title: Rhythmic coordination of hippocampal-prefrontal ensembles for odor-place associative memory and decision making

abstract: Memory-guided decision making involves long-range coordination across sensory and cognitive brain networks, with key roles for the hippocampus and prefrontal cortex (PFC). To investigate these coordination mechanisms, we monitored activity in hippocampus (CA1), PFC, and olfactory bulb in rats performing an odor-place associative memory guided decision task on a T-maze. During odor sampling, the beta (20-30 Hz) and respiratory (7-8 Hz) rhythms (RR) were prominent across the three regions, with CA1-PFC beta and RR coherence enhanced during the odor-cued decision making period. Beta phase modulation of CA1 and PFC neuronal activity during this period was linked to accurate decisions, suggesting that this temporal modulation influences sensory-cued decision making. Single neurons and ensembles in both CA1 and PFC encoded and predicted animals upcoming choices. Our findings indicate that rhythmic coordination within the hippocampal-prefrontal network supports utilization of odor cues for memory-guided decision making.


title: Slow oscillation-spindle coupling is negatively associated with emotional memoryformation following stress

abstract: Both stress and sleep enhance emotional memory. They also interact, with the largest effect of sleep on emotional memory being seen when stress occurs shortly before or after encoding. Slow wave sleep (SWS) is critical for long-term episodic memory, facilitated by the temporal coupling of slow oscillations and sleep spindles. Prior work in humans has shown these associations for neutral information in non-stressed participants. Whether coupling interacts with stress to facilitate emotional memory formation is unknown. Here, we addressed this question by reanalyzing an existing dataset of 64 individuals. Participants underwent a psychosocial stressor (32) or comparable control (32) prior to the encoding of 150-line drawings of neutral, positive, and negative images. All participants slept overnight with polysomnography, before being given a surprise memory test the following day. In the stress group, time spent in SWS was positively correlated with memory for images of all valences. Results were driven by those who showed a high cortisol response to the stressor, compared to low responders. The amount of slow oscillation-spindle coupling during SWS was negatively associated with neutral and emotional memory in the stress group only. The association with emotional memory was significantly stronger than for neutral memory within the stress group. These results suggest that stress around the time of initial memory formation impacts the relationship between slow wave sleep and memory.

category: neuroscience


title: Population density modeling of mixed polymorphic phenotypes: an application of spatial mark-resight models

abstract: Melanism is a form of pigmentation polymorphism where individuals have darker colouration than what is considered the "wild" phenotype. In the case of leopards, Panthera pardus, melanism occurs at higher frequencies amongst populations in tropical and subtropical moist forests of south and southeast Asia, presenting a unique challenge in estimating and monitoring these populations. Unlike the wild phenotype that is readily recognizable by its rosette patterns, melanism results in individuals being unidentifiable or  unmarked through photographic captures obtained using white flash cameras. Spatial mark-resight (SMR) models that require only a subset of the population to be  marked offer the opportunity to estimate population density. In this study, we present an application of SMR models to estimate leopard densities using camera trap survey data from three sampling years at Manas National Park (MNP), India. By using an SMR model that allowed us to include captures of unidentified sightings of marked individuals, we were also able to incorporate captures where identity was either not confirmed or only known from a single flank. Following 18,674 trap-days of sampling across three years, we obtained 728 leopard photo-captures, of which 22.6% (165) were melanistic. We estimated leopard densities of 4.33, 2.61 and 3.37 individuals/100km2 across the three years. To our best knowledge, these represent the first known estimates of leopard densities from populations comprising both melanistic and wild phenotypes. Finally, we highlight that SMR models present an opportunity to revisit past camera trap survey data for leopards and other species such as Jaguars, P. onca, that exhibit phenotypic polymorphism towards generating valuable information on populations.

category: ecology


title: Influenza-induced activation of recruited alveolar macrophages during the early inflammatory phase drives lung injury and lethality

abstract: Severe respiratory virus infections initiate a robust host immune response that contributes to disease severity. Immunomodulatory strategies that limit virus-initiated inflammation are of critical importance. In this study, we compared the host response to influenza A virus (IAV) infection in susceptible animals (wild-type, WT) to resilient mice (Vimentin-/- mice). We identified distinct gene expression patterns in recruited monocyte-derived alveolar macrophages (MoAMs) associated with three phases (Infiltrating, Early Inflammatory, Late Inflammatory) that evolve in sequence over the course of IAV infection. We report a core set of pro-inflammatory genes involved in the WT MoAM Early Inflammatory response that is suppressed in Vim-/- MoAMs. Moreover, we identify CEBPB, Jun-AP1, and IRF transcriptions factors as regulators of this attenuated inflammatory response. We performed causal experiments using bone-marrow chimeras to credential that Vim-/- MoAMs with suppressed pro-inflammatory genes confer protection from influenza-induced mortality in WT susceptible mice. Taken together, these data support the notion that vimentin plays a causal role in determining the pro-inflammatory function of recruited MoAMs and drives IAV-induced lung injury.

category: immunology


title: A single N6-methyladenosine site in lncRNA HOTAIR regulates its function in breast cancer cells

abstract: N6-methyladenosine (m6A) modification of RNA plays important roles in normal and cancer biology, but knowledge of its function on long noncoding RNAs (lncRNAs) remains limited. Here, we investigate whether m6A regulates the function of the human HOTAIR lncRNA, which contributes to multiple pro-tumor phenotypes in triple-negative breast cancer (TNBC) cells. We identify at least 8 individual m6A sites within HOTAIR, with a single site (A783) consistently methylated. Mutation of A783 impairs cellular proliferation and invasion in HOTAIR-overexpressing TNBC cells. m6A at A783 regulates HOTAIRs ability to localize to chromatin and induce gene pathways that affect tumor progression. In contrast, A783U mutant HOTAIR demonstrates loss-of-function and antimorph behaviors by impairing gene expression changes induced by WT HOTAIR and, in some cases, inducing opposite changes in gene expression. HOTAIR interacts with nuclear m6A reader YTHDC1 and high HOTAIR is significantly associated with shorter overall patient survival, particularly in the context of high YTHDC1. At the molecular level, YTHDC1-HOTAIR interactions are required for chromatin localization and regulation of gene repression. Our work demonstrates how modification of one base in a lncRNA can elicit a distinct gene regulation mechanism and drive disease-associated phenotypic changes such as proliferation and invasion.

category: molecular biology


title: DotMotif: An open-source tool for connectome subgraph isomorphism search and graph queries

abstract: Recent advances in neuroscience have enabled the exploration of brain structure at the level of individual synaptic connections. These connectomics datasets continue to grow in size and complexity; methods to search for and identify interesting graph patterns offer a promising approach to quickly reduce data dimensionality and enable discovery. These graphs are often too large to be analyzed manually, presenting significant barriers to searching for structure and testing hypotheses. We combine graph database and analysis libraries with an easy-to-use neuroscience grammar suitable for rapidly constructing queries and searching for subgraphs and patterns of interest. Our approach abstracts many of the computer science and graph theory challenges associated with nanoscale brain network analysis and allows scientists to quickly conduct research at scale. We demonstrate the utility of these tools by searching for motifs on simulated data and real public connectomics datasets, and we share simple and complex structures relevant to the neuroscience community. We contextualize our findings and provide case studies and software to motivate future neuroscience exploration.


title: Information Content of Trees: Three-taxon Statements Inference Rules and Dependency

abstract: AO_SCPLOWBSTRACTC_SCPLOWThe three-taxon statement is the fundamental unit of rooted trees in Cladistics, stating that for three terminal taxa, two are more related to each other than to a third. Because of their fundamental role in phylogenetics, three-taxon statements are present in methodological research of various disciplines in evolutionary biology, as in consensus methods, supertree methods, species-tree methods, distance metrics, and even phylogenetic reconstruction. However, three-taxon statements methods are subject to important flaws related to information redundancy. We aim to study the behavior of three-taxon statements and the interactions among them in order to enhance their performance in evolutionary studies. We show here how specific interactions between three-taxon statements are responsible of the emergence of redundancy and dependency within trees, and how they can be used for the improvement of weighting procedures. Our proposal is subsequently empirically tested in the supertree framework using simulations. We show that three-taxon statements using fractional weights perform drastically better than classical methods such as MRP or methods using unweighted statements. Our study shows that appropriate fractional weighting of three taxon statements is of critical importance for removing redundancy in any method using three-taxon statements, as in consensus, supertrees, distance metrics, and phylogenetic or biogeographic analyses.

category: evolutionary biology


title: Inference and validation of an integrated regulatory network of autism

abstract:
BackgroundAutism is a complex neurodevelopmental disorder. Functional roles and mechanisms of several non-coding transcripts including long noncoding RNAs (lncRNAs) have been shown to influence the pathobiology of autism. We hypothesize that there are more autism-associated lncRNAs to be discovered. In this work, we utilize a systems biology approach to identify novel lncRNAs that might play a role in the molecular pathogenesis of autism.

MethodsBased on the data provided by the Simons Foundation Autism Research Initiative (SFARI), a three-component regulatory network comprising mRNAs, microRNAs (miRNAs) and lncRNAs was constructed. Functional enrichment analysis was performed to identify molecular pathways potentially mediated by components of the network. The potential association of four candidate lncRNAs with autism was investigated experimentally by developing and verifying a valproic acid (VPA)-exposed mouse model of autism.

ResultsWe composed a network of 33 mRNA nodes, 25 miRNA nodes and 4 lncRNA nodes associated with neurologically relevant pathways and functions. We then verified the differential expression of four candidate lncRNAs: Gm10033, 1500011B03Rik, A930005H10Rik and Gas5 in the brain of VPA-exposed mice. We furthermore identified a novel splice variant of Gm10033, designated as Gm10033-{Delta}Ex2, which was expressed in various mouse tissues.

ConclusionsThe integrative approach combines the analysis of a three-component regulatory network with experimental validation of targets in an animal model of autism. As a result of the analysis, we prioritized a set of candidate autism-associated lncRNAs. These links add to the common understanding of the molecular and cellular mechanisms that are involved in disease etiology, specifically in the autism.

category: systems biology


title: Conflict detection in a sequential decision task is associated with increased cortico-subthalamic coherence and prolonged subthalamic oscillatory response in the beta band.

abstract: Making accurate decisions often involves the integration of current and past evidence. Here we examine the neural correlates of conflict and evidence integration during sequential decision making. Patients implanted with deep-brain stimulation (DBS) electrodes and age-matched healthy controls performed an expanded judgement task, in which they were free to choose how many cues to sample. Behaviourally, we found that while patients sampled numerically more cues, they were less able to integrate evidence and showed suboptimal performance. Using recordings of Magnetoencephalography (MEG) and local field potentials (LFP, in patients) in the subthalamic nucleus (STN), we found that beta oscillations signalled conflict between cues within a sequence. Following cues that differed from previous cues, beta power in the STN and cortex first decreased and then increased. Importantly, the conflict signal in the STN outlasted the cortical one, carrying over to the next cue in the sequence. Furthermore, after a conflict, there was an increase in coherence between the dorsal premotor cortex and subthalamic nucleus in the beta band. These results extend our understanding of cortico-subcortical dynamics of conflict processing, and do so in a context where evidence must be accumulated in discrete steps, much like in real life. Thus, the present work leads to a more nuanced picture of conflict monitoring systems in the brain and potential changes due to disease.


title: Single nuclei chromatin profiling of ventral midbrain reveals cell identity transcription factors and cell type-specific gene regulatory variation

abstract: Cell types in ventral midbrain are involved in diseases with variable genetic susceptibility such as Parkinsons disease and schizophrenia. Many genetic variants affect regulatory regions and alter gene expression. We report 20 658 single nuclei chromatin accessibility profiles of ventral midbrain from two genetically and phenotypically distinct mouse strains. We distinguish ten cell types based on chromatin profiles and analysis of accessible regions controlling cell identity genes highlights cell type-specific key transcription factors. Regulatory variation segregating the mouse strains manifests more on transcriptome than chromatin level. However, cell type-level data reveals changes not captured at tissue level. To discover the scope and cell-type specificity of cis-acting variation in midbrain gene expression, we identify putative regulatory variants and show them to be enriched at differentially expressed loci. Finally, we find TCF7L2 to mediate trans-acting variation selectively in midbrain neurons. Our dataset provides an extensive resource to study gene regulation in mesencephalon.

category: genomics


title: Connecting conformational stiffness of the protein with energy landscape by a single experiment

abstract:
Proteins are versatile biopolymers whose functions are determined by their structures. Understanding the structural dynamicity, with respect to energy landscape, is essential to describe their biological functions. The ability to study the dynamical properties of a single protein molecule is thus crucial, but ensuring that multiple physical properties can be simultaneously extracted within a single experiment on the exact same protein molecule in real-time has hitherto been infeasible.

Here, we present magnetic tweezers technology that surmounts this limitation, providing real-time dynamic information about changes in several molecular properties ({Delta}G0, conformation, and mean first passage time of unfolding and refolding) from a single experiment, by remeasuring the very same protein molecule in varying chemical condition. We illustrate the versatility of the method by studying electrolyte-dependent conformational flexibility and the energy landscape of substrate protein L under force. Changing salt concentrations reshapes the energy landscape by two specific ways: it speeds-up refolding kinetics while slowing down unfolding kinetics. From the same trajectory, we calculate the stiffness of the protein polymer, a quantity that varies with salt concentration. The data is described within the framework of a modified  electrolyte FJC model that we propose and study here. The observed correlation between{Delta} G0, kinetics and polymer elasticity connect protein chain physics and the energy landscape, while the experimental methodology we describe of getting energy landscape from a single experiment could have wide-ranging applications.

category: biophysics


title: Comparative analysis of non structural protein 1 of SARS-CoV2 with SARS-CoV1 and MERS-CoV: An in silico study

abstract: The recently emerged SARS-CoV2 caused a major pandemic of coronavirus disease (COVID-19). Non structural protein 1 (nsp1) is found in all beta coronavirus that causes several severe respiratory diseases. This protein is considered as a virulence factor and has an important role in pathogenesis. This study aims to elucidate the structural conformations of non structural protein 1 (nsp1), prediction of epitope sites and identification of important residues for targeted therapy against COVID-19. In this study, molecular modelling coupled with molecular dynamics simulations were performed to analyse the conformational change of nsp1 of SARS-CoV1, SARS-CoV2 and MERS-CoV at molecular level. Principal component analysis escorted by free energy landscape revealed that SARS-CoV2 nsp1 protein shows greater flexibility, compared to SARS-CoV1 and MERS-CoV nsp1. From the sequence alignment, it was observed that 28 mutations are present in SERS-CoV2 nsp1 protein compared to SERS-CoV1 nsp1. Several B-cell and T-cell epitopes were identified by immunoinformatics approach. SARS-CoV2 nsp1 protein binds with the interface region of the palm and finger domain of POLA1 by using hydrogen bond and salt bridge interactions. These findings can be used to develop therapeutics specific against COVID-19.

category: bioinformatics


title: SAMHD1 mutations in mantle cell lymphoma are recurrent and confer in vitro resistance to nucleoside analogues

abstract: The genomic landscape of mantle cell lymphoma (MCL) includes frequent alterations of TP53, ATM, CCND1 and KMT2D. Thus far, the mutational landscape provides little information for treatment stratification. We characterized a cohort of MCL by targeted next generation sequencing and discovered SAMHD1 as a novel recurrently mutated gene (8.5% of investigated cases, 4/47 samples). Furthermore, we provide evidence of in vitro resistance of SAMHD1 mutated patient-derived MCL cells to cytarabine and fludarabine.

category: cancer biology


title: A comprehensive and centralized database for exploring omics data in Autoimmune Diseases

abstract: Autoimmune diseases are heterogeneous pathologies with difficult diagnosis and few therapeutic options. In the last decade, several omics studies have provided significant insights into the molecular mechanisms of these diseases. Nevertheless, data from different cohorts and pathologies are stored independently in public repositories and a unified resource is imperative to assist researchers in this field. Here, we present ADEx (https://adex.genyo.es), a database that integrates 82 curated transcriptomics and methylation studies covering 5609 samples for some of the most common autoimmune diseases. The database provides, in an easy-to-use environment, advanced data analysis and statistical methods for exploring omics datasets, including meta-analysis, differential expression or pathway analysis.


title: Digital twinning of Cellular Capsule Technology: emerging outcomes from the perspective of porous media mechanics

abstract:
Spheroids encapsulated within alginate capsules are emerging as suitable in vitro tools to investigate the impact of mechanical forces on tumor growth since the internal tumor pressure can be retrieved from the deformation of the capsule. Here we focus on the particular case of Cellular Capsule Technology (CCT).

We show in this contribution that a modeling approach accounting for the triphasic nature of the spheroid (extracellular matrix, tumor cells and interstitial fluid) offers a new perspective of analysis revealing that the pressure retrieved experimentally cannot be interpreted as a direct picture of the pressure sustained by the tumor cells and, as such, cannot therefore be used to quantify the critical pressure which induces stress-induced phenotype switch in tumor cells.

The proposed multiphase reactive poro-mechanical model was cross-validated. Parameter sensitivity analyses on the digital twin revealed that the main parameters determining the encapsulated growth configuration are different from those driving growth in free condition, confirming that radically different phenomena are at play. Results reported in this contribution support the idea that multiphase reactive poro-mechanics is an exceptional theoretical framework to attain an in-depth understanding of CCT experiments, to confirm their hypotheses and to further improve their design.


title: Modeling the variability of the electromotor commandsystem of pulse electric fish

abstract: Mormyrids, a family of weakly electric fish, use electric pulses for communication and for extracting information from the environment (active electroreception). The electromotor system controls the timing of pulse generation. Ethological studies have described several sequences of pulse intervals (SPIs) which are related to distinct behaviors (e.g. mating or exploratory behaviors). Accelerations, scallops, rasps, and cessations are four SPI patterns reported in these fish, each showing characteristic temporal structures and large variability. This paper presents a computational model of the electromotor command circuit that reproduces SPI patterns as a function of the inputs to the model while keeping the same internal network configuration. The topology of the model is based on a simplified representation of the network with four neuron clusters (nuclei). An initial ad hoc tuned configuration (S-T) was built to reproduce nucleus characteristics and network topology as described by detailed morphological and electrophysiological studies. Then, a genetic algorithm (GA) was developed and applied to automatically tune the synaptic parameters of the model connectivity. Two different configurations obtained from the GA are presented here: one optimized to a set of synthetic examples of SPI patterns (S-GA) and another configuration adjusted to patterns recorded from freely-behaving Gnathonemus Petersii specimens (R-GA). Robustness analyses to input variability were performed to discard overfitting and assess validity. Results show that the set of SPI patterns are consistently reproduced, both for synthetic data and for recorded data. This model can be used as a tool to test novel hypotheses regarding temporal structure in electrogeneration.


title: Taking fright: the decline of Australian Pied Oystercatchers Haematopus longirostris at South Ballina Beach, New South Wales

abstract: This study reviewed data from the Richmond River Area Pied Oystercatcher Protection Program 1997-2013 and Richmond River Area Shorebird Protection Program 2014-2018, on the far north coast of the State of New South Wales (NSW), Australia. The Australian Pied Oystercatcher Haematopus longirostris breeding population size for South Ballina Beach has decreased from 15-16 pairs in 1994-1996 to 7-9 pairs in 2016-2018. This is despite control of the European Red Fox Vulpes vulpes successfully reducing depredation of eggs and chicks and > 207 oystercatchers fledging from beaches in the Richmond River area in 1997-2018. The negative trend for South Ballina is contrasted with the positive trend for Bombing Range Beach, where the population size has increased from 4-5 pairs in 2002-2004 to 8-9 pairs in 2016-2018. Vehicle-based recreation has increased at South Ballina in the past two decades versus Bombing Range has remained closed to the public. It is proposed that human recreation disturbance is preventing recruitment into the South Ballina oystercatcher breeding population. Without strong protection of habitat from such disturbance, the NSW oystercatcher breeding population size is predicted to continue to decrease.


title: Phenotypic melanoma heterogeneity is regulated through cell-matrix interaction-dependent changes in tumor microarchitecture

abstract:
Phenotypic heterogeneity of cancer cells plays a critical role in shaping treatment response. This type of heterogeneity is organized spatially with specific phenotypes, such as sharply demarcated clusters of proliferating and cell cycle-arrested cells, predominating within discrete domains within a tumor. What determines the occurrence of specific tumor cell phenotypes in distinct microdomains of solid cancers is poorly understood. Here, we show that in melanoma spatial organization of phenotypic heterogeneity is dictated by the expression and activity of MITF. We reveal that this lineage survival oncogene controls ECM composition and organization, and ROCK-driven mechanotransduction through focal adhesion maturation and actin cytoskeleton functionality. In turn, altered tumor microarchitecture and structural integrity impact tumor solid stress which then mediates phenotypic heterogeneity through p27Kip1. Rho-ROCK-myosin signaling is necessary to transmit the effect of the reciprocal cell-ECM regulation into phenotypic heterogeneity. Our findings place cell-ECM crosstalk as a central driver of phenotypic tumor heterogeneity.

SignificancePhenotypic heterogeneity is a major culprit of cancer therapy failure. We demonstrate that phenotypic heterogeneity is controlled through tumor cell-ECM crosstalk resulting in altered tumor microarchitecture, mechanotransduction and Rho-ROCK-myosin signaling. Melanoma shares these physical properties with any solid cancer underscoring the importance of our findings for therapeutically targeting this phenomenon.


title: Collective ERK/Akt activity waves orchestrate epithelial homeostasis by driving apoptosis-induced survival

abstract: Cell death events continuously challenge epithelial barrier function, yet are crucial to eliminate old or critically damaged cells. How such apoptotic events are spatio-temporally organized to maintain epithelial homeostasis remains unclear. We observe waves of Extracellular Signal-Regulated Kinase (ERK) and AKT serine/threonine kinase (Akt) activity pulses that originate from apoptotic cells and propagate radially to healthy surrounding cells. This requires Epidermal Growth Factor Receptor (EGFR) and matrix metalloproteinase (MMP) signaling. At the single-cell level, ERK/Akt waves act as spatial survival signals that locally protect cells in the vicinity of the epithelial injury from apoptosis for a period of 3-4h. At the cell population level, ERK/Akt waves maintain epithelial homeostasis (EH) in response to mild or intense environmental insults. Disruption of this spatial signaling system results in the inability of a model epithelial tissue to ensure barrier function in response to environmental insults.

category: cell biology


title: Vigilance response of a key prey species to anthropogenic and natural threats in Detroit

abstract: Rapid urbanization coupled with increased human activity induces pressures that affect predator-prey relations through a suite of behavioral mechanisms, including alteration of avoidance and coexistence dynamics. Synergisms of natural and anthropogenic threats existing within urban environments exacerbate the necessity for species to differentially modify behavior to each risk. Here, we explore the behavioral response of a key prey species, cottontail rabbits (Sylvilagus floridanus), to pressures from humans, domestic dogs, and a natural predator, coyotes (Canis latrans) in a human-dominated landscape. We conducted the first camera survey in urban parks throughout Detroit, Michigan in 2017-2020 to assess vigilance response corresponding to a heterogeneous landscape created from variation in the occupancy of threats. We predicted a scaled response where cottontail rabbits would be most vigilant in areas with high coyote activity, moderately vigilant in areas with high domestic dog activity, and the least vigilant in areas of high human activity. From 8,165 independent cottontail rabbit detections in Detroit across 11,616 trap nights, one-third were classified as vigilant. We found vigilance behavior increased with coyote occupancy and in locations with significantly high domestic dog activity, but found no significant impact of human occupancy or their spatial hotspots. We also found little spatial overlap between rabbits and threats, suggesting rabbits invest more in spatial avoidance; thus, less effort is required for vigilance. Our results elucidate strategies of a prey species coping with various risks to advance our understanding of the adaptability of wildlife in urban environments. In order to promote coexistence between people and wildlife in urban greenspaces, we must understand and anticipate the ecological implications of human-induced behavioral modifications.


title: Ctenophore extracellular DNA traps demonstrate conserved antimicrobial behaviors presentat the emergence of animals

abstract: The formation of extracellular DNA traps (ETosis) is a first response mechanism by specific immune cells following exposure to microbes 1,2. First characterized in vertebrate neutrophils, cells capable of ETosis have been recently discovered in several invertebrate taxa and the formation of invertebrate DNA traps has been most thoroughly examined in bivalves 3-5. Here we report that ctenophores - thought to have diverged very early from the metazoan stem lineage 6,7 - possess immune cell types capable of ETosis, suggesting that this cellular immune response behavior was likely present early in metazoan evolution. To assess conservation of ET activation between evolutionarily distant phyla, we deployed a comparative approach integrating data from the model ctenophore Mnemiopsis leidyi and the oyster Crassostrea gigas to develop a novel imaging analysis pipeline to quantify ETosis in large numbers of cells. We demonstrate that both Mnemiopsis and Crassostrea immune cells can undergo ETosis after exposure to diverse microbes and pharmacological stimuli. Our results suggest that the range of cellular immune behaviors and signaling cascades that produce extracellular DNA traps were likely present prior to the divergence of extant metazoan lineages and thus ETosis represents an evolutionarily ancient defense against pathogens existing at the dawn of animal multicellularity.


title: Neuro-computational mechanisms of action-outcome learning under moral conflict

abstract: Predicting how actions result in conflicting outcomes for self and others is essential for social functioning. We tested whether Reinforcement Learning Theory captures how participants learn to choose between symbols that define a moral conflict between financial self-gain and other-pain. We tested whether choices are better explained by model-free learning (decisions based on combined historical values of past outcomes), or model-based learning (decisions based on the current value of separately expected outcomes) by including trials in which participants know that either self-gain or other-pain will not be delivered. Some participants favored options benefiting themselves, others, preventing other-pain. When removing the favored outcome, participants instantly altered their choices, suggesting model-based learning. Computational modelling confirmed choices were best described by model-based learning in which participants track expected values of self-gain and other-pain separately, with an individual valuation parameter capturing their relative weight. This valuation parameter predicted costly helping in an independent task. The expectations of self-gain and other-pain were also biased: the favoured outcome was associated with more differentiated symbol-outcome probability reports than the less favoured outcome. FMRI helped localize this bias: signals in the pain-observation network covaried with pain prediction errors without linear dependency on individual preferences, while the ventromedial prefrontal cortex contained separable signals covarying with pain prediction errors in ways that did and did not reflected individual preferences.


title: NMDAR-mediated transcriptional control of gene expression during the development of medial ganglionic eminence-derived interneurons

abstract: Medial ganglionic eminence (MGE)-derived parvalbumin (PV)+, somatostatin (SST)+ and Neurogliaform (NGFC)-type cortical and hippocampal interneurons, have distinct molecular, anatomical and physiological properties. However, the molecular mechanisms regulating their diversity remain poorly understood. Here, via single-cell transcriptomics, we show that the obligate NMDA-type glutamate receptor (NMDAR) subunit gene Grin1 mediates subtype-specific transcriptional regulation of gene expression in MGE-derived interneurons, leading to altered subtype abundances. Notably, MGE-specific conditional Grin1 loss results in a systemic downregulation of diverse transcriptional, synaptogenic and membrane excitability regulatory programs. These widespread gene expression abnormalities mirror aberrations that are typically associated with neurodevelopmental disorders, particularly schizophrenia. Our study hence provides a road map for the systematic examination of NMDAR signaling in interneuron subtypes, revealing potential MGE-specific genetic targets that could instruct future therapies of psychiatric disorders.


title: Responsiveness variability during anaesthesia relates to inherent differences in brain structure and function of the fronto-parietal networks

abstract: Anaesthesia combined with functional neuroimaging provides a powerful approach for understanding the brain mechanisms of consciousness. Although propofol is used ubiquitously in clinical interventions that reversibly suppress consciousness, it shows large inter-individual variability, and the brain bases of this variability remain poorly understood. We asked whether three networks key to conscious cognition -- the dorsal attention (DAN), executive control (ECN), and default mode (DMN) -- underlie responsiveness variability under anaesthesia. Healthy participants (N=17) were moderately anaesthetized during narrative understanding and resting state conditions inside the Magnetic Resonance Imaging scanner. A target detection task measured behavioural responsiveness. An independent behavioural study (N=25) qualified the attention demands of narrative understanding. 30% of participants were unaffected in their response times, thus thwarting a key aim of anaesthesia -- the suppression of behavioural responsiveness. Individuals with stronger functional connectivity within the DAN and ECN, between them, and to the DMN, and with larger grey matter volume in frontal regions were more resilient to anaesthesia. For the first time, we show that responsiveness variability during propofol anaesthesia relates to inherent differences in brain structure and function of the fronto-parietal networks, which can be predicted prior to sedation. Results highlight novel markers for improving awareness monitoring during clinical anaesthesia.


title: Genome-Wide High Resolution Expression Map and Functions of Key Cell Fate Determinants Reveal the Dynamics of Crown Root Development in Rice

abstract: Shoot borne adventitious/crown roots (AR/CR) shape up the root architecture in grasses. Mechanisms underlying initiation and subsequent outgrowth of CR remain largely unknown. Here, we provide genome-wide modulation in the landscape of transcriptional signatures during distinct developmental stages of CR formation in highly derived grass species, rice. Our studies implicate the role of potential epigenetic modifiers, transcription factors and cell division regulators in priming the initiation of CR primordia followed by progressive activation of conserved transcription regulatory modules to ensure their outgrowth. In depth analysis of spatio-temporal expression patterns of key cell fate determinants and functional analyses of rice WUSCHEL RELATED HOMEOBOX10 (OsWOX10) and PLETHORA (OsPLT1) genes reveal their unprecedented role in controlling root architecture. We further show that OsPLT1 activates local auxin biosynthesis and forms an integral part of ERF3-OsWOX11-OsRR2 regulatory module during CR primordia development. Interestingly, OsPLT genes, when expressed in the transcriptional domain of root-borne lateral root primordia of Arabidopsis plt mutant, rescued their outgrowth demonstrating the conserved role of PLT genes in root primordia outgrowth irrespective of their developmental origin. Together, these findings unveil the molecular framework of cellular reprogramming during trans-differentiation of shoot tissue to root leading to culmination of robust root architecture in grass species which got evolutionary diverged from dicots.

category: plant biology


abstract: A major goal of computational neuroscience is the development of powerful data analyses that operate on large datasets. These analyses form an essential toolset to derive scientific insights from new experiments. Unfortunately, a major obstacle currently impedes progress: novel data analyses have a hidden dependence upon complex computing infrastructure (e.g. software dependencies, hardware), acting as an unaddressed deterrent to potential analysis users. While existing analyses are increasingly shared as open source software, the infrastructure needed to deploy these analyses - at scale, reproducibly, cheaply, and quickly - remains totally inaccessible to all but a minority of expert users. In this work we develop Neuroscience Cloud Analysis As a Service (NO_SCPLOWEUROC_SCPLOWCAAS): a fully automated analysis platform that makes state-of-the-art data analysis tools accessible to the neuroscience community. Based on modern large-scale computing advances, NO_SCPLOWEUROC_SCPLOWCAAS is an open source platform with a drag-and-drop interface, entirely removing the burden of infrastructure purchase, configuration, deployment, and maintenance from analysis users and developers alike. NO_SCPLOWEUROC_SCPLOWCAAS offers two major scientific benefits to any data analysis. First, NO_SCPLOWEUROC_SCPLOWCAAS provides automatic reproducibility of analyses at no extra effort to the analysis developer or user. Second, NO_SCPLOWEUROC_SCPLOWCAAS cleanly separates tool implementation from usage, allowing for immediate use of arbitrarily complex analyses, at scale. We show how these benefits drive the design of simpler, more powerful data analyses. Furthermore, we show that many popular data analysis tools offered through NO_SCPLOWEUROC_SCPLOWCAAS outperform typical analysis solutions (in terms of speed and cost) while improving ease of use, dispelling the myth that cloud compute is prohibitively expensive and technically inaccessible. By removing barriers to fast, efficient cloud computation, NO_SCPLOWEUROC_SCPLOWCAAS can dramatically accelerate both the dissemination and the effective use of cutting-edge analysis tools for neuroscientific discovery.


title: Resin-acid derivatives bind to multiple sites on the voltage-sensor domain of the Saker channel

abstract:
Voltage-gated potassium (KV) channels can be opened by negatively charged resin acids and their derivatives. These resin acids have been proposed to attract the positively charged voltage-sensor helix (S4) toward the extracellular side of the membrane by binding to a pocket located between the lipid-facing extracellular ends of the transmembrane segments S3 and S4. By contrast to this proposed mechanism, neutralization of the top gating charge of the Shaker KV channel increased resin-acid induced opening, suggesting other mechanisms and sites of action. Here we explored the binding of two resin-acid derivatives, Wu50 and Wu161, to the activated/open state of the Shaker KV channel by a combination of in-silico docking, molecular dynamics simulations, and electrophysiology of mutated channels. We identified three potential resin-acid binding sites around S4: (1) The S3/S4 site previously suggested, in which positively charged residues introduced at the top of S4 are critical to keep the compound bound, (2) a site in the cleft between S4 and the pore domain (S4/pore site), in which a tryptophan at the top of S6 and the top gating charge of S4 keeps the compound bound, and (3) a site located on the extracellular side of the voltage-sensor domain, in a cleft formed by S1-S4 (the top-VSD site). The multiple binding sites around S4 and the anticipated helical-screw motion of the helix during activation make the effect of resin-acid derivatives on channel function intricate. The propensity of a specific resin acid to activate and open a voltage-gated channel likely depends on its exact binding dynamics and the types of interactions it can form with the protein in a state-specific manner.

eTOC SummarySilver[a] Ejneby et al use molecular dynamics simulations and electrophysiology to show that the voltage-gated Shaker potassium channel has multiple binding sites for resin-acid derivatives that can regulate its opening.


title: Multimodal multiscale analysis reveals flexible DNA contacts of bacterial nucleoprotein filaments

abstract:
Gene silencing in bacteria is mediated by chromatin proteins, of which Escherichia coli H-NS is a paradigmatic example. H-NS forms nucleoprotein filaments with either one or two DNA duplexes. However, the structures, arrangements of DNA-binding domains (DBDs), and positions of DBD-DNA contacts in linear and bridged filaments are uncertain. To characterize the contacts that silence transcription by RNA polymerase, we combined {middle dot}OH footprinting, molecular dynamics, statistical modeling, and DBD mapping using a chemical nuclease (Fe2+-EDTA) tethered to the DBDs (TEN-map). We find that H-NS DBDs contact DNA at indistinguishable locations in bridged or linear filaments and that the DBDs vary in orientation and position with ~10-bp average spacing. Our results support a hemi-sequestration model of linear-to-bridged H-NS switching in which linear filaments able to inhibit only transcription initiation switch to bridged filaments able to inhibit both initiation and elongation using the same irregularly spaced DNA contact sites.

HighlightsO_LITethered-nuclease mapping (TEN-map) of H-NS DNA-binding domains detects DNA contacts
C_LIO_LIBridged and linear H-NS filaments use the same DNA contact sites
C_LIO_LIH-NS-DNA contacts are unevenly spaced with ~10 bp average separation
C_LIO_LIAT-steps, minor groove width, and electrostatic potential best predict contact sites
C_LI


title: Bacterial H-NS contacts DNA at the same irregularly spaced sites in both bridged and hemi-sequestered linear filaments


title: High rates of genome rearrangements and pathogenicity of Shigella spp.

abstract:
Shigella are pathogens originating within the Escherichia lineage but frequently classified as a separate genus. Shigella genomes contain numerous insertion sequences (ISs) that lead to pseudogenization of affected genes and an increase of non-homologous recombination. Here, we study 414 genomes of E. coli and Shigella strains to assess the contribution of genomic rearrangements to Shigella evolution. We found that Shigella experienced exceptionally high rates of intragenomic rearrangements and had a decreased rate of homologous recombination compared to pathogenic and non-pathogenic E. coli. The high rearrangement rate resulted in independent disruption of syntenic regions and parallel rearrangements in different Shigella lineages. Specifically, we identified two types of chromosomally encoded E3 ubiquitin-protein ligases acquired independently by all Shigella strains that also showed a high level of sequence conservation in the promoter and further in the 5 intergenic region. In the only available enteroinvasive E. coli (EIEC) strain, which is a pathogenic E. coli with a phenotype intermediate between Shigella and non-pathogenic E. coli, we found a rate of genome rearrangements comparable to those in other E. coli and no functional copies of the two Shigella-specific E3 ubiquitin ligases. These data indicate that accumulation of ISs influenced many aspects of genome evolution and played an important role in the evolution of intracellular pathogens. Our research demonstrates the power of comparative genomics-based on synteny block composition and an important role of non-coding regions in the evolution of genomic islands.

ImportancePathogenic Escherichia coli strains frequently cause infections in humans. Many E. coli exist in nature and their ability to cause disease is fueled by their ability to incorporate novel genetic information by extensive horizontal gene transfer of plasmids and pathogenicity islands. The emergence of antibiotic-resistant Shigella spp., which are pathogenic forms of E. coli, coupled with the absence of an effective vaccine against them, highlights the importance of the continuing study of these pathogenic bacteria. Our study contributes to the understanding of genomic properties associated with molecular mechanisms underpinning the pathogenic nature of Shigella. We characterize the contribution of insertion sequences to the genome evolution of these intracellular pathogens and suggest a role of upstream regions of chromosomal ipaH genes in the Shigella pathogenesis. The methods of rearrangement analysis developed here are broadly applicable to the analysis of genotype-phenotype correlation in historically recently emerging bacterial pathogens.


title: Unilateral and Bilateral Subthalamic stimulation differently promote apathy: a translational approach

abstract: Apathy, depression, and anxiety represent the main neuropsychiatric symptoms of Parkinsons disease (PD). How subthalamic nucleus deep brain stimulation (STN-DBS) influences these symptoms, especially apathy, is a controversial topic. The present translational study investigates and compares the effect of bilateral or unilateral STN-DBS on this neuropsychiatric triad, combining a pre-clinical approach in rodents and a clinical follow-up of patients with PD. While depression and anxiety related behaviors remain unchanged, bilateral but not unilateral STN-DBS consistently induces apathy in patients and a reward seeking deficit in rodents. Together, these data substantiate the claim that STN-DBS may induce apathy by itself and suggest that bilateral but not the unilateral stimulation might be a critical factor.


title: Activity Dependent Stimulation Increases Synaptic Efficacy In Spared Pathways In An Anesthetized Rat Model Of Spinal Cord Contusion Injury

abstract: The purpose of this study was to assess the ability of intraspinal microstimulation (ISMS), triggered by action potentials (spikes) recorded in motor cortex, to alter synaptic efficacy in descending motor pathways in an anesthetized rat model of spinal cord injury (SCI). Experiments were carried out in adult, male, Sprague Dawley rats with a moderate contusion injury at T8. For activity-dependent stimulation (ADS) sessions, a recording microelectrode was used to detect neuronal spikes in motor cortex that triggered ISMS in the spinal cord grey matter. SCI rats were randomly assigned to one of four experimental groups differing by: a) cortical spike-ISMS stimulus delay (10 or 25 ms) and b) number of ISMS pulses (1 or 3). Four weeks after SCI, ADS sessions were conducted in three consecutive 1-hour conditioning bouts for a total of 3 hours. At the end of each conditioning bout, changes in synaptic efficacy were assessed using intracortical microstimulation (ICMS) to examine the number of spikes evoked in spinal cord neurons during 5-minute test bouts. A multichannel microelectrode recording array was used to record cortically-evoked spike activity from multiple layers of the spinal cord. The results showed that ADS resulted in an increase in cortically-evoked spikes in spinal cord neurons at specific combinations of spike-ISMS delays and numbers of pulses. Efficacy in descending motor pathways was increased throughout all dorsoventral depths of the hindlimb spinal cord. These results show that after an SCI, ADS can increase synaptic efficacy in spared pathways between motor cortex and spinal cord. This study provides further support for ADS as an effective therapeutic approach for enhancing descending motor control after SCI.


title: Energy deficit-independent stress response in the Frataxin-depleted heart: evidence that Integrated Stress Response can predominate over mTORC1 activation

abstract: Friedreichs ataxia (FRDA) is an inherited disorder caused by depletion of frataxin (FXN), a mitochondrial protein required for iron-sulfur cluster (ISC) biogenesis. Cardiac dysfunction is the main cause of death. Yet pathogenesis, and, more generally, how the heart adapts to FXN loss, remain poorly understood, though are expected to be linked to an energy deficit. We modified a transgenic (TG) mouse model of inducible FXN depletion that permits phenotypic evaluation of the heart at FXN levels < 20% of normal, without heart failure. We investigated substrate-specific bioenergetics and nutrient and stress signaling in the heart, to evaluate how this model responds to FXN depletion. After > 8 weeks with FXN levels < 20% of normal, TG hearts did not display overt hypertrophy and were in fact smaller; global protein translation was lower, while protein degradative pathways were unaltered. Cardiac contractility was maintained, likely due to preserved {beta}-oxidation, though oxidative phosphorylation capacity for pyruvate was lower. Bioenergetics alterations matched mitochondrial proteomics changes, including a non-uniform decrease in abundance of ISC-containing proteins. In parallel, both mTORC1 signaling and the integrated stress response (ISR) were activated. The lack of overt cardiac hypertrophy, consistent with lower global protein translation, suggests that ISR predominated over mTORC1 activation. Suppression of a major ATP demanding process could benefit the FXN-depleted heart, at least short term. Thus, the FXN-depleted heart may enter a protective state, not necessarily linked to a major energy deficit. Finally, we propose the model used here as a pre-clinical model of cardiomyopathy in FRDA.

category: biochemistry


title: scGRNom: a computational pipeline of integrative multi-omics analyses for predicting cell-type disease genes and regulatory networks

abstract: Understanding cell-type-specific gene regulatory mechanisms from genetic variants to diseases remains challenging. To address this, we developed an open-source computational pipeline, scGRNom, to predict the cell-type disease genes and regulatory networks from multi-omics data, including cell-type chromatin interactions, epigenomics, and single-cell transcriptomics. With applications to Schizophrenia and Alzheimers Disease, our predicted cell-type regulatory networks link transcription factors and enhancers to disease genes for excitatory and inhibitory neurons, microglia, and oligodendrocytes. The enrichments of cell-type disease genes reveal cross-disease and disease-specific functions and pathways. Finally, machine learning analysis found that cell-type disease genes shared by diseases have improved clinical phenotype predictions.


title: DNA methylation reveals distinct cells of origin for pancreatic neuroendocrine carcinomas (PanNECs) and pancreatic neuroendocrine tumors (PanNETs)

abstract: Pancreatic Neuroendocrine Carcinomas (PanNECs) are high-grade, poorly-differentiated tumors grouped together with Pancreatic Neuroendocrine Tumors (PanNETs) and placed within the Pancreatic Neuroendocrine Neoplasms (PanNENs) WHO tumor classification. Despite recent studies suggesting the endocrine origin of low-grade PanNETs, high-grade PanNEC origin remains unknown. DNA methylation analysis using the Illumina 850K beadchip array was conducted on 57 PanNEN samples, including 14 PanNECs. Distinct methylation profiles separated PanNEN samples into two major groups, clearly distinguishing high-grade PanNECs from other PanNETs including high-grade NETG3. DNA mutations, copy number changes and Immunohistochemistry of pancreatic cell-type markers PDX1, ARX and SOX9 were utilized to further characterize PanNECs and their hierarchical cell of origin in the pancreas. Phylo-epigenetic and cell-type signature features using methylation data from normal alpha, beta, acinar and ductal adult cells indicate an exocrine cell of origin for PanNECs, thus separating them in cell lineage from other PanNENs of endocrine origin. Our study provides a robust and clinically relevant method relying on methylation profiles to clearly distinguish PanNECs from PanNETG3s to improve patient stratification and treatment.


title: Co-occupancy analysis reveals novel transcriptional synergies for axon growth

abstract: Transcription factors (TFs) act as powerful levers to regulate neural physiology and can be targeted to improve cellular responses to injury or disease. Because TFs often depend on cooperative activity, a major challenge is to identify and deploy optimal sets. Here we developed a novel bioinformatics pipeline, centered on TF co-occupancy of regulatory DNA, and used it to predict factors that potentiate the effects of pro-regenerative Klf6. High content screens of neurite outgrowth identified cooperative activity by 12 candidates, and systematic testing in an animal model of corticospinal tract (CST) damage substantiated three novel instances of pairwise cooperation. Combined Klf6 and Nr5a2 drove the strongest growth, and transcriptional profiling of CST neurons identified Klf6/Nr5a2-responsive gene networks involved in macromolecule biosynthesis and DNA repair. These data identify novel TF combinations that promote enhanced CST growth, clarify the transcriptional correlates, and provide a bioinformatics roadmap to detect TF synergy.


title: State-dependent signatures of Anti-NMDA-Receptor Encephalitis: a dynamic functional connectivity study

abstract:
ObjectiveTraditional static functional connectivity (FC) analyses have shown functional network alterations in patients with anti-NMDA receptor encephalitis (NMDARE). Here, we use a dynamic FC approach that increases the temporal resolution of connectivity analyses from minutes to seconds. We hereby explore the spatiotemporal variability of large-scale brain network activity in NMDARE and assess the discriminatory power of functional brain states in a supervised classification approach.

MethodsWe included resting-state fMRI data from 57 patients and 61 controls to extract four discrete connectivity states and assess state-wise group differences in FC, dwell time, transition frequency, fraction time and occurrence rate. Additionally, for each state, logistic regression models with embedded feature selection were trained to predict group status in a leave-one-out cross-validation scheme.

ResultsCompared to controls, patients exhibited diverging dynamic FC patterns in three out of four states mainly encompassing the default-mode network and frontal areas. This was accompanied by a characteristic shift in the dwell time pattern and higher volatility of state transitions in patients. Moreover, dynamic FC measures were associated with disease severity, disease duration and positive and negative schizophrenia-like symptoms. Predictive power was highest in dynamic FC models and outperformed static analyses, reaching up to 78.6% classification accuracy.

ConclusionsBy applying time-resolved analyses, we disentangle state-specific FC impairments and characteristic changes in temporal dynamics not detected in static analyses, offering new perspectives on functional reorganization underlying NMDARE. Correlation of dynamic FC measures with disease symptoms and severity indicates their clinical relevance and potential as prognostic biomarkers in NMDARE.


title: High Content Screening and Proteomic Analysis Identify a Kinase Inhibitor that rescuespathological phenotypes in a Patient-Derived Model of Parkinson's Disease

abstract: Combining high throughput screening approaches with induced pluripotent stem cell (iPSC)-based disease modeling represents a promising unbiased strategy to identify therapies for neurodegenerative disorders. Here we applied high content imaging on iPSC-derived neurons from patients with familial Parkinsons disease bearing the G209A (p.A53T) -synuclein (Syn) mutation and launched a screening campaign on a small kinase inhibitor library. We thus identified the multi-kinase inhibitor BX795 that at a single dose effectively restores disease-associated neurodegenerative phenotypes. Proteomics profiling mapped the molecular pathways underlying the protective effects of BX795, comprising a cohort of 118 protein-mediators of the core biological processes of RNA metabolism, protein synthesis, modification and clearance, and stress response, all linked to the mTORC1 signaling hub. In agreement, expression of human p.A53T-Syn in neuronal cells affected key components of the mTORC1 pathway resulting in aberrant protein synthesis that was restored in the presence of BX795 with concurrent facilitation of autophagy. Taken together, we have identified a promising small molecule with neuroprotective actions as candidate therapeutic for PD and other protein conformational disorders.


title: Global FAW population genomic signature supports complex introduction events across the Old World

abstract: Native to the Americas, the invasive Spodoptera frugiperda (fall armyworm; FAW) was reported in West Africa in 2016, followed by chronological order of detections across the Old World and the hypothesis of an eastward Asia expansion. We explored population genomic signatures of American and Old World FAW and identified 12 maternal mitochondrial DNA genome lineages across the invasive range, while from 870 high-quality nuclear single nucleotide polymorphic DNA markers five distinct New World population clusters were identified, broadly reflected their native geographical ranges and absence of host-plant preferences. We identified unique admixed Old World populations, and admixed and non-admixed Asian FAW individuals, all of which suggested multiple introductions underpinned the pests global spread. Directional gene flow from the East into eastern Africa was also detected, in contrast to the west-to-east spread hypothesis. Our study demonstrated population genomic approaches via international partnership to address global emerging pest threats and biosecurity challenges.


title: Room Temperature Isothermal Colorimetric Padlock Probe Rolling Circle Amplification for Viral RNA Detection

abstract: Seasonal flu and pandemics, which account for millions of infections and hundreds of thousands of deaths, require rapid and reliable detection mechanisms to implement preventive and therapeutic measures. Current detection methods of viral infections have limitations in speed, accuracy, accessibility, and usability. This project presents a novel, widely applicable viral diagnostic test that uses a modified version of rolling circle amplification (RCA) to be sensitive, specific, direct RNA targeted, colorimetric and operable at room temperature. We are specifically detecting the following high-impact viruses: SARS-CoV-2, Influenza A (H1N1pdm09), and Influenza B (Victoria Lineage), although our test can be adapted to any viral infection. Results using synthetic viral DNA and RNA sequences show that our diagnostic test takes approximately one hour, detects femtomolar concentrations of RNA strands, and differentiates between virus strains. We believe implementing our diagnostic test will provide faster responses to future viral-related outbreaks for quicker societal recovery.

category: synthetic biology


title: Crystal structure of inhibitor-bound human MSPL that can activate high pathogenic avian influenza

abstract: Infection of certain influenza viruses is triggered when its hemagglutinin (HA) is cleaved by host cell proteases such as proprotein convertases and type II transmembrane serine proteases (TTSP). HA with a monobasic motif is cleaved by trypsin-like proteases, including TMPRSS2 and HAT, while the multibasic motif found in high pathogenicity avian influenza HA is cleaved by furin, PC5/6, or MSPL. MSPL belongs to the TMPRSS family and preferentially cleaves [R/K]-K-K-R{downarrow} sequences. Here, we solved the crystal structure of the extracellular region of human MSPL in complex with an irreversible substrate-analog inhibitor. The structure revealed three domains clustered around the C-terminal -helix of the SPD. The inhibitor structure and its putative model show that the P1-Arg inserts into the S1 pocket, whereas the P2-Lys and P4-Arg interacts with the Asp/Glu-rich 99-loop that is unique to MSPL. Based on the structure of MSPL, we also constructed a homology model of TMPRSS2, which is essential for the activation of the SARS-CoV-2 spike protein and infection. The model may provide the structural insight for the drug development for COVID-19.


title: Temporal hierarchy of intrinsic neural timescales converges with spatial core-periphery organization

abstract: The human cortex exhibits intrinsic neural timescales that shape a temporal hierarchy. Whether this temporal hierarchy follows the spatial hierarchy of its topography namely the core-periphery organization remains an open issue. Using Magnetoencephalography data, we investigate intrinsic neural timescales during rest and task states; we measure the autocorrelation window in short (ACW-50) and, introducing a novel variant, long (ACW-0) windows. We demonstrate longer ACW-50 and ACW-0 in networks located at the core compared to those at the periphery with rest and task states showing a high ACW correlation. Calculating rest-task differences, i.e., subtracting the shared core-periphery organization, reveals task-specific ACW changes in distinct networks. Finally, employing kernel density estimation, machine learning, and simulation, we demonstrate that ACW-0 exhibits better prediction in classifying a regions time window as core or periphery. Overall, our findings provide fundamental insight into how the human cortexs temporal hierarchy converges with its spatial core-periphery hierarchy.


title: Ethylene-triggered subcellular trafficking of CTR1 enhances the response to ethylene gas

abstract: Ethylene gas controls plant growth and stress responses. Ethylene-exposed dark-grown seedlings exhibit dramatic growth reduction, yet the seedlings rapidly return to the basal growth rate when ethylene gas is removed. However, the underlying mechanism governing this reversible acclimation of dark-grown seedlings to ethylene remains enigmatic. Here, we report that ethylene triggers the translocation of the Raf-like protein kinase CONSTITUTIVE TRIPLE RESPONSE1 (CTR1), a negative regulator of ethylene signaling, from the endoplasmic reticulum to the nucleus. Nuclear-localized CTR1 stabilizes the ETHYLENE-INSENSITIVE3 (EIN3) transcription factor via interaction with the EIN3-BINDING F-box (EBF) proteins, thus enhancing the ethylene response and delaying growth recovery. These findings uncover a mechanism of the ethylene signaling pathway that links the spatiotemporal dynamics of cellular signaling components to organismal responses.


title: Overlapping roles of JIP3 and JIP4 in promoting axonal transport of lysosomes in human iPSC-derived neurons

abstract: The dependence of neurons on microtubule-based motors for the movement of lysosomes over long distances raises questions about adaptations that allow neurons to meet these demands. Recently, JIP3/MAPK8IP3, a neuronally enriched putative adaptor between lysosomes and motors, was identified as a critical regulator of axonal lysosome abundance. In this study, we establish a human induced pluripotent stem cell (iPSC)-derived neuron model for the investigation of axonal lysosome transport and maturation and show that loss of JIP3 results in the accumulation of axonal lysosomes and the Alzheimers disease-related amyloid precursor protein (APP)-derived A{beta}42 peptide. We furthermore reveal an overlapping role of the homologous JIP4 gene in lysosome axonal transport. These results establish a cellular model for investigating the relationship between lysosome axonal transport and amyloidogenic APP processing and more broadly demonstrate the utility of human iPSC-derived neurons for the investigation of neuronal cell biology and pathology.


title: Steady-State Regulation of Secretory Cargo Export by Inositol Trisphosphate Receptors and Penta-EF-Hand Proteins

abstract: Ca2+ release by inositol trisphosphate receptors (IP3Rs) regulates diverse physiological processes in many cell types. Notably, agonist-stimulated Ca2+ signaling involving IP3Rs can modulate ER export rates through activation of the Ca2+-dependent adaptor ALG-2. It is unknown, however, whether IP3Rs and ALG-2 regulate ER export rates at steady state. Here we report that partial depletion of IP3Rs from normal rat kidney (NRK) epithelial cells caused a marked increase of ER export of the transmembrane cargo VSV-G. Depletion of IP3R-3, the major IP3R isoform in NRK cells, had a larger impact on secretion than the other extant isoform, IP3R-l. Under standard growth conditions, spontaneous cytosolic Ca2+ oscillations usually occurred simultaneously in successive groups of contiguous cells, generating intercellular Ca2+ waves (ICWs) that moved across the monolayer. Unexpectedly, IP3R-3-depleted cells exhibited increased cell participation in this spontaneous signaling. IP3R-3-depleted cells also exhibited increased agonist-dependent Ca2+ signaling, suggesting a general potentiation of the remaining IP3R channels. Increased spontaneous signaling was accompanied by increased ALG-2 and decreased peflin at ER exit sites (ERES), resulting in increased targeting of COPII coat to ERES. Furthermore, the increased secretion rate associated with IP3R depletion required ALG-2. Unexpectedly, IP3R depletion also resulted in partial depletion of ER luminal Ca2+ stores, though this phenomenon was not involved in the secretion change. We conclude that in NRK cells, IP3Rs regulate spontaneous Ca2+ signaling that helps determine the basal secretion rate by modulating COPII targeting to ERES. Furthermore, the IP3R channel density and/or isoform composition significantly impacts this phenomenon.


title: Visual processing and fold-change detection by the larva of the simple chordate Ciona

abstract: Visual processing transforms the complex visual world into useful information. Ciona, a close relative of vertebrates, has one of the simplest nervous systems known, yet has a range of visuomotor behaviors. Among them are negative phototaxis and a looming-shadow response. These two behaviors are mediated by separate photoreceptor groups acting via distinct, but overlapping, neural circuits. We show here that processing circuits underlying both behaviors transform visual inputs to generate fold-change detection (FCD) outputs. In FCD, the response scales with the relative fold changes in input, but is invariant to the overall magnitude of the stimulus. Several different circuit architectures can generate FCD responses. Both the behavioral outputs and the putative circuitry for the two visuomotor behaviors point to them using different FCD circuits. Pharmacological treatment points to circuits in the posterior brain vesicle of Ciona, a region we speculate shares homology with the vertebrate midbrain, as important for FCD.


title: Quantifying Numerical and Spatial Reliability of Amygdala and Hippocampal Subdivisions in FreeSurfer

abstract: On-going, large-scale neuroimaging initiatives can aid in uncovering neurobiological causes and correlates of poor mental health, disease pathology, and many other important conditions. As projects grow in scale with hundreds, even thousands, of individual participants and scans collected, quantification of brain structures by automated algorithms is becoming the only truly tractable approach. Here, we assessed the spatial and numerical reliability for newly deployed automated segmentation of hippocampal subfields and amygdala nuclei in FreeSurfer 7. In a sample of participants with repeated structural imaging scans (N=923), we found numerical reliability (as assessed by intraclass correlations, ICCs) was reasonable: [~]95% of hippocampal subfields have "excellent" numerical reliability (ICCs[≥]0.90), however, only 67% of amygdala subnuclei met this same threshold. Spatial reliability was similarly reasonable, with 58% of hippocampal subfields and 44% of amygdala subnuclei having Dice coefficients[≥]0.70. Notably, multiple regions had poor numerical and/or spatial reliability. We also examined correlations between spatial reliability and person-level factors (e.g., participant age; T1 image quality). Both sex and image scan quality were related to variations in spatial reliability metrics. Examined collectively, our work suggests caution should be exercised for a few hippocampal subfields and amygdala nuclei with more variable reliability.


title: Self-fertilization, but not mating strategy, predicts the evolution of sex allocation plasticity in a hermaphroditic flatworm genus

abstract: Sex allocation (SA) theory in simultaneous hermaphrodites predicts that optimal SA is influenced by local sperm competition (LSC), which occurs when related sperm compete to fertilize a given set of eggs. Different factors, including the mating strategy and the ability to self-fertilize, are predicted to affect LSC and hence the optimal SA. Moreover, since the LSC experienced by an individual can vary temporally and spatially, this can favour the evolution of SA plasticity. Here, using seven species of the free-living flatworm genus Macrostomum, we document sizable interspecific variation in SA, but neither their mating strategy nor their ability to self-fertilize significantly predicted SA among these species. Since we also found considerable interspecific variation in SA plasticity, we further estimated standardized effect sizes for plasticity in response to i) the presence of mating partners (i.e. in isolation vs. with partners) and ii) the strength of LSC (i.e. in small vs. large groups). We found that self-fertilization predicted SA plasticity with respect to the presence of mating partners, with plasticity being lower for self-fertilizing species. Finally, we showed that interspecific variation in SA is higher than intraspecific variation due to SA plasticity. Our study suggests that both SA and SA plasticity are evolutionarily labile, with self-fertilization predicting the latter in Macrostomum.


title: MAGI1 inhibits the AMOTL2/p38 stress pathway and prevents luminal breast tumorigenesis

abstract: Alterations to cell polarization or to intercellular junctions are often associated with epithelial cancer progression, including breast cancers (BCa). We show here that the loss of the junctional scaffold protein MAGI1 is associated with bad prognosis in luminal BCa, and promotes tumorigenesis. E-cadherin and the actin binding scaffold AMOTL2 accumulate in MAGI1 deficient cells which are subjected to increased stiffness. These alterations are associated with low YAP activity, the terminal Hippo-pathway effector, but with an elevated ROCK and p38 Stress Activated Protein Kinase activities. Blocking ROCK prevented p38 activation, suggesting that MAGI1 limits p38 activity in part through releasing actin strength. Importantly, the increased tumorigenicity of MAGI1 deficient cells is rescued in the absence of AMOTL2 or after inhibition of p38, demonstrating that MAGI1 acts as a tumor-suppressor in luminal BCa by inhibiting an AMOTL2/p38 stress pathway.


title: A comprehensive framework for handling location error in animal tracking data

abstract: Animal tracking data are being collected more frequently, in greater detail, and on smaller taxa than ever before. These data hold the promise to increase the relevance of animal movement for understanding ecological processes, but this potential will only be fully realized if their accompanying location error is properly addressed. Historically, coarsely-sampled movement data have proved invaluable for understanding large scale processes (e.g., home range, habitat selection, etc.), but modern fine-scale data promise to unlock far more ecological information. While GPS location error can often be ignored in coarsely sampled data, fine-scale data require more care, and tools to do this have not kept pace. Current approaches to dealing with location error largely fall into two categories--either discarding the least accurate location estimates prior to analysis or simultaneously fitting movement and error parameters in a hidden-state model. In some cases these approaches can provide a level of correction, but they have known limitations, and in some cases they can be worse than doing nothing. Here, we provide a general framework to account for location error in the analysis of triangulated and trilatcralizcd animal tracking data, which includes GPS, Argos Doppler-shift, triangulated VHF, trilatcralized acoustic and cellular location data. We apply our error-modelselection framework to 190 GPS, cellular, and acoustic devices representing 27 models from 14 manufacturers. Collectively, these devices were used to track a wide range of taxa comprising birds, fish, reptiles, and mammals of different sizes and with different behaviors, in urban, suburban, and wild settings. In almost half of the tested device models, error-model selection was necessary to obtain the best performing error model, and in almost a quarter of tested device models, the reported DOP values were actually misinformative. Then, using empirical tracking data from multiple species, we provide an overview of modern, error-informed movement analyses, including continuous-time path reconstruction, home-range distribution, home-range overlap, speed, and distance estimation. Adding to these techniques, we introduce new error-informed estimators for outlier detection and autocorrelation visualization. Because error-induced biases depend on many factors--sampling schedule, movement characteristics, tracking device, habitat, etc.--differential bias can easily confound biological inference and lead researchers to draw false conclusions. We demonstrate how error-informed analyses on calibrated tracking data can provide more accurate estimates are that are insensitive to location error, and allow researchers to use all of their data.


title: Predicting feral cat-reduction targets and costs on large islands using stochastic population models

abstract: Feral cats are some of the most destructive invasive predators worldwide, particularly in insular environments; hence, density-reduction campaigns are often applied to alleviate the predation mortality they add to native fauna. Density-reduction and eradication efforts are costly procedures with important outcomes for native fauna recovery, so they require adequate planning to be successful. These plans need to include empirical density-reduction models that can guide yearly culling quotas, and resource roll-out for the duration of the culling period. This ensures densities are reduced over the long term and that no resources are wasted. We constructed a stochastic population model with cost estimates to test the relative effectiveness and cost-efficiency of two main culling scenarios for a 10-year eradication campaign of cats on Kangaroo Island, Australia: (1) constant proportional annual cull (one-phase), and (2) high initial culling followed by a constant proportional maintenance cull (two-phase). A one-phase cull of at least 0.35 of the annual population size would reduce the final population to 0.1 of its original size, while a two-phase cull with an initial cull of minimum 0.6 and minimum 0.5 maintenance cull would reduce the final population to 0.01 of its initial size by 2030. Cost estimates varied widely depending on the methods applied (shooting, trapping, aerial poison baits, Felixer poison-delivery system), but using baiting, trapping and Felixers with additional shooting to meet culling quotas was the most cost-effective combination (minimum cost: AU$19.56 million; range: AU$16.87 million-AU$20.69 million). Our model provides an adaptable and general assessment tool for cat reductions in Australia and potentially elsewhere, and provides relative culling costs for the Kangaroo Island programme specifically.


title: LayNii: A software suite for layer-fMRI.

abstract:
High-resolution fMRI in the sub-millimeter regime allows researchers to resolve brain activity across cortical layers and columns non-invasively. While these high-resolution data make it possible to address novel questions of directional information flow within and across brain circuits, the corresponding data analyses are challenged by MRI artifacts, including image blurring, image distortions, low SNR, and restricted coverage. These challenges often result in insufficient spatial accuracy of conventional analysis pipelines. Here we introduce a new software suite that is specifically designed for layer-specific functional MRI: LayNii. This toolbox is a collection of command-line executable programs written in C/C++ and is distributed open-source and as pre-compiled binaries for Linux, Windows, and macOS. LayNii is designed for layer-fMRI data that suffer from SNR and coverage constraints and thus cannot be straightforwardly analyzed in alternative software packages. Some of the most popular programs of LayNii contain  layerification and columnarization in the native voxel space of functional data as well as many other layer-fMRI specific analysis tasks: layer-specific smoothing, model-based vein mitigation of GE-BOLD data, quality assessment of artifact dominated sub-millimeter fMRI, as well as analyses of VASO data.

HighlightsO_LIA new software toolbox is introduced for layer-specific functional MRI: LayNii.
C_LIO_LILayNii is a suite of command-line executable C++ programs for Linux, Windows, and macOS.
C_LIO_LILayNii is designed for layer-fMRI data that suffer from SNR and coverage constraints.
C_LIO_LILayNii performs layerification in the native voxel space of functional data.
C_LIO_LILayNii performs layer-smoothing, GE-BOLD deveining, QA, and VASO analysis.
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title: Deep multitask learning of gene risk for comorbid neurodevelopmental disorders

abstract: Autism Spectrum Disorder (ASD) and Intellectual Disability (ID) are comorbid neurodevelopmental disorders with complex genetic architectures. Despite large-scale sequencing studies only a fraction of the risk genes were identified for both. Here, we present a novel network-based gene risk prioritization algorithm named DeepND that performs cross-disorder analysis to improve prediction power by exploiting the comorbidity of ASD and ID via multitask learning. Our model leverages information from gene coexpression networks that model human brain development using graph convolutional neural networks and learns which spatio-temporal neurovelopmental windows are important for disorder etiologies. We show that our approach substantially improves the state-of-the-art prediction power in both single-disorder and cross-disorder settings. DeepND identifies prefrontal and primary motor-somatosensory cortex brain region, and periods from early fetal to mid fetal periods and from early childhood to young adulthood as the highest neurodevelopmental risk windows for both ASD and ID. Finally, we investigate frequent ASD and ID associated copy number variation regions and report our findings for several susceptibility gene candidates. DeepND can be generalized to analyze any combinations of comorbid disorders and is released at http://github.com/ciceklab/deepnd.


title: Metal-Organic Framework Encapsulated Whole-Cell Vaccines Enhance Humoral Immunity against Bacterial Infection

abstract: The increasing rate of resistance of bacterial infection against antibiotics requires next generation approaches to fight potential pandemic spread. The development of vaccines against pathogenic bacteria has been difficult owing, in part, to the genetic diversity of bacteria. Hence, there are many potential target antigens and little a priori knowledge of which antigen/s will elicit protective immunity. The painstaking process of selecting appropriate antigens could be avoided with whole-cell bacteria; however, whole-cell formulations typically fail to produce long-term and durable immune responses. These complications are one reason why no vaccine against any type of pathogenic E. coli has been successfully clinically translated. As a proof of principle, we demonstrate a method to enhance the immunogenicity of a model pathogenic E. coli strain by forming a slow releasing depot. The E. coli strain CFT073 was biomimetically mineralized within a metal-organic framework (MOF). This process encapsulates the bacteria within 30 minutes in water and at ambient temperatures. Vaccination with this new formulation substantially enhances antibody production and results in significantly enhanced survival in a mouse model of bacteremia compared to standard inactivated formulations.


title: Nuclear and cellular, micro and nano calcification in Alzheimer's disease patients and correlation to phosphorylated Tau.

abstract: Brain calcification (calcium phosphate mineral formation) has been reported in the past 100 years in the brains of Alzheimers disease (AD) patients. However, the association between calcification and AD, the triggers for calcification, and its role within the disease are not clear. On the other hand, hyperphosphorylated tau protein (pTau) tangles have been widely studied and recognized as an essential factor in developing AD. In this work, calcification in the brains of AD patients is characterized by advanced electron microscopy and fluorescence microscopy. Results are then compared to samples from cognitively healthy, age-matched donors, and the colocalization of calcification and pTau is investigated. Here, we show that AD patients brains present microcalcification associated with the neural cell nuclei and cell projections, and that these are strongly related to the presence of pTau. The link between microcalcification and pTau suggests a potential new mechanism of brain cell damage. Together with the formation of amyloid plaques and neurofibrillary tangles, microcalcification in neuronal cells adds to a better understanding of the pathology of AD. Finally, the presence of microcalcification in the neuronal cells of AD patients may assist in AD diagnosis, and may open new avenues for developing intervention strategies based on inhibition of calcification.

category: pathology


title: Human Prefoldin Modulates Co-transcriptional Pre-mRNA Splicing

abstract: Prefoldin is a heterohexameric complex conserved from archaea to humans that plays a cochaperone role during the co-translational folding of actin and tubulin monomers. Additional functions of prefoldin have been described, including a positive contribution to transcription elongation and chromatin dynamics in yeast. Here we show that prefoldin perturbations provoked transcriptional alterations across the human genome. Severe pre-mRNA splicing defects were also detected, particularly after serum stimulation. We found impairment of co-transcriptional splicing during transcription elongation, which explains why the induction of long genes with a high number of introns was affected the most. We detected genome-wide prefoldin binding to transcribed genes and found that it correlated with the negative impact of prefoldin depletion on gene expression. Lack of prefoldin caused global decrease in Ser2 and Ser5 phosphorylation of the RNA polymerase II carboxy-terminal domain. It also reduced the recruitment of the CTD kinase CDK9 to transcribed genes, and the association of splicing factors PRP19 and U2AF65 to chromatin, which is known to depend on CTD phosphorylation. Altogether the reported results indicate that human prefoldin is able to act locally on the genome to modulate gene expression by influencing phosphorylation of elongating RNA polymerase II, and thereby regulating co-transcriptional splicing.


title: Dissecting Response to Cancer Immunotherapy by Applying Bayesian Network Analysis to Flow Cytometry Data

abstract: Cancer immunotherapy, specifically immune checkpoint blockade therapy, has been found to be effective in the treatment of metastatic cancers. However, only a subset of patients achieve clinical responses. Consequently, elucidating immune system-related pre-treatment biomarkers that are predictive with respect to sustained clinical response is a major research priority. Another research priority is evaluating changes in the immune system before and after treatment in responders and non-responders. Our group has been studying immune signaling networks as an accurate reflection of the global immune state. Flow cytometry (FACS, Fluorescence-activated cell sorting) data characterizing immune signaling in peripheral blood mononuclear cells (PBMC) from gastroesophageal adenocarcinoma (GEA) patients were used to analyze changes in immune signaling networks in this setting. Here, we describe a novel computational pipeline developed by us to perform secondary analyses of FACS data using systems biology / machine learning techniques and concepts. It is centered around comparative Bayesian network analyses of immune signaling networks and is capable of detecting true positive signals that conventional methods (such as FlowJo manual gating) might miss. Future studies are planned to validate and follow up immune markers (and combinations / interactions thereof) associated with clinical responses that were identified by this computational pipeline.


title: Robustness in spiking networks: a geometric perspective

abstract: Neural systems are remarkably robust against various perturbations, a phenomenon that still requires a clear explanation. Here, we graphically illustrate how neural networks can become robust. We study spiking networks that generate low-dimensional representations, and we show that the neurons subthreshold voltages are confined to a convex region in a lower-dimensional voltage subspace, which we call a  bounding box. Any changes in network parameters (such as number of neurons, dimensionality of inputs, firing thresholds, synaptic weights, or transmission delays) can all be understood as deformations of this bounding box. Using these insights, we show that functionality is preserved as long as perturbations do not destroy the integrity of the bounding box. We suggest that the principles underlying robustness in these networks--low-dimensional representations, heterogeneity of tuning, and precise negative feedback--may be key to understanding the robustness of neural systems at the circuit level.


title: Collective motion as a distinct behavioral state of the individual

abstract: The collective motion of swarms depends on adaptations at the individual level. We explored these and their effects on swarm formation and maintenance in locusts. The walking kinematics of individual insects were monitored under laboratory settings, before, as well as during collective motion in a group, and again after separation from the group. It was found that taking part in collective motion induced in the individual unique behavioural kinematics, suggesting the existence of a distinct behavioural mode that we term a "collective-motion-state". This state, characterized by behavioural adaptation to the social context, is long lasting, not induced by crowding per-se, but only by experiencing collective motion. Utilizing computational models, we show that this adaptability increases the robustness of the swarm. Overall, our findings suggest that collective-motion is not only an emergent property of the group, but also depends on a behavioural mode, rooted in endogenous mechanisms of the individual.


title: Diet-regulated production of PDGFcc by macrophages controls energy storage

abstract: Macrophages control inflammation in obese animals, and may also directly or indirectly regulate energy storage. In a genetic screen we identify a PDGF-family growth factor, Pvf3, produced by macrophages and required for lipid storage in Drosophila larvaes fat body cells. We next demonstrate using genetic and pharmacological approaches that Pvf3 ortholog PDGFcc, produced by Ccr2-independent embryo-derived tissue macrophages, is also required for storage in mammalian white adipose tissue. PDGFcc production by resident macrophages is regulated by diet, acts on white adipocytes in a paracrine manner, and controls adipocyte hypertrophy in high-fat diet fed and genetically hyperphagic mice. Upon PDGFcc blockade, excess lipids are redirected at the organismal level toward thermogenesis and hepatic storage in adults. This process is altogether independent from inflammation and insulin resistance promoted by Ccr2-dependent monocytes/macrophages. Our data identify a conserved macrophagedependent mechanism that controls energy storage, conducive to the design of pharmacological interventions.


title: Prediction of amphipathic helix - membrane interactions with Rosetta

abstract: Amphipathic helices have hydrophobic and hydrophilic/charged residues situated on opposite faces of the helix. They can anchor peripheral membrane proteins to the membrane, be attached to integral membrane proteins, or exist as independent peptides. Despite the widespread presence of membrane-interacting amphipathic helices, there is no computational tool within Rosetta to model their interactions with membranes. In order to address this need, we developed the AmphiScan protocol with PyRosetta, which runs a grid search to find the most favorable position of an amphipathic helix with respect to the membrane. The performance of the algorithm was tested in benchmarks with the RosettaMembrane, ref2015_memb, and franklin2019 score functions on six engineered and 44 naturally-occurring amphipathic helices using membrane coordinates from the OPM and PDBTM databases, OREMPRO server, and MD simulations for comparison. The AmphiScan protocol predicted the coordinates of amphipathic helices within less than 3[A] of the reference structures and identified membrane-embedded residues with a Matthews Correlation Constant (MCC) of up to 0.57. Overall, AmphiScan stands as fast, accurate, and highly-customizable protocol that can be pipelined with other Rosetta and Python applications.


title: A learned map for places and concepts in the human MTL

abstract:
Distinct lines of research in both humans and animals point to a specific role of the hippocampus in both spatial and episodic memory function. The discovery of concept cells in the hippocampus and surrounding medial-temporal lobe (MTL) regions suggests that the MTL maps physical and semantic spaces with a similar neural architecture. Here, we studied the emergence of such maps using MTL micro-wire recordings from 20 patients navigating a virtual environment featuring salient landmarks with established semantic meaning. We present several key findings: The array of local field potentials in the MTL contains sufficient information to decode subjects instantaneous location in the environment. Closer examination revealed that the field potentials represent both the subjects locations in virtual space and in high-dimensional semantic space. We further show that both spatial and semantic representations strengthen over time. This learning effect appears as subjects increase their knowledge of the environments spatial and semantic layout. Similarly, we observe a learning effect on temporal sequence coding. Over time, field potentials come to represent future locations, even after controlling for spatial proximity. This predictive coding of future states, more so than the strength of spatial representations per se, explains variability in subjects navigation performance. Our results thus support the conceptualization of the MTL as a memory space, building semantic knowledge, spatial and non-spatial, from episodic experience to plan future actions and predict their outcomes.

Significance statementUsing rare micro-wire recordings, we studied the representation of spatial, semantic and temporal information in the human MTL. Our findings demonstrate that subjects acquire a cognitive map that simultaneously represents the spatial and semantic relations between landmarks. We further show that the same learned representation is used to predict future states, implicating MTL cell assemblies as the building blocks of prospective memory functions.


title: Improving oligo-conjugated antibody signal in multimodal single-cell analysis

abstract:
Simultaneous measurement of surface proteins and gene expression within single cells using oligo-conjugated antibodies offers high resolution snapshots of complex cell populations. Signal from oligo-conjugated antibodies is quantified by high-throughput sequencing and is highly scalable and sensitive. In this study, we investigated the response of oligo-conjugated antibodies towards four variables: Concentration, staining volume, cell number at staining, and tissue. We find that staining with recommended antibody concentrations cause unnecessarily high background and that concentrations can be drastically reduced without loss of biological information. Reducing volume only affects antibodies targeting abundant epitopes used at low concentrations and is counteracted by reducing cell numbers. Adjusting concentrations increases signal, lowers background and reduces costs. Background signal can account for a major fraction of the total sequencing and is primarily derived from antibodies used at high concentrations. Together, this study provides new insight into the titration response and background of oligo-conjugated antibodies and offers concrete guidelines on how such panels can be improved.

Impact statementOligo-conjugated antibodies are a powerful tool but require thorough optimization to reduce background signal, increase sensitivity, and reduce sequencing costs.


title: Integrated analysis of glycan and RNA in single cells

abstract: Single-cell sequencing has emerged as an indispensable technology to dissect cellular heterogeneity but never been applied to the simultaneous analysis of glycan and RNA. Using oligonucleotide-labeled lectins, we first established lectin-based glycan profiling of single cells by sequencing (scGlycan-seq). We then combined the scGlycan-seq with single-cell transcriptome profiling (scRNA-seq) for joint analysis of glycan and RNA in single cells (scGR-seq). Using scGR-seq, we analyzed the two modalities in human induced pluripotent stem cells (hiPSCs) before and after differentiation into neural progenitor cells at the single cell resolution. The combination of RNA and glycan separated the two cell types clearer than either one of them. Furthermore, integrative analysis of glycan and RNA modalities in single cells found known and novel lectins that were specific to hiPSCs and coordinated with neural differentiation. Taken together, we demonstrate that scGR-seq can reveal the cellular heterogeneity and biological roles of glycans across multicellular systems.


title: Beyond category-supervision: instance-level contrastive learning models predict human visual system responses to objects

abstract: Anterior regions of the ventral visual stream encode substantial information about object categories. Are top-down category-level forces critical for arriving at this representation, or can this representation be formed purely through domain-general learning of natural image structure? Here we present a fully self-supervised model which learns to represent individual images, rather than categories, such that views of the same image are embedded nearby in a low-dimensional feature space, distinctly from other recently encountered views. We find (i) category information implicitly emerges in the local similarity structure of this feature space, and (ii) these models learn hierarchical features which capture the structure of brain responses across the human ventral visual stream, on par with category-supervised models. These results provide computational support for a domain-general framework guiding the formation of visual representation, where the proximate goal is not explicitly about category information, but is instead to learn unique, compressed descriptions of the visual world.


title: Beyond category-supervision: Computational support for domain-general pressures guiding human visual system representation


title: A self-supervised domain-general learning framework for human ventral stream representation