title: Is single-step genomic REML with the algorithm for proven and young more computationally efficient when less generations of data are present?

abstract:
Efficient computing techniques allow the estimation of variance components for virtually any traditional dataset. When genomic information is available, variance components can be estimated using genomic REML (GREML). If only a portion of the animals have genotypes, single-step GREML (ssGREML) is the method of choice. The genomic relationship matrix (G) used in both cases is dense, limiting computations depending on the number of genotyped animals. The algorithm for proven and young (APY) can be used to create a sparse inverse of G[Formula] with close to linear memory and computing requirements. In ssGREML, the inverse of the realized relationship matrix (H-1) also includes the inverse of the pedigree relationship matrix, which can be dense with long pedigree, but sparser with short. The main purpose of this study was to investigate whether costs of ssGREML can be reduced using APY with truncated pedigree and phenotypes. We also investigated the impact of truncation on variance components estimation when different numbers of core animals are used in APY. Simulations included 150K animals from 10 generations, with selection. Phenotypes (h2 = 0.3) were available for all animals in generations 1-9. A total of 30K animals in generations 8 and 9, and 15K validation animals in generation 10 were genotyped for 52,890 SNP. Average information REML and ssGREML with G-1 and [Formula] using 1K, 5K, 9K, and 14K core animals were compared. Variance components are impacted when the core group in APY represents the number of eigenvalues explaining a small fraction of the total variation in G. The most time-consuming operation was the inversion, with more than 50% of the total time. Next, numerical factorization consumed nearly 30% of the total computing time. On average, a 7% decrease in the computing time for ordering was observed by removing each generation of data. APY can be successfully applied to create the inverse of the genomic relationship matrix used in ssGREML for estimating variance components. To ensure reliable variance component estimation, it is important to use a core size that corresponds to the number of largest eigenvalues explaining around 98% of total variation in G. When APY is used, pedigrees can be truncated to increase the sparsity of H and slightly reduce computing time for ordering and symbolic factorization, with no impact on the estimates.

Lay SummaryThe estimation of variance components is computationally expensive under large-scale genetic evaluations due to several inversions of the coefficient matrix. Variance components are used as parameters for estimating breeding values in mixed model equations (MME). However, resulting breeding values are not Best Linear Unbiased Predictions (BLUP) unless the variance components approach the true parameters. The increasing availability of genomic data requires the development of new methods for improving the efficiency of variance component estimations. Therefore, this study aimed to reduce the costs of single-step genomic REML (ssGREML) with the Algorithm for Proven and Young (APY) for estimating variance components with truncated pedigree and phenotypes. In addition, we investigated the influence of truncation on variance components and genetic parameter estimates. Under APY, the size of the core group influences the similarity of breeding values and their reliability compared to the full genomic matrix. In this study, we found that to ensure reliable variance component estimation it is required to consider a core size that corresponds to the number of largest eigenvalues explaining around 98% of the total variation in G to avoid biased parameters. In terms of costs, the use of APY slightly decreased the time for ordering and symbolic factorization with no impact on estimations.

Teaser TextEstimation of variance components is becoming computationally challenging due to the increasing size of genomic information. We investigated the impacts of using the algorithm for proven and young (APY) in genetic evaluations. The use of APY has no impact on variance components and genetic parameters estimation.


title: Pathogen Detection in RNA-Seq Data with Pathonoia

abstract:
MotivationRecent evidence suggests that bacterial and viral infections may cause or exacerbate many human diseases. One method of choice to detect microbes in tissue is RNA sequencing. While the detection of specific microbes using RNA sequencing offers good sensitivity and specificity, untargeted approaches suffer from very high false positive rates and a lack of sensitivity for lowly abundant organisms.

ResultsWe introduce Pathonoia, an algorithm that detects viruses and bacteria in RNA sequencing data with high precision and recall. Pathonoia first applies an established k-mer based method for species identification and then aggregates this evidence over all reads in a sample. In addition, we provide an easy-to-use analysis framework that highlights potential microbe-host cell interactions by correlating the microbial to host gene expression. Pathonoia outperforms competing algorithms in microbial detection specificity, both on in silico and real datasets. Lastly, we present two case studies in human liver and brain in which microbial infection might exacerbate disease.

AvailabilityA Python package for Pathonoia sample analysis and a guided analysis Jupyter notebook for bulk RNAseq datasets are available on GitHub https://github.com/kepsi/Pathonoia.

Contactaliebho1@jhu.edu and s.bonn@uke.de

Graphical Abstract

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category: bioinformatics


title: MOJITOO: a fast and universal method for integration of multimodal single cell data

abstract:
The advent of multi-modal single cell sequencing techniques have shed new light on molecular mechanisms by simultaneously inspecting transcriptomes, epigenomes and proteomes of the same cell. However, to date, the existing computational approaches for integration of multimodal single cell data are either computationally expensive, require the delineation of parameters or can only be applied to particular modalities.

We present a single cell multi-modal integration method, named MOJITOO (Multi-mOdal Joint IntegraTion of cOmpOnents). MOJITOO uses canonical correlation analysis for a fast and parameter free detection of a shared representation of cells from multimodal single cell data. Moreover, estimated canonical components can be used for interpretation, i.e. association of modality specific molecular features with the latent space. We evaluate MOJITOO using bi- and tri-modal single cell data sets and show that MOJITOO outperforms existing methods regarding computational requirements, preservation of original latent spaces and clustering.


title: Pharmacometabolomics reveals urinary diacetylspermine as a biomarker of doxorubicin effectiveness in triple negative breast cancer

abstract: Triple-negative breast cancer (TNBC) patients receive chemotherapy treatment, including doxorubicin, due to the lack of targeted therapies. Drug resistance is a major cause of treatment failure in TNBC and therefore, there is a need to identify biomarkers that determine effective drug response. Here, a pharmacometabolomics study was performed using TNBC patient-derived xenograft models to detect urinary metabolic biomarkers of doxorubicin effectiveness. Diacetylspermine was identified as a urine metabolite that robustly changed in response to effective doxorubicin treatment, which persisted after the final dose. Diacetylspermine was directly traced back to the tumor and correlated with tumor volume. Ex vivo tumor slices revealed that doxorubicin directly increases diacetylspermine production by increasing tumor spermidine/spermine N1-acetyltransferase 1 expression and activity, which was corroborated by elevated polyamine flux. In breast cancer patients, tumor diacetylspermine was elevated compared to matched non-cancerous tissue and increased in HER2+ and TNBC compared to ER+ subtypes. In addition, 12-hour urine diacetylspermine was associated with breast cancer tumor volume and poor tumor grade. This study describes a pharmacometabolomics strategy for identifying cancer metabolic biomarkers that indicate drug response. Our findings characterize urine diacetylspermine as a non-invasive biomarker of doxorubicin effectiveness in TNBC.

category: cancer biology


title: Actin networks modulate heterogenous NF-κB dynamics in response to TNFα

abstract: The canonical NF-{kappa}B transcription factor RELA is a master regulator of immune and stress responses and is commonly upregulated in PDAC tumours. Using live imaging, we characterised single cell RELA translocation dynamics in two human PDAC cell lines and identified high cell-to-cell variability in RELA responses to TNF, including unresponsive, damped, and sustained nuclear RELA localisation. Using a combination of quantitative single cell imaging and Bayesian analysis, we determined that heterogeneity in RELA nuclear translocation between and within PDAC cell lines is dependent on cytoskeletal organisation, in particular actin abundance and distribution. Subsequently, RELA nuclear localisation could be up or downregulated through biochemical modulation of cell shape and the cytoskeleton, particularly by disrupting nucleation of actin stress fibres and branched actin via formin and ARP2/3 inhibition. Together, our data provide evidence that actin configuration regulates RELA translocation during the inflammatory response and that targeting actin dynamics can be used to modulate misregulated NF-{kappa}B signalling in PDAC.


title: Phenotypic dissection of epithelial lineages and therapeutic manipulation of differentiation programs in human Adenoid Cystic Carcinomas

abstract: Adenoid Cystic Carcinoma (ACC) is a rare and aggressive form of salivary gland cancer, characterized by the co-existence within tumor tissues of two distinct populations of malignant cells, phenotypically similar to the myoepithelial and ductal lineages of normal salivary glands. Using a novel computational approach for single-cell RNA-seq analysis, we identified two cell-surface markers (CD49f, KIT) that enable the differential purification of myoepithelial-like (CD49fhigh/KITneg) and ductal-like (CD49flow/KIT+) cells from ACC patient derived xenografts (PDX). Using prospective xeno-transplantation experiments, we demonstrate that myoepithelial-like cells act as progenitors of ductal-like cells. Using three-dimensional (3D) organoid cultures, we demonstrate that agonists of retinoic acid (RA) signaling promote differentiation of myoepithelial-like cells into ductal-like cells, while inhibitors of RA signaling selectively kill ductal-like cells. Finally, we demonstrate that BMS493, an inverse agonist of RA signaling, can be successfully leveraged for the in vivo treatment of human ACCs.


title: Environment constrains fitness advantages of division of labor in microbial consortia engineered for metabolite push or pull interactions

abstract:
Fitness benefits from division of labor in microbial consortia are well documented, but the dependency of the benefits on environmental context is poorly understood. Two synthetic Escherichia coli consortia were built to test the relationships between exchanged organic acid, local environment, and opportunity costs of different metabolic strategies. Opportunity costs quantify benefits not realized due to selecting one phenotype over another. The consortia catabolized glucose and exchanged either acetic or lactic acid to create producer-consumer food webs. The organic acids had different inhibitory properties and different opportunity costs associated with their positions in central metabolism. The exchanged metabolites modulated different consortial dynamics. The acetic acid-exchanging (AAE) consortium had a  push interaction motif where acetic acid was secreted faster by the producer than the consumer imported it, while the lactic acid-exchanging (LAE) consortium had a  pull interaction motif where the consumer imported lactic acid at a comparable rate to its production. The LAE consortium outperformed wild type (WT) batch cultures under the environmental context of weakly buffered conditions, achieving a 55% increase in biomass titer, a 51% increase in biomass per proton yield, an 86% increase in substrate conversion, and the complete elimination of byproduct accumulation all relative to the WT. However, the LAE consortium had the tradeoff of a 42% lower specific growth rate. The AAE consortium did not outperform the WT in any considered fitness metric. Fitness advantages of the LAE consortium were sensitive to environment; increasing the medium buffering capacity negated the fitness advantages compared to WT.

IMPORTANCEMost naturally occurring microorganisms persist in consortia where metabolic interactions are common and often essential to ecosystem function. This study uses synthetic ecology to test how different cellular interaction motifs influence fitness properties of consortia. Environmental context ultimately controlled the division of labor fitness as shifts from weakly buffered to highly buffered conditions negated the benefits of the strategy. Understanding the limits of division of labor advances our understanding of natural community functioning which is central to nutrient cycling and provides design rules for assembling consortia used in applied bioprocessing.

category: synthetic biology


title: Synaptic and intrinsic potentiation in O-LM interneurons is induced by theta patterns of stimulation

abstract: Oriens lacunosum-moleculare (O-LM) interneurons display a non-conventional form of long-term synaptic potentiation (LTP) conferred by calcium-permeable AMPA receptors (CP-AMPAR). So far, this form of LTP has been induced in O-LM cells by physiologically unrealistic protocols. We report here the induction of both synaptic and intrinsic potentiation in O-LM interneurons following stimulation of afferent glutamatergic inputs in the theta ({theta}) frequency range. LTP is induced by synaptic activation of CP-AMPAR whereas long-term potentiation of intrinsic excitability (LTP-IE) results from the mGluR1-dependent down-regulation of Kv7 voltage-dependent potassium channel and hyperpolarization activated and cyclic nucleotide-gated (HCN) channel through the depletion of phosphatidylinositol-4,5-bi-phosphate (PIP2). LTP and LTP-IE are reversible, demonstrating that both synaptic and intrinsic changes are bidirectional in O-LM cells. We conclude that physiological stimuli such as {theta} patterns induce synaptic and intrinsic potentiation in O-LM interneurons.

category: neuroscience


title: Microenvironmental sensing by fibroblasts controls macrophage population size

abstract:
Animal tissues are comprised of diverse cell types. However, the mechanisms controlling the number of each cell type within tissue compartments remain poorly understood. Here, we report that different cell types utilize distinct strategies to control population numbers. Proliferation of fibroblasts, stromal cells important for tissue integrity, is limited by space availability. In contrast, proliferation of macrophages, innate immune cells involved in defense, repair, and homeostasis, is constrained by growth factor availability. Examination of density-dependent gene expression in fibroblasts revealed that Hippo and TGF-{beta} target genes are both regulated by cell density. We found YAP1, the transcriptional co-activator of the Hippo signaling pathway, directly regulates expression of Csf1, the lineage-specific growth factor for macrophages, through an enhancer of Csf1 that is specifically active in fibroblasts. Activation of YAP1 in fibroblasts elevates Csf1 expression and is sufficient to increase the number of macrophages at steady state. Our data also suggest that expression programs in fibroblasts that change with density may result from sensing of mechanical force through actin-dependent mechanisms. Altogether, we demonstrate that two different modes of population control are connected and coordinated to regulate cell numbers of distinct cell types. Sensing of the tissue environment may serve as a general strategy to control tissue composition.

Significance StatementCollections of distinct cell types constitute animal tissues. To perform their unique functions, each cell type must exist in the correct number and proportion in a given tissue compartment. However, many of the mechanisms regulating and coordinating cell population sizes remain enigmatic. Our study characterizes two different modes of population size control, utilized by two ubiquitous cell types, macrophages and fibroblasts. Macrophage populations are more sensitive to the presence of growth factors in the environment and fibroblasts are more sensitive to space limitations. Intriguingly, space-sensing mechanisms in fibroblasts directly control the production of growth factor for macrophages and thus macrophage numbers. This link suggests a mechanism by which macrophage compartment size is controlled by stromal cells according to the microenvironment.

category: immunology


title: ATLIGATOR: Editing protein interactions with an atlas-based approach

abstract:
MotivationRecognition of specific molecules by proteins is a fundamental cellular mechanism and relevant for many applications. Being able to modify binding is a key interest and can be achieved by repurposing established interaction motifs. We were specifically interested in a methodology for the design of peptide binding modules. By leveraging interaction data from known protein structures, we plan to accelerate the design of novel protein or peptide binders.

ResultsWe developed ATLIGATOR - a computational method to support the analysis and design of a proteins interaction with a single side chain. Our program enables the building of interaction atlases based on structures from the PDB. From these atlases pocket definitions are extracted that can be searched for frequent interactions. These searches can reveal similarities in unrelated proteins as we show here for one example. Such frequent interactions can then be grafted onto a new protein scaffold as a starting point of the design process. The ATLIGATOR tool is made accessible through a python API as well as a CLI with python scripts.

Availability and ImplementationSource code can be downloaded at github (https://www.github.com/Hoecker-Lab/atligator), installed from PyPI ("atligator") and is implemented in Python 3.


title: RaMP-DB 2.0: a renovated knowledgebase for deriving biological and chemical insight from genes, proteins, and metabolites

abstract: RaMP-DB 2.0 is a web interface, API, relational database and R package designed for straightforward and comprehensive functional interpretation of metabolomic and multi-omic data. Since its first release in 2018, RaMP-DB 2.0 has been upgraded with an expanded breadth and depth of functional and chemical annotation. Content from the source databases (Reactome, HMDB, and Wikipathways) has been updated, and new data types related to metabolite annotations have been incorporated. Structural information incorporated in RaMP-DB 2.0 includes SMILES strings, InChIs, InChIKeys. Chemical classes have been sourced from ClassyFire and LIPID MAPS. Accordingly, the RaMP-DB 2.0 R package has been updated and supports queries on pathways, common reactions, ontologies, chemical classes, and chemical structures. Additionally, RaMP-DB 2.0 now supports enrichment analyses on pathways and chemical classes. Our process for integrating annotations across resources has also been upgraded to lessen the burden of harmonization, thereby supporting more frequent updates. The code used to build all components of RaMP-DB 2.0 is freely available on GitHub at https://github.com/ncats/ramp-db and https://github.com/ncats/RaMP-Backend.


title: Number neurons in the nidopallium of young domestic chicks

abstract:
Numerical cognition is ubiquitous in the animal kingdom. Domestic chicks are a widely used developmental model for studying numerical cognition. Soon after hatching, chicks can perform sophisticated numerical tasks. Nevertheless, the neural basis of their numerical abilities has remained unknown. Here, we describe for the first time number neurons in the caudal nidopallium (functionally equivalent to the mammalian prefrontal cortex) of young domestic chicks. Number neurons that we found in young chicks showed remarkable similarities to those in the prefrontal cortex and caudal nidopallium of adult animals. Thus, our results suggest that numerosity perception based on the labeled-line code provided by number neurons might be an inborn feature of the vertebrate brain.

SignificanceNumerosity, i.e. the number of items in a set, is a significant aspect in the perception of the environment. Behavioural and in silico experiments suggest that number sense belongs to a core knowledge system and can be present already at birth. However, neurons sensitive to the number of visual items have been so far described only in the brain of adult animals. Therefore, it remained unknown to what extent their selectivity would depend on visual learning and experience. We found number neurons in the caudal nidopallium (a higher associative area with functional similarities to the mammalian prefrontal cortex) of very young, numerically naive domestic chicks. This result suggests that numerosity perception is possibly an inborn feature of the vertebrate brain.


title: Recruitment of Corticotropin-releasing Hormone CRH Neurons in response ton Categorically Distinct Stress Challenges in the Mouse Brain

abstract: 1.Corticotropin-releasing hormone (CRH) neurons in the paraventricular hypothalamic nucleus (Pa) are in the position to integrate stress-related information and initiate adaptive neuroendocrine-, autonomic-, metabolic- and behavioral responses. In addition to hypophyseotropic cells, CRH is widely expressed in the CNS, however their involvement in organization of the stress response is not fully understood. In these experiments, we took the advantage of recently available Crh-IRES-Cre; Ai9 mouse line to study the recruitment of hypothalamic and extrahypothalamic CRH neurons in categorically distinct, acute stress reactions. Reporter mice were exposed to restraint, ether, high salt and lipopolisacharide stress. The induced activation of CRH neurons was detected by colocalization of immediate early gene c-Fos in Td tomato expressing cells. We found differential activation of CRH neurons in central amygdaloid nucleus (Ce), bed nucleus stria terminalis lateral division, ventral posterior (BSTLVP), medial preoptic nucleus (MPO), ventromedial hypothalamic nucleus (VMH), premammillary nucleus (PM) and prepositus hypoglossal nucleus (Pr) in response to physiological (ether, high salt and LPS) and psychological (restraint) stressors. CRH positive cells in Pa became activated, however in the Barringtons nucleus and locus coeruleus no actiovation could be observed due to most tested stressors. Furthermore no CRH neuron activation occured in dorsal (BSTLD) and posterior (BSTLP) region of lateral division of bed nucleus stria terminalis after restraint stress. In the inferior olive only ether exposition resulted in CRH neuron activation. These results confirm activation of CRH neurons in the Pa, reveals new subset of stress-related CRH cells through the mouse brain and disprove the recruitment of CRH cells in the SOL and in the Barringtons nucleus to acute psychological stress in mice.


title: Multi-trait selection to build resilience in conifer forests: a case study on spruce-shoot weevil interactions

abstract: Tree planting programs now need to consider climate change increasingly, therefore, the resistance to pests plays an essential role in enabling tree adaptation to new ranges through tree population movement. The weevil Pissodes strobi (Peck) is a major pest of spruces and substantially reduces lumber quality. We revisited a large Interior spruce provenance/progeny trial (2,964 genotypes, 42 families) of varying susceptibility, established in British Columbia. We employed multivariate mixed linear models to estimate covariances between, and genetic control of, juvenile height growth and resistance traits. We performed linear regressions and ordinal logistic regressions to test for impact of parental origin on growth and susceptibility to the pest, respectively. A significant environmental component affected the correlations between resistance and height, with outcomes dependent on families. Parents sourced from above 950 m a.s.l. elevation negatively influenced host resistance to attacks, probably due to higher P. engelmannii proportion. For the genetic contribution of parents sourced from above 1,200 m a.s.l., however, we found less attack severity, probably due to a marked mismatch in phenologies. This clearly highlights that hybrid status might be a good predictor for weevil attacks and delineates the boundaries of successful spruce population movement. Families resulting from crossing susceptible with resistant parents generally showed fast-growing trees were the least affected by weevil attacks. Such results indicate that these "hybrids" might be genetically better equipped with an optimized resource allocation between defence and growth and might provide the solution for concurrent improvement in resistance against weevil attacks, whilst maintaining tree productivity.

category: genetics


title: Genomes of the extinct Sicilian wolf reveal a complex history of isolation and admixture with ancient dogs

abstract:
The Sicilian wolf represented the only population of wolves living on a Mediterranean island until the first half of the twentieth century (1930s-1960s) 1-7. Previous studies hypothesised that they remained isolated from mainland wolves from the end of the Last Glacial Maximum (LGM) 8,9, until human persecutions led them to extinction 1-7.

There are only seven known Sicilian wolf specimens from the 19th and 20th century preserved in museums in Italy and recent morphometric analyses assigned them to the new subspecies Canis lupus cristaldii 10. To better understand the origins of the Sicilian wolf, and its relationship to other wolf populations, we sequenced four whole genomes (3.8x-11.6x) and five mitogenomes. We investigated the relationship between Sicilian wolves and other modern breeds to identify potential admixture. Furthermore, considering that the last land-bridge between Sicily and Italy disappeared after the LGM 11, around 17 kya, we explored the possibility that the Sicilian wolf retained ancestry from ancient wolf and dog lineages. Additionally, we explored whether the long-term isolation might have affected the genomic diversity, inbreeding levels and genetic load of the Sicilian wolf.

Our findings show that the Sicilian wolves shared most ancestry with the modern Italian wolf population but are better modelled as admixed with European dog breeds, and shared traces of Eneolithic and Bronze age European dogs. We also find signatures of severe inbreeding and low genomic diversity at population and individual levels due to long-term isolation and drift, suggesting also low effective population size.

category: genomics


title: Molecular and connectomic vulnerability shape cross-disorder cortical abnormalities

abstract: Numerous brain disorders demonstrate structural brain abnormalities, which are thought to arise from molecular perturbations or connectome miswiring. The unique and shared contributions of these molecular and connectomic vulnerabilities to brain disorders remain unknown, and has yet to be studied in a single multi-disorder framework. Using MRI morphometry from the ENIGMA consortium, we construct maps of cortical abnormalities for thirteen neurodevelopmental, neurological, and psychiatric disorders from N = 21 000 patients and N = 26 000 controls, collected using a harmonized processing protocol. We systematically compare cortical maps to multiple micro-architectural measures, including gene expression, neurotransmitter density, metabolism, and myelination (molecular vulnerability), as well as global connectomic measures including number of connections, centrality, and connection diversity (connectomic vulnerability). We find that regional molecular vulnerability and macroscale brain network architecture interact to drive the spatial patterning of cortical abnormalities in multiple disorders. Local attributes, particularly neurotransmitter receptor profiles, constitute the best predictors of both disorder-specific cortical morphology and cross-disorder similarity. Finally, we find that cross-disorder abnormalities are consistently subtended by a small subset of network epicentres in bilateral sensory-motor, medial temporal lobe, precuneus, and superior parietal cortex. Collectively, our results highlight how local biological attributes and global connectivity jointly shape cross-disorder cortical abnormalities.


title: The evolution of BDNF is defined by strict purifying selection and prodomain spatial coevolution, but what does it mean for human brain disease?

abstract:
The mammalian gene Brain-Derived Neurotrophic Factor (BDNF) is an essential mediator of brain assembly, development, and maturation which has been implicated in a variety of brain disorders such as neurodevelopmental disorders (e.g. autism spectrum disorder), neuropsychiatric disorders (e.g. depression, PTSD, schizophrenia), and neurodegenerative disorders (e.g. Parkinsons). Loss of BDNF during early development is embryonic lethal, and depletion of BDNF during adolescence or adulthood can result in disease-related neuropathology across a broad range of model organisms. In order to better understand the role of BDNF in disease, we seek to provide an evolutionary context to BDNFs role within the brain by elucidating the molecular and genetic comparative history of BDNF across species. We conduct sequence alignment and phylogenetic reconstruction of the BDNF gene across a diverse selection of over 160 mammalian species spanning [~]177 million years of evolution. Selective evolutionary change was examined via several independent computational models of codon evolution including FEL, MEME, and BGM. We report strict purifying selection in the main functional domain of BDNF (NGF domain, essentially comprising the mature BDNF protein). Specifically, we discover 6 sites in our homologous alignment which are under episodic selection in the early regulatory region of BDNF (i.e. the prodomain) and 23 pairs of coevolving sites that are a part of complex spatial relationships that are distributed across the entire BDNF gene. Thus, we propose that our discovery of both local and distal sites of co-evolution within the pro- and mature-domains of BDNF that likely reflect the evolutionary fine-tuning of BDNFs unique and complex regulatory capacities whilst also retaining its core yet diverse ontogenic functionality within the central nervous system. This discovery consequently supports the idea that the BDNF prodomain is more prone to change than the mature domain, however the fact that this region has also been subject to negative purifying selection also highlights genetic sensitivity and thus partially explains the prodomains disease relevance (e.g. Val66Met and other variants) to numerous neuropsychiatric disorders.

HIGHLIGHTSO_LIWe extracted coding sequences for Brain-Derived Neurotrophic Factor (BDNF) from over 160 mammalian genomes that span approximately [~]177 million years of evolution.
C_LIO_LIWe observe strict purifying selection in the main functional domain (NGF) of the BDNF gene in mammals.
C_LIO_LIWe observe novel results with 6 sites in our homologous alignment which are under episodic selection in the early regulatory region of BDNF (i.e. the prodomain).
C_LIO_LIWe observe 23 pairs of coevolving sites within BDNF. Many of which are a part of complex spatial relationships and are distributed across the entire BDNF gene.
C_LIO_LIThese data define exactly how "BDNF is highly conserved" by defining exactly where and how the mammalian BDNF has evolved, confirming the widespread belief that the BDNF prodomain is more prone to change than the mature BDNF protein.
C_LI


title: A proxy measure of striatal dopamine predicts individual differences in temporal precision.

abstract: The perception of time is characterized by pronounced variability across individuals, with implications for a diverse array of psychological functions. The neurocognitive sources of this variability are poorly understood but accumulating evidence suggests a role for inter-individual differences in striatal dopamine levels. Here we present a pre-registered study that tested the predictions that spontaneous eye blink rates, which provide a proxy measure of striatal dopamine availability, would be associated with aberrant interval timing (lower temporal precision or overestimation bias). Neurotypical adults (N=69) underwent resting state eye tracking and completed visual psychophysical interval timing and control tasks. Elevated spontaneous eye blink rates were associated with poorer temporal precision but not with inter-individual differences in perceived duration or performance on the control task. These results signify a role for striatal dopamine in variability in human time perception and can help explain deficient temporal precision in psychiatric populations characterized by elevated dopamine levels.


title: An in vitro neurogenetics platform for precision disease modeling in the mouse

abstract: The mouse is often the model of choice for genetic analysis of neurological disorders, but the introduction of disease mutations into a single inbred strain sometimes fails to yield phenotypes relevant to human disease. Interrogating genetically diverse panels of mice can identify better models of human sensitivity and resistance to candidate disease variants. We developed an in vitro methodology for modeling multiple stages of central nervous system development using a panel of genetically diverse mouse embryonic stem cell lines. Chemical knockdown of the neurodevelopmental gene Dyrk1a demonstrated profound strain differences in the cellular response to the ablation of DYRK1A activity throughout development in vitro. Responsive strains showed in vitro developmental defects consistent with observations in vivo on Dyrk1a knockout mice, and transcriptomic analysis of sensitive and resistant cell strain backgrounds successfully identified key molecular pathways in neural development known to be associated with Dyrk1a haploinsufficiency in vivo. Thus, we demonstrate that high throughput comparative phenotype analysis of differentiated cells from human and genetically diverse mouse pluripotent stem cells bearing disease mutations can provide a facile route to identification of optimal mouse strains for precision disease modeling in vivo.


title: CRISPR-Cas systems in Fusobacterium: An untapped genetic frontier

abstract: Fusobacterium nucleatum has recently received significant attention for its strong connection with the acceleration and gravity of multiple cancers (e.g., colorectal, pancreatic, esophageal). However, our understanding of the molecular mechanisms that drive infection by this  oncomicrobe have been hindered by a lack of universal genetic tools. Herein we report a global bioinformatic identification and characterization of multiple Fusobacterium CRISPR-Cas adaptive immune systems including Cas13c, and detailed report of the proteins, spacer/repeat loci, trans- activating CRISPR RNA (tracrRNA), and CRISPR RNA (cRNA) from a Type II-A CRISPR-Cas9 system. Since most Fusobacterium are currently genetically intractable, this CRISPR-Cas bioinformatic roadmap could be used to build new genome editing and transcriptional tuning tools to characterize an increasingly important genus of human opportunistic-pathogens connected to the onset, progression, and severity of cancer.

category: microbiology


title: Tissue-Specific Control of Ribosomal RNA Synthesis Revealed by Transcription Factor Profiling

abstract:
Ribosomal RNAs (rRNAs) are the most abundant cellular RNAs, and their synthesis from rDNA repeats by RNA Polymerase I accounts for the bulk of all transcription. Despite substantial variation in rRNA transcription rates across cell types, little is known about cell-type-specific factors that bind rDNA and regulate rRNA transcription to meet tissue-specific needs. Using hematopoiesis as a model system, we mapped about 2200 ChIP-Seq datasets for 250 transcription factors (TFs) and chromatin proteins to human and mouse rDNA, and identified robust binding of multiple TF families to canonical TF motifs on rDNA. Using a 47S-FISH-Flow assay developed for nascent rRNA quantification, we demonstrated that targeted degradation of CEBPA (C/EBP alpha), a critical hematopoietic TF with conserved rDNA binding, caused rapid reduction in rRNA transcription due to reduced Pol I occupancy. Our work identifies numerous potential rRNA regulators, and provides a template for dissection of TF roles in rRNA transcription.

HIGHLIGHTSO_LIMultiple cell-type-specific transcription factors (TFs) bind canonical motifs on rDNA.
C_LIO_LIThe hematopoietic TF CEBPA binds to active rDNA alleles at a conserved site.
C_LIO_LICEBPA promotes Polymerase I occupancy and rRNA transcription in myeloid progenitors.
C_LIO_LIWe present  47S-FISH-Flow, a sensitive assay to quantify nascent rRNA.
C_LI

category: molecular biology


title: XPD protects CTCF-Cohesin binding sites from somatic mutagenesis

abstract: Xeroderma pigmentosum group D (XPD) is a DNA helicase involved in transcription initiation and nucleotide excision repair. Missense mutations in XPD are putative drivers in bladder cancer (BLCA) and are associated with a specific single base substitution mutational signature. However, the impact of XPD on the genome-wide distribution of somatic mutations remains unexplored. We analysed somatic mutation distribution in whole-genome sequenced (WGS) BLCA samples with (XPD mutant) and without XPD mutations (WT). XPD genotype had a large impact on the distribution of somatic mutations. XPD mutant samples had increased mutation density at open chromatin, including striking mutation hotspots at CTCF-cohesin binding sites (CBS). We validate these findings in additional WGS cohorts and BLCA exomes. Analysis of XPD occupancy and CBS hotspot mutations in other cancer types suggest that XPD protects CBS from DNA damage. Our study implicates XPD in genomic integrity maintenance at topologically-associating domain boundaries marked by CTCF-cohesin binding.


title: RET activation controlled by MAB21L4-CacyBP interaction drives squamous cell carcinoma

abstract:
Epithelial squamous cell carcinomas (SCC) most commonly originate in the skin, where they display disruptions in the normally tightly regulated homeostatic balance between keratinocyte proliferation and terminal differentiation. We performed a transcriptome-wide screen for genes of unknown function that possess inverse expression patterns in differentiating keratinocytes compared to cutaneous SCC (cSCC) and identified MAB21L4 (C2ORF54) as an enforcer of terminal differentiation that suppresses carcinogenesis. Loss of MAB21L4 in human cSCC organoids enabled malignant transformation through increased expression of the receptor tyrosine kinase rearranged during transfection (RET). In addition to transcriptional upregulation of RET, MAB21L4 deletion preempted recruitment of the CacyBP-Siah1 E3 ligase complex to RET and reduced its ubiquitylation. Both genetic disruption of RET or selective RET inhibition with BLU-667 (pralsetinib) suppressed tumorigenesis in SCC organoids and in vivo tumors while inducing concomitant differentiation. Our results suggest that targeting RET activation is a potential therapeutic strategy for treating SCC.

Statement of SignificanceFew targeted therapies are available to individuals with cSCC who seek or require non-surgical management. Our study demonstrates that downregulation of RET is required for epithelial differentiation and opposes carcinogenesis in cSCC as well as SCC arising from other epithelial tissues.


title: High efficiency multiplex biallelic heritable editing in Arabidopsis using an RNA virus

abstract: Delivery of gene editing components such as the Cas nuclease and single guide RNAs (sgRNAs) into plant cells is commonly accomplished by agrobacterium-mediated transformation. Although Arabidopsis is easy to transform, generation of biallelic edited plants requires screening a large number of plants in subsequent generations. Here, we describe optimization of the Tobacco rattle virus (TRV) for in planta delivery of sgRNAs fused to a tRNAIleu that induces efficient multiplex somatic and biallelic heritable editing in Arabidopsis. Inclusion of tRNAIleu enhances the systemic movement of TRV and the mutant phenotype is visible in the initial TRV::sgRNA-tRNAIleu infected Arabidopsis, which allows for the uncovering of lethal phenotypes. Mutant progeny are recovered in the next generation (M1) at frequencies ranging from 30-60%, with 100% mutant recovery in the following (M2) generation. TRV::tRNAIleu system described here allows generation of biallelic edited plants in a single generation and is amenable for large-scale high throughput CRISPR screens.

category: plant biology


title: Imbalance of Neuregulin1-ErbB2/3 signaling underlies altered myelin homeostasis in models of Charcot-Marie-Tooth disease type 4H

abstract: Charcot Marie Tooth disease (CMT) is one of the most common inherited neurological disorders, affecting either axons from the motor and/or sensory neurons or Schwann cells (SC) of the peripheral nervous system, and caused by more than 100 genes. We previously identified mutations in FGD4, as responsible for CMT4H, an autosomal recessive demyelinating form of CMT. FGD4 encodes FRABIN a GDP/GTP nucleotide exchange factor (GEF), particularly for the small GTPase cdc42. Remarkably, nerves from patients with CMT4H display excessive redundant myelin called outfoldings that arise from focal hypermyelination, suggesting that FRABIN could play a role in the control of PNS myelination. To gain insights into the role of FGD4/FRABIN in SC myelination, we generated a knock-out mouse model, with conditional ablation of fgd4 in SC. We showed that the specific deletion of FRABIN in SCs leads to aberrant myelination in vitro, in dorsal root ganglion (DRG)/SCs cocultures as well in vivo, in distal sciatic nerves. We observed that those myelination defects are related to an upregulation of some interactors of the NRG1 type III/ErbB2/3 signaling pathway, which is known to ensure a proper level of myelination in the PNS. Based on a yeast two-hybrid screen, we identified SNX3 as a new partner of FRABIN, which is involved in the regulation of endocytic trafficking. Interestingly, we showed that loss of FRABIN impairs endocytic trafficking which may contribute to the defective NRG1 type III/ErbB2/3 signaling and myelination. Finally, we showed that the reestablishment of proper levels of the NRG1 type III/ErbB2/3 pathway using Niacin treatment reduces myelin outfoldings in nerves of CMT4H mice. Overall, our work reveals a new role of FRABIN in the regulation of NRG1 type III/ErbB2/3 NRG1signaling and myelination and opens future therapeutic strategies based on the modulation of NRG1 type III/ErbB2/3 NRG1to reduce CMT4H pathology and more generally others demyelinating CMT.


title: PopB-PcrV Interactions are Essential for Pore Formation in the Pseudomonas aeruginosa Type III Secretion System Translocon

abstract: The type III secretion system (T3SS) is a syringe-like virulence factor which delivers bacterial proteins directly into the cytoplasm of host cells. An essential component of the system is the translocon, which creates a pore in the host cell membrane through which proteins are injected. In Pseudomonas aeruginosa, the translocation pore is formed by proteins PopB and PopD and attaches to the T3SS needle via the needle tip protein PcrV. The pore is multimeric, but the exact stoichiometry and structure of the pore are unknown. We took a genetic approach to map contact points within the system by taking advantage of the fact that the translocator proteins of Pseudomonas aeruginosa and the related Aeromonas hydrophila T3SS are incompatible and cannot be freely exchanged. We created chimeric versions of P. aeruginosa PopB and A. hydrophila AopB to intentionally disrupt and restore protein-protein interactions. We identified a chimeric B-translocator that specifically breaks an interaction with the needle tip protein and interferes with the formation of the translocation pore. Breaking the interaction did not disrupt membrane insertion, arguing that the needle tip protein chaperones formation of the translocation pore.


title: An atlas of plant full-length RNA reveals tissue-specific and evolutionarily-conserved regulation of poly(A) tail length

abstract: Introductory paragraphPoly(A) tail is a hallmark of eukaryotic mRNA and its length plays an essential role in regulating mRNA metabolism1-3. However, a comprehensive resource for plant poly(A) tail length has yet to be established. Here, we applied a poly(A)-enrichment-free, Nanopore-based method4,5 to profile full-length RNA with poly(A) tail information in plants. Our atlas contains over 120 million polyadenylated mRNA molecules from seven different tissues of Arabidopsis, as well as the shoot tissue of maize, soybean and rice. In most tissues, the size of plant poly(A) tails shows peaks at approximately 20 and 45 nt, presumably the sizes protected by one and two poly(A) binding proteins (PABP), respectively2,6, while the poly(A) tails in pollen exhibit a distinct pattern with strong peaks centered at 55 and 80 nt. Moreover, poly(A) tail length is regulated in a gene-specific manner -- mRNAs with short half-lives in general have long poly(A) tails, while mRNAs with long half-lives are featured with relatively short poly(A) tails that peak at ~45 nt, suggesting that protection of poly(A) tail in this size by PABP is essential for mRNA stability. Across species, poly(A) tails in the nucleus are almost twice as long as in the cytoplasm, implying a conserved rapid shortening process of poly(A) tail occurs before the mRNA is stabilized in cytoplasm. Our comprehensive dataset lays the groundwork for future functional and evolutionary studies on poly(A) tail length regulation in plants.


title: The Goldilocks Principle conferred by LDH isoenzymes controls murine T cell glycolysis and differentiation

abstract: Isoenzyme divergence is a prevalent mechanism governing tissue-specific and developmental stage-specific metabolism in mammals. The isoenzyme pattern (spectrum) of lactate dehydrogenase (LDH) reflects the status of glucose metabolism in different organs such as muscle, liver, and heart. T cells are highly dependent on glucose metabolism for survival, proliferation, and differentiation. However, the LDH isoenzyme spectrum in T cells and its potential impact on T cell-mediated immune response remain unclear. Here, we discovered that the LDH spectrum in murine T cells is characterized by three tetrameric isoenzymes composed of LDHA and LDHB (LDH-3/4/5). Genetic deletion of LDHA or LDHB altered the isoenzyme spectrum by removing all heterotetramers and leaving T cell with LDH-1 (the homotetramer of LDHB) or LDH-5 (the homotetramer of LDHA), respectively. Accordingly, altering the isoenzyme spectrum by deleting LDHA or LDHB compromises T cell metabolic fitness and effector cell differentiation in vivo. Unexpectedly, deleting LDHA suppressed glycolysis, whereas deleting LDHB further enhanced it, indicating that an optimal zone of glycolytic activity is critical to driving effector T cell differentiation. Mechanistically, the LDH isoenzyme spectrum imposed by LDHA and LDHB is required to optimize glycolysis to maintain a balanced NAD+/NADH pool, a hallmark of metabolic fitness. Together, our results suggest that the LDH isoenzyme spectrum enables "Goldilocks levels" of glycolytic and redox activity (i.e., not too high, not too low, but just right) to control T cell differentiation function.


title: Staphylococcal protein A inhibits IgG-mediated phagocytosis by blocking the interaction of IgGs with FcγRs and FcRn

abstract: Immunoglobulin G molecules are crucial for the human immune response against bacterial infections. IgGs can trigger phagocytosis by innate immune cells, like neutrophils. To do so, IgGs should bind to the bacterial surface via their variable Fab regions and interact with Fc{gamma} receptors (Fc{gamma}Rs) and complement C1 via the constant Fc domain. C1 binding to IgG-labeled bacteria activates the complement cascade, which results in bacterial decoration with C3-derived molecules that are recognized by complement receptors (CRs) on neutrophils. Next to Fc{gamma}Rs and CRs on the membrane, neutrophils also express the intracellular neonatal Fc receptor (FcRn). We previously reported that staphylococcal protein A (SpA), a key immune evasion protein of Staphylococcus aureus, potently blocks IgG-mediated complement activation and killing of S. aureus by interfering with IgG hexamer formation. SpA is also known to block IgG-mediated phagocytosis in absence of complement but the mechanism behind it remains unclear. Here we demonstrate that SpA blocks IgG-mediated phagocytosis and killing of S. aureus through inhibition of the interaction of IgGs with Fc{gamma}Rs (Fc{gamma}RIIa and Fc{gamma}RIIIb, but not Fc{gamma}RI) and FcRn. Furthermore, our data show that multiple SpA domains are needed to effectively block IgG1-mediated phagocytosis. This provides a rationale for the fact that SpA from S. aureus contains four to five repeats. Taken together, our study elucidates the molecular mechanism by which SpA blocks IgG-mediated phagocytosis and supports the idea that next to Fc{gamma}Rs, also the intracellular FcRn receptor is essential for efficient phagocytosis and killing of bacteria by neutrophils.


title: Mutations in TIC100 impair and repair chloroplast protein import and impact retrograde signalling

abstract:
Chloroplast biogenesis requires synthesis of proteins in the nucleocytoplasm and the chloroplast itself. Nucleus-encoded chloroplast proteins are imported via multiprotein translocons in the organelles envelope membranes. Controversy exists around whether a 1 MDa complex comprising TIC20, TIC100 and other proteins constitutes the inner membrane TIC translocon. The Arabidopsis cue8 virescent mutant is broadly defective in plastid development. We identify CUE8 as TIC100. The tic100cue8 mutant accumulates reduced levels of 1 MDa complex components and exhibits reduced import of two nucleus-encoded chloroplast proteins of different import profiles. A search for suppressors of tic100cue8 identified a second mutation within the same gene, tic100soh1, which rescues the visible, 1 MDa complex-subunit abundance, and chloroplast protein import phenotypes. tic100soh1 retains but rapidly exits virescence, and rescues the synthetic lethality of tic100cue8 when retrograde signalling is impaired by the gun1 mutation. Alongside the strong virescence, changes in RNA editing and the presence of unimported precursor proteins show that a strong signalling response is triggered when TIC100 function is altered. Our results are consistent with a role for TIC100, and by extension the 1 MDa complex, in the chloroplast import of photosynthetic and non-photosynthetic proteins, a process which initiates retrograde signalling.

One sentence summaryComplementary mutations in TIC100 of the chloroplast inner envelope membrane cause reductions or corrective improvements in chloroplast protein import, and highlight a signalling role.


title: Structure and Protein-Protein Interactions of Ice Nucleation Proteins Drive Their Activity

abstract: ABSTRACTMicrobially-produced ice nucleating proteins (INpro) are unique molecular structures with the highest known catalytic efficiency for ice formation. Their critical role in rain formation and frost damage of crops together with their diverse commercial applications warrant an in-depth under-standing of their inherent ice nucleation mechanism. We used the machine-learning based software Al-phaFold to develop the first ab initio structural model of a bacterial INpro which is a novel beta-helix structure consisting of repeated stacks of two beta strands connected by two sharp turns. Using the synchrotron radiation circular dichroism, we validated the {beta}-strand content of the model. Combining functional studies of purified recombinant INpro, electron microscopy and modeling, we further demonstrate that the formation of dimers and higher-order oligomers is key to INpro activity. This work presents a major advance in understanding the molecular foundation for bacterial ice-nucleation activity and the basis for investigating the mechanistic role of INpro-induced ice formation in the atmosphere, and for commercial design and production of ice-nucleating particles for industrial applications.


title: Visualizing Synaptic Dopamine Efflux with a 2D Nanofilm

abstract: Chemical neurotransmission constitutes one of the fundamental modalities of communication between neurons. Monitoring release of these chemicals has traditionally been difficult to carry out at spatial and temporal scales relevant to neuron function. To understand chemical neurotransmission more fully, we need to improve the spatial and temporal resolutions of measurements for neurotransmitter release. To address this, we engineered a chemi-sensitive, two-dimensional nanofilm that facilitates subcellular visualization of the release and diffusion of the neurochemical dopamine with synaptic resolution, quantal sensitivity, and simultaneously from hundreds of release sites. Using this technology, we were able to monitor the spatiotemporal dynamics of dopamine release in dendritic processes, a poorly understood phenomenon. We found that dopamine release is broadcast from a subset of dendritic processes as hotspots that have a mean spatial spread of {approx}3.2 {micro}m (full width at half maximum) and are observed with a mean spatial frequency of 1 hotspot per {approx}7.5 {micro}m of dendritic length. Major dendrites of dopamine neurons and fine dendritic processes, as well as dendritic arbors and dendrites with no apparent varicose morphology participated in dopamine release. Remarkably, these release hotspots colocalized with Bassoon, suggesting that Bassoon may contribute to organizing active zones in dendrites, similar to its role in axon terminals.


title: Automated assessment reveals extinction risk of reptiles is widely underestimated across space and phylogeny

abstract: The Red List of Threatened Species, published by the International Union for Conservation of Nature (IUCN), is a crucial tool for conservation decision making. However, despite substantial effort, numerous species remain unassessed, or have insufficient data available to be assigned a Red List threat category. Moreover, the Red Listing process is subject to various sources of uncertainty and bias. The development of robust automated assessment methods could serve as an efficient and highly useful tool to accelerate the assessment process and offer provisional assessments. Here we aimed to: 1) present a machine learning based automated threat assessment method that can be used on less known species; 2) offer provisional assessments for all reptiles - the only major tetrapod group without a comprehensive Red List assessment; and 3) evaluate potential effects of human decision biases on the outcome of assessments. We use the method presented here to assess 4,369 reptile species that are currently unassessed or classified as Data Deficient by the IUCN. Our models range in accuracy from 88% to 93% for classifying species as threatened/non-threatened, and from 82% to 87% for predicting specific threat categories. Unassessed and Data Deficient reptiles were more likely to be threatened than assessed species, adding to mounting evidence that they should be considered threatened by default. The overall proportion of threatened species greatly increased when we included our provisional assessments. Assessor identities strongly affected prediction outcomes, suggesting that assessor effects need to be carefully considered in extinction risk assessments. Regions and taxa we identified as likely to be more threatened should be given increased attention in new assessments and conservation planning. Lastly, the method we present here can be easily implemented to help bridge the assessment gap on other less known taxa.

category: ecology


title: mRNA expression explains metabolic and thermal physiology

abstract:
Quantifying mRNA expression, which is heritable and physiologically inducible, reveals biologically important networks and pathways underlying complex traits. Here, we quantify mRNA expression in Fundulus heteroclitus, a small teleost fish, among three populations acclimated to 12{degrees}C and 28{degrees}C and relate it to variation in six, complex, physiological traits (whole animal metabolism (WAM), critical thermal maximum (CTmax), and four substrate specific cardiac metabolic rates (CaM)). Although 366 heart mRNAs and 528 brain mRNAs had significant differential expression between the two acclimation temperatures, none of the mRNA acclimation responses were shared across all three populations in any tissue. Yet, within an acclimation temperature across all three populations, weighted gene co-expression network analyses show that mRNA expression patterns explained WAM, CTmax, and CaM trait variation. These analyses revealed 9 significant heart MEs (first principal component of module expression) and 4 significant brain MEs. Heart MEs explained variation in WAM, CTmax, and two of the four substrate specific cardiac metabolic rates at 12{degrees}C, and CTmax at 28C. In contrast, brain MEs explained CTmax and WAM at 28{degrees}C but not at 12{degrees}C. Combining MEs as multiple correlations, 82% of variation in WAM at 12{degrees}C was explained by four heart MEs, 80% of variation in fatty-acid CaM at 12{degrees}C was explained by three heart MEs, and 72% of variation in CTmax at 28{degrees}C was explained by three brain MEs. These MEs were enriched for Kyoto Encyclopedia of Genes and Genomes (KEGG) terms related to specific metabolic pathways, suggesting that they represent biologically relevant pathways. Together these data suggest that mRNA co-expression explains complex traits; moreover, physiological traits are more reliant on heart expression at 12{degrees}C and brain expression at 28{degrees}C.

Author SummaryDespite an abundance of genomic data, the molecular and genetic underpinnings of complex traits remain poorly understood. To better understand the molecular basis of complex traits, we used heart and brain mRNA expression to explain complex traits- physiological responses to temperature- in individuals collected from three saltmarsh fish (Fundulus heteroclitus) populations acclimated to 12{degrees}C and 28{degrees}C. We found that while physiological traits did not differ among populations, the mRNAs important for acclimation responses were >88% unique to a single population and differed between heart and brain tissues. We also found tissue specific co-expressed mRNAs that explain up to 82% of complex traits including whole animal metabolism, upper thermal tolerance, and substrate specific cardiac metabolism measured at 12{degrees}C or 28{degrees}C acclimation conditions. Notably, sets of co-expressed mRNAs related to these traits are enriched for molecular pathways affecting metabolism, giving insight into the molecular underpinnings of these traits.


title: AbLang: An antibody language model for completing antibody sequences

abstract:
MotivationGeneral protein language models have been shown to summarise the semantics of protein sequences into representations that are useful for state-of-the-art predictive methods. However, for antibody specific problems, such as restoring residues lost due to sequencing errors, a model trained solely on antibodies may be more powerful. Antibodies are one of the few protein types where the volume of sequence data needed for such language models is available, for example in the Observed Antibody Space (OAS) database.

ResultsHere, we introduce AbLang, a language model trained on the antibody sequences in the OAS database. We demonstrate the power of AbLang by using it to restore missing residues in antibody sequence data, a key issue with B-cell receptor repertoire sequencing, over 40% of OAS sequences are missing the first 15 amino acids. AbLang restores the missing residues of antibody sequences better than using IMGT germlines or the general protein language model ESM-1b. Further, AbLang does not require knowledge of the germline of the antibody and is seven times faster than ESM-1b.

Availability and ImplementationAbLang is a python package available at https://github.com/oxpig/AbLang.


title: Meta-analysis of Microbiome Association Networks Reveal Patterns of Dysbiosis in Diseased Microbiomes

abstract: The human gut microbiome is composed of a diverse and dynamic population of microbial species which play key roles in modulating host health and physiology. While individual microbial species have been found to be associated with certain disease states, increasing evidence suggests that higher-order microbial interactions may have an equal or greater contribution to host fitness. To better understand microbial community dynamics, we utilize complex networks to study interactions through a meta-analysis of microbial association networks between healthy and disease gut microbiomes. Taking advantage of the large number of metagenomes derived from healthy individuals and patients with various diseases, together with recent advances in network inference that can deal with sparse compositional data, we inferred microbial association networks based on co-occurrence of gut microbial species and made the networks publicly available as a resource (github repository named GutNet). Through our meta-analysis of inferred networks, we were able to identify network-associated features that help stratify between healthy and disease states such as the differentiation of various bacterial phyla and enrichment of Proteobacteria interactions in diseased networks. Additionally, our findings show that the contributions of taxa in microbial associations are disproportionate to their abundances and that rarer taxa of microbial species play an integral part in shaping dynamics of microbial community interactions. Overall, this meta-analysis revealed valuable insights into microbial community dynamics between healthy and disease phenotypes.


title: Framework for Denoising Monte Carlo Photon Transport Simulations Using Deep Learning

abstract:
SignificanceThe Monte Carlo (MC) method is widely used as the gold-standard for modeling light propagation inside turbid media like human tissues, but combating its inherent stochastic noise requires one to simulate large number photons, resulting in high computational burdens.

AimWe aim to develop an effective image denoising technique using deep learning (DL) to dramatically improve low-photon MC simulation result quality, equivalently bringing further acceleration to the MC method.

ApproachWe have developed a cascade-network combining DnCNN with UNet, in the meantime, extended a range of established image denoising neural-network architectures, including DnCNN, UNet, DRUNet, and ResMCNet, in handling three-dimensional (3-D) MC data and compared their performances against model-based denoising algorithms. We have also developed a simple yet effective approach to create synthetic datasets that can be used to train DL based MC denoisers.

ResultsOverall, DL based image denoising algorithms exhibit significantly higher image quality improvements over traditional model-based denoising algorithms. Among the tested DL denoisiers, our Cascade network yields a 14 - 19 dB improvement in signal-noise ratio (SNR), which is equivalent to simulating 25 x to 78 x more photons. Other DL-based methods yielded similar results, with our method performing noticeably better with low-photon inputs, and ResMCNet along with DRUNet performing better with high-photon inputs. Our Cascade network achieved the highest quality when denoising complex domains, including brain and mouse atlases.

ConclusionIncorporating state-of-the-art DL denoising techniques can equivalently reduce the computation time of MC simulations by one to two orders of magnitude. Our open-source MC denoising codes and data can be freely accessed at http://mcx.space/.

category: biophysics


title: Endogenous 1-deoxysphingolipid synthesis compromises anchorage-independent growth and plasma membrane endocytosis in cancer cells

abstract: Serine palmitoyltransferase (SPT) predominantly incorporates serine and fatty acyl-CoAs into diverse sphingolipids that serve as structural components of membranes and signaling molecules within or amongst cells. However, SPT also uses alanine as a substrate in the contexts of low serine availability, alanine accumulation, or disease-causing mutations in hereditary sensory neuropathy type I (HSAN1), resulting in the synthesis and accumulation of 1-deoxysphingolipids. These species promote cytotoxicity in neurons and impact diverse cellular phenotypes, including suppression of anchorage-independent cancer cell growth. While altered serine and alanine can promote 1-deoxysphingolipid synthesis, they impact numerous other metabolic pathways important for cancer cells. Here we combined isotope tracing, quantitative metabolomics, and functional studies to better understand the mechanistic drivers of 1-deoxysphingolipid toxicity in cancer cells. Both alanine treatment and SPTLC1C133W expression induce 1-deoxy(dihydro)ceramide synthesis and accumulation but fail to broadly impact the metabolism or growth of adherent cells. However, spheroid culture and soft agar colony formation were compromised when endogenous 1-deoxysphingolipid synthesis was induced. Consistent with these impacts on anchorage-independent cell growth, we observed that 1-deoxysphingolipid synthesis reduced plasma membrane endocytosis. These results highlight a potential role for SPT promiscuity in linking altered amino acid metabolism to plasma membrane endocytosis.


title: Epigenetic anti-cancer treatment with a stabilized carbocyclic Decitabine analogue

abstract: 5-Aza-2-deoxycytidine (Decitabine, AzadC) is a nucleoside analogue, which is in clinical use to treat patients with myelodysplastic syndrome or acute myeloid leukemia. Its mode of action is unusual because the compound is one of the few drugs that act at the epigenetic level of the genetic code. AzadC is incorporated as an antimetabolite into the genome and creates covalent, inhibitory links to DNA methyltransferases (DNMTs) that methylate 2-deoxycytidine (dC) to 5-methyl-dC (mdC). Consequently, AzadC treatment leads to a global loss of mdC, which presumably results in a reactivation of silenced genes, among them tumor suppressor and DNA damage response genes. Because AzadC suffers from severe instability, which limits its use in the clinic, a more sophisticated AzadC derivative would be highly valuable. Here, we report that a recently developed carbocyclic AzadC analogue (cAzadC) blocks DNMT1 in the AML cell line MOLM-13 as efficient as AzadC. Moreover, cAzadC has a surprisingly strong anti-proliferative effect and leads to a significantly higher number of double strand breaks compared to AzadC, while showing less off-target toxicity. These results show that cAzadC triggers more deleterious repair and apoptotic pathways in cancer cells than AzadC, which makes cAzadC a promising next generation epigenetic drug.


title: Hyperglycemia in type 2 diabetes: physiological and clinical implications of a brain centered model.

abstract: The hyperglycemia of type 2 diabetes has been classically believed to be a result of insulin resistance and relative insulin deficiency. However, the unexpected outcomes of insulin receptor knockout and insulin suppression experiments and the unexplained patterns in clinical data have exposed the limitations of the peripheral regulation models. Absence of fasting hyperglycemia by insulin receptor knockouts or insulin suppression, evidence for hyperinsulinemia preceding insulin resistance, the perplexing hyperinsulinemic normoglycemic state, reduced glucose transport to the brain preceding hyperglycemia, absent or poor correlation between fasting glucose and insulin, very strong positive correlation between indices of insulin resistance and {beta} cell function in population data are some of the anomalous findings which glucose homeostasis models have not addressed so far. On the other hand the increasing evidence of central neuronal mechanisms of glucose regulation necessitates incorporation of brain glucose regulation in the models. Although models considering brain glucose regulation have been suggested, their multiple physiological and clinical implications have not been thoroughly examined. Based on updated evidence, we propose a refined model of glucose regulation that considers brain glucose levels as the ultimate target of homeostasis and combines central and peripheral mechanisms of regulation. In this model, considering reduced rate of blood to brain transmission of glucose and insulin as primary pathology explains most of the patterns including apparent anomalies with or without including insulin resistance. A brain centered model accounts for the limited and inconsistent success of glucose normalization in effectively reducing diabetic complications and mortality. A serious attempt to reevaluate alternative models is required since the brain centered model implies radical changes in the target and the course of diabetes treatment.

category: physiology


title: Combined multiple transcriptional repression mechanisms generate ultrasensitivity and oscillations

abstract: Transcriptional repression can occur via various mechanisms, such as blocking, sequestration, and displacement. For instance, the repressors can hold the activators to prevent binding with DNA or can bind to the DNA-bound activators to block their transcriptional activity. Although the transcription can be completely suppressed with a single mechanism, multiple repression mechanisms are utilized together to inhibit transcriptional activators in many systems, such as circadian clocks and NF-{kappa}B oscillators. This raises the question of what advantages arise if seemingly redundant repression mechanisms are combined. Here, by deriving equations describing the multiple repression mechanisms, we find that their combination can synergistically generate a sharply ultrasensitive transcription response and thus strong oscillations. This rationalizes why the multiple repression mechanisms are used together in various biological oscillators. The critical role of such combined transcriptional repression for strong oscillations is further supported by our analysis of formerly identified mutations disrupting the transcriptional repression of the mammalian circadian clock. The hitherto unrecognized source of the ultrasensitivity, the combined transcriptional repressions, can lead to robust synthetic oscillators with a previously unachievable simple design.

category: systems biology


title: Dopamine and ALK4 signaling synergize to induce PCBP1-mediated alternative splicing of FosB and sustained behavioral sensitization to cocaine

abstract: {Delta}FosB, an alternative spliced product of FosB, is an essential component of dopamine-induced reward pathways and a master switch for addiction. However, the molecular mechanisms of its generation and regulation by dopamine signaling are unknown. Here we report that dopamine D1 receptor signaling synergizes with the activin/ALK4/Smad3 pathway to potentiate the generation of {Delta}FosB mRNA in medium spiny neurons (MSNs) of the nucleus-accumbens (NAc) through activation of the RNA binding protein PCBP1, a regulator of mRNA splicing. Concurrent activation of PCBP1 and Smad3 by D1 and ALK4 signaling induced their interaction, nuclear translocation, and binding to sequences in exon-4 and intron-4 of FosB mRNA. Ablation of either ALK4 or PCBP1 in MSNs impaired {Delta}FosB mRNA induction and nuclear translocation of {Delta}FosB protein in response to repeated co-stimulation of D1 and ALK4 receptors. Importantly, ALK4 was required in NAc MSNs of adult mice for behavioral sensitization to cocaine. These findings uncover an unexpected mechanism for {Delta}FosB generation and drug-induced sensitization through convergent dopamine and ALK4 signaling.


title: Wearing an Eye Mask During Overnight Sleep Improves Episodic Learning and Alertness

abstract:
Ambient light can influence sleep structure and timing. We explored how wearing an eye-mask to block light during overnight sleep impacts on memory and alertness, changes that could benefit everyday tasks like studying or driving. In Experiment 1, ninety-four 18-35-year-olds wore an eye-mask while they slept every night for a week and underwent a control condition in which light was not blocked for another week. Five habituation nights were followed by a cognitive battery on the sixth and seventh days. This revealed superior episodic encoding and an improvement on alertness when using the mask. In Experiment 2, thirty-five 18-35-year-olds used a wearable device to monitor sleep with and without the mask. This replicated the encoding benefit and showed that it was predicted by time spent in slow wave sleep. Our findings suggest that wearing an eye-mask during overnight sleep can improve episodic encoding and alertness the next day.

Statement of relevanceSleep is crucial for alertness and for preparing the human brain to encode new information. However, it can be disrupted by external stimuli such as light or sounds. This study explored wearing an eye mask as a potential cognitive enhancer which protects overnight sleep by blocking ambient light. We found that wearing a mask increased alertness and facilitated the encoding of novel information the next day. Furthermore, the benefit to memory was predicted by time spent in slow wave sleep while wearing the mask. This suggests wearing an eye mask during sleep is an effective, economical, and non-invasive behaviour that could benefit cognitive function and lead to measurable impacts on every-day life.


title: Characterization of second-order mixing effects in reconstructed cross-spectra of random neural fields

abstract: Functional connectivity in electroencephalography (EEG) and magnetoencephalography (MEG) data is commonly assessed by using measures that are insensitive to instantaneously interacting sources and as such would not give rise to false positive interactions caused by instantaneous mixing of true source signals (first-order mixing). Recent studies, however, have drawn attention to the fact that such measures are still susceptible to instantaneous mixing from lagged sources (i.e. second-order mixing) and that this can lead to a large number of false positive interactions. In this study we relate first- and second-order mixing effects on the cross-spectra of reconstructed source activity to the properties of the resolution operators that are used for the reconstruction. We derive two identities that relate first- and second-order mixing effects to the transformation properties of measurement and source configurations and exploit them to establish several basic properties of signal mixing. First, we provide a characterization of the configurations that are maximally and minimally sensitive to second-order mixing. It turns out that second-order mixing effects are maximal when the measurement locations are far apart and the sources coincide with the measurement locations. Second, we provide a description of second-order mixing effects in the vicinity of the measurement locations in terms of the local geometry of the point-spread functions of the resolution operator. Third, we derive a version of Lagranges identity for cross-talk functions that establishes the existence of a trade-off between the magnitude of first- and second-order mixing effects. It also shows that, whereas the magnitude of first-order mixing is determined by the inner product of cross-talk functions, the magnitude of second-order mixing is determined by a generalized cross-product of cross-talk functions (the wedge product) which leads to an intuitive geometric understanding of the trade-off. All results are derived within the general framework of random neural fields on cortical manifolds.


title: Selective activation of subthalamic nucleus output quantitatively scales movements

abstract: The subthalamic nucleus (STN), a diencephalic nucleus strongly connected with the basal ganglia, is a common target for deep brain stimulation (DBS) treatments of Parkinsonian motor symptoms. The STN is thought to suppress movement by enhancing inhibitory basal ganglia output via the indirect pathway, and disrupting STN output using DBS can restore movement in Parkinsons patients. However, previous studies on STN DBS usually relied on electrical stimulation, which cannot selectively target STN output neurons. Moreover, most studies did not measure behavior precisely during STN manipulations. Here we selectively stimulated STN projection neurons, by expressing channelrhodopsin in vesicular glutamate transporter 2 (VGlut2)-positive projection neurons in the STN. We also quantified behavior in freely moving male mice with high spatial and temporal resolution using 3D motion capture at 200 frames per second. We found STN stimulation resulted in movements with very short latencies (10-15 ms). Unilateral stimulation quantitatively determines orientation, head yaw, and head roll consistently in the ipsiversive direction, toward thee side of stimulation. On the other hand, head raising (increased head pitch) was observed after stimulation on either side. Strikingly, a single pulse of light was sufficient to generate movement, and there was a highly linear relationship between stimulation frequency and kinematics. These results question the common assumption that STN suppresses movement; instead they suggest that STN output can precisely specific action parameters via direct projections to brainstem regions.


title: A Population Response Model of Ensemble Coding

abstract: Ensemble representations have been considered as one of strategies that the visual system adopts to cope with its limited capacity. Thus, they include various statistical summaries such as mean, variance, and distributional properties and are formed over many stages of visual processing. The current study proposes a population coding model of ensemble perception to provide a theoretical and computational framework for these various facets of ensemble perception. The proposed model consists of a simple feature layer and a pooling layer. We assumed ensemble representations as population responses in the pooling layer and decoded various statistical properties from population responses. Our model successfully predicted averaging performance in orientation, size, color, and motion direction across different tasks. Furthermore, it predicted variance discrimination performance and the priming effects of feature distributions. Finally, it explained the well-known variance and set size effects and has a potential for explaining the adaptation and clustering effects.


title: Sex differences in predictors and regional patterns of brain-age-gap estimates

abstract:
BackgroundThe brain-age-gap estimate (brainAGE) quantifies the difference between chronological age and age predicted by applying machine-learning models to neuroimaging data, and is considered a biomarker of brain health. Understanding sex-differences in brainAGE is a significant step toward precision medicine.

MethodsGlobal and local brainAGE (G-brainAGE and L-brainAGE, respectively) were computed by applying machine learning algorithms to brain structural magnetic resonance imaging data from 1113 healthy young adults (54.45% females; age range: 22-37 years) participating in the Human Connectome Project. Sex-differences were determined in G-brainAGE and L-brainAGE. Random forest regression was used to determine sex-specific associations between G-brainAGE and non-imaging measures pertaining to sociodemographic characteristics and mental, physical, and cognitive functions.

ResultsL-brainAGE showed sex-specific differences in brain ageing. In females, compared to males, L-brainAGE was higher in the cerebellum and brainstem and lower in the prefrontal cortex and insula. Although sex-differences in G-brainAGE were minimal, associations between G-brainAGE and non-imaging measures differed between sexes with the exception for poor sleep quality, which was common to both. The most important predictor of higher G-brainAGE was non-white race in males and systolic blood pressure in females.

ConclusionsThe results demonstrate the value of applying sex-specific analyses and machine learning methods to advance our understanding of sex-related differences in factors that influence the rate of brain ageing and provide a foundation for targeted interventions.


title: Network architecture producing swing to stance transitions in an insect walking system

abstract: The walking system of the stick insect is one of the most thoroughly described invertebrate systems. We know a lot about the role of sensory input in the control of stepping of a single leg. However, the neuronal organization and connectivity of the central neural networks underlying the rhythmic activation and coordination of leg muscles still remain elusive. It is assumed that these networks can couple in the absence of phasic sensory input due to the observation of spontaneous recurrent patterns (SRPs) of coordinated motor activity equivalent to fictive stepping-phase transitions. Here we sought to quantify the phase of motor activity within SRPs in the isolated and interconnected meso- and metathoracic ganglia. We show that SRPs occur not only in the meso-, but also in the metathoracic ganglia of the stick insect, discovering a qualitative difference between them. We construct a network based on neurophysiological data capable of reproducing the measured SRP phases to investigate this difference. By comparing network output to the biological measurements we confirm the plausibility of the architecture and provide a hypothesis to account for these qualitative differences. The neural architecture we present couples individual central pattern generators to reproduce the fictive stepping-phase transitions observed in deafferented stick insect preparations after pharmacological activation, providing insights into the neural architecture underlying coordinated locomotion.


title: Brainstem somatostatin-expressing cells control the emotional regulation of pain behavior

abstract: In mammals, threat-related behavior is typically induced by a noxious physical stressor and is associated with a broad range of behavioral responses such as freezing and avoidance. These behavioral responses are associated with the regulation of pain responses allowing individuals to cope with noxious stimuli. Whereas the structures and mechanisms involved in pain behavior are well documented, little is known about the precise neuronal circuits mediating the emotional regulation of pain behavior. Here we used a combination of behavioral, anatomical, optogenetic, and electrophysiological approaches to show that somatostatin-expressing neurons in the ventrolateral periaqueductal gray matter (vlPAG SST cells) promote antinociceptive responses during the presentation of conditioned stimuli (CS) predicting footshocks. Whereas the optogenetic inhibition of vlPAG SST cells during CS presentation promoted analgesia, their optogenetic activation reduced analgesia by potentiating pain responses in the spinal cord through a relay in the rostral ventromedial medulla (RVM). Together these results identify a brainstem circuit composed of vlPAG SST cells specifically projecting to the RVM and mediating fear conditioned analgesia (FCA) to regulate pain responses during threatful situations.


title: Parallels of quantum superposition in ecological models: from counterintuitive patterns to eco-evolutionary interpretations of cryptic species

abstract: Superposition, i.e. the ability of a particle (electron, photon) to occur in different states or positions simultaneously, is a hallmark in the subatomic world of quantum mechanics but non-sensical from the perspective of macro-systems such as ecosystems and other complex systems of people and nature. Using time series and spatial analysis of bird, phytoplankton and benthic invertebrate communities, this paper shows that superposition can occur analogously in redundancy analysis (RDA), a form of canonical ordination frequently used by ecologists. Specifically, we used correlation analysis to show that species can be associated simultaneously with different orthogonal axes in RDA models, a pattern reminiscent of superposition. We discuss this counterintuitive result in relation to the statistical and mathematical features of RDA and the recognized limitations with current traditional species concepts based on vegetative morphology. We suggest that such "quantum weirdness" is reconcilable with classical ecosystems logic when the focus of research shifts from morphological species to cryptic species that consist of genetically and ecologically differentiated subpopulations. We support our argument with theoretical discussions of eco-evolutionary interpretations that should become testable once suitable data are available.


title: Trophic ecology of deep-sea megafauna in the ultra-oligotrophic Southeastern Mediterranean Sea

abstract: The trophic ecology of fourteen species of bathybenthic and bathypelagic fishes and six species of bathybenthic decapod crustaceans from the continental slope and rise of the Southeastern Mediterranean Sea (SEMS) was examined using stable isotope analysis. Mean {delta}13C values among fish species varied by more than 4.0{per thousand}, from -20.85{per thousand} (Macroramphosus scolopax) to -16.57{per thousand} (Conger conger and Centrophorus granulosus), and increased as a function of depth (200 - 1400 m). Mean {delta}13C values of the crustaceans showed smaller variation, between -16.38{per thousand} (Polycheles typhlops) and -18.50{per thousand} (Aristeus antennatus). This suggests a shift from pelagic to regenerated benthic carbon sources with depth. Benthic carbon regeneration is further supported by the low benthic-pelagic POM-{delta}13C values, averaging -24.7 {+/-} 1.2{per thousand}, and the mixing model results, presenting very low contribution of epipelagic POM to the bathyal fauna. Mean {delta}15N values of fish and crustacean species ranged 7.91 {+/-} 0.36{per thousand} to 11.36 {+/-} 0.39{per thousand} and 6.15 {+/-} 0.31{per thousand} to 7.69 {+/-} 0.37{per thousand}, respectively, resulting in trophic position estimates, occupying the third and the fourth trophic levels. Thus, despite the proximity to the more productive areas of the shallow shelf, low number of trophic levels (TL~1.0) and narrow isotopic niche breadths (SEAc <1) were observed for bathybenthic crustaceans (TL = 3.62 {+/-} 0.22) and bathypelagic fishes (TL = 4.33 {+/-} 0.34) in the study area - probably due to the ultra-oligotrophic state of the SEMS resulting in limited carbon sources. Our results, which provide the first trophic description of deep-sea megafauna in the SEMS, offer insight into the carbon sources and food web structure of deep-sea ecosystems in oligotrophic marginal seas, and can be further used in ecological modeling and support the sustainable management of marine resources in the deep Levantine Sea.


title: Complex genetics cause and constrain fungal persistence in different parts of the mammalian body

abstract: Determining how genetic polymorphisms enable certain fungi to persist in mammalian hosts can improve understanding of opportunistic fungal pathogenesis, a source of substantial human morbidity and mortality. We examined the genetic basis of fungal persistence in mice using a cross between a clinical isolate and the lab reference strain of the budding yeast Saccharomyces cerevisiae. Employing chromosomally-encoded barcodes, we tracked the relative abundances of 822 genotyped, haploid segregants in multiple organs over time and performed linkage mapping of their persistence in hosts. Detected loci showed a mix of general and antagonistically pleiotropic effects across organs. General loci showed similar effects across all organs, while antagonistically pleiotropic loci showed contrasting effects in the brain and the kidneys, liver, and spleen. Persistence in an organ required both generally beneficial alleles and organ-appropriate pleiotropic alleles. This genetic architecture resulted in many segregants persisting in the brain or in non-brain organs, but few segregants persisting in all organs. These results show complex combinations of genetic polymorphisms collectively cause and constrain fungal persistence in different parts of the mammalian body.


title: A quantitative, genome-wide analysis in Drosophila reveals transposable elements' influence on gene expression is species-specific

abstract: Transposable elements (TEs) are parasitic DNA sequences that are able to move and multiply along the chromosomes of all genomes. They are controlled by the host through the targeting of silencing epigenetic marks, which may affect the chromatin structure of neighboring sequences, including genes. In this study, we used transcriptomic and epigenomic high-throughput data produced from ovarian samples of Drosophila melanogaster and Drosophila simulans wild-type strains, in order to finely quantify the influence of TE insertions on gene RNA levels and histone marks (H3K4me3 and H3K9me3). We find general, negative impacts of TE insertions on gene RNA levels and H3K4me3 enrichment, and global, positive effects on H3K9me3 enrichment. However, we also uncover that TE insertions within exons are associated with a reduction in H3K9me3, which we propose is associated with the removal of TE sequences from the transcript through splicing. Overall, we find that gene RNA and histone mark levels show contrasted dependencies on TE insertions regarding the species. The fold-decrease in TE-carrying gene proportions between extreme expression classes is 2.6 in D. melanogaster and 1.8 in D. simulans, while it is strongly contrasted between extreme classes of H3K4me3 enrichment: 4.4 in D. melanogaster and 19.2 in D. simulans. This provides a new light on the considerable natural variability provided by TEs, which may be associated with contrasted adaptive and evolutionary potentials.


title: Automatically tracking feeding behavior in populations of foraging worms

abstract: C. elegans feeds on bacteria and other small microorganisms which it ingests using its pharynx, a neuromuscular pump. Currently, measuring feeding behavior requires tracking a single animal, indirectly estimating food intake from population-level metrics, or using restrained animals. Therefore, to enable large throughput feeding measurements of unrestrained, crawling worms on agarose plates, we developed an imaging protocol and a complementary image analysis tool called PharaGlow. We image up to 50 freely moving worms simultaneously and extract locomotion and feeding behaviors. Our tool reliably detects pharyngeal pumping in adult worms with a maximum deviation of 5% in the number of pumps compared to an expert annotator. We demonstrate the tools robustness and high-throughput capabilities by measuring feeding in different use-case scenarios. This includes tracing pharyngeal dynamics during development, revealing their highly conserved nature throughout all life cycle stages. We also observed pumping after food deprivation, corroborating previous studies in which starvation time strongly influences pumping. Finally, we further validated our behavioral tracker by exploring two previously characterized pumping defective mutants: unc-31 and eat-18. Remarkably, our analysis of eat-18 mutants identified unreported defects in pumping and overall locomotion regulation, highlighting the potential of this toolkit. Pharaglow therefore enables the observation and analysis of the temporal dynamics of food intake with high-throughput and precision in a user-friendly system.

category: animal behavior and cognition


title: Understanding immune-driven brain aging by human brain organoid microphysiological analysis platform

abstract: The aging of the immune system drives systemic aging and the pathogenesis of age-related diseases. However, a significant knowledge gap remains in understanding immune-driven aging, especially in brain aging, due to the limited current in vitro models of neuro-immune interaction. Here we report the development of a human brain organoid microphysiological analysis platform (MAP) to discover the dynamic process of immune-driven brain aging. We create the organoid MAP by 3D printing that can confine organoid growth and perfuse oxygen and nutrients (and immune cells) to generate standardized human cortical organoids that promote viability, maturation, and commitment to human forebrain identity. Dynamic rocking flow is incorporated for the platform that allows us to perfuse primary monocytes from young (20 to 30-year-old) and aged (>60-year-old) donors and culture human cortical organoids for modeling and analyzing the aged immune cell interacting organoid tissues systematically. We discovered the aged monocytes had increased infiltration and promoted the expression of aging-related markers (e.g., p16 in astrocytes neighboring to monocytes) within human cortical organoids, indicating that aged monocytes may drive brain aging. We believe that our human brain organoid MAP provides promising solutions for basic research and translational applications in aging, neuroimmunological diseases, autoimmune disorders, and cancers.

category: bioengineering


title: Organ Scaffold Characterizations Using Intravital Microscopy

abstract:
This study contains intravital microscopy (IVM) data to characterize organ scaffolds created using decellularization. Decellularization creates cell-free collagen-based matrices from native organs, which can be used as scaffolds for regenerative medicine applications. This data set contains in vivo assays evaluating the effectiveness of decellularization and structural and functional integrity of the acellular nephron in the post-transplantation environment. Qualitative and quantitative assessments of scaffold DNA concentrations, tissue fluorescence signals, structural and functional integrities of various decellularized nephron segments, and velocity within the microcirculation were acquired and compared to the native (non-transplanted) organ. Cohorts of 2-3-month-old male Sprague Dawley rats were used: non-transplanted (n = 4), transplanted day 0 (n=4), transplanted day 1 (n = 4), transplanted day 2 (n = 4), and transplanted day 7 (n = 4). OIF formatted files illustrate IVM measurement processes and are made publicly available in a data repository. Such data is intended to support scientific reproducibility, complement future renal studies, and extend the use of this powerful imaging application to analyze other organ scaffold systems.

O_TBL View this table:
org.highwire.dtl.DTLVardef@4937b8org.highwire.dtl.DTLVardef@e91b6forg.highwire.dtl.DTLVardef@83eeforg.highwire.dtl.DTLVardef@15be0d4org.highwire.dtl.DTLVardef@105a2e5_HPS_FORMAT_FIGEXP  M_TBL C_TBL Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.18703949.


title: Neural Collective Matrix Factorization for Integrated Analysis of Heterogeneous Biomedical Data

abstract:
MotivationIn many biomedical studies, there arises the need to integrate data from multiple directly or indirectly related sources. Collective matrix factorization (CMF) and its variants are models designed to collectively learn from arbitrary collections of matrices. The latent factors learnt are rich integrative representations that can be used in downstream tasks such as clustering or relation prediction with standard machine learning models. Previous CMF-based methods have numerous modeling limitations. They do not adequately capture complex non-linear interactions and do not explicitly model varying sparsity and noise levels in the inputs, and some cannot model inputs with multiple datatypes. These inadequacies limit their use on many biomedical datasets.

ResultsTo address these limitations, we develop Neural Collective Matrix Factorization (NCMF), the first fully neural approach to CMF. We evaluate NCMF on two relation prediction tasks, gene-disease association prediction and adverse drug event prediction, using multiple datasets. In each case, data is obtained from heterogeneous publicly available databases, and used to learn representations to build predictive models. NCMF is found to outperform previous CMF-based methods and state-of-the-art graph embedding methods for representation learning in our experiments. Our experiments illustrate the versatility and efficacy of NCMF for seamless integration of heterogeneous data.

Availabilityhttps://github.com/ncmfsrc/ncmf

Contactvaibhav.rajan@nus.edu.sg