title: Phylogenetically conserved peritoneal fibrosis response to an immunologic adjuvant in ray-finned fishes

abstract: Antagonistic interactions between hosts and parasites may drive the evolution of novel host defenses, or new parasite strategies. Host immunity is therefore one of the fastest evolving traits. But where do the novel immune traits come from? Here, we test for phylogenetic conservation in a rapidly evolving immune trait - peritoneal fibrosis. Peritoneal fibrosis is a costly defense against novel specialist tapeworm Schistocephalus solidus (Cestoda) expressed in some freshwater populations of threespine stickleback fish (Gasterosteus aculeatus, Perciformes). We asked whether stickleback fibrosis is a derived species-specific trait or an ancestral immune response that was widely distributed across ray-finned fish (Actinopterygii) only to be employed by threespine stickleback against the specialist parasite. We combined literature review on peritoneal fibrosis with a comparative experiment using either parasite-specific, or non-specific, immune challenge in deliberately selected species across fish tree of life. We show that ray-finned fish are broadly, but not universally, able to induce peritoneal fibrosis when challenged with a generic stimulus (Alum adjuvant). The experimental species were, however, largely indifferent to the tapeworm antigen homogenate. Peritoneal fibrosis, thus, appears to be a common and deeply conserved fish immune response that was co-opted by stickleback to adapt to a new selective challenge.


title: Transcription Factor EB regulates phosphatidylinositol-3-phosphate levels on endomembranes and alters lysosome positioning in the bladder cancer model

abstract:
Lysosomes orchestrate degradation and recycling of exogenous and endogenous material, thus controlling cellular homeostasis. Little is known how this organelle changes during malignant transformation. We investigate the intracellular landscape of lysosomes in a cellular model of bladder cancer. Employing standardized cell culture on micropatterns we identify a phenotype of peripheral lysosome positioning prevailing in bladder cancer but not normal urothelium. We show that lysosome positioning is controlled by transcription factor EB (TFEB) and that lysosomal dispersion results from TFEB activation downstream of lysosomal Ca2+ release. Remarkably, we find that TFEB regulates phosphatidylinositol-3-phosphate (PtdIns3P) levels on endomembranes which recruit FYVE-domain containing proteins, such as the motor adaptor protrudin, for anterograde movement of lysosomes. Altogether, we uncover lysosome positioning as result of PtdIns3P activation downstream of TFEB as a potential biomarker for bladder cancer. Moreover, we reveal a novel role of TFEB in regulating cellular PtdIns levels, conceptually clarifying the dual role of TFEB as regulator of endosomal maturation and autophagy, two distinct processes controlled by PtdIns3P.

Statement of significanceHere we provide the first atlas for the landscape of the lysosomal compartment in bladder cancer and reveal the mechanistic role of TFEB in regulating endosomal PtdIns3P levels and subsequent lysosomal dispersion. We unveiled lysosomal positioning as a potential biomarker for malignant bladder cancer which might arise as an actionable target for cancer therapy.

category: cancer biology


category: cell biology


title: Single-cell analysis of mosquito hemocytes identifies signatures of immune cell sub-types and cell differentiation

abstract: Mosquito immune cells, known as hemocytes, are integral to cellular and humoral responses that limit pathogen survival and mediate immune priming. However, without reliable cell markers and genetic tools, studies of mosquito immune cells have been limited to morphological observations, leaving several aspects of their biology uncharacterized. Here, we use single-cell RNA sequencing (scRNA-seq) to characterize mosquito immune cells, demonstrating an increased complexity to previously defined prohemocyte, oenocytoid, and granulocyte subtypes. Through functional assays relying on phagocytosis, phagocyte depletion, and RNA-FISH experiments, we define markers to accurately distinguish immune cell subtypes and provide evidence for immune cell maturation and differentiation. In addition, gene-silencing experiments demonstrate the importance of lozenge in defining the mosquito oenocytoid cell fate. Together, our scRNA-seq analysis provides an important foundation for studies of mosquito immune cell biology and a valuable resource for comparative invertebrate immunology.

category: immunology


title: Modelling cell guidance and curvature control in evolving biological tissues

abstract: Tissue geometry is an important influence on the evolution of many biological tissues. The local curvature of an evolving tissue induces tissue crowding or spreading, which leads to differential tissue growth rates, and to changes in cellular tension, which can influence cell behaviour. Here, we investigate how directed cell motion interacts with curvature control in evolving biological tissues. Directed cell motion is involved in the generation of angled tissue growth and anisotropic tissue material properties, such as tissue fibre orientation. We develop a new cell-based mathematical model of tissue growth that includes both curvature control and cell guidance mechanisms to investigate their interplay. The model is based on conservation principles applied to the density of tissue synthesising cells at or near the tissues moving boundary. The resulting mathematical model is a partial differential equation for cell density on a moving boundary, which is solved numerically using a hybrid front-tracking method called the cell-based particle method. The inclusion of directed cell motion allows us to model new types of biological growth, where tangential cell motion is important for the evolution of the interface, or for the generation of anisotropic tissue properties. We illustrate such situations by applying the model to simulate both the resorption and infilling components of the bone remodelling process, and to simulate root hair growth. We also provide user-friendly MATLAB code to implement the algorithms.

category: biophysics


title: Improved analyses of GWAS summary statistics by reducing data heterogeneity and errors

abstract: Summary statistics from genome-wide association studies (GWAS) have facilitated the development of various summary data-based methods, which typically require a reference sample for linkage disequilibrium (LD) estimation. Analyses using these methods may be biased by errors in GWAS summary data and heterogeneity between GWAS and LD reference. Here we propose a quality control method, DENTIST, that leverages LD among genetic variants to detect and eliminate errors in GWAS or LD reference and heterogeneity between the two. Through simulations, we demonstrate that DENTIST substantially reduces false-positive rate (FPR) in detecting secondary signals in the summary-data-based conditional and joint (COJO) association analysis, especially for imputed rare variants (FPR reduced from >28% to <2% in the presence of heterogeneity between GWAS and LD reference). We further show that DENTIST can improve other summary-data-based analyses such as fine-mapping analysis, and integrative analysis of GWAS and expression quantitative trait locus data.

category: genetics


title: Kinetic assays of DNA polymerase fidelity: a new theoretical perspective beyond Michaelis-Menten kinetics

abstract: The high fidelity of DNA polymerase (DNAP) is critical for the faithful replication of DNA. There are several quantitative approaches to measure DNAP fidelity. Directly counting the error frequency in the replication products gives the true fidelity but it turns out very hard to implement in practice. Two biochemical kinetic approaches, the steady-state assay and the transient-state assay, were then suggested and widely adopted. In these assays, the error frequency is indirectly estimated by using kinetic theories combined with the measured apparent kinetic rates. However, whether it is equivalent to the true fidelity has never been clarified theoretically, and in particular there are different strategies using these assays to quantify the proofreading efficiency of DNAP but often lead to inconsistent results. In this paper, we make a comprehensive examination on the theoretical foundation of the two kinetic assays, based on the theory of DNAP fidelity recently proposed by us. Our studies show that while the conventional kinetic assays are generally valid to quantify the discrimination efficiency of DNAP, they are valid to quantify the proofreading efficiency of DNAP only when the kinetic parameters satisfy some constraints which will be given explicitly in this paper.These results may inspire more carefully-designed experiments to quantify DNAP fidelity.


title: Evolutionary conserved nitric oxide synthesis proteins responding to bacterial MAMPs are located to the endoplasmic reticulum and are also involved in secondary metabolite synthesis and sterol production

abstract: Nitric oxide (NO) is typically produced by most Eukaryotic organisms however the mechanisms underpinning the biosynthesis of NO is only known in animals. Mammals deploy a common pathway for the synthesis of NO involving multiple nitric oxide synthases (NOSs), which are produced under diverse conditions. NO-production forms part of the innate immunity response to bacterial Microbial Associated Molecular Patterns (MAMPs). Previously, we have shown that the fungal plant pathogen Fusarium graminearum rapidly upregulates innate immune response associated genes in response to MAMPs. Here, we report that F. graminearum produces NO in response to bacterial MAMPs and show that in F. graminearum, NO is produced by an FgNCP and an FgCYP located to the endoplasmic reticulum membrane where both proteins are predicted to be N-terminally attached by a transmembrane or embedded hydrophobic alpha helix. Deletion of any of these proteins lowered pathogenicity to wheat and radically reduced NO-production. Knockout of the FgNCP also completely blocked deoxynivalenol synthesis needed for pathogenicity indicating that the FgNCP also delivers electrons to another CYP (TRI4) located at the ER. The FgCYP we found to be involved in NO-productions is the same or similar to proteins involved in Eukaryote sterol synthesis (CYP51) reducing lanosterol on the way to the final main sterols different for different Eukaryotes. Lanosterol enriched membranes are known to be inhibited in endocytosis and we found that the deletion of the FgCYP producing NO also completely stopped endocytosis. We further tested consequences of these indications of more than one function and suggest the CYP-protein is most likely an FgCYPNO,ERG involved in both NO and ergosterol synthesis and the NCP is involved in NO, trichothecene and ergosterol synthesis, an FgNCPNO,TRI,ERG. The two proteins shown here to be responsible for NO production in F. graminearum are both highly conserved in Eukaryotes from amoeba to human and homologues are likely candidates for the production of NO in many other eukaryotes including mammals. In consequence with this, a mouse orthologue to FgNCPNO,TRI,ERG could successfully replace FgNCPNO,TRI,ERG both for its role in NO production and plant pathogenicity. Combined, these results provide compelling evidence that the multiple functions of these conserved proteins can be part of the explanation for the links between chronic inflammation, sterols and blood pressure in human.


title: Ventricular, atrial and outflow tract heart progenitors arise from spatially and molecularly distinct regions of the primitive streak.

abstract: The heart develops from two sources of mesoderm progenitors, the first and second heart field (FHF and SHF). Using a single cell transcriptomic assay in combination with genetic lineage tracing, we find the FHF and SHF are subdivided into distinct pools of progenitors in gastrulating mouse embryos at earlier stages than previously thought. Each subpopulation has a distinct origin in the primitive streak. The first progenitors to leave the primitive streak contribute to the left ventricle, shortly after right ventricle progenitor emigrate, followed by the outflow tract and atrial progenitors. Moreover, a subset of atrial progenitors are gradually incorporated in posterior locations of the FHF. Although cells allocated to the outflow tract and atrium leave the primitive streak at a similar stage, they arise from different regions. Outflow tract cells originate from distal locations in the primitive streak while atrial progenitors are positioned more proximally. Moreover, single cell RNA sequencing demonstrates that the primitive streak cells contributing to the ventricles have a distinct molecular signature from those forming the outflow tract and atrium. We conclude that cardiac progenitors are pre-patterned within the primitive streak and this prefigures their allocation to distinct anatomical structures of the heart. Together, our data provide a new molecular and spatial map of mammalian cardiac progenitors that will support future studies of heart development, function and disease.

category: developmental biology


title: Worth the effort? A practical examination of random effects in hidden Markov models for animal telemetry data

abstract:
O_LIHidden Markov models (HMMs) that include individual-level random effects have recently been promoted for inferring animal movement behaviour from biotelemetry data. These "mixed HMMs" come at significant cost in terms of implementation and computation, and discrete random effects have been advocated as a practical alternative to more computationally-intensive continuous random effects. However, the performance of mixed HMMs has not yet been sufficiently explored to justify their widespread adoption, and there is currently little guidance for practitioners weighing the costs and benefits of mixed HMMs for a particular research objective.
C_LIO_LII performed an extensive simulation study comparing the performance of a suite of fixed and random effect models for individual heterogeneity in the hidden state process of a 2-state HMM. I focused on sampling scenarios more typical of telemetry studies, which often consist of relatively long time series (30 - 250 observations per animal) for relatively few individuals (5 - 100 animals).
C_LIO_LII generally found mixed HMMs did not improve state assignment relative to standard HMMs. Reliable estimation of random effects required larger sample sizes than are often feasible in telemetry studies. Continuous random effect models performed reasonably well with data generated under discrete random effects, but not vice versa. Random effects accounting for unexplained individual variation can improve estimation of state transition probabilities and measurable covariate effects, but discrete random effects can be a relatively poor (and potentially misleading) approximation for continuous variation.
C_LIO_LIWhen weighing the costs and benefits of mixed HMMs, three important considerations are study objectives, sample size, and model complexity. HMM applications often focus on state assignment with little emphasis on heterogeneity in state transition probabilities, in which case random effects in the hidden state process simply may not be worth the additional effort. However, if explaining variation in state transition probabilities is a primary objective and sufficient explanatory covariates are not available, then random effects are worth pursuing as a more parsimonious alternative to individual fixed effects.
C_LIO_LITo help put my findings in context and illustrate some potential challenges that practitioners may encounter when applying mixed HMMs, I revisit a previous analysis of long-finned pilot whale biotelemetry data.
C_LI

category: ecology


title: Nitrogen deposition is negatively related to species richness and abundance of threatened species in Swiss butterflies

abstract:
Nitrogen (N) deposition caused by agriculture and combustion of fossil fuels is a major threat to plant diversity, but the effects on higher trophic levels are less clear. In this study we investigated how N deposition may affect species richness and abundance (number of individuals per species) in butterflies. We started with reviewing the literature and found that vegetation parameters might be as important as climate and habitat variables in explaining variation in butterfly species richness. It thus seems likely that increased N deposition indirectly affects butterfly communities via its influence on plant communities. We then analysed data from the Swiss biodiversity monitoring program surveying species diversity of vascular plants and butterflies in 383 study sites of 1 km2 that are regularly distributed over Switzerland, covering a modelled N deposition gradient from 2 to 44 kg N ha -1 yr-1. Using traditional linear models and structural equation models, we found that high N deposition was consistently linked to low butterfly diversity, suggesting a net loss of butterfly diversity through increased N deposition. At low elevations, N deposition may contribute to a reduction in butterfly species richness via microclimatic cooling due to increased plant biomass. At higher elevations, negative effects of N deposition on butterfly species richness may also be mediated by reduced plant species richness. In most butterfly species, abundance was negatively related to N deposition, but the strongest negative effects were found for species of conservation concern. We conclude that in addition to factors such as intensified agriculture, habitat fragmentation and climate change, N deposition is likely to play a key role in negatively affecting butterfly diversity and abundance.

Article Impact StatementNitrogen deposition negatively affects butterfly species richness and butterfly abundance, particularly in species of conservation concern.

Data accessibility and reproducibility of resultsData and R-scripts to reproduce the results of this manuscript including figures and tables are provided at https://github.com/TobiasRoth/NDep_butterflies. Raw data for analyses are provided in the folder "data", and the folder "R" contains the R-Script that was used to export the data from the BDM database and to produce the figures and tables of the manuscript.


title: Geography is more important than life history in the recent diversification of the tiger salamander complex

abstract:
AO_SCPLOWBSTRACTC_SCPLOWThe North American tiger salamander species complex, including its best-known species, the Mexican axolotl, has long been a source of biological fascination. The complex exhibits a wide range of variation in developmental life history strategies, including populations and individuals that undergo metamorphosis, those able to forego metamorphosis and retain a larval, aquatic lifestyle (i.e., paedomorphosis), and those that do both. This life history variation has been assumed to lead to reproductive isolation and speciation, but the degree to which it has shaped population- and species-level divergence is poorly understood. Using a large multi-locus dataset from hundreds of samples across North America, we identified genetic clusters across the geographic range of the tiger salamander complex. These clusters often contain a mixture of paedomorphic and metamorphic taxa, indicating that geographic isolation has played a larger role in lineage divergence than paedomorphosis in this system. This conclusion is bolstered by geography-informed analyses indicating no effect of life history strategy on population genetic differentiation and by model-based analyses demonstrating gene flow between adjacent metamorphic and paedomorphic populations. This fine-scale genetic perspective on life-history variation establishes a framework for understanding how plasticity, local adaptation, and gene flow contribute to lineage divergence. Many members of the tiger salamander complex are endangered, and the Mexican axolotl is an important model system in regenerative and biomedical research. Our results chart a course for more informed use of these taxa in experimental, ecological, and conservation research.

SO_SCPLOWIGNIFICANCEC_SCPLOW SO_SCPLOWTATEMENTC_SCPLOWPopulation structure and speciation are shaped by a combination of biotic and abiotic factors. The tiger salamander complex has been considered to be a key group where life history variation has led to a rapid rate of speciation, driven in large part by the evolution of obligate paedomorphosis-a condition where adults maintain an aquatic, larval phenotype. Using a large multi-locus dataset, we present evidence of gene flow between taxa with different life history strategies, suggesting that obligate paedomorphosis is not a strong driver of speciation in the tiger salamander complex. Many of these nominal taxa are listed as critically endangered, and our genetic results provide information and guidance that will be useful for their conservation.

category: evolutionary biology


title: Whole-proteome Tree of Insects: Grouping and phylogeny without sequence alignment

abstract:
An "organism tree" of insects, the largest and most species-diverse group of all living animals, can be considered as a conceptual tree to capture a simplified narrative of the complex evolutionary courses of the extant insects. Currently, the most common approach has been to construct a "protein tree", as a surrogate for the organism tree, by Multiple Sequence Alignment (MSA) of highly homologous regions of a set of select proteins to represent each organism. However, such selected regions account for a very small fraction of the whole-proteome of each organism.

Information Theory provides a method of comparing two sets of all proteins, two whole-proteomes, without MSA: By treating each whole-proteome sequence as a "book" of amino acid alphabets, the information contents of two whole-proteomes can be quantitatively compared using the text comparison method of the theory, without sequence alignment, providing an opportunity to construct a "whole-proteome tree" of insects as a surrogate for an organism tree of insects.

A whole-proteome tree of the insects in this study shows that: (a) all the founders of the major groups of the insects have emerged in an explosive "burst" near the root of the tree, (b) the most basal group of all the insects is a subgroup of Hemiptera consisting of aphids and psyllids, and (c) there are other notable differences in the phylogeny of the groups compared to those of the recent protein trees of insects.


title: ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing

abstract:
Computational biology and bioinformatics provide vast data gold-mines from protein sequences, ideal for Language Models taken from NLP. These LMs reach for new prediction frontiers at low inference costs. Here, we trained two auto-regressive models (Transformer-XL, XLNet) and four auto-encoder models (BERT, Albert, Electra, T5) on data from UniRef and BFD containing up to 393 billion amino acids. The LMs were trained on the Summit supercomputer using 5616 GPUs and TPU Pod up-to 1024 cores.

Dimensionality reduction revealed that the raw protein LM-embeddings from unlabeled data captured some biophysical features of protein sequences. We validated the advantage of using the embeddings as exclusive input for several subsequent tasks. The first was a per-residue prediction of protein secondary structure (3-state accuracy Q3=81%-87%); the second were per-protein predictions of protein sub-cellular localization (ten-state accuracy: Q10=81%) and membrane vs. water-soluble (2-state accuracy Q2=91%). For the per-residue predictions the transfer of the most informative embeddings (ProtT5) for the first time outperformed the state-of-the-art without using evolutionary information thereby bypassing expensive database searches. Taken together, the results implied that protein LMs learned some of the grammar of the language of life. To facilitate future work, we released our models at https://github.com/agemagician/ProtTrans.

category: bioinformatics


title: A modelling framework for the prediction of the herd-level probability of infection from longitudinal data

abstract: The collective control programmes (CPs) that exist for many infectious diseases of farm animals rely on the application of diagnostic testing at regular time intervals for the identification of infected animals or herds. The diversity of these CPs complicates the trade of animals between regions or countries because the definition of freedom from infection differs from one CP to another. In this paper, we describe a statistical model for the prediction of herd-level probabilities of infection from longitudinal data collected as part of CPs against infectious diseases of cattle. The model was applied to data collected as part of a CP against bovine viral diarrhoea virus (BVDV) infection in Loire-Atlantique, France. The model represents infection as a herd latent status with a monthly dynamics. This latent status determines test results through test sensitivity and test specificity. The probability of becoming status positive between consecutive months is modelled as a function of risk factors (when available) using logistic regression. Modelling is performed in a Bayesian framework, using either Stan or JAGS. Prior distributions need to be provided for the sensitivities and specificities of the different tests used, for the probability of remaining status positive between months as well as for the probability of becoming positive between months. When risk factors are available, prior distributions need to be provided for the coefficients of the logistic regression, replacing the prior for the probability of becoming positive. From these prior distributions and from the longitudinal data, the model returns posterior probability distributions for being status positive for all herds on the current month. Data from the previous months are used for parameter estimation. The impact of using different prior distributions and model implementations on parameter estimation was evaluated. The main advantage of this model is its ability to predict a probability of being status positive in a month from inputs that can vary in terms of nature of test, frequency of testing and risk factor availability/presence. The main challenge in applying the model to the BVDV CP data was in identifying prior distributions, especially for test characteristics, that corresponded to the latent status of interest, i.e. herds with at least one persistently infected (PI) animal. The model is available on Github as an R package (https://github.com/AurMad/STOCfree) and can be used to carry out output-based evaluation of disease CPs.


title: Bayesian Decoder Models with a Discriminative Observation Process

abstract: The Bayesian state-space neural encoder-decoder modeling framework is an established solution to reveal how changes in brain dynamics encode physiological covariates like movement or cognition. Although the framework is increasingly being applied to progress the field of neuroscience, its application to modeling high-dimensional neural data continues to be a challenge. Here, we propose a novel solution that avoids the complexity of encoder models that characterize high-dimensional data as a function of the underlying state processes. We build a discriminative model to estimate state processes as a function of current and previous observations of neural activity. We then develop the filter and parameter estimation solutions for this new class of state-space modeling framework called the "direct decoder" model. We applied the model to decode movement trajectories of a rat in a W-shaped maze from the ensemble spiking activity of place cells and achieve comparable performance to modern decoding solutions, without needing an encoding step in the model development. We further demonstrate how a dynamical auto-encoder can be built using the direct decoder model; where the underlying state process links the high-dimensional neural activity to the behavioral readout. We applied the dynamical auto-encoder model in estimating the intention to verbally communicate of an epileptic participant and their companions. The result shows that the dynamical auto-encoder can optimally estimate the low-dimensional dynamical manifold which represents the relationship between the brain and behavior.


title: Suppression of chromosome instability limits acquired drug resistance

abstract:
Numerical chromosome instability, or nCIN, defined as the high frequency of whole chromosome gains and losses, is prevalent in many solid tumors. nCIN has been shown to promote intra-tumor heterogeneity and corresponds with tumor aggressiveness, drug resistance and tumor relapse. While increased nCIN has been shown to promote the acquisition of genomic changes responsible for drug resistance, the potential to modulate nCIN in a therapeutic manner has not been well explored. Here we assess the role of nCIN in the acquisition of drug resistance in non small cell lung cancer. We show that generation of whole chromosome segregation errors in non small cell lung cancer cells is sensitive to manipulation of microtubule dynamics and that enhancement of chromosome cohesion strongly suppresses nCIN and reduces intra-tumor heterogeneity. We demonstrate that suppression of nCIN has no impact on non small cell lung cancer cell proliferation in vitro nor in tumor initiation in mouse xenograft models. However, suppression of nCIN alters the timing and molecular mechanisms that drive acquired drug resistance. These findings suggest mechanisms to suppress nCIN may serve as effective co-therapies to limit tumor evolution and sustain drug response.

Statement of SignificanceModulation of microtubule dynamics in cells that exhibit chromosome instability (CIN) is sufficient to promote mitotic fidelity, reduce genomic heterogeneity, and limit acquisition of drug resistance.


title: Wide spectrum of neuronal and network phenotypes in human stem cell-derived excitatory neurons with Rett syndrome-associated MECP2 mutations

abstract: Rett syndrome (RTT) is a severe neurodevelopmental disorder primarily caused by heterozygous loss-of-function mutations in the X-linked gene MECP2 that is a global transcriptional regulator. Mutations in the methyl-CpG binding domain (MBD) of MECP2 disrupt its interaction with methylated DNA. Here, we investigate the effect of MECP2 L124W missense mutation in the MBD of an atypical RTT patient in comparison to severe MECP2 null mutations. L124W protein had a limited ability to disrupt heterochromatic chromocenters due to decreased binding dynamics. We isolated two pairs of isogenic WT and L124W induced pluripotent stem cells. L124W induced excitatory neurons expressed stable protein, exhibited increased input resistance and decreased voltage-gated Na+ and K+ currents, and their neuronal dysmorphology was limited to decreased dendritic complexity. Three isogenic pairs of MECP2 null neurons had the expected more extreme morphological and electrophysiological phenotypes. We examined development and maturation of L124W and MECP2 null excitatory neural network activity using micro-electrode arrays. Relative to isogenic controls, L124W neurons had an increase in synchronous network burst frequency, in contrast to MECP2 null neurons that suffered a significant decrease in synchronous network burst frequency and a transient extension of network burst duration. We capture these findings in a computational neural network model that shows the observed changes in network dynamics are best explained by changes in intrinsic adaptation currents in individual neurons. Our multilevel results demonstrate that RTT excitatory neurons show a wide spectrum of morphological, electrophysiological and circuitry phenotypes that are dependent on the severity of the MECP2 mutation.

category: neuroscience


title: Independence of Cued and Contextual Components of Fear Conditioning is Gated by the Lateral Habenula

abstract: Fear is an extreme form of aversion that, if inappropriately generalized, initiates pathological conditions such as panic or anxiety. Fear conditioning (FC) is the best understood model of fear learning. During FC two independent associations link the cue and the training context to fear expression. The lateral habenula (LHb) is a general encoder of aversion. However, its role in fear learning has not been intensively studied. Here we studied the role of the LHb in FC using optogenetics and pharmacological tools in rats. Disrupting the neuronal activity of the LHb during training abolishes the expression of fear to isolated presentation of the training context or the cue, yet the recall of both associations when the cue is played in the training context reveals a conserved memory. Our results demonstrate that the LHb is required for the formation of independently expressible contextual and cued memories, a previously uncharacterized role in FC.


title: The Contribution of Environmental Enrichment to Phenotypic Variation in Mice and Rats

abstract:
The reproducibility and translation of neuroscience research is assumed to be undermined by introducing environmental complexity and heterogeneity. Rearing laboratory animals with minimal (if any) environmental stimulation is thought to control for biological variability but may not adequately test the robustness of our animal models. Standard laboratory housing is associated with reduced demonstrations of species typical behaviors and changes in neurophysiology that may impact the translation of research results. Modest increases in environmental enrichment (EE), mitigate against insults used to induce animal models of disease, directly calling into question the translatability of our work. This may in part underlie the disconnect between preclinical and clinical research findings. Enhancing environmental stimulation for our model organisms promotes ethological natural behaviors but may simultaneously increase phenotypic trait variability. To test this assumption, we conducted a systematic review and evaluated coefficients of variation between EE and standard housed mice and rats. Given findings of suboptimal reporting of animal laboratory housing conditions, we also developed a methodological reporting table for enrichment use in neuroscience research. Our data show that animals housed in environmental enrichment were not more variable than those in standard housing. Therefore, environmental heterogeneity introduced into the laboratory, in the form of enrichment, does not compromise data integrity. Overall, human life is complicated and by embracing such nuanced complexity into our laboratories we may paradoxically improve upon the rigor and reproducibility of our research.

Significance StatementEnvironmental complexity is thought to increase phenotypic variability, undermining research translation. We conducted a systematic review and compared coefficients of variation between environmentally enriched and standard housed laboratory animals. Despite there being no differences in variability across several phenotypic traits, there are stark contrasts in the display of ethological natural behaviors between these housing conditions. Environmental enrichment is recognized as being beneficial for animal welfare and mitigates against insults used to induce animal models of disease. In contrast, standard laboratory cages are recognized as being impoverished and  unnatural. From these observations, it is apparent that our current "gold standard" caging system is not a true control condition as it does not adequately test the robustness of our animal models.


title: Effects of plant community history, soil legacy and plant diversity on soil microbial communities

abstract: Plant and soil microbial diversity are linked through a range of interactions, including the exchange of carbon and nutrients but also herbivory and pathogenic effects. Over time, associations between plant communities and their soil microbiota may strengthen and become more specific, resulting in stronger associations between plant and soil microbial diversity. We tested this hypothesis in a 4-year long field experiment in which we factorially combined plant community history and soil legacy with plant diversity (1, 2, 4, 8, 60 species). Plant community history and soil legacy refer to the presence ("old") or absence ("new") of a common history of plants and soils in 52 different plant species compositions during 8 years in a long-term biodiversity experiment in Jena, Germany. After 4 years of growth, we took soil samples in the new field experiment and determined soil bacterial and fungal composition in terms of operational taxonomic units (OTUs) using 16S rRNA gene and ITS DNA sequencing. Plant community history did not affect overall soil community composition but differentially affected bacterial richness and abundances of specific bacteria taxa in association with particular plant species compositions. Soil legacy markedly increased soil bacterial richness and evenness and decreased fungal evenness. Soil fungal richness increased with plant species richness, regardless of plant community history or soil legacy, with the strongest difference between plant monocultures and mixtures. Particular plant species compositions and functional groups were associated with particular bacterial and fungal community compositions. Grasses increased and legumes decreased fungal richness and evenness. Our findings indicate that as experimental ecosystems varying in plant diversity develop over 8 years, plant species associate with specific soil microbial taxa. This can have long-lasting effects on belowground community composition in re-assembled plant communities, as reflected in strong soil legacy signals still visible after 4 years of growing new plant communities. Effects of plant community history on soil communities are subtle and may take longer to fully develop.


title: The role of syndapin-2 mediated transcytosis across the blood-brain barrier   on amyloid-beta accumulation in the brain

abstract: A deficient transport of amyloid-(A{beta}) across the blood-brain barrier (BBB), and its diminished clearance from the brain, contributes to neurodegenerative and vascular pathologies, including Alzheimers (AD) and cerebral angiopathy, respectively. At the BBB, A{beta} efflux transport is associated with the low-density receptor-related protein 1 (LRP1). However, the precise mechanisms governing A{beta} transport across the BBB, in health and disease, remain to be fully understood. Recent evidence indicates that the LRP1 transcytosis occurs through a tubulation-mediated mechanism stabilised by syndapin-2. Here, we show that syndapin-2 is associated with A{beta} clearance via LRP1 across the BBB. We further demonstrate that risk factors for AD, A{beta} expression and ageing, are associated with a decline in the native expression of syndapin-2 within brain endothelium. Our data reveal that the syndapin-2-mediated pathway, and its balance with the endosomal sorting, are important for A{beta} clearance proposing a measure to evaluate AD and ageing, as well as a target for counteracting A{beta} build-up. Moreover, we provide evidence for the impact of the avidity of A{beta} assemblies in their trafficking across the brain endothelium and in LRP1 expression levels, which may affect the overall clearance of A{beta} across the BBB.


title: A Meta-analysis of the known Global Distribution and Host Range of the Ralstonia Species Complex

abstract: The Ralstonia species complex is a genetically diverse group of plant wilt pathogens. Ralstonia strains are classified by a "phylotype-sequevar" phylogenetic system. Since the development of the phylotype-sequevar system, over one hundred papers have described the genetic diversity of Ralstonia strains isolated from agriculturally important crops, ornamental plants, and plants in natural ecosystems. Our goal is to create a database that contains the reported global distribution and host range of Ralstonia sequevars. In this third release, we have catalogued information from 93 manuscripts that report one or more Ralstonia strain isolated from 86 geographic regions. The database is hosted as a GitHub repository (https://github.com/lowepowerlab/Ralstonia_Global_Diversity) that will be updated regularly.

category: microbiology


title: SPACE exploration of RNA-binding proteins as major chromatin components

abstract: RNA-binding proteins (RBPs) play diverse roles in regulating co-transcriptional RNA-processing and chromatin functions, but our knowledge of the repertoire of chromatin-associated RBPs (caRBPs) and their interactions with chromatin remains limited. Here, we developed SPACE (Silica Particle Assisted Chromatin Enrichment) to isolate global and regional chromatin components with high specificity and sensitivity, and SPACEmap to identify the chromatin-contact regions in proteins. Applied to mouse embryonic stem cells, SPACE identified 1,459 chromatin-associated proteins, [~]48% of which are annotated as RBPs, indicating their dual roles in chromatin and RNA-binding. Additionally, SPACEmap stringently verified chromatin-binding of 404 RBPs and identified their chromatin-contact regions. Notably, SPACEmap showed that about half of the caRBPs bind to chromatin by intrinsically disordered regions (IDRs). Studying SPACE and total proteome dynamics from mES cells grown in 2iL and serum medium indicates significant correlation (R = 0.62). One of the most dynamic caRBPs is Dazl, which we find co-localized with PRC2 at transcription start sites of genes that are distinct from Dazl mRNA binding. Dazl and other PRC2-colocalised caRBPs are rich in intrinsically disordered regions (IDRs), which could contribute to the formation and regulation of phase-separated PRC condensates. Together, our approach provides an unprecedented insight into IDR-mediated interactions and caRBPs with moonlighting functions in native chromatin.

category: molecular biology


title: Chromatin-contact atlas reveals disorder-mediated protein interactions


title: Chromatin-contact atlas reveals disorder-mediated protein interactions and moonlighting chromatin-associated RBPs


title: How robust are cross-population signatures of polygenic adaptation in humans?

abstract: Over the past decade, summary statistics from genome-wide association studies (GWASs) have been used to detect and quantify polygenic adaptation in humans. Several studies have reported signatures of natural selection at sets of SNPs associated with complex traits, like height and body mass index. However, more recent studies suggest that some of these signals may be caused by biases from uncorrected population stratification in the GWAS data with which these tests are performed. Moreover, past studies have predominantly relied on SNP effect size estimates obtained from GWAS panels of European ancestries, which are known to be poor predictors of phenotypes in non-European populations. Here, we collated GWAS data from multiple anthropometric and metabolic traits that have been measured in more than one cohort around the world, including the UK Biobank, FINRISK, Chinese NIPT, Biobank Japan, APCDR and PAGE. We then evaluated how robust signals of polygenic score overdispersion (which have been interpreted as suggesting polygenic adaptation) are to the choice of GWAS cohort used to identify associated variants and their effect size estimates. We did so while using the same panel to obtain population allele frequencies (The 1000 Genomes Project). We observe many discrepancies across tests performed on the same phenotype and find that association studies performed using multiple different cohorts, like meta-analyses and mega-analyses, tend to produce polygenic scores with strong overdispersion across populations. This results in apparent signatures of polygenic adaptation which are not observed when using effect size estimates from biobank-based GWASs of homogeneous ancestries. Indeed, we were able to artificially create score overdispersion when taking the UK Biobank cohort and simulating a meta-analysis on multiple subsets of the cohort. Finally, we show that the amount of overdispersion in scores for educational attainment - a trait with strong social implications and high potential for misinterpretation - is also strongly dependent on the specific GWAS used to build them. This suggests that extreme caution should be taken in the execution and interpretation of future tests of polygenic score overdispersion based on population differentiation, especially when using summary statistics from a GWAS that combines multiple cohorts.


title: Transcriptional analysis of Colletotrichum fructicola	 from Different Geographic regions inoculated to Camellia oleifera

abstract: Anthracnose, caused by Colletotrichum. Spp., is an important disease affecting oil tea (Camellia oleifera). Extensive molecular studies have demonstrated that Colletotrichum fructicola is the dominant pathogen of oil tea anthracnose in China. The study aims to investigate differences in molecular processes and regulatory genes at different stages of infection of C. fructicola, to aide in understanding differences in pathogenic mechanisms of C. fructicola of different geographic populations. Materials and Methods: We compared the pathogenicity of C. fructicola from different populations (Wuzhishan, Hainan province and Shaoyang, Hunan province), and gene expression of representative strains of the two populations before and after inoculation in oil tea using RNA sequencing. In results we found that C. fructicola from Wuzhishan has a stronger ability to infect and impact oil tea leaf tissue. Up-regulated genes in oil tea following infection with the two geographic populations were associated with a number of ribosome-related GO terms and ribosome metabolic related KEGG pathways, and were significantly enriched in galactosidase activity, glutamine family amino acid metabolism, arginine and proline metabolism. In addition, up-regulated gene lists associated with infection in the Wuzhishan strains were significantly enriched purine metabolism pathways as well, while Shaoyang strains were not significantly enriched in these processes. Differences in gene expression were indicative of greater active transcription and translation in the Wuzhishan population while more active glycoprotein metabolism was observed following inoculation with strains from Shaoyang. These results indicate that C. fructicola obtained sugars and amino acids from oil tea tissue to resist host immune pressure. Moreover, more active in transcriptional and translational activity and the greater regulation of purine metabolism pathway in the Wuzhishan strain might contribute to its stronger pathogenicity.


title: Causal inference in environmental sound recognition

abstract: Sound is caused by physical events in the world. Do humans infer these causes when recognizing sound sources? We tested whether the recognition of common environmental sounds depends on the inference of a basic physical variable - the source intensity (i.e., the power that produces a sound). A sources intensity can be inferred from the intensity it produces at the ear and its distance, which is normally conveyed by reverberation. Listeners could thus use intensity at the ear and reverberation to constrain recognition by inferring the underlying source intensity. Alternatively, listeners might separate these acoustic cues from their representation of a sounds identity in the interest of invariant recognition. We compared these two hypotheses by measuring recognition accuracy for sounds with typically low or high source intensity (e.g., pepper grinders vs. trucks) that were presented across a range of intensities at the ear or with reverberation cues to distance. The recognition of low-intensity sources (e.g., pepper grinders) was impaired by high presentation intensities or reverberation that conveyed distance, either of which imply high source intensity. Neither effect occurred for high-intensity sources. The results suggest that listeners implicitly use the intensity at the ear along with distance cues to infer a sources power and constrain its identity. The recognition of real-world sounds thus appears to depend upon the inference of their physical generative parameters, even generative parameters whose cues might otherwise be separated from the representation of a sounds identity.

category: animal behavior and cognition


title: Prophage-encoded phage defence proteins with cognate self-immunity

abstract: Temperate phages are pervasive in bacterial genomes, existing as vertically-inherited islands called prophages. Prophages are vulnerable to the predation of their host bacterium by exogenous phages. Here we identify BstA, a novel family of prophage-encoded phage defense proteins found in diverse Gram-negative bacteria. BstA drives potent suppression of phage epidemics through abortive infection. During lytic replication, the bstA-encoding prophage is not itself inhibited by BstA due to a self-immunity mechanism conferred by the anti-BstA (aba) element, a short stretch of DNA within the bstA locus. Inhibition of phage replication by distinct BstA proteins from Salmonella, Klebsiella and Escherichia prophages is functionally interchangeable, but each possesses a cognate aba element. The specificity of the aba element ensures that immunity is exclusive to the replicating prophage, and cannot be exploited by heterologous BstA-encoding phages. BstA allows prophages to defend host cells against exogenous phage attack, without sacrificing their own lytic autonomy.


title: Multitask Learning over Shared Subspaces

abstract:
This paper uses constructs from machine learning to define pairs of learning tasks that either shared or did not share a common subspace. Human subjects then learnt these tasks using a feedback-based approach. We found, as hypothesised, that subject performance was significantly higher on the second task if it shared the same subspace as the first. Additionally, accuracy was positively correlated over subjects learning same-subspace tasks, and negatively correlated for those learning different-subspace tasks. These results were compared to the behaviour of a Neural Network model trained using sequential Bayesian learning. Human performance was found to be consistent with a minimal capacity variant of this model. Networks with an increased representational capacity, and networks without Bayesian learning, did not show these transfer effects. We propose that the concept of shared subspaces provides a useful framework for the experimental study of human multitask and transfer learning.

Author summaryHow does knowledge gained from previous experience affect learning of new tasks ? This question of "Transfer Learning" has been addressed by teachers, psychologists, and more recently by researchers in the fields of neural networks and machine learning. Leveraging constructs from machine learning, we designed pairs of learning tasks that either shared or did not share a common subspace. We compared the dynamics of transfer learning in humans with those of a multitask neural network model, finding that human performance was consistent with a minimal capacity variant of the model. Learning was boosted in the second task if the same subspace was shared between tasks. Additionally, accuracy between tasks was positively correlated but only when they shared the same subspace. Our results highlight the roles of subspaces, showing how they could act as a learning boost if shared, and be detrimental if not.


title: Cell type-aware analysis of RNA-seq data

abstract: Most tissue samples are composed of different cell types. Differential expression analysis without accounting for cell type composition cannot separate the changes due to cell type composition or cell type-specific expression. We propose a computational framework to address these limitations: Cell Type Aware analysis of RNA-seq (CARseq). CARseq employs a negative binomial distribution that appropriately models the count data from RNA-seq experiments. Simulation studies show that CARseq has substantially higher power than a linear model-based approach and it also provides more accurate estimate of the rankings of differentially expressed genes. We have applied CARseq to compare gene expression of schizophrenia/autism subjects versus controls, and identified the cell types underlying the difference and similarities of these two neuron-developmental diseases. Our results are consistent with the results from differential expression analysis using single cell RNA-seq data.


title: MAVE-NN: learning genotype-phenotype maps from multiplex assays of variant effect

abstract: Multiplex assays of variant effect (MAVEs) are a family of methods that includes deep mutational scanning (DMS) experiments on proteins and massively parallel reporter assays (MPRAs) on gene regulatory sequences. However, a general strategy for inferring quantitative models of genotype-phenotype (G-P) maps from MAVE data is lacking. Here we introduce MAVE-NN, a neural-network-based Python package that implements a broadly applicable information-theoretic framework for learning G-P maps--including biophysically interpretable models--from MAVE datasets. We demonstrate MAVE-NN in multiple biological contexts, and highlight the ability of our approach to deconvolve mutational effects from otherwise confounding experimental nonlinearities and noise.


title: Predictive pre-activation of orthographic and lexical-semantic representations facilitates visual word recognition

abstract: To a crucial extent, the efficiency of reading results from the fact that visual word recognition is faster in predictive contexts. Predictive coding models suggest that this facilitation results from pre-activation of predictable stimulus features across multiple representational levels before stimulus onset. Still, it is not sufficiently understood which aspects of the rich set of linguistic representations that are activated during reading - visual, orthographic, phonological, and/or lexical-semantic - contribute to context-dependent facilitation. To investigate in detail which linguistic representations are pre-activated in a predictive context and how they affect subsequent stimulus processing, we combined a well-controlled repetition priming paradigm, including words and pseudowords (i.e., pronounceable nonwords), with behavioral and magnetoencephalography measurements. For statistical analysis, we used linear mixed modeling, which we found had a higher statistical power compared to conventional multivariate pattern decoding analysis. Behavioral data from 49 participants indicate that word predictability (i.e., context present vs. absent) facilitated orthographic and lexical-semantic, but not visual or phonological processes. Magnetoencephalography data from 38 participants show sustained activation of orthographic and lexical-semantic representations in the interval before processing the predicted stimulus, suggesting selective pre-activation at multiple levels of linguistic representation as proposed by predictive coding. However, we found more robust lexical-semantic representations when processing predictable in contrast to unpredictable letter strings, and pre-activation effects mainly resembled brain responses elicited when processing the expected letter string. This finding suggests that pre-activation did not result in  explaining away predictable stimulus features, but rather in a  sharpening of brain responses involved in word processing.


title: Neural Network Poisson Models for Behavioural and Neural Spike Train Data

abstract: AO_SCPLOWBSTRACTC_SCPLOWOne of the most important and challenging application areas for complex machine learning methods is to predict, characterize and model rich, multi-dimensional, neural data. Recent advances in neural recording techniques have made it possible to monitor the activities of a large number of neurons across different brain regions as animals perform behavioural tasks. This poses the critical challenge of establishing links between neural activity at a microscopic scale, which might for instance represent sensory input, and at a macroscopic scale, which then generates behaviour. Predominant modeling methods apply rather disjoint techniques to these scales; by contrast, we suggest an end-to-end model which exploits recent developments of flexible, but tractable, neural network point-process models to characterize dependencies between stimuli, actions, and neural data. We apply this model to a public dataset collected using Neuropixel probes in mice performing a visually-guided behavioural task as well as a synthetic dataset produced from a hierarchical network model with reciprocally connected sensory and integration circuits intended to characterize animal behaviour in a fixed-duration motion discrimination task. We show that our model outperforms previous approaches and contributes novel insights into the relationships between neural activities and behaviour.


title: Linear vector models of time perception account for saccade and stimulus novelty interactions

abstract: Various models (e.g., scalar, state-dependent network, and vector models) have been proposed to explain the global aspects of time perception, but they have not been tested against specific visual phenomena like perisaccadic time compression and novel stimulus time dilation. Here, in two separate experiments (N=31), we tested how the perceived duration of a novel stimulus is influenced by 1) a simultaneous saccade, in combination with 2) a prior series of repeated stimuli in human participants. This yielded a novel behavioral interaction: pre-saccadic stimulus repetition neutralizes perisaccadic time compression. We then tested these results against simulations of the above models. Our data yielded low correlations against scalar model simulations, high but non-specific correlations for our feedforward neural network, and correlations that were both high and specific for a vector model based on identity of objective and subjective time. These results demonstrate the power of global time perception models in explaining disparate empirical phenomena and suggest that subjective time has a similar essence to times physical vector.


title: PD-1-induced T cell exhaustion is controlled by a Drp1-dependent mechanism

abstract: PD-1 signalling downregulates the T cell response, promoting an exhausted state in tumor-infiltrating T cells, through mostly unveiled molecular mechanisms. Drp1-dependent mitochondrial fission plays a crucial role to sustain T cell motility, proliferation, survival and glycolytic engagement and, interestingly, such processes are exactly those inhibited by PD-1 in tumor-infiltrating T cells. Here we show that the signature of PD-1pos CD8+ T cells infiltrating MC38-derived murine tumor mass is having downregulated Drp1 activity and more fused mitochondria, compared to PD-1neg counterparts. Also, PD-1pos lymphocytic elements infiltrating human colon cancer rarely express active Drp1. Mechanistically, PD-1 signalling directly prevents mitochondria fragmentation following T cell stimulation by downregulating Drp1 phosphorylation on Ser616, via regulation of the ERK1/2 and mTOR pathways. In addition, downregulation of Drp1 activity in tumor-infiltrating PD-1pos CD8+ T cells seems to be a mechanism exploited by PD-1 signalling to reduce motility and proliferation of these cells. Overall, our data indicate that the modulation of Drp1 activity in tumor-infiltrating T cells may become a valuable target to ameliorate the anti-cancer immune response in future immunotherapy approaches.


title: The representation of bodies in high level visual, prefrontal and inferior parietal cortex varies with explicit vs. implicit expression perception

abstract: Recent studies provide an increasingly understanding of how visual objects categories like faces or bodies are represented in the brain but also raised the question whether a category based or more network inspired models are more powerful. Two important and so far sidestepped issues in this debate concern, first, how major category attributes like the emotional expression directly influence category representation and second, whether category and attribute representation are sensitive to task demands. This study investigated the impact of a crucial category attribute like emotional expression on category activity and whether this varies with the participants task. Using (fMRI) we measured BOLD responses while participants viewed whole body expressions and performed either an explicit (emotion) or an implicit (shape) recognition task. Our results based on multivariate methods show that the type of task is the strongest determinant of brain activity and can be decoded in EBA, VLPFC and IPL. Brain activity was higher for the explicit task condition in VLPFC and was not emotion specific. This pattern suggests that during explicit recognition of the body expression, body category representation may be strengthened, and emotion and action related activity suppressed. Taken together these results stress the importance of the task and of the role of category attributes for understanding the functional organization of high level visual cortex.


title: Accurate recognition of colorectal cancer with semi-supervised deep learning on pathological images

abstract:
BackgroundMachine-assisted recognition of colorectal cancer (CRC) has been mainly focused on supervised deep learning that suffers from a significant bottleneck of requiring massive labeled data. We hypothesize that semi-supervised deep learning leveraging a small amount of labeled data with abundant available unlabeled data can provide a powerful alternative strategy.

MethodWe proposed a semi-supervised model based on the mean teacher architecture that provides pathological predictions at both patch- and patient-levels. We demonstrated the general utility of the model utilizing 13,111 CRC whole slide images from 8,803 subjects gathered from 13 independent centers. We compared our proposed method with the prevailing supervised learning and six pathologists. Two extended evaluations on 15,000 lung and 294,912 lymph node images were also performed to confirm the generality of utility of semi-supervised learning for different cancers.

ResultsWith a small amount of labeled training patches ([~]3,150 labeled, [~]40,950 unlabeled or [~]6,300 labeled, [~]37,800 unlabeled), the semi-supervised learning (SSL) performed significantly better than the supervised learning (SL, which only used the labeled data) (area under the curve, AUC: 0.90 {+/-} 0.06 vs. 0.84 {+/-} 0.07, P value = 0.02 or AUC: 0.98 {+/-} 0.01 vs. 0.92 {+/-} 0.04, P value = 0.0004). Moreover, we found no significant difference between SL using massive [~]44,100 labeled patches and SSL ([~]6,300 labeled, [~]37,800 unlabeled) at patch-level diagnoses (AUC:0.98 {+/-} 0.01 vs. 0.987 {+/-} 0.01, P value = 0.134) and patient-level diagnoses (average AUC: 0.974 vs. 0.980, P value = 0.117). SSL was close to human pathologists in diagnosis performance (average AUC: 0.972 vs. 0.969). This extended evaluation on lung and lymph node also confirmed when a small amount of labeled data were used, SSL was better than SL, and achieved similar performance as that of SL with massive labeling.

ConclusionsWe reported that SSL can achieve excellent performance through a multi-center study. Because SSL dramatically reduces the need and cost of pathological image annotation, it has great potential to effectively build pathological artificial intelligence (AI) platforms in practice.

category: pathology


title: Collagen (I) homotrimer potentiates the osteogenesis imperfecta (oim) mutant allele and reduces survival in male mice

abstract: Type I collagen is the major structural component of bone where it exists as an (1)2(2)1 heterotrimer in all vertebrates. The osteogenesis imperfecta (oim) mouse model comprising solely homotrimeric (1)3 type I collagen, due to a dysfunctional 2 chain, has a brittle bone phenotype implying that the heterotrimeric form is required for physiological bone function. However, humans with rare null alleles preventing synthesis of the 2 chain have connective tissue and cardiovascular abnormalities (cardiac valvular Ehlers Danlos Syndrome), without evident bone fragility. Conversely a prevalent human single nucleotide polymorphism leading to increased homotrimer synthesis is associated with osteoporosis. Whilst the oim line is well-studied, whether homotrimeric type I collagen is functionally equivalent to the heterotrimeric form in bone has not been demonstrated. Col1a2 null and oim mouse lines were used in this study and bones analysed by microCT and 3-point bending. RNA was also extracted from heterozygote tissues and allelic discrimination analyses performed using qRT-PCR. Here we comprehensively show for the first time that mice lacking the 2(I) chain do not have impaired bone biomechanical or structural properties, unlike oim homozygous mice. However Mendelian inheritance was affected in male mice of both lines and male mice null for the 2 chain exhibited age-related loss of condition. The brittle bone phenotype of oim homozygotes could result from detrimental effects of the oim mutant allele, however, the phenotype of oim heterozygotes is known to be less severe. We used allelic discrimination to show that the oim mutant allele is not downregulated in heterozygotes. We then tested whether gene dosage was responsible for the less severe phenotype of oim heterozygotes by generating compound heterozygotes. Data showed that compound heterozygotes had impaired bone structural properties as compared to oim heterozygotes, albeit to a lesser extent than oim homozygotes. Hence, we concluded that the presence of heterotrimeric collagen-1 in oim heterozygotes alleviates the effect of the oim mutant allele but a genetic interaction between homotrimeric collagen-1 and the oim mutant allele leads to bone fragility.

category: physiology


title: IWS1 phosphorylation promotes cell proliferation and predicts poor prognosis in EGFR mutant lung adenocarcinoma patients, through the cell cycle-regulated U2AF2 RNA splicing.

abstract: Our previous studies have shown that IWS1 is a phosphorylation target of AKT in human lung cancer. RNA-seq studies using lung adenocarcinoma cells lacking IWS1, identified an exon 2 deficient splice variant of U2AF2, affecting U2AF65 RS domain and its binding with Prp19. This depends on phosphorylated IWS1 and the assembly of LEDGF/SRSF1 splicing complexes, via H3K36 trimethylation through the cell cycle. Inhibition of the pathway results in Sororin downregulation, a target and regulator of ERK, G2/M phase arrest, impaired cell proliferation and tumor growth, more pronounced in EGFR mutant cells. Analysis of lung adenocarcinoma samples revealed that the IWS1 phosphorylation pathway correlates with advanced stage, relapse, metastasis and poor survival in patients harboring EGFR mutations. This work highlights the instrumental role of the AKT/p-IWS1 axis to the epigenetic regulation of RNA processing and oncogenic signals, proposing it as a drug target in EGFR mutant lung adenocarcinoma.


title: The lncRNA APOLO interacts with the transcription factor WRKY42 to trigger root hair cell expansion in response to cold

abstract:
Plant long noncoding RNAs (lncRNAs) have emerged as important regulators of chromatin dynamics, impacting on transcriptional programs leading to different developmental outputs. The lncRNA AUXIN REGULATED PROMOTER LOOP (APOLO) directly recognizes multiple independent loci across the Arabidopsis genome and modulates their three-dimensional chromatin conformation, leading to transcriptional shifts. Here, we show that APOLO recognizes the locus encoding the root hair (RH) master regulator ROOT HAIR DEFECTIVE 6 (RHD6) and controls RHD6 transcriptional activity leading to cold-enhanced RH elongation through the consequent activation of the transcription factor gene RHD6-like RSL4. Furthermore, we demonstrate that APOLO interacts with the transcription factor WRKY42 and modulates its binding to the RHD6 promoter. WRKY42 is required for the activation of RHD6 by low temperatures and WRKY42 deregulation impairs cold-induced RH expansion. Collectively, our results indicate that a novel ribonucleoprotein complex involving APOLO and WRKY42 forms a regulatory hub which activates RHD6 by shaping its epigenetic environment and integrates signals governing RH growth and development.

SUMMARYThe lncRNA APOLO directly regulates the transcription of the root hair-master gene RHD6. In response to cold, APOLO is induced and it decoys the H3K27me3-binding protein LHP1 away from RHD6. In addition, APOLO modulates the binding of the transcription factor WRKY42 to the RHD6 promoter at low temperatures.

category: plant biology


title: Dynamics in Natural and Designed Elastins and Their Relation to Elastic Fiber Structure and Recoil

abstract:
Elastin fibers assemble in the extracellular matrix from the precursor protein tropoelastin and provide the flexibility and spontaneous recoil required for arterial function. Unlike many proteins, a structure-function mechanism for elastin has been elusive. We have performed detailed NMR relaxation studies of the dynamics of the minielastins 24x' and 20x' using solution NMR, and of purified bovine elastin fibers in the presence and absence of mechanical stress using solid state NMR. The low sequence complexity of the minielastins enables us to determine dynamical timescales and degrees of local ordering with residue-specific resolution in the cross-link and hydrophobic modules using NMR relaxation. We find an extremely high degree of disorder, with order parameters for the entirety of the hydrophobic domains near zero, resembling that of simple chemical polymers and less than the order parameters that have been observed in other intrinsically disordered proteins. We find that backbone order parameters in natural, purified elastin fibers are comparable to those found in 24x' and 20x' in solution. The difference in dynamics, compared to the minielastins, is that backbone correlation times are significantly slowed in purified elastin. Moreover, when elastin is mechanically stretched, the high chain disorder in purified elastin is retained - showing that any change in local ordering is below that detectable in our experiment. Combined with our previous finding of a 10-fold increase in the ordering of water when fully hydrated elastin fibers are stretched by 50%, these results support the hypothesis that stretch induced solvent ordering, i.e., the hydrophobic effect, is a key player in the elastic recoil of elastin as opposed to configurational entropy loss.

SIGNIFICANCEElastin is responsible for the spontaneous recoil of arterial walls that is necessary for cardiovascular function. Despite this critical role, the mechanism driving entropic recoil has remained unclear. Elastin is unusual in that it is intrinsically disordered in both soluble and fibrous forms. Using NMR, we have determined the timescales and amplitudes of dynamics in two soluble elastin mimetics and in relaxed and stretched states of purified bovine elastin fibers. Although dynamical timescales are different, both the soluble elastin mimetic and fibrillar elastin display an exceptionally high degree of disorder. No detectable increase in protein ordering was observed upon stretching, suggesting that entropic recoil is primarily driven by the hydrophobic effect and not configurational entropy loss.


title: Structural basis of DegP-protease temperature-dependent activation

abstract: Protein quality control is an essential cellular function mainly executed by a vast array of different proteases and molecular chaperones. One of the bacterial HtrA (high temperature requirement A) protein family members, the homo-oligomeric DegP-protease, plays a crucial role in the Escherichia coli (E. coli) protein quality control machinery by removing unfolded proteins or preventing their aggregation and chaperoning them to their final folded state within the periplasm. DegP contains two regulatory PDZ domains, which play key roles in substrate recognition and in the transformation of DegP between inactive hexameric and proteolytic active cage-like structures. Here, we analyze the interaction and dynamics of the DegP PDZ-domains underlying this transformation by high-resolution NMR spectroscopy complemented with biochemical cleavage assays. We identify an interdomain molecular lock, which controls the interactions between the two PDZ domains, regulated by fine-tuned temperature-dependent protein dynamics, and which is potentially conserved in proteins harboring tandem PDZ domains.


title: Bioinformatic Analysis of Structure and Function of LIM Domains of Human Zyxin Family Proteins

abstract: Members of the human Zyxin family are LIM domain-containing proteins that perform critical cellular functions and are indispensable for cellular integrity. Despite their importance, not much is known about their structure, functions, interactions and dynamics. To provide insights into these, we used a set of in-silico tools and databases and analyzed their amino acid sequence, phylogeny, post-translational modifications, structure-dynamics, molecular interactions, and functions. Our analysis revealed that zyxin members are ohnologs. Presence of a conserved nuclear export signal composed of LxxLxL/LxxxLxL consensus sequence, as well as a possible nuclear localization signal, suggesting that Zyxin family members may have nuclear and cytoplasmic roles. The molecular modeling and structural analysis indicated that Zyxin family LIM domains share similarities with transcriptional regulators and have positively charged electrostatic patches, which may indicate that they have previously unanticipated nucleic acid binding properties. Intrinsic dynamics analysis of Lim domains suggest that only Lim1 has similar internal dynamics properties, unlike Lim2/3. Furthermore, we analyzed protein expression and mutational frequency in various malignancies, as well as mapped protein-protein interaction networks they are involved in. Overall, our comprehensive bioinformatic analysis suggests that these proteins may play important roles in mediating protein-protein and protein-nucleic acid interactions.

category: biochemistry


title: Validation and tuning of in situ transcriptomics image processing workflows with crowdsourced annotations

abstract:
Recent advancements in in situ methods, such as multiplexed in situ RNA hybridization and in situ RNA sequencing, have deepened our understanding of the way biological processes are spatially organized in tissues. Automated image processing and spot-calling algorithms for analyzing in situ transcriptomics images have many parameters which need to be tuned for optimal detection. Having ground truth datasets (images where there is very high confidence on the accuracy of the detected spots) is essential for evaluating these algorithms and tuning their parameters.

We present a first-in-kind open-source toolkit and framework for in situ transcriptomics image analysis that incorporates crowdsourced annotations, alongside expert annotations, as a source of ground truth for the analysis of in situ transcriptomics images. The kit includes tools for preparing images for crowdsourcing annotation to optimize crowdsourced workers ability to annotate these images reliably, performing quality control (QC) on worker annotations, extracting candidate parameters for spot-calling algorithms from sample images, tuning parameters for spot-calling algorithms, and evaluating spot-calling algorithms and worker performance. These tools are wrapped in a modular pipeline with a flexible structure that allows users to take advantage of crowdsourced annotations from any source of their choice. We tested the pipeline using real and synthetic in situ transcriptomics images and annotations from the Amazon Mechanical Turk system obtained via Quanti.us. Using real images from in situ experiments and simulated images produced by one of the tools in the kit, we studied worker sensitivity to spot characteristics and established rules for annotation QC. We explored and demonstrated the use of ground truth generated in this way for validating spot-calling algorithms and tuning their parameters, and confirmed that consensus crowdsourced annotations are a viable substitute for expert-generated ground truth for these purposes.

Data AvailabilityThe iPython notebooks, input images, and In Situ Transcriptomics Annotation (INSTA) pipeline software are available from https://github.com/czbiohub/instapipeline. The SpotImage software is available from https://github.com/czbiohub/spotimage. The files and iPython notebooks used to generate the figures for this paper are available from https://github.com/czbiohub/instapaper.

category: bioengineering


title: High-density Neural Recordings from Feline Sacral Dorsal Root Ganglia with Thin-film Array

abstract: Objective: Dorsal root ganglia (DRG) are promising sites for recording sensory activity. Current technologies for DRG recording are stiff and typically do not have sufficient site density for high-fidelity neural data techniques. Approach: In acute experiments, we demonstrate single-unit neural recordings in sacral DRG of anesthetized felines using a 4.5 m-thick, high-density flexible polyimide microelectrode array with 60 sites and 30-40 m site spacing. We delivered arrays into DRG with ultrananocrystalline diamond shuttles designed for high stiffness affording a smaller footprint. We recorded neural activity during sensory activation, including cutaneous brushing and bladder filling, as well as during electrical stimulation of the pudendal nerve and anal sphincter. We used specialized neural signal analysis software to sort densely packed neural signals. Main results: We successfully delivered arrays in five of six experiments and recorded single-unit sensory activity in four experiments. The median neural signal amplitude was 55 V peak-to-peak and the maximum unique units recorded at one array position was 260, with 157 driven by sensory or electrical stimulation. In one experiment, we used the neural analysis software to track eight sorted single units as the array was retracted ~500 m. Significance: This study is the first demonstration of ultrathin, flexible, high-density electronics delivered into DRG, with capabilities for recording and tracking sensory information that are a significant improvement over conventional DRG interfaces.


title: Action Imagery and Observation in Neurorehabilitation for Parkinson's Disease (ACTION-PD): development and pilot randomised controlled trial of a user-informed home training intervention to improve everyday functional actions

abstract:
BackgroundParkinsons disease (PD) causes difficulties with everyday manual activities, but few studies have addressed these therapeutically. Training with action observation (AO) and motor imagery (MI) can significantly improve performance in healthy individuals, particularly when these techniques are applied simultaneously (AO+MI). Both AO and MI have shown promising effects in PD, but previous studies have used these separately. This article describes the development and pilot testing of an intervention combining AO+MI and physical practice to improve functional manual actions in PD.

MethodsThe home-based intervention, delivered using a tablet computer app, was iteratively designed by an interdisciplinary team including people with PD, and further developed through focus groups and initial testing. The intervention was then tested in a six-week randomised controlled trial (ISRCTN 11184024) of 10 participants with mild to moderate PD (6 intervention; 4 treatment as usual).

Results and ConclusionsUsage and qualitative data provided preliminary evidence of acceptability and usability, indicating that a feasibility RCT is warranted. Exploratory analyses suggested potential improvements in manual actions. The importance of personalisation, choice, and motivation was highlighted, as well as the need to facilitate engagement in motor imagery. The findings also have broader relevance for AO+MI interventions in PD and other populations.


title: What executive function network is that? An image-based meta-analysis of network labels

abstract: The current state of label conventions used to describe brain networks related to executive functions is highly inconsistent, leading to confusion among researchers regarding network labels. Visually similar networks are referred to by different labels, yet these same labels are used to distinguish networks within studies. We performed a literature review of fMRI studies and identified nine frequently-used labels that are used to describe topographically or functionally similar neural networks: central executive network (CEN), cognitive control network (CCN), dorsal attention network (DAN), executive control network (ECN), executive network (EN), frontoparietal network (FPN), working memory network (WMN), task positive network (TPN), and ventral attention network (VAN). Our aim was to meta-analytically determine consistency of network topography within and across these labels. We hypothesized finding considerable overlap in the spatial topography among the neural networks associated with these labels. An image-based meta-analysis was performed on 158 group-level statistical maps (SPMs) received from authors of 69 papers listed on PubMed. Our results indicated that there was very little consistency in the SPMs labeled with a given network name. We identified four clusters of SPMs representing four spatially distinct executive function networks. We provide recommendations regarding label nomenclature and propose that authors looking to assign labels to executive function networks adopt this template set for labeling networks.


title: Cerebral laterality for writing in right- and left-handers: A functional transcranial Doppler ultrasound study

abstract: The cerebral lateralization of written language has received very limited research attention in comparison to the wealth of studies on the cerebral lateralization of oral language. The purpose of the present study was to further our understanding of written language lateralization, by elucidating the relative contribution of language and motor functions. We compared written word generation with a task that has equivalent visuomotor demands but does not include language: the repeated drawing of symbols. We assessed cerebral laterality using functional transcranial Doppler ultrasound (fTCD), a non-invasive, perfusion-sensitive neuroimaging technique in 23 left- and 31 right-handed participants. Findings suggest that the linguistic aspect of written word generation recruited more left-hemispheric areas during writing, in right-handers compared to left-handers. This difference could be explained by greater variability in cerebral laterality patterns within left-handers or the possibility that the areas subserving language in left-handers are broader than in right-handers. Another explanation is that the attentional demands of the more novel symbol copying task (compared to writing) contributed more right-hemispheric activation in right-handers, but this could not be captured in left-handers due to ceiling effects. Future work could investigate such attentional demands using both simple and complex stimuli in the copying condition.


title: Spectral Signatures of L-DOPA-Induced Dyskinesia Depend on L-DOPA Dose and are Suppressed by Ketamine

abstract: L-DOPA-induced dyskinesias (LID) are debilitating motor symptoms of dopamine-replacement therapy for Parkinsons disease (PD) that emerge after years of L-DOPA treatment. While there is an abundance of research into the cellular and synaptic origins of LID, less is known about how LID impacts systems-level circuits and neural synchrony, how synchrony is affected by the dose and duration of L-DOPA exposure, or how potential novel treatments for LID, such as sub-anesthetic ketamine, alter this activity. Sub-anesthetic ketamine treatments have recently been shown to reduce LID, and ketamine is known to affect neural synchrony. To investigate these questions, we measured movement and local-field potential (LFP) activity from the motor cortex (M1) and the striatum of preclinical rodent models of PD and LID. In the first experiment, we investigated the effect of the LID priming procedures and L-DOPA dose on neural signatures of LID. Two common priming procedures were compared: a high-dose procedure that exposed unilateral 6-hydroxydopamine-lesioned rats to 12 mg/kg L-DOPA for 7 days, and a low-dose procedure that exposed rats to 7 mg/kg L-DOPA for 21 days. Consistent with reports from other groups, 12 mg/kg L-DOPA triggered LID and 80-Hz oscillations; however, these 80-Hz oscillations were not observed after 7 mg/kg administration despite clear evidence of LID, indicating that 80-Hz oscillations are not an exclusive signature of LID. We also found that weeks-long low-dose priming resulted in the emergence of non-oscillatory broadband gamma activity (> 30 Hz) in the striatum and theta-to-high-gamma cross-frequency coupling (CFC) in M1. In a second set of experiments, we investigated how ketamine exposure affects spectral signatures of low-dose L-DOPA priming. During each neural recording session, ketamine was delivered through 5 injections (20 mg/kg, i.p.) administered every 2 hours. We found that ketamine exposure suppressed striatal broadband gamma associated with LID but enhanced M1 broadband activity. We also found that M1 theta-to-high-gamma CFC associated with the LID on-state was suppressed by ketamine. These results suggest that ketamines therapeutic effects are region specific. Our findings also have clinical implications, as we are the first to report novel oscillatory signatures of the common low-dose LID priming procedure that more closely models dopamine replacement therapy in individuals with PD. We also identify neural correlates of the anti-dyskinetic activity of sub-anesthetic ketamine treatment.


title: MetaWorks: A flexible, scalable bioinformatic pipeline for high-throughput multi-marker biodiversity assessments

abstract: Multi-marker metabarcoding is increasingly being used to generate biodiversity information across different domains of life from microbes to fungi to animals such as for molecular ecology and biomonitoring applications in different sectors from academic research to regulatory agencies and industry. Current popular bioinformatic pipelines support microbial and fungal marker analysis, while ad hoc methods are often used to process animal metabarcode markers from the same study. MetaWorks provides a harmonized processing environment, pipeline, and taxonomic assignment approach for demultiplexed Illumina reads for all biota using a wide range of metabarcoding markers such as 16S, ITS, and COI. A Conda environment is provided to quickly gather most of the programs and dependencies for the pipeline. Several workflows are provided such as: taxonomically assigning exact sequence variants, provides an option to generate operational taxonomic units, and facilitates single-read processing. Pipelines are automated using Snakemake to minimize user intervention and facilitate scalability. All pipelines use the RDP classifier to provide taxonomic assignments with confidence measures. We extend the functionality of the RDP classifier for taxonomically assigning 16S (bacteria), ITS (fungi), and 28S (fungi), to also support COI (animals), rbcL (eukaryotes, land plants, diatoms), 12S (fish), 18S (eukaryotes, diatoms) and ITS (fungi, plants). MetaWorks properly handles ITS by trimming flanking conserved rRNA gene regions as well as protein coding genes by providing two options for removing obvious pseudogenes. MetaWorks is available at https://github.com/terrimporter/MetaWorks along with quick-start instructions using test data, detailed workflow descriptions, and a tutorial for new users.


title: Species packing and the latitudinal gradient in beta-diversity

abstract: The decline in species richness at higher latitudes is among the most fundamental patterns in ecology. Whether changes in species composition across space (beta-diversity) contribute to this gradient of overall species richness (gamma-diversity) remains hotly debated. Previous studies that failed to resolve the issue suffered from a well-known tendency for small samples in areas with high gamma-diversity to have inflated measures of beta-diversity. Here, we provide here a novel analytical test, using beta-diversity metrics that correct the gamma-diversity and sampling biases, to compare beta-diversity and species packing across a latitudinal gradient in tree species richness of 21 large forest plots along a large environmental gradient in East Asia. We demonstrate that after accounting for topography and correcting the gamma-diversity bias, tropical forests still have higher beta-diversity than temperate analogs. This suggests that beta-diversity contributes to the latitudinal species richness gradient as a component of gamma-diversity. Moreover, both niche specialization and niche marginality (a measure of niche spacing along an environmental gradient) also increase towards the equator, after controlling for the effect of topographic heterogeneity. This supports the joint importance of tighter species packing and larger niche space in tropical forests while also demonstrating the importance of local processes in controlling beta-diversity.


title: GAF is essential for zygotic genome activation and chromatin accessibility in the early Drosophila embryo

abstract: Following fertilization, the genomes of the germ cells are reprogrammed to form the totipotent embryo. Pioneer transcription factors are essential for remodeling the chromatin and driving the initial wave of zygotic gene expression. In Drosophila melanogaster, the pioneer factor Zelda is essential for development through this dramatic period of reprogramming, known as the maternal- to-zygotic transition (MZT). However, it was unknown whether additional pioneer factors were required for this transition. We identified an additional maternally encoded factor required for development through the MZT, GAGA Factor (GAF). GAF is necessary to activate widespread zygotic transcription and to remodel the chromatin accessibility landscape. We demonstrated that Zelda preferentially controls expression of the earliest transcribed genes, while genes expressed during widespread activation are predominantly dependent on GAF. Thus, progression through the MZT requires coordination of multiple pioneer-like factors, and we propose that as development proceeds control is gradually transferred from Zelda to GAF.


title: Transcriptional response of the calcification and stress response toolkits in an octocoral under heat and pH stress

abstract: Up to one-third of all described marine species inhabit coral reefs, but the future of these hyperdiverse ecosystems is insecure due to local and global threats, such as overfishing, eutrophication, ocean warming, and acidification. Although these impacts are expected to have a net detrimental effect on reefs, it has been shown that some organisms like octocorals may remain unaffected, or benefit from, anthropogenically induced environmental change, and may replace stony corals in future reefs. Despite their potential importance in future shallow-water coastal environments, the molecular mechanisms leading to the resilience to anthropogenic-induced stress observed in octocorals remain unknown. Here, we use manipulative experiments, proteomics, and transcriptomics to show that the molecular toolkit used by Pinnigorgia flava, a common Indo-Pacific gorgonian octocoral, to deposit its calcium-carbonate skeleton is resilient to heat and seawater acidification stress. Sublethal heat stress triggered a stress response in P. flava but did not affect the expression of 27 transcripts encoding Skeletal Organic Matrix (SOM) proteins. Exposure to seawater acidification did not cause a stress response but triggered the downregulation of many transcripts, including an osteonidogen homolog present in the SOM. The observed transcriptional decoupling of the skeletogenic and stress-response toolkits provides insights into the mechanisms of resilience to anthropogenically-driven environmental change observed in octocorals.


title: Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Protein Structures and Interaction Networks

abstract:
Geometric deep learning has well-motivated applications in the context of biology, a domain where relational structure in datasets can be meaningfully leveraged. Currently, efforts in both geometric deep learning and, more broadly, deep learning applied to biomolecular tasks have been hampered by a scarcity of appropriate datasets accessible to domain specialists and machine learning researchers alike. However, there has been little exploration of how to best to integrate and construct geometric representations of these datatypes. To address this, we introduce Graphein as a turn-key tool for transforming raw data from widely-used bioinformatics databases into machine learning-ready datasets in a high-throughput and flexible manner. Graphein is a Python library for constructing graph and surface-mesh representations of protein structures and biological interaction networks for computational analysis. Graphein provides utilities for data retrieval from widely-used bioinformatics databases for structural data, including the Protein Data Bank, the recently-released AlphaFold Structure Database, and for biomolecular interaction networks from STRINGdb, BioGrid, TRRUST and RegNetwork. The library interfaces with popular geometric deep learning libraries: DGL, PyTorch Geometric and PyTorch3D though remains framework agnostic as it is built on top of the PyData ecosystem to enable inter-operability with scientific computing tools and libraries. Graphein is designed to be highly flexible, allowing the user to specify each step of the data preparation, scalable to facilitate working with large protein complexes and interaction graphs, and contains useful pre-processing tools for preparing experimental files. Graphein facilitates network-based, graph-theoretic and topological analyses of structural and interaction datasets in a high-throughput manner. As example workflows, we make available two new protein structure-related datasets, previously unused by the geometric deep learning community. We envision that Graphein will facilitate developments in computational biology, graph representation learning and drug discovery.

Availability and implementationGraphein is written in Python. Source code, example usage and tutorials, datasets, and documentation are made freely available under the MIT License at the following URL: graphein.ai


title: Local Gazetteers Reveal Contrasting Patterns of Historical Distribution Changes between Apex Predators and Mesopredators in Eastern China

abstract:
BackgroundHumans have been causing the sixth wave of mass extinction of biodiversity. The situation of predators, especially of carnivores, is a key indicator of biodiversity, and the mesopredator release is a typical phenomenon in ecosystem recess. Local gazetteers  are a rich resource for historical biodiversity research. But there are obvious biases in previous studies focusing in only presence records and neglecting the absence records. We recollected and analyze the records by fixed methods to research historical change of biodiversity.

MethodsInnovatively, this research uses both presence and absence records from local gazetteers to reconstruct the distribution of 8 kinds of mammalian predators (i.e. tiger, leopard, bear, wolf, fox, civet, dhole and mustelid) in eastern China from 1573 A.D. to 1949 A.D. (sorted into 4 periods). Then we analyze the distribution changes, the relation between animals and the influence from human.

ResultsWith the human population booming, the distribution of large/apex predators retreated overall, but the distribution of mesopredators expanded overall. Besides, the predator distribution relations formed different groups, not match the body size groups totally.

ConclusionsBased on our reconstructions, we provide direct proof of human disturbance on mammal distribution in China, and extend support for the mesopredator release hypothesis. And we tested the predator guild hypothesis by proving that dhole were successful to coexist with tiger and leopard in history.

ProspectsWe have also collected records for other wild animals from local gazetteers in China. Based on the collection, we have built the Database of Wild Mammal Records in Chinese Local Gazetteers and are building the Database of Wild Bird Records in Chinese Local Gazetteers. We aim to continue relevant studies using these databases in the future.


title: The Mycobacterium tuberculosis sRNA F6 modifies expression of essential chaperonins, GroEL2 and GroES

abstract: Almost 140 years after the identification of Mycobacterium tuberculosis as the etiological agent of tuberculosis, important aspects of its biology remain poorly described. Little is known about the role of post-transcriptional control of gene expression and RNA biology, including the role of most of the small RNAs (sRNAs) identified to date. We have carried out a detailed investigation of the M. tuberculosis sRNA, F6, and shown it to be dependent on SigF for expression, and significantly induced in starvation conditions in vitro and in a mouse model of infection. Further exploration of F6 using an in vitro starvation model of infection indicates that F6 affects the expression of the essential chaperonins, GroEL2 and GroES. Our results point towards a role for F6 during periods of low metabolic activity typically associated with long-term survival of M. tuberculosis in human granulomas.