MODY 2: Mutation identification and molecular ancestry in a Brazilian family

Maturity Onset Diabetes of the Young (MODY) is a heterogeneous group of genetic diseases characterized by a primary defect in insulin secretion and hyperglycemia, non-ketotic disease, monogenic autosomal dominant mode of inheritance, age at onset less than 25 years, and lack of auto-antibodies. It accounts for 2–5% of all cases of non-type 1 diabetes. MODY subtype 2 is caused by mutations in the glucokinase (GCK) gene. In this study, we sequenced the GCK gene of two volunteers with clinical diagnosis for MODY2 and we were able to identify four mutations including one for a premature stop codon (c.76C>T). Based on these results, we have developed a specific PCR-RFLP assay to detect this mutation and tested 122 related volunteers from the same family. This mutation in the GCK gene was detected in 21 additional subjects who also had the clinical features of this genetic disease. In conclusion, we identified new GCK gene mutations in a Brazilian family of Italian descendance, with one due to a premature stop codon located in the second exon of the gene. We also developed a specific assay that is fast, cheap and reliable to detect this mutation. Finally, we built a molecular ancestry model based on our results for the migration of individuals carrying this genetic mutation from Northern Italy to Brazil.     

Structure-wise discrimination of adenine and guanine by proteins on the basis of their nonbonded interactions

We have analyzed the nonbonded interactions of the structurally similar moieties, adenine and guanine forming complexes with proteins. The results comprise (a) the amino acid–ligand atom preferences, (b) solvent accessibility of ligand atoms before and after complex formation with proteins, and (c) preferred amino acid residue atoms involved in the interactions. We have observed that the amino acid preferences involved in the hydrogen bonding interactions vary for adenine and guanine. The structural variation between the purine atoms is clearly reflected by their burial tendency in the solvent environment. Correlation of the mean amino acid preference values show the variation that exists between adenine and guanine preferences of all the amino acid residues. All our observations provide evidence for the discriminating nature of the proteins in recognizing adenine and guanine.     

The Mechanism of Supercoiled DNA Recognition by Eukaryotic Type I Topoisomerases: II. A Comparison of the Enzyme Interaction with Specific and Nonspecific Oligonucleotides

Data on the interaction of DNA type I topoisomerases from the murine and human placenta cells with specific and nonspecific oligonucleotides of various structures and lengths are summarized. The relative contributions of various contacts between the enzymes and DNA that have previously been detected by X-ray analysis to the total affinity of the topoisomerases for DNA substrates are estimated. Factors that determine the differences in the enzyme interactions with specific and nonspecific single- and double-stranded DNAs are revealed. The results of the X-ray analysis of human DNA topoisomerase I are interpreted taking into account data on the comprehensive thermodynamic and kinetic analysis of the enzyme interaction with the specific and nonspecific DNAs.     

The role of nutrition on epigenetic modifications and their implications on health

Nutrition plays a key role in many aspects of health and dietary imbalances are major determinants of chronic diseases including cardiovascular disease, obesity, diabetes and cancer. Adequate nutrition is particularly essential during critical periods in early life (both pre- and postnatal). In this regard, there is extensive epidemiologic and experimental data showing that early sub-optimal nutrition can have health consequences several decades later.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Structure-based protein design with deep learning

Since the first revelation of proteins functioning as macromolecular machines through their three dimensional structures, researchers have been intrigued by the marvelous ways the biochemical processes are carried out by proteins. The aspiration to understand protein structures has fueled extensive efforts across different scientific disciplines. In recent years, it has been demonstrated that proteins with new functionality or shapes can be designed via structure-based modeling methods, and the design strategies have combined all available information — but largely piece-by-piece — from sequence derived statistics to the detailed atomic-level modeling of chemical interactions. Despite the significant progress, incorporating data-derived approaches through the use of deep learning methods can be a game changer. In this review, we summarize current progress, compare the arc of developing the deep learning approaches with the conventional methods, and describe the motivation and concepts behind current strategies that may lead to potential future opportunities.     

Dynamic and Reversible Aggregation of the Human CAP Superfamily Member GAPR-1 in Protein Inclusions in Saccharomyces cerevisiae

Many proteins that can assemble into higher order structures termed amyloids can also concentrate into cytoplasmic inclusions via liquid–liquid phase separation. Here, we study the assembly of human Golgi-Associated plant Pathogenesis Related protein 1 (GAPR-1), an amyloidogenic protein of the Cysteine-rich secretory proteins, Antigen 5, and Pathogenesis-related 1 proteins (CAP) protein superfamily, into cytosolic inclusions in Saccharomyces cerevisiae. Overexpression of GAPR-1-GFP results in the formation GAPR-1 oligomers and fluorescent inclusions in yeast cytosol. These cytosolic inclusions are dynamic and reversible organelles that gradually increase during time of overexpression and decrease after promoter shut-off. Inclusion formation is, however, a regulated process that is influenced by factors other than protein expression levels. We identified N-myristoylation of GAPR-1 as an important determinant at early stages of inclusion formation. In addition, mutations in the conserved metal-binding site (His54 and His103) enhanced inclusion formation, suggesting that these residues prevent uncontrolled protein sequestration. In agreement with this, we find that addition of Zn²⁺ metal ions enhances inclusion formation. Furthermore, Zn²⁺ reduces GAPR-1 protein degradation, which indicates stabilization of GAPR-1 in inclusions. We propose that the properties underlying both the amyloidogenic properties and the reversible sequestration of GAPR-1 into inclusions play a role in the biological function of GAPR-1 and other CAP family members.     

Biosynthesis of bacterial glycogen: purification and characterization of ADPglucose pyrophosphorylase with modified regulatory properties from Escherichia coli B mutant CL1136-504

The l-thyroxine binding site in human serum thyroxine-binding globulin was investigated by affinity labeling with N-bromoacetyl-l-thyroxine (BrAcT₄). Competitive binding studies showed that, in the presence of 100 molar excess of BrAcT₄, binding of thyroxine to thyroxine-binding globulin was nearly totally abolished. The reaction of BrAcT₄ to form covalent binding was inhibited in the presence of thyroxine and the affinity-labeled thyroxinebinding globulin lost its ability to bind thyroxine. These results indicate BrAcT₄ and thyroxine competed for the same binding site. Affinity labeling with 2 mol of BrAcT₄/mol of thyroxine-binding globulin resulted in the covalent attachment of 0.7 mol of ligand. By amino acid analysis and high voltage paper electrophoresis, methionine was identified as the major residue labeled (75%). Lysine, tyrosine, and histidine were also found to be labeled to the extent of 8, 8, and 5%, respectively.     

Plant phylogeny drives arboreal caterpillar assemblages across the Holarctic

1. Assemblages of insect herbivores are structured by plant traits such as nutrient content, secondary metabolites, physical traits, and phenology. Many of these traits are phylogenetically conserved, implying a decrease in trait similarity with increasing phylogenetic distance of the host plant taxa. Thus, a metric of phylogenetic distances and relationships can be considered a proxy for phylogenetically conserved plant traits and used to predict variation in herbivorous insect assemblages among co‐occurring plant species.
2. Using a Holarctic dataset of exposed‐feeding and shelter‐building caterpillars, we aimed at showing how phylogenetic relationships among host plants explain compositional changes and characteristics of herbivore assemblages.
3. Our plant–caterpillar network data derived from plot‐based samplings at three different continents included >28,000 individual caterpillar–plant interactions. We tested whether increasing phylogenetic distance of the host plants leads to a decrease in caterpillar assemblage overlap. We further investigated to what degree phylogenetic isolation of a host tree species within the local community explains abundance, density, richness, and mean specialization of its associated caterpillar assemblage.
4. The overlap of caterpillar assemblages decreased with increasing phylogenetic distance among the host tree species. Phylogenetic isolation of a host plant within the local plant community was correlated with lower richness and mean specialization of the associated caterpillar assemblages. Phylogenetic isolation had no effect on caterpillar abundance or density. The effects of plant phylogeny were consistent across exposed‐feeding and shelter‐building caterpillars.
5. Our study reveals that distance metrics obtained from host plant phylogeny are useful predictors to explain compositional turnover among hosts and host‐specific variations in richness and mean specialization of associated insect herbivore assemblages in temperate broadleaf forests. As phylogenetic information of plant communities is becoming increasingly available, further large‐scale studies are needed to investigate to what degree plant phylogeny structures herbivore assemblages in other biomes and ecosystems.