title: longfin causes cis-ectopic expression of the kcnh2a ether-a-go-go K+ channel to autonomously prolong fin outgrowth

abstract: Organs stop growing to achieve a characteristic size and shape in scale with the animals body. Likewise, regenerating organs sense injury extents to instruct appropriate replacement growth. Fish fins exemplify both phenomena through their tremendous diversity of form and remarkably robust regeneration. The classic zebrafish mutant longfint2 develops and regenerates dramatically elongated fins and underlying ray skeleton. We show longfint2 chromosome 2 overexpresses the ether-a-go-go-related voltage-gated potassium channel kcnh2a. Genetic disruption of kcnh2a in cis rescues longfint2, indicating longfint2 is a regulatory kcnh2a allele. We find longfint2 fin overgrowth originates from prolonged outgrowth periods including by showing Kcnh2a chemical inhibition during late stage regeneration fully suppresses overgrowth. Cell transplantations demonstrate longfint2-ectopic kcnh2a acts tissue autonomously within the fin intra-ray mesenchymal lineage. Temporal inhibition of the Ca2+-dependent phosphatase calcineurin indicates it likewise entirely acts late in regeneration to attenuate fin outgrowth. Epistasis experiments suggest longfint2-expressed Kcnh2a inhibits calcineurin output to supersede growth cessation signals. We conclude ion signaling within the growth-determining mesenchyme lineage controls fin size by tuning outgrowth periods rather than altering positional information or cell-level growth potency.


title: Ancestral mitochondrial apparatus derived from the bacterial type II secretion system

abstract: The type 2 secretion system (T2SS) is present in some Gram-negative eubacteria and used to secrete proteins across the outer membrane. Here we report that certain representative heteroloboseans, jakobids, malawimonads and hemimastigotes unexpectedly possess homologues of core T2SS components. We show that at least some of them are present in mitochondria, and their behaviour in biochemical assays is consistent with the presence of a mitochondrial T2SS-derived system (miT2SS). We additionally identified 23 protein families co-occurring with miT2SS in eukaryotes. Seven of these proteins could be directly linked to the core miT2SS by functional data and/or sequence features, whereas others may represent different parts of a broader functional pathway, possibly also involving the peroxisome. Its distribution in eukaryotes and phylogenetic evidence together indicate that the miT2SS-centred pathway is an ancestral eukaryotic trait. Our findings thus have direct implications for the functional properties of the early mitochondrion.

category: evolutionary biology


title: Analysis of diverse eukaryotes suggests the existence of an ancestral 1 mitochondrial apparatus derived from the bacterial type II secretion system


title: Cold exposure drives weight gain and adiposity following chronic suppression of brown adipose tissue

abstract: Therapeutic activation of thermogenic brown adipose tissue (BAT) may be feasible to prevent, or treat, cardiometabolic disease. However, rodents are commonly housed below thermoneutrality ([~]20{degrees}C) which can modulate their metabolism and physiology including the hyperactivation of brown (BAT) and beige white adipose tissue. We housed animals at thermoneutrality from weaning to chronically supress BAT, mimic human physiology and explore the efficacy of chronic, mild cold-exposure and {beta}3-adrenoreceptor agonism under these conditions. Using metabolic phenotyping and exploratory proteomics we show that transfer from 28{degrees}C to 20{degrees}C drives weight gain and a 125% increase in subcutaneous fat mass, an effect not seen with YM-178 administration thus suggesting a direct effect of a cool ambient temperature in promoting weight gain and further adiposity in obese rats. Following chronic suppression of BAT, uncoupling protein 1 mRNA was undetectable in IWAT in all groups. Using exploratory adipose tissue proteomics, we reveal novel gene ontology terms associated with cold-induced weight gain in BAT and IWAT whilst Reactome pathway analysis highlights the regulation of mitotic (i.e. G2/M transition) and metabolism of amino acids and derivatives pathways. Conversely, YM-178 had minimal metabolic-related effects but modified pathways involved in proteolysis (i.e. eukaryotic translation initiation) and RNA surveillance across both tissues. Taken together these findings are indicative of a novel mechanism whereby animals increase body weight and fat mass following chronic suppression of adaptive thermogenesis from weaning. In addition, treatment with a B3-adrenoreceptor agonist did not improve metabolic health in obese animals raised at thermoneutrality.

category: physiology


title: A parametrized computational framework for description and design of genetic circuits of morphogenesis based on contact-dependent signaling and changes in cell-cell adhesion

abstract: Synthetic development is a nascent field of research that uses the tools of synthetic biology to design genetic programs directing cellular patterning and morphogenesis in higher eukaryotic cells, such as mammalian cells. One specific example of such synthetic genetic programs was based on cell-cell contact-dependent signaling using synthetic Notch pathways, and was shown to drive formation of multilayered spheroids by modulating cell-cell adhesion via differential expression of cadherin-family proteins. The design method for these genetic programs relied on trial and error, which limited the number of possible circuits and parameter ranges that could be explored. Here we build a parametrized computational framework that, given a cellcell communication network driving changes in cell adhesion and initial conditions as inputs, predicts developmental trajectories. We first built a general computational framework where contact-dependent cell-cell signaling networks and changes in cell-cell adhesion could be designed in a modular fashion. We then use a set of available in vitro results (that we call the "training set" in analogy to similar pipelines in the machine learning field) to parametrize the computational model with values for adhesion and signaling. We then show that this parametrized model can qualitatively predict experimental results from a "testing set" of available in vitro data that varied the genetic network in terms of adhesion combinations, initial number of cells and even changes to the network architecture. Finally, this parametrized model is used to recommend novel network implementation for the formation of a 4-layered structure that has not been reported previously. The framework that we develop here could function as a testing ground to identify the reachable space of morphologies that can be obtained by controlling contact-dependent cell-cell communications and adhesion. Additionally, we discuss how the model could be expanded to include other forms of communication or effectors for the computational design of the next generation of synthetic developmental trajectories.

category: synthetic biology


title: Noncoding RNAs endogenously rule the cancerous regulatory realm while proteins govern the normal

abstract: All cancers share a commonality in genome activation regulated by a systems endogenous network distinct from normal tissue, but such a network remains elusive. Here, we unearth a systems regulatory network endogenous for all types of cancers and normal human respectively from massive data, including all RNAseq data available from SRA and TCGA, and reveal distinctive systems realm for cancer and normal. In the cancerous realm, noncoding RNAs, especially pseudogenes, dominate endogenous network modules and centrality, and they work as the strongest systems inducers that cis-regulate their targets. However in the normal realm proteins dominate the entire endogenous network centrally controlled by ribosomal proteins and they trans-regulate their targets. Our finding establishes a systems picture of an endogenous mechanism overlooking the cancerous and normal realm, in which noncoding RNAs rule the overall cancer realm while proteins govern the normal one. This fundamentally refreshes the conventional concept of cancerous mechanism.

category: genomics


title: Functional single-cell genomics of human cytomegalovirus infection

abstract: The complex life cycle of herpesviruses is orchestrated by the interplay of host factors and hundreds of viral genes. Understanding how they work together and how perturbations of viral and host factors impact infection represents both a fundamental problem in virology and the basis for designing antiviral interventions. Here, we use CRISPR screening to comprehensively define the functional contribution of each viral and host factor to human cytomegalovirus (HCMV) infection in primary cells. We then record the transcriptomes of tens of thousands of single cells, and monitor how genetic perturbation of critical host and viral factors alters the timing, course, and progression of infection. We find that normally, the large majority of cells follow a stereotypical transcriptional trajectory. Perturbing critical host factors does not change this trajectory per se, but can either stall, delay or accelerate progression along the trajectory, allowing us to pinpoint systematically the stage of infection at which each host factor acts. Conversely, perturbation of viral factors can create distinct, abortive trajectories. Our results reveal a dichotomy between the roles of host and viral factors and more generally provide a road map for functional dissection of host-pathogen interactions.

category: systems biology


title: Polygenic adaptation after a sudden change in environment

abstract: Polygenic adaptation is thought to be ubiquitous, yet remains poorly understood. Here, we model this process analytically, in the plausible setting of a highly polygenic, quantitative trait that experiences a sudden shift in the fitness optimum. We show how the mean phenotype changes over time, depending on the effect sizes of loci that contribute to variance in the trait, and characterize the allele dynamics at these loci. Importantly, we describe the two phases of the allele dynamics: a rapid phase in which directional selection introduces small frequency differences between alleles whose effects are aligned with or opposed to the shift, which ultimately lead to small differences in their probability of fixation during a second, longer phase, governed by stabilizing selection. As we discuss, our key results should hold in more general settings, and have important implications for efforts to identify the genetic basis of adaptation in humans and other species.


title: Minimal DNA Electron Transfer Catalysts Switched by a Chaotropic Ion

abstract: Here we demonstrate that a DNA nanodevice can perform switchable electron transfer. The nanodevice is comprised of two strands, one of which can be selectively switched between a G-quadruplex and duplex or single-stranded conformations. In the G-quadruplex state, it binds the cofactor hemin, enabling peroxidase activity. This switching ability arises from our discovery that perchlorate, a chaotropic Hofmeister ion, selectively destabilizes duplex over G-quadruplex DNA. By varying perchlorate concentration, we show that the device can be switched between states that do and do not catalyze electron transfer catalysis. State switching can be achieved in three ways: thermally, by dilution, or by concentration. In each case, when operated in the presence of the cofactor hemin, the device catalyzes electron transfer in only the G-quadruplex state.


title: Range expansion shifts clonal interference patterns in evolving populations

abstract: Increasingly, predicting and even controlling evolutionary processes is a sought after goal in fields ranging from agriculture, artificial intelligence, astrobiology, oncology, and infectious diseases. However, our ability to predict evolution and plan such interventions in real populations is limited in part by our understanding of how spatial structure modulates evolutionary dynamics. Among current clinical assays applied to predict drug response in infectious diseases, for instance, many do not explicitly consider spatial structure and its influence on phenotypic heterogeneity, despite it being an inextricable characteristic of real populations. As spatially structured populations are subject to increased interference of beneficial mutants compared to their well-mixed counter-parts, among other effects, this population heterogeneity and structure may non-trivially impact drug response. In spatially-structured populations, the extent of this mutant interference is density dependent and thus varies with relative position within a meta-population in a manner modulated by mutant frequency, selection strength, migration speed, and habitat length, among other factors. In this study, we examine beneficial mutant fixation dynamics along the front of an asexual population expanding its range. We observe that multiple distinct evolutionary regimes of beneficial mutant origin-fixation dynamics are maintained at characteristic length scales along the front of the population expansion. Using an agent-based simulation of range expansion with mutation and selection in one dimension, we measure these length scales across a range of population sizes, selection strengths, and mutation rates. Furthermore, using simple scaling arguments to adapt theory from well-mixed populations, we find that the length scale at the tip of the front within which  local mutant fixation occurs in a successive mode decreases with increasing mutation rate, as well as population size in a manner predicted by our derived analytic expression. Finally, we discuss the relevance of our findings to real cellular populations, arguing that this conserved region of successive mutant fixation dynamics at the wave tip can be exploited by emerging evolutionary control strategies.


title: Lytic infection with murine gammaherpesvirus 68 activates host and viral RNA polymerase III-dependent promoters to enhance non-coding RNA expression

abstract:
RNA polymerase III (pol III) transcribes multiple non-coding (nc) RNAs that are essential for cellular function. Pol III-dependent transcription is also engaged during certain viral infections, including the gammaherpesviruses ({gamma}HVs), where pol III-dependent viral ncRNAs promote pathogenesis. Additionally, several host ncRNAs are upregulated during {gamma}HV infection and play integral roles in pathogenesis by facilitating viral establishment and gene expression. Here, we sought to investigate how pol III promoters and transcripts are regulated during gammaherpesvirus infection using the murine gammaherpesvirus 68 ({gamma}HV68) system. To compare the transcription of host and viral pol III-dependent ncRNAs, we analyzed a series of pol III promoters for host and viral ncRNAs using a luciferase reporter optimized to measure pol III activity. We measured promoter activity from the reporter gene at the translation level via luciferase activity and at the transcription level via RT-qPCR. We further measured endogenous ncRNA expression at single cell-resolution by flow cytometry. These studies demonstrated that lytic infection with {gamma}HV68 increased the transcription from multiple host and viral pol III promoters, and further identified the ability of accessory sequences to influence both baseline and inducible promoter activity after infection. RNA flow cytometry revealed the induction of endogenous pol III-derived ncRNAs that tightly correlated with viral gene expression. These studies highlight how lytic gammaherpesvirus infection alters the transcriptional landscape of host cells to increase pol III-derived RNAs, a process that may further modify cellular function and enhance viral gene expression and pathogenesis.

IMPORTANCEGammaherpesviruses are a prime example of how viruses can alter the host transcriptional landscape to establish infection. Despite major insights into how these viruses modify RNA polymerase II-dependent generation of messenger RNAs, how these viruses influence the activity of host RNA polymerase III remains much less clear. Small non-coding RNAs produced by RNA polymerase III are increasingly recognized to play critical regulatory roles in cell biology and virus infection. Studies of RNA polymerase III dependent transcription are complicated by multiple promoter types and diverse RNAs with variable stability and processing requirements. Here, we characterized a reporter system to directly study RNA polymerase III-dependent responses during gammaherpesvirus infection and utilized single-cell flow cytometry-based methods to reveal that gammaherpesvirus lytic replication broadly induces pol III activity to enhance host and viral non-coding RNA expression within the infected cell.

category: microbiology


title: Representation of Task Structure in Human Hippocampus and Orbitofrontal Cortex

abstract: The hippocampus is thought to support episodic memory, or memory for specific events, but recent work also suggests that it may be involved in extracting structure from the world to guide future decisions and predictions. Recent evidence in rodents suggests that the hippocampus supports decision-making in cooperation with orbitofrontal cortex (OFC), possibly based on representation of task structure. Here, we used functional magnetic resonance imaging (fMRI) to test how the human hippocampus and OFC represents decision-relevant information extracted from previous experiences. Participants performed a task in which they learned values of different foods in grocery store contexts. The task was structured such that we could examine the degree to which neural representations could reflect generalized information about different task structures. Specifically, we manipulated whether a foods desirability varied with store context or not. Some foods were desirable in some store contexts and not in others; some foods were always desirable or undesirable. Participants needed to extract these two task sub-structures (i.e., context-determined vs. context-invariant) from the task structure. We examined hippocampal and OFC activity patterns during a decision-making task after participants were trained with the task structure. Our results showed that both hippocampus and OFC carried task structure information that was relevant to the decision outcomes. Hippocampal and lateral OFC representations differentiated between context-determined (deterministic) and context-invariant (probabilistic) task structures. The degree of this differentiation, an index of task structure representation, was highly correlated between hippocampus and lateral OFC. These results add to a mounting evidence suggesting that the hippocampus and OFC support decision-making by representing task relevant information to the decision outcomes after the task structure is learned.

category: neuroscience


title: Replacement of microglia by brain-engrafted macrophages provide protection against concussive injury

abstract: Brain resident microglia have a distinct origin compared to macrophages in other organs. Under physiological conditions, microglia are maintained by self-renewal from the local pool, independent of hematopoietic progenitors. Pharmacological depletion of microglia during therapeutic whole-brain irradiation prevents synaptic loss and long-term recognition memory deficits but the mechanisms behind these protective effects are unknown. Here we demonstrate that after a combination of therapeutic whole-brain irradiation and microglia depletion, macrophages originating from circulating monocytes engraft into the brain and replace the microglia pool. Comparisons of transcriptomes reveal that brain-engrafted macrophages have an intermediate phenotype that resembles both monocytes and embryonic microglia. Brain-engrafted macrophages display reduced phagocytic activity for synaptic compartments compared to microglia from normal brains in response to a secondary concussive brain injury. In addition to sparing mice from brain radiotherapy-induced long-term cognitive deficits, replacement of microglia by brain-engrafted macrophages can prevent concussive injury-induced memory loss. These results demonstrate the long-term functional role of brain-engrafted macrophages as a possible therapeutic tool against radiation-induced cognitive deficits.


title: Replacement of microglia by brain-engrafted macrophages provide long term protection against brain irradiation and concussive injury


title: Brain-engrafted macrophages provide protection against therapeutic irradiation and secondary concussive injury


title: Context-invariant neural dynamics underlying the encoding of Bayesian uncertainty, but not confidence

abstract:
Classic decision theories, such as reinforcement learning, typically require the presence of explicit outcomes for learning and belief updating. However, ecological environments are often opaque and explicit feedback, such as those based on values, might not be immediately accessible. It remains unclear whether the neural dynamics underlying belief updating in absence of outcomes differ from those responsible for decision-making based on accessible outcomes. Here, we investigated this question in healthy humans (n=28) using Bayesian modeling and two multi-option fMRI tasks, one with and one without immediate outcome. Model-based fMRI analysis revealed two opposing networks encoding belief updating regardless of the presence of immediate outcomes. A "confidence-building" network including the hippocampus, amygdala, and medial prefrontal cortex (mPFC) became more active as beliefs about action-outcome probabilities were confirmed by newly acquired information. Meanwhile, an "uncertainty-building" network including the anterior insular (AIC), dorsal anterior cingulate (dACC), and dorsolateral prefrontal (dlPFC) cortices became more active as new evidence conflicted with action-outcome estimates. Interestingly, dynamic causal modeling revealed that the confidence network was driven either by the hippocampus when outcomes were not available, or by the mPFC and amygdala when value-based outcomes were immediately accessible. Convsersely, the AIC always drove the activities of dACC and dlPFC, under the modulation of increasing uncertainty, independent of outcome availability. These findings reveal similar network compositions but distinct neural dynamics underlying belief updating in changing environments with and without explicit outcomes, highlighting an asymmetric relationship between decision confidence and uncertainty computation across levels of analysis.

HighlightsO_LIWe investigated belief updating in two tasks, with and without explicit feedback.
C_LIO_LIModel-based fMRI analysis revealed similar neural responses across tasks.
C_LIO_LIThe anterior insula drove an uncertainty-encoding network, across tasks.
C_LIO_LIThe anterior hippocampus drove a confidence-encoding network, w/o feedbacks.
C_LIO_LIThe medial PFC and amygdala drove a confidence-encoding network, with feedbacks.
C_LI


title: Platinum chemotherapy induces lymphangiogenesis in cancerous and healthy tissues that can be prevented with adjuvant anti-VEGFR3 therapy

abstract:
Chemotherapy has been used to inhibit cancer growth for decades, but emerging evidence shows it can affect the tumor stroma unintentionally promoting cancer malignancy. After treatment of primary tumors, remaining drugs drain via lymphatics. Though all drugs interact with the lymphatics, we know little of their impact on them. Here, we show a previously unknown effect of platinums, a widely used class of chemotherapeutics, to directly induce systemic lymphangiogenesis and activation. These changes are dose-dependent, long-lasting, and occur in healthy and cancerous tissue in multiple mouse models of breast cancer. We saw similar effects in human ovarian and breast cancer patients whose treatment regimens included platinums. Carboplatin treatment of healthy mice prior to mammary tumor inoculation increases cancer metastasis as compared to no pre-treatment. These platinum-induced phenomena could be blocked by VEGFR3 inhibition. These findings have implications for cancer patients receiving platinums and may support the inclusion of anti-VEGFR3 therapy into treatment regimens or differential design of treatment regimens to alter these potential effects.

SummaryPlatinum chemotherapy induces VEGFR3-dependent lymphangiogenesis, priming tissues for metastasis of breast cancer. Inhibition of VEGFR3 via antibody blockade can reverse these effects.

category: cancer biology


title: Amitosis confers benefits of sex in the absence of sex to Tetrahymena

abstract: Sex appears to be the most successful reproductive strategy in eukaryotes despite its many costs. While a complete explanation for sexs success remains elusive, several evolutionary benefits of sex have been identified. It is predicted that, by forgoing these benefits, asexual lineages are evolutionary dead-ends. Consistent with this prediction, many asexual lineages show signs of accelerated accumulation of deleterious mutations compared to their sexual relatives. Despite these low expectations, some asexual eukaryotic lineages appear to be successful, including the ciliate Tetrahymena. Here, we show that the mechanism of somatic nuclear division in Tetrahymena, known as amitosis, provides benefits similar to sex, allowing for the long-term success of asexual lineages. We found that, when compared to mitosis, amitosis with chromosome copy number control reduces mutation load deterministically, slows the accumulation of deleterious mutations under genetic drift, and accelerates adaptation. These benefits arise because, like sex, amitosis can generate substantial genetic variation in fitness among (asexual) progeny. Our results indicate that the ability of Tetrahymena to persist in the absence of sex may depend on non-sexual genetic mechanisms conferring benefits typically provided by sex, as has been found in other asexual lineages.


title: Parallel and Population-specific Gene Regulatory Evolution in Cold-Adapted Fly Populations

abstract: Changes in gene regulation at multiple levels may comprise an important share of the molecular changes underlying adaptive evolution in nature. However, few studies have assayed within- and between-population variation in gene regulatory traits at a transcriptomic scale, and therefore inferences about the characteristics of adaptive regulatory changes have been elusive. Here, we assess quantitative trait differentiation in gene expression levels and alternative splicing (intron usage) between three closely-related pairs of natural populations of Drosophila melanogaster from contrasting thermal environments that reflect three separate instances of cold tolerance evolution. The cold-adapted populations were known to show population genetic evidence for parallel evolution at the SNP level, and here we find evidence for parallel expression evolution between them, with stronger parallelism at larval and adult stages than for pupae. We also implement a flexible method to estimate cis- versus trans-encoded contributions to expression or splicing differences at the adult stage. The apparent contributions of cis- versus trans-regulation to adaptive evolution vary substantially among population pairs. While two of three population pairs show a greater enrichment of cis-regulatory differences among adaptation candidates, trans-regulatory differences are more likely to be implicated in parallel expression changes between population pairs. Genes with significant cis-effects are enriched for signals of elevated genetic differentiation between cold- and warm-adapted populations, suggesting that they are potential targets of local adaptation. These findings expand our knowledge of adaptive gene regulatory evolution and our ability to make inferences about this important and widespread process.


title: Reduction of insulin/IGF-1 receptor rejuvenates immunity via positive feedback circuit

abstract: Immunosenescence is considered an inevitable decline in immune function during aging. Here we show that genetic inhibition of the DAF-2/insulin/IGF-1 receptor drastically delays immunosenescence and rejuvenates immunity in C. elegans. We find that p38 mitogen-activated protein kinase 1 (PMK-1), a key determinant of immunosenescence, is dispensable for this rejuvenated immunity. Instead, we demonstrate that longevity-promoting DAF-16/FOXO and heat-shock transcription factor 1 (HSF-1) increase immunocompetence in old daf-2(-) animals. The upregulation of DAF-16/FOXO and HSF-1 decreases the expression of the zip-10/bZIP transcription factor, which in turn downregulates INS-7, an agonistic insulin-like peptide, resulting in further reduction of insulin/IGF-1 signaling (IIS). Thus, reduced IIS bypasses immunosenescence and rejuvenates immunity via the upregulation of anti-aging transcription factors that modulate an endocrine insulin-like peptide through a positive feedback mechanism. Because many functions of IIS are conserved across phyla, our study may lead to the development of strategies for human immune rejuvenation.

category: genetics


title: Structural and Dynamic Insights Into α-Synuclein Dimer Conformations

abstract: Parkinsons disease is associated with the aggregation of the protein -synuclein. While -synuclein can exist in multiple oligomeric states, the dimer has been a subject of extensive debates. Here, using an array of biophysical approaches, we demonstrate -synuclein in vitro exhibits primarily a monomer-dimer equilibrium in nanomolar concentrations and up to a few micromolars. We then use spatial information from hetero-isotopic cross-linking mass spectrometry experiments as restrains in discrete molecular dynamics simulations to obtain the ensemble structure of dimeric species. Out of eight structural sub-populations of dimers we identify one that is compact, stable, abundant, and exhibits partially exposed {beta}-sheet structures. This compact dimer is the only one where the hydroxyls of tyrosine 39 are in a proximity that can promote dityrosine covalent linkage implicated in amyloidogenesis. We propose that this -synuclein dimer features etiological relevance to Parkinsons disease.

category: biophysics


title: A proximity-dependent biotinylation map of a human cell: an interactive web resource

abstract: Compartmentalization is a defining characteristic of eukaryotic cells, partitioning cellular processes into discrete subcellular locations. High throughput microscopy1 and biochemical fractionation coupled with mass spectrometry2-6 have helped to define the proteomes of a variety of organelles and macromolecular structures. However, many other intracellular compartments have remained refractory to such approaches, due for example to difficulty in purifying non-membrane bound structures. Proximity-dependent biotinylation techniques such as BioID provide an alternative approach for defining the composition of cellular compartments in living cells7-10. Here we present a BioID-based map of a human cell based on 192 markers from 32 different subcellular compartments, comprising 35,902 high confidence proximity interactions, and defining the intracellular locations of 4,145 unique proteins in HEK 293 cells. Our localization predictions meet or exceed previous-approaches, with higher specificity, and enabled the discovery of proteins at the mitochondrial outer membrane-endoplasmic reticulum (ER) interface that are critical for mitochondrial homeostasis. Based on this dataset, we have established humancellmap.org as a community resource that provides online tools for localization analysis of user BioID data, and demonstrate how this resource can be used to better understand BioID datasets.

category: molecular biology


title: CDR3 binding chemistry controls TCR V-domain rotational probability and germline CDR2 'scanning' of polymorphic MHC

abstract: The mechanism which adapts the T-cell antigen receptor (TCR) within a given major histocompatibility complex (MHC/HLA) genotype is essential for protection against pathogens. Historically attributed to relative affinity, genetically vast TCRs are surprisingly focused towards a micromolar affinity for their respective peptide (p) plus MHC (pMHC) ligands. Thus, the somatic diversity of the TCR with respect to MHC-restriction, and (ultimately) to pathogens, remains enigmatic. Here, we derive a triple integral solution (from fixed geometry) for any given V domain in TCR bound to pMHC. Solved complexes involving HLA-DR and HLA-DQ, where genetic linkage to the TCR is most profound, were examined in detail. Certain V domains displayed rare geometry within this panel--specifying a restricted rotational probability/volumetric density (dV). Remarkably, hydrogen (H) bond charge-relays distinguished these structures from the others; suggesting that CDR3 binding chemistry dictates CDR2 contacts on the opposite MHC-II alpha helix. Together, these data suggest that TCR recapitulate dV and specialise target pMHC recognition.

category: immunology


title: Estrogen Drives Melanocortin Neurons To Increase Spontaneous Activity and Reduce Sedentary Behavior

abstract: Estrogen depletion in rodents and humans leads to inactivity, unhealthy fat accumulation, and diabetes1,2, underscoring the conserved metabolic benefits of estrogen that inevitably decline with aging. In rodents, the preovulatory surge in 17{beta}-estradiol (E2) temporarily allows energy expenditure to outpace energy intake, thus coordinating increased physical activity with peak sexual receptivity. To investigate how estrogen rebalances energy allocation in females, we examine estrogen receptor alpha (ER) signaling in the ventrolateral ventromedial hypothalamic nucleus (VMHvl)3-7. We uncover a small population of VMHvlER neurons expressing the melanocortin-4 receptor (MC4R) that integrates estrogen and melanocortin signals and projects to arousal centers in the hippocampus and hindbrain, enabling bursts of physical activity. ER recruitment to the Mc4r gene promotes upregulation of Mc4r in VMHvl neurons during the preovulatory surge or following E2 treatment. We leveraged three models to stimulate VMHvlMC4R neurons, restore MC4R signaling in the VMHvl of hyperphagic MC4R null females, or increase Mc4r levels in the VMHvl by CRISPR-mediated activation. All models increase spontaneous activity, whereas silencing VMHvlMC4R neurons blunts normal activity. Direct activation of the VMHvlMC4R node overrides the inactivity and hypometabolism following hormone depletion. These data extend the impact of MC4R signaling - the most common cause of monogenic human obesity8 - beyond the regulation of food intake. Our findings also rationalize reported sex differences in melanocortin signaling, including the greater disease severity of MC4R insufficiency in women9. The hormone-dependent node identified here illuminates the power of estrogen in motivating behavior during the female reproductive cycle and for maintaining an active lifestyle.


title: An experimentally-derived measure of inter-replicate variation in reference samples: the same-same permutation methodology

abstract: The multiple testing problem is a well-known statistical stumbling block in high-throughput data analysis, where large scale repetition of statistical methods introduces unwanted noise into the results. While approaches exist to overcome the multiple testing problem, these methods focus on theoretical statistical clarification rather than incorporating experimentally-derived measures to ensure appropriately tailored analysis parameters. Here, we introduce a method for estimating inter-replicate variability in reference samples for a quantitative proteomics experiment using permutation analysis. This can function as a modulator to multiple testing corrections such as the Benjamini-Hochberg ordered Q value test. We refer to this as a  same-same analysis, since this method incorporates the use of six biological replicates of the reference sample and determines, through non-redundant triplet pairwise comparisons, the level of quantitative noise inherent within the system. The method can be used to produce an experiment-specific Q value cut-off that achieves a specified false discovery rate at the quantitation level, such as 1%. The same-same method is applicable to any experimental set that incorporates six replicates of a reference sample. To facilitate access to this approach, we have developed a same-same analysis R module that is freely available and ready to use via the internet.

category: biochemistry


title: Sugars dominate the seagrass rhizosphere

abstract: Seagrasses are one of the most efficient sinks of carbon dioxide on Earth1: They bury carbon 35 times faster than tropical rainforests on a per unit area basis2. While we know that carbon sequestration in terrestrial plants is intimately linked to the microorganisms living in their soils3-6, the interactions of seagrasses with their rhizospheres are poorly understood. We show that three seagrass species from two oceans excrete simple sugars, mainly sucrose, into their rhizosphere that accumulate to over 200 {micro}M. Such high concentrations are at least 80 times higher than previously observed in the ocean, and surprising, as sugars are quickly consumed by microorganisms. In situ analyses and incubation experiments indicated that phenolic compounds from the seagrass inhibited microbial consumption of sucrose. Metagenomic and metatranscriptomic analyses of the microbial communities in the seagrass rhizosphere revealed that many members had the genes for degrading sucrose, but these were only expressed by a few specialists that also expressed genes for degrading phenolics. Our results explain why sucrose accumulates under seagrass meadows, where it comprises as much as 40% of the dissolved organic carbon. Destruction of extant seagrass canopies would allow sediment microorganisms to consume the tremendous deposits of sucrose buried underneath their meadows, thereby releasing large amounts of CO2 into the oceans and atmosphere.


title: Multiphoton imaging of neural structure and activity in Drosophila through the intact cuticle

abstract: We developed a multiphoton imaging method to capture neural structure and activity in behaving flies through the intact cuticles. Our measurements show that the fly head cuticle has surprisingly high transmission at wavelengths > 900 nm, and the difficulty of through-cuticle imaging is due to the air sacs and/or fat tissue underneath the head cuticle. By compressing the air sacs, we performed deep multiphoton imaging of fly brains through the intact cuticle. Our anatomical and functional imaging results show that 2- and 3-photon imaging are comparable in superficial regions such as the mushroom body, but 3-photon imaging is superior in deeper regions such as the central complex and beyond. We further demonstrated 2-photon through-cuticle functional imaging of odor-evoked calcium responses from the mushroom body {gamma}-lobes in behaving flies short-term and long-term (12 consecutive hours). The through-cuticle imaging method developed here extends the time limits of in vivo imaging in flies, and opens up new ways to capture neural structure and activity from the intact fly brain.


title: A multilayer network model of neuron-astrocyte populations in vitro reveals mGluR5 inhibition is protective following traumatic injury

abstract:
Astrocytes communicate bidirectionally with neurons, enhancing synaptic plasticity and promoting the synchronization of neuronal microcircuits. Despite recent advances in understanding neuron-astrocyte signaling, little is known about astrocytic modulation of neuronal activity at the population level, particularly in disease or following injury. We used high-speed calcium imaging of mixed cortical cultures in vitro to determine how population activity changes after disruption of glutamatergic signaling and mechanical injury. We constructed a multilayer network model of neuron-astrocyte connectivity, which captured distinct topology and response behavior from single cell type networks. mGluR5 inhibition decreased neuronal activity, but did not on its own disrupt functional connectivity or network topology. In contrast, injury increased the strength, clustering, and efficiency of neuronal but not astrocytic networks, an effect that was not observed in networks pre-treated with mGluR5 inhibition. Comparison of spatial and functional connectivity revealed that functional connectivity is largely independent of spatial proximity at the microscale, but mechanical injury increased the spatial-functional correlation. Finally, we found that astrocyte segments of the same cell often belong to separate functional communities based on neuronal connectivity, suggesting that astrocyte segments function as independent entities. Our findings demonstrate the utility of multilayer network models for characterizing the multiscale connectivity of two distinct but functionally dependent cell populations.

AUTHOR SUMMARYAstrocytes communicate bidirectionally with neurons, enhancing synaptic plasticity and promoting the synchronization of neuronal microcircuits. We constructed a multilayer network model of neuron-astrocyte connectivity based on calcium activity in mixed cortical cultures, and used this model to evaluate the effect of glutamatergic inhibition and mechanical injury on network topology. We found that injury increased the strength, clustering, and efficiency of neuronal but not astrocytic networks, an effect that was not observed in injured networks pre-treated with a glutamate receptor antagonist. Our findings demonstrate the utility of multilayer network models for characterizing the multiscale connectivity of two distinct but functionally dependent cell populations.


title: Visual discrimination of optical material properties: a large-scale study

abstract: Complex visual processing involved in perceiving the object materials can be better elucidated by taking a variety of research approaches. Sharing stimulus and response data is an effective strategy to make the results of different studies directly comparable and can assist researchers with different backgrounds to jump into the field. Here, we constructed a database containing several sets of material images annotated with visual discrimination performance. We created the material images using physically-based computer graphics techniques and conducted psychophysical experiments with them in both laboratory and crowdsourcing settings. The observers task was to discriminate materials on one of six dimensions (gloss contrast, gloss distinctness-of-image, translucent vs. opaque, metal vs. plastic, metal vs. glass, and glossy vs. painted). The illumination consistency and object geometry were also varied. We used a non-verbal procedure (an oddity task) applicable for diverse use-cases such as cross-cultural, cross-species, clinical, or developmental studies. Results showed that the material discrimination depended on the illuminations and geometries and that the ability to discriminate the spatial consistency of specular highlights in glossiness perception showed larger individual differences than in other tasks. In addition, analysis of visual features showed that the parameters of higher-order color texture statistics can partially, but not completely, explain task performance. The results obtained through crowdsourcing were highly correlated with those obtained in the laboratory, suggesting that our database can be used even when the experimental conditions are not strictly controlled in the laboratory. Several projects using our dataset are underway.


title: High and stable ATP levels prevent aberrant intracellular protein aggregation

abstract: ATP at millimolar levels has recently been implicated in the solubilization of cellular proteins. However, the significance of this high ATP level under physiological conditions and the mechanisms that maintain ATP remain unclear. We herein demonstrated that AMP-activated protein kinase (AMPK) and adenylate kinase (ADK) cooperated to maintain cellular ATP levels regardless of glucose levels. Single cell imaging of ATP-reduced yeast mutants revealed that ATP levels in these mutants repeatedly underwent stochastic and transient depletion, which induced the cytotoxic aggregation of endogenous proteins and pathogenic proteins, such as huntingtin and -synuclein. Moreover, pharmacological elevations in ATP levels in an ATP-reduced mutant prevented the accumulation of -synuclein aggregates and its cytotoxicity. The removal of cytotoxic aggregates depended on proteasomes, and proteasomal activity cooperated with AMPK or ADK to resist proteotoxic stresses. The present study is the first to demonstrate that cellular ATP homeostasis ensures proteostasis and revealed that suppressing the high volatility of cellular ATP levels prevented cytotoxic protein aggregation, implying that AMPK and ADK are important factors that prevent proteinopathies, such as neurodegenerative diseases.

category: cell biology


title: High resolution, dynamic imaging of early mouse and human liver bud morphogenesis in three dimensions

abstract:
BackgroundLiver organogenesis has thus far served as a paradigm for solid organ formation. The developing liver bud is a well established model of organogenesis, and murine genetic studies demonstrate key molecules involved in key morphogenetic changes. However, the analysis of the liver bud is typically limited to 2D tissue sections, which precludes extensive visualization, quantitation, and analysis. Further, the lack of human liver bud data has further hindered our understanding of human liver organogenesis. Therefore, new analytical and visualization approaches are needed to elicit further morphogenetic details of liver organogenesis and to elucidate differences between mouse and human liver bud growth.

ResultsTo address this need, we focused on high resolution imaging, visualization, and analysis of early liver growth by using available online databases for both mouse (EMAP, Toronto Phenogenomics center) and human (3D Atlas of Human Embryology), noninvasive multimodality imaging studies of the murine embryo, and mouse/human liver weight data. First, we performed three-dimensional (3D reconstructions) of stacked, digital tissue sections that had been initially segmented for the liver epithelium and the septum transversum mesenchyme (STM). 3D reconstruction of both mouse and human data sets enabled visualization and analysis of the dynamics of liver bud morphogenesis, including hepatic cord formation and remodeling, mechanisms of growth, and liver-epithelial STM interactions. These studies demonstrated potentially under-appreciated mechanisms of growth, including rapid exponential growth that is matched at the earliest stages by STM growth, and unique differences between mouse and human liver bud growth. To gain further insight into the exponential liver bud growth that was observed, we plotted volumetric data from 3D reconstruction together with fetal liver growth data from multimodality (optical projection tomography, magnetic resonance imaging, micro-CT) and liver weight data to compose complete growth curves during mouse (E8.5-E18) and human (day 25-300) liver development. For further analysis, we performed curve fitting and parameter estimation, using Gompertzian models, which enables the comparison between mouse and human liver bud growth, as well as comparisons to processes like liver regeneration. To demonstrate the importance of mesenchyme in rapid liver bud growth and morphogenesis in the human liver bud, we performed functional analysis in which human pluripotent stem cell (hPSC)-derived hepatic organoids were used to model collective migration that occurs in vivo, demonstrating that migration is strongly dependent upon mesenchyme.

DiscussionOur data demonstrates improved visualization with 3D images, under-appreciated and potentially new mechanisms of growth, complete liver growth curves with quantitative analysis through embryonic and fetal stages, and a new functional human stem cell-derived liver organoid assay demonstrating mesenchyme-driven collective migration. These data enhance our understanding of liver organogenesis.

category: developmental biology


title: High resolution, serial imaging of early mouse and human liver bud morphogenesis in three dimensions


title: Eliminating accidental deviations to minimize generalization error and maximize replicability: applications in connectomics and genomics

abstract:
Replicability, the ability to replicate scientific findings, is a prerequisite for scientific discovery and clinical utility. Troublingly, we are in the midst of a replicability crisis. A key to replicability is that multiple measurements of the same item (e.g., experimental sample or clinical participant) under fixed experimental constraints are relatively similar to one another. Thus, statistics that quantify the relative contributions of accidental deviations--such as measurement error--as compared to systematic deviations--such as individual differences--are critical. We demonstrate that existing replicability statistics, such as intra-class correlation coefficient and fingerprinting, fail to adequately differentiate between accidental and systematic deviations in very simple settings. We therefore propose a novel statistic, discriminability, which quantifies the degree to which an individuals samples are relatively similar to one another, without restricting the data to be univariate, Gaussian, or even Euclidean. Using this statistic, we introduce the possibility of optimizing experimental design via increasing discriminability and prove that optimizing discriminability improves performance bounds in subsequent inference tasks. In extensive simulated and real datasets (focusing on brain imaging and demonstrating on genomics), only optimizing data discriminability improves performance on all subsequent inference tasks for each dataset. We therefore suggest that designing experiments and analyses to optimize discriminability may be a crucial step in solving the replicability crisis, and more generally, mitigating accidental measurement error.

Author SummaryIn recent decades, the size and complexity of data has grown exponentially. Unfortunately, the increased scale of modern datasets brings many new challenges. At present, we are in the midst of a replicability crisis, in which scientific discoveries fail to replicate to new datasets. Difficulties in the measurement procedure and measurement processing pipelines coupled with the influx of complex high-resolution measurements, we believe, are at the core of the replicability crisis. If measurements themselves are not replicable, what hope can we have that we will be able to use the measurements for replicable scientific findings? We introduce the "discriminability" statistic, which quantifies how discriminable measurements are from one another, without limitations on the structure of the underlying measurements. We prove that discriminable strategies tend to be strategies which provide better accuracy on downstream scientific questions. We demonstrate the utility of discriminability over competing approaches in this context on two disparate datasets from both neuroimaging and genomics. Together, we believe these results suggest the value of designing experimental protocols and analysis procedures which optimize the discriminability.


title: Sequential and efficient neural-population coding of complex task information

abstract: Recent work has highlighted that many types of variables are represented in each neocortical area. How can these many neural representations be organized together without interference, and coherently maintained/updated through time? We recorded from large neural populations in posterior cortices as mice performed a complex, dynamic task involving multiple interrelated variables. The neural encoding implied that correlated task variables were represented by uncorrelated neural-population modes, while pairs of neurons exhibited a variety of signal correlations. This finding relates to principles of efficient coding for task-specific information, with neural-population modes as the encoding unit, and applied across posterior cortical regions and layers 2/3 and 5. Remarkably, this encoding function was multiplexed with sequential neural dynamics as well as reliably followed changes in task-variable correlations through time. We suggest that neural circuits can implement time-dependent encoding in a simple way by using random sequential dynamics as a temporal scaffold.


title: Effect of number and placement of EEG electrodes onmeasurement of neural tracking of speech

abstract: Measurement of neural tracking of natural running speech from the electroencephalogram (EEG) is an increasingly popular method in auditory neuroscience and has applications in audiology. The method involves decoding the envelope of the speech signal from the EEG signal, and calculating the correlation with the envelope of the audio stream that was presented to the subject. Typically EEG systems with 64 or more electrodes are used. However, in practical applications, set-ups with fewer electrodes are required. Here, we determine the optimal number of electrodes, and the best position to place a limited number of electrodes on the scalp. We propose a channel selection strategy based on an utility metric, which allows a quick quantitative assessment of the influence of a channel (or a group of channels) on the reconstruction error. We consider two use cases: a subject-specific case, where the optimal number and position of the electrodes is determined for each subject individually, and a subject-independent case, where the electrodes are placed at the same positions (in the 10-20 system) for all the subjects. We evaluated our approach using 64-channel EEG data from 90 subjects. In the subject-specific case we found that the correlation between actual and reconstructed envelope first increased with decreasing number of electrodes, with an optimum at around 20 electrodes, yielding 29% higher correlations using the optimal number of electrodes compared to all electrodes. This means that our strategy of removing electrodes can be used to improve the correlation metric in high-density EEG recordings. In the subject-independent case, we obtained a stable decoding performance when decreasing from 64 to 22 channels. When the number of channels was further decreased, the correlation decreased. For a maximal decrease in correlation of 10%, 32 well-placed electrodes were sufficient in 91% of the subjects.


title: Cell cycle-dependent active stress drives epithelia remodeling

abstract:
Epithelia have distinct cellular architectures, which are established in development, re-established after wounding, and maintained during tissue homeostasis despite cell turnover and mechanical perturbations. In turn, cell shape also controls tissue function as a regulator of cell differentiation, proliferation, and motility. Here we investigate cell shape changes in a model epithelial monolayer. After the onset of confluence, cells continue to proliferate and change shape over time, eventually leading to a final architecture characterized by arrested motion and more regular cell shapes. Such monolayer remodeling is robust, with qualitatively similar evolution in cell shape and dynamics observed across disparate perturbations. Here we quantify differences in monolayer remodeling guided by the active vertex model to identify underlying order parameters controlling epithelial architecture. When monolayers are formed atop extracellular matrix with varied stiffness, we find the cell density at which motion arrests varies significantly but the cell shape remains constant, consistent with the onset of tissue rigidity. In contrast, pharmacological perturbations can significantly alter the cell shape at which tissue dynamics is arrested, consistent with varied amounts of active stress within the tissue. Across all experimental conditions the final cell shape is well correlated to the cell proliferation rate, and cell cycle inhibition immediately arrests cell motility. Finally, we demonstrate cell-cycle variation in junctional tension as a source of active stress within the monolayer. Thus, the architecture and mechanics of epithelial tissue can arise from an interplay between cell mechanics and stresses arising from cell cycle dynamics.

SIGNIFICANCE STATEMENTThe morphology of biological tissue is determined by the shape and density of constituent cells. Here we measure the dynamics of cells in model epithelial tissues to study the evolution of their shape and density over time. Guided by a mathematical model, we find that cell shape is controlled by rigidity and active stresses within the tissue. We then show that cell cycle dynamics are the source of active stress that drives epithelial remodeling.


title: Telemetry reveals rapid duel-driven song plasticity in a naturalistic social environment

abstract: Singing by songbirds is a complex motor skill learnt during juvenile development or, in  open-ended learners, before the onset of the breeding season. Outside of these specific periods, it is believed that birdsong does not change. Challenging this, here we demonstrate that in a seasonal songbird, social interactions during the breeding season induce a novel form of singing plasticity in naturalistic social environments. Using custom-made telemetric backpack technology to monitor song-based communication from freely-behaving canaries, we show that males temporally overlap their songs during aggressive  duels. Singing duels induce an unexpected fast plasticity in song length, thereby enhancing singing performance and flexibility of a sexually-selected behavior. Remarkably, dueling canaries sing acoustically-similar songs, suggesting that competition within a specific song acoustic space drives dueling behavior. Overall, our findings reveal a previously unrecognized type of song plasticity different from the well-studied slow song plasticity as an imitation process for display purposes.

category: animal behavior and cognition


title: Mutational signatures of replication timing and epigenetic modification persist through the global divergence of mutation spectra across the great ape phylogeny

abstract:
Great ape clades exhibit variation in the relative mutation rates of different three-base-pair genomic motifs, with closely related species having more similar mutation spectra than distantly related species. This pattern cannot be explained by classical demographic or selective forces, but imply that DNA replication fidelity has been perturbed in different ways on each branch of the great ape phylogeny. Here, we use whole-genome variation from 88 great apes to investigate whether these species mutation spectra are broadly differentiated across the entire genome, or whether mutation spectrum differences are driven by DNA compartments that have particular functional features or chromatin states. We perform principal component analysis and mutational signature deconvolution on mutation spectra ascertained from compartments defined by features including replication timing and ancient repeat content, finding evidence for consistent species-specific mutational signatures that do not depend on which functional compartments the spectra are ascertained from. At the same time, we find that many compartments have their own characteristic mutational signatures that appear stable across the great ape phylogeny. For example, in a mutation spectrum PCA compartmentalized by replication timing, the second PC explaining 21.2% of variation separates all species late-replicating regions from their early-replicating regions. Our results suggest that great ape mutation spectrum evolution is not driven by epigenetic changes that modify mutation rates in specific genomic regions, but instead by trans-acting mutational modifiers that affect mutagenesis across the whole genome fairly uniformly.

SIGNIFICANCE STATEMENTAll heritable variation begins with damage or copying mistakes affecting the DNA of sperm, eggs, or embryos. Different DNA motifs can have different mutation rates, and these rates can evolve over time: the spectrum of mutability of three-base-pair motifs has evolved rapidly during great ape diversification. Here, we show that even as ape mutation spectra diverged from each other, ape genomes preserved a landscape of spatial mutation spectrum variation. We can thus deconvolute the mutational process into a mixture of fast-evolving signatures with uniform spatial distributions and conserved signatures that target specific regions. Our findings may ultimately help determine the factors, either genetic or environmental, that contribute to temporal and spatial variation in germline mutagenesis.


title: Reconstructing the history of variation in effective population size along phylogenies.

abstract:
AO_SCPLOWBSTRACTC_SCPLOWThe nearly-neutral theory predicts specific relations between effective population size (Ne) and patterns of divergence and polymorphism, which depend on the shape of the distribution of fitness effects (DFE) of new mutations. However, testing these relations is not straightforward, owing to the difficulty in estimating Ne. Here, we introduce an integrative framework allowing for an explicit reconstruction of the phylogenetic history of Ne, thus leading to a quantitative test of the nearly-neutral theory and an estimation of the allometric scaling of the ratios of non-synonymous over synonymous polymorphism ({pi}N /{pi}S) and divergence (dN/dS) with respect to Ne. As an illustration, we applied our method to primates, for which the nearly-neutral predictions were mostly verified. Under a purely nearly-neutral model with a constant DFE across species, we find that the variation in{pi} N /{pi}S and dN/dS as a function of Ne is too large to be compatible with current estimates of the DFE based on site frequency spectra. The reconstructed history of Ne shows a ten-fold variation across primates. The mutation rate per generation u, also reconstructed over the tree by the method, varies over a three-fold range and is negatively correlated with Ne. As a result of these opposing trends for Ne and u, variation in{pi} S is intermediate, primarily driven by Ne but substantially influenced by u. Altogether, our integrative framework provides a quantitative assessment of the role of Ne and u in modulating patterns of genetic variation, while giving a synthetic picture of their history over the clade.

SO_SCPLOWIGNIFICANCEC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWSTATEMENTC_SCPLOWNatural selection tends to increase the frequency of mutants of higher fitness and to eliminate less fit genetic variants. However, chance events over the life of the individuals in the population are susceptible to introduce deviations from these trends, which are expected to have a stronger impact in smaller populations. In the long-term, these fluctuations, called random drift, can lead to the accumulation of mildly deleterious mutations in the genomes of living species, and for that reason, the effective population size (usually denoted Ne, and which captures the relative strength of drift, relative to selection) has been proposed as a major determinant of the evolution of genome architecture and content. A proper quantitative test of this hypothesis, however, is hampered by the fact that Ne is difficult to estimate in practice. Here, we propose a Bayesian integrative approach for reconstructing the broad-scale variation in Ne across an entire phylogeny, which in turns allows for quantifying how Ne correlates with life history traits and with various measures of genetic diversity and selection strength, between and within species. We apply this approach to the phylogeny of primates, and observe that selection is indeed less efficient in primates characterized by smaller effective population sizes.


title: Dynamic interactions and intracellular fate of label-free GO within mammalian cells: role of lateral sheet size

abstract: Graphene oxide (GO) holds great potential for biomedical applications, however fundamental understanding of the way it interacts with biological systems is still lacking even though it is essential for successful clinical translation. In this study, we exploit intrinsic fluorescent properties of thin GO sheets to establish the relationship between lateral dimensions of the material, its cellular uptake mechanisms and intracellular fate over time. Label-free GO with distinct lateral dimensions, small (s-GO) and ultra-small (us-GO) were thoroughly characterised both in water and in biologically relevant cell culture medium. Interactions of the material with a range of non-phagocytic mammalian cell lines (BEAS-2B, NIH/3T3, HaCaT, 293T) were studied using a combination of complementary analytical techniques (confocal microscopy, flow cytometry and TEM). The uptake mechanism was initially interrogated using a range of pharmaceutical inhibitors and validated using polystyrene beads of different diameters (0.1 and 1 m). Subsequently, RNA-Seq was used to follow the changes in the uptake mechanism used to internalize s-GO flakes over time. Regardless of lateral dimensions, both types of GO were found to interact with the plasma membrane and to be internalized by a panel of cell lines studied. However, s-GO was internalized mainly via macropinocytosis while us-GO was mainly internalized via clathrin- and caveolae-mediated endocytosis. Importantly, we report the shift from macropinocytosis to clathrin-dependent endocytosis in the uptake of s-GO at 24 h, mediated by upregulation of mTORC1/2 pathway. Finally, we show that both s-GO and us-GO terminate in lysosomal compartments for up to 48 h. Our results offer an insight into the mechanism of interaction of GO with non-phagocytic cell lines over time that can be exploited for the design of biomedically-applicable 2D transport systems.


title: Efficient and robust coding in heterogeneous recurrent networks

abstract: Cortical networks show a large heterogeneity of neuronal properties. However, traditional coding models have focused on homogeneous populations of excitatory and inhibitory neurons. Here, we analytically derive a class of recurrent networks of spiking neurons that close to optimally track a continuously varying input online, based on two assumptions: 1) every spike is decoded linearly and 2) the network aims to reduce the mean-squared error between the input and the estimate. From this we derive a class of predictive coding networks, that unifies encoding and decoding and in which we can investigate the difference between homogeneous networks and heterogeneous networks, in which each neurons represents different features and has different spike-generating properties. We find that in this framework,  type 1 and  type 2 neurons arise naturally and networks consisting of a heterogeneous population of different neuron types are both more efficient and more robust against correlated noise. We make two experimental predictions: 1) we predict that integrators show strong correlations with other integrators and resonators are correlated with resonators, whereas the correlations are much weaker between neurons with different coding properties and 2) that  type 2 neurons are more coherent with the overall network activity than  type 1 neurons.


title: A Neural Circuit Model of Proprioceptive Feedback from Muscles Recruited during an Isometric Knee Extension

abstract:
The influence of proprioceptive feedback on muscle activity during isometric tasks is the subject of conflicting studies. To better understand the relationship, we performed an isometric knee extension task experiment at four pre-set angles of the knee, recording from five muscles, and for two different hip positions. We applied muscle synergy analysis using NMF on the sEMG recordings to identify structure in the data which changed with internal knee angle, suggesting a link between proprioception and muscle activity. We hypothesised that such patterns in the data arise from the way proprioceptive and cortical signals are integrated in neural circuits of the spinal cord. Using the MIIND neural simulation platform, we developed a computational model based on current understanding of spinal circuits with an adjustable proprioceptive input. The model produces the same synergy patterns as observed in the experimental data indicating that such synergies are indeed encoded in the neural connectivity of the spinal cord and modulated by the proprioceptive input. When matching the proprioceptive input to the knee angles of the experiment, the model predicts the need for three distinct inputs: two to control the normal reciprocity between the agonist and antagonist muscles, and an additional to match the non-linear trend towards the limit of extension. Finally, we discuss the risks of using NMF for synergy analysis and demonstrate how to increase confidence in its results. Future modelling of human motor outputs should include interneuronal spinal circuits such as this to distinguish the modulatory role of supraspinal and peripheral afferent inputs to the spinal cord, during both passive and dynamic tasks.

Significance statementSensory feedback from muscles has a significant role in motor control, but its role in tasks where limbs are held in a fixed position is disputed, because the effect is reduced when muscles are not stretched. Here, we first identified patterns of muscle activity during such tasks which changed with different leg positions. We developed a computational spinal motor circuit model with adjustable muscle stretch input, which reproduced the same patterns of activity as observed experimentally. The model predicts three distinct muscle stretch signals required to produce the activity patterns for all leg positions. Because the connections in the model are based on well known spinal circuits, it is likely the observed activity patterns are generated in the spinal cord.


title: Proximity proteomics in a marine diatom reveals a putative cell surface-to-chloroplast iron trafficking pathway

abstract: Iron is a biochemically critical metal cofactor in enzymes involved in photosynthesis, cellular respiration, nitrate assimilation, nitrogen fixation, and reactive oxygen species defense. Marine microeukaryotes have evolved a phytotransferrin-based iron uptake system to cope with iron scarcity, a major factor limiting primary productivity in the global ocean. Diatom phytotransferrin is endocytosed, however proteins downstream of this environmentally ubiquitous iron receptor are unknown. We applied engineered ascorbate peroxidase APEX2-based subcellular proteomics to catalog proximal proteins of phytotransferrin in the model marine diatom Phaeodactylum tricornutum. Proteins encoded by poorly characterized iron-sensitive genes were identified including three that are expressed from a chromosomal gene cluster. Two of them showed unambiguous colocalization with phytotransferrin adjacent to the chloroplast. Further phylogenetic, domain, and biochemical analyses suggest their involvement in intracellular iron processing. Proximity proteomics holds enormous potential to glean new insights into iron acquisition pathways and beyond in these evolutionarily, ecologically, and biotechnologically important microalgae.


title: Parallel Factor Analysis for multidimensional decomposition of fNIRS data

abstract:
SignificanceCurrent techniques for data analysis in functional near-infrared spectroscopy (fNIRS), such as artifact correction, do not allow to integrate the information originating from both wavelengths, considering only temporal and spatial dimensions of the signals structure. Parallel factor analysis (PARAFAC) has previously been validated as a multidimensional decomposition technique in other neuroimaging fields.

AimWe aimed to introduce and validate the use of PARAFAC for the analysis of fNIRS data, which is inherently multidimensional (time, space, wavelength).

ApproachWe used data acquired in 17 healthy adults during a verbal fluency task to compare the efficacy of PARAFAC for motion artifact correction to traditional 2D decomposition techniques, i.e. target principal (tPCA) and independent component analysis (ICA). Correction performance was further evaluated under controlled conditions with simulated artifacts and hemodynamic response functions.

ResultsPARAFAC achieved significantly higher improvement in data quality as compared to tPCA and ICA. Correction in several simulated signals further validated its use and promoted it as a robust method independent of the artifacts characteristics.

ConclusionsThis study describes the first implementation of PARAFAC in fNIRS and provides validation for its use to correct artifacts. PARAFAC is a promising data-driven alternative for multidimensional data analyses in fNIRS and this study paves the way for further applications.


title: Lymphoid follicle formation and human vaccination responses recapitulated in an organ-on-a-chip

abstract: Lymphoid follicles (LFs) are responsible for generation of adaptive immune responses in secondary lymphoid organs and form ectopically during chronic inflammation. A human model of LF formation would provide a tool to understand LF development and an alternative to non-human primate models for preclinical evaluation of vaccines. Here, we show that primary human blood B- and T-lymphocytes autonomously assemble into ectopic LFs when cultured in a three-dimensional (3D) extracellular matrix gel within an organ-on-a-chip microfluidic device. Dynamic fluid flow is required for LF formation and prevention of lymphocyte autoactivation. These germinal center-like LFs contain B cells expressing Activation-Induced Cytidine Deaminase and exhibit plasma cell (PC) differentiation upon activation. To explore their utility for vaccine testing, autologous monocyte-derived dendritic cells were integrated into LF Chips. The human LF chips demonstrated improved antibody responses to split virion influenza vaccination compared to 2D cultures, which were enhanced by addition of a squalene-in-water emulsion adjuvant, and this was accompanied by increases in LF size and number. When inoculated with commercial influenza vaccine, PC formation and production of anti-hemagglutinin IgG were observed, as well as secretion of cytokines similar to those observed in vaccinated humans over clinically relevant timescales.


title: The Role of State Uncertainty in the Dynamics of Dopamine

abstract: Reinforcement learning models of the basal ganglia map the phasic dopamine signal to reward prediction errors (RPEs). Conventional models assert that, when a stimulus predicts a reward with fixed delay, dopamine activity during the delay should converge to baseline through learning. However, recent studies have found that dopamine ramps up before reward in certain conditions even after learning, thus challenging the conventional models. In this work, we show that sensory feedback causes an unbiased learner to produce RPE ramps. Our model predicts that, when feedback gradually decreases during a trial, dopamine activity should resemble a  bump, whose ramp-up phase should furthermore be greater than that of conditions where the feedback stays high. We trained mice on a virtual navigation task with varying brightness, and both predictions were empirically observed. In sum, our theoretical and experimental results reconcile the seemingly conflicting data on dopamine behaviors under the RPE hypothesis.


title: DeepImageJ: A user-friendly environment to run deep learning models in ImageJ

abstract: DeepImageJ is a user-friendly solution that enables the generic use of pre-trained deep learn ing (DL) models for biomedical image analysis in ImageJ. The deepImageJ environment gives access to the largest bioimage repository of pre-trained DL models (BioImage Model Zoo). Hence, non-experts can easily perform common image processing tasks in life-science research with DL-based tools including pixel and object classification, instance segmentation, denoising or virtual staining. DeepImageJ is compatible with existing state-of-the-art solutions and it is equipped with utility tools for developers to include new models. Very recently, several train ing frameworks have adopted the deepImageJ format to deploy their work in one of the most used software in the field (ImageJ). Beyond its direct use, we expect deepImageJ to contribute to the broader dissemination and reuse of DL models in life-sciences applications and bioimage informatics.

category: bioengineering


title: Reference transcriptome data in silkworm, Bombyx mori

abstract:
BackgroundThe silkworm Bombyx mori is a lepidopteran model insect with biological and industrial importance. Its high-quality genome sequence has recently become available and the utilization of this information in combination with extensive transcriptomic analyses is expected to provide an elaborate gene model. It will also be possible to clarify gene expression in detail using this approach.

ResultsWe herein performed RNA-seq analysis of ten major tissues/subparts of silkworm larvae. Sequences were mapped onto the reference genome assembly and reference transcriptome data was successfully constructed. The reference data provided a nearly complete sequence for sericin-1, a major silk gene with a complex structure. We also markedly improved the gene model for other genes. Transcriptomic expression was investigated in each tissue and a number of transcripts were identified that were exclusively expressed in tissues such as the testis. Transcripts strongly expressed in the midgut formed tight genomic clusters, suggesting that they originated from tandem gene duplication. Transcriptional factor genes expressed in specific tissues or the silk gland subparts were also identified.

ConclusionsWe successfully constructed reference transcriptome data in the silkworm and found that a number of transcripts showed unique expression profiles. These results will facilitate basic studies on the silkworm and accelerate its applications, which will contribute to further advances in lepidopteran and entomological research and the practical use of these insects.


title: A functional corona around extracellular vesicles enhancesangiogenesis during skin regeneration and signals in immune cells

abstract: Nanoparticles can acquire a protein corona defining their biological identity. Corona functions were not yet considered for cell-derived extracellular vesicles (EVs). Here we demonstrate that nanosized EVs from therapy-grade human placental-expanded (PLX) stromal cells are surrounded by an imageable and functional protein corona when enriched with permissive technology. Scalable EV separation from cell-secreted soluble factors via tangential flow-filtration and subtractive tandem mass-tag proteomics revealed significant enrichment of predominantly immunomodulatory and proangiogenic proteins. Western blot, calcein-based flow cytometry, super-resolution and electron microscopy verified EV identity. PLX-EVs protected corona proteins from protease digestion. EVs significantly ameliorated human skin regeneration and angiogenesis in vivo, induced differential signaling in immune cells, and dose-dependently inhibited T cell proliferation in vitro. Corona removal by size-exclusion or ultracentrifugation abrogated angiogenesis. Re-establishing an artificial corona by cloaking EVs with defined proangiogenic proteins served as a proof-of-concept. Understanding EV corona formation will improve rational EV-inspired nanotherapy design.


title: Integrating multi-omics data through deep learning for accurate cancer prognosis prediction

abstract:
BackgroundGenomic information is nowadays widely used for precise cancer treatments. Since the individual type of omics data only represents a single view that suffers from data noise and bias, multiple types of omics data are required for accurate cancer prognosis prediction. However, it is challenging to effectively integrate multi-omics data due to the large number of redundant variables but relatively small sample size. With the recent progress in deep learning techniques, Autoencoder was used to integrate multi-omics data for extracting representative features. Nevertheless, the generated model is fragile from data noises. Additionally, previous studies usually focused on individual cancer types without making comprehensive tests on pan-cancer. Here, we employed the denoising Autoencoder to get a robust representation of the multi-omics data, and then used the learned representative features to estimate patients risks.

ResultsBy applying to 15 cancers from The Cancer Genome Atlas (TCGA), our method was shown to improve the C-index values over previous methods by 6.5% on average. Considering the difficulty to obtain multi-omics data in practice, we further used only mRNA data to fit the estimated risks by training XGboost models, and found the models could achieve an average C-index value of 0.627. As a case study, the breast cancer prognosis prediction model was independently tested on three datasets from the Gene Expression Omnibus (GEO), and shown able to significantly separate high-risk patients from low-risk ones (C-index>0.6, p-values<0.05). Based on the risk subgroups divided by our method, we identified nine prognostic markers highly associated with breast cancer, among which seven genes have been proved by literature review.

ConclusionOur comprehensive tests indicated that we have constructed an accurate and robust framework to integrate multi-omics data for cancer prognosis prediction. Moreover, it is an effective way to discover cancer prognosis-related genes.

category: bioinformatics


title: Understanding patterns of HIV multi-drug resistance through models of temporal and spatial drug heterogeneity

abstract: 1Triple-drug therapies have transformed HIV from a fatal condition to a chronic one. These therapies should prevent HIV drug resistance evolution, because one or more drugs suppress any partially-resistant viruses. In practice, such therapies drastically reduced, but did not eliminate, resistance evolution. In this article, we reanalyze published data from an evolutionary perspective and demonstrate several intriguing patterns about HIV resistance evolution - resistance evolves (1) even after years on successful therapy, (2) sequentially, often via one mutation at a time and (3) in a partially predictable order. We describe how these observations might emerge under two models of HIV drugs varying in space or time. Despite decades of work in this area, much opportunity remains to create models with realistic parameters for three drugs, and to match model outcomes to resistance rates and genetic patterns from patients on triple-drug therapy. Further, lessons from HIV may inform other systems.

category: evolutionary biology


title: Evolutionary impact of size-selective harvesting on shoaling behavior: Individual-level mechanisms and possible consequences for natural and fishing mortality

abstract: Intensive and size-selective harvesting is an evolutionary driver of life-history as well as individual behavioral traits. Yet, whether and to what degree harvesting modifies the collective behavior of exploited species is largely unknown. We present a multi-generation harvest selection experiment with zebrafish (Danio rerio) as a model species to understand the effects of size-selective harvesting on shoaling behavior. The experimental system is based on a large-harvested (typical of most wild capture fisheries targeting larger size classes) and small-harvested (typical of specialized fisheries and gape-limited predators targeting smaller size classes) selection lines. By combining high resolution tracking of fish behavior with computational agent-based modeling we show that shoal cohesion changed in the direction expected by a trade-off between vigilance and the use of social cues. In particular, we document a decrease of vigilance in the small-harvested line, which was linked to an increase in the attention to social cues, favoring more cohesive shoals. Opposing outcomes were found for the large-harvested line, which formed less cohesive shoals. Using the agent-based model we outline possible consequences of changes is shoaling behavior for both fishing and natural mortality. The changes in shoaling induced by large size-selective harvesting may decrease fishing mortality, but increase mortality by natural predators. Our work suggests an insofar overlooked evolutionary mechanism by which size-selective harvesting can affect mortality and in turn population dynamics of exploited fish.

category: ecology


title: Fine human genetic map based on UK10K data set

abstract: Recombination is a major force that shapes genetic diversity. Determination of recombination rate is important and can theoretically be improved by increasing the sample size. However, it is challenging to estimate recombination rates when the sample size is extraordinarily large because of computational burden. In this study, we used a refined artificial intelligence approach to estimate the recombination rate of the human genome using the UK10K human genomic dataset with 7,562 genomic sequences and its three subsets with 200, 400 and 2,000 genomic sequences under the Out-of-Africa demography model. We not only obtained an accurate human genetic map, but also found that the fluctuation of estimated recombination rate is reduced along the human genome when the sample size is increased. UK10K recombination activity is less concentrated than its subsets. Our results demonstrate how the sample size affects the estimated recombination rate, and analyses of a larger number of genomes result in a more precise estimation of recombination rate.


abstract: Annotating gene structures and functions to genome assemblies is necessary to make assembly resources useful for biological inference. Gene Ontology (GO) term assignment is the most used functional annotation system, and new methods for GO assignment have improved the quality of GO-based function predictions. The Gene Ontology Meta Annotator for Plants (GOMAP) is an optimized, high-throughput, and reproducible pipeline for genome-scale GO annotation of plants. We containerized GOMAP to increase portability and reproducibility and also optimized its performance for HPC environments. Here we report on the pipelines availability and performance for annotating large, repetitive plant genomes and describe how GOMAP was used to annotate multiple maize genomes as a test case. Assessment shows that GOMAP expands and improves the number of genes annotated and annotations assigned per gene as well as the quality (based on Fmax) of GO assignments in maize. GOMAP has been deployed to annotate other species including wheat, rice, barley, cotton, and soy. Instructions and access to the GOMAP Singularity container are freely available online at https://bioinformapping.com/gomap/. A list of annotated genomes and links to data is maintained at https://dill-picl.org/projects/gomap/.


title: Gene Ontology Meta Annotator for Plants (GOMAP)


title: AMR - An R Package for Working with Antimicrobial Resistance Data

abstract:
Antimicrobial resistance is an increasing threat to global health. Evidence for this trend is generated in microbiological laboratories through testing microorganisms for resistance against antimicrobial agents. International standards and guidelines are in place for this process as well as for reporting data on (inter-)national levels. However, there is a gap in the availability of standardized and reproducible tools for working with laboratory data to produce the required reports. It is known that extensive efforts in data cleaning and validation are required when working with data from laboratory information systems. Furthermore, the global spread and relevance of antimicrobial resistance demands to incorporate international reference data in the analysis process.

In this paper, we introduce the AMR package for R that aims at closing this gap by providing tools to simplify antimicrobial resistance data cleaning and analysis, while incorporating international guidelines and scientifically reliable reference data. The AMR package enables standardized and reproducible antimicrobial resistance analyses, including the application of evidence-based rules, determination of first isolates, translation of various codes for microorganisms and antimicrobial agents, determination of (multi-drug) resistant microorganisms, and calculation of antimicrobial resistance, prevalence and future trends. The AMR package works independently of any laboratory information system and provides several functions to integrate into international workflows (e.g., WHONET software provided by the World Health Organization).


title: Caveat in Fisher's theorem reveals fitness can change without mutations

abstract: The fitness of microbial genotypes is linked to their reproduction rate: Mutants reproducing faster than their wild-type counterparts are favoured by selection, but otherwise the mutation is lost. Here I show that relative differences in fitness between two mutants can change over time without invoking new mutations, contravening textbook population genetics theory. Widespread fitness measurements assume the ratio between Malthusian reproduction rates of competing genotypes is constant. But they are not. Here I competed two constructs of Escherichia coli, one harbouring the non-transmissible plasmid pGW155B. The plasmid protects the bacterium against tetracycline, and yet, it was maintained without using the antibiotic. pGW155B imposes a slower reproduction rate due to carriage costs but it also prompts a known trade-off between reproduction and survival, so the construct harbouring pGW155B attains higher densities at the equilibrium. Consequently, if selection favours survival the bacterium could maintain the plasmid, despite its slower reproduction, without using tetracycline. Exclusive reliance on reproduction rates may therefore yield inaccurate fitness measurements, altering our intuition about how natural selection operates, unless competing genotypes reach their equilibrium. This means that selection for plasmid carriage could be stronger than previously thought.


title: Effective mechanical potential of cell-cell interaction explains basic structural units of three-dimensional morphogenesis

abstract:
Mechanical forces of cell-cell interactions have been suggested to be critical for the emergence of diverse three-dimensional morphologies of multicellular organisms. The direct evaluation of the forces in living systems has been difficult due to technical limitations. Here, we developed a framework for inferring and modeling mechanical forces of cell-cell interactions. First, by analogy to coarse-grained models in molecular and colloidal sciences, cells were assumed to be spherical particles, where the mean forces (i.e. effective forces) of pairwise cell-cell interactions were considered. Then, the forces were statistically inferred from live imaging data, and subsequently, we successfully detected effective mechanical potentials of cell-cell interactions as a function of the cell-cell distances in Madin-Darby canine kidney (MDCK) cells, C.elegans early embryos, and mouse pre-implantation embryos. The qualitative and quantitative differences in the inferred potentials can be a control parameter for morphological transition during the mouse compaction process, and can also reproduce various three-dimensional morphologies including aggregates, cavities, tubes, cups, and two-dimensional sheets, which constitute basic structures observed during morphogenesis. We propose that effective potentials of cell-cell interactions are measurable, and their qualitative and quantitative features are critical for the emergence of diverse three-dimensional morphogenesis.

Significance statementEmergence of diverse morphologies of multicellular organisms is one of the most intriguing phenomena in nature. Mechanical forces generated by cells play central roles in morphogenesis, however, their measurement is technically limited. Furthermore, due to the complex situations in living systems, a model for describing the emergent properties of multicellular systems has not been established. Here, we developed a method for inferring mechanical potential energy of cell-cell interactions, and showed that the quantitative differences in the potential is alone sufficient to describe basic three-dimensional morphologies observed during embryogenesis and organogenesis. This framework sheds light on the emergent properties of multicellular systems.


title: Network dynamics underlying OFF responses in the auditory cortex

abstract: Across sensory systems, complex spatio-temporal patterns of neural activity arise following the onset (ON) and offset (OFF) of stimuli. While ON responses have been widely studied, the mechanisms generating OFF responses in cortical areas have so far not been fully elucidated. We examine here the hypothesis that OFF responses are single-cell signatures of recurrent interactions at the network level. To test this hypothesis, we performed population analyses of two-photon calcium recordings in the auditory cortex of awake mice listening to auditory stimuli, and compared linear single-cell and network models. While the single-cell model explained some prominent features of the data, it could not capture the structure across stimuli and trials. In contrast, the network model accounted for the low-dimensional organisation of population responses and their global structure across stimuli, where distinct stimuli activated mostly orthogonal dimensions in the neural state-space.


title: Low-dimensional learned feature spaces quantify individual and group differences in vocal repertoires

abstract: Increases in the scale and complexity of behavioral data pose an increasing challenge for data analysis. A common strategy involves replacing entire behaviors with small numbers of handpicked, domain-specific features, but this approach suffers from several crucial limitations. For example, handpicked features may miss important dimensions of variability, and correlations among them complicate statistical testing. Here, by contrast, we apply the variational autoencoder (VAE), an unsupervised learning method, to learn features directly from data and quantify the vocal behavior of two model species: the laboratory mouse and the zebra finch. The VAE converges on a parsimonious representation that outperforms handpicked features on a variety of common analysis tasks, enables the measurement of moment-by-moment vocal variability on the timescale of tens of milliseconds in the zebra finch, provides strong evidence that mouse ultrasonic vocalizations do not cluster as is commonly believed, and captures the similarity of tutor and pupil birdsong with qualitatively higher fidelity than previous approaches. In all, we demonstrate the utility of modern unsupervised learning approaches to the quantification of complex and high-dimensional vocal behavior.


title: Population coding of strategic variables during foraging in freely-moving macaques

abstract: To optimize their foraging strategy, animals must continuously make decisions about where to look for food and when to move between locations of possible food sources. Until now it was difficult to examine the neural bases of foraging in naturalistic environments because previous approaches have relied on restrained animals performing trial-based foraging tasks. Here, we allowed unrestrained monkeys to freely interact with concurrent reward options while we wirelessly recorded population activity in dorsolateral prefrontal cortex (dlPFC). Although the relevant reward dynamics were hidden from the animals, they were nonetheless encoded in the population activity and helped predict foraging choices. Surprisingly, the decoded reward dynamics were represented in a subspace of the high-dimensional population activity, and predicted animals subsequent choice better than either the true experimental variables or the raw neural responses. Our results indicate that monkeys foraging strategy is based on a cortical model of reward dynamics as animals freely explore their environment.


title: Fully-automated and ultra-fast cell-type identification using specific marker combinations from single-cell transcriptomic data

abstract: Single-cell transcriptomics enables systematic charting of cellular composition of complex tissues. Identification of cell populations often relies on unsupervised clustering of cells based on the similarity of their scRNA-seq profiles, followed by manual annotation of cell clusters using established marker genes. However, manual selection of marker genes is a time-consuming process that may lead to sub-optimal annotation results as the selected markers must be informative of both the individual cell clusters and various cell types present in the complex samples. Here, we developed a computational platform, termed ScType, which enables data-driven, fully-automated and ultra-fast cell-type identification based solely on given scRNA-seq data, combined with our comprehensive cell marker database as background information. Using a compendium of six scRNA-seq datasets from various human and mouse tissues, we show how ScType provides an unbiased and accurate cell-type annotation by guaranteeing the specificity of positive and negative marker genes both across cell clusters and cell types. We also demonstrate how ScType enables distinguishing between healthy and malignant cell populations, based on single-cell calling of single-nucleotide variants, making it a versatile tool for exploration and use of single-cell transcriptomic data for anticancer applications. The widely-applicable method is deployed both as an interactive web-tool (https://sctype.app), and as an open-source R-package, connected with a comprehensive ScType database of specific markers.