STUDY ON THE PROLIFERATIVE STATE OF HAEMOPOIETIC STEM CELLS (CFU)

Hydroxyurea was used to study the proliferation rate of haemopoietic stem cells (CFUJ in normal mice, after irradiation or transplantation into irradiated recipients. It was demonstrated that the proliferation rate of endogenous CFU_S (endo-CFU,) and exogenous CFU_S (exo-CFU_s) are identical. After irradiation (650 R) the surviving endo-CFU_s begin to proliferate immediately. By contrast exo-CFU, transplanted into the irradiated recipient mouse (850 R), begin to proliferate only after about 30 hr. However, injection of isoproterenol (which stimulates adenyl cyclase) or dibutyryl cyclic adenosine 3′,5′-monophosphate shortly after marrow cell graft, triggers the transplanted CFU_S into cell cycle as shown by an almost immediately increased sensitivity to hydroxyurea. Isoproterenol is capable of inducing DNA synthesis also in stem cells of normal mice but it takes about 20 hr before CFU, become to be increasingly sensitive to hydroxyurea.     

Disentangling genetic and epigenetic determinants of ultrafast adaptation

A major rationale for the advocacy of epigenetically mediated adaptive responses is that they facilitate faster adaptation to environmental challenges. This motivated us to develop a theoretical–experimental framework for disclosing the presence of such adaptation‐speeding mechanisms in an experimental evolution setting circumventing the need for pursuing costly mutation–accumulation experiments. To this end, we exposed clonal populations of budding yeast to a whole range of stressors. By growth phenotyping, we found that almost complete adaptation to arsenic emerged after a few mitotic cell divisions without involving any phenotypic plasticity. Causative mutations were identified by deep sequencing of the arsenic‐adapted populations and reconstructed for validation. Mutation effects on growth phenotypes, and the associated mutational target sizes were quantified and embedded in data‐driven individual‐based evolutionary population models. We found that the experimentally observed homogeneity of adaptation speed and heterogeneity of molecular solutions could only be accounted for if the mutation rate had been near estimates of the basal mutation rate. The ultrafast adaptation could be fully explained by extensive positive pleiotropy such that all beneficial mutations dramatically enhanced multiple fitness components in concert. As our approach can be exploited across a range of model organisms exposed to a variety of environmental challenges, it may be used for determining the importance of epigenetic adaptation‐speeding mechanisms in general.     

A novel harmony search-K means hybrid algorithm for clustering gene expression data

Recent progress in bioinformatics research has led to the accumulation of huge quantities of biological data at various data sources. The DNA microarray technology makes it possible to simultaneously analyze large number of genes across different samples. Clustering of microarray data can reveal the hidden gene expression patterns from large quantities of expression data that in turn offers tremendous possibilities in functional genomics, comparative genomics, disease diagnosis and drug development. The k- ¬means clustering algorithm is widely used for many practical applications. But the original k-¬means algorithm has several drawbacks. It is computationally expensive and generates locally optimal solutions based on the random choice of the initial centroids. Several methods have been proposed in the literature for improving the performance of the k-¬means algorithm. A meta-heuristic optimization algorithm named harmony search helps find out near-global optimal solutions by searching the entire solution space. Low clustering accuracy of the existing algorithms limits their use in many crucial applications of life sciences. In this paper we propose a novel Harmony Search-K means Hybrid (HSKH) algorithm for clustering the gene expression data. Experimental results show that the proposed algorithm produces clusters with better accuracy in comparison with the existing algorithms.     

First morphogenetic identification of <i>Fusarium solani</i> isolated from orange fruit in Egypt

Losses due to postharvest decay may occur at any time during postharvest handling, from harvest to consumption affecting the produce quality and quantity. Accurate identification of the pathogen causing postharvest disease is essential to the selection of an appropriate disease control approach. Nine isolates of Fusarium recovered from orange fruit were identified as Fusarium solani. The fungus is involved with fruit decay. The obtained cultures were purified and grown on potato-dextrose agar (PDA), malt yeast agar (MYA), and Czapek's nutrient media (CNM) under light for identification. A pathogenicity test was carried out to fulfil Koch's postulates. The pathogen could only enter ripe orange fruit through wounds and cracks causing the rot disease. The identification of the fungal isolates was confirmed to be F. solani by DNA sequencing, which was 99 to 100% homologous to those deposited in the Gen- Bank. The identity of nine fungal isolates was confirmed to be F. solani by DNA sequencing of the internal transcribed spacer (ITS) rDNA region (GenBank Accession Nos. DQ486874 to DQ486881 and KC758879). To our knowledge, this is the first morphogenetic identification of F. solani isolated from orange fruit in Egypt.