title: Manifold learning analysis suggests novel strategies for aligning single-cell multi-modalities and revealing functional genomics for neuronal electrophysiology

abstract: Recent single-cell multi-modal data reveal multi-scale characteristics of single cells, such as transcriptomics, morphology, and electrophysiology. However, our understanding of functional genomics and gene regulation leading to various cellular characteristics remains elusive. To address this, we applied multiple machine learning methods to align gene expression and electrophysiological data of single neuronal cells in the mouse brain. We found that nonlinear manifold learning outperforms other methods. After manifold alignment, the cell clusters highly correspond to transcriptomic and morphological cell-types, suggesting a strong nonlinear relationship between gene expression and electrophysiology at the cell-type level. The aligned cells form developmental trajectories and show continuous changes of electrophysiological features, implying the underlying developmental process. We also found that the manifold-aligned cell clusters differentially expressed genes can predict many electrophysiological features. Functional enrichment and gene regulatory network analyses for those cell clusters revealed potential genome functions and molecular mechanisms from gene expression to neuronal electrophysiology.


title: A-to-I mRNA editing in a ferric siderophore receptor improves competition for iron in Xanthomonas oryzae

abstract: Adenosine-to-inosine (A-to-I) RNA editing, which is catalyzed by the adenosine deaminase RNA-specific family of enzymes, is a frequent post-transcriptional modification in metazoans. Research on A-to-I editing in bacteria is limited, and the importance is underestimated. In this study, we show that bacteria may use A-to-I editing as an alternative strategy to promote uptake of metabolic iron. The T408A editing event of xfeA in Xanthomonas oryzae pv. oryzicola (Xoc) senses extracytoplasmic iron and changes the hydrogen bonding network of ligand channel domains. The frequency of A-to-I RNA editing during iron-deficient conditions increased by 76.87%, which facilitated the passage of iron through the XfeA outer membrane channel. When bacteria were subjected to high iron concentrations, the percentage of A-to-I editing in xfeA decreased, which reduced iron transport via XfeA. Furthermore, A-to-I RNA editing increased expression of multiple genes in the chemotaxis pathway, including methyl-accepting chemotaxis proteins (MCPs) that sense concentrations of exogenous ferric enterobactin (Fe-Ent) at the cytoplasmic membrane. A-to-I RNA editing helps Xoc move towards an iron-rich environment and supports our contention that editing in xfeA facilitates entry of a ferric siderophore. Overall, our results reveal a new signaling mechanism that bacteria use to facilitate iron uptake and improve their competitiveness.

category: microbiology


title: Dynamics of cell mass and size control in multicellular systems and the human body

abstract: Cellular processes, in particular homeostasis and growth, require an intricate and complex exchange of matter between a cell and its surroundings. Yet experimental difficulties have prevented a detailed description of the dynamics of a cells mass and volume along different cellular processes, limiting our understanding of cell physiology in health and disease. It has been recently observed that single mammalian cells fluctuate their mass in a timescale of seconds. This result challenges central and long-standing cell growth models, according to which cells increase their mass either linearly or exponentially throughout the cell cycle. However, it remains unclear to what extent cell mass fluctuations may be sustained in multicellular organisms. Here I provide a mathematical model for cell mass fluctuations and explore how such fluctuations can be successfully sustained in multicellular organisms. I postulate that cells do not synchronise their mass fluctuations, but they are executed with their phases uniformly distributed. I derive a mathematical expression to estimate the resulting mass shift between fluid compartments in an organism due to cell mass fluctuations. Together with a new estimate of 4x1013 human cells in the body, I demonstrate that my hypothesis leads to shifts of mass between the intracellular and extracellular fluid compartments in the human body that are approximately or smaller than 0.25 mg and, therefore, perfectly viable. The proposed model connects cell physiology with information theory and entropy.

category: cell biology


title: Leveraging auxiliary data from arbitrary distributions to boost GWAS discovery with Flexible cFDR

abstract:
Genome-wide association studies (GWAS) have identified thousands of genetic variants that are associated with complex traits. However, a stringent significance threshold is required to identify robust genetic associations. Leveraging relevant auxiliary covariates has the potential to boost statistical power to exceed the significance threshold. Particularly, abundant pleiotropy and the non-random distribution of SNPs across various functional categories suggests that leveraging GWAS test statistics from related traits and/or functional genomic data may boost GWAS discovery. While type 1 error rate control has become standard in GWAS, control of the false discovery rate can be a more powerful approach. The conditional false discovery rate (cFDR) extends the standard FDR framework by conditioning on auxiliary data to call significant associations, but current implementations are restricted to auxiliary data satisfying specific parametric distributions, typically GWAS p-values for related traits. We relax these distributional assumptions, enabling an extension of the cFDR framework that supports auxiliary covariates from arbitrary continuous distributions ("Flexible cFDR"). Our method can be applied iteratively, thereby supporting multi-dimensional covariate data. Through simulations we show that Flexible cFDR increases sensitivity whilst controlling FDR after one or several iterations. We further demonstrate its practical potential through application to an asthma GWAS, leveraging various functional genomic data to find additional genetic associations for asthma, which we validate in the larger, independent, UK Biobank data resource.

Author summaryGenome-wide association studies (GWAS) detect regions of the human genome that are associated with various traits, including complex diseases, but the power to detect these genomic regions is currently limited by sample size. The conditional false discovery rate (cFDR) provides a tool to leverage one GWAS study to improve power in another. The motivation is that if two traits have some genetic correlation, then our interpretation of a low but not significant p-value for the trait of interest will differ depending on whether that SNP shows strong or absent evidence of association with the related trait. Here, we describe an extension to the cFDR framework, called "Flexible cFDR", that controls the FDR and supports auxiliary data from arbitrary distributions, surpassing current implementations of cFDR which are restricted to leveraging GWAS p-values from related traits. In practice, our method can be used to iteratively leverage various types of functional genomic data with GWAS data to increase power for GWAS discovery. We describe the use of Flexible cFDR to supplement data from a GWAS of asthma with auxiliary data from functional genomic experiments. We identify associations novel to the original GWAS and validate these discoveries with reference to a larger, more highly-powered GWAS of asthma.

category: genetics


title: CYRI-A regulates macropinocytic cup maturation and mediates integrin uptake, limiting invasive migration

abstract: The Scar/WAVE complex is the major driver of actin nucleation at the plasma membrane, resulting in lamellipodia and membrane ruffles. While lamellipodia aid migration, membrane ruffles can generate macropinosomes - cup-like structures - important for nutrient uptake and regulation of cell surface receptor levels. How macropinosomes are formed and the role of the actin machinery in their formation and resolution is still not well understood. Mammalian CYRI-B is a recently described negative regulator of the Scar/WAVE complex by RAC1 sequestration, but its other paralogue, CYRI-A has not been characterised. Here we implicate CYRI-A as a key regulator of macropinosome maturation and integrin internalisation from the cell surface. We find that CYRI-A is recruited to nascent macropinosomes in a transient but distinct burst, downstream of PIP3-mediated RAC1 activation and the initial burst of actin assembly driving cup formation, but upstream of internalisation and RAB5 recruitment to the macropinosome. Together, our data place CYRI-A as a local suppressor of actin dynamics, enabling the resolution of the macropinocytic cup. The failure of CYRI-depleted cells to resolve their macropinocytic cups results in reduced integrin a5b1 internalisation, leading to enhanced spreading, invasive behaviour and anchorage-independent 3D growth. We thus describe a new role for CYRI-A as a highly dynamic regulator of RAC1 activity at macropinosomes, modulating homeostasis of integrin surface presentation, with important functional consequences.


title: Activation of central 5HT2A receptor in brain inhibited the seizure-induced respiratory arrest in the DBA/1 mouse SUDEP model

abstract: Sudden unexpected death in epilepsy (SUDEP) is the leading cause of death among epilepsy patients, occurring even more frequently in cases with anti-epileptic drug resistance. However, the underlying mechanism of SUDEP remains elusive. Our previous study demonstrated that enhancement of serotonin (5-HT) synthesis by intraperitoneal (IP) injection of 5-hydroxytryptophan (5-HTP) significantly reduced the incidence of seizure-induced respiratory arrest (S-IRA) in a DBA/1 mouse SUDEP model. Given that the 5-HT2A receptor (5-HT2AR) plays an important role in mediating the respiration system in the brain, we hypothesized that 5-HT2AR plays a key role in S-IRA and SUDEP. To test this hypothesis, we examined whether the decreased incidence of S-IRA evoked by either acoustic stimulation or pentylenetetrazole (PTZ) injection following 5-HTP administration will be blocked by treatment with ketanserin (KET), a selective antagonist of 5HT2AR, in the DBA/1 mouse SUDEP model. We observed that the reduction in S-IRA by 5-HTP was significantly reversed by IP or intracerebroventricular injection of KET. Considering the localization of 5-HT2AR in the pre-Botzinger complex (PBC), which plays a key role in regulating respiratory rhythm, we next examined whether KET acts on 5-HT2AR in the PBC. To test this hypothesis, we activated the neural circuit between the dorsal raphe nucleus (DR) and PBC using optogenetics technology. We observed that stimulation of TPH2-ChETA-expressing neurons in the DR reduced the incidence of S-IRA evoked by PTZ, and this suppressant effect was significantly reversed by administration of KET in the bilateral PBC with no changes in electroencephalogram activity. The neural circuit between the DR and PBC was confirmed by injection of cholera toxin subunit B555 (CTB-555), a nerve tracer, in the DR or PBC separately. Calcium signaling evoked by PTZ within neurons of the PBC during seizures was significantly reduced by photostimulation of the DR. Taken together, our findings suggest that 5-HT2AR plays a critical role in regulating S-IRA and targeting the serotonergic neural circuit between the DR and PBC is a promising approach to preventing SUDEP.

category: neuroscience


title: Optogenetic activation of the neural circuit between dorsal raphe nucleus and the pre-Botzinger complex contributes to inhibition of the seizure-induced respiratory arrest in the DBA/1 mouse SUDEP model


title: Optogenetic activation of the serotonergic neural circuit between dorsal raphe nucleus and the pre-Botzinger complex contributes to inhibition of the seizure-induced respiratory arrest in the DBA/1 mouse SUDEP model


title: Optogenetic activation of the serotonergic neural circuit between dorsal raphe nucleus and the pre-Bötzinger complex contributes to inhibition of the seizure-induced respiratory arrest in the DBA/1 mouse SUDEP model


title: Genomic surveillance for multidrug-resistant or hypervirulent Klebsiella pneumoniae among bloodstream isolates at a United States academic medical center

abstract:
BackgroundKlebsiella pneumoniae (K. pneumoniae) strains have been divided into two major categories: classical K. pneumonia, which are frequently multidrug-resistant and cause hospital-acquired infections in patients with impaired defenses, and hypervirulent K. pneumoniae, which cause severe disseminated community-acquired infections in immunologically normal hosts. Both types of infections may lead to bacteremia and are associated with significant morbidity and mortality. The relative burden of these two types of K. pneumoniae among bloodstream isolates within the United States is not well understood.

MethodsWe examined consecutive K. pneumoniae isolates cultured from the blood of hospitalized patients at Northwestern Memorial Hospital (NMH) in Chicago, Illinois April 2015 - April 2017. Bloodstream isolates underwent whole genome sequencing, and clinically relevant data (sequence type [ST], capsule loci, virulence factors, and antimicrobial resistance genes) were inferred from the genome using the bioinformatic tools Kleborate and Kaptive. Patient demographic, comorbidity, and infection information, as well as phenotypic antimicrobial resistance of the isolate were extracted from the electronic medical record. Candidate hypervirulent isolates were tested in a murine model of pneumonia. Complete genome sequences of these candidate hypervirulent isolates were obtained and plasmid content was evaluated.

ResultsK. pneumoniae bloodstream isolates (n=104) from NMH were highly diverse consisting of 75 distinct STs and 51 unique capsule loci. The majority of these isolates (n=58, 55.8%) were susceptible to all tested antibiotics except ampicillin, but 17 (16.3%) were multidrug-resistant. A total of 32 (30.8%) of these isolates were STs of known high-risk clones, including ST258 and ST45. In particular, 18 (17.3%) were resistant to ceftriaxone, 17 harbored extended-spectrum beta-lactamases, and 9 (8.7%) were resistant to meropenem. Four (3.8%) of the 104 isolates were hypervirulent K. pneumoniae, as evidenced by hypermucoviscous phenotypes, high levels of virulence in a murine model of pneumonia, and the presence of large plasmids similar to characterized hypervirulence plasmids. Of particular concern, several of these plasmids contained tra conjugation loci suggesting the potential for transmission. Two of these hypervirulent strains belonged to the well characterized ST23 lineage and one to the emerging ST66 lineage.

ConclusionsWhile NMH K. pneumoniae bloodstream infections are caused by highly diverse strains, the most prevalent STs were those of multidrug-resistant high-risk clones. A small number of hypervirulent K. pneumoniae were observed in patients with no recent travel history, suggesting that these isolates are undergoing community spread in the United States.


title: Sinorhizobium meliloti functions required for resistance to antimicrobial NCR peptides and bacteroid differentiation

abstract:
Legumes of the Medicago genus form symbiosis with the bacterium Sinorhizobium meliloti and develop root nodules housing large numbers of the intracellular symbionts. Members of the Nodule-specific Cysteine Rich peptide (NCRs) family induce the endosymbionts into a terminal differentiated state. Individual cationic NCRs are antimicrobial peptides that have the capacity to kill the symbiont but the nodule cell environment prevents killing. Moreover, the bacterial broad-specificity peptide uptake transporter BacA and exopolysaccharides contribute to protect the endosymbionts against the toxic activity of NCRs. Here, we show that other S. meliloti functions participate in the protection of the endosymbionts, including an additional broad-specificity peptide uptake transporter encoded by the yejABEF genes, lipopolysaccharide modifications mediated by lpsB and lpxXL as well as rpoH1, encoding a stress sigma factor. Mutants of these genes show in vitro a strain-specific increased sensitivity profile against a panel of NCRs and form nodules in which bacteroid differentiation is affected. The lpsB mutant nodule bacteria do not differentiate, the lpxXL and rpoH1 mutants form some seemingly fully differentiated bacteroids although most of the nodule bacteria are undifferentiated, while the yejABEF mutants form hypertrophied but nitrogen-fixing bacteroids. The nodule bacteria of all the mutants have a strongly enhanced membrane permeability, which is dependent on the transport of NCRs to the endosymbionts. Our results suggest that S. meliloti relies on a suite of functions including peptide transporters, the bacterial envelope structures and stress response regulators to resist the aggressive assault of NCR peptides in the nodule cells.

ImportanceThe nitrogen fixing symbiosis of legumes with rhizobium bacteria has a predominant ecological role in the nitrogen cycle and has the potential to provide the nitrogen required for plant growth in agriculture. The host plants allow the rhizobia to colonize specific symbiotic organs, the nodules, in large numbers in order to produce sufficient reduced nitrogen for the plant needs. Some legumes, including Medicago spp., produce massively antimicrobial peptides to keep this large bacterial population in check. These peptides, known as NCRs, have the potential to kill the rhizobia but in nodules, they rather inhibit the division of the bacteria, which maintain a high nitrogen fixing activity. In this study, we show that the tempering of the antimicrobial activity of the NCR peptides in the Medicago symbiont Sinorhizobium meliloti is multifactorial and requires the YejABEF peptide transporter, the lipopolysaccharide outer membrane composition and the stress response regulator RpoH1.


title: Social network architecture and the tempo of cumulative cultural evolution

abstract: The ability to build upon previous knowledge--cumulative cultural evolution--is a hallmark of human societies. While cumulative cultural evolution depends on the interaction between social systems, cognition and the environment, there is increasing evidence that cumulative cultural evolution is facilitated by larger and more structured societies. However, such effects may be interlinked with patterns of social wiring, thus the relative importance of social network architecture as an additional factor shaping cumulative cultural evolution remains unclear. By simulating innovation and diffusion of cultural traits in populations with stereotyped social structures, we disentangle the relative contributions of network architecture from those of population size and connectivity. We demonstrate that while more structured networks, such as those found in multilevel societies, can promote the recombination of cultural traits into high-value products, they also hinder spread and make products more likely to go extinct. We find that transmission mechanisms are therefore critical in determining the outcomes of cumulative cultural evolution. Our results highlight the complex interaction between population size, structure and transmission mechanisms, with important implications for future research.

category: evolutionary biology


title: Task dependence of neural representations of scene attributes but not scene categories in the prefrontal cortex

abstract:
Natural scenes deliver rich sensory information about the world. Decades of research has shown that the scene-selective network in the visual cortex represents various aspects of scenes. However, less is known about how such complex scene information is processed beyond the visual cortex, such as in the prefrontal cortex. It is also unknown how task context impacts the process of scene perception, modulating which scene content is represented in the brain. In this study, we investigate these questions using scene images from four natural scene categories, which also depict two types of scene attributes, temperature (warm or cold), and sound level (noisy or quiet). A group of healthy human subjects from both sexes participated in the present study using fMRI. In the study, participants viewed scene images under two different task conditions; temperature judgment and sound-level judgment. We analyzed how these scene attributes and categories are represented across the brain under these task conditions. Our findings show that scene attributes (temperature and sound-level) are only represented in the brain when they are task-relevant. However, scene categories are represented in the brain, in both the parahippocampal place area and the prefrontal cortex, regardless of task context. These findings suggest that the prefrontal cortex selectively represents scene content according to task demands, but this task selectivity depends on the types of scene content; task modulates neural representations of scene attributes but not of scene categories.

Significance statementResearch has shown that visual scene information is processed in scene-selective regions in the occipital and temporal cortices. Here, we ask how scene content is processed and represented beyond the visual brain, in the prefrontal cortex (PFC). We show that both scene categories and scene attributes are represented in PFC, with interesting differences in task dependency: Scene attributes are only represented in PFC when they are task-relevant, but scene categories are represented in PFC regardless of the task context. Taken together, our work shows that scene information is processed beyond the visual cortex, and scene representation in PFC reflects how adaptively our minds extract relevant information from a scene.


title: The ascending arousal system promotes optimal performance through meso-scale network integration in a visuospatial attentional task

abstract:
Previous research has shown that the autonomic nervous system provides essential constraints over ongoing cognitive function. However, there is currently a relative lack of direct empirical evidence for how this interaction manifests in the brain at the macro-scale level. Here, we examine the role of ascending arousal and attentional load on large-scale network dynamics by combining pupillometry, functional MRI and graph theoretical analysis to analyze data from a visual motion-tracking task with a parametric load manipulation. We found that attentional load effects were observable in measures of pupil diameter and in a set of brain regions that parametrically modulated their BOLD activity and meso-scale network-level integration. In addition, the regional patterns of network reconfiguration were correlated with the spatial distribution of the 2a adrenergic receptor. Our results further solidify the relationship between ascending noradrenergic activity, large-scale network integration, and cognitive task performance.

Author SummaryIn our daily lives, it is usual to encounter highly demanding cognitive tasks. They have been traditionally regarded as challenges that are solved mainly through cerebral activity, specifically via information-processing steps carried by neurons in the cerebral cortex. Activity in cortical networks thus constitutes a key factor for improving our understanding cognitive processes. However, recent evidence has shown that evolutionary older players in the central nervous system, such as brainstems ascending modulatory systems, might play an equally important role in diverse cognitive mechanisms. Our article examines the role of the ascending arousal system on large-scale network dynamics by combining pupillometry, functional MRI and graph theoretical analysis.


title: Distinct neural representations of content and ordinal structure in auditory sequence memory

abstract: Two forms of information - frequency (content) and ordinal position (structure) - have to be stored when retaining a sequence of auditory tones in working memory (WM). However, the neural representations and coding characteristics of content and structure, particularly during WM maintenance, remain elusive. Here, in two electroencephalography (EEG) studies, by transiently perturbing the  activity-silent WM retention state and decoding the reactivated WM information, we demonstrate that content and structure are stored in a dissociative manner with distinct characteristics throughout WM process. First, each tone in the sequence is associated with two codes in parallel, characterizing its frequency and ordinal position, respectively. Second, during retention, a structural retrocue successfully reactivates structure but not content, whereas a following white noise triggers content but not structure. Third, structure representation remains stable whereas content code undergoes a dynamic transformation through memory progress. Finally, the noise-triggered content reactivations during retention correlate with subsequent WM behavior. Overall, our results support distinct content and structure representations in auditory WM and provide a novel approach to access the silently stored WM information in the human brain. The dissociation of content and structure could facilitate efficient memory formation via generalizing stable structure to new auditory contents.


title: Granzyme B prevents aberrant IL-17 production and intestinal pathogenicity in CD4+ T cells

abstract: CD4+ T cell activation and differentiation are important events that set the stage for proper immune responses. Many factors are involved in the activation and differentiation of T cells, and these events are tightly controlled to prevent unwanted and/or exacerbated immune responses that may harm the host. It has been well documented that granzyme B, a potent serine protease involved in cell-mediated cytotoxicity, is readily expressed by certain CD4+ T cells, such as regulatory T cells and CD4+CD8+ intestinal intraepithelial lymphocytes, both of which display cytotoxicity associated with granzyme B. However, because not all CD4+ T cells expressing granzyme B are cytotoxic, additional roles for this protease in CD4+ T cell biology remain unknown. Here, using a combination of in vivo and in vitro approaches, we report that granzyme B-deficient CD4+ T cells display increased IL-17 production. In the adoptive transfer model of intestinal inflammation, granzyme B-deficient CD4+ T cells triggered a more rapid disease onset than their WT counterparts, and presented a differential transcription profile. Similar results were also observed in granzyme B-deficient mice infected with Citrobacter rodentium. Our results suggest that granzyme B modulates CD4+ T cell differentiation, providing a new perspective into the biology of this enzyme.

category: immunology


title: Commensal Microbiota Regulates Skin Barrier Function And Repair Via Signaling Through The Aryl Hydrocarbon Receptor

abstract: The epidermis forms a barrier that defends the body from desiccation and entry of harmful substances, while sensing and integrating environmental signals. The tightly orchestrated cellular changes required for the proper formation and maintenance of this epidermal barrier occur in the context of the skin microbiome. Using germ free mice, we demonstrate the microbiota is necessary for proper differentiation and repair of the epidermal barrier. These effects were mediated by the aryl hydrocarbon receptor (AHR) in keratinocytes, a xenobiotic receptor also implicated in epidermal differentiation. Murine skin lacking keratinocyte AHR was more susceptible to barrier damage and infection, during steady state and epicutaneous sensitization. Colonization with a defined consortium of human skin isolates restored barrier competence in an AHR-dependent manner. We reveal a fundamental mechanism whereby the microbiota regulates skin barrier formation and repair, with far-reaching implications for the numerous skin disorders characterized by epidermal barrier dysfunction.


title: Redefining the role of Ca2+-permeable channels in photoreceptor degeneration using diltiazem

abstract: Hereditary degeneration of photoreceptors has been linked to over-activation of Ca2+-permeable channels, excessive Ca2+-influx, and downstream activation of Ca2+-dependent calpain-type proteases. Unfortunately, after more than 20 years of pertinent research, unequivocal evidence proving significant and reproducible photoreceptor protection with Ca2+-channel blockers is still lacking. Here, we show that both D- and L-cis enantiomers of the anti-hypertensive drug diltiazem were very effective at blocking photoreceptor Ca2+-influx, most probably by blocking the pore of Ca2+-permeable channels. Yet, unexpectedly, this block neither reduced the activity of calpain-type proteases, nor did it result in photoreceptor protection. Remarkably, application of the L-cis enantiomer of diltiazem even led to a strong increase in photoreceptor cell death. These findings shed doubt on the previously proposed links between Ca2+ and retinal degeneration and are highly relevant for future therapy development as they may serve to refocus research efforts towards alternative, Ca2+-independent degenerative mechanisms.


title: Genotyping common, large structural variations in 5,202 genomes using pangenomes, the Giraffe mapper, and the vg toolkit

abstract: We introduce Giraffe, a pangenome short read mapper that can efficiently map to a collection of haplotypes threaded through a sequence graph. Giraffe, part of the variation graph toolkit (vg)1, maps reads to thousands of human genomes at around the same speed BWA-MEM2 maps reads to a single reference genome, while maintaining comparable accuracy to VG-MAP, vgs original mapper. We have developed efficient genotyping pipelines using Giraffe. We demonstrate improvements in genotyping for single-nucleotide variants (SNVs), small insertions and deletions (indels) and structural variations (SVs) genome-wide. We use Giraffe to genotype about 167 thousand structural variants ascertained from long read studies in 5,202 human genomes sequenced with short reads, including the complete 1000 Genomes Project dataset, at an average cost of $1.50 per sample. We determine the frequency of these variations in diverse human populations, characterize their complex allelic variations and identify thousands of expression quantitative trait loci (eQTLs) driven by these variations.

category: bioinformatics


title: Cancer-specific overmethylation of histone H3 lysines is linked with methionine addiction and malignancy

abstract: Methionine addiction is a fundamental and general hallmark of cancer and is an area of current intense interest. Methionine addiction results from the overuse of methionine by cancer cells for excess transmethylation reactions. In order to identify excess transmethylation reactions in cancer and further understand the basis of methionine addiction, we compared the histone H3 lysine-methylation status and malignancy between methionine-addicted cancer cells and their methionine-independent revertants which have regained the ability to grow on low levels of methionine or independently of exogenous methionine. The levels of trimethylated histone H3 lysine marks were reduced in methionine-independent revertants compared to parental cancer cells in vitro. Tumorigenicity and experimental metastatic potential in nude mice were also highly reduced in the methionine-independent revertants compared to the parental cells. Our present results demonstrate that overmethylation of histone H3 lysines is linked with methionine addiction of cancer and to malignancy which suggests a possible causal relationship.

category: cancer biology


title: The linkage of methionine addiction, overmethylation of histone H3 lysines and malignancy demonstrated when cancer cells revert to methionine-independence


title: Genomic basis of drought resistance in Fagus sylvatica

abstract:
In the course of global climate change, central Europe is experiencing more frequent and prolonged periods of drought. The drought years 2018 and 2019 affected European beeches (Fagus sylvatica L.) differently: even in the same stand, drought damaged trees neighboured healthy trees, suggesting that the genotype rather than the environment was responsible for this conspicuous pattern. We used this natural experiment to study the genomic basis of drought resistance with Pool-GWAS. Contrasting the extreme phenotypes identified 106 significantly associated SNPs throughout the genome. Most annotated genes with associated SNPs (>70%) were previously implicated in the drought reaction of plants. Non-synonymous substitutions led either to a functional amino acid exchange or premature termination. A SNP-assay with 70 loci allowed predicting drought phenotype in 98.6% of a validation sample of 92 trees. Drought resistance in European beech is a moderately polygenic trait that should respond well to natural selection, selective management, and breeding.

Impact StatementEuropean beech harbours substantial genetic variation at genomic loci associated with drought resistance and the loci identified in this study can help to accelerate and monitor adaptation to climate change.

category: plant biology


title: Genetically Engineered Proportional-Integral Feedback Controllers for Robust Perfect Adaptation in Mammalian Cells

abstract: To support their survival, cells adapt to environmental disturbances by maintaining a constant internal milieu. Robust perfect adaptation is a strategy that utilizes integral feedback to promote adaptation by robustly driving regulated physiological variables to their pre-disturbance levels. Present in natural systems, this stringent regulatory strategy promises to enable the engineering of sophisticated genetic programs with diverse applications. Here, we present the first synthetic implementations of integral and proportional-integral feedback controllers in mammalian cells. We show that the integral controller robustly and precisely maintains a desired level of a transcription factor, in spite of induced disturbances and network perturbations. Augmenting proportional feedback reduces stochastic variability while maintaining robust perfect adaptation. We demonstrate the benefits of these controllers in mitigating the impact of resource burden and investigate their use in cell therapy. The synthetic biological realization of robust perfect adaptation holds promise for substantial advances in industrial biotechnology and cell-based therapies.

category: synthetic biology


title: Transient grb10a Knockdown Permanently Alters Growth, Cardiometabolic Phenotype and the Transcriptome in Danio rerio

abstract: Embryonic growth trajectory is a risk factor for chronic metabolic and cardiovascular disorder. Grb10 is a negative regulator of the main pathways driving embryonic growth. This study investigates the long-term cardiometabolic consequences and transcriptomic profiles of transient disruption of grb10a expression in Danio rerio. Knockdown was associated with increased embryonic growth (+7%) and metabolic rate (+25%), and decreased heart rate (- 50%) in early life. Juvenile growth and respiratory rate were also elevated (+30% and 7-fold increase respectively). The transcriptome was permanently remodelled by this transient disruption, with dysregulation of multiple growth, cardiac, and metabolic pathways. Phenotypic alteration persisted into adulthood, resulting in a leaner body with elevated skeletal and cardiac muscle content and aerobic scope (43%). This study not only confirms for the first time that transient disruption of a single gene can result in permanent transcriptomic remodelling but correlates this remodelling with persistent alterations to the adult cardiometabolic phenotype.

category: developmental biology


title: Composition Wheels: Visualizing dissolved organic matter using common composition metrics across a variety of Canadian Ecozones

abstract: Dissolved organic matter (DOM) is a ubiquitous component of aquatic systems, impacting aquatic health and drinking water quality. These impacts depend on the mixture of organic molecules that comprise DOM. Changing climates are altering both the amount and character of DOM being transported from the terrestrial system into adjacent surface waters, yet DOM composition is not monitored as often as overall concentration. Many DOM characterization methods exist, confounding comparison of DOM composition across different studies. The objective of this research is to determine which parameters in a suite of relatively simple and common DOM characterization techniques explain the most variability in DOM composition from surface and groundwater sites. Further, we create a simple visualization tool to easily compare compositional differences in DOM. A large number of water samples (n=250) was analyzed from six Canadian ecozones for DOM concentration, ultraviolet-visible light absorbance, molecular size, and elemental ratios. Principal component analyses was used to identify quasi-independent DOM compositional parameters that explained the highest variability in the dataset: spectral slope, specific-UV absorbance at 255nm, humic substances fraction, and dissolved organic carbon to dissolved organic nitrogen ratio. A  Composition Wheel was created by plotting these four parameters as a polygon. Our results find similarities in DOM composition irrespective of site differences in vegetation and climate. Further, two main end-member Composition Wheel shapes were revealed that correspond to DOM in organic-rich groundwaters and DOM influenced by photodegradation. The Composition Wheel approach uses easily visualized differences in polygon shape to quantify how DOM evolves by natural processes along the aquatic continuum and to track sources and degradation of DOM.

category: ecology


title: Network reconstruction and modelling made reproducible with moped

abstract: Mathematical modeling of metabolic networks is a powerful approach to investigate the underlying principles of metabolism and growth. Such approaches include, amongst others, differential equation based modeling of metabolic systems, constraint based modeling and topological analysis of metabolic networks. Most of these methods are well established and are implemented in numerous software packages, but these are scattered between different programming languages, packages and syntaxes. This complicates establishing straight forward pipelines integrating model construction and simulation. We present the Python package moped which serves as an integrative hub for reproducible construction, modification, curation and analysis of metabolic models. moped supports draft reconstruction of models directly from genome/proteome sequences and path-way/genome databases utilizing GPR annotations, providing a completely reproducible model construction and curation process within executable Python scripts. Alternatively, existing models published in SBML format can be easily imported. Models are represented as Python objects, for which a wide spectrum of easy-to-use modification and analysis methods exist. The model structure can be manually altered by adding, removing or modifying reactions, and gap filling reactions can be found and inspected. This greatly supports the development of draft models, as well as the curation and testing of models. Moreover, moped provides several analysis methods, in particular including the calculation of biosynthetic capacities using metabolic network expansion. The integration with other Python based tools is facilitated through various model export options. For example, a model can be directly converted into a CobraPy object for constraint-based analyses. moped is a fully documented and expandable Python package. We demonstrate the capability to serve as a hub for integrating reproducible model construction and curation, database import, topological analysis and export for constraint-based analyses.


title: Whole genome sequencing of nearly isogeneic WMI and WLI inbred rats identifies genes potentially involved in depression

abstract:
BackgroundThe WMI and WLI inbred rat substrains were generated from the stress-prone, and not yet fully inbred, Wistar Kyoto (WKY) strain using bi-directional selection for immobility in the forced swim test followed by over 38 generations of inbreeding. Despite the low level of genetic diversity among WKY progenitors, the WMI substrain is more vulnerable to stress relative to its WLI control substrain. Here we quantify numbers and classes of sequence variants distinguishing these substrains and test the hypothesis that they are nearly isogenic.

ResultsThe WLI and WMI genomic DNA were sequenced using Illumina xTen, IonTorrent and 10X Chromium technologies to obtain a combined coverage of over 100X. We identified 4,296 high quality homozygous SNPs and indels that differ between the WMI and WLI substrains. Gene ontology analysis of these variants showed an enrichment for neurogenesis related pathways. In addition, high impact variations were detected in genes previously implicated in depression (e.g. Gnat2), depression-like behavior (e.g. Prlr, Nlrp1a), other psychiatric disease (e.g. Pou6f2, Kdm5a, Reep3, Wdfy3) or stress response (e.g. Pigr).

ConclusionsThe high coverage sequencing data confirms the near isogenic nature of the two substrains, which combined with the variants detected can lead to the identification of genetic factors underlying greater susceptibility for depression, stress reactivity, and addiction.


title: Functional maps of the primate cortex revealed by through-skull wide-field optical imaging

abstract: The primate cerebral cortex is organized into specialized areas representing different functional modalities (e.g., vision, audition, touch) and their associations along a continuous surface. The functional maps of these areas, however, are often investigated in a single modality at a time. Here, we developed and applied to awake primates a polarization-enhanced wide-field optical imaging method for measuring cortical hemodynamics through the intact skull. Adjacent somatosensory, auditory, and visual cortices were noninvasively localized and rapidly parcellated in awake marmosets (Callithrix jacchus), a primate model featuring a smooth cortex. Detailed somatotopy, tonotopy, and retinotopy were also mapped out on an individual-subject basis, with a new pure-tone-responsive tonotopic gradient discovered outside the auditory core. Moreover, the motion-sensitive extent surrounding the primate-specific MT/V5 and the location of a face-sensitive patch were both revealed with respect to retinotopy. This approach provides a powerful tool for mapping the functional landscape across modalities in a single non-human primate subject, and thus opens new opportunities for probing how primate cortical system is organized to enable real-world behaviors.


title: Drawing the Borders of Olfactory Space

abstract: In studies of vision and audition, stimuli can be chosen to span the visible or audible spectrum; in olfaction, the axes and boundaries defining the analogous odorous space are unknown. As a result, the population of olfactory space is likewise unknown, and anecdotal estimates of 10,000 odorants have endured. The journey a molecule must take to reach olfactory receptors (OR) and produce an odor percept suggests some chemical criteria for odorants: a molecule must be 1) volatile enough to enter the air phase, 2) non-volatile and hydrophilic enough to sorb into the mucous layer coating the olfactory epithelium, 3) hydrophobic enough to enter an OR binding pocket, and 4) activate at least one OR. Here, we developed a simple and interpretable quantitative model that reliably predicts if a molecule is odorous or odorless based solely on the first three criteria. Applying our model to a database of all possible small organic molecules, we estimate that over 30 billion possible compounds are odorous, 6 orders of magnitude larger than current estimates of 10,000. With this model in hand, we can define the boundaries of olfactory space in terms of molecular volatility and hydrophobicity, enabling representative sampling of olfactory stimulus space.


title: Neural mechanisms underlying the temporal control of sequential saccade planning in the frontal eye fields

abstract: Sequences of saccadic eye movements are instrumental in navigating our visual environment. While neural activity has been shown to ramp up to a threshold before single saccades, the neural underpinnings of multiple saccades is unknown. To understand the neural control of rapid saccade sequences, we recorded from the frontal eye field (FEF) of macaque monkeys while they performed a sequential saccade task. We show that concurrent planning of two saccade plans brings forth processing bottlenecks, specifically by decreasing the growth rate and increasing the threshold of saccade-related ramping activity. The rate disruption affected both saccade plans, and a computational model wherein activity related to the two saccade plans bilaterally and asymmetrically inhibited each other, predicted the behavioral and neural results observed experimentally. Borrowing from models in psychology, our results demonstrate a capacity-sharing mechanism of processing bottlenecks, wherein multiple saccade plans in a sequence, compete for the processing capacity by perturbation of the saccade-related ramping activity. Finally, we show that in contrast to movement related neurons, visual activity in FEF neurons is not affected by the presence of multiple saccade targets, indicating that for perceptually simple tasks, inhibition amongst movement-related neurons mainly instantiates capacity sharing. Taken together, we show how psychology-inspired models of capacity sharing can be mapped onto neural responses to understand the control of rapid saccade sequences.


title: Transcriptomic profiling and microsatellite identification in cobia (Rachycentron canadum), using high throughput RNA-sequencing

abstract: Cobia (Rachycentron canadum) is a marine teleost species with great productive potential worldwide. However, the genomic information currently available for this species in public databases is limited. Such lack of information hinders gene expression assessments that might bring forward novel insights into the physiology, ecology, evolution, and genetics of this potential aquaculture species. In this study, we report the first de novo transcriptome assembly of R. canadum liver, improving the availability of novel gene sequences for this species. Illumina sequencing of liver transcripts generated 1,761,965,794 raw reads, which were filtered into 1,652,319,304 high-quality reads. De novo assembly resulted in 101,789 unigenes and 163,096 isoforms, with an average length of 950.61 and 1,617.34 nt, respectively. Moreover, we found that 126,013 of these transcripts bear potentially coding sequences, and 125,993 of these elements (77.3%) correspond to functionally annotated genes found in six different databases. We also identified 701 putative ncRNA and 35,414 putative lncRNA. Interestingly, homologues for 410 of these putative lncRNAs have already been observed in previous analyzes with Danio rerio, Lates calcarifer, Seriola lalandi dorsalis, Seriola dumerili or Echeneis naucrates. Finally, we identified 7,894 microsatellites related to cobias putative lncRNAs. Thus, the information derived from the transcriptome assembly described herein will likely assist future nutrigenomics and breeding programs involving this important fish farming species.


title: Attentional Modulation of Hierarchical Speech Representations in a Multitalker Environment

abstract: Humans are remarkably adept in listening to a desired speaker in a crowded environment, while filtering out non-target speakers in the background. Attention is key to solving this difficult cocktail-party task, yet a detailed characterization of attentional effects on speech representations is lacking. It remains unclear across what levels of speech features and how much attentional modulation occurs in each brain area during the cocktail-party task. To address these questions, we recorded whole-brain BOLD responses while subjects either passively listened to single-speaker stories, or selectively attended to a male or a female speaker in temporally-overlaid stories in separate experiments. Spectral, articulatory, and semantic models of the natural stories were constructed. Intrinsic selectivity profiles were identified via voxelwise models fit to passive listening responses. Attentional modulations were then quantified based on model predictions for attended and unattended stories in the cocktail-party task. We find that attention causes broad modulations at multiple levels of speech representations while growing stronger towards later stages of processing, and that unattended speech is represented up to the semantic level in parabelt auditory cortex. These results provide insights on attentional mechanisms that underlie the ability to selectively listen to a desired speaker in noisy multi-speaker environments.


title: The cost of attentional reorienting on conscious visual perception: an MEG study

abstract:
How do attentional networks influence conscious perception? To answer this question, we used magnetoencephalography (MEG) in human participants, and assessed the effects of spatially nonpredictive or predictive supra-threshold peripheral cues on the conscious perception of near-threshold Gabors. Three main results emerged. (1) As compared with invalid cues, both nonpredictive and predictive valid cues increased conscious detection. Yet, only predictive cues shifted the response criterion towards a more liberal decision (i.e., willingness to report the presence of a target under conditions of greater perceptual uncertainty) and affected target contrast leading to 50% detections. (2) Conscious perception following valid predictive cues was associated to enhanced activity in frontoparietal networks. These responses were lateralized to the left hemisphere during attentional orienting, and to the right hemisphere during target processing. The involvement of frontoparietal networks occurred earlier in valid than in invalid trials, a possible neural marker of the cost of re-orienting attention. (3) When detected targets were preceded by invalid predictive cues, and thus reorienting to the target was required, neural responses occurred in left hemisphere temporo-occipital regions during attentional orienting, and in right hemisphere anterior insular and temporo-occipital regions during target processing. These results confirm and specify the role of frontoparietal networks in modulating conscious processing, and detail how invalid orienting of spatial attention disrupts conscious processing.

Significance StatementDo we need to pay attention to external objects in order to become aware of them? Characterizing the spatiotemporal dynamics of attentional effects on visual perception is critical to understand how humans process and select relevant information. Participants detected near-threshold visual targets preceded by supra-threshold spatial cues with varying degrees of predictivity, while their brain activity was recorded using magnetoencephalography. Results demonstrated that valid predictive cues biased participants conscious perception through an early recruitment of frontoparietal regions, and that attentional costs associated to invalid predictive cues were related to activation of the right hemisphere ventral network. This work characterizes the neural dynamics associated with the cost of attentional reorienting on conscious processing.


title: Shaping sustainable harvest boundaries for marine populations despite estimation bias

abstract:
Biased estimates of population status are a pervasive conservation problem. This problem has plagued assessments of commercial exploitation of marine species and can threaten the sustainability of both populations and fisheries. We develop a computer-intensive approach to minimize adverse effects of persistent estimation bias in assessments by optimizing operational harvest measures (harvest control rules) with closed-loop simulation of resource-management feedback systems: management strategy evaluation. Using saithe (Pollachius virens), a bottom-water, apex predator in the North Sea, as a real-world case study, we illustrate the approach by first diagnosing robustness of the existing harvest control rule and then optimizing it through propagation of biases (overestimated stock abundance and underestimated fishing pressure) along with select process and observation uncertainties. Analyses showed that severe biases lead to overly optimistic catch limits and then progressively magnify the amplitude of catch fluctuation, thereby posing unacceptably high overharvest risks. Consistent performance of management strategies to conserve the resource can be achieved by developing more robust control rules. These rules explicitly account for estimation bias through a computational grid search for a set of control parameters (threshold abundance that triggers management action, Btrigger, and target exploitation rate, Ftarget) that maximize yield while keeping stock abundance above a precautionary level. When the biases become too severe, optimized control parameters- for saithe, raising Btrigger and lowering Ftarget-would safeguard against overharvest risk (<3.5% probability of stock depletion) and provide short-term stability in catch limit (<20% year-to-year variation), thereby minimizing disruption to fishing communities. The precautionary approach to fine-tuning adaptive risk management through management strategy evaluation offers a powerful tool to better shape sustainable harvest boundaries for exploited resource populations when estimation bias persists. By explicitly accounting for emergent sources of uncertainty our proposed approach ensures effective conservation and sustainable exploitation of living marine resources even under profound uncertainty.

Open Research StatementData sets and code utilized for this research are available on Figshare. DOI: https://doi.org/10.6084/m9.figshare.13281266


title: YieldNet: A Convolutional Neural Network for Simultaneous Corn and Soybean Yield Prediction Based on Remote Sensing Data

abstract: AO_SCPLOWBSTRACTC_SCPLOWLarge scale crop yield estimation is, in part, made possible due to the availability of remote sensing data allowing for the continuous monitoring of crops throughout its growth state. Having this information allows stakeholders the ability to make real-time decisions to maximize yield potential. Although various models exist that predict yield from remote sensing data, there currently does not exist an approach that can estimate yield for multiple crops simultaneously, and thus leads to more accurate predictions. A model that predicts yield of multiple crops and concurrently considers the interaction between multiple crops yield. We propose a new model called YieldNet which utilizes a novel deep learning framework that uses transfer learning between corn and soybean yield predictions by sharing the weights of the backbone feature extractor. Additionally, to consider the multi-target response variable, we propose a new loss function. Numerical results demonstrate that our proposed method accurately predicts yield from one to four months before the harvest, and is competitive to other state-of-the-art approaches.


title: Visualizing subcellular structures in neuronal tissue with expansion microscopy

abstract: Protein expansion microscopy (proExM) is a powerful technique that crosslinks proteins to a swellable hydrogel to physically expand and optically clear biological samples. The resulting increased resolution (~70 nm) and physical separation of labeled proteins make it an attractive tool for studying the localization of subcellular organelles in densely packed tissues, such as the brain. However, the digestion and expansion process greatly reduces fluorescence signals making it necessary to optimize ExM conditions per sample for specific end goals. Here we describe a proExM workflow optimized for resolving subcellular organelles (mitochondria and the Golgi apparatus) and reporter-labeled spines in fixed mouse brain tissue. By directly comparing proExM staining and digestion protocols, we found that immunostaining before proExM and using a proteinase K based digestion for 8 hours consistently resulted in the best fluorescence signal to resolve subcellular organelles while maintaining sufficient reporter labeling to visualize spines and trace individual neurons. With these methods, we more accurately quantified mitochondria size and number and better visualized Golgi ultrastructure in reconstructed CA2 neurons of the hippocampus.


title: Somatic Cell Nuclear Transfer Embryos Show Massive Dysregulation of Genes Involved in Transcription Pathway

abstract: Transcription is the most fundamental molecular event that occurs with zygotic genome activation (ZGA) during embryo development. However, the potential association between transcription pathways and low cloning efficiency of nuclear transfer (NT) embryos remains elusive. Here, we integrated a series of RNA-seq data on NT embryos to deciphering the molecular barriers of NT embryo development. Comparative transcriptome analysis indicated that incomplete activation of transcription pathways functions as a barrier for NT embryos. Then, the gene regulatory network (GRN) identified that crucial factors responsible for transcription play a coordinated role in epigenome erasure and pluripotency regulation during normal embryo development. But in NT embryos, massive genes involved in transcription pathways were varying degrees of inhibition. Our study therefore provides new insights into understanding the barriers to NT embryo reprogramming.


abstract:
An examination is presented of scientific research publication trends during the global coronavirus (COVID-19) pandemic in 2020. After reviewing the timing of the emergence of the pandemic in 2020 and the growth of governmental responses, available secondary sources are used to highlight impacts of COVID-19 on scientific research. A bibliometric analysis is then undertaken to analyze developments in COVID-19 related scientific publications through to October of 2020 by broad trends, fields, countries, and organizations. Two publication data sources are used: PubMed and the Web of Science.

While there has been a massive absolute increase in PubMed and Web of Science papers directly focused on COVID-19 topics, especially in medical, biological science, and public health fields, this is still a relatively small proportion of publication outputs across all fields of science. Using Web of Science publication data, the paper examines the extent to which researchers across all fields of science have pivoted their research outputs to focus on topics related to COVID-19. A COVID-19 research pivot is defined as the extent to which the proportion of output in a particular research field has shifted to a focus on COVID-19 topics in 2020 (to date) compared with 2019. Significant variations are found by specific fields (identified by Web of Science Subject Categories). In a top quintile of fields, not only in medical specialties, biomedical sciences, and public health but also in subjects in social sciences and arts and humanities, there are relatively high to medium research pivots. In lower quintiles, including other subjects in science, social science, and arts and humanities, low to zero COVID-19 research pivoting is identified.

In a new Appendix to the paper, an updated analysis is provided through to mid-April 2022.

CitationShapira, P. "Scientific publications and COVID-19 "research pivots" during the pandemic: An initial bibliometric analysis," bioRxiv 2020.12.06.413682; doi: https://doi.org/10.1101/2020.12.06.413682

Version NotesVersion 1: Original paper, completed on December 6, 2020; posted at bioRxiv on December 7, 2020.

Version 2: Minor grammar items corrected.

Version 3: Updated bibliometric analysis through to mid-April 2022 added on April 29, 2022, as new Appendix 2.

category: scientific communication and education


title: Development of a novel connectivity-based electric-field modelling approach for individualized targeting of transcranial magnetic stimulation treatment.

abstract:
BackgroundResting state functional connectivity (rsFC) offers promise for individualizing stimulation targets for transcranial magnetic stimulation (TMS) treatments. However current targeting approaches do not account for non-focal TMS effects or large-scale connectivity patterns. To overcome these limitations, we propose a novel targeting optimization approach that combines whole-brain rsFC and electric-field (e-field) modelling to identify single-subject, symptom-specific TMS targets.

MethodsIn this proof of concept study, we recruited 91 anxious misery (AM) patients and 25 controls. We measured depression symptoms (MADRS/HAMD) and recorded rsFC. We used a PCA regression to predict symptoms from rsFC and estimate the parameter vector, for input into our e-field augmented model. We modeled 17 left dlPFC and 7 M1 sites using 24 equally spaced coil orientations. We computed single-subject predicted {Delta}MADRS/HAMD scores for each site/orientation using the e-field augmented model, which comprises a linear combination of the following elementwise products 1) the estimated connectivity/symptom coefficients, 2) a vectorized e-field model for site/orientation, 3) the pre-treatment rsFC matrix, scaled by a proportionality constant.

ResultsIn AM patients, our pre-stimulation connectivity-based model predicted a significant decrease depression for sites near BA46, but not M1 for coil orientations perpendicular to the cortical gyrus. In control subjects, no site/orientation combination showed a significant predicted change.

DiscussionThese results corroborate previous work suggesting the efficacy of left dlPFC stimulation for depression treatment, and predict better outcomes with individualized targeting. They also suggest that our novel connectivity-based e-field modelling approach may effectively identify potential TMS treatment responders and individualize TMS targeting to maximize the therapeutic impact.


title: Dendritic signal integration in a Drosophila Mushroom Body Output Neuron (MBON) essential for learning and memory

abstract: The ability to associate neutral stimuli with valence information and to store these associations as memories forms the basis for decision making. To determine the underlying computational principles, we build a realistic computational model of a central decision module within the Drosophila mushroom body (MB), the flys center for learning and memory. Our model combines the electron microscopy-based architecture of one MB output neuron (MBON-3), the synaptic connectivity of its 948 presynaptic Kenyon cells (KCs), and its in vivo membrane properties obtained from patch-clamp recordings. We show that this neuron is electrotonically compact and that synaptic input corresponding to simulated odor input robustly drives its spiking behavior. Therefore, sparse innervation by KCs can efficiently control and modulate MBON activity in response to learning with minimal requirements on the specificity of synaptic localization. This architecture allows efficient storage of large numbers of memories using the flexible stochastic connectivity of the circuit.


title: The cellular architecture of memory modules in Drosophila supports stochastic input integration


title: Strategic trade-offs between choice biases and accuracy for decisions based on asymmetric, rare evidence

abstract: Solutions to challenging inference problems are often subject to a fundamental trade-off between bias (being systematically wrong) that is minimized with complex inference strategies and variance (being oversensitive to uncertain observations) that is minimized with simple inference strategies. However, this trade-off is based on the assumption that the strategies being considered are optimal for their given complexity and thus has unclear relevance to the frequently suboptimal inference strategies used by humans. We examined inference problems involving rare, asymmetrically available evidence, which a large population of human subjects solved using a diverse set of strategies that were suboptimal relative to the Bayesian ideal observer. These suboptimal strategies reflected an inversion of the classic bias-variance trade-off: subjects who used more complex, but imperfect, Bayesian-like strategies tended to have lower variance but high bias because of incorrect tuning to latent task features, whereas subjects who used simpler heuristic strategies tended to have higher variance because they operated more directly on the observed samples but displayed weaker, near-normative bias. Our results yield new insights into the principles that govern individual differences in behavior that depends on rare-event inference, and, more generally, about the information-processing trade-offs that are sensitive to not just the complexity, but also the optimality of the inference process.


title: Suboptimal human inference inverts the bias-variance trade-off for decisions with asymmetric evidence


title: Global transcriptomics reveals specialized roles for splicing regulatory proteins in the macrophage innate immune response

abstract: Pathogen sensing via pattern recognition receptors triggers massive reprogramming of macro-phage gene expression. While the signaling cascades and transcription factors that activate these responses are well-known, the role of post-transcriptional RNA processing in modulating innate immune gene expression remains understudied. Recent phosphoproteomics analyses revealed that members of the SR and hnRNP families of splicing regulatory proteins are dynamically post-translationally modified in infected macrophages. To begin to test if these splicing factors play a privileged role in controlling the innate immune transcriptome, we analyzed steady state gene expression and alternatively spliced isoform production in ten SR/hnRNP knockdown RAW 264.7 macrophage cell lines following infection with the bacterial pathogen Salmonella enterica serovar Typhimurium (Salmonella). We identified thousands of transcripts whose abundance was increased or decreased by SR/hnRNP knockdown in macrophages. We observed that different SR/hnRNPs control the expression of distinct gene regulons in uninfected and Salmonella-infected macrophages, with several key innate immune genes (Nos2, Mx1, Il1a) relying on multiple SR/hnRNPs to maintain proper induction and/or repression. Knockdown of SR/hnRNPs promoted differential isoform usage (DIU) for a number of key immune sensors and signaling molecules and many of these splicing changes were again, distinct in uninfected and Salmonella-infected macrophages. Finally, after observing a surprising degree of similarity between the DEGs and DIUs in hnRNP K and U knockdown macrophages, we found that these cells are better able to restrict vesicular stomatitis virus replication than control cells, supporting a role for these hnRNPs in controlling infection outcomes in macrophages ex vivo. Based on these findings, we conclude that many innate immune genes have evolved to rely on one or more splicing regulatory factors to ensure the proper timing and magnitude of their induction, bolstering a model wherein pre-mRNA splicing is a critical regulatory node in the innate immune response.


title: A new hypothesis for type 1 diabetes risk: The at-risk allele at rs3842753 associates with increased beta cell INS mRNA in a meta-analysis of single cell RNA sequencing data

abstract: Type 1 diabetes is characterized by the autoimmune destruction of insulin secreting {beta} cells. Genetic variations upstream at the insulin (INS) locus contribute to ~10% of type 1 diabetes heritable risk. Multiple studies showed an association between rs3842753 C/C genotype and type 1 diabetes susceptibility, but the molecular mechanisms remain unclear. To date, no large-scale studies have looked at the effect of genetic variation at rs3842753 on INS mRNA at the single cell level. We aligned all human islet single cell RNA sequencing datasets available to us in 2020 to the reference genome GRCh38.98 and genotyped rs3842753, integrating 2315 {beta} cells and 1223 {beta}-like cells from 13 A/A protected donors, 23 A/C heterozygous donors, and 35 C/C at-risk donors, including adults without diabetes and with type 2 diabetes. INS expression mean and variance were significantly higher in single {beta} cells from females compared with males. Comparing across {beta} cells and {beta}-like cells, we found that rs3842753 C containing cells (either homozygous or heterozygous) had the highest INS expression. We also found that {beta} cells with the rs3842753 C allele had significantly higher ER stress marker gene expression compared to the A/A homozygous genotype. These findings support the emerging concept that inherited risk of type 1 diabetes may be associated with inborn, persistent elevated insulin production which may lead to {beta} cell ER stress and fragility.


title: Sequence determinants of the aggregation of proteins within condensates generated by liquid-liquid phase separation

abstract: The transition between the native and amyloid states of proteins can proceed via a deposition pathway via oligomeric intermediates or via a condensation pathway via liquid droplet intermediates generated through liquid-liquid phase separation. Here we investigate the sequence determinants of aggregation from within the droplet state based on generic interactions. We describe a model in which these sequence determinants can be captured by three features, the droplet-promoting propensity, the aggregation-promoting propensity and the binding mode entropy. By using this approach, we propose a formula to identify aggregation-promoting mutations in droplet-forming proteins. This analysis provides insights into the amino acid code for the conversion of proteins between liquid-like and solid-like condensates.


title: Heterogeneity of monocyte subsets and susceptibility to influenza virus contribute to inter-population variability of protective immunity

abstract:
There is considerable inter-individual and inter-population variability in response to viruses. The potential of monocytes to elicit type-I interferon responses has attracted attention to their role in viral infections. Here, we use an ex vivo model to characterize the role of cellular heterogeneity in human variation of monocyte responses to influenza A virus (IAV) exposure. Using single-cell RNA-sequencing, we show widespread inter-individual variability in the percentage of IAV-infected monocytes. We show that cells escaping viral infection display increased mRNA expression of type-I interferon stimulated genes and decreased expression of ribosomal genes, relative to both infected cells and those never exposed to IAV. While this host defense strategy is shared between CD16+/CD16- monocytes, we also uncover CD16+-specific mRNA expression of IL6 and TNF in response to IAV, and a stronger resistance of CD16+ monocytes to IAV infection. Notably, individuals with high cellular susceptibility to IAV are characterized by a lower activation at basal state of an IRF/STAT-induced transcriptional network, which includes antiviral genes such as IFITM3, MX1, and OAS3. Finally, using flow cytometry and bulk RNA-sequencing across 200 individuals of African and European ancestry, we observe a higher number of CD16+ monocytes and lower susceptibility to IAV infection among monocytes from individuals of African-descent. Collectively, our results reveal the effects of IAV infection on the transcriptional landscape of human monocytes and highlight previously unappreciated differences in cellular susceptibility to IAV infection between individuals of African and European ancestry, which may account for the greater susceptibility of Africans to severe influenza.

Significance StatementMonocytes may play a critical role during severe viral infections. Our study tackles how heterogeneity in monocyte subsets and activation contributes to shape individual differences in the transcriptional response to viral infections. Using single-cell RNA-sequencing, we reveal heterogeneity in monocyte susceptibility to IAV infection, both between CD16+/CD16- monocytes and across individuals, driven by differences in basal activation of an IRF/STAT-induced antiviral program. Furthermore, we show a decreased ability of IAV to infect and replicate in monocytes from African-ancestry individuals, with possible implications for antigen presentation and lymphocyte activation. These results highlight the importance of early cellular activation in determining an individuals innate immune response to viral infection.

category: genomics


title: A massively multi-scale approach to characterising tissue architecture by synchrotron micro-CT applied to the human placenta

abstract: Multi-scale structural assessment of biological soft tissue is challenging but essential to gain insight into structure-function relationships of tissue/organ. Using the human placenta as an example, this study brings together sophisticated sample preparation protocols, advanced imaging, and robust, validated machine-learning segmentation techniques to provide the first massively multi-scale and multi-domain information that enables detailed morphological and functional analyses of both maternal and fetal placental domains. Finally, we quantify the scale-dependent error in morphological metrics of heterogeneous placental tissue, estimating the minimal tissue scale needed in extracting meaningful biological data. The developed protocol is beneficial for high-throughput investigation of structure-function relationships in both normal and diseased placentas, allowing us to optimise therapeutic approaches for pathological pregnancies. In addition, the methodology presented is applicable in characterisation of tissue architecture and physiological behaviours of other complex organs with similarity to the placenta, where an exchange barrier possesses circulating vascular and avascular fluid spaces.

category: bioengineering


title: Trafficking regulator of GLUT4-1 (TRARG1) is a GSK3 substrate

abstract: Trafficking regulator of GLUT4-1, TRARG1, positively regulates insulin-stimulated GLUT4 trafficking and insulin sensitivity. However, the mechanism(s) by which this occurs remain(s) unclear. Using biochemical and mass spectrometry analyses we found that TRARG1 is dephosphorylated in response to insulin in a PI3K/Akt-dependent manner and is a novel substrate for GSK3. Priming phosphorylation of murine TRARG1 at serine 84 allows for GSK3-directed phosphorylation at serines 72, 76 and 80. A similar pattern of phosphorylation was observed in human TRARG1, suggesting that our findings are translatable to human TRARG1. Pharmacological inhibition of GSK3 increased cell surface GLUT4 in cells stimulated with a submaximal insulin dose, and this was impaired following Trarg1 knockdown, suggesting that TRARG1 acts as a GSK3-mediated regulator in GLUT4 trafficking. These data place TRARG1 within the insulin signaling network and provide insights into how GSK3 regulates GLUT4 trafficking in adipocytes.


title: DNA-sequence dependent positioning of the linker histone in a nucleosome: a single-pair FRET study

abstract:
Linker histones (LH) bind to nucleosomes with their globular domain (gH) positioned in either an on- or an off-dyad binding mode. Here, we study the effect of the linker DNA (L-DNA) sequence on the binding of a full-length LH, Xenopus laevis H1.0b, to a Widom 601 nucleosome core particle (NCP) flanked by two 40 bp long L-DNA arms, by single-pair FRET spectroscopy. We varied the sequence of the 11 bp of L-DNA adjoining the NCP on either side, making the sequence either A-tract, purely GC, or mixed, with 64% AT. The labelled gH consistently exhibited higher FRET efficiency with the labelled L-DNA containing the A-tract, than that with the pure-GC stretch, even when the stretches were swapped. However, it did not exhibit higher FRET efficiency with the L-DNA containing 64% AT-rich mixed DNA when compared to the pure-GC stretch. We explain our observations with a model that shows that the gH binds on-dyad and that two arginines mediate recognition of the A-tract via its characteristically narrow minor groove. To investigate whether this on-dyad minor groove-based recognition was distinct from previously identified off-dyad major groove-based recognition, a nucleosome was designed with A-tracts on both the L-DNA arms. One A-tract was complementary to thymine and the other to deoxyuridine. The major groove of the thymine-tract was lined with methyl groups that were absent from the major groove of the deoxyuridine tract. The gH exhibited similar FRET for both these A-tracts, suggesting that it does not interact with the thymine methyl groups exposed on the major groove. Our observations thus complement previous studies that suggest that different LH isoforms may employ different ways of recognizingff AT-rich DNA and A-tracts. This adaptability may enable the LH to universally compact scaffold-associated regions and constitutive heterochromatin, which are rich in such sequences.

Statement of SignificanceLinker histones (LHs) associate with the smallest repeat unit of chromatin, the nucleosome. They have been observed to have affinity for AT-rich DNA, which is found in constitutive heterochromatin and scaffold-associated regions (SAR), which could explain how the LHs can compact such parts of the chromatin. How the LH recognizes such sequences is poorly understood. Using single-pair FRET and modelling, we provide experimental evidence of DNA-sequence-induced changes in the orientation of a LH bound to a nucleosome, and thereby reveal a new mechanism by which the LH can recognize A-tract sequences that are abundantly present in the SAR. Our results show that, depending on how the LH associates with the nucleosome, it can employ more than one mechanism to recognize AT-rich DNA.

category: biophysics


title: Pre-Implantation Alcohol Exposure Induces Lasting Sex-Specific DNA Methylation Programming Errors in the Developing Forebrain

abstract:
BackgroundPrenatal alcohol exposure is recognized for altering DNA methylation profiles of brain cells during development, and to be part of the molecular basis underpinning Fetal Alcohol Spectrum Disorder (FASD) etiology. However, we have negligible information on the effects of alcohol exposure during pre-implantation, the early embryonic window marked with dynamic DNA methylation reprogramming, and on how this may rewire the brain developmental program.

ResultsUsing a pre-clinical in vivo mouse model, we show that a binge-like alcohol exposure during pre-implantation at the 8-cell stage leads to surge in morphological brain defects and adverse developmental outcomes during fetal life. Genome-wide DNA methylation analyses of fetal forebrains uncovered sex-specific alterations, including partial loss of DNA methylation maintenance at imprinting control regions, and abnormal de novo DNA methylation profiles in various biological pathways (e.g., neural/brain development).

ConclusionThese findings support that alcohol-induced DNA methylation programming deviations during pre-implantation could contribute to the manifestation of neurodevelopmental phenotypes associated with FASD.


title: L-DOPA modulates activity in the vmPFC, Nucleus Accumbens and VTA during threat extinction learning in humans

abstract:
Learning to be safe is central for adaptive behaviour when threats are no longer present. Detecting the absence of an expected threat is key for threat extinction learning and an essential process for the behavioural treatment of anxiety related disorders. One possible mechanism underlying extinction learning is a dopaminergic mismatch signal that encodes the absence of an expected threat. Here we show that such a dopamine-related pathway underlies extinction learning in humans. Dopaminergic enhancement via administration of L-DOPA (vs. Placebo) was associated with reduced retention of differential psychophysiological threat responses at later test, which was mediated by activity in the ventromedial prefrontal cortex that was specific to extinction learning. L-DOPA administration enhanced signals at the time-point of an expected, but omitted threat in extinction learning within the nucleus accumbens, which were functionally coupled with the ventral tegmental area and the amygdala. Computational modelling of threat expectancies further revealed prediction error encoding in nucleus accumbens that was reduced when L-DOPA was administered. Our results thereby provide evidence that extinction learning is influenced by L-DOPA and provide a mechanistic perspective to augment extinction learning by dopaminergic enhancement in humans.

Summary COI statementNo conflict of interest for any of the authors. The funder had no role in the design of the study, the collection and analysis of data, or the preparation of the manuscript.


title: Joint species distributions reveal the combined effects of host plants, abiotic factors and species competition as drivers of species abundances in fruit flies

abstract: AO_SCPLOWBSTRACTC_SCPLOWThe relative importance of ecological factors and species interactions for phytophagous insect species distributions has long been a controversial issue. Using field abundances of eight sympatric Tephritid fruit flies on 21 host plants, we inferred flies realized niches using joint species distribution modelling and network inference, on the community as a whole and separately on three groups of host plants. These inferences were then confronted to flies fundamental niches estimated through laboratory-measured fitnesses on host plants. Species abundances were mainly determined by host plants followed by climatic factors, with a minor role for competition between species sharing host plants. The relative importance of these factors mildly changed when we focused on particular host plant groups. Despite overlapping fundamental niches, specialists and generalists had almost distinct realized niches, with possible competitive exclusion of generalists by specialists on Cucurbitaceae, and different assembly rules: specialists were mainly influenced by their adaptation to host plants while generalist abundances varied regardless of their fundamental host use.


title: Comprehensive analysis of Japanese archipelago population history by detecting ancestry-marker polymorphisms without using ancient DNA data

abstract: Modern Japanese have two major ancestral populations: the indigenous Jomon people and continental immigrants. To figure out the formation process of current Japanese population, we developed a reference-free detection method of variants derived from ancestral populations using a summary statistic, the ancestry-marker index (AMI), and identified 208,648 SNPs that appear to have been derived from the Jomon people (Jomon-derived variants). The analysis of Jomon-derived variants in 10,842 modern Japanese individuals recruited from all over Japan revealed that the admixture proportions of the Jomon people varied between prefectures. The estimated allele frequencies of genome-wide SNPs in the ancestral populations of modern Japanese suggested their phenotypic characteristics possibly for adaptation to their respective livelihoods. According to our findings, we propose a formation model of modern Japanese population; regional variations in admixture proportions of the Jomon people and continental East Asians formed genotypic and phenotypic gradations of current Japanese archipelago populations.


title: Detection of ancestry-derived variants of modern Japanese revealed the formation process of regional gradations of the current Japanese archipelago population


title: Oscillatory tracking of pseudo-rhythmic speech is constrained by linguistic predictions

abstract: Neuronal oscillations putatively track speech in order to optimize sensory processing. However, it is unclear how isochronous brain oscillations can track pseudo-rhythmic speech input. Here we propose that oscillations can track pseudo-rhythmic speech when considering that speech time is dependent on predictions flowing from internal language models. We show that the temporal dynamics of speech are dependent on the predictability of words in a sentence. A computational model including oscillations, feedback, and inhibition is able to track the natural pseudo-rhythmic speech input. As the model processes, it generates temporal phase codes, which are a candidate mechanism for carrying information forward in time. The model is optimally sensitive to the natural temporal speech dynamics and can explain empirical data on temporal speech illusions. Our results reveal that speech tracking does not only rely on the input acoustics but instead entails an interaction between oscillations and constraints flowing from internal language models.


title: Quantifying phase separation property of chromatin associated proteins under physiological conditions using anti-1,6-hexanediol index

abstract:
BackgroundLiquid-liquid phase separation (LLPS) is an important organizing principle for biomolecular condensation and chromosome compartmentalization. However, while many proteins have been reported to undergo LLPS, quantitative and global analysis of chromatin LLPS property remains absent.

ResultsHere, by combing chromatin associated protein pull-down, quantitative proteomics and 1,6-hexanediol treatment, we developed Hi-MS and defined anti-1,6-HD index of chromatin-associated proteins (AICAP) to quantitative measurement of LLPS property of chromatin-associated proteins in their endogenous state and physiological abundance. The AICAP values were verified by previously reported experiments and were reproducible across different MS platforms. Moreover, the AICAP values were highly correlate with protein functions. Proteins act in active/regulatory biological process often exhibit low AICAP values, while proteins act in structural and repressed biological process often exhibit high AICAP values. We further revealed that chromatin organization changes more in compartment A than B, and the changes in chromatin organization at various levels, including compartments, TADs and loops are highly correlated to the LLPS properties of their neighbor nuclear condensates.

ConclusionsOur work provided the first global quantitative measurement of LLPS properties of chromatin-associated proteins and higher-order chromatin structure, and demonstrate that the active/regulatory chromatin components, both protein (trans) and DNA (cis), exhibit more hydrophobicity-dependent LLPS properties than the repressed/structural chromatin components.


title: Cortical depth-dependent human fMRI of resting-state networks using EPIK

abstract:
Recent laminar-fMRI studies have provided substantial understanding of the evoked cortical responses in multiple sub-systems; in contrast, the laminar component of resting-state networks spread over the whole brain has been less studied due to technical limitations. Animal research strongly suggests that the supragranular layers of the cortex play a critical role in maintaining network communication; however, whether this is true in the human cerebral cortex remains unclear. Here, we used EPIK, which offers unprecedented coverage at sub-millimetre resolution, to investigate cortical broad resting-state dynamics with depth specificity in healthy volunteers. Our results suggest that human default mode network connectivity is primarily supported by intermediate and superficial layers of the cortex and that the preferred cortical depth used for communication can vary from one network to another. We also identified significantly lower ALFF and ReHo laminar slopes in scans acquired during task performance compared to rest, as well as varied laminar connectivity patterns. The evaluation of laminar-fMRI across the brain encompasses unprecedented computational challenges; nonetheless, it enables the investigation of a new dimension of the human neocortex, which may be key in the characterization of neurological disorders from a novel perspective.

Significance statementResting-state networks sustain conscious awareness and diverse cognitive processing in the absence of tasks. In contrast to cortical areas, the cortical depth across different networks has been poorly investigated, mainly due to the small brain coverage enforced in high-resolution imaging methods. Here, using an optimized fMRI sequence, we demonstrate the critical involvement of the supragranular layers of the cerebral cortex in the maintenance of the resting-state dynamics. Given the cytoarchitectonics of the human neocortex, and based on our results, the cortical thickness constitutes an important dimension in the characterization of resting-state oscillations in the healthy brain, and its functional study may facilitate the identification of novel targets in neurological diseases.

Key pointsO_LIEPIK-fMRI of a motor task reproduces previous laminar activation profiles in M1.
C_LIO_LIHuman resting-state network correlations peak at different cortical depths.
C_LIO_LIThe cortical slope of ALFF and ReHo is decreased during task compared to rest.
C_LI


title: The convergence and divergence of episodic and semantic functions across lateral parietal cortex

abstract: Several decades of neuropsychological and neuroimaging research have highlighted the importance of lateral parietal cortex (LPC) across a myriad of cognitive domains. Yet, despite the prominence of this region the underlying function of LPC remains unclear. Two domains that have placed particular emphasis on LPC involvement are semantic memory and episodic memory retrieval. From each domain, sophisticated models have been proposed as to the underlying function, as well as the more domain-general assumption that LPC is engaged by any form of internally-directed cognition (episodic and semantic retrieval both being examples if this process). Here we directly address these alternatives using a combination of fMRI, functional connectivity and DTI white-matter connectivity data. The results show that ventral LPC (angular gyrus) was positively engaged during episodic retrieval but disengaged during semantic memory retrieval. In addition, the level of activity negatively varied with task difficulty in the semantic task whereas episodic activation was independent of difficulty. In contrast, dorsal LPC (intraparietal sulcus) showed domain general activation that was positively correlated with task difficulty. In terms of functional and structural connectivity, a dorsal-ventral and anterior-posterior gradient of connectivity was found to different processing networks (e.g., mid-angular gyrus (AG) connected with episodic retrieval). We propose a unifying model in which LPC as a whole might share a common underlying neurocomputation (e.g., multimodal buffering) with variations in the emergent, expressed cognitive functions across subregions arising from differences in the underlying white matter connectivity.


title: Systematic comparison of incomplete-supervision approaches for biomedical imaging classification

abstract:
Deep learning based classification of biomedical images requires manual annotation by experts, which is time-consuming and expensive. Incomplete-supervision approaches including active learning, pre-training and semi-supervised learning address this issue and aim to increase classification performance with a limited number of annotated images. Up to now, these approaches have been mostly benchmarked on natural image datasets, where image complexity and class balance typically differ considerably from biomedical classification tasks. In addition, it is not clear how to combine them to improve classification performance on biomedical image data.

We thus performed an extensive grid search combining seven active learning algorithms, three pre-training methods and two training strategies as well as respective baselines (random sampling, random initialization, and supervised learning). For four biomedical datasets, we started training with 1% of labeled data and increased it by 5% iteratively, using 4-fold cross-validation in each cycle. We found that the contribution of pre-training and semi-supervised learning can reach up to 25% macro F1-score in each cycle. In contrast, the state-of-the-art active learning algorithms contribute less than 5% to macro F1-score in each cycle. Based on performance, implementation ease and computation requirements, we recommend the combination of BADGE active learning, ImageNet-weights pre-training, and pseudo-labeling as training strategy, which reached over 90% of fully supervised results with only 25% of annotated data for three out of four datasets.

We believe that our study is an important step towards annotation and resource efficient model training for biomedical classification challenges.


title: Lexical frequency and sentence context influence the brain's response to single words

abstract: Typical adults read remarkably quickly. Such fast reading is facilitated by brain processes that are sensitive to both word frequency and contextual constraints. It is debated as to whether these attributes have additive or interactive effects on language processing in the brain. We investigated this issue by analysing existing magnetoencephalography data from 99 participants reading intact and scrambled sentences. Using a cross-validated model comparison scheme, we found that lexical frequency predicted the word-by-word elicited MEG signal in a widespread cortical network, irrespective of sentential context. In contrast, index (ordinal word position) was more strongly encoded in sentence words, in left front-temporal areas. This confirms that frequency influences word processing independently of predictability, and that contextual constraints affect word-by-word brain responses. With a conservative multiple comparisons correction, only the interaction between lexical frequency and surprisal survived, in anterior temporal and frontal cortex, and not between lexical frequency and entropy, nor between lexical frequency and index. However, interestingly, the uncorrected index*frequency interaction revealed an effect in left frontal and temporal cortex that reversed in time and space for intact compared to scrambled sentences. Finally, we provide evidence to suggest that, in sentences, lexical frequency and predictability may independently influence early (<150ms) and late stages of word processing, but also interact during late stages of word processing (>150-250ms), thus helping to converge previous contradictory eye-tracking and electrophysiological literature. Current neuro-cognitive models of reading would benefit from accounting for these differing effects of lexical frequency and predictability on different stages of word processing.


title: Moving pictures: Reassessing docking experiments with a dynamic view of protein interfaces

abstract:
The modeling of protein assemblies at the atomic level remains a central issue in structural biology, as protein interactions play a key role in numerous cellular processes. This problem is traditionally addressed using docking tools, where the quality of the models is based on their similarity to a single reference experimental structure. However, using a static reference does not take into account the dynamic quality of the protein interface. Here, we used all-atom classical Molecular Dynamics simulations to investigate the stability of the reference interface for three complexes that previously served as targets in the CAPRI competition. For each one of these targets, we also ran MD simulations for ten models that are distributed over the High, Medium and Acceptable accuracy categories. To assess the quality of these models from a dynamic perspective, we set up new criteria which take into account the stability of the reference experimental protein interface. We show that, when the protein interfaces are allowed to evolve along time, the original ranking based on the static CAPRI criteria no longer holds as over 50% of the docking models undergo a category change (which can be either toward a better or a lower accuracy group) when reassessing their quality using dynamic information.

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/415885v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@1e4f4a8org.highwire.dtl.DTLVardef@7a4bccorg.highwire.dtl.DTLVardef@1064caforg.highwire.dtl.DTLVardef@948619_HPS_FORMAT_FIGEXP  M_FIG C_FIG

category: biochemistry


title: Structures of outer-arm dynein array on microtubule doublet reveal a motor coordination mechanism

abstract: Thousands of outer-arm dyneins (OADs) are arrayed in the axoneme to drive a rhythmic ciliary beat. Coordination among multiple OADs is essential for generating mechanical forces to bend microtubule doublets (MTDs). Using electron microscopy, we determined high-resolution structures of OAD arrays bound to MTD in two different states. OAD preferentially binds to MTD protofilaments with a pattern resembling the native tracks for its distinct microtubule-binding domains. Upon MTD binding, free OADs are induced to adopt a stable parallel conformation, primed for array formation. Extensive tail-to-head (TTH) interactions between OADs are observed, which need to be broken for ATP turnover by the dynein motor. We propose that OADs in an array sequentially hydrolyze ATP to slide MTDs. ATP-hydrolysis in turn relaxes the TTH interfaces to effectuate free nucleotide cycles of downstream OADs. These findings lead to a model explaining how conformational changes in the axoneme produce coordinated action of dyneins.