title: The chemotherapeutic drug methotrexate selects for antibiotic resistance

abstract:
Understanding drivers of antibiotic resistance evolution is fundamental for designing optimal treatment strategies and interventions to reduce the spread of antibiotic resistance. Various cytotoxic drugs used in cancer chemotherapy have antibacterial properties, but how bacterial populations are affected by these selective pressures is unknown. Here we test the hypothesis that the widely used cytotoxic drug methotrexate affects the evolution and selection of antibiotic resistance through the same mechanisms as the antibiotic trimethoprim. We show that methotrexate can select for trimethoprim resistance determinants located on the chromosome or a plasmid in clinical strains of Escherichia coli. Additionally, methotrexate can co-select for virtually any antibiotic resistance determinant when present together with trimethoprim resistance on a multidrug-resistance clinical plasmid. These selective effects occur at concentrations 40- to >320-fold below the methotrexate minimal inhibitory concentration for E. coli, suggesting a selective role of methotrexate chemotherapy for antibiotic resistance in patients that strongly depend on effective antibiotic treatment.

Significance statementThe presented data show that methotrexate has the potential to select for virtually any given antibiotic resistance gene when genetically linked to trimethoprim resistance. This study highlights the need for increased awareness of the presence of acquired antibiotic resistance determinants in the gut of patients with impaired immunity undergoing methotrexate treatment to preserve the effects of downstream antibiotic treatments.


title: A practical PPE decontamination method using warm air and ambient humidity

abstract: Despite a year-and-a-half of Sars-CoV-2 pandemic experience, personal protective equipment (PPE) remains in short supply1. Current decontamination methods are complex, slow, expensive and particularly ill-suited for low to middle income nations where the need is greatest. We propose a low temperature, ambient humidity decontamination method (WASP-D) based on the thirty minute or less half-life of Sars-CoV-2 (and other common pathogens) at temperatures above 45{degrees}C, combined with the observation that most PPE are designed to be safely transported and stored at temperatures below 50{degrees}C. Decontamination at 12 hours, 46{degrees}C (115{degrees}F) and ambient humidity should consistently reduce SARS-CoV-2 viral load by a factor of 106, without negatively affecting PPE materials or performance.

category: microbiology


title: Homemade Bread: Repurposing an Ancient Technology for in vitro Tissue Engineering

abstract: Numerous synthetic and naturally-occurring biomaterials have been developed to provide such architectures to support the proliferation of mammalian cells in vitro and in vivo. Our group, and others, have shown that scaffolds derived from plants can be utilized for tissue engineering applications in biomedicine and in the burgeoning cultured meat industry. Such scaffolds are ideally straightforward and inexpensive to prepare, allowing researchers to take advantage of their intrinsic 3D microarchitectures. These efforts inspired us to continue to pursue the development of novel and unconventional biomaterials that are easily produced and high performing in vitro. With this in mind, few plant-derived materials are more ubiquitous than bread. Having observed the porosity of the crumb (i.e. the internal bulk) we sought to investigate whether it might support the proliferation of mammalian cells in vitro. Here, we develop and validate a yeast-free "soda bread" that maintains its mechanical stability over several weeks in culture conditions. Importantly, we also demonstrate that control over the mechanical stability of the scaffold can also be achieved with both chemical and enzymatic means. The scaffolding is a heterogeneous and complex structure of isolated and interconnected pores which allow for the proliferation of multiple cell types. We demonstrate here that mouse fibroblasts, myoblasts and pre-osteoblasts are able to proliferate up to four weeks in culture. Immunohistochemistry demonstrates that the fibroblasts are able to deposit their own fibronectin extracellular matrix and that mouse myoblasts are able to differentiate and fuse into myotubes. Although the pre-osteoblasts proliferated over the course of four weeks their ability to differentiate was inconclusive. Metabolic analyses of proliferation, cytotoxicity and oxidative stress reveal that cells remain highly viable and functional on these novel bread scaffolds. While the results presented in this proof-of-concept study create many new questions and opportunities, the results open up novel possibilities in the development of edible scaffolds that may be utilized in future food applications. Bread derived scaffolds represent a surprising alternative to synthetic or animal-derived scaffolds for addressing a diverse variety of tissue engineering challenges in food science. Future studies will delve deeper into investigating these how possibilities might take advantage of the immense breadth of knowledge about bread making and examine their applicability in the development of lab grown foods and broader applications in cellular agriculture.

category: bioengineering


title: MUNIn (Multiple sample UNifying long-range chromatin Interaction detector): a statistical framework for identifying long-range chromatin interactions from multiple samples

abstract: Chromatin spatial organization (interactome) plays a critical role in genome function. Deep understanding of chromatin interactome can shed insights into transcriptional regulation mechanisms and human disease pathology. One essential task in the analysis of chromatin interactomic data is to identify long-range chromatin interactions. Existing approaches, such as HiCCUPS, FitHiC/FitHiC2 and FastHiC, are all designed for analyzing individual cell types or samples. None of them accounts for unbalanced sequencing depths and heterogeneity among multiple cell types or samples in a unified statistical framework. To fill in the gap, we have developed a novel statistical framework MUNIn (Multiple sample UNifying long-range chromatin Interaction detector) for identifying long-range chromatin interactions from multiple samples. MUNIn adopts a hierarchical hidden Markov random field (H-HMRF) model, in which the status (peak or background) of each interacting chromatin loci pair depends not only on the status of loci pairs in its neighborhood region, but also on the status of the same loci pair in other samples. To benchmark the performance of MUNIn, we performed comprehensive simulation studies and real data analysis, and showed that MUNIn can achieve much lower false positive rates for detecting sample-specific interactions (33.1 - 36.2%), and much enhanced statistical power for detecting shared peaks (up to 74.3%), compared to uni-sample analysis. Our data demonstrated that MUNIn is a useful tool for the integrative analysis of interactomic data from multiple samples.

category: genetics


title: Investigation of reward learning and feedback sensitivity in non-clinical participants with a history of early life stress

abstract: Early life stress (ELS) is an important risk factor for the development of depression. Impairments in reward learning and feedback sensitivity are suggested to be an intermediate phenotype in depression aetiology therefore we hypothesised that similar impairments are present in healthy adults with a history of ELS. We recruited 64 adults with high levels of ELS and no diagnosis of a current mental health disorder and 65 controls. Participants completed the probabilistic reversal learning task and probabilistic reward task followed by depression, anhedonia, social status, and stress scales. Participants with high levels of ELS showed decreased positive feedback sensitivity in the probabilistic reversal learning task compared to controls. High ELS participants also trended towards possessing a decreased model-free learning rate. This was coupled with a decreased learning ability in the acquisition phase of block 1 following the practice session. Neither group showed a reward induced response bias in the probabilistic reward task however high ELS participants exhibited decreased stimuli discrimination. Due to the PRT not meeting its primary endpoint a separate cohort of control participants were tested in a modified PRT where they showed a response bias. This indicates the PRT can be successfully carried out online. Overall, these data suggest that healthy participants without a mental health diagnosis and high levels of ELS show deficits in positive feedback sensitivity and reward learning in the probabilistic reversal learning task that are distinct from depressed patients. These deficits may be relevant to increased depression vulnerability.

category: neuroscience


title: Sex-specific lipid profiles in muscle of Atlantic salmon juveniles

abstract: Energy allocation in juvenile fish can have important implications for future life-history progression. Inherited and environmental factors determine when and where individuals allocate energy, and timely and sufficient energy reserves are crucial for reaching key life stages involved in the timing of maturation and sea migration. In Atlantic salmon, lipid reserves are predominantly found in the viscera and myosepta in the muscle and have been shown to play a key role in determining the timing of maturity. This life-history trait is tightly linked to fitness in many species and can be different between males and females, however, the details of relative energy allocation in juveniles of different sexes is not well understood. Therefore, the aim of this study was to investigate the effects of sex, genetics and environment during juvenile development of salmon on the amount and composition of their lipid reserves. To do so, juvenile salmon were fed one of two different lipid food contents during their first summer and autumn under common-garden conditions. Muscle lipid composition and concentrations were determined by thin layer chromatography. The muscle lipid class concentrations covaried negatively with body length and males showed higher concentrations than females for phosphatidylcholine, cholesterol, sphingomyelin, and triacylglycerol. This sex-specific difference in major lipid classes presents a new scope for understanding the regulation of lipids during juvenile development and gives direction for understanding how lipids may interact and influence major life-history traits in Atlantic salmon.

category: molecular biology


title: Beating your neighbor to the berry patch

abstract: Foragers often compete for resources that ripen (or otherwise improve) gradually. What strategy is optimal in this situation? It turns out that there is no optimal strategy. There is no evolutionarily stable strategy (ESS), and the only Nash equilibrium (NE) is unstable: strategies similar to the NE can always invade. But in spite of this instability, the NE is predictive. If harvesting attempts are costly or there are many competitors, the process tends to remain near the unstable NE. In this case, the resource often goes unharvested. Harvesting attempts--when they happen at all--usually occur when the resource is barely ripe enough to offset costs. The more foragers there are, the lower the chance that the resource will be harvested and the greater its mean value when harvested. This counterintuitive behavior is exhibited not only by theoretical models and computer simulations, but also by human subjects in an experimental game.

category: evolutionary biology


title: A model of resource partitioning between foraging bees based on positive and negative associations

abstract: Central place foraging pollinators tend to develop multi-destination routes (traplines) to visit patchily distributed plant resources. While the formation of traplines by individual pollinators has been studied in details, how populations of foragers exploit resources in a common area is an open question, difficult to address experimentally. We explored conditions for the emergence of resource partitioning among traplining bees using agent-based models built from experimental data of bumblebees foraging on artificial flowers. In the models, bees learn to develop routes as a consequence of feedback loops that change their probabilities of moving between flowers. While a positive reinforcement of movements leading to rewarding flowers is sufficient for the emergence of resource partitioning when flowers are evenly distributed, addition of negative reinforcement of movements leading to unrewarding flowers is necessary when flowers are patchily distributed. In environments with more complex spatial structure, the negative experiences of individual bees on flowers favour spatial segregation and efficient collective foraging.

category: animal behavior and cognition


title: Epidural Electrical Stimulation of the Cervical Dorsal Roots Restores Voluntary Arm Control In Paralyzed Monkeys

abstract: Recovering arm control is a top priority for people with paralysis. Unfortunately, the complexity of the neural mechanisms underlying arm control practically limited the effectiveness of neurotechnology approaches. Here, we exploited the neural function of surviving spinal circuits to restore voluntary arm and hand control in three monkeys with spinal cord injury using spinal cord stimulation. Our neural interface leverages the functional organization of the dorsal roots to convey artificial excitation via electrical stimulation to relevant spinal segments at appropriate movement phases. Stimulation bursts targeting specific spinal segments produced sustained arm movements enabling monkeys with arm paralysis to perform an unconstrained reach-and-grasp task. Stimulation specifically improved strength, task performances and movement quality. Electrophysiology suggested that residual descending inputs were necessary to produce coordinated movements. The efficacy and reliability of our approach hold realistic promises of clinical translation.


title: Epidural Electrical Stimulation of the Cervical Dorsal Roots Restores Voluntary Upper Limb Control In Paralyzed Monkeys


title: Automatic wound detection and size estimation using deep learning algorithms

abstract:
Evaluating and tracking wound size is a fundamental metric for the wound assessment process. Good location and size estimates can enable proper diagnosis and effective treatment. Traditionally, laboratory wound healing studies include a collection of images at uniform time intervals exhibiting the wounded area and the healing process in the test animal, often a mouse. These images are then manually observed to determine key metrics --such as wound size progress- relevant to the study. However, this task is a time-consuming and laborious process. In addition, defining the wound edge could be subjective and can vary from one individual to another even among experts. Furthermore, as our understanding of the healing process grows, so does our need to efficiently and accurately track these key factors for high throughput (e.g., over large-scale and long-term experiments). Thus, in this study, we develop a deep learning-based image analysis pipeline that aims to intake non-uniform wound images and extract relevant information such as the location of interest, wound only image crops, and wound periphery size over-time metrics. In particular, our work focuses on images of wounded laboratory mice that are used widely for translationally relevant wound studies and leverages a commonly used ring-shaped splint present in most images to predict wound size. We apply the method to a dataset that was never meant to be quantified and, thus, presents many visual challenges. Additionally, the data set was not meant for training deep learning models and so is relatively small in size with only 256 images. We compare results to that of expert measurements and demonstrate preservation of information relevant to predicting wound closure despite variability from machine-to-expert and even expert-to-expert. The proposed system resulted in high fidelity results on unseen data with minimal human intervention. Furthermore, the pipeline estimates acceptable wound sizes when less than 50% of the images are missing reference objects.

Author summaryKnowledge of the wound size changes over-time allows us to observe important insights such as rate of closure, time to closure, and expansion events, which are key indicators for predicting healing status. To better perform wound measurements it is essential to utilize a technique that returns accurate and consistent results every time. Over the last years, collecting wound images is becoming easier and more popular as digital cameras and smartphones are more accessible. Commonly, scientists/clinicians trace the wound in these images manually to observe changes in the wound, which is normally a slow and labor-intensive process and also requires a trained eye. The clinical goal is to more efficiently and effectively treat wounds by employing easy to use and precise wound measurement techniques. Therefore, the objective should be devising automatic and precise wound measurement tools to be used for wound assessment. To this end, we leveraged a combination of various state-of-the-art computer vision and machine learning-based methods for developing a versatile and automatic wound assessment tool. We applied this tool to analyze the images of wound inflicted lab mice and showed that our developed tool automated the overall wound measurement process, therefore, resulting in high fidelity results without significant human intervention. Furthermore, we compared results to two expert measurements. We found variability in measurement even across experts further validating the need for a consistent approach. However, qualitative behavior, which is most important for predicting wound closure, is preserved.

category: bioinformatics


title: Evaluation of feeding behaviour traits to predict efficiency traits in pigs using partial least square regression

abstract:
The improvement of efficiency traits, such as protein efficiency (PE), digestible energy efficiency (EnE) and lipid gain (LipG), are relevant given their associations with environmental pollution, cost of productions, and the quality of meat. However, these traits are difficult traits to measure and usually require slaughtering of pigs. Efficiency traits are complex, and several factors, such as genetic predisposition, feed composition, but also individual feeding behaviour may contribute to efficiency. The objective of this study was therefore to evaluate the potential of using feeding behaviour traits to predict efficiency traits under dietary protein restriction. A total of 587 Swiss Large White pigs, consisting of 312 females and 275 castrated males, had ad libitum access to feed and water, and were fed a protein-reduced diet (80% of recommended digestible protein and essential amino acids) from 22.5 {+/-} 1.6 to 106.6 {+/-} 4.6 kg BW. Individual feed intake was monitored and carcass composition (lean and fat mass) at slaughter was determined by dual-energy X-ray absorptiometry (DXA). The PE and EnE were calculated as the ratio of protein or energy in the carcass (estimated by DXA) to the total protein or energy consumed. Feeding behaviour traits monitored were daily feed intake (DFI; g/day), feed intake per meal (FIM; g/meal), number of daily meals (NDM; meals/day), duration of meal (DUM; min/meal), feeding rate (FR; g/min), and feeder occupation (FO; min/day). A partial least square (PLS) regression was used to predict PE, EnE and LipG from feeding behaviour traits, while including farrowing series (for PE only), age at slaughter and body weight at slaughter. Accuracy of PLS regression was assessed based on RMSE and R2 for calibration and validation sets, and on concordance correlation coefficient (CCC), which were estimated over 100 replicates of calibration and validation sets. Models with a number of latent variables of 5, 2 and 3 were identified as optimal for PE, EnE, and LipG, which explained 34.64%, 55.42% and 82.68% of the total variation in PE, EnE, and LipG, respectively. Significant CCC were found between predicted and observed values for PE (0.50), EnE (0.70), and LipG (0.90). In conclusion, individual feeding behaviour traits can better predict EnE and LipG than for PE under dietary protein restriction when fed ad libitum.

ImplicationsThis study suggests that five feeding behaviour traits, which are automatically recorded via feeder stations in large numbers with little effort, together with body weight and age, may be used to predict protein efficiency, energy efficiency and lipid gain in Swiss Large White pigs receiving a protein reduced diet with considerable accuracy. This will allow for easy collection of large amounts of data on these traits for precision feeding and genetic selection strategies, especially when additional traits are added in the future to further improve accuracy.

category: physiology


title: Caspases switch off m6A RNA modification pathway to reactivate a ubiquitous human tumor virus

abstract:
The methylation of RNA at the N6 position of adenosine (m6A) orchestrates multiple biological processes to control development, differentiation, and cell cycle, as well as various aspects of the virus life cycle. How the m6A RNA modification pathway is regulated to finely tune these processes remains poorly understood. Here, we discovered the m6A reader YTHDF2 as a caspase substrate via proteome-wide prediction, followed by in vitro and in vivo validations. We further demonstrated that cleavage-resistant YTHDF2 blocks, while cleavage-mimicking YTHDF2 fragments promote, the replication of a common human oncogenic virus, Epstein-Barr virus (EBV). Intriguingly, our study revealed a feedback regulation between YTHDF2 and caspase-8 via m6A modification of CASP8 mRNA and YTHDF2 cleavage during EBV replication. Further, we discovered that caspases cleave multiple components within the m6A RNA modification pathway to benefit EBV replication. Together, our study establishes that caspase disarming of the m6A RNA modification machinery fosters EBV reactivation.

Teaser

Cellular m6A RNA modification machinery is cleaved by caspases to foster the reproduction of a common human tumor virus


title: Flexible fitting of PROTAC concentration-response curves with changepoint Gaussian Processes

abstract: A proteolysis targeting chimera (PROTAC) is a new technology that marks proteins for degradation in a highly specific manner. During screening, PROTAC compounds are tested in concentration-response (CR) assays to determine their potency, and parameters such as the half-maximal degradation concentration (DC50) are estimated from the fitted CR curves. These parameters are used to rank compounds, with lower DC50 values indicating greater potency. However, PROTAC data often exhibit bi-phasic and poly-phasic relationships, making standard sigmoidal CR models inappropriate. A common solution includes manual omitting of points (the so called "masking" step) allowing standard models to be used on the reduced datasets. Due to its manual and subjective nature, masking becomes a costly and non-reproducible procedure. We, therefore, used a Bayesian changepoint Gaussian Processes model that can flexibly fit both non-sigmoidal and sigmoidal CR curves without user input. Parameters, such as the DC50, the maximum effect Dmax, and the point of departure (PoD) are estimated from the fitted curves. We then rank compounds based on one or more parameters, and propagate the parameter uncertainty into the rankings, enabling us to confidently state if one compound is better than another. Hence, we used a flexible and automated procedure for PROTAC screening experiments. By minimizing subjective decisions, our approach reduces time, cost, and ensures reproducibility of the compound ranking procedure. The code and data are provided on GitHub (https://github.com/elizavetase-menova/gp_concentration_response).

category: cell biology


title: Pseudoreplication in genomics-scale datasets

abstract: In genomics-scale datasets, loci are closely packed within chromosomes and hence provide correlated information. Averaging across loci as if they were independent creates pseudoreplication, which reduces the effective degrees of freedom (df) compared to the nominal degrees of freedom, df. This issue has been known for some time, but consequences have not been systematically quantified across the entire genome. Here we measured pseudoreplication (quantified by the ratio df/df) for a common metric of genetic differentiation (FST) and a common measure of linkage disequilibrium between pairs of loci (r2). Based on data simulated using models (SLiM and msprime) that allow efficient forward-in-time and coalescent simulations while precisely controlling population pedigrees, we estimated df and df/df by measuring the rate of decline in the variance of mean FST and mean r2 as more loci were used. For both indices, df increases with Ne and genome size, as expected. However, even for large Ne and large genomes, df for mean r2 plateaus after a few thousand loci, and a variance components analysis indicates that the limiting factor is uncertainty associated with sampling individuals rather than genes. Pseudoreplication is less extreme for FST, but df/df [≤]0.01 can occur in datasets using tens of thousands of loci. Commonly-used block-jackknife methods consistently overestimated var(FST), producing very conservative confidence intervals. Predicting df based on our modeling results as a function of Ne, L, S, and genome size provides a robust way to quantify precision associated with genomics-scale datasets.


title: Stimulus-specific plasticity in human visual gamma-band activity and functional connectivity

abstract: Under natural conditions, the visual system often sees a given input repeatedly. This provides an opportunity to optimize processing of the repeated stimuli. Stimulus repetition has been shown to strongly modulate neuronal-gamma band synchronization, yet crucial questions remained open. Here we used magnetoencephalography in 30 human subjects and find that gamma decreases across ~10 repetitions and then increases across further repetitions, revealing plastic changes of the activated neuronal circuits. Crucially, changes induced by one stimulus did not affect responses to other stimuli, demonstrating stimulus specificity. Changes partially persisted when the inducing stimulus was repeated after 25 minutes of intervening stimuli. They were strongest in early visual cortex and increased interareal feedforward influences. Our results suggest that early visual cortex gamma synchronization enables adaptive neuronal processing of recurring stimuli. These and previously reported changes might be due to an interaction of oscillatory dynamics with established synaptic plasticity mechanisms.


title: The Impact of Neuronal Structure on Cortical Network Architecture

abstract: It has become increasingly clear that the neurons in the cerebral cortex are not randomly interconnected. This wiring specificity can result from synapse formation mechanisms that interconnect neurons depending on their activity or genetically defined identity. Here we report that in addition to these synapse formation mechanisms, the structural composition of the neuropil provides a third prominent source by which wiring specificity emerges in cortical networks. This structurally determined wiring specificity reflects the packing density, morphological diversity and similarity of the dendritic and axonal processes. The higher these three factors are, the more recurrent the topology of the networks. Conversely, low density, diversity and similarity yield feedforward networks. These principles predict connectivity patterns from subcellular to network scales that are remarkably consistent with empirical observations from a rich body of literature. Thus, cortical network architectures reflect the specific morphological properties of their constituents to much larger degrees than previously thought.


title: The Impact of Neuron Morphology on Cortical Network Architecture


title: Community composition of microbial microcosms follows simple assembly rules at evolutionary timescales

abstract: Managing and engineering microbial communities relies on the ability to predict their composition. While progress has been made on predicting compositions on short, ecological timescales, there is still little work aimed at predicting compositions on evolutionary timescales. Therefore, it is still unknown for how long communities typically remain stable after reaching ecological equilibrium, and how repeatable and predictable are changes when they occur. Here, we address this knowledge gap by tracking the composition of 87 two- and three-species bacterial communities for ~400 generations. We find that community composition typically changed during evolution, but that the composition of replicate communities remained similar. Furthermore, these changes were predictable in a bottom-up approach - changes in the composition of trios were consistent with those that occurred in pairs during coevolution. Our results demonstrate that simple assembly rules can hold even on evolutionary timescales, suggesting it may be possible to forecast the evolution of microbial communities.


title: Gene expression profiling of malaria parasites reveals common virulence gene expression in adult first-time infected patients and severecases

abstract: Sequestration of Plasmodium falciparum-infected erythrocytes to host endothelium through the parasite-derived PfEMP1 adhesion proteins is central to the development of malaria pathogenesis. PfEMP1 proteins have diversified and expanded to encompass many sequence variants conferring each parasite a similar array of human endothelial receptor binding phenotypes. Here, we analyzed RNA-seq profiles of parasites isolated from 32 P. falciparum infected adult travelers returning to Germany. Patients were categorized into either malaria naive (n=15) or pre-exposed (n=17), and into severe (n=8) or non-severe (n=24) cases. For differential expression analysis of PfEMP1-encoding var gene transcripts were de novo assembled from RNA-seq data and, in parallel, var expressed sequence tags were analyzed and used to predict the encoded domain composition of the transcripts. Both approaches showed in concordance that severe malaria was associated with PfEMP1 containing the endothelial protein C receptor (EPCR)-binding CIDR1 domain, whereas CD36-binding PfEMP1 was linked to non-severe malaria outcomes. First-time infected adults were more likely to develop severe symptoms and tended to be infected for a longer period. Thus, parasites with more pathogenic PfEMP1 variants are more common in patients with a naive immune status and/or adverse inflammatory host responses to first infections favors growth of EPCR-binding parasites.


title: Spatial and Temporal Localization of SPIRRIG and WAVE/SCAR Reveal Roles for These Proteins in Actin-Mediated Root Hair Development

abstract: Root hairs are single cell protrusions that enable roots to optimize nutrient and water acquisition. They attain their tubular shapes by confining growth to the cell apex, a process called tip growth. The actin cytoskeleton and endomembrane systems are essential for tip growth; however, little is known about how these cellular components coordinate their activities during this process. Here, we show that SPIRRIG (SPI), a BEACH domain-containing protein involved in membrane trafficking, and BRK1 and SCAR2, subunits of the WAVE/SCAR (W/SC) actin nucleating promoting complex, display polarized localizations to root hairs at distinct developmental stages. SPI accumulates at the root hair apex via post-Golgi vesicles and positively regulates tip growth by maintaining tip-focused vesicle secretion and filamentous-actin integrity. BRK1 and SCAR2 on the other hand, mark the root hair initiation domain to specify the position of root hair emergence. Consistent with the localization data, tip growth was reduced in spi and the position of root hair emergence was disrupted in brk1 and scar1234. BRK1 depletion coincided with SPI accumulation as root hairs transitioned from initiation to tip growth. Taken together, our work uncovers a role for SPI in facilitating actin-dependent root hair development through pathways that might intersect with W/SC.

category: plant biology


title: The Nab2 RNA binding protein promotes sex-specific splicing of Sex lethal in Drosophila neuronal tissue

abstract: The Drosophila polyadenosine RNA binding protein Nab2, which is orthologous to a human protein lost in a form of inherited intellectual disability, controls axon projection, locomotion, and memory. Here we define an unexpectedly specific role for Nab2 in regulating splicing of [~]150 exons/introns in the head transcriptome and link the most prominent of these, female retention of a male-specific exon in the sex determination factor Sex-lethal (Sxl), to a role in m6A-dependent mRNA splicing. Genetic evidence indicates that aberrant Sxl splicing underlies multiple phenotypes in Nab2 mutant females. At a molecular level, Nab2 associates with Sxl pre-mRNA and ensures proper female-specific splicing by preventing m6A hypermethylation by Mettl3 methyltransferase. Consistent with these results, reducing Mettl3 expression rescues developmental, behavioral and neuroanatomical phenotypes in Nab2 mutants. Overall these data identify Nab2 as a required regulator of m6A-regulated Sxl splicing and imply a broader link between Nab2 and Mettl3-regulated brain RNAs.

category: developmental biology


title: Characterization and significance of extracellular polymeric substances, reactive oxygen species, and extracellular electron transfer in methanogenic biocathode

abstract: The microbial electrolysis cell assisted anaerobic digestion (MEC-AD) holds great promises over conventional anaerobic digestion. This article reports an experimental investigation of extracellular polymeric substances (EPS), reactive oxygen species (ROS), and the expression of genes associated with extracellular electron transfer (EET) in methanogenic biocathodes. The MEC-AD systems were examined using two cathode materials: carbon fibers and stainless-steel mesh. A higher abundance of hydrogenotrophic Methanobacterium sp. and homoacetogenic Acetobacterium sp. appeared to play a major role in superior methanogenesis from stainless steel biocathode than carbon fibers. Moreover, the higher secretion of EPS accompanied by the lower ROS level in stainless steel biocathode indicated that higher EPS perhaps protected cells from harsh metabolic conditions (possibly unfavorable local pH) induced by faster catalysis of hydrogen evolution reaction. In contrast, EET-associated gene expression patterns were comparable in both biocathodes. Thus, these results indicated hydrogenotrophic methanogenesis is the key mechanism, while cathodic EET has a trivial role in distinguishing performances between two cathode electrodes. These results provide new insights into the efficient methanogenic biocathode development.


title: Bayesian modeling of skewed X inactivation ingenetically diverse mice identifies a novel Xce allele associated with copy number changes

abstract: Female mammals are functional mosaics of their parental X-linked gene expression due to X chromosome inactivation (XCI). This process inactivates one copy of the X chromosome in each cell during embryogenesis and that state is maintained clonally through mitosis. In mice, the choice of which parental X chromosome remains active is determined by the X chromosome controlling element (Xce), which has been mapped to a 176 kb candidate interval. A series of functional Xce alleles has been characterized or inferred for classical inbred strains based on biased, or skewed, inactivation of the parental X chromosomes in crosses between strains. To further explore the function-structure basis and location of the Xce, we measured allele-specific expression of X-linked genes in a large population of F1 females generated from Collaborative Cross strains. Using published sequence data and applying a Bayesian "Polya urn" model of XCI skew, we report two major findings. First, inter-individual variability in XCI suggests mouse epiblasts contain on average 20-30 cells contributing to brain. Second, NOD/ShiLtJ has a novel and unique functional allele, Xcef, that is the weakest in the Xce allelic series. Despite phylogenetic analysis confirming that NOD/ShiLtJ carries a haplotype almost identical to the well-characterized C57BL/6J (Xceb), we observed unexpected patterns of XCI skewing in females carrying the NOD/ShiLtJ haplotype within the Xce. Copy number variation is common at the Xce locus and we conclude that the observed allelic series is a product of independent and recurring duplications shared between weak Xce alleles.


title: Sensitizing Staphylococcus aureus to antibacterial host defense by decoding and blocking the lipid flippase MprF

abstract: The pandemic of antibiotic resistance represents a major human health threat demanding new antimicrobial strategies. MprF is the synthase and flippase of the phospholipid lysyl-phosphatidylglycerol that increases virulence and resistance of methicillin-resistant Staphylococcus aureus (MRSA) and other pathogens to cationic host defense peptides and antibiotics. With the aim to design MprF inhibitors that could sensitize MRSA to both, human antimicrobials and antibiotics and support the clearance of staphylococcal infections with minimal selection pressure, we developed MprF-targeting monoclonal antibodies, which bound and blocked the MprF flippase subunit. Antibody M-C7.1 targeted a specific loop in the flippase domain that proved to be exposed at both sides of the bacterial membrane, thereby enhancing the mechanistic understanding into bacterial lipid translocation. M-C7.1 rendered MRSA susceptible to host antimicrobial peptides and antibiotics such as daptomycin. Moreover, it impaired MRSA survival in human phagocytes, which recommends MprF inhibitors for new anti-MRSA approaches. MprF-directed monoclonal antibodies provide a proof of concept for development of precisely targeted anti-virulence approaches, which block bacterial antimicrobial resistance mechanisms.


title: RNA polymerase backtracking results in the accumulation of fission yeast condensin at active genes

abstract: The mechanisms leading to the accumulation of the SMC complexes condensins around specific transcription units remain unclear. Observations made in bacteria suggested that RNA polymerases (RNAP) constitute an obstacle to SMC translocation, particularly when RNAP and SMC travel in opposite directions. Here we show in fission yeast that gene termini harbour intrinsic condensin-accumulating features whatever the orientation of transcription, which we attribute to the frequent backtracking of RNAP at gene ends. Consistent with this, to relocate backtracked RNAP2 from gene termini to gene bodies was sufficient to cancel the accumulation of condensin at gene ends and to redistribute it evenly within transcription units, indicating that RNAP backtracking may play a key role in positioning condensin. Formalization of this hypothesis in a mathematical model suggests that the inclusion of a sub-population of RNAP with longer dwell-times is essential to fully recapitulate the distribution profiles of condensin around active genes. Taken together, our data strengthen the idea that dense arrays of proteins tightly-bound to DNA alter the distribution of condensin on chromosomes.


title: SMC Complexes Are Guarded by the SUMO Protease Ulp2 Against SUMO-Chain-Mediated Turnover

abstract: Structural maintenance of chromosomes (SMC) complexes, cohesin, condensin and Smc5/6, are essential for viability and participate in multiple processes, including sister chromatid cohesion, chromosome condensation, and DNA repair. Here we show that SUMO chains target all three SMC complexes and are antagonized by the SUMO protease Ulp2 to prevent their turnover. We uncover that the essential role of the cohesin-associated subunit Pds5 is to counteract SUMO chains jointly with Ulp2. Importantly, fusion of Ulp2 to kleisin Scc1 supports viability of PDS5 null cells and protects cohesin from proteasomal degradation mediated by the SUMO-targeted ubiquitin ligase Slx5/Slx8. The lethality of PDS5 deleted cells can also be bypassed by simultaneous loss of the PCNA unloader, Elg1, and the cohesin releaser, Wpl1, but only when Ulp2 is functional. Condensin and Smc5/6 complex are similarly guarded by Ulp2 against unscheduled SUMO-chain assembly, which we propose to time the availability of SMC complexes on chromatin.


title: An open-access volume electron microscopy atlas of whole cells and tissues

abstract: Understanding cellular architecture is essential for understanding biology. Electron microscopy (EM) uniquely visualizes cellular structures with nanometer resolution. However, traditional methods, such as thin-section EM or EM tomography, have limitations inasmuch as they only visualize a single slice or a relatively small volume of the cell, respectively. Focused Ion Beam-Scanning Electron Microscopy (FIB-SEM) demonstrated the ability to image cellular samples at 4-nm isotropic voxels with rather limited imageable volume. Here, we present 3D EM images of whole cells and tissues with two orders of magnitude increases in imageable volume at 4-nm voxels. Such data with a combined fine resolution scale and large sample size do not currently exist, and are enabled by the advances in higher precision and stability of FIB milling, together with enhanced signal detection and faster SEM scanning. More importantly, we have generated a volume EM atlas encompassing ten diverse datasets of whole cells and tissues, from cancer cells to immune cells, and from mouse pancreatic islets to Drosophila neural tissues. These open-access data (via OpenOrganelle) represent a foundation to nucleate a new field of high-resolution whole-cell volume EM and subsequent analyses, and invite biologists to explore this new paradigm and pose fundamentally new questions.


title: Genome-wide Identification of the Genetic Basis of Amyotrophic Lateral Sclerosis

abstract: Amyotrophic lateral sclerosis (ALS) is an archetypal complex disease centered on progressive death of motor neurons. Despite heritability estimates of 52%, GWAS studies have discovered only seven genome-wide significant hits, which are relevant to <10% of ALS patients. To increase the power of gene discovery, we integrated motor neuron functional genomics with ALS genetics in a hierarchical Bayesian model called RefMap. Comprehensive transcriptomic and epigenetic profiling of iPSC-derived motor neurons enabled RefMap to systematically fine-map genes and pathways associated with ALS. As a significant extension of the known genetic architecture of ALS, we identified a group of 690 candidate ALS genes, which is enriched with previously discovered risk genes. Extensive conservation, transcriptome and network analyses demonstrated the functional significance of these candidate genes in motor neurons and disease progression. In particular, we observed a genetic convergence on the distal axon, which supports the prevailing view of ALS as a distal axonopathy. Of the new ALS genes we discovered, we further characterized KANK1 that is enriched with coding and noncoding, common and rare ALS-associated genetic variation. Modelling patient mutations in human neurons reduced KANK1 expression and produced neurotoxicity with disruption of the distal axon. RefMap can be applied broadly to increase the discovery power in genetic association studies of human complex traits and diseases.

category: genomics


title: Synaptic plasticity regulated by phosphorylation of PSD-95 Serine 73 in dorsal CA1 is required for contextual fear extinction

abstract: The ability to extinguish fearful memories is essential for survival. Accumulating data indicate that the dorsal CA1 area (dCA1) contributes to this process. However, the cellular and molecular basis of fear memory extinction remains poorly understood. Postsynaptic density protein 95 (PSD-95) regulates the structure and function of glutamatergic synapses. Here, using dCA1-targeted genetic and chemogenetic manipulations in vivo combined with PSD-95 immunostaining and 3D electron microscopy ex vivo, we demonstrate that phosphorylation of PSD-95 at serine 73 PSD-95(S73) is necessary for contextual fear extinction-induced expression of PSD-95 and synaptic plasticity. Moreover, PSD-95(S73) phosphorylation is not necessary for fear memory formation and recall but is required for extinction of contextual fear. Overall, our data shows how PSD-95-dependent synaptic plasticity in the hippocampus contributes to the persistence of fear memories.


title: Mammary ductal epithelium controls cold-induced adipocyte thermogenesis

abstract: Sympathetic activation during cold exposure increases adipocyte thermogenesis via expression of mitochondrial protein uncoupling protein 1 (UCP1)1. The propensity of adipocytes to express UCP1 is under a critical influence of the adipose microenvironment and varies among various fat depots2-7. Here we report that cold-induced adipocyte UCP1 expression in female mouse subcutaneous white adipose tissue (scWAT) is regulated by mammary gland ductal epithelial cells in the adipose niche. Single cell RNA-sequencing (scRNA-seq) show that under cold condition glandular alveolar and hormone-sensing luminal epithelium subtypes express transcripts that encode secretory factors involved in regulating adipocyte UCP1 expression. We term mammary duct secretory factors as "mammokines". Using whole-tissue immunofluorescence 3D visualization, we reveal previously undescribed sympathetic nerve-ductal points of contact and show that sympathetic nerve-activated mammary ducts limit adipocyte UCP1 expression via cold-induced mammokine production. Both in vivo and ex vivo ablation of mammary ductal epithelium enhances cold-induced scWAT adipocyte thermogenic gene program. The mammary duct network extends throughout most scWATs in female mice, which under cold exposure show markedly less UCP1 expression, fat oxidation, energy expenditure, and subcutaneous fat mass loss compared to male mice. These results show a previously uncharacterized role of sympathetic nerve-activated glandular epithelium in adipocyte thermogenesis. Overall, our findings suggest an evolutionary role of mammary duct luminal cells in defending glandular adiposity during cold exposure, highlight mammary gland epithelium as a highly active metabolic cell type, and implicate a broader role of mammokines in mammary gland physiology and systemic metabolism.


title: Design of intrinsically disordered proteins that undergo phase transitions with lower critical solution temperatures

abstract: Many naturally occurring elastomers are intrinsically disordered proteins (IDPs) built up of repeating units and they can demonstrate two types of thermoresponsive phase behavior. Systems characterized by lower critical solution temperatures (LCST) undergo phase separation above the LCST whereas systems characterized by upper critical solution temperatures (UCST) undergo phase separation below the UCST. There is congruence between thermoresponsive coil-globule transitions and phase behavior whereby the theta temperatures above or below which the IDPs transition from coils to globules serve as useful proxies for the LCST / UCST values. This implies that one can design sequences with desired values for the theta temperature with either increasing or decreasing radii of gyration above the theta temperature. Here, we show that the Monte Carlo simulations performed in the so-called intrinsic solvation (IS) limit version of the temperature-dependent the ABSINTH (self-Assembly of Biomolecules Studied by an Implicit, Novel, Tunable Hamiltonian) implicit solvation model, yields a useful heuristic for discriminating between sequences with known LCST versus UCST phase behavior. Accordingly, we use this heuristic in a supervised approach, integrate it with a genetic algorithm, combine this with IS limit simulations, and demonstrate that novel sequences can be designed with LCST phase behavior. These calculations are aided by direct estimates of temperature dependent free energies of solvation for model compounds that are derived using the polarizable AMOEBA (atomic multipole optimized energetics for biomolecular applications) forcefield. To demonstrate the validity of our designs, we calculate coil-globule transition profiles using the full ABSINTH model and combine these with Gaussian Cluster Theory calculations to establish the LCST phase behavior of designed IDPs.

category: biophysics


title: Inter- and intra-tumor heterogeneity in EMT states confers functional diversity in cells that lead collective invasion.

abstract:
The collective invasion of cohesive tumor cells promotes dissemination and metastasis. Here, we investigated how tumor cells are conferred with the ability to collectively invade in genetically engineered mouse mammary tumor models and breast cancer patient tumors. We discovered that the Epithelial-Mesenchymal Transition (EMT) program that induced collective invasion in basal-type tumors was phenotypically and mechanistically distinct from the K14-dependent EMT necessary for invasion in luminal B type tumors. In basal-type tumors, TGF{beta} induced multiple distinct states defined by different degrees of EMT reprogramming and rates of collective invasion. Notably, the EMT states with an enhanced ability to lead invasion in basal-type tumors were dependent on a complex alliance between parallel TGF{beta}-Smad2/3-Zeb1/2 and Egfr-Erk1/2-Fra1 pathways that involved a new mode of signal integration. Together, our results reveal inter- and intra-tumor heterogeneity in cells that lead collective invasion, suggesting breast tumor subtype specific mechanisms of metastasis.

SignificanceOur results indicate that defining how cells invade and metastasize requires an understanding of how EMT functions differently in distinct subtypes of breast tumors.

category: cancer biology


title: precisionFDA Truth Challenge V2: Calling variants from short- and long-reads in difficult-to-map regions

abstract: The precisionFDA Truth Challenge V2 aimed to assess the state-of-the-art of variant calling in difficult-to-map regions and the Major Histocompatibility Complex (MHC). Starting with FASTQ files, 20 challenge participants applied their variant calling pipelines and submitted 64 variant callsets for one or more sequencing technologies (~35X Illumina, ~35X PacBio HiFi, and ~50X Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with the new GIAB benchmark sets and genome stratifications. Challenge submissions included a number of innovative methods for all three technologies, with graph-based and machine-learning methods scoring best for short-read and long-read datasets, respectively. New methods out-performed the 2016 Truth Challenge winners, and new machine-learning approaches combining multiple sequencing technologies performed particularly well. Recent developments in sequencing and variant calling have enabled benchmarking variants in challenging genomic regions, paving the way for the identification of previously unknown clinically relevant variants.


title: Hybrid Clustering of single-cell gene-expression and cell spatial information via integrated NMF and k-means

abstract:
MotivationRecent advances in single cell transcriptomics have allowed us to examine the identity of single cells, which has led to the discovery of new cell types and high resolution maps of cell type composition in tissues. Technologies that measure multiple modalities of single cell data provide a more comprehensive picture of a cell, but they also create challenges for data integration tasks.

ResultsIn our work, we jointly consider the spatial location and gene expression profiles of cells to determine their identity. Specifically, we have developed scHybridNMF (single-cell Hybrid Nonnegative Matrix Factorization), which performs cell type identification by incorporating single cell gene expression data with cell location data. We combined nonnegative matrix factorization (NMF) with k-means clustering to cohesively represent high-dimensional gene expression data and low-dimensional location data, respectively. We show that scHybridNMF can utilize location data to improve cell type clustering. In particular, we show that under multiple scenarios, including the cases where there is a small number of genes profiled and the location data is noisy, scHybridNMF outperforms sparse NMF, k-means, and an existing method (HMRF) that also uses cell location and gene expression data for cell type identification.

Availabilityhttps://github.com/soobleck/scHybridNMF

Contacthpark@cc.gatech.edu, xiuwei.zhang@gatech.edu


title: Anatomic position determines oncogenic specificity in melanoma

abstract: Oncogenic alterations to DNA are not transforming in all cellular contexts1,2. This may be due to pre-existing transcriptional programs in the cell of origin. Here, we define anatomic position as a major determinant of why cells respond to specific oncogenes. Cutaneous melanoma arises throughout the body, whereas the acral subtype arises on the palms of the hands, soles of the feet, or under the nails3. We sequenced the DNA of cutaneous and acral melanomas from a large cohort of human patients and found a specific enrichment for BRAF mutations in cutaneous melanoma but CRKL amplifications in acral melanoma. We modeled these changes in transgenic zebrafish models and found that CRKL-driven tumors predominantly formed in the fins of the fish. The fins are the evolutionary precursors to tetrapod limbs, indicating that melanocytes in these acral locations may be uniquely susceptible to CRKL. RNA profiling of these fin/limb melanocytes, compared to body melanocytes, revealed a positional identity gene program typified by posterior HOX13 genes. This positional gene program synergized with CRKL to drive tumors at acral sites. Abrogation of this CRKL-driven program eliminated the anatomic specificity of acral melanoma. These data suggest that the anatomic position of the cell of origin endows it with a unique transcriptional state that makes it susceptible to only certain oncogenic insults.


title: Learning from Failure: Action Performance Errors Stimulate Intentional Strategies, Not Implicit Learning

abstract: Errors in task performance, such as the failure to strike a ball with a bat, are common in everyday actions. How do humans respond to such errors and the corresponding absence of rewarding outcomes? We test the hypothesis that action performance failures drive implicit refinements in motor plans. We employ a learning paradigm wherein we manipulate the location and size of a reach target while "clamping" visual feedback of the motion in a fixed direction, resulting in either performance failures or success. Our results fail to support the view that performance errors trigger implicit recalibration, and rather suggest that they set in motion a distinct, verbally-responsive, volitional strategy to select actions which rapidly reduce future errors. Our findings also indicate that for implicit learning to occur, exposure to sensory prediction errors is necessary. When prediction-error-driven implicit learning and performance-error-driven deliberative strategies combine, improvement in behavior is greater. However, when actions are always successful and strategies are not employed, performance gains are smaller. Flexibly employing cognitive strategies could thus be a way of controlling how much and how quickly we learn from errors.


title: TCRβ Sequencing Reveals Spatial and Temporal Evolution of Clonal CD4 T cell Responses in a Breach of Tolerance Model of Inflammatory Arthritis

abstract: Effective tolerogenic intervention in Rheumatoid Arthritis (RA) will rely upon understanding the evolution of articular antigen specific CD4 T cell responses. TCR clonality of endogenous CD4 T cell infiltrates in early inflammatory arthritis was assessed to monitor evolution of the TCR repertoire in the inflamed joint and associated lymph node (LN). Mouse models of antigen-induced breach of self-tolerance and chronic polyarthritis were used to recapitulate early and late phases of RA. The infiltrating endogenous, antigen experienced CD4 T cells in inflamed joints and LNs were analysed using flow cytometry and TCR{beta} sequencing. TCR repertoires from inflamed late phase LNs displayed increased clonality and diversity compared to early phase LNs, while inflamed joints remained similar with time. Repertoires from late phase LNs accumulated clones with a diverse range of TRBV genes, while inflamed joints at both phases contained clones expressing similar TRBV genes. Repertoires from LNs and joints at the late phase displayed reduced CDR3{beta} sequence overlap compared to the early disease phase, however the most abundant clones in LNs accumulate in the joint at the later phase. The results indicate CD4 T cell repertoire clonality and diversity broadens with progression of inflammatory arthritis and is first reflected in LNs before mirroring in the joint. These observations imply that antigen specific tolerogenic therapies could be more effective if targeted at earlier phases of disease when CD4 T cell clonality is least diverse.

category: immunology


title: Mayaro Virus Infection Elicits an Innate Immune Response and Represses Autophagy in Anopheles stephensi

abstract:
Mayaro virus (MAYV) is an arboviral pathogen in the genus Alphavirus that is circulating in South America with potential to spread to naive regions. MAYV is also one of the few viruses with the ability to be transmitted by mosquitoes in the genus Anopheles, as well as the typical arboviral transmitting mosquitoes in the genus Aedes. Few studies have investigated the infection response of Anopheles mosquitoes. In this study we detail the transcriptomic and small RNA responses of An. stephensi to infection with MAYV via infectious bloodmeal at 2, 7, and 14 days post infection (dpi). 487 unique transcripts were significantly regulated, 78 putative novel miRNAs were identified, and an siRNA response is observed targeting the MAYV genome. Gene ontology analysis of transcripts regulated at each timepoint suggested activation of the Toll pathway at 7 dpi and repression of pathways related to autophagy and apoptosis at 14 dpi. These findings provide a basic understanding of the infection response of An. stephensi to MAYV and help to identify host factors which might be useful to target to inhibit viral replication in Anopheles mosquitoes.

AUTHOR SUMMARYMayaro virus (MAYV) is a mosquito-borne Alphavirus responsible for outbreaks in South America and the Caribbean. In this study we infected Anopheles stephensi with MAYV and sequenced mRNA and small RNA to understand how MAYV infection impacts gene transcription and the expression of small RNAs in the mosquito vector. Genes involved with innate immunity and signaling pathways related to cell death are regulated in response to MAYV infection of An. stephensi, we also discover novel miRNAs and describe the expression patterns of miRNAs, siRNAs, and piRNAs following bloodmeal ingestion. These results suggest that MAYV does induce a molecular response to infection in its mosquito vector species.


title: Mayaro Virus Infection Elicits an Innate Immune Response in Anopheles stephensi


title: Predictive attenuation of touch and tactile gating are distinct perceptual phenomena

abstract: In recent decades, research on somatosensory perception has led to two important observations. First, self-generated touches that are predicted by voluntary movements become attenuated compared to externally generated touches of the same intensity (attenuation). Second, externally generated touches feel weaker and are more difficult to detect during movement than at rest (gating). Currently, researchers often consider gating and attenuation the same suppression process; however, this assumption is unwarranted because, despite more than forty years of research, no study has combined them in a single paradigm. We quantified how people perceive self-generated and externally generated touches during movement and rest. We show that whereas voluntary movement gates the precision of both self-generated and externally generated touch, the amplitude of self-generated touch is robustly attenuated compared to externally generated touch. Furthermore, attenuation and gating do not interact and are not correlated, and we conclude that they represent distinct perceptual phenomena.


title: Biotic homogenisation in bird communities leads to large-scale changes in species associations

abstract:
AimThe impact of global change on biodiversity is commonly assessed in terms of changes in species distributions, community richness and community composition. Whether and how much associations between species, i.e. the degree of correlation in their spatial co-occurrence, are also changing is much less documented and mostly limited to local studies of ecological networks. In this study, we quantify changes in large-scale patterns of species associations in bird communities in relation to changes in species composition.

LocationFrance.

Time period2001-2017.

Major taxa studiedCommon breeding birds.

MethodsWe use network approaches to build three community-aggregated indices reflecting complementary aspects of species association networks. We characterise the spatio-temporal dynamics of these indices using a large-scale and high-resolution dataset of bird co-abundances of 109 species monitored for 17 years (2001-2017) from 1,969 sites across France. We finally test whether spatial and temporal changes in species association networks are related to species homogenisation estimated as the spatio-temporal dynamics of {beta}-diversity and the proportion of habitat generalists. The consistency of these relationships is tested across three main habitats, namely woodland, grassland and human settlements.

ResultsWe document a directional change in association-based indices in response to modifications in {beta}-diversity and in the proportion of generalists in space and time. Weaker associations and sparser networks were related to lower {beta}-diversity and a higher proportion of generalists, suggesting an overlooked aspect of biotic homogenisation affecting species associations. We report that this overall pattern is not constant across habitats, with opposite relationships between biotic homogenisation and change in species association networks in urban versus forest communities suggesting distinct homogenisation processes.

Main ConclusionsAlthough species association contain only partial signatures of species interactions, our study highlights that biotic homogenisation translates to finer changes in community structure by affecting the number, strength and type of species associations.

category: ecology


title: Triplex and other DNA motifs show motif-specific associations with mitochondrial DNA deletions and species lifespan.

abstract:
The "theory of resistant biomolecules" posits that long-lived species show resistance to molecular damage at the level of their biomolecules. Here, we test this hypothesis in the context of mitochondrial DNA (mtDNA) as it implies that predicted mutagenic DNA motifs should be inversely correlated with species maximum lifespan (MLS).

First, we confirmed that guanine-quadruplex and direct repeat (DR) motifs are mutagenic, as they associate with mtDNA deletions in the human major arc of mtDNA, while also adding mirror repeat (MR) and intramolecular triplex motifs to a growing list of potentially mutagenic features. What is more, triplex motifs showed disease-specific associations with deletions and an apparent interaction with guanine-quadruplex motifs.

Surprisingly, even though DR, MR and guanine-quadruplex motifs were associated with mtDNA deletions, their correlation with MLS was explained by the biased base composition of mtDNA. Only triplex motifs negatively correlated with MLS even after adjusting for body mass, phylogeny, mtDNA base composition and effective number of codons.

Taken together, our work highlights the importance of base composition for the comparative biogerontology of mtDNA and suggests that future research on mitochondrial triplex motifs is warranted.


title: Integrating deep learning and unbiased automated high-content screening to identify complex disease signatures in human fibroblasts

abstract: Drug discovery for diseases such as Parkinsons disease are impeded by the lack of screenable cellular phenotypes. We present an unbiased phenotypic profiling platform that combines automated cell culture, high-content imaging, Cell Painting, and deep learning. We applied this platform to primary fibroblasts from 91 Parkinsons disease patients and matched healthy controls, creating the largest publicly available Cell Painting image dataset to date at 48 terabytes. We use fixed weights from a convolutional deep neural network trained on ImageNet to generate deep embeddings from each image and train machine learning models to detect morphological disease phenotypes. Our platforms robustness and sensitivity allow the detection of individual-specific variation with high fidelity across batches and plate layouts. Lastly, our models confidently separate LRRK2 and sporadic Parkinsons disease lines from healthy controls (receiver operating characteristic area under curve 0.79 (0.08 standard deviation)), supporting the capacity of this platform for complex disease modeling and drug screening applications.


title: Spontaneous thalamic activity modulates the cortical innervation of the primary visual nucleus of the thalamus

abstract: Sensory processing relies on the correct development of thalamocortical loops. Visual corticothalamic axons (CTAs) invade the dorsolateral geniculate nucleus (dLGN) of the thalamus in early postnatal mice according to a regulated program that includes activity-dependent mechanisms. Spontaneous retinal activity influences the thalamic incursion of CTAs, yet the perinatal thalamus also generates intrinsic patterns of spontaneous activity whose role in modulating afferent connectivity remains unknown. Here, we found that patterned spontaneous activity in the dLGN contributes to proper spatial and temporal innervation of CTAs. Disrupting patterned spontaneous activity in the dLGN delays corticogeniculate innervation under normal conditions and upon eye enucleation. The delayed innervation was evident throughout the first two postnatal weeks but resumes after eye-opening, suggesting that visual experience is necessary for the homeostatic recovery of corticogeniculate innervation.


title: Active Participation of Membrane Lipids in Inhibition of Multidrug Transporter P-Glycoprotein

abstract: P-glycoprotein (Pgp) is a major efflux pump in humans, overexpressed in a variety of cancers and associated with the development of multi-drug resistance. Allosteric modulation by various ligands (e.g., transport substrates, inhibitors, and ATP) has been biochemically shown to directly influence structural dynamics, and thereby, the function of Pgp. However, the molecular details of such effects, particularly with respect to the role and involvement of the surrounding lipids, are not well established. Here, we employ all-atom molecular dynamics (MD) simulations to study the conformational landscape of Pgp in the presence of a high-affinity, third-generation inhibitor, tariquidar, in comparison to the nucleotide-free (APO) and the ATP-bound states, in order to characterize the mechanical effects of the inhibitor that might be of relevance to its blocking mechanism of Pgp. Simulations in a multi-component lipid bilayer show a dynamic equilibrium between open(er) and more closed inward-facing (IF) conformations in the APO state, with binding of ATP shifting the equilibrium towards conformations more prone to ATP hydrolysis and subsequent events in the transport cycle. In the presence of the inhibitor bound to the drug-binding pocket within the transmembrane domain (TMD), Pgp samples more open IF conformations, and the nucleotide binding domains (NBDs) become highly dynamic. Interestingly, and reproduced in multiple independent simulations, the inhibitor is observed to facilitate recruitment of lipid molecules into the Pgp lumen through the two proposed drug-entry portals, where the lipid head groups from the cytoplasmic leaflet penetrate into and, in some cases, translocate inside the TMD, while the lipid tails remain extended into the bulk lipid environment. These "wedge" lipids likely enhance the inhibitor-induced conformational restriction of the TMD leading to the differential modulation of coupling pathways observed with the NBDs downstream. We suggest a novel inhibitory mechanism for tariquidar, and potentially for related third-generation Pgp inhibitors, where lipids are seen to enhance the inhibitory role in the catalytic cycle of membrane transporters.


title: Noradrenergic Regulation of Two-Armed Bandit Performance

abstract: Reversal learning depends on cognitive flexibility. Many reversal learning studies assess cognitive flexibility based on the number of reversals that occur over a test session. Reversals occur when an option is repeatedly chosen, e.g. eight times in a row. This design feature encourages win-stay behavior and thus makes it difficult to understand how win-stay decisions influence reversal performance. We used an alternative design, reversals over blocks of trials independent of performance, to study how perturbations of the medial orbital cortex and the noradrenergic system influence reversal learning. We found that choice accuracy varies independently of win-stay behavior and the noradrenergic system controls sensitivity to positive feedback during reversal learning.


title: Identification of an endocannabinoid gut-brain vagal mechanism controlling food reward and energy homeostasis

abstract:
The regulation of food intake, a sine qua non requirement for survival, thoroughly shapes feeding and energy balance by integrating both homeostatic and hedonic values of food. Unfortunately, the widespread access to palatable food has led to the development of feeding habits that are independent from metabolic needs. Among these, binge eating (BE) is characterized by uncontrolled voracious eating. While reward deficit seems to be a major contributor of BE, the physiological and molecular underpinnings of BE establishment remain elusive. Here, we combined a physiologically relevant BE mouse model with multiscale in vivo approaches to explore the functional connection between the gut-brain axis and the reward and homeostatic brain structures.

Our results show that BE elicits compensatory adaptations requiring the gut-to-brain axis which, through the vagus nerve, relies on the permissive actions of peripheral endocannabinoids (eCBs) signaling. Selective inhibition of peripheral CB1 receptors resulted in a vagus-dependent increased hypothalamic activity, modified metabolic efficiency, and dampened activity of mesolimbic dopamine circuit, altogether leading to the suppression of palatable eating. We provide compelling evidence for a yet unappreciated physiological integrative mechanism by which variations of peripheral eCBs control the activity of the vagus nerve, thereby in turn gating the additive responses of both homeostatic and hedonic brain circuits which govern homeostatic and reward-driven feeding.

In conclusion, we reveal that vagus-mediated eCBs/CB1R functions represent an interesting and innovative target to modulate energy balance and counteract food-reward disorders.


title: Automated Segmentation of Amyloid-β Stained Whole Slide Images of Brain Tissue

abstract: Neurodegenerative disease pathologies have been reported in both grey matter (GM) and white matter (WM) with different density distributions, an automated separation of GM/WM would be extremely advantageous for aiding in neuropathologic deep phenotyping. Standard segmentation methods typically involve manual annotations, where a trained researcher traces the delineation of GM/WM in ultra-high-resolution Whole Slide Images (WSIs). This method can be time-consuming and subjective, preventing the analysis of large amounts of WSIs at scale. This paper proposes an automated segmentation pipeline combining a Convolutional Neural Network (CNN) module for segmenting GM/WM regions and a post-processing module to remove artifacts/residues of tissues as well as generate XML annotations that can be visualized via Aperio ImageScope. First, we investigate two baseline models for medical image segmentation: FCN, and U-Net. Then we propose a patch-based approach, ResNet-Patch, to classify the GM/WM/background regions. In addition, we integrate a Neural Conditional Random Field (NCRF) module, ResNet-NCRF, to model and incorporate the spatial correlations among neighboring patches. Although their mechanisms are greatly different, both U-Net and ResNet-Patch/ResNet-NCRF achieve Intersection over Union (IoU) of more than 90% in GM and more than 80% in WM, while ResNet-Patch achieves 1% superior to U-Net with lower variance among various WSIs. ResNet-NCRF further improves the IoU by 3% for WM compared to ResNet-Patch before post-processing. We also apply gradient-weighted class activation mapping (Grad-CAM) to interpret the segmentation masks and provide relevant explanations and insights.


title: Competition within low-density bacterial populations as an unexpected factor regulating carbon decomposition in bulk soil

abstract:
Bacterial decomposition of organic matter in soils is generally believed to be mainly controlled by the access bacteria have to their substrate. The influence of bacterial traits on this control has, however, received little attention. Here, we develop a bioreactive transport model to screen the interactive impacts of dispersion and bacterial traits on mineralization. We compare the model results with two sets of previously performed cm-scale soil-core experiments in which the mineralization of the pesticide 2,4-D was measured under well-controlled initial distributions and transport conditions. Bacterial dispersion away from the initial substrate location induced a significant increase in 2,4-D mineralization, revealing the existence of a regulation of mineralization by the bacterial decomposer density, in addition to the dilution of substrate. This regulation of degradation by density becomes dominant for bacteria with an efficient uptake of substrate at low substrate concentrations (a common feature of oligotrophs). The model output suggests that the distance between bacteria adapted to oligotrophic environments is a stronger regulator of degradation than the distance between these bacteria and the substrate initial location. Such oligotrophs, commonly found in soils, compete with each other for substrate even at remarkably low population densities. The ratio-dependent Contois growth model, which includes a density regulation in the expression of the uptake efficiency, provide a more versatile representation than the substrate-dependent Monod model in these conditions. In view of their strong interactions, bioreactive and transport processes cannot be handled independently but should be integrated, in particular when reactive processes of interest are carried out by oligotrophs.

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=87 SRC="FIGDIR/small/384735v3_ufig1.gif" ALT="Figure 1">
View larger version (28K):
org.highwire.dtl.DTLVardef@187f3f4org.highwire.dtl.DTLVardef@a14d46org.highwire.dtl.DTLVardef@1d8362aorg.highwire.dtl.DTLVardef@1cc40f8_HPS_FORMAT_FIGEXP  M_FIG C_FIG Highlights- The impact of spatial distributions on decomposition depends on bacterial traits
- Decomposition can be reduced by competition between bacteria even at low densities
- Bacterial density regulation counterbalances substrate accessibility regulation
- Regulation of decomposition by bacterial density is more acute for oligotrophs


title: Combining climatic and genomic data improves range-wide tree height growth prediction in a forest tree

abstract: Population response functions based on climatic and phenotypic data from common gardens have long been the gold standard for predicting quantitative trait variation in new environments. However, prediction accuracy might be enhanced by incorporating genomic information that captures the neutral and adaptive processes behind intra-population genetic variation. We used five clonal common gardens containing 34 provenances (523 genotypes) of maritime pine (Pinus pinaster Aiton) to determine whether models combining climatic and genomic data capture the underlying drivers of height-growth variation, and thus improve predictions at large geographical scales. The plastic component explained most of the height-growth variation, probably resulting from population responses to multiple environmental factors. The genetic component stemmed mainly from climate adaptation, and the distinct demographic and selective histories of the different maritime pine gene pools. Models combining climate-of-origin and gene pool of the provenances, and positive-effect height-associated alleles (PEAs) captured most of the genetic component of height-growth and better predicted new provenances compared to the climate-based population response functions. Regionally-selected PEAs were better predictors than globally-selected PEAs, showing high predictive ability in some environments, even when included alone in the models. These results are therefore promising for the future use of genome-based prediction of quantitative traits.


title: Single-nuclei RNA-sequencing of plant tissues

abstract:
Single-cell genomics provides unprecedented potential for research on plant development and environmental responses. Here, we introduce a generic procedure for plant nuclei isolation combined with nanowell-based library preparation. Our method enables the transcriptome analysis of thousands of individual plant nuclei. It serves as alternative to the use of protoplast isolation, which is currently a standard methodology for plant single-cell genomics, although it can be challenging for some plant tissues. We show the applicability of our nuclei isolation method by using different plant materials from several species. The potential of our snRNA-seq method is shown through the characterization of transcriptomes of seedlings and developing flowers from Arabidopsis thaliana. We evaluated the transcriptome dynamics during the early stages of anther development, identify stage-specific transcription factors regulating this process and the prediction of their target genes. Our nuclei isolation procedure can be applied in different plant species and tissues, thus expanding the toolkit for plant single-cell genomics experiments.

SIGNIFICANCE STATEMENTWe introduce an optimized plant nuclei isolation procedure followed by single nuclei RNA-seq that can be applied to different plant tissues without the need for protoplast isolation.


title: ISA API: An open platform for interoperable life science experimental metadata

abstract:
BackgroundThe Investigation/Study/Assay (ISA) Metadata Framework is an established and widely used set of open-source community specifications and software tools for enabling discovery, exchange and publication of metadata from experiments in the life sciences. The original ISA software suite provided a set of user-facing Java tools for creating and manipulating the information structured in ISA-Tab - a now widely used tabular format. To make the ISA framework more accessible to machines and enable programmatic manipulation of experiment metadata, a JSON serialization ISA-JSON was developed.

ResultsIn this work, we present the ISA API, a Python library for the creation, editing, parsing, and validating of ISA-Tab and ISA-JSON formats by using a common data model engineered as Python object classes. We describe the ISA API feature set, early adopters and its growing user community.

ConclusionsThe ISA API provides users with rich programmatic metadata handling functionality to support automation, a common interface and an interoperable medium between the two ISA formats, as well as with other life science data formats required for depositing data in public databases.


title: Set-Min sketch: a probabilistic map for power-law distributions with application to k-mer annotation

abstract:
AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSMotivationC_ST_ABSIn many bioinformatics pipelines, k-mer counting is often a required step, with existing methods focusing on optimizing time or memory usage. These methods usually produce very large count tables explicitly representing k-mers themselves. Solutions avoiding explicit representation of k-mers include Minimal Perfect Hash Functions (MPHFs) or Count-Min sketches. The former is only applicable to static maps not subject to updates, while the latter suffers from potentially very large point-query errors, making it unsuitable when counters are required to be highly accurate.

ResultsWe introduce Set-Min sketch - a sketching technique for representing associative maps inspired by Count-Min sketch - and apply it to the problem of representing k-mer count tables. Set-Min is provably more accurate than both Count-Min and Max-Min - an improved variant of Count-Min for static datasets that we define here. We show that Set-Min sketch provides a very low error rate, both in terms of the probability and the size of errors, at the expense of a very moderate memory increase. On the other hand, Set-Min sketches are shown to take up to an order of magnitude less space than MPHF-based solutions, especially for large values of k. Space-efficiency of Set-Min takes advantage of the power-law distribution of k-mer counts in genomic datasets.

Availabilityhttps://github.com/yhhshb/fress


title: Melt into the groupElectrophysiological Evidence of Gestalt Perception of Human Dyad

abstract: It has been shown recently that the human brain has dedicated networks for perception of human bodies in synchronous motion or in situation of interaction. However, below motion and interaction, how does the brain process a simple plurality of humans in close positioning? We used EEG frequency tagging technique to investigate integration of human dyad elements in a global percept. We presented to participants images of two silhouettes, a man and a woman flickering at different frequencies (5.88 vs.7.14Hz). Clear response at these stimulation frequencies reflected response to dyad parts, both when the dyad was presented upright and inverted. However, an emerging intermodulation component (7.14 + 5.88 = 13.02 Hz), a nonlinear response regarded as an objective signature of holistic representation, was significantly enhanced in upright relatively to inverted position. Inversion effect was significant only for the intermodulation component as opposed to stimulation frequencies revealing that dyad configuration perception overrides structural properties of dyad elements. Inversion effect was not significant for a pair of non-human objects. Our results show that merely facing two humans in close positioning leads to perceptually bind them and suggest that the perception of individuals is of different nature when they form a plurality.


title: Fast Alignment-Free Similarity Estimation By Tensor Sketching

abstract:
The sharp increase in next-generation sequencing technologies capacity has created a demand for algorithms capable of quickly searching a large corpus of biological sequences. The complexity of biological variability and the magnitude of existing data sets have impeded finding algorithms with guaranteed accuracy that efficiently run in practice. Our main contribution is the Tensor Sketch method that efficiently and accurately estimates edit distances. In our experiments, Tensor Sketch had 0.956 Spearmans rank correlation with the exact edit distance, improving its best competitor Ordered MinHash by 23%, while running almost 5 times faster. Finally, all sketches can be updated dynamically if the input is a sequence stream, making it appealing for large-scale applications where data cannot fit into memory.

Conceptually, our approach has three steps: 1) represent sequences as tensors over their sub-sequences, 2) apply tensor sketching that preserves tensor inner products, 3) implicitly compute the sketch. The sub-sequences, which are not necessarily contiguous pieces of the sequence, allow us to outperform k-mer-based methods, such as min-hash sketching over a set of k-mers. Typically, the number of sub-sequences grows exponentially with the sub-sequence length, introducing both memory and time overheads. We directly address this problem in steps 2 and 3 of our method. While the sketching of rank-1 or super-symmetric tensors is known to admit efficient sketching, the sub-sequence tensor does not satisfy either of these properties. Hence, we propose a new sketching scheme that completely avoids the need for constructing the ambient space.

Our tensor-sketching techniques main advantages are three-fold: 1) Tensor Sketch has higher accuracy than any of the other assessed sketching methods used in practice. 2) All sketches can be computed in a streaming fashion, leading to significant time and memory savings when there is overlap between input sequences. 3) It is straightforward to extend tensor sketching to different settings leading to efficient methods for related sequence analysis tasks. We view tensor sketching as a framework to tackle a wide range of relevant bioinformatics problems, and we are confident that it can bring significant improvements for applications based on edit distance estimation.


title: Sensitivity to Immune Checkpoint Blockade and Progression-Free Survival is associated with baseline CD8+ T cell clone size and cytotoxicity

abstract:
Immune checkpoint blockers (ICB) exert their anti-cancer effects via CD8+ T cells, although how responses vary over sub-populations and across clones is incompletely understood. We performed single-cell RNA-sequencing of CD8+ T cells and their receptors pre- and post-ICB across eight patients, integrating results with bulk-sequencing data (n=209). We identify seven subsets with divergent responses to ICB, finding the effector cluster demonstrates the most pronounced changes. Likewise, transcriptomic response to ICB relates to clone size, with large clones demonstrating increased numbers of regulated genes of higher immunological pertinence. Cytotoxic effector clones were more likely to persist long-term following ICB and overlapped with public tumour-infiltrating lymphocyte clonotypes. Notably, pre-treatment CD8+ cytotoxicity associated with progression-free survival, highlighting the importance of the baseline CD8+ immune landscape in long-term response. This work further advances understanding of the molecular determinants of ICB response and assists in the search for peripheral prognostic biomarkers.

ONE SENTENCE SUMMARYUsing single-cell and bulk RNA sequencing we explore checkpoint immunotherapy activity on peripheral CD8+ T cells in metastatic melanoma; demonstrating that cell subset and clone size determine gene expression responses to treatment, and that pre-treatment cytotoxicity and clonality of peripheral CD8+ T cells is clinically prognostic.


title: Gene Expression Meta-Analysis Reveals Interferon-induced Genes

abstract:
BackgroundSevere Acute Respiratory Syndrome (SARS) corona virus (CoV) infections are a serious public health threat because of their pandemic-causing potential. This work analyzes mRNA expression data from SARS infections through meta-analysis of gene signatures, possibly identifying therapeutic targets associated with major SARS infections.

MethodsThis work defines 37 gene signatures representing SARS-CoV, Middle East Respiratory Syndrome (MERS)-CoV, and SARS-CoV2 infections in human lung cultures and/or mouse lung cultures or samples and compares them through Gene Set Enrichment Analysis (GSEA). To do this, positive and negative infectious clone SARS (icSARS) gene panels are defined from GSEA-identified leading-edge genes between two icSARS-CoV derived signatures, both from human cultures. GSEA then is used to assess enrichment and identify leading-edge icSARS panel genes between icSARS gene panels and 27 other SARS-CoV gene signatures. The meta-analysis is expanded to include five MERS-CoV and three SARS-CoV2 gene signatures. Genes associated with SARS infection are predicted by examining the intersecting membership of GSEA-identified leading-edges across gene signatures.

ResultsSignificant enrichment (GSEA p<0.001) is observed between two icSARS-CoV derived signatures, and those leading-edge genes defined the positive (233 genes) and negative (114 genes) icSARS panels. Non-random significant enrichment (null distribution p<0.001) is observed between icSARS panels and all verification icSARSvsmock signatures derived from human cultures, from which 51 over- and 22 under-expressed genes are shared across leading-edges with 10 over-expressed genes already associated with icSARS infection. For the icSARSvsmock mouse signature, significant, non-random significant enrichment held for only the positive icSARS panel, from which nine genes are shared with icSARS infection in human cultures. Considering other SARS strains, significant, non-random enrichment (p<0.05) is observed across signatures derived from other SARS strains for the positive icSARS panel. Five positive icSARS panel genes, CXCL10, OAS3, OASL, IFIT3, and XAF1, are found across mice and human signatures regardless of SARS strains.

ConclusionThe GSEA-based meta-analysis approach used here identifies genes with and without reported associations with SARS-CoV infections, highlighting this approachs predictability and usefulness in identifying genes that have potential as therapeutic targets to preclude or overcome SARS infections.


title: Evolution of two-component quorum sensing systems

abstract: Quorum sensing (QS) is a cell-to-cell communication system that enables bacteria to coordinate their gene expression depending on their population density, via the detection of small molecules called autoinducers. In this way bacteria can act collectively to initiate processes like bioluminescence, virulence and biofilm formation. Autoinducers are detected by receptors, some of which are part of Two Component Signal Transduction Systems (TCS), which comprise of a (usually membrane-bound) sensor histidine kinase (HK) and a cognate response regulator (RR). Different QS systems are used by different bacterial taxa, and their relative evolutionary relationships have not been extensively studied. To address this, we used the KEGG database to identify all the QS HKs and RRs that are part of TCS and examined their conservation across microbial taxa. We compared the combinations of the highly conserved domains in the different families of receptors and response regulators using the SMART and KEGG databases, and we also carried out phylogenetic analyses for each family, and all families together. The distribution of the different QS systems across taxa, indicates flexibility in HK/RR pairing, and highlights the need for further study of the most abundant systems. For both the QS receptors and the response regulators, our analysis indicates close evolutionary relationships between certain families, highlighting a common evolutionary history which can inform future applications, such as the design of novel inhibitors for pathogenic QS systems.


title: A domestic plant differs from its wild relative along multiple axes of within-plant trait variability and diversity

abstract:
O_LIFor 10,000 years humans have altered plant traits through domestication and ongoing crop improvement, shaping plant form and function in agroecosystems. To date, studies have focused on how these processes have shaped whole-plant or average traits; however, plants also have characteristic levels of trait variability among their repeated parts, which can be heritable and mediate critical ecological interactions. As concerns about sustainable pest management increase, there is growing interest in approaches that increase trait diversity in crop agroecosystems. Here, we examine an under-appreciated scale of trait variation - among leaves, within plants - that may have changed through the process of domestication and improvement in a key crop.
C_LIO_LIWe explore how levels of within-plant, among-leaf trait variability differ between cultivars and wild relatives of alfalfa (Medicago sativa), a key forage crop with an 8,000 year cultivation history. We grew individual plants from 30 wild populations and 30 cultivars, encompassing a range of domestication and improvement histories. For each plant, we quantify variability in a broad suite of physical, nutritive, and chemical leaf traits, including measures of chemical dissimilarity (beta diversity) among leaves.
C_LIO_LIWe find that intra-individual trait variability has changed over the course of domestication and crop improvement, with effects often larger than changes in trait means. Cultivated alfalfa had elevated variability in SLA, trichomes, and C:N; increased diversity in defensive compounds; and reduced variability in phytochemical composition. We also elucidate fundamental associations between trait means and overall investment in secondary metabolites with patterns of among-leaf variability and chemical diversity.
C_LIO_LIWe conclude that within-plant variability is an overlooked dimension of trait diversity in this globally critical agricultural crop. We find that trait variability is actually higher in cultivated plants compared to wild progenitors for multiple nutritive, physical, and chemical traits, highlighting a scale of variation that may mitigate loss of trait diversity at other scales in alfalfa agroecosystems and in other crops with similar domestication and improvement histories.
C_LI


title: DeepMosaic: Control-independent mosaic single nucleotide variant detection using deep convolutional neural networks

abstract: Introductory paragraphMosaic variants (MVs) reflect mutagenic processes during embryonic development1 and environmental exposure2, accumulate with aging, and underlie diseases such as cancer and autism3. The detection of MVs has been computationally challenging due to sparse representation in non-clonally expanded tissues. While heuristic filters and tools trained on clonally expanded MVs with high allelic fractions are proposed, they show relatively lower sensitivity and more false discoveries4-9. Here we present DeepMosaic, combining an image-based visualization module for single nucleotide MVs, and a convolutional neural networks-based classification module for control-independent MV detection. DeepMosaic achieved higher accuracy compared with existing methods on biological and simulated sequencing data, with a 96.34% (158/164) experimental validation rate. Of 932 mosaic variants detected by DeepMosaic in 16 whole genome sequenced samples, 21.89-58.58% (204/932-546/932) MVs were overlooked by other methods. Thus, DeepMosaic represents a highly accurate MV classifier that can be implemented as an alternative or complement to existing methods.


title: The discriminatory power of the T cell receptor

abstract: T cells use their T-cell receptors (TCRs) to discriminate between lower-affinity self and higher affinity non-self pMHC antigens. Although the discriminatory power of the TCR is widely believed to be near-perfect, technical difficulties have hampered efforts to precisely quantify it. Here, we describe a method for measuring very low TCR/pMHC affinities, and use it to measure the discriminatory power of the TCR, and the factors affecting it. We find that TCR discrimination, although enhanced compared with conventional cell-surface receptors, is imperfect: primary human T cells can respond to pMHC with affinities as low as KD ~1 mM. The kinetic proofreading mechanism fit our data, providing the first estimates of both the time delay (2.8 s) and number of biochemical steps (2.67) that are consistent with the extraordinary sensitivity of antigen recognition. Our findings explain why self pMHC frequently induce autoimmune diseases and anti-tumour responses, and suggest ways to modify TCR discrimination.


title: Transmission of SARS-CoV-2 from humans to animals and potential host adaptation

abstract: SARS-CoV-2, the agent of the COVID-19 pandemic, can infect a wide range of mammals. Since its spread in humans, secondary host jumps of SARS-CoV-2 from humans to a variety of domestic and wild populations of mammals have been documented. The evolution of SARS-CoV-2 in different host species is of fundamental interest while also providing indication of how SARS-CoV-2 may have adapted to human hosts soon after the initial host jump, a time window for which there are no genome sequences available. Moreover, the study of SARS-CoV-2 circulating in animals is critical to assess the risk that the transmission of animal-adapted viral lineages back into humans (i.e., spillback) may pose. Here, we compared the genomic landscapes of SARS-CoV-2 isolated from animal species relative to that in humans, profiling the mutational biases indicative of potentially different selective pressures in animals. We focused on viral genomes collected in infected mink (Neovison vison) and white-tailed deer (Odocoileus virginianus) for which reports of multiple independent spillover events and subsequent animal-to-animal transmission are available. We identified six candidate mutations for animal-specific adaptation in mink (NSP9_G37E, Spike_F486L, Spike_N501T, Spike_Y453F, ORF3a_T229I, ORF3a_L219V), and one in deer (NSP3a_L1035F), though these mutations appear to confer minimal advantage for circulation in humans. Additionally, circulation of SARS-CoV-2 in mink and deer has not caused considerable changes to the evolutionary trajectory of SARS-CoV-2 thus far. Finally, our results suggest that minimal adaptation was required for human-to-animal spillover and subsequent onward transmission in mink and deer, highlighting the  generalist nature of SARS-CoV-2 as a pathogen of mammalian hosts.