title: Mutators drive evolution of multi-resistance to antibiotics

abstract: Combination drug treatments are an approach used to counter the evolution of resistance-the guiding principle being that they can prevent multiple independent resistance mutations from arising sequentially in the same genome. Here, we show that bacterial populations with  mutators, organisms defective in DNA repair, can evolve multi-resistance under conditions where purely wild-type populations cannot. We exposed experimental populations of Escherichia coli to rising concentrations of single-drug and combination antibiotic treatments. Introducing mutators at low-to-intermediate frequencies permitted the evolution of multi-resistance. Notably, the evolution of multi-resistance did not require direct selection for both resistance mutations, as the elevated mutation rates allowed it to evolve under single-drug and combination treatments alike. Using eco-evolutionary simulations, we show that hitch-hiking with single resistance mutations allowed the mutator allele to sweep to fixation. The resulting increase in mutation supply was the key to evolving multi-resistance sequentially. While simulations also demonstrated that multi-resistance can arise in large populations, the size required exceeded those typical of infection. Ultimately, our results suggest that the utility of combination therapy may be limited when mutators are present, and when achieving or maintaining therapeutic antibiotic concentrations is difficult.

category: evolutionary biology


title: A Hessian-based decomposition characterizes how performance in complex motor skills depends on individual strategy and variability

abstract:
In complex real-life motor skills such as unconstrained throwing, performance depends on how accurate is on average the outcome of noisy, high-dimensional, and redundant actions. What characteristics of the action distribution relate to performance and how different individuals select specific action distributions are key questions in motor control. Previous computational approaches have highlighted that variability along the directions of first order derivatives of the action-to-outcome mapping affects performance the most, that different mean actions may be associated to regions of the actions space with different sensitivity to noise, and that action covariation in addition to noise magnitude matters. However, a method to relate individual high-dimensional action distribution and performance is still missing. Here we introduce a de-composition of performance into a small set of indicators that compactly and directly characterize the key performance-related features of the distribution of high-dimensional redundant actions. Central to the method is the observation that, if performance is quantified as a mean score, the Hessian (second order derivatives) of the action-to-score function determines how the noise of the action distribution affects the average score. We can then approximate the mean score as the sum of the score of the mean action and a tolerance-variability index which depends on both Hessian and action covariance. Such index can be expressed as the product of three terms capturing noise magnitude, noise sensitivity, and alignment of the most variable and most noise sensitive directions. We apply this method to the analysis of unconstrained throwing actions by non-expert participants and show that, consistently across four different throwing targets, each participant shows a specific selection of mean action score and tolerance-variability index as well as specific selection of noise magnitude and alignment indicators. Thus, participants with different strategies may display the same performance because they can trade off suboptimal mean action for better tolerance-variability and higher action variability for better alignment with more tolerant directions in action space.

Author summaryWhy do people differ in their performance of complex motor skills? In many real-life motor tasks achieving a goal requires selecting an appropriate high-dimensional action out of infinitely many goal-equivalent actions. Because of sensorimotor noise, we are unable to execute the exact same movement twice and our performance depends on how accurate we are on average. Thus, to understand why people perform differently we need to characterize how their action distribution relates to their mean task score. While better performance is often associated to smaller variability around a more accurate mean action, performance also depends on the relationship between the directions of highest variability in action space and the directions in which action variability affects the most the outcome of the action. However, characterizing such geometric relationship when actions are high dimensional is challenging. In this work we introduce a method that allows to characterize the key performance-related features of the distribution of high-dimensional actions by a small set of indicators. We can then compare such indicators in different people performing a complex task (such as unconstrained throwing) and directly characterize the most skilled ones but also identify different strategies that distinguish people with similar performance.

category: neuroscience


title: Comparing statistical and mechanistic models to identify the drivers of mortality within a rear-edge beech population

abstract:
AO_SCPLOWBSTRACTC_SCPLOWSince several studies have been reporting an increase in the decline of forests, a major issue in ecology is to better understand and predict tree mortality. The interactions between the different factors and the physiological processes giving rise tree mortality, as well as the inter-individual variability in mortality risk, still need to be better assessed.

This study investigates mortality in a rear-edge population of European beech (Fagus sylvatica L.) using a combination of statistical and process-based modelling approaches. Based on a survey of 4323 adult beeches since 2002 within a natural reserve, we first used statistical models to quantify the effects of competition, tree growth, size, defoliation and fungi presence on mortality. Secondly, we used an ecophysiological process-based model (PBM) to separate out the different mechanisms giving rise to temporal and inter-individual variations in mortality by simulating depletion of carbon stocks, loss of hydraulic conductance and damage due to late frosts in response to climate.

The combination of all these simulated processes was associated with the temporal variations in the population mortality rate. The individual probability of mortality decreased with increasing mean growth, and increased with increasing crown defoliation, earliness of budburst, fungi presence and increasing competition, in the statistical model. Moreover, the interaction between tree size and defoliation was significant, indicating a stronger increase in mortality associated to defoliation in smaller than larger trees. Finally, the PBM predicted a higher conductance loss together with a higher level of carbon reserves for trees with earlier budburst, while the ability to defoliate the crown was found to limit the impact of hydraulic stress at the expense of the accumulation of carbon reserves.

We discuss the convergences and divergences obtained between statistical and process-based approaches and we highlight the importance of combining them to characterize the different processes underlying mortality, and the factors modulating individual vulnerability to mortality.

category: ecology


title: Deconstructing taxa x taxa x environment interactions in the microbiota: A theoretical examination

abstract:
O_LIA major objective of microbial ecology is to identify how the composition of gut microbial taxa shapes host phenotypes. However, most studies focus solely on community-level patterns and pairwise interactions and ignore the potentially significant effects of higher-order interactions involving three or more component taxa.
C_LIO_LIStudies on higher-order interactions among microbial taxa are scarce for many reasons, including experimental intractability, daunting diversity and complexity of many microbial systems, and the potential confounding role of the environment. Moreover, we still lack the empirical and statistical tools to isolate and understand the role of higher-order interactions on the host.
C_LIO_LIHere, we apply a mathematical approach to quantifying the effects of higher-order interactions among taxa on host infection risk. To do so, we adapt the Hadamard-Walsh method recently used in evolutionary genetics to quantify the nonlinear effects of mutations on fitness. We apply our approach to an in silico dataset built to resemble a population of insect hosts with gut-associated microbial communities at risk of infection from an intestinal parasite. Critically, we examine these interactions across a breadth of environmental contexts, using nutrient content of the insect diet as a model for context.
C_LIO_LIWe find that the effect of higher-order interactions is considerable and can change appreciably across environmental contexts. Strikingly, the relative eminence of different orders (pairwise vs. third order, fourth order, and fifth order) changes as a function of environmental context. Furthermore, we show-in our theoretical microcosm-that higher-order interactions can stabilize community structure thereby reducing host susceptibility to parasite invasion.
C_LIO_LIOur approach illustrates how incorporating the effects of higher-order interactions among gut microbiota across environments can be essential for understanding their effects on host phenotypes. We conclude that higher-order interactions among taxa can profoundly shape important organismal phenotypes, and they deserve greater attention in host-associated microbiome studies.
C_LI


title: Damped oscillations of the probability of random events followed by absolute refractory period: exact analytical results

abstract: There are numerous examples of natural and artificial processes that represent stochastic sequences of events followed by an absolute refractory period during which the occurrence of a subsequent event is impossible. In the simplest case of a generalized Bernoulli scheme for uniform random events followed by the absolute refractory period, the event probability as a function of time can exhibit damped transient oscillations. Using stochastically-spiking point neuron as a model example, we present an exact and compact analytical description for the oscillations without invoking the standard renewal theory. The resulting formulas stand out for their relative simplicity, allowing one to analytically obtain the amplitude damping of the 2nd and 3rd peaks of the event probability.


title: Estimations of the weather effects on brain functions using functional MRI: a cautionary note

abstract: The influences of environmental factors such as weather on the human brain are still largely unknown. A few neuroimaging studies have demonstrated seasonal effects, but were limited by their cross-sectional design or sample sizes. Most importantly, the stability of the MRI scanner hasnt been taken into account, which may also be affected by environments. In the current study, we analyzed longitudinal resting-state functional MRI (fMRI) data from eight individuals, where the participants were scanned over months to years. We applied machine learning regression to use different resting-state parameters, including the amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and functional connectivity matrix, to predict different weather and environmental parameters. For careful control, the raw EPI and the anatomical images were also used for predictions. We first found that daylight length and air temperatures could be reliably predicted with cross-validation using the resting-state parameters. However, similar prediction accuracies could also be achieved by using one frame of EPI image, and even higher accuracies could be achieved by using segmented or raw anatomical images. Finally, the signals outside of the brain in the anatomical images and signals in phantom scans could also achieve higher prediction accuracies, suggesting that the predictability may be due to the baseline signals of the MRI scanner. After all, we did not identify detectable influences of weather on brain functions other than the influences on the baseline signals of MRI scanners. The results highlight the difficulty of studying long-term effects using MRI.


title: Secondary Structure Motifs Made Searchable to Facilitate the Functional Peptide Design

abstract: To ensure a physicochemically desired sequence motif to adapt a specific type of secondary structures, we compile an -helix database allowing complicate search patterns to facilitate a data-driven design of therapeutic peptides. Nearly 1.7 million helical peptides in >130 thousand proteins are extracted along with their interacting partners from the protein data bank (PDB). The sequences of the peptides are indexed with patterns and gaps and deposited in our Therapeutic Peptide Design dataBase (TP-DB). We here demonstrate its utility in three medicinal design cases. By our pattern-based search engine but not PHI-BLAST, we can identify a pathogenic protein, Helicobacter pylori neutrophil-activating protein (HP-NAP), a virulence factor of H. pylori, which contains a motif DYKYLE that belongs to the affinity determinant motif DYKXX[DE] of the FLAG-tag and can be recognized by the anti-FLAG M2 antibody. By doing so, the known purification-tag-specific antibody is repurposed into a diagnostic kit for H. pylori. Also by leveraging TP-DB, we discovered a stretch of helical peptide matching the potent membrane-insertion pattern WXXWXXW, elucidated by MD simulations. The newly synthesized peptide has a better minimal inhibitory concentration (MIC) and much lower cytotoxicity against Candida albicans (fungus) than that of previously characterized homologous antimicrobial peptides. In a similar vein, taking the discontinued anchoring residues in the helix-helix interaction interface as the search pattern, TP-DB returns several helical peptides as potential tumor suppressors of hepatocellular carcinoma (HCC) whose helicity and binding affinity were examined by MD simulations. Taken together, we believe that TP-DB and its pattern-based search engine provide a new opportunity for a (secondary-)structure-based design of peptide drugs and diagnostic kits for pathogens without inferring evolutionary homology between sequences sharing the same pattern. TP-DB is made available at http://dyn.life.nthu.edu.tw/design/.

category: bioinformatics


title: Mitigating biomass composition uncertainties in flux balance analysis using ensemble representations

abstract: The biomass equation is a critical component in genome-scale metabolic models (GEMs): it is used as the de facto objective function in flux balance analysis (FBA). This equation accounts for the quantities of all known biomass precursors that are required for cell growth based on the macromolecular and monomer compositions measured at certain conditions. However, it is often reported that the macromolecular composition of cells could change across different environmental conditions; the use of the same single biomass equation in FBA, under multiple conditions, is questionable. Thus, we first investigated the qualitative and quantitative variations of macromolecular compositions of three representative host organisms, Escherichia coli, Saccharomyces cerevisiae and Cricetulus griseus, across different environmental/genetic variations. While macromolecular building blocks such as DNA, RNA, protein, and lipid composition vary notably, variations in fundamental biomass monomer units such as nucleotides and amino acids are not appreciable. We further observed that while macromolecular compositions are similar across taxonomically closer species, certain monomers, especially fatty acids, vary substantially. Based on the analysis results, we subsequently propose a new extension to FBA, named "Flux Balance Analysis with Ensemble Biomass (FBAwEB)", to embrace the natural variation in selected components of the biomass equation. The current study clearly highlights that certain components of the biomass equation are very sensitive to different conditions, and the ensemble representation of biomass equation in the FBA framework enables us to account for such natural variations accurately during GEM-guided in silico simulations.

category: systems biology


title: Molecular Determinants of μ-Conotoxin KIIIA interaction with the Voltage-Gated Sodium Channel Nav1.7

abstract: The voltage-gated sodium (Nav) channel subtype Nav1.7 plays a critical role in pain signaling, making it an important drug target. Here we studied the molecular interactions between -conotoxin KIIIA (KIIIA) and the human Nav1.7 channel (hNav1.7). We developed a structural model of hNav1.7 using Rosetta computational modeling and performed in silico docking of KIIIA using RosettaDock to predict residues forming specific pairwise contacts between KIIIA and hNav1.7. We experimentally validated these contacts using mutant cycle analysis. Comparison between our KIIIA-hNav1.7 model and the cryo-EM structure of KIIIA-hNav1.2 revealed key similarities and differences between Nav channel subtypes with potential implications for the molecular mechanism of toxin block. The accuracy of our integrative approach, combining structural data with computational modeling, experimental validation, and molecular dynamics simulations, suggests that Rosetta structural predictions will be useful for rational design of novel biologics targeting specific Nav channels.

category: biophysics


title: Deep learning does not outperform classical machine learning for cell-type annotation

abstract:
Deep learning has revolutionized image analysis and natural language processing with remarkable accuracies in prediction tasks, such as image labeling and semantic segmentation or named-entity recognition and semantic role labeling. Specifically, the combination of algorithmic and hardware advances with the appearance of large and well-labeled datasets has led up to seminal contributions in these fields.

The emergence of large amounts of data from single-cell RNA-seq and the recent global effort to chart all cell types in the Human Cell Atlas has attracted an interest in deep-learning applications. However, all current approaches are unsupervised, i.e., learning of latent spaces without using any cell labels, even though supervised learning approaches are often more powerful in feature learning and the most popular approach in the current AI revolution by far. Here, we ask why this is the case. In particular we ask whether supervised deep learning can be used for cell annotation, i.e. to predict cell-type labels from single-cell gene expression profiles. After evaluating 10 classification methods across 14 datasets, we notably find that deep learning does not outperform classical machine-learning methods in the task. Thus, cell-type prediction based on gene-signature derived cell-type labels is potentially too simplistic a task for complex non-linear methods, which demands better labels of functional single-cell readouts.


title: Regulatory regions in natural transposable element insertions drive interindividual differences in response to immune challenges in Drosophila

abstract:
BackgroundVariation in gene expression underlies interindividual variability in relevant traits including immune response. However, the genetic variation responsible for these gene expression changes remain largely unknown. Among the non-coding variants that could be relevant, transposable element insertions are promising candidates as they have been shown to be a rich and diverse source of cis-regulatory elements.

ResultsIn this work, we used a population genetics approach to identify transposable element insertions likely to increase the tolerance of Drosophila melanogaster to bacterial infection by affecting the expression of immune-related genes. We identified 12 insertions associated with allele-specific expression changes in immune-related genes. We experimentally validated three of these insertions including one likely to be acting as a silencer, one as an enhancer, and one with a dual role as enhancer and promoter. The direction in the change of gene expression associated with the presence of several of these insertions was consistent with an increased survival to infection. Indeed, for one of the insertions, we showed that this is the case by analyzing both natural populations and CRISPR/Cas9 mutants in which the insertion was deleted from its native genomic context.

ConclusionsWe showed that transposable elements contribute to gene expression variation in response to infection in D. melanogaster and that this variation is likely to affect their survival capacity. Because the role of transposable elements as regulatory elements is not restricted to Drosophila, TEs are likely to play a role in immune response in other organisms as well.


title: Neural pathways linking hypoxia with pectoral fin movements in Danio rerio

abstract: Zebrafish larvae respond to hypoxia by increasing a number of ventilatory behaviors. During development, these animals switch from skin-resident to gill-resident neuroendocrine cells around 7 days post fertilization (d.p.f.) to detect hypoxia and drive adaptive behaviors. Here, we probe the neural pathways that receive inputs from skin-resident neuroendocrine cells and alter pectoral fin movements. We first show that a 5 d.p.f. larva increases its pectoral fin movements and heart activity upon hypoxia exposure. Next, we map the downstream neural circuitry and show that individual vagal sensory neurons receive inputs from multiple oxygen-sensing neuroendocrine cells. We then use calcium imaging to show that neurons in the second, but not third, vagal sensory ganglia show increases in the magnitude of their hypoxia-evoked responses. Finally, we link purinergic signaling between neuroendocrine cells and second vagal sensory neurons to increases in pectoral fin movements. Collectively, we suggest that vagal sensory neurons transform hypoxic stimuli into respiratory behaviors.


title: Re-treatment with direct-acting antivirals policy is needed to eliminate Hepatitis C among persons who inject drugs

abstract:
Background and AimsHepatitis C virus (HCV) infection is a leading cause of chronic liver disease and mortality worldwide. Direct-acting antiviral (DAA) therapy leads to high cure rates. However, persons who inject drugs (PWID) are at risk for reinfection after cure and may require DAA retreatment to reach the World Health Organizations (WHO) goal of HCV elimination by 2030. We aim to project the frequency of retreatment and DAA cost needed to achieve WHO goals.

DesignWe use an agent-based model (ABM) that accounts for the complex interplay of demographic factors, risk behaviors, social networks, and geographic location for HCV transmission among PWID.

Setting and participants32,000 in-silico PWID in metropolitan Chicago.

Intervention and comparatorPossible treatment adherence rates (i.e., DAA cure rates) of 60%-90% with DAA treatment enrollment rates of 2.5%-10% and retreatments per PWID of 0 (retreatment prohibited), 1, 2, 3, or no retreatment restriction were simulated. DAA cost is assumed $25,000 (USD) per treatment.

FindingsModeling results indicate that prohibition of retreatment in PWID would jeopardize achieving the WHO goal of reducing the incidence of new chronic HCV infections by 90% by 2030. We predict that with a DAA treatment rate of >7.5% per year and high (90%) adherence, 75%, 19%, 5% and <2% of PWID will require 1, 2, 3, and 4 treatment courses with overall DAA cost of $325 million to achieve the WHO goal in metropolitan Chicago. We estimate a 28% increase in the overall DAA cost under low adherence (70%) compared to high adherence (90%).

ConclusionsModeling results predict the frequency of DAA retreatment needed to achieve the WHO goal and underscore the importance of retreatment of HCV re-infections.

category: epidemiology


title: Amyloid-β induced membrane damage instigates tunneling nanotubes by exploiting PAK1 dependent actin remodulation

abstract: Alzheimers disease (AD) pathology progresses gradually via anatomically connected brain regions. Earlier studies have shown that amyloid-{beta}1-42 oligomers (oA{beta}) can be directly transferred between connected neurons. However, the mechanism of transfer is not fully revealed. We observed formation of oA{beta} induced tunneling nanotubes (TNTs), nanoscaled f-actin containing membrane conduit, in differentially differentiated SH-SY5Y neuronal models. Time-lapse images showed that TNTs propagate oligomers from one cell to another. Preceding the TNT-formation, we detected oA{beta} induced plasma membrane (PM) damage and calcium-dependent repair through lysosomal-exocytosis and significant membrane surface expansion, followed by massive endocytosis to re-establish the PM. Massive endocytosis was monitored by an influx of the membrane-impermeable dye TMA-DPH and PM damage was quantified by propidium iodide influx in the absence of calcium. The massive endocytosis eventually caused accumulation of internalized oA{beta} in Lamp1 positive multi vesicular bodies/lysosomes via the actin cytoskeleton remodulating p21-activated kinase1 (PAK1) dependent endocytic pathway. Three dimensional quantitative and qualitative confocal imaging, structured illumination superresolution microscopy (SIM) and flowcytometry data revealed that oA{beta} induces activated phospho-PAK1, which modulates the formation of long stretched f-actin extensions between cells. Moreover, formation of TNTs can be inhibited by preventing PAK1 dependent internalization of oA{beta} using small-molecule inhibitor IPA-3, a highly selective cell permeable auto-regulatory inhibitor of PAK1. The present study gives insight that the TNTs are probably instigated as a consequence of oA{beta} induced PM damage and repair process, followed by PAK1 dependent endocytosis and actin remodeling, probably to maintain cell surface expansion and/or membrane tension in equilibrium.

category: cell biology


title: Universal latent axes capturing Parkinson's patient deep phenotypic variation reveals patients with a high genetic risk for Alzheimer's disease are more likely to develop a more aggressive form of Parkinson's.

abstract: The generation of deeply phenotyped patient cohorts offers an enormous potential to identify disease subtypes but are currently limited by the cohort size and the heterogeneity of the clinical assessments collected across different cohorts. Identifying the universal axes of clinal severity and progression is key to accelerating our understanding of how disease manifests and progresses. These universal axes would accelerate our understanding of how Parkinsons disease (PD) manifests and progresses through which patients may be appropriately compared appropriately stratified, and personalised therapeutic strategies and treatments can be developed and targeted. We developed a Bayesian multiple phenotype mixed model incorporating the genetic relationships between individuals which is able to reduce a wide-array of different clinical measurements into a smaller number of continuous underlying factors named phenotypic axis. We identify three principal axes of PD patient phenotypic variation which are reproducibly found across three independent, deeply and diversely phenotyped cohorts. Together they explain over 75% of the observed clinical variation and remain robustly captured with a fraction of the clinically-recorded features. The most influential axis was associated with the genetic risk of Alzheimers disease (AD) and involves genetic pathways associated with neuroinflammation. Our results suggest PD patients with a high genetic risk for AD are more likely to develop a more aggressive form of PD including, but not limited to, dementia.


title: Oxazepam and cognitive reappraisal: a randomised experiment

abstract:
BackgroundCognitive reappraisal is a strategy for emotional regulation, important in the context of anxiety disorders. It is not known whether anxiolytic effects of benzodiazepines affect cognitive reappraisal.

AimsWe aimed to investigate the effect of 25 mg oxazepam on cognitive reappraisal.

MethodsIn a preliminary investigation, 33 healthy male volunteers were randomised to oxazepam or placebo, and then underwent an experiment where they were asked to use cognitive reappraisal to upregulate or downregulate their emotional response to images with negative or neutral emotional valence. We recorded unpleasantness ratings, skin conductance, superciliary corrugator muscle activity, and heart rate. Participants completed rating scales measuring empathy (Interpersonal Reactivity Index, IRI), anxiety (State-Trait Anxiety Inventory, STAI), alexithymia (Toronto Alexithymia Scale-20, TAS-20), and psychopathy (Psychopathy Personality Inventory-Revised, PPI-R).

ResultsUpregulation to negative-valence images in the cognitive reappraisal task caused increased unpleasantness ratings, corrugator activity, and heart rate compared to downregulation. Upregulation to both negative- and neutral-valence images caused increased skin conductance responses. Oxazepam caused lower unpleasantness ratings to negative-valence stimuli, but did not interact with reappraisal instruction on any outcome. Self-rated trait empathy was associated with stronger responses to negative-valence stimuli, whereas self-rated psychopathic traits were associated with weaker responses to negative-valence stimuli.

ConclusionsWhile 25 mg oxazepam caused lower unpleasantness ratings in response to negative-valence images, we did not observe an effect of 25 mg oxazepam on cognitive reappraisal.


title: Systematic detection of brain protein-coding genes under positive selection during primate evolution and their roles in cognition

abstract: The human brain differs from that of other primates, but the genetic basis of these differences remains unclear. We investigated the evolutionary pressures acting on almost all human protein-coding genes (N=11,667; 1:1 orthologs in primates) based on their divergence from those of early hominins, such as Neanderthals, and non-human primates. We confirm that genes encoding brain-related proteins are among the most strongly conserved protein-coding genes in the human genome. Combining our evolutionary pressure metrics for the protein-coding genome with recent datasets, we found that this conservation applied to genes functionally associated with the synapse and expressed in brain structures such as the prefrontal cortex and the cerebellum. Conversely, several genes presenting signatures commonly associated with positive selection appear as causing brain diseases or conditions, such as micro/macrocephaly, Joubert syndrome, dyslexia, and autism. Among those, a number of DNA damage response genes associated with microcephaly in humans such as BRCA1, NHEJ1, TOP3A, and RNF168 show strong signs of positive selection and might have played a role in human brain size expansion during primate evolution. We also showed that cerebellum granule neurons express a set of genes also presenting signatures of positive selection and that may have contributed to the emergence of fine motor skills and social cognition in humans. This resource is available online and can be used to estimate evolutionary constraints acting on a set of genes and to explore their relative contributions to human traits.

category: genetics


title: Simplified high-throughput methods for deep proteome analysis on the timsTOF Pro

abstract: Recent advances in mass spectrometry technology have seen remarkable increases in proteomic sequencing speed, while improvements to dynamic range have remained limited. An exemplar of this is the new timsTOF Pro instrument, which thanks to its trapped ion mobility, pushes effective fragmentation rates beyond 100Hz and provides accurate CCS values as well as impressive sensitivity. Established data dependent methodologies underutilize these advances by relying on long analytical columns and extended LC gradients to achieve comprehensive proteome coverage from biological samples. Here we describe the implementation of methods for short packed emitter columns that fully utilize instrument speed and CCS values by combining rapid generation of deep peptide libraries with enhanced matching of single shot data dependent sample analysis. Impressively, with only a 17 minute separation gradient (50 samples per day), the combination of high performance chromatography and CCS enhanced library based matching resulted in an average of 5,931 protein identifications within individual samples, and 7,244 proteins cumulatively across replicates from HeLa cell tryptic digests. Additionally, an ultra-high throughput setup utilizing 5 min gradients (180 samples per day) yielded an average of 3,666 protein identifications within individual samples and 4,659 proteins cumulatively across replicates. These workflows are simple to implement on available technology and do not require complex software solutions or custom-made consumables to achieve high throughput and deep proteome analysis from biological samples.

category: biochemistry


title: From spikes to intercellular waves: tuning intercellular Ca2+ signaling dynamics modulates organ size control

abstract:
Information flow within and between cells depends in part on calcium (Ca2+) signaling dynamics. However, the biophysical mechanisms that govern emergent patterns of Ca2+ signaling dynamics at the organ level remain elusive. Recent experimental studies in developing Drosophila wing imaginal discs demonstrate the emergence of four distinct patterns of Ca2+ activity: Ca2+ spikes, intercellular Ca2+ transients, tissue-level Ca2+ waves, and a global "fluttering" state. Here, we used a combination of computational modeling and experimental approaches to identify two different populations of cells within tissues that are connected by gap junctional proteins. We term these two subpopulations "initiator cells" defined by elevated levels of Phospholipase C (PLC) activity and "standby cells," which exhibit baseline activity. We found that the strength of hormonal stimulation and extent of gap junctional communication jointly determine the predominate class of Ca2+ signaling activity. Further, single-cell Ca2+ spikes are stimulated by insulin, while intercellular Ca2+ waves depend on Gq activity. Our computational model successfully recapitulates how the dynamics of Ca2+ transients varies during organ growth. Phenotypic analysis of perturbations to Gq and insulin signaling support an integrated model of cytoplasmic Ca2+ as a dynamic reporter of overall tissue growth. Further, we show that perturbations to Ca2+signaling tune the final size of organs. This work provides a platform to further study how organ size regulation emerges from the crosstalk between biochemical growth signals and heterogeneous cell signaling states.

Author SummaryCalcium (Ca2+) is a universal second messenger that regulates a myriad of cellular processes such as cell division, cell proliferation and apoptosis. Multiple patterns of Ca2+ signaling including single cell spikes, multicellular Ca2+ transients, large-scale Ca2+ waves, and global "fluttering" have been observed in epithelial systems during organ development. Key molecular players and biophysical mechanisms involved in formation of these patterns during organ development are not well understood. In this work, we developed a generalized multicellular model of Ca2+ that captures all the key categories of Ca2+ activity as a function of key hormonal signals. Integration of model predictions and experiments reveals two subclasses of cell populations and demonstrates that Ca2+ signaling activity at the organ scale is defined by a general decrease in gap junction communication as organ growth. Our experiments also reveal that a "goldilocks zone" of optimal Ca2+ activity is required to achieve optimal growth at the organ level.


title: Dynamic pneumococcal genetic adaptations support bacterial growth and inflammation during coinfection with influenza

abstract: Streptococcus pneumoniae (pneumococcus) is one of the primary bacterial pathogens that complicates influenza virus infections. These bacterial coinfections increase influenza-associated morbidity and mortality through a number of immunological and viral-mediated mechanisms, but the specific bacterial genes that contribute to post-influenza pathogenicity are not known. Here, we used genome-wide transposon mutagenesis (Tn-Seq) to reveal bacterial genes that confer improved fitness in influenza-infected hosts. The majority of the 32 identified genes are involved in bacterial metabolism, including nucleotide biosynthesis, amino acid biosynthesis, protein translation, and membrane transport. We generated single-gene deletion (SGD) mutants of five identified genes: SPD1414, SPD2047 (cbiO1), SPD0058 (purD), SPD1098, and SPD0822 (proB), to investigate their effect on in vivo fitness, disease severity, and host immune responses. Growth of SGD mutants was slightly attenuated in vitro and in vivo, but each still grew to high titers in the lungs of mock- and influenza-infected hosts. Despite high bacterial loads, mortality was significantly reduced or delayed with all SGD mutants. Time-dependent reductions in pulmonary neutrophils, inflammatory macrophages, and select proinflammatory cytokines and chemokines were also observed. Immunohistochemical staining further revealed that neutrophil phenotype and distribution was altered in the lungs of influenza-SGD coinfected animals. These studies demonstrate a critical role for specific bacterial genes and for bacterial metabolism in driving virulence and modulating immune function during influenza-associated bacterial pneumonia.

category: microbiology


title: Whole body regeneration deploys a rewired embryonic gene regulatory network logic

abstract:
For over a century, researchers have been trying to understand the relationship between embryogenesis and regeneration. A long-standing hypothesis is that biological processes implicated in embryonic development are re-deployed during regeneration. In the past decade, we have begun to understand the relationships of genes and their organization into gene regulatory networks (GRN) driving embryonic development and regeneration in diverse taxa.

Here, we compare embryonic and regeneration GRNs in the same species to investigate how regeneration re-uses genetic interactions originally set aside for embryonic development. Using a well-suited embryonic development and whole-body regeneration model, the sea anemone Nematostella vectensis, we show that at the transcriptomic level the regenerative program partially re-uses elements of the embryonic gene network along with a small cohort of genes that are specifically activated during the process of regeneration. We further identified co-expression modules that are either i) highly conserved between these two developmental trajectories and involved in core biological processes (e.g., terminal differentiation) or ii) regeneration specific modules that drive cellular events, such as apoptosis, that are unique to regeneration.

Our global transcriptomic approach suggested that regeneration reactivates embryonic gene modules following regeneration-specific network logic. We thus verified this observation by functionally dissecting the role of MEK/ERK signaling during regeneration and established a first blueprint of the regeneration MEK/ERK-dependent GRN in Nematostella. Comparing the latter to the existing GRN underlying embryogenic development of the same species, we show at the network level that i) regeneration is a partial redeployment of the embryonic GRN, ii) embryonic gene modules are rewired during regeneration and iii) they are interconnected to novel down-stream targets, including "regeneration-specific" genes.

Significance statementIn this intra-species transcriptomic comparison of embryonic development and regeneration in a whole-body regeneration model, the sea anemone Nematostella vectensis, we identified that 1) regeneration is a transcriptionally modest event compared to embryonic development and 2) that although regeneration re-uses embryonic genetic interactions, it does so by using regeneration specific network logic. In addition to identifying that apoptosis is a regeneration-specific event in Nematostella, this study reveals that GRN modules are reshuffled from one developmental trajectory to the other, even when accomplishing the same task (e.g. forming a fully functional organism). These findings highlight the plasticity of network architecture and set the basis for determining and functionally dissecting regeneration-inducing regulatory elements. From an evolutionary perspective, our study sets the foundation for further comparative work and provides new opportunities to understand why certain organisms can regenerate while others cannot.

category: developmental biology


title: Eating in a losing cause: limited benefit of modified macronutrient consumption following infection in the oriental cockroach Blatta orientalis

abstract:
BackgroundHost-pathogen interactions can lead to dramatic changes in host feeding behaviour. One aspect of this includes self-medication, where infected individuals consume substances such as toxins or alter their macronutrient consumption to enhance immune competence. Another widely adopted animal response to infection is illness-induced anorexia, which is thought to assist host immunity directly or by limiting the nutritional resources available to pathogens. Here, we recorded macronutrient preferences of the global pest cockroach, Blatta orientalis to investigate how shifts in host macronutrient dietary preference and quantity of carbohydrate (C) and protein (P) interact with immunity following bacterial infection.

ResultsWe find that B. orientalis avoids diets enriched for P under normal conditions, and that high P diets reduce cockroach survival in the long term. However, following bacterial challenge, cockroaches significantly reduced their overall nutrient intake, particularly of carbohydrates, and increased the relative ratio of protein (P:C) consumed. Surprisingly, these behavioural shifts had a limited effect on cockroach immunity and survival, with minor changes to immune protein abundance and antimicrobial activity between individuals placed on different diets, regardless of infection status.

ConclusionsWe show that cockroach feeding behaviour can be modulated by a pathogen, resulting in an illness-induced anorexia-like feeding response and a shift from a C-enriched to a more P:C equal diet. However, our results also indicate that such responses do not provide significant immune protection in B. orientalis, suggesting that the hosts dietary shift might also result from random rather than directed behaviour. The lack of an apparent benefit of the shift in feeding behaviour highlights a possible reduced importance for diet in immune regulation in these invasive animals, although further investigations employing pathogens with alternative infection strategies are warranted.


title: Temozolomide-induced guanine mutations create exploitable vulnerabilities of guanine-rich DNA and RNA regions in drug resistant gliomas

abstract:
Temozolomide (TMZ) is a chemotherapeutic agent that has been the first-line standard of care for the aggressive brain cancer glioblastoma (GBM) since 2005. Though initially beneficial, TMZ- resistance is universal and second-line interventions are an unmet clinical need. Here we took advantage the mechanism of action of TMZ to target guanines (G) and investigated G-rich g- quadruplex (G4) and splice site changes that occur upon TMZ-resistance. We report TMZ-resistant GBM has guanine mutations that disrupt the G-rich DNA G4s and splice sites that lead to deregulated alternative splicing. These alterations create vulnerabilities, which are selectively targeted by either the G4 stabilizing drug TMPyP4 or a novel splicing kinase inhibitor of cdc2- like kinase. Finally, we show that the G4 and RNA-binding protein EWSR1 aggregates in the cytoplasm in TMZ-resistant GBM cells and patient samples. Together, our findings provide insight into targetable vulnerabilities of TMZ-resistant GBM and present cytoplasmic EWSR1 as a putative biomarker.

TeaserTargeting temozolomide mutations in drug resistant glioma via g-quadruplex and splicing modulators with a putative biomarker.

category: cancer biology


title: Analysis of meiosis in Pristionchus pacificus reveals plasticity in homolog pairing and synapsis in the nematode lineage

abstract: Meiosis is conserved across eukaryotes yet varies in the details of its execution. Here we describe a new comparative model system for molecular analysis of meiosis, the nematode Pristionchus pacificus, a distant relative of the widely studied model organism Caenorhabditis elegans. P. pacificus shares many anatomical and other features that facilitate analysis of meiosis in C. elegans. However, while C. elegans has lost the meiosis-specific recombinase Dmc1 and evolved a recombination-independent mechanism to synapse its chromosomes, P. pacificus expresses both DMC-1 and RAD-51. We find that SPO-11 and DMC-1 are required for stable homolog pairing, synapsis, and crossover formation, while RAD-51 is dispensable for these key meiotic processes. RAD-51 and DMC-1 localize sequentially to chromosomes during meiotic prophase and show nonoverlapping functions. We also present a new genetic map for P. pacificus that reveals a crossover landscape very similar to that of C. elegans, despite marked divergence in the regulation of synapsis and crossing-over between these lineages.


title: Invariant Object Representation Based on Principle of Maximum Dependence Capturing

abstract: Sensory inputs conveying information about the environment are often noisy and incomplete, yet the brain can achieve remarkable consistency in object recognition. This cognitive robustness is thought to be enabled by transforming the varying input patterns into invariant representations of objects, but how this transformation occurs computationally remains unclear. Here we propose that sensory coding should follow a principle of maximal dependence capturing to encode associations among structural components that can uniquely identify objects. We show that a computational framework incorporating dimension expansion and a specific form of sparse coding can capture structures that contain maximum information about specific objects, allow redundancy coding, and enable consistent representation of object identities. Using symbol and face recognition, we demonstrate that a two-layer system can generate representations that remain invariant under conditions of occlusion, corruption, or high noise.


title: Staufen blocks autophagy in neurodegeneration

abstract:
ObjectiveThe mechanistic target of rapamycin (mTOR) kinase is one of the master coordinators of cellular stress responses, regulating metabolism, autophagy, and apoptosis. We recently reported that Staufen1 (STAU1), a stress granule (SG) protein, was overabundant in fibroblast cell lines from patients with spinocerebellar ataxia type 2 (SCA2), amyotrophic lateral sclerosis, frontotemporal degeneration, Huntingtons, Alzheimers, and Parkinsons diseases as well as animal models, and patient tissues. STAU1 overabundance is associated with mTOR hyperactivation and links SG formation with autophagy. Our objective was to determine the mechanism of mTOR regulation by STAU1.

MethodsWe determined STAU1 abundance with disease- and chemical-induced cellular stressors in patient cells and animal models. We also used RNA binding assays to contextualize STAU1 interaction with MTOR mRNA.

ResultsSTAU1 and mTOR were overabundant in BAC-C9orf72, ATXN2Q127, and Thy1-TDP-43 transgenic mouse models. Reducing STAU1 levels in these mice normalized mTOR levels and activity and autophagy-related marker proteins. We also saw increased STAU1 levels in HEK293 cells transfected to express C9orf72-relevant dipeptide repeats (DPRs). Conversely, DPR accumulations were not observed in cells treated by STAU1 RNAi. Overexpression of STAU1 in HEK293 cells increased mTOR levels through direct MTOR mRNA interaction, activating downstream targets and impairing autophagic flux. Targeting mTOR by rapamycin or RNAi normalized STAU1 abundance in a SCA2 cellular model.

InterpretationSTAU1 interaction with mTOR drives its hyperactivation and inhibits autophagic flux in multiple models of neurodegeneration. Staufen, therefore, constitutes a novel target to modulate mTOR activity, autophagy, and for the treatment of neurodegenerative diseases.


title: The drug-induced phenotypic landscape of colorectal cancer organoids

abstract: Patient derived organoids resemble the biology of tissues and tumors, enabling ex vivo modeling of human diseases from primary patient samples. Organoids can be used as models for drug discovery and are being explored to guide clinical decision making. Patient derived organoids can have heterogeneous morphologies with unclear biological causes and relationship to treatment response. Here, we used high-throughput, image-based profiling to quantify phenotypes of over 5 million individual colorectal cancer organoids after treatment with more than 500 small molecules. Integration of data using a joint multi-omics modelling framework identified organoid size and cystic vs. solid organoid architecture as axes of morphological variation across organoids. Mechanistically, we found that organoid size was linked to IGF1 receptor signaling, while a cystic organoid architecture was associated with an LGR5+ stemness program. Treatment-induced organoid morphology reflected organoid viability, drug mechanism of action, and was biologically interpretable using joint modelling. Inhibition of MEK led to cystic reorganization of organoids and increased expression of LGR5, while inhibition of mTOR induced IGF1 receptor signaling. In conclusion, we identified shared axes of variation for colorectal cancer organoid morphology, their underlying biological mechanisms, and pharmacological interventions with the ability to move organoids along them. Image-based profiling of patient derived organoids coupled with multi-omics integration facilitates drug discovery by linking drug responses with underlying biological mechanisms.

category: genomics


title: iNetModels 2.0: an interactive visualization and database of multi-omics data

abstract: It is essential to reveal the associations between different omics data for a comprehensive understanding of the altered biological process in human wellness and disease. To date, very few studies have focused on collecting and exhibiting multi-omics associations in a single database. Here, we present iNetModels, an interactive database and visualization platform of Multi-Omics Biological Networks (MOBNs). This platform describes the associations between the clinical chemistry, anthropometric parameters, plasma proteomics and metabolomics as well as metagenomics for oral and gut microbiome obtained from the same individuals. Moreover, iNetModels includes tissue- and cancer-specific Gene Co-expression Networks (GCNs) for exploring the connections between the specific genes. This platform allows the user to interactively explore a single feature's association with other omics data and customize its particular context (e.g. male/female specific). The users can also register their own data for sharing and visualization of the MOBNs and GCNs. Moreover, iNetModels allows users who do not have a bioinformatics background to facilitate human wellness and diseases research. iNetModels can be accessed freely at https://inetmodels.com without any limitation.


title: Pervasive Translation in Mycobacterium tuberculosis

abstract: Most bacterial ORFs are identified by automated prediction algorithms. However, these algorithms often fail to identify ORFs lacking canonical features such as a length of >50 codons or the presence of an upstream Shine-Dalgarno sequence. Here, we use ribosome profiling approaches to identify actively translated ORFs in Mycobacterium tuberculosis. Most of the ORFs we identify have not been previously described, indicating that the M. tuberculosis transcriptome is pervasively translated. The newly described ORFs are predominantly short, with many encoding proteins of [≤]50 amino acids. Codon usage of the newly discovered ORFs suggests that most have not been subject to purifying selection, and hence do not contribute to cell fitness. Nevertheless, we identify 90 new ORFs (median length of 52 codons) that bear the hallmarks of purifying selection. Thus, our data suggest that pervasive translation of short ORFs in Mycobacterium tuberculosis serves as a rich source for the evolution of new functional proteins.


title: A simple pressure-assisted method for MicroED specimen preparation

abstract: Micro-crystal electron diffraction (MicroED) has shown great potential for structure determination of macromolecular crystals too small for X-ray diffraction. However, specimen preparation remains a major bottleneck. Here, we report a simple method for preparing MicroED specimens, named Preassis, in which excess liquid is removed through an EM grid with the assistance of pressure. We show the ice thicknesses can be controlled by tuning the pressure in combination with EM grids with appropriate hole sizes. Importantly, Preassis can handle a wide range of protein crystals grown in various buffer conditions including those with high viscosity, as well as samples with low crystal contents. Preassis is a simple and universal method for MicroED specimen preparation, and will significantly broaden the applications of MicroED.

category: molecular biology


title: Tipping-point analysis uncovers critical transition signals from gene expression profiles

abstract:
Differentiation involves bifurcations between discrete cell states, each defined by a distinct gene expression profile. Single-cell RNA profiling allows the detection of bifurcations. However, while current methods capture these events, they do not identify characteristic gene signals. Here we show that BioTIP - a tipping-point theory-based analysis - can accurately, robustly, and reliably identify critical transition signals (CTSs). A CTS is a small group of genes with high covariance in expression that mark the cells approaching a bifurcation. We validated its accuracy in the cardiogenesis with known a tipping point and demonstrated the identified CTSs contain verified differentiation-driving transcription factors. We then demonstrated the application on a published mouse gastrulation dataset, validated the predicted CTSs using independent in-vivo samples, and inferred the key developing mesoderm regulator Etv2. Taken together, BioTIP is broadly applicable for the characterization of the plasticity, heterogeneity, and rapid switches in developmental processes, particularly in single-cell data analysis.

HighlightsO_LIIdentifying significant critical transition signals (CTSs) from expression noise
C_LIO_LIA significant CTS contains or is targeted by key transcription factors
C_LIO_LIBioTIP identifies CTSs accurately and independent of trajectory topologies
C_LIO_LISignificant CTSs reproducibly indicate bifurcations across datasets
C_LI


title: The organizer of chromatin topology RIF1 ensures cellular resilience to DNA replication stress.

abstract: Eukaryotic genomes are duplicated from thousands of replication origins that fire sequentially forming a defined spatiotemporal pattern of replication clusters. The temporal order of DNA replication is determined by chromatin architecture and, more specifically, by chromatin contacts that are stabilized by RIF1. Here we show that RIF1 localizes in close proximity to newly synthesized DNA. In cells exposed to the DNA replication inhibitor aphidicolin, suppression of RIF1 markedly decreased the efficacy of protein isolation on nascent DNA (iPOND), suggesting that the iPOND procedure is biased by chromatin topology. RIF1 was required to limit the accumulation of DNA lesions induced by aphidicolin treatment and promoted the recruitment of cohesins in the vicinity of nascent DNA. Collectively, the data suggest that the stabilization of chromatin topology by RIF1 limits replication-associated genomic instability.


title: Independent population coding of the past and the present in prefrontal cortex during learning

abstract:
Medial prefrontal cortex (mPfC) activity represents information about the state of the world, including present behaviour, such as decisions, and the immediate past, such as short-term memory. Unknown is whether information about different states of the world are represented in the same mPfC neural population and, if so, how they are kept distinct. To address this, we analyse here mPfC population activity of rats learning rules in a Y-maze, with self-initiated choice trials to an arm-end followed by a self-paced return during the inter-trial interval (ITI). We find that trial and ITI population activity from the same population fall into different low-dimensional subspaces. These subspaces encode different states of the world: multiple features of the task can be decoded from both trial and ITI activity, but the decoding axes for the same feature are roughly orthogonal between the two task phases, and the decodings are predominantly of features of the present during the trial but features of the preceding trial during the ITI. These subspace distinctions are carried forward into sleep, where population activity is preferentially reactivated in post-training sleep, but differently for activity from the trial and ITI subspaces. Our results suggest that the problem of interference when representing different states of the world is solved in mPfC by population activity occupying different subspaces for the world states, which can be independently decoded by downstream targets and independently addressed by upstream inputs.

Significance statementActivity in the medial prefrontal cortex plays a roles in representing the current and past states of the world. We show that during a maze task the activity of a single population in medial prefrontal cortex represents at least two different states of the world. These representations were sequential and sufficiently distinct that a downstream population could separately read out either state from that activity. Moreover, the activity representing different states is differently reactivated in sleep. Different world states can thus be represented in the same medial prefrontal cortex population, but in such a way that prevents potentially catastrophic interference between them.


title: Activity subspaces in medial prefrontal cortex distinguish states of the world


title: Compensating for a shifting world: evolving reference frames of visual and auditory signals across three multimodal brain areas

abstract:
Stimulus locations are detected differently by different sensory systems, but ultimately they yield similar percepts and behavioral responses. How the brain transcends initial differences to compute similar codes is unclear. We quantitatively compared the reference frames of two sensory modalities, vision and audition, across three interconnected brain areas involved in generating saccades, namely the frontal eye fields (FEF), lateral and medial parietal cortex (M/LIP), and superior colliculus (SC). We recorded from single neurons in head-restrained monkeys performing auditory- and visually-guided saccades from variable initial fixation locations, and evaluated whether their receptive fields were better described as eye-centered, head-centered, or hybrid (i.e. not anchored uniquely to head- or eye-orientation). We found a progression of reference frames across areas and across time, with considerable hybrid-ness and persistent differences between modalities during most epochs/brain regions. For both modalities, the SC was more eye-centered than the FEF, which in turn was more eye-centered than the predominantly hybrid M/LIP. In all three areas and temporal epochs from stimulus onset to movement, visual signals were more eye-centered than auditory signals. In the SC and FEF, auditory signals became more eye-centered at the time of the saccade than they were initially after stimulus onset, but only in the SC at the time of the saccade did the auditory signals become predominantly eye-centered. The results indicate that visual and auditory signals both undergo transformations, ultimately reaching the same final reference frame but via different dynamics across brain regions and time.

New and NoteworthyModels for visual-auditory integration posit that visual signals are eye-centered throughout the brain, while auditory signals are converted from head-centered to eye-centered coordinates. We show instead that both modalities largely employ hybrid reference frames: neither fully head-nor eye-centered. Across three hubs of the oculomotor network (intraparietal cortex, frontal eye field and superior colliculus) visual and auditory signals evolve from hybrid to a common eye-centered format via different dynamics across brain areas and time.


title: DREAM Interrupted: Severing LIN-35-MuvB association in Caenorhabditis elegans impairs DREAM function but not its chromatin localization

abstract: The mammalian pocket protein family, which includes the Retinoblastoma protein (pRb) and Rb-like pocket proteins p107 and p130, regulates entry into and exit from the cell cycle by repressing cell cycle gene expression. Although pRb plays a dominant role in mammalian systems, p107 and p130 are the ancestral pocket proteins. The Rb-like pocket proteins interact with the highly conserved 5-subunit MuvB complex and an E2F-DP transcription factor heterodimer, forming the DREAM (for Dp, Rb-like, E2F, and MuvB) complex. DREAM complex assembly on chromatin culminates in repression of target genes mediated by the MuvB subcomplex. Here, we examined how the Rb-like pocket protein contributes to DREAM formation and function by disrupting the interaction between the sole Caenorhabditis elegans pocket protein LIN-35 and the MuvB subunit LIN-52 using CRISPR/Cas9 targeted mutagenesis. A triple alanine substitution of LIN-52s LxCxE motif severed LIN-35-MuvB association and caused classical DREAM mutant phenotypes, including synthetic multiple vulvae, high-temperature arrest, and ectopic expression of germline genes in the soma. However, RNA-seq revealed limited upregulation of DREAM target genes when LIN-35-MuvB association was severed, as compared to gene upregulation following LIN-35 loss. Based on chromatin immunoprecipitation, disrupting LIN-35-MuvB association did not affect the chromatin localization of E2F-DP, LIN-35, or MuvB components. In a previous study we showed that in worms lacking LIN-35, E2F-DP and MuvB chromatin occupancy was reduced genome-wide. With LIN-35 present but unable to associate with MuvB, our present study suggests that the E2F-DP-LIN-35 interaction promotes E2F-DPs chromatin localization, which we hypothesize supports MuvB chromatin occupancy indirectly through DNA. Altogether, this study highlights how the pocket proteins association with MuvB supports DREAM function but is not required for DREAMs chromatin occupancy.


title: Agonist-independent Prostaglandin EP3 Receptor signaling is required to prevent insulin hypersecretion and metabolic dysfunction in a non-obese mouse model of insulin resistance

abstract:
When homozygous for the LeptinOb mutation (Ob), Black-and-Tan Brachyury (BTBR) mice become morbidly obese and severely insulin resistant, and by 10 weeks of age, frankly diabetic. Previous work has shown Prostaglandin EP3 Receptor (EP3) expression and activity is up-regulated in islets from BTBR-Ob mice as compared to lean controls, actively contributing to their beta-cell dysfunction. In this work, we aimed to test the impact of beta-cell-specific EP3 loss on the BTBR-Ob phenotype by crossing Ptger3 floxed mice with the Rat insulin promoter (RIP)-CreHerr driver strain. Instead, germline recombination of the floxed allele in the founder mouse - an event whose prevalence we identified as directly associated with underlying insulin resistance of the background strain - generated a full-body knockout. Full-body EP3 loss provided no diabetes protection to BTBR-Ob mice, but, unexpectedly, significantly worsened BTBR-lean insulin resistance and glucose tolerance. This in vivo phenotype was not associated with changes in beta-cell fractional area or markers of beta-cell replication ex vivo. Instead, EP3-null BTBR-lean islets had essentially uncontrolled insulin hypersecretion. The selective up-regulation of constitutively-active EP3 splice variants in islets from young, lean BTBR mice as compared to C57BL/6J, where no phenotype of EP3 loss has been observed, provides a potential explanation for the hypersecretion phenotype. In support of this, high islet EP3 expression in Balb/c females vs. Balb/c males was fully consistent with their sexually-dimorphic metabolic phenotype after loss of EP3-coupled Gz protein. Taken together, our findings provide a new dimension to the understanding of EP3 as a critical brake on insulin secretion.

New and NoteworthyIslet Prostaglandin EP3 receptor (EP3) signaling is well-known as up-regulated in the pathophysiological conditions of type 2 diabetes, contributing to beta-cell dysfunction. Unexpected findings in mouse models of non-obese insulin sensitivity and resistance provide a new dimension to our understanding of EP3 as a key modulator of insulin secretion. A previously-unknown relationship between mouse insulin resistance and the penetrance of Rat insulin promoter-driven germline floxed allele recombination is critical to consider when creating beta-cell-specific knockouts.

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category: physiology


title: Prostaglandin EP3 Receptor signaling is required to prevent insulin hypersecretion and metabolic dysfunction in a non-obese mouse model of insulin resistance


title: Curiosity eliminates the exploration-exploitation dilemma

abstract: Balancing exploration with exploitation is seen as a mathematically intractable dilemma that all animals face. In this paper, we provide an alternative view of this classic problem that does not depend on exploring to optimize for reward. We argue that the goal of exploration should be pure curiosity, or learning for learnings sake. Through theory and simulations we prove that explore-exploit problems based on this can be solved by a simple rule that yields optimal solutions: when information is more valuable than rewards, be curious, otherwise seek rewards. We show that this rule performs well and robustly under naturalistic constraints. We suggest three criteria can be used to distinguish our approach from other theories.

category: animal behavior and cognition


title: Embracing curiosity eliminates the exploration-exploitation dilemma


title: Histopathological Study Of Different Organs Of Charles Foster Rats Under The Exposure Of Pueraria tuberosa

abstract: The present study was undertaken to investigate the safe doses of Pueraria tuberosa water extract (PTWE) on different organs. The OECD guidelines 407 of repeated toxicity was followed with respect to the selection of dose and days for different organs. The selected doses of PTWE were 250, 500, 1000 and 2000 mg/kg b wt for 7, 14, 21 and 28 days. Haematoxylin and eosin staining was used to study the morphological alterations in heart, intestine, testis, adrenal gland and spleen. In the present study, no adverse alterations in cardiac fibers of the heart, size and shapes in crypts and villi of intestine, seminiferous tubules and spermatozoa count in testis, three zones of adrenal gland, and spleen were seen in all treated groups of PTWE. There were no adverse morphological alterations found in described organs. The PTWE are safe at 1000 mg/kg b wt. up to 28 days and 2000 mg/ kg b. wt up to 21 days, respectively.

category: pharmacology and toxicology


title: Modeling and Characterization of Inter-Individual Variability in CD8 T Cell Responses in Mice

abstract:
To develop vaccines it is mandatory yet challenging to account for inter-individual variability during immune responses. Even in laboratory mice, T cell responses of single individuals exhibit a high heterogeneity that may come from genetic backgrounds, intra-specific processes (e.g. antigen-processing and presentation) and immunization protocols.

To account for inter-individual variability in CD8 T cell responses in mice, we propose a dynamical model coupled to a statistical, nonlinear mixed effects model. Average and individual dynamics during a CD8 T cell response are characterized in different immunization contexts (vaccinia virus and tumor). On one hand, we identify biological processes that generate inter-individual variability (activation rate of naive cells, the mortality rate of effector cells, and dynamics of the immunogen). On the other hand, introducing categorical covariates to analyze two different immunization regimens, we highlight the steps of the response impacted by immunogens (priming, differentiation of naive cells, expansion of effector cells and generation of memory cells). The robustness of the model is assessed by confrontation to new experimental data.

Our approach allows to investigate immune responses in various immunization contexts, when measurements are scarce or missing, and contributes to a better understanding of inter-individual variability in CD8 T cell immune responses.

category: immunology


title: Binned Relative Environmental Change Indicator (BRECI): A tool to communicate the nature of differences between environmental niche model outputs

abstract: Niche models are now widely used in many branches of the biological sciences and are often used to contrast the distribution of favourable environments between regions or under changes in environmental conditions such as climate change. Evaluating model performance and selecting optimal models is now accepted as best-practice, and a number of methods are available assist this process. One aspect of ENM application which has not received as much attention is developing methods to communicate the degree and nature of changes between model outputs (typically as raster maps). The method described in this paper, Binned Relative Environmental Change Index (BRECI), seeks to address this shortfall in communicating model results.

category: ecology


title: Easy Kinetics: a novel enzyme kinetic characterization software

abstract: Here will be presented the software Easy Kinetics, a publicly available graphical interface that allows rapid evaluation of the main kinetics parameters in an enzyme catalyzed reaction. In contrast to other similar commercial software using algorithms based on non-linear regression models to reach these results, Easy Kinetics is based on a completely different original algorithm, requiring in input the spectrophotometric measurements of {Delta}Abs/min taken twice at only two different substrate concentrations. The results generated show however a significant concordance with those ones obtained with the most common commercial software used for enzyme kinetics characterization, GraphPad Prism 8(C), suggesting that Easy Kinetics can be used for routine tests in enzyme kinetics as an alternative valid software.


title: Subtype-specific and co-occurring genetic alterations in B-cell non-Hodgkin lymphoma

abstract: B-cell non-Hodgkins lymphoma (B-NHL) encompasses multiple clinically and phenotypically distinct subtypes of malignancy with unique molecular etiologies. Common subtypes of B-NHL such as diffuse large B-cell lymphoma (DLBCL) have been comprehensively interrogated at the genomic level. But rarer subtypes such as mantle cell lymphoma (MCL) remain sparsely characterized. Furthermore, multiple B-NHL subtypes have thus far not been comprehensively compared using the same methodology to identify conserved or subtype-specific patterns of genomic alterations. Here, we employed a large targeted hybrid-capture sequencing approach encompassing 380 genes to interrogate the genomic landscapes of 685 B-NHL tumors at high depth; including DLBCL, MCL, follicular lymphoma (FL), and Burkitt lymphoma (BL). We identified conserved hallmarks of B-NHL that were deregulated in the majority of tumor from each subtype, including the frequent genetic deregulation of the ubiquitin proteasome system (UPS). In addition, we identified subtype-specific patterns of genetic alterations, including clusters of co-occurring mutations and DNA copy number alterations. The cumulative burden of mutations within a single cluster were more discriminatory of B-NHL subtypes than individual mutations, implicating likely patterns of genetic cooperation that contribute to disease etiology. We therefore provide the first cross-sectional analysis of mutations and DNA copy number alterations across major B-NHL subtypes and a framework of co-occurring genetic alterations that deregulate genetic hallmarks and likely cooperate in lymphomagenesis.


title: Single EGF mutants unravel the mechanism for stabilization of Epidermal Growth Factor Receptor (EGFR) system

abstract: The Epidermal Growth Factor Receptor (EGFR) is a membrane-anchored tyrosine kinase that is able to selectively respond to multiple extra-cellular stimuli. Previous studies have indicated that the modularity of this system is affected by ligand-induced differences in the stability of the dimerized receptor in a process known as "Biased signaling". However, this hypothesis has not been explored using single-mutant ligands thus far. Herein, we developed a new approach to identify residues responsible for functional divergence combining the conservation and co-evolution information of ortholog and paralog genes encoding the epidermal growth factor (EGF) ligand. Then, we mutated these residues and assessed the mutants effects on the receptor by employing a combination of molecular dynamics (MD) and biochemical techniques. Although the EGF mutants had comparable binding affinities to the wild type ligand for EGFR, the EGF mutants induced a different phosphorylation and cell growth pattern in multiple cell lines. The MD simulations of the EGF mutants show a long-range effect on the receptor dimer interface. For the first time in this study, a single mutation in EGF is shown to be enough to alter the activation of the pathway at the cellular level. These results also support the theory of biased signaling in the tyrosine kinase receptor system and demonstrate a promising new way to study ligand-receptor interactions.

category: bioinformatics


title: Binding of single-mutant epidermal growth factor (EGF) ligands alter the stability of the EGF receptor dimer and promote growth signaling


title: Intramolecular Communication and Allosteric Sites in Enzymes Unraveled by Time-Dependent Linear Response Theory

abstract: It has been an established idea in recent years that protein is a physiochemically connected network. Allostery, understood in this new context, is a manifestation of residue communicating between remote sites in this network, and hence a rising interest to identify functionally relevant communication pathways and the frequent communicators within. However, there have been limited computationally trackable general methods to discover proteins allosteric sites in atomistic resolution with good accuracy. In this study, we devised a time-dependent linear response theory (td-LRT) integrating intrinsic protein dynamics and perturbation forces that excite proteins temporary reconfiguration at the non-equilibrium state, to describe atom-specific time responses as the propagating mechanical signals and discover that the most frequent remote communicators can be important allosteric sites, mutation of which could deteriorate the hydride transfer rate in DHFR by 3 orders. The preferred directionality of the signal propagation can be inferred from the asymmetric connection matrix (CM), where the coupling strength between a pair of residues is suggested by their communication score (CS) in the CM, which is found consistent with experimentally characterized nonadditivity of double mutants. Also, the intramolecular communication centers (ICCs), having high CSs, are found evolutionarily conserved, suggesting their biological importance. We also identify spatially clustered top ICCs as the newly found allosteric site in ATG4B. Among 2016 FDA-approved drugs screened to target the site, two interacting with the site most favorably, confirmed by MD simulations, are found to inhibit ATG4B biochemically and be tumor suppressive in colorectal, pancreatic and breast cancer cell lines with an observed additive therapeutic effect when co-used with an active-site inhibitor.


title: Reproducible microbial community dynamics of two drinking water systems treating similar source waters.

abstract:
Understanding whether the spatial-temporal dynamics of the drinking water microbiome are reproducible in full-scale drinking water systems is an important step towards devising engineering strategies to manipulate it. Yet, direct comparisons across full-scale drinking water systems are challenging because multiple factors, from source water to treatment process choice and configuration, can be unique to each system. This study compared the spatial-temporal dynamics of the drinking water microbiome in two drinking water treatment plants (DWTPs) with identical sequence of treatment strategies treating source waters from the same river system and with treated drinking water distributed in same large-scale (but independent) distribution system (DWDS) with similar disinfectant residual regiment. Dissimilarities in source water communities were tempered by the pre-disinfection treatments, resulting in highly similar post-filtration microbial communities between the two systems. However, high community turnover due to disinfection resulted in highly dissimilar microbial communities in the finished water between the two systems. Interestingly however, the microbial communities in the two systems increased in similarity during transit through the DWDS despite presence of a disinfectant residual. Overall our study finds that the drinking water microbiome demonstrated reproducible spatial and temporal dynamics within both independent but nearly identical DWTPs and their corresponding DWDSs.

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title: Accurate, ultra-low coverage genome reconstruction and association studies in Hybrid Swarm mapping populations

abstract: Genetic association studies seek to uncover the link between genotype and phenotype, and often utilize inbred reference panels as a replicable source of genetic variation. However, inbred reference panels can differ substantially from wild populations in their genotypic distribution, patterns of linkage-disequilibrium, and nucleotide diversity. As a result, associations discovered using inbred reference panels may not reflect the genetic basis of phenotypic variation in natural populations. To address this problem, we evaluated a mapping population design where dozens to hundreds of inbred lines are outbred for few generations, which we call the Hybrid Swarm. The Hybrid Swarm approach has likely remained underutilized relative to pre-sequenced inbred lines due to the costs of genome-wide genotyping. To reduce sequencing costs and make the Hybrid Swarm approach feasible, we developed a computational pipeline that reconstructs accurate whole genomes from ultra-low-coverage (0.05X) sequence data in Hybrid Swarm populations derived from ancestors with phased haplotypes. We evaluate reconstructions using genetic variation from the Drosophila Genetic Reference Panel as well as variation from neutral simulations. We compared the power and precision of GWAS using the Hybrid Swarm, inbred lines, recombinant inbred lines, and highly outbred populations across a range of allele frequencies, effect sizes, and genetic architectures. Our simulations show that these different mapping panels vary in their power and precision, largely depending on the architecture of the trait. The Hybrid Swam and RILs outperform inbred lines for quantitative traits, but not for monogenic ones. Taken together, our results demonstrate the feasibility of the Hybrid Swarm as a cost-effective method of fine-scale genetic mapping.


title: Artisanal and farmers bread making practices differently shape fungal species diversity in French sourdoughs

abstract: Preserving microbial diversity in food systems is one of the many challenges to be met to achieve food security and quality. Although industrialization led to the selection and spread of specific fermenting microbial strains, there are still ongoing artisanal processes that may allow the conservation of a wider diversity of microbial species. We examined whether the diversity of artisanal practices could lead to an increased level in fungal species diversity for bread making. We used an interdisciplinary participatory research approach including bakers, psycho-sociologists and microbiologists to analyse French bread making practices and describe fungal communities in naturally fermented sourdough of 27 bakers and 12 farmer bakers. Their bread making practices were classified in two groups: the farmer- like practices group and the artisanal-like practices group. Surprisingly, the well-known bakery yeast, Saccharomyces cerevisiae, was dominant (i.e. with a relative abundance over 50%) in only 24% of sourdoughs while other yeast species of the closely related Kazachstania genus were dominant in 54% of sourdoughs. Bread making practices were found to drive the distribution of yeast species. The most remarkable difference was the occurrence of Kazachstania humilis in sourdoughs made with artisanal- like practices and the occurrence of Kazachstania bulderi in sourdoughs made with farmer-like practices. Phenotyping of these two species in laboratory sourdough mimicking media revealed signatures of domestication for K. humilis but not for K. bulderi. Overall, our results showed that preserving bread making practices diversity allows the preservation of a higher taxonomic and phenotypic diversity in microbial communities.


title: Estimation of Speciation Times Under the Multispecies Coalescent

abstract:
MotivationThe coalescent model is now widely accepted as an effective model for incorporating variation in the evolutionary histories of individual genes into methods for phylogenetic inference from genome-scale data. However, because model-based analysis under the coalescent can be computationally expensive for large data sets, a variety of inferential frameworks and corresponding algorithms have been proposed for estimation of species-level phylogenies and the associated parameters, including the speciation times and effective population sizes.

ResultsWe consider the problem of estimating the timing of speciation events along a phylogeny in a coalescent framework. We propose a maximum a posteriori estimator based on composite likelihood (MAPCL) for inferring these speciation times under a model of DNA sequence evolution for which exact site pattern probabilities can be computed. We demonstrate that the MAPCL estimates are statistically consistent and asymptotically normally distributed, and we show how this result can be used to estimate their asymptotic variance. We also provide a more computationally efficient estimator of the asymptotic variance based on the nonparametric bootstrap. We evaluate the performance of our method using simulation and by application to an empirical dataset for gibbons.

Availability and implementationThe method has been implemented in the PAUP* program, freely available at https://paup.phylosolutions.com for Macintosh, Windows, and Linux operating systems.

Contactpeng.650@osu.edu

Supplementary informationSupplementary data are available at Bioinformatics online.

category: evolutionary biology


title: Formation of synthetic RNP granules using engineered phage-coat-protein -RNA complexes

abstract:
Observations of RNA-protein (RNP) granules within living cells have generated important insights on intracellular processes in recent years. Here, we demonstrate that PP7-coat protein (PCP) and Q{beta}-coat protein (QCP) co-expressed with synthetic long non-coding RNA (slncRNA) encoded with multiple CP binding sites self-assemble into phase-separated synthetic RNP (SRNP) granules within E. coli cells and in vitro. SNRP granules exhibit hallmarks of RNP granule formation including phase separation from a semi-dilute liquid in vitro, and retention of structure after cell lysis. In vivo real-time tracking of SRNP granules reveals that they are found in cell poles of exponentially growing cells, and that their structure exhibits gel-like properties by the slow stochastic insertion and shedding of CP-slncRNA complexes. We propose a transcriptional model that takes into account the cytosolic structure of E. coli (i.e., the cytosol is divided into a biomolecularly dense domain in the nucleoid-dominated region and a dilute liquid domain in the polar regions), and use it to provide a theoretical framework for explaining the increase in intracellular CP-titer as a function slncRNA structure, and the appearance of SRNP granules in non-polar regions of stationary phase cells. Consequently, the SRNP-granule data and resultant model has implications for various bacterial transcriptional and translational processes, and provides an alternative explanation for the super-Poisson kinetics attributed to transcriptional bursts.

Introductory paragraphsynthetic long non-coding RNA molecules encoded with multiple phage coat protein binding sites form phase separated RNP granules when co-expressed with their cognate binding proteins.

category: biophysics


title: Complement C3 and C3aR mediate different aspects of emotional behaviours; relevance to risk for psychiatric disorder

abstract: Complement is a key component of the immune system with roles in inflammation and host-defence. Here we reveal novel functions of complement pathways impacting on emotional reactivity of potential relevance to the emerging links between complement and risk for psychiatric disorder. We used mouse models to assess the effects of manipulating components of the complement system on emotionality. Mice lacking the complement C3a Receptor (C3aR-/-) demonstrated a selective increase in unconditioned (innate) anxiety whilst mice deficient in the central complement component C3 (C3-/-) showed a selective increase in conditioned (learned) fear. The dissociable behavioural phenotypes were linked to different signalling mechanisms. Effects on innate anxiety were independent of C3a, the canonical ligand for C3aR, consistent with the existence of an alternative ligand mediating innate anxiety, whereas effects on learned fear were due to loss of iC3b/CR3 signalling. Our findings show that specific elements of the complement system and associated signalling pathways contribute differentially to heightened states of anxiety and fear commonly seen in psychopathology.

category: neuroscience


title: Deconvoluting signals downstream of growth and immune receptor kinases by phosphocodes of the BSU1 family phosphatases

abstract: Hundreds of leucine-rich repeat receptor kinases (LRR-RKs) have evolved to control diverse processes of growth, development, and immunity in plants; the mechanisms that link LRR-RKs to distinct cellular responses are not understood. Here we show that two LRR-RKs, the brassinosteroid hormone receptor BRI1 (BRASSINOSTEROID INSENSITIVE 1) and the flagellin receptor FLS2 (FLAGELLIN SENSING 2), regulate downstream glycogen synthase kinase 3 (GSK3) and mitogen-activated protein (MAP) kinases, respectively, through phosphocoding of the BRI1-SUPPRESSOR1 (BSU1) phosphatase. BSU1 was previously identified as a component that inactivates GSK3s in the BRI1 pathway. We found surprisingly that loss of the BSU1 family phosphatases activates effector-triggered immunity (ETI) and impairs flagellin-triggered MAP kinase activation and immunity. The flagellin-activated BOTRYTIS-INDUCED KINASE 1 (BIK1) phosphorylates BSU1 at serine-251. Mutation of serine-251 reduces the ability of BSU1 to mediate flagellin-induced MAP kinase activation and immunity, but not its abilities to suppress ETI and interact with GSK3, which is enhanced through the phosphorylation of BSU1 at serine-764 upon brassinosteroid signaling. These results demonstrate that BSU1 plays an essential role in immunity and transduces brassinosteroid-BRI1 and flagellin-FLS2 signals using different phosphorylation sites. Our study illustrates that phosphocoding in shared downstream components provides signaling specificities for diverse plant receptor kinases.

category: plant biology


title: The whale shark genome reveals patterns of vertebrate gene family evolution

abstract: Chondrichthyes (cartilaginous fishes) are fundamental for understanding vertebrate evolution, yet their genomes are understudied. We report long-read sequencing of the whale shark genome to generate the best gapless chondrichthyan genome assembly yet with higher contig contiguity than all other cartilaginous fish genomes, and studied vertebrate genomic evolution of ancestral gene families, immunity, and gigantism. We found a major increase in gene families at the origin of gnathostomes (jawed vertebrates) independent of their genome duplication. We studied vertebrate pathogen recognition receptors (PRRs), which are key in initiating innate immune defense, and found diverse patterns of gene family evolution, demonstrating that adaptive immunity in gnathostomes did not fully displace germline-encoded PRR innovation. We also discovered a new Toll-like receptor (TLR29) and three NOD1 copies in the whale shark. We found chondrichthyan and giant vertebrate genomes had decreased substitution rates compared to other vertebrates, but gene family expansion rates varied among vertebrate giants, suggesting substitution and expansion rates of gene families are decoupled in vertebrate genomes. Finally, we found gene families that shifted in expansion rate in vertebrate giants were enriched for human cancer-related genes, consistent with gigantism requiring adaptations to suppress cancer.


title: CHD4-NURD controls mouse neonate spermatogonia survival

abstract: Testis development and sustained germ cell production in adults rely on the establishment and maintenance of spermatogonia stem cells and their proper differentiation into spermatocytes. Chromatin remodeling complexes regulate critical processes during gamete development by restricting or promoting accessibility of DNA repair and gene expression machineries to the chromatin. Here, we investigated the role of CHD4 and CHD3 catalytic subunits of the NURD complex during spermatogenesis. Germ cell-specific deletion of Chd4 early in gametogenesis, but not Chd3, resulted in arrested early gamete development due to failed cell survival of neonate undifferentiated spermatogonia stem cell population. Candidate assessment revealed that CHD4 controls expression of Dmrt1 and its downstream target Plzf, both described as prominent regulators of spermatogonia stem cell maintenance. Our results show the requirement of CHD4 in mammalian gametogenesis pointing to functions in gene expression early in the process.


title: Mouse CHD4-NURD is required for spermatogonia survival and normal meiotic progression


title: Mouse CHD4-NURD is required for neonatal spermatogonia survival and normal gonad development


title: MERTK on mononuclear phagocytes regulates T cell antigen recognition at autoimmune and tumor sites

abstract: Understanding mechanisms of immune regulation is key to developing immunotherapies for autoimmunity and cancer. We examined the role of mononuclear phagocytes during peripheral T cell regulation in type 1 diabetes and melanoma. MERTK expression and activity in mononuclear phagocytes in the pancreatic islets, promoted islet T cell regulation, resulting in reduced sensitivity of T cell scanning for cognate antigen in pre-diabetic islets. MERTK-dependent regulation led to reduced T cell activation and effector function at the disease site in the islets and prevented rapid progression of type 1 diabetes. In human islets, MERTK-expressing cells were increased in remaining insulin-containing islets of type 1 diabetic patients, suggesting that MERTK protects the islets from autoimmune destruction. MERTK also regulated T cell arrest in melanoma tumors. These data indicate that MERTK signaling in mononuclear phagocytes drives T cell regulation at inflammatory disease sites in peripheral tissues through a mechanism that reduces the sensitivity of scanning for antigen leading to reduced responsiveness to antigen.


title: Label-retention expansion microscopy

abstract: Expansion microscopy (ExM) increases the effective resolving power of any microscope by expanding the sample with swellable hydrogel. Since its invention, ExM has been successfully applied to a wide range of cell, tissue and animal samples. Still, fluorescence signal loss during polymerization and digestion limits molecular-scale imaging using ExM. Here we report the development of label-retention ExM (LR-ExM) with a set of trifunctional anchors that not only prevent signal loss but also enable high-efficiency labeling using SNAP and CLIP tags. We have demonstrated multicolor LR-ExM for a variety of subcellular structures. Combining LR-ExM with super-resolution Stochastic Optical Reconstruction Microscopy (STORM), we have achieved molecular resolution in the visualization of polyhedral lattice of clathrin-coated pits in situ.

category: bioengineering


title: A novel metric reveals previously unrecognized distortion in dimensionality reduction of scRNA-Seq data

abstract: High-dimensional data are becoming increasingly common in nearly all areas of science. Developing approaches to analyze these data and understand their meaning is a pressing issue. This is particularly true for single-cell RNA-seq (scRNA-seq), a technique that simultaneously measures the expression of tens of thousands of genes in thousands to millions of single cells. The emerging consensus for analysis workflows significantly reduces the dimensionality of the dataset before performing downstream analysis, such as assignment of cell types. One problem with this approach is that dimensionality reduction can introduce substantial distortion into the data; consider the familiar example of trying to represent the three-dimensional earth as a two-dimensional map. It is currently unclear if such distortion affects analysis of scRNA-seq data. Here, we introduce a straightforward approach to quantifying this distortion by comparing the local neighborhoods of points before and after dimensionality reduction. We found that popular techniques like t-SNE and UMAP introduce substantial distortion even for relatively simple simulated data sets. For scRNA-seq data, we found the distortion in local neighborhoods was often greater than 95% in the representations typically used for downstream analyses. This level of distortion can introduce errors into cell type identification, pseudotime ordering, and other analyses. We found that principal component analysis can generate accurate embeddings, but only when using dimensionalities that are much higher than typically used in scRNA-seq analysis. Our work suggests the need for a new generation of dimensional reduction algorithms that can accurately embed high dimensional data in its true latent dimension.


title: Epithelial-Mesenchymal Plasticity is regulated by inflammatory signalling networks coupled to cell morphology.

abstract:
Morphology dictates how cells sense physical and soluble cues in their environment; thus contributing to fate decisions. The differentiation of epithelial cells into mesenchymal forms, or epithelial-mesenchymal plasticity (EMP), is essential for metazoan development and homeostasis. Here we show that the decision to engage EMP is coupled to cell morphology by cell-cell adhesions by microtubule and nuclear organization (MTNO). Using an integrative  omic approach we identify Junctional Adhesion Molecule 3 (JAM3) as a new tumour suppressor in breast cancer patients. JAM3 depletion in epithelial cells alters MTNO and causes differentiation into mesenchymal forms. Soluble TGF{beta} also changes MTNO, and synergizes with JAM3 depletion to promote mesenchymal morphogenesis. Through systematic proteomic analysis we show that changes in MTNO lead to the upregulation of an inflammatory signalling network where YAP/TAZ, FOXO, IKK-NFKB, and JNK pathways are active; but where insulin signalling is suppressed. The actions of the MT-motor Kinesin-1 serve to both change MTNO and promote the upregulation of the core EMP network. Critically, the upregulation of the EMP network predicts the mesenchymal state across cancers.

Graphical Abstract

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category: systems biology


title: A minimal model of neural computation with dendritic plateau potentials.

abstract: AO_SCPLOWBSTRACTC_SCPLOWOver the last two decades, advances in neurobiology have established the essential role of active processes in neural dendrites for almost every aspect of cognition, but how these processes contribute to neural computation remains an open question. We show how two kinds of events within the dendrite, synaptic spikes and localized dendritic plateau potentials, interact on two distinct timescales to give rise to a powerful model of neural computation. In this theoretical model called dendritic plateau computation, a neurons computational function is determined by the compartmentalization of its dendritic tree into functionally independent but mutually coupled segments. We demonstrate the versatility of this mechanism in a simulated navigation experiment, where it allows an individual neuron to reliably detect a specific movement trajectory over hundreds of milliseconds with a high tolerance for timing variability. We conclude by discussing the implications of this model for our understanding of neural computation.