N-terminal β-strand underpins biochemical specialization of an ATG8 isoform

Autophagy-related protein 8 (ATG8) is a highly conserved ubiquitin-like protein that modulates autophagy pathways by binding autophagic membranes and a number of proteins, including cargo receptors and core autophagy components. Throughout plant evolution, ATG8 has expanded from a single protein in algae to multiple isoforms in higher plants. However, the degree to which ATG8 isoforms have functionally specialized to bind distinct proteins remains unclear. Here, we describe a comprehensive protein-protein interaction resource, obtained using in planta immunoprecipitation (IP) followed by mass spectrometry (MS), to define the potato ATG8 interactome. We discovered that ATG8 isoforms bind distinct sets of plant proteins with varying degrees of overlap. This prompted us to define the biochemical basis of ATG8 specialization by comparing two potato ATG8 isoforms using both in vivo protein interaction assays and in vitro quantitative binding affinity analyses. These experiments revealed that the N-terminal β-strand-and, in particular, a single amino acid polymorphism-underpins binding specificity to the substrate PexRD54 by shaping the hydrophobic pocket that accommodates this protein's ATG8-interacting motif (AIM). Additional proteomics experiments indicated that the N-terminal β-strand shapes the broader ATG8 interactor profiles, defining interaction specificity with about 80 plant proteins. Our findings are consistent with the view that ATG8 isoforms comprise a layer of specificity in the regulation of selective autophagy pathways in plants

Bloom’s Syndrome and PICH Helicases Cooperate with Topoisomerase IIα in Centromere Disjunction before Anaphase

Centromeres are specialized chromosome domains that control chromosome segregation during mitosis, but little is known about the mechanisms underlying the maintenance of their integrity. Centromeric ultrafine anaphase bridges are physiological DNA structures thought to contain unresolved DNA catenations between the centromeres separating during anaphase. BLM and PICH helicases colocalize at these ultrafine anaphase bridges and promote their resolution. As PICH is detectable at centromeres from prometaphase onwards, we hypothesized that BLM might also be located at centromeres and that the two proteins might cooperate to resolve DNA catenations before the onset of anaphase. Using immunofluorescence analyses, we demonstrated the recruitment of BLM to centromeres from G2 phase to mitosis. With a combination of fluorescence in situ hybridization, electron microscopy, RNA interference, chromosome spreads and chromatin immunoprecipitation, we showed that both BLM-deficient and PICH-deficient prometaphase cells displayed changes in centromere structure. These cells also had a higher frequency of centromeric non disjunction in the absence of cohesin, suggesting the persistence of catenations. Both proteins were required for the correct recruitment to the centromere of active topoisomerase IIα, an enzyme specialized in the catenation/decatenation process. These observations reveal the existence of a functional relationship between BLM, PICH and topoisomerase IIα in the centromere decatenation process. They indicate that the higher frequency of centromeric ultrafine anaphase bridges in BLM-deficient cells and in cells treated with topoisomerase IIα inhibitors is probably due not only to unresolved physiological ultrafine anaphase bridges, but also to newly formed ultrafine anaphase bridges. We suggest that BLM and PICH cooperate in rendering centromeric catenates accessible to topoisomerase IIα, thereby facilitating correct centromere disjunction and preventing the formation of supernumerary centromeric ultrafine anaphase bridges

Synthetic biology to access and expand nature's chemical diversity

Bacterial genomes encode the biosynthetic potential to produce hundreds of thousands of complex molecules with diverse applications, from medicine to agriculture and materials. Accessing these natural products promises to reinvigorate drug discovery pipelines and provide novel routes to synthesize complex chemicals. The pathways leading to the production of these molecules often comprise dozens of genes spanning large areas of the genome and are controlled by complex regulatory networks with some of the most interesting molecules being produced by non-model organisms. In this Review, we discuss how advances in synthetic biology — including novel DNA construction technologies, the use of genetic parts for the precise control of expression and for synthetic regulatory circuits — and multiplexed genome engineering can be used to optimize the design and synthesis of pathways that produce natural products

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

To which world regions does the valence–dominance model of social perception apply?

Over the past 10 years, Oosterhof and Todorov’s valence–dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov’s methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov’s original analysis strategy, the valence–dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence–dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution.C.L. was supported by the Vienna Science and Technology Fund (WWTF VRG13-007); L.M.D. was supported by ERC 647910 (KINSHIP); D.I.B. and N.I. received funding from CONICET, Argentina; L.K., F.K. and Á. Putz were supported by the European Social Fund (EFOP-3.6.1.-16-2016-00004; ‘Comprehensive Development for Implementing Smart Specialization Strategies at the University of Pécs’). K.U. and E. Vergauwe were supported by a grant from the Swiss National Science Foundation (PZ00P1_154911 to E. Vergauwe). T.G. is supported by the Social Sciences and Humanities Research Council of Canada (SSHRC). M.A.V. was supported by grants 2016-T1/SOC-1395 (Comunidad de Madrid) and PSI2017-85159-P (AEI/FEDER UE). K.B. was supported by a grant from the National Science Centre, Poland (number 2015/19/D/HS6/00641). J. Bonick and J.W.L. were supported by the Joep Lange Institute. G.B. was supported by the Slovak Research and Development Agency (APVV-17-0418). H.I.J. and E.S. were supported by a French National Research Agency ‘Investissements d’Avenir’ programme grant (ANR-15-IDEX-02). T.D.G. was supported by an Australian Government Research Training Program Scholarship. The Raipur Group is thankful to: (1) the University Grants Commission, New Delhi, India for the research grants received through its SAP-DRS (Phase-III) scheme sanctioned to the School of Studies in Life Science; and (2) the Center for Translational Chronobiology at the School of Studies in Life Science, PRSU, Raipur, India for providing logistical support. K. Ask was supported by a small grant from the Department of Psychology, University of Gothenburg. Y.Q. was supported by grants from the Beijing Natural Science Foundation (5184035) and CAS Key Laboratory of Behavioral Science, Institute of Psychology. N.A.C. was supported by the National Science Foundation Graduate Research Fellowship (R010138018). We acknowledge the following research assistants: J. Muriithi and J. Ngugi (United States International University Africa); E. Adamo, D. Cafaro, V. Ciambrone, F. Dolce and E. Tolomeo (Magna Græcia University of Catanzaro); E. De Stefano (University of Padova); S. A. Escobar Abadia (University of Lincoln); L. E. Grimstad (Norwegian School of Economics (NHH)); L. C. Zamora (Franklin and Marshall College); R. E. Liang and R. C. Lo (Universiti Tunku Abdul Rahman); A. Short and L. Allen (Massey University, New Zealand), A. Ateş, E. Güneş and S. Can Özdemir (Boğaziçi University); I. Pedersen and T. Roos (Åbo Akademi University); N. Paetz (Escuela de Comunicación Mónica Herrera); J. Green (University of Gothenburg); M. Krainz (University of Vienna, Austria); and B. Todorova (University of Vienna, Austria). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.https://www.nature.com/nathumbehav/am2023BiochemistryGeneticsMicrobiology and Plant Patholog

To which world regions does the valence–dominance model of social perception apply?

Over the past 10 years, Oosterhof and Todorov’s valence–dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov’s methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov’s original analysis strategy, the valence–dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence–dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

A multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic.

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion-regulation strategy that modifies how one thinks about a situation. Participants from 87 countries and regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vesus both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing interventions had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world