5′UTR Variants of Ribosomal Protein S19 Transcript Determine Translational Efficiency: Implications for Diamond-Blackfan Anemia and Tissue Variability

Background: Diamond-Blackfan anemia (DBA) is a lineage specific and congenital erythroblastopenia. The disease is associated with mutations in genes encoding ribosomal proteins resulting in perturbed ribosomal subunit biosynthesis. The RPS19 gene is mutated in approximately 25 % of DBA patients and a variety of coding mutations have been described, all presumably leading to haploinsufficiency. A subset of patients carries rare polymorphic sequence variants within the 59untranslated region (59UTR) of RPS19. The functional significance of these variants remains unclear. Methodology/Principal Findings: We analyzed the distribution of transcriptional start sites (TSS) for RPS19 mRNAs in testis and K562 cells. Twenty-nine novel RPS19 transcripts were identified with different 59UTR length. Quantification of expressed w.t. 59UTR variants revealed that a short 59UTR correlates with high levels of RPS19. The total levels of RPS19 transcripts showed a broad variation between tissues. We also expressed three polymorphic RPS19 59UTR variants identified in DBA patients. The sequence variants include two insertions (c.-147_-146insGCCA and c.-147_-146insAGCC) and one deletion (c.-144_-141delTTTC). The three 59UTR polymorphisms are associated with a 20–30 % reduction in RPS19 protein levels when compared to the wild-type (w.t.) 59UTR of corresponding length. Conclusions: The RPS19 gene uses a broad range of TSS and a short 59UTR is associated with increased levels of RPS19. Comparisons between tissues showed a broad variation in the total amount of RPS19 mRNA and in the distribution of TS

siRNA Silencing of Proteasome Maturation Protein (POMP) Activates the Unfolded Protein Response and Constitutes a Model for KLICK Genodermatosis

Keratosis linearis with ichthyosis congenita and keratoderma (KLICK) is an autosomal recessive skin disorder associated with a single-nucleotide deletion in the 5′untranslated region of the proteasome maturation protein (POMP) gene. The deletion causes a relative switch in transcription start sites for POMP, predicted to decrease levels of POMP protein in terminally differentiated keratinocytes. To investigate the pathophysiology behind KLICK we created an in vitro model of the disease using siRNA silencing of POMP in epidermal air-liquid cultures. Immunohistochemical analysis of the tissue constructs revealed aberrant staining of POMP, proteasome subunits and the skin differentiation marker filaggrin when compared to control tissue constructs. The staining patterns of POMP siRNA tissue constructs showed strong resemblance to those observed in skin biopsies from KLICK patients. Western blot analysis of lysates from the organotypic tissue constructs revealed an aberrant processing of profilaggrin to filaggrin in samples transfected with siRNA against POMP. Knock-down of POMP expression in regular cell cultures resulted in decreased amounts of proteasome subunits. Prolonged silencing of POMP in cultured cells induced C/EBP homologous protein (CHOP) expression consistent with an activation of the unfolded protein response and increased endoplasmic reticulum (ER) stress. The combined results indicate that KLICK is caused by reduced levels of POMP, leading to proteasome insufficiency in differentiating keratinocytes. Proteasome insufficiency disturbs terminal epidermal differentiation, presumably by increased ER stress, and leads to perturbed processing of profilaggrin. Our findings underline a critical role for the proteasome in human epidermal differentiation

Red and Green Algal Origin of Diatom Membrane Transporters: Insights into Environmental Adaptation and Cell Evolution

Membrane transporters (MTs) facilitate the movement of molecules between cellular compartments. The evolutionary history of these key components of eukaryote genomes remains unclear. Many photosynthetic microbial eukaryotes (e.g., diatoms, haptophytes, and dinoflagellates) appear to have undergone serial endosymbiosis and thereby recruited foreign genes through endosymbiotic/horizontal gene transfer (E/HGT). Here we used the diatoms Thalassiosira pseudonana and Phaeodactylum tricornutum as models to examine the evolutionary origin of MTs in this important group of marine primary producers. Using phylogenomics, we used 1,014 diatom MTs as query against a broadly sampled protein sequence database that includes novel genome data from the mesophilic red algae Porphyridium cruentum and Calliarthron tuberculosum, and the stramenopile Ectocarpus siliculosus. Our conservative approach resulted in 879 maximum likelihood trees of which 399 genes show a non-lineal history between diatoms and other eukaryotes and prokaryotes (at the bootstrap value ≥70%). Of the eukaryote-derived MTs, 172 (ca. 25% of 697 examined phylogenies) have members of both red/green algae as sister groups, with 103 putatively arising from green algae, 19 from red algae, and 50 have an unresolved affiliation to red and/or green algae. We used topology tests to analyze the most convincing cases of non-lineal gene history in which red and/or green algae were nested within stramenopiles. This analysis showed that ca. 6% of all trees (our most conservative estimate) support an algal origin of MTs in stramenopiles with the majority derived from green algae. Our findings demonstrate the complex evolutionary history of photosynthetic eukaryotes and indicate a reticulate origin of MT genes in diatoms. We postulate that the algal-derived MTs acquired via E/HGT provided diatoms and other related microbial eukaryotes the ability to persist under conditions of fluctuating ocean chemistry, likely contributing to their great success in marine environments

The psychological science accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data

A global experiment on motivating social distancing during the COVID-19 pandemic

Finding communication strategies that effectively motivate social distancing continues to be a global public health priority during the COVID-19 pandemic. This cross-country, preregistered experiment (n = 25,718 from 89 countries) tested hypotheses concerning generalizable positive and negative outcomes of social distancing messages that promoted personal agency and reflective choices (i.e., an autonomy-supportive message) or were restrictive and shaming (i.e., a controlling message) compared with no message at all. Results partially supported experimental hypotheses in that the controlling message increased controlled motivation (a poorly internalized form of motivation relying on shame, guilt, and fear of social consequences) relative to no message. On the other hand, the autonomy-supportive message lowered feelings of defiance compared with the controlling message, but the controlling message did not differ from receiving no message at all. Unexpectedly, messages did not influence autonomous motivation (a highly internalized form of motivation relying on one’s core values) or behavioral intentions. Results supported hypothesized associations between people’s existing autonomous and controlled motivations and self-reported behavioral intentions to engage in social distancing. Controlled motivation was associated with more defiance and less long-term behavioral intention to engage in social distancing, whereas autonomous motivation was associated with less defiance and more short- and long-term intentions to social distance. Overall, this work highlights the potential harm of using shaming and pressuring language in public health communication, with implications for the current and future global health challenges

The Psychological Science Accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data

Prognosis and clinical presentation of BRCA2-associated breast cancer

54 female breast cancer patients from 22 families with BRCA2 germ line mutations from Sweden and Denmark were compared with 214 age- and date of diagnosis-matched controls identified among breast cancer patients from South Sweden. At diagnosis, BRCA2-associated cases were more often node-positive (N+). OR=1.9 (95% confidence interval (CI)=1.0-3.6; P=0.036), and were more often clinical stage IV: OR=4.6 (95% CI=1.3-17; P=0.021) than the controls. Bilateral disease was also more common among the BRCA2-associated cases: OR=2. 4 (95% CI=1.1-5.3; P=0.027). Breast cancer-specific survival (BCSS) was significantly worse among the BRCA2-associated cases: RR=2.0 (95% CI=1.2-3.4; P=0.010). When stage was corrected for in a multivariate analysis, BCSS was no longer significantly worse for the BRCA2-associated cases: RR=1.6 (95% CI=0.85-3.1). The corresponding effect after correction for bilateral disease was: RR=1.8 (95% CI=1.0-3.1; P=0.034). The unfavourable prognosis in BRCA2-associated breast cancer seems, to a great extent, to be a consequence of the higher clinical stage at diagnosis. The increased presence of bilateral cancers appears to have less impact on survival in this group of hereditary breast cancer. Data presented here needs to be taken into account when counselling healthy carriers of BRCA2 germ line mutations

Scientific Deep Machine Learning Concepts for the Prediction of Concentration Profiles and Chemical Reaction Kinetics: Consideration of Reaction Conditions

Emerging concepts from scientific deep machine learning such as physics-informed neural networks (PINNs) enable a data-driven approach for the study of complex kinetic problems. We present an extended framework that combines the advantages of PINNs with the detailed consideration of experimental parameter variations for the simulation and prediction of chemical reaction kinetics. The approach is based on truncated Taylor series expansions for the underlying fundamental equations, whereby the external variations can be interpreted as perturbations of the kinetic parameters. Accordingly, our method allows for an efficient consideration of experimental parameter settings and their influence on the concentration profiles and reaction kinetics. A particular advantage of our approach, in addition to the consideration of univariate and multivariate parameter variations, is the robust model-based exploration of the parameter space to determine optimal reaction conditions in combination with advanced reaction insights. The benefits of this concept are demonstrated for higher-order chemical reactions including catalytic and oscillatory systems in combination with small amounts of training data. All predicted values show a high level of accuracy, demonstrating the broad applicability and flexibility of our approach