Most tweeted biology preprints, last 24 hours
*There are gaps in historical Twitter data, most notably in spring 2020. This may result in some preprints appearing with less tweets than they should.
197 results found. For more information, click each entry to expand.
2 tweets bioRxiv neuroscience
Nicholas A. Steinmetz, Cagatay Aydin, Anna Lebedeva, Michael Okun, Marius Pachitariu, Marius Bauza, Maxime Beau, Jai Bhagat, Claudia Böhm, Martijn Broux, Susu Chen, Jennifer Colonell, Richard J. Gardner, Bill Karsh, Dimitar Kostadinov, Carolina Mora-Lopez, Junchol Park, Jan Putzeys, Britton A. Sauerbrei, Rik J. J. van Daal, Abraham Z. Vollan, Marleen Welkenhuysen, Zhiwen Ye, Joshua T. Dudman, Barundeb Dutta, Adam W Hantman, Kenneth D. Harris, Albert K Lee, Edvard I. Moser, John O'Keefe, Alfonso Renart, Karel Svoboda, Michael Häusser, Sebastian Haesler, Matteo Carandini, Timothy D Harris
To study the dynamics of neural processing across timescales, we require the ability to follow the spiking of thousands of individually separable neurons over weeks and months, during unrestrained behavior. To address this need, we introduce the Neuropixels 2.0 probe together with novel analysis algorithms. The new probe has over 5,000 sites and is miniaturized such that two probes plus a headstage, recording 768 sites at once, weigh just over 1 g, suitable for implanting chronically in small mammals. Recordings with high quality signals persisting for at least two months were reliably obtained in two species and six different labs. Improved site density and arrangement combined with new data processing methods enable automatic post-hoc stabilization of data despite brain movements during behavior and across days, allowing recording from the same neurons in the mouse visual cortex for over 2 months. Additionally, an optional configuration allows for recording from multiple sites per available channel, with a penalty to signal-to-noise ratio. These probes and algorithms enable stable recordings from >10,000 sites during free behavior in small animals such as mice. ### Competing Interest Statement The authors have declared no competing interest.
2 tweets bioRxiv molecular biology
Nikki R. Kong, Mahmoud A. Bassal, Hong Kee Tan, Jesse V. Kurland, Kol Jia Yong, John J. Young, Yang Yang, Fudong Li, Jonathan Lee, Yue Liu, Chan-Shuo Wu, Alicia Stein, Hongbo Luo, Leslie E. Silberstein, Martha L. Bulyk, Daniel G Tenen, Li Chai
The zinc finger transcription factor SALL4 is highly expressed in embryonic stem cells, down-regulated in most adult tissues, but reactivated in many aggressive cancers. This unique expression pattern makes SALL4 an attractive target for designing therapeutic strategies. However, whether SALL4 binds DNA directly to regulate gene expression is unclear and many of its targets in cancer cells remain elusive. Here, through an unbiased screen of protein binding microarray (PBM) and Cleavage Under Targets and Release Using Nuclease (CUT&RUN) experiments, we identified and validated the DNA binding domain of SALL4 and its consensus binding sequence. Combined with RNA-seq analyses after SALL4 knockdown, we discovered hundreds of new SALL4 target genes that it directly regulates in aggressive liver cancer cells, including genes encoding a family of Histone 3 Lysine 9-specific Demethylases (KDMs). Taken together, these results elucidated the mechanism of SALL4 DNA binding and revealed novel pathways and molecules to target in SALL4-dependent tumors. ### Competing Interest Statement The authors have declared no competing interest.
2 tweets bioRxiv immunology
Annette B. Vogel, Isis Kanevsky, Ye Che, Kena A. Swanson, Alexander Muik, Mathias Vormehr, Lena M. Kranz, Kerstin C. Walzer, Stephanie Hein, Alptekin Güler, Jakob Loschko, Mohan S. Maddur, Kristin Tompkins, Journey Cole, Bonny G. Lui, Thomas Ziegenhals, Arianne Plaschke, David Eisel, Sarah C. Dany, Stephanie Fesser, Stephanie Erbar, Ferdia Bates, Diana Schneider, Bernadette Jesionek, Bianca Sänger, Ann-Kathrin Wallisch, Yvonne Feuchter, Hanna Junginger, Stefanie A. Krumm, André P. Heinen, Petra Adams-Quack, Julia Schlereth, Christoph Kröner, Shannan Hall-Ursone, Kathleen Brasky, Matthew C. Griffor, Seungil Han, Joshua A. Lees, Ellene H. Mashalidis, Parag V. Sahasrabudhe, Charles Y. Tan, Danka Pavliakova, Guy Singh, Camila Fontes-Garfias, Michael Pride, Ingrid L. Scully, Tara Ciolino, Jennifer Obregon, Michal Gazi, Ricardo Carrion, Kendra J. Alfson, Warren V. Kalina, Deepak Kaushal, Pei-Yong Shi, Thorsten Klamp, Corinna Rosenbaum, Andreas N. Kuhn, Özlem Türeci, Philip R. Dormitzer, Kathrin U. Jansen, Ugur Sahin
To contain the coronavirus disease 2019 (COVID-19) pandemic, a safe and effective vaccine against the new severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is urgently needed in quantities sufficient to immunise large populations. In this study, we report the design, preclinical development, immunogenicity and anti-viral protective effect in rhesus macaques of the BNT162b2 vaccine candidate. BNT162b2 contains an LNP-formulated nucleoside-modified mRNA that encodes the spike glycoprotein captured in its prefusion conformation. After expression of the BNT162b2 coding sequence in cells, approximately 20% of the spike molecules are in the one-RBD ‘up’, two-RBD ‘down’ state. Immunisation of mice with a single dose of BNT162b2 induced dose level-dependent increases in pseudovirus neutralisation titers. Prime-boost vaccination of rhesus macaques elicited authentic SARS-CoV-2 neutralising geometric mean titers 10.2 to 18.0 times that of a SARS-CoV-2 convalescent human serum panel. BNT162b2 generated strong TH1 type CD4+ and IFNγ+ CD8+ T-cell responses in mice and rhesus macaques. The BNT162b2 vaccine candidate fully protected the lungs of immunised rhesus macaques from infectious SARS-CoV-2 challenge. BNT162b2 is currently being evaluated in a global, pivotal Phase 2/3 trial ([NCT04368728]). ### Competing Interest Statement U.S. and O.T. are management board members and employees at BioNTech SE (Mainz, Germany); K.C.W., B.G.L., D.S., B.J., T.K. and C.R. are employees at BioNTech SE; A.B.V., A.M., M.V., L.M.K., S.He., A.G., T.Z., A.P., D.E., S.C.D., S.F., S.E., F.B., B.S., A.W., Y.F., H.J., S.A.K., A.P.H., P.A., J.S., C.K., and A.N.K. are employees at BioNTech RNA Pharmaceuticals GmbH (Mainz, Germany); A.B.V., A.M., K.C.W., A.G., S.F., A.N.K and U.S. are inventors on patents and patent applications related to RNA technology and COVID-19 vaccine; A.B.V., A.M., M.V., L.M.K., K.C.W., S.He., B.G.L., A.P., D.E., S.C.D., S.F., S.E., D.S., B.J., B.S., A.P.H., P.A., J.S., C.K., T.K., C.R., A.N.K., O.T. and U.S. have securities from BioNTech SE; I.K., Y.C., K.A.S., J.L., M.M., K.T., M.C.G., S.H., J.A.L.,E.H.M., P.V.S., C.Y.T., D.P., G.S., M.P., I.L.S., T.C., J.O., W.V.K., P.R.D. and K.U.J. are employees of Pfizer and may hold stock options; C.F.-G. and P.-Y.S. received compensation from Pfizer to perform neutralisation assays; J.C., S.H.-U, K.B., R.C., jr., K.J.A. and D.K., are employees of Southwest National Primate Research Center, which received compensation from Pfizer to conduct the animal challenge work; no other relationships or activities that could appear to have influenced the submitted work. : /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT04368728&atom=%2Fbiorxiv%2Fearly%2F2020%2F09%2F08%2F2020.09.08.280818.atom
2 tweets bioRxiv evolutionary biology
Emerging evidence suggests that urbanization shapes the ecology and evolution of species interactions. Islands are particularly susceptible to urbanization due to the fragility of their ecosystems; however, few studies have examined the effects of urbanization on species interactions on islands. To address this gap, we studied the effects of urbanization on interactions between Darwin’s finches and its key food resource, Tribulus cistoides , in three towns on the Galápagos Islands. We assessed the effects of urbanization on seed and mericarp removal, mericarp morphology, and finch community composition using natural population surveys, experimental manipulations, and finch observations. We found that both seed and fruit removal rates were higher in urban compared to non-urban populations in the natural and experimental populations, and that urbanization modified selection on mericarp size and defense. Urban environments supported smaller and less diverse finch communities than non-urban environments. Together, our results suggest that urbanization can dramatically alter ecological interactions between Darwin’s finches and T. cistoides , leading to modified selection on T. cistoides populations. Our study demonstrates that urban development on islands can have profound effects on the ecology and evolution of trophic interactions. ### Competing Interest Statement The authors have declared no competing interest.
2 tweets bioRxiv evolutionary biology
The Neanderthal and Denisovan genomes enabled the discovery of sequences that differ between modern and archaic humans, the majority of which are noncoding. However, our understanding of the regulatory consequences of these differences remains limited, in part due to the decay of regulatory marks in ancient samples. Here, we used a massively parallel reporter assay in embryonic stem cells, neural progenitor cells and bone osteoblasts to investigate the regulatory effects of the 14,042 single-nucleotide modern human-specific variants. Overall, 1,791 (13%) of sequences containing these variants showed active regulatory activity, and 407 (23%) of these drove differential expression between human groups. Differentially active sequences were associated with divergent transcription factor binding motifs, and with genes enriched for vocal tract and brain anatomy and function. This work provides insight into the regulatory function of variants that emerged along the modern human lineage and the recent evolution of human gene expression.
2 tweets bioRxiv neuroscience
Digitized neuroanatomical atlases are crucial for localizing brain structures and analyzing functional networks identified by magnetic resonance imaging (MRI). To aid in MRI data analysis, we have created a comprehensive parcellation of the rhesus macaque subcortex using a high-resolution ex vivo structural imaging scan. The structural scan and its parcellation were warped to the updated NIMH Macaque Template (NMT v2), an in vivo population template, where the parcellation was refined to produce the Subcortical Atlas of the Rhesus Macaque (SARM). The subcortical parcellation and nomenclature reflect those of the 4th edition of the Rhesus Monkey Brain in Stereotaxic Coordinates (RMBSC4; Paxinos et al., in preparation). The SARM features six parcellation levels, arranged hierarchically from fine regions-of-interest (ROIs) to broader composite regions, suited for fMRI studies. As a test, we ran a functional localizer for the dorsal lateral geniculate (DLG) nucleus in three macaques and found significant fMRI activation in this atlas region. The SARM has been made openly available to the neuroimaging community and can easily be used with common MR data processing software, such as AFNI, where the atlas can be embedded into the software alongside cortical macaque atlases. Highlights ### Competing Interest Statement The authors have declared no competing interest.
2 tweets bioRxiv neuroscience
Brandon C Farmer, Holden C Williams, Nicholas A Devanney, Margaret A Piron, Grant K Nation, David J Carter, Adeline E Walsh, Rebika Khanal, Lyndsay E A Young, Jude C Kluemper, Gabriela Hernandez, Elizabeth J Allenger, Rachel Mooney, J. Anthony Brandon, Vedant A Gupta, Philip A Kern, Matthew S Gentry, Josh M Morganti, Ramon C Sun, Lance A. Johnson
Cerebral glucose hypometabolism is consistently observed in individuals with Alzheimers disease, as well as in young cognitively normal carriers of the E4 allele of Apolipoprotein E, the strongest genetic predictor of late-onset AD. While this clinical feature has been described for over two decades, the mechanism underlying these changes in cerebral glucose metabolism remains a critical knowledge gap in the field. Here, we undertook a multi-omic approach by combining single-cell RNA sequencing and stable isotope resolved metabolomics to define a metabolic rewiring across astrocytes, brain tissue, mice, and human subjects expressing APOE4. Single-cell analysis of brain tissue from mice expressing human APOE revealed E4-associated decreases in genes related to oxidative phosphorylation, particularly in astrocytes. This shift was confirmed on a metabolic level with isotopic tracing of 13C-glucose in E4 mice and astrocytes, which showed decreased pyruvate entry into the TCA cycle and increases in lactate synthesis. Metabolic phenotyping of E4 astrocytes showed elevated glycolytic activity, decreased oxygen consumption, blunted oxidative flexibility, and a lower rate of glucose oxidation in the presence of lactate. Together, these cellular findings suggested an E4 associated increase in aerobic glycolysis (i.e. the Warburg effect). To test whether this phenomenon translated to APOE4 humans, we analyzed the plasma metabolome of young and middle-aged human participants with and without the E4 allele, and used indirect calorimetry to measure whole body oxygen consumption and energy expenditure. In line with data from E4-expressing mice, young female E4 carriers showed a striking decrease in energy expenditure compared to non-carriers. This decrease in energy expenditure was primarily driven by a lower rate of oxygen consumption, and was exaggerated following a dietary glucose challenge. Further, the stunted oxygen consumption was accompanied by markedly increased lactate in the plasma of E4 carriers, and a pathway analysis of the plasma metabolome suggested an increase in aerobic glycolysis. Together, these results suggest astrocyte, brain and system-level metabolic reprogramming in the presence of APOE4, a Warburg like endophenotype that is observable in young humans decades prior to clinically manifest AD. ### Competing Interest Statement The authors have declared no competing interest.
2 tweets bioRxiv pharmacology and toxicology
COVID-19 (coronavirus disease 2019) is a pandemic caused by SARS-CoV-2 (severe acute respiratory syndrome-coronavirus 2) infection affecting millions of persons around the world. There is an urgent unmet need to provide an easy-to-produce, affordable medicine to prevent transmission and provide early treatment for this disease. The nasal cavity and the rhinopharynx are the sites of initial replication of SARS-CoV-2. Therefore, a nasal spray may be a suitable dosage form for this purpose. The main objective of our study was to test the antiviral action of three candidate nasal spray formulations against SARS-CoV-2. We have found that iota-carrageenan in concentrations as low as 6 mcg/ mL inhibits SARS-CoV-2 infection in Vero cell cultures. The concentrations found to be active in vitro against SARS-CoV-2 may be easily achieved by the application of nasal sprays already marketed in several countries. Xylitol at a concentration of 5 % m/V has proved to be viricidal on its own and the association with iota-carrageenan may be beneficial, as well. ### Competing Interest Statement The study has been funded by Amcyte Pharma Inc. (US) Juan Manuel Figueroa, Andrea Dugour and Carlos Palacios receive funding from Fundacion Pablo Cassara (Argentina) Julio Cesar Vega receives salary from Laboratorio Pablo Cassara and is inventor of a US patent application related to this manuscript.
2 tweets bioRxiv microbiology
Coronaviruses (CoVs) infect a wide range of animals and birds. Their tropism is primarily determined by the ability of the spike (S) protein to bind to a host cell surface receptor. The rapid outbreak of emerging novel coronavirus, SARS-CoV 2 in China inculcates the need for the development of hasty and effective intervention strategies. Medicinal plants and natural compounds have been traditionally used to treat viral infections. Here, we generated VSV based pseudotyped viruses (pvs) of SARS-, MERS-, and SARS-2 CoVs to screen entry inhibitors from natural products. In the first series of experiments, we demonstrated that pseudotyped viruses specifically bind on their receptors and enter into the cells. SARS and MERS polyclonal antibodies neutralize SARSpv and SARS-2pv, and MERSpv respectively. Incubation of soluble ACE2 inhibited entry of SARS and SARS-2 pvs but not MERSpv. In addition, expression of ACE2 and DPP4 in non-permissive BHK21 cells enabled infection by SARSpv, SARS-2pv, and MERSpv respectively. Next, we showed the antiviral properties of known enveloped virus entry inhibitors, Spirulina and Green tea extracts against CoVpvs. SARSpv, MERSpv, and SARS-2pv entry were blocked with higher efficiency when preincubated with either green tea or spirulina extracts. Green tea provided a better inhibitory effect than the spirulina extracts by binding to the S1 domain of spike and blocking the interaction of spike with its receptor. Further studies are required to understand the exact mechanism of viral inhibition. In summary, we demonstrate that pseudotyped virus is an ideal tool for screening viral entry inhibitors. Moreover, spirulina and green tea could be promising antiviral agents against emerging viruses. ### Competing Interest Statement The authors have declared no competing interest.
2 tweets bioRxiv cell biology
The epithelial-mesenchymal transition (EMT) drives cellular movements during development to create specialized tissues and structures in metazoans, using mechanisms often coopted during metastasis. Neural crest cells are a multipotent stem cell population that undergo a developmentally regulated EMT and are prone to metastasis in the adult, providing an excellent model to study cell state changes and mechanisms underlying EMT. A hallmark of neural crest EMT during avian development is temporally restricted expression followed by rapid down-regulation of the Wnt antagonist Draxin . Using live RNA imaging, here we demonstrate that rapid clearance of Draxin transcripts is mediated post-transcriptionally via localization to processing bodies (P-bodies), small cytoplasmic granules which are established sites of RNA processing. Contrasting with recent work in immortalized cell lines suggesting that P-bodies are sites of storage rather than degradation, we show that targeted decay of Draxin occurs within P-bodies during neural crest migration. Furthermore, P-body disruption via DDX6 knockdown inhibits not only endogenous Draxin down-regulation but also neural crest EMT in vivo . Together, our data highlight a novel and important role for P-bodies in an intact organismal context−controlling a developmental EMT program via post-transcriptional target degradation. ### Competing Interest Statement The authors have declared no competing interest.
2 tweets bioRxiv evolutionary biology
Despite the importance of natural selection in species' evolutionary history, phylogenetic methods that take into account population-level processes ignore selection. Assuming neutrality is often based on the idea that selection occurs at a minority of loci in the genome and is unlikely to significantly compromise phylogenetic inferences. However, selection might behave more pervasively, as it the case of nearly neutral evolving mutations. Genome-wide processes like GC-bias and some of the variation segregating at the coding regions are known to evolve in the nearly neutral range. As we are now using genome-wide data to estimate species tree, it is just natural to ask whether weak, but pervasive, selection is likely to blur species tree inferences. Here, we employed a polymorphism-aware phylogenetic model, specially tailored for measuring signatures of nucleotide usage biases, to test the impact of nearly neutrally in the substitution process. Analyses with simulated data indicate that while the inferred relationships among species are not significantly compromised, the genetic distances are systematically underestimated, with the deeper nodes suffering more than the younger ones. Such biases have implications for molecular dating. We found signatures of GC-bias considerably affecting the estimated divergence times (up to 21%) of worldwide fruit fly populations. Our findings call for the need to account for nearly neutral forces (or any other form of pervasive selection) when quantifying divergence or dating species evolution. ### Competing Interest Statement The authors have declared no competing interest.
2 tweets bioRxiv neuroscience
Current state-of-the-art object recognition models are largely based on convolutional neural network (CNN) architectures, which are loosely inspired by the primate visual system. However, these CNNs can be fooled by imperceptibly small, explicitly crafted perturbations, and struggle to recognize objects in corrupted images that are easily recognized by humans. Here, by making comparisons with primate neural data, we first observed that CNN models with a neural hidden layer that better matches primate primary visual cortex (V1) are also more robust to adversarial attacks. Inspired by this observation, we developed VOneNets, a new class of hybrid CNN vision models. Each VOneNet contains a fixed weight neural network front-end that simulates primate V1, called the VOneBlock, followed by a neural network back-end adapted from current CNN vision models. The VOneBlock is based on a classical neuroscientific model of V1: the linear-nonlinear-Poisson model, consisting of a biologically-constrained Gabor filter bank, simple and complex cell nonlinearities, and a V1 neuronal stochasticity generator. After training, VOneNets retain high ImageNet performance, but each is substantially more robust, outperforming the base CNNs and state-of-the-art methods by 18% and 3%, respectively, on a conglomerate benchmark of perturbations comprised of white box adversarial attacks and common image corruptions. Finally, we show that all components of the VOneBlock work in synergy to improve robustness. While current CNN architectures are arguably brain-inspired, the results presented here demonstrate that more precisely mimicking just one stage of the primate visual system leads to new gains in ImageNet-level computer vision applications. ### Competing Interest Statement The authors have declared no competing interest.
1 tweet bioRxiv neuroscience
Pengcheng Zhou, Jacob Reimer, Ding Zhou, Amol Pasarkar, Ian Kinsella, Emmanouil Froudarakis, Dimitri Yatsenko, Paul G. Fahey, Agnes Bodor, JoAnn Buchanan, Dan Bumbarger, Gayathri Mahalingam, Russel Torres, Sven Dorkenwald, Dodam Ih, Kisuk Lee, Ran Lu, Thomas Macrina, Jingpeng Wu, Nuno Maçarico da Costa, R. Clay Reid, Andreas S. Tolias, Liam Paninski
Combining two-photon calcium imaging (2PCI) and electron microscopy (EM) provides arguably the most powerful current approach for connecting function to structure in neural circuits. Recent years have seen dramatic advances in obtaining and processing CI and EM data separately. In addition, several joint CI-EM datasets (with CI performed in vivo, followed by EM reconstruction of the same volume) have been collected. However, no automated analysis tools yet exist that can match each signal extracted from the CI data to a cell segment extracted from EM; previous efforts have been largely manual and focused on analyzing calcium activity in cell bodies, neglecting potentially rich functional information from axons and dendrites. There are two major roadblocks to solving this matching problem: first, dense EM reconstruction extracts orders of magnitude more segments than are visible in the corresponding CI field of view, and second, due to optical constraints and non-uniform brightness of the calcium indicator in each cell, direct matching of EM and CI spatial components is nontrivial. In this work we develop a pipeline for fusing CI and densely-reconstructed EM data. We model the observed CI data using a constrained nonnegative matrix factorization (CNMF) framework, in which segments extracted from the EM reconstruction serve to initialize and constrain the spatial components of the matrix factorization. We develop an efficient iterative procedure for solving the resulting combined matching and matrix factorization problem and apply this procedure to joint CI-EM data from mouse visual cortex. The method recovers hundreds of dendritic components from the CI data, visible across multiple functional scans at different depths, matched with densely-reconstructed three-dimensional neural segments recovered from the EM volume. We publicly release the output of this analysis as a new gold standard dataset that can be used to score algorithms for demixing signals from 2PCI data. Finally, we show that this database can be exploited to (1) learn a mapping from 3d EM segmentations to predict the corresponding 2d spatial components estimated from CI data, and (2) train a neural network to denoise these estimated spatial components. This neural network denoiser is a stand-alone module that can be dropped in to enhance any existing 2PCI analysis pipeline.
1 tweet bioRxiv bioinformatics
Nikhil Bhagwat, Amadou Barry, Erin W. Dickie, Shawn T Brown, Gabriel Allan Devenyi, Koji Hatano, Elizabeth DuPre, Alain Dagher, Mallar Chakravarty, Celia M. T. Greenwood, Bratislav Misic, David N. Kennedy, Jean-Baptiste Poline
The choice of preprocessing pipeline introduces variability in neuroimaging analyses that affects the reproducibility of scientific findings. Features derived from structural and functional MR imaging data are sensitive to the algorithmic or parametric differences of preprocessing tasks, such as image normalization, registration, and segmentation to name a few. Therefore it is critical to understand and potentially mitigate the cumulative biases of pipelines in order to distinguish biological effects from methodological variance. Here we use an open structural MR imaging dataset (ABIDE), supplemented with the Human Connectome Project (HCP), to highlight the impact of pipeline selection on cortical thickness measures. Specifically, we investigate the effect of 1) software tool (e.g. ANTs, CIVET, FreeSurfer), 2) cortical parcellation (DKT, Destrieux, Glasser), and 3) quality control procedure (manual, automatic). We divide our statistical analyses by 1) method type, i.e. task-free (unsupervised) versus task-driven (supervised), and 2) inference objective, i.e. neurobiological group differences versus individual prediction. Results show that software, parcellation, and quality control significantly impact task-driven neurobiological inference. Additionally, software selection strongly impacts neurobiological and individual task-free analyses, and quality control alters the performance for the individual-centric prediction tasks. This comparative performance evaluation partially explains the source of inconsistencies in neuroimaging findings. Furthermore, it underscores the need for more rigorous scientific workflows and accessible informatics resources to replicate and compare preprocessing pipelines to address the compounding problem of reproducibility in the age of large-scale, data-driven computational neuroscience. ### Competing Interest Statement The authors have declared no competing interest.
1 tweet bioRxiv immunology
Carlo Cervia, Jakob Nilsson, Yves Zurbuchen, Alan Valaperti, Jens Schreiner, Aline Wolfensberger, Miro E. Raeber, Sarah Adamo, Marc Emmenegger, Sara Hasler, Philipp P. Bosshard, Elena De Cecco, Esther Bächli, Alain Rudiger, Melina Stüssi-Helbling, Lars C. Huber, Annelies S. Zinkernagel, Dominik J. Schaer, Adriano AA Aguzzi, Ulrike Held, Elsbeth Probst-Müller, Silvana K. Rampini, Onur Boyman
Background: Infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes an acute illness termed coronavirus disease 2019 (COVID-19). Humoral immune responses likely play an important role in containing SARS-CoV-2, however, the determinants of SARS-CoV-2-specific antibody responses are unclear. Methods: Using immunoassays specific for the SARS-CoV-2 spike protein, we determined SARS-CoV-2-specific immunoglobulin A (IgA) and immunoglobulin G (IgG) in sera and mucosal fluids of two cohorts, including patients with quantitative reverse-transcriptase polymerase chain reaction (RT-qPCR)-confirmed SARS-CoV-2 infection (n = 56; median age 61 years) with mild versus severe COVID-19, and SARS-CoV-2-exposed healthcare workers (n = 109; median age 36 years) with or without symptoms and tested negative or positive by RT-qPCR. Findings: On average, SARS-CoV-2-specific serum IgA titers in mild COVID-19 cases became positive eight days after symptom onset and were often transient, whereas serum IgG levels remained negative or reached positive values 9-10 days after symptom onset. Conversely, patients with severe COVID-19 showed a highly significant increase of SARS-CoV-2-specific serum IgA and IgG titers as a function of duration since symptom onset, independent of patient age and comorbidities. Very high levels of SARS-CoV-2-specific serum IgA correlated with severe acute respiratory distress syndrome (ARDS). Interestingly, some of the SARS-CoV-2-exposed healthcare workers with negative SARS-CoV-2-specific IgA and IgG serum titers had detectable SARS-CoV-2-specific IgA antibodies in their nasal fluids and tears. Moreover, SARS-CoV-2-specific IgA levels in nasal fluids of these healthcare workers were inversely correlated with patient age. Interpretation: These data show that systemic IgA and IgG production against SARS-CoV-2 develops mainly in severe COVID-19, with very high IgA levels seen in patients with severe ARDS, whereas mild disease may be associated with transient serum titers of SARS-CoV-2-specific antibodies but stimulate mucosal SARS-CoV-2-specific IgA secretion. The findings suggest four grades of antibody responses dependent on COVID-19 severity. ### Competing Interest Statement The authors have declared no competing interest.
1 tweet bioRxiv cell biology
COVID-19, SARS, and MERS are featured by fibrinolytic dysfunction. To test the role of the fibrinolytic niche in the regeneration of alveolar epithelium, we compared the self-renewing capacity of alveolar epithelial type 2 (AT2) cells and its differentiation to AT1 cells between wild type (wt) and fibrinolytic niche deficient mice (Plau-/- and Serpine1Tg). A significant reduction in both proliferation and differentiation of deficient AT2 cells was observed in vivo and in 3D organoid cultures. This decrease was mainly restored by uPA derived A6 peptide, a binding fragment to CD44 receptors. The proliferative and differential rate of CD44+ AT2 cells was greater than that of CD44- controls. There was a reduction in transepithelial ion transport in deficient monolayers compared to wt cells. Moreover, we found a marked suppression in total AT2 cells and CD44+ subpopulation in lungs from brain dead patients with acute respiratory distress syndrome (ARDS) and a mouse model infected by influenza viruses. Thus, we demonstrate that the fibrinolytic niche can regulate AT2-mediated homeostasis and regeneration via a novel uPA-A6-CD44+-ENaC cascade.
1 tweet bioRxiv genomics
Martin S. C. Larke, Takayuki Nojima, Jelena M. Telenius, Jacqueline A Sharpe, Jacqueline A. Sloane-Stanley, Sue Butler, Robert A. Beagrie, Damien J Downes, Ron Schwessinger, A. Marieke Oudelaar, Julia Truch, Bryony Crompton, M. A. Bender, Nicholas J. Proudfoot, Douglas R Higgs, Jim R Hughes
Gene transcription occurs via a cycle of linked events including initiation, promoter proximal pausing and elongation of RNA polymerase II (Pol II). A key question is how do transcriptional enhancers influence these events to control gene expression? Here we have used a new approach to quantify transcriptional initiation and pausing in vivo, while simultaneously identifying transcription start sites (TSSs) and pause-sites (TPSs) from single RNA molecules. When analyzed in parallel with nascent RNA-seq, these data show that differential gene expression is achieved predominantly via changes in transcription initiation rather than Pol II pausing. Using genetically engineered mouse models deleted for specific enhancers we show that these elements control gene expression via Pol II recruitment and/or initiation rather than via promoter proximal pause release. Together, our data show that enhancers, in general, control gene expression predominantly by Pol II recruitment and initiation rather than via pausing.
1 tweet bioRxiv scientific communication and education
The world continues to face an ongoing viral pandemic that presents a serious threat to human health. The virus underlying the COVID-19 disease, SARS-CoV-2, caused over 29 million confirmed cases and 925,000 deaths since January 2020. Although the last pandemic occurred only a decade ago, the way science operates and responds to current events has experienced a paradigm shift in the interim. The scientific community responded rapidly to the COVID-19 pandemic, releasing over 16,000 COVID-19 scientific articles within 4 months of the first confirmed case, of which 6,753 were hosted by preprint servers. Focussing on bioRxiv and medRxiv, two growing preprint servers for biomedical research, we investigated the attributes of COVID-19 preprints, their access and usage rates and characteristics of sharing across online platforms. Our results highlight the unprecedented role of preprint servers in the dissemination of COVID-19 science, and the impact of the pandemic on the scientific communication landscape. ### Competing Interest Statement JP is the executive director of ASAPbio, a non-profit organization promoting the productive use of preprints in the life sciences. GD is a bioRxiv Affiliate, part of a volunteer group of scientists that screen preprints deposited on the bioRxiv server. MP is the community manager for preLights, a non-profit preprint highlighting service. GD and JAC are contributors to preLights and ASAPbio Fellows. The authors declare no other competing interests.
1 tweet bioRxiv bioinformatics
Cell atlases often include samples that span locations, labs, and conditions, leading to complex, nested batch effects in data. Thus, joint analysis of atlas datasets requires reliable data integration. Choosing a data integration method is a challenge due to the difficulty of defining integration success. Here, we benchmark 38 method and preprocessing combinations on 77 batches of gene expression, chromatin accessibility, and simulation data from 23 publications, altogether representing >1.2 million cells distributed in nine atlas-level integration tasks. Our integration tasks span several common sources of variation such as individuals, species, and experimental labs. We evaluate methods according to scalability, usability, and their ability to remove batch effects while retaining biological variation. Using 14 evaluation metrics, we find that highly variable gene selection improves the performance of data integration methods, whereas scaling pushes methods to prioritize batch removal over conservation of biological variation. Overall, BBKNN, Scanorama, and scVI perform well, particularly on complex integration tasks; Seurat v3 performs well on simpler tasks with distinct biological signals; and methods that prioritize batch removal perform best for ATAC-seq data integration. Our freely available reproducible python module can be used to identify optimal data integration methods for new data, benchmark new methods, and improve method development. ### Competing Interest Statement F.J.T. reports receiving consulting fees from Roche Diagnostics GmbH and Cellarity Inc., and ownership interest in Cellarity, Inc. and Dermagnostix
1 tweet bioRxiv neuroscience
Reinforcement learning is a learning paradigm that can account for how organisms learn to adapt their behavior in complex environments with sparse rewards. However, implementations in spiking neuronal networks typically rely on input architectures involving place cells or receptive fields. This is problematic, as such approaches either scale badly as the environment grows in size or complexity, or presuppose knowledge on how the environment should be partitioned. Here, we propose a learning architecture that combines unsupervised learning on the input projections with clustered connectivity within the representation layer. This combination allows input features to be mapped to clusters; thus the network self-organizes to produce task-relevant activity patterns that can serve as the basis for reinforcement learning on the output projections. On the basis of the MNIST and Mountain Car tasks, we show that our proposed model performs better than either a comparable unclustered network or a clustered network with static input projections. We conclude that the combination of unsupervised learning and clustered connectivity provides a generic representational substrate suitable for further computation.
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