title: Environmental stressors induced strong small-scale phenotypic differentiation in a wide-dispersing marine snail

abstract: Heterogeneous environments pose a particular challenge for organisms because the same phenotype is unlikely to perform best regardless of the variety of encountered stressors. To understand how species meet this challenge, we investigated the extent to which contrasting environmental pressures induced ecological and phenotypic responses in a natural population of a wide-dispersing marine snail at a small spatial scale. We analyzed several traits of Heleobia australis (Rissooidea: Cochliopidae) collected from heterogeneous, but highly connected, habitats from the intertidal area of the Bahia Blanca estuary, Argentina. We also conducted molecular analyses by amplifying the COI gene in individuals sampled from each habitat. We found that sympatric subpopulations of H. australis exhibited a strong phenotypic divergence in shell characters and body weight in response to thermal, saline, and dehydration stress, crab predation risk, and parasitic castrators. We proved that this differentiation occurred even early in life as most of the characters observed in juveniles mirrored those found in adults. We also found a divergence in penis size in snails collected from each habitat and raised in common garden laboratory conditions. The molecular analyses confirmed that the individuals studied constituted a single species despite the strong phenotypic differences among subpopulations. The small-scale phenotypic differentiation suggests that H. australis experienced a fine-grained environment where conditions imposed by different sources of stress favored the expression of beneficial traits. We discuss the role of plasticity in shaping adaptive phenotypic responses that increase the likelihood of persistence of subpopulations facing environmental stress conditions.


title: Impulsivity and risk-seeking as Bayesian inference under dopaminergic control

abstract: Bayesian models successfully account for several of dopamine (DA)s effects on contextual calibration in interval timing and reward estimation. In these models, tonic levels of DA control the precision of stimulus encoding, which is weighed against contextual information when making decisions. When DA levels are high, the animal relies more heavily on the (highly precise) stimulus encoding, whereas when DA levels are low, the context affects decisions more strongly. Here, we extend this idea to intertemporal choice and probability discounting tasks. In intertemporal choice tasks, agents must choose between a small reward delivered soon and a large reward delivered later, whereas in probability discounting tasks, agents must choose between a small reward that is always delivered and a large reward that may be omitted with some probability. Beginning with the principle that animals will seek to maximize their reward rates, we show that the Bayesian model predicts a number of curious empirical findings in both tasks. First, the model predicts that higher DA levels should normally promote selection of the larger/later option, which is often taken to imply that DA decreases  impulsivity, and promote selection of the large/risky option, often taken to imply that DA increases  risk-seeking. However, if the temporal precision is sufficiently decreased, higher DA levels should have the opposite effect--promoting selection of the smaller/sooner option (higher impulsivity) and the small/safe option (lower risk-seeking). Second, high enough levels of DA can result in preference reversals. Third, selectively decreasing the temporal precision, without manipulating DA, should promote selection of the larger/later and large/risky options. Fourth, when a different post-reward delay is associated with each option, animals will not learn the option-delay contingencies, but this learning can be salvaged when the post-reward delays are made more salient. Finally, the Bayesian model predicts correlations among behavioral phenotypes: Animals that are better timers will also appear less impulsive.

category: neuroscience


title: Genome evolution in an agricultural pest following adoption of transgenic crops

abstract:
Replacement of synthetic insecticides with transgenic crops for pest management has been both economically and environmentally beneficial. These benefits have often eroded as pests evolved resistance to transgenic crops, but a broad understanding of the timing and complexity of adaptive changes which lead to field-evolved resistance in pest species is lacking. Wild populations of Helicoverpa zea, a major lepidopteran crop pest and the target of transgenic Cry toxin-expressing cotton and corn, have recently evolved widespread, damaging levels of resistance. Here, we quantified patterns of genomic change in wild H. zea collected between 2002 and 2017 when adoption rates of Cry-expressing crops expanded in North America. Using a combination of genomic approaches, we identified significant temporal changes in allele frequency throughout the genomes of field-collected H. zea. Many of these changes occurred concurrently with increasingly damaging levels of resistance to Cry toxins between 2012 and 2016, in a pattern consistent with polygenic selection. Surprisingly, none of the eleven previously described Cry resistance genes showed signatures of selection in wild H. zea. Furthermore, we observed evidence of a very strong selective sweep in one region of the H. zea genome, yet this strongest change was not additively associated with Cry resistance. This first, whole genome analysis of field-collected specimens to study evolution of Cry resistance demonstrates the potential and need for a more holistic approach to examining pest adaptation to changing agricultural practices.

Significance StatementEvolution of pest resistance to management approaches in agricultural landscapes is common and results in economic losses. Early detection of pest resistance evolution prior to significant crop damage would benefit the agricultural community. It has been hypothesized that new genomic approaches could track molecular signals of emerging resistance problems and trigger efforts to pre-empt widespread damage. We tested this hypothesis by quantifying genomic changes in the pest Helicoverpa zea over a 15 year period concurrent with commercialization and subsequent loss of efficacy of transgenic Bt-expressing crops. Our results demonstrate the complex nature of evolution in agricultural ecosystems and provide insight into the potential for and pitfalls associated with use of genomic approaches for resistance monitoring. We discuss approaches for improvement.

category: evolutionary biology


title: A model for learning based on the joint estimation of stochasticity and volatility

abstract: Previous research has stressed the importance of uncertainty for controlling the speed of learning, and of how such control depends on the learner inferring the noise properties of the environment, especially volatility: the speed of change. However, learning rates are jointly determined by the comparison between volatility and a second factor, moment-to-moment stochasticity. Yet much previous research has focused on simplified cases corresponding to estimation of either factor alone. Here, we introduce a new learning model, in which both factors are learned simultaneously from experience. By considering the full problem of joint estimation, we highlight a set of previously unappreciated issues, arising from the mutual interdependence of inference about volatility and stochasticity. This interdependence both complicates and enriches the interpretation of previous results, such as those thought to implicate volatility in psychiatric conditions. This provides a novel mechanism for understanding pathological learning in amygdala damage and anxiety disorders.


title: Generalization in data-driven models of primary visual cortex

abstract: AO_SCPLOWBSTRACTC_SCPLOWDeep neural networks (DNN) have set new standards at predicting responses of neural populations to visual input. Most such DNNs consist of a convolutional network (core) shared across all neurons which learns a representation of neural computation in visual cortex and a neuron-specific readout that linearly combines the relevant features in this representation. The goal of this paper is to test whether such a representation is indeed generally characteristic for visual cortex, i.e. gener-alizes between animals of a species, and what factors contribute to obtaining such a generalizing core. To push all non-linear computations into the core where the generalizing cortical features should be learned, we devise a novel readout that reduces the number of parameters per neuron in the readout by up to two orders of magnitude compared to the previous state-of-the-art. It does so by taking advantage of retinotopy and learns a Gaussian distribution over the neurons receptive field po-sition. With this new readout we train our network on neural responses from mouse primary visual cortex (V1) and obtain a gain in performance of 7% compared to the previous state-of-the-art network. We then investigate whether the convolutional core indeed captures general cortical features by using the core in transfer learning to a different animal. When transferring a core trained on thousands of neurons from various animals and scans we exceed the performance of training directly on that animal by 12%, and outperform a commonly used VGG16 core pre-trained on imagenet by 33%. In addition, transfer learning with our data-driven core is more data-efficient than direct training, achieving the same performance with only 40% of the data. Our model with its novel readout thus sets a new state-of-the-art for neural response prediction in mouse visual cortex from natural images, generalizes between animals, and captures better characteristic cortical features than current task-driven pre-training approaches such as VGG16.


title: Conformational Dynamics of NSP11 Peptide of SARS-CoV-2 Under Membrane Mimetics and Different Solvent Conditions

abstract: The intrinsically disordered proteins/regions (IDPs/IDPRs) are known to be responsible for multiple cellular processes and are associated with many chronic diseases. In viruses, the existence of a disordered proteome is also proven and is related to its conformational dynamics inside the host. The SARS-CoV-2 has a large proteome, in which, structure and functions of many proteins are not known yet, along with nsp11. In this study, we have performed extensive experimentation on nsp11. Our results based on the CD spectroscopy gives characteristic disordered spectrum for IDPs. Further, we investigated the conformational behavior of nsp11 in the presence of membrane mimetic environment, -helix inducer, and natural osmolyte. In the presence of negatively charged and neutral liposomes, nsp11 remains disordered. However, with SDS micelle, it adopted an -helical conformation, suggesting the helical propensity of nsp11. Finally, we again confirmed the IDP behavior of nsp11 using MD simulations. In future, this conformational dynamic study could help to clarify its functional importance in SARS-CoV-2 infection.

category: biochemistry


title: Functional Characterization of an Electromagnetic Perceptive Protein

abstract:
Magnetoreception, the response to geomagnetic fields is a well described phenomenon in nature. However, it is likely that convergent evolution led to different mechanisms in different organisms. One intriguing example is the unique Electromagnetic Perceptive Gene (EPG) from the glass catfish Kryptopterus vitreolus, that can remotely control cellular function, upon magnetic stimulation in in-vitro and in-vivo. Here, we report for the first time the cellular location and orientation of the EPG protein. We utilized a differential labelling technique to determine that the EPG protein is a membrane anchored protein with an N-terminal extracellular domain. The kinetics and diffusion dynamics of the EPG protein in response to magnetic stimulation was also elucidated using single particle imaging and tracking. Pulse chase labelling and Total Internal Reflection Fluorescence (TIRF) imaging revealed an increase in EPG kinetics post magnetic activation at a single particle level. Trajectory analysis show notably different EPG protein kinetics before and after magnetic stimulation in both 2 (free vs bound particle) and 3 state (free vs intermediate vs bound particle) tracking models. This data provides additional information to support and understand the underlying biophysical mechanisms behind EPG activation by magnetic fields and provides evidence for the basis of magnetoreception in the EPG protein that will aid in future studies that seek to further understand this novel mechanism. This study is important for understanding magnetoreception as well as developing new technologies for magnetogenetics - the utilization of electromagnetic fields to remotely control cellular function.

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category: synthetic biology


title: Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure

abstract: Numerous genome-wide association studies (GWAS) conducted to date revealed genetic variants associated with various diseases, including breast and prostate cancers. Despite the availability of these large-scale data, relatively few variants have been functionally characterized, mainly because the majority of single-nucleotide polymorphisms (SNPs) map to the non-coding regions of the human genome. The functional characterization of these non-coding variants and the identification of their target genes remain challenging. In this communication, we explore the potential functional mechanisms of non-coding SNPs by integrating GWAS with the high-resolution chromosome conformation capture (Hi-C) data for breast and prostate cancers. We show that more genetic variants map to regulatory elements through the 3D genome structure than the 1D linear genome lacking physical chromatin interactions. Importantly, the association of enhancers, transcription factors, and their target genes with breast and prostate cancers tends to be higher when these regulatory elements are mapped to high-risk SNPs through spatial interactions compared to simply using a linear proximity. Finally, we demonstrate that topologically associating domains (TADs) carrying high-risk SNPs also contain gene regulatory elements whose association with cancer is generally higher than those belonging to control TADs containing no high-risk variants. Our results suggest that many SNPs may contribute to the cancer development by affecting the expression of certain tumor-related genes through long-range chromatin interactions with gene regulatory elements. Integrating large-scale genetic datasets with the 3D genome structure offers an attractive and unique approach to systematically investigate the functional mechanisms of genetic variants in disease risk and progression.

category: genomics


title: VPS13D bridges the ER to Miro containing membranes

abstract:
Mitochondria, which are excluded from the secretory pathway, depend on lipid transport proteins for their lipid supply from the ER, where most lipids are synthesized. In yeast, the outer mitochondrial membrane GTPase Gem1 is an accessory factor of ERMES, an ER-mitochondria tethering complex that contains lipid transport domains and that functions, partially redundantly with Vps13, in lipid transfer between the two organelles. In metazoa, where VPS13, but not ERMES, is present, the Gem1 orthologue Miro was linked to mitochondria dynamics but not to lipid transport. Here we show that Miro, including its peroxisome-enriched splice variant, recruits the lipid transport protein VPS13D, which in turn binds the ER in a VAP-dependent way and thus could provide a lipid conduit between the ER and mitochondria. These findings reveal a so far missing link between function(s) of Gem1/Miro in yeast and higher eukaryotes, where Miro is a Parkin substrate, with potential implications for Parkinsons disease pathogenesis.

SummaryVPS13D mutations result in severe mitochondrial defects. Guillen-Samander et al, show that VPS13D binds VAP in the ER, and interacts with Miro on mitochondria and peroxisomes, so that it can provide a bridge for lipid transport between these organelles.

category: cell biology


title: Pescoids and chimeras to probe early evo-devo in the fish Astyanax mexicanus

abstract: The fish species Astyanax mexicanus with its sighted and blind eco-morphotypes has become an original model to challenge vertebrate developmental evolution. Recently, we demonstrated that phenotypic evolution can be impacted by early developmental events starting from the production of oocytes in the fish ovaries. A. mexicanus offers an amenable model to test the influence of maternal effect on cell fate decisions during early development, yet the mechanisms by which the information contained in the eggs is translated into specific developmental programs remain obscure due to the lack of specific tools in this emergent model. Here we describe methods for the generation of gastruloids from yolkless-blastoderm explants to test the influence of embryonic and extraembryonic properties on cell fate decisions, as well as the production of chimeric embryos obtained by intermorph cell transplantations to probe cell autonomous or non-autonomous processes. We show that Astyanax gastruloids have the potential to recapitulate the main ontogenetic events observed in intact embryos, including the internalization of mesodermal progenitors and eye development, as followed with Zic:GFP reporter lines. In addition, intermorph cell grafts resulted in proper integration of exogenous cells into the embryonic tissues, with lineages becoming more restricted from mid-blastula to gastrula. The implementation of these approaches in A. mexicanus will bring new light on the cascades of events, from the maternal pre-patterning of the early embryo to the evolution of brain regionalization.

category: developmental biology


title: Tractography dissection variability: what happens when 42 groups dissect 14 white matter bundles on the same dataset?

abstract: White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.


title: The cis-regulatory effects of modern human-specific variants

abstract: The Neanderthal and Denisovan genomes enabled the discovery of sequences that differ between modern and archaic humans, the majority of which are noncoding. However, our understanding of the regulatory consequences of these differences remains limited, in part due to the decay of regulatory marks in ancient samples. Here, we used a massively parallel reporter assay in embryonic stem cells, neural progenitor cells and bone osteoblasts to investigate the regulatory effects of the 14,042 single-nucleotide modern human-specific variants. Overall, 1,791 (13%) of sequences containing these variants showed active regulatory activity, and 407 (23%) of these drove differential expression between human groups. Differentially active sequences were associated with divergent transcription factor binding motifs, and with genes enriched for vocal tract and brain anatomy and function. This work provides insight into the regulatory function of variants that emerged along the modern human lineage and the recent evolution of human gene expression.


title: Developmental effects of oxytocin neurons on social affiliation and processing of social information

abstract:
Hormones regulate behavior either through activational effects that facilitate the acute expression of specific behaviors or through organizational effects that shape the development of the nervous system thereby altering adult behavior. Much research has implicated the neuropeptide oxytocin (OXT) in acute modulation of various aspects of social behaviors across vertebrate species, and OXT signaling is associated with the developmental social deficits observed in autism spectrum disorders, however, little is known about the role of OXT in the neurodevelopment of the social brain. We show that perturbation of OXT neurons during early zebrafish development led to a loss of dopaminergic neurons, associated with visual processing and reward, and blunted the neuronal response to social stimuli in the adult brain. Ultimately, adult fish whose OXT neurons were ablated in early life, displayed altered functional connectivity within social decision-making brain nuclei both in naive state and in response to social stimulus and became less social. We propose that OXT neurons have an organizational role, namely to shape forebrain neuroarchitecture during development and to acquire an affiliative response towards conspecifics.

Significance StatementSocial behavior is developed over the lifetime of an organism and the neuropeptide oxytocin modulates social behaviors across vertebrate species, and is associated with neuro-developmental social deficits such as autism. However, whether oxytocin plays a role in the developmental maturation of neural systems that are necessary for social behavior remains poorly explored. We show that proper behavioral and neural response to social stimuli depends on a developmental process orchestrated by oxytocin neurons. Animals whose oxytocin system is ablated in early life show blunted neuronal and behavioral responses to social stimuli as well as wide ranging disruptions in the functional connectivity of the Social Brain. We provide a window into the mechanisms underlying oxytocin-dependent developmental processes that implement adult sociality.


title: Ablation of Proliferating Osteoblast Lineage Cells After Fracture Leads to Atrophic Nonunion in a Mouse Model

abstract: Nonunion is defined as the permanent failure of a fractured bone to heal, often necessitating surgical intervention. Atrophic nonunions are a subtype that are particularly difficult to treat. Animal models of atrophic nonunion are available; however, these require surgical or radiation-induced trauma to disrupt periosteal healing. These methods are invasive and not representative of many clinical nonunions where osseous regeneration has been arrested by a "failure of biology". We hypothesized that arresting osteoblast cell proliferation after fracture would lead to atrophic nonunion in mice. Using mice that express a thymidine kinase (tk) "suicide gene" driven by the 3.6Col1a1 promoter (Col1-tk), proliferating osteoblast lineage cells can be ablated upon exposure to the nucleoside analog ganciclovir (GCV). Wild-type (WT; control) and Col1-tk littermates were subjected to a full femur fracture and intramedullary fixation at 12 weeks age. We confirmed abundant tk+ cells in fracture callus of Col-tk mice dosed with water or GCV, specifically many osteoblasts, osteocytes, and chondrocytes at the cartilage-bone interface. Histologically, we observed altered callus composition in Col1-tk mice at 2 and 3 weeks post fracture, with significantly less bone and more fibrous tissue. Col1-tk mice, monitored for 12 weeks with in vivo radiographs and microCT scans, had delayed bone bridging and reduced callus size. Following sacrifice, ex vivo microCT and histology demonstrated failed union with residual bone fragments and fibrous tissue in Col1-tk mice. Biomechanical testing demonstrated a failure to recover torsional strength in Col1-tk mice, in contrast to WT. Our data indicates that suppression of proliferating osteoblast-lineage cells for at least 2 weeks after fracture blunts the formation and remodeling of a mineralized callus leading to a functional nonunion. We propose this as a new murine model of atrophic nonunion.

category: bioengineering


title: Synthesis and single-molecule imaging reveal stereospecific enhancement of binding kinetics by the antitumor eEF1A antagonist SR-A3

abstract: Ternatin-family cyclic peptides inhibit protein synthesis by targeting the eukaryotic elongation factor-1 (eEF1A). A potentially related cytotoxic natural product ("A3") was isolated from Aspergillus, but only 4 of its 11 stereocenters could be assigned. Here, we synthesized SR-A3 and SS-A3 - two out of 128 possible A3 epimers - and discovered that synthetic SR-A3 is indistinguishable from naturally derived A3. Relative to SS-A3, SR-A3 exhibits enhanced residence time and rebinding kinetics, as revealed by single-molecule fluorescence imaging of elongation reactions catalyzed by eEF1A in vitro. Increased residence time - stereospecifically conferred by the unique {beta}-hydroxyl in SR-A3 - was also observed in cells. Consistent with its prolonged duration of action, thrice-weekly dosing with SR-A3 led to dramatically increased survival in an aggressive Myc-driven mouse lymphoma model. Our results demonstrate the potential of SR-A3 as a cancer therapeutic and exemplify an evolutionary mechanism for enhancing cyclic peptide binding kinetics via stereospecific side-chain hydroxylation.

category: pharmacology and toxicology


title: Evaluating state space discovery by persistent cohomology in the spatial representation system

abstract: Persistent cohomology is a powerful technique for discovering topological structure in data. Strategies for its use in neuroscience are still undergoing development. We comprehensively and rigorously assess its performance in simulated neural recordings of the brains spatial representation system. Grid, head direction, and conjunctive cell populations each span low-dimensional topological structures embedded in high-dimensional neural activity space. We evaluate the ability for persistent cohomology to discover these structures for different dataset dimensions, variations in spatial tuning, and forms of noise. We quantify its ability to decode simulated animal trajectories contained within these topological structures. We also identify regimes under which mixtures of populations form product topologies that can be detected. Our results reveal how dataset parameters affect the success of topological discovery and suggest principles for applying persistent cohomology, as well as persistent homology, to experimental neural recordings.


title: Uncertainty is Maintained and Used in Working Memory

abstract: 1What are the contents of working memory? In both behavioral and neural computational models, a working memory representation is typically described by a single number, namely a point estimate of a stimulus. Here, we asked if people also maintain the uncertainty associated with a memory, and if people use this uncertainty in subsequent decisions. We collected data in a two-condition orientation change detection task; while both conditions measured whether people used memory uncertainty, only one required maintaining it. For each condition, we compared an optimal Bayesian observer model, in which the observer uses an accurate representation of uncertainty in their decision, to one in which the observer does not. We find that this "Use Uncertainty" model fits better for all participants in both conditions. In the first condition, this result suggests that people use uncertainty optimally in a working memory task when that uncertainty information is available at the time of decision, confirming earlier results. Critically, the results of the second condition suggest that this uncertainty information was maintained in working memory. We test model variants and find that our conclusions do not depend on our assumptions about the observers encoding process, inference process, or decision rule. Our results provide evidence that people have uncertainty that reflects their memory precision on an item-specific level, maintain this information over a working memory delay, and use it implicitly in a way consistent with an optimal observer. These results challenge existing computational models of working memory to update their frameworks to represent uncertainty.


title: Multiplane Mesoscope reveals distinct cortical interactions following expectation violations

abstract: Cortical columns interact through dynamic routing of neuronal activity. Monitoring these interactions in animals performing a behavioral task as close as possible to real time will advance our understanding of cortical computation. We developed the Multiplane Mesoscope which combines three established concepts in microscopy: spatio-temporal multiplexing, remote focusing, and random-access mesoscopy. With the Multiplane Mesoscope, we recorded excitatory and inhibitory neuronal subpopulations simultaneously across two cortical areas and multiple cortical layers in behaving mice. In the context of a visual detection of change task, we used this novel platform to study cortical areas interactions and quantified the cell-type specific distribution of neuronal correlations across a set of visual areas and layers. We found that distinct cortical subnetworks represent expected and unexpected visual events. Our findings demonstrate that expectation violations modify signal routing across cortical columns and establish the Allen Brain Observatory Multiplane Mesoscope as a unique platform to study signal routing across connected pairs of cortical areas.


title: Automated CUT&Tag profiling of chromatin heterogeneity in mixed-lineage leukemia

abstract: Acute myeloid and lymphoid leukemias often harbor chromosomal translocations involving the Mixed Lineage Leukemia-1 gene, encoding the KMT2A lysine methyltransferase. The most common translocations produce in-frame fusions of KMT2A to other chromatin regulatory proteins. Here we develop a strategy to map the genome-wide occupancy of oncogenic KMT2A fusion proteins in primary patient samples regardless of fusion partner. By modifying the versatile CUT&Tag method for full automation we identify common and tumor-specific patterns of aberrant chromatin regulation induced by different KMT2A fusion proteins. Integration of automated and single-cell CUT&Tag uncovers epigenomic heterogeneity within patient samples and predicts sensitivity to therapeutic agents.


title: BiSulfite Bolt: A BiSulfite Sequencing Analysis Platform

abstract:
BackgroundBisulfite sequencing is commonly employed to measure DNA methylation. Processing bisulfite sequencing data is often challenging due to the computational demands of mapping a low complexity, asymmetrical library and the lack of a unified processing toolset to produce an analysis ready methylation matrix from read alignments. To address these shortcomings, we have developed BiSulfite Bolt (BSBolt); a fast and scalable bisulfite sequencing analysis platform. BSBolt performs a pre-alignment sequencing read assessment step to improve efficiency when handling asymmetrical bisulfite sequencing libraries.

FindingsWe evaluated BSBolt against simulated and real bisulfite sequencing libraries. We found that BSBolt provides accurate and fast bisulfite sequencing alignments and methylation calls. We also compared BSBolt to several existing bisulfite alignment tools and found BSBolt outperforms Bismark, BSSeeker2, BISCUIT, and BWA-Meth based on alignment accuracy and methylation calling accuracy.

ConclusionBSBolt offers streamlined processing of bisulfite sequencing data through an integrated toolset that offers support for simulation, alignment, methylation calling, and data aggregation. BSBolt is implemented as a python package and command line utility for flexibility when building informatics pipelines. BSBolt is available at https://github.com/NuttyLogic/BSBolt under an MIT license.

category: bioinformatics


title: CancerVar: an Artificial Intelligence empowered platform for clinical interpretation of somatic mutations in cancer

abstract: Several knowledgebases, such as CIViC and OncoKB, have been manually curated to support clinical interpretations of a limited number of "hotspot" somatic mutations in cancer, yet discrepancies or even conflicting interpretations have been observed among these knowledgebases. Additionally, while these knowledgebases have been extremely useful, they typically cannot interpret novel mutations, which may also have functional and clinical impacts in cancer. To address these challenges, we developed an automated interpretation tool called CancerVar (Cancer Variants interpretation) to score more than 12.9 million somatic mutations and classify them into four tiers: strong clinical significance, potential clinical significance, uncertain clinical significance, and benign/likely benign, based on the AMP/ASCO/CAP 2017 guideline. Considering that the AMP/ASCO/CAP rule-based scoring system may have inherent limitations, such as lack of a clear guidance on weighing different pieces of functional evidence or unclear definition for certain clinical evidence, it may cause misinterpretation for certain variants that have functional impacts but no proven clinical significance. To address this issue, we further introduced a deep learning-based scoring system to predict oncogenicity of mutations by semi-supervised generative adversarial network (SGAN) method using both functional and clinical evidence. We trained and validated the SGAN model on 5,234 somatic mutations from an in-house database of clinical reports on cancer patients, and achieved a good performance when testing on 6,226 variants that were curated by us through literature search. We also compared the prediction with several independent datasets and showed great utility in classifying variants with previously unknown interpretations. CancerVar is also incorporated into a web server that can generate automated texts with summarized descriptive interpretations, such as diagnostic, prognostic, targeted drug responses and clinical trial information for many hotspot mutations. In summary, CancerVar can facilitate clinical interpretation and hypothesis generation for somatic mutations, and greatly reduce manual workload for retrieving relevant evidence and implementing existing guidelines.

category: cancer biology


title: A critical role of stable grain filling rate in maximizing rice yield revealed by whole plant carbon nitrogen interaction modeling

abstract: Crop yield is co-determined by potential size of the harvest organ, photosynthetic potential of source organs, and pattern of partitioning and use of photosynthates among sink organs. Given a sufficient potential size of the harvest organ at flowering, how to fully fill them remains a central challenge in crop breeding for high yields. Here, we develop a kinetic model of rice grain filling, scaling primary biochemical and biophysical processes to whole-plant carbon and nitrogen dynamics. Predicted post-anthesis physiological and agronomic behaviors validate experimental observations under six endogenous and external perturbations. By large scale in silico screening, we show here that a stable grain filling rate from flowering to harvest is required to maximize grain yield, which is validated here in two independent super-high yielding rice cultivars (~21 t ha-1 rough rice yield at 14% moisture). On the other hand, we show grain yields in an elite rice cultivar may increase by about 30-40% by stabilizing its grain filling rate. Intriguingly, we have found that the sum of grain filling rates around 15 and 38 days after flowering largely determines grain yield, and have further developed a novel in situ approach quantifying grain filling rates and grain yield precisely with the measurements of ear respiratory rates (r>0.93). Potential post-anthesis molecular targets to maximize rice yield include delaying leaf senescence, enhancing leaf sucrose synthesis and export, limiting root growth, strengthening stem starch synthesis, accelerating endosperm starch synthesis, and moderating endosperm cell division. Our study provides an effective computational framework for post-anthesis crop physiology research and ideotype design.

category: plant biology


title: Large-scale societal dynamics are reflected in human mood and brain

abstract: The stock market is a bellwether of socio-economic changes that may directly affect individual well-being. Using large-scale UK-biobank data generated over 14 years, we applied specification curve analysis to rigorously identify significant associations between the local stock market index (FTSE100) and 479,791 UK residents mood, as well as their alcohol intake and blood pressure adjusting the results for a large number of potential confounders, including age, sex, linear and non-linear effects of time, research site, other stock market indexes. Furthermore, we found similar associations between FTSE100 and volumetric measures of affective brain regions in a subsample (n=39,755; measurements performed over 5.5 years), which were particularly strong around phase transitions characterized by maximum volatility in the market. The main findings did not depend on applied effect-size estimation criteria (linear methods or mutual information criterion) and were replicated in two independent US-based studies (Parkinsons Progression Markers Initiative; n=424; performed over 2,5 years and MyConnectome; n=1; 81 measurements over 1,5 years). Our results suggest that phase transitions in the society, indexed by stock market, exhibit close relationships with human mood, health and the affective brain from an individual to population level.


title: Evidence accumulation, not "self-control," explains dorsolateral prefrontal activationduring normative choice

abstract: What role do cognitive control regions like the dorsolateral prefrontal cortex (dlPFC) play in normative behavior (e.g., generosity, healthy eating)? Some models suggest that dlPFC activation during normative choice reflects the use of control to overcome default hedonistic preferences. Here, we develop an alternative account, showing that an attribute-based neural drift diffusion model (anDDM) predicts trial-by-trial variation in dlPFC response across three fMRI studies and two self-control contexts (altruistic sacrifice and healthy eating). Using the anDDM to simulate a variety of self-control dilemmas generated a novel prediction: although dlPFC activity might typically increase for norm-consistent choices, deliberate self-regulation focused on normative goals should decrease or even reverse this pattern (i.e., greater dlPFC response for hedonic, self-interested choices). We confirmed these predictions in both altruistic and dietary choice contexts. Our results suggest that dlPFC response during normative choice may depend more on value-based evidence accumulation than inhibition of our baser instincts.


title: Creating Clear and Informative Image-based Figures for Scientific Publications

abstract: Scientists routinely use images to display data. Readers often examine figures first; therefore, it is important that figures are accessible to a broad audience. Many resources discuss fraudulent image manipulation and technical specifications for image acquisition; however, data on the legibility and interpretability of images are scarce. We systematically examined these factors in non-blot images published in the top 15 journals in three fields; plant sciences, cell biology and physiology (n=580 papers). Common problems included missing scale bars, misplaced or poorly marked insets, images or labels that were not accessible to colorblind readers, and insufficient explanations of colors, labels, annotations, or the species and tissue or object depicted in the image. Papers that met all good practice criteria examined for all image-based figures were uncommon (physiology 16%, cell biology 12%, plant sciences 2%). We present detailed descriptions and visual examples to help scientists avoid common pitfalls when publishing images. Our recommendations address image magnification, scale information, insets, annotation, and color and may encourage discussion about quality standards for bioimage publishing.


title: Phosphoproteomics identifies PI3K inhibitor-selective adaptive responses in pancreatic cancer cell therapy and resistance

abstract:
The PI3K pathway is highly active in human cancers. The four class I isoforms of PI3K are activated by distinct mechanisms leading to a common downstream signaling. Their downstream redundancy is thought to be responsible for treatment failures of PI3K inhibitors. We challenged this concept, by mapping the differential phosphoproteome evolution in response to PI3K inhibitors with different isoform selectivity patterns in pancreatic cancer, a disease currently without effective therapy. In this cancer, the PI3K signal was shown to control cell proliferation. We compared the effects of LY294002 that inhibit with equal potency all class I isoenzymes and downstream mTOR with the action of inhibitors with higher isoform-selectivity towards PI3K, PI3K{beta} or PI3K{gamma} (namely A66, TGX-221 and AS-252424). A bioinformatics global pathway analysis of phosphoproteomics data allowed us to identify common and specific signals activated by PI3K inhibitors supported by the biological data. AS-252424 was the most effective treatment and induced apoptotic pathway activation as well as the highest changes in global phosphorylation-regulated cell signal. However, AS-252424 treatment induced re-activation of Akt, therefore decreasing the treatment outcome on cell survival. Reversely, AS-252424 and A66 combination treatment prevented p-Akt reactivation and led to synergistic action in cell lines and patient organoids. The combination of clinically approved -selective BYL-719 with {gamma}-selective IPI-549 was more efficient than single molecule treatment on xenograft growth. Mapping unique adaptive signaling responses to isoform-selective PI3K inhibition will help to design better combinative treatments that prevent the induction of selective compensatory signals.

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/313833v3_ufig1.gif" ALT="Figure 1">
View larger version (29K):
org.highwire.dtl.DTLVardef@32004eorg.highwire.dtl.DTLVardef@b22f25org.highwire.dtl.DTLVardef@352a98org.highwire.dtl.DTLVardef@7f97a1_HPS_FORMAT_FIGEXP  M_FIG C_FIG SignificanceHalf of all human cancers show increased PI3K activity but the mutational pattern of the PI3K pathway is not sufficient to predict sensitivity to PI3K inhibitors. By identifying for the first time specific signaling induced by PI3K inhibitors with different isoform-selectivity patterns, we provide insight in how to handle heterogeneity of PI3K expression in tumor samples for the choice of available PI3K-targetting drugs. Our work provides a roadmap to target the PI3K pathway, balancing the use of isoform-selective PI3K inhibitors with personalized information extending beyond the specific mutational status.


title: Characterization of immunoactive and immunotolerant CD4+ T cells in breast cancer by measuring activity of signaling pathways that determine immune cell function

abstract:
Cancer immunotolerance can be reversed by checkpoint blockade immunotherapy in some patients, but response prediction remains a challenge. CD4+ T cells play an important role in activating adaptive immune responses against cancer. Conversion to an immune suppressive state impairs the anti-cancer immune response and is mainly effected by CD4+ Treg cells. A number of signal transduction pathways activate and control functions of CD4+ T cell subsets. As previously described, assays have been developed which enable quantitative measurement of the activity of signal transduction pathways (e.g. TGF{beta}, NF{kappa}B, PI3K-FOXO, JAK-STAT1/2, JAK-STAT3, Notch) in a cell or tissue sample. Using these assays, pathway activity profiles for various CD4+ T cell subsets were defined and cellular mechanisms underlying breast cancer-induced immunotolerance investigated in vitro. Results were used to measure the immune response state in a clinical breast cancer study.

MethodsSignal transduction pathway activity scores were measured on Affymetrix expression microarray data of resting and immune-activated CD4+ T cells, immune-activated CD4+ T cells incubated with breast cancer tissue supernatants, CD4+ Th1, Th2, and Treg cells, and of clinical study samples in which CD4+ T cells were derived from blood, lymph node and cancer tissue from primary breast cancer patients (n=10).

ResultsIn vitro CD4+ T cell activation induced PI3K, NF{kappa}B, JAK-STAT1/2, and JAK-STAT3 pathway activity. Simultaneous incubation with primary cancer supernatant reduced PI3K and NF{kappa}B, and partly reduced JAK-STAT3, pathway activity, while simultaneously increasing TGF{beta} pathway activity; characteristic of an immune tolerant state. CD4+ Th1, Th2, and Treg cells all had a specific pathway activity profile, with activated immune suppressive Treg cells characterized by high NF{kappa}B, JAK-STAT3, TGF{beta}, and Notch pathway activity scores. An immune tolerant pathway profile was identified in CD4+ T cells from tumor infiltrate of a subset of primary breast cancer patients which could be contributed to activated Treg cells. A Treg pathway profile was also identified in blood samples.

ConclusionSignaling pathway assays can be used to quantitatively measure the functional immune response state of lymphocyte subsets in vitro and in vivo. Clinical results suggest that in primary breast cancer the adaptive immune response of CD4+ T cells has frequently been replaced by immunosuppressive Treg cells, potentially causing resistance to checkpoint inhibition. In vitro study results suggest that this effect is mediated by soluble factors from cancer tissue (e.g. TGF{beta}). Signaling pathway activity analysis on TIL and/or blood samples is expected to improve predicting and monitoring response to checkpoint inhibitor immunotherapy.


title: When the ventral visual stream is not enough: A deep learning account of medial temporal lobe involvement in perception

abstract: The medial temporal lobe (MTL) supports a constellation of memory-related behaviors. Its involvement in perceptual processing, however, has been subject to enduring debate. This debate centers on perirhinal cortex (PRC), an MTL structure at the apex of the ventral visual stream (VVS). Here we leverage a deep learning framework that approximates visual behaviors supported by the VVS--i.e. lacking PRC. We first apply this approach retroactively, modeling 30 published visual discrimination experiments: Excluding non-diagnostic stimulus sets, there is a striking correspondence between VVS-modeled and PRC-lesioned behavior, while each are outperformed by PRC-intact participants. We corroborate and extend these results with a novel experiment, directly comparing PRC-intact human performance to electrophysiological recordings from the macaque VVS: PRC-intact participants outperform a linear readout of high-level visual cortex. By situating lesion, electrophysiological, and behavioral results within a shared computational framework, this work resolves decades of seemingly inconsistent findings surrounding PRC involvement in perception.


title: The Power of Social Information in Ant-Colony House-Hunting: A Computational Modeling Approach

abstract: The decentralized cognition of animal groups is both a challenging biological problem and a potential basis for bio-inspired design. The understanding of these systems and their application can benefit from modeling and analysis of the underlying algorithms. In this study, we define a modeling framework that can be used to formally represent all components of such algorithms. As an example application of the framework, we adapt to it the much-studied house-hunting algorithm used by emigrating colonies of Temnothorax ants to reach consensus on a new nest. We provide a Python simulator that encodes accurate individual behavior rules and produces simulated behaviors consistent with empirical observations, on both the individual and group levels. Critically, through multiple simulated experiments, our results highlight the value of individual sensitivity to site population in ensuring consensus. With the help of this social information, our model successfully reproduces experimental results showing the high cognitive capacity of colonies and their rational time investment during decision-making, and also predicts the pros and cons of social information with regard to the colonies ability to avoid and repair splits. Additionally, we use the model to make new predictions about several unstudied aspects of emigration behavior. Our results indicate a more complex relationship between individual behavior and the speed/accuracy trade-off than previously appreciated. The model proved relatively weak at resolving colony divisions among multiple sites, suggesting either limits to the ants ability to reach consensus, or an aspect of their behavior not captured in our model. It is our hope that these insights and predictions can inspire further research from both the biology and computer science community.

category: animal behavior and cognition


title: Multi-Atlas Image Soft Segmentation via Computation of the Expected Label Value

abstract: The use of multiple atlases is common in medical image segmentation. This typically requires deformable registration of the atlases (or the average atlas) to the new image, which is computationally expensive and susceptible to entrapment in local optima. We propose to instead consider the probability of all possible atlas-to-image transformations and compute the expected label value (ELV), thereby not relying merely on the transformation deemed "optimal" by the registration method. Moreover, we do so without actually performing deformable registration, thus avoiding the associated computational costs. We evaluate our ELV computation approach by applying it to brain, liver, and pancreas segmentation on datasets of magnetic resonance and computed tomography images.


title: The outer membrane loops of OmpA control the slow rate of in vitro folding

abstract: Outer membrane proteins are all beta barrels and these barrels have a variety of well-documented loop conformations. Here we test the effect of three different loop types on outer membrane protein A (OmpA) folding. We designed twelve 5-residue loops and experimentally tested the effect of replacing the long loops of outer membrane protein OmpA with the designed loops. Our studies succeeded in creating the smallest known outer membrane barrel. We find that significant changes in OmpA loops do not have a strong overall effect on OmpA folding. However, when decomposing folding into a fast rate and a slow rate we find that changes in loops strongly affect the slow rate of OmpA folding. Extracellular loop types with higher levels of hydrogen bonds had more instances of increasing the slow folding rate and extracellular loop types with low levels of hydrogen bonds had more instances of decreasing the slow folding rate. Having the slow rate affected by loop composition is consistent with the slow rate being associated with the insertion step of outer membrane protein folding.

category: biophysics


title: The extracellular loops of OmpA control the slow rate of in vitro folding


title: Granger Causality Inference in EEG Source Connectivity Analysis: A State-Space Approach

abstract: This paper considers a problem of estimating brain effective connectivity from EEG signals using a Granger causality (GC) concept characterized on state-space models. We propose a state-space model for explaining coupled dynamics of the source and EEG signals where EEG is a linear combination of sources according to the characteristics of volume conduction. Our formulation has a sparsity prior on the source output matrix that can further classify active and inactive sources. The scheme is comprised of two main steps: model estimation and model inference to estimate brain connectivity. The model estimation consists of performing a subspace identification and the active source selection based on a group-norm regularized least-squares. The model inference relies on the concept of state-space GC that requires solving a discrete-time Riccati equation for the covariance of estimation error. We verify the performance on simulated data sets that represent realistic human brain activities under several conditions including percentages of active sources, a number of EEG electrodes and the location of active sources. The performance of estimating brain networks is compared with a two-stage approach using source reconstruction algorithms and VAR-based Granger analysis. Our method achieved better performances than the two-stage approach under the assumptions that the true source dynamics are sparse and generated from state-space models. The method is applied to a real EEG SSVEP data set and we found that the temporal lobe played a role of a mediator of connections between temporal and occipital areas, which agreed with findings in previous studies.


title: Linking big biomedical datasets to modular analysis with Portable Encapsulated Projects

abstract: Organizing and annotating biological sample data is critical in data-intensive bioinformatics. Unfortunately, metadata formats from a data provider are often incompatible with requirements of a processing tool. There is no broadly accepted standard to organize metadata across biological projects and bioinformatics tools, restricting the portability and reusability of both annotated datasets and analysis software. To address this, we present Portable Encapsulated Projects (PEP), a formal specification for biological sample metadata structure. The PEP specification accommodates typical features of data-intensive bioinformatics projects with many samples, whether from individual experiments, organisms, or single cells. In addition to standardization, the PEP specification provides descriptors and modifiers for different organizational layers of a project, which improve portability among computing environments and facilitate use of different processing tools. PEP includes a schema validator framework, allowing formal definition of required metadata attributes for any type of biomedical data analysis. We have implemented packages for reading PEPs in both Python and R to provide a language-agnostic interface for organizing project metadata. PEP therefore presents an important step toward unifying data annotation and processing tools in data-intensive biological research projects.


title: Fabrication and electromechanical characterization of free-standing asymmetric membranes

abstract:
All biological cell membranes maintain an electric transmembrane potential of around 100 mV, due in part to an asymmetric distribution of charged phospholipids across the membrane. This asymmetry is crucial to cell health and physiological processes such as intracell signaling, receptor-mediated endocytosis, and membrane protein function. Experimental artificial membrane systems incorporate essential cell membrane structures, such as the phospholipid bilayer, in a controllable manner where specific properties and processes can be isolated and examined. Here, we describe a new approach to fabricate and characterize planar, free-standing, asymmetric membranes and use it to examine the effect of headgroup charge on membrane stiffness. The approach relies on a thin film balance used to form a freestanding membrane by adsorbing aqueous phase lipid vesicles to an oil-water interface and subsequently thinning the oil to form a bilayer. We validate this lipid-in-aqueous approach by analyzing the thickness and compressibility of symmetric membranes with varying zwitterionic DOPC and anionic DOPG content as compared to previous lipid-in-oil methods. We find that as the concentration of DOPG increases, membranes become thicker and stiffer. Asymmetric membranes are fabricated by controlling the lipid vesicle composition in the aqueous reservoirs on either side of the oil. Membrane compositional asymmetry is qualitatively demonstrated using a fluorescence quenching assay and quantitatively characterized through voltage-dependent capacitance measurements. Stable asymmetric membranes with DOPC on one side and DOPC/DOPG mixtures on the other were created with transmembrane potentials ranging from 15 to 80 mV. Introducing membrane charge asymmetry decreases both the thickness and stiffness in comparison to symmetric membranes with the same overall phospholipid composition. These initial successes demonstrate a viable pathway to quantitatively characterize asymmetric bilayers that can be extended to accommodate more complex membranes and membrane processes in the future.

O_TEXTBOXSIGNIFICANCE

A defining characteristic of the cell membrane is asymmetry in phospholipid composition between the interior and exterior bilayer leaflet. Although several methods have been used to artificially create membranes with asymmetry, there has not been extensive characterization of the impact of asymmetry on membrane material properties. Here, a technique to fabricate free-standing asymmetric membranes is developed which facilitates the visualization and electromechanical characterization of the bilayer. Asymmetry in anionic phospholipid concentration is quantified by measurements of membrane capacitance at varying voltages, which also allows for determination of the membrane compressibility. This method represents an advance in the development of artificial biomembranes by reliably creating phospholipid bilayers with asymmetry and facilitates the interrogation of more complex biological processes in the future.

C_TEXTBOX


title: RAL GTPases mediate EGFR-driven intestinal stem cell hyperproliferation and tumourigenesis.

abstract: RAS-like (RAL) GTPases function in Wnt signalling-dependent intestinal stem cell proliferation and regeneration. Whether RAL proteins work as canonical RAS effectors in the intestine, and the mechanisms of how they contribute to tumourigenesis remain unclear. Here, we show that RAL GTPases are necessary and sufficient to activate EGFR/MAPK signalling in the intestine, via induction of EGFR internalisation. Knocking down Drosophila RalA from intestinal stem and progenitor cells leads to increased levels of plasma membrane-associated EGFR and decreased MAPK pathway activation. Importantly, in addition to impacting stem cell proliferation during damage-induced intestinal regeneration, this role of RAL GTPases impacts on EGFR-dependent tumorigenic growth in the intestine and in human mammary epithelium. However, the effect of oncogenic RAS in the intestine is independent from RAL function. Altogether, our results reveal previously unrecognised cellular and molecular contexts where RAL GTPases become essential mediators of adult tissue homeostasis and malignant transformation.


title: A general decoding strategy explains the relationship between behavior and correlated variability

abstract:
Improvements in perception are frequently accompanied by decreases in correlated variability in sensory cortex. This relationship is puzzling because overall changes in correlated variability should minimally affect optimal information coding. We hypothesize that this relationship arises because instead of using optimal strategies for decoding the specific stimuli at hand, observers prioritize generality: a single set of neuronal weights to decode any stimuli. We tested this using a combination of multineuron recordings in the visual cortex of behaving rhesus monkeys and a cortical circuit model. We found that general decoders optimized for broad rather than narrow sets of visual stimuli better matched the animals decoding strategy, and that their performance was more related to the magnitude of correlated variability. In conclusion, the inverse relationship between perceptual performance and correlated variability can be explained by observers using a general decoding strategy, capable of decoding neuronal responses to the variety of stimuli encountered in natural vision.

IMPACT STATEMENTThe frequently observed relationship between perceptual performance and correlated variability in sensory cortex can be explained by observers using a decoding strategy that prioritizes generality for many stimuli over precision.


title: Alteration of gut microbiota with rifampicin does not impair maternal care in the European earwig

abstract: AO_SCPLOWBSTRACTC_SCPLOWThe microbes residing within the gut of an animal host often increase their own fitness by modifying their hosts physiological, reproductive, and behavioural functions. Whereas recent studies suggest that they may also shape host sociality and therefore have critical effects on animal social evolution, the impact of the gut microbiota on maternal care remains unexplored. This is surprising, as this behaviour is widespread among animals, often determines the fitness of both juveniles and parents, and is essential in the evolution of complex animal societies. Here, we tested whether life-long alterations of the gut microbiota with rifampicin - a broad-spectrum antibiotic - impair pre- and post-hatching maternal care in the European earwig. Our results first confirm that rifampicin altered the mothers gut microbial communities and indicate that the composition of the gut microbiota differs before and after egg care. Contrary to our predictions, however, the rifampicin-induced alterations of the gut microbiota did not modify pre- or post-hatching care. Independent of maternal care, rifampicin increased the females feces production and resulted in lighter eggs and juveniles. By contrast, rifampicin altered none of the other 21 physiological, reproductive and longevity traits measured over the 300 days of a females lifetime. Overall, these findings reveal that altering the gut microbiota with a large spectrum antibiotic such as rifampicin does not necessarily affect host sociality. They also emphasize that not all animals have evolved a co-dependence with their microbiota and call for caution when generalizing the central role of gut microbes in host biology.


title: Alteration of gut microbiota with a broad-spectrum antibiotic does not impair maternal care in the European earwig.


title: A colony-level optimization model provides a potential mechanism for the evolution of novel castes in eusocial ant colonies

abstract: Ant species often have multiple morphologically distinct  castes within a single colony. Given that most of these castes are involved in non-reproductive tasks, and since such individuals thus never reproduce, the question of how ant castes can evolve is a non-trivial one. Over the years, several models have been proposed in order to explain the evolution of castes in ant colonies. Here, we attempt to answer this question using an economics-based approach, developing an optimization model that implements adaptation and selection at the colony level. We argue that due to the nature of ant colonies, selection is shifted to the group level, and, due to this, individual ants are sheltered from negative selection. We show that our framework can explain the evolution of novel castes in ant colonies, and discuss the novelty of our model with regard to previous models that have been proposed. We also show that our model is consistent with several empirical observations of ant colonies.


title: Effects of High Magnetic Fields on Diffusion of Biologically Active Molecules

abstract: The diffusion of biologically active molecules is a ubiquitous process, controlling many mechanisms and the characteristic time scales for pivotal processes in living cells. Here, we show how a high static magnetic field (MF) affects the diffusion of paramagnetic and diamagnetic species, including oxygen, hemoglobin, ROS and drugs. We derive and solve the equation describing diffusion of such biologically active molecules in the presence of a MF as well as reveal the underlying mechanism of the MF effect on diffusion. We find that a high MF accelerates diffusion of diamagnetic species while slowing the diffusion of paramagnetic molecules in cell cytoplasm. When applied to oxygen and hemoglobin diffusion in red blood cells, our results suggest that a MF may significantly alter the gas exchange in an erythrocyte and cause swelling. Our prediction that the diffusion rate and characteristic time can be controlled by a MF opens new avenues for experimental studies foreseeing numerous biomedical applications.


title: Rapid Cortical Adaptation and the Role of Thalamic Synchrony During Wakefulness

abstract:
Rapid sensory adaptation is observed across all sensory systems, and strongly shapes sensory percepts in complex sensory environments. Yet despite its ubiquity and likely necessity for survival, the mechanistic basis is poorly understood. A wide range of primarily in-vitro and anesthetized studies have demonstrated the emergence of adaptation at the level of primary sensory cortex, with only modest signatures in earlier stages of processing. The nature of rapid adaptation and how it shapes sensory representations during wakefulness, and thus the potential role in perceptual adaptation, is underexplored, as are the mechanisms that underlie this phenomenon. To address these knowledge gaps, we recorded spiking activity in primary somatosensory cortex (S1) and the upstream ventral posteromedial (VPm) thalamic nucleus in the vibrissa pathway of awake male and female mice, and quantified responses to whisker stimuli delivered in isolation and embedded in an adapting sensory background. We found that cortical sensory responses were indeed adapted by persistent sensory stimulation; putative excitatory neurons were profoundly adapted, and inhibitory neurons only modestly so. Further optogenetic manipulation experiments and network modeling suggest this largely reflects adaptive changes in synchronous thalamic firing combined with robust engagement of feedforward inhibition, with little contribution from synaptic depression. Taken together, these results suggest that cortical adaptation in the regime explored here results from changes in the timing of thalamic input, and the way in which this differentially impacts cortical excitation and feedforward inhibition, pointing to a prominent role of thalamic gating in rapid adaptation of primary sensory cortex.

Significance StatementRapid adaptation of sensory activity strongly shapes representations of sensory inputs across all sensory pathways over the timescale of seconds, and has profound effects on sensory perception. Despite its ubiquity and theoretical role in the efficient encoding of complex sensory environments, the mechanistic basis is poorly understood, particularly during wakefulness. In this study in the vibrissa pathway of awake mice, we show that cortical representations of sensory inputs are strongly shaped by rapid adaptation, and that this is mediated primarily by adaptive gating of the thalamic inputs to primary sensory cortex and the differential way in which these inputs engage cortical sub-populations of neurons.


title: Mechanisms underlying vaccination protocols that may optimally elicit broadly neutralizing antibodies against highly mutable pathogens

abstract: Effective prophylactic vaccines usually induce the immune system to generate potent antibodies that can bind to an antigen and thus prevent it from infecting host cells. B cells produce antibodies by a Darwinian evolutionary process called affinity maturation (AM). During AM, the B cell population evolves in response to the antigen to produce antibodies that bind specifically and strongly to the antigen. Highly mutable pathogens pose a major challenge to the development of effective vaccines because antibodies that are effective against one strain of the virus may not protect against a mutant strain. Antibodies that can protect against diverse strains of a mutable pathogen have high "breadth" and are called broadly neutralizing antibodies (bnAbs). In spite of extensive studies, an effective vaccination strategy that can generate bnAbs in humans does not exist for any highly mutable pathogen. Here we study a minimal model to explore the mechanisms underlying how the selection forces imposed by antigens can be optimally chosen to guide AM to maximize the evolution of bnAbs. For logistical reasons, only a finite number of antigens can be administered in a finite number of vaccinations; that is, guiding the non-equilibrium dynamics of AM to produce bnAbs must be accomplished non-adiabatically. The time-varying Kullback-Leibler divergence (KLD) between the existing B cell population distribution and the fitness landscape imposed by antigens is a quantitative metric of the thermodynamic force acting on B cells. If this force is too small, adaptation is minimal. If the force is too large, contrary to expectations, adaptation is not faster; rather, the B cell population is extinguished for reasons that we describe. We define the conditions necessary for the force to be set optimally such that the flux of B cells from low to high breadth states is maximized. Even in this case we show why the dynamics of AM prevent perfect adaptation. If two shots of vaccination are allowed, the optimal protocol is characterized by a relatively low optimal KLD during the first shot that appropriately increases the diversity of the B cell population so that the surviving B cells have a high chance of evolving into bnAbs upon subsequently increasing the KLD during the second shot. Phylogenetic tree analysis further reveals the evolutionary pathways that lead to bnAbs. The connections between the mechanisms revealed by our analyses and recent simulation studies of bnAb evolution, the problem of generalist versus specialist evolution, and learning theory are discussed.

category: immunology


title: ATP biphasically modulates LLPS of TDP-43 PLD by specifically binding arginine residues

abstract: Mysteriously neurons maintain ATP concentrations of [~]3 mM but whether ATP modulates TDP-43 LLPS remains completely unexplored. Here we characterized the effect of ATP on LLPS of TDP-43 PLD and seven mutants by DIC and NMR. The results revealed: 1) ATP induces and subsequently dissolves LLPS of TDP-43 PLD by specifically binding Arg saturated at 1:100. 2) ATP modifies the conformation-specific electrostatic property beyond just imposing screening effect. 3) Reversibility of LLPS of TDP-43 PLD and further exaggeration into aggregation appear to be controlled by a delicate network composed of both attractive and inhibitory interactions. Results together establish that ATP might be a universal but specific regulator for most, if not all, R-containing intrinsically-disordered regions by altering physicochemical properties, conformations, dynamics, LLPS and aggregation. Under physiological conditions, TDP-43 is highly bound with ATP and thus inhibited for LLPS, highlighting a central role of ATP in cell physiology, pathology and aging.


title: Microglia Stimulate Zebrafish Brain Repair Via a Specific Inflammatory Cascade

abstract: The adult zebrafish brain, unlike mammals, has a remarkable regenerative capacity. Although inflammation inhibits regeneration in mammals, it is necessary for zebrafish brain repair. Microglia are resident brain immune cells that regulate the inflammatory response. To explore the microglial role in repair, we used liposomal clodronate, colony stimulating factor-1 receptor (csf1r) inhibition to ablate microglia and two genetic mutants that lacks microglia during brain injury. We found that microglial ablation inhibited injury-induced neurogenesis and regeneration. Microglial suppression specifically attenuated cell proliferation at the progenitor cell amplification stage of neurogenesis. Notably, the loss of microglia impaired phospho-stat3 (signal transducer and activator of transcription 3) and {beta}-catenin signaling by dynamic regulation of tumor necrosis factor-a after injury, and the ectopic activation of stat3 and {beta}-catenin rescued neurogenesis defects caused by microglial loss. Microglial absence leads to neutrophil accumulation, hindering the resolution of inflammation and macrophages are not sufficient for regeneration. These findings reveal specific roles of microglia and inflammatory signaling during zebrafish telencephalic regeneration that should provide strategies to improve mammalian brain repair.


title: Simulation-guided engineering of antibiotics for improved bacterial uptake

abstract: The Gram-negative bacterial outer membrane poses a major obstacle to the development of much-needed antibiotics against drug-resistant infections. Its chemical composition and porin proteins differ from Gram-positive bacteria and mammalian cells, and heuristics developed for mammalian cell uptake apply poorly. Recently, machinelearning methods have predicted small-molecule uptake into Gram-negative bacteria, offering the possibility to rationally optimize this aspect of antibiotic lead development. Here, we report physics-based methods to prospectively predict Gram-negative bacterial uptake, select, and synthesize promising chemical derivatives targeting E. coli DNA gyrase B. Our methods do not require empirical parameterization and are readily adaptable to new chemical scaffolds. These physics-based predictions well capture experimentally measured uptake (r > 0.95) and are indeed predictive of antimicrobial activity (r > 0.92). These methods can be used prospectively in combination with target-binding simulations to optimize both bacterial uptake and target binding, overcoming important barriers to antibiotic lead generation before small-molecule synthesis.

category: microbiology


title: Protein-bound molybdenum cofactor is bioavailable and rescues molybdenum cofactor-deficient C. elegans

abstract: The molybdenum cofactor (Moco) is a 520 dalton prosthetic group that is synthesized in all domains of life. In animals, four oxidases (among them sulfite oxidase) use Moco as a prosthetic group. Moco is essential in animals; humans with mutations in genes that encode Moco-biosynthetic enzymes display lethal neurological and developmental defects. Moco supplementation seems a logical therapy, however the instability of Moco has precluded biochemical and cell biological studies of Moco transport and bioavailability. The nematode Caenorhabditis elegans can take up Moco from its bacterial diet and transport it to cells and tissues that express Moco-requiring enzymes, suggesting a system for Moco uptake and distribution. Here we show that protein-bound Moco is the stable, bioavailable species of Moco taken up by C. elegans from its diet and is an effective dietary supplement, rescuing a C. elegans model of Moco deficiency. We demonstrate that diverse Moco:protein complexes are stable and bioavailable, suggesting a new strategy for the production and delivery of therapeutically active Moco to treat human Moco deficiency.


title: Discovery of novel putative tumor suppressors from CRISPR screens reveals rewired lipid metabolism in AML cells

abstract: CRISPR knockout screens in hundreds of cancer cell lines have revealed a substantial number of context-specific essential genes that, when associated with a biomarker such as lineage or oncogenic mutation, offer candidate tumor-specific vulnerabilities for targeted therapies or novel drug development. Data-driven analysis of knockout fitness screens also yields many other functionally coherent modules that show emergent essentiality or, in rarer cases, the opposite phenotype of faster proliferation. We develop a systematic approach to classify these suppressors of proliferation, which are highly enriched for tumor suppressor genes, and define a network of 145 genes in 22 discrete modules. One surprising module contains several elements of the glycerolipid biosynthesis pathway and operates exclusively in a subset of AML lines, which we call Fatty Acid Synthesis/Tumor Suppressor (FASTS) cells. The proliferation suppressor activity of genes involved in the synthesis of saturated fatty acids, coupled with a more severe fitness phenotype for the desaturation pathway, suggests that these cells operate at the limit of their carrying capacity for saturated fatty acids, which we confirmed biochemically. Overexpression of genes in this module is associated with a survival advantage in an age-matched cohort of AML patients, suggesting the gene cluster driving an in vitro phenotype may be associated with a novel, clinically relevant subtype.

category: genetics


title: DUBStepR: correlation-based feature selection for clustering single-cell RNA sequencing data

abstract: Feature selection (marker gene selection) is widely believed to improve clustering accuracy, and is thus a key component of single cell clustering pipelines. However, we found that the performance of existing feature selection methods was inconsistent across benchmark datasets, and occasionally even worse than without feature selection. Moreover, existing methods ignored information contained in gene-gene correlations. We therefore developed DUBStepR (Determining the Underlying Basis using Stepwise Regression), a feature selection algorithm that leverages gene-gene correlations with a novel measure of inhomogeneity in feature space, termed the Density Index (DI). Despite selecting a relatively small number of genes, DUBStepR substantially outperformed existing single-cell feature selection methods across diverse clustering benchmarks. In a published scRNA-seq dataset from sorted monocytes, DUBStepR sensitively detected a rare and previously invisible population of contaminating basophils. DUBStepR is scalable to over a million cells, and can be straightforwardly applied to other data types such as single-cell ATAC-seq. We propose DUBStepR as a general-purpose feature selection solution for accurately clustering single-cell data.


title: An inverse modelling study on the local volume changes during early growth of the fetal human brain

abstract: We take a data-driven approach to deducing the local volume changes accompanying early development of the fetal human brain. Our approach uses fetal brain atlas MRI data for the geometric changes in representative cases. Using a nonlinear continuum mechanics model of morphoelastic growth, we invert the deformation obtained from MRI registration to arrive at a field for the growth deformation gradient tensor. Our field inversion uses a combination of direct and adjoint methods for computing gradients of the objective function while constraining the optimization by the physics of morphoelastic growth. We thus infer a growth deformation gradient field that obeys the laws of morphoelastic growth. The errors between the MRI data and the forward displacement solution driven by the inverted growth deformation gradient field are found to be smaller than the reference displacement by well over an order of magnitude, and can be driven even lower. The results thus reproduce the three-dimensional growth during the early development of the fetal brain with controllable error. Our findings confirm that early growth is dominated by in plane cortical expansion rather than thickness increase.


title: Inhibition of polo-like kinase 1 (PLK1) facilitates reactivation of gamma-herpesviruses in B-cell lymphomas and their elimination

abstract: Both Kaposis sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV) establish the persistent, life-long infection primarily at the latent status, and contribute to certain types of tumors, including B cell lymphomas, especially in immuno-compromised individuals, such as people living with HIV (PLWH). Lytic reactivation of these viruses can be employed to kill tumor cells harboring latently infected viral episomes, through the viral cytopathic effects and the subsequent antiviral immune responses. In this study, we identified that polo-like kinase 1 (PLK1) is induced by KSHV de novo infection as well as lytic switch from KSHV latency. We further demonstrated that PLK1 depletion or inhibition facilitates KSHV reactivation and promotes cell death of KSHV-reactivated lymphoma cells. Mechanistically, PLK1 regulates Myc that is critical to both maintenance of KSHV latency and support of cell survival, and preferentially affects the level of H3K27me3 inactive mark both globally and at certain loci of KSHV viral episomes. Lastly, we recognized that PLK1 inhibition synergizes with STAT3 inhibition to efficiently induce KSHV reactivation. Furthermore, we also confirmed that PLK1 depletion or inhibition yields the similar effect on EBV reactivation and cell death of EBV-reactivated lymphoma cells. Additionally, we noticed the PLK1 in B cells is elevated in the context of HIV infection and by HIV Nef protein, which would favor KSHV/EBV latency. Above all, our findings illustrated that PLK1 is a novel host target that can be inhibited to benefit the viral oncolysis to eliminate KSHV/EBV-infected lymphoma cells, particularly for PLWH.


title: Electrostatic Plasma Membrane Targeting Contributes to Dlg Function in Cell Polarity and Tumorigenesis

abstract: Discs large (Dlg) is an essential polarity protein and a tumor suppressor originally characterized in Drosophila but is also well conserved in vertebrates. Like the majority of polarity proteins, plasma membrane (PM)/cortical localization of Dlg is required for its function in polarity and tumorigenesis, but the exact mechanisms targeting Dlg to PM remain to be fully elucidated. Here we show that, similar to the recently discovered polybasic polarity proteins such as Lgl and aPKC, Dlg also contains a positively charged polybasic domain that electrostatically binds the PM phosphoinositides PI4P and PI(4,5)P2. Electrostatic targeting by the polybasic domain contributes significantly to the PM localization of Dlg in follicular and early embryonic epithelial cells, and is crucial for Dlg to regulate both polarity and tumorigenesis. The electrostatic PM targeting of Dlg is controlled by a potential phosphorylation-dependent allosteric regulation of its polybasic domain, and is specifically enhanced by the interactions between Dlg and another basolateral polarity protein and tumor suppressor Scrib. Our studies highlight an increasingly significant role of electrostatic PM targeting of polarity proteins in regulating cell polarity.


title: Time-dependent synergy for multi-agent anticancer therapy

abstract: A synergy between two therapeutic agents occurs when the effect of using both is greater than the sum of the effects of using each of them separately. There are several methods of detecting synergies in the literature, but they do not take into account the relationship between the times in which the factors act. In the article, we propose and justify the use of second-order sensitivity analysis as a potential tool for the detection and visualization of this type of synergy. We test and illustrate the proposed approach using four exemplary models of combined radio-chemotherapy of cancer.


title: Cancer methylomes characterization enabled by Rocker-meth

abstract: Differentially DNA methylated regions (DMRs) inform on the role of epigenetic changes in cancer. We present Rocker-meth, a computational method exploiting a heterogeneous hidden Markov model to detect DMRs across multiple experimental platforms. Its application to more than 6,000 methylation profiles across 14 tumor types provides a comprehensive catalog of tumor type-specific and shared DMRs, also amenable to single-cell DNA-methylation data. In depth integrative analysis including orthogonal omics shows the enhanced ability of Rocker-meth in recapitulating known associations, further uncovering the pan-cancer relationship between DNA hypermethylation and transcription factor deregulation depending on the baseline chromatin state.


title: Leafminer attack induces plant-mediated facilitation of conspecific pupae in the soil

abstract:
O_LIHerbivore population dynamics are strongly influenced by the interactions established through their shared host. Such plant-mediated interactions can occur between different herbivore species and between different life developmental stages of the same herbivore. Yet, whether these interactions occur between leaf-feeding herbivores and their soil-dwelling pupae is unknown.
C_LIO_LIWe studied whether tomato (Solanum lycopersicum) leaf-herbivory by the American serpentine leafminer Lyriomiza trifolii affects the performance of conspecific pupae in the soil adjacent to the plant. To gain mechanistic insights, we performed insect bioassays with the jasmonate-deficient tomato mutant def-1 and its wild type, along with the analysis of phytohormones, gene expression and root volatiles.
C_LIO_LILeafminer metamorphosis in the soil was accelerated when wild type plants were attacked aboveground by conspecifics, but the opposite was observed in def-1. Changes in pupal developmental rate were mediated by belowground volatiles. Accordingly, leafminer herbivory differentially modulated jasmonate and abscisic acid signaling and the accumulation of specific volatiles in the roots of wild type versus def-1 plants
C_LIO_LIOur results demonstrate that aboveground herbivores can facilitate their soil-dwelling pupae by inducing def-1-dependent systemic responses. This study expands the repertoire of plant-herbivore interactions to herbivory-induced modulation of metamorphosis, with potentially important consequences for plant and herbivore community dynamics.
C_LI


title: Transcranial Random Noise Stimulation acutely lowers the response threshold of human motor circuits

abstract:
AO_SCPLOWBSTRACTC_SCPLOWTranscranial random noise stimulation (tRNS) over cortical areas has been shown to acutely improve performance in sensory detection tasks. One explanation for this behavioural effect is stochastic resonance, a mechanism that explains how signal processing in non-linear systems can benefit from added noise. While acute noise benefits of electrical random noise stimulation have been demonstrated at the behavioural level as well as in in vitro preparations of neural tissue, it is currently largely unknown whether similar effects can be shown at the neural population level using neurophysiological readouts of human cortex. Here we hypothesized that acute tRNS will increase the responsiveness of primary motor cortex (M1) when probed with transcranial magnetic stimulation. Neural responsiveness was operationalized via the well-known concept of the resting motor threshold (RMT). We showed that tRNS acutely decreases RMT. This effect was small, but it was consistently replicated across four experiments including different cohorts (total N=81, 46 females, 35 males), two tRNS electrode montages, and different control conditions. Our experiments provide critical neurophysiological evidence that tRNS can acutely generate noise benefits by enhancing the neural population response of human M1.

SO_SCPLOWIGNIFICANCEC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWSTATEMENTC_SCPLOWA hallmark feature of stochastic resonance is that signal processing can benefit from added noise. This has mainly been demonstrated at the single-cell level in vitro where the neural response to weak input signals can be enhanced by simultaneously applying random noise. Our finding that tRNS acutely increases the excitability of corticomotor circuits extends the principle of noise benefits to the neural population level in human cortex. Our finding is in line with the notion that tRNS might affect cortical processing via the stochastic resonance phenomenon. It suggests that enhancing the response of cortical populations to an external stimulus might be one neurophysiological mechanism mediating performance improvements when tRNS is applied to sensory cortex during perception tasks.

category: neuroscience


title: A Spectral Theory for Wright's Inbreeding Coefficients and Related Quantities

abstract:
Wrights inbreeding coefficient, FST, is a fundamental measure in population genetics. Assuming a predefined population subdivision, this statistic is classically used to evaluate population structure at a given genomic locus. With large numbers of loci, unsupervised approaches such as principal component analysis (PCA) have, however, become prominent in recent analyses of population structure. In this study, we describe the relationships between Wrights inbreeding coefficients and PCA for a model of K discrete populations. Our theory provides an equivalent definition of FST based on the decomposition of the genotype matrix into between and within-population matrices. The average value of Wrights FST over all loci included in the genotype matrix can be obtained from the PCA of the between-population matrix. Assuming that a separation condition is fulfilled and for reasonably large data sets, this value of FST approximates the proportion of genetic variation explained by the first (K - 1) principal components accurately. The new definition of FST is useful for computing inbreeding coefficients from surrogate genotypes, for example, obtained after correction of experimental artifacts or after removing adaptive genetic variation associated with environmental variables. The relationships between inbreeding coefficients and the spectrum of the genotype matrix not only allow interpretations of PCA results in terms of population genetic concepts but extend those concepts to population genetic analyses accounting for temporal, geographical and environmental contexts.

Authors summaryPrincipal component analysis (PCA) is the most-frequently used approach to describe population genetic structure from large population genomic data sets. In this study, we show that PCA not only estimates ancestries of sampled individuals, but also computes the average value of Wrights inbreeding coefficient over the loci included in the genotype matrix. Our result shows that inbreeding coefficients and PCA eigenvalues provide equivalent descriptions of population structure. As a consequence, PCA extends the definition of this coefficient beyond the framework of allelic frequencies. We give examples on how FST can be computed from ancient DNA samples for which genotypes are corrected for coverage, and in an ecological genomic example where a proportion of genetic variation is explained by environmental variables.

category: evolutionary biology


title: Neural dynamics of semantic categorization in semantic variant of Primary Progressive Aphasia.

abstract:
Semantic representations are processed along a posterior-to-anterior gradient reflecting a shift from perceptual (e.g., it has eight legs) to conceptual (e.g., venomous spiders are rare) information. One critical region is the anterior temporal lobe (ATL): patients with semantic variant primary progressive aphasia (svPPA), a clinical syndrome associated with ATL neurodegeneration, manifest a deep loss of semantic knowledge. We test the hypothesis that svPPA patients perform semantic tasks by over-recruiting areas implicated in perceptual processing. We compared MEG recordings of svPPA patients and healthy controls during a categorization task. While behavioral performance did not differ, svPPA patients showed indications of greater activation over bilateral occipital cortices and superior temporal gyrus, and inconsistent engagement of frontal regions. These findings suggest a pervasive reorganization of brain networks in response to ATL neurodegeneration: the loss of this critical hub leads to a dysregulated (semantic) control system, and defective semantic representations are seemingly compensated via enhanced perceptual processing.

Impact StatementFollowing anterior temporal lobe neurodegeneration, defective semantic representations are compensated via enhanced perceptual processing and associated with a dysregulation of the semantic control system.


title: Disentangling age-dependent DNA methylation: deterministic, stochastic, and nonlinear

abstract: DNA methylation variability arises due to concurrent genetic and environmental influences. Each of them is a mixture of regular and noisy sources, whose relative contribution has not been satisfactorily understood yet. We conduct a systematic assessment of the age-dependent methylation by the signal-to-noise ratio and identify a wealth of "deterministic" CpG probes (about 90%), whose methylation variability likely originates due to genetic and general environmental factors. The remaining 10% of "stochastic" CpG probes are arguably governed by the biological noise or incidental environmental factors. Investigating the mathematical functional relationship between methylation levels and variability, we find that in about 90% of the age-associated differentially methylated positions, the variability changes as the square of the methylation level, whereas in the most of the remaining cases the dependence is linear. Furthermore, we demonstrate that the methylation level itself in more than 15% cases varies nonlinearly with age (according to the power law), in contrast to the previously assumed linear changes. Our findings present ample evidence of the ubiquity of strong DNA methylation regulation, resulting in the individual age-dependent and nonlinear methylation trajectories, whose divergence explains the cross-sectional variability. It may also serve a basis for constructing novel nonlinear epigenetic clocks.

category: systems biology


title: The interaction between endogenous GABA, functional connectivity and behavioral flexibility is critically altered with advanced age

abstract: The flexible adjustment of ongoing behavior challenges the nervous systems dynamic control mechanisms and has shown to be specifically susceptible to age-related decline. Previous work links endogenous gamma-aminobutyric acid (GABA) with behavioral efficiency across perceptual and cognitive domains, with potentially the strongest impact on those behaviors that require a high level of dynamic control. Based on the integrated analyses of behavior and modulation of interhemispheric phase-based connectivity during dynamic motor state transitions and endogenous GABA concentration, we provide converging evidence for age-related differences in the behaviorally more beneficial state of endogenous GABA concentration. We suggest that the increased interhemispheric connectivity seen in the older adults represents a compensatory mechanism caused by rhythmic entrainment of neural populations in homotopic motor cortices. This mechanism appears to be most relevant in the presence of a less optimal tuning of the inhibitory tone to uphold the required flexibility of behavioral action.


title: Increased amphetamine-induced hyperactivity in translin (Tsn) KO mice is driven by elevated adiposity

abstract:
The translin/trax microRNA-degrading enzyme mediates activity-induced changes in translation that underlie several long-lasting forms of cellular plasticity. As translin and trax are expressed in dopaminergic and striatal neurons, we proceeded to investigate whether deletion of Tsn blocks amphetamine sensitization, a long-lasting, translation-dependent form of behavioral plasticity,

Although we expected constitutive Tsn deletion to impair amphetamine sensitization, we found, instead, that it enhances the hyperlocomotion produced by the initial dose of amphetamine. Since these mice display elevated adiposity, which alters pharmacokinetics of many drugs, we measured brain amphetamine levels in Tsn knockout mice and found that these are elevated. We also found that diet-induced increases in adiposity in WT mice correlate with elevated brain amphetamine levels. As amphetamine and its analogues are widely used to treat attention deficit disorder, which is associated with obesity, further studies are needed to assess the impact of adiposity on amphetamine levels in these patients.


title: Circadian fluctuations in glucocorticoid level predict perceptual discrimination sensitivity

abstract: Slow neurobiological rhythms, such as the circadian secretion of glucocorticoid (GC) hormones, modulate a wide variety of body functions. Whether and how such endocrine fluctuations also exert an influence on perceptual abilities is largely uncharted. Here, we show that phasic, moderate increases in GC availability prove beneficial to auditory discrimination. In an age-varying sample of N = 68 healthy human participants, we characterise the covariation of saliva cortisol with perceptual sensitivity in an auditory pitch-discrimination task at five time points across the sleep--wake cycle. First, momentary saliva cortisol levels were captured well by the time relative to wake-up and overall sleep duration. Second, within individuals, higher cortisol level just prior to behavioural testing predicted better pitch discrimination ability, expressed as a steepened psychometric curve. This effect of glucocorticoids held under a set of statistical control models. Our results pave the way for more in-depth studies on neuroendocrinological determinants of sensory encoding and perception.