title: How to characterise shared space use networks

abstract: Studying the social behaviour of small or cryptic species often relies on constructing shared space use networks from sparse point-based observations of individuals (e.g. live trapping data). Such an approach assumes that individuals that have more observed space sharing events (e.g. detections in the same trapping location) will also have interacted more. However, there is very little guidance on how to construct shared space use networks, how much data are required for making such networks, or how to interpret the relationships they generate. In this study, we quantify the robustness of shared space use networks to different sampling regimes and network-generation algorithms. We first use empirical data to highlight that characteristics of how animals use space can help us to establish new ways to model the potential for individuals to co-occur. We then show that a method that explicitly models individuals home range and subsequent overlap in space among individuals (spatial overlap networks) requires fewer data for inferring observed networks that are correlated with the true shared space use network (relative to networks constructed from space sharing events). As a result, we show that shared space use networks based on estimating spatial overlap are also more powerful for detecting biological effects present in the true shared space use network. Finally, we discuss when it is appropriate to make inferences from shared space use about social interactions. Our study confirms the potential for using sparse trapping data from cryptic species to address a range of important questions in ecology and evolution.


title: The minimum land area requiring conservation attention to safeguard biodiversity

abstract: More ambitious conservation efforts are needed to stop the global biodiversity crisis. Here, we estimate the minimum land area to secure important sites for terrestrial fauna, ecologically intact areas, and the optimal locations for representation of species ranges and ecoregions. We discover that at least 64 million km2 (44% of terrestrial area) requires conservation attention. Over 1.8 billion people live on these lands so responses that promote agency, self-determination, equity, and sustainable management for safeguarding biodiversity are essential. Spatially explicit land-use scenarios suggest that 1.3 million km2 of land requiring conservation could be lost to intensive human land-uses by 2030, which requires immediate attention. However, there is a seven-fold difference between the amount of habitat converted under optimistic and pessimistic scenarios, highlighting an opportunity to avert this crisis. Appropriate targets in the post-2020 Global Biodiversity Framework to ensure conservation of the identified land would contribute substantially to safeguarding biodiversity.

category: ecology


title: Astrocyte-like glia-specific gene deathstar is crucial for normal development, adult locomotion and lifespan of male Drosophila

abstract:
Drosophila melanogaster is a proper model organism for studying the development and function of the nervous system. The Drosophila nervous system consists of distinct cell types with significant homologies to various cell types of more advanced organisms, including human. Among all cell types of the nervous system, astrocyte-like glia (ALG) have conserved functions to mammals and are essential for normal physiology and behaviours of the fly.

In this study, we exploited the gene expression profile of single cells in Drosophila optic lobe to identify the genes with specific expression pattern in each cell type. Through a bioinformatical analysis of the data, a novel ALG-specific gene (here assigned as deathstar, dea) was identified. Immunostaining of deathstar in the central nervous system (CNS) showed its presence in specific regions of Drosophila ventral nerve cord, which previously has been characterized as ALG cells. Consistent with the bioinformatical analysis, deathstar-related signals were overlapped with the signals of the previously reported ALG marker, Eaat1, supporting its specific expression in ALG cells.

At the physiological level, RNAi-mediated suppression of deathstar gene impeded the normal development of male flies without any effects on females. Cell type-specific expression of deathstar RNAi showed that deathstar gene affects locomotion behaviour and lifespan of D. melanogaster, in an ALG-specific manner.

Taken together, we showed that bioinformatical analysis of a previously reported expression data of Drosophila optic lobe successfully predicted the ALG-specific expression pattern of deathstar gene. Moreover, it was consistent with the ALG-specific effects of this gene on locomotion and lifespan of D. melanogaster, in vivo.

category: genetics


title: Mesmerize: a dynamically adaptable user-friendly analysis platform for 2D & 3D calcium imaging data.

abstract: Calcium imaging is an increasingly valuable technique for understanding neural circuits, neuroethology, and cellular mechanisms. The analysis of calcium imaging data presents challenges in image processing, data organization, analysis, and accessibility. Tools have been created to address these problems independently, however a comprehensive user-friendly package does not exist. Here we present "Mesmerize", an efficient, expandable and user-friendly analysis platform, which uses a Findable, Accessible, Interoperable and Reproducible (FAIR) system to encapsulate the entire analysis process, from raw data to interactive visualizations for publication. Mesmerize provides a user-friendly graphical interface to state-of-the-art analysis methods for signal extraction & downstream analysis. We demonstrate the broad scientific scope of Mesmerizes applications by analyzing neuronal datasets from mouse and a volumetric zebrafish dataset. We also applied contemporary time-series analysis techniques to analyze a novel dataset comprising neuronal, epidermal, and migratory mesenchymal cells of the protochordate Ciona intestinalis.

category: neuroscience


title: Targeting cellular DNA damage responses in cancer: An in vitro-calibrated agent-based model simulating monolayer and spheroid treatment responses to ATR-inhibiting drugs

abstract:
We combine a systems pharmacology approach with an agent-based modelling approach to simulate LoVo cells subjected to AZD6738, an ATR (ataxia telangiectasia mutated and rad3-related kinase) inhibiting anti-cancer drug that can hinder tumour proliferation by targeting cellular DNA damage responses. The agent-based model used in this study is governed by a set of empirically observable rules. By adjusting only the rules when moving between monolayer and multi-cellular tumour spheroid simulations, whilst keeping the fundamental mathematical model and parameters intact, the agent-based model is first parameterised by monolayer in vitro data and is thereafter used to simulate treatment responses in in vitro tumour spheroids subjected to dynamic drug delivery. Spheroid simulations are subsequently compared to in vivo data from xenografts in mice. The spheroid simulations are able to capture the dynamics of in vivo tumour growth and regression for approximately eight days post tumour injection.

Translating quantitative information between in vitro and in vivo research remains a scientifically and financially challenging step in preclinical drug development processes. However, well-developed in silico tools can be used to facilitate this in vitro to in vivo translation, and in this article we exemplify how data-driven, agent-based models can be used to bridge the gap between in vitro and in vivo research. We further highlight how agent-based models, that are currently underutilised in pharmaceutical contexts, can be used in preclinical drug development.

category: cancer biology


title: Characterising sensorimotor adaptation in Complex Regional Pain Syndrome

abstract: It has been suggested that sensorimotor conflict contributes to the maintenance of some pathological pain conditions, implying that there are problems with the adaptation processes that normally resolve such conflict. We tested whether sensorimotor adaptation is impaired in people with Complex Regional Pain Syndrome (CRPS) by characterising their adaption to lateral prismatic shifts in vision. People with unilateral upper-limb CRPS Type I (n = 17), and pain-free individuals (n = 18; matched for age, sex, and handedness) completed prism adaptation with their affected/non-dominant and non-affected/dominant arms. We examined 1) the rate at which participants compensated for the optical shift during prism exposure (i.e. strategic recalibration), 2) endpoint errors made directly after prism adaptation (sensorimotor realignment) and the retention of these errors, and 3) kinematic markers associated with strategic control. Direct comparisons between people with CRPS and controls revealed no evidence of any differences in strategic recalibration, including no evidence for differences in a kinematic marker associated with trial-by-trial changes in movement plans during prism exposure. All participants made significant endpoint errors after prism adaptation exposure, indicative of sensorimotor realignment. Overall, the magnitude of this realignment did not differ between people with CRPS and pain-free controls. However, when endpoint errors were considered separately for each hand, people with CRPS made greater errors (indicating more rather than less realignment) when using their affected hand than their non-affected hand. No such difference was seen in controls. Taken together, these findings provide no evidence of impaired strategic control or sensorimotor realignment in people with CRPS. In contrast, they provide some indication that there could be a greater propensity for sensorimotor realignment in the CRPS-affected arm, consistent with more flexible representations of the body and peripersonal space. Our study challenges an implicit assumption of the theory that sensorimotor conflict might underlie some pathological pain conditions.


title: The genome of the zoonotic malaria parasite Plasmodium simium reveals adaptations to host-switching

abstract:
BackgroundPlasmodium simium, a malaria parasite of non-human primates (NHP) was recently shown to cause zoonotic infections in humans in Brazil. We sequenced the P. simium genome to investigate its evolutionary history and to identify any genetic adaptions that may underlie the ability of this parasite to switch between host species.

ResultsPhylogenetic analyses based on whole genome sequences of P. simium from humans and NHPs reveals that P. simium is monophyletic within the broader diversity of South American Plasmodium vivax, suggesting P. simium first infected NHPs as a result of a host-switch of P. vivax from humans. The P. simium isolates show the closest relationship to Mexican P. vivax isolates. Analysis of erythrocyte invasion genes reveals differences between P. vivax and P. simium, including large deletions in the Duffy Binding Protein 1 (DBP1) and Reticulocyte Binding Protein 2a genes of P. simium. Analysis of P. simium isolated from NHPs and humans revealed a deletion of 38 amino acids in DBP1 present in all human-derived isolates, whereas NHP isolates were multi-allelic.

ConclusionsAnalysis of the P. simium genome confirmed a close phylogenetic relationship between P. simium and P. vivax, and suggests a very recent American origin for P. simium. The presence of the DBP1 deletion in all human-derived isolates tested suggests that this deletion, in combination with other genetic changes in P. simium, may facilitate the invasion of human red blood cells and may explain, at least in part, the basis of the recent zoonotic infections.

category: genomics


title: Circulating miR-181 is a prognostic biomarker for amyotrophic lateral sclerosis

abstract:
Amyotrophic lateral sclerosis (ALS) is a relentless neurodegenerative syndrome of the human motor neuron system, for which no effective treatment exists. Variability in the rate of disease progression limits the efficacy of ALS clinical trials, suggesting that developing of better biomarkers for prognosis will facilitate therapeutic progress. Here, we applied unbiased next-generation sequencing to investigate the potential of plasma cell-free microRNAs as biomarkers of ALS prognosis, in 252 patients with detailed clinical-phenotyping. First, we identified miRNAs, whose plasma levels remain stable over the course of disease in a longitudinal cohort of 22 patients. Next, we demonstrated that high levels of miR-181, a miRNA enriched in neurons of the brain and spinal cord, predicts a >2 fold risk of death in discovery cohort (126 patients) and an independent replication cohort (additional 122 patients). miR-181 performance is comparable with the established neurofilament light chain (NfL) biomarker and when combined together, miR-181+NfL establish a novel RNA-protein biomarker pair with superior prediction capacity of ALS prognosis. Therefore, plasma miR-181 predicts ALS disease course, and a novel miRNA-protein biomarker approach, based on miR-181+NfL, boosts precision of patient stratification and may greatly enhance the power of clinical trials.

One Sentence Summaryplasma miR-181 levels indicate high mortality risk in ALS patients.


title: Divergent sex-specific effects of an IgE receptor polymorphism: from immunity to health, and ultimately, fitness

abstract: The genotype of an individual is an important predictor of their immune function, and subsequently, their ability to control or avoid infection and ultimately contribute offspring to the next generation. However, the same genotype, subjected to different environments, can also result in different outcomes. The sexes represent two such different environments. Sexual dimorphism is widespread across the animal kingdom. Despite this, very little is known about the importance of sex for the expression of genotype in the context of health and disease, particularly in natural populations. We identified a synonymous polymorphism in the high-affinity Immunoglobulin E (IgE) receptor (GC and non-GC haplotypes) that has sex-specific effects on immune gene expression, susceptibility to infection and reproductive success of individuals in a natural population of field voles (Microtus agrestis). We found that the effect of the GC haplotype on the expression of genes affecting inflammation displayed a significant interaction with sex. While males with the GC haplotype had upregulated pro-inflammatory genes, in particular the pro-inflammatory cytokine Il33, females had upregulated anti-inflammatory genes, in particular the anti-inflammatory cytokine inhibitor Socs3. Furthermore we found that the effect of the GC haplotype on the probability of infection with a common microparasite, Babesia microti, displayed a significant interaction with sex. While males with the GC haplotype did not differ significantly in their susceptibility to infection, females with the GC haplotype were more likely to be infected. Finally, we found that the effect of the GC haplotype on reproductive success also displayed a significant interaction with sex. While males with the GC haplotype had a lower reproductive success, females with the GC haplotype did not differ in the number of offspring they produced. To our knowledge, this is the first time that a polymorphism with sex-specific effects across all three levels (immune gene expression, susceptibility to infection and reproductive success) has been documented in a natural population.


title: Sex-specific effects of an IgE polymorphism on immunity, susceptibility to infection and reproduction in a wild rodent


title: Cellular Fitness Phenotypes of Cancer Target Genes from On-cobiology to Cancer Therapeutics

abstract: To define the growing significance of cellular targets of cancer drugs, we examined the fitness dependency of cellular targets or effectors of cancer drug targets across human cancer cells from 19 cancer types. We observed that the deletion of 35 out of 47 cellular mediators or targets of oncology drugs did not result in the expected loss of cell fitness in appropriate cancer types for which drugs targeting or utilizing these molecules were approved. Additionally, our analysis recognized 43 cellular targets as fitness genes in several cancer types in which these drugs were not approved, and thus, providing clues repurposing approved oncology drugs in cancer types. For example, we found the widespread upregulation and fitness dependency of the components of the mevalonate and purine biosynthesis pathways (currently targeted by bisphosphonates, statins, and pemetrexed in certain cancers) and an association between the overexpression of these targets and reduction in the overall survival duration of patients with breast and other hard-to-treat cancers, for which such drugs are not approved. In brief, the present analysis raised cautions about off-target and undesirable effects of certain oncology drugs in a subset of cancers where the in-tended cellular effectors of drug might not be fitness genes and offers a potential rationale for repurposing certain approved oncology drugs for targeted therapeutics in additional cancer types.


title: Cellular Fitness Phenotypes of Cancer Target Genes from Oncobiology to Cancer Therapeutics


title: A comprehensive survey of developmental programs reveals a dearth of tree-like lineage graphs and ubiquitous regeneration

abstract:
BackgroundMulticellular organisms are characterized by a wide diversity of forms and complexity despite a restricted set of key molecules and mechanisms at the base of organismal development. Development combines three basic processes -- asymmetric cell division, signaling and gene regulation -- in a multitude of ways to create this overwhelming diversity of multicellular life-forms. Here, we use a generative model to test the limits to which such processes can be combined to generate multiple differentiation paths during development, and attempt to chart the diversity of multicellular organisms generated.

ResultsWe sample millions of biologically feasible developmental schemes, allowing us to comment on the statistical properties of cell-differentiation trajectories they produce. We characterize model-generated  organisms using the graph topology of their cell-type lineage maps. Remarkably, tree-type lineage differentiation maps are the rarest in our data. Additionally, a majority of the  organisms generated by our model appear to be endowed with the ability to regenerate using pluripotent cells.

ConclusionsOur results indicate that, in contrast to common views, cell-type lineage graphs are unlikely to be tree-like. Instead, they are more likely to be directed acyclic graphs, with multiple lineages converging on the same terminal cell-type. Furthermore, the high incidence of pluripotent cells in model-generated organisms stands in line with the long-standing hypothesis that whole body regeneration is an epiphenomenon of development. We discuss experimentally testable predictions of our model, and some ways to adapt the generative framework to test additional hypotheses about general features of development.

category: developmental biology


title: Advances in Spiral fMRI: A High-resolution Study with Single-shot Acquisition

abstract:
Spiral fMRI has been put forward as a viable alternative to rectilinear echo-planar imaging, in particular due to its enhanced average k-space speed and thus high acquisition efficiency. This renders spirals attractive for contemporary fMRI applications that require high spatiotemporal resolution, such as laminar or columnar fMRI. However, in practice, spiral fMRI is typically hampered by its reduced robustness and ensuing blurring artifacts, which arise from imperfections in both static and dynamic magnetic fields.

Recently, these limitations have been overcome by the concerted application of an expanded signal model that accounts for such field imperfections, and its inversion by iterative image reconstruction. In the challenging ultra-high field environment of 7 Tesla, where field inhomogeneity effects are aggravated, both multi-shot and single-shot 2D spiral imaging at sub-millimeter resolution was demonstrated with high depiction quality and anatomical congruency.

In this work, we further these advances towards a time series application of spiral readouts, namely, single-shot spiral BOLD fMRI at 0.8 mm in-plane resolution. We demonstrate that high-resolution spiral fMRI at 7 T is not only feasible, but delivers both excellent image quality, BOLD sensitivity, and spatial specificity of the activation maps, with little artifactual blurring. Furthermore, we show the versatility of the approach with a combined in/out spiral readout at a more typical resolution (1.5 mm), where the high acquisition efficiency allows to acquire two images per shot for improved sensitivity by echo combination.

HighlightsO_LIThis work reports the first fMRI study at 7T with high-resolution spiral readout gradient waveforms.
C_LIO_LIWe achieve spiral fMRI with sub-millimeter resolution (0.8 mm, FOV 230 mm), acquired in a single shot (36 slices in 3.3 s).
C_LIO_LISpiral images exhibit intrinsic geometric congruency to anatomical scans, and spatially specific activation patterns.
C_LIO_LIImage reconstruction rests on a signal model expanded by measured trajectories and static field maps, inverted by cg-SENSE.
C_LIO_LIWe assess generalizability of the approach for spiral in/out readouts, providing two images per shot (1.5 mm resolution).
C_LI


title: Evidence for shared ancestry between Actinobacteria and Firmicutes bacteriophages

abstract: Bacteriophages typically infect a small set of related bacterial strains. The transfer of bacteriophages between more distant clades of bacteria has often been postulated, but remains mostly unaddressed. In this work we leverage the sequencing of a novel cluster of phages infecting Streptomyces bacteria and the availability of large numbers of complete phage genomes in public repositories to address this question. Using phylogenetic and comparative genomics methods, we show that several clusters of Actinobacteria-infecting phages are more closely related between them, and with a small group of Firmicutes phages, than with any other actinobacteriophage lineage. These data indicate that this heterogeneous group of phages shares a common ancestor with well-defined genome structure. Analysis of genomic %GC content and codon usage bias shows that these actinobacteriophages are poorly adapted to their Actinobacteria hosts, suggesting that this phage lineage could have originated in an ancestor of the Firmicutes, adapted to the low %GC content members of this phylum, and later migrated to the Actinobacteria, or that selective pressure for enhanced translational throughput is significantly lower for phages infecting Actinobacteria hosts.


title: Inhibition of both mutant and wild-type RAS-GTP in KRAS G12C colorectal cancer through cotreatment with G12C and EGFR inhibitors

abstract: The combination of KRAS G12C inhibitors with EGFR inhibitors has reproducibly been shown to be beneficial. Here, we reveal a new benefit of this combination: it effectively inhibits both wild-type and mutant RAS. A role for WT RAS inhibition has not previously been reported for this important combination of targeted therapies. We believe that targeting both mutant and wild-type RAS helps explain why this combination of inhibitors is effective.


title: Automated identification of maximal differential cell populations in flow cytometry data

abstract: We introduce a new cell population score called SpecEnr (specific enrichment) and describe a method that discovers robust and accurate candidate biomarkers from flow cytometry data. Our approach identifies a new class of candidate biomarkers we define as driver cell populations, whose abundance is associated with a sample class (e.g. disease), but not as a result of a change in a related population. We show that the driver cell populations we find are also easily interpretable using a lattice-based visualization tool. Our method is implemented in the R package flowGraph, freely available on GitHub (github.com/aya49/flowGraph) and on BioConductor.

category: bioinformatics


title: Beyond taxonomic identification: integration of ecological responses to a soil bacterial 16S rRNA gene database.

abstract: High-throughput sequencing 16S rRNA gene surveys have enabled new insights into the diversity of soil bacteria, and furthered understanding of the ecological drivers of abundances across landscapes. However, current analytical approaches are of limited use in formalising syntheses of the ecological attributes of taxa discovered, because derived taxonomic units are typically unique to individual studies and sequence identification databases only characterise taxonomy. To address this, we used sequences obtained from a large nationwide soil survey (GB Countryside Survey, henceforth "CS") to create a comprehensive soil specific 16S reference database, with coupled ecological information derived from the survey metadata. Specifically, we modelled taxon responses to soil pH at the OTU level using hierarchical logistic regression (HOF) models, to provide information on putative landscape scale pH-abundance responses. We identify that most of the soil OTUs examined exhibit predictable abundance responses across soil pH gradients, though with the exception of known acidophilic lineages, the pH optima of OTU relative abundance was variable and could not be generalised by broad taxonomy. This highlights the need for tools and databases to predict ecological traits at finer taxonomic resolution. We further demonstrate the utility of the database by testing against geographically dispersed query 16S datasets; evaluating efficacy by quantifying matches, and accuracy in predicting pH responses of query sequences from a separate large soil survey. We found that the CS database provided good coverage of dominant taxa; and that the taxa indicating soil pH in a query dataset corresponded with the pH classifications of top matches in the CS database. Furthermore we were able to predict query dataset community structure, using predicted abundances of dominant taxa based on query soil pH data and the HOF models of matched CS database taxa. The database with associated HOF model outputs is released as an online portal for querying single sequences of interest (https://shiny-apps.ceh.ac.uk/ID-TaxER), and as a DADA2 database for use in bioinformatics pipelines. The further development of advanced informatics infrastructures incorporating modelled ecological attributes along with new functional genomic information will likely facilitate large scale exploration and prediction of soil microbial functional biodiversity under current and future environmental change scenarios.

category: microbiology


title: Effective downregulation of BCR-ABL tumorigenicity by RNA targeted CRISPR-Cas13a

abstract:
AimTo induce BCR-ABL gene silencing using CRISPR Cas13a.

BackgroundCML is a clonal myeloproliferative disorder of pluripotent stem cells driven by a reciprocal translocation between chromosome 9 and 22, forming a BCR-ABL fusion gene. Tyrosinekinase inhibitor drugs like imatinib are the mainstay of treatment and cases resistant to these drugs have a poor prognosis in the absence of a compatible stem-cell donor. However, with rapid advancements in gene-editing technologies, most studies are now focusing on developing a translational model targeting single-gene disorders with a prospective permanent cure.

ObjectiveTo explore the potential application of the RNA targeting CRISPR-Cas13a system for effective knockdown of BCR-ABL fusion transcript in a CML cell line, K562.

MethodCRISPR Cas13a crRNA was designed specific to the chimeric BCR-ABL gene and the system was transfected as a two-plasmid system into a CML cell line, K562. The effects were enumerated by evaluating the expression levels of downstream genes dependent on the expression of the BCR-ABL gene. Also, next-generation sequencing was used to ascertain the effects of CRISPR on the gene.

ResultsThe CRISPR system was successfully able to lower the expression of downstream genes (pCRKL and pCRK) dependent on the activated BCR-ABL kinase signal by up-to 4.3 folds. The viability of the CRISPR treated cells were also significantly lowered by 373.83-fold (p-value= 0.000891196). The time-dependent kinetics also highlighted the significant in-vitro suppressive activity to last up to 8 weeks (p-value: 0.025). As per the cDNA sequencing data from Oxford MinION next-generation sequencer, the CRISPR treated cells show 62.37% suspected cleaved reads.

ConclusionThese preliminary results highlight an excellent potential application of RNA targeting CRISPRs in Haematological neoplasms like CML and should pave way for further research in this direction.

category: molecular biology


title: Adaptive divergence in shoot gravitropism creates hybrid sterility in an Australian wildflower

abstract:
Natural selection is a significant driver of speciation. Yet it remains largely unknown whether local adaptation can drive speciation through the evolution of hybrid sterility between populations. Here, we show that adaptive divergence in shoot gravitropism, the ability of a plants shoot to bend upwards in response to the downward pull of gravity, contributes to the evolution of hybrid sterility in an Australian wildflower, Senecio lautus. We find that shoot gravitropism has evolved multiple times in association with plant height between adjacent populations inhabiting contrasting environments, suggesting that these traits have evolved by natural selection. We directly tested this prediction using a hybrid population subjected to eight rounds of recombination and three rounds of selection in the field. It revealed that shoot gravitropism responds to natural selection in the expected direction of the locally adapted population. This provided an ideal platform to test whether genetic differences in gravitropism contribute to hybrid sterility in S. lautus. Using this advanced hybrid population, we discovered that crossing individuals with extreme differences in gravitropism reduce their ability to produce seed by 21%, providing strong evidence that this adaptive trait is genetically correlated with hybrid sterility. Our results suggest that natural selection can drive the evolution of locally adaptive traits that also create hybrid sterility, thus indicating an evolutionary connection between local adaptation and the origin of new species.

Significance statementNew species originate as populations become reproductively isolated from one another. Despite recent progress in uncovering the genetic basis of reproductive isolation, it remains unclear whether intrinsic reproductive barriers, such as hybrid sterility, evolve as a by-product of local adaptation to contrasting environments or evolve through non-ecological processes, such as meiotic drive. Here, we show that differences in a plants response to the pull of gravity have repeatedly evolved amongst coastal populations of an Australian wildflower, thus implicating a role of natural selection in their evolution. We found a strong genetic correlation between variation in this adaptive trait and hybrid sterility, suggesting that intrinsic reproductive barriers contribute to the origin of new species as populations adapt to heterogeneous environments.

category: evolutionary biology


title: Frequency selectivity of persistent cortical oscillatory responses to auditory rhythmic stimulation

abstract:
Cortical oscillations have been proposed to play a functional role in speech and music perception, attentional selection and working memory, via the mechanism of neural entrainment. One of the most compelling arguments for neural entrainment is that its modulatory effect on ongoing oscillations outlasts rhythmic stimulation. We tested the existence of this phenomenon by studying cortical neural oscillations during and after presentation of melodic stimuli in a passive perception paradigm. Melodies were composed of [~]60 and [~]80 Hz tones embedded in a 2.5 Hz stream. Using intracranial and surface recordings in humans, we reveal consistent neural response properties throughout the cortex, well beyond the auditory regions. Persistent oscillatory activity in the high-gamma band was observed in response to the tones. By contrast, in response to the 2.5 Hz stream, no persistent activity in any frequency band was observed. We further show that our data are well-captured by a model of damped harmonic oscillator and can be classified into three classes of neural dynamics, with distinct damping properties and eigenfrequencies. This model provides a mechanistic and quantitative explanation of the frequency selectivity of auditory neural entrainment in the human cortex.

Significance statementIt has been proposed that the functional role of cortical oscillations is subtended by a mechanism of entrainment, the synchronisation in phase or amplitude of neural oscillations to a periodic stimulation. We tested whether the modulatory effect on ongoing oscillations outlasts the rhythmic stimulation, a phenomenon considered to be one of the most compelling arguments for entrainment. Using intracranial and surface recordings of human listening to rhythmic auditory stimuli, we reveal consistent oscillatory responses throughout the cortex, with persistent activity of high-gamma oscillations. On the contrary, neural oscillations do not outlast low-frequency acoustic dynamics. We interpret our results as reflecting harmonic oscillator properties - a model ubiquitous in physics but rarely used in neuroscience.


title: Recombination and selection against introgressed DNA

abstract:
DNA introgressed from one species into another is typically deleterious at many genomic loci in the recipient species. It is therefore purged by selection over time. Here, we use mathematical modeling and whole-genome simulations to study the influence of recombination on the purging of introgressed DNA. We find that aggregate recombination controls the genome-wide rate of purging in the first few generations after admixture, when purging is most rapid. Aggregate recombination is quantified by [Formula], the average recombination rate across all locus pairs, and analogous metrics. It is influenced by the number of crossovers (i.e., the map length) and their locations along chromosomes, and by the number of chromosomes and heterogeneity in their size. A comparative prediction of our analysis is that species with fewer chromosomes should purge introgressed DNA more profoundly, and therefore should exhibit a weaker genomic signal of historical introgression. With regard to patterns across the genome, we show that, in heterogametic species with autosomal recombination in both sexes, more purging is expected on sex chromosomes than on autosomes, all else equal. The opposite prediction holds for species without autosomal recombination in the heterogametic sex. Finally, we show that positive genomic correlations between local recombination rate and introgressed ancestry, as recently observed in several taxa, are likely driven not by recombinations effect in unlinking neutral from deleterious introgressed alleles, but rather by its effect on the rate of purging of the deleterious alleles themselves.

Note on this versionAn earlier version of this manuscript had two parts: (1) Calculations of the variance of genetic relatedness between individuals with particular pedigree relationships, taking into account the randomness of recombination and segregation in their pedigree. (2) An investigation of the rate of purging of introgressed DNA following admixture, based in part on results from part (1). Part (1) has since been published as Veller et al. (2020). The present manuscript has been reconfigured to focus on part (2).


title: Predictive Coding Models for Pain Perception

abstract: Pain is a complex, multidimensional experience that involves dynamic interactions between sensory-discriminative and affective-emotional processes. Pain experiences have a high degree of variability depending on their context and prior anticipation. Viewing pain perception as a perceptual inference problem, we propose a predictive coding paradigm to characterize evoked and non-evoked pain. We record the local field potentials (LFPs) from the primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) of freely behaving rats--two regions known to encode the sensory-discriminative and affective-emotional aspects of pain, respectively. We further use predictive coding to investigate the temporal coordination of oscillatory activity between the S1 and ACC. Specifically, we develop a phenomenological predictive coding model to describe the macroscopic dynamics of bottom-up and top-down activity. Supported by recent experimental data, we also develop a biophysical neural mass model to describe the mesoscopic neural dynamics in the S1 and ACC populations, in both naive and chronic pain-treated animals. Our proposed predictive coding models not only replicate important experimental findings, but also provide new prediction about the impact of the model parameters on the physiological or behavioral read-out--thereby yielding mechanistic insight into the uncertainty of expectation, placebo or nocebo effect, and chronic pain.


abstract: The authors have withdrawn this preprint titled "Differential robustness to specific potassium channel deletions in midbrain dopaminergic neurons". Upon review of breeding and genotyping data, Kcnn3-/- mice could not be trusted as representative of the expected genetic deletion. As a consequence data generated from these animals do not constitute a valid description of the Kcnn3-/- genotype in dopaminergic neurons. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.


title: Strand asymmetry influences mismatch resolution during single-strand annealing

abstract:
BackgroundBiases of DNA repair can shape the nucleotide landscape of genomes at evolutionary timescales. However, such biases have not yet been measured in chromatin for lack of technologies.

ResultsHere we develop a genome-wide assay whereby the same DNA lesion is repaired in different chromatin contexts. We insert thousands of barcoded transposons carrying a reporter of DNA mismatch repair in the genome of mouse embryonic stem cells. Upon inducing a double-strand break between tandem repeats, a mismatch is generated when the single strand annealing repair pathway is used. Regardless of the mismatch, we observed a 60-80% bias in the resolution in favor of one strand. The location of the lesion in the genome and the type of mismatch had little influence on the bias in this context. Instead, changing the position of the double-strand break in the reporter gave a complete reversion of the bias.

ConclusionThese results suggest that the processing of the double-strand break has a major influence on the repair of mismatches during single-strand annealing, irrespective of the surrounding chromatin context.


title: Rhomboid protease RHBDL4 promotes retrotranslocation of aggregation-prone proteins for degradation

abstract: Protein degradation is fundamentally important to ensure cell homeostasis. In the endoplasmic reticulum (ER), the ER-associated degradation (ERAD) pathway targets incorrectly folded and unassembled proteins into the cytoplasm for turnover by the proteasome. In contrast, lysosomal degradation serves as a failsafe mechanism for removing proteins that resist ERAD by forming aggregates. Previously, we showed that the ER- resident rhomboid protease RHBDL4, together with p97, mediates membrane protein degradation. However, whether RHBDL4 acts in concert with additional ERAD components is unclear, and its full substrate spectrum remains to be defined. Here, we show that besides membrane proteins, RHBDL4 cleaves aggregation-prone luminal ERAD substrates. Because RHBDL4 with mutations in the rhomboid domain leads to stabilization of substrates at the cytoplasmic side, we hypothesize that analogue to the homologue ERAD factor derlin, RHBDL4 is directly involved in substrate retrotranslocation. RHBDL4s interaction with the erlin ERAD complex and reciprocal interaction of rhomboid substrates with erlins suggest that RHBDL4 and erlins form a complex that clips substrates and thereby rescues aggregation-prone peptides in the ER lumen from terminal aggregation.

category: cell biology


title: RAF conformational autoinhibition and 14-3-3 proteins promote paradoxical activation

abstract: RAF kinase inhibitors can, in some conditions, increase RAF kinase signaling. This process, which is commonly referred to as "paradoxical activation" (PA), is incompletely understood. RAF kinases are regulated by autoinhibitory conformational changes, and the role of these conformational changes in PA is unclear. Our mathematical investigations reveal that a dynamic equilibrium between autoinhibited and non-autoinhibited forms of RAF, along with the RAF inhibitor stabilization of the non-autoinhibited form, can be sufficient to create PA. Using both computational and experimental methods we demonstrate that 14-3-3 proteins, which stabilize both RAF autoinhibition and RAF dimerization, potentiate PA. Our model led us to hypothesize that increased 14-3-3 expression would amplify PA for the third generation RAF inhibitors that normally display minimal to no PA. Our subsequent experiments find that 14-3-3 overexpression increases PA, increases RAF dimerization, and promotes resistance to these inhibitors, effectively "breaking" these "paradox breaker" and pan-RAF inhibitors. Overall, this work reveals a robust mechanism for PA based solely on equilibrium dynamics of canonical interactions in RAF signaling and identifies conditions which allow PA to occur.


title: Integration of Odor-Induced Activity of Kenyon Cells in an Electrotonically Compact Drosophila Mushroom Body Output Neuron (MBON)

abstract: The formation of an ecologically useful lasting memory requires that the brain has an accurate internal representation of the surrounding environment. In addition, it must have the ability to integrate a variety of different sensory stimuli and associate them with rewarding and aversive behavioral outcomes. Over the previous years, a number of studies have dissected the anatomy and elucidated some of the working principles of the Drosophila mushroom body (MB), the flys center for learning and memory. As a consequence, we now have a functional understanding of where and how in the MB sensory stimuli converge and are associated. However, the molecular and cellular dynamics at the critical synaptic intersection for this process, the Kenyon cell-mushroom body output neuron (KC-MBON) synapse, are largely unknown. Here, we introduce a first approach to understand this integration process and the physiological changes occurring at the KC-MBON synapse during Kenyon cell (KC) activation. We use the published connectome of the Drosophila MB to construct a functional computational model of the MBON-3 dendritic structure. We simulate synaptic input by individual KC-MBON synapses by current injections into precisely (m) identified local dendritic sections, and the input from a model population of KCs representing an odor by a spatially distributed cluster of current injections. By recording the effect of the simulated current injections on the membrane potential of the neuron, we show that the MBON-3 is electrotonically compact. This suggests that odor-induced MBON activity is likely governed by input strength while the positions of KC input synapses are largely irrelevant.


title: Effects of dopamine receptor antagonism and amphetamine-induced psychomotor sensitization on sign- and goal-tracking after extended training

abstract: The dopamine system is important for incentive salience attribution, where motivational value is assigned to conditioned cues that predict appetitive reinforcers. However, the role of dopamine in this process may change with extended training. We tested the effects of dopamine D1-like and D2-like receptor antagonism on the expression of sign-tracking and goal-tracking conditioned responses following extended Pavlovian conditioned approach (PCA) training. We also tested if amphetamine-induced psychomotor sensitization accelerates the enhanced acquisition of sign-tracking that is observed with extended training. In experiment 1, 24 male Long-Evans rats received 20 PCA sessions in which one lever (CS+, 10 s) predicted 0.2 mL sucrose (10%, w/v) delivery and the other lever (CS-) did not. SCH-23390 (D1-like antagonist) or eticlopride (D2-like antagonist) were administered before non-reinforced behavioural tests at doses of 0, 0.01, and 0.1 mg/kg (s.c.). In experiment 2, rats received vehicle or 2 mg/kg amphetamine (i.p.) for 7 days (n = 12/group). Ten days later, they received 16 PCA training sessions. Both doses of SCH-23390 reduced sign- and goal-tracking, but also reduced locomotor behaviour. A low dose of eticlopride (0.01 mg/kg) selectively reduced goal-tracking, without affecting sign-tracking or locomotor behaviour. Amphetamine produced psychomotor sensitization, and this did not affect the acquisition of sign- or goal-tracking. Following extended PCA training, dopamine D2-like receptor activity is required for the expression of goal-tracking but not sign-tracking. Psychomotor sensitization to amphetamine did not impact incentive salience attribution; however, more selective manipulations of the dopamine system may be needed.


title: Barley RIC157 is involved in RACB-mediated susceptibility to powdery mildew

abstract: Successful obligate pathogens benefit from host cellular processes. For the biotrophic ascomycete fungus Blumeria graminis f.sp. hordei (Bgh) it has been shown that barley RACB, a small monomeric G-protein (ROP, RHO of plants), is required for full susceptibility to fungal penetration. The susceptibility function of RACB probably lies in its role in cell polarisation, which may be co-opted by the pathogen for invasive ingrowth of its haustorium. However, the actual mechanism of how RACB supports the fungal penetration success is little understood. RIC proteins (ROP-Interactive and CRIB-(Cdc42/Rac Interactive Binding) motif-containing) are considered scaffold proteins which can interact directly with ROPs via a conserved CRIB motif. Here we describe a yet uncharacterised RIC protein, RIC157, which can interact directly with RACB in planta. We show that RIC157 undergoes a recruitment from the cytoplasm to the cell periphery in the presence of activated RACB. During fungal infection, RIC157 and activated RACB colocalise at the penetration site, particularly at the haustorial neck. In a RACB-dependent manner, transiently overexpressed RIC157 renders barley epidermal cells more susceptible to fungal penetration. This suggests that RIC157 promotes fungal penetration into barley epidermal cells via its function downstream of RACB.

category: plant biology


title: Using single visits into integrated occupancy models to make the most of existing monitoring programs

abstract: A major challenge in statistical ecology consists of integrating knowledge from different datasets to produce robust ecological indicators. To estimate species distribution, occupancy models are a flexible framework that can accommodate several datasets obtained from different sampling methods. However, repeating visits at sampling sites is a prerequisite for using standard occupancy models. Occupancy models were recently developed to analyze detection/non-detection data collected during a single visit. To date, single-visit occupancy models have never been used to integrate several different datasets. Here, we showcase an approach that combines two datasets into an integrated single-visit occupancy model. As a case study, we estimated the distribution of Bottlenose dolphins (Tursiops truncatus) over the North-western Mediterranean Sea by combining 24,624 km of aerial surveys and 21,464 km of at-sea monitoring. We compared the outputs of single- vs. repeated-visit occupancy models into integrated occupancy models. Integrated models allowed a better sampling coverage of species home-range, which provided a better precision for occupancy estimates than occupancy models using datasets in isolation. Overall, single- and repeated-visit integrated occupancy models produced similar inference about the distribution of bottlenose dolphins. We suggest that single-visit occupancy models open promising perspectives for the use of existing ecological datasets.


title: GraphProt2: A graph neural network-based method for predicting binding sites of RNA-binding proteins

abstract: CLIP-seq is the state-of-the-art technique to experimentally determine transcriptome-wide binding sites of RNA-binding proteins (RBPs). However, it relies on gene expression which can be highly variable between conditions, and thus cannot provide a complete picture of the RBP binding landscape. This creates a demand for computational methods to predict missing binding sites. Here we present GraphProt2, a computational RBP binding site prediction framework based on graph convolutional neural networks (GCNs). In contrast to current CNN methods, GraphProt2 offers native support for the encoding of base pair information as well as variable length input, providing increased flexibility and the prediction of nucleotide-wise RBP binding profiles. We demonstrate its superior performance compared to GraphProt and two CNN-based methods on single as well as combined CLIP-seq datasets. Conceived as an end-to-end method, GraphProt2 includes all necessary functionalities, from dataset generation over model training to the evaluation of binding preferences and binding site prediction. Various input types and features are supported, accompanied by comprehensive statistics and visualizations to inform the user about datatset characteristics and learned model properties. All this makes GraphProt2 the most versatile and complete RBP binding site prediction method available so far.


title: Temperature-induced prophage dictates evolution of virulence in bacteria

abstract: Viruses are key actors of ecosystems and have major impacts on global biogeochemical cycles. Prophages deserve particular attention as they are ubiquitous in bacterial genomes and can enter a lytic cycle when triggered by environmental conditions. We explored how temperature affects the interactions between prophages and other biological levels by using an opportunistic pathogen, the bacterium Serratia marcescens, that harbours several prophages and that had undergone an evolution experiment under several temperature regimes. We found that the release of one of the prophages was temperature-sensitive and malleable to evolutionary changes. We further discovered that the virulence of the bacterium in an insect model also evolved and was positively correlated with phage release rates. We determined through analysis of genetic and epigenetic data that changes in the outer cell wall structure possibly explain this phenomenon. We hypothezise that the temperature-dependent phage release rate acted as a selection pressure on S. marcescens and that it resulted in modified bacterial virulence in the insect host. Our study system illustrates how viruses can mediate the influence of abiotic environmental changes to other biological levels and thus be involved in ecosystem feedback loops.


title: The effect of a temperature-sensitive prophage on the evolution of virulence in an opportunistic bacterial pathogen


title: Bacterial quorum sensing allows graded and bimodal cellular responses to variations in population density

abstract: Quorum sensing (QS) is a mechanism of cell-cell communication that connects gene expression to environmental conditions (e.g. density) in many bacterial species, mediated by diffusible signal molecules. Current functional studies focus on a dichotomy of QS on/off (or, quorate / sub-quorate) states, overlooking the potential for intermediate, graded responses to shifts in the environment. Here, we track QS regulated protease (lasB) expression and show that Pseudomonas aeruginosa can deliver a graded behavioral response to fine-scale variation in population density, on both the population and single-cell scales. On the population scale, we see a graded response to variation in environmental population density. On the single-cell scale, we see significant bimodality at higher densities, with separate OFF and ON sub-populations that respond differentially to changes in density; static OFF cells and increasing intensity of expression among ON cells. Together these results indicate that QS can tune gene expression to graded environmental change, with no critical cell mass or  quorum at which behavioral responses are activated on either the individual cell or population scale. In an infection context, our results indicate there is not a hard threshold separating sub-quorate  stealth mode and a quorate  attack mode.


title: Family History of Depression is Associated with Alterations in Task-Dependent Connectivity between the Cerebellum and Ventromedial Prefrontal Cortex

abstract:
BackgroundA family history of major depressive disorder (MDD) increases the likelihood of a future depressive episode, which itself poses a significant risk for disruptions in reward processing and social cognition. However, it is unclear whether a family history of MDD is associated with alterations in the neural circuitry underlying reward processing and social cognition.

MethodsWe subdivided 279 participants from the Human Connectome Project into three groups: 71 with a lifetime history of MDD, 103 with a family history of MDD (FH), and 105 healthy controls (HC). We then evaluated task-based fMRI data on a social cognition and a reward processing task and found a region of the ventromedial prefrontal cortex (vmPFC) that responded to both tasks, independent of group. To investigate whether the vmPFC shows alterations in functional connectivity between groups, we conducted psychophysiological interaction (PPI) analyses using the vmPFC as a seed region.

ResultsWe found that FH (relative to HC) was associated with increased sadness scores, and MDD (relative to both FH and HC) was associated with increased sadness and MDD symptoms. Additionally, the FH group had increased vmPFC functional connectivity within the nucleus accumbens, left dorsolateral PFC, and subregions of the cerebellum relative to HC during the social cognition task.

ConclusionsThese findings suggest that aberrant neural mechanisms among those with a familial risk of MDD may underlie vulnerability to altered social cognition.


title: Predator complementarity dampens variability of phytoplankton biomass in a diversity-stability trophic cascade

abstract: Trophic cascades - indirect effects of predators that propagate down through food webs - have been extensively documented. It has also been shown that predator diversity can mediate these trophic cascades, and separately, that herbivore biomass can influence the stability of primary producers. However, whether predator diversity can cause cascading effects on the stability of lower trophic levels has not yet been studied. We conducted a laboratory microcosm experiment and a field mesocosm experiment manipulating the presence and coexistence of two heteropteran predators and measuring their effects on zooplankton herbivores and phytoplankton basal resources. We predicted that if the predators partitioned their zooplankton prey, for example by size, then co-presence of the predators would reduce zooplankton prey mass and lead to 1) increased average values and 2) decreased temporal variability of phytoplankton basal resources. We present evidence that the predators partitioned their zooplankton prey, leading to a synergistic suppression of zooplankton; and that in turn, this suppression of zooplankton reduced the variability of phytoplankton biomass. However, mean phytoplankton biomass was unaffected. Our results demonstrate that predator diversity may indirectly stabilize basal resource biomass via a "diversity-stability trophic cascade," seemingly dependent on predator complementarity, but independent of a classic trophic cascade in which average biomass is altered. Therefore predator diversity, especially if correlated with diversity of prey use, could play a role in regulating ecosystem stability. Furthermore, this link between predator diversity and producer stability has implications for potential biological control methods for improving the reliability of crop yields.


title: Statistical power: implications for planning MEG studies

abstract: Statistical power is key for robust, replicable science. Here, we systematically explored how numbers of trials and subjects affect statistical power in MEG sensor-level data. More specifically, we simulated "experiments" using the MEG resting-state dataset of the Human Connectome Project (HCP). We divided the data in two conditions, injected a dipolar source at a known anatomical location in the "signal condition", but not in the "noise condition", and detected significant differences at sensor level with classical paired t-tests across subjects, using amplitude, squared amplitude, and global field power (GFP) measures. Group-level detectability of these simulated effects varied drastically with anatomical origin. We thus examined in detail which spatial properties of the sources affected detectability, looking specifically at the distance from closest sensor and orientation of the source, and at the variability of these parameters across subjects. In line with previous single-subject studies, we found that the most detectable effects originate from source locations that are closest to the sensors and oriented tangentially with respect to the head surface. In addition, cross-subject variability in orientation also affected group-level detectability, boosting detection in regions where this variability was small and hindering detection in regions where it was large. Incidentally, we observed a considerable covariation of source position, orientation, and their cross-subject variability in individual brain anatomical space, making it difficult to assess the impact of each of these variables independently of one another. We thus also performed simulations where we controlled spatial properties independently of individual anatomy. These additional simulations confirmed the strong impact of distance and orientation and further showed that orientation variability across subjects affects detectability, whereas position variability does not. Importantly, our study indicates that strict unequivocal recommendations as to the ideal number of trials and subjects for any experiment cannot be realistically provided for neurophysiological studies and should be adapted according to the brain regions under study.


title: Low membrane fluidity triggers lipid phase separation and protein segregation in vivo

abstract: All living organisms adapt their membrane lipid composition in response to changes in their environment or diet. These conserved membrane-adaptive processes have been studied extensively. However, key concepts of membrane biology linked to regulation of lipid composition including homeoviscous adaptation maintaining stable levels of membrane fluidity, and gel-fluid phase separation resulting in domain formation, heavily rely upon in vitro studies with model membranes or lipid extracts. Using the bacterial model organisms Escherichia coli and Bacillus subtilis, we now show that inadequate in vivo membrane fluidity interferes with essential complex cellular processes including cytokinesis, envelope expansion, chromosome replication/segregation and maintenance of membrane potential. Furthermore, we demonstrate that very low membrane fluidity is indeed capable of triggering large-scale lipid phase separation and protein segregation in intact, protein-crowded membranes of living cells; a process that coincides with the minimal level of fluidity capable of supporting growth. Importantly, the in vivo lipid phase separation is not associated with a breakdown of the membrane diffusion barrier function, thus explaining why the phase-separation process induced by low fluidity is biologically reversible.


title: Energy Expenditure during Cell Spreading Regulates the Stem Cells Responses to Matrix Stiffness

abstract: Cells respond to the mechanical properties of the extracellular matrix (ECM) through formation of focal adhesions (FAs), re-organization of the actin cytoskeleton and adjustment of cell contractility. These are energy-demanding processes, but a potential causality between mechanical cues (matrix stiffness) and cellular (energy) metabolism remains largely unexplored. Here, we culture human mesenchymal stem cells (hMSCs) on stiff (20 kPa) or soft (1 kPa) substrate and demonstrate that cytoskeletal reorganization and FA formation spreading on stiff substrates lead to a drop in intracellular ATP levels, correlates with the activation of AMP-activated protein kinase (AMPK). The resulting increase in ATP levels further facilitates cell spreading and reinforces cell tension of the steady state, and coincides with nuclear localization of YAP/TAZ and Runx2. While on soft substrates (1 kPa), lowered ATP levels limit these cellular mechanoresponses. Furthermore, genetic ablation of AMPK lowered cellular ATP levels on stiff substrate and strongly reduced responses to substrate stiffness. Together, these findings reveal a hitherto unidentified relationship between energy expenditure and the cellular mechanoresponse, and point to AMPK as a key mediator of stem cell fate in response to ECM mechanics.


title: The neural computation of human prosocial choices in complex motivational states

abstract:
Motives motivate human behavior. Most behaviors are driven by more than one motive, yet it is unclear how different motives interact and how such motive combinations affect the neural computation of the behaviors they drive. To answer this question, we induced two prosocial motives simultaneously (multi-motive condition) and separately (single motive conditions). After the different motive inductions, participants performed the same choice task in which they allocated points in favor of the other person (prosocial choice) or in favor of themselves (egoistic choice). We used fMRI to assess prosocial choice-related brain responses and drift diffusion modelling to specify how motive combinations affect individual components of the choice process. Our results showed that the combination of the two motives in the multi-motive condition increased participants choice biases prior to the behavior itself. On the neural level, these changes in initial prosocial bias were associated with neural responses in the bilateral dorsal striatum. In contrast, the efficiency of the prosocial decision process was comparable between the multi-motive and the single-motive conditions. These findings provide insights into the computation of prosocial choices in complex motivational states, the motivational setting that drives most human behaviors.

HighlightsO_LIActivating different social motives simultaneously can enhance prosocial choices
C_LIO_LIMulti-motive combinations change initial prosocial biases
C_LIO_LIDorso-striatal activation increases with larger increase of prosocial bias
C_LIO_LIMulti-motive combinations modulate relative response caution
C_LI


title: Distinct Processing of Selection and Execution Errors in Neural Signatures of Outcome Monitoring

abstract: Losing a point in tennis could result from poor shot selection or faulty stroke execution. To explore how the brain responds to these different types of errors, we examined feedback-locked EEG activity while participants completed a modified version of a standard three-armed bandit probabilistic reward task. Our task framed unrewarded outcomes as either the result of errors of selection or errors of execution. We examined whether amplitude of a medial frontal negativity (the Feedback-Related Negativity; FRN) was sensitive to the different forms of error attribution. Consistent with previous reports, selection errors elicited a large FRN relative to rewards and amplitude of this signal correlated behavioral adjustment following these errors. A different pattern was observed in response to execution errors. These outcomes produced a larger FRN, a frontocentral attenuation in activity preceding this component, and a subsequent enhanced error positivity in parietal sites. Notably, the only correlations with behavioral adjustment were with the early frontocentral attenuation and amplitude of the parietal signal; FRN differences between execution errors and rewarded trials did not correlate with subsequent changes in behavior. Our findings highlight distinct neural correlates of selection and execution error processing, providing insight into how the brain responds to the different classes of error that determine future action.


title: Face familiarity detection with complex synapses

abstract:
Synaptic plasticity is a complex phenomenon involving multiple biochemical processes that operate on different timescales. We recently showed that this complexity can greatly increase the memory capacity of neural networks when the variables that characterize the synaptic dynamics have limited precision, as in biological systems. These types of complex synapses have been tested mostly on simple memory retrieval problems involving random and uncorrelated patterns. Here we turn to a real-world problem, face familiarity detection, and we show that also in this case it is possible to take advantage of synaptic complexity to store in memory a large number of faces that can be recognized at a later time. In particular, we show that the familiarity memory capacity of a system with complex synapses grows almost linearly with the number of the synapses and quadratically with the number of neurons. Complex synapses are superior to simple ones, which are characterized by a single variable, even when the total number of dynamical variables is matched. We further show that complex and simple synapses have distinct signatures that are testable in proposed experiments. Our results indicate that a memory system with complex synapses can be used in real-world tasks such as face familiarity detection.

SignificanceThe complexity of biological synapses is probably important for enabling us to remember the past for a long time and rapidly store new memories. The advantage of complex synapses in terms of memory capacity is significant when the variables that characterize the synaptic dynamics have limited precision. This advantage has been estimated under the simplifying assumption that the memories to be stored are random and uncorrelated. Here we show that synaptic complexity is important also in a more challenging and realistic face familiarity detection task. We built a simple neural circuit that can report whether a face has been previously seen or not. This circuit incorporates complex synapses that operate on multiple timescales. The memory performance of this circuit is significantly higher than in the case in which synapses are simple, indicating that the complexity of biological synapses can be important also in real-world memory tasks.


title: The metastable brain associated with autistic-like traits of typically developing individuals

abstract:
Metastability in the brain is thought to be a mechanism involved in dynamic organization of cognitive and behavioral functions across multiple spatiotemporal scales. However, it is not clear how such organization is realized in underlying neural oscillations in a high-dimensional state space. It was shown that macroscopic oscillations often form phase-phase coupling (PPC) and phase-amplitude coupling (PAC) which result in synchronization and amplitude modulation, respectively, even without external stimuli. These oscillations can also make spontaneous transitions across synchronous states at rest. Using resting-state electroencephalographic signals and the autism-spectrum quotient scores acquired from healthy humans, we show experimental evidence that the PAC combined with PPC allows amplitude modulation to be transient, and that the metastable dynamics with this transient modulation is associated with autistic-like traits. In individuals with a longer attention span, such dynamics tended to show fewer transitions between states by forming delta-alpha PAC. We identified these states as two-dimensional metastable states that could share consistent patterns across individuals. Our findings suggest that the human brain dynamically organizes inter-individual differences in a hierarchy of macroscopic oscillations with multiple timescales by utilizing metastability.

Author SummaryThe human brain organizes cognitive and behavioral functions dynamically. For decades, the dynamic organization of underlying neural oscillations has been a fundamental topic in neuroscience research. Even without external stimuli, macroscopic oscillations often form phase-phase coupling and phase-amplitude coupling (PAC) that result in synchronization and amplitude modulation, respectively, and can make spontaneous transitions across synchronous states at rest. Using resting-state electroencephalography signals acquired from healthy humans, we show evidence that these two neural couplings enable amplitude modulation to be transient, and that this transient modulation can be viewed as the transition among oscillatory states with different PAC strengths. We also demonstrate that such transition dynamics are associated with the ability to maintain attention to detail and to switch attention, as measured by autism-spectrum quotient scores. These individual dynamics were visualized as a trajectory among states with attracting tendencies, and involved consistent brain states across individuals. Our findings have significant implications for unraveling variability in the individual brains showing typical and atypical development.


title: Electrode pooling: How to boost the yield of switchable silicon probes for neuronal recordings

abstract: State-of-the-art silicon probes for electrical recording from neurons have thousands of recording sites. However, due to volume limitations there are typically many fewer wires carrying signals off the probe, which restricts the number of channels that can be recorded simultaneously. To overcome this fundamental constraint, we propose a novel method called electrode pooling that uses a single wire to serve many recording sites through a set of controllable switches. Here we present the framework behind this method and an experimental strategy to support it. We then demonstrate its feasibility by implementing electrode pooling on the Neuropixels 1.0 electrode array and characterizing its effect on signal and noise. Finally we use simulations to explore the conditions under which electrode pooling saves wires without compromising the content of the recordings. We make recommendations on the design of future devices to take advantage of this strategy.


title: Constricted migration is associated with stable 3D genome structure differences in cancer cells

abstract: To spread from a localized tumor, metastatic cancer cells must squeeze through constrictions that cause major nuclear deformations. Since chromosome structure affects nucleus stiffness, gene regulation and DNA repair, here we investigate the relationship between 3D genome structure and constricted migration in cancer cells. Using melanoma (A375) cells, we identify phenotypic differences in cells that have undergone multiple rounds of constricted migration. These cells display a stably higher migration efficiency, elongated morphology, and differences in the distribution of Lamin A/C and heterochromatin. Hi-C experiments reveal differences in chromosome spatial compartmentalization specific to cells that have passed through constrictions and related alterations in expression of genes associated with migration and metastasis. Certain features of the 3D genome structure changes, such as a loss of B compartment interaction strength, are consistently observed after constricted migration in clonal populations of A375 cells and in MDA-MB-231 breast cancer cells. Our observations suggest that consistent types of chromosome structure changes are induced or selected by passage through constrictions and that these may epigenetically encode stable differences in gene expression and cellular migration phenotype.

category: systems biology


title: Multi-Study Learning for Real-time Neurochemical Sensing in Humans using the "Study Strap Ensemble"

abstract:
We propose the "study strap ensemble," which combines advantages of two common approaches to fitting prediction models when multiple training datasets ("studies") are available: pooling studies and fitting one model versus averaging predictions from multiple models each fit to individual studies. The study strap ensemble fits models to bootstrapped datasets, or "pseudo-studies." These are generated by resampling from multiple studies with a hierarchical resampling scheme that generalizes the randomized cluster bootstrap. The study strap is controlled by a tuning parameter that determines the proportion of observations to draw from each study. When the parameter is set to its lowest value, each pseudo-study is resampled from only a single study. When it is high, the study strap ignores the multi-study structure and generates pseudo-studies by merging the datasets and drawing observations like a standard bootstrap. We empirically show the optimal tuning value often lies in between, and prove that special cases of the study strap draw the merged dataset and the set of original studies as pseudo-studies. We extend the study strap approach with an ensemble weighting scheme that utilizes information in the distribution of the covariates of the test dataset.

Our work is motivated by neuroscience experiments using real-time neurochemical sensing during awake behavior in humans. Current techniques to perform this kind of research require measurements from an electrode placed in the brain during awake neurosurgery and rely on prediction models to estimate neurotransmitter concentrations from the electrical measurements recorded by the electrode. These models are trained by combining multiple datasets that are collected in vitro under heterogeneous conditions in order to promote accuracy of the models when applied to data collected in the brain. A prevailing challenge is deciding how to combine studies or ensemble models trained on different studies to enhance model generalizability.

Our methods produce marked improvements in simulations and in this application. All methods are available in the studyStrap CRAN package.


title: Hierachical Resampling for Bagging in Multi-Study Prediction with Applications to Human Neurochemical Sensing


title: Linear reinforcement learning: Flexible reuse of computation in planning, grid fields, and cognitive control

abstract: It is thought that the brains judicious reuse of previous computation underlies our ability to plan flexibly, but also that inappropriate reuse gives rise to inflexibilities like habits and compulsion. Yet we lack a complete, realistic account of either. Building on control engineering, we introduce a new model for decision making in the brain that reuses a temporally abstracted map of future events to enable biologically-realistic, flexible choice at the expense of specific, quantifiable biases. It replaces the classic nonlinear, model-based optimization with a linear approximation that softly maximizes around (and is weakly biased toward) a default policy. This solution exposes connections between seemingly disparate phenomena across behavioral neuroscience, notably flexible replanning with biases and cognitive control. It also gives new insight into how the brain can represent maps of long-distance contingencies stably and componentially, as in entorhinal response fields, and exploit them to guide choice even under changing goals.


title: Network potential identifies therapeutic miRNA cocktails in Ewings Sarcoma

abstract:
MicroRNA (miRNA)-based therapies are an emerging class of targeted therapeutics with many potential applications. Ewing Sarcoma patients could benefit dramatically from personalized miRNA therapy due to inter-patient heterogeneity and a lack of druggable (to this point) targets. However, because of the broad effects miRNAs may have on different cells and tissues, trials of miRNA therapies have struggled due to severe toxicity and unanticipated immune response. In order to overcome this hurdle, a network science-based approach is well-equipped to evaluate and identify miRNA candidates and combinations of candidates for the repression of key oncogenic targets while avoiding repression of essential housekeeping genes. We first characterized 6 Ewing sarcoma cell lines using mRNA sequencing. We then estimated a measure of tumor state, which we term network potential, based on both the mRNA gene expression and the underlying protein-protein interaction network in the tumor. Next, we ranked mRNA targets based on their contribution to network potential. We then identified miRNAs and combinations of miRNAs that preferentially act to repress mRNA targets with the greatest influence on network potential. Our analysis identified TRIM25, APP, ELAV1, RNF4, and HNRNPL as ideal mRNA targets for Ewing sarcoma therapy. Using predicted miRNA-mRNA target mappings, we identified miR-3613-3p, let-7a-3p, miR-300, miR-424-5p, and let-7b-3p as candidate optimal miRNAs for preferential repression of these targets. Ultimately, our work, as exemplified in the case of Ewing sarcoma, describes a novel pipeline by which personalized miRNA cocktails can be designed to maximally perturb gene networks contributing to cancer progression.

Author SummaryPrecision medicine in cancer aims to find the right treatment, for the right patient, at the right time. Substantial variation between patient tumors, even of the same disease site, has limited the application of precision medicine in the clinic. In this study, we present novel computational tools for the identification of targets for cancer therapy using widely available sequencing data. We used a network-science based approach that leveraged multiple types of omic data to identify functionally relevant disease targets. Further, we developed algorithms to identify potential miRNA-based therapies that inhibit these predicted disease targets. We applied this pipeline to a novel Ewing Sarcoma transcriptomics data-set as well as publicly available patient data from the St. Jude Cloud. We identified a number of promising therapeutic targets for this rare disease, including EWSR1, the proposed driver of Ewing Sarcoma development. These novel data and methods will provide researchers with new tools for the development of precision medicine treatments in a variety of cancer systems.


title: Dopamine and stress signalling interplay patterns social organization in mice

abstract: The rules leading to the emergence of a social organization and the role of social hierarchy on normal and pathological behaviours remain elusive. Here we show that groups of four isogenic male mice rapidly form enduring social ranks in a dominance hierarchy. Highest ranked individuals display enhanced anxiety and working memory, are more social and more susceptible to stress-related maladaptive behaviours. Are these differences causes or consequences to social life? We show that anxiety emerges from life in colony whereas sociability is a pre-existing trait. Strikingly, highest ranked individuals exhibit lower bursting activity of VTA dopamine neurons. Both pharmacogenetic inhibition of this neuronal population and the genetic inactivation of glucocorticoid receptor signalling in dopamine-sensing brain areas promote the accession to higher social ranks. Altogether, these results indicate that the shaping of social fate relies upon the interplay of dopamine system and stress response, impacting individual behaviour and potentially mental health.

category: animal behavior and cognition


title: Mapping Human Pluripotent Stem Cell Derived Erythroid Differentiation by Single-Cell Transcriptome Analysis

abstract: There is an imbalance between the supply and demand of functional red blood cells (RBCs) in clinical applications. This imbalance can be addressed by regenerating RBCs using several in vitro methods. Induced pluripotent stem cells (iPSCs) can handle the low supply of cord blood and the ethical issues in embryonic stem cell research and provide a promising strategy to eliminate immune rejection. However, no complete single-cell level differentiation pathway exists for the iPSC-derived RBC differentiation system. In this study, we used iPSC line BC1 to establish a RBCs regeneration system. The 10x genomics single-cell transcriptome platform was used to map the cell lineage and differentiation trajectories on day 14 of the regeneration system. We observed that iPSCs differentiation was not synchronized during embryoid body (EB) culture. The cells (day 14) mainly consisted of mesodermal and various blood cells, similar to the yolk sac hematopoiesis. We identified six cell classifications and characterized the regulatory transcription factors (TFs) networks and cell-cell contacts underlying the system. iPSCs undergo two transformations during the differentiation trajectory, accompanied by the dynamic expression of cell adhesion molecules and estrogen-responsive genes. We identified different stages of erythroid cells such as burst-forming unit erythroid (BFU-E) and orthochromatic erythroblasts (ortho-E) and found that the regulation of TFs (e.g., TFDP1 and FOXO3) is erythroid-stage specific. Immune erythroid cells were identified in our system. This study provides systematic theoretical guidance for optimizing the iPSCs-derived RBCs differentiation system, and this system is a useful model for simulating in vivo hematopoietic development and differentiation.


title: Bacterial lipopolysaccharide induces settlement and metamorphosis in a marine larva

abstract:
How larvae of the many phyla of marine invertebrates find places appropriate for settlement, metamorphosis, growth and reproduction is an enduring question in marine science. Biofilm induced metamorphosis has been observed in marine invertebrate larvae from nearly every major marine phylum. Despite the widespread nature of this phenomenon the mechanism of induction remains poorly understood. The serpulid polychaete Hydroides elegans is a well-established model for investigating bacteria-induced larval development. A broad range of biofilm bacterial species elicit larval metamorphosis in H. elegans via at least two mechanisms, including outer membrane vesicles and phage-tail bacteriocins. We investigated the interaction between larvae of H. elegans and the inductive bacterium Cellulophaga lytica, which produces an abundance of OMVs but not phage-tail bacteriocins. We asked whether the OMVs of C. lytica induce larval settlement due to cell membrane components or through delivery of specific cargo. Employing a biochemical structure-function approach with a strong ecological focus, the cells and outer membrane vesicles produced by C. lytica were interrogated to determine the nature of the inductive molecule. Here we report that the cue produced by C. lytica that induces larvae of H. elegans to metamorphose is lipopolysaccharide (LPS). The widespread prevalence of LPS and its associated taxonomic and structural variability suggest it may be a broadly employed cue for bacterially induced larval settlement of marine invertebrates.

Significance StatementNew surfaces in the sea are quickly populated by dense communities of invertebrate animals, whose establishment and maintenance require site-specific settlement of larvae from the plankton. Although it is recognized that larvae selectively settle in sites where they can metamorphose and thrive, and that the biofilm bacteria residing on these surfaces supply inductive cues, the nature of the cues used to identify  right places has remained enigmatic. In this paper, we reveal that lipopolysaccharide (LPS) from the outer membrane of a marine Gram-negative bacterium cue metamorphosis for a marine worm and discuss the likelihood that LPS provides the variation necessary to explain settlement site selectivity for many of the bottom-living invertebrate animals that metamorphose in response to bacterial biofilms.


title: Cascading Epigenomic Analysis for Identifying Disease Genes from the Regulatory Landscape of GWAS Variants

abstract:
The majority of genetic variants detected in genome wide association studies (GWAS) exert their effects on phenotypes through gene regulation. Motivated by this observation, we propose a multi-omic integration method that models the cascading effects of genetic variants from epigenome to transcriptome and eventually to the phenome in identifying target genes influenced by risk alleles. This cascading epigenomic analysis for GWAS, which we refer to as CEWAS, comprises two types of models: one for linking cis genetic effects to epigenomic variation and another for linking cis epigenomic variation to gene expression. Applying these models in cascade to GWAS summary statistics generates gene level statistics that reflect genetically-driven epigenomic effects. We show on sixteen brain-related GWAS that CEWAS provides higher gene detection rate than related methods, and finds disease relevant genes and gene sets that point toward less explored biological processes. CEWAS thus presents a novel means for exploring the regulatory landscape of GWAS variants in uncovering disease mechanisms.

SummaryThe majority of genetic variants detected in genome wide association studies (GWAS) exert their effects on phenotypes through gene regulation. Motivated by this observation, we propose a multi-omic integration method that models the cascading effects of genetic variants from epigenome to transcriptome and eventually to the phenome in identifying target genes influenced by risk alleles. This cascading epigenomic analysis for GWAS, which we refer to as CEWAS, combines the effect of genetic variants on DNA methylation as well as gene expression. We show on sixteen brain-related GWAS that CEWAS provides higher gene detection rate than related methods, and finds disease relevant genes and gene sets that point toward less explored biological processes.


title: Genetic Association Study of Childhood Aggression across raters, instruments and age

abstract: Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data - i.e. within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE=0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P=1.6E-06), PCDH7 (P=2.0E-06) and IPO13 (P=2.5E-06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg =0.46 between self- and teacher-assessment to rg =0.81 between mother- and teacher-assessment. We obtained moderate to strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range |rg| : 0.19 - 1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg =~ -0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range |rg| : 0.46 - 0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.


title: Constitutively enhanced genome integrity maintenance and direct stress mitigation characterize transcriptome of extreme stress-adapted Arabidopsis halleri

abstract: Heavy metal-rich toxic soils and ordinary soils are both natural habitats of Arabidopsis halleri. The molecular divergence underlying survival in sharply contrasting environments is unknown. Here we comparatively address metal physiology and transcriptomes of A. halleri originating from the most highly heavy metal-contaminated soil in Europe, Ponte Nossa (Noss/IT), and from non-metalliferous (NM) soil. Noss exhibits enhanced hypertolerance and attenuated accumulation of cadmium (Cd), and transcriptomic Cd responsiveness is decreased, compared to plants of NM soil origin. Among the condition-independent transcriptome characteristics of Noss, the most highly overrepresented functional class of "meiotic cell cycle" comprises 21 transcripts with elevated abundance in vegetative tissues, in particular Argonaute 9 (AGO9) and the synaptonemal complex transverse filament protein-encoding ZYP1a/b. Increased AGO9 transcript levels in Noss are accompanied by decreased long terminal repeat retrotransposon expression, and are shared by plants from milder metalliferous sites in Poland and Germany. Expression of Iron-regulated Transporter (IRT1) is very low and of Heavy Metal ATPase 2 (HMA2) strongly elevated in Noss, which can account for its specific Cd handling. In plants adapted to the most extreme abiotic stress, broadly enhanced functions comprise genes with likely roles in somatic genome integrity maintenance, accompanied by few alterations in stress-specific functional networks.


title: BitEpi: A Fast and Accurate Exhaustive Higher-Order Epistasis Search

abstract:
MotivationComplex genetic diseases may be modulated by a large number of epistatic interactions affecting a polygenic phenotype. Identifying these interactions is difficult due to computational complexity, especially in the case of higher-order interactions where more than two genomic variants are involved.

ResultsIn this paper, we present BitEpi, a fast and accurate method to test all possible combinations of up to four bi-allelic variants (i.e. Single Nucleotide Variant or SNV for short). BitEpi introduces a novel bitwise algorithm that is 2.1 and 56 times faster for 3-SNV and 4-SNV search, than established software. The novel entropy statistic used in BitEpi is 44% more accurate to identify interactive SNVs, incorporating a p-value-based significance testing. We demonstrate BitEpi on real world data of 4,900 samples and 87,000 SNPs. We also present EpiExplorer to visualize the potentially large number of individual and interacting SNVs in an interactive Cytoscape graph. EpiExplorer uses various visual elements to facilitate the discovery of true biological events in a complex polygenic environment.


title: A cross-nearest neighbor/Monte Carlo algorithm for single molecule localization microscopy defines interactions between p53, Mdm2, and MEG3

abstract: The functions of long noncoding (lnc)RNAs such as MEG3 are defined by their interactions with other RNAs and proteins. These interactions, in turn, are shaped by their subcellular localization and temporal context. Therefore, it is important to be able to analyze the relationships of lncRNAs while preserving cellular architecture. The ability of MEG3 to suppress cell proliferation led to its recognition as a tumor suppressor. MEG3 has been proposed to activate p53 by disrupting the interaction of p53 with Mdm2. To test this mechanism in the native cellular context, we employed two-color direct stochastic optical reconstruction microscopy (dSTORM), a single-molecule localization microscopy (SMLM) technique to detect and quantify the localizations of p53, Mdm2, and MEG3 in U2OS cells. We developed a new cross-nearest neighbor/Monte Carlo algorithm to quantify the association of these molecules. Proof of concept for our method was obtained by examining the association between FKBP1A and mTOR, MEG3 and p53, and Mdm2 and p53. In contrast to previous models, our data support a model in which MEG3 modulates p53 independently of the interaction with Mdm2.


title: Astral microtubule crosslinking by Feo safeguards uniform nuclear distribution in the Drosophila syncytium

abstract: The early insect embryo develops as a multinucleated cell distributing the genome uniformly to the cell cortex. Mechanistic insight for nuclear positioning beyond cytoskeletal requirements is missing. Contemporary hypotheses propose actomyosin driven cytoplasmic movement transporting nuclei, or repulsion of neighbor nuclei driven by microtubule motors. Here, we show that microtubule crosslinking by Feo and Klp3A is essential for nuclear distribution and internuclear distance maintenance in Drosophila. Germline knockdown causes irregular, less dense nuclear delivery to the cell cortex and smaller distribution in ex vivo embryo explants. A minimal internuclear distance is maintained in explants from control embryos but not from Feo inhibited embryos, following micromanipulation assisted repositioning. A dimerization deficient Feo abolishes nuclear separation in embryo explants while the full-length protein rescues the genetic knockdown. We conclude that Feo and Klp3A crosslinking of antiparallel microtubule overlap generates a length-regulated mechanical link between neighboring microtubule asters. Enabled by a novel experimental approach, our study illuminates an essential process of embryonic multicellularity.


title: Advancing motion denoising of multiband resting state functional connectivity fMRI data

abstract: Simultaneous multi-slice (multiband) accelerated functional magnetic resonance imaging (fMRI) provides dramatically improved temporal and spatial resolution for resting-state functional connectivity (RSFC) studies of the human brain in health and disease. However, multiband acceleration also poses unique challenges for denoising of subject motion induced data artifacts, the presence of which is a major confound in RSFC research that substantively diminishes reliability and reproducibility. We comprehensively evaluated existing and novel approaches to volume censoring-based motion denoising in the Human Connectome Project (HCP) dataset. We show that assumptions underlying common metrics for evaluating motion denoising pipelines, especially those based on quality control-functional connectivity (QC-FC) correlations and differences between high- and low-motion participants, are problematic, and appear to be inappropriate in their current widespread use as indicators of comparative pipeline performance and as targets for investigators to use when tuning pipelines for their own datasets. We further develop two new quantitative metrics that are instead agnostic to QC-FC correlations and other measures that rely upon the null assumption that no true relationships exist between trait measures of subject motion and functional connectivity, and demonstrate their use as benchmarks for comparing volume censoring methods. Finally, we develop and validate quantitative methods for determining dataset-specific optimal volume censoring parameters prior to the final analysis of a dataset, and provide straightforward recommendations and code for all investigators to apply this optimized approach to their own RSFC datasets.


title: Advancing motion denoising of multiband resting-state functional connectivity fMRI data


title: 17q21.31 sub-haplotypes underlying H1-associated risk for Parkinsons disease are associated with LRRC37A/2 expression in astrocytes

abstract: Parkinsons disease (PD) is genetically associated with the H1 haplotype of the MAPT 17q.21.31 locus, although the causal gene and variants underlying this association have not been identified. To better understand the genetic contribution of this region to PD, we fine-mapped the 17q21.31 locus in order to identify novel mechanisms conferring risk for the disease. We identified three novel H1 sub-haplotype blocks across the 17q21.31 locus associated with PD risk. Protective sub-haplotypes were associated with increased LRRC37A/2 copy number and expression in human brain tissue. We found that LRRC37A/2 is a membrane-associated protein that plays a role in cellular migration, chemotaxis and astroglial inflammation. In human substantia nigra, LRRC37A/2 was primarily expressed in astrocytes, interacted directly with soluble -synuclein, and co-localized with Lewy bodies in PD brain tissue. These data indicate that a novel candidate gene, LRRC37A/2, contributes to the association between the 17q21.31 locus and PD via its interaction with -synuclein and its effects on astrocytic function and inflammatory response. These data are the first to associate the genetic association at the 17q21.31 locus with PD pathology, and highlight the importance of variation at the 17q21.31 locus in the regulation of multiple genes other than MAPT and KANSL1, as well as its relevance to non-neuronal cell types.