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Phenotypic plasticity, the ability to produce multiple phenotypes from a single genotype, represents an excellent model with which to examine the relationship between gene expression and phenotypes. Analyses of the molecular foundations of phenotypic plasticity are challenging, however, especially in the case of complex social phenotypes. Here we apply a machine learning approach to tackle this challenge by analyzing individual-level gene expression profiles of Polistes dominula paper wasps following the loss of a queen. We find that caste-associated gene expression profiles respond strongly to queen loss, and that this change is partly explained by attributes such as age but occurs even in individuals that appear phenotypically unaffected. These results demonstrate that large changes in gene expression may occur in the absence of outwardly detectable phenotypic changes, resulting here in a socially mediated de-differentiation of individuals at the transcriptomic level but not at the levels of ovarian development or behavior., Connecting genotypes to complex social behaviour is challenging. Taylor et al. use machine learning to show a strong response of caste-associated gene expression to queen loss, wherein individual wasp’s expression profiles become intermediate between queen and worker states, even in the absence of behavioural changes.

There is a need for large-scale, longitudinal studies to determine the mechanisms by which the gut microbiome and its interactions with the host affect human health and disease. Current methods for profiling the microbiome typically utilize next-generation sequencing applications that are expensive, slow, and complex. Here, we present a synthetic biology platform for affordable, on-demand, and simple analysis of microbiome samples using RNA toehold switch sensors in paper-based, cell-free reactions. We demonstrate species-specific detection of mRNAs from 10 different bacteria that affect human health and four clinically relevant host biomarkers. We develop a method to quantify mRNA using our toehold sensors and validate our platform on clinical stool samples by comparison to RT-qPCR. We further highlight the potential clinical utility of the platform by showing that it can be used to rapidly and inexpensively detect toxin mRNA in the diagnosis of Clostridium difficile infections., National Institutes of Health (U.S.) (Grant T32-DK007191)

Carbon dots (CDs) have been studied for years as one of the most promising fluorescent nanomaterials. However, CDs with red or solid-state fluorescence are rarely reported. Herein, through a one-pot solvothermal treatment, hydrophobic CDs (H-CDs) with blue dispersed emission and red aggregation-induced emission are obtained. When water is introduced, the hydrophobic interaction leads to aggregation of the H-CDs. The formation of H-CD clusters induces the turning off of the blue emission, as the carbonized cores suffer from π-π stacking interactions, and the turning on of the red fluorescence, due to restriction of the surfaces’ intramolecular rotation around disulfide bonds, which conforms to the aggregation-induced-emission phenomenon. This on-off fluorescence of the H-CDs is reversible when the H-CD powder is completely dissolved. Moreover, the H-CD solution dispersed in filter paper is nearly colorless. Finally, we develop a reversible two switch-mode luminescence ink for advanced anti-counterfeiting and dual-encryption., Carbon dots that display long-wavelength and multicolor emission are desirable for biological and anti-counterfeiting applications. Here, the authors design hydrophobic carbon dots with reversible two-mode fluorescence, which exhibit blue emission when dissolved in solution, and red solid-state fluorescence when aggregated.

7 billion tonnes of alkaline materials are produced globally each year as a product or by-product of industrial activity. The aqueous dissolution of these materials creates high pH solutions that dissolves CO2 to store carbon in the form of solid carbonate minerals or dissolved bicarbonate ions. Here we show that these materials have a carbon dioxide storage potential of 2.9–8.5 billion tonnes per year by 2100, and may contribute a substantial proportion of the negative emissions required to limit global temperature change to, The potential of biomass energy carbon capture and storage is unclear. Here the authors estimated the negative emissions potential from highly alkaline materials, by-products and wastes and showed that these materials have a CO2 storage potential of 2.5–7.5 billion tonnes per year by 2100.

Biological lignin valorization has emerged as a major solution for sustainable and cost-effective biorefineries. However, current biorefineries yield lignin with inadequate fractionation for bioconversion, yet substantial changes of these biorefinery designs to focus on lignin could jeopardize carbohydrate efficiency and increase capital costs. We resolve the dilemma by designing ‘plug-in processes of lignin’ with the integration of leading pretreatment technologies. Substantial improvement of lignin bioconversion and synergistic enhancement of carbohydrate processing are achieved by solubilizing lignin via lowering molecular weight and increasing hydrophilic groups, addressing the dilemma of lignin- or carbohydrate-first scenarios. The plug-in processes of lignin could enable minimum polyhydroxyalkanoate selling price at as low as $6.18/kg. The results highlight the potential to achieve commercial production of polyhydroxyalkanoates as a co-product of cellulosic ethanol. Here, we show that the plug-in processes of lignin could transform biorefinery design toward sustainability by promoting carbon efficiency and optimizing the total capital cost., The current biorefineries yield lignin with inadequate fractionation for bioconversion, yet substantial changes of these biorefinery designs could jeopardize carbohydrate efficiency and increase capital costs. Here the authors resolve the dilemma by designing ‘plug-in processes of lignin’ to enable economic waste valorization.

Maximizing the conversion of biogenic carbon feedstocks into chemicals and fuels is essential for fermentation processes as feedstock costs and processing is commonly the greatest operating expense. Unfortunately, for most fermentations, over one-third of sugar carbon is lost to CO2 due to the decarboxylation of pyruvate to acetyl-CoA and limitations in the reducing power of the bio-feedstock. Here we show that anaerobic, non-photosynthetic mixotrophy, defined as the concurrent utilization of organic (for example, sugars) and inorganic (for example, CO2) substrates in a single organism, can overcome these constraints to increase product yields and reduce overall CO2 emissions. As a proof-of-concept, Clostridium ljungdahlii was engineered to produce acetone and achieved a mass yield 138% of the previous theoretical maximum using a high cell density continuous fermentation process. In addition, when enough reductant (that is, H2) is provided, the fermentation emits no CO2. Finally, we show that mixotrophy is a general trait among acetogens., Microbial fermentation yield is limited by CO2 loss in glycolysis. Here, the authors engineered Clostridium ljungdahlii for the anaerobic, non-photosynthetic mixotrophy production of acetone, increasing carbon product yield while reducing CO2 emissions from a biogenic feedstock fermentation.

Culture contamination, end-product toxicity, and energy efficient product recovery are long-standing bioprocess challenges. To solve these problems, we propose a high-pressure fermentation strategy, coupled with in situ extraction using the abundant and renewable solvent supercritical carbon dioxide (scCO2), which is also known for its broad microbial lethality. Towards this goal, we report the domestication and engineering of a scCO2-tolerant strain of Bacillus megaterium, previously isolated from formation waters from the McElmo Dome CO2 field, to produce branched alcohols that have potential use as biofuels. After establishing induced-expression under scCO2, isobutanol production from 2-ketoisovalerate is observed with greater than 40% yield with co-produced isopentanol. Finally, we present a process model to compare the energy required for our process to other in situ extraction methods, such as gas stripping, finding scCO2 extraction to be potentially competitive, if not superior., End-product toxicity, culture contamination, and energy efficient product recovery are long-standing issues in bioprocessing. Here, the authors address these problems using a fermentation strategy that combines microbial production of branched alcohols with supercritical carbon dioxide extraction.

The Japanese government has announced a commitment to net-zero greenhouse gas emissions by 2050. It envisages an important role for hydrogen in the nation’s future energy economy. This paper explores the possibility that a significant source for this hydrogen could be produced by electrolysis fueled by power generated from offshore wind in China. Hydrogen could be delivered to Japan either as liquid, or bound to a chemical carrier such as toluene, or as a component of ammonia. The paper presents an analysis of factors determining the ultimate cost for this hydrogen, including expenses for production, storage, conversion, transport, and treatment at the destination. It concludes that the Chinese source could be delivered at a volume and cost consistent with Japan’s idealized future projections., Hydrogen is regarded as important to Japan’s clean energy transition. Here the authors consider the production of hydrogen by electrolysis fueled by offshore wind power in China, and the potential for delivery to Japan as part of Japan’s transition.

The temperature scales of screening of local magnetic and orbital moments are important characteristics of strongly correlated substances. In a recent paper X. Deng et al. using dynamic mean-field theory (DMFT) have identified temperature scales of the onset of screening in orbital and spin channels in some correlated metals from the deviation of temperature dependence of local susceptibility from the Curie law. We argue that the scales obtained this way are in fact much larger, than the corresponding Kondo temperatures, and, therefore, do not characterize the screening process. By reanalyzing the results of this paper we find the characteristic (Kondo) temperatures for screening in the spin channel $T_K\approx 100$ K for V$_2$O$_3$ and $T_K\approx 350$ K for Sr$_2$RuO$_4$, which are almost an order of magnitude smaller than those for the onset of the screening estimated in the paper ($1000$ K and $2300$ K, respectively); for V$_2$O$_3$ the obtained temperature scale $T_K$ is therefore comparable to the temperature of completion of the screening, $T^{\rm comp}\sim 25$ K, which shows that the screening in this material can be described in terms of a single temperature scale., This is a post-peer-review, pre-copyedit version of an article published in Matters Arising section of Nature Communications. The final authenticated version is available online at http://dx.doi.org/10.1038/s41467-021-21641-2

Author(s): Cao, Wei; Banerjee, Kaustav | Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Author(s): Daya, Michelle; Rafaels, Nicholas; Brunetti, Tonya M; Chavan, Sameer; Levin, Albert M; Shetty, Aniket; Gignoux, Christopher R; Boorgula, Meher Preethi; Wojcik, Genevieve; Campbell, Monica; Vergara, Candelaria; Torgerson, Dara G; Ortega, Victor E; Doumatey, Ayo; Johnston, Henry Richard; Acevedo, Nathalie; Araujo, Maria Ilma; Avila, Pedro C; Belbin, Gillian; Bleecker, Eugene; Bustamante, Carlos; Caraballo, Luis; Cruz, Alvaro; Dunston, Georgia M; Eng, Celeste; Faruque, Mezbah U; Ferguson, Trevor S; Figueiredo, Camila; Ford, Jean G; Gan, Weiniu; Gourraud, Pierre-Antoine; Hansel, Nadia N; Hernandez, Ryan D; Herrera-Paz, Edwin Francisco; Jimenez, Silvia; Kenny, Eimear E; Knight-Madden, Jennifer; Kumar, Rajesh; Lange, Leslie A; Lange, Ethan M; Lizee, Antoine; Maul, Pissamai; Maul, Trevor; Mayorga, Alvaro; Meyers, Deborah; Nicolae, Dan L; O'Connor, Timothy D; Oliveira, Ricardo Riccio; Olopade, Christopher O; Olopade, Olufunmilayo; Qin, Zhaohui S; Rotimi, Charles; Vince, Nicolas; Watson, Harold; Wilks, Rainford J; Wilson, James G; Salzberg, Steven; Ober, Carole; Burchard, Esteban G; Williams, L Keoki; Beaty, Terri H; Taub, Margaret A; Ruczinski, Ingo; Mathias, Rasika A; Barnes, Kathleen C; CAAPA | Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Inspired by the social and economic benefits of diversity, we analyze over 9 million papers and 6 million scientists to study the relationship between research impact and five classes of diversity: ethnicity, discipline, gender, affiliation, and academic age. Using randomized baseline models, we establish the presence of homophily in ethnicity, gender and affiliation. We then study the effect of diversity on scientific impact, as reflected in citations. Remarkably, of the classes considered, ethnic diversity had the strongest correlation with scientific impact. To further isolate the effects of ethnic diversity, we used randomized baseline models and again found a clear link between diversity and impact. To further support these findings, we use coarsened exact matching to compare the scientific impact of ethnically diverse papers and scientists with closely-matched control groups. Here, we find that ethnic diversity resulted in an impact gain of 10.63% for papers, and 47.67% for scientists., Diversity is believed to raise effectiveness and performance but it contains many aspects. Here the authors studied the relationship between research impact and five classes of diversity and found that ethnic diversity had the strongest correlation with scientific impact.

Recently, we classified the oceans into 30 biogeographic realms based on species’ endemicity. Castro-Insua et al. criticize the choices of dissimilarity coefficients and clustering approaches used in our paper, and reanalyse the data using alternative techniques. Here, we explain how the approaches used in our original paper yield results in line with existing biogeographical knowledge and are robust to alternative methods of analysis. We also repeat the analysis using several similarity coefficients and clustering algorithms, and a neural network theory method. Although each combination of methods produces outputs differing in detail, the overall pattern of realms is similar. The coarse nature of the present boundaries of the realms reflects the limited field data but may be improved with additional data and mapping to environmental variables.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Author(s): Siddiqi, Farah H; Menzies, Fiona M; Lopez, Ana; Stamatakou, Eleanna; Karabiyik, Cansu; Ureshino, Rodrigo; Ricketts, Thomas; Jimenez-Sanchez, Maria; Esteban, Miguel Angel; Lai, Liangxue; Tortorella, Micky D; Luo, Zhiwei; Liu, Hao; Metzakopian, Emmanouil; Fernandes, Hugo JR; Bassett, Andrew; Karran, Eric; Miller, Bruce L; Fleming, Angeleen; Rubinsztein, David C | Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The PCAWG Consortium has recently released an unprecedented set of tumor whole genome sequence (WGS) data from 2,658 cancer patients across 38 different primary tumor sites1. WGS is able to document the quantity and distribution of telomeric repeats2. In one of the papers analyzing the PCAWG dataset, Sieverling et al.3 confirmed previous data4 indicating that tumors with truncating ATRX or DAXX alterations, referred to as ATRX/DAXXtrunc, have an aberrant telomere variant repeat (TVR) distribution. By regarding these mutations, vs. TERT modifications (TERTmod; i.e. promoter mutations +/− amplifications +/− structural variations), as indicators of Alternative Lengthening of Telomeres (ALT) vs. telomerase, they built a random forest classifier for ALT-probability, and then associated genomic characteristics with the putative Telomere Maintenance Mechanism (TMM)3. However, we show here that equating ATRX/DAXXtrunc and TERTmod with ALT and telomerase, respectively, results in TMM predictions which correlate poorly with TMM assay data. ATRX/DAXXtrunc mutations are heterogeneously distributed in ALT-positive (ALT+) tumors of different types, as are TERTmod in telomerase-positive tumors4. Although these mutations are strongly associated with TMM, most tumors do not harbor them, making them an inadequate basis for building a classifier in a large-scale pan-cancer study4–7. Here, we provide a new analysis of the PCAWG data, based on C-circle assay (CCA)8 that is available for a subset of these tumors4,9,10. We show that the Sieverling et al. score overestimates the proportion of ALT associated with ATRX/DAXXtrunc and misclassifies ALT tumors when these mutations are absent. We also show some TVR correlate with ATRX/DAXXtrunc mutations, regardless of TMM. Finally, we propose a new classifier to identify ALT tumors in the PCAWG cohort.

Origin licensing ensures precise once per cell cycle replication in eukaryotic cells. The Origin Recognition Complex, Cdc6 and Cdt1 load Mcm2-7 helicase (MCM) into a double hexamer, bound around duplex DNA. The complex formed by ORC-Cdc6 bound to duplex DNA (OC) recruits the MCM-Cdt1 complex into the replication origins. Through the stacking of both complexes, the duplex DNA is inserted inside the helicase by an unknown mechanism. In this paper we show that the DNA insertion comes with a topological problem in the stacking of OC with MCM-Cdt1. Unless an essential, conserved C terminal winged helix domain (C-WHD) of Cdt1 is present, the MCM splits into two halves. The binding of this domain with the essential C-WHD of Mcm6, allows the latching between the MCM-Cdt1 and OC, through a conserved Orc5 AAA-lid interaction. Our work provides new insights into how DNA is inserted into the eukaryotic replicative helicase, through a series of synchronized events., During pre-Replication Complex, eukaryotic cells load two MCMs into a head-to-head Double Hexamer around duplex DNA (DH). Here the authors preRC assembly assay with purified proteins to reveal insights into S. cerevisiae’s first steps that lead to the DH formation.

The importance of statistical analyses on 2D materials-based electronic devices and circuits is sometimes overlooked. Here the authors discuss the most pressing integration issues for such devices and emphasize the need for yield, variability, reliability, and stability benchmarking, and outline viable strategies resulting in research papers that are useful for the industry.

We study mentorship in scientific collaborations, where a junior scientist is supported by potentially multiple senior collaborators, without them necessarily having formal supervisory roles. We identify 3 million mentor–protégé pairs and survey a random sample, verifying that their relationship involved some form of mentorship. We find that mentorship quality predicts the scientific impact of the papers written by protégés post mentorship without their mentors. We also find that increasing the proportion of female mentors is associated not only with a reduction in post-mentorship impact of female protégés, but also a reduction in the gain of female mentors. While current diversity policies encourage same-gender mentorships to retain women in academia, our findings raise the possibility that opposite-gender mentorship may actually increase the impact of women who pursue a scientific career. These findings add a new perspective to the policy debate on how to best elevate the status of women in science.

Miscanthus is a perennial wild grass that is of global importance for paper production, roofing, horticultural plantings, and an emerging highly productive temperate biomass crop. We report a chromosome-scale assembly of the paleotetraploid M. sinensis genome, providing a resource for Miscanthus that links its chromosomes to the related diploid Sorghum and complex polyploid sugarcanes. The asymmetric distribution of transposons across the two homoeologous subgenomes proves Miscanthus paleo-allotetraploidy and identifies several balanced reciprocal homoeologous exchanges. Analysis of M. sinensis and M. sacchariflorus populations demonstrates extensive interspecific admixture and hybridization, and documents the origin of the highly productive triploid bioenergy crop M. × giganteus. Transcriptional profiling of leaves, stem, and rhizomes over growing seasons provides insight into rhizome development and nutrient recycling, processes critical for sustainable biomass accumulation in a perennial temperate grass. The Miscanthus genome expands the power of comparative genomics to understand traits of importance to Andropogoneae grasses., The perennial grass Miscanthus is a promising biomass crop. Here, via genomics and transcriptomics, the authors reveal its allotetraploid origin, characterize gene expression associated with rhizome development and nutrient recycling, and describe the hybrid origin of the triploid M. x giganteus.

The CRISPR-Cas12a RNA-guided complexes have tremendous potential for nucleic acid detection but are limited to the picomolar detection limit without an amplification step. Here, we develop a platform with engineered crRNAs and optimized conditions that enabled us to detect various clinically relevant nucleic acid targets with higher sensitivity, achieving a limit of detection in the femtomolar range without any target pre-amplification step. By extending the 3′- or 5′-ends of the crRNA with different lengths of ssDNA, ssRNA, and phosphorothioate ssDNA, we discover a self-catalytic behavior and an augmented rate of LbCas12a-mediated collateral cleavage activity as high as 3.5-fold compared to the wild-type crRNA and with significant improvement in specificity for target recognition. Particularly, the 7-mer DNA extension to crRNA is determined to be universal and spacer-independent for enhancing the sensitivity and specificity of LbCas12a-mediated nucleic acid detection. We perform a detailed characterization of our engineered ENHANCE system with various crRNA modifications, target types, reporters, and divalent cations. With isothermal amplification of SARS-CoV-2 RNA using RT-LAMP, the modified crRNAs are incorporated in a paper-based lateral flow assay that can detect the target with up to 23-fold higher sensitivity within 40–60 min., CRISPR-Cas12a based detection systems can be sensitive down to the picomolar range. Here the authors modify the 3′- and 5′-ends of the crRNA and show this enhances trans-cleavage for improved sensitivity.

Non-invasive assessment of the risk of lymph node metastasis (LNM) in patients with papillary thyroid carcinoma (PTC) is of great value for the treatment option selection. The purpose of this paper is to develop a transfer learning radiomics (TLR) model for preoperative prediction of LNM in PTC patients in a multicenter, cross-machine, multi-operator scenario. Here we report the TLR model produces a stable LNM prediction. In the experiments of cross-validation and independent testing of the main cohort according to diagnostic time, machine, and operator, the TLR achieves an average area under the curve (AUC) of 0.90. In the other two independent cohorts, TLR also achieves 0.93 AUC, and this performance is statistically better than the other three methods according to Delong test. Decision curve analysis also proves that the TLR model brings more benefit to PTC patients than other methods., A non-destructive and efficient method for predicting the risk of lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) patients is highly needed. Here, the authors develop a transfer learning radiomics model for preoperative prediction of LNM in patients with PTC in a multicenter scenario.

Molècules de senyalització extracel·lular; Mecanismes de la malaltia; Metàstasi Moléculas de señalización extracelular; Mecanismos de la enfermedad; Metástasis Extracellular signalling molecules, Mechanisms of disease; Metastasis Metastasis, the spread of malignant cells from a primary tumour to distant sites, causes 90% of cancer-related deaths. The integrin ITGB3 has been previously described to play an essential role in breast cancer metastasis, but the precise mechanisms remain undefined. We have now uncovered essential and thus far unknown roles of ITGB3 in vesicle uptake. The functional requirement for ITGB3 derives from its interactions with heparan sulfate proteoglycans (HSPGs) and the process of integrin endocytosis, allowing the capture of extracellular vesicles and their endocytosis-mediated internalization. Key for the function of ITGB3 is the interaction and activation of focal adhesion kinase (FAK), which is required for endocytosis of these vesicles. Thus, ITGB3 has a central role in intracellular communication via extracellular vesicles, proposed to be critical for cancer metastasis. The authors thank Hector Peinado and his laboratory team (Microenvironment & Metastasis Group, Molecular Oncology Program, Spanish National Cancer Research Centre (CNIO)). The authors thank Dr. Manel Bosch for helpful discussion and assistance with confocal microscopy. The authors thank Dr. Anne Spang and Dr Jordi Berenguer for helpful suggestions and discussion on the paper, and Jane Marshall for language review and editing support. This work was supported by Fondo de Investigaciones Sanitarias (PI14/01320), Redes Temáticas de Investigación Cooperativa en Salud (RD12/0036/0057) and CIBERONC (CB16/12/00363). SRC acknowledges support from the Generalitat de Catalunya (2014 SGR 1131). The CRG/UPF Proteomics Unit is part of the Spanish Infrastructure for Omics Technologies (ICTS OmicsTech) and it is a member of the ProteoRed PRB3 consortium which is supported by grant PT17/0019 of the PE I + D + i 2013-2016 from the Instituto de Salud Carlos III (ISCIII) and ERDF.

Influenza viruses are presumed, but not conclusively known, to spread among humans by several possible routes. We provide evidence of a mode of transmission seldom considered for influenza: airborne virus transport on microscopic particles called “aerosolized fomites.” In the guinea pig model of influenza virus transmission, we show that the airborne particulates produced by infected animals are mainly non-respiratory in origin. Surprisingly, we find that an uninfected, virus-immune guinea pig whose body is contaminated with influenza virus can transmit the virus through the air to a susceptible partner in a separate cage. We further demonstrate that aerosolized fomites can be generated from inanimate objects, such as by manually rubbing a paper tissue contaminated with influenza virus. Our data suggest that aerosolized fomites may contribute to influenza virus transmission in animal models of human influenza, if not among humans themselves, with important but understudied implications for public health., Influenza viruses are believed to transmit through the air as respiratory droplets or aerosols. In the guinea pig model, Asadi et al. show that influenza virus can also be transmitted as aerosolized fomites, which are microscopic dust particles stirred up from a virus-contaminated environment.

Cytokinesis requires the constriction of ESCRT-III filaments on the side of the midbody, where abscission occurs. After ESCRT recruitment at the midbody, it is not known how the ESCRT-III machinery localizes to the abscission site. To reveal actors involved in abscission, we obtained the proteome of intact, post-abscission midbodies (Flemmingsome) and identified 489 proteins enriched in this organelle. Among these proteins, we further characterized a plasma membrane-to-ESCRT module composed of the transmembrane proteoglycan syndecan-4, ALIX and syntenin, a protein that bridges ESCRT-III/ALIX to syndecans. The three proteins are highly recruited first at the midbody then at the abscission site, and their depletion delays abscission. Mechanistically, direct interactions between ALIX, syntenin and syndecan-4 are essential for proper enrichment of the ESCRT-III machinery at the abscission site, but not at the midbody. We propose that the ESCRT-III machinery must be physically coupled to a membrane protein at the cytokinetic abscission site for efficient scission, uncovering common requirements in cytokinesis, exosome formation and HIV budding., ESCRT filaments drive the final abscission between two daughter cells but how they physically interact with the membrane is unclear. Using proteomics, the authors show that syndecan-4/syntenin/ALIX couples the ESCRT machinery to the abscission site and thus promotes efficient abscission.

14 páginas, 6 figuras. Supplementary information is available for this paper at https://doi.org/10.1038/s41467-020-15832-6. Sequence data are deposited on NCBI GEO database with the accession code GSE138580, Genetic diversity of Mycobacterium tuberculosis affects immune responses and clinical outcomes of tuberculosis (TB). However, how bacterial diversity orchestrates immune responses to direct distinct TB severities is unknown. Here we study 681 patients with pulmonary TB and show that M. tuberculosis isolates from cases with mild disease consistently induce robust cytokine responses in macrophages across multiple donors. By contrast, bacteria from patients with severe TB do not do so. Secretion of IL-1β is a good surrogate of the differences observed, and thus to classify strains as probable drivers of different TB severities. Furthermore, we demonstrate that M. tuberculosis isolates that induce low levels of IL-1β production can evade macrophage cytosolic surveillance systems, including cGAS and the inflammasome. Isolates exhibiting this evasion strategy carry candidate mutations, generating sigA recognition boxes or affecting components of the ESX-1 secretion system. Therefore, we provide evidence that M. tuberculosis strains manipulate host-pathogen interactions to drive variable TB severities, This work was financed by FCT-Fundação para a Ciência e a Tecnologia/ Ministério da Ciência, Tecnologia e Inovação grant POCI-01-0145-FEDER-028955 (to M.S.) and by the Northern Portugal Regional Operational Program (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER) (NORTE-01-0145-FEDER-000013, to M.I.V., F.R., A.G.C., and N.S.O.). I.C.acknowledges the support of Ministerio de Ciencia, Innovación y Universidades (SAF2016-77346-R) and the European Research Council (638553-TB-ACCELERATE). H.N.B. acknowledges the support of Bolsa D. Manuel de Mello and of the Portuguese Society for Pneumology; A.B. and M.S. were also recipients of an International Exchanges Grant from the Royal Society. J.S. is funded by a research fellow NORTE-01-0145-FEDER-000012; B.C. and K.L.F. are funded by FCT Ph.D scholarships SFRH/BD/114403/2016 and SFRH/BD/114405/2016, respectively; M.I.V. is funded by FCT through DL 57/2016 (CRP) and MS through Estimulo Individual ao Emprego Científico. We thank the excellent support from the i3S scientific platforms, namely Animal facility, Advanced Light Microscopy, and BioSciences Screening, member of the national infrastructure PPBI-Portuguese Platform of Bioimaging (PPBI-POCI-01-0145-FEDER-022122)and Genomics (GenCore) part of the GenomePT project (POCI-01-0145-FEDER022184), supported by COMPETE 2020 - Operational Programme for Competitiveness and Internationalisation (POCI), Lisboa Portugal Regional Operational Programme (Lisboa2020), Algarve Portugal Regional Operational Programme (CRESC Algarve2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), and by Fundação para a Ciência e a Tecnologia (FCT).

We examined the long-term impact of coauthorship with established, highly-cited scientists on the careers of junior researchers in four scientific disciplines. Here, using matched pair analysis, we find that junior researchers who coauthor work with top scientists enjoy a persistent competitive advantage throughout the rest of their careers, compared to peers with similar early career profiles but without top coauthors. Such early coauthorship predicts a higher probability of repeatedly coauthoring work with top-cited scientists, and, ultimately, a higher probability of becoming one. Junior researchers affiliated with less prestigious institutions show the most benefits from coauthorship with a top scientist. As a consequence, we argue that such institutions may hold vast amounts of untapped potential, which may be realised by improving access to top scientists., By examining publication records of scientists from four disciplines, the authors show that coauthoring a paper with a top-cited scientist early in one's career predicts lasting increases in career success, especially for researchers affiliated with less prestigious institutions.

HFD-bound and HFD-free simulation systems presented in the paper; see table_of_simulations.pdf Contents of the simulation_archive: _FORCEFIELD: Force field parameters and topologies in GROMACS format amber-ff14SB.ff: The required force field parameters compiled for all systems.*** actin: chicken actin | topology (mol.itp)***, structure (mol.gro) ncap: mouse HFD domain (CAP) | topology (mol.itp)***, structure (mol.gro) ADP: ADP | topology (mol.itp)***, structure (mol.gro) MMG: multisite Mg2+ | topology (mol.itp)***, structure (mol.gro) cofilin: rabbit cofilin | topology (mol.itp)***, structure (mol.gro) dock: the "platform" region | topology (mol.itp), structure (mol.gro), the position restraints (position_restraints.itp) _parametrize_HIC: Amber format parameters for methyl-histidine (Nτ-Methyl-L-histidine, HIC) to be used together with amber-ff14SB force field. Charges were calculated based on the protocol by Duan, Y. et al. A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations. J. Comput. Chem. 24, 1999–2012 (2003). Missing bonded parameters were adopted from GAFF2. *** Converted to GROMACS from amber format using the ParmEd tool (https://github.com/ParmEd/ParmEd) HFD-bound: contains the directories for each simulation repeat listed in the table of simulations. 1, 2, and 3: simulations that were started by replacing the terminal actins with HFD-bound actins. 1' and 2': simulations that were started by docking HFD after some simulation without HFD (see below HFD-free simulations 1 and 2) HFD-free: contains the directories for each simulation repeat listed in the table of simulations. 1, 2, and 3: simulations of the cofilin-decorated actin filament. 2': simulations that was started by removing HFD from the HFD-bound system (see above HFD-bound simulation 2) Each subdirectory (under 1 2 3, etc.) contains prod.mdp: simulation setting file topol.top: GROMACS topology file t0.pdb: initial coordinates for simulation obtained after a set of restrained NVT and NpT equilibration steps prod0.tpr: the GROMACS tpr file index.ndx: index file nW.pdb: t0.pdb with all water molecules removed nW.xtc: the simulation trajectory with all water molecules removed. _FORCEFIELD: link to ../../_FORCEFIELD, {"references":["Kotila, T., Wioland, H., Enkavi, G. et al. Mechanism of synergistic actin filament pointed end depolymerization by cyclase-associated protein and cofilin. Nat Commun 10, 5320 (2019) doi:10.1038/s41467-019-13213-2"]}

Even-denominator fractional quantum Hall (FQH) states, such as 5/2 and 7/2, have been well known in a two-dimensional electron gas (2DEG) for decades and are still investigated as candidates of non-Abelian statistics. In this paper, we present the observation of a 3/2 FQH plateau in a single-layer 2DEG with lateral confinement at a bulk filling factor of 5/3. The 3/2 FQH plateau is quantized at \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left( {\frac{h}{{e^2}}} \right)/\left( {\frac{3}{2}} \right)$$\end{document}he2∕32 within 0.02%, and can survive up to 300 mK. This even-denominator FQH plateau may imply intriguing edge structure and excitation in FQH system with lateral confinement. The observations in this work demonstrate that understanding the effect of the lateral confinement on the many-body system is critical in the pursuit of important theoretical proposals involving edge physics, such as the demonstration of non-Abelian statistics and the realization of braiding for fault-tolerant quantum computation., Fractional quantum Hall states in 2D electron gases arise due to strong electron-electron interactions, which makes a general theoretical understanding difficult. Fu et al. present data showing the ν = 5/3 quantum Hall state has a 3/2 plateau in the diagonal resistance that has not been captured by existing models.

Titanium dioxide is the only known material that can enable gas-phase CO2 photocatalysis in its anatase and rutile polymorphic forms. Materials engineering of polymorphism provides a useful strategy for optimizing the performance metrics of a photocatalyst. In this paper, it is shown that the less well known rhombohedral polymorph of indium sesquioxide, like its well-documented cubic polymorph, is a CO2 hydrogenation photocatalyst for the production of CH3OH and CO. Significantly, the rhombohedral polymorph exhibits higher activity, superior stability and improved selectivity towards CH3OH over CO. These gains in catalyst performance originate in the enhanced acidity and basicity of surface frustrated Lewis pairs in the rhombohedral form., Polymorphs, compounds with identical chemical stoichiometries yet different atomic configurations, expand the range of potential chemical properties and new applications. Here, authors show rhombohedral indium oxides to be highly active and selective for photocatalytic CO2 hydrogenation.

Quantitative and well-targeted design of modern alloys is extremely challenging due to their immense compositional space. When considering only 50 elements for compositional blending the number of possible alloys is practically infinite, as is the associated unexplored property realm. In this paper, we present a simple property-targeted quantitative design approach for atomic-level complexity in complex concentrated and high-entropy alloys, based on quantum-mechanically derived atomic-level pressure approximation. It allows identification of the best suited element mix for high solid-solution strengthening using the simple electronegativity difference among the constituent elements. This approach can be used for designing alloys with customized properties, such as a simple binary NiV solid solution whose yield strength exceeds that of the Cantor high-entropy alloy by nearly a factor of two. This study provides general design rules that enable effective utilization of atomic level information to reduce the immense degrees of freedom in compositional space without sacrificing physics-related plausibility., Designing complex concentrated alloys with targeted properties for high performance remains challenging because of their complex local atomic environments. Here, the authors show how to engineer atomic-level pressure to customize complexity-induced properties such as solid-solution strengthening.

Three-dimensional topological nodal lines, the touching curves of two bands in momentum space, which give rise to drumhead surface states, provide an opportunity to explore a variety of exotic phenomena. However, solid evidence for a flat drumhead surface state remains elusive. In this paper, we report a realization of three-dimensional nodal line dispersions and drumhead surface states in phononic crystal. Profiting from its macroscopic nature, the phononic crystal permits a flexible and accurate fabrication for materials with ring-like nodal lines and drumhead surface states. Phononic nodal rings of the lowest two bands and, more importantly, topological drumhead surface states are unambiguously demonstrated. Our system provides an ideal platform to explore the intriguing properties of acoustic waves endowed with extraordinary dispersions., 3D topological nodal lines that give rise to drumhead surface states could help study a range of exotic topological phenomena. Here, Deng et al. experimentally demonstrate 3D nodal ring dispersion and topological drumhead surface states for acoustic waves in a phononic crystal.

Multinational enterprises (MNE) need to be a part of the solution in the fight against climate change, as claimed by investors and consumers, reducing emissions within their operations and supply chains. This paper measures the carbon footprint of U.S. MNE foreign affiliates (US-MNE) operating beyond the U.S. borders. Using a multiregional input-output model and information about US-MNE activities, the US-MNE carbon footprint ranks US-MNE as the 12th top emitter of the world. In relative terms, one dollar of value added generated by US-MNE affiliates operating abroad requires higher emissions than the domestic average and the ratio increases when only developing host countries are considered. Only 8% of total carbon footprint returns to the U.S. as virtual carbon embodied in the U.S. final consumption. Potential technology transfers between the U.S. parent company and affiliates to reduce US-MNE carbon footprint have been performed to evaluate potential rippled effects of mitigation actions., Multinational enterprises (MNE) play a key role in climate mitigation as the significance of the environmental impacts of MNE. Here the authors measured the carbon footprint of U.S. MNE affiliates throughout their global value chains and show their carbon footprint beyond borders at 0.5082 GtCO2 in 2009.

Separation of a homogeneous mixture of different components to reach an ordered out-of-equilibrium state in solution has attracted continuous attention. While this can be achieved using external chemical fuels or photo energy, an alternative energy source is heat. Here we realize a temperature-controlled cycle of transitions between ordered and disordered states based on a mixture of two kinds of building blocks that self-assemble into cubic structures (nanocubes). An almost statistical mixture of nanocubes (disordered state) is thermodynamically most stable at lower temperature (25 °C), while homoleptic assemblies composed of single components are preferentially produced at higher temperature (100 °C) followed by rapid cooling. The scrambling of the building blocks between the nanocubes takes place through the exchange of free building blocks dissociated from the nanocubes. Based on this mechanism, it is possible to accelerate, retard, and perfectly block the scrambling by the guest molecules encapsulated in the nanocubes., In this paper, the authors study the temperature-controlled dynamic behavior of a system of nanocubes self-assembled from two different building blocks. Non-intuitively, the disordered, equilibrium state (a mixture of heteroleptic cubes) and the ordered, out-of-equilibrium state (a mixture of homoleptic cubes) are cycled by heating and subsequent rapid cooling.

Complex dynamical fluctuations, from intracellular noise, brain dynamics or computer traffic display bursting dynamics consistent with a critical state between order and disorder. Living close to the critical point has adaptive advantages and it has been conjectured that evolution could select these critical states. Is this the case of living cells? A system can poise itself close to the critical point by means of the so-called self-organized criticality (SOC). In this paper we present an engineered gene network displaying SOC behaviour. This is achieved by exploiting the saturation of the proteolytic degradation machinery in E. coli cells by means of a negative feedback loop that reduces congestion. Our critical motif is built from a two-gene circuit, where SOC can be successfully implemented. The potential implications for both cellular dynamics and behaviour are discussed., This work was supported by the Botin Foundation by Banco Santander through its Santander Universities Global Division, the Spanish Ministry of Economy and Competitiveness, grant AEI-PID2019-111680GB-I00/AEI/10.13039/501100011033, an AGAUR FI 2018 grant, and the Santa Fe Institute (where the key idea was conceived). J.S. and A.G. have been partially funded by the CERCA Programme of the Generalitat de Catalunya. J.S. acknowledges support from Agencia Estatal de Investigación grant RTI2018-098322-B-I00 and Ramón y Cajal contract RYC-2017-22243. A.G. has been funded by the AGAUR grant 2017-SGR-1049 and by the MINECO-FEDER-UE grants PGC-2018-098676-B-100 and RTI2018-093860-B-C21.

Neuronal activity in sensory cortex fluctuates over time and across repetitions of the same input. This variability is often considered detrimental to neural coding. The theory of neural sampling proposes instead that variability encodes the uncertainty of perceptual inferences. In primary visual cortex (V1), modulation of variability by sensory and non-sensory factors supports this view. However, it is unknown whether V1 variability reflects the statistical structure of visual inputs, as would be required for inferences correctly tuned to the statistics of the natural environment. Here we combine analysis of image statistics and recordings in macaque V1 to show that probabilistic inference tuned to natural image statistics explains the widely observed dependence between spike count variance and mean, and the modulation of V1 activity and variability by spatial context in images. Our results show that the properties of a basic aspect of cortical responses—their variability—can be explained by a probabilistic representation tuned to naturalistic inputs., The neural sampling theory suggests that neuronal variability encodes the uncertainty of probabilistic inferences. This paper shows that response variability in primary visual cortex reflects the statistical structure of visual inputs, as required for inferences correctly tuned to the statistics of the natural environment.

Networks provide a powerful representation of interacting components within complex systems, making them ideal for visually and analytically exploring big data. However, the size and complexity of many networks render static visualizations on typically-sized paper or screens impractical, resulting in proverbial ‘hairballs’. Here, we introduce a Virtual Reality (VR) platform that overcomes these limitations by facilitating the thorough visual, and interactive, exploration of large networks. Our platform allows maximal customization and extendibility, through the import of custom code for data analysis, integration of external databases, and design of arbitrary user interface elements, among other features. As a proof of concept, we show how our platform can be used to interactively explore genome-scale molecular networks to identify genes associated with rare diseases and understand how they might contribute to disease development. Our platform represents a general purpose, VR-based data exploration platform for large and diverse data types by providing an interface that facilitates the interaction between human intuition and state-of-the-art analysis methods., Data-rich networks can be difficult to interpret beyond a certain size. Here, the authors introduce a platform that uses virtual reality to allow the visual exploration of large networks, while interfacing with data repositories and other analytical methods to improve the interpretation of big data.

Oxford Nanopore (ONT) is a leading long-read technology which has been revolutionizing transcriptome analysis through its capacity to sequence the majority of transcripts from end-to-end. This has greatly increased our ability to study the diversity of transcription mechanisms such as transcription initiation, termination, and alternative splicing. However, ONT still suffers from high error rates which have thus far limited its scope to reference-based analyses. When a reference is not available or is not a viable option due to reference-bias, error correction is a crucial step towards the reconstruction of the sequenced transcripts and downstream sequence analysis of transcripts. In this paper, we present a novel computational method to error correct ONT cDNA sequencing data, called isONcorrect. IsONcorrect is able to jointly use all isoforms from a gene during error correction, thereby allowing it to correct reads at low sequencing depths. We are able to obtain a median accuracy of 98.9–99.6%, demonstrating the feasibility of applying cost-effective cDNA full transcript length sequencing for reference-free transcriptome analysis., Nanopore sequencing technologies applied to transcriptome analysis suffer from high error rates, limiting them largely to reference-based analyses. Here, the authors develop a computational error correction method for transcriptome analysis that reduces the median error rate from ~7% to ~1%.

Author(s): Coignard, Juliette; Lush, Michael; Beesley, Jonathan; O'Mara, Tracy A; Dennis, Joe; Tyrer, Jonathan P; Barnes, Daniel R; McGuffog, Lesley; Leslie, Goska; Bolla, Manjeet K; Adank, Muriel A; Agata, Simona; Ahearn, Thomas; Aittomaki, Kristiina; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Arnold, Norbert; Aronson, Kristan J; Arun, Banu K; Augustinsson, Annelie; Azzollini, Jacopo; Barrowdale, Daniel; Baynes, Caroline; Becher, Heko; Bermisheva, Marina; Bernstein, Leslie; Bialkowska, Katarzyna; Blomqvist, Carl; Bojesen, Stig E; Bonanni, Bernardo; Borg, Ake; Brauch, Hiltrud; Brenner, Hermann; Burwinkel, Barbara; Buys, Saundra S; Caldes, Trinidad; Caligo, Maria A; Campa, Daniele; Carter, Brian D; Castelao, Jose E; Chang-Claude, Jenny; Chanock, Stephen J; Chung, Wendy K; Claes, Kathleen BM; Clarke, Christine L; GEMO Study Collaborators; EMBRACE Collaborators; Collee, J Margriet; Conroy, Don M; Czene, Kamila; Daly, Mary B; Devilee, Peter; Diez, Orland; Ding, Yuan Chun; Domchek, Susan M; Dork, Thilo; Dos-Santos-Silva, Isabel; Dunning, Alison M; Dwek, Miriam; Eccles, Diana M; Eliassen, A Heather; Engel, Christoph; Eriksson, Mikael; Evans, D Gareth; Fasching, Peter A; Flyger, Henrik; Fostira, Florentia; Friedman, Eitan; Fritschi, Lin; Frost, Debra; Gago-Dominguez, Manuela; Gapstur, Susan M; Garber, Judy; Garcia-Barberan, Vanesa; Garcia-Closas, Montserrat; Garcia-Saenz, Jose A; Gaudet, Mia M; Gayther, Simon A; Gehrig, Andrea; Georgoulias, Vassilios; Giles, Graham G; Godwin, Andrew K; Goldberg, Mark S; Goldgar, David E | Abstract: A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-23162-4.

We study mentorship in scientific collaborations, where a junior scientist is supported by potentially multiple senior collaborators, without them necessarily having formal supervisory roles. We identify 3 million mentor–protege pairs and survey a random sample, verifying that their relationship involved some form of mentorship. We find that mentorship quality predicts the scientific impact of the papers written by proteges post mentorship without their mentors. We also find that increasing the proportion of female mentors is associated not only with a reduction in post-mentorship impact of female proteges, but also a reduction in the gain of female mentors. While current diversity policies encourage same-gender mentorships to retain women in academia, our findings raise the possibility that opposite-gender mentorship may actually increase the impact of women who pursue a scientific career. These findings add a new perspective to the policy debate on how to best elevate the status of women in science. Here, the authors study mentorship in scientific collaborations, and find that mentorship quality predicts the scientific impact of proteges post mentorship. Moreover, female proteges collaborating with male mentors become more impactful post mentorship than those who collaborate with female mentors.

Author(s): Liu, Zhu; Ciais, Philippe; Deng, Zhu; Lei, Ruixue; Davis, Steven J; Feng, Sha; Zheng, Bo; Cui, Duo; Dou, Xinyu; Zhu, Biqing; Guo, Rui; Ke, Piyu; Sun, Taochun; Lu, Chenxi; He, Pan; Wang, Yuan; Yue, Xu; Wang, Yilong; Lei, Yadong; Zhou, Hao; Cai, Zhaonan; Wu, Yuhui; Guo, Runtao; Han, Tingxuan; Xue, Jinjun; Boucher, Olivier; Boucher, Eulalie; Chevallier, Frederic; Tanaka, Katsumasa; Wei, Yiming; Zhong, Haiwang; Kang, Chongqing; Zhang, Ning; Chen, Bin; Xi, Fengming; Liu, Miaomiao; Breon, Francois-Marie; Lu, Yonglong; Zhang, Qiang; Guan, Dabo; Gong, Peng; Kammen, Daniel M; He, Kebin; Schellnhuber, Hans Joachim | Abstract: A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20254-5.

The self-organization of strongly interacting electrons into superlattice structures underlies the properties of many quantum materials. How these electrons arrange within the superlattice dictates what symmetries are broken and what ground states are stabilized. Here we show that cryogenic scanning transmission electron microscopy (cryo-STEM) enables direct mapping of local symmetries and order at the intra-unit-cell level in the model charge-ordered system Nd1/2Sr1/2MnO3. In addition to imaging the prototypical site-centered charge order, we discover the nanoscale coexistence of an exotic intermediate state which mixes site and bond order and breaks inversion symmetry. We further show that nonlinear coupling of distinct lattice modes controls the selection between competing ground states. The results demonstrate the importance of lattice coupling for understanding and manipulating the character of electronic self-organization and that cryo-STEM can reveal local order in strongly correlated systems at the atomic scale., In this paper, the authors demonstrate that cryogenic scanning transmission electron microscopy allows for the direct mapping of the local arrangements and symmetries of electronic order, providing a useful method for studying strongly correlated systems. They show this using the example of Nd1/2Sr1/2MnO3, a model charge ordered material.

The α-type ADP-ribosylated peptides represent a class of important molecular tools in the field of protein ADP-ribosylation, however, they are difficult to access because of their inherent complicated structures and the lack of effective synthetic tools. In this paper, we present a biomimetic α-selective ribosylation reaction to synthesize a key intermediate, α-ADP-ribosyl azide, directly from native β-nicotinamide adenine dinucleotide in a clean ionic liquid system. This reaction in tandem with click chemistry then offers a two-step modular synthesis of α-ADP-ribosylated peptides. These syntheses can be performed open air in eppendorf tubes, without the need for specialized instruments or training. Importantly, we demonstrate that the synthesized α-ADP-ribosylated peptides show high binding affinity and desirable stability for enriching protein partners, and reactivity in post-stage poly ADP-ribosylations. Owing to their simple chemistry and multidimensional bio-applications, the presented methods may provide a powerful platform to produce general molecular tools for the study of protein ADP-ribosylation., ADP-ribosylated peptides are important molecular tools, however, the lack of effective synthetic methods hinders the access to their complex structures. Here, the authors present a biomimetic α-selective ribosylation reaction coupled with click chemistry ultimately providing a two-step modular synthesis of α-ADP-ribosylated peptides.