries' increasing demand for new lipophilic antioxidants.     

Targeting tetraspanins in cancer

Introduction: Tetraspanins are a family of small proteins that cross the membrane four times and form complexes by interacting between themselves and with a variety of transmembrane and cytosolic proteins, building a network of interactions referred to as tetraspanin web or tetraspanin enriched microdomains (TEMs). These domains provide a signaling platform involved in many important cellular functions and malignant processes. Areas covered: The authors describe the methods and the rationale for targeting tetraspanins in the therapy of cancer in this review. Expert opinion: Targeting tetraspanins in cancer may be a promising therapy due to the importance of tetraspanins in several steps of tumor formation, communication with the environment, dissemination, and metastasis.     

TRAF1 is a negative regulator of TNF signaling. enhanced TNF signaling in TRAF1-deficient mice.

TNF receptor-associated factor 1 (TRAF1) is a unique TRAF protein because it lacks a RING finger domain and is predominantly expressed in activated lymphocytes. To elucidate the function of TRAF1, we generated TRAF1-deficient mice. TRAF1(-/-) mice are viable and have normal lymphocyte development. TRAF1(-/-) T cells exhibit stronger than wild-type (WT) T cell proliferation to anti-CD3 mAb, which persisted in the presence of IL-2 or anti-CD28 antibodies. Activated TRAF1(-/-) T cells, but not TRAF1(+/+) T cells, responded to TNF by proliferation and activation of the NF-kappa B and AP-1 signaling pathways. This TNF effect was mediated by TNFR2 (p75) but not by TNFR1 (p55). Furthermore, skin from TRAF1(-/-) mice was hypersensitive to TNF-induced necrosis. These findings suggest that TRAF1 is a negative regulator of TNF signaling.     

Chromosomal translocations and semen quality: A study on 144 male translocation carriers

Research question

Chromosomal translocations are known genetic causes of male infertility. Are certain translocations or chromosomal regions more directly associated with sperm defects? Is there a threshold of sperm impairment that can be relevant for detection of translocations?

Application of Multi-SOM clustering approach to macrophage gene expression analysis

The production of increasingly reliable and accessible gene expression data has stimulated the development of computational tools to interpret such data and to organize them efficiently. The clustering techniques are largely recognized as useful exploratory tools for gene expression data analysis. Genes that show similar expression patterns over a wide range of experimental conditions can be clustered together. This relies on the hypothesis that genes that belong to the same cluster are coregulated and involved in related functions. Nevertheless, clustering algorithms still show limits, particularly for the estimation of the number of clusters and the interpretation of hierarchical dendrogram, which may significantly influence the outputs of the analysis process. We propose here a multi level SOM based clustering algorithm named Multi-SOM. Through the use of clustering validity indices, Multi-SOM overcomes the problem of the estimation of clusters number. To test the validity of the proposed clustering algorithm, we first tested it on supervised training data sets. Results were evaluated by computing the number of misclassified samples. We have then used Multi-SOM for the analysis of macrophage gene expression data generated in vitro from the same individual blood infected with 5 different pathogens. This analysis led to the identification of sets of tightly coregulated genes across different pathogens. Gene Ontology tools were then used to estimate the biological significance of the clustering, which showed that the obtained clusters are coherent and biologically significant.