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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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Gene detection models outperform gene expression for large-scale scRNA-seq analysis

Technical variation in feature measurements such as gene expression and locus accessibility is a key challenge of large-scale single cell genomic datasets. We show that this technical variation in both scRNA-seq and scATAC-seq datasets can be mitigated by performing analysis on feature detection patterns alone and ignoring feature quantification measurements. This result holds when datasets have low detection noise relative to quantification noise. We demonstrate state-of-the-art performance of detection pattern models using our new framework, scBFA, for both cell type identification and trajectory inference. Performance gains can also be realized in one line of R code in existing pipelines.

bioinformatics

The convergent evolution of caste in ants and honey bees is based on a shared core of ancient reproductive genes and many plastic genes

Eusociality has convergently evolved multiple times, but the genomic basis of caste-based division of labor and degree to which independent origins of eusociality have utilized common genes remain largely unknown. Here we characterize caste-specific transcriptomic profiles across development and adult body segments from pharaoh ants (Monomorium pharaonis) and honey bees (Apis mellifera), representing two independent origins of eusociality. We identify a substantial shared core of genes upregulated in the abdomens of queen ants and honey bees that also tends to be upregulated in mated female flies, suggesting that these genes are part of a conserved insect reproductive groundplan. Outside of this shared groundplan, few genes are differentially expressed in common. Instead, the majority of the thousands of caste-associated genes are plastically-expressed, rapidly evolving, and relatively evolutionarily young. These results emphasize that the recruitment of both highly conserved and lineage-specific genes underlie the convergent evolution of novel traits such as eusociality.

evolutionary biology

Unc 51-like autophagy-activating kinase (ULK1) mediates clearance of free {alpha}-globin in {beta}-thalassemia

Erythroid maturation is coordinated to maximize the production of hemoglobin A heterotetramers (2{beta}2) and minimize the accumulation of potentially toxic free - or {beta}-globin subunits. In {beta}-thalassemia, mutations in the {beta}-globin gene cause a build-up of free -globin, which forms intracellular precipitates that impair erythroid cell maturation and viability. Protein quality-control systems mitigate {beta}-thalassemia pathophysiology by degrading toxic free -globin. We show that loss of the Unc 51-like autophagy-activating kinase gene Ulk1 in {beta}-thalassemic mice reduces autophagic clearance of -globin in red cell precursors and exacerbates disease phenotypes, whereas inactivation of the canonical autophagy gene Atg5 has minimal effects. Systemic treatment with rapamycin to inhibit the ULK1 inhibitor mTORC1 reduces -globin precipitates and lessens pathologies in {beta}-thalassemic mice, but not in those lacking Ulk1. Similarly, rapamycin reduces free -globin accumulation in erythroblasts derived from {beta}-thalassemic patient CD34+ hematopoietic progenitors. Our findings identify a new, drug-regulatable pathway for ameliorating {beta}-thalassemia.\n\nOne Sentence SummaryRapamycin alleviates {beta}-thalassemia by stimulating ULK1-dependent autophagy of toxic free -globin.

cell biology

Identifying Emerging Phenomenon in Plant Long Temporal Phenotyping Experiments

The rapid improvement of phenotyping capability, accuracy, and throughput have greatly increased the volume and diversity of phenomics data. A remaining challenge is an efficient way to identify phenotypic patterns to improve our understanding of the quantitative variation of complex phenotypes, and to attribute gene functions. To address this challenge, we developed a new algorithm to identify emerging phenomena from large-scale temporal plant phenotyping experiments. An emerging phenomenon is defined as a group of genotypes who exhibit a coherent phenotype pattern during a relatively short time. Emerging phenomena are highly transient and diverse, and are dependent in complex ways on both environmental conditions and development. Identifying emerging phenomena may help biologists to examine potential relationships among phenotypes and genotypes in a genetically diverse population and to associate such relationships with the change of environments or development. We present an emerging phenomenon identification tool called Temporal Emerging Phenomenon Finder (TEP-Finder). Using large-scale longitudinal phenomics data as input, TEP-Finder first encodes the complicated phenotypic patterns into a dynamic phenotype network. Then, emerging phenomena in different temporal scales are identified from dynamic phenotype network using a maximal clique based approach. Meanwhile, a directed acyclic network of emerging phenomena is composed to model the relationships among the emerging phenomena. The experiment that compares TEP-Finder with two state-of-art algorithms shows that the emerging phenomena identified by TEP-Finder are more functionally specific, robust, and biologically significant. The source code, manual, and sample data of TEP-Finder are all available at: http://phenomics.uky.edu/TEP-Finder/.

bioinformatics

Active membrane conductances and morphology of a collision detection neuron broaden its impedance profile and improve membrane synchrony

Our brain processes information through the coordinated efforts of billions of individual neurons, each of which transforms a small part of the overall information stream. Central to this is how neurons integrate and transform complex patterns of synaptic inputs. The neuronal membrane impedance determines the change in membrane potential in response to input currents, and therefore sets the gain and timing for synaptic integration. Using single and dual dendritic recordings in vivo, pharmacology, and computational modeling, we characterized the role of two active conductances gH and gM, meditated respectively by hyperpolarization-activated cyclic nucleotide gated (HCN) channels and by muscarine sensitive M-channels, in shaping the membrane impedance of a collision detection neuron in female Schistocerca americana grasshoppers. The neuron is known by its acronym LGMD, which stands for lobula giant movement detector. In contrast to other neurons where these conductances have been studied, we found that gH and gM promote broadband, synchronous integration over the LGMDs functional range of membrane potentials and input frequencies. Additionally, we found that the branching morphology of the LGMD helped increase both the gain and synchrony associated with the neurons membrane impedance. The same result held for a wide range of dendritic morphologies, including those of mammalian neocortical pyramidal neurons and cerebellar Purkinje cells. Thus, these findings further our understanding of the integration properties of individual neurons by showing the unexpected role played by two widespread active conductances and by dendritic morphology in shaping synaptic integration.\n\nSignificance StatementInformation in the brain is processed by neurons that receive thousands of synaptic inputs. Understanding how neurons integrate these inputs is critical to neuroscience. Neuronal integration depends on complex interactions of synaptic input patterns and the electrochemical properties of dendrites. Although examining the input patterns and dendritic processing in vivo is not yet possible in the mammalian brain, it is within simpler nervous systems. Here, we used an identified collision detection neuron in grasshoppers to examine how its morphology and membrane properties determine the gain and synchrony of synaptic integration in relation to the computations it performs. The neuronal properties examined are ubiquitous and therefore will further a general understanding of neuronal computations, including those in our own brain.

neuroscience

Characterization of α 3 Glycine Receptors with Ginkgolide B and Picrotoxin

Ginkgolide B (GB) and picrotoxin (PTX) are antagonists of the major inhibitory receptors of the central nervous system: GABA and glycine receptors (GlyRs). GlyRs contain one or more of the four alpha subunit isoforms of which 1 and 2 have been extensively studied. This report compares GB and PTX block of 3 GlyRs expressed in HEK 293 cells, using whole-cell patch clamp techniques. In CNS, 3 exists as a heteropentamer in conjunction with beta subunits in a 2:3{beta} ratio. Thus, the nature of block was also tested in 3{beta} heteromeric glycine receptors. GB and PTX blocked 3 GlyRs both in the presence (liganded state) and absence of glycine (unliganded state). This property is unique to 3 subunits; 1 and 2 subunits are only blocked in the liganded state. The GB block of 3 GlyRs is voltage-dependent (more effective when the cell is depolarized) and non-competitive, while the PTX block is competitive and not voltage-dependent. The heteromeric and homomeric 3 GlyRs recovered significantly faster from unliganded GB block compared to liganded GB block, but no such distinction was found for PTX block suggesting more than one binding site for GB. This study sheds light on features of the 3 GlyR that distinguish it from the more widely studied 1 and 2 subunits. Understanding these properties can help decipher the physiological functioning of GlyRs in the CNS and may permit development of subunit specific drugs.

neuroscience

Protein aggregation capture on microparticles enables multi-purpose proteomics sample preparation

Universal proteomics sample preparation is challenging due to the high heterogeneity of biological samples. Here we describe a novel mechanism that exploits the inherent instability of denatured proteins for non-specific immobilization on microparticles by protein aggregation capture. To demonstrate the general applicability of this mechanism, we analyzed phosphoproteomes, tissue proteomes, and interaction proteomes as well as dilute secretomes. The findings presents a practical, sensitive and cost-effective proteomics sample preparation method.

biochemistry

Elevated expression of LGR5 and WNT signalling factors in neuroblastoma cells with acquired drug resistance

Neuroblastoma (NB) is the most common paediatric solid cancer with high fatality, relapses and acquired resistance to drug therapy. The clinical challenge NB poses requires new therapeutic approaches to improve survival rates.\n\nThe WNT signalling pathway is crucial in embryonic development but has also been reported to be dysregulated in glioblastoma, ovarian, breast and colorectal cancer. LGR5 is a receptor which potentiates the WNT/{beta}-catenin signalling pathway, hence contributing to cancer stem cell proliferation and self-renewal. LGR5 has been reported to promote both development and survival of colorectal cancer and glioblastomas.\n\nOur previous study illustrated that LGR5 is associated with aggressiveness in NB cell lines established at different stages of treatment. Following these findings, we investigated whether LGR5 is involved in acquired drug resistance via the WNT pathway in NB cell lines.\n\nCell lines in this study have an acquired drug resistance to vincristine (VCR) or doxorubicin (DOX).\n\nIn this study, we showed LGR5-LRP6 cooperation with enhanced expression of both proteins in SHSY5YrVCR, IMR32rDOX, IMR5rVCR and IMR5rDOX NB cell lines compared to paired parental cells. We also found elevated expression of {beta}-catenin in cell lines with acquired drug resistance is indicative of {beta}-catenin-dependent WNT signalling.\n\nThis study warrants further investigation into the role of the WNT signalling pathway in acquired drug resistance.

cancer biology

A Cyclin A - Myb-MuvB - Aurora B network regulates the choice between mitotic cycles and polyploid endoreplication cycles.

Cells switch to polyploid endoreplication cycles during development, wound healing, and cancer. We used integrated approaches in Drosophila to determine how mitotic cycles are remodeled into endoreplication cycles, and how similar this remodeling is between developmental and induced endoreplicating cells (devECs and iECs). We found that while only devECs had a dampened E2F1 transcriptome, repression of a Cyclin A - Myb-MuvB - Aurora B mitotic network promoted endoreplication in both devECs and iECs. Cyclin A associated with and activated Myb-MuvB to induce transcription of mitotic genes, with expression of one, Aurora B, being key for mitotic commitment. Knockdown of Cyclin A, Myb, Aurora B, or downstream cytokinetic proteins induced distinct types of endoreplication, suggesting that repression of different mitotic network steps may explain the known diversity of polyploid cycles. These findings reveal how remodeling of a mitotic network promotes polyploid cycles that contribute to development, wound healing, and cancer.

developmental biology

Long Range Order and Short Range Disorder in Saccharomyces cerevisiae Biofilm

AbstractBiofilm, a colony forming cooperative response of microorganisms under environmental stress, is a major concern for food safety, water safety and drug resistance. Most current works focus on controlling biofilm growth by targeting single genes. Here, we investigated transcriptome-wide expressions of the biofilm yeast Saccharomyces cerevisiae in wildtype, and 6 previously identified biofilm regulating overexpression strains (DIG1, SAN1, TOS8, ROF1, SFL1, HEK2). When tested across various statistical distributions, all transcriptome-wide data fitted well with lognormal distribution above TPM value of 5. Using this threshold as a low expression filter, Pearson auto-and cross-correlation reveal a strong transcriptome-wide invariance among all genotypes, which is also reflected by the random selection of 50 gene expressions. Focusing on the 50 highly expressed genes, however, they differ significantly between the genotypes. Principal components analysis (PCA) shows global similarity between DIG1, SAN1, ROF1, SFL1 and HEK2. Thus, although single overexpression strains may show significant favourable local and acute expression changes (short range disorder), the almost unperturbed global and collective structure between the genotypes indicate gradual adaptive response converging to original stable biofilm states (long range order). Hierarchical clustering and Gene Ontology show 11 groups of local (e.g. mitochondria processes, amine & nucleotide metabolic processes) and 6 groups of global (e.g. transcription, translation & cell cycle) processes for all genotypes. These data indicate that there is a strong global regulatory structure that keeps the overall biofilm stable in all investigated strains.

systems biology

Evaluation of FlowVR: a virtual reality game for improvement of depressive mood

ObjectiveThis study evaluated the efficacy of FlowVR, a virtual reality (VR) game designed to improve mood and reduce feelings of depression. The aim is to contribute to the question of whether and how VR could be used for depression therapy, as research in this area is quite rare.\n\nMethod18 healthy participants (9 female; Mage = 25.9) underwent three conditions, playing FlowVR in VR with a head-mounted display, playing FlowVR on a tablet or reading a text on a tablet. For each condition, they were tested on a separate day at the same time of day within a two-week period. Before and after every condition participants completed the Becks Depression Inventory II (BDI-II), the state part of the State-Trait-Anxiety-Depression-Inventory (STADI(S)) and the Positive Affect Negative Affect Schedule-Expanded Form (PANAS-X).\n\nResultsWhile the participants showed only a reduction in acute anxiety in the control and the tablet conditions, they showed improved affectivity in all variables measured in the VR condition. In addition, VR had significantly better results than the control condition in improving positive affectivity, negative affectivity and acute feelings of depression. Using a less conservative statistical approach, these significant differences could also be found between the tablet and the VR condition. There were no significant differences between the tablet and the control condition.\n\nConclusionThe results indicate that due to its immersive nature, VR can be used effectively to improve mood and temporarily reduce feelings of depression. Long-term effects of FlowVR on participants with depression must be investigated in consecutive research.

neuroscience

The CRUNCH model does not account for load-dependent changes in visuospatial working memory in older adults: Evidence for the file-drawer problem in neuroimaging

Numerous neuroimaging studies have shown that older adults tend to activate the brain to a greater extent than younger adults during the performance of a task. This is typically interpreted as evidence for cognitive compensation. The Compensation-Related Utilisation of Neural Circuits Hypothesis (CRUNCH) model is a highly influential model of compensation, and states that increased functional magnetic resonance imaging (fMRI) activity in older adults compared to younger adults should reverse at higher levels of task difficulty. We tested the CRUNCH model using a visuospatial working memory paradigm, and found that fMRI activity in older vs. younger adults was in the opposite direction to that predicted by the model. Given that the CRUNCH model is the predominant model of compensation, this result was surprising. We followed up our results with a systematic review of the CRUNCH in healthy ageing literature using p-curve analysis. We find evidence for selective reporting, or the file-drawer problem, in the cognitive compensation literature. Further experimental work is required to validate the CRUNCH model in cognitive ageing.\n\nAbbreviationsCRUNCH: compensation-related utilisation of neural circuits hypothesis; fMRI: functional magnetic resonance imaging\n\nHighlights- CRUNCH is the leading model of cognitive compensation in ageing\n- We find fMRI activity in old vs. young adults in opposite direction predicted by CRUNCH\n- We report quantitative evidence of selective reporting in CRUNCH literature

neuroscience

Reliability and Generalizability of Similarity-Based Fusion of MEG and fMRI Data in Human Ventral and Dorsal Visual Streams

To build a representation of what we see, the human brain recruits regions throughout the visual cortex in cascading sequence. Recently, an approach was proposed to evaluate the dynamics of visual perception in high spatiotemporal resolution at the scale of the whole brain. This method combined functional magnetic resonance imaging (fMRI) data with magnetoencephalography (MEG) data using representational similarity analysis and revealed a hierarchical progression from primary visual cortex through the dorsal and ventral streams. To assess the replicability of this method, here we present results of a visual recognition neuro-imaging fusion experiment, and compare them within and across experimental settings. We evaluated the reliability of this method by assessing the consistency of the results under similar test conditions, showing high agreement within participants. We then generalized these results to a separate group of individuals and visual input by comparing them to the fMRI-MEG fusion data of Cichy et al (2016), revealing a highly similar temporal progression recruiting both the dorsal and ventral streams. Together these results are a testament to the reproducibility of the fMRI-MEG fusion approach and allows for the interpretation of these spatiotemporal dynamic in a broader context.

neuroscience

Transient Replication in Specialized Cells Favors Conjugative Transfer of a Selfish DNA Element

Bacterial evolution is driven to a large extent by horizontal gene transfer (HGT) - the processes that distribute genetic material between species rather than by vertical descent. HGT is mostly mediated by an assortment of different selfish DNA elements, several of which have been characterized in great molecular detail. In contrast, very little is known on adaptive features optimizing horizontal fitness. By using single DNA molecule detection and time-lapse microscopy, we analyze here the fate of an integrative and conjugative element (ICE) in individual cells of the bacterium Pseudomonas putida. We uncover how the ICE excises and irregularly replicates, exclusively in a sub-set of specialized host cells. As postulated, ICE replication is dependent on its origin of transfer and its DNA relaxase. Rather than being required for ICE maintenance, however, we find that ICE replication serves more effective conjugation to recipient cells, providing selectable benefit to its horizontal transfer.

microbiology

PAR protein activation-deactivation cycles stabilize long-axis polarization in C. elegans

In the Caenorhabditis elegans zygote, PAR protein patterns, driven by mutual anatagonism, determine the anterior-posterior axis and facilitate the redistribution of proteins for the first cell division. Yet, the factors that determine the selection of the polarity axis remain unclear. We present a reaction-diffusion model in realistic cell geometry, based on biomolecular reactions and accounting for the coupling between membrane and cytosolic dynamics. We find that the kinetics of the phosphorylation-dephosphorylation cycle of PARs and the diffusive protein fluxes from the cytosol towards the membrane are crucial for the robust selection of the anterior-posterior axis for polarisation. The local ratio of membrane surface to cytosolic volume is the main geometric cue that initiates pattern formation, while the choice of the long-axis for polarisation is largely determined by the length of the aPAR-pPAR interface, and mediated by processes that minimise the diffusive fluxes of PAR proteins between cytosol and membrane.

biophysics

Inference of splicing motifs through visualization of recurrent networks

Neural models have been able to obtain state-of-the-art performances on several genome sequence-based prediction tasks. Such models take only nucleotide sequences as input and learn relevant features on its own. However, extracting the interpretable motifs from the model remains a challenge. This work explores various existing visualization techniques in their ability to infer relevant sequence information learned by a recurrent neural network (RNN) on the task of splice junction identification. The visualization techniques have been modulated to suit the genome sequences as input. The visualizations inspect genomic regions at the level of a single nucleotide as well as a span of consecutive nucleotides. This inspection is performed based on modification of input sequences (perturbation-based) or the embedding space (back-propagation based). We infer features pertaining to both canonical and non-canonical splicing from a single neural model. Results indicate that the visualization techniques produce comparable performance for branchpoint detection. However, in case of canonical donor and acceptor junction motifs, perturbation based visualizations perform better than back-propagation based visualizations and vice-versa for non-canonical motifs.

bioinformatics

SPR-measured kinetics of PROTAC ternary complexes influence target degradation rate

Bifunctional degrader molecules, known as proteolysis-targeting chimeras (PROTACs), function by recruiting a target to an E3 ligase, forming a target:PROTAC:ligase ternary complex. Despite the importance of this key intermediate species, no detailed validation of a method to directly determine binding parameters for ternary complex kinetics has been reported, and it remains to be addressed whether tuning the kinetics of PROTAC ternary complexes may be an effective strategy to improve the efficiency of targeted protein degradation. Here, we develop an SPR-based assay to quantify the stability of PROTAC-induced ternary complexes by measuring for the first time the kinetics of their formation and dissociation in vitro using purified proteins. We benchmark our assay using four PROTACs that target the bromodomains (BDs) of BET proteins Brd2, Brd3 and Brd4 to the E3 ligase VHL. We reveal marked differences in ternary complex off-rates for different PROTACs that exhibit either positive or negative cooperativity for ternary complex formation relative to binary binding. The positively cooperative degrader MZ1 forms comparatively stable and long-lived ternary complexes with either Brd4BD2 or Brd2BD2 and VHL. Equivalent complexes with Brd3BD2 are destabilised due to a single amino acid difference (Glu/Gly swap) present in the bromodomain. We observe that this difference in ternary complex dissociative half-life correlates to a greater initial rate of intracellular degradation of Brd2 and Brd4 relative to Brd3. These findings establish a novel assay to measure the kinetics of PROTAC ternary complexes and elucidate the important kinetic parameters that drive effective target degradation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=121 SRC="FIGDIR/small/451948v2_ufig2.gif" ALT="Figure 2"> View larger version (32K): org.highwire.dtl.DTLVardef@10e7c1eorg.highwire.dtl.DTLVardef@1f6a57forg.highwire.dtl.DTLVardef@1eb6e46org.highwire.dtl.DTLVardef@194cb2a_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry

Sparse Coding with a Somato-Dendritic Rule

Cortical neurons are silent most of the time. This sparse activity is energy efficient, and the resulting neural code has favourable properties for associative learning. Most neural models of sparse coding use some form of homeostasis to ensure that each neuron fires infrequently. But homeostatic plasticity acting on a fast timescale may not be biologically plausible, and could lead to catastrophic forgetting in embodied agents that learn continuously. We set out to explore whether inhibitory plasticity could play that role instead, regulating both the population sparseness and the average firing rates. We put the idea to the test in a hybrid network where rate-based dendritic compartments integrate the feedforward input, while spiking somas compete through recurrent inhibition. A somato-dendritic learning rule allows somatic inhibition to modulate nonlinear Hebbian learning in the dendrites. Trained on MNIST digits and natural images, the network discovers independent components that form a sparse encoding of the input and support linear decoding. These findings con-firm that intrinsic plasticity is not strictly required for regulating sparseness: inhibitory plasticity can have the same effect, although that mechanism comes with its own stability-plasticity dilemma. Going beyond point neuron models, the network illustrates how a learning rule can make use of dendrites and compartmentalised inputs; it also suggests a functional interpretation for clustered somatic inhibition in cortical neurons.

neuroscience