title: AMP-Kinase mediates regulation of glomerular volume and podocyte survival

abstract: We reported that Shroom3 knockdown, via Fyn inhibition, induced albuminuria with foot process effacement (FPE) without glomerulosclerosis (FSGS) or podocytopenia. Interestingly, knockdown mice had reduced podocyte volumes. Human minimal change disease, where podocyte Fyn inactivation was reported, also showed lower glomerular volumes than FSGS. We hypothesized that lower glomerular volume prevented the progression to podocytopenia. To test this hypothesis, we utilized unilateral- and 5/6th nephrectomy models in Shroom3 knockdown mice. Knockdown mice exhibited lower glomerular volume, and less glomerular and podocyte hypertrophy after nephrectomy. FYN-knockdown podocytes had similar reductions in podocyte volume, implying Fyn was downstream of Shroom3. Using SHROOM3- or FYN-knockdown, we confirmed reduced podocyte protein content, along with significantly increased phosphorylated AMP-kinase, a negative regulator of anabolism. AMP-Kinase activation resulted from increased cytoplasmic redistribution of LKB1 in podocytes. Inhibition of AMP-Kinase abolished the reduction in glomerular volume and induced podocytopenia in mice with FPE, suggesting a protective role for AMP-Kinase activation. In agreement with this, treatment of glomerular injury models with AMP-Kinase activators restricted glomerular volume, podocytopenia and progression to FSGS. In summary, we demonstrate the important role of AMP-Kinase in glomerular volume regulation and podocyte survival. Our data suggest that AMP-Kinase activation adaptively regulates glomerular volume to prevent podocytopenia in the context of podocyte injury.


title: Capsaicin pretreatment alleviates postoperative pain and reduces primary sensory neuron Ca2+ activity

abstract: After surgeries, especially thoracotomy incision, patients develop unbearable pain. Opioids are used for reducing pain but often cause serious side effects. Previously, we found that capsaicin pretreatment of the incision area alleviated spontaneous and thermal pain in a postoperative pain animal model. In the present study, we aimed to monitor primary sensory neuron Ca2+ activity in in vivo dorsal root ganglia (DRG) in a postoperative pain model using Pirt-GCaMP3 treated with capsaicin or controls. Intraplantar injection of capsaicin (0.05%) alleviated spontaneous, mechanical, and thermal postoperative pain. The Ca2+ response in in vivo DRG and in in situ spinal cord was significantly enhanced in the ipsilateral side compared to contralateral side or naive control. Primary sensory nerve fiber length was significantly decreased in the incision skin area in capsaicin-pretreated animals detected by immunohistochemistry and placental alkaline phosphatase (PLAP) staining. Thus, capsaicin pretreatment alleviates postoperative pain by suppressing Ca2+ response due to degeneration of primary sensory nerve fibers in the skin.

category: neuroscience


title: The Normalization Model Captures the Effects of Object-based Attention in the Human Visual Cortex

abstract: Divisive normalization of the neural responses by the activity of the neighboring neurons has been proposed as a fundamental operation in the nervous system based on its success in predicting neural responses recorded in primate electrophysiology studies. Nevertheless, experimental evidence for the existence of this operation in the human brain is still scant. Here, using functional MRI, we explored the role of normalization across the visual hierarchy in the human visual cortex. Using stimuli form the two categories of human bodies and houses, we presented objects in isolation or in clutter and asked participants to attend or ignore the stimuli.Focusing on the primary visual area V1, the object-selective regions LO and pFs, and the category-selective regions EBA and PPA, we first modeled single-voxel responses using a weighted sum, a weighted average, and a normalization model and demonstrated that the response to multiple stimuli could best be described by a model that takes normalization into account. We then explored the observed effects of attention on cortical responses and demonstrated that these effects were predicted by the normalization model, but not by the weighted sum or the weighted average models. Our results thus provide compelling evidence for normalization as a canonical computation operating in the human brain.


title: Evidence for Normalization as a Fundamental Operation Across the Human Visual Cortex


title: Influence of environmental temperature on mouth-form plasticity in Pristionchus pacificus acts through daf-11-dependent cGMP signaling

abstract: Mouth-form plasticity in the nematode Pristionchus pacificus has become a powerful system to identify the genetic and molecular mechanisms associated with phenotypic (developmental) plasticity. In particular, the identification of developmental switch genes that can sense environmental stimuli and reprogram developmental processes has confirmed long-standing evolutionary theory. Together with the associated gene regulatory networks, these developmental switch genes have been important to show that plasticity is consistent with the Modern Synthesis of evolution. However, how these genes are involved in the direct sensing of the environment, or if the switch genes act downstream of another, primary environmental sensing mechanism, remains currently unknown. Here, we study the influence of environmental temperature on mouth-form plasticity. Using forward and reverse genetic technology including CRISPR/Cas9, we show that mutations in the guanylyl cyclase Ppa-daf-11, the Ppa-daf-25/AnkMy2 and the cyclic nucleotide-gated channel Ppa-tax-2 eliminate the response to elevated temperatures. Together, our study indicates that DAF-11, DAF-25 and TAX-2 have been co-opted for environmental sensing during mouth-form plasticity regulation in P. pacificus. This work suggests that developmental switch genes integrate environmental signals including perception by cGMP signaling.

category: genetics


title: Structural basis of the interaction between SETD2 methyltransferase and hnRNP L paralogs for governing co-transcriptional splicing

abstract: The RNA recognition motif (RRM) binds to nucleic acids as well as proteins. More than one such domain is found in the pre-mRNA processing hnRNP proteins. While the mode of RNA recognition by RRMs is known, the molecular basis of their protein interaction remains obscure. Here we describe the mode of interaction between hnRNP L and LL with the methyltransferase SETD2. We demonstrate that for the interaction to occur, a leucine pair within a highly conserved stretch of SETD2 insert their side chains in hydrophobic pockets formed by hnRNP L RRM2. Notably, the structure also highlights that RRM2 can form a ternary complex with SETD2 and RNA. Remarkably, mutating the leucine pair in SETD2 also results in its reduced interaction with other hnRNPs. Importantly, the similarity that the mode of SETD2-hnRNP L interaction shares with other related protein-protein interactions reveals a conserved design by which splicing regulators interact with one another.

category: biochemistry


title: AxonDeep: Automated Optic Nerve Axon Segmentation in Mice with Deep Learning.

abstract:
PurposeOptic nerve damage is the principal feature of glaucoma and contributes to vision loss in many diseases. In animal models, nerve health has traditionally been assessed by human experts that grade damage qualitatively or manually quantify axons from sampling limited areas from histologic cross sections of nerve. Both approaches are prone to variability and are time consuming. First-generation automated approaches have begun to emerge, but all have significant shortcomings. Here, we seek improvements through use of deep-learning approaches for segmenting and quantifying axons from cross sections of mouse optic nerve.

MethodsTwo deep-learning approaches were developed and evaluated: (1) a traditional supervised approach using a fully convolutional network trained with only labeled data and (2) a semi-supervised approach trained with both labeled and unlabeled data using a generative-adversarial-network framework.

ResultsFrom comparisons with an independent test set of images with manually marked axon centers and boundaries, both deep-learning approaches outperformed an existing baseline automated approach and similarly to two independent experts. Performance of the semi-supervised approach was superior and implemented into AxonDeep.

ConclusionAxonDeep performs automated quantification and segmentation of axons from healthy appearing nerves, and those with mild to moderate degrees of damage, similar to that of experts without the variability and constraints associated with manual performance.

Translational RelevanceUse of deep learning for axon quantification provides rapid, objective, and higher throughput analysis of optic nerve that would otherwise not be possible.

category: bioengineering


title: Imaging sensory transmission and neuronal plasticity in primary sensory neurons with genetically-encoded voltage indicators

abstract:
Detection of somatosensory inputs requires conversion of external stimuli into electrical signals by activation of primary sensory neurons. The mechanisms by which heterogeneous primary sensory neurons encode different somatosensory inputs remains unclear. In vivo dorsal root ganglia (DRG) imaging using genetically-encoded Ca2+ indicators (GECIs) is currently the best technique for this purpose by providing an unprecedented spatial and populational resolution. It permits the simultaneous imaging of >1800 neurons/DRG in live mice. However, this approach is not ideal given that Ca2+ is a second messenger and has inherently slow response kinetics. In contrast, genetically-encoded voltage indicators (GEVIs) have the potential to track voltage changes in multiple neurons in real time but often lack the brightness and dynamic range required for in vivo use. Here, we used soma-targeted ASAP4.4-Kv, a novel GEVI, to dissect the temporal dynamics of noxious and non-noxious neuronal signals during mechanical, thermal, or chemical stimulation in DRG of live mice. ASAP4.4-Kv is sufficiently bright and fast enough to optically characterize individual neuron coding dynamics. Notably, using ASAP4.4-Kv, we uncovered cell-to-cell electrical synchronization between adjacent DRG neurons and robust dynamic transformations in sensory coding following tissue injury. Finally, we found that a combination of GEVI and GECI imaging empowered in vivo optical studies of sensory signal processing and integration mechanisms with optimal spatiotemporal analysis.

HighlightsO_LIIn vivo ultra fast and sensitive dynamic voltage imaging of peripheral primary sensory neurons by a newly generated genetically-encoded voltage indicator.
C_LIO_LIIdentification of mechanical, thermal, or chemical stimuli-evoked voltage signals with superior temporal resolution.
C_LIO_LISingle-cell detection of changes in sub- and suprathreshold voltage dynamics across different disease conditions.
C_LIO_LICombination of voltage (by ASAP4.4-Kv) and Ca2+ (by Pirt-GCaMP3) signals to facilitate the understanding of signal processing and integration of primary sensory neurons, especially for noxious versus non-noxious sensation.
C_LI


title: Imaging sensory transmission and neuronal plasticity in primary sensory neurons with genetically-encoded voltage indicator, ASAP4.4-Kv


title: Kap-β2/Transportin mediates β-catenin nuclear transport in Wnt signaling

abstract: Wnt signaling is essential for many aspects of embryonic development including the formation of the primary embryonic axis. In addition, excessive Wnt signaling drives multiple diseases including cancer highlighting its importance for disease pathogenesis. {beta}-catenin is a key effector in this pathway that translocates into the nucleus and activates Wnt responsive genes. However, due to our lack of understanding of {beta}-catenin nuclear transport, therapeutic modulation of Wnt signaling has been challenging. Here, we took an unconventional approach to address this long-standing question by exploiting a heterologous model system, the budding yeast Saccharomyces cerevisiae, which contains a conserved nuclear transport machinery. In contrast to prior work, we demonstrate that {beta}-catenin accumulates in the nucleus in a Ran dependent manner, suggesting the use of a nuclear transport receptor (NTR). Indeed, a systematic and conditional inhibition of NTRs revealed that only Kap104, the orthologue of Kap-{beta}2/Transportin-1 (TNPO1), was required for {beta}-catenin nuclear import. We further demonstrate direct binding between TNPO1 and {beta}-catenin that is mediated by a conserved amino acid sequence that resembles a PY NLS. Finally, using Xenopus secondary axis and TCF/LEF reporter assays, we demonstrate that our results in yeast can be directly translated to vertebrates. By elucidating the NLS in {beta}-catenin and its cognate NTR, our study provides new therapeutic targets for a host of human diseases caused by excessive Wnt signaling. Indeed, we demonstrate that a small chimeric peptide designed to target TNPO1 can reduce Wnt signaling as a first step towards therapeutics.

category: developmental biology


title: Optimal spatial monitoring of populations described by reaction-diffusion models

abstract: Using spatialised population measurements and related geographic habitat data, it is quite feasible nowadays to derive parsimonious spatially explicit population models and to carry on their parameter estimation. To achieve such goal, reaction-diffusion models are fairly common in conservation biology and agricultural plant health where they are used, for example, for landscape planning or epidemiological surveillance. Unfortunately, if the mathematical methods and computational power are readily available, biological measurements are not. Despite the high throughput of some habitat related remote sensors, the experimental cost of biological measurements are, in our view, one of the worst bottleneck against a widespread usage of reaction-diffusion models. Hence, in this paper, we will recall some classical methods for optimal experimental design that we deem useful to spatial ecologist. Using two case studies, one in landscape ecology and one in conservation biology, we will show how to construct a priori experimental design minimizing variance of parameter estimates, enabling optimal experimental setup with pre and post hoc filtering for accommodating additional constraints.

category: ecology


title: Tmem138, a photoreceptor connecting cilium (CC) protein, is required for rhodopsin transport across the cilium and outer segment (OS) biogenesis

abstract: Photoreceptor connecting cilium (CC) is structurally analogous to the transition zone (TZ) of primary cilia and gates the molecular trafficking between the inner and the outer segment (OS). Retinal dystrophies with underlying CC defects are manifested in a broad array of syndromic conditions known as ciliopathies as well as non-syndromic retinal degenerations. Despite extensive studies, protein trafficking across the photoreceptor CC is largely unknown. Here we genetically inactivated mouse Tmem138, a gene encoding a ciliary membrane protein localized to the ciliary TZ and linked to Joubert syndrome (JBTS). Germline deletion of Tmem138 abolished OS morphogenesis followed by rapid photoreceptor degeneration. Tmem138 was found localized to the photoreceptor CC and, accordingly, the molecular compartments of the CC and axoneme of the mutant photoreceptors were altered despite ciliogenesis proceeding normally at the early stage of photoreceptor development. To gain further insights into Tmem138 function in OS biogenesis, we focused on trafficking of rhodopsin, the most abundant protein of the OS. Mislocalization of rhodopsin was readily observed as early as P5 in the mutant photoreceptors prior to growth of the OS. Ablation of Tmem138 in mature rods recapitulated the molecular changes in the germline mutants, causing well-formed outer segment discs to disintegrate accompanied by mislocalization of rhodopsin in the cell body. Furthermore, Tmem138 interacted with rhodopsin, and two additional CC compartment proteins Ahi1 and Tmem231, which were both altered in the mutant photoreceptors. Taken together, these results suggest that Tmem138 has a distinct role in gating the transport of rhodopsin and likely other OS bound proteins through formation of CC transport complex(es).

category: cell biology


title: Dynamic FRET-FLIM based screens of signal transduction pathways: a feasibility study

abstract:
Fluorescence Lifetime Imaging (FLIM) is an intrinsically quantitative method to screen for protein-protein interactions and frequently used to record the outcome of signal transduction events. With new highly sensitive and photon efficient FLIM instrumentation, the technique also becomes attractive to screen, with high temporal resolution, for fast changes in Forster Resonance Energy Transfer (FRET), such as those occurring upon activation of cell signaling.

We studied the effects of siRNA-mediated individual knockdown of an extensive set of 22 different phosphodiesterases (PDEs) on baseline levels and agonist-induced changes of the second messenger cAMP. Using HeLa cells stably expressing our FRET-FLIM sensor we imaged many hundreds of cells at 5 second intervals for each condition. Following segmentation of cells by the deep-learning implementation Cellpose, FLIM time traces were calculated and fitted for dynamic analysis with custom-made Python scripts. Taking advantage of the quantitative FLIM data, we found very limited effects of PDE knockdown on baseline and agonist-induced peak levels of cAMP. However, cAMP breakdown in the decay phase was significantly slower when PDE3A and, to a lesser amount, PDE10A were knocked down, identifying these isoforms as dominant in HeLa cells.

In conclusion, we present a robust platform that combines photon-efficient FLIM instrumentation with systematic gene knockdown and an automated open-source analysis pipeline. Our quantitative platform provides detailed kinetic analysis of cellular signals in individual cells with unprecedented throughput.


title: Hnf1b-CreER, a model used for fate mapping pancreatic lineages, achieves efficient Cre-mediated recombination in duct and islet δ cells

abstract: The Hnf1b-CreERT2 BAC transgenic (Tg(Hnf1b-cre/ERT2)1Jfer) has been used extensively to trace the progeny of pancreatic ducts in developmental, regeneration, or cancer models. Hnf1b-CreERT2 transgenics have been used to show that cells from that form a duct-like plexus in the embryonic pancreas are bipotent duct-endocrine progenitors, whereas adult mouse duct cells are not a common source of {beta} cells in various regenerative settings. The interpretation of such genetic lineage tracing studies is critically dependent on a correct understanding of the cell type specificity of recombinase activity with each reporter system. We have re-examined the performance of Hnf1b-CreERT2 with a Rosa26-RFP reporter transgene. This showed inducible recombination of up to 96% adult duct cells, a much higher efficiency than previously used reporter transgenes. Despite this high duct-cell excision, recombination in  and {beta} cells remained very low, similar to previously used reporters. However, nearly half of somatostatin-expressing {delta} cells showed reporter activation, which was due to Cre expression in {delta} cells rather than to duct to {delta} cell conversions. The high recombination efficiency in duct cells indicates that the Hnf1b-CreERT2 model can be useful for both ductal fate mapping and genetic inactivation studies. The recombination in {delta} cells does not modify the interpretation of studies that failed to show duct conversions to other cell types, but needs to be considered if this model is used in studies that aim to modify the plasticity of pancreatic duct cells.


title: Hnf1b-CreER causes efficient recombination of a Rosa26-RFP reporter in duct and islet δ cells


title: Elucidating the structural features of ABCA1 in its heterogeneous membrane environment.

abstract: ATP Binding Cassette Transporter A1 (ABCA1) plays an integral part in Reverse Cholesterol Transport (RCT) and is critical for maintaining lipid homeostasis. One theory of lipid efflux by the transporter (alternating access) proposes that ABCA1 harbours two different conformations that provide alternating access for lipid binding and release. This is followed by a sequestration via a direct interaction between ABCA1 and its partner, ApoA1. The alternative theory (lateral access) proposes that ABCA1 obtains lipids laterally from the membrane to form a temporary extracellular "reservoir". This reservoir contains an isolated lipid monolayer due to the net accumulation of lipids in the exofacial leaflet. Recently, a full-length Cryo-EM structure of this 2,261-residue transmembrane protein showed its discreetly folded domains and have detected the presence of a tunnel enclosed within ECDs but not in theTMDs giving it an outward-facing conformation. This structure was hypothesized to substantiate the lateral access theory, whereby ApoA1 obtained lipids from the proximal end laterally. Utilizing long time-scale multiple replica atomistic molecular dynamics simulations (MDS), we simulated the structure in a large heterogeneous lipid environment and found that along with several large conformational changes, the protein harbours a continuous tunnel that traverses the entire length of the protein. In this study, we have characterized ABCA1 and the lipid dynamics along with the protein-lipid interactions in the heterogeneous environment, providing novel insights into understanding ABCA1 conformation at an atomistic level.

category: biophysics


title: The spatial landscape of progression and immunoediting in primary melanoma at single cell resolution

abstract:
Cutaneous melanoma is a highly immunogenic malignancy, surgically curable at early stages, but life- threatening when metastatic. Here we integrate high-plex imaging, 3D high-resolution microscopy, and spatially-resolved micro-region transcriptomics to study immune evasion and immunoediting in primary melanoma. We find that recurrent cellular neighborhoods involving tumor, immune, and stromal cells change significantly along a progression axis involving precursor states, melanoma in situ, and invasive tumor. Hallmarks of immunosuppression are already detectable in precursor regions. When tumors become locally invasive, a consolidated and spatially restricted suppressive environment forms along the tumor-stromal boundary. This environment is established by cytokine gradients that promote expression of MHC-II and IDO1, and by PD1-PDL1 mediated cell contacts involving macrophages, dendritic cells, and T cells. A few millimeters away, cytotoxic T cells synapse with melanoma cells in fields of tumor regression. Thus, invasion and immunoediting can co-exist within a few millimeters of each other in a single specimen.

STATEMENT OF SIGNIFICANCEThe reorganization of the tumor ecosystem in primary melanoma is an excellent setting in which to study immunoediting and immune evasion. Guided by classical histopathology, spatial profiling of proteins and mRNA reveals recurrent morphological and molecular features of tumor evolution that involve localized paracrine cytokine signaling and direct cell-cell contact.

category: cancer biology


title: Prevalent and Dynamic Binding of the Cell Cycle Checkpoint Kinase Rad53 to Gene Promoters

abstract: Replication of the genome must be coordinated with gene transcription and cellular metabolism. These processes are controlled in part by the Rad53 (CHEK2 in mammals) checkpoint kinase and the Mrc1 replisome component, especially following replication stress in the presence of limiting deoxyribonucleotides. We examined cell cycle regulated, genome-wide binding of Rad53 to chromatin. The kinase bound to sites of active DNA replication initiation and fork progression, but unexpectedly to the promoters of numerous genes (>20% of all genes) involved in many cellular functions. At some genes, Rad53 promoter binding correlated with changes in gene expression. Rad53 promoter binding to certain genes is influenced by sequence-specific transcription factors and less by checkpoint signaling. In checkpoint mutants, untimely activation of late-replicating origins reduces the transcription of nearby genes, with concomitant localization of Rad53 to their gene bodies. We suggest that the Rad53 checkpoint kinase coordinates genome-wide replication and transcription under stress conditions.

category: molecular biology


title: Biomechanics and Myofibrillar Alignment Enhance Contractile Development and Reproducibility in Stem Cell Derived Cardiac Muscle

abstract: Human pluripotent stem cell derived cardiomyocytes (hPSC-CMs) allow novel investigations of human cardiac disease, but disorganized mechanics and immaturity of hPSC-CMs on two-dimensional (2D) surfaces have been hurdles for efficient and reproducible study of these cells. Here, we developed a platform of micron-scale 2D cardiac tissues (M2DCTs) to precisely control biomechanics in arrays of thousands of purified, independently contracting cardiac muscle strips in 2D. By defining geometry and workload in M2DCTs in this reductionist platform that does not incorporate other cell types, we show that myofibrillar alignment and auxotonic contractions at physiologic workload critically drive maturation of cardiac contractile function, calcium handling, and electrophysiology. Additionally, the organized biomechanics in this system facilitates rapid and automated extraction of contractile kinetic parameters from brightfield microscopy images, increasing the reproducibility and throughput of pharmacologic testing. Finally, we show that M2DCTs enable precise and efficient dissection of contractile kinetics in cardiomyopathy disease models.


title: optix is involved in eyespot development via a possible positional information mechanism

abstract: Novel organismal traits might reuse ancestral gene-regulatory networks (GRNs) in their development, but data supporting this mechanism are still sparse. Here we propose that a conserved venation gene network, used in patterning insect wings, has been recruited to pattern the sharp and distinct rings of color in butterfly eyespot development. This network involves Decapentaplegic (Dpp), acting as a central morphogen, activating optix and spalt at different concentration thresholds. It also involves Spalt cross-regulating optix resulting in the formation of a sharp boundary between the two genes. First, using in situ hybridizations, we show that dpp is expressed in the eyespot centers during the early pupal stage and that CRISPR-Cas9 embryonic knockouts of dpp, optix, and spalt result in the loss of eyespots, loss of the orange ring, and loss of the black scales, respectively. Furthermore, using RNAi during the pupal stage, we show that dpp down-regulation results in the complete or partial loss of eyespots. Using CRISPR disruptions of optix or spalt, followed by immunostainings, we show that Spalt represses optix in the central region of the eyespot, limiting optix expression to a more peripheral ring. We further illustrate that optix disruptions alter scale pigmentation and scale ultrastructure as they transform orange to brown scales. Altogether, the regulatory interactions between dpp, spalt and optix mimic those found in earlier larval developmental stages, in the anterior compartment of an insects wing, where these genes play a role in venation patterning. The network similarities suggest that the venation GRN was co-opted to aid in the differentiation of the eyespot rings.


title: Reuse of a wing venation gene-regulatory network in patterning the eyespot rings of butterflies


title: A single heterozygous mutation in COG4 disrupts zebrafish early development via Wnt signaling

abstract: Saul-Wilson syndrome (SWS) is a rare, skeletal dysplasia with progeroid appearance and primordial dwarfism. It is caused by a heterozygous, dominant variant (p.G516R) in COG4, a subunit of the Conserved Oligomeric Golgi (COG) complex involved in intracellular vesicular transport. Our previous work has shown the intracellular disturbances caused by this mutation; however, the pathological mechanism of SWS needs further investigation. We sought to understand the molecular mechanism of specific aspects of the SWS phenotype by analyzing SWS-derived fibroblasts and zebrafish embryos expressing this dominant variant. SWS fibroblasts accumulate glypicans, a group of heparan sulfate proteoglycans (HSPGs) critical for growth and bone development through multiple signaling pathways. Consistently, we find that glypicans are increased in embryos expressing the COG4p.G516R variant. These animals show phenotypes consistent with convergent extension (CE) defects during gastrulation, shortened body length, and malformed jaw cartilage chondrocyte intercalation at larval stages. Since non-canonical Wnt signaling was shown in zebrafish to be related to the regulation of these processes by Glypican 4, we assessed wnt levels and found a selective increase of wnt4 transcripts in the presence of COG4p.G516R. Moreover, overexpression of wnt4 mRNA phenocopies these developmental defects. LGK974, an inhibitor of Wnt signaling corrects the shortened body length at low concentrations but amplifies it at slightly higher concentrations. WNT4 and the non-canonical Wnt signaling component phospho-JNK are also elevated in cultured SWS-derived fibroblasts. Similar results from SWS cell lines and zebrafish point to altered non-canonical Wnt signaling as one possible mechanism underlying SWS pathology.


title: Reactive/Non-cooperative individuals advance Population's Synchronization: Modeling of Dictyostelium discoideum Concerted Signaling during Aggregation Phase

abstract: Orchestrated chemical signaling of single cells sounds to be a linchpin of emerging organization and multicellular life form. The social amoeba Dictiostelium discoiudium is a well-studied model organism to explore overall pictures of grouped behavior in developmental biology. The chemical waves secreted by aggregating Dictiostelium is a superb example of pattern formation. The waves are either circular or spiral in shape, according to the incremental population density of a self-aggregating community of individuals. Here, we revisit the spatiotemporal patterns that appear in an excitable medium due to synchronization of randomly firing individuals, but with a more parsimonies attitude. According to our model, a fraction of these individuals is refusal to amplify external stimulants. Our simulations indicate that the cells enhance the systems asymmetry and as a result, nucleate early sustainable spiral territory zones, provided that their relative population does not exceed a tolerable threshold.


title: Label-free three-dimensional analyses of live cells with deep-learning-based segmentation exploiting refractive index distributions

abstract:
Visualisations and analyses of cellular and subcellular organelles in biological cells is crucial for the study of cell biology. However, existing imaging methods require the use of exogenous labelling agents, which prevents the long-time assessments of live cells in their native states. Here we propose and experimentally demonstrate three-dimensional segmentation of subcellular organelles in unlabelled live cells, exploiting a 3D U-Net-based architecture. We present the high-precision three-dimensional segmentation of cell membrane, nucleus membrane, nucleoli, and lipid droplets of various cell types. Time-lapse analyses of dynamics of activated immune cells are also analysed using label-free segmentation.

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title: MLC Seq: De novo sequencing of full-length tRNA isoforms by mass ladder complementation

abstract: tRNAs can exist in distinct isoforms because of different chemical modifications, which confounds attempts to accurately sequence individual tRNA species using next generation sequencing approaches or to quantify different RNA modifications at specific sites on a tRNA strand. Herein, we develop a mass spectrometric (MS) ladder complementation sequencing (MLC-Seq), allowing for direct and simultaneous sequencing of full-length tRNA molecules, including those with low abundance. MLC-seq is achieved by improved instrumentation, and advanced algorithms that identify each tRNA species and related isoforms in an RNA mixture, and assemble full MS ladders from partial ladders with missing ladder components. Using MLC-Seq, we successfully obtained the sequence of tRNA-Phe from yeast and tRNA-Glu from mouse hepatocytes, and simultaneously revealed new tRNA isoforms derived from nucleotide modifications. Importantly, MLC-Seq pinpointed the location and stoichiometry changes of RNA modifications in tRNA-Glu upon the treatment of dealkylated enzyme AlkB, which confirmed its known enzymatic activity and suggested previously unidentified effects in RNA editing.


title: Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification

abstract:
BackgroundMachine learning (ML) methodology development for classification of immune states in adaptive immune receptor repertoires (AIRR) has seen a recent surge of interest. However, so far, there does not exist a systematic evaluation of scenarios where classical ML methods (such as penalized logistic regression) already perform adequately for AIRR classification. This hinders investigative reorientation to those scenarios where further method development of more sophisticated ML approaches may be required.

ResultsTo identify those scenarios where a baseline method is able to perform well for AIRR classification, we generated a collection of synthetic benchmark datasets encompassing a wide range of dataset architecture-associated and immune state-associated sequence pattern (signal) complexity. We trained {approx}1300 ML models with varying assumptions regarding immune signal on{approx}850 datasets with a total of {approx}210000 repertoires containing {approx}42 billion TCR{beta} CDR3 amino acid sequences, thereby surpassing the sample sizes of current state-of-the-art AIRR ML setups by two orders of magnitude. We found that L1-penalized logistic regression achieved high prediction accuracy even when the immune signal occurs only in 1 out of 50000 AIR sequences.

ConclusionsWe provide a reference benchmark to guide new AIRR ML classification methodology by: (i) identifying those scenarios characterised by immune signal and dataset complexity, where baseline methods already achieve high prediction accuracy and (ii) facilitating realistic expectations of the performance of AIRR ML models given training dataset properties and assumptions. Our study serves as a template for defining specialized AIRR benchmark datasets for comprehensive benchmarking of AIRR ML methods.

category: bioinformatics


title: Hippocampal TRPV1 channels in the modulation of contextual fear conditioning

abstract: Psychiatric disorders have been linked to impairments in fear memory circuitry. Thus, pharmacological approaches that impair aversive memories have been investigated as new treatments. The TRPV1 channel modulates biological processes related to memory consolidation and retrieval. However, TRPV1 seems involved in memories generated by high intense conditioning. Anandamide (AEA), the main endocannabinoid, is an agonist of both, TRPV1 channels and CB1 receptors which are colocalized in several brain structures. Remarkably, AEA has twenty-times more affinity for CB1 than for TRPV1, which may be involved in the intensity-dependent recruitment of this channel. In order to evaluate the role of intensity of the conditioning in the recruitment of TRPV1, the animals were submitted to the contextual fear conditioning (CFC) and conditioned with low, moderate or high intensity. Before the retrieval a TRPV1 blocker was administered into the dorsal hippocampus (dHPC). The levels of AEA were quantified by Mass Spectrometry. The RNA levels of Arc, Zif and Trkb, involved in memory and plasticity, were quantified by PCR. Our results showed that TRPV1 blockers impair the retrieval of memory in animals conditioned with moderate and high intensity but not low ones. As revealed by Mass Spectrometry, this different recruitment among intensities seems to be associated with the levels of AEA released. Moreover, the impairment in freezing induced by blocking TRPV1 was prevented by a subeffective dose of the cannabinoid receptor CB1 antagonist which suggest that TRPV1 blockers act increasing AEA availability in the synaptic cleft to act through CB1 receptors. Despite blocking TRPV1 channels impairs freezing in moderate and high intensities, it increases the RNA levels of Arc, Zif and Trkb only in animals conditioned with the moderate intensity. In accordance, the treatment impairs retrieval in both intensities but only in the moderate intensity is able to prevent the reinstatement. Summarizing, our results suggested that intensity of the conditioning modulates AEA levels which in turns determines if TRPV1 will be recruited at the retrieval and which molecular pathways will be engaged due to TRPV1 blocking.

category: pharmacology and toxicology


title: Simultaneous pure T2 and varying T2'-weighted BOLD fMRI using Echo Planar Time-resolved Imaging (EPTI) for mapping laminar fMRI responses

abstract: Spin-echo (SE) BOLD fMRI has high microvascular specificity, and thus provides a more reliable means to localize neural activity compared to conventional gradient-echo BOLD fMRI. However, the most common SE BOLD acquisition method, SE-EPI, is known to suffer from T2' contrast contamination with undesirable draining vein bias. To address this, in this study, we extended a recently developed distortion/blurring-free multi-shot EPI technique, Echo-Planar Time-resolved Imaging (EPTI), to cortical-depth dependent SE-fMRI at 7T to test whether it could provide purer SE BOLD contrast with minimal T2' contamination for improved neuronal specificity. From the same acquisition, the time-resolved feature of EPTI also provides a series of asymmetric SE (ASE) images with varying T2' weightings, and enables extraction of data equivalent to conventional SE EPI with different echo train lengths (ETLs). This allows us to systematically examine how T2'-contribution affects different SE acquisition strategies using a single dataset. A low-rank spatiotemporal subspace reconstruction was implemented for the SE-EPTI acquisition, which incorporates corrections for both shot-to-shot phase variations and dynamic B0 drifts. SE-EPTI was used in a visual task fMRI experiment to demonstrate that i) the pure SE image provided by EPTI results in the highest microvascular specificity; ii) the ASE EPTI series, with a graded introduction of T2' weightings at time points farther away from the pure SE, show a gradual sensitivity increase along with increasing draining vein bias; iii) the longer ETL seen in conventional SE EPI acquisitions will induce more draining vein bias. Consistent results were observed across multiple subjects, demonstrating the robustness of the proposed technique for SE-BOLD fMRI with high specificity.


title: Simultaneous pure T2 and varying T2'-weighted BOLD fMRI using Echo Planar Time-resolved Imaging for mapping cortical-depth dependent responses


title: Local structure-function relationships in human brain networks across the human lifespan

abstract: The human connectome is the set of physical pathways linking brain regions to one another. Empirical and in silico studies have demonstrated that the structure of this network helps shape patterns of functional coupling between brain regions. To better understand this link between structure and function, a growing number of studies have derived geometric, dynamic, and topological predictors from structural connectivity in order to make predictions about correlation structure. These studies, however, have typically focused on global (whole-brain) predictions using a restricted set of predictors. Here, we investigate a wide range of predictors and shift focus onto predictions of local (regional) patterns of functional coupling. We show that, globally, no individual predictor performs well and, that even the best predictors are largely driven by their ability to predict functional coupling between directly connected regions. We then use the same predictors to make predictions of local coupling and find marked improvement. Notably, the most predictable local FC is linked to sensorimotor regions, which are best predicted by measures based on topological similarity, mean first passage times of random walkers, and the brains embedding in Euclidean space. We then show that by combining the predictive power of more than one predictor using multi-linear models, we can further improve local predictions. Finally, we investigate how global and local structure-function coupling differences across the human lifespan. We find that, globally, the magnitude of coupling decreases with biological age, which is paralleled by an increase in the number of multi-step pathways. We also show that, locally, structure-function coupling is preserved in higher order cognitive systems, but preferentially decreases with age in sensorimotor systems. Our results illuminate the heterogeneous landscape of structure-function coupling across the cerebral cortex and help clarify its differences with age.


title: 3D-MASNet: 3D Mixed-scale Asymmetric Convolutional Segmentation Network for 6-month-old Infant Brain MR Images

abstract: Precise segmentation of infant brain MR images into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) is essential for studying neuroanatomical hallmarks of early brain development. However, for 6-month-old infants, the extremely low-intensity contrast caused by inherent myelination hinders accurate tissue segmentation. Existing convolutional neural networks (CNNs) based segmentation model for this task generally employ single-scale symmetric convolutions, which are inefficient for encoding the isointense tissue boundaries in limited samples of baby brain images. Here, we propose a 3D mixed-scale asymmetric convolutional segmentation network (3D-MASNet) framework for brain MR images of 6-month-old infant. We replaced the traditional convolutional layer of an existing to-be-trained network with a 3D mixed-scale convolution block consisting of asymmetric kernels (MixACB) during the training phase and then equivalently converted it into the original network. Five canonical CNN segmentation models were evaluated using both T1- and T2-weighted images of 23 6-month-old infants from iSeg-2019 datasets, which contained manual labels as ground truth. MixACB significantly enhanced the average accuracy of all five models and obtained the largest improvement in the fully convolutional network model (CC-3D-FCN) and the highest performance in the Dense U-Net model. This approach further obtained Dice coefficient accuracies of 0.931, 0.912, and 0.961 in GM, WM, and CSF, respectively, ranking first among 30 teams on the validation dataset of the iSeg-2019 Grand Challenge. Thus, the proposed 3D-MASNet can improve the accuracy of existing CNNs-based segmentation models as a plug-and-play solution that offers a promising technique for future infant brain MRI studies.


title: A Spatiotemporal Map of Reading Aloud

abstract: Reading words aloud is a fundamental aspect of literacy. The rapid rate at which multiple distributed neural substrates are engaged in this process can only be probed via techniques with high spatiotemporal resolution. We probed this with direct intracranial recordings covering most of the left hemisphere in 46 humans as they read aloud regular, exception and pseudo-words. We used this to create a spatiotemporal map of word processing and to derive how broadband gamma activity varies with multiple word attributes critical to reading speed: lexicality, word frequency and orthographic neighborhood. We found that lexicality is encoded earliest in mid-fusiform (mFus) cortex and precentral sulcus, and is represented reliably enough to allow single-trial lexicality decoding. Word frequency is first represented in mFus and later in the inferior frontal gyrus (IFG) and inferior parietal sulcus (IPS), while orthographic neighborhood sensitivity resides solely in IPS. We thus isolate the neural correlates of the distributed reading network involving mFus, IFG, IPS, precentral sulcus and motor cortex and provide direct evidence for dual-route models of reading, with parallel processes via the lexical route from mFus to IFG, and the sub-lexical route from IPS and precentral sulcus to anterior IFG.


title: Alpha oscillatory activity causally linked to working memory retention: insights from online phase-locking closed-loop transcranial alternating current stimulation (tACS)

abstract: Although previous studies have reported correlations between alpha oscillations and the "retention" sub-process of working memory (WM), causal evidence has been limited in human neuroscience due to the lack of delicate modulation of human brain. Conventional tACS is not suitable for demonstrating the causal evidence for parietal alpha oscillations in WM retention because of its inability to modulate brain oscillations within a short period (i.e., the retention sub-process). Here, we developed an online phase-corrected closed-loop transcranial alternating current stimulation (tACS) system capable of precisely correcting for the phase differences between tACS and concurrent endogenous oscillations. This system permits both up- and down-regulation of brain oscillations at the target stimulation frequency within a short stimulation period, and is here applied to empirically demonstrate that parietal alpha oscillations causally relate to WM retention. Our experimental design included both in-phase and anti-phase alpha-tACS applied to 39 participants during the retention sub-processes of a modified Sternberg paradigm. Compared to in-phase alpha-tACS, anti-phase alpha-tACS decreased both WM performance and alpha activity. Moreover, the in-phase tACS-induced changes in WM performance were positively correlated with alpha oscillatory activity. These findings strongly support a causal link between alpha oscillations and WM retention, and illustrate the broad application prospects of phase-corrected tACS.


title: Alpha Oscillatory Activity Causally Linked to Working Memory Retention: Insights from Online Phase-corrected Closed-loop Transcranial Alternating Current Stimulation (tACS)


title: Presynaptic HCN channels constrain GABAergic synaptic transmission in pyramidal cells of the medial prefrontal cortex

abstract: Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels are widely expressed in neurons in the central nervous system. It has been documented that HCN channels regulate the intrinsic excitability of pyramidal cells in the medial prefrontal cortex (mPFC) of rats. Here, we report that HCN channels limited GABAergic transmission onto pyramidal cells in the mPFC. Pharmacological block of HCN channels resulted in a significant increase in the frequency of both spontaneous and miniature inhibitory postsynaptic currents (IPSCs) in mPFC pyramidal cells. Such facilitation effect on mIPSCs required presynaptic Ca2+ influx and reversed by high-dose cAMP. Such facilitation did not exist in the presence of the T-type Ca2+ channel selective blockers. Immunofluorescence staining revealed that HCN channels expressed in presynaptic GABAergic terminals, as well as in both soma and neurite of parvalbumin-expressing (PV-expressing) basket cells in the mPFC. The present results indicate that HCN channels in GABAergic interneurons, most likely PV-expressing basket cells, constrain inhibitory control over layer 5-6 pyramidal cells through restricting presynaptic Ca2+ entry.


title: DNA Methyltransferase 1 and 3a Expression in the Frontal Cortex Regulates Palatable Food Consumption

abstract: DNA methylation is an important regulatory mechanism in the control of neuronal function. Both during development and following exposure to salient stimuli, plasticity in the methylation of cytosine residues leads to a change in neuron excitability that subsequently sculpts animal behavior. However, although the response of DNA methyltransferase enzymes in adult neurons to stimuli such as drugs of abuse have been described, less is known about how these enzymes regulate methylation at specific loci to change the drive to ingest natural rewards. Specifically, we do not understand how changes in methylation within important brain areas known to regulate palatable food intake can affect ingestion, while a detailed investigation of the neurophysiological and genomic effects of perturbing methyltransferase function has not been pursued. By deleting DNA methyltransferase 1 and 3a in the mouse prefrontal cortex, we observed the requirement for these enzymes in the regulation of nutrient rich food consumption in the absence of any effect on the intake of low fat and low sugar chow. We also determined that the deletion profoundly affected neuron excitability within pyramidal cells resident in superficial layers II/III of the cortex but had little effect in deep layer V neurons. Finally, reduced representation bisulfite sequencing revealed both hypo and hypermethylation in response to methyltransferase deletion, an effect that was observed in binding sites for retinoic acid receptor beta (RAR{beta}) located within regulatory regions of genes known to affect neuronal function. Together, our data suggest that alterations in the actions of RAR{beta} could shift neuronal activity to reduce palatable food intake.


title: Inhibition of immunoglobulin class-switching prevents pemphigus onset in desmoglein 3-specific B cell receptor knock-in mouse

abstract: Although immunoglobulin class-switching is essential for humoral immunity, its role in B-cell immune tolerance remains unclear. Pemphigus vulgaris is an autoimmune blistering disease caused by IgG targeting desmoglein 3, an adhesion molecule of keratinocytes. In this study, we generated knock-in mice that express anti-Dsg3 AK23 autoantibodies. Knock-in B cells developed normally in vivo and showed Ca2+ influx upon IgM cross-linking in vitro. The mice predominantly produced circulating AK23 IgM but little IgG antibodies. Although no IgG deposition or blister formation was observed in Dsg3-bearing tissues, Dsg3 immunization forced to induce pemphigus phenotype after class-switching to IgG in vivo. Transcriptomic analysis revealed that FCGR2B and Fc{gamma}RIIB-related genes were downregulated in B cells from peripheral blood of pemphigus patients. Indeed, in AK23 knock-in mice, Fcgr2b deficiency or haploinsufficiency spontaneously led to class-switching, AK23 IgG production, and pemphigus phenotype development. Thus, inhibition of pathogenic class-switching is a crucial tolerogenic process to prevent pemphigus onset, where attenuated Fc{gamma}RIIB signaling is one of the key predispositions to break this tolerogenic state.

category: immunology


title: A cell-penetrant peptide blocking C9ORF72-repeat RNA nuclear export suppresses neurodegeneration

abstract: Hexanucleotide repeat expansions in C9ORF72 are the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), a spectrum of incurable debilitating neurodegenerative diseases. Here, we report a novel ALS/FTD drug concept with in vivo and in vitro therapeutic activity in preclinical models of C9ORF72-ALS/FTD. Our data demonstrate that supplementation or oral administration of a cell-penetrant peptide, which competes with the SRSF1:NXF1 interaction, confers neuroprotection by inhibiting the nuclear export of pathological C9ORF72-repeat transcripts in various models of disease including primary neurons, patient-derived motor neurons and Drosophila. Our drug-like rationale for disrupting the nuclear export of microsatellite repeat transcripts in neurological disorders provides a promising alternative to conventional small molecule inhibitors often limited by poor blood-brain barrier penetrance.


title: DIRECT DETECTION OF LISTERIA MONOCYTOGENES BY RECOMBINASE POLYMERASE AMPLIFICATION

abstract: Listeria monocytogenes is one of the most common types of food poisoning bacteria which can cause serious foodborne diseases or even lethality. Generally, L. monocytogenes can be detected using traditional microbiology or molecular biology techniques, notably PCR. However, the application of these methods at the field is restricted due to the strict requirement of equipment and skilled personnel. In this study, recombinase polymerase amplification (RPA), an isothermal PCR assay was developed to rapidly detect L. monocytogenes in the crude samples. The results showed that the RPA reaction, without requiring complex thermal cycles, was well-performed in the optimal conditions of 39{degrees}C within only 25 minutes. The limit of detection was identified as 310 fg of L. monocytogenes genomic DNA, which was 1000-fold more sensitive than the conventional PCR. In addition, RPA also succeeded to directly detect L. monocytogenes cells at a concentration as low as 2.5 x 101 Colony Forming Unit (CFU)/ml in pure cultures and 2.5 x 102 CFU/ml in crude samples without sample extraction or processing. Therefore, RPA established in this study could be an alternative standard method to confirm the presence of L. monocytogenes in food. Accordingly, this rapid and sensitive method could be further applied to clinical testing for the diagnosis of L. monocytogenes infection, especially in areas with limited settings.


title: Rapid genome editing by CRISPR-Cas9-POLD3 fusion

abstract: Precision CRISPR gene editing relies on the cellular homology-directed DNA repair (HDR) to introduce custom DNA sequences to target sites. The HDR editing efficiency varies between cell types and genomic sites, and the sources of this variation are incompletely understood. Here, we have studied the effect of 450 DNA repair protein - Cas9 fusions on CRISPR genome editing outcomes. We find the majority of fusions to improve precision genome editing only modestly in a locus- and cell-type specific manner. We identify Cas9-POLD3 fusion that enhances editing by speeding up the initiation of DNA repair. We conclude that while DNA repair protein fusions to Cas9 can improve HDR CRISPR editing, most need to be optimized to the particular cell type and genomic site, highlighting the diversity of factors contributing to locus-specific genome editing outcomes.


title: The impact of resource provisioning on the epidemiological responses of different parasites

abstract:
O_LIEvents such as anthropogenic activities and periodic tree masting can alter resource provisioning in the environment, directly affecting animals, and potentially impacting the spread of infectious diseases in wildlife. The effect of these supplemental resources on infectious diseases can manifest through different pathways, affecting host susceptibility, transmission and host demography.
C_LIO_LITo date however, empirical research has tended to examine these different pathways in isolation, for example by quantifying the effects of provisioning on host behaviour in the wild or changes in immune responses in controlled laboratory studies. Further, while theory has investigated the interactions between these pathways, thus far this work has focussed on a narrow subset of pathogen types, typically directly-transmitted microparasites. Given the diverse ways that provisioning can affect host susceptibility, contact patterns or host demography, we may expect the epidemiological consequences of provisioning to depend on key aspects of parasite life-history, such as the duration of infection and transmission mode.
C_LIO_LIWe developed a suite of generic epidemiological models to compare how resource provisioning alters responses for different parasites that vary in their biology (micro- and macro-parasite), transmission mode (direct, environmental, and vector transmitted) and duration of infection (acute, latent, and chronic). Next, we parameterised these different parasite types using data from the diverse parasite community of wild wood mice as a case study.
C_LIO_LIWe show there are common epidemiological responses to host resource provisioning across all parasite types examined. In particular, the response to provisioning could be driven in opposite directions, depending on which host pathways (contact rate, susceptibility or host demography) are most altered by the addition of resources to the environment. Broadly, these responses were qualitatively consistent across all parasite types, emphasising the importance of identifying general trade-offs between provisioning-altered parameters.
C_LIO_LIDespite the qualitative consistency in responses to provisioning across parasite types, we found notable quantitative differences between parasites, suggesting specific epidemiological outcomes could strongly depend on parasite type, infection duration and permanency of recovery, and whether the parasite is directly, environmentally, or vector transmitted. These analyses therefore highlight the importance of knowing key specific aspects of host-parasite biology, such as host contact behaviours, parasite interactions with the host immune system, and how resource availability shapes host demographics, in order to understand and predict epidemiological responses to provisioning for any specific host-parasite system.
C_LI


title: Inferring Population Size Histories using Coalescent Hidden Markov Models with TMRCA and Total Branch Length as Hidden States

abstract:
Unraveling the complex demographic histories of natural populations is a central problem in population genetics. Understanding past demographic events is of general anthropological interest and is also an important step in establishing accurate null models when identifying adaptive or disease-associated genetic variation. An important class of tools for inferring past population size changes are Coalescent Hidden Markov Models (CHMMs). These models make efficient use of the linkage information in population genomic datasets by using the local genealogies relating sampled individuals as latent states that evolve across the chromosome in an HMM framework. Extending these models to large sample sizes is challenging, since the number of possible latent states increases rapidly.

Here, we present our method CHIMP (CHMM History-Inference ML Procedure), a novel CHMM method for inferring the size history of a population. It can be applied to large samples (hundreds of haplotypes) and only requires unphased genomes as input. The two implementations of CHIMP that we present here use either the height of the genealogical tree (TMRCA) or the total branch length, respectively, as the latent variable at each position in the genome. The requisite transition and emission probabilities are obtained by numerically solving certain systems of differential equations derived from the ancestral process with recombination. The parameters of the population size history are subsequently inferred using an Expectation-Maximization algorithm. In addition, we implement a composite likelihood scheme to allow the method to scale to large sample sizes.

We demonstrate the efficiency and accuracy of our method in a variety of benchmark tests using simulated data and present comparisons to other state-of-the-art methods. Specifically, our implementation using TMRCA as the latent variable shows comparable performance and provides accurate estimates of effective population sizes in intermediate and ancient times. Our method is agnostic to the phasing of the data, which makes it a promising alternative in scenarios where high quality data is not available, and has potential applications for pseudo-haploid data.


title: Karyon: a computational framework for the diagnosis of hybrids, aneuploids, and other non-standard architectures in genome assemblies.

abstract: Recent technological developments have made genome sequencing and assembly accessible to many groups. However, the presence in sequenced organisms of certain genomic features such as high heterozygosity, polyploidy, aneuploidy, or heterokaryosis can challenge current standard assembly procedures and result in highly fragmented assemblies. Hence, we hypothesized that genome databases must contain a non-negligible fraction of low-quality assemblies that result from such type of intrinsic genomic factors. Here we present Karyon, a Python-based toolkit that uses raw sequencing data and de novo genome assembly to assess several parameters and generate informative plots to assist in the identification of non-chanonical genomic traits. Karyon includes automated de novo genome assembly and variant calling pipelines. We tested Karyon by diagnosing 35 highly fragmented publicly available assemblies from 19 different Mucorales (Fungi) species. Our results show that 6 (17%) of the assemblies presented signs of unusual genomic configurations, suggesting that these are common, at least within the Fungi.

category: genomics


title: Identification of a new Infectious Pancreatic Necrosis Virus (IPNV) isolate in Atlantic salmon (Salmo salar L.) that causes mortality in resistant fish

abstract: Infectious pancreatic necrosis (IPN) is an important viral disease of salmonids that can affect fish during various life cycles. In Atlantic salmon, selecting for genetically resistant animals against IPN has been one of the most highly praised success stories in the history of fish breeding. The findings that resistance against this disease has a significant genetic component, which is mainly controlled by variations in a single gene, has helped to reduce the IPN outbreaks over the past decade to a great extent. In this paper, we present the identification of a new isolate of the IPN virus, from a field outbreak, that had caused mortality, even in the genetically resistant animals. We recovered and assembled the full-length genome of this virus, following deep-sequencing of an infected tissue. The comparative sequence analysis revealed that for the critical amino acid motifs, previously found to be associated with the degree of virulence, the newly identified isolate is similar to the viruss avirulent form. However, we detected a set of deduced amino acid residues, particularly in the hypervariable region of the polyprotein, that collectively are unique to this strain compared to all other reference sequences assessed in this study. We suggest that these mutations have likely equipped the virus with the capacity to escape the host defence mechanism more efficiently, even in the genetically deemed IPN resistant animals.


title: Genetic Dissection of the RNA Polymerase II Transcription Cycle

abstract: How DNA sequence affects the dynamics and position of RNA Polymerase II (Pol II) during transcription remains poorly understood. Here we used naturally occurring genetic variation in F1 hybrid mice to explore how DNA sequence differences affect the genome-wide distribution of Pol II. We measured the position and orientation of Pol II in eight organs collected from heterozygous F1 hybrid mice using ChRO-seq. Our data revealed a strong genetic basis for the precise coordinates of transcription initiation and promoter proximal pause, allowing us to redefine molecular models of core transcriptional processes. Our results implicate the strength of base pairing between A-T or G-C dinucleotides as key determinants to the position of Pol II initiation and pause. We report evidence that initiation site selection follows a stochastic process similar to brownian motion along the DNA template. We found widespread differences in the position of transcription termination, which impact the primary structure and stability of mature mRNA. Finally, we report evidence that allelic changes in transcription often affect mRNA and ncRNA expression across broad genomic domains. Collectively, we reveal how DNA sequences shape core transcriptional processes at single nucleotide resolution in mammals.


title: Serine catabolism generates NADPH to support hepatic lipogenesis

abstract: Carbohydrate can be converted into fat by de novo lipogenesis1,2. This process is known to occur in adipose and liver, and its activity is upregulated in fatty liver disease3. Chemically, de novo lipogenesis involves polymerization and reduction of acetyl-CoA, using NADPH as the electron donor1. While regulation of the responsible enzymes has been extensively studied, the feedstocks used to generate acetyl-CoA and NADPH remain unclear. Here we show that, while de novo lipogenesis in adipose is supported by glucose and its catabolism via the pentose phosphate pathway to make NADPH, liver makes fat without relying on glucose. Instead, liver derives acetyl-CoA from acetate and lactate, and NADPH from folate-mediated serine catabolism. Such NADPH generation involves the cytosolic serine pathway running in liver in the opposite direction observed in most tissues and tumors4,5, with NADPH made by the SHMT1-MTHFD1-ALDH1L1 reaction sequence. Thus, specifically in liver, folate metabolism is wired to support cytosolic NADPH production for lipogenesis. More generally, while the same enzymes are involved in fat synthesis in liver and adipose, different substrates are utilized, opening the door to tissue-specific pharmacological interventions.


title: Differential ADAR editing landscapes in major depressive disorder and suicide

abstract: Neuropsychiatric disorders, including depression and suicide, are becoming an increasing public health concern. Rising rates of both depression and suicide, exacerbated by the current COVID19 pandemic, have only hastened our need for objective and reliable diagnostic biomarkers. These can aide clinicians treating depressive disorders in both diagnosing and developing treatment plans. While differential gene expression analysis has highlighted the serotonin signaling cascade among other critical neurotransmitter pathways to underly the pathology of depression and suicide, the biological mechanisms remain elusive. Here we propose a novel approach to better understand molecular underpinnings of neuropsychiatric disorders by examining patterns of differential RNA editing by adenosine deaminases acting on RNA (ADARs). We take advantage of publicly available RNA-seq datasets to map ADAR editing landscapes in a global gene-centric view. We use a unique combination of Guttman scaling and random forest classification modeling to create, describe and compare ADAR editing profiles focusing on both spatial and biological sex differences. We use a subset of experimentally confirmed ADAR editing sites located in known protein coding regions, the excitome, to map ADAR editing profiles in Major Depressive Disorder (MDD) and suicide. Using Guttman scaling, we were able to describe significant changes in editing profiles across brain regions in males and females with respect to cause of death (COD) and MDD diagnosis. The spatial distribution of editing sites may provide insight into biological mechanisms under-pinning clinical symptoms associated with MDD and suicidal behavior. Additionally, we use random forest modeling including these differential profiles among other markers of global editing patterns in order to highlight potential biomarkers that offer insights into molecular changes underlying synaptic plasticity. Together, these models identify potential prognostic, diagnostic and therapeutic biomarkers for MDD diagnosis and/or suicide.


title: Theory of local k-mer selection with applications to long-read alignment

abstract:
MotivationSelecting a subset of k-mers in a string in a local manner is a common task in bioinformatics tools for speeding up computation. Arguably the most well-known and common method is the minimizer technique, which selects the  lowest-ordered k-mer in a sliding window. Recently, it has been shown that minimizers are a sub-optimal method for selecting subsets of k-mers when mutations are present. There is however a lack of understanding behind the theory of why certain methods perform well.

ResultsWe first theoretically investigate the conservation metric for k-mer selection methods. We derive an exact expression for calculating the conservation of a k-mer selection method. This turns out to be tractable enough for us to prove closed-form expressions for a variety of methods, including (open and closed) syncmers, (, b, n)-words, and an upper bound for minimizers. As a demonstration of our results, we modified the minimap2 read aligner to use a more optimal k-mer selection method and demonstrate that there is up to an 8.2% relative increase in number of mapped reads.

Availability and supplementary informationSimulations and supplementary methods available at https://github.com/bluenote-1577/local-kmer-selection-results. os-minimap2 is a modified version of minimap2 and available at https://github.com/bluenote-1577/os-minimap2.

Contactjshaw@math.toronto.edu


title: Tripeptide loop closure: a detailed study of reconstructions based on Ramachandran distributions

abstract:
Tripeptide loop closure (TLC) is a standard procedure to reconstruct protein backbone conformations, by solving a zero dimensional polynomial system yielding up to 16 solutions. In this work, we first show that multiprecision is required in a TLC solver to guarantee the existence and the accuracy of solutions. We then compare solutions yielded by the TLC solver against tripeptides from the Protein Data Bank. We show that these solutions are geometrically diverse (up to 3[A] RMSD with respect to the data), and sound in terms of potential energy. Finally, we compare Ramachandran distributions of data and reconstructions for the three amino acids. The distribution of reconstructions in the second angular space ({varphi}2,{psi} 2) stands out, with a rather uniform distribution leaving a central void.

We anticipate that these insights, coupled to our robust implementation in the Structural Bioinformatics Library (https://sbl.inria.fr/doc/Tripeptide_loop_closure-user-manual.html), will boost the interest of TLC for structural modeling in general, and the generation of conformations of flexible loops in particular.


title: Anchored and labile pools of Calcineurin are enabled by a disordered AKAP scaffold

abstract: Disordered scaffold proteins provide multivalent landing pads that, via a series of embedded Short Linear Motifs (SLiMs), bring together the components of a complex to orchestrate precise spatial and temporal regulation of cellular processes. One such protein is AKAP5, which contains SLiMs that anchor PKA and Calcineurin, and recruit substrate (the TRPV1 receptor). Calcineurin is anchored to AKAP5 by a well-characterised PxIxIT SLiM. Here we show, using a combination of biochemical and biophysical approaches, that the Calcineurin PxIxIT-binding groove also recognises several hitherto unknown lower-affinity SLiMs in addition to the PxIxIT motif. We demonstrate that the assembly is in reality a complex system with conserved SLiMs spanning a wide affinity range. The capture is analogous to that seen for many DNA-binding proteins that have a weak non-specific affinity for DNA outside the canonical binding site, but different in that it involves (i) two proteins, and (ii) hydrophobic rather than electrostatic interactions. It is also compatible with the requirement for both stable anchoring of the enzyme and responsive downstream signalling. We conclude that the AKAP5 C-terminus is enriched in lower-affinity/mini-SLiMs that, together with the canonical SLiM, maintain a structurally disordered but tightly regulated signalosome.


title: Hidden multivalency in phosphatase recruitment by a disordered AKAP scaffold


title: TIR signaling promotes the interactions between EDS1/PAD4 and ADR1-L1 and oligomerization of ADR1-L1

abstract: Both plants and animals use nucleotide-binding leucine-rich repeat (NLR) immune receptors to perceive pathogens and trigger immunity. Toll/interleukin-1 receptor (TIR)-type plant NLRs (TNLs) require the lipase-like protein family members Enhanced Disease Susceptibility 1 (EDS1)/ Phytoalexin Deficient 4 (PAD4)/ Senescence-Associated Gene 101 (SAG101) and helper NLRs (hNLRs) for downstream signaling, the biochemical mechanisms of which remain unclear. Here, we report that TIR signaling promotes the association of EDS1 and PAD4 with hNLR ACTIVATED DISEASE RESISTANCE 1-Like 1 (ADR1-L1), and the oligomerization of ADR1-L1s for downstream immune activation and cell death.

category: plant biology


title: Positive Selection and Heat-Response Transcriptomes Reveal Adaptive Features of the Arabidopsis Desert Relative, Anastatica hierochuntica

abstract:
O_LIPlant adaptation to a desert environment and its endemic heat stress is poorly understood at the molecular level. The naturally heat-tolerant Brassicaceae species Anastatica hierochuntica is an ideal extremophyte model to identify genetic adaptations that have evolved to allow plants to tolerate heat stress and thrive in deserts.
C_LIO_LIWe generated an A. hierochuntica reference transcriptome and pinpointed extremophyte adaptations by comparing Arabidopsis thaliana and A. hierochuntica transcriptome responses to heat and identifying positively selected genes in A. hierochuntica.
C_LIO_LIThe two species exhibit similar transcriptome adjustment in response to heat and the A. hierochuntica transcriptome does not exist in a constitutive heat "stress-ready" state. Furthermore, the A. hierochuntica global transcriptome as well as heat-responsive orthologs, display a lower basal and higher heat-induced expression than in A. thaliana. Genes positively selected in multiple extremophytes are associated with stomatal opening, nutrient acquisition, and UV-B induced DNA repair while those unique to A. hierochuntica are consistent with its photoperiod-insensitive, early-flowering phenotype.
C_LIO_LIWe suggest that evolution of a flexible transcriptome confers the ability to quickly react to extreme diurnal temperature fluctuations characteristic of a desert environment while positive selection of genes involved in stress tolerance and early flowering could facilitate an opportunistic desert lifestyle.
C_LI


title: Positive Selection and Heat-Response Transcriptomes Reveal Adaptive Features of the Brassicaceae Desert Model, Anastatica hierochuntica


title: Computing Minimal Boolean Models of Gene Regulatory Networks

abstract: Models of Gene Regulatory Networks (GRNs) capture the dynamics of the regulatory processes that occur within the cell as a means to understand the variability observed in gene expression between different conditions. Arguably the simplest mathematical construct used for modeling is the Boolean network, which dictates a set of logical rules for transition between states described as Boolean vectors. Due to the complexity of gene regulation and the limitations of experimental technologies, in most cases knowledge about regulatory interactions and Boolean states is partial. In addition, the logical rules themselves are not known a-priori. Our goal in this work is to present a methodology for inferring this information from the data, and to provide a measure for comparing network states under different biological conditions. We present a novel methodology for integrating experimental data and performing a search for the optimal consistent structure via optimization of a linear objective function under a set of linear constraints. We also present a statistical approach for testing the similarity of inferred network states under different conditions. Finally, we extend our methodology into a heuristic that can handle large datasets that are generated by single-cell RNA-Sequencing(scRNA-Seq). We demonstrate the effectiveness of these tools using a public scRNA-Seq dataset and the GRN that is associated with it. Our methodology will enable researchers to obtain a better understanding of the dynamics of gene regulatory networks and their biological role.

category: systems biology


title: Learning orthogonalizes visual cortical population codes

abstract: The response of a neuronal population to a stimulus can be summarized by a vector in a high-dimensional space. Learning theory suggests that the brain should be most able to produce distinct behavioral responses to two stimuli when the rate vectors they evoke are close to orthogonal. To investigate how learning modifies population codes, we measured the orientation tuning of 4,000-neuron populations in visual cortex before and after training on a visual discrimination task. Learning suppressed responses to the task-informative stimuli, most strongly amongst weakly-tuned neurons. This suppression reflected a simple change at the population level: sparsening of population responses to relevant stimuli, resulting in orthogonalization of their rate vectors. A model of F-I curve modulation, requiring no synaptic plasticity, quantitatively predicted the learning effect.


title: Study of compatibility and determination of the suitable pollinizer for Argane tree (Argania spinosa L.)

abstract:
During the breeding program studies, the pollen donor parents (pollinizers) were observed to be characterized by a strong flowering rate and very low fruit set, even after hand pollination. Then the notion of pollinizers in the argane species was born, first mentioned, checked, documented and confirmed like other conventional tree species. Since the argane tree is completely self-incompatible, the presence of compatible pollinizers is necessary for the fruit set. Indeed, pollinizers need to be selected accurately based on the synchronization of bloom periods and compatibility to receiver trees (female). The pollinizer is essential in any breeding program and for new orchard plantations. The current study was conducted on 13 argane genotypes including two pollinizers. The flowering period, bloom phenology, floral structure and fruit set of crossed genotypes were monitored, illustrated and a season phenogram was established. The pollen viability and germination were also evaluated. In order to test compatibility, the hand pollination using two selected pollinizer pollens was compared to open pollination. Then, the compatibility system was monitored and evaluated through analysis of crossing diallel programs and through the index of self-incompatibility. The flowering periods are genotype depending and one to three blooms have been observed during the two years study (2018-2019) and the argane tree is a tristylous species (Mesostylous, brevistylous and longistylous flowers). The in vitro tests showed that the pollen originated from crossed genotypes were viable and able to germinate. The cross-compatibility rate depends on cross associations and it varies from 39 to 84 %. In fact, this study showed that the effect of pollen-parent (xenia) occurs in all fruit components of argane tree. It was observed, for the first time, that both compatible pollinizers and xenic effects of pollen on argane fruit have occurred. Artificial pollination is currently feasible for breeding programs and the screening of elite genotypes. Then the selected pollinizer is quite required for the development of argane tree cropping.

HighlightsO_LIPollinizers in the argane species first mentioned
C_LIO_LIPollinizer is essential in any breeding program and for new orchard plantations
C_LIO_LIArgane tree is self-incompatible
C_LIO_LIPollen-parent effect, (xenia) occurs in all fruit components of argane tree
C_LI


title: Automated detection of artefacts in neonatal EEG with residual neural networks

abstract:
Background and ObjectiveTo develop a computational algorithm that detects and identifies different artefact types in neonatal electroencephalography (EEG) signals.

MethodsAs part of a larger algorithm, we trained a Residual Deep Neural Network on expert human annotations of EEG recordings from 79 term infants recorded in a neonatal intensive care unit (112 h of 18-channel recording). The network was trained using 10 fold cross validation in Matlab. Artefact types included: device interference, EMG, movement, electrode pop, and non-cortical biological rhythms. Performance was assessed by prediction statistics and further validated on a separate independent dataset of 13 term infants (143 h of 3-channel recording). EEG pre-processing steps, and other post-processing steps such as averaging probability over a temporal window, were also included in the algorithm.

ResultsThe Residual Deep Neural Network showed high accuracy (95%) when distinguishing periods of clean, artefact-free EEG from any kind of artefact, with a median accuracy for individual patient of 91% (IQR: 81%-96%). The accuracy in identifying the five different types of artefacts ranged from 57%-92%, with electrode pop being the hardest to detect and EMG being the easiest. This reflected the proportion of artefact available in the training dataset. Misclassification as clean was low for each artefact type, ranging from 1%-11%. The detection accuracy was lower on the validation set (87%). We used the algorithm to show that EEG channels located near the vertex were the least susceptible to artefact.

ConclusionArtefacts can be accurately and reliably identified in the neonatal EEG using a deep learning algorithm. Artefact detection algorithms can provide continuous bedside quality assessment and support EEG review by clinicians or analysis algorithms.

HighlightsO_LIWe applied a Residual Deep Neural Network as part of an artefact detection algorithm in neonatal electroencephalograms.
C_LIO_LIThe algorithm shows high accuracy in identifying artefactual data in general and for specific artefact types.
C_LIO_LIEEG channels near the top of the head are less prone to artefact.
C_LI


title: TRIM25 and ZAP target the Ebola virus ribonucleoprotein complex to mediate interferon-induced restriction

abstract:
Ebola virus (EBOV) causes highly pathogenic disease in primates. Through screening a library of human interferon-stimulated genes (ISGs), we identified TRIM25 as a potent inhibitor of EBOV transcription-and-replication-competent virus-like particle (trVLP) propagation. TRIM25 overexpression inhibited the accumulation of viral genomic and messenger RNAs independently of the RNA sensor RIG-I or secondary proinflammatory gene expression. Deletion of TRIM25 strongly attenuated the sensitivity of trVLPs to inhibition by type-I interferon. The antiviral activity of TRIM25 required ZAP and the effect of type-I interferon was modulated by the CpG dinucleotide content of the viral genome. We find that TRIM25 interacts with the EBOV vRNP, resulting in its autoubiquitination and ubiquitination of the viral nucleoprotein (NP). TRIM25 is recruited to incoming vRNPs shortly after cell entry, and leads to dissociation of NP from the vRNA. We propose that TRIM25 targets the EBOV vRNP, exposing CpG-rich viral RNA species to restriction by ZAP.

HighlightsO_LITRIM25 and ZAP play a major role on type I IFN-mediated inhibition of EBOV trVLP replication
C_LIO_LITRIM25 interacts with the EBOV NP and is recruited to vRNPs in the cytoplasm after viral entry
C_LIO_LITRIM25 ubiquitinates NP and displaces it from the viral genome, facilitating ZAP interaction
C_LIO_LIZAP targets CpGs in the EBOV genome to inhibit EBOV trVLP replication
C_LI

category: microbiology


title: RNase E endonuclease activity and its inhibition by pseudoridine

abstract: The conserved endoribonuclease RNase E dominates the dynamic landscape of RNA metabolism and underpins control mediated by small regulatory RNAs in diverse bacterial species. We explored the enzymes hydrolytic mechanism, allosteric activation, and interplay with partner proteins in the multi-component RNA degradosome assembly. RNase E cleaves single-stranded RNA with preference to attack the phosphate located at the 5{square} nucleotide preceding uracil, and we corroborate key interactions that select that base. Unexpectedly, RNase E activity is impeded strongly when the recognised uracil is isomerised to 5-ribosyluracil (pseudouridine), from which we infer the detailed geometry of the hydrolytic attack process. Kinetics analyses support models for recognition of secondary structure in substrates by RNase E and for allosteric auto-regulation. The catalytic power of the enzyme is boosted when it is assembled into the multi-enzyme RNA degradosome, most likely as a consequence of substrate channeling. Our results rationalize the origins of substrate preferences of RNase E and illuminate its catalytic mechanism, supporting the roles of allosteric domain closure and cooperation with other components of the RNA degradosome complex.


title: Coordination of KIF3A and KIF13A regulates leading edge localization of MT1-MMP in cancer cells

abstract: MT1-MMP plays a crucial role in promoting the cellular invasion of cancer cells by degrading the extracellular matrix to create a path for migration. During this process, its localization at the leading edge of migrating cells is critical, and it is achieved by targeted transport of MT1-MMP-containing vesicles along microtubules by kinesin superfamily proteins (KIFs). Here we identified three KIFs involved in MT1-MMP vesicle transport: KIF3A, KIF13A, and KIF9. Knockdown of KIF3A and KIF13A effectively inhibited MT1-MMP-dependent collagen degradation and invasion, while knockdown of KIF9 increased collagen degradation and invasion. Our data suggest that KIF9 competes with KIF3A/KIF13A to bring MT1-MMP vesicles to different locations in the plasma membrane. Live-cell imaging analyses have indicated that KIF3A and KIF13A coordinate to transport the same MT1-MMP-containing vesicles. Taken together, we have identified a unique interplay between three KIFs to regulate leading edge localization of MT1-MMP and MT1-MMP-dependent cancer cell invasion.


title: Kinetic Monitoring Of Neuronal Stress Response To Proteostasis Dysfunction

abstract: Proteostasis dysfunction and activation of the unfolded protein response (UPR) are characteristic of all major neurodegenerative diseases. Nevertheless, although the UPR and proteostasis dysfunction has been studied in great detail in model organisms like yeast and mammalian cell lines, it has not yet been examined in neurons. In this study, we applied a viral vector-mediated expression of a reporter protein based on a UPR transcription factor, ATF4, and time-lapse fluorescent microscopy to elucidate how mouse primary neurons respond to pharmacological and genetic perturbations to neuronal proteostasis. In in vitro models of endoplasmic reticulum (ER) stress and proteasome inhibition, we used the ATF4 reporter to reveal the time course of the neuronal stress response relative to neurite degeneration and asynchronous cell death. We showed how potential neurodegenerative disease co-factors, ER stress and mutant -synuclein overexpression, impacted neuronal stress response and overall cellular health. This work therefore introduces a viral vector-based reporter that yields a quantifiable readout suitable for non-cell destructive kinetic monitoring of proteostasis dysfunction in neurons by harnessing ATF4 signaling as part of the UPR activation.


title: Automatic instance segmentation of mitochondria in electron microscopy data

abstract: We present a new method for rapid, automated, large-scale 3D mitochondria instance segmentation, developed in response to the ISBI 2021 MitoEM Challenge. In brief, we trained separate machine learning algorithms to predict (1) mitochondria areas and (2) mitochondria boundaries in image volumes acquired from both rat and human cortex with multi-beam scanning electron microscopy. The predictions from these algorithms were combined in a multi-step post-processing procedure, that resulted in high semantic and instance segmentation performance. All code is provided via a public repository.


title: Splice sites obey the power-law during splicing in leukemia cells

abstract: Alternative splicing is an essential characteristic of living cells that usually infers a various exon-exon junction governed by different splice sites. The traditional classification based on the mode of use designates splice site to one of the two groups, constitutive or alternative. Here, we considered another criterion and reorganized splice sites into "unisplice" and "multisplice" groups according to the number of undertaken splicing events. This approach provided us with a new insight in the organization and functionality of leukemia cells. We determined features associated with uni- and multisplice sites and found that combinatorics of these sites follows strict rules of the power-law in the t(8;21)-positive leukemia cells. We also found that system splicing characteristics of the transcriptome of leukemia cells remained persistent after drastic changes in the transcript composition caused by knockdown of the RUNX1-RUNX1T1 oncogene. In this work, we show for the first time that leukemia cells possess a sub-set of unisplice sites with a hidden multisplice potential. These findings reveal a new side in organization and functioning of the leukemic cells and open up new perspectives in the study of the t(8;21)-positive leukemia.


title: Generative neural networks separate common and specific transcriptional responses

abstract: Genome-wide transcriptome profiling identifies genes that are prone to differential expression across contexts ("common DEGs"), as well as genes with changes specific to the experimental manipulation. Distinguishing common DEGs from those that are specifically changed in a context of interest allows more efficient prediction of which genes are specific to a given biological process under scrutiny. Currently, commonly differentially expressed genes or pathways can only be identified through the laborious manual curation of highly controlled experiments, an inordinately time-consuming and impractical endeavor. Here we pioneer an approach for identifying common patterns using generative neural networks. This approach produces a background set of transcriptomic experiments from which a null distribution of gene and pathway changes can be generated. By comparing the set of differentially expressed genes found in a target experiment against the generated background set, common results can be easily separated from specific ones. This "Specific cOntext Pattern Highlighting In Expression data" (SOPHIE) approach is broadly applicable to new platforms or any species with a large collection of gene expression data. We apply SOPHIE to diverse datasets including those from human, human cancer, and the bacterial pathogen Pseudomonas aeruginosa. SOPHIE identifies common DEGs in concordance with previously described, manually and systematically determined common DEGs. Further, molecular validation indicates that SOPHIE detects highly specific, but low magnitude, biologically relevant, transcriptional changes. SOPHIEs measure of specificity can complement log fold change values generated from traditional differential expression analyses. For example, by filtering the set of differentially expressed genes, one can identify those genes that are specifically relevant to the experimental condition of interest. Consequently, these results can inform future research directions.


title: Describing small angle scattering profiles by a limited set of intensities

abstract: Small angle scattering (SAS) probes the size and shape of particles at low resolution through the analysis of the scattering of X-rays or neutrons passing through a solution of particles. One approach to extracting structural information from SAS data is the indirect Fourier transform (IFT). The IFT approach parameterizes the real space pair distribution function (P (r)) of a particle using a set of orthogonal basis functions, which simultaneously determines the scattering profile (I(q)) using corresponding reciprocal space basis functions. This article presents an extension of an IFT algorithm proposed by Moore which used a trigonometric series to describe the basis functions, where the real space and reciprocal space basis functions are Fourier mates. An equation is presented relating the Moore coefficients to the intensities of the SAS profile at specific positions as well as a series of new equations that describe the size and shape parameters of a particle from this distinct set of intensity values. An analytical real space regularizer is derived to smooth the P (r) curve and ameliorate systematic deviations caused by series termination, commonly used in IFT methods though not described in Moores original approach, which is particularly susceptible to such effects. The algorithm is provided as a script, denss.fit_data.py, as part of the DENSS software package for SAS, which includes both command line and interactive graphical interfaces. Results of the program using experimental data show that it is as accurate, and often more accurate, than existing tools.


title: Moore than meets the eye: A modified and regularized indirect Fourier Transform(er)


title: Principles of gene regulation quantitatively connect DNA to RNA and proteins in bacteria

abstract: Bacteria allocate their proteome to cellular functions differently in different growth conditions. It is largely unknown how such allocation arises from known mechanisms of gene regulation while constrained by limited translation capacity and fixed protein density. Here, we performed absolute transcriptomic and proteomic analysis for E. coli across many conditions, obtaining a plethora of results on promoters and mRNAs characteristics that clash with conventional expectations: the majority of mRNAs exhibit similar translational efficiencies, while the promoter strengths are vastly different across genes. These characteristics prescribe two principles of gene regulation guiding bacteria to attain the desired protein allocation under global constraints: Total transcriptional output is tightly coordinated with ribosomal activity, and the concentrations of individual proteins are largely set by transcription. These two principles lead to a quantitative formulation of Central Dogma which unravels the complex relationship between gene regulatory activities and mRNA/protein concentrations across conditions. The knowledge obtained will be invaluable for accurately inferring gene regulatory interactions from  omics data, as well as for guiding the design of genetic circuits for synthetic biology applications in E. coli and other organisms.


title: G-Protein coupled Purinergic P2Y12 receptor interacts and internalizes TauRD-mediated by membrane-associated actin cytoskeleton remodelling in microglia

abstract: In Alzheimers disease, the microtubule-associated protein, Tau misfolds to form aggregates and filaments in the intra- and extracellular region of neuronal cells. Microglial cells are the resident brain macrophage cells that are involved in constant surveillance and are activated by the extracellular deposits. Purinergic receptors are involved in chemotactic migration of microglial cells towards the site of inflammation. In our recent study, we found that microglial P2Y12 receptor has been involved in phagocytosis of full-length Tau species such as monomers, oligomers and aggregates by actin-driven chemotaxis. In this study, we have showed the interaction of repeat-domain of Tau (TauRD) with microglial P2Y12 receptor and analysed the corresponding residues for interaction by various in-silico approaches. In cellular studies, TauRD was found to interact with microglial P2Y12R and induces its cellular expression as confirmed by coimmunoprecipitation and western blot analysis respectively. Similarly, immunofluorescence microscopic studies emphasized that TauRD were phagocytosed by microglial P2Y12R via the membrane-associated actin remodelling as filopodia extension. Furthermore, the P2Yl2R-mediated TauRD internalization has activated the microglia with an increase in the Iba1 level and TauRD become accumulated at peri-nuclear region as localized with Iba1. Altogether, microglial P2Y12R interacts with TauRD and mediates directed migration and activation for its internalization.

category: neuroscience


title: Quantifying brain state transition cost via Schrödinger's bridge

abstract:
Quantifying brain state transition cost is a fundamental problem in systems neuroscience. Previous studies utilized network control theory to measure the cost by considering a neural system as a deterministic dynamical system. However, this approach does not capture the stochasticity of neural systems, which is important for accurately quantifying brain state transition cost. Here, we propose a novel framework based on optimal control in stochastic systems. In our framework, we quantify the transition cost as the Kullback-Leibler divergence from an uncontrolled transition path to the optimally controlled path, which is known as Schrodinger bridge. To test its utility, we applied this framework to functional magnetic resonance imaging data from the Human Connectome Project and computed the brain state transition cost in cognitive tasks. We demonstrate correspondence between brain state transition cost and the difficulty of tasks. The results suggest that our framework provides a general theoretical tool for investigating cognitive functions from the viewpoint of transition cost.

Author SummaryIn our daily lives, we perform numerous tasks with different kinds and levels of cognitive demand. To successfully perform these tasks, the brain needs to modulate its spontaneous activity to reach an appropriate state for each task. Previous studies utilized optimal control in deterministic systems to measure cost for brain state transition. However, there has not been a unified framework for quantifying brain state transition cost that takes account of stochasticity of neural activities. Here, we propose a novel framework for measuring brain state transition cost, utilizing the idea of optimal control in stochastic systems. We assessed the utility of our framework for quantifying the cost of transitioning between various cognitive tasks. Our framework can be applied to very diverse settings due to its generality.


title: Quantifying brain state transition cost via Schrödinger bridge