title: Interpretable machine learning models for single-cell ChIP-seq imputation

abstract:
MotivationSingle-cell ChIP-seq (scChIP-seq) analysis is challenging due to data sparsity. High degree of data sparsity in biological high-throughput single-cell data is generally handled with imputation methods that complete the data, but specific methods for scChIP-seq are lacking. We present SIMPA, a scChIP-seq data imputation method leveraging predictive information within bulk data from ENCODE to impute missing protein-DNA interacting regions of target histone marks or transcription factors.

ResultsImputations using machine learning models trained for each single cell, each target, and each genomic region accurately preserve cell type clustering and improve pathway-related gene identification on real data. Results on simulated data show that 100 input genomic regions are already enough to train single-cell specific models for the imputation of thousands of undetected regions. Furthermore, SIMPA enables the interpretation of machine learning models by revealing interaction sites of a given single cell that are most important for the imputation model trained for a specific genomic region. The corresponding feature importance values derived from promoter-interaction profiles of H3K4me3, an activating histone mark, highly correlate with co-expression of genes that are present within the cell-type specific pathways. An imputation method that allows the interpretation of the underlying models facilitates users to gain an even deeper understanding of individual cells and, consequently, of sparse scChIP-seq datasets.

Availability and implementationOur interpretable imputation algorithm was implemented in Python and is available at https://github.com/salbrec/SIMPA


title: Dnmt3a knockout in excitatory neurons impairs postnatal synapse maturation and is partly compensated by repressive histone modification H3K27me3

abstract: Two epigenetic pathways of repression, DNA methylation and Polycomb repressive complex 2 (PRC2) mediated gene silencing, regulate neuron development and function, but their respective contributions are unknown. We found that conditional loss of the de novo DNA methyltransferase Dnmt3a in mouse excitatory neurons altered expression of synapse-related genes, stunted synapse maturation, and impaired working memory and social interest. Loss of Dnmt3a abolished postnatal accumulation of CG and non-CG DNA methylation, leaving neurons with an unmethylated, fetal-like epigenomic pattern at -140,000 genomic regions. The PRC2-associated histone modification H3K27me3 increased at many of these sites, partially compensating for the loss of DNA methylation. Our data support a dynamic interaction between two fundamental modes of epigenetic repression during postnatal maturation of excitatory neurons, which together confer robustness on neuronal regulation.

category: neuroscience


title: TENET: Gene network reconstruction using transfer entropy reveals key regulatory factors from single cell transcriptomic data

abstract:
Accurate prediction of gene regulatory rules is important towards understanding of cellular processes. Existing computational algorithms devised for bulk transcriptomics typically require a large number of time points to infer gene regulatory networks (GRNs), are applicable for a small number of genes, and fail to detect potential causal relationships effectively. Here, we propose a novel approach  TENET to reconstruct GRNs from single cell RNA sequencing (scRNAseq) datasets. Employing transfer entropy (TE) to measure the amount of causal relationships between genes, TENET predicts large-scale gene regulatory cascades/relationships from scRNAseq data. TENET showed better performance than other GRN reconstructors, in identifying key regulators from public datasets. Specifically from scRNAseq, TENET identified key transcriptional factors in embryonic stem cells (ESCs) and during direct cardiomyocytes reprogramming, where other predictors failed. We further demonstrate that known target genes have significantly higher TE values, and TENET predicted higher TE genes were more influenced by the perturbation of their regulator. Using TENET, we identified and validated that Nme2 is a culture condition specific stem cell factor. These results indicate that TENET is uniquely capable of identifying key regulators from scRNAseq data.

Key PointsO_LITENET measures putative causal relationships between genes using transfer entropy.
C_LIO_LITENET shows outstanding performance in identifying key regulators compared to existing methods.
C_LIO_LITENET can reveal previously uncharacterized regulators.
C_LI

category: bioinformatics


title: Single cell transcriptomic analysis identifies Langerhans cells immunocompetency is critical for ability to induce tolerogenic T cells.

abstract: Human epidermal Langerhans cells (LCs) can coordinate both immunogenic and tolerogenic immune responses, creating an attractive opportunity for immunomodulation strategies. To investigate transcriptional determinants of human primary LC tolerance we applied single cells RNA-sequencing combined with transcriptional network modelling and functional analysis. Unsupervised clustering of single cell transcriptomes revealed that steady-state LCs exist in immature and immunocompetent states, and become fully immunocompetent on migration. Interestingly, LC migration, which has been shown to result in upregulation of the transcription factor IRF4, led in parallel to increased expression of a tolerogenic gene module including IDO1, LGALS1, LAMTOR1 and IL10RA, which translated to efficient induction of regulatory T cells in co-culture assays by immunocompetent LCs. Using protein expression analysis and perturbation with inhibitors, we confirmed the role of IDO1 as a mediator of LC tolerogenic responses induced during LC migration. Computational analysis of regulons and Partial Information Decomposition analyses identified IRF4 as a key driver for LC tolerogenic programmes. The predicted IRF4-regulated genes were confirmed by analysis of CRISPR-Cas9 edited LCs. These findings suggest that efficient priming of tolerogenic responses by LCs requires upregulation of a migration-coupled maturation program which is superimposed with a tolerance-inducing genomic module.

category: systems biology


title: A dynamic normalization model of temporal attention

abstract: Vision is dynamic, handling a continuously changing stream of input, yet most models of visual attention are static. Here, we develop a dynamic normalization model of visual temporal attention and constrain it with new psychophysical human data. We manipulated temporal attention-the prioritization of visual information at specific points in time-to a sequence of two stimuli separated by a variable time interval. Voluntary temporal attention improved perceptual sensitivity only over a specific interval range. To explain these data, we modeled voluntary and involuntary attentional gain dynamics. Voluntary gain enhancement took the form of a limited resource over short time intervals, which recovered over time. Taken together, our theoretical and experimental results formalize and generalize the idea of limited attentional resources across space at a single moment to limited resources across time at a single location.


title: Multimodal Learning of Pheromone Locations

abstract: Memorizing pheromonal locations is critical for many mammalian species as it involves finding mates and avoiding competitors. In rodents, pheromonal information is perceived by the main and accessory olfactory systems. However, the role of somatosensation in context dependent learning and memorizing of pheromone locations remains unexplored. We addressed this problem by training female mice on a multimodal task to locate pheromones by sampling volatiles emanating from male urine through the orifices of varying dimensions or shapes that are sensed by their vibrissae. In this novel pheromone location assay, female mice preference towards male urine scent decayed over time when they were permitted to explore pheromones v/s neutral stimuli, water. On training them for the associations involving olfactory and whisker systems, it was established that they were able to memorize the location of opposite sex pheromones, when tested 15 days later. This memory was not formed either when the somatosensory inputs through whisker pad were blocked or when the pheromonal cues were replaced with that of same sex. The association between olfactory and somatosensory systems were further confirmed by the enhanced expression of the Activity regulated cytoskeleton protein. Further, the activation of main olfactory bulb circuitry by pheromone volatiles did not cause any modulation in learning and memorizing non-pheromonal volatiles. Our study thus provides the evidence for associations formed between different sensory modalities facilitating the long-term memory formation relevant to social and reproductive behaviors.


title: Discovery of dual inhibitors of KPC-3 and KPC-15 of Klebsiella pneumoniae :an in-silico molecular docking and dynamics study

abstract:
BackgroundThe development of carbapenem resistance against Klebsiella pneumoniae is a situation of grave concern and requires urgent attention. Among the KPC produced by K.pneumoniae, KPC-3, and KPC-15, play a significant role in the development of resistance to carbapenem.

Materials and methodsThe binding sites of KPC-3 and KPC-15 were predicted by the COACH server. Drug-like ligands from ZINC were then screened by ligand-based drug screening (LBVS) by keeping Relebactam as a template. The top 50,000 selected ligands were then screened by structure-based virtual screening using idock. For keeping an account of the dual inhibitors stability in complex with KPC-3 and KPC-15, MDS were carried out for each complex.

ResultsBased on consensus weighted ranks, the top 3 ligands with the dual inhibitory property are ZINC76060350 (consensus weighted rank - 1.5), ZINC05528590 (2), ZINC72290395 (3.5). All the top 3 dual inhibitors have a reasonable probability of passing through the blood-brain barrier. The RDKit and Morgan fingerprint scores between Relebactam and the top three ligands were 0.24, 0.22, 0.23, and 0.26, 0.19, 0.25, respectively (showing only 20% similarity). The MD simulation result revealed good binding stability of ligand ZINC05528590 with both KPC-3 and KPC-15, whereas ligand ZINC76060350 showed good binding stability to KPC-3.

ConclusionThe ligand ZINC05528590 could be taken forward to develop a new drug against a multi-resistant- Klebsiella pneumoniae infection. At the same time, ZINC76060350 can be considered to develop a new drug against KPC-15 resistant Klebsiella pneumoniae.


title: SSnet: A Deep Learning Approach for Protein-Ligand Interaction Prediction

abstract: Computational prediction of Protein-Ligand Interaction (PLI) is an important step in the modern drug discovery pipeline as it mitigates the cost, time, and resources required to screen novel therapeutics. Deep Neural Networks (DNN) have recently shown excellent performance in PLI prediction. However, the performance is highly dependent on protein and ligand features utilized for the DNN model. Moreover, in current models, the deciphering of how protein features determine the underlying principles that govern PLI is not trivial. In this work, we developed a DNN framework named SSnet that utilizes secondary structure information of proteins extracted as the curvature and torsion of the protein backbone to predict PLI. We demonstrate the performance of SSnet by comparing against a variety of currently popular machine and non-machine learning models using various metrics. We visualize the intermediate layers of SSnet to show a potential latent space for proteins, in particular to extract structural elements in a protein that the model finds influential for ligand binding, which is one of the key features of SSnet. We observed in our study that SSnet learns information about locations in a protein where a ligand can bind including binding sites, allosteric sites and cryptic sites, regardless of the conformation used. We further observed that SSnet is not biased to any specific molecular interaction and extracts the protein fold information critical for PLI prediction. Our work forms an important gateway to the general exploration of secondary structure based deep learning, which is not just confined to protein-ligand interactions, and as such will have a large impact on protein research while being readily accessible for de novo drug designers as a standalone package.


title: Influence of native endophytic bacteria on the growth and bacterial crown rot tolerance of papaya (Carica papaya)

abstract: The native plant microbiome is composed of diverse communities that influence its overall health, with some species known to promote plant growth and pathogen resistance. Here, we show the antimicrobial and growth promoting activities of autoclaved culture metabolites (ACMs) from native endophytic bacteria (NEB) in a papaya cultivar that is tolerant to bacterial crown rot (BCR) caused by Erwinia mallotivora. Initially, bacterial colonization in recovering tissues of this cultivar was observed before onset of tissue regeneration or  regrowth. We further isolated and characterized these bacteria and were able to identify two culturable stem NEB under genera Kosakonia (EBW), related to Enterobacter, and Sphingomonas (EBY). We also identified root NEB (BN, BS and BT) under genus Bacillus. Inhibition assays indicated that ACMs from these NEB promptly (18-30h) and efficiently inhibited (60-65%) E. mallotivora proliferation in vitro. Interestingly, when ACMs from BN and EBW were inoculated in surface-sterilized papaya seeds, germination was variably retarded (20-60% reduction) depending on plant genotype, but plant biomass accumulation was significantly stimulated, at around two-fold increase. Moreover, greenhouse experiments show that ACMs from all isolates, especially EBW, significantly reduced BCR incidence and severity in susceptible genotype, at around two-fold. In general, our observations of pathogen antagonism, plant growth promotion leading to disease reduction by ACMs of native endophytic bacteria suggested its contribution to increased fitness of papaya and tolerance against the (re)emerging BCR disease.

category: plant biology


title: Adenosine receptor and its downstream targets, mod(mdg4) and Hsp70, work as a signaling pathway modulating cytotoxic damage in Drosophila

abstract: Adenosine (Ado) is an important signaling molecule involved in stress responses. Studies in mammalian models have shown that Ado regulates signaling mechanisms involved in  danger-sensing and tissue-protection. Yet, little is known about the role of Ado signaling in Drosophila. In the present study, we observed lower extracellular Ado concentration and suppressed expression of Ado transporters in flies expressing mutant huntingtin protein (mHTT). We altered Ado signaling using genetic tools and found that the overexpression of Ado metabolic enzymes, as well as the suppression of Ado receptor (AdoR) and transporters (ENTs), were able to minimize mHTT-induced mortality. We also identified the downstream targets of the AdoR pathway, the modifier of mdg4 (Mod(mdg4)) and heat-shock protein 70 (Hsp70), which carry out its function. Finally, we showed that a decrease in Ado signaling affect other Drosophila stress reactions, including paraquat and heat-shock treatments. Our study provides important insights into how Ado regulates stress responses in Drosophila.

category: genetics


title: OBERON3 and SUPPRESSOR OF MAX2 1-LIKE proteins form a regulatory module specifying phloem identity

abstract: Spatial specificity of cell fate decisions is central for organismal development. The phloem tissue mediates long-distance transport of energy metabolites along plant bodies and is characterized by an exceptional degree of cellular specialization. How a phloem-specific developmental program is implemented is, however, unknown. Here we reveal that the ubiquitously expressed PHD-finger protein OBE3 forms a central module with the phloem- specific SMXL5 protein for establishing phloem identity in Arabidopsis thaliana. By protein interaction studies and phloem-specific ATAC-seq analyses, we show that OBE3 and SMXL5 proteins form a complex in nuclei of phloem stem cells where they establish a phloem-specific chromatin profile. This profile allows expression of OPS, BRX, BAM3, and CVP2 genes acting as mediators of phloem differentiation. Our findings demonstrate that OBE3/SMXL5 protein complexes establish nuclear features essential for determining phloem cell fate and highlight how a combination of ubiquitous and local regulators generate specificity of developmental decisions in plants.


title: Model balancing: in search of consistent metabolic states and in-vivo kinetic constants

abstract: Enzyme kinetic constants in vivo are largely unknown, which limits the construction of large metabolic models. While model fitting, in principle, aims at fitting kinetic constants to measured metabolic fluxes, metabolite concentrations, and enzyme concentrations, the resulting estimation problems are typically non-convex and hard to solve, especially if models are large. Here we assume that metabolic fluxes are known and show how consistent kinetic constants, metabolite concentrations, and enzyme concentrations can be determined simultaneously from data. If one specific term is omitted - a term that penalises small enzyme concentrations - we obtain a convex optimality problem with a unique local optimum. The estimation method with or without this term, called model balancing, applies to models with a wide range of rate laws and accounts for thermodynamic constraints on kinetic constants and metabolite concentrations through thermodynamic forces. It can be used to estimate in-vivo kinetic constants from omics data, to complete and adjust available data, or to construct plausible metabolic states with a predefined flux distribution. As a demonstrative case, we balance a model of E. coli central metabolism with artificial or experimental data. The tests show what information about kinetic constants can be obtained from omics data, and reveal the practical limits of estimating in-vivo kinetic constants.


title: Two distinct bacterial biofilm components trigger metamorphosis in the colonial hydrozoan Hydractinia echinata

abstract:
In the marine environment bacterial-induced metamorphosis of larvae is a widespread cross-kingdom communication phenomenon and critical for the persistence of many marine invertebrates. However, the identities of most inducing bacterial signals and the underlying cellular mechanisms remain enigmatic. Larvae of Hydractinia echinata provide an excellent model for investigating bacteria-stimulated settlement as they transform upon detection of the signal into the colonial adult stage within 24 h. Although H. echinata served as cell biological model system for decades, the influence of bacterial signals on the morphogenic transition remained largely unexplored. Using a bioassay-guided analysis, we first identified that specific bacterial (lyso)phospholipids, naturally present in bacterial biofilms, elicit metamorphosis in Hydractinia larvae in a dose-response matter. In particular, lysophospholipids as single compounds or in combinations at 50 {micro}M concentrations induced metamorphosis in up to 50% of all larvae phospholipid within 48 h. By using fluorescence-labeled bacterial phospholipids, we demonstrated their incorporation into the larval membranes, where interactions with internal signaling cascades could occur. In addition, two structurally distinct exopolysaccharides, the newly identified Rha-Man polysaccharide from Pseudoalteromonas sp. P1-9 and curdlan from Alcaligenes faecalis caused up to 75% of all larvae to transform within 24 h. We also found that combinations of (lyso)phospholipids and curdlan induced the transformation in almost all larvae within 24 h, thereby exceeding the morphogenic activity observed for single compounds and axenic bacterial biofilms. Our results demonstrate that multiple and structurally distinct bacterial-derived metabolites converge to induce high transformation rates of Hydractinia larvae, which might ensure optimal habitat selection despite the general widespread occurrence of both compound classes.

Significance StatementBacterial biofilms profoundly influence the recruitment and settlement of marine invertebrates, critical steps for diverse marine processes such as coral reef formation, marine fisheries and the fouling of submerged surfaces. Yet, the complex composition of biofilms often makes it challenging to characterize the individual signals and regulatory mechanisms. Developing tractable model systems to characterize these co-evolved interactions is the key to understand fundamental processes in evolutionary biology. Here, we characterized for the first time two types of bacterial signaling molecules that induce the morphogenic transition and analyzed their abundance and combinatorial activity. This study highlights the crucial role of the converging activity of multiple bacterial signals in development-related cross-kingdom signaling.

AreasMajor: Chemical Biology, Microbiology, Developmental Biology

category: ecology


title: Donut-like organization of inhibition underlies categorical neural responses in the midbrain

abstract: Categorical neural responses underlie various forms of selection and decision-making. Such binary-like responses promote robust signaling of the winner in the presence of input ambiguity and neural noise. Here, we show that a  donut-like inhibitory mechanism in which each competing option suppresses all options except itself, is highly effective at generating categorical neural responses. It surpasses motifs of feedback inhibition, recurrent excitation, and divisive normalization invoked frequently in decision-making models. We demonstrate experimentally not only that this mechanism operates in the midbrain spatial selection network in barn owls, but also that it is necessary for categorical signaling by it. The functional pattern of neural inhibition in the midbrain forms an exquisitely structured  multi-holed donut consistent with this networks combinatorial inhibitory function for stimulus selection. Additionally, modeling reveals a generalizable neural implementation of the donut-like motif for categorical selection. Self-sparing inhibition may, therefore, be a powerful circuit module central to categorization.


title: Single cell transcriptome analysis reveals RGS1 as a new marker and promoting factor for T cell exhaustion in multiple cancers

abstract: T cell exhaustion is one of the main reasons of tumor immune escape. Using single cell transcriptome data of CD8+ T cells in multiple cancers, we identified different cell types, in which Pre_exhaust and exhausted T cells participated in negative regulation of immune system process. By analyzing the co-expression network patterns and differentially expressed genes of Pre_exhaust, exhausted and effector T cells, we identified 35 genes related to T cell exhaustion, which high GSVA scores were associated with significantly poor prognosis in various cancers. In the differentially expressed genes, RGS1 showed the greatest fold change in Pre_exhaust and exhausted cells of three cancers compared with effector T cells, and high expression of RGS1 was also associated with poor prognosis in various cancers. Additionally, RGS1 protein was upregulated significantly in tumor tissues in the immunohistochemistry verification. Furthermore, RGS1 displayed positive correlation with the 35 genes, especially highly correlated with PDCD1, CTLA4, HAVCR2 and TNFRSF9 in CD8+ T cells and cancer tissues, indicating important roles of RGS1 in CD8+ T cell exhaustion. Considering the GTP-hydrolysis activity of RGS1 and significantly high mRNA and protein expression in cancer tissues, we speculated that RGS1 potentially mediate the T cell retention to lead to the persistent antigen stimulation, resulting in T cell exhaustion. In conclusion, our findings suggest that RGS1 is a new marker and promoting factor for CD8+ T cell exhaustion, and provide theoretical basis for research and immunotherapy of exhausted cells.

category: cancer biology


title: The making of calibration sausage exemplified by recalibrating the transcriptomic timetree of jawed vertebrates

abstract: Molecular divergence dating has the potential to overcome the incompleteness of the fossil record in inferring when cladogenetic events (splits, divergences) happened, but needs to be calibrated by the fossil record. Ideally but unrealistically, this would require practitioners to be specialists in molecular evolution, in the phylogeny and the fossil record of all sampled taxa, and in the chronostratigraphy of the sites the fossils were found in. Paleontologists have therefore tried to help by publishing compendia of recommended calibrations, and molecular biologists unfamiliar with the fossil record have made heavy use of such works (in addition to using scattered primary sources and copying from each other). Using a recent example of a large node-dated timetree inferred from molecular data, I reevaluate all thirty calibrations in detail, present the current state of knowledge on them with its various uncertainties, rerun the dating analysis, and conclude that calibration dates cannot be taken from published compendia or other secondary or tertiary sources without risking strong distortions to the results, because all such sources become outdated faster than they are published: 50 of the sources I cite to constrain calibrations were published in 2019, half of the total of 276 after mid-2016, and 90% after mid-2005. It follows that the present work cannot serve as such a compendium either; in the slightly longer term, it can only highlight known and overlooked problems. Future authors will need to solve each of these problems anew through a thorough search of the primary paleobiological and chronostratigraphic literature on each calibration date every time they infer a new timetree; and that literature is not optimized for that task, but largely has other objectives.

category: evolutionary biology


title: Optimal evolutionary control for artificial selection on molecular phenotypes

abstract: Controlling an evolving population is an important task in modern molecular genetics, including directed evolution for improving the activity of molecules and enzymes, in breeding experiments in animals and in plants, and in devising public health strategies to suppress evolving pathogens. An optimal intervention to direct evolution should be designed by considering its impact over an entire stochastic evolutionary trajectory that follows. As a result, a seemingly suboptimal intervention at a given time can be globally optimal as it can open opportunities for desirable actions in the future. Here, we propose a feedback control formalism to devise globally optimal artificial selection protocol to direct the evolution of molecular phenotypes. We show that artificial selection should be designed to counter evolutionary tradeoffs among multi-variate phenotypes to avoid undesirable outcomes in one phenotype by imposing selection on another. Control by artificial selection is challenged by our ability to predict molecular evolution. We develop an information theoretical framework and show that molecular time-scales for evolution under natural selection can inform how to monitor a population in order to acquire sufficient predictive information for an effective intervention with artificial selection. Our formalism opens a new avenue for devising artificial selection methods for directed evolution of molecular functions.


title: Evidence for novel transient cell clusters in the neonatal mouse retina

abstract: Waves of spontaneous activity sweep across the neonatal mouse retinal ganglion cell (RGC) layer, driven by directly interconnected cholinergic starburst amacrine cells from postnatal day (P) 0-10, followed by waves driven by glutamatergic bipolar cells. We found transient clusters of auto-fluorescent cells in the RGC layer during the period of cholinergic waves. They appear around the optic nerve head at P2 and become gradually displaced towards the periphery between P2-8 and then they disappear. Pan-retinal multielectrode array recordings reveal that cholinergic wave origins follow a similar, non-random developmental center-to-periphery pattern. Electrical imaging unmasks hotspots of dipole electrical activity occurring in the vicinity of wave origins. We propose that these activity hotspots are the sites for wave initiation and may originate from the transient cell clusters, reminiscent of activity in transient subplate neurons in the developing cortex, suggesting a universal hyper-excitability mechanism in developing CNS networks during the critical period for brain wiring.


title: Evolution of olfactory receptors tuned to mustard oils in herbivorous Drosophilidae

abstract: The diversity of herbivorous insects is attributed to their propensity to specialize on toxic plants. In an evolutionary twist, toxins betray the identity of their bearers when herbivores co-opt them as cues for host-plant finding, but the mechanisms underlying this process are poorly understood. We focused on Scaptomyza flava, an herbivorous drosophilid specialized on isothiocyanate (ITC)-producing (Brassicaceae) plants, and identified Or67b paralogs that were triplicated as mustard-specific herbivory evolved. Using heterologous systems for the expression of olfactory receptors, we found that S. flava Or67bs, but not homologs from microbe-feeding relatives, responded selectively to ITCs, each paralog detecting different ITC subsets. Consistent with this, S. flava was attracted to ITCs, as was Drosophila melanogaster expressing S. flava Or67b3 in the homologous Or67b olfactory circuit. Thus, our results show that plant toxins were likely co-opted as olfactory attractants through gene duplication and functional specialization (neofunctionalization and subfunctionalization) in drosophilid flies.


title: Organelle specific protein profiling with light mediated proximal labeling in living cells

abstract: Organelle specific protein identification is essential for understanding how cell functions on a subcellular level. Here, we report a light mediated proximal labeling (LIMPLA) strategy for organelle specific protein profiling in living cells. In this strategy, various commercial mitochondria-localized fluorescent trackers, such as Mitoview 405 and Rhodamine 123, can activate 2-Propynylamine (PA) to label proximal proteins in mitochondria under illumination. PA tagged proteins are subsequently derivatized via click chemistry with azido fluorescent dye for imaging or with azido biotin for further enrichment and mass-spec identification. This strategy can be generalized to other organelles specific protein labeling. For example, proteins in nucleus are labeled by utilizing the commercial nucleus tracker DRAQ5. As compared with other chemical strategies for subcellular protein labeling, there are several advantages for this LIMPLA strategy. First, this approach allows minimal interference to the cells status by avoiding exogenous gene tansduction and some special treatment such as hydrogen peroxide or serum starvation. Second, all reagents used in this strategy are commercially available without additional synthesis work. Further, this strategy holds the potential for analyzing proximal proteins of specific macromolecules that can be tagged with fluorescent dye by metabolic labeling strategy.

category: biochemistry


title: NanoCaller for accurate detection of SNPs and indels in difficult-to-map regions from long-read sequencing by haplotype-aware deep neural networks

abstract: Long-read sequencing enables variant detection in genomic regions that are considered difficult-to-map by short-read sequencing. To fully exploit the benefits of longer reads, here we present a deep-learning method NanoCaller, which detects SNPs using long-range haplotype information, then phases long reads with called SNPs and calls indels with local realignment. Evaluation on 8 human genomes demonstrated that NanoCaller generally achieves better performance than competing approaches. We experimentally validated 41 novel variants in a widely-used benchmarking genome, which cannot be reliably detected previously. In summary, NanoCaller facilitates the discovery of novel variants in complex genomic regions from long- read sequencing.


title: Graded recruitment of pupil-linked neuromodulation by parametric stimulation of the vagus nerve

abstract: AO_SCPLOWBSTRACTC_SCPLOWVagus nerve stimulation (VNS) is thought to affect neural activity by recruiting brain-wide release of neuromodulators. VNS is used in treatment-resistant epilepsy, and is increasingly being explored for other disorders, such as depression, and as a cognitive enhancer. However, the promise of VNS is only partially fulfilled due to a lack of mechanistic understanding of the transfer function between stimulation parameters and neuromodulatory response, together with a lack of biosensors for assaying stimulation efficacy in real time. We here develop an approach to VNS in head-fixed mice on a treadmill and show that pupil dilation is a reliable and convenient biosensor for VNS-evoked cortical neuromodulation. In an  optimal zone of stimulation parameters, current leakage and off-target effects are minimized and the extent of pupil dilation tracks VNS-evoked basal-forebrain cholinergic axon activity in neocortex. Thus, pupil dilation is a sensitive readout of the moment-by-moment, titratable effects of VNS on brain state.


title: Tracking niche change through time: simultaneous inference of ecological niche evolution and estimation of contemporary niches

abstract:
O_LIThe ecological niche of species is often studied from two different perspectives. Environmental niche modelling (ENM) infers a species current niche from contemporary occurrence records, while phylogenetic comparative methods (PCM) infer the history of niche evolution. Although these two areas of research are conceptually linked, they are analysed independently, within separate analytical frameworks.
C_LIO_LIHere we provide a new method, NEMo (Niche Evolution Model), for simultaneous inference of niche evolution and estimation of contemporary niches of species. NEMo explicitly models three fundamental processes of niche evolution - adaptation, speciation, and dispersal - applying a reversible jump algorithm to infer occurrences of these processes on a phylogeny. The model permits ENMs to account for the role of history in shaping current species distributions, and offers more realistic models of evolution in PCMs.
C_LIO_LISimulations show that NEMo has high accuracy for estimating the ecological niche of species, and reasonable power to identify the occurrences of the three processes on phylogeny. When applied to a real case study (the Australian plant genus Acacia), the method is more effective at predicting a key environmental niche axis (salt tolerance) than using ENM alone, and it infers temporal patterns in the evolution of drought tolerance in response to aridification that are consistent with prior expectations
C_LIO_LINEMo makes it possible to combine many types of data to study niche evolution and estimate species niches, not only species distributions and phylogeny, but also paleoclimate, species tolerance range, and fossil records.
C_LI


title: Predictive olfactory learning in Drosophila

abstract: Olfactory learning and conditioning in the fruit fly is typically modelled by correlation-based associative synaptic plasticity. It was shown that the conditioning of an odor-evoked response by a shock depends on the connections from Kenyon cells (KC) to mushroom body output neurons (MBONs). Although on the behavioral level conditioning is recognized to be predictive, it remains unclear how MBONs form predictions of aversive or appetitive values (valences) of odors on the circuit level. We present behavioral experiments that are not well explained by associative plasticity between conditioned and unconditioned stimuli, and we suggest two alternative models for how predictions can be formed. In error-driven predictive plasticity, dopaminergic neurons (DANs) represent the error between the predictive odor value and the shock strength. In target-driven predictive plasticity, the DANs represent the target for the predictive MBON activity. Predictive plasticity in KC-to-MBON synapses can also explain trace-conditioning, the valence-dependent sign switch in plasticity, and the observed novelty-familiarity representation. The model offers a framework to dissect MBON circuits and interpret DAN activity during olfactory learning.


title: The co-stimulatory activity of Tim-3 requires Akt and MAPK signaling and immune synapse recruitment

abstract:
Expression of the transmembrane protein Tim-3 is increased on dysregulated T cells undergoing chronic T cell activation, including in chronic infection and solid tumors. We and others previously reported that Tim-3 exerts apparently paradoxical co-stimulatory activity in T cells (and other cells), including enhancement of ribosomal S6 protein phosphorylation (pS6). Here we examined the upstream signaling pathways that control Tim3-mediated increases in pS6 in T cells. We have also defined the localization of Tim-3 relative to the T cell immune synapse and impacts on downstream signaling. Recruitment of Tim-3 to the immune synapse was mediated exclusively by the transmembrane domain, replacement of which impaired Tim-3 co-stimulation of pS6. Strikingly, enforced localization of the Tim-3 cytoplasmic domain to the immune synapse in the context of a chimeric antigen receptor still allowed for robust T cell activation. Our findings are consistent with a model whereby Tim-3 enhances TCR-proximal signaling under acute conditions.

One Sentence SummaryHere we define elements of signaling and localization associated with Tim-3 co-stimulatory function in T cells.

category: immunology


title: A standardized gnotobiotic mouse model harboring a minimal 15-member mouse gut microbiota recapitulates SOPF/SPF phenotypes

abstract: Mus musculus is the classic mammalian model for biomedical research. Despite global efforts to standardize breeding and experimental procedures, the undefined composition and interindividual diversity of the microbiota of laboratory mice remains a limitation. In an attempt to standardize the gut microbiome in preclinical mouse studies, we developed a simplified mouse microbiota composed of 15 strains from 7 of the 20 most prevalent bacterial families representative of the fecal microbiota of C57BL/6J Specific (and Opportunistic) Pathogen-Free (SPF/SOPF) animals and derived a new standardized gnotobiotic mouse model called GM15. GM15 recapitulates extensively the functionalities found in the C57BL/6J SOPF microbiota metagenome, and GM15 animals are phenotypically similar to SOPF or SPF animals in two different facilities. They are also less sensitive to the deleterious effects of post-weaning malnutrition. The GM15 model provides increased reproducibility and robustness of preclinical studies by limiting the confounding effect of fluctuation in microbiota composition, and offers new opportunities for research focused on how the microbiota shapes host physiology in health and disease.

category: microbiology


title: Engineering indel and substitution variants of diverse and ancient enzymes using Graphical Representation of Ancestral Sequence Predictions (GRASP)

abstract:
Ancestral sequence reconstruction is a technique that is gaining widespread use in molecular evolution studies and protein engineering. Accurate reconstruction requires the ability to handle appropriately large numbers of sequences, as well as insertion and deletion ("indel") events, but available approaches exhibit limitations. To address these limitations, we developed Graphical Representation of Ancestral Sequence Predictions (GRASP), which efficiently implements maximum likelihood methods to enable the inference of ancestors of families with more than 10,000 members. GRASP implements partial order graphs (POGs) to represent and infer insertion and deletion events across ancestors, enabling the identification of building blocks for protein engineering.

To validate the capacity to engineer novel proteins from realistic data, we predicted ancestor sequences across three distinct enzyme families: glucose-methanol-choline (GMC) oxidoreductases, cytochromes P450, and dihydroxy/sugar acid dehydratases (DHAD). All tested ancestors demonstrated enzymatic activity. Our study demonstrates the ability of GRASP (1) to support large data sets over 10,000 sequences and (2) to employ insertions and deletions to identify building blocks for engineering biologically active ancestors, by exploring variation over evolutionary time.

Author summaryMassive sequencing projects expose the extent of natural, genetic diversity. Here, we describe a method with capacity to perform ancestor sequence reconstruction from data sets in excess of 10,000 sequences, poised to recover ancestral diversity, including the evolutionary events that determine present-time biological function and structure.

We introduce a novel strategy for suggesting "indel variants" that are distinct from, but can be explored alongside, substitution variants for creating ancestral libraries. We demonstrate how indels can be used as building blocks to form "hybrid ancestors"; based on this strategy, we synthesise ancestor variants, with varying enzymatic activities, for wide-ranging applications in the biotechnology sector.


title: Designing signaling environments to steer transcriptional diversity in neural progenitor cell populations

abstract:
Stem and progenitor populations within developing embryos are diverse, composed of different subpopulations of precursor cells with varying developmental potential. How these different subpopulations are coordinately regulated by their signaling environments is not well understood. In this paper we develop a framework for controlling progenitor population structure in cell culture using high-throughput single cell mRNA-seq and computational analysis. We find that the natural transcriptional diversity of neural stem cell populations from the developing mouse brain collapses during in vitro culture. Cell populations are depleted of committed neuroblast progenitors and become dominated by a single pre-astrocytic cell population. By analyzing the response of neural stem cell populations to forty combinatorial signaling conditions, we demonstrate that signaling environments can restructure cell populations by modulating the relative abundance of pre-astrocytic and pre-neuronal subpopulations according to a simple log-linear model. Our work demonstrates that single-cell RNA-seq can be applied to learn how to modulate the diversity of stem cell populations, providing a new strategy for population-level stem cell control.

HighlightsO_LINatural progenitor diversity in the brain collapses during in vitro culture to a single progenitor type
C_LIO_LILoss of progenitor diversity alters fate potential of cells during differentiation
C_LIO_LILarge scale single-cell signaling screen identifies signals that reshape population structure towards neuronal cell types
C_LIO_LISignals regulate population structure according to a simple log-linear model
C_LI

GRAPHICAL ABSTRACT

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title: Effect of high-frequency low-intensity pulsed electric field on protecting SH-SY5Y cells against hydrogen peroxide and β-amyloid-induced cell injury via ERK pathway

abstract: As the most common type of neurodegenerative diseases (NDDs), Alzheimers disease (AD) is thought to be caused mainly by the excessive aggregation of {beta}-amyloid protein (A{beta}). However, a growing number of studies have found that reactive oxygen species (ROS) play a key role in the onset and progression of AD. The present study aimed to probe the neuroprotective effect of high-frequency low-intensity pulsed electric field (H-LIPEF) for SH-SY5Y cells against hydrogen peroxide (H2O2) and A{beta}-induced cytotoxicity. By looking in a systematic way into the frequency- and amplitude-dependent neuroprotective effect of pulsed electric field (PEF), the study finds that H-LIPEF at 200 Hz produces the optimal protective effect for SH-SY5Y cells. The underlying mechanisms were confirmed to be due to the activation of extracellular signal-regulated kinase (ERK) pathway and the downstream prosurvival and antioxidant proteins. Because the electric field can be modified to focus on specific area in a non-contact manner, the study suggests that H-LIPEF holds great potential for treating NDDs, whose effect can be further augmented with the administering of drugs or natural compounds at the same time.


title: Binary and analog variation of synapses between cortical pyramidal neurons

abstract: Learning from experience depends at least in part on changes in neuronal connections. We present the largest map of connectivity to date between cortical neurons of a defined type (L2/3 pyramidal cells), which was enabled by automated analysis of serial section electron microscopy images with improved handling of image defects. We used the map to identify constraints on the learning algorithms employed by the cortex. Previous cortical studies modeled a continuum of synapse sizes (Arellano et al. 2007) by a log-normal distribution (Loewenstein, Kuras, and Rumpel 2011; de Vivo et al. 2017; Santuy et al. 2018). A continuum is consistent with most neural network models of learning, in which synaptic strength is a continuously graded analog variable. Here we show that synapse size, when restricted to synapses between L2/3 pyramidal cells, is well-modeled by the sum of a binary variable and an analog variable drawn from a log-normal distribution. Two synapses sharing the same presynaptic and postsynaptic cells are known to be correlated in size (Sorra and Harris 1993; Koester and Johnston 2005; Bartol et al. 2015; Kasthuri et al. 2015; Dvorkin and Ziv 2016; Bloss et al. 2018; Motta et al. 2019). We show that the binary variables of the two synapses are highly correlated, while the analog variables are not. Binary variation could be the outcome of a Hebbian or other synaptic plasticity rule depending on activity signals that are relatively uniform across neuronal arbors, while analog variation may be dominated by other influences. We discuss the implications for the stability-plasticity dilemma.


title: Material category of visual objects computed from specular image structure

abstract: Recognising materials and their properties from visual information is vital for successful interactions with our environment, from avoiding slippery floors to handling fragile objects. Yet there is no simple mapping of retinal image intensities to the physical properties that define materials. While studies have investigated how material properties like surface gloss are perceived from regularities in image structure, such as the size, sharpness, contrast, and position of bright patches caused by specular reflections, little is known how this translates to the recognition of different material classes like plastic, pearl, satin, or steel, and the underlying mechanisms involved. We investigated this by collecting human psychophysical judgments about complex glossy objects rendered in natural illumination fields. We found that variations in specular image structure - produced either by different reflectance properties or direct manipulation of image features - caused categorical shifts in material appearance, suggesting that specular reflections provide diagnostic information about a wide range of material classes, including many that should be defined by more complex scattering functions. Moreover, differences in material category were predicted by, but also appeared to mediate, cues for surface gloss, providing evidence against a traditional feedforward view of neural processing that assumes combinations of mid-level properties mediate our holistic, categorical impressions. Instead, our results suggest that the image structure that triggers our perception of surface gloss plays a direct role in visual categorisation and, importantly, that the perception and neural processing of stimulus properties should not be studied in isolation but rather in the context of recognition.


title: An antigenic diversification threshold for falciparum malaria transmission at high endemicity

abstract:
In malaria and several other important infectious diseases, high prevalence occurs concomitantly with incomplete immunity. This apparent paradox poses major challenges to malaria elimination in highly endemic regions, where asymptomatic Plasmodium falciparum infections are present across all age classes creating a large reservoir that maintains transmission. This reservoir is in turn enabled by extreme antigenic diversity of the parasite and turnover of new variants. We present here the concept of a threshold in local pathogen diversification that defines a sharp transition in transmission intensity below which new antigen-encoding genes generated by either recombination or migration cannot establish. Transmission still occurs below this threshold, but diversity of these genes can neither accumulate nor recover from interventions that further reduce it. An analytical expectation for this threshold is derived and compared to numerical results from a stochastic individual-based model of malaria transmission that incorporates the major antigen-encoding multigene family known as var. This threshold corresponds to an "innovation" number we call Rdiv; it is different from, and complementary to, the one defined by the classic basic reproductive number of infectious diseases, R0, which does not easily apply under large and dynamic strain diversity. This new threshold concept can be exploited for effective malaria control and applied more broadly to other pathogens with large multilocus antigenic diversity.

Author summaryThe vast diversity of the falciparum malaria parasite as seen by the immune system of hosts in high transmission regions, underlies both high prevalence of asymptomatic infections and partial protection to re-infection despite previous exposure. This large antigenic diversity of the parasite challenges control and elimination efforts. We propose a threshold quantity for antigenic innovation, we call Rdiv, measuring the potential of transmission to accumulate new antigenic variants over time. When Rdiv is pushed below one by reduced transmission intensity, new genes encoding this variation can no longer accumulate, resulting in a lower number of strains and facilitating further intervention. This innovation number can be applied to other infectious diseases with fast turnover of antigens, where large standing diversity similarly opposes successful intervention.


title: Epitope-tagging of the endogenous murine BiP/GRP78/Hspa5 locus allows direct analysis of the BiP interactome and protein misfolding in vivo.

abstract: BiP/GRP78, encoded by the Hspa5 gene, is the major HSP70 family member in the endoplasmic reticulum (ER) lumen, and controls ER protein folding. The essential functions of BiP in facilitating proper protein folding are mainly mediated through its dynamic interaction with unfolded or misfolded client proteins, and by serving as a negative regulator of the Unfolded Protein Response. A mechanistic understanding of the dynamics of BiP interaction with its protein partners is essential to understand ER biology, and therefore, we have sought to develop a tractable model to study misfolded protein interaction with BiP. For this purpose, we have used homologous recombination to insert a 3xFLAG epitope tag into the endogenous murine Hspa5 gene, just upstream from the essential KDEL signal necessary for ER localization of BiP. Tagging BiP in this way did not alter Hspa5 expression under basal or ER-stress induced conditions in hepatocytes ex vivo or in fibroblasts. Furthermore, the tag did not alter the cellular localization of BiP or its functionality. All of these findings in primary tissue culture were also confirmed in vivo in livers of heterozygous mice harboring one WT and one FLAG-tagged Hspa5 allele. Hepatocyte-specific BiP-FLAG modification did not alter liver function or UPR signaling. Importantly, immunoprecipitation with anti-FLAG antibody completely pulled down FLAG-tagged BiP from lysates of BiP-FLAG expressing livers. Affinity purification-mass spectrometry (AP-MS) of BiP-FLAG protein complexes isolated from the BiP-FLAG-expressing livers of tunicamycin (TM)- and vehicle-treated mice revealed a marked increase in interaction of glycoproteins with BiP-FLAG in response to inhibition of N-glycosylation due to TM-treatment, validating utility of our BiP-Flag mice as a tool to identify ER misfolded proteins in vivo. Significantly, our AP-MS analysis also provided in vivo evidence demonstrating that BiP-FLAG binds to UPR transducers IRE1 and PERK under basal conditions but is released upon TM-treatment to activate UPR. We have also employed this mouse model to demonstrate that proinsulin in pancreatic {beta} cells misfolds and interacts with BiP-FLAG in healthy mice. In summary, we generated a novel model that can be used to investigate the BiP interactome in vivo under physiological and pathophysiological conditions in a cell type-specific manner. This tool provides, for the first time, an unbiased approach to identify unfolded and misfolded BiP-client proteins, and a new approach to study ER protein misfolding in a cell-type and temporal manner to uncover the role of BiP in many essential ER processes.

category: molecular biology


title: Epitope-tagging of the endogenous murine BiP/GRP78/Hspa5 locus allows direct analysis of the BiP interactome and protein misfolding in vivo


title: Plant Trans-Golgi Network/Early Endosome pH regulation requires Cation Chloride Cotransporter (CCC1)

abstract: Plant cells maintain a low luminal pH in the Trans-Golgi-Network/Early Endosome (TGN/EE), the organelle in which the secretory and endocytic pathways intersect. Impaired TGN/EE pH regulation translates into severe plant growth defects. The identity of the proton pump and proton/ion antiporters that regulate TGN/EE pH have been determined, but an essential component required to complete the TGN/EE membrane transport circuit remains unidentified - a pathway for cation and anion efflux. Here, we have used complementation, genetically encoded fluorescent sensors, and pharmacological treatments to demonstrate that the TGN/EE localised Arabidopsis Cation Chloride Cotransporter (CCC1) is this missing component necessary for regulating TGN/EE pH and function. Loss of CCC1 function leads to alterations in TGN/EE-mediated processes including endo- and exocytosis, and trafficking to the vacuole, and response to abiotic stress, consistent with the multitude of phenotypes observed in ccc1 knockout plants. This discovery places CCC1 as a central component of plant cellular function.


title: To Group or not to group: Group size dynamics and intestinal parasites in Indian peafowl populations

abstract: Animals can form groups for various reasons including safety from predators, access to potential mates and benefits of allo-parental care. However, there are costs associated with living in a group such as competition for food and/or mates with other members of the group, higher chances of disease transmission, etc. Group size dynamics can change with the biotic and abiotic environment around individuals. In the current study, we explored the links between group size dynamics and intestinal parasites of Indian peafowl (Pavo cristatus) in the context of seasons and food provisioning. Data for group size was collected across three seasons (Pre-Monsoon, Monsoon and Post-Monsoon) at three field sites (Morachi Chincholi, Nashik and Rajasthan). Individual and group sightings of peafowl were noted down along with group size and composition (no. of males, females, adults, juveniles, sub-adults). Faecal samples were collected from food provision and non-provision areas across the same three seasons at same field sites. Parasite load in the samples was quantified using microscopic examination. Group size was significantly higher in Pre-Monsoon season as compared to Monsoon and Post-Monsoon seasons. Monsoon and Post-Monsoon seasons had higher intestinal parasite prevalence and load as compared to Pre-Monsoon season. Thus, group size and intestinal parasites of Indian peafowl have an inverse relationship across seasons. Parasite load was significantly greater at food provision sites as compared to non-provision sites while parasite prevalence was comparable. Aggregation of individuals at the food provision sites may influence the parasite transmission and group-size dynamics in Indian peafowl. In conclusion, Indian peafowl are behaviourally plastic and fission-fusion of social groups may allow them to tackle ecological pressures such as predation and parasite transmission in different seasons.


title: Consequences of combining sex-specific life-history traits

abstract: Males and females evolved distinct life-history strategies, reflected in diverse inter-linked life-history traits. The sex that allocates more resources towards offspring relies on an increased life span, and long life requires an efficient immune system. The other sex needs to attract mates and thus allocates its resources towards ornamentation, which may negatively correlate with investment into the immune defense. Such sex-specific resource allocation trade-offs are not always strictly female or male-specific but may depend on the overall resources allocated towards life-history traits. Informed by experimental data, we designed a theoretical framework that combines multiple life-history traits. We disentangled specific life-history strategies from particular sex, allowing us to include species with reversed sex-roles and male parental investment. We computed the lifetime reproductive success (combining fitness components from diverse sex-specific life-history traits) observing a strong bias in adult sex ratio depending on sex-specific resource allocation towards life-history traits. Overall, our work provides a generalized method to combine various life-history traits with sex-specific differences to calculate lifetime reproductive success. The results explain specific population-level empirical observations as a consequence of sexual dimorphism in life-history traits.


title: Biophysical basis of cellular multi-specificity encoded in a model molecular switch

abstract: Molecular switches are central to signal transduction in protein interaction networks. One switch protein can independently regulate distinct cellular processes, but the molecular mechanisms enabling this functional multi-specificity remain unclear. Here we integrate system-scale cellular and biophysical measurements to study how a paradigm switch, the small GTPase Ran/Gsp1, achieves its functional multi-specificity. We make 55 targeted point mutations to individual interactions of Ran/Gsp1 and show through quantitative, systematic genetic and physical interaction mapping that Ran/Gsp1 interface perturbations have widespread cellular consequences that cluster by biological processes but, unexpectedly, not by the targeted interactions. Instead, the cellular consequences of the interface mutations group by their biophysical effects on kinetic parameters of the GTPase switch cycle, and cycle kinetics are allosterically tuned by distal interface mutations. We propose that the functional multi-specificity of Ran/Gsp1 is encoded by a differential sensitivity of biological processes to different kinetic parameters of the Gsp1 switch cycle, and that Gsp1 partners binding to the sites of distal mutations act as allosteric regulators of the switch. Similar mechanisms may underlie biological regulation by other GTPases and biological switches. Finally, our integrative platform to determine the quantitative consequences of cellular perturbations may help explain the effects of disease mutations targeting central switches.


title: The mechanisms of in vivo commensal control of Clostridioides difficile virulence

abstract:
We define multiple mechanisms by which commensals protect against or worsen Clostridioides difficile infection. Leveraging new systems-level models we show how metabolically distinct species of Clostridia modulate the pathogens colonization, growth, and virulence to impact host survival. Gnotobiotic mice colonized with the amino acid fermenter Paraclostridium bifermentans survived infection while mice colonized with the butyrate- producer, Clostridium sardiniense, more rapidly succumbed. Systematic in vivo analyses revealed how each commensal altered the gut nutrient environment, modulating the pathogens metabolism, regulatory networks, and toxin production. Oral administration of P. bifermentans rescued conventional mice from lethal C. difficile infection via mechanisms identified in specifically colonized mice. Our findings lay the foundation for mechanistically informed therapies to counter C. difficile infections using systems biologic approaches to define host-commensal-pathogen interactions in vivo.

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title: Modeling gene expression evolution with EvoGeneX uncovers differences in evolution of species, organs and sexes

abstract:
While DNA sequence evolution has been well studied, the expression of genes is also subject to evolution, yet the evolution of gene expression is currently not well understood. Recently, new tissue/organ-specific gene expression datasets spanning several organisms across the tree of life, have become available, providing the opportunity to study gene expression evolution in more detail. While a theoretical model to study the evolution of continuous traits exists, in practice computational methods often cannot confidently distinguish between alternative evolutionary scenarios. This lack of power has been attributed to modest numbers of species considered in these studies.

We hypothesised that biological replicates can be used to increase predictive power of these models. With this in mind, we introduce EvoGeneX, a computationally efficient method to uncover the mode of gene expression evolution based on the Ornstein-Uhlenbeck process. Importantly, in addition to modelling expression variations between species, EvoGeneX models within-species variation.

Furthermore, to facilitate comparative analysis of gene expression evolution, we introduce a formal approach, based on Michaelis-Menten equation, to measure the dynamics of evolutionary divergence of a group of genes in terms of groups asymptotic divergence level and rate.

Finally, we used these tools to preform the first analysis the evolution of gene expression across different body parts, species, and sexes of the Drosophila genus. Our analysis revealed that neutral expression evolution can be confidently rejected in favor of purifying selection in nearly half of the genes. In addition, we quantified differences in the evolutionary dynamics of male and female gonads and uncovered interesting examples of adaptive gene expression evolution.


title: Different forms of variability could explain a difference between human and rat decision making

abstract: When observers make rapid, difficult perceptual decisions, their response time is highly variable from trial to trial. In a visual motion discrimination task, it has been reported that human accuracy declines with increasing response time, whereas rat accuracy increases with response time. This is of interest because different mathematical theories of decision-making differ in their predictions regarding the correlation of accuracy with response time. On the premise that perceptual decision-making mechanisms are likely to be conserved among mammals, we seek to unify the rodent and primate results in a common theoretical framework. We show that a bounded drift diffusion model (DDM) can explain both effects with variable parameters: trial-to-trial variability in the starting point of the diffusion process produces the pattern typically observed in rats, whereas variability in the drift rate produces the pattern typically observed in humans. We further show that the same effects can be produced by deterministic biases, even in the absence of parameter stochasticity or parameter change within a trial.


title: Mechanical control of morphogenetic robustness in an inherently challenging environment

abstract:
Epithelial sheets undergo highly reproducible remodeling to shape organs. This stereotyped morphogenesis depends on a well-defined sequence of events leading to the regionalized expression of developmental patterning genes that finally triggers downstream mechanical forces to drive tissue remodeling at a pre-defined position. However, how tissue mechanics controls morphogenetic robustness when challenged by intrinsic perturbations in close proximity has never been addressed.

Here, we show that a bias in force propagation ensures stereotyped morphogenesis despite the presence of mechanical noise in the environment. We found that knockdown of the Arp2/3 complex member Arpc5 specifically affects fold directionality without altering neither the developmental nor the force generation patterns. By combining in silico modeling, biophysical and ad hoc genetic tools, our data reveal that junctional Myosin II planar polarity favors long-range force channeling and ensures folding robustness, avoiding force scattering and thus isolating the fold domain from surrounding mechanical perturbations.

category: developmental biology


title: Scanning electron microscopy preparation of the cellular actin cortex: a quantitative comparison between critical point drying and hexamethyldisilazane drying

abstract: The cellular cortex is an approximately 200-nm-thick actin network that lies just beneath the cell membrane. It is responsible for the mechanical properties of cells, and as such, it is involved in many cellular processes, including cell migration and cellular interactions with the environment. To develop a clear view of this dense structure, high-resolution imaging is essential. As one such technique, electron microscopy, involves complex sample preparation procedures. The final drying of these samples has significant influence on potential artifacts, like cell shrinkage and the formation of artifactual holes in the actin cortex. In this study, we compared the three most used final sample drying procedures: critical-point drying (CPD), CPD with lens tissue (CPD-LT), and hexamethyldisilazane drying. We show that both hexamethyldisilazane and CPD-LT lead to fewer artifactual mesh holes within the actin cortex than CPD. Moreover, CPD-LT leads to significant reduction in cell height compared to hexamethyldisilazane and CPD. We conclude that the final drying procedure should be chosen according to the reduction in cell height, and so CPD-LT, or according to the spatial separation of the single layers of the actin cortex, and so hexamethyldisilazane.

category: biophysics


title: Protein sequence design with a learned potential

abstract: AO_SCPLOWBSTRACTC_SCPLOWThe task of protein sequence design is central to nearly all rational protein engineering problems, and enormous effort has gone into the development of energy functions to guide design. We investigate the capability of a deep neural network model to automate design of sequences onto protein backbones, having learned directly from crystal structure data and without any human-specified priors. The model generalizes to native topologies not seen during training, producing experimentally stable designs. We evaluate the generalizability of our method to a de novo TIM-barrel scaffold. The model produces novel sequences, and high-resolution crystal structures of two designs show excellent agreement with the in silico models. Our findings demonstrate the tractability of an entirely learned method for protein sequence design.


title: Regulation of mitophagy by the NSL complex underlies genetic risk for Parkinson's disease at Chr16q11.2 and on the MAPT H1 allele

abstract: Parkinsons disease (PD) is a common incurable neurodegenerative disease. The identification of genetic variants via genome-wide association studies (GWAS) has considerably advanced our understanding of the PD genetic risk. Understanding the functional significance of the risk loci is now a critical step towards translating these genetic advances into an enhanced biological understanding of the disease. Impaired mitophagy is a key causative pathway in familial PD, but its relevance to idiopathic PD is unclear. We used a mitophagy screening assay to evaluate the functional significance of risk genes identified through GWAS. We identified two new regulators of PINK1-mitophagy, KAT8 and KANSL1, previously shown to modulate lysine acetylation. We show that KAT8 and KANSL1 modulate PINK1 gene expression and subsequent PINK1-mitophagy. These findings suggest PINK1-mitophagy is a contributing factor to idiopathic PD. KANSL1 is located on chromosome 17q21 where the risk associated gene has long been considered to be MAPT. While our data does not exclude a possible association between the MAPT gene and PD, it provides strong evidence that KANSL1 plays a crucial role in the disease. Finally, these results enrich our understanding of physiological events regulating mitophagy and establish a novel pathway for drug targeting in neurodegeneration.


title: Lumbar corticospinal tract in rodents modulates sensory inputs but does not convey motor command

abstract:
It is generally assumed that the main function of the corticospinal tract (CST) is to convey motor commands to bulbar or spinal motoneurons. Yet the CST has also been shown to modulate sensory signals at their entry point in the spinal cord, through presynaptic inhibition. By sequentially investigating different routes of corticofugal pathways through electrophysiological recordings and an intersectional viral strategy, we here demonstrate that motor and sensory modulation commands in mice belong to segregated paths within the CST. Sensory modulation is excuted exclusively by the CST via a population of lumbar interneurons located in the deep dorsal horn. In contrast, the cortex conveys the motor command via a relay in the upper spinal cord or supraspinal motor centers. At lumbar level, the main role of the CST is thus the modulation of sensory inputs, which is an essential component of the selective tuning of sensory feedback, to ensure well-coordinated and skilled movement.

Impact statementWhile the corticospinal tract is often considered exclusively as a motor path, this study demonstrates that, in the mouse lumbar cord, its main role is the modulation of sensory inputs.


title: Subliminal perception can be predicted from prestimulus activity

abstract: Individuals are able to discriminate visual stimuli they report not consciously seeing. This phenomenon is known as "subliminal perception." Such capacity is often assumed to be relatively automatic in nature, and rely on stimulus-driven activity in low-level cortical areas. Instead, here we asked to what extent neural activity before stimulus presentation influences subliminal perception. We asked participants to discriminate the location of a briefly presented low-contrast visual stimulus, and then rate how well they saw the stimulus. Consistent with previous studies, participants correctly discriminated with slightly above chance-level accuracy the location of a stimulus they reported not seeing. Signal detection analyses indicated that while subjects categorized their percepts as "unconscious", their capacity to discriminate these stimuli lay on the same continuum as conscious vision. We show that the accuracy of discriminating the location of a subliminal stimulus could be predicted with relatively high accuracy (AUC = .70) based on lateralized electroencephalographic (EEG) activity before the stimulus, the hemifield where the stimulus was presented, and accuracy of previous trials discrimination response. Altogether, our results suggest that rather than being a separate unconscious capacity, subliminal perception is based on similar processes as conscious vison.


title: Predictive feedback, early sensory representations and fast responses to predicted stimuli depend on NMDA receptors

abstract: Learned associations between stimuli allow us to model the world and make predictions, crucial for efficient behavior; e.g., hearing a siren, we expect to see an ambulance and quickly make way. While there are theoretical and computational frameworks for prediction, the circuit and receptor-level mechanisms are unclear. Using high-density EEG, Bayesian modeling and machine learning, we show that inferred "causal" relationships between stimuli and frontal alpha activity account for reaction times (a proxy for predictions) on a trial-by-trial basis in an audio-visual delayed match-to-sample task which elicited predictions. Predictive beta feedback activated sensory representations in advance of predicted stimuli. Low-dose ketamine, a NMDA receptor blocker - but not the control drug dexmedetomidine - perturbed behavioral indices of predictions, their representation in higher-order cortex, feedback to posterior cortex and pre-activation of sensory templates in higher-order sensory cortex. This study suggests predictions depend on alpha activity in higher-order cortex, beta feedback and NMDA receptors, and ketamine blocks access to learned predictive information.


title: Computed tomography reveals hip dysplasiain the extinct Pleistocene saber-tooth cat Smilodon

abstract: Reconstructing the behavior of extinct species is challenging, particularly for those with no living analogues. However, damage preserved as paleopathologies on bone can record how an animal moved in life, potentially reflecting behavioral patterns. Here, we assess hypothesized etiologies of pathology in a pelvis and associated right femur of a Smilodon fatalis saber-toothed cat, one of the best-studied species from the Pleistocene-age Rancho La Brea asphalt seeps, California, USA, using visualization by computed tomography (CT). The pelvis exhibits massive destruction of the right hip socket that was interpreted, for nearly a century, to have developed from trauma and infection. CT imaging reveals instead that the pathological distortions characterize chronic remodeling that began at birth and led to degeneration of the joint over the animals life. These results suggest that this individual suffered from hip dysplasia, a congenital condition common in domestic dogs and cats. This individual reached adulthood but could not have hunted properly nor defended territory on its own, likely relying on a social group for feeding and protection. While extant social felids are rare, these fossils and others with similar pathologies are consistent with a spectrum of social strategies in Smilodon supported by a predominance of previous studies.

category: paleontology


title: Role of the transcriptional regulator SP140 in resistance to bacterial infections via repression of type I interferons

abstract:
Type I interferons (IFNs) are essential for anti-viral immunity, but often impair protective immune responses during bacterial infections. An important question is how type I IFNs are strongly induced during viral infections, and yet are appropriately restrained during bacterial infections. The Super susceptibility to tuberculosis 1 (Sst1) locus in mice confers resistance to diverse bacterial infections. Here we provide evidence that Sp140 is a gene encoded within the Sst1 locus that represses type I IFN transcription during bacterial infections. We generated Sp140-/- mice and find they are susceptible to infection by Legionella pneumophila and Mycobacterium tuberculosis. Susceptibility of Sp140-/- mice to bacterial infection was rescued by crosses to mice lacking the type I IFN receptor (Ifnar-/-). Our results implicate Sp140 as an important negative regulator of type I IFNs that is essential for resistance to bacterial infections.

Impact StatementRepression of type I interferons by SP140 is essential for resistance to Legionella pneumophila and Mycobacterium tuberculosis.


title: Error correction enables use of Oxford Nanopore technology for reference-free transcriptome analysis

abstract: Oxford Nanopore (ONT) is a leading long-read technology which has been revolutionizing transcriptome analysis through its capacity to sequence the majority of transcripts from end-to-end. This has greatly increased our ability to study the diversity of transcription mechanisms such as transcription initiation, termination, and alternative splicing. However, ONT still suffers from high error rates which have thus far limited its scope to reference-based analyses. When a reference is not available or is not a viable option due to reference-bias, error correction is a crucial step towards the reconstruction of the sequenced transcripts and downstream sequence analysis of transcripts. In this paper, we present a novel computational method to error correct ONT cDNA sequencing data, called isONcorrect. IsONcorrect is able to jointly use all isoforms from a gene during error correction, thereby allowing it to correct reads at low sequencing depths. We are able to obtain a median accuracy of 98.9-99.6%, demonstrating the feasibility of applying cost-effective cDNA full transcript length sequencing for reference-free transcriptome analysis.


title: Bayesian cell-type deconvolution and gene expression inference reveals tumor-microenvironment interactions

abstract: Understanding the interactions between cells in their environment is a major challenge in genomics. Here we developed BayesPrism, a Bayesian method to jointly predict cellular composition and gene expression in each cell type, including heterogeneous malignant cells, from bulk RNA-seq using scRNA-seq as prior information. We conducted an integrative analysis of 1,412 bulk RNA-seq samples in primary glioblastoma, head and neck squamous cell carcinoma, and melanoma using single-cell datasets of 85 patients. We identified cell types correlated with clinical outcomes and explored spatial heterogeneity in malignant cell states and non-malignant cell type composition. We refined subtypes using gene expression in malignant cells, after excluding confounding non-malignant cell types. Finally, we identified genes whose expression in malignant cells correlated with infiltration of macrophages, T cells, fibroblasts, and endothelial cells across multiple tumor types. Our work introduces a new lens that uses scRNA-seq to accurately infer cellular composition and expression in large cohorts of bulk data.

category: genomics


title: RNA-binding protein Syncrip regulates Starvation-Induced Hyperactivity in adult Drosophila

abstract:
How to respond to starvation determines fitness. One prominent behavioral response is increased locomotor activities upon starvation, also known as Starvation-Induced Hyperactivity (SIH). SIH is paradoxical as it promotes food seeking but also increases energy expenditure. Despite its importance in fitness, the genetic contributions to SIH as a behavioral trait remains unexplored. Here, we examined SIH in the Drosophila melanogaster Genetic Reference Panel (DGRP) and performed genome-wide association studies. We identified 23 significant loci, corresponding to 14 genes, significantly associated with SIH in adult Drosophila. Gene enrichment analyses indicated that genes encoding ion channels and mRNA binding proteins (RBPs) were most enriched in SIH. We are especially interested in RBPs because they provide a potential mechanism to quickly change protein expression in response to environmental challenges. Using RNA interference, we validated the role of syp in regulating SIH. syp encodes Syncrip (Syp), an RBP. While ubiquitous knockdown of syp led to semi-lethality in adult flies, adult flies with neuron-specific syp knockdown were viable and exhibited decreased SIH. Using the Temporal and Regional Gene Expression Targeting (TARGET) system, we further confirmed the role of Syp in adult neurons in regulating SIH. To determine how syp is regulated by starvation, we performed RNA-seq using the heads of flies maintained under either food or starvation conditions. RNA-seq analyses revealed that syp was alternatively spliced under starvation while its expression level was unchanged. We further generated an alternatively-spliced-exon-specific knockout (KO) line and found that KO flies showed reduced SIH. Together, this study demonstrates a significant genetic contribution to SIH as a behavioral trait, identifies syp as a SIH gene, and highlights the significance of RBPs and post-transcriptional processes in the brain in regulating behavioral responses to starvation.

Author summaryAnimals living in the wild often face periods of starvation. How to physiologically and behaviorally respond to starvation is essential for survival. One behavioral response is Starvation-Induced Hyperactivity (SIH). We used the Drosophila melanogaster Genetic Reference Panel, derived from a wild population, to study the genetic basis of SIH. Our results show that there is a significant genetic contribution to SIH in this population, and that genes encoding RNA binding proteins (RBPs) are especially important. Using RNA interference and the TARGET system, we confirmed the role of an RBP Syp in adult neurons in SIH. Using RNA-seq and Western blotting, we found that syp was alternatively spliced under starvation while its expression level was unchanged. Further studies from syp exon-specific knockout flies showed that alternative splicing involving two exons in syp was important for SIH. Together, this study identifies syp as a SIH gene and highlights an essential role of post-transcriptional modification in regulating this behavior.


title: 4DNvestigator: Time Series Genomic Data Analysis Toolbox

abstract:
Data on genome organization and output over time, or the 4D Nucleome (4DN), require synthesis for meaningful interpretation. Development of tools for the efficient integration of these data is needed, especially for the time dimension. We present the "4DNvestigator", a user-friendly network based toolbox for the analysis of time series genome-wide genome structure (Hi-C) and gene expression (RNA-seq) data. Additionally, we provide methods to quantify network entropy, tensor entropy, and statistically significant changes in time series Hi-C data at different genomic scales.

Availabilityhttps://github.com/lindsly/4DNvestigator


title: A silent disco: Persistent entrainment of low-frequency neural oscillations underlies beat-based, but not pattern-based temporal expectations

abstract:
The brain uses temporal structure in the environment, like rhythm in music and speech, to predict the timing of events, thereby optimizing their processing and perception. Temporal expectations can be grounded in different aspects of the input structure, such as a regular beat or a predictable pattern. One influential account posits that a generic mechanism underlies beat-based and pattern-based expectations, namely entrainment of low frequency neural oscillations to rhythmic input, while other accounts assume different underlying neural mechanisms. Here, we addressed this outstanding issue by examining EEG activity and behavioral responses during silent periods following rhythmic auditory sequences. We measured responses outlasting the rhythms both to avoid confounding the EEG analyses with evoked responses, and to directly test whether beat-based and pattern-based expectations persist beyond stimulation, as predicted by entrainment theories. To properly disentangle beat-based and pattern-based expectations, which often occur simultaneously, we used non-isochronous rhythms with a beat, a predictable pattern, or random timing. In Experiment 1 (N = 32), beat-based expectations affected behavioral ratings of probe events for two beat-cycles after the end of the rhythm, while the effects of pattern-based expectations subsided almost instantly. In Experiment 2 (N = 27), using EEG, we found enhanced spectral power at the beat frequency for beat-based sequences both during listening and the silence, but for pattern-based sequences, enhanced power at a pattern-specific frequency was only present during listening, not silence. Moreover, we found a negative deflection in the evoked signal following pattern-based, but not beat-based sequences. Finally, we show how multivariate pattern decoding and multi scale entropy - measures sensitive to non-oscillatory components of the signal - can be used to probe temporal expectations. Together, our results suggest that different mechanisms implement temporal expectations, depending on the input structure. We suggest climbing activity may reflect pattern-based, and persistent low frequency oscillations beat-based expectations specifically.

Highlights- Temporal expectations can be based on both regular beats and predictable patterns
- Behavioral effects persist longer for beat-based than pattern-based expectations
- EEG power tracks the beat, but not the pattern, outlasting rhythmic stimuli
- Pattern-based, but not beat-based expectations elicit a CNV-like ERP component
- Decoding and entropy may index temporal expectations in a time-resolved way


title: The formation of microbial exoskeletons is driven by a controlled calcium-concentrating subcellular niche

abstract:
In nature, bacteria reside in biofilms - multicellular differentiated communities held together by extracellular matrix. In this work, we identified a novel subpopulation essential for biofilm formation - mineral-forming cells. This subpopulation contains an intracellular calcium-accumulating niche, in which the formation of a calcium carbonate mineral is initiated. As the biofilm colony develops, this mineral grows in a controlled manner, forming a functional macrostructure that serves the entire community.

The molecular mechanisms promoting calcite scaffold formation were conserved between three distant phyla - the Gram-positive Bacillus subtilis, Gram-negative Pseudomonas aeruginosa and the actinobacterium Mycobacterium abscessus. Biofilm development of all three species was similarly impaired by inhibition of calcium uptake and carbonate accumulation. Moreover, chemical inhibition and mutations targeting mineralization both significantly reduced the attachment of P. aeruginosa to the lung, as well as the subsequent damage inflicted by biofilms to lung tissues, and restored their sensitivity to antibiotics.

The evolutionary conserved cellular pathway controlling the fundamental feature of biofilm development uncovered in this work offers novel druggable targets for antibiotics to combat otherwise untreatable biofilm infections.


title: Geographical and environmental contributions to genomic divergence in mangrove forests

abstract: Assessing the relative importance of geographical and environmental factors to the spatial distribution of genetic variation can provide information about the processes that maintain genetic variation in natural populations. With a globally wide but very restricted habitat distribution, mangrove trees are a useful model for studies aiming to understand the contributions of these factors. Mangroves occur along the continent-ocean interface of tropical and subtropical latitudes, regions considered inhospitable to many other types of plants. Here, we used landscape genomics approaches to investigate the relative contributions of geographical and environmental variables to the genetic variation of two black mangrove species, Avicennia schaueriana and Avicennia germinans, along the South American coast. Using single nucleotide polymorphisms, our results revealed an important role of ocean currents and geographical distance in the gene flow of A. schaueriana and an isolation-by-environment pattern in the organization of the genetic diversity of A. germinans. Additionally, for A. germinans, we observed significant correlations between genetic variation with evidence of selection and the influence of precipitation regimens, solar radiation and temperature patterns. These discoveries expand our knowledge about the evolution of mangrove trees and provide important information to predict future responses of coastal species to the expected global changes during this century.


title: A semi-empirical model of the aerodynamics of manoeuvring insect flight

abstract: Blade element modelling provides a quick analytical method for estimating the aerodynamic forces produced during insect flight, but such models have yet to be tested rigorously using kinematic data recorded from free-flying insects. This is largely because of the paucity of detailed free-flight kinematic data, but also because analytical limitations in existing blade element models mean that they cannot incorporate the complex three-dimensional movements of the wings and body that occur during insect flight. Here, we present a blade element model with empirically-fitted aerodynamic force coefficients that incorporates the full three-dimensional wing kinematics of manoeuvring Eristalis hoverflies, including torsional deformation of their wings. The two free parameters were fitted to a large free-flight dataset comprising N = 26, 541 wingbeats, and the fitted model captured approximately 80% of the variation in the stroke-averaged forces in the sagittal plane. We tested the robustness of the model by subsampling the data, and found little variation in the parameter estimates across subsamples comprising 10% of the flight sequences. The simplicity and generality of the model that we present is such that it can be readily applied to kinematic datasets from other insects, and also used for the study of insect flight dynamics.


title: Trial-by-trial predictions of subjective time from human brain activity

abstract: Human experience of time exhibits systematic, context-dependent deviations from veridical clock time; for example, time is experienced differently at work than on holiday. Here we test the proposal that differences from clock time in subjective experience of time arise because time estimates are constructed by accumulating the same quantity that guides perception: salient events. Healthy human participants watched naturalistic, silent videos of up to [~]1 minute in duration and estimated their duration while fMRI was acquired. We were able to reconstruct trial-by-trial biases in participants duration reports, which reflect subjective experience of time (rather than veridical clock time), purely from salient events in their visual cortex BOLD activity. This was not the case for control regions in auditory and somatosensory cortex, despite being able to predict clock time from all three brain areas. Our results reveal that the information arising during sensory processing of our dynamic environment provides a sufficient basis for reconstructing human subjective time estimates.


title: Fundamental resource specialization of herbivorous butterflies decreases toward lower latitudes

abstract:
AimIt is generally assumed that the degree of resource specialization in herbivorous insects increases towards lower latitudes. However, latitudinal patterns in herbivore diet breadth at large spatial scales remain poorly understood. In this work, we investigated drivers of latitudinal variation in lepidopteran "fundamental" resource specialization, which we defined as the host breadth when not limited by interspecific interactions at the same trophic level.

LocationThe Japanese archipelago (22{degrees}N-45{degrees}N), including hemiboreal, temperate, and subtropical zones.

TaxonHerbivorous butterflies.

MethodsSpecies-specific fundamental host breadth was calculated based on pooled geographical occurrence and host-use records. We investigated the latitudinal pattern and significant drivers of the degree of specialization in regional species pools at a 10-km grid level. As potential drivers, we focused on geography, current climate, and diversity and body size of butterflies. Through Bayesian structural equation modeling, we investigated the complicated relationships between these variables and community-level resource specialization represented by three different indices of host breadth.

ResultsWe found that fundamental resource specialization of butterfly communities increases toward higher latitudes. This pattern is contrary to the presumed general trend found in studies based on realized resource specialization within local communities. We found that the observed pattern is driven mainly by factors related to climate, butterfly diversity, and body size in each community. Above all, annual mean temperature most strongly drove community-level fundamental host breadth of butterflies.

Main conclusionsOur findings suggest that fundamental resource specialization may show different latitudinal patterns from the conventional prediction based on knowledge of realized resource specialization. Our results emphasize the importance of the current climate as a major factor regulating butterfly morphology and fundamental host breadth, regardless of whether the impact is direct or indirect.


title: Succination of Dihydrolipoyllysine Succinyltransferase by Fumarate Exacerbates Defective Mitochondrial ATP Production during Complex I Deficiency

abstract:
The NDUFS4 knockout (KO) mouse phenotype resembles the human Complex I deficiency Leigh Syndrome. The irreversible succination of protein thiols by fumarate is increased in select regions of the NDUFS4 KO brain affected by neurodegeneration, suggesting a mechanistic role in neurodegenerative decline. We report that dihydrolipoyllysine-residue succinyltransferase (DLST), a component of the -ketoglutarate dehydrogenase complex (KGDHC) of the tricarboxylic acid (TCA) cycle, is succinated in the NDUFS4 KO brain. Succination of DLST reduced KGDHC activity in the brainstem (BS) and olfactory bulb (OB) of KO mice. The defective production of KGDHC derived succinyl-CoA resulted in decreased mitochondrial substrate level phosphorylation, further aggravating the OXPHOS ATP deficit. Protein succinylation, an acylation modification that requires succinyl-CoA, was reduced in the KO mice. Our data demonstrate that the biochemical deficit extends beyond impaired Complex I assembly and OXPHOS deficiency, functionally impairing select components of the TCA cycle to drive metabolic perturbations in affected neurons.

HighlightsO_LICysteine succination by fumarate is increased in model of Complex I deficiency
C_LIO_LISuccination of DLST impairs KGDHC activity, limits SLP, and reduces lysine succinylation
C_LIO_LIIrreversible succination drives neuropathology independent of the bioenergetic defect
C_LI


title: Propranolol promotes bone formation and limits resorption through novel mechanisms during anabolic parathyroid hormone treatment in female C57BL/6J mice

abstract: Although the non-selective {beta}-blocker, propranolol, improves bone density with PTH treatment in mice, the mechanism of this effect is unclear. To address this, we used a combination of in vitro and in vivo approaches to address how propranolol influences bone remodeling in the context of PTH treatment. In female C57BL/6J mice, intermittent PTH and propranolol had complementary effects in the trabecular bone of the distal femur and L5 vertebra, with combination treatment achieving micro-architectural parameters beyond that of PTH alone. Combined treatment improved the serum bone formation marker, P1NP, but did not impact other histomorphometric parameters relating to osteoblast function at the L5. In vitro, propranolol amplified the acute, PTH-induced, intracellular calcium signal in osteoblast-like cells. The most striking finding, however, was suppression of PTH-induced bone resorption. Despite this, PTH-induced receptor activator of nuclear factor kappa-B ligand (RANKL) mRNA and protein levels were unaltered by propranolol, which led us to hypothesize that propranolol could act directly on osteoclasts. Using in situ methods, we found Adrb2 expression in osteoclasts in vivo, suggesting {beta}-blockers may directly impact osteoclasts. Taken together, this work suggests a strong anti-osteoclastic effect of non-selective {beta}-blockers in vivo, indicating that combining propranolol with PTH could be beneficial to patients with extremely low bone density.

category: physiology


title: Changes in partner traits drive variation in plant-nectar robber interactions across habitats

abstract: The frequency and outcome of biotic interactions commonly vary with environmental conditions, even without changes to community composition. Yet the drivers of such environmentally-mediated change in biotic interactions are poorly understood, limiting our ability to predict how environmental change will impact communities. Studying nectar robbery by stingless bees of Odontonema cuspidatum (Acanthaceae) in a coffee agroecosystem, we documented a temporally consistent difference in nectar robbing intensity between anthropogenic and seminatural habitats. Plants growing in coffee fields (anthropogenic habitat) experienced significantly more nectar robbery than plants growing in forest fragments (seminatural habitat). Using a combination of field surveys and manipulative experiments, we found that nectar robbery was higher in coffee fields primarily due to environmental effects on a) neighborhood floral context and b) O. cuspidatum floral traits. This led to both preferential foraging by nectar robbers in coffee fields, and to changes in foraging behavior on O. cuspidatum that increased robbery. Nectar robbery significantly reduced fruit set in O. cuspidatum. These results suggest that the effects of anthropogenic environmental change on species traits may be more important than its effect on species density in determining how interaction frequency and outcome are affected by such environmental change.