Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 52,871 bioRxiv papers from 244,990 authors.
Most tweeted bioRxiv papers, last 24 hours
218 results found. For more information, click each entry to expand.
9 tweets genomics
Chromosome folding is extensively modulated as cells progress through the cell cycle. During mitosis, condensin complexes fold chromosomes in helically arranged nested loop arrays. In interphase, the cohesin complex generates loops that can be stalled at CTCF sites leading to positioned loops and topologically associating domains (TADs), while a separate process of compartmentalization drives the spatial segregation of active and inactive chromatin domains. We used synchronized cell cultures to determine how the mitotic chromosome conformation is transformed into the interphase state. Using Hi-C, chromatin binding assays, and immunofluorescence we show that by telophase condensin-mediated loops are lost and a transient folding intermediate devoid of most loops forms. By late telophase, cohesin-mediated CTCF-CTCF loops and positions of TADs start to emerge rapidly. Compartment boundaries are also established in telophase, but long-range compartmentalization is a slow process and proceeds for several hours after cells enter G1. Our results reveal the kinetics and order of events by which the interphase chromosome state is formed and identify telophase as a critical transition between condensin and cohesin driven chromosome folding.
8 tweets physiology
Anthony P. Coll, Michael Chen, Pranali Taskar, Debra Rimmington, Satish Patel, John Tadross, Irene Cimino, Ming Yang, Paul Welsh, Samuel Virtue, Deborah A Goldspink, Emily Miedzybrodzka, Y.C. Loraine Tung, Sergio Rodriguez-Cuenca, Rute A Tomaz, Heather P Harding, Audrey Melvin, Giles S. H. Yeo, David Preiss, Antonio Vidal-Puig, Ludovic Vallier, David Ron, Fiona M Gribble, Frank Reimann, Naveed Sattar, David B Savage, Bernard B Allan, Stephen O'Rahilly
Metformin, the world's most prescribed anti-diabetic drug, is also effective in preventing Type 2 diabetes in people at high risk, by lowering body weight, fat mass and circulating insulin levels through mechanisms that are incompletely understood. Recent observational studies reporting the association of metformin use and circulating levels of GDF15 led us to hypothesize that GDF15, which signals through a specific receptor complex in the hindbrain to reduce body weight, might mediate these effects. We measured GDF15 in people without diabetes from a randomized placebo-controlled trial of metformin. Over 18 months, participants allocated metformin lost significant weight and levels of GDF15 were persistently elevated compared to placebo. The change in plasma GDF15 in this study correlated positively with weight loss. In wild-type mice, oral metformin increased circulating GDF15 with GDF15 expression increasing predominantly in the distal intestine and the kidney. Metformin prevented weight gain in response to high fat diet in wild-type mice but not in mice lacking GDF15 or its receptor GFRAL. In obese, high fat-fed mice, the effects of metformin to reduce body weight were reversed by a GFRAL antagonist antibody. Metformin had effects on both energy intake and energy expenditure that required GDF15. The insulin sensitising effects of metformin determined by insulin tolerance were abolished in mice lacking GDF15. Metformin significantly reduced fasting glucose and insulin levels in wild type but not in mice lacking GDF15. In summary, metformin increases the circulating levels of GDF15, which appears to be necessary for many of its actions as a metabolic chemopreventive agent.
8 tweets neuroscience
Fanny M. Elahi, Danielle J. Harvey, Marie Altendahl, Kaitlin B. Casaletto, Nicole Fernandes, Adam M. Staffaroni, Pauline Maillard, Jason D Hinman, Bruce L Miller, Charles DeCarli, Joel H. Kramer, Edward J. Goetzl
We test the hypothesis that endothelial cells take on an inflammatory phenotype in functionally intact human subjects with radiographic evidence of white matter injury. Markers within all three complement effector pathways and regulatory proteins were quantified from endothelial-derived exosomes (EDE) of subjects (age 70-82) with (n=11) and without (n=16) evidence of white matter hyperintensity on MRI. Group differences and associations with systemic markers of immune activation (IL6, ICAM1), cognition and neuroimaging were calculated via regression modelling. EDE complement factors within the alternative and classical pathways were found to be higher and regulatory proteins lower in subjects with WMH. EDE levels of several factors demonstrated significant associations with cognitive slowing and systolic blood pressure. The inhibitor of the membrane attack complex, CD46, showed a significant positive association with cerebral grey matter volume. Systemic inflammatory markers, IL6 and ICAM1, were positively associated with EDE levels of several factors. These findings provide the first in vivo evidence of the association of endothelial cell inflammation with white matter injury, cognition, and brain degeneration in functionally normal older individuals, and form the basis for future biomarker development in early or preclinical stages of vascular cognitive impairment and dementia.
8 tweets plant biology
The FRIGIDA locus (FRI, AT4G00650) has been extensively studied in Arabidopsis thaliana because of its role creating flowering time diversity. The FRI protein regulates flowering induction by binding partner proteins on its N- and C-terminus domains and creating a supercomplex that promotes transcription of the floral repressor FLC. Despite the knowledge accumulated on FRI, the function of the highly conserved central domain of the protein is still unknown. Functional characterization of naturally occurring DNA polymorphisms can provide useful information about the role of a protein and the localization of its operative domains. In the case of FRI, deleterious mutations are positively selected and widespread in nature, making them a powerful tool to study the function of the different domains of the protein. Here we explore natural sequence variation in the FRI locus in more than 1000 Arabidopsis accessions. We identify new mutations predicted to compromise the function of the protein and confirm our predictions by cloning 22 different alleles of FRI and expressing them in a common null genetic background. Our analysis allows us to pinpoint two single amino acid changes in the central domain that render the protein non-functional. We show that these two mutations determine the stability and cellular localization of the FRI protein. In summary, our work makes use of natural variants at the FRI locus to help understanding the function of the central domain of the FRI protein.
7 tweets zoology
In the past few years, diagnoses by veterinarians of recurrent canine hookworm infections have dramatically increased, suggesting that anthelmintic resistance (AR) may have evolved in the parasite Ancylostoma caninum. To investigate this, we established three suspected-resistant and two susceptible A. caninum isolates in research dogs for further study. The egg hatch assay (EHA) and the larval development assay (LDA) were used for detecting resistance to benzimidazoles, and macrocyclic lactones, respectively. Resistance ratios ranged from 6.0 to >100 and 5.5 to 69.8 for the EHA and LDA, respectively. Following treatments with fenbendazole, pyrantel and milbemycin oxime, reduction in fecal egg counts ranged from 64 to 86%, 0 to 2% and 58 to 92%, respectively. Deep amplicon sequencing of the isotype-1 beta-tubulin gene identified a high frequency of resistance-associated single nucleotide polymorphisms at codon 167 in the resistant isolates and clinical cases. These data conclusively demonstrate multiple anthelmintic resistance in A. caninum, and provide pivotal evidence that this is an emerging problem in the United States. Consequently, these findings should provide some concern to the global health community, as the scale-up of mass drug administration for soil-transmitted helminths (STH) is now placing similar selection pressures for benzimidazole resistance in human hookworms.
7 tweets bioinformatics
Spectral matching sequence database search engines commonly used on mass spectrometry-based proteomics experiments excel at identifying peptide sequence ions, and in addition, possible sequence ions carrying post-translational modifications (PTMs), but most do not provide confidence metrics for the exact localization of those PTMs when several possible sites are available. Localization is absolutely required for downstream molecular cell biology analysis of PTM function in vitro and in vivo. Therefore, we developed PTMProphet, a free and open-source software tool integrated into the Trans-Proteomic Pipeline, which reanalyzes identified spectra from any search engine for which pepXML output is available to provide localization confidence to enable appropriate further characterization of biologic events. Localization of any type of mass modification (e.g., phosphorylation) is supported. PTMProphet applies Bayesian mixture models to compute probabilities for each site/peptide spectrum match where a PTM has been identified. These probabilities can be combined to compute a global false localization rate at any threshold to guide downstream analysis. We describe the PTMProphet tool, its underlying algorithms and demonstrate its performance on ground-truth synthetic peptide reference datasets, one previously published small dataset, one new larger dataset, and also on a previously published phospho-enriched dataset where the correct sites of modification are unknown. Data have been deposited to ProteomeXchange with identifier PXD013210.
7 tweets bioinformatics
Background: Highly accurate next-generation sequencing (NGS) of genetic variants is key to many areas of science and medicine, such as cataloguing population genetic variation and diagnosing patients with genetic diseases. Certain genomic loci and regions can be prone to higher rates of systematic sequencing and alignment bias that pose a challenge to achieving high accuracy, resulting in false positive variant calls. Current standard practices to differentiate between loci that can and cannot be sequenced with high confidence utilise consensus between different sequencing methods as a proxy for sequencing confidence. This assumption is not accurate in cases where all sequencing pipelines have consensus on the same errors due to similar systematic biases in sequencing. Alternative methods are therefore required to identify systematic biases. Methods: We have developed a novel statistical method based on summarising sequenced reads from whole genome clinical samples and cataloguing them in "Incremental Databases" (IncDBs) that maintain individual confidentiality. Variant statistics were analysed and catalogued for each genomic position that consistently showed systematic biases with the corresponding sequencing pipeline. Results: We have demonstrated that systematic errors in NGS data are widespread, with persistent low-fraction alleles present at 1.26-2.43% of the human autosomal genome across three different Illumina-based pipelines, each consisting of at least 150 patient samples. We have identified a variety of genomic regions that are more or less prone to systematic biases, such as GC-rich regions (OR = 6.47-8.19) and the NIST high-confidence genomic regions (OR = 0.154-0.191). We have verified our predictions on a gold-standard reference genome and have shown that these systematic biases can lead to suspect variant calls at clinically important loci, including within introns and exons. Conclusions: Our results recommend increased caution to minimise the effect of systematic biases in whole genome sequencing and alignment. This study supports the utility of a statistical approach to enhance quality control of clinically sequenced samples in order to flag up variant calls made at known suspect loci for further analysis or exclusion, using anonymised summary databases from which individual patients cannot be re-identified, so that results can be shared more widely.
7 tweets neuroscience
Deep convolutional neural networks (DCNNs) rival humans in object recognition. The layers (or levels of representation) in DCNNs have been successfully aligned with processing stages along the ventral stream for visual processing. Here, we propose a model of concept learning that uses visual representations from these networks to build memory representations of novel categories, which may rely on the medial temporal lobe (MTL) and medial prefrontal cortex (mPFC). Our approach opens up two possibilities: a ) formal investigations can involve photographic stimuli as opposed to stimuli handcrafted and coded by the experimenter; b ) model comparison can determine which level of representation within a DCNN a learner is using during categorization decisions. Pursuing the latter point, DCNNs suggest that the shape bias in children relies on representations at more advanced network layers whereas a learner that relied on lower network layers would display a color bias. These results confirm the role of natural statistics in the shape bias (i.e., shape is predictive of category membership) while highlighting that the type of statistics matter, i.e., those from lower or higher levels of representation. We use the same approach to provide evidence that pigeons performing seemingly sophisticated categorization of complex imagery may in fact be relying on representations that are very low-level (i.e., retinotopic). Although complex features, such as shape, relatively predominate at more advanced network layers, even simple features, such as spatial frequency and orientation, are better represented at the more advanced layers, contrary to a standard hierarchical view.
7 tweets biochemistry
Gerard G Lambert, Hadrien Depernet, Guillaume Gotthard, Darrin T Schultz, lsabelle Navizet, Talley Lambert, Daphne S. Bindels, Vincent Levesque, Jennifer N Nero Moffatt, Anya Salih, Antoine Royant, Nathan C. Shaner
Using mRNA-Seq and de novo transcriptome assembly, we identified, cloned and characterized nine previously undiscovered fluorescent protein (FP) homologs from Aequorea victoria and a related Aequorea species, with most sequences highly divergent from avGFP. Among these FPs are the brightest GFP homolog yet characterized and a reversibly photochromic FP that responds to UV and blue light. Beyond green emitters, Aequorea species express purple- and blue-pigmented chromoproteins (CPs) with absorbances ranging from green to far-red, including two that are photoconvertible. X-ray crystallography revealed that Aequorea CPs contain a chemically novel chromophore with an unexpected crosslink to the main polypeptide chain. Because of the unique attributes of several of these newly discovered FPs, we expect that Aequorea will, once again, give rise to an entirely new generation of useful probes for bioimaging and biosensing.
6 tweets bioinformatics
Small non-coding RNAs (sncRNAs) play important roles in health and disease. Next Generation Sequencing technologies are considered as the most powerful and versatile methodologies to explore small RNA (sRNA) transcriptomes in diverse experimental and clinical studies. Small RNA-Seq data analysis proved to be challenging due to non-unique genomic origin, short length and abundant post-transcriptional modifications of sRNA species. Here we present Manatee, an algorithm for quantification of sRNA classes and detection of uncharacterized expressed non-coding loci. Manatee adopts a novel approach for abundance estimation of genomic reads that combines sRNA annotation with reliable alignment density information and extensive reads salvation. Comparison of Manatee against state-of-the-art implementations using real/simulated data sets demonstrates its superior accuracy in quantification of diverse sRNA classes providing at the same time insights about unannotated expressed loci. It is user-friendly, easily embeddable in pipelines and provides a simplified output suitable for direct usage in downstream analyses and functional studies.
6 tweets developmental biology
Commonly referred to as the maternal-to-zygotic transition, the shift of developmental control from maternal-to-zygotic genomes is a key event during animal and plant embryogenesis. Together with the degradation of parental gene products, the increased transcriptional activities of the zygotic genome remodels the early embryonic transcriptome during this transition. Although evidence from multiple flowering plants suggests that zygotes become transcriptionally active soon after fertilization, the timing and developmental requirements of zygotic genome activation in Arabidopsis thaliana (Arabidopsis) remained a matter of debate until recently. In this report, we optimized an expansion microscopy technique for robust immunostaining of Arabidopsis ovules and seeds. This enabled the detection of marks indicative of active transcription in zygotes before the first cell division. Moreover, we employed a live-imaging culture system together with transcriptional inhibitors to demonstrate that such active transcription is required in zygotes. Our results indicate that zygotic genome activation occurs soon after fertilization and is physiologically required prior to the initial zygotic division in Arabidopsis.
6 tweets synthetic biology
Base editors engineered from an inactivated Cas9 and a DNA editing enzyme offer an unprecedented opportunity for the precise modification of genes, but have yet to be used at a genome-scale throughput. Here, we test the ability of an editor based on a cytidine deaminase, the Target-AID base editor, to systematically modify genes genome-wide using the set of yeast essential genes. We tested the effect of mutating around 17,000 sites across more than 1,500 genes in a single experiment. We identified over 1,100 sites where mutations have a significant impact on fitness. Using previously determined and preferred Target-AID mutational outcomes, we predicted the protein variants caused by each of these gRNAs. We found that gRNAs with significant effects on fitness are enriched in variants predicted to be deleterious by independent methods based on site conservation and predicted protein destabilization. Finally, we identify key features to design effective gRNAs in the context of base editing. Our results show that base editing is a powerful tool to identify key amino acid residues at the scale of proteomes.
6 tweets ecology
High-throughput sequencing techniques such as metagenomic and metatranscriptomic technologies allow cataloging of functional characteristics of microbial community members as well as their taxonomic identity. Such studies have found that a community's composition in terms of ecologically relevant functional traits or guilds can be conserved more strictly across varying settings than taxonomic composition is. I use a standard ecological resource-consumer model to examine the dynamics of traits relevant to resource consumption, and analyze determinants of functional composition. This model demonstrates that interaction with essential resources can regulate the community-wide abundance of ecologically relevant traits, keeping them at consistent levels despite large changes in the abundances of the species housing those traits in response to changes in the environment, and across variation between communities in species composition. Functional composition is shown to be able to track differences in environmental conditions faithfully across differences in community composition. Mathematical conditions on consumers' vital rates and functional responses sufficient to produce conservation of functional community structure across taxonomic differences are presented.
6 tweets evolutionary biology
Microbes are embedded in complex microbiomes where they engage in a wide array of inter- and intra-specific interactions. However, whether these interactions are a significant driver of natural biodiversity is not well understood. Two contrasting hypotheses have been put forward to explain how species interactions could influence diversification. 'Ecological Controls' (EC) predicts a negative diversity-diversification relationship, where the evolution of novel types becomes constrained as available niches become filled. In contrast, 'Diversity Begets Diversity' (DBD) predicts a positive relationship, with diversity promoting diversification via niche construction and other species interactions. Using the Earth Microbiome Project, the largest standardized survey of global biodiversity to date, we provide support for DBD as the dominant driver of microbiome diversity. Only in the most diverse microbiomes does DBD reach a plateau, consistent with increasingly saturated niche space. Genera that are strongly associated with a particular biome show a stronger DBD relationship than non-residents, consistent with prolonged evolutionary interactions driving diversification. Genera with larger genomes also experience a stronger DBD response, which could be due to a higher potential for metabolic interactions and niche construction offered by more diverse gene repertoires. Our results demonstrate that the rate at which microbiomes accumulate diversity is crucially dependent on resident diversity. This fits a scenario in which species interactions are important drivers of microbiome diversity. Further (population genomic or metagenomic) data are needed to elucidate the nature of these biotic interactions in order to more fully inform predictive models of biodiversity and ecosystem stability.
5 tweets microbiology
CRISPR-Cas systems are adaptive immune systems that protect bacteria from bacteriophage (phage) infection. To provide immunity, RNA-guided protein surveillance complexes recognize foreign nucleic acids, triggering their destruction by Cas nucleases. While the essential requirements for immune activity are well understood, the physiological cues that regulate CRISPR-Cas expression are not. Here, a forward genetic screen identifies a two-component system (KinB/AlgB), previously characterized in regulating Pseudomonas aeruginosa virulence and biofilm establishment, as a regulator of the biogenesis of the Type I-F CRISPR-Cas surveillance complex. Downstream of the KinB/AlgB system, activators of biofilm production AlgU (a σE orthologue) and AlgR, act as repressors of CRISPR-Cas surveillance complex expression during planktonic and surface-associated growth. AmrZ, another biofilm activator, functions as a surface-specific repressor of CRISPR-Cas activity. Pseudomonas phages and plasmids have taken advantage of this regulatory scheme, and carry hijacked homologs of AmrZ, which are functional CRISPR-Cas repressors. This suggests that while CRISPR-Cas regulation may be important to limit self-toxicity, endogenous repressive pathways represent a vulnerability for parasite manipulation.
5 tweets genomics
The human liver is an essential multifunctional organ, and liver diseases are rising with limited treatment options. However, the cellular complexity and heterogeneity of the liver remain poorly understood. Here, we performed single-cell RNA-sequencing of ~5,000 cells from normal liver tissue of 6 human donors to construct the first human liver cell atlas. Our analysis revealed previously unknown sub-types among endothelial cells, Kupffer cells, and hepatocytes with transcriptome-wide zonation of these populations. We show that the EPCAM+ population is highly heterogeneous and consists of hepatocyte progenitors, cholangiocytes and a MUC6+ stem cell population with a specific potential to form liver organoids. As proof-of-principle, we applied our atlas to unravel phenotypic changes in cells from hepatocellular carcinoma tissue and to investigate cellular phenotypes of human hepatocytes and liver endothelial cells engrafted into a humanized FAH-/- mouse liver. Our human liver cell atlas provides a powerful and innovative resource enabling the discovery of previously unknown cell types in the normal and diseased liver.
5 tweets neuroscience
Essential features of the world are often hidden and must be inferred by constructing internal models based on indirect evidence. Here, to study the mechanisms of inference we established a foraging task that is naturalistic and easily learned, yet can distinguish inference from simpler strategies such as the direct integration of sensory data. We show that both mice and humans learn a strategy consistent with optimal inference of a hidden state. However, humans acquire this strategy more than an order of magnitude faster than mice. Using optogenetics in mice we show that orbitofrontal and anterior cingulate cortex inactivation impact task performance, but only orbitofrontal inactivation reverts mice from an inference-based to a stimulus-bound decision strategy. These results establish a cross-species paradigm for studying the problem of inference-based decision-making and begin to dissect the network of brain regions crucial for its performance.
5 tweets evolutionary biology
Natural selection drives populations towards higher fitness, but second-order selection for adaptability and mutational robustness can also influence the dynamics of adaptation. In many microbial systems, diminishing returns epistasis contributes to a tendency for more-fit genotypes to be less adaptable, but no analogous patterns for robustness are known. To understand how robustness varies across genotypes, we measure the fitness effects of hundreds of individual insertion mutations in a panel of yeast strains. We find that more-fit strains are less robust: they have distributions of fitness effects (DFEs) with lower mean and higher variance. These shifts in the DFE arise because many mutations have more strongly deleterious effects in faster-growing strains. This negative correlation between fitness and robustness implies that second-order selection for robustness will tend to conflict with first-order selection for fitness.
5 tweets microbiology
Mapping the complex biogeography of microbial communities in situ with high taxonomic and spatial resolution poses a major challenge because of the high density and rich diversity of species in environmental microbiomes and the limitations of optical imaging technology. Here, we introduce High Phylogenetic Resolution microbiome mapping by Fluorescence In-Situ Hybridization (HiPR-FISH), a versatile and cost-effective technology that uses binary encoding and spectral imaging and machine learning based decoding to create micron-scale maps of the locations and identities of hundreds of microbial species in complex communities. We demonstrate the ability of 10-bit HiPR-FISH to distinguish 1023 E. coli strains, each fluorescently labeled with a unique binary barcode. HiPR-FISH, in conjunction with custom algorithms for automated probe design and segmentation of single-cells in the native context of tissues, reveals the intricate spatial architectures formed by bacteria in the human oral plaque microbiome and disruption of spatial networks in the mouse gut microbiome in response to antibiotic treatment. HiPR-FISH provides a framework for analyzing the spatial organization of microbial communities in tissues and the environment at single cell resolution.
5 tweets neuroscience
Astrocytes contact thousands of synapses throughout the territory covered by its fine bushy processes. Astrocytes respond to neuronal activity with an increase in calcium concentration that is in turn linked to their capacity to modulate neuronal activity. It remains unclear whether astrocytes behave as a single functional unit that integrates all of these inputs, or if multiple functional subdomains reside within an individual astrocyte. We utilized the topographic organization of ferret visual cortex to test whether local neuronal activity can elicit spatially restricted events within an individual astrocyte. We monitored calcium activity throughout the extent of astrocytes in ferret visual cortex while presenting visual stimuli that elicit coordinated neuronal activity spatially restricted to functional columns. We found visually-driven calcium responses throughout the entire astrocyte that was largely independent in individual subdomains, often responding to different visual stimulus orientations. A model of the spatial interaction of astrocytes and neuronal orientation maps recapitulated these measurements, consistent with the hypothesis that astrocyte subdomains integrate local neuronal activity. Together, these results suggest that astrocyte responses to neural circuit activity are dominated by functional subdomains that respond locally and independently to neuronal activity.
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