title: Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning

abstract: Understanding the spatial organization of tissues is of critical importance for both basic and translational research. While recent advances in tissue imaging are opening an exciting new window into the biology of human tissues, interpreting the data that they create is a significant computational challenge. Cell segmentation, the task of uniquely identifying each cell in an image, remains a substantial barrier for tissue imaging, as existing approaches are inaccurate or require a substantial amount of manual curation to yield useful results. Here, we addressed the problem of cell segmentation in tissue imaging data through large-scale data annotation and deep learning. We constructed TissueNet, an image dataset containing >1 million paired whole-cell and nuclear annotations for tissue images from nine organs and six imaging platforms. We created Mesmer, a deep learning-enabled segmentation algorithm trained on TissueNet that performs nuclear and whole-cell segmentation in tissue imaging data. We demonstrated that Mesmer has better speed and accuracy than previous methods, generalizes to the full diversity of tissue types and imaging platforms in TissueNet, and achieves human-level performance for whole-cell segmentation. Mesmer enabled the automated extraction of key cellular features, such as subcellular localization of protein signal, which was challenging with previous approaches. We further showed that Mesmer could be adapted to harness cell lineage information present in highly multiplexed datasets. We used this enhanced version to quantify cell morphology changes during human gestation. All underlying code and models are released with permissive licenses as a community resource.


title: Effects of diffusion signal modeling and segmentation approaches on subthalamic nucleus parcellation

abstract:
The subthalamic nucleus (STN) is commonly used as a surgical target for deep brain stimulation in movement disorders such as Parkinsons Disease. Tractography-derived connectivity-based parcellation (CBP) has been recently proposed as a suitable tool for non-invasive in vivo identification and pre-operative targeting of specific functional territories within the human STN. However, a well-established, accurate and reproducible protocol for STN parcellation is still lacking. The present work aims at testing the effects of different tractography-based approaches for the reconstruction of STN functional territories.

We reconstructed functional territories of the STN on the high-quality dataset of 100 unrelated healthy subjects and on the test-retest dataset of the Human Connectome Project (HCP) repository. Connectivity-based parcellation was performed with a hypothesis-driven approach according to cortico-subthalamic connectivity, after dividing cortical areas into three groups: associative, limbic and sensorimotor. Four parcellation pipelines were compared, combining different signal modeling techniques (single-fiber vs multi-fiber) and different parcellation approaches (winner takes all parcellation vs fiber density thresholding). We tested these procedures on STN regions of interest obtained from three different, commonly employed, subcortical atlases. We evaluated the pipelines both in terms of between-subject similarity, assessed on the cohort of 100 unrelated healthy subjects, and of within-subject similarity, using a second cohort of 44 subjects with available test-retest data. We found that each parcellation provides converging results in terms of location of the identified parcels, but with significative variations in size and shape. Higher between-subject similarity was found with multi-fiber signal modeling techniques combined with fiber density thresholding. All the pipelines obtained very high within-subject similarity, with tensor-based approaches outperforming multi-fiber pipelines. We suggest that a fine-tuning of tractography-based parcellation may lead to higher reproducibility and aid the development of an optimized surgical targeting protocol.

category: neuroscience


title: Parvalbumin Interneurons Inhibition onto BLA Projecting Neurons of the Anterior Insula Orchestrates Aversive Taste Memory Retrieval

abstract:
Memory retrieval refers to the fundamental ability of organisms to make use of acquired, sometimes inconsistent, information about the world. While memory acquisition has been studied extensively, the neurobiological mechanisms underlying memory retrieval remain largely unknown. The anterior insula (aIC) is indispensable in the ability of mammals to retrieve associative information regarding tastants that have been previously linked with gastric malaise. Here, we show that aversive taste memory retrieval promotes cell-type-specific activation in the aIC. Aversive, but not appetitive taste memory retrieval, relies on specific changes in activity and connectivity at parvalbumin (PV) inhibitory synapses onto aIC pyramidal neurons projecting to the basolateral amygdala. PV aIC interneurons, coordinate aversive taste memory retrieval, and are necessary for its dominance when conflicting internal representations are encountered. This newly described interaction of PV and a subset of excitatory neurons can explain the coherency of aversive memory retrieval, an evolutionary pre-requisite for animal survival.

Graphical Abstract

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org.highwire.dtl.DTLVardef@1e73ba2org.highwire.dtl.DTLVardef@1fc234dorg.highwire.dtl.DTLVardef@719d74org.highwire.dtl.DTLVardef@1184bb9_HPS_FORMAT_FIGEXP  M_FIG C_FIG O_LIRetrieval of Conditioned Taste Aversion (CTA) memories at the anterior insular cortex activates Parvalbumin (PV) interneurons and increases synaptic inhibition onto activated pyramidal neurons projecting to the basolateral amygdala (aIC-BLA).
C_LIO_LIUnlike innately appetitive taste memory retrieval, CTA retrieval increases the amplitude and frequency of synaptic inhibition onto aIC-BLA projecting neurons, that is dependent on activity in aIC PV interneurons.
C_LIO_LIActivation of aIC PV interneurons is necessary for the expression of learned taste avoidance, in both sexes, regardless of stimulus identity.
C_LIO_LIExtinction of aversive taste memories suppresses the frequency, but not the amplitude of synaptic inhibition on aIC-BLA projecting neurons.
C_LIO_LIThe reinstatement of aversive taste memories following extinction is dependent upon activation of aIC PV interneurons and increases in the frequency of inhibition on aIC-BLA projecting neurons.
C_LI


title: Approximate Hidden Semi-Markov Models for Dynamic Connectivity Analysis in Resting-State fMRI

abstract: Motivated by a study on adolescent mental health, we conduct a dynamic connectivity analysis using resting-state functional magnetic resonance imaging (fMRI) data. A dynamic connectivity analysis investigates how the interactions between different regions of the brain, represented by the different dimensions of a multivariate time series, change over time. Hidden Markov models (HMMs) and hidden semi-Markov models (HSMMs) are common analytic approaches for conducting dynamic connectivity analyses. However, existing approaches for HSMMs are limited in their ability to incorporate covariate information. In this work, we approximate an HSMM using an HMM for modeling multivariate time series data. The approximate HSMM model allows one to explicitly model dwell-time distributions that are available to HSMMs, while maintaining the theoretical and methodological advances that are available to HMMs. We conducted a simulation study to show the performance of the approximate HSMM relative to other approaches. Finally, we used the approximate HSMM to conduct a dynamic connectivity analysis, where we showed how dwell-time distributions vary across the severity of non-suicidal self-injury (NSSI) in female adolescents, and how those with moderate or severe NSSI have greater state-switching frequency.


title: Using empirical datasets to quantify uncertainty in inferences of landscape genetic resistance due to variation of individual-based genetic distance metrics

abstract:
O_LIEstimates of gene flow are commonly based on inferences of landscape resistance in ecological and evolutionary research and they frequently inform decision-making processes in conservation management. It is therefore imperative that inferences of a landscape factors relevance and its resistance are robust across approaches and reflect real-world gene flow instead of methodological artefacts. Here, we tested the impact of 160 different individual-based pairwise genetic metrics on consistency of landscape genetic inferences.
C_LIO_LIWe used three empirical datasets that adopted individual-based sampling schemes and varied in scale (35-25,000 km2) and total number of samples (184-790) and comprise the wild boar, Sus scrofa, the red fox, Vulpes vulpes and the common wall lizard, Podarcis muralis. We made use of a machine-learning algorithm implemented in RO_SCPLOWESISTANCEC_SCPLOWGA to optimally fit resistances of landscape factors to genetic distance metrics and ranked their importance. Employed for nine landscape factors this resulted in 4,320 unique combinations of dataset, landscape factor and genetic distance metric, which provides the basis for quantifying uncertainty in inferences of landscape resistance.
C_LIO_LIOur results demonstrate that there are clear differences in Akaike information criteria (AICc)-based model support and marginal R2-based model fit between different genetic distance metrics. Metrics based on between 1-10 axes of eigenvector-based multivariate analyses (Factorial correspondence analysis, FCA; Principal component analysis, PCA) outperformed more widely used metrics, including the proportion of shared alleles (DPS), with AICc and marginal R2 values often an order of magnitude greater in the former. Across datasets, inferences of the directionality of a landscape factors influence on gene flow, e.g. facilitating or impeding it, changed across different genetic distance metrics. The directionality of the inferred resistance was largely consistent when considering metrics based on between 1-10 FCA/PCA axes.
C_LIO_LIInferences of landscape genetic resistance need to be corroborated using calculations of multiple individual-based pairwise genetic distance metrics. Our results call for the adoption of eigenvector-based quantifications of pairwise genetic distances. Specifically, a preliminary step of analysis should be incorporated, which explores model ranks across genetic distance metrics derived from FCA and PCA, and, contrary to findings of a simulation study, we demonstrate that it suffices to quantify these distances spanning the first ten axes only.
C_LI

category: ecology


title: Social partner cooperativeness influences brain oxytocin transcription in Trinidadian guppies (Poecilia reticulata)

abstract: For non-kin cooperation to be maintained, individuals need to respond adaptively to the cooperative behaviour of their social partners. Currently, however, little is known about the biological responses of individuals to experiencing cooperation. Here, we quantify the neuroregulatory response of Trinidadian guppies (Poecilia reticulata) experiencing cooperation or defection by examining the transcriptional response of the oxytocin gene (oxt; also known as isotocin), which has been implicated in cooperative decision-making. We exposed wild-caught females to social environments where partners either cooperated or defected during predator inspection, or to a control (non-predator inspection) context, and quantified the relative transcription of the oxt gene. We tested an experimental group, originating from a site where individuals are under high predation threat and have previous experience of large aquatic predators (HP), and a control group, where individuals are under low predation threat and naive to large aquatic predators (LP). In HP, but not LP, fish brain mid-section oxt relative transcription varied depending on social partner behaviour. HP fish experiencing cooperation during predator inspection had lower oxt transcription than those experiencing defection. This effect was not present in the control population or in the control context, where the behaviour of social partners did not affect oxt transcription. Our findings provide insight into the neuromodulation underpinning behavioural responses to social experiences, and ultimately to the proximate mechanisms underlying social decision-making.

category: animal behavior and cognition


title: Small molecule SWELL1-LRRC8 complex induction improves glycemic control and nonalcoholic fatty liver disease in murine Type 2 diabetes

abstract: Type 2 diabetes (T2D) is associated with insulin resistance, impaired insulin secretion from the pancreatic {beta}-cell, and nonalcoholic fatty liver disease (NAFLD). SWELL1 (LRRC8a) ablation impairs adipose and skeletal muscle insulin-pAKT2 signaling, {beta}-cell insulin secretion and glycemic control - suggesting that SWELL1-LRRC8 complex dysfunction contributes to T2D pathogenesis. Here, we show that ICl,SWELL and SWELL1 protein are reduced in adipose and {beta}-cells in murine and human T2D. Combining cryo-electron microscopy, molecular docking, medicinal chemistry, and functional studies, we define a structure activity relationship to rationally-designed active derivatives (SN-40X) of a SWELL1 channel inhibitor (DCPIB/SN-401), that bind the SWELL1-LRRC8 hexameric complex, restore SWELL1-LRRC8 protein, plasma membrane trafficking, signaling and islet insulin secretion via SWELL1-dependent mechanisms. In vivo, SN-401 and active SN-40X compounds restore glycemic control and prevents NAFLD by improving insulin-sensitivity and insulin secretion in murine T2D. These findings demonstrate that small molecule SWELL1 modulators restore SWELL1-dependent insulin-sensitivity and insulin secretion in T2D and may represent a first-in-class therapeutic approach for T2D and NAFLD.

category: physiology


title: Instructor-learner neural synchronization during elaborated feedback predicts learning transfer

abstract:
The provision of feedback with complex information beyond the correct answer, i.e., elaborated feedback, can powerfully shape learning outcomes such as transfer, i.e., the ability to extend what has been learned in one context to new contexts. However, an understanding of neurocognitive processes of elaborated feedback during instructor-learner interactions remains elusive. Here, a two-person interactive design is used during simultaneous recording of functional near-infrared spectroscopy (fNIRS) signals from adult instructor-learner dyads. Instructors either provided elaborated feedback (i.e., correct answer and an example) or simple feedback (i.e., correct answer only) to learners during a concept learning task. Our results showed that elaborated feedback produced comparable levels of retention to simple feedback, however, transfer was significantly enhanced by elaboration. We also noted significant instructor-learner neural synchronization in frontoparietal regions during the provision of elaborated feedback, especially when examples were provided. Further, interpersonal neural synchronization in the parietal cortex successfully predicted transfer of knowledge to novel contexts. This prediction was retained for both learner-delayed and learner-preceding neural synchronization. These findings point toward transfer effects of elaborated feedback provided in a social context can be predictable through interpersonal neural synchronization, which may hold important implications for real-world learning and pedagogical efficacy.

Educational Impact and Implications StatementFeedback provides learners with crucial information regarding the gap between what has currently been achieved and what remains to be achieved, and thus plays a critical role in any learning process. In real-world settings, feedback is typically provided and received through social interaction, and high-quality "elaborated feedback" contains complex information that goes beyond the correct answer. This study aims to elucidate the neurocognitive processes underpinning elaborated feedback during instructor-learner interactions. We detected significant instructor-learner neural synchronization in mutual frontoparietal brain regions during elaborated feedback, particularly during the provision of specific elaborated information (i.e., concrete examples). Moreover, this synchronization (including learner-delayed and learner-preceded synchronization) in the parietal region predicted whether the learners transferred learning to novel examples of learned psychology concepts. This study advances current understanding on the neural mechanisms for elaborated feedback and the role of social interaction in feedback effects. These results may have important implications for successful real-world learning and communication, and related pedagogical applications in educational settings.

category: scientific communication and education


title: A Comparison of Cell-Based and Cell-Cultured as Appropriate Common or Usual Names to Label Products Made from the Cells of Fish.

abstract:
Using an online experiment with a nationally representative sample of 1200 adult American consumers, two "common or usual names," "Cell-Based Seafood" and "Cell-Cultured Seafood," were assessed using five criteria. Displayed on packages of frozen Atlantic Salmon, the names were evaluated on their ability to differentiate the novel products from conventionally-produced fish, to identify their potential allergenicity, and after learning its meaning, to be seen by participants as an appropriate term for describing the process for creating the product. In addition, the names were evaluated as to whether they would be interpreted as disparaging of new or existing products, and whether they elicited reactions contrary to the assertion that the products are nutritious, healthy and safe. The results confirmed earlier research showing that "Cell-Based Seafood" slightly outperformed "Cell-Cultured Seafood" as a common or usual name. Labeling products with the term "Cell-Based Seafood" meets important regulatory criteria by enabling consumers to distinguish such products from conventional seafood products, and by indicating the presence of allergens. From a marketing perspective, "Cell-Based" is also viewed as an appropriate term for describing the process for producing the products, meeting the criteria for transparency. Consumers also had more positive reactions to "Cell-Based Seafood" and were slightly more inclined to want to taste and purchase "Cell-Based" products both before and after learning the meaning of "Cell-Based" and "Cell-Cultured." Therefore, "Cell-Based Seafood" should be adopted as the best common or usual name to label cell-based seafood products.

Practical ApplicationWidespread adoption and consistent use of a single "common or usual name" for "Cell-Based" seafood, meat, poultry and other products by the food industry, regulators, journalists, marketers, environmental, consumer, and animal rights advocates, and other key stakeholders would help shape public perceptions and understanding of this rapidly advancing technology and its products. This study confirms that "Cell-Based Seafood" is the best performing term to label seafood products made from the cells of fish. It meets relevant FDA regulatory requirements and slightly outperforms "Cell-Cultured Seafood" with regard to positive consumer perceptions, interest in tasting and likelihood of purchasing these novel products.


title: Abnormal function in dentate nuclei precedes the onset of psychosis: a resting-state fMRI study in high-risk individuals

abstract:
ObjectiveThe cerebellum serves a wide range of functions and is suggested to be composed of discrete regions dedicated to unique functions. We recently developed a new parcellation of the dentate nuclei (DN), the major output nuclei of the cerebellum, which optimally divides the structure into three functional territories that contribute uniquely to default-mode, motor-salience, and visual processing networks as indexed by resting-state functional connectivity (RsFc). Here we test for the first time whether RsFc differences in the DN precede the onset of psychosis in individuals at risk of developing schizophrenia.

MethodsWe used the MRI dataset from the Shanghai At Risk for Psychosis study that included subjects at high risk to develop schizophrenia (N=144), with longitudinal follow-up to determine which subjects developed a psychotic episode within one year of their fMRI scan (converters N=23). Analysis used the three functional parcels (default-mode, salience-motor, and visual territory) from the DN as seed regions of interest for whole-brain RsFc analysis.

ResultsRsFc analysis revealed abnormalities at baseline in high-risk individuals who developed psychosis, compared to high-risk individuals who did not develop psychosis. The nature of the observed abnormalities was found to be anatomically specific such that abnormal RsFc was localized predominantly in cerebral cortical networks that matched the three functional territories of the DN that were evaluated.

ConclusionsWe show for the first time that abnormal RsFc of the DN may precede the onset of psychosis. This new evidence highlights the role of the cerebellum as a potential target for psychosis prediction and prevention.


title: GMSECT: Genome-Wide Massive Sequence Exhaustive Com-parison Tool for structural and copy number variations

abstract: GMSECT is a parallel robust  Application Interface that efficiently handles the large genomic sequences for rapid and efficient processing. It is a  message passing interface based parallel computing  Tool that can be operated on a cluster for  Massive Sequences Exhaustive Comparison, to identify matches such as the structural variants. The GMSECT algorithm can be implemented using other parallel application programming interfaces as well such as Posix-Threads or can even be implemented in a serial submission fashion. There is complete flexibility to the choice of comparison tool that can be deployed and with the optional parameters as of the choice of comparison tools to suit the speed, sensitivity and specificity of pair wise alignment. The algorithm is simple and robust, and can be applied to compare multiple genomes, chromosomes or large sequences, of different individuals for personalized genome comparison and works good for homologous as well as distant species. The tool can even be applied to smaller genomes like the microbial genome such as the Escherichia coli or algae such as Chlamydomonas reihardtti or yeast Saccharomyces cerevisiae to quickly conduct comparisons, and thus finds its application to the pharmaceuticals and microbial product based firms for research and development. The application Interface can efficiently and rapidly compare massive sequences to detect for the presence of numerous types of DNA variation existing in the genome ranging from single nucleotide polymorphism (SNPs) to larger structural alterations, such as copy-number variants (CNVs) and inversions. The new algorithm has been tested for comparing the chromosome 21 of Celeras R27c compilation with all the 48 chromosomes of Celeras R27c compilation and with all the 48 chromosomes of the human Build 35 reference sequence, which took just 2 Hours and 10 minutes using the pair wise blast algorithm choice and with 110 processors each with 2.2 GHz capacity and 2 GB memory. GMSECT facilitates rapid scanning and interpretation in personalized sequencing project. The application interface with the above resources and alignment choice is estimated to do exhaustive comparison of the human genome with itself in just 2.35 days. An exhaustive comparison of an individuals genome with a reference genome would comprise of a two  self genome comparison and a  non-self genome comparison which is estimated to take about 9.4 days with the above resources. With the advent of personalized genome sequencing project, it would be desirable to compare 100s of individuals genome with a reference genome. This would involve a  non-self genome and a  self genome comparison for each genome, and would take around 7 days for each individuals genome using GMSECT and the above mentioned resources.

category: bioinformatics


title: Identification of the Rigid Core for Aged Liquid Droplets of the TDP-43 Low Complexity Domain

abstract:
The biomolecular condensation of proteins with low complexity sequences plays a functional role in RNA metabolism and a pathogenic role in neurodegenerative diseases. The formation of dynamic liquid droplets brings biomolecules together to achieve complex cellular functions. The rigidification of liquid droplets into {beta}-strand-rich hydrogel structures composed of protein fibrils is thought to be purely pathological in nature. However, low complexity sequences often harbor multiple fibril-prone regions with delicately balanced functional and pathological interactions. Here, we investigate the maturation of liquid droplets formed by the low complexity domain of the TAR DNA-binding protein 43 (TDP-43). Solid state nuclear magnetic resonance measurements on the aged liquid droplets identify a structured core region distinct from the region thought to be most important for pathological fibril formation and aggregation. The results of this study show that multiple segments of this low complexity domain are prone to form fibrils, and that stabilization of {beta}-strand-rich structure in one segment precludes the other region from adopting rigid fibril structure.

Table of Contents Graphic

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category: biophysics


title: Single Image-based Vignetting Correction for Improving the Consistency of Neural Activity Analysis in 2-Photon Functional Microscopy

abstract: High-resolution functional 2-photon microscopy of neural activity is a cornerstone technique in current neuroscience, enabling, for instance, the image-based analysis of relations of the organization of local neuron populations and their temporal neural activity patterns. Interpreting local image intensity as a direct quantitative measure of neural activity presumes, however, a consistent within- and across-image relationship between the image intensity and neural activity, which may be subject to interference by illumination artifacts. In particular, the so-called vignetting artifact - the decrease of image intensity towards the edges of an image - is, at the moment, widely neglected in the context of functional microscopy analyses of neural activity, but potentially introduces a substantial center-periphery bias of derived functional measures. In the present report, we propose a straightforward protocol for single image-based vignetting correction. Using immediate-early-gene-based 2-photon microscopic neural image data of the mouse brain, we show the necessity of correcting both image brightness and contrast to improve within- and across-image intensity consistency and demonstrate the plausibility of the resulting functional data.


title: Acetylcholine boosts dendritic NMDA spikes in a CA3 pyramidal neuron model

abstract:
Acetylcholine has been proposed to facilitate the formation of memory ensembles within the hippocampal CA3 network, by enhancing plasticity at CA3-CA3 recurrent synapses. Regenerative NMDA receptor (NMDAR) activation in CA3 neuron dendrites (NMDA spikes) increase synaptic Ca2+ influx and can trigger this synaptic plasticity. Acetylcholine inhibits potassium channels which enhances dendritic excitability and therefore could facilitate NMDA spike generation. Here, we investigate NMDAR-mediated nonlinear synaptic integration in stratum radiatum (SR) and stratum lacunosum moleculare (SLM) dendrites in a reconstructed CA3 neuron computational model and study the effect of acetylcholine on this nonlinearity. We found that distal SLM dendrites, with a higher input resistance, had a lower threshold for NMDA spike generation compared to SR dendrites. Simulating acetylcholine by blocking potassium channels (M-type, A-type, Ca2+-activated, and inwardly-rectifying) increased dendritic excitability and reduced the number of synapses required to generate NMDA spikes, particularly in the SR dendrites. The magnitude of this effect was heterogeneous across different dendritic branches within the same neuron. These results predict that acetylcholine facilitates dendritic integration and NMDA spike generation in selected CA3 dendrites which could strengthen connections between specific CA3 neurons to form memory ensembles.

Highlights- Using biophysical computational models of CA3 pyramidal neurons we estimated the quantitative effects of acetylcholine on nonlinear synaptic integration.
- Nonlinear NMDA spikes can be triggered by fewer synapses in distal dendrites due to increased local input resistance.
- Acetylcholine broadly reduces the number of synapses needed to trigger NMDA spikes, but the magnitude of the effect varies across dendrite branches within a single neuron.
- No single potassium channel type is the dominant mediator of the excitability effects of acetylcholine.


title: Acid sphingomyelinase deactivation post-ischemia/ reperfusion promotes cerebral angiogenesis and brain remodeling via small extracellular vesicles

abstract: Functional inhibitors of acid sphingomyelinase are clinically used as anti-depressants since [~]60 years. Here, we show that acid sphingomyelinase inhibition by the antidepressants amitriptyline, fluoxetine and desipramine protects from ischemia/reperfusion and elicits a profound brain remodeling response with increased angiogenesis, improved blood-brain barrier integrity, reduced brain leukocyte infiltration and increased neuronal survival. Angiogenesis is promoted by small extracellular vesicles with bona fide characteristics of exosomes, which are released from endothelial cells and which constitute an elegant target for the amplification of stroke recovery.


title: The spatiotemporal organization of experience dictates hippocampal involvement in primary visual cortical plasticity

abstract: The hippocampus and neocortex are theorized to be crucial partners in the formation of long-term memories. Here, we assess hippocampal involvement in two related forms of experience-dependent plasticity in the primary visual cortex (V1) of mice. Like control animals, those with hippocampal lesions exhibit potentiation of visually evoked potentials following passive daily exposure to a phase reversing oriented grating stimulus, which is accompanied by long-term habituation of a reflexive behavioral response. Thus, low-level recognition memory is formed independently of the hippocampus. However, response potentiation resulting from daily exposure to a fixed sequence of four oriented gratings is severely impaired in mice with hippocampal damage. A feature of sequence plasticity in V1 of controls, but absent in lesioned mice, is generation of predictive responses to an anticipated stimulus element when it is withheld or delayed. Thus, hippocampus is involved in encoding temporally structured experience, even in primary sensory cortex.


title: AB12PHYLO: an integrated pipeline for Maximum Likelihood phylogenetic inference from ABI trace data

abstract:
Multi-gene phylogenies constructed from multiplexed and Sanger sequencing data are regularly used in mycology and other disciplines as a cost-effective way of species identification and as a first means to investigate genetic diversity samples.

Today, a number of tools exist for each of the steps in this analysis, including quality control and trimming, the generation of a multiple sequence alignment (MSA), extraction of informative sites, and the construction of the final phylogenetic tree. A BLAST search in a reference database is often performed to identify sequences of type specimens to compare the samples with in the phylogeny. Made over the past decades, these tools are all independent from and often not perfectly adapted to one another.

We present AB12PHYLO, an integrated pipeline that can perform all necessary steps from reading in raw Sanger sequencing data through visualizing and editing phylogenies. In addition, AB12PHYLO can calculate basic summary statistics for each gene in the phylogeny.

AB12PHYLO is designed as a wrapper of several open access and commonly used tools for each of the intermediate stages, and intended to simplify the phylogenetic pipeline while still allowing a high degree of access. It comes as a command-line version for the highest reproducibility and an intuitive graphical user interface (GUI) for easy adoption by IT-agnostic end-users. The use of AB12PHYLO significantly reduces the hands-on working time for these analyses.

category: evolutionary biology


title: When is it Worth Working for Water? A Utility Maximization Theory

abstract: In the laboratory, animals motivation to work tends to be positively correlated with reward magnitude. But in nature, rewards earned by work are essential to survival (e.g., working to find water), and the payoff of that work can vary on long timescales (e.g., seasonally). Under these constraints, the strategy of working less when rewards are small could be fatal. We found that instead, rats in a closed economy did more work for water rewards when the rewards were stably smaller, a phenomenon also observed in human labor supply curves. Like human consumers, rats also showed elasticity of demand, consuming far more water per day when its price in effort was lower. The neural mechanisms underlying such "rational" market behaviors remain largely unexplored. We propose a dynamic utility maximization model that can account for the dependence of rat labor supply (trials/day) on the wage rate (ml/trial), and also predict the temporal dynamics of when rats work. Based on data from mice, we hypothesize that SFOGLUT neurons in lamina terminalis continuously compute the instantaneous marginal utility of voluntary work for water reward, and causally determine the amount and timing of work.


title: Rattus Economicus: A neural model for rational regulation of water-seeking effort in rodents


title: PuBliCiTy: Python Bioimage Computing Toolkit

abstract:
The Python Bioimage Computing Toolkit (PuBliCiTy) is an evolving set of functions, scripts, and classes, written primarily in Python, to facilitate the analysis of biological images, of two or more dimensions, from electron or light microscopes. While the early development was guided by the goal of replacing an existing internal code-base with Python code, the effort later came to include novel tools, specially in the areas of machine learning infrastructure and model development. The toolkit is built on top of the so-called python data science stack, which includes numpy, scipy, scikit-image, scikit-learn, and pandas. It also contains some deep learning models, written in TensorFlow and PyTorch, and a web-app for image annotation, which uses Flask as the web framework. The main features of the toolkit are: (1) simplifying the interface of some routinely used functions from underlying libraries; (2) providing helpful tools for the analysis of large images; (3) providing a web interface for image annotation, which can be used remotely and on tablets with pencils; (4) providing machine learning model implementations that are easy to read, train, and deploy - written in a way that minimizes complexity for users without a computer science or software development background. The source code is released under an MIT-like license at github.com/hms-idac/PuBliCiTy. Details, tutorials, and up-to-date documentation can be found at the projects page as well.

Project pagegithub.com/hms-idac/PuBliCiTy


title: ISTDECO: In Situ Transcriptomics Decoding by Deconvolution

abstract:
In Situ Transcriptomics (IST) is a set of image-based transcriptomics approaches that enables localisation of gene expression directly in tissue samples. IST techniques produce multiplexed image series in which fluorescent spots are either present or absent across imaging rounds and colour channels. A spots presence and absence form a type of barcoded pattern that labels a particular type of mRNA. Therefore, the expression of a gene can be determined by localising the fluorescent spots and decode the barcode that they form. Existing IST algorithms usually do this in two separate steps: spot localisation and barcode decoding. Although these algorithms are efficient, they are limited by strictly separating the localisation and decoding steps. This limitation becomes apparent in regions with low signal-to-noise ratio or high spot densities. We argue that an improved gene expression decoding can be obtained by combining these two steps into a single algorithm. This allows for an efficient decoding that is less sensitive to noise and optical crowding.

We present IST Decoding by Deconvolution (ISTDECO), a principled decoding approach combining spectral and spatial deconvolution into a single algorithm. We evaluate ISTDECO on simulated data, as well as on two real IST datasets, and compare with state-of-the-art. ISTDECO achieves state-of-the-art performance despite high spot densities and low signal-to-noise ratios. It is easily implemented and runs efficiently using a GPU.

ISTDECO implementation, datasets and demos are available online at: github.com/axanderssonuu/istdeco


title: Interpretable Drug Target Predictions using Self-Expressiveness

abstract: The identification of missing drug targets is critical for the development of treatments and for the molecular elucidation of drug side effects. Drug targets have been predicted by exploiting molecular, biological or pharmacological features of drugs and protein targets. Yet, developing integrative and interpretable machine learning models for predicting drug targets remains a challenging task. We present Inception, an integrative and interpretable matrix completion model for predicting drug targets. Inception is a self-expressive model that learns two similarity matrices: one for drugs and another for protein targets. These learned similarity matrices are key for our models interpretability: they can explain how a predicted drug-target interaction can be explain in terms of a linear combination of chemical, biological and pharmacological similarities. We develop a novel objective function with efficient closed-form solution. To demonstrate the ability of Inception at recovering missing drug-target interactions (DTIs), we perform cross-validation experiments with stringent controls of data imbalance, chemical similarities between drugs and sequence similarities between targets. We also assess the performance of our model using a simulated prospective approach. Having trained our model with DTIs from a snapshot 2011 of the DrugBank database, we test whether we could predict DTIs from a 2020 snapshot of DrugBank. Inception outperforms two state-of-the-art drug target prediction models in all the scenarios. This suggests that Inception could be useful for predicting missing drug target interactions while providing interpretable predictions.


title: Taxon-specific phytoplankton growth, nutrient utilization, and light limitation in the oligotrophic Gulf of Mexico

abstract: The highly stratified, oligotrophic regions of the oceans are predominantly nitrogen limited in the surface ocean and light limited at the deep chlorophyll maximum (DCM). Hence, determining light and nitrogen co-limitation patterns for diverse phytoplankton taxa is crucial to understanding marine primary production throughout the euphotic zone. During two cruises in the deep-water Gulf of Mexico, we measured primary productivity (H13CO3-), nitrate uptake (15NO3-), and ammonium uptake (15NH4+) throughout the water column. Primary productivity declined with depth from the mixed-layer to the DCM, averaging 27.1 mmol C m-2 d-1. The fraction of growth supported by NO3- was consistently low, with upper euphotic zone values ranging from 0.01 to 0.14 and lower euphotic zone values ranging from 0.03 to 0.44. Nitrate uptake showed strong diel patterns (maximum during the day), while ammonium uptake exhibited no diel variability. To parameterize taxon-specific phytoplankton nutrient and light utilization, we used a data assimilation approach (Bayesian Markov Chain Monte Carlo) including primary productivity, nutrient uptake, and taxon-specific growth rate measurements. Parameters derived from this analysis define distinct niches for five phytoplankton taxa (Prochlorococcus, Synechococcus, diatoms, dinoflagellates, and prymnesiophytes) and may be useful for constraining biogeochemical models of oligotrophic open-ocean systems.

category: plant biology


title: Spontaneous neural oscillations influence behavior and sensory representations by suppressing neuronal excitability

abstract: The ability to process and respond to external input is critical for adaptive behavior. Why, then, do neural and behavioral responses vary across repeated presentations of the same sensory input? Spontaneous fluctuations of neuronal excitability are currently hypothesized to underlie the trial-by-trial variability in sensory processing. To test this, we capitalized on invasive electrophysiology in neurosurgical patients performing an auditory discrimination task with visual cues: specifically, we examined the interaction between prestimulus alpha oscillations, excitability, task performance, and decoded neural stimulus representations. We found that strong prestimulus oscillations in the alpha+ band (i.e., alpha and neighboring frequencies), rather than the aperiodic signal, correlated with a low excitability state, indexed by reduced broadband high-frequency activity. This state was related to slower reaction times and reduced neural stimulus encoding strength. We propose that the alpha+ rhythm modulates excitability, thereby resulting in variability in behavior and sensory representations despite identical input.


title: Genetic Basis of Variation in Cocaine and Methamphetamine Consumption in Outbred Populations of Drosophila melanogaster

abstract:
We used Drosophila melanogaster to map the genetic basis of naturally occurring variation in voluntary consumption of cocaine and methamphetamine. We derived an outbred advanced intercross population (AIP) from 37 sequenced inbred wild-derived lines of the Drosophila melanogaster Genetic Reference Panel (DGRP), which are maximally genetically divergent, have minimal residual heterozygosity, are not segregating for common inversions, and are not infected with Wolbachia pipientis. We assessed consumption of sucrose, methamphetamine-supplemented sucrose and cocaine-supplemented sucrose, and found considerable phenotypic variation for consumption of both drugs, in both sexes. We performed whole genome sequencing and extreme QTL mapping on the top 10% of consumers for each replicate, sex and condition, and an equal number of randomly selected flies. We evaluated changes in allele frequencies among high consumers and control flies and identified 3,033 variants significantly (P < 1.9 x 10-8) associated with increased consumption, located in or near 1,962 genes. Many of these genes are associated with nervous system development and function, and 77 belong to a known gene-gene interaction subnetwork. We assessed the effects of RNA interference (RNAi) on drug consumption for 22 candidate genes; 17 had a significant effect in at least one sex. We constructed allele-specific AIPs which were homozygous for alternative candidate alleles for 10 SNPs and measured average consumption for each population; nine SNPs had significant effects in at least one sex. The genetic basis of voluntary drug consumption in Drosophila is polygenic and implicates genes with human orthologs and associated variants with sex- and drug-specific effects.

Significance StatementThe use of cocaine and methamphetamine presents significant socioeconomic problems. However, identifying the genetic underpinnings that determine susceptibility to substance use is challenging in human populations. The fruit fly, Drosophila melanogaster, presents a powerful genetic model since we can control the genetic background and environment, 75% of disease-causing genes in humans have a fly counterpart, and flies - like humans - exhibit adverse effects upon cocaine and methamphetamine exposure. We showed that the genetic architecture underlying variation in voluntary cocaine and methamphetamine consumption differs between sexes and is dominated by variants in genes associated with connectivity and function of the nervous system. Results obtained from the Drosophila gene discovery model can guide studies on substance abuse susceptibility in human populations.

category: genetics


title: Brain expression quantitative trait locus and network analysis reveals downstream effects and putative drivers for brain-related diseases

abstract:
Gaining insight into the downstream consequences of non-coding variants is an essential step towards the identification of therapeutic targets from genome-wide association study (GWAS) findings. Here we have harmonized and integrated 8,727 RNA-seq samples with accompanying genotype data from multiple brain-regions from 14 datasets. This sample size enabled us to perform both cis- and trans-expression quantitative locus (eQTL) mapping. Upon comparing the brain cortex cis-eQTLs (for 12,307 unique genes at FDR<0.05) with a large blood cis-eQTL analysis (n=31,684 samples), we observed that brain eQTLs are more tissue specific than previously assumed.

We inferred the brain cell type for 1,515 cis-eQTLs by using cell type proportion information. We conducted Mendelian Randomization on 31 brain-related traits using cis-eQTLs as instruments and found 159 significant findings that also passed colocalization. Furthermore, two multiple sclerosis (MS) findings had cell type specific signals, a neuron-specific cis-eQTL for CYP24A1 and a macrophage specific cis-eQTL for CLECL1.

To further interpret GWAS hits, we performed trans-eQTL analysis. We identified 2,589 trans-eQTLs (at FDR<0.05) for 373 unique SNPs, affecting 1,263 unique genes, and 21 replicated significantly using single-nucleus RNA-seq data from excitatory neurons.

We also generated a brain-specific gene-coregulation network that we used to predict which genes have brain-specific functions, and to perform a novel network analysis of Alzheimers disease (AD), amyotrophic lateral sclerosis (ALS), multiple sclerosis (MS) and Parkinsons disease (PD) GWAS data. This resulted in the identification of distinct sets of genes that show significantly enriched co-regulation with genes inside the associated GWAS loci, and which might reflect drivers of these diseases.

category: genomics


title: Deciphering enhancer sequence using thermodynamics-based models and convolutional neural networks

abstract: Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and underlying mechanisms; however, there has been no systematic comparison of these models characterizing their relative strengths and shortcomings. Here, we interrogated a rich data set of neuroectodermal enhancers in Drosophila, representing cis- and trans- sources of expression variation, with a suite of biophysical and machine learning models. We performed rigorous comparisons of thermodynamics-based models implementing different mechanisms of activation, repression, and cooperativity. Moreover, we developed a convolutional neural network (CNN) model, called CoNSEPT, that learns enhancer "grammar" in an unbiased manner. CoNSEPT is the first general-purpose CNN tool for predicting enhancer function in varying conditions, and we show that such complex models can suggest interpretable mechanisms. We found model-based evidence for mechanisms previously established for the studied system, including cooperative activation and short-range repression. The data also favored one hypothesized activation mechanism over another and suggested an intriguing role for a direct, distance-independent repression mechanism. Our modeling shows that while fundamentally different models can yield similar fits to data, they vary in their utility for mechanistic inference. CoNSEPT is freely available at: https://github.com/PayamDiba/CoNSEPT.


title: Mako: a graph-based pattern growth approach to detect complex structural variants

abstract: Complex structural variants (CSVs) are genomic alterations that have more than two breakpoints and are considered as simultaneous occurrence of simple structural variants. However, detecting the compounded mutational signals of CSVs is challenging through a commonly used model-match strategy. As a result, there has been limited progress for CSV discovery compared with simple structural variants. We systematically analyzed the multi-breakpoint connection feature of CSVs, and proposed Mako, utilizing a bottom-up guided model-free strategy, to detect CSVs from paired-end short-read sequencing. Specifically, we implemented a graph-based pattern growth approach, where the graph depicts potential breakpoint connections and pattern growth enables CSV detection without predefined models. Comprehensive evaluations on both simulated and real datasets revealed that Mako outperformed other algorithms. Notably, validation rates of CSV on real data based on experimental and computational validations as well as manual inspections are around 70%, where the medians of experimental and computational breakpoint shift are 13bp and 26bp, respectively. Moreover, Mako CSV subgraph effectively characterized the breakpoint connections of a CSV event and uncovered a total of 15 CSV types, including two novel types of adjacent segments swap and tandem dispersed duplication. Further analysis of these CSVs also revealed impact of sequence homology in the formation of CSVs. Mako is publicly available at https://github.com/jiadong324/Mako.


title: Detecting Selection in Low-Coverage High-Throughput Sequencing Data using Principal Component Analysis

abstract: 1Identification of selection signatures between populations is often an important part of a population genetic study. Leveraging high-throughput DNA sequencing larger sample sizes of populations with similar ancestries has become increasingly common. This has led to the need of methods capable of identifying signals of selection in populations with a continuous cline of genetic differentiation. Individuals from continuous populations are inherently challenging to group into meaningful units which is why existing methods rely on principal components analysis for inference of the selection signals. These existing methods require called genotypes as input which is problematic for studies based on low-coverage sequencing data. Here, we present two selections statistics which we have implemented in the PCAngsd framework. These methods account for genotype uncertainty, opening for the opportunity to conduct selection scans in continuous populations from low and/or variable coverage sequencing data. To illustrate their use, we applied the methods to low-coverage sequencing data from human populations of East Asian and European ancestries and show that the implemented selection statistics can control the false positive rate and that they identify the same signatures of selection from low-coverage sequencing data as state-of-the-art software using high quality called genotypes. Moreover, we show that PCAngsd outperform selection statistics obtained from called genotypes from low-coverage sequencing data.


title: On the emergence of orientational order in folded proteins with implications for allostery

abstract: The beautiful structures of single and multi-domain proteins are clearly ordered in some fashion but cannot be readily classified using group theory methods that are successfully used to describe periodic crystals. For this reason, protein structures are considered to be aperiodic, and may have evolved this way for functional purposes, especially in instances that require a combination of softness and rigidity within the same molecule. By analyzing the solved protein structures, we show that orientational symmetry is broken in the aperiodic arrangement of the secondary structural elements (SSEs), which we deduce by calculating the nematic order parameter, P2. We find that the folded structures are nematic droplets with a broad distribution of P2. We argue that non-zero values of P2, leads to an arrangement of the SSEs that can resist external stresses forces, which is a requirement for allosteric proteins. Such proteins, which resist mechanical forces in some regions while being flexible in others, transmit signals from one region of the protein to another (action at a distance) in response to binding of ligands (oxygen, ATP or other small molecules).


title: Modeling of Deformable Cell Separation in a Microchannel with Sequenced Pillars

abstract: Embedded pillar microstructures are an efficient approach for controlling and sculpting shear flow in a microchannel but have not yet demonstrated to be effective for deformability-based cell separation and sorting. Although simple pillar configurations (lattice, line sequence) worked well for size-based separation of rigid particles, they had a low separation efficiency for circulating cells. The objective of this study was to optimize sequenced microstructures for separation of deformable cells. This was achieved by numerical analysis of pairwise cell migration in a microchannel with multiple pillars, which size, longitudinal spacing, and lateral location as well as the cell elasticity and size varied. This study revealed two basic pillar configurations optimized for deformability-based separation: 1) "duplet" that consists of two closely spaced pillars positioned far below the centerline and above the centerline halfway to the wall; and 2) "triplet" composed of three widely-spaced pillars located below, above and at the centerline, respectively. The duplet configuration is well suited for deformable cell separation in short channels, while the triplet or a combination of duplets and triplets provides even better separation in long channels. These optimized pillar microstructures can dramatically improve microfluidic methods for sorting and isolation of blood and rare circulating tumor cells.

category: bioengineering


title: Ventral Stress Fibers Induce Plasma Membrane Deformation in Human Fibroblasts

abstract: Interactions between the actin cytoskeleton and the plasma membrane are essential for many eukaryotic cellular processes. During these processes, actin fibers deform the cell membrane outward by applying forces parallel to the fibers major axis (as in migration) or they deform the membrane inward by applying forces perpendicular to the fibers major axis (as during cytokinesis). Here we describe a novel actin-membrane interaction in human dermal myofibroblasts. When labeled with a cytosolic fluorophore, the myofibroblasts developed prominent fluorescent structures on the ventral side of the cell. These structures are present in the cell membrane and colocalize with ventral actin stress fibers, suggesting that the fibers bend the membrane to form a "cytosolic pocket" for the fluorophores to flow into, creating the observed structures. The existence of this pocket was confirmed by transmission electron microscopy. Dissolving the stress fibers, inhibiting fiber protein binding, or inhibiting myosin II binding of actin removed the observed structures. However, decreasing cellular contractility did not remove the structures. Taken together, our results illustrate a novel actin-membrane bending topology where the membrane is deformed outwards rather than being pinched inwards, resembling the topological inverse of cytokinesis.

category: cell biology


title: Copy number evolution in simple and complex tandem repeats across the C57BL/6 and C57BL/10 inbred mouse lines

abstract: Simple sequence tandem repeats are among the most rapidly evolving compartments of the genome. Some repeat expansions are associated with mammalian disease or meiotic segregation distortion, yet the rates of copy number change across generations are not well known. Here, we use 14 distinct sub-lineages of the C57BL/6 and C57BL/10 inbred mouse strains, which have been evolving independently over about 300 generations, to estimate the rates of copy number changes in genome-wide tandem repeats. Rates of change varied across simple repeats and across lines. Notably, CAG, whose expansions in coding regions are associated with many neurological and other genetic disorders, was highly stable in copy number, likely indicating purifying selection. Rates of change were generally positively correlated with copy number, but the direction and magnitude of changes varied across lines. Some mouse lines experienced consistent losses or gains across most genome-wide simple repeats, but this did not correlate with copy number changes in complex repeats. Rates of copy number change were similar between simple repeats and the much more abundant complex repeats once they were normalized by copy number. Finally, the Y-specific centromeric repeat had a 4-fold higher rate of change than the homologous centromeric repeat on other chromosomes. Structural differences in satellite complexity, or restriction to the Y chromosome and the elevated mutation rate of the male germline, may explain the higher rate of change. Overall, our work underscores the mutational fluidity of long tandem arrays of repeats, and the correlations and constraints between genome-wide tandem repeats which suggest that turnover is not a completely neutral process.


title: Calling differential DNA methylation at cell-type resolution: avoiding misconceptions and promoting best practices

abstract: The accurate detection of cell-type specific DNA methylation alterations in the context of general epigenome studies is an important task to improve our understanding of epigenomics in disease development. Although a number of statistical algorithms designed to address this problem have emerged, the task remains challenging. Here we show that a recent commentary by Rahmani et al, that aims to address misconceptions and best practices in the field, continues to suffer from critical misconceptions in how statistical algorithms should be compared and evaluated. In addition, we report contradictory results on real EWAS datasets.


title: FGFR inhibitor mediated dismissal of SWI/SNF complexes from YAP-dependent enhancers induces adaptive therapeutic resistance

abstract: How cancer cells adapt to evade the therapeutic effects of drugs targeting oncogenic drivers is poorly understood. Here we report an epigenetic mechanism leading to the adaptive resistance of triple-negative breast cancer (TNBC) to fibroblast growth factor receptor (FGFR) inhibitors. Prolonged FGFR inhibition suppresses the function of BRG1-dependent chromatin remodeling leading to an epigenetic state that derepresses YAP-associated enhancers. These chromatin changes induce the expression of several amino acid transporters resulting in increased intracellular levels of specific amino acids that reactivate mTORC1. Collectively, these findings reveal a novel feedback loop involving an epigenetic state transition and metabolic reprogramming that leads to adaptive therapeutic resistance.

category: cancer biology


title: Satellite Cell Expression of RAGE is Important for Collateral Vessel Formation

abstract:
ObjectiveThe growth and remodeling of vascular networks is an important component of the prognosis for patients with peripheral artery disease. One protein that has been previously implicated to play a role in this process is the receptor for advanced glycation end products or RAGE. This study sought to determine the cellular source of RAGE in the ischemic hindlimb and the role of RAGE signaling in this cell type.

Approach and ResultsUsing a hind limb ischemia model of vascular growth, this study found skeletal muscle satellite cells to be a novel major cellular source of RAGE in ischemic tissue by both staining and cellular sorting. While wild type satellite cells increased TNF and MCP-1 production in response to ischemia in vivo and a RAGE ligand in vitro, satellite cells from RAGE knockout mice lacked the increase in cytokine production both in vivo in response to ischemia and in vitro after stimuli with the RAGE ligand HMGB-1. Furthermore, encapsulated wild type satellite cells improved perfusion after hind limb ischemia surgery by both perfusion staining and vessel quantification but RAGE knockout satellite cells provided no improvement over empty capsules.

ConclusionsThus, RAGE expression and signaling in satellite cells is crucial for their response to stimuli and angiogenic and arteriogenic functions.

Graphical Abstract

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title: The Disease-Associated Proteins Drosophila Nab2 and Ataxin-2 Interact with Shared RNAs and Coregulate Neuronal Morphology

abstract: Nab2 encodes a conserved polyadenosine RNA-binding protein (RBP) with broad roles in post-transcriptional regulation, including in poly(A) RNA export, poly(A) tail length control, transcription termination, and mRNA splicing. Mutation of the Nab2 human ortholog ZC3H14 gives rise to an autosomal recessive intellectual disability, but understanding of Nab2/ZC3H14 function in metazoan nervous systems is limited, in part because no comprehensive identification of metazoan Nab2/ZC3H14-associated RNA transcripts has yet been conducted. Moreover, many Nab2/ZC3H14 functional protein partnerships likely remain unidentified. Here we present evidence that Drosophila melanogaster Nab2 interacts with the RBP Ataxin-2 (Atx2), a neuronal translational regulator, and implicate these proteins in coordinate regulation of neuronal morphology and adult viability. We then present the first high-throughput identifications of Nab2- and Atx2-associated RNAs in Drosophila brain neurons using an RNA immunoprecipitation-sequencing (RIP-Seq) approach. Critically, the RNA interactomes of each RBP overlap, and Nab2 exhibits high specificity in its RNA associations in neurons in vivo, associating with a small fraction of all polyadenylated RNAs. The identities of shared associated transcripts (e.g. drk, me31B, stai) and of transcripts specific to Nab2 or Atx2 (e.g. Arpc2, tea, respectively) promise insight into neuronal functions of and interactions between each RBP. Significantly, Nab2-associated RNAs are overrepresented for internal A-rich motifs, suggesting these sequences may partially mediate Nab2 target selection. Taken together, these data demonstrate that Nab2 opposingly regulates neuronal morphology and shares associated neuronal RNAs with Atx2, and that Drosophila Nab2 associates with a more specific subset of polyadenylated mRNAs than its polyadenosine affinity alone may suggest.


title: Closed-loop automated reaching apparatus (CLARA) for interrogating motor systems

abstract: Objective: Personalized neurostimulation is a rapidly expanding category of therapeutics for a broad range of indications. Development of these innovative neurological devices requires high-throughput systems for closed-loop stimulation of model organisms, while monitoring physiological signals and complex, naturalistic behaviors. To address this need, we developed CLARA, a closed-loop automated reaching apparatus. Approach: Using breakthroughs in computer vision, CLARA integrates fully-automated, markerless kinematic tracking of multiple features we use to classify animal behavior and precisely deliver neural stimulation based on behavioral outcomes. CLARA is compatible with advanced neurophysiological tools, enabling the testing of neurostimulation devices and identification of novel neurological biomarkers. Results: The CLARA system tracks unconstrained skilled reach behavior in 3D at 150hz without physical markers. The system fully automates trial initiation and pellet delivery and is capable of accurately delivering stimulation in response to trial outcome with sub-quarter second latency. Mice perform the skilled reach task in the CLARA system at a proficiency similar to manually trained animals. Kinematic data from the CLARA system provided novel insights into the dynamics of reach consistency over the course of learning, suggesting that changes are driven entirely by unsuccessful reach accuracy. Additionally, using the closed-loop capabilities of CLARA, we demonstrate that vagus nerve stimulation (VNS) delivered on reach success improves skilled reach performance and increases reach trajectory consistency in healthy animals. Significance: The CLARA system is the first mouse behavior apparatus that uses markerless pose tracking to provide real-time closed-loop stimulation in response to the outcome of an unconstrained motor task. Additionally, we demonstrate that the CLARA system was essential for our finding that VNS given after successful completion of a motor task improves performance in healthy animals. This approach has high translational relevance for developing neurostimulation technology based on complex human behavior.


title: Multi-scale hierarchical neural network models that bridge from single neurons in the primate primary visual cortex to object recognition behavior

abstract:
Primate visual object recognition relies on the representations in cortical areas at the top of the ventral stream that are computed by a complex, hierarchical network of neural populations. While recent work has created reasonably accurate image-computable hierarchical neural network models of those neural stages, those models do not yet bridge between the properties of individual neurons and the overall emergent behavior of the ventral stream. One reason we cannot yet do this is that individual artificial neurons in multi-stage models have not been shown to be functionally similar to individual biological neurons. Here, we took an important first step by building and evaluating hundreds of hierarchical neural network models in how well their artificial single neurons approximate macaque primary visual cortical (V1) neurons. We found that single neurons in certain models are surprisingly similar to their biological counterparts and that the distributions of single neuron properties, such as those related to orientation and spatial frequency tuning, approximately match those in macaque V1. Critically, we observed that hierarchical models with V1 stages that better match macaque V1 at the single neuron level are also more aligned with human object recognition behavior. Finally, we show that an optimized classical neuroscientific model of V1 is more functionally similar to primate V1 than all of the tested multi-stage models, suggesting room for further model improvements with tangible payoffs in closer alignment to human behavior. These results provide the first multi-stage, multi-scale models that allow our field to ask precisely how the specific properties of individual V1 neurons relate to recognition behavior.

HighlightsO_LIImage-computable hierarchical neural network models can be naturally extended to create hierarchical "brain models" that allow direct comparison with biological neural networks at multiple scales - from single neurons, to population of neurons, to behavior.
C_LIO_LISingle neurons in some of these hierarchical brain models are functionally similar to single neurons in macaque primate visual cortex (V1)
C_LIO_LISome hierarchical brain models have processing stages in which the entire distribution of artificial neuron properties closely matches the biological distributions of those same properties in macaque V1
C_LIO_LIHierarchical brain models whose V1 processing stages better match the macaque V1 stage also tend to be more aligned with human object recognition behavior at their output stage
C_LI


title: Vaccine genetics of IGHV1-2 VRC01-class broadly neutralizing antibody precursor naive human B cells

abstract: A successful HIV vaccine must overcome the hurdle of being able to activate naive precursor B cells encoding features within their germline B cell receptors (BCR) that allow recognition of broadly neutralizing epitopes. Knowledge of whether broadly neutralizing antibody (bnAb) precursor B cells are circulating at sufficient frequencies within individuals in communities heavily impacted by HIV may be important. Using a germline-targeting eOD-GT8 immunogen and high-throughput droplet-based single cell BCR sequencing, we demonstrate that large numbers of paired BCR sequences from multiple donors can be efficiently screened to elucidate precursor frequencies of rare, naive VRC01-class B cells. The results indicate that IGHV1-2 alleles incompatible with VRC01-class responses are relatively common in various human populations, and germline variation within IGHV1-2 associates with gene usage frequencies in the naive BCR repertoire.

category: immunology


title: Bacterial clearance caused by a single anti-M protein antibody simultaneously binding two separate epitopes

abstract: Group A streptococci have evolved multiple strategies to evade human antibodies, making it challenging to create effective vaccines or antibody treatments. Here, we have generated antibodies derived from the memory B cells of an individual who had successfully cleared a group A streptococcal infection. The antibodies bind with high affinity in the central region of the surface-bound M protein. Such antibodies are typically non-opsonic. However, one antibody could effectively promote vital immune functions, including phagocytosis and in vivo protection. Remarkably, this antibody primarily interacts through a bivalent dual-Fab cis mode, where the Fabs bind to two distinct epitopes in the M protein. The dual-Fab cis binding phenomenon is conserved across different groups of M types. In contrast, other antibodies binding with normal single-Fab mode to the same region can not bypass the M proteins virulent effects. A broadly binding, protective monoclonal antibody could be a candidate for anti-streptococcal therapy. Our findings highlight the concept of dual-Fab cis binding as a means to access conserved, and normally non-opsonic regions, for protective antibody targeting.


title: Protection induced by a human monoclonal antibody recognizing two different epitopes in a conserved region of streptococcal M proteins


title: A human monoclonal antibody bivalently binding two different epitopes in streptococcal M protein protects against infection


title: The Orsay Virus as a model for population-wide viral infection dynamics

abstract:
To this day, epidemics pose a considerable threat to mankind. Experimental models that simulate the spread of infectious diseases are thus crucial to the inception of effective control policies. Current models have had great success incorporating virulence and host immune response but do rarely take host genetics, behavior and host environment into account. Here, we present a full-scale imaging setup that utilizes the infection of the nematode C. elegans with a positive-stranded RNA virus (Orsay Virus) to probe key epidemiological parameters and simulate the spread of infection in a whole population. We demonstrate that our system is able to quantify infection levels and host behavior at a high sampling rate and show that different host genetic backgrounds can influence viral spread, while also highlighting the influence of infection on various host behaviors. Future work will allow the isolation of key behavioral and environmental factors that affect viral spread, potentially enabling novel policies to combat the spread of viral infections.

Significance StatementIn the ongoing COVID-19 pandemic, we struggle to find effective control policies that "stop the spread". While current animal models of virus spread in populations are highly sophisticated, they rarely explore effects of host behavior and its environment. We developed an experimental animal model system that allows us to visualize virus transmission in whole populations of C. elegans while also measuring behaviors. We were able to demonstrate how C. elegans genetics influences the progression of viral infection in a population and how animals adjust their behavior when infected. In the future, we envision that animal model systems like ours are used to test the effects of viral control policies on viral spread before they are applied in real world scenarios.


title: Memory CD8+ T cells mediate early pathogen-specific protection through localized delivery of chemokines and IFNγ to clusters of inflammatory monocytes

abstract: While cognate antigen drives clonal expansion of memory CD8+ T cells to achieve sterilizing immunity in immunized hosts, not much is known on how cognate antigen contributes to early mechanisms of protection before clonal expansion occurs. Herein, using distinct models of immunization, we establish that cognate antigen recognition by CD8+ TM cells on dendritic cells initiates their rapid and coordinated production of a burst of CCL3, CCL4 and XCL1 chemokines under the transcriptional control of IRF4. Using intravital microscopy imaging and in vivo monoclonal antibody labelling, we reveal that memory CD8+ T cells undergo antigen-mediated arrest in splenic red pulp clusters of CCR2+ monocytes where they locally deliver both IFN{gamma}- and chemokine-potentiating microbicidal activities to achieve early protection. Thus, rapid and effective memory CD8+ T cell responses require a complex series of spatially and temporally coordinated stepwise molecular and cellular events that quickly restrict microbial pathogen growth and optimize the local delivery of effector molecules before clonal expansion occurs.


title: Ammonia-oxidizing archaea possess a wide range of cellular ammonia affinities

abstract: Nitrification, the oxidation of ammonia to nitrate, is an essential process in the biogeochemical nitrogen cycle. The first step of nitrification, ammonia oxidation, is performed by three, often co- occurring guilds of chemolithoautotrophs: ammonia-oxidizing bacteria (AOB), archaea (AOA), and complete ammonia oxidizers (comammox). Substrate kinetics are considered to be a major niche-differentiating factor between these guilds, but few AOA strains have been kinetically characterized. Here, the ammonia oxidation kinetic properties of 12 AOA representing all major phylogenetic lineages were determined using microrespirometry. Members of the genus Nitrosocosmicus have the lowest substrate affinity of any characterized AOA, which are similar to previously determined affinities of AOB. This contrasts previous assumptions that all AOA possess much higher substrate affinities than their comammox or AOB counterparts. The substrate affinity of ammonia oxidizers correlated with their cell surface area to volume ratios. In addition, kinetic measurements across a range of pH values strongly supports the hypothesis that - like for AOB - ammonia and not ammonium is the substrate for the ammonia monooxygenase enzyme of AOA and comammox. Together, these data will facilitate predictions and interpretation of ammonia oxidizer community structures and provide a robust basis for establishing testable hypotheses on competition between AOB, AOA, and comammox.

category: microbiology


title: Genomic characterization of four novel bacteriophages infecting the clinical pathogen Klebsiella pneumoniae

abstract: Bacteriophages are an invaluable source of novel genetic diversity. Sequencing of phage genomes can reveal new proteins with potential uses as biotechnological and medical tools, and help unravel the diversity of biological mechanisms employed by phages to take over the host during viral infection. Aiming to expand the available collection of phage genomes, we have isolated, sequenced, and assembled the genome sequences of four phages that infect the clinical pathogen Klebsiella pneumoniae: vB_KpnP_FBKp16, vB_KpnP_FBKp27, vB_KpnM_FBKp34, and Jumbo phage vB_KpnM_FBKp24. The four phages show very low (0-13%) identity to genomic phage sequences deposited in the Genbank database. Three of the four phages encode tRNAs and have a GC content very dissimilar to that of the host. Importantly, the genome sequences of the phages reveal potentially novel DNA packaging mechanisms as well as distinct clades of tubulin spindle and nucleus shell proteins that some phages use to compartmentalize viral replication. Overall, this study contributes to uncovering previously unknown virus diversity, and provides novel candidates for phage therapy applications against antibiotic-resistant K. pneumoniae infections.


title: Feline leukemia virus (FeLV) endogenous and exogenous recombination events result in multiple FeLV-B subtypes during natural infection

abstract:
Feline leukemia virus (FeLV) is associated with a range of clinical signs in felid species. The primary hosts of FeLV are domestic cats of the Felis genus that also harbor endogenous FeLV (enFeLV) elements stably integrated in their genomes. EnFeLV elements display 86% nucleotide identity to exogenous, horizontally transmitted FeLV (FeLV-A). Variation between enFeLV and FeLV-A is primarily in the long terminal repeat (LTR) and env regions, which potentiates generation of FeLV-B recombinant subtypes during natural infection with enhanced virulence. The aim of this study was to examine exogenous FeLV (exFeLV) and enFeLV recombination events in a natural FeLV epizootic. We previously described that of 32 individuals in a closed colony with productive FeLV-A infection, 22 had detectable circulating FeLV-B. We cloned and sequenced the env gene of FeLV-B, FeLV-A, and enFeLV spanning known recombination breakpoints, examining between 1-13 clones per individual to assess sequence diversity and recombination sites. We documented multiple recombination breakpoints resulting in the production of unique FeLV-B genotypes. At least half of the cats harbored more than one FeLV-B variant, and almost all animals had variants similar to those recovered from at least one other individual in the colony. This analysis reveals that FeLV-B is predominantly generated de novo within each host, though horizontal transmission may be inferred based upon FeLV-B sequence identities between individuals. This work represents a comprehensive analysis of endogenous-exogenous retroviral interactions with important insights into host-viral interactions that underlie disease pathogenesis in a natural setting.

ImportanceFeline leukemia virus (FeLV) is a felid retrovirus associated with a variety of disease outcomes. Exogenous FeLV-A is the most common horizontally transmitted virus subgroup. Domestic cats (Felis catus) harbor endogenous copies of FeLV (enFeLV) in their genomes. Recombination between FeLV-A and enFeLV may result in emergence of largely replication-defective, but highly virulent recombinant strains. FeLV-B, the most common recombinant form, results when enFeLV env recombines with FeLV-A during FeLV replication. This study evaluated endogenous-exogenous recombination outcomes in a naturally-infected closed colony of domestic cats to determine recombination sites and FeLV-B genotypic heterogeneity associated with enhanced disease virulence. While FeLV-A and enFeLV genotypes were highly conserved, a large number of unique FeLV-B variants were identified in association with predicted recombination hotspots. The findings provide insight into recombination events between viral and host genomes that result in new, and potentially more pathogenic, viral strains.


title: A simple, cost-effective and automation-friendly direct PCR approach for bacterial community analysis

abstract:
Bacterial communities in water, soil, and humans play an essential role in environmental ecology and human health. PCR-based amplicon analysis, such as 16S ribosomal RNA sequencing, is a fundamental tool for quantifying and studying microbial composition, dynamics, and interactions. However, given the complexity of microbial communities, a substantial number of samples becomes necessary to analyses that parse the factors that determine microbial composition. A common bottleneck in performing these kinds of experiments is genomic DNA (gDNA) extraction, which is time-consuming, expensive, and often biased on the types of species. Direct PCR methods are a potentially simpler and more accurate alternative to gDNA extraction methods that do not require the intervening purification step. In this study, we evaluated three variations of direct PCR methods using diverse heterogeneous bacterial cultures, ZymoBIOMICS Microbial Community Standards, and groundwater. By comparing direct PCR methods with DNeasy blood and tissue kits and DNeasy Powersoil kits, we found a specific variant of the direct PCR method exhibits a comparable overall efficiency to the conventional DNeasy Powersoil protocol. We also found the method showed higher efficiency for extracting gDNA from the gram negative strains compared to DNeasy blood and tissue protocol. This direct PCR method is 1600 times cheaper ($0.34 for 96 samples), 10 times simpler (15 min hands-on time for 96 samples) than DNeasy Powersoil protocol. The direct PCR method can also be fully automated, and is compatible with small volume samples, thereby permitting scaling of samples and replicates needed to support high-throughput large-scale bacterial community analysis.

IMPORTANCEUnderstanding bacterial interaction and assembling in complex microbial communities using 16S ribosomal RNA sequencing normally requires a large experimental load. However, the current DNA extraction methods including cell disruption and genomic DNA purification are normally biased, costly, time and labor consuming, and not amenable to miniaturization by droplets or 1536 well plates due to the significant DNA loss during purification step for tiny volume and low cell density samples. Direct PCR method could potentially solve these problems. In this study, we demonstrate a direct PCR method which exhibits similar efficiency as the widely used method - DNeasy Powersoil protocol, while 1600 times cheaper and 10 times faster to execute. This simple, cost-effective, and automation friendly direct PCR based 16S ribosomal RNA sequencing method allows us to study the dynamics, microbial interaction and assembly of varying microbial communities in a high throughput fashion.


title: An ancient retroviral RNA element hidden in mammalian genomes and its involvement in co-opted retroviral gene regulation

abstract: Retroviruses utilize multiple unique RNA elements to control several aspects of RNA processing, such as splicing, subcellular export, and translation. However, it is mostly unclear whether such functional RNA elements are present in endogenous retroviruses (ERVs), many of which were inserted into the host genomes millions of years ago. Previously, in human ERV-derived syncytin-1 gene, we found a cis-acting RNA element named SPRE that enhances its protein expression. In this study, we found a 17-nt common sequence in SPRE of syncytin-1 and another ERV-derived gene, syncytin-2, and the sequence is confirmed to be essential for the expression of the proteins. We detected the sequences of SPRE-like elements in 41 ERV families. Though the SPRE-like elements were not found in currently prevailing (i.e. exogenous) viral sequences, more than thousands of copies of the elements were found in several mammalian genomes, suggesting the ancient integration and propagation of the SPRE-harboring retroviruses in mammalian lineages. Indeed, other mammalian ERV-derived genes: mac-syncytin-3 of macaque, syncytin-Ten1 of tenrec, and syncytin-Car1 of Carnivora contain the SPRE-like elements, and we validated their function for efficient protein expression by in vitro assays. A reporter assay revealed that the enhancement of gene expression by SPRE depended on reporter genes. Moreover, the mutation in SPRE did not affect the gene expression in codon-optimized syncytin-2. However, the same mutation in SPRE impaired the gene expression in wild-type syncytin-2, suggesting that the SPRE dependency of Syncytin-2 expression is due to the negative factors such as inefficient codon frequency or repressive elements within the coding sequence. These results provide new implications that ERVs harbor unique RNA elements involved in the regulation of ERV-derived genes.

category: molecular biology


title: Role of BRCA2 DNA-binding and C-terminal domain on its mobility and conformation in DNA repair

abstract: BRCA2 is an essential protein in genome maintenance, homologous recombination and replication fork protection. Its function includes multiple interaction partners and requires timely localization to relevant sites in the nucleus. We investigated the importance of the highly conserved DNA binding domain (DBD) and C-terminal domain (CTD) of BRCA2. We generated BRCA2 variants missing one or both domains in mouse ES cells and defined their contribution in HR function and dynamic localization in the nucleus, by single particle tracking of BRCA2 mobility. Changes in molecular architecture of BRCA2 induced by binding partners of purified BRCA2 was determined by scanning force microscopy. BRCA2 mobility and DNA damage-induced increase in the immobile fraction was largely unaffected by C- terminal deletions. The purified proteins missing CTD and/or DBD were defective in architectural changes correlating with reduced homologous recombination function in cells. These results emphasize BRCA2 activity at sites of damage beyond promoting RAD51 delivery.


title: A CTDNEP1-lipin 1-mTOR regulatory network restricts ER membrane biogenesis to enable chromosome motions necessary for mitotic fidelity

abstract: The endoplasmic reticulum (ER) dramatically restructures in open mitosis to become excluded from the mitotic spindle; however, the significance of ER reorganization to mitotic progression is not known. Here, we demonstrate that limiting ER membrane biogenesis enables mitotic chromosome movements necessary for chromosome biorientation and prevention of micronuclei formation. Aberrantly expanded ER membranes increase the effective viscosity of the mitotic cytoplasm to physically restrict chromosome dynamics - slowed chromosome motions impede correction of mitotic errors induced by transient spindle disassembly, leading to severe micronucleation. We define the mechanistic link between regulation of ER membrane biogenesis and mitotic fidelity by demonstrating that a CTDNEP1-lipin 1-mTOR regulatory network limits ER lipid synthesis to prevent chromosome missegregation. Together, this work shows that ER membranes reorganize in mitosis to enable chromosome movements necessary for mitotic error correction and reveal dysregulated lipid metabolism as a potential source of aneuploidy in cancer cells.


title: The Cell Surface Receptors Ror1/2 Control Cardiac Myofibroblast Differentiation

abstract:
BackgroundA hallmark of heart failure is cardiac fibrosis, which results from the injury-induced differentiation response of resident fibroblasts to myofibroblasts that deposit extracellular matrix. During myofibroblast differentiation, fibroblasts progress through polarization stages of early pro-inflammation, intermediate proliferation, and late maturation, but the regulators of this progression are poorly understood. Planar cell polarity receptors, receptor tyrosine kinase like orphan receptor 1 and 2 (Ror1/2), can function to promote cell differentiation and transformation. In this study, we investigated the role of the Ror1/2 in a model of heart failure with emphasis on myofibroblast differentiation.

Methods and ResultsThe role of Ror1/2 during cardiac myofibroblast differentiation was studied in cell culture models of primary murine cardiac fibroblast activation and in knockout mouse models that underwent transverse aortic constriction (TAC) surgery to induce cardiac injury by pressure overload. Expression of Ror1 and Ror2 were robustly and exclusively induced in fibroblasts in hearts after TAC surgery, and both were rapidly upregulated after early activation of primary murine cardiac fibroblasts in culture. Cultured fibroblasts isolated from Ror1/2-KO mice displayed a pro-inflammatory phenotype indicative of impaired myofibroblast differentiation. Although the combined ablation of Ror1/2 in mice did not result in a detectable baseline phenotype, TAC surgery led to the death of all mice by day 6 that was associated with myocardial hyper-inflammation and vascular leakage.

ConclusionsTogether, these results show that Ror1/2 are essential for the progression of myofibroblast differentiation and for the adaptive remodeling of the heart in response to pressure overload.


title: Implications of the evolution of agriculture and resource foraging for the maintenance of species diversity and community structure

abstract: Agriculture is found in numerous taxa such as humans, ants, beetles, fishes and even bacteria. This type of niche construction has evolved independently from hunting, though many species remain primarily predators. When a consumer has a positive effect on its resource, we can expect an allocative cost of agriculture, as the agricultural care diverts time and energy from other activities. Defending the resource against predators may divert time from its consumption (exploitation cost). The cost may also occur on the foraging of alternative resources, for instance if the consumer spends more time nearby the farmed resource and underexploiting resources elsewhere (opportunity cost). We here investigate transitions from predation to agriculture in a simple three-species model of a farmer that consumes two resources and has a positive effect on one. We study the conditions for the (co)evolution of the investment into agriculture and specialization on the two resources, and its consequences on the ecological dynamics of the community. Eco-evolutionary dynamics generate a feedback between the evolution of agriculture and specialization on the helped resource, that can lead to varying selected intensity of agriculture, from generalist strategies with no agriculture, to specialist farmers, with possible coexistence between these two extreme strategies.


title: Implications of the (co)evolution of agriculture and resource foraging for the maintenance of species diversity and community structure


title: Limited selection towards lighter seeds in 1 Danish grasslands over an eight-year period

abstract: Time-series analysis of cover data from 236 Danish grassland sites demonstrated community selection on seed mass. Across four grassland habitat types and during an eight-year period there was significant community selection towards lighter seeds. In the analysis, the continuous seed size variable was used to group plant species into functional types. This method was chosen in order to account for the sampling process of the abundance data, and is in contrast to most other analyses of trait selection, where the community weighted mean of the traits is used as the dependent variable. Generally, little is known on the underlying causes of possible plant trait community selection in semi-natural grasslands that are not subjected to successional processes.


title: Limited selection towards lighter seeds in Danish grasslands over an eight-year period


title: Selection towards lighter seeds in Danish grasslands over an eight-year period


title: " Idol with feet of clay ": reliable predictions of forest ecosystem functioning require flawless climate forcings.

abstract:
Climate change affects various aspects of the functioning of ecosystem, especially photosynthesis, respiration and carbon storage. We need accurate modelling approaches (impact models) to simulate the functioning, vitality and provision of ecosystem services of forests in a warmer world. These impact models require climate data as forcings, which are often produced by climate models comparing more or less well with observational climate data. The bias percentage of the climate forcings propagates throughout the modeling chain from the climate model to the impact model.

In this study, we aimed to quantify these bias percentage, addressing three questions: (1) Do the impact model predictions vary when forcing it with different climate models, and how do the predictions under climate model vs. observational climate forcing differ? (2) Does the variability in the impact climate simulations caused by climate forcings fade out at large spatial scale? (3) How the fact of using simulated climatic data affects the process-based model predictions in the case of stressful events?

To answer these questions, we present results obtained over the historical period (e.g. 1970-2010) with the CASTANEA ecophysiological forest model and use the data from three climate models. Our analysis focuses on French forests, studying European beech (Fagus sylvatica), temperate deciduous oaks (Quercus robur and Q. petraea), Scots pine (Pinus sylvestris) and spruce (Picea abies) monospecific stands.

We show that prediction of photosynthesis, respiration and wood growth highly depends on the climate model used, whether debiased or not, and also on species and region considered. Overall, we observed an improvement of prediction after a monthly mean bias or monthly quantile mapping correction for three model considered, but not with the same success. Then we highlighted a large variability in the processes simulated by the impact model under different climate forcings when considering the plot (i.e. scale of a few hectares) scale. This variability fades out at larger scale (e.g. the scale of an ecological region, i.e. 100 km2), owing to an aggregation effect. Moreover, process predictions obtained under different climate forcings are more variable during driest years. These results highlight the necessity to quantify bias and uncertainties in climate forcings before predicting fluxes dynamics with process-based model.


title: Multiple targets of balancing selection in Leishmania donovani complex parasites

abstract: The Leishmania donovani species complex are the causative agents of visceral leishmaniasis, which cause 20-40,000 fatalities a year. Here, we conduct a screen for balancing selection in this species complex. We used 387 publicly-available L. donovani and L. infantum genomes, and sequence 93 isolates of L. infantum from Brazil to describe the global diversity of this species complex. We identify five genetically-distinct populations that are sufficiently represented by genomic data to search for signatures of selection. We find that signals of balancing selection are generally not shared between populations, consistent with transient adaptive events, rather than long-term balancing selection. We then apply multiple diversity metrics to identify candidate genes with robust signatures of balancing selection, identifying a curated set of 19 genes with robust signatures. These include zeta toxin, nodulin-like and flagellum attachment proteins. This study highlights the extent of genetic divergence between L. donovani complex parasites and provides genes for further study.


title: Deriving accurate molecular indicators of protein synthesis through Raman-based sparse classification

abstract: Raman spectroscopy has the ability to retrieve molecular information from live biological samples non-invasively through optical means. Coupled with machine learning, it is possible to use the large amount of information contained in a Raman spectrum to create models that can predict the state of new samples based on statistical analysis from previous measurements. Furthermore, in case of linear models, the separation coefficients can be used to interpret which bands are contributing to the discrimination between experimental conditions, which correspond here to single-cell measurements of macrophages under in vitro immune stimulation. We here evaluate a typical linear method using discriminant analysis and PCA, and compare it to regularized logistic regression (Lasso). We find that the use of PCA is not beneficial to the classification performance. Furthermore, the Lasso approach yields sparse separation vectors, since it suppresses spectral coefficients which do not improve classification, making interpretation easier. To further evaluate the approach, we apply the Lasso technique to a well-defined case where protein synthesis is inhibited, and show that the separating features are consistent with RNA accumulation and protein levels depletion. Surprisingly, when Raman features are selected purely in terms of their classification power (Lasso), the selected coefficients are contained in side bands, while typical strong Raman peaks are not present in the discrimination vector. We propose that this occurs because large Raman bands are representative of a wide variety of cellular molecules and are therefore less suited for accurate classification.

category: biochemistry


title: Structural basis for the hyperthermostability of an archaeal glutaminase induced by post-translational succinimide formation

abstract: Stability of proteins from hyperthermophiles enabled by reduction of conformational flexibility is realized through various mechanisms. Presence of a stable, hydrolysis-resistant succinimide arising from cyclization of the side chains of aspartyl/asparaginyl residues with backbone amide -NH of the succeeding residue would restrain the torsion angle {Psi}. Here, we describe the crystal structure of Methanocaldococcus jannaschii glutamine amidotransferase (MjGATase) and address the mechanism of a succinimide-induced increased thermostability using molecular dynamics simulations. This study reveals the interplay of negatively charged electrostatic shield and n[->]{pi}* interactions in preventing succinimide hydrolysis. The stable succinimidyl residue induces formation of a  conformational-lock, reducing protein flexibility. Protein destabilization upon replacement with the {Phi}-restricted prolyl residue highlights the specificity of the conformationally restrained succinimidyl residue in imparting hyperthermostability. The conservation of succinimide-forming tripeptide sequence (E(N/D)(E/D)) in a group of archaeal GATases suggests an adaptation of this otherwise detrimental post-translational modification as an inducer of thermostability.