Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 70,235 bioRxiv papers from 306,680 authors.
Most tweeted bioRxiv papers, last 24 hours
280 results found. For more information, click each entry to expand.
152 tweets neuroscience
The International Brain Laboratory, Valeria Aguillon, Dora Angelaki, Hannah M. Bayer, Niccolo Bonacchi, Matteo Carandini, Fanny Cazettes, Anne K. Churchland, Gaelle Chapuis, Yang Dan, Eric Dewitt, Mayo Faulkner, Forrest Hamish, Laura Haetzel, Michael Hausser, Sonja Hofer, Fei Hu, Anup Khanal, Christopher Krasniak, Inês Laranjeira, Zachary Mainen, Guido Meijer, Nathaniel Miska, Thomas Mrsic-Flogel, Jean-Paul Noel, Alejandro Pan Vazquez, Josh Sanders, Karolina Socha, Rebecca Terry, Anne Urai, Hernando Martinez Vergara, Miles Wells, Christian Wilson, Ilana Witten, Lauren Wool, Anthony Zador
Progress in neuroscience is hindered by poor reproducibility of mouse behavior. Here we show that in a visual decision making task, reproducibility can be achieved by automating the training protocol and by standardizing experimental hardware, software, and procedures. We trained 101 mice in this task across nine laboratories at seven research institutions in three countries, and obtained 3 million mouse choices. In trained mice, variability in behavior between labs was indistinguishable from variability within labs. Psychometric curves showed no significant differences in visual threshold, bias, or lapse rates across labs. Moreover, mice across laboratories adopted similar strategies when stimulus location had asymmetrical probability that changed over time. We provide detailed instructions and open-source tools to set up and implement our method in other laboratories. These results establish a new standard for reproducibility of rodent behavior and provide accessible tools for the study of decision making in mice.
61 tweets biochemistry
Cells have evolved specialized protein disaggregases to reverse toxic protein aggregation and restore protein functionality. In nonmetazoan eukaryotes, the AAA+ disaggregase Hsp78 resolubilizes and reactivates proteins in mitochondria. Curiously, metazoa lack Hsp78. Hence, whether metazoan mitochondria reactivate aggregated proteins is unknown. Here, we establish that a mitochondrial AAA+ protein, Skd3 (human CLPB), couples ATP hydrolysis to protein disaggregation and reactivation. The Skd3 ankyrin-repeat domain combines with conserved AAA+ elements to enable stand-alone disaggregase activity. A mitochondrial inner-membrane protease, PARL, removes an autoinhibitory peptide from Skd3 to greatly enhance disaggregase activity. Indeed, PARL-activated Skd3 dissolves alpha-synuclein fibrils connected to Parkinson's disease. Human cells lacking Skd3 exhibit reduced solubility of various mitochondrial proteins, including anti-apoptotic Hax1. Importantly, Skd3 variants linked to 3-methylglutaconic aciduria, a severe mitochondrial disorder, display diminished disaggregase activity (but not always reduced ATPase activity), which predicts disease severity. Thus, Skd3 is a potent protein disaggregase critical for human health.
35 tweets genetics
Most loci identified by GWAS have been found in populations of European ancestry (EA). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EA individuals, we identified 5,552 trait-variant associations at P<5x10-9, including 71 novel loci not found in EA populations. We also identified novel ancestry-specific variants not found in EA, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional, and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EA-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations, and compared genetic architecture and the impact of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.
34 tweets immunology
Cellular metabolism regulates immune cell activation, differentiation and effector functions to the extent that its perturbation can augment immune responses. However, the analytical technologies available to study cellular metabolism lack single-cell resolution, obscuring metabolic heterogeneity and its connection to immune phenotype and function. To that end, we utilized high-dimensional, antibody-based technologies to simultaneously quantify the single-cell metabolic regulome in combination with phenotypic identity. Mass cytometry (CyTOF)-based application of this approach to early human T cell activation enabled the comprehensive reconstruction of the coordinated metabolic remodeling of naive CD8+ T cells and aligned with conventional bulk assays for glycolysis and oxidative phosphorylation. Extending this analysis to a variety of tissue-resident immune cells revealed tissue-restricted metabolic states of human cytotoxic T cells, including metabolically repressed subsets that expressed CD39 and PD1 and that were enriched in colorectal carcinoma versus healthy adjacent tissue. Finally, combining this approach with multiplexed ion beam imaging by time-of-flight (MIBI-TOF) demonstrated the existence of spatially enriched metabolic neighborhoods, independent of cell identity and additionally revealed exclusion of metabolically repressed cytotoxic T cell states from the tumor-immune boundary in human colorectal carcinoma. Overall, we provide an approach that permits the robust approximation of metabolic states in individual cells along with multimodal analysis of cell identity and functional characteristics that can be applied to human clinical samples to study cellular metabolism how it may be perturbed to affect immunological outcomes.
32 tweets microbiology
Emma B. Hodcroft, Robert Dyrdak, Cristina Andres, Adrian Egli, Josiane Reist, Diego Garcia Martinez de Artola, Julia Alcoba Florez, Hubert G. M. Niesters, Andres Anton, Randy Poelman, Marijke Reynders, Elke Wollants, Richard A. Neher, Jan Albert
Background: Worldwide outbreaks of enterovirus D68 (EV-D68) in 2014 and 2016 have caused serious respiratory and neurological disease. Methods: We collected samples from several European countries during the 2018 outbreak and determined 53 near full-length genome ('whole genome') sequences. These sequences were combined with 718 whole genome and 1,987 VP1-gene publicly available sequences. Findings: In 2018, circulating strains clustered into multiple subgroups in the B3 and A2 subclades, with different phylogenetic origins. Clusters in subclade B3 emerged from strains circulating primarily in the US and Europe in 2016, though some had deeper roots linking to Asian strains, while clusters in A2 traced back to strains detected in East Asia in 2015-2016. In 2018, all sequences from the USA formed a distinct subgroup, containing only three non-US samples. Alongside the varied origins of seasonal strains, we found that diversification of these variants begins up to 18 months prior to the first diagnostic detection during a EV-D68 season. EV-D68 displays strong signs of continuous antigenic evolution and all 2018 A2 strains had novel patterns in the putative neutralizing epitopes in the BC- and DE-loops. The pattern in the BC-loop of the USA B3 subgroup had not been detected on that continent before. Patients with EV-D68 in subclade A2 were significantly older than patients with a B3 subclade virus. In contrast to other subclades, the age distribution of A2 is distinctly bimodal and was found primarily among children and in the elderly. Interpretation: We hypothesize that EV-D68's rapid evolution of surface proteins, extensive diversity, and high rate of geographic mixing could be explained by substantial reinfection of adults.
24 tweets neuroscience
Identifying brain biomarkers of disease risk is a growing priority in neuroscience. The ability to identify meaningful biomarkers is limited by measurement reliability; unreliable measures are unsuitable for predicting clinical outcomes. Measuring brain activity using task-fMRI is a major focus of biomarker development; however, the reliability of task-fMRI has not been systematically evaluated. We present converging evidence demonstrating poor reliability of task-fMRI measures. First, a meta-analysis of 90 experiments (N=1,008) revealed poor overall reliability (mean ICC=.397). Second, the test-retest reliabilities of activity in a priori regions of interest across 11 common fMRI tasks collected in the context of the Human Connectome Project (N=45) and the Dunedin Study (N=20) were poor (ICCs=.067-.485). Collectively, these findings demonstrate that common task-fMRI measures are not currently suitable for brain biomarker discovery or individual differences research. We review how this state of affairs came to be and highlight avenues for improving task-fMRI reliability.
23 tweets biochemistry
De novo emergence, and emergence of the earliest proteins specifically, demands a transition from disordered polypeptides into structured proteins with well defined functions. However, can peptides confer evolutionary relevant functions, let alone with minimal abiotic amino acid alphabets? How can such polypeptides evolve into mature proteins? Specifically, while nucleic acids binding is presumed a primordial function, it demands basic amino acids that do not readily form abiotically. To address these questions, we describe an experimentally-validated trajectory from a phase-separating polypeptide to a dsDNA-binding protein. The intermediates comprise sequence-duplicated, functional proteins made of only 10 amino acid types, with ornithine, which can form abiotically, as the only basic amino acid. Statistical, chemical modification of ornithine sidechains to arginine promoted structure and function. The function concomitantly evolved from phase separation with RNA (coacervates) to avid and specific dsDNA binding thereby demonstrating a smooth, gradual peptide-to-protein transition with respect to sequence, structure, and function.
22 tweets microbiology
Allyson L Byrd, Menghan Liu, Kei E Fujimura, Svetlana Lyalina, Deepti R Nagarkar, Bruno Charbit, Etienne Patin, Oliver J Harrison, Lluis Quintana-Murci, Darragh Duffy, Matthew L. Albert, The Milieu Interieur Consortium
Analysis of 1,363 deeply sequenced gut microbiome samples from 946 healthy donors of the Milieu Intérieur cohort provides new opportunities to discover how the gut microbiome is associated with host factors and lifestyle parameters. Using a genome-based taxonomy to achieve higher resolution analysis, we found an enrichment of Prevotella species in males, and that bacterial profiles are dynamic across five decades of life (20-69), with Bacteroidota species consistently increased with age while Actinobacteriota species, including Bifidobacterium, decreased. Longitudinal sampling revealed short-term stability exceeds inter-individual differences; however, the degree of stability was variable between donors and influenced by their baseline community composition. We then integrated the microbiome results with systemic immunophenotypes to show that host/microbe associations discovered in animal models, such as T regulatory cells and short chain fatty acids, could be validated in human data. These results will enable personalized medicine approaches for microbial therapeutics and biomarkers.
21 tweets microbiology
Plants grow within a complex web of species interacting with each other and with the plant. Many of these interactions are governed by a wide repertoire of chemical signals, and the resulting chemical landscape of the rhizosphere can strongly affect root health and development. To understand how microbe-microbe interactions influence root development in Arabidopsis, we established a model system for plant-microbe-microbe-environment interactions. We inoculated seedlings with a 185-member bacterial synthetic community (SynCom), manipulated the abiotic environment, and measured bacterial colonization of the plant. This enabled classification of the SynCom into four modules of co-occurring strains. We deconstructed the SynCom based on these modules, identifying microbe-microbe interactions that determine root phenotypes. These interactions primarily involve a single bacterial genus, Variovorax, which completely reverts severe root growth inhibition (RGI) induced by a wide diversity of bacterial strains as well as by the entire 185-member community. We demonstrate that Variovorax manipulate plant hormone levels to balance this ecologically realistic root community's effects on root development. We identify a novel auxin degradation operon in the Variovorax genome that is necessary and sufficient for RGI reversion. Therefore, metabolic signal interference shapes bacteria-plant communication networks and is essential for maintaining the root's developmental program. Optimizing the feedbacks that shape chemical interaction networks in the rhizosphere provides a promising new ecological strategy towards the development of more resilient and productive crops.
20 tweets plant biology
Adrian Wolny, Lorenzo Cerrone, Athul Vijayan, Rachele Tofanelli, Amaya Vilches Barro, Marion Louveaux, Christian Wenzl, Susanne Steigleder, Constantin Pape, Alberto Bailoni, Salva Duran-Nebreda, George Bassel, Jan U. Lohmann, Fred A. Hamprecht, Kay Schneitz, Alexis Maizel, Anna Kreshuk
Quantitative analysis of plant and animal morphogenesis requires accurate segmentation of individual cells in volumetric images of growing organs. In the last years, deep learning has provided robust automated algorithms that approach human performance, with applications to bio image analysis now starting to emerge. Here, we present PlantSeg, a pipeline for volumetric segmentation of plant tissues into cells. PlantSeg employs a convolutional neural network to predict cell boundaries and graph partitioning to segment cells based on the neural network predictions. PlantSeg was trained on fixed and live plant organs imaged with confocal and light sheet microscopes. PlantSeg delivers accurate results and generalizes well across different tissues, scales, and acquisition settings. We present results of PlantSeg applications in diverse developmental contexts. PlantSeg is free and open-source, with both a command line and a user-friendly graphical interface.
20 tweets bioinformatics
Mapping of reads to reference sequences is an essential step in a wide range of biological studies. The large size of datasets generated with next-generation sequencing technologies motivates the development of fast mapping software. Here, I describe URMAP, a new read mapping algorithm. URMAP is an order of magnitude faster than BWA and Bowtie2 with comparable accuracy on a benchmark test using simulated paired 150nt reads of a well-studied human genome. Software is freely available at https://drive5.com/urmap.
20 tweets cell biology
Meng Lu, Francesca W. van Tartwijk, Julie Qiaojin Lin, Wilco Nijenhuis, Pierre Parutto, Marcus Fantham, Charles N. Christensen, Edward Avezov, Christine E. Holt, Alan Tunnacliffe, David Holcman, Lukas C Kapitein, Gabriele Kaminski Schierle, C.F. Kaminski
The endoplasmic reticulum (ER) comprises morphologically and functionally distinct domains, sheets and interconnected tubules. These domains undergo dynamic reshaping, in response to changes in the cellular environment. However, the mechanisms behind this rapid remodeling within minutes are largely unknown. Here, we report that ER remodeling is actively driven by lysosomes, following lysosome repositioning in response to changes in nutritional status. The anchorage of lysosomes to ER growth tips is critical for ER tubule elongation and connection. We validate this causal link via the chemo- and optogenetically driven re-positioning of lysosomes, which leads to both a redistribution of the ER tubules and its global morphology. Lysosomes sense metabolic change in the cell and regulate ER tubule distribution accordingly. Dysfunction in this mechanism during axonal extension may lead to axonal growth defects. Our results demonstrate a critical role of lysosome-regulated ER dynamics and reshaping in nutrient responses and neuronal development.
16 tweets neuroscience
Animals actively sample from the sensory world by generating complex patterns of movement that evolve in three dimensions. At least some of these movements have been shown to influence neural codes in sensory areas. For example, in primary visual cortex (V1), locomotion-related neural activity influences sensory gain, encodes running speed, and predicts the direction of visual flow. As most experiments exploring movement-related modulation of V1 have been performed in head-fixed animals, it remains unclear whether or how the naturalistic movements used to interact with sensory stimuli--like head orienting--influence visual processing. Here we show that 3D head orienting movements modulate V1 neuronal activity in a direction-specific manner that also depends on the presence or absence of light. We identify two largely independent populations of movement-direction-tuned neurons that support this modulation, one of which is direction-tuned in the dark and the other in the light. Finally, we demonstrate that V1 gains access to a motor efference copy related to orientation from secondary motor cortex, which has been shown to control head orienting movements. These results suggest a mechanism through which sensory signals generated by purposeful movement can be distinguished from those arising in the outside world, and reveal a pervasive role of 3D movement in shaping sensory cortical dynamics.
15 tweets bioinformatics
In this work we develop a novel algorithm for reconstructing the genomes of ancestral individuals, given genotype or sequence data from contemporary individuals and an extended pedigree of family relationships. A pedigree with complete genomes for every individual enables the study of allele frequency dynamics and haplotype diversity across generations, including deviations from neutrality such as transmission distortion. When studying heritable diseases, ancestral haplotypes can be used to augment genome-wide association studies or compute polygenic risk scores for the reconstructed individuals. The building blocks of our reconstruction algorithm are segments of Identity-By-Descent (IBD) shared between two or more genotyped individuals. The method alternates between finding a source for each IBD segment and assembling IBD segments placed within each ancestral individual. After each iteration we perform conflict resolution to remove IBD segments that do not align with well- reconstructed haplotypes and upweight the probability that these segments should be placed in other individuals. We repeat this process until we are no longer successfully reconstructing additional ancestral haplotypes. Unlike previous approaches, our method is able to accommodate complex pedigree structures with hundreds of individuals genotyped at millions of SNPs. We apply our method to an Old Order Amish pedigree from Lancaster, Pennsylvania, whose founders came to the United States from Europe during the early 18th century. The pedigree includes 1338 individuals from the past 10 generations, 394 with genotype data. The motivation for reconstruction is to understand the genetic basis of diseases segregating in the family through tracking haplotype transmission over time. Using our algorithm thread, we are able to reconstruct an average of 230 ancestral individuals per autosome. thread was developed for endogamous populations, but can be applied to any extensive pedigree with the recent generations genotyped. We anticipate that this type of practical ancestral reconstruction will become more common and necessary to understand rare and complex heritable diseases in extended families.
15 tweets bioinformatics
As the volume of next generation sequencing data increases, an urgent need for algorithms to efficiently process the data arises. Universal hitting sets (UHS) were recently introduced as an alternative to the central idea of minimizers in sequence analysis with the hopes that they could more efficiently address common tasks such as computing hash functions for read overlap, sparse suffix arrays, and Bloom filters. A UHS is a set of k-mers that hit every sequence of length L, and can thus serve as indices to L-long sequences. Unfortunately, methods for computing small UHSs are not yet practical for real-world sequencing instances due to their serial and deterministic nature, which leads to long runtimes and high memory demands when handling typical values of k (e.g. k > 13). To address this bottleneck, we present two algorithmic innovations to significantly decrease runtime while keeping memory usage low: (i) we leverage advanced theoretical and architectural techniques to parallelize and decrease memory usage in calculating k-mer hitting numbers; and (ii) we build upon techniques from randomized Set Cover to select universal k-mers much faster. We implemented these innovations in PASHA, the first randomized parallel algorithm for generating near-optimal UHSs, which newly handles k > 13. We demonstrate empirically that PASHA produces sets only slightly larger than those of serial deterministic algorithms; moreover, the set size is provably guaranteed to be within a small factor of the optimal size. PASHA's runtime and memory usage improvements are orders of magnitude faster than the current best algorithms. We expect our newly-practical construction of UHSs to be adopted in many high-throughput sequence analysis pipelines.
14 tweets genomics
Most protein encoding genes in eukaryotes contain introns which are interwoven with exons. After transcription, introns need to be removed in order to generate the final mRNA which can be translated into an amino acid sequence. Precise excision of introns by the spliceosome requires conserved dinucleotides which mark the splice sites. However, there are variations of the highly conserved combination of GT at the 5' end and AG at the 3' end of an intron in the genome. GC-AG and AT-AC are two major non-canonical splice site combinations which have been known for years. During the last years, various minor non-canonical splice site combinations were detected with numerous dinucleotide permutations. Here we expand systematic investigations of non-canonical splice site combinations in plants to all eukaryotes by analysing fungal and animal genome sequences. Comparisons of splice site combinations between these three kingdoms revealed several differences such as a substantially increased CT-AC frequency in fungal genome sequences. Canonical GT-AG splice site combinations in antisense transcripts could be one explanation for this observation. In addition, high numbers of GA-AG splice site combinations were observed in Eurytemora affinis and Oikopleura dioica. A variant in one U1 snRNA isoform might allow the recognition of GA as 5' splice site. In depth investigation of splice site usage based on RNA-Seq read mappings indicates a generally higher flexibility of the 3' splice site compared to the 5' splice site across animals, fungi, and plants.
14 tweets neuroscience
Large-scale mapping of the location of synapses and their molecular properties in the mouse has shown that diverse synapse types are spatially distributed across the brain. The diversity of synapses is known as the synaptome and the spatial distribution as the synaptome architecture. Synaptome maps in the mouse show each brain region has a characteristic compositional signature. The signature can store behavioral representations and is modified in mouse genetic models of human disease. The human synaptome remains unexplored and whether it has any conserved features with the mouse synaptome is unknown. As a first step toward creating a human synaptome atlas, we have labelled and imaged synapses expressing the excitatory synapse protein PSD95 in twenty human brain regions in four phenotypically normal individuals. We quantified the number, size and intensity of approximately a billion individual synaptic puncta and compared their regional distributions. We found that each region showed a distinct signature of synaptic puncta parameters. Comparison of brain regions showed the synaptome of cortical and hippocampal structures were similar but distinct to the synaptome of cerebellum and brainstem. Comparison of human and mouse synaptome revealed conservation of synaptic puncta parameters, hierarchical organization of brain regions and network architecture. These data show that the synaptome of humans and mouse share conserved features despite the 1000-fold difference in brain size and 90 million years since a common ancestor. This first draft human synaptome atlas illustrates the feasibility of generating a systematic atlas of the human synaptome in health and disease.
13 tweets genetics
The Kruppel-associated box zinc finger protein (KRAB-ZFP) family amplified and diversified in mammals by segmental duplications, but the function of the majority of this gene family remains largely unexplored due to the inaccessibility of the gene clusters to conventional gene targeting. We determined the genomic binding sites of 61 murine KRAB-ZFPs and genetically deleted in mouse embryonic stem (ES) cells five large KRAB-ZFP gene clusters encoding nearly one tenth of the more than 700 mouse KRAB-ZFPs. We demonstrate that clustered KRAB-ZFPs directly bind and silence retrotransposons and block retrotransposon-borne enhancers from gene activation in ES cells. Homozygous knockout mice generated from ES cells deleted in one of two KRAB-ZFP clusters were born at sub-mendelian frequencies in some matings, but heterozygous intercrosses could also yield knockout progeny with no overt phenotype. We further developed a retrotransposon capture-sequencing approach to assess mobility of the MMETn family of endogenous retrovirus like elements, which are transcriptionally activated in KRAB-ZFP cluster KOs, in a pedigree of KRAB-ZFP cluster KO and WT mice. We identified numerous somatic and several germ-line MMETn insertions, and found a modest increase in activity in mutant animals, but these events were detected in both wild-type and KO mice in stochastic and highly variable patterns. Our data suggests that the majority of young KRAB-ZFPs play a non-essential role in transposon silencing, likely due to the large redundancy with other KRAB-ZFPs and other transposon restriction pathways in mice.
12 tweets bioinformatics
Joint analysis of multiple single cell RNA-sequencing (scRNA-seq) data is confounded by technical batch effects across experiments, biological or environmental variability across cells, and different capture processes across sequencing platforms. Manifold alignment is a principled, effective tool for integrating multiple data sets and controlling for confounding factors. We demonstrate that the semi-supervised t-distributed Gaussian process latent variable model (sstGPLVM), which projects the data onto a mixture of fixed and latent dimensions, can learn a unified low-dimensional embedding for multiple single cell experiments with minimal assumptions. We show the efficacy of the model as compared with state-of-the-art methods for single cell data integration on simulated data, pancreas cells from four sequencing technologies, stem cells from male and female donors, and mouse brain cells from both spatial seqFISH+ and traditional scRNA-seq.
12 tweets ecology
While glacier ice cores provide climate information over tens to hundreds of thousands of years, study of microbes is challenged by ultra-low-biomass conditions, and virtually nothing is known about co-occurring viruses. Here we establish ultra-clean microbial and viral sampling procedures and apply them to two ice cores from the Guliya ice cap (northwestern Tibetan Plateau, China) to study these archived communities. This method reduced intentionally contaminating bacterial, viral, and free DNA to background levels in artificial-ice-core control experiments, and was then applied to two authentic ice cores to profile their microbes and viruses. The microbes differed significantly across the two ice cores, presumably representing the very different climate conditions at the time of deposition that is similar to findings in other cores. Separately, viral particle enrichment and ultra-low-input quantitative viral metagenomic sequencing from ~520 and ~15,000 years old ice revealed 33 viral populations (i.e., species-level designations) that represented four known genera and likely 28 novel viral genera (assessed by gene-sharing networks). In silico host predictions linked 18 of the 33 viral populations to co-occurring abundant bacteria, including Methylobacterium, Sphingomonas, and Janthinobacterium, indicating that viruses infected several abundant microbial groups. Depth-specific viral communities were observed, presumably reflecting differences in the environmental conditions among the ice samples at the time of deposition. Together, these experiments establish a clean procedure for studying microbial and viral communities in low-biomass glacier ice and provide baseline information for glacier viruses, some of which appear to be associated with the dominant microbes in these ecosystems.
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