Noncanonical and reversible cysteine ubiquitination prevents the overubiquitination of PEX5 at the peroxisomal membrane

PEX5, the peroxisomal protein shuttling receptor, binds newly synthesized proteins in the cytosol and transports them to the organelle. During its stay at the peroxisomal protein translocon, PEX5 is monoubiquitinated at its cysteine 11 residue, a mandatory modification for its subsequent ATP-dependent extraction back into the cytosol. The reason why a cysteine and not a lysine residue is the ubiquitin acceptor is unknown. Using an established rat liver-based cell-free in vitro system, we found that, in contrast to wild-type PEX5, a PEX5 protein possessing a lysine at position 11 is polyubiquitinated at the peroxisomal membrane, a modification that negatively interferes with the extraction process. Wild-type PEX5 cannot retain a polyubiquitin chain because ubiquitination at cysteine 11 is a reversible reaction, with the E2-mediated deubiquitination step presenting faster kinetics than PEX5 polyubiquitination. We propose that the reversible nonconventional ubiquitination of PEX5 ensures that neither the peroxisomal protein translocon becomes obstructed with polyubiquitinated PEX5 nor is PEX5 targeted for proteasomal degradation.

Sensitization trajectories to multiple allergen components in a population-based birth-cohort

BACKGROUND

The characteristics of allergic sensitization profiles can differ between populations and geographic regions, contributing differently to the association with allergic diseases. Consequently, the sensitization trajectories found in previous studies conducted in Northern Europe may not apply in Southern European countries.

OBJECTIVE

To identify trajectories of allergic sensitization profiles during childhood and evaluate the association with allergic outcomes, using data from a Portuguese birth cohort.

METHODS

A random sample from Generation XXI was screened for allergic sensitization at 10 years of age. Among 452 allergic sensitized children, 186 were tested with ImmunoCAP^™ ISAC multiplex array that detects 112 molecular components, at three follow-ups (4, 7, and 10 years old). Information on allergic outcomes (asthma, rhinitis, atopic dermatitis) was obtained at the 13-year-old follow-up. Latent class analysis (LCA) was used to identify clusters of participants with similar sensitization profiles. Then, sensitization trajectories were defined based on the most prevalent transitions between clusters over time. Logistic regression was applied to estimate the association between sensitization trajectories and allergic diseases.

RESULTS

Five trajectories were proposed: "no/few sensitizations," "early persistent house dust mites (HDM)," "early HDM and persistent/late grass pollen," "late grass pollen," and "late HDM." The "early HDM and persistent/late grass pollen" trajectory was associated with rhinitis and "early persistent HDM" with asthma and rhinitis.

CONCLUSION

Distinct sensitization trajectories pose different risks in the development of allergic diseases. These trajectories present some differences from those in Northern European countries and are important for planning adequate prevention health plans.

Effect of Polymer Dissolution Temperature and Conditioning Time on the Morphological and Physicochemical Characteristics of Poly(Vinylidene Fluoride) Membranes Prepared by Non-Solvent Induced Phase Separation

This work reports on the production of poly(vinylidene fluoride) (PVDF) membranes by non-solvent induced phase separation (NIPS) using N,N-dimethylformamide (DMF) as solvent and water as non-solvent. The influence of the processing conditions in the morphology, surface characteristics, structure, thermal and mechanical properties were evaluated for polymer dissolution temperatures between 25 and 150 °C and conditioning time between 0 and 10 min. Finger-like pore morphology was obtained for all membranes and increasing the polymer dissolution temperature led to an increase in the average pore size (≈0.9 and 2.1 µm), porosity (≈50 to 90%) and water contact angle (up to 80°), in turn decreasing the β PVDF content (≈67 to 20%) with the degree of crystallinity remaining approximately constant (≈56%). The conditioning time did not significantly affect the polymer properties studied. Thus, the control of NIPS parameters proved to be suitable for tailoring PVDF membrane properties.

A hybrid approach toward biomedical relation extraction training corpora: combining distant supervision with crowdsourcing

Biomedical relation extraction (RE) datasets are vital in the construction of knowledge bases and to potentiate the discovery of new interactions. There are several ways to create biomedical RE datasets, some more reliable than others, such as resorting to domain expert annotations. However, the emerging use of crowdsourcing platforms, such as Amazon Mechanical Turk (MTurk), can potentially reduce the cost of RE dataset construction, even if the same level of quality cannot be guaranteed. There is a lack of power of the researcher to control who, how and in what context workers engage in crowdsourcing platforms. Hence, allying distant supervision with crowdsourcing can be a more reliable alternative. The crowdsourcing workers would be asked only to rectify or discard already existing annotations, which would make the process less dependent on their ability to interpret complex biomedical sentences. In this work, we use a previously created distantly supervised human phenotype-gene relations (PGR) dataset to perform crowdsourcing validation. We divided the original dataset into two annotation tasks: Task 1, 70% of the dataset annotated by one worker, and Task 2, 30% of the dataset annotated by seven workers. Also, for Task 2, we added an extra rater on-site and a domain expert to further assess the crowdsourcing validation quality. Here, we describe a detailed pipeline for RE crowdsourcing validation, creating a new release of the PGR dataset with partial domain expert revision, and assess the quality of the MTurk platform. We applied the new dataset to two state-of-the-art deep learning systems (BiOnt and BioBERT) and compared its performance with the original PGR dataset, as well as combinations between the two, achieving a 0.3494 increase in average F-measure. The code supporting our work and the new release of the PGR dataset is available at https://github.com/lasigeBioTM/PGR-crowd.