Molecular insights into RBR E3 ligase ubiquitin transfer mechanisms

RING‐in‐between‐RING (RBR) ubiquitin (Ub) ligases are a distinct class of E3s, defined by a RING1 domain that binds E2 Ub‐conjugating enzyme and a RING2 domain that contains an active site cysteine similar to HECT‐type E3s. Proposed to function as RING/HECT hybrids, details regarding the Ub transfer mechanism used by RBRs have yet to be defined. When paired with RING‐type E3s, E2s perform the final step of Ub ligation to a substrate. In contrast, when paired with RBR E3s, E2s must transfer Ub onto the E3 to generate a E3~Ub intermediate. We show that RBRs utilize two strategies to ensure transfer of Ub from the E2 onto the E3 active site. First, RING1 domains of HHARI and RNF144 promote open E2~Ubs. Second, we identify a Ub‐binding site on HHARI RING2 important for its recruitment to RING1‐bound E2~Ub. Mutations that ablate Ub binding to HHARI RING2 also decrease RBR ligase activity, consistent with RING2 recruitment being a critical step for the RBR Ub transfer mechanism. Finally, we demonstrate that the mechanism defined here is utilized by a variety of RBRs.     

Metabolic fingerprints of human primary endothelial and fibroblast cells

Introduction

Human primary cells originating from different locations within the body could differ greatly in their metabolic phenotypes, influencing both how they act during physiological/pathological processes and how susceptible/resistant they are to a variety of disease risk factors. A novel way to monitor cellular metabolism is through cell energetics assays, so we explored this approach with human primary cell types, as models of sclerotic disorders.

Objectives

In order to better understand pathophysiological processes at the cellular level, our goals were to measure metabolic pathway activities of endothelial cells and fibroblasts, and determine their metabolic phenotype profiles.

Methods

Biolog Phenotype MicroArray? technology was used for the first time to characterize metabolic phenotypes of diverse primary cells. These colorimetric assays enable detection of utilization of 367 specific biochemical substrates by human endothelial cells from the coronary artery (HCAEC), umbilical vein (HUVEC) and normal, healthy lung fibroblasts (NHLF).

Results

Adenosine, inosine, d-mannose and dextrin were strongly utilized by all three cell types, comparable to glucose. Substrates metabolized solely by HCAEC were mannan, pectin, gelatin and prevalently tricarballylic acid. HUVEC did not show any uniquely metabolized substrates whereas NHLF exhibited strong utilization of sugars and carboxylic acids along with amino acids and peptides.

Conclusion

Taken together, we show for the first time that this simple energetics assay platform enables metabolic characterization of primary cells and that each of the three human cell types examined gives a unique and distinguishable profile.

     

Adaptation to developmental diet influences the response to selection on age at reproduction in the fruit fly

Experimental evolution (EE) is a powerful tool for addressing how environmental factors influence life‐history evolution. While in nature different selection pressures experienced across the lifespan shape life histories, EE studies typically apply selection pressures one at a time. Here, we assess the consequences of adaptation to three different developmental diets in combination with classical selection for early or late reproduction in the fruit fly Drosophila melanogaster. We find that the response to each selection pressure is similar to that observed when they are applied independently, but the overall magnitude of the response depends on the selection regime experienced in the other life stage. For example, adaptation to increased age at reproduction increased lifespan across all diets; however, the extent of the increase was dependent on the dietary selection regime. Similarly, adaptation to a lower calorie developmental diet led to faster development and decreased adult weight, but the magnitude of the response was dependent on the age‐at‐reproduction selection regime. Given that multiple selection pressures are prevalent in nature, our findings suggest that trade‐offs should be considered not only among traits within an organism, but also among adaptive responses to different—sometimes conflicting—selection pressures, including across life stages.     

Predicting the success of an invader: Niche shift versus niche conservatism

Invasive species can encounter environments different from their source populations, which may trigger rapid adaptive changes after introduction (niche shift hypothesis). To test this hypothesis, we investigated whether postintroduction evolution is correlated with contrasting environmental conditions between the European invasive and source ranges in the Asian tiger mosquito Aedes albopictus. The comparison of environmental niches occupied in European and source population ranges revealed more than 96% overlap between invasive and source niches, supporting niche conservatism. However, we found evidence for postintroduction genetic evolution by reanalyzing a published ddRADseq genomic dataset from 90 European invasive populations using genotype–environment association (GEA) methods and generalized dissimilarity modeling (GDM). Three loci, among which a putative heat‐shock protein, exhibited significant allelic turnover along the gradient of winter precipitation that could be associated with ongoing range expansion. Wing morphometric traits weakly correlated with environmental gradients within Europe, but wing size differed between invasive and source populations located in different climatic areas. Niche similarities between source and invasive ranges might have facilitated the establishment of populations. Nonetheless, we found evidence for environmental‐induced adaptive changes after introduction. The ability to rapidly evolve observed in invasive populations (genetic shift) together with a large proportion of unfilled potential suitable areas (80%) pave the way to further spread of Ae. albopictus in Europe.     

A chromosome-scale assembly of the bilberry genome identifies a complex locus controlling berry anthocyanin composition

Bilberry (Vaccinium myrtillus L.) belongs to the Vaccinium genus, which includes blueberries (Vaccinium spp.) and cranberry (V. macrocarpon). Unlike its cultivated relatives, bilberry remains largely undomesticated, with berry harvesting almost entirely from the wild. As such, it represents an ideal target for genomic analysis, providing comparisons with the domesticated Vaccinium species. Bilberry is prized for its taste and health properties and has provided essential nutrition for Northern European indigenous populations. It contains high concentrations of phytonutrients, with perhaps the most important being the purple colored anthocyanins, found in both skin and flesh. Here, we present the first bilberry genome assembly, comprising 12 pseudochromosomes assembled using Oxford Nanopore (ONT) and Hi-C Technologies. The pseudochromosomes represent 96.6% complete BUSCO genes with an assessed LAI score of 16.3, showing a high conservation of synteny against the blueberry genome. Kmer analysis showed an unusual third peak, indicating the sequenced samples may have been from two individuals. The alternate alleles were purged so that the final assembly represents only one haplotype. A total of 36,404 genes were annotated after nearly 48% of the assembly was masked to remove repeats. To illustrate the genome quality, we describe the complex MYBA locus, and identify the key regulating MYB genes that determine anthocyanin production. The new bilberry genome builds on the genomic resources and knowledge of Vaccinium species, to help understand the genetics underpinning some of the quality attributes that breeding programs aspire to improve. The high conservation of synteny between bilberry and blueberry genomes means that comparative genome mapping can be applied to transfer knowledge about marker-trait association between these two species, as the loci involved in key characters are orthologous.     

Microbial biofilms: new catalysts for maximizing productivity of long-term biotransformations

The performance of biocatalytic reactions is often hampered by product and/or substrate toxicity and short-term reaction times due to instable biocatalysts. Microbes in biofilms show a remarkable resistance against biocides and form stable communities. In nature, especially in environments characterized by harsh conditions such as heavily contaminated sites, cells grow pre-dominantly in biofilms, which enable them to cope with physiological stress. This robustness was utilized to design a bioprocess concept based on catalytic biofilms for stable long-term transformations of toxic reactants. Sixty-nine bacterial strains have been screened to find organisms suitable for biofilm-based biotransformations. This included host strains important for recombinant enzyme expression and strains isolated from biofilters or contaminated soils. Nearly all organisms with bioremediation potential showed good biofilm forming capacities. Pseudomonas sp. strain VLB120DeltaC was chosen as a model organism due to its excellent biofilm forming capacity and its well-studied capability of catalyzing asymmetric epoxidations. A tubular reactor was used for the biotransformation of styrene to (S)-styrene oxide as a model reaction. The process was stable for at least 55 days at a maximal volumetric productivity of 16 g/(L(aq) day) and a yield of 9 mol%. In situ product extraction prevented product inhibition of the catalyst. Biofilm physiology and dynamics are characterized during the biotransformation and limitations and advantages of this reaction concept are discussed.     

The Mass Distance Fingerprint: a statistical framework for de novo detection of predominant modifications using high-accuracy mass spectrometry

We describe a statistical measure, Mass Distance Fingerprint, for automatic de novo detection of predominant peptide mass distances, i.e., putative protein modifications. The method's focus is to globally detect mass differences, not to assign peptide sequences or modifications to individual spectra. The Mass Distance Fingerprint is calculated from high accuracy measured peptide masses. For the data sets used in this study, known mass differences are detected at electron mass accuracy or better. The proposed method is novel because it works independently of protein sequence databases and without any prior knowledge about modifications. Both modified and unmodified peptides have to be present in the sample to be detected. The method can be used for automated detection of chemical/post-translational modifications, quality control of experiments and labeling approaches, and to control the modification settings of protein identification tools. The algorithm is implemented as a web application and is distributed as open source software.     

A workflow to increase the detection rate of proteins from unsequenced organisms in high-throughput proteomics experiments

We present and evaluate a strategy for the mass spectrometric identification of proteins from organisms for which no genome sequence information is available that incorporates cross-species information from sequenced organisms. The presented method combines spectrum quality scoring, de novo sequencing and error tolerant BLAST searches and is designed to decrease input data complexity. Spectral quality scoring reduces the number of investigated mass spectra without a loss of information. Stringent quality-based selection and the combination of different de novo sequencing methods substantially increase the catalog of significant peptide alignments. The de novo sequences passing a reliability filter are subsequently submitted to error tolerant BLAST searches and MS-BLAST hits are validated by a sampling technique. With the described workflow, we identified up to 20% more groups of homologous proteins in proteome analyses with organisms whose genome is not sequenced than by state-of-the-art database searches in an Arabidopsis thaliana database. We consider the novel data analysis workflow an excellent screening method to identify those proteins that evade detection in proteomics experiments as a result of database constraints.