Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 53,026 bioRxiv papers from 245,564 authors.
Most tweeted bioRxiv papers, last 24 hours
293 results found. For more information, click each entry to expand.
145 tweets neuroscience
Identifying brain biomarkers of disease risk and treatment response is a growing priority in neuroscience. The ability to identify meaningful biomarkers is fundamentally limited by measurement reliability; measures that do not yield reliable values are unsuitable as biomarkers to predict 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 with 1,088 participants reporting 1,146 ICCs for task-fMRI revealed poor overall reliability (mean ICC = .397). Second, the test-retest reliabilities of activity in a priori regions of interest across 11 commonly used fMRI tasks collected in the Human Connectome Project and the Dunedin Longitudinal Study were poor (ICCs = .067 - .485). Collectively, these findings demonstrate that commonly used task-fMRI measures are not currently suitable for brain biomarker discovery or individual differences research in cognitive neuroscience (i.e., brain-behavior mapping). We review how this state of affairs came to be and consider several avenues for improving the reliability of task-fMRI.
85 tweets bioinformatics
Hybrid genome assembly has emerged as an important technique in bacterial genomics, but cost and labor requirements limit large-scale application. We present Ultraplexing, a method to improve per-sample sequencing cost and hands-on-time of Nanopore sequencing for hybrid assembly by at least 50%, compared to molecular barcoding while maintaining high assembly quality (Quality Value; QV >= 42). Ultraplexing requires the availability of Illumina data and uses inter-sample genetic variability to assign reads to isolates, which obviates the need for molecular barcoding. Thus, Ultraplexing can enable significant sequencing and labor cost reductions in large-scale bacterial genome projects.
84 tweets neuroscience
Single neurons in visual cortex provide unreliable measurements of visual features due to their high trial-to-trial variability. It is not known if this "noise" extends its effects over large neural populations to impair the global encoding of sensory stimuli. We recorded simultaneously from ~20,000 neurons in mouse visual cortex and found that the neural population had discrimination thresholds of 0.3 degrees in an orientation decoding task. These thresholds are ~100 times smaller than those reported behaviorally in mice. The discrepancy between neural and behavioral discrimination could not be explained by the types of stimuli we used, by behavioral states or by the sequential nature of trial-by-trial perceptual learning tasks. These results imply that the limits of sensory perception in mice are not set by neural noise in sensory cortex, but by the limitations of downstream decoders.
58 tweets neuroscience
A neuronal population encodes information most efficiently when its activity is uncorrelated and high-dimensional, and most robustly when its activity is correlated and lower-dimensional. Here, we analyzed the correlation structure of natural image coding, in large visual cortical populations recorded from awake mice. Evoked population activity was high dimensional, with correlations obeying an unexpected power-law: the n-th principal component variance scaled as 1/n. This was not inherited from the 1/f spectrum of natural images, because it persisted after stimulus whitening. We proved mathematically that the variance spectrum must decay at least this fast if a population code is smooth, i.e. if small changes in input cannot dominate population activity. The theory also predicts larger power-law exponents for lower-dimensional stimulus ensembles, which we validated experimentally. These results suggest that coding smoothness represents a fundamental constraint governing correlations in neural population codes.
28 tweets genomics
Dimensionality reduction is often used to visualize complex expression profiling data. Here, we use the Uniform Manifold Approximation and Projection (UMAP) method on published transcript profiles of 1484 single gene deletions of Saccharomyces cerevisiae. Proximity in low-dimensional UMAP space identifies clusters of genes that correspond to protein complexes and pathways, and finds novel protein interactions even within well-characterized complexes. This approach is more sensitive than previous methods and should be broadly useful as additional transcriptome datasets become available for other organisms.
25 tweets scientific communication and education
A potential motivation for scientists to deposit their scientific work as preprints is to enhance its citation or social impact, an effect which has been empirically observed for preprints in physics, astronomy and mathematics deposited to arXiv. In this study we assessed the citation and altmetric advantage of bioRxiv, a preprint server for the biological sciences. We retrieved metadata of all bioRxiv preprints deposited between November 2013 and December 2017, and matched them to articles that were subsequently published in peer-reviewed journals. Citation data from Scopus and altmetric data from Altmetric.com were used to compare citation and online sharing behaviour of bioRxiv preprints, their related journal articles, and non-deposited articles published in the same journals. We found that bioRxiv-deposited journal articles received a sizeable citation and altmetric advantage over non-deposited articles. Regression analysis reveals that this advantage is not explained by multiple explanatory variables related to the article and its authorship. bioRxiv preprints themselves are being directly cited in journal articles, regardless of whether the preprint has been subsequently published in a journal. bioRxiv preprints are also shared widely on Twitter and in blogs, but remain relatively scarce in mainstream media and Wikipedia articles, in comparison to peer-reviewed journal articles.
25 tweets plant biology
Detailed functional analyses of many fundamentally-important plant genes via conventional loss-of-function approaches are impeded by severe pleiotropic phenotypes. In particular, mutations in genes that are required for basic cellular functions and/or reproduction often interfere with the generation of homozygous mutant plants, precluding further functional studies. To overcome this limitation, we devised a CRISPR-based tissue-specific knockout system, CRISPR-TSKO, enabling the generation of somatic mutations in particular plant cell types, tissues, and organs. In Arabidopsis, CRISPR-TSKO mutations in essential genes caused well-defined, localized phenotypes in the root cap, stomatal lineage, or entire lateral roots. The underlying modular cloning system allows for efficient selection, identification, and functional analysis of mutant lines directly in the first transgenic generation. The efficacy of CRISPR-TSKO opens new avenues to discover and analyze gene functions in spatial and temporal contexts of plant life while avoiding pleiotropic effects of system-wide loss of gene function.
23 tweets synthetic biology
Metabolic heterogeneity between individual cells of a population harbors offers significant challenges for fundamental and applied research. Identifying metabolic heterogeneity and investigating its emergence requires tools to zoom into metabolism of individual cells. While methods exist to measure metabolite levels in single cells, we lack capability to measure metabolic flux, i.e. the ultimate functional output of metabolic activity, on the single-cell level. Here, combining promoter engineering, computational protein design, biochemical methods, proteomics and metabolomics, we developed a biosensor to measure glycolytic flux in single yeast cells, by drawing on the robust cell-intrinsic correlation between glycolytic flux and levels of fructose-1,6-bisphosphate (FBP), and by transplanting the B. subtilis FBP-binding transcription factor CggR into yeast. As proof of principle, using fluorescence microscopy, we applied the sensor to identify metabolic subpopulations in yeast cultures. We anticipate that our biosensor will become a valuable tool to identify and study metabolic heterogeneity in cell populations.
20 tweets microbiology
Stefano Campanaro, Laura Treu, Luis M Rodríguez Rojas, Adam Kovalovszki, Ryan Ziels, Irena Maus, Xinyu Zhu, Panagiotis G Kougias, Arianna Basile, Gang Luo, Andreas Schlüter, Konstantinos T. Konstantinidis, Irini Angelidaki
Background: Microorganisms in biogas reactors are essential for degradation of organic matter and methane production.. However, a comprehensive genome-centric comparison, including relevant metadata for each sample, is still needed to identify the globally distributed biogas community members and serve as a reliable repository. Results: Here, 134 publicly available metagenomes derived from different biogas reactors were used to recover 1,635 metagenome-assembled genomes (MAGs) representing different biogas bacterial and archaeal species. All genomes were estimated to be >50% complete and nearly half ≥90% complete with ≤5% contamination. In most samples, specialized microbial communities were established, while only a few taxa were widespread among the different reactor systems. Metabolic reconstruction of the MAGs enabled the prediction of functional traits related to biomass degradation and methane production from waste biomass. An extensive evaluation of the replication index provided an estimation of the growth rate for microbes involved in different steps of the food chain. The recovery of many MAGs belonging to Candidate Phyla Radiation and other underexplored taxa suggests their specific involvement in the anaerobic degradation of organic matter. Conclusions: The outcome of this study highlights a high flexibility of the biogas microbiome, allowing it to modify its composition and to adapt to the environmental conditions, including temperatures and a wide range of substrates. Our findings enhance our mechanistic understanding of the AD microbiome and substantially extend the existing repository of genomes. The established database represents a relevant resource for future studies related to this engineered ecosystem.
19 tweets scientific communication and education
As the life sciences have become more data intensive, the pressure to incorporate the requisite training into life-science education and training programs has increased. To facilitate curriculum development, various sets of (bio)informatics competencies have been articulated; however, these have proved difficult to implement in practice. Addressing this issue, we have created a curriculum-design and -evaluation tool to support the development of specific Knowledge, Skills and Abilities (KSAs) that reflect the scientific method and promote both bioinformatics practice and the achievement of competencies. Twelve KSAs were extracted via formal analysis, and stages along a developmental trajectory, from uninitiated student to independent practitioner, were identified. Demonstration of each KSA by a performer at each stage was initially described (Performance Level Descriptors, PLDs), evaluated, and revised at an international workshop. This work was subsequently extended and further refined to yield the Mastery Rubric for Bioinformatics (MR-Bi). The MR-Bi was validated by demonstrating alignment between the KSAs and competencies, and its consistency with principles of adult learning. The MR-Bi tool provides a formal framework to support curriculum building, training, and self-directed learning. It prioritizes the development of independence and scientific reasoning, and is structured to allow individuals (regardless of career stage, disciplinary background, or skill level) to locate themselves within the framework. The KSAs and their PLDs promote scientific problem formulation and problem solving, lending the MR-Bi durability and flexibility. With its explicit developmental trajectory, the tool can be used by developing or practicing scientists to direct their (and their team's) acquisition of new, or to deepen existing, bioinformatics KSAs. The MR-Bi can thereby contribute to the cultivation of a next generation of bioinformaticians who are able to design reproducible and rigorous research, and to critically analyze results from their own, and others', work.
16 tweets bioinformatics
Next generation sequencing produces large volumes of short sequences with broad applications. The noise due to sequencing errors led to the development of several correction methods. The main correction paradigm expects a high (from 30-40X) uniform coverage to correctly infer a reference set of subsequences from the reads, that are used for correction. In practice, most accurate methods use k-mer spectrum techniques to obtain a set of reference k-mers. However, when correcting NGS datasets that present an uneven coverage, such as RNA-seq data, this paradigm tends to mistake rare variants for errors. It may therefore discard or alter them using highly covered sequences, which leads to an information loss and may introduce bias. In this paper we present two new contributions in order to cope with this situation. First, we show that starting from non-uniform sequencing coverages, a De Bruijn graph can be cleaned from most errors while preserving biological variability. Second, we demonstrate that reads can be efficiently corrected via local alignment on the cleaned De Bruijn graph paths. We implemented the described method in a tool dubbed BCT and evaluated its results on RNA-seq and metagenomic data. We show that the graph cleaning strategy combined with the mapping strategy leads to save more rare k-mers, resulting in a more conservative correction than previous methods. BCT is also capable to better take advantage of the signal of high depth datasets. We suggest that BCT, being scalable to large metagenomic datasets as well as correcting shallow single cell RNA-seq data, can be a general corrector for non-uniform data. Availability: BCT is open source and available at github.com/Malfoy/BCT under the Affero GPL License.
16 tweets developmental biology
More than 95% of fertilized Drosophila oocytes from outbred stocks develop fully regardless of maternal age, in contrast to human oocytes, which frequently generate non-viable aneuploid embryos. Since Drosophila oocytes are normally stored only briefly prior to ovulation, unlike their human counterparts, we investigated the effects of storage on oocyte quality. Using a novel system to acquire oocytes held for known periods, we analyzed by ribosome profiling how translation and cellular function change over time. Oocyte developmental capacity decays in a precise temperature-dependent manner over 1-4 weeks, due to a progressive inability to complete meiosis. Meiotic metaphase genes, the Fmr1 translational regulator, and the small heat shock protein chaperones Hsp26 and Hsp27 are preferentially translated during storage, and oocytes lacking Hsp26 and Hsp27 age prematurely. However translation falls generally 2.3-fold with age despite constant mRNA levels, and this inability to maintain translational equilibrium correlates with oocyte functional decline. These findings show that meiotic chromosome segregation in Drosophila oocytes is uniquely sensitive to prolonged quiescence, and suggest that the extended storage of mature human oocytes contributes to their chromosome instability. If so, then these problems may be more amenable to intervention than previously supposed.
15 tweets cell biology
Cell-cell communication mediated by receptor-ligand complexes is crucial for coordinating diverse biological processes, such as development, differentiation and responses to infection. In order to understand how the context-dependent crosstalk of different cell types enables physiological processes to proceed, we developed CellPhoneDB, a novel repository of ligands, receptors and their interactions. Our repository takes into account the subunit architecture of both ligands and receptors, representing heteromeric complexes accurately. We integrated our resource with a statistical framework that predicts enriched cellular interactions between two cell types from single-cell transcriptomics data. Here, we outline the structure and content of our repository, the procedures for inferring cell-cell communication networks from scRNA-seq data and present a practical step-by-step guide to help implement the protocol. CellPhoneDB v2.0 is a novel version of our resource that incorporates additional functionalities to allow users to introduce new interacting molecules and reduce the time and resources needed to interrogate large datasets. CellPhoneDB v2.0 is publicly available at https://github.com/Teichlab/cellphonedb and as a user-friendly web interface at http://www.cellphonedb.org/. In our protocol, we demonstrate how to reveal meaningful biological discoveries from CellPhoneDB v2.0 using published data sets.
14 tweets genetics
The aberrant gain of DNA methylation at CpG islands (CGIs) is frequently observed in colorectal tumours and may silence the expression of tumour suppressors such as MLH1. Current models propose that these CGIs are targeted by de novo DNA methyltransferases (DNMTs) in a sequence-specific manner but this has not been tested. Using ectopically integrated CGIs, we find that aberrantly methylated CGIs are subject to low levels of de novo DNMT activity in colorectal cancer cells. By delineating DNMT targets, we find that instead de novo DNMT activity is targeted primarily to CGIs marked by the histone modification H3K36me3, a mark associated with transcriptional elongation. These H3K36me3 marked CGIs are heavily methylated in colorectal tumours and the normal colon suggesting that de novo DNMT activity at CGIs in colorectal cancer is focused on similar targets to normal tissues and not greatly remodelled by tumourigenesis.
14 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.
13 tweets neuroscience
Colin Groot, B.T. Thomas Yeo, Jacob W Vogel, Xiuming Zhang, Nanbo Sun, Elizabeth C Mormino, Yolande AL Pijnenburg, Bruce L Miller, Howard J. Rosen, Renaud La Joie, Frederik Barkhof, Philip Scheltens, Gil D. Rabinovici, Wiesje M van der Flier, Rik Ossenkoppele
Posterior cortical atrophy is a clinical-radiological syndrome characterized by visual processing deficits and atrophy in posterior parts of the brain, most often caused by Alzheimers disease pathology. Recent consensus criteria describe four distinct phenotypical variants of posterior cortical atrophy defined by clinical and radiological features; i) object perception/occipitotemporal (ventral), ii) space perception/temporoparietal (dorsal), iii) non-visual/dominant parietal and iv) primary visual (caudal). We employed a data-driven approach to identify atrophy factors related to these proposed variants in a multi-center cohort of 119 individuals with posterior cortical atrophy (age: 64 SD 7, 38% male, MMSE: 21 SD 5, 71% amyloid-B positive, 29% amyloid-B status unknown). A Bayesian modelling framework based on latent Dirichlet allocation was used to compute four latent atrophy factors in accordance with the four proposed variants. The model uses standardized gray matter density images as input (adjusted for age, sex, intracranial volume, field strength and whole-brain gray matter volume) and provides voxelwise probabilistic maps for all atrophy factors, allowing every individual to express each factor to a degree without a priori classification. The model revealed four distinct yet partially overlapping atrophy factors; right-dorsal, right-ventral, left-ventral, and limbic. Individual participant profiles revealed that the vast majority of participants expressed multiple factors, rather than predominantly expressing a single factor. To assess the relationship between atrophy factors and cognition, neuropsychological test scores covering four posterior cortical atrophy-specific cognitive domains were assessed (object perception, space perception, non-visual parietal functions and primary visual processing) and we used general linear models to examine the association between atrophy factor expression and cognition. We found that object perception and primary visual processing were associated with atrophy that predominantly reflects the right-ventral factor. Furthermore, space perception was associated with atrophy that predominantly represents the right-ventral and right-dorsal factors. Similar to the atrophy factors, most participants had mixed clinical profiles with impairments across multiple domains. However, when selecting four participants with an isolated impairment, we observed atrophy patterns and factor expressions that were largely in accordance with the hypothesized variants. Taken together, our results indicate that variants of posterior cortical atrophy exist but these constitute phenotypical extremes and most individuals fall along a broad clinical-radiological spectrum, indicating that classification into four mutually exclusive variants is unlikely to be clinically useful.
13 tweets neuroscience
Grid and head direction codes in the medial entorhinal cortex represent cognitive spaces for navigation and memory. In grid cells the expression of the grid code is thought to be independent of head direction, whereas in conjunctive cells the grid code is tuned to a single head direction. This distinction between non-directional grid cells and unidirectional conjunctive cells is also present in models and proposed functions for grid codes. However, while grid cells are not tuned to a single direction, whether their firing is independent of direction is less clear. Here we demonstrate location-dependent modulation of grid cell firing by head direction. Individual firing fields recorded from mouse and rat grid cells have multiple and different preferred directions. This local directionality of grid firing is accounted for by models in which grid cells integrate inputs from conjunctive cells with co-aligned, spatially non-uniform firing fields. Thus, the firing of grid cells is consistent with their integration of upstream grid codes. For downstream neurons in the dentate gyrus that receive input from grid cells, integration of rich directional information within the grid code may contribute to pattern separation computations by decorrelating different points of view from the same spatial location.
12 tweets plant biology
In certain plant hybrids, autoimmunity is triggered by immune components that interact in the absence of a pathogen trigger. Often, NLR immune receptors are involved, with a particularly interesting case in Arabidopsis thaliana involving variants of the NLR RPP7 as well as variants of RPW8/HR proteins, which are homologs of animal MLKL and fungal HELL domain proteins. We demonstrate that HR4Fei-0 but not the closely related HR4Col-0 protein directly disrupts intramolecular association of RPP7bLerik1-3, which in turn initiates P-loop dependent NLR signaling. In agreement, RPP7bLerik1-3 forms a higher-order complex only in the presence of HR4Fei-0 but not HR4Col-0. In addition, we find that HR4Fei-0 on its own can form detergent-resistant oligomers suggestive of amyloid-like aggregates, which in turn can directly kill cells in an RPP7bLerik1-3-independent manner. Our work provides in vivo biochemical evidence for a plant resistosome complex and the mechanisms by which RPW8/HR proteins trigger cell death.
12 tweets cancer biology
Sharon Christensen, Bastiaan vd Roest, Nicolle Besselink, Roel Janssen, Sander Boymans, John Martens, Marie-Laure Yaspo, Peter Priestley, Center for Personalized Cancer Treatment, Ewart Kuijk, Edwin Cuppen, Arne van Hoeck
5-Fluorouracil (5-FU) is a chemotherapeutic drug component that is commonly used for the treatment of solid cancers. It is proposed that 5-FU possesses anticancer properties via the interference with nucleotide synthesis and incorporation into DNA. As both mechanisms may have a mutational impact on both surviving tumor and healthy cells, we treated intestinal organoids with 5-FU followed by whole genome sequencing analysis and uncovered a highly characteristic mutational pattern that is dominated by T>G substitutions in a CTT context. Analysis of tumor whole genome sequencing data confirmed that this signature can also be identified in vivo in colorectal and breast cancer patients that have undergone treatment with 5-FU. We also found that more 5-FU mutations are induced in TP53 null backgrounds which may be of clinical relevance. Taken together, our results demonstrate that 5-FU is mutagenic and may drive tumor evolution and increase the risk of secondary malignancies. Furthermore, the identified signature shows a strong resemblance to COSMIC signature 17, the hallmark signature of treatment-naive esophageal and gastric tumors, which indicates that distinct endogenous and exogenous triggers can converge onto highly similar mutational signatures.
12 tweets neuroscience
A large variety of methods exist to estimate brain coupling in the frequency domain from electrophysiological data measured e.g. by EEG and MEG. Those data are to reasonable approximation, though certainly not perfectly, Gaussian distributed. This work is based on the well-known fact that for Gaussian distributed data, the cross-spectrum completely determines all statistical properties. In particular, for an infinite number of data, all normalized coupling measures at a given frequency are a function of complex coherency. However, it is largely unknown what the functional relations are. We here present those functional relations for six different measures: the weighted phase lag index, the phase lag index, the absolute value and imaginary part of the phase locking value (PLV), power envelope correlation, and power envelope correlation with correction for artifacts of volume conduction. With the exception of PLV, the final results are simple closed form formulas. We tested for empirical resting state EEG on sensor level to what extent a model, namely the respective function of coherency, can explain the observed couplings. We found that for measures of phase-phase coupling deviations from the model are in general minor, while power envelope correlations systematically deviate from the model for all frequencies. For power envelope correlation with correction for artifacts of volume conduction the model cannot explain the observed couplings at all. We also analyzed power envelope correlation as a function of time and frequency in an event related experiment using a stroop reaction task and found significant event related deviations mostly in the alpha range.
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