Analysis of the mutational spectrum of the FGFR2 gene in Pfeiffer syndrome

Pfeiffer syndrome (PS) is one of the classical craniosynostosis syndromes correlated with specific mutations in the human fibroblast growth factor receptor (FGFR) genes, FGFR1 and FGFR2. In this study, we set out to examine the exons in FGFR2 most commonly associated with mutations in PS, exons IIIa and IIIc, in a panel of 78 unrelated individuals with PS by the most sensitive method (direct DNA sequencing). We have identified a total of 18 different mutations among 40 patients; eight of these mutations have not been previously described. The mutational spectrum displays a non-random character with the frequent involvement of cysteine codons. Received: 6 January 1999 / Accepted: 10 March 1999     

Lipopolysaccharide recognition protein, MD-2, facilitates cellular uptake of E. coli-derived plasmid DNA in synovium

BACKGROUND: Several cell types are susceptible to transfection in vivo using naked plasmid DNA. The mechanisms involved in mediating in vivo transfection are incompletely known, but evidence suggests that receptor-mediated endocytosis is important for specific types of cells. In this study we tested the hypothesis that residual Escherichia coli lipopolysaccharide (LPS) forms a non-covalent complex with expression plasmid DNA, and host-cell-derived soluble LPS-binding proteins bind to the DNA-LPS complexes in order to facilitate receptor-mediated endocytosis. METHODS: Cells from the murine synovial lining were used as an in vivo model system and in vivo luciferase imaging was used to quantify levels of transgene expression. Using a series of gene-deleted mice, the roles of LPS recognition complex proteins, lipopolysaccharide-binding protein (LBP), CD14 and MD-2, in the process of in vivo transfection were determined. RESULTS: Luciferase expression assays revealed that mice lacking LBP or CD14 had increased luciferase expression (p < 0.023 and < 0.165, respectively), while mice deleted of MD-2 had significant reductions in luciferase expression (p < 0.001). Gene deletion of hyaluronic acid binding protein CD44 was used as a control and had no statistically significant effect on transgene expression in vivo. In muscle tissue, where neither cell surface nor soluble MD-2 is expressed, no MD-2 dependence of plasmid transfection was identified, suggesting the role of MD-2 is tissue or cell type specific. Additionally, depleting mice of macrophages showed that luciferase expression is occurring within fibroblast-like synoviocytes. CONCLUSIONS: Our data support a physical association between LPS and E. coli-derived plasmid DNA, and that in vivo transfection of fibroblast-like synoviocytes is dependent on the soluble form of the LPS-binding protein MD-2.     

Changes in the activities of various lipid and carbohydrate biosynthetic enzymes in the diatom Cyclotella cryptica in response to silicon deficiency

The effects of silicon deficiency on the activities of several enzymes involved in lipid and storage carbohydrate synthesis in the diatom Cyclotella cryptica were determined. The activity of UDPglucose pyrophosphorylase was not affected after 4 h of silicon-deficient growth, but the activity of UDPglucose: beta-(1----3)-glucan-beta-3-glucosyltransferase (chrysolaminarin synthase) was reduced by 31% during this period. Acetyl-CoA synthetase, acetyl-CoA hydrolase, and citrate synthase activities were present in cell-free extracts of C. cryptica, but did not change in response to 4 h of silicon deficiency. However, the activity of acetyl-CoA carboxylase increased approximately two- and fourfold after 4 and 15 h of silicon-deficient growth, respectively. This induction could be blocked by cycloheximide (20 micrograms/ml) and actinomycin D (10 micrograms/ml), suggesting that silicon deficiency may induce an increase in the rate of acetyl-CoA carboxylase synthesis. These changes in enzymatic activity may be partially responsible for the accumulation of lipids that has been observed in C. cryptica and other diatoms in response to silicon deficiency.     

Activation and de novo synthesis of hydrogenase in chlamydomonas

Two distinct processes are involved in the formation of active hydrogenase during anaerobic adaptation of Chlamydomonas reinhardtii cells. In the first 30 minutes of anaerobiosis, nearly all of the hydrogenase activity can be attributed to activation of a constituitive polypeptide precursor, based on the insensitivity of the process to treatment with cycloheximide (15 micrograms per milliliter). This concentration of cycloheximide inhibits protein synthesis by greater than 98%. After the initial activation period, de novo protein synthesis plays a critical role in the adaptation process since cycloheximide inhibits the expression of hydrogense in maximally adapted cells by 70%. Chloramphenicol (500 micrograms per milliliter) has a much lesser effect on the adaptation process.

Incubation of cell-free extracts under anaerobic conditions in the presence of dithionite, dithiothreitol, NADH, NADP, ferredoxin, ATP, Mg²⁺, Ca²⁺, and iron does not lead to active hydrogenase formation. Futhermore, in vivo reactivation of oxygen-inactivated hydrogenase does not appear to take place.

The adaptation process is very sensitive to the availability of iron. Iron-deficient cultures lose the ability to form active hydrogenase before growth, photosynthesis, and respiration are significantly affected. Preincubation of iron-deficient cells with iron 2 hours prior to the adaptation period fully restores the capacity of the cells to synthesize functional hydrogenase.

     

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.     

Heterozygous mutations in SIX3 and SHH are associated with schizencephaly and further expand the clinical spectrum of holoprosencephaly

Schizencephaly (SCH) is a clinically and etiologically heterogeneous cerebral malformation presenting as unilateral or bilateral hemispheric cleft with direct connection between the inner and outer liquor spaces. The SCH cleft is usually lined by gray matter, which appears polymicrogyric implying an associated impairment of neuronal migration. The majority of SCH patients are sporadic, but familial SCH has been described. An initial report of heterozygous mutations in the homeobox gene EMX2 could not be confirmed in 52 patients investigated in this study in agreement with two independent SCH patient cohorts published previously. SCH frequently occurs with additional cerebral malformations like hypoplasia or aplasia of the septum pellucidum or optic nerve, suggesting the involvement of genes important for the establishment of midline forebrain structures. We therefore considered holoprosencephaly (HPE)-associated genes as potential SCH candidates and report for the first time heterozygous mutations in SIX3 and SHH in a total of three unrelated patients and one fetus with SCH; one of them without obvious associated malformations of midline forebrain structures. Three of these mutations have previously been reported in independent patients with HPE. SIX3 acts directly upstream of SHH, and the SHH pathway is a key regulator of ventral forebrain patterning. Our data indicate that in a subset of patients SCH may develop as one aspect of a more complex malformation of the ventral forebrain, directly result from mutations in the SHH pathway and hence be considered as yet another feature of the broad phenotypic spectrum of holoprosencephaly.     

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.