title: Coordinating With a Robot Partner Affects Action Monitoring Related Neural Processing

abstract: Robots start to play a role in our social landscape, and they are progressively becoming responsive, both physically and socially. It begs the question of how humans react to and interact with robots in a coordinated manner and what the neural underpinnings of such behavior are. This exploratory study aims to understand the differences in human-human and human-robot interactions at a behavioral level and from a neurophysiological perspective. For this purpose, we adapted a collaborative dynamical paradigm from Hwang et al. (1). All 16 participants held two corners of a tablet while collaboratively guiding a ball around a circular track either with another participant or a robot. In irregular intervals, the ball was perturbed outward creating an artificial error in the behavior, which required corrective measures to return to the circular track again. Concurrently, we recorded electroencephalography (EEG). In the behavioral data, we found an increased velocity and positional error of the ball from the track in the human-human condition vs. human-robot condition. For the EEG data, we computed event-related potentials. To explore the temporal and spatial differences in the two conditions, we used time-regression with overlap-control and corrected for multiple-comparisons using Threshold-Free-Cluster Enhancement. We found a significant difference between human and robot partners driven by significant clusters at fronto-central electrodes. The amplitudes were stronger with a robot partner, suggesting a different neural processing. All in all, our exploratory study suggests that coordinating with robots affects action monitoring related processing. In the investigated paradigm, human participants treat errors during human-robot interaction differently from those made during interactions with other humans.


title: Adolescent ethanol exposure decreases cholinergic markers, blunts behaviorally-evoked acetylcholine and increases in apical dendritic branching within the orbital frontal cortex.

abstract:
During adolescence, heavy binge-like ethanol consumption can lead to frontocortical structural and functional impairments. These impairments are likely driven by adolescence being a critical time point for maturation of brain regions associated with higher-order cognitive functioning. Rodent models of heavy binge-like ethanol exposure show consistent disruptions to the typical development of the prefrontal cortex (PFC). All deep cortical layers receive cholinergic projections that originate from the Nucleus basalis of Meynert (NbM) complex. These cholinergic projections are highly involved in learning, memory, and attention. Adolescent intermittent ethanol exposure (AIE) induces cholinergic dysfunction as a result of an epigenetic suppression of the genes that drive the cholinergic phenotype. The current study used a model of AIE to assess structural and functional changes to the frontal cortex and NbM following binge-like ethanol exposure in adolescence. Western blot analysis revealed long-term disruptions of the cholinergic circuit following AIE: choline acetyltransferase (ChAT) was suppressed in the NbM and vesicular acetylcholine transporter (VAChT) was suppressed in the orbitofrontal cortex (OFC). In vivo microdialysis for acetylcholine efflux during a spatial memory task determined changes in cholinergic modulation within the PFC following AIE. However, AIE spared performance on the spatial memory task and on an operant reversal task. In a second study, Golgi-Cox staining determined that AIE increased apical dendritic complexity in the OFC, with sex influencing whether the increase in branching occurred near or away from the soma. Spine density or maturity was not affected, likely compensating for a disruption in neurotransmitter function following AIE.

Significance StatementAdolescent ethanol exposure decreases cholinergic markers in the basal forebrain to orbital frontal cortical circuit, which lead to a massive suppression of behaviorally-activated tonic release acetylcholine and sex-dependent increases in dendritic branching. We concluded that cholinergic dysfunction is a contributor to cognitive impairments associated with heavy alcohol exposure during adolescence.

Data SharingThe data that support the findings of this study are available from the corresponding author upon reasonable request.

category: neuroscience


title: High Gamma and Beta Temporal Interference Stimulation in the Human Motor Cortex Improves Motor Functions

abstract:
BackgroundTemporal interference (TI) stimulation is a new technique of noninvasive brain stimulation. Envelope-modulated waveforms with two high-frequency carriers can activate neurons in target brain regions without stimulating the overlying cortex, which has been validated in mouse brains. However, whether TI stimulation can work on the human brain has not been elucidate.

ObjectiveTo assess the effectiveness and safety aspect of the envelope-modulated waveform of TI stimulation on human primary motor cortex (M1).

MethodsParticipants attended three sessions of 30-min TI stimulation at 2 mA during a random reaction time task (RRTT) or a serial reaction time task (SRTT). Motor cortex excitability was measured before and after TI stimulation.

ResultsIn the RRTT experiment, only 70 Hz TI stimulation had a promoting effect on the reaction time (RT) performance and excitability of the motor cortex compared to sham stimulation. Meanwhile, compared with the sham condition, only 20 Hz TI stimulation significantly facilitated motor learning in the SRTT experiment, which was significantly positively correlated with the increase in motor evoked potential.

ConclusionThese results indicate that the envelope-modulated waveform of TI stimulation has a significant promoting effect on human motor functions, experimentally suggesting the effectiveness of TI stimulation in humans for the first time and pave the way for further explorations.


title: Lumican regulates cervical corticospinal axon collateralization via non-autonomous crosstalk between distinct corticospinal neuron subpopulations

abstract: Corticospinal neurons (CSN) are the cortical projection neurons that innervate the spinal cord and some brainstem targets with segmental precision to control voluntary movement of specific functional motor groups, limb sections, or individual digits. CSN subpopulations exhibit striking axon targeting specificity from development into maturity: Evolutionarily newer rostrolateral CSN exclusively innervate bulbar-cervical targets (CSNBC-lat), while evolutionarily older caudomedial CSN (CSNmedial) are more heterogeneous, with distinct subpopulations extending axons to either bulbar-cervical or thoraco-lumbar segments. However, molecular regulation over specificity of CSN segmental target innervation is essentially unknown. The cervical cord, with its evolutionarily enhanced precision of forelimb movement, is innervated by multiple CSN subpopulations, suggesting inter-neuronal interactions in establishing cervical corticospinal circuitry. Here, we identify that Lumican, previously unrecognized in axon development, controls the balance of innervation between CSNBC-lat and CSNmedial within the cervical spinal cord. Remarkably, Lumican, an extracellular matrix protein expressed by CSNBC-lat, non-cell-autonomously suppresses axon collateralization in the cervical cord by CSNmedial. Intersectional viral labeling and mouse genetics further identify that Lumican controls axon collateralization by multiple CSN subpopulations in caudomedial sensorimotor cortex. These results identify inter-axonal molecular crosstalk between CSN subpopulations as a novel mechanism controlling corticospinal circuitry, target density, and competitive specificity. Further, this mechanism has potential implications for evolutionary diversification of corticospinal circuitry with finer scale precision.


title: Fast and accurate annotation of acoustic signals with deep neural networks

abstract:
Acoustic signals serve communication within and across species throughout the animal kingdom. Studying the genetics, evolution, and neurobiology of acoustic communication requires annotating acoustic signals: segmenting and identifying individual acoustic elements like syllables or sound pulses. To be useful, annotations need to be accurate, robust to noise, and fast.

We here introduce DAS, a method that annotates acoustic signals across species based on a deep-learning derived hierarchical presentation of sound. We demonstrate the accuracy, robustness, and speed of DAS using acoustic signals with diverse characteristics from insects, birds, and mammals. DAS comes with a graphical user interface for annotating song, training the network, and for generating and proofreading annotations. The method can be trained to annotate signals from new species with little manual annotation and can be combined with unsupervised methods to discover novel signal types. DAS annotates song with high throughput and low latency, allowing realtime annotations for closed-loop experimental interventions. Overall, DAS is a universal, versatile, and accessible tool for annotating acoustic communication signals.


title: A FOXN1 mutation competitively displaces wild-type FOXN1 from higher order nuclear condensates to cause immunodeficiency

abstract: The transcription factor FOXN1 is a master regulator of thymic epithelial cell development and function. Here we demonstrate that FOXN1 expression is differentially regulated during organogenesis and participates in multi-molecular nuclear condensates essential for the factors transcriptional activity. FOXN1s C-terminal sequence regulates the diffusion velocity within these aggregates and modulates the binding to proximal gene regulatory regions. These dynamics are significantly altered in a patient with a mutant FOXN1 which is modified in its C-terminal sequence. This mutant is transcriptionally inactive and acts as a dominant negative factor displacing wild-type FOXN1 from condensates and causing athymia and severe lymphopenia in heterozygotes. Expression of the mutated mouse ortholog, selectively impairs mouse thymic epithelial cell (TEC) differentiation revealing a gene dose dependency for individual TEC subtypes. We have therefore identified the cause for a primary immunodeficiency disease and determined the mechanism by which this FOXN1 gain-of-function mutant mediates its dominant negative effect.

category: immunology


title: Generation and first characterization of TRDC-Knockout pigs lacking γδ T cells

abstract: The TRDC-Locus encodes the T cell receptor delta constant region, one component of the {gamma}{delta} T cell receptor which is essential for development of {gamma}{delta} T cells. In contrast to peptide recognition by {beta} T cells, antigens activating {gamma}{delta} T cells are mostly MHC independent and not well characterized. Therefore, the function of {gamma}{delta} T cells and their contribution to protection against infections is still unclear. Higher numbers of circulating {gamma}{delta} T cells compared to mice, render the pig a suitable animal model to study {gamma}{delta} T cells. Knocking-out the porcine TRDC-locus by intracytoplasmic microinjection and somatic cell nuclear transfer resulted in healthy living {gamma}{delta} T cell deficient offspring. Flow cytometric analysis revealed that TRDC-KO pigs lack {gamma}{delta} T cells in peripheral blood mononuclear cells (PBMC) and spleen cells. The composition of the remaining leucocyte subpopulations was not affected by the depletion of {gamma}{delta} T cells. Genome-wide transcriptome analyses in PBMC revealed a pattern of changes reflecting the impairment of known or expected {gamma}{delta} T cell dependent pathways. Histopathology did not reveal developmental abnormalities of secondary lymphoid tissues. However, in a vaccination experiment the KO pigs stayed healthy but had a significantly lower neutralizing antibody titer as the syngenic controls.


title: Transcriptome profiling of embryonic retinal pigment epithelium reprogramming

abstract: The plasticity of human retinal pigment epithelium (RPE) has been observed during proliferative vitreoretinopathy, a defective repair process during which injured RPE gives rise to fibrosis. In contrast, following injury, the RPE of the embryonic chicken can be reprogrammed to regenerate neural retina in an FGF2-dependent manner. To characterize the mechanisms underlying embryonic RPE reprogramming, we used laser capture microdissection to isolate RNA from 1) intact RPE, 2) transiently reprogrammed RPE (t-rRPE) 6 hours post-retinectomy, and 3) reprogrammed RPE (rRPE) 6 hours post-retinectomy with FGF2 treatment. Using RNA-seq, we observed the acute repression of genes related to cell cycle progression in the injured t-rRPE, as well as up-regulation of genes associated with injury. In contrast, the rRPE was strongly enriched for MAPK-responsive genes and retina development factors, confirming that FGF2 and the downstream MAPK cascade are the main drivers of embryonic RPE reprogramming. Clustering and pathway enrichment analysis were used to create an integrated network of the core processes associated with RPE reprogramming, including key terms pertaining to injury response, migration, actin dynamics, and cell cycle progression. Finally, we employed gene set enrichment analysis to suggest a previously uncovered role for epithelial-mesenchymal transition (EMT) machinery in the initiation of embryonic chick RPE reprogramming. The EMT program is accompanied by extensive, coordinated regulation of extracellular matrix (ECM) regulators, and these observations together suggest an early role for ECM and EMT-like dynamics during reprogramming. Our study provides for the first time an in-depth transcriptomic analysis of embryonic RPE reprogramming and will prove useful in guiding future efforts to understand proliferative disorders of the RPE and to promote retinal regeneration.

category: developmental biology


title: Tolerance of Wildlife in Protected Area Borderlands

abstract: Increases in human-wildlife conflict globally threaten human wellbeing and biodiversity conservation. Sustainable solutions that promote coexistence of people and wildlife are needed, especially in human-dominated landscapes surrounding protected areas. Peoples attitudes toward wildlife influence their behaviours, including tolerance for human-wildlife interactions, poaching, and habitat degradation. Better understanding of how to improve peoples attitudes toward wildlife is instrumental to promoting coexistence between people and wildlife in shared spaces. Efforts to promote coexistence often fail because they are based on the inaccurate assumption that peoples attitudes towards wildlife are directly and proportionally related to wildlife-based financial incentives and costs. In reality, peoples attitudes towards wildlife are far more complex. We analysed surveys (n=237) from Mozambique to examine peoples attitudes toward wildlife in the buffer zones surrounding protected areas using logistic regression and Getis-Ord hot-spot analysis (GI*). Mozambique, which is under-represented in the wildlife-based research literature, is characterized by extreme poverty and rewilding efforts. We found that most respondents were tolerant of wildlife and tolerance was positively correlated with peoples age, gender, and agreement with rules governing wildlife conservation. Peoples tolerance for wildlife was also reinforced if they receive benefits from wildlife and are situated further from the park fence. Predation, human harm, and crop loss were not significant predictors of tolerance. We found no evidence of spatial patterns in tolerance for wildlife. Our results suggest that wildlife conservation programs are more likely to be successful if benefits are distributed equitably and community members are actively involved in decision making.

category: ecology


title: Identifying key federal, state, and private lands strategies for achieving 30x30 in the US

abstract: Achieving ambitious conservation goals to conserve at least 30% of US lands and waters by 2030 ("30x30") will require a multi-scale baseline understanding of current protections, key decision makers, and policy tools for moving forward. To help conservationists and decision makers support the science-based call to address the biodiversity and climate crises, we analyze the current spatial patterns of imperiled species biodiversity and carbon stores in the U.S. relative to protected areas. Analyses demonstrate that 30x30 is numerically achievable nationally, but high spatial heterogeneity highlights the need for tailored approaches from a mix of authorities at federal, regional, and state scales. Critically, current land protections rarely overlap with areas essential for conserving imperiled species biodiversity and mitigating climate change. Nearly one-fifth of unprotected biodiversity hotspots and carbon-rich areas are also at risk of either land conversion or climate exposure by 2050. We discuss this baseline relative to key policy considerations for making practical, substantive progress toward the goal.


title: Desiccation stress acts as cause as well as cost of dispersal in Drosophila melanogaster

abstract:
O_LIEnvironmental stress is one of the important causes of biological dispersal. At the same time, the process of dispersal itself can incur and/or increase susceptibility to stress for the dispersing individuals. Therefore, in principle, stress can serve as both a cause and a cost of dispersal.
C_LIO_LIDesiccation stress is an environmentally relevant stress faced by many organisms, known to shape their population dynamics and distribution. However, the potentially contrasting roles of desiccation stress as a cause and a cost of dispersal have not been investigated. Furthermore, while desiccation stress often affects organisms in a sex-biased manner, it is not known whether the desiccation-dispersal relationship varies between males and females.
C_LIO_LIWe studied the role of desiccation stress as a cause and cost of dispersal in a series of experiments using D. melanogaster adults in two-patch dispersal setups. We were interested in knowing whether (a) dispersers are the individuals that are more susceptible to desiccation stress, (b) dispersers pay a cost in terms of reduced resistance to desiccation stress, (c) dispersal evolution alters the desiccation cost of dispersal, and (d) females pay a reproductive cost of dispersal. For this, we modulated the degree of desiccation stress faced by the flies as well as the provision of rest following a dispersal event.
C_LIO_LIOur data showed that desiccation stress served as a significant cause of dispersal in both sexes. Further investigation revealed an increase in both male and female dispersal propensity with increasing desiccation duration. Next, we found a male-biased cost of dispersal in terms of reduced desiccation resistance. This trend was preserved in dispersal-selected and non-selected controls as well, where the desiccation cost of dispersal in females was very low compared to the males. Finally, we found that the females instead paid a significant reproductive cost of dispersal.
C_LIO_LIOur results highlight the complex relationship between desiccation stress and dispersal, whereby desiccation resistance can show both a positive and a negative association with dispersal. Furthermore, the sex differences observed in these trait associations may translate into differences in movement patterns, thereby giving rise to sex-biased dispersal.
C_LI


title: Machine learning algorithms in big data analyses identify determinants of insulin gene transcription

abstract: Machine learning (ML)-workflows enable unprejudiced/robust evaluation of complex datasets. Here, we analyzed over 490,000,000 data points to compare 10 different ML-workflows in a large (N=11,652) training dataset of human pancreatic single-cell (sc-)transcriptomes to identify genes associated with the presence or absence of insulin transcript(s). Prediction accuracy/sensitivity of each ML-workflow were tested in a separate validation dataset (N=2,913). Ensemble ML-workflows, in particular Random Forest ML-algorithm delivered high predictive power (AUC=0.83) and sensitivity (0.98), compared to other algorithms. The transcripts identified through these analyses also demonstrated significant correlation with insulin in bulk RNA-seq data from human islets. The top-10 features, (including IAPP, ADCYAP1, LDHA and SST) common to the three Ensemble ML-workflows were significantly dysregulated in scRNA-seq datasets from Ire-1{beta}-/- mice that demonstrate dedifferentiation of pancreatic {beta}-cells in a model of type 1 diabetes (T1D) and in pancreatic single cells from individuals with type 2 Diabetes (T2D). Our findings provide direct comparison of ML-workflows in big data analyses, identify key determinants of insulin transcription and provide workflows for future analyses.

category: genetics


title: Time-course RNASeq of Camponotus floridanus forager and nurse ant brains indicate links between plasticity in the biological clock and behavioral division of labor

abstract:
BackgroundCircadian clocks allow organisms to anticipate daily fluctuations in their environment by driving rhythms in physiology and behavior. Inter-organismal differences in daily rhythms, called chronotypes, exist and can shift with age. In ants, age, caste-related behavior and chronotype appear to be linked. "Around-the-clock" active nurse ants are usually younger and, with age, transition into rhythmically active foragers. Moreover, ants can shift between these behavioral castes depending on social context. We investigated how changes in daily gene expression could be contributing to such behavioral plasticity in Camponotus floridanus carpenter ants by combining time-course behavioral assays and RNA-Sequencing of forager and nurse brains.

ResultsWe found that nurse brains have three times fewer 24h oscillating genes than foragers. However, several hundred genes that oscillated every 24h in forager brains showed robust 8h oscillations in nurses, including the core clock genes Period and Shaggy. These differentially rhythmic genes consisted of several components of the circadian entrainment pathway, and showed enrichments for functions related to metabolism, cellular communication and protein modification. We additionally found that Vitellogenin, known to regulate division of labor in social insects, showed robust 24h oscillations in nurse brains but not in foragers. Furthermore, the protein products of several genes that were differentially expressed between the two ant castes were previously found in the trophallactic fluid of C. floridanus. This suggests a putative role for trophallaxis in regulating behavioral division of labor through caste-specific gene expression.

ConclusionWe provide a first look at the chronobiological differences in gene expression between forager and nurse ant brains. This endeavor allowed us to identify putative molecular mechanisms underlying plastic timekeeping. Several components of the ant circadian clock and its output can seemingly oscillate at different harmonics of the circadian rhythm. We propose that such chronobiological plasticity has evolved to allow for distinct regulatory networks that underlie behavioral castes, while supporting swift caste transitions in response to colony demands. Behavioral division of labor is common among social insects. The links between chronobiological and behavioral plasticity that we found in C. floridanus, thus, likely represent a more general phenomenon that warrants further investigation.

category: animal behavior and cognition


title: Stand-alone lipoylated H-protein of the glycine cleavage system enables glycine cleavage and the synthesis of glycine from one-carbon compounds in vitro

abstract:
H-protein, one of the four component proteins (H, T, P and L) of glycine cleavage system (GCS), is generally considered a shuttle protein interacting with the other three GCS-proteins via a lipoyl swinging arm. We report that without P-, T- and L-proteins, lipoylated H-protein (Hlip) enables GCS reactions in both glycine cleavage and synthesis directions in vitro. This apparent catalytic activity is closely related to the cavity on the H-protein surface where the lipoyl arm is attached. Heating or mutation of selected residues in the cavity destroys or reduces the stand-alone activity of Hlip, which can be restored by adding the other three GCS-proteins. Systematic study of the Hlip-catalyzed overall GCS reactions and the individual reaction steps provides a first step towards understanding the stand-alone function of Hlip. The results in this work provide some inspiration for further understanding the mechanism of the GCS and give some interesting implications on the evolution of the GCS.

Significance statementGlycine cleavage system (GCS) plays central roles in C1 and amino acids metabolisms and the biosynthesis of purines and nucleotides. Manipulations of GCS are desired to promote plant growth or to treat serious pathophysiological processes such as aging, obesity and cancers. Reversed GCS reactions form the core of the reductive glycine pathway (rGP), one of the most promising pathway for the assimilation of formate and CO2 in the emerging C1-synthetic biology. H-protein, one of the four GCS component proteins (H, T, P and L) is generally considered a shuttle protein interacting with the other three proteins via a lipoyl swinging arm. Here, we discovered that without P-, T- and L-proteins, H-protein alone can catalyze GCS reactions in both glycine cleavage and synthesis directions in vitro. The surprising catalytic activities are related to a structural region of H-protein which can be manipulated. The results have impacts on engineering GCS to treat related diseases, to improve photorespiration, and to efficiently use C1-carbon for biosynthesis.

category: biochemistry


title: Electron transfer parameters for Methemoglobin formation in mutant Hemoglobin α-chains.

abstract: Hemoglobin mediated transport of dioxygen (O2) critically depends on the stability of the reduced (Fe2+) form of the Heme cofactors. Some protein mutations stabilize oxidized (Fe3+) state (Methemoglobin, Hb M) causing methemoglobinemia and can be lethal above 30 %. Majority of the analyses of factors influencing Hb oxidation are retrospective and give insights only for inner sphere mutations of Heme (His58, His87). Herein, we report the first all atom MD simulations on redox states and calculations of the Marcus ET parameters for the -chain Hb oxidation and reduction rates for Hb M. The Hb (wild type), and most of the studied -chain variants maintain globin structure except the Hb M Iwate (H87Y). Using linear response approximation we calculated average energy gaps (<{Delta}E>), total ({lambda}), protein ({lambda}prot), solvent ({lambda}solv) reorganization energies, and redox potentials (E{degrees}), and oxidation free energies ({Delta}G{degrees}). The total {lambda} ranges from 0.685 - 0.730 eV in agreement with literature on Hb and similar Heme proteins. The mutants forming Hb M tend to lower the E{degrees} and thus stabilize the oxidized (Fe3+) state (e.g. the Hb Miyagi variant with K61E mutation). Solvent reorganization ({lambda}solv 73 - 96 %) makes major contributions to {lambda}, while protein reorganization ({lambda}prot) accounts for 27 - 30 % except for the Miyagi and J-Buda variants ({lambda}prot [~] 4 %). Analysis of Heme-solvent H-bonding interactions among variants provide insights into the role of Lys61 residue in stabilizing Fe2+ state and ET parameters. The ET parameters provide valuable insights into the Hb oxidation to Hb M in agreement with the experimental data. Thus our methodology explains the effect of mutations on the structure, stability and Hb oxidation, and has potential for the prediction of methemoglobinemia.


title: A NOVEL PARADIGM FOR DEEP REINFORCEMENT LEARNING OF BIOMIMETIC SYSTEMS

abstract: Mechanisms behind neural control of movement have been an active area of research. Goal-directed movement is a common experimental setup used to understand these mechanisms and relevant neural pathways. On the one hand, optimal feedback control theory is used to model and make quantitative predictions of the coordinated activations of the effectors, such as muscles, joints or limbs. While on the other hand, evidence shows that higher centres such as Basal Ganglia and Cerebellum are involved in activities such as reinforcement learning and error correction. In this paper, we provide a framework to build a digital twin of relevant sections of the human spinal cord using our NEUROiD platform. The digital twin is anatomically and physiologically realistic model of the spinal cord at cellular, spinal networks and system level. We then build a framework to learn the supraspinal activations necessary to perform a simple goal directed movement of the upper limb. The NEUROiD model is interfaced to an Opensim model for all the musculoskeletal simulations. We use Deep Reinforcement Learning to obtain the supraspinal activations necessary to perform the goal directed movement. As per our knowledge, this is the first time an attempt is made to learn the stimulation pattern at the spinal cord level, especially by limiting the observation space to only the afferent feedback received on the Ia, II and Ib fibers. Such a setup results in a biologically realistic constrained environment for learning. Our results show that (1) Reinforcement Learning algorithm converges naturally to the triphasic response observed during goal directed movement (2) Increasing the complexity of the goal gradually helped to accelerate learning (3) Modulation of the afferent inputs were sufficient to execute tasks which were not explicitly learned, but were closely related to the learnt task.

category: bioengineering


title: A Novel Paradigm for Deep Reinforcement Learning of Biomimetic Systems


title: A machine-learning algorithm correctly classifies cortical evoked potentials from both natural retinal stimulation and electrical stimulation of the optic nerve

abstract:
ObjectiveOptic nerves intraneural stimulation is an emerging neuroprosthetic approach to provide artificial vision to totally blind patients. An open question is the possibility to evoke individual non-overlapping phosphenes via selective intraneural optic nerve stimulation. To begin answering this question, first, we aim at showing in preclinical experiments with animals that each intraneural electrode could evoke a distinguishable activity pattern in the primary visual cortex.

ApproachWe performed both patterned visual stimulation and patterned electrical stimulation in healthy rabbits while recording evoked cortical activity with an electrocorticogram array in the primary visual cortex. Electrical stimulation was delivered to the optic nerve with the intraneural array OpticSELINE. We used a support vector machine algorithm paired to a linear regression model to classify cortical responses originating from visual stimuli located in different portions of the visual field and electrical stimuli from the different electrodes of the OpticSELINE.

Main resultsCortical activity induced by visual and electrical stimulation could be classified with nearly 100% accuracy relative to the specific location in the visual field or electrode in the array from which it originated. For visual stimulation, the accuracy increased with the separation of the stimuli and reached 100% for separation higher than 7 degrees. For electrical stimulation, at low current amplitudes, the accuracy increased with the distance between electrodes, while at higher current amplitudes, the accuracy was nearly 100% already for the shortest separation.

SignificanceOptic nerves intraneural stimulation with the OpticSELINE induced discernible cortical activity patterns. These results represent a leap forward for intraneural optic nerve stimulation towards artificial vision.


title: Comprehensive machine-learning-based analysis of microRNA-target interactions reveals variable transferability of interaction rules across species

abstract:
BackgroundMicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally via base-pairing with complementary sequences on messenger RNAs (mRNAs). Due to the technical challenges involved in the application of high-throughput experimental methods, datasets of direct bona-fide miRNA targets exist only for a few model organisms. Machine learning (ML) based target prediction methods were successfully trained and tested on some of these datasets. There is a need to further apply the trained models to organisms where experimental training data is unavailable. However, it is largely unknown how the features of miRNA-target interactions evolve and whether there are features that have been fixed during evolution, questioning the general applicability of these ML methods across species.

ResultsIn this paper, we examined the evolution of miRNA-target interaction rules and used data science and ML approaches to investigate whether these rules are transferable between species. We analyzed eight datasets of direct miRNA-target interactions in four organisms (human, mouse, worm, cattle). Using ML classifiers, we achieved high accuracy for intra-dataset classification and found that the most influential features of all datasets significantly overlap. To explore the relationships between datasets we measured the divergence of their miRNA seed sequences and evaluated the performance of cross-datasets classification. We showed that both measures coincide with the evolutionary distance of the compared organisms.

ConclusionsOur results indicate that the transferability of miRNA-targeting rules between organisms depends on several factors, the most associated factors being the composition of seed families and evolutionary distance. Furthermore, our feature importance results suggest that some miRNA-target features have been evolving while some have been fixed during evolution. Our study lays the foundation for the future developments of target prediction tools that could be applied to "non-model" organisms for which minimal experimental data is available.

Availability and implementation The code is freely available at https://github.com/gbenor/TPVOD

category: bioinformatics


title: Bioinformatics analysis of potential key genes and mechanisms in type 2 diabetes mellitus

abstract: Type 2 diabetes mellitus (T2DM) is etiologically related to metabolic disorder. The aim of our study was to screen out candidate genes of T2DM and to elucidate the underlying molecular mechanisms by bioinformatics methods. Expression profiling by high throughput sequencing data of GSE154126 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between T2DM and normal control were identified. And then, functional enrichment analyses of gene ontology (GO) and REACTOME pathway analysis was performed. Protein-protein interaction (PPI) network and module analyses were performed based on the DEGs. Additionally, potential miRNAs of hub genes were predicted by miRNet database. Transcription factors (TFs) of hub genes were detected by NetworkAnalyst database. Further, validations were performed by receiver operating characteristic curve (ROC) analysis and real-time polymerase chain reaction (RT-PCR). In total, 925 DEGs were identified in T2DM, including 447 up regulated genes and 478 down-regulated genes. Functional enrichment analysis results showed that up regulated DEGs were significantly enriched in defense response, neutrophil degranulation, cell adhesion and extracellular matrix organization. The top 10 hub genes, JUN, VCAM1, RELA, U2AF2, ADRB2, FN1, CDK1, TK1, A2M and ACTA2 were identified from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Furthermore, ROC analysis and RT-PCR revealed that JUN, VCAM1, RELA, U2AF2, ADRB2, FN1, CDK1, TK1, A2M and ACTA2 might serve as biomarkers in T2DM. Bioinformatics analysis is a useful tool to explore the molecular mechanism and pathogenesis of T2DM. The identified hub genes may participate in the onset and advancement of T2DM and serve as therapeutic targets.


title: CNAHap: a germline haplotyping method using tumor allele-specific copy number alteration

abstract: Haplotype phasing is indispensable to study human genetics. The pervasiveness of large copy number variant segments in solid tumors brings possibilities to resolve long germline phasing blocks utilizing allele imbalance in tumor data. Although there exist such studies, none of them provide easy-use software based on availability and usability. Herein, we present a novel tool, CNAHap, to determine the allele-specific copy number in tumor and then phase germline variants according to the imbalanced alleles in tumor genomes. We also provide interactive web interfaces to visualize the copy number and phase landscape from CNAHap. On in silico datasets, CNAHap demonstrates higher allele-specific copy number calling accuracy than the benchmark tool and generates long phasing blocks. As a case study on Hepatocellular carcinoma, CNAHap successfully generates huge phase blocks with the averages of N50 and N90 as 25M and 7M, respectively, and finds the Olfactory receptor family is recurrent amplified. Our results illustrate the efficacy of CNAHap in determining tumor allele-specific copy numbers and their long germline haplotypes. CNAHap is available at https://github.com/bowentan/CNAHap and the CNAHap visualization web interfaces are hosted at bio.oviz.org.


title: Anatomy of unfolding: The site-specific fold stability of Yfh1 measured by 2D NMR

abstract: Most techniques allow detection of protein unfolding either by following the behaviour of single reporters or as an averaged all-or-none process. We recently added 2D NMR spectroscopy to the well-established techniques able to obtain information on the process of unfolding using resonances of residues in the hydrophobic core of a protein. Here, we questioned whether an analysis of the individual stability curves from each resonance could provide additional site-specific information. We used the Yfh1 protein that has the unique feature to undergo both cold and heat denaturation at temperatures above water freezing at low ionic strength. We show that stability curves inconsistent with the average NMR curve from hydrophobic core residues mainly comprise exposed outliers that do nevertheless provide precious information. By monitoring both cold and heat denaturation of individual residues we gain knowledge on the process of cold denaturation and convincingly demonstrate that the two unfolding processes are intrinsically different.

category: biophysics


title: An EMG-assisted Muscle-Force Driven Finite Element Analysis Pipeline to Investigate Joint- and Tissue-Level Mechanical Responses in Functional Activities: Towards a Rapid Assessment Toolbox

abstract: Joint tissue mechanics (e.g., stress and strain) are believed to have a major involvement in the onset and progression of musculoskeletal disorders, e.g., knee osteoarthritis (KOA). Accordingly, considerable efforts have been made to develop musculoskeletal finite element (MS-FE) models to estimate highly-detailed tissue mechanics that predict cartilage degeneration. However, creating such models is time-consuming and requires advanced expertise. This limits these complex, yet promising MS-FE models to research applications with few participants and making the models impractical for clinical assessments. Also, these previously developed MS-FE models are not assessed for any activities other than the gait. This study introduces and validates a semi-automated rapid state-of-the-art MS-FE modeling and simulation toolbox incorporating an electromyography (EMG) assisted MS model and a muscle-force driven FE model of the knee with fibril-reinforced poro(visco)elastic cartilages and menisci. To showcase the usability of the pipeline, we estimated joint- and tissue-level knee mechanics in 15 KOA individuals performing different daily activities. The pipeline was validated by comparing the estimated muscle activations and joint mechanics to existing experimental data. Also, to examine the importance of EMG-assisted MS analyses, results were compared against outputs from the same FE models but driven by static-optimization-based MS models. The EMG-assisted MS-FE pipeline bore a closer resemblance to experiments, compared to the static-optimization-based MS-FE pipeline. More importantly, the developed pipeline showed great potentials as a rapid MS-FE analysis toolbox to investigate multiscale knee mechanics during different activities of individuals with KOA.


title: Revisiting Decompression Sickness Risk and Mobility in the Context of the SmartSuit, a Hybrid Planetary Spacesuit

abstract: Gas pressurized spacesuits are cumbersome, cause injuries, and make completing tasks efficiently difficult. Decreasing the gas pressure of the spacesuit is an effective method of improving mobility, but reduction in the total spacesuit pressure also results in a higher risk for decompression sickness (DCS). The risk of DCS is currently mitigated by breathing pure oxygen before the Extravehicular Activity (EVA) for up to 4 hours to remove inert gases from body tissues, but this has a negative operational impact due to the time needed to perform the prebreathe. In this paper, we review and quantify these important trade-offs between spacesuit pressure, mobility, and prebreathe time (or risk of DCS) in the context of future planetary EVAs. These trade-offs are highly dependent on the atmospheric conditions used in the space habitat or space station, and therefore, these conditions are also important considerations for future planetary exploration activities. In our analysis, we include three habitat scenarios (International Space Station: 14.7 psia, 21% O2, Adjusted Space Shuttle: 10.2 psia, 26.5% O2, and Exploration: 8.2 psia, 34% O2) to further quantify these differences. In addition, we explore these trade-offs in the context of the SmartSuit spacesuit architecture, a hybrid spacesuit with a soft robotic layer that, not only increases mobility with assistive actuators in the lower body, but it also applies 1 psia of mechanical counterpressure (MCP). The additional MCP in hybrid spacesuits can be used to supplement the gas pressure (i.e., increasing the total spacesuit pressure), therefore reducing the risk of DCS (or reduce prebreathe time). Alternatively, the MCP can be used to reduce the gas pressure (i.e., maintaining the same total spacesuit pressure), therefore increasing mobility. Finally, we propose a variable pressure concept of operations for the SmartSuit spacesuit architecture, where these two MCP applications are effectively combined during the same EVA to maximize the benefits of both configurations. Our framework quantifies critical spacesuit and habitat trade-offs for future planetary exploration, and contributes to the assessment of human health and performance during future planetary EVAs.

category: physiology


title: Pathogenesis-related protein 1 (PR-1) genes in soybean: genome-wide identification, structural analysis and expression profiling under multiple biotic and abiotic stresses

abstract: Plant pathogenesis-related (PR) proteins are a large group of proteins, classified in 17 families, that are induced by pathological conditions. Here, we characterized the soybean PR-1 (GmPR-1) gene repertoire at the sequence, structural and expression levels. We found 24 GmPR-1 genes, clustered in two phylogenetic groups. GmPR-1 genes are under strong purifying selection, particularly those that emerged by tandem duplications. GmPR-1 promoter regions are abundant in cis-regulatory elements associated with major stress-related transcription factor families, namely WRKY, ERF, HD-Zip, C2H2, NAC, and GATA. We observed that 23 GmPR-1 genes are induced by stress conditions or exclusively expressed upon stress. We explored 1972 transcriptome samples, including 26 stress conditions, revealing that most GmPR-1 genes are differentially expressed in a plethora of biotic and abiotic stresses. Our findings highlight stress-responsive GmPR-1 genes with potential biotechnological applications, such as the development of transgenic lines with increased resistance to biotic and abiotic stresses.

category: plant biology


title: Tissue-specific mRNA profiling of the Brassica napus-Sclerotinia sclerotiorum interaction uncovers novel regulators of plant immunity

abstract:
White mold in Brassica napus (canola) is caused by the fungal pathogen Sclerotinia sclerotiorum and is responsible for significant losses in crop yield across the globe. With advances in high-throughput transcriptomics, our understanding of the B. napus defense response to S. sclerotiorum is becoming clearer; however, the response of individual tissue layers directly at the site of infection has yet to be explored. Using laser microdissection coupled with RNA sequencing, we profiled the epidermis, mesophyll and vascular leaf tissue layers in response to S. sclerotiorum. This strategy increases the number of genes detected compared to whole-leaf assessments and provides unprecedented information on tissue-specific gene expression networks in response to pathogen attack. Our findings provide novel insight into the conserved and specific roles of ontogenetically distinct leaf tissue layers in response to infection. Using bioinformatics tools, we identified several defense genes that might coordinate plant immunity responses shared across different tissue layers within the leaf. These genes were functionally characterized by challenging T-DNA insertion lines of Arabidopsis with necrotrophic, hemi-biotrophic, and biotrophic pathogens, ultimately converging on the PR5-like RECEPTOR KINASE (PRK5). Together, these data provide insight on the complexity of the B. napus defense response directly at the site of infection.

HighlightLaser microdissection coupled RNA sequencing of the B. napus - S. sclerotiorum interaction identifies candidate genes predicted to guide plant immunity against pathogen attack.


title: A dynamical model of TGF-β activation in asthmatic airways

abstract: Excessive activation of the regulatory cytokine transforming growth factor {beta} (TGF-{beta}) via contraction of airway smooth muscle (ASM) is associated with the development of asthma. In this study, we develop an ordinary differential equation model that describes the change in density of the key airway wall constituents, ASM and extracellular matrix (ECM), and their interplay with subcellular signalling pathways leading to the activation of TGF-{beta}. We identify bistable parameter regimes where there are two positive steady states, corresponding to either reduced or elevated TGF-{beta} concentration, with the latter leading additionally to increased ASM and ECM density. We associate the former with a healthy homeostatic state and the latter with a diseased (asthmatic) state. We demonstrate that external stimuli, inducing TGF-{beta} activation via ASM contraction (mimicking an asthmatic exacerbation), can perturb the system irreversibly from the healthy state to the diseased one. We show that the properties of the stimuli, such as their frequency or strength, and the clearance of surplus active TGF-{beta}, are important in determining the long-term dynamics and the development of disease. Finally we demonstrate the utility of this model in investigating temporal responses to bronchial thermoplasty, a therapeutic intervention in which ASM is ablated by applying thermal energy to the airway wall. The model predicts the parameter-dependent threshold damage required to obtain irreversible reduction in ASM content suggesting that certain asthma phenotypes are more likely to benefit from this intervention.

category: systems biology


title: Mathematical Model for the Study of Mitochondrial Retrograde Signaling Dynamics

abstract:
Mitochondria, semi-autonomous eukaryotic organelles, participate in energy production and metabolism, making mitochondrial quality control crucial. As most mitochondrial proteins are encoded by nuclear genes, quality control depends on proper mitochondria-nucleus communication, designated mitochondrial retrograde signaling. Early studies focused on retrograde signaling participants and specific gene knockouts. However, mitochondrial signal modulation remains elusive. Using yeast, we simulated signal propagation following mitochondrial damage and proposed a mathematical model based ordinary differential equations. Mitochondrial retrograde signaling decisions were described using a Boolean model. Dynamics were analyzed through an ordinary differential equation-based model and extended to evaluate the model response to noisy damage signals. Simulation revealed localized protein concentration dynamics, including waveforms, frequency response, and robustness under noise. Retrograde signaling is bistable with three localized steady states, and increased damage compromises robustness. We elucidated mitochondrial retrograde signaling, thus providing a basis for drug design against yeast and fungi.

Author SummaryThe yeast RTG pathway regulates mitochondrial metabolism and mitochondrial quality through passing mitochondrial signal to the nucleus to modulate gene expressions. Using microscopic data of RTG proteins translocation from cytosol to nucleus, the parameters were found by fitting 16 knockout conditions simulated from the proposed differential equation-based model. Further, through dose response, ultrasensitivity, frequency response and noise interference, we demonstrated a switch-like property of RTG pathway activation, a capacity charging property of RTG protein translocation, a low pass filter property of signals in different frequencies, and noise amplification due to mitochondrial signal. The proposed mathematical model enables us to understand the dynamics and mechanisms in mitochondrial retrograde signaling in yeast and provides potential antifungal treatment strategies.


title: Mathematical Modeling and Analysis of Mitochondrial Retrograde Signaling Dynamics


title: Functional expression of the ATP-gated P2X7 receptor in human iPSC-derived neurons and astrocytes

abstract: The P2X7 receptor (P2X7R) is a cation membrane channel activated by extracellular adenosine 5'-triphosphate. Activation of this receptor results in numerous downstream events including the modulation of neurotransmission, release of pro-inflammatory mediators, cell proliferation or cell death. While the expression of P2X7Rs is well documented on microglia and oligodendrocytes, the presence of functional P2X7Rs on neurons and astrocytes remains debated. Furthermore, to date, functional studies on the P2X7R are mostly limited to studies in cells from rodents and immortalised cell lines expressing human P2X7Rs. To assess the functional expression of P2X7Rs in human neurons and astrocytes, we differentiated human-induced pluripotent stem cells (hiPSCs) into forebrain cortical neurons that co-express FOXG1 and {beta}III-tubulin as well as S100 {beta}-expressing astrocytes. Immunostaining revealed prominent punctate P2X7R staining on the soma and processes of hiPSC-derived neurons and astrocytes. In addition, our data show that stimulation with the potent nonselective P2X7R agonist BzATP induces robust calcium rises in hiPSC-derived neurons and astrocytes, which were blocked by the selective P2X7R antagonist AFC-5128. Together, our findings provide evidence for the functional expression of P2X7Rs in hiPSC-derived forebrain cortical neurons and astrocytes demonstrating that these cells offer the potential for investigating P2X7R-mediated pathophysiology and drug screening in vitro.


title: Perceiving and remembering speech depend on nonlinearity in movements producing and exploring speech

abstract: Speech perception and memory for speech require active engagement. Gestural theories have emphasized mainly the effect of speakers movements on speech perception. They fail to address the effects of listener movement, focusing on communication as a boundary condition constraining movement among interlocutors. The present work attempts to break new ground by using multifractal geometry of physical movement as a common currency for supporting both sides of the speaker-listener dyads. Participants self-paced their listening to a narrative, after which they completed a test of memory querying their narrative comprehension and their ability to recognize words from the story. The multifractal evidence of nonlinear interactions across timescales predicted the fluency of speech perception. Self-pacing movements that enabled listeners to control the presentation of speech sounds constituted a rich exploratory process. The multifractal nonlinearity of this exploration supported several aspects of memory for the perceived spoken language. These findings extend the role of multifractal geometry in the speakers movements to the narrative case of speech perception. In addition to posing novel basic research questions, these findings make a compelling case for calibrating multifractal structure in text-to-speech synthesizers for better perception and memory of speech.


title: Perceiving and remembering speech depend on multifractal nonlinearity in movements producing and exploring speech


title: The Effect of Attention Load on Balance Control Performance

abstract: Posture balance control is an essential ability that is affected by the attention load. We investigated the effect of attention load on posture balance control experimentally and computationally. Fifteen young individuals participated in an experiment containing simultaneous performing of a balance control task and an auditory task. A previous computational model was extended by introducing the effect of attention load as a gain in a Proportional-Integral-Derivative (PID) controller. Results demonstrated that the sensitivity of the posture balance control to the attention load should be considered besides other influential factors in designing sport or physical rehabilitation exercises. Simulations suggested that the issues of joint impedance stiffness or viscosity might also be compensated by changing the attention load.


title: The strange role of brain lesion size in cognitive neuropsychology

abstract:
The size of brain lesions is a variable that is frequently considered in cognitive neuropsychology. In particular, lesion-deficit inference studies often control for lesion size, and the association of lesion size with post-stroke cognitive deficits and its predictive value are studied. In the present article, the role of lesion size in cognitive deficits and its computational or design-wise consideration is discussed and questioned. First, I argue that the commonly discussed role or effect of lesion size in cognitive deficits eludes us. A generally valid understanding of the causal relation of lesion size, lesion location, and cognitive deficits is unachievable. Second, founded on the theory of covariate control, I argue that lesion size control is no valid covariate control. Instead, it is identified as a procedure with only situational benefits, which is supported by empirical data. This theoretical background is used to suggest possible research practices in lesion-deficit inference, post-stroke outcome prediction, and behavioural studies. Last, control for lesion size is put into a bigger methodological and also historical context - it is identified to relate to a long-known association problem in neuropsychology, which was previously discussed from the perspectives of a mislocalisation in lesion-deficit mapping and the symptom complex approach.

O_LSTHighlightsC_LST- Lesion size is a factor that is often considered or controlled in neuropsychology
- No general causal relation between lesion size, lesion location and deficit exists
- Lesion size in brain mapping, outcome prediction and behavioural study is discussed
- Lesion size control is no valid covariate control
- Practical suggestions and guidelines how to consider lesion size are provided


title: The effects of emotional valence and intensity on cognitive and affective empathy after insula lesions

abstract: The insula plays a central role in empathy. However, the complex structure of empathic deficits following insular damage is not fully understood. While previous lesion research has shown variable deficits in patients with insular damage on basic discrimination tasks or self-report measures, it is unclear in how far patients with insular damage are impaired in cognitive (CE) and affective empathy (AE) functions depending on valence and arousal of stimuli using an ecologically valid paradigm. In the present study, patients with insular lesions (n = 20) and demographically-matched healthy controls (n = 24) viewed 16 videos (duration: 60 sec each) that varied in terms of valence and emotional intensity. The videos showed a person (target) reporting on a personal life event. In CE conditions, subjects continuously rated the affective state of the target, while in AE conditions they continuously rated their own affect. Mean Squared Error (MSE) assessed deviations between subject and target ratings (CE: deviation between targets and participants ratings of targets emotions; AE: deviation between targets and participants self-ratings of emotion). Patients differed from controls only in negative, low intensity AE, rating their own affective state less negative than the target rated his/her affect. This deficit was not related to trait empathy, neuropsychological or clinical parameters, or laterality of lesion. Our findings provide important insights into the profile of social cognition impairment after insular damage. Empathic functions may be widely spared after insular damage in a naturalistic, dynamic setting, potentially due to the intact interpretation of social context cues by residual networks outside the lesion. The particular role of the insula in AE for negative states may evolve specifically in situations that bear higher uncertainty, which points to a threshold role of the insula in online ratings of AE.


title: A fluorescent nanosensor paint reveals the heterogeneity of dopamine release from neurons at individual release sites

abstract: The neurotransmitter dopamine is released from discrete axonal structures called varicosities. Its release is essential in behaviour and is critically implicated in prevalent neuropsychiatric diseases. Existing dopamine detection methods are not able to detect and distinguish discrete dopamine release events from multiple varicosities. This prevents an understanding of how dopamine release is regulated across populations of discrete varicosities. Using a near infrared fluorescent (980 nm) dopamine nanosensor  paint (AndromeDA), we show that action potential-evoked dopamine release is highly heterogeneous across release sites and also requires molecular priming. Using AndromeDA, we visualize dopamine release at up to 100 dopaminergic varicosities simultaneously within a single imaging field with high temporal resolution (15 images/s). We find that  hotspots of dopamine release are highly heterogeneous and are detected at only ~17% of all varicosities. In neurons lacking Munc13 proteins, which prime synaptic vesicles, dopamine release is abolished during electrical stimulation, demonstrating that dopamine release requires vesicle priming. In summary, AndromeDA reveals the spatiotemporal organization of dopamine release.


title: Single-cell characterisation of mononuclear phagocytes in the human intestinal mucosa

abstract: Subsets of mononuclear phagocytes, including macrophages and classical dendritic cells (cDC), are highly heterogeneous in peripheral tissues such as the intestine, with each subset playing distinct roles in immune responses. Understanding this complexity at the cellular level has proven difficult due to the expression of overlapping phenotypic markers and the inability to isolate leukocytes of the mucosal lamina propria (LP) effector site, without contamination by the isolated lymphoid follicles (ILFs), which are embedded in the mucosa and which are responsible for the induction of immunity. Here we exploit our novel method for separating lamina propria from isolated lymphoid follicles to carry out single-cell RNA-seq, CITE-seq and flow cytometry analysis of MNPs in the human small intestinal and colonic LP, without contamination by lymphoid follicles. As well as classical monocytes, non-classical monocytes, mature macrophages, cDC1 and CD103+ cDC2, we find that a CD1c+ CD103- cDC subset, which shares features of both cDC2 and monocytes, is similar to the cDC3 that have recently been described in human peripheral blood. As well as differing between the steady-state small intestine and colon, the proportions of the different MNP subsets change during different stages of inflammatory bowel disease (IBD) inflammation. Putative cDC precursors (pre-cDC) were also present in the intestine, and trajectory analysis revealed clear developmental relationships between these and subsets of mature cDC, as well as between tissue monocytes and macrophages. By providing novel insights into the heterogeneity and development of intestinal MNP, our findings should help develop targeted approaches for modulating intestinal immune responses.


title: Epigenomic and transcriptomic differences between low-grade and acute inflammation in LPS-induced murine immune cells

abstract: Chronic, low-grade inflammation has a widespread and significant impact on health, especially in Western society. While inflammation is beneficial for the removal of microbes, low-grade inflammation never resolves and can cause or worsen other diseases. The process by which low-grade inflammation occurs remains poorly understood. Here we exposed murine bone-marrow derived monocytes to chronic lipopolysaccharide (LPS) stimulation at low dose or high dose, as well as a PBS control. The cells were profiled for genome-wide H3K27ac modification and gene expression. The gene expression of TRAM-deficient and IRAK-M-deficient monocytes with LPS exposure was also analyzed. We discover that low-grade inflammation preferentially utilizes the TRAM/TRIF-dependent pathway of TLR4 signaling, and induces the expression of interferon response genes. In contrast, acute inflammation uniquely upregulates metabolic and proliferative pathways that also appear to be TRAM-dependent. The extensive differences in the epigenomic landscape between low-dose and high-dose conditions suggest the importance of epigenetic regulations in driving differential responses. Our data provide potential targets for future mechanistic or therapeutic studies.


title: Large-scale phylogenomics of the genus Macrostomum (Platyhelminthes) reveals cryptic diversity and novel sexual traits

abstract: Free-living flatworms of the genus Macrostomum are small and transparent animals, representing attractive study organisms for a broad range of topics in evolutionary, developmental, and molecular biology. The genus includes the model organism M. lignano for which extensive molecular resources are available, and recently there is a growing interest in extending work to additional species in the genus. These endeavours are currently hindered because, even though >200 Macrostomum species have been taxonomically described, molecular phylogenetic information and geographic sampling remain limited. We report on a global sampling campaign aimed at increasing taxon sampling and geographic representation of the genus. Specifically, we use extensive transcriptome and single-locus data to generate phylogenomic hypotheses including 145 species. Across different phylogenetic methods and alignments used, we identify several consistent clades, while their exact grouping is less clear, possibly due to a radiation early in Macrostomum evolution. Moreover, we uncover a large undescribed diversity, with 94 of the studied species likely being new to science, and we identify multiple novel morphological traits. Furthermore, we identify cryptic speciation in a taxonomically challenging assemblage of species, suggesting that the use of molecular markers is a prerequisite for future work, and we describe the distribution of possible synapomorphies and suggest taxonomic revisions based on our finding. Our large-scale phylogenomic dataset now provides a robust foundation for comparative analyses of morphological, behavioural and molecular evolution in this genus.

category: evolutionary biology


title: Small RNA-sequencing for Analysis of Circulating miRNAs: Benchmark Study

abstract: Small RNA-sequencing (RNA-Seq) is being increasingly used for profiling of circulating microRNAs (miRNAs), a new group of promising biomarkers. Unfortunately, small RNA-Seq protocols are prone to biases limiting quantification accuracy, which motivated development of several novel methods. Here, we present comparison of all small RNA-Seq library preparation approaches that are commercially available for quantification of miRNAs in biofluids. Using synthetic and human plasma samples, we compared performance of traditional two-adaptor ligation protocols (Lexogen, Norgen) as well as methods using randomized adaptors (NEXTflex), polyadenylation (SMARTer), circularization (RealSeq), capture probes (EdgeSeq) or unique molecular identifiers, UMIs (QIAseq). Globally, there was no single protocol outperforming others across all metrics. We documented limited overlap of measured miRNA profiles between methods largely owing to protocol-specific biases. We found that methods designed to minimize bias largely differ in their performance and we identified contributing factors. We found that usage of UMIs has rather negligible effect and if designed incorrectly can even introduce spurious results. Together, these results identify strengths and weaknesses of current methods and provide guidelines for applications of small RNA-Seq in biomarker research.

category: genomics


title: GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning

abstract:
IntroductionMultidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mtb DNA sequences offers an alternative to laboratory-based drug-susceptibility testing. User-friendly and accurate resistance prediction tools are needed to enable public health and clinical practitioners to rapidly diagnose resistance and inform treatment regimens.

MethodsWe present Translational Genomics platform for Tuberculosis (GenTB), a web-based application to predict antibiotic resistance from next-generation sequence data. The user can choose between two potential predictors, a Random Forest (RF) classifier and a Wide and Deep Neural Network (WDNN) to predict phenotypic resistance to 13 and 10 anti-tuberculosis drugs, respectively. We benchmark GenTBs predictive performance along with leading TB resistance prediction tools (Mykrobe and TB-Profiler) using a ground truth dataset of 20,408 isolates with laboratory-based drug susceptibility data.

ResultsAll four tools reliably predicted resistance to first-line tuberculosis drugs but had varying performance for second-line drugs. The mean sensitivities for GenTB-RF and GenTB-WDNN across the nine shared drugs was 77.6% (95% CI 76.6 - 78.5%) and 75.4% (95% CI 74.5 - 76.4%) respectively, and marginally higher than the sensitivities of TB-Profiler at 74.4% (95% CI 73.4 - 75.3%) and Mykrobe at 71.9% (95% CI 70.9 - 72.9%). The higher sensitivities were at an expense of [≤]1.5% lower specificity: Mykrobe 97.6% (95% CI 97.5 - 97.7%), TB-Profiler 96.9% (95% CI 96.7 to 97.0%), GenTB-WDNN 96.2% (95% CI 96.0 to 96.4%), and GenTB-RF 96.1% (95% CI 96.0 to 96.3%). Genotypic resistance sensitivity was 11% and 9% lower for isoniazid and rifampicin respectively, on isolates sequenced at low depth (<10x across 95% of the genome) emphasizing the need to quality control input sequence data before prediction. We discuss differences between tools in reporting results to the user including variants underlying the resistance calls and any novel or indeterminate variants

ConclusionGenTB is an easy-to-use online tool to rapidly and accurately predict resistance to anti-tuberculosis drugs. GenTB can be accessed online at https://gentb.hms.harvard.edu, and the source code is available at https://github.com/farhat-lab/gentb-site.


title: MQuad enables clonal substructure discovery using single cell mitochondrial variants

abstract: Mitochondrial mutations are increasingly recognised as informative endogenous genetic markers that can be used to reconstruct cellular clonal structure using single-cell RNA or DNA sequencing data. However, there is a lack of effective computational methods to identify informative mtDNA variants in noisy and sparse single-cell sequencing data. Here we present an open source computational tool MQuad that accurately calls clonally informative mtDNA variants in a population of single cells, and an analysis suite for complete clonality inference, based on single cell RNA or DNA sequencing data. Through a variety of simulated and experimental single cell sequencing data, we showed that MQuad can identify mitochondrial variants with both high sensitivity and specificity, outperforming existing methods by a large extent. Furthermore, we demonstrated its wide applicability in different single cell sequencing protocols, particularly in complementing single-nucleotide and copy-number variations to extract finer clonal resolution. MQuad is a Python package available via https://github.com/single-cell-genetics/MQuad.


title: Exploring the structure and mechanics of thin supported inverse bicontinuous cubic phase lipid films

abstract: Inverse bicontinuous cubic phase membranes are ubiquitous in nature but their properties and functions are still not fully understood. To shed light on this topic, we herein realize thin supported cubic phase lipid films, characterize their structure and provide the first study of the mechanical properties of these non-lamellar architectures.


title: Extended-Ensemble Docking to Probe Evolution of Ligand Binding Sites in Proteins Undergoing Large-Scale Structural Changes for Their Function

abstract: Proteins can sample a broad landscape as they undergo conformational transition between different functional states. As key players in almost all cellular processes, proteins are important drug targets. Considering the different conformational states of a protein is therefore central for a successful drug-design strategy. Here we introduce a novel docking protocol, termed as extended-ensemble docking, pertaining to proteins that undergo large-scale (global) conformational changes during their function. In its application to multidrug ABC-transporter P-glycoprotein (Pgp), extensive non-equilibrium molecular dynamics simulations employing system-specific collective variables capturing the alternate access mechanism of Pgp, are first used to construct the transition cycle of the transporter. An extended set of conformational states representing the full transition between the inward- and the outward-facing states of Pgp, is then used to seed high-throughput docking calculations of a set of known substrates, non-substrates, and modulators of the transporter. Large differences are observed in the predicted binding affinities to the conformational ensemble, with compounds showing stronger binding affinities to intermediate conformations compared to the starting crystal structure. Hierarchical clustering of the individual binding modes of the different compounds shows all ligands preferably bind to the large central cavity of the protein, formed at the apex of the transmembrane domain (TMD), whereas only small binding populations are observed in the previously described R and H sites present within the individual TMD leaflets. Based on the results, the central cavity is further divided into two major subsites: first subsite preferably binds smaller substrates and high-affinity inhibitors, whereas the second one shows preference for larger substrates and low-affinity modulators. These central sites along with the low-affinity interaction sites present within the individual TMD leaflets may respectively correspond to the proposed high- and low-affinity binding sites in Pgp. We propose further optimization strategy for developing more potent inhibitor of Pgp, based on increasing its specificity to the extended ensemble of the protein instead of using a single protein structure, as well as its selectivity for the high-affinity binding site. In contrast to earlier in-silico studies using single static structures of Pgp, our results show better agreement with experimental studies, pointing to the importance of incorporating the global conformational flexibility of proteins in future drug-discovery endeavors.


title: TOR represses stress responses through global regulation of H3K27 trimethylation in plants

abstract: Target of Rapamycin (TOR) functions as a central sensory hub to link a wide range of external stimuli to gene expression. However, the mechanisms underlying stimulus-specific transcriptional reprogramming by TOR remains elusive. Our in silico analysis in Arabidopsis demonstrates that TOR-repressed genes are associated with either bistable or silent chromatin states. Both states regulated by TOR signaling pathway are associated with high level of H3K27me3 deposited by CURLY LEAF (CLF) in specific context with LIKE HETEROCHROMATIN PROTEIN1 (LHP1). Combinations of epigenetic modifications H3K4me3 and H3K27me3 implicate bistable feature which alternates between on and off state allowing rapid transcriptional changes upon external stimuli. Chromatin remodeler SWI2/SNF2 ATPase BRAHMA (BRM) activates TOR-repressed genes only at bistable chromatin domains to rapidly induce biotic stress responses. Here we demonstrated both in silico and in vivo that TOR represses transcriptional stress responses through global maintenance of H3K27me3.


title: Combining evolutionary and assay-labelled data for protein fitness prediction

abstract: Predictive modelling of protein properties has become increasingly important to the field of machine-learning guided protein engineering. In one of the two existing approaches, evolutionarily-related sequences to a query protein drive the modelling process, without any property measurements from the laboratory. In the other, a set of protein variants of interest are assayed, and then a supervised regression model is estimated with the assay-labelled data. Although a handful of recent methods have shown promise in combining the evolutionary and supervised approaches, this hybrid problem has not been examined in depth, leaving it unclear how practitioners should proceed, and how method developers should build on existing work. Herein, we present a systematic assessment of methods for protein fitness prediction when evolutionary and assay-labelled data are available. We find that a simple baseline approach we introduce is competitive with and often outperforms more sophisticated methods. Moreover, our simple baseline is plug-and-play with a wide variety of established methods, and does not add any substantial computational burden. Our analysis highlights the importance of systematic evaluations and sufficient baselines.

category: synthetic biology


title: Unravelling the shared genetic mechanisms underlying 18 autoimmune diseases using a systems approach

abstract: Autoimmune diseases (AiDs) are complex heterogeneous diseases characterized by hyperactive immune responses against self. Genome-wide association studies have identified thousands of single nucleotide polymorphisms (SNPs) associated with several AiDs. While these studies have identified a handful of pleiotropic loci that confer risk to multiple AiDs, they lack the power to detect shared genetic factors residing outside of these loci. Here, we integrated chromatin contact, expression quantitative trait loci and protein-protein interaction (PPI) data to identify genes that are regulated by both pleiotropic and non-pleiotropic SNPs. The PPI analysis revealed complex interactions between the shared and disease-specific genes. Furthermore, pathway enrichment analysis demonstrated that the shared genes co-occur with disease-specific genes within the same biological pathways. In conclusion, our results are consistent with the hypothesis that genetic risk loci associated with multiple AiDs converge on a core set of biological processes that potentially contribute to the emergence of polyautoimmunity.


title: Imipramine and olanzapine block apoE4-catalyzed polymerization of Aβ and show evidence of improving Alzheimer's disease cognition

abstract:
The apolipoprotein E (APOE) {varepsilon}4 allele confers the strongest risk for late-onset Alzheimers disease (AD) besides age itself, but the mechanism(s) underlying this risk are debated. The critical test of any proposed AD mechanism is whether it leads to effective treatments. We developed a high-throughput assay to identify inhibitors of apoE4-catalyzed polymerization of the amyloid {beta} (A{beta}) peptide into neurotoxic fibrils. Screening a human drug library, we identified five non-toxic, blood-brain-barrier-permeable hit compounds that reduced apoE4-promoted A{beta} and tau neuropathology in cultured neurons. Two hit compounds, imipramine and olanzapine, but not other (non-hit) antipsychotics or antidepressants, when prescribed to AD patients for their normal clinical indications, led to improvements in cognition and clinical diagnosis. Imipramine and olanzapine have no structural, functional, or clinical similarities other than their ability to inhibit apoE4-catalyzed A{beta} polymerization, thus identifying this mechanism as an essential contribution of apoE4 to AD.

One Sentence SummaryHigh-throughput drug screens, studies in Alzheimers disease cell culture models, and analyses of human clinical data identified inhibitors of the apoE4-A{beta} interaction as a novel class of Alzheimers disease therapeutics.


title: Delayed dosing of minocycline plus N-acetylcysteine reduces neurodegeneration in distal brain regions and restores spatial memory after experimental traumatic brain injury

abstract: Multiple drugs to treat traumatic brain injury (TBI) have failed clinical trials. Most drugs lose efficacy as the time interval increases between injury and treatment onset. Insufficient therapeutic time window is a major reason underlying failure in clinical trials. Few drugs have been developed with therapeutic time windows sufficiently long enough to treat TBI because little is known about which brain functions can be targeted if therapy is delayed hours to days after injury. We identified multiple injury parameters that are improved by first initiating treatment with the drug combination minocycline (MINO) plus N-acetylcysteine (NAC) at 72 hours after injury (MN72) in a mouse closed head injury (CHI) experimental TBI model. CHI produces spatial memory deficits resulting in impaired performance on Barnes maze, hippocampal neuronal loss, and bilateral damage to hippocampal neurons, dendrites, spines and synapses. MN72 treatment restores Barnes maze acquisition and retention, protects against hippocampal neuronal loss, limits damage to dendrites, spines and synapses, and accelerates recovery of microtubule associated protein 2 (MAP2) expression, a key protein in maintaining proper dendritic architecture and synapse density. These data show that in addition to the structural integrity of the dendritic arbor, spine and synapse density can be successfully targeted with drugs first dosed days after injury. Retention of substantial drug efficacy even when first dosed 72 hours after injury makes MINO plus NAC a promising candidate to treat clinical TBI.


title: The opportunistic intracellular bacterial pathogen Rhodococcus equi elicits type I interferons by engaging cytosolic DNA sensing in macrophages

abstract:
Rhodococcus equi is a major cause of foal pneumonia and an opportunistic pathogen in immunocompromised humans. While alveolar macrophages constitute the primary replicative niche for R. equi, little is known about how intracellular R. equi is sensed by macrophages. Here, we discovered that that in addition to previously characterized pro-inflammatory cytokines (e.g., Tnfa, Il6, Il1b), macrophages infected with R. equi induce a robust type I IFN response, including Ifnb and interferon-stimulated genes (ISGs), similar to the evolutionarily related pathogen, Mycobacterium tuberculosis. Follow up studies using a combination of mammalian and bacterial genetics, demonstrated that induction of this type I IFN expression program is largely dependent on the cGAS/STING/TBK1 axis of the cytosolic DNA surveillance pathway, suggesting that R. equi perturbs the phagosomal membrane and causes DNA release into the cytosol following phagocytosis. Consistent with this we found that a population of ~12% of R. equi phagosomes recruited the galectin-3, -8 and -9 danger receptors. Interesting, neither phagosomal damage nor induction of type I IFN required the R. equis virulence-associated plasmid. Importantly, R. equi infection of both mice and foals stimulated ISG expression, in organs (mice) and circulating monocytes (foals). By demonstrating that R. equi activates cytosolic DNA sensing in macrophages and elicits type I IFN responses in animal models, our work provides novel insights into how R. equi engages the innate immune system and furthers our understanding how this zoonotic pathogen causes inflammation and disease.

IMPORTANCERhodococcus equi is a facultative intracellular bacterial pathogen of horses and other domestic animals, as well as an opportunistic pathogen of immunocompromised and rarely immunocompetent humans. In human patients, Rhodococcus pneumonia bears some pathological similarities to pulmonary tuberculosis, and poses a risk for misdiagnosis. In horses, R. equi infection has a major detrimental impact on the equine breeding industry due to a lack of an efficacious vaccine and its ubiquitous distribution in soil. Given the prevalence of subclinical infection and high false positive rate in current screening methods, there exists a critical need to identify factors contributing to positive patient outcomes. Our research identifies innate immune sensing events and immune transcriptional signatures that may lead to biomarkers for clinical disease, more accurate screening methods, and insight into susceptibility to infection.


title: Endocervical regulatory T cells are associated with decreased genital inflammation and lower HIV target cell abundance

abstract: Regulatory T cells (Tregs) play important roles in tissue homeostasis, but few studies have investigated tissue Tregs in the context of genital inflammation, HIV target cell density, and vaginal microbiota in humans. In women from Nairobi (n=64), the proportion of CD4+ CD25+ CD127low Tregs in the endocervix correlated with those in blood (r=0.31, p=0.01), with a higher Treg frequency observed in the endocervix (median 3.8 vs 2.0%, p<0.0001). Most Tregs expressed FoxP3 in both compartments, and CTLA-4 expression was higher on endocervical Tregs compared to blood (median 50.8 vs 6.0%, p<0.0001). More than half (34/62, 55%) of participants displayed a non-Lactobacillus dominant vaginal microbiota, which was not associated with endocervical Tregs or CD4+ T cell abundance. In a multivariable linear regression, endocervical Treg proportions were inversely associated with the number of elevated pro-inflammatory cytokines (p=0.03). Inverse Treg associations were also observed for specific cytokines including IL-1{beta}, G-CSF, Eotaxin, IL-1RA, IL-8, and MIP-1 {beta}. Higher endocervical Treg proportions were associated with lower abundance of endocervical CD4+ T cells (0.30 log10 CD4+ T cells per log10 Treg, p=0.00028), with a similar trend for Th17 cells (p=0.09). Selectively increasing endocervical Tregs may represent a pathway to reduce genital tract inflammation in women.


title: Laboratory mice with a wild microbiota generate strong allergic immune responses

abstract:
Allergic disorders are caused by a combination of hereditary and environmental factors. The hygiene hypothesis postulates that early life microbial exposures impede the development of subsequent allergic disease. However, unambiguous evidence that microbes reduce the development of allergic disorders is still lacking. Recently developed  wildling mice contain a rich and diverse commensal and encounter a repertoire of microbes typical of the wild, with pathogenic potential. Here, we probed the hygiene hypothesis by comparing the development of allergic inflammation in wildlings to that of genetically identical mice lacking diverse microbial exposure. We find that wildlings develop stronger allergic inflammation in response to house dust mites with allergic T cell responses driven not only by cognate peptide antigens, but also by innate cytokines. In all, the results suggest that high microbial content and diversity potentiates, rather than restricts, allergic immune responses.

One sentence summaryStrong allergic inflammation in the face of rich and diverse microbial exposures


title: Strain diversity of plant-associated Lactiplantibacillus plantarum

abstract: The intraspecific phenotypic and genetic diversity of Lactiplantibacillus plantarum (formerly Lactobacillus plantarum) was examined for five strains isolated from fermented olives and eight strains from cactus fruit, fermented tomatoes, teff injera, wheat boza, and wheat sourdough starter sources. Carbohydrate utilization and stress tolerance characteristics showed that the olive isolates grew more robustly in galactose and raffinose, showed higher tolerance to 12% v/v EtOH, and exhibited a greater capacity to inhibit an olive spoilage strain of Saccharomyces cerevisiae than L. plantarum from the other plant sources. Certain traits were variable between fermented olive isolates such as the capacity for biofilm formation and survival at pH 2 or 50 {degrees}C. By comparison, all L. plantarum from fruit sources grew better at a pH of 3.5 than the strains from fermented grains. Multi-locus sequence typing and genome sequencing indicated that strains from the same source type tended to be genetically related. Comparative genomics was unable to resolve strain differences, with the exception of the most phenotypically impaired and robust isolates. The findings show that L. plantarum is adapted for growth on specific plants or plant food types, but that intraspecific variation may be important for ecological fitness of L. plantarum within individual habitats.

category: microbiology


title: Pulse labeling reveals the tail end of protein folding by proteome profiling

abstract: Accurate and efficient folding of nascent protein sequences into their native state requires support from the protein homeostasis network. Herein we probed which newly translated proteins are less thermostable to infer which polypeptides require more time to fold within the proteome. Specifically, we determined which of these proteins were more susceptible to misfolding and aggregation under heat stress using pulse SILAC coupled mass spectrometry. These proteins are abundant, short, and highly structured. Notably these proteins display a tendency to form {beta}-sheet structures, a configuration which typically requires more time for folding, and were enriched for Hsp70/Ssb and TRiC/CCT binding motifs, suggesting a higher demand for chaperone-assisted folding. These polypeptides were also more often components of stable protein complexes in comparison to other proteins. All evidence combined suggests that a specific subset of newly translated proteins requires more time following synthesis to reach a thermostable native state in the cell.

category: cell biology


title: H2S Prodrug, SG-1002, Protects Against Myocardial Oxidative Damage and Hypertrophy via Induction of Cystathionine beta-Synthase and Antioxidant Proteins

abstract: Endogenously produced hydrogen sulfide (H2S) is critical for cardiovascular homeostasis. Therapeutic strategies aimed at increasing H2S levels have proven cardioprotective in models of acute myocardial infarction (MI) and heart failure (HF). The present study was undertaken to investigate the effects of a novel H2S prodrug, SG-1002, on stress induced hypertrophic signaling in murine HL-1 cardiac muscle cells. Treatment of HL-1 cells with SG-1002 under serum starvation without or with H2O2 increased the levels of H2S, H2S producing enzyme, cystathionine {beta}-synthase (CBS) as well as antioxidant protein levels, such as super oxide dismutase1 (SOD1) and catalase and decreased oxidative stress. SG-1002 also decreased the expression of hypertrophic/HF protein markers such as atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) in stressed HL-1 cells. Treatment with SG-1002 caused a significant induction of cell viability and a marked reduction of cellular cytotoxicity in HL-1 cells under serum starvation incubated or with H2O2. Experimental results of this study suggest that SG-1002 attenuates myocardial cellular oxidative damage and/or hypertrophic signaling via increasing H2S levels or H2S producing enzyme, CBS and antioxidant proteins.


title: Mismatch between bird species sensitivity and the protection of intact habitats across the Americas

abstract: Protected areas, the most prevalent international policy mechanism for biodiversity conservation, are highly heterogeneous in their effectiveness at buffering ecosystems and species habitats from human pressure. Protected areas with intense human pressure cannot protect species that are highly sensitive to human activities. Here, we use 60 million bird observations from the eBird citizen science platform to estimate the sensitivity to human pressure of each bird species breeding in the Americas (Nearctic and Neotropical regions). We find that high-sensitivity species, while found in all ecoregions, are concentrated in the tropical biomes. Ecoregions with large proportions of high-sensitivity species do not have more intact protected habitat, resulting in a low coverage of intact protected habitat for many high-sensitivity species. What is more, 139 high-sensitivity species have little or no intact protected habitat within their distributions while being threatened with extinction. Finally, we show that protected area intactness is decreasing faster in ecoregions with many high-sensitivity species. Our results highlight a major mismatch between species conservation needs and the coverage of intact protected habitats, and will likely hamper the long-term effectiveness of protected areas at retaining species. We highlight ecoregions where the protection and management of intact habitats, complemented by the restoration of degraded ones, is urgently needed to avoid extinctions.


title: Deep learning for early warning signals of regime shifts

abstract: Many natural systems exhibit regime shifts where slowly changing environmental conditions suddenly shift the system to a new and sometimes very different state. As the tipping point is approached, the dynamics of complex and varied systems all simplify down to a small number of possible  normal forms that determine how the new regime will look. Indicators such as increasing lag-1 autocorrelation and variance provide generic early warning signals (EWS) by detecting how dynamics slow down near the tipping point. But they do not indicate what type of new regime will emerge. Here we develop a deep learning algorithm that can detect EWS in systems it was not explicitly trained on, by exploiting information about normal forms and scaling behaviour of dynamics near tipping points that are common to many dynamical systems. The algorithm detects EWS in 268 empirical and model time series from ecology, thermoacoustics, climatology, and epidemiology with much greater sensitivity and specificity than generic EWS. It can also predict the normal form that will characterize the oncoming regime shift. Such approaches can help humans better manage regime shifts. The algorithm also illustrates how a universe of possible models can be mined to recognize naturally-occurring tipping points.


title: Whole genome duplications and the diversification of the Globin-X genes of vertebrates

abstract: The globin superfamily of vertebrate genes is a textbook example of how the interplay between local gene duplications, whole-genome duplications, and regulatory changes can facilitate the evolution of novel protein functions. Almost every vertebrate examined possesses copies of hemoglobin and myoglobin in their genomes, and both cytoglobin and neuroglobin are present in the vast majority of vertebrate genomes surveyed as well. The phylogenetic distribution of globin-E, globin-Y and globin-X (GbX), however, is more spotty, suggesting multiple independent gene losses. Globin-X is an enigmatic globin with a wide phyletic distribution that spans protostomes and deuterostomes. Unlike canonical globins such as hemoglobins and myoglobins, functional data suggest that GbX does not have a primary respiratory function. Instead, available evidence suggests that GbX may play a role in protecting cells from oxidative damage and in reducing nitrite and it is predicted to be bound to the cell membrane. Recently released genomes from key vertebrate taxa provide an excellent opportunity to address questions about the early stages of evolution of these genes in vertebrates. In the current study, we integrate bioinformatic, synteny and phylogenetic analyses to characterize the diversity of GbX genes in non-teleost ray-finned fishes, resolve relationships between the GbX genes of cartilaginous fish and the GbX genes of bony vertebrates, and demonstrate that the GbX genes of cyclostomes and gnathostomes have independent duplicative histories. Our study highlights the role that whole genome duplications (WGDs) have played in expanding the repertoire of genes in vertebrate genomes. Our results indicate that GbX paralogs have a remarkably high rate of retention following WGDs in comparison to other globin genes, and also provide an evolutionary framework for interpreting results of experiments that examine functional properties of GbX and patterns of tissue-specific expression. By identifying GbX genes products of different WGDs in the vertebrate tree of life, our results can guide the design of experimental work to explore whether gene duplicates that originate via WGDs have evolved novel functional properties or expression profiles relative to singleton or tandemly duplicated copies of GbX.


title: Human -Synuclein Inhibits Platelets Aggregation in vitro by Interfering with the -Thrombin/Protease-Activated Receptor 1 Functional Axis

abstract: -Synuclein (Syn) is a small (140 amino acids) disordered, acidic (pI: 4.7) protein, highly conserved in vertebrates and implicated in the pathogenesis of Parkinsons disease (PD), a neurodegenerative disease characterized by the deposition of Syn amyloid fibrils in dopaminergic neurons. Beyond the central nervous system, significant expression of Syn has also been measured in the blood (~1 M), where platelets are the main cellular hosts of Syn. Although the pathological implication of Syn in PD is widely accepted, the physiological role of blood Syn is still elusive. Starting from the notion that platelets are either the major cellular reservoir of Syn in the blood and, concomitantly, act as key players in hemostasis, being activated also by -thrombin (T) via cleavage of protease-activated receptors (PARs), we decided to investigate the possibility that Syn could modulate platelet activation by interfering with the T-PAR functional axis. Using multiple electrode aggregometry, i.e. a fast and specific platelet-function-testing method, as well as steady-state fluorescence spectroscopy, surface plasmon resonance, and fluorescence microscopy, we show here that monomeric Syn functions as a negative regulator of T-mediated platelets activation. Syn acts either directly, via competitive inhibition of PAR1 activation by T and TRAP6 agonist, and indirectly, by scavenging T on the platelet plasma membrane. A simple electrostatic model of Syn platelet antiaggregating effect is proposed and the possible role of the protein at the interplay of amyloidosis and thrombosis is discussed.


title: Differential expression of single-cell RNA-seq data using Tweedie models

abstract: SO_SCPLOWUMMARYC_SCPLOWThe performance of computational methods and software to identify differentially expressed genes in single-cell RNA-sequencing (scRNA-seq) has been shown to be influenced by several factors, including the choice of the normalization method used and the choice of the experimental platform (or library preparation protocol) to profile gene expression in individual cells. Currently, it is up to the practitioner to choose the most appropriate differential expression (DE) method out of over 100 DE tools available to date, each relying on their own assumptions to model scRNA-seq data. Here, we propose to use generalized linear models with the Tweedie distribution that can flexibly capture a large dynamic range of observed scRNA-seq data across experimental platforms induced by heavy tails, sparsity, or different count distributions to model the technological variability in scRNA-seq expression profiles. We also propose a zero-inflated Tweedie model that allows zero probability mass to exceed a traditional Tweedie distribution to model zero-inflated scRNA-seq data with excessive zero counts. Using both synthetic and published plate- and droplet-based scRNA-seq datasets, we performed a systematic benchmark evaluation of more than 10 representative DE methods and demonstrate that our method (Tweedieverse) outperforms the state-of-the-art DE approaches across experimental platforms in terms of statistical power and false discovery rate control. Our open-source software (R package) is available at https://github.com/himelmallick/Tweedieverse.