Primary structure and processing of lysosomal alpha-glucosidase; homology with the intestinal sucrase-isomaltase complex.

Lysosomal alpha-glucosidase (acid maltase) is essential for degradation of glycogen in lysosomes. Enzyme deficiency results in glycogenosis type II. The amino acid sequence of the entire enzyme was derived from the nucleotide sequence of cloned cDNA. The cDNA comprises 3636 nt, and hybridizes with a messenger RNA of approximately 3.6 kb, which is absent in fibroblasts of two patients with glycogenosis type II. The encoded protein has a molecular mass of 104.645 kd and starts with a signal peptide. Sites of proteolytic processing are established by identification of N-terminal amino acid sequences of the 110-kd precursor, and the 76-kd and 70-kd mature forms of the enzyme encoded by the cDNA. Interestingly, both amino-terminal and carboxy-terminal processing occurs. Sites of sugar-chain attachment are proposed. A remarkable homology is observed between this soluble lysosomal alpha-glucosidase and the membrane-bound intestinal brush border sucrase-isomaltase enzyme complex. It is proposed that these enzymes are derived from the same ancestral gene. Around the putative active site of sucrase and isomaltase, 10 out of 13 amino acids are identical to the corresponding amino acids of lysosomal alpha-glucosidase. This strongly suggests that the aspartic acid residue at this position is essential for catalytic function of lysosomal alpha-glucosidase.     

A novel homozygous 10 nucleotide deletion in BBS10 causes Bardet–Biedl syndrome in a Pakistani family

Bardet–Biedl Syndrome is a multisystem autosomal recessive disorder characterized by central obesity, polydactyly, hypogonadism, learning difficulties, rod-cone dystrophy and renal dysplasia. Bardet–Biedl Syndrome has a prevalence rate ranging from 1 in 100,000 to 1 in 160,000 births although there are communities where Bardet–Biedl Syndrome is found at a higher frequency due to consanguinity. We report here a Pakistani consanguineous family with two affected sons with typical clinical features of Bardet–Biedl Syndrome, in addition to abnormal liver functioning and bilateral basal ganglia calcification, the latter feature being typical of Fahr's disease. Homozygous regions obtained from SNP array depicted three known genes BBS10, BBS14 and BBS2. Bidirectional sequencing of all coding exons by traditional sequencing of all these three genes showed a homozygous deletion of 10 nucleotides (c.1958_1967del), in BBS10 in both affected brothers. The segregation analysis revealed that the parents, paternal grandfather, maternal grandmother and an unaffected sister were heterozygous for the deletion. Such a large deletion in BBS10 has not been reported previously in any population and is likely to be contributing to the phenotype of Bardet–Biedl Syndrome in this family.     

Attenuation of pattern recognition receptor signaling is mediated by a MAP kinase kinase kinase

Pattern recognition receptors (PRRs) play a key role in plant and animal innate immunity. PRR binding of their cognate ligand triggers a signaling network and activates an immune response. Activation of PRR signaling must be controlled prior to ligand binding to prevent spurious signaling and immune activation. Flagellin perception in Arabidopsis through FLAGELLIN‐SENSITIVE 2 (FLS2) induces the activation of mitogen‐activated protein kinases (MAPKs) and immunity. However, the precise molecular mechanism that connects activated FLS2 to downstream MAPK cascades remains unknown. Here, we report the identification of a differentially phosphorylated MAP kinase kinase kinase that also interacts with FLS2. Using targeted proteomics and functional analysis, we show that MKKK7 negatively regulates flagellin‐triggered signaling and basal immunity and this requires phosphorylation of MKKK7 on specific serine residues. MKKK7 attenuates MPK6 activity and defense gene expression. Moreover, MKKK7 suppresses the reactive oxygen species burst downstream of FLS2, suggesting that MKKK7‐mediated attenuation of FLS2 signaling occurs through direct modulation of the FLS2 complex.     

Mutations in the calcium-binding motifs of CDH23 and the 35delG mutation in GJB2 cause hearing loss in one family

We have ascertained a multi-generation family with apparent autosomal recessive non-syndromic childhood hearing loss (DFNB). Failure to demonstrate linkage in a genome-wide scan with 300 polymorphic markers has suggested genetic heterogeneity for the hearing loss in this family. This heterogeneity could be demonstrated by analysis of candidate loci and genes for DFNB. Patients in one branch of the family (branch C) are homozygous for the 35delG mutation in the GJB2 gene (DFNB1). Patients in two other branches (A and B) carry two new mutations in the cadherin 23 ( CDH23) gene (DFNB12). A homozygous CDH23 c.6442G-->A (D2148N) mutation is present in branch A. Patients in branch B are compound heterozygous for this mutation and the c.4021G-->A (D1341N) mutation. The substituted aspartic acid residues are highly conserved and are part of the calcium-binding sites of the extracellular cadherin (EC) domains. Molecular modeling of the mutated EC domains of CDH23 based on the structure of E-cadherin indicates that calcium-binding is impaired. In addition, other aspartic and glutamic acid residue substitutions in the highly conserved calcium-binding sites reported to cause DFNB12 are also likely to result in a decreased affinity for calcium. Since calcium provides rigidity to the elongated structure of cadherin molecules enabling homophilic lateral interaction, these mutations are likely to impair interactions of CDH23 molecules either with CDH23 or with other proteins. DFNB12 is the first human disorder that can be attributed to inherited missense mutations in the highly conserved residues of the extracellular calcium-binding domain of a cadherin.     

Next-Generation Sequencing of a 40 Mb Linkage Interval Reveals TSPAN12 Mutations in Patients with Familial Exudative Vitreoretinopathy

Familial exudative vitreoretinopathy (FEVR) is a genetically heterogeneous retinal disorder characterized by abnormal vascularisation of the peripheral retina, often accompanied by retinal detachment. To date, mutations in three genes (FZD4, LRP5, and NDP) have been shown to be causative for FEVR. In two large Dutch pedigrees segregating autosomal-dominant FEVR, genome-wide SNP analysis identified an FEVR locus of ∼40 Mb on chromosome 7. Microsatellite marker analysis suggested similar at risk haplotypes in patients of both families. To identify the causative gene, we applied next-generation sequencing in the proband of one of the families, by analyzing all exons and intron-exon boundaries of 338 genes, in addition to microRNAs, noncoding RNAs, and other highly conserved genomic regions in the 40 Mb linkage interval. After detailed bioinformatic analysis of the sequence data, prioritization of all detected sequence variants led to three candidates to be considered as the causative genetic defect in this family. One of these variants was an alanine-to-proline substitution in the transmembrane 4 superfamily member 12 protein, encoded by TSPAN12. This protein has very recently been implicated in regulating the development of retinal vasculature, together with the proteins encoded by FZD4, LRP5, and NDP. Sequence analysis of TSPAN12 revealed two mutations segregating in five of 11 FEVR families, indicating that mutations in TSPAN12 are a relatively frequent cause of FEVR. Furthermore, we demonstrate the power of targeted next-generation sequencing technology to identify disease genes in linkage intervals.     

Neuropsychopharmacology and Neurogenetic Aspects of Executive Functioning: Should Reward Gene Polymorphisms Constitute a Diagnostic Tool to Identify Individuals at Risk for Impaired Judgment?

Executive functions are processes that act in harmony to control behaviors necessary for maintaining focus and achieving outcomes. Executive dysfunction in neuropsychiatric disorders is attributed to structural or functional pathology of brain networks involving prefrontal cortex (PFC) and its connections with other brain regions. The PFC receives innervations from different neurons associated with a number of neurotransmitters, especially dopamine (DA). Here we review findings on the contribution of PFC DA to higher-order cognitive and emotional behaviors. We suggest that examination of multifactorial interactions of an individual's genetic history, along with environmental risk factors, can assist in the characterization of executive functioning for that individual. Based upon the results of genetic studies, we also propose genetic mapping as a probable diagnostic tool serving as a therapeutic adjunct for augmenting executive functioning capabilities. We conclude that preservation of the neurological underpinnings of executive functions requires the integrity of complex neural systems including the influence of specific genes and associated polymorphisms to provide adequate neurotransmission.     

Inferring differences in the distribution of reaction rates across conditions

Elucidating changes in the distribution of reaction rates in metabolic pathways under different conditions is a central challenge in systems biology. Here we present a method for inferring regulation mechanisms responsible for changes in the distribution of reaction rates across conditions from correlations in time-resolved data. A reversal of correlations between conditions reveals information about regulation mechanisms. With the use of a small in silico hypothetical network, based on only the topology and directionality of a known pathway, several regulation scenarios can be formulated. Confronting these scenarios with experimental data results in a short list of possible pathway regulation mechanisms associated with the reversal of correlations between conditions. This procedure allows for the formulation of regulation scenarios without detailed prior knowledge of kinetics and for the inference of reaction rate changes without rate information. The method was applied to experimental time-resolved metabolomics data from multiple short-term perturbation-response experiments in S. cerevisiae across aerobic and anaerobic conditions. The method's output was validated against a detailed kinetic model of glycolysis in S. cerevisiae, which showed that the method can indeed infer the correct regulation scenario.     

Statistical data processing in clinical proteomics

This review discusses data analysis strategies for the discovery of biomarkers in clinical proteomics. Proteomics studies produce large amounts of data, characterized by few samples of which many variables are measured. A wealth of classification methods exists for extracting information from the data. Feature selection plays an important role in reducing the dimensionality of the data prior to classification and in discovering biomarker leads. The question which classification strategy works best is yet unanswered. Validation is a crucial step for biomarker leads towards clinical use. Here we only discuss statistical validation, recognizing that biological and clinical validation is of utmost importance. First, there is the need for validated model selection to develop a generalized classifier that predicts new samples correctly. A cross-validation loop that is wrapped around the model development procedure assesses the performance using unseen data. The significance of the model should be tested; we use permutations of the data for comparison with uninformative data. This procedure also tests the correctness of the performance validation. Preferably, a new set of samples is measured to test the classifier and rule out results specific for a machine, analyst, laboratory or the first set of samples. This is not yet standard practice. We present a modular framework that combines feature selection, classification, biomarker discovery and statistical validation; these data analysis aspects are all discussed in this review. The feature selection, classification and biomarker discovery modules can be incorporated or omitted to the preference of the researcher. The validation modules, however, should not be optional. In each module, the researcher can select from a wide range of methods, since there is not one unique way that leads to the correct model and proper validation. We discuss many possibilities for feature selection, classification and biomarker discovery. For validation we advice a combination of cross-validation and permutation testing, a validation strategy supported in the literature.