title: Deep Heterogeneous Dilation of LSTM for Transient-phase Gesture Prediction through High-density Electromyography: Application in Neurorobotics

abstract: Deep networks have been recently proposed to estimate motor intention using conventional bipolar surface electromyography (sEMG) signals for myoelectric control of neurorobots. In this regard, Deepnets are generally challenged by long training times (affecting practicality and calibration), complex model architectures (affecting the predictability of the outcomes), and a large number of trainable parameters (increasing the need for big data). Capitalizing on our recent work on homogeneous temporal dilation in a Recurrent Neural Network (RNN) model, this paper proposes, for the first time, heterogeneous temporal dilation in an LSTM model and applies that to high-density surface electromyography (HD-sEMG), allowing for the decoding of dynamic temporal dependencies with tunable temporal foci. In this paper, a 128-channel HD-sEMG signal space is considered due to the potential for enhancing the spatiotemporal resolution of human-robot interfaces. Accordingly, this paper addresses a challenging motor intention decoding problem of neurorobots, namely, transient intention identification. Our approach uses only the dynamic and transient phase of gesture movements when the signals are not stabilized or plateaued, which can significantly enhance the temporal resolution of human-robot interfaces. This would eventually enhance seamless real-time implementations. Additionally, this paper introduces the concept of "dilation foci" to modulate the modeling of temporal variation in transient phases. In this work a high number (e.g., 65) of gestures is included, which adds to the complexity and significance of the understudied problem. Our results show state-of-the-art performance for gesture prediction in terms of accuracy, training time, and model convergence.


title: Deep Heterogeneous Dilation of LSTM for Transient-phase Gesture Prediction through High-density Electromyography: Towards Application in Neurorobotics

category: bioengineering


title: Prediction of cancer mutation states using multiple data modalities reveals the utility and consistency of gene expression and DNA methylation

abstract:
In studies of cellular function in cancer, researchers are increasingly able to choose from many -omics assays as functional readouts. Choosing the correct readout for a given study can be difficult, and which layer of cellular function is most suitable to capture the relevant signal may be unclear. In this study, we consider prediction of cancer mutation status (presence or absence) from functional -omics data as a representative problem. Since functional signatures of cancer mutation have been identified across many data types, this problem presents an opportunity to quantify and compare the ability of different -omics readouts to capture signals of dysregulation in cancer. The TCGA Pan-Cancer Atlas contains genetic alteration data including somatic mutations and copy number variants (CNVs), as well as several -omics data types. From TCGA, we focus on RNA sequencing, DNA methylation arrays, reverse phase protein arrays (RPPA), microRNA, and somatic mutational signatures as -omics readouts.

Across a collection of genes recurrently mutated in cancer, RNA sequencing tends to be the most effective predictor of mutation state. Surprisingly, we found that for many of the genes we considered, one or more other data types are approximately equally effective predictors. Performance was more variable between mutations than it was between data types for the same mutation, and there was often little difference between the top data types. We also found that combining data types into a single multi-omics model provided little or no improvement in predictive ability over the best individual data type. Based on our results, for the design of studies focused on the functional outcomes of cancer mutations, there are often multiple -omics types that can serve as effective readouts, although gene expression seems to be a reasonable default option.

category: bioinformatics


title: Gene expression and DNA methylation consistently predict cancer mutation states


title: Widespread redundancy in -omics profiles of cancer mutation states


title: Techniques to Produce and Evaluate Realistic Multivariate Synthetic Data

abstract:
BackgroundProper data modeling in biomedical research requires sufficient data for exploration and reproducibility purposes. A limited sample size can inhibit objective performance evaluation.

ObjectiveWe are developing a synthetic population (SP) generation technique to address the limited sample size condition. We show how to estimate a multivariate empirical probability density function (pdf) by converting the task to multiple one-dimensional (1D) pdf estimations.

MethodsKernel density estimation (KDE) in 1D was used to construct univariate maps that converted the input variables (X) to normally distributed variables (Y). Principal component analysis (PCA) was used to transform the variables in Y to the uncoupled representation (T), where the univariate pdfs were assumed normal with specified variances. A standard random number generator was used to create synthetic variables with specified variances in T. Applying the inverse PCA transform to the synthetic variables in T produced the SP in Y. Applying the inverse maps produced the respective SP in X. Multiple tests were developed to compare univariate and multivariate pdfs and covariance matrices between the input (sample) and synthetic samples. Three datasets were investigated (n = 667) each with 10 input variables.

ResultsFor all three datasets, both the univariate (in X, Y, and T) and multivariate (in X, Y, and T) tests showed that the univariate and multivariate pdfs from synthetic samples were statistically similar to their pdfs from the respective samples. Application of several tests for multivariate normality indicated that the SPs in Y were approximately normal. Covariance matrix comparisons (in X and Y) also indicated the same similarity.

ConclusionsThe work demonstrates how to generate multivariate synthetic data that matches the real input data by converting the input into multiple 1D problems. The work also shows that it is possible to convert a multivariate input pdf to a form that approximates a multivariate normal, although the technique is not dependent upon this finding. Further studies are required to evaluate the generalizability of the approach.


title: Biology-inspired data-driven quality control for scientific discovery in single-cell transcriptomics

abstract: Quality control (QC) of cells, a critical step in single-cell RNA sequencing data analysis, has largely relied on arbitrarily fixed data-agnostic thresholds on QC metrics such as gene complexity and fraction of reads mapping to mitochondrial genes. The few existing data-driven approaches perform QC at the level of samples or studies without accounting for biological variation in the commonly used QC criteria. We demonstrate that the QC metrics vary both at the tissue and cell state level across technologies, study conditions, and species. We propose data-driven QC (ddqc), an unsupervised adaptive quality control framework that performs flexible and data-driven quality control at the level of cell states while retaining critical biological insights and improved power for downstream analysis. On applying ddqc to 6,228,212 cells and 835 mouse and human samples, we retain a median of 39.7% more cells when compared to conventional data-agnostic QC filters. With ddqc, we recover biologically meaningful trends in gene complexity and ribosomal expression among cell-types enabling exploration of cell states with minimal transcriptional diversity or maximum ribosomal protein expression. Moreover, ddqc allows us to retain cell-types often lost by conventional QC such as metabolically active parenchymal cells, and specialized cells such as neutrophils or gastric chief cells. Taken together, our work proposes a revised paradigm to quality filtering best practices - iterative QC, providing a data-driven quality control framework compatible with observed biological diversity.


title: Risk-utility tradeoff shapes memory strategies for evolving patterns

abstract: Keeping a memory of evolving stimuli is ubiquitous in biology, an example of which is immune memory for evolving pathogens. However, learning and memory storage for dynamic patterns still pose challenges in machine learning. Here, we introduce an analytical energy-based framework to address this problem. By accounting for the tradeoff between utility in keeping a high-affinity memory and the risk in forgetting some of the diverse stimuli, we show that a moderate tolerance for risk enables a repertoire to robustly classify evolving patterns, without much fine-tuning. Our approach offers a general guideline for learning and memory storage in systems interacting with diverse and evolving stimuli.

category: biophysics


title: T Cell Receptor Non-Equilibrium Kinetics

abstract: An atomic-scale mechanism describing the role of mechanosensing in T Cell Receptor (TCR) recognition of peptides in the binding groove of the peptide-major histocompatibility complex (pMHC) may inform the design of novel TCRs for immunotherapies. Using steered molecular dynamic simulations, our study demonstrates that mutations to peptides in the binding groove of the pMHC - which are known to discretely alter the T cell response to an antigen - influence MHC conformation and thus the overall strength of the TCR-pMHC bond including duration and length under constant load. Moreover, physiochemical features of the TCR-pMHC dynamic bond strength, such as hydrogen bonds and Lennard-Jones contacts, correlate with the immunogenic response elicited by the specific peptide in the MHC groove. Thus, formation of transient TCR-pMHC bonds is a characteristic of immunogenic peptides and is mediated by stabilized interactions.x


title: Eicosanoids in the pancreatic tumor microenvironment: a multicellular, multifaceted progression

abstract: Eicosanoids, oxidized fatty acids that serve as cell-signaling molecules, have been broadly implicated in tumorigenesis. To identify eicosanoids relevant to pancreatic tumorigenesis, we profiled normal pancreas and pancreatic ductal adenocarcinoma (PDAC) in mouse models and patient samples using mass spectrometry. We interrogated RNA sequencing datasets for eicosanoid synthase or receptor expression. Findings were confirmed by immunostaining. In murine models, we identified elevated levels of PGD2, prostacyclin, and thromboxanes in neoplasia while PGE2, 12-HHTre, HETEs, and HDoHEs are elevated specifically in tumors. Analysis of scRNA-seq datasets suggests that PGE2 and prostacyclins are derived from fibroblasts, PGD2 and thromboxanes from myeloid cells, and PGD2 and 5-HETE from tuft cells. In patient samples, we identified a transition from PGD2 to PGE2-producing enzymes in the epithelium during the transition to PDAC, fibroblast/tumor expression of PTGIS, and myeloid/tumor cell expression of TBXAS1. Altogether, our analyses identify key changes in eicosanoid species during pancreatic tumorigenesis and the cell types responsible for their synthesis.

category: cancer biology


title: On the dynamics of spatial updating

abstract: Most of our knowledge on the human neural bases of spatial updating comes from fMRI studies in which recumbent participants moved in virtual environments. As a result, little is known about the dynamic of spatial updating during real body motion. Here, we exploited the high temporal resolution of electroencephalography (EEG) to investigate the dynamics of cortical activation in a spatial updating task where participants had to remember their initial orientation while they were passively rotated about their vertical axis in the dark. After the rotations, the participants pointed towards their initial orientation. We contrasted the EEG signals with those recorded in a control condition in which participants had no cognitive task to perform during body rotations. We found that the amplitude of the P1N1 complex of the rotation-evoked potential (RotEPs) (recorded over the vertex) was significantly greater in the Updating task. The analyses of the cortical current in the source space revealed that the main significant task-related cortical activities started during the N1P2 interval (136-303 ms after rotation onset). They were essentially localised in the temporal and frontal (supplementary motor complex, dorsolateral prefrontal cortex, anterior prefrontal cortex) regions. During this time-window, the right superior posterior parietal cortex (PPC) also showed significant task-related activities. The increased activation of the PPC became bilateral over the P2N2 component (303-470 ms after rotation onset). In this late interval, the cuneus and precuneus started to show significant task-related activities. Together, the present results are consistent with the general scheme that the first task-related cortical activities during spatial updating are related to the encoding of spatial goals and to the storing of spatial information in working memory. These activities would precede those involved in higher order processes also relevant for updating body orientation during rotations linked to the egocentric and visual representations of the environment.

category: paleontology


title: Selective inhibition of PfATP6 by artemisinins and identification of new classes of inhibitors after expression in yeast

abstract:
Treatment failures with artemisinin combination therapies (ACTs) threaten global efforts to eradicate malaria. They highlight the importance of identifying drug targets and new inhibitors and of studying how existing antimalarial classes work.

Herein we report the successful development of an heterologous expression-based compound screening tool. Validated drug target P. falciparum calcium ATPase6 (PfATP6) and a mammalian ortholog (SERCA1a) were functionally expressed in yeast providing a robust, sensitive, and specific screening tool. Whole-cell and in vitro assays consistently demonstrated inhibition and labelling of PfATP6 by artemisinins. Mutations in PfATP6 resulted in fitness costs that were ameliorated in the presence of artemisinin derivatives when studied in the yeast model.

As previously hypothesised, PfATP6 is a target of artemisinins. Mammalian SERCA1a can be mutated to become more susceptible to artemisinins. The inexpensive, low technology yeast screening platform has identified unrelated classes of druggable PfATP6 inhibitors. Resistance to artemisinins may depend on mechanisms that can concomitantly address multi-targeting by artemisinins and fitness costs of mutations that reduce artemisinin susceptibility.

category: pharmacology and toxicology


title: FEMA: Fast and efficient mixed-effects algorithm for population-scale whole brain imaging data

abstract: The linear mixed effects model (LME) is a versatile modeling approach to deal with correlations among observations. Despite the rising importance of LME due to the complex designs of large-scale longitudinal population neuroimaging studies, LME has seldom been used in whole-brain imaging analyses due to its heavy computational requirements. Here, we introduce a fast and efficient mixed-effects algorithm (FEMA) that makes whole-brain vertexwise, voxelwise and connectome-wise LME analyses possible. In a series of realistic simulations, we demonstrate the equivalency of statistical power and control of type I errors between FEMA and classical LME, while showing orders of magnitude improvement in the computational speed. By applying FEMA on diffusion images and resting state functional connectivity matrices from the Adolescent Brain Cognitive Development StudySM (ABCD) release 4.0 data, we show annualized changes in voxelwise fractional anisotropy (FA) and functional connectomes in early adolescence, highlighting a critical time of maturing connections among cortical and subcortical regions. FEMA enables researchers to quickly examine the relationships between large numbers of neuroimaging metrics and variables of interest while considering complex study designs including repeated measures and family structures.

category: neuroscience


title: Offline memory replay in recurrent neuronal networks emerges from constraints on online dynamics

abstract: During spatial exploration, neural circuits in the hippocampus store memories of sequences of sensory events encountered in the environment. When sensory information is absent during "offline" resting periods, brief neuronal population bursts can "replay" sequences of activity that resemble bouts of sensory experience. These sequences can occur in either forward or reverse order, and can even include spatial trajectories that have not been experienced, but are consistent with the topology of the environment. The neural circuit mechanisms underlying this variable and flexible sequence generation are unknown. Here we demonstrate in a recurrent spiking network model of hippocampal area CA3 that experimental constraints on network dynamics such as population sparsity, stimulus selectivity, rhythmicity, and spike rate adaptation enable additional emergent properties, including variable offline memory replay. In an online stimulus-driven state, we observed the emergence of neuronal sequences that swept from representations of past to future stimuli on the timescale of the theta rhythm. In an offline state driven only by noise, the network generated both forward and reverse neuronal sequences, and recapitulated the experimental observation that offline memory replay events tend to include salient locations like the site of a reward. These results demonstrate that biological constraints on the dynamics of recurrent neural circuits are sufficient to enable memories of sensory events stored in the strengths of synaptic connections to be flexibly read out during rest and sleep, which is thought to be important for memory consolidation and planning of future behavior.


title: Visuomotor adaptation modulates the clustering of sleep spindles into trains

abstract:
Sleep spindles are thought to promote memory consolidation. Recently, we have shown that visuomotor adaptation (VMA) learning increases the density of spindles and promotes the coupling between spindles and slow oscillations, locally, with the level of spindle-SO synchrony predicting overnight memory retention. Yet, growing evidence suggests that the rhythmicity in spindle occurrence may also influence the stabilization of declarative and procedural memories. Here, we examined if VMA learning promotes the temporal organization of sleep spindles into trains. We found that VMA increased the proportion of spindles and spindle-SO couplings in trains. In agreement with our previous work, this modulation was observed over the contralateral hemisphere to the trained hand, and predicted overnight memory retention. Interestingly, spindles grouped in a cluster showed greater amplitude and duration than isolated spindles. The fact that these features increased as a function of train length, provides evidence supporting a biological advantage of this temporal arrangement. Our work opens the possibility that the periodicity of NREM oscillations may be relevant in the stabilization of procedural memories.

CONTRIBUTION STATEMENTEver since the discovery of memory systems, the study of the mechanisms supporting the consolidation of declarative and procedural memories has progressed somewhat in parallel. We now know, however, that structures originally thought of as purely declarative such as the hippocampus, participate in the consolidation of procedural tasks. Recently, we showed that sleep predicts long-term motor memory through the local synchrony between fast sleep spindles and slow oscillations, a mechanism initially described for the consolidation of declarative memories. Novel evidence has linked the rhythmicity in the occurrence of spindles to memory stabilization. This framework proposes that temporally clustered spindles into trains of two or more separated by 3-6 seconds, may favor the reinstatement and subsequent reprocessing of previously acquired memories. This temporal arrangement may facilitate mnemonic replay and neocortical integration. In the present study, we show that motor learning promotes the organization of spindles into trains, locally, over the contralateral hemisphere, and that this modulation predicts overnight memory retention. Spindle grouping also augmented the proportion of spindle-SO couplings in trains. Importantly, spindles in a cluster increased their duration and amplitude as a function of train length, pointing to a physiological benefit of this temporal organization.


title: Balancing memory fidelity and representational stability in the female mouse accessory olfactory bulb

abstract: Sensory systems must balance the value of efficient coding schemes against the need to update specific memorized representations without perturbing other memories. Here we describe a unique solution to this challenge that is implemented by the vomeronasal system (VNS) to encode and remember multiple conspecific individuals as part of the Bruce Effect (BE). In the BE, exposure of a pregnant female mouse to the odors of an unfamiliar male leads to failure of the pregnancy ( pregnancy block) via the VNS. Following mating and sensory exposure, however, the female becomes protected from a pregnancy block by the stud individual. While this form of natural learning has been proposed to depend on changes in the representation of his odors in her accessory olfactory bulb (AOB), a key VNS structure, there are no direct comparisons of in vivo sensory responses before and after imprinting. It has further been suggested that these changes simply render the AOB insensitive to stud odors. However, the combinatorial odor code used by the AOB and the significant overlap in the odor composition of different males means that silencing responses to one individual is likely to degrade responses to others, posing potential problems for more general sensory encoding. To identify the neuronal correlates of learning in the context of the BE, we recorded extracellular responses of AOB neurons in vivo in mated and unmated female mice upon controlled presentation of urinary chemosignals, including urine from both the stud and males of a distinct strain. We find that while initial sensory responses in the AOB (within a timescale required to guide social interactions) remain stable, responses to extended stimulation (as required for eliciting the pregnancy block) display selective attenuation of stud-responsive neurons. Based on our results, we propose a model that reconciles the formation of strong, selective memories with the need to sustain robust representational bandwidth by noting a distinction between the representations of brief and extended stimuli. This temporal disassociation allows attenuation of slow-acting endocrine processes in a stimulus-specific manner, without compromising consistent ongoing representations of stimuli that guide behavior.


title: Virally Encoded Connectivity Transgenic Overlay RNA sequencing (VECTORseq) defines projection neurons involved in sensorimotor integration

abstract: Behavior arises from concerted activity throughout the brain. Consequently, a major focus of modern neuroscience is defining the physiology and behavioral roles of projection neurons linking different brain areas. Single-cell RNA sequencing has facilitated these efforts by revealing molecular determinants of cellular physiology and markers that enable genetically targeted perturbations such as optogenetics, but existing methods for sequencing of defined projection populations are low-throughput, painstaking, and costly. We developed a straightforward, multiplexed approach, Virally Encoded Connectivity Transgenic Overlay RNA sequencing (VECTORseq). VECTORseq repurposes commercial retrogradely infecting viruses typically used to express functional transgenes, e.g., recombinases and fluorescent proteins, by treating viral transgene mRNA as barcodes within single-cell datasets. VECTORseq is compatible with different viral families, resolves multiple populations with different projection targets in one sequencing run, and identifies cortical and subcortical excitatory and inhibitory projection populations. Our study provides a roadmap for high-throughput identification of neuronal subtypes based on connectivity.


title: Computational and neural mechanisms of affected beliefs

abstract: The feedback people receive on their behavior shapes the process of belief formation and self-efficacy in mastering a given task. However, the neural and computational mechanisms of how the subjective value of these beliefs, and the corresponding affect, bias the learning process remain unclear. We investigated these mechanisms during the learning of self-efficacy beliefs using fMRI, pupillometry, and computational modeling, and by analyzing individual differences in affective experience. Biases in the formation of self-efficacy beliefs were associated with affect, pupil dilation, and neural activity within the anterior insula, amygdala, ventral tegmental area/ substantia nigra, and mPFC. Specifically, neural and pupil responses map the valence of the prediction errors in correspondence with individuals experienced affect and learning bias during belief formation. Together with the functional connectivity dynamics of the anterior insula within this network, our results hint at neural and computational mechanisms that integrate affect into the process of belief formation.


title: Neurocomputational mechanisms of affected beliefs


title: Long-Term Inactivation of Sodium Channels as a Mechanism of Adaptation in CA1 Pyramidal Neurons

abstract:
Many hippocampal CA1 pyramidal cells function as place cells, increasing their firing rate when a specific place field is traversed. The dependence of CA1 place cell firing on position within the place field is asymmetric. We investigated the source of this asymmetry by injecting triangular depolarizing current ramps to approximate the spatially-tuned, temporally-diffuse depolarizing synaptic input received by these neurons while traversing a place field. Ramps were applied to CA1 pyramidal neurons from male rats in vitro (slice electrophysiology) and in silico (multi-compartmental NEURON model). Under control conditions, CA1 neurons fired more action potentials at higher frequencies on the up-ramp versus the down-ramp. This effect was more pronounced for dendritic compared to somatic ramps. We incorporated a four-state Markov scheme for NaV1.6 channels into our model and calibrated the spatial dependence of long-term inactivation according to the literature; this spatial dependence was sufficient to explain the difference in dendritic versus somatic ramps. Long-term inactivation reduced the firing frequency by decreasing open-state occupancy, and reduced spike amplitude during trains by decreasing occupancy in closed states, which comprise the available pool. PKC activator phorbol-dibutyrate, known to reduce NaV long-term inactivation, removed spike amplitude attenuation in vitro more visibly in dendrites and greatly reduced adaptation, consistent with our hypothesized mechanism. Intracellular application of a peptide inducing long-term NaV inactivation elicited spike amplitude attenuation during spike trains in the soma and greatly enhanced adaptation. Our synergistic experimental/computational approach shows that long-term inactivation of NaV1.6 is a key mechanism of adaptation in CA1 pyramidal cells.

Significance statementThe hippocampus plays an important role in certain types of memory, in part through context-specific firing of "place cells"; these cells were first identified in rodents as being particularly active when an animal is in a specific location in an environment, called the place field of that neuron. In this in vitro/in silico study, we found that long-term inactivation of sodium channels causes adaptation in the firing rate that could potentially skew the firing of CA1 hippocampal pyramidal neurons earlier within a place field. A computational model of the sodium channel revealed differential regulation of spike frequency and amplitude by long-term inactivation, which may be a general mechanism for spike frequency adaptation in the central nervous system.


title: Peripheral NOD-like receptor deficient inflammatory macrophages trigger neutrophil infiltration disrupting daytime locomotion

abstract: Inflammation is known to disrupt normal behavior, yet the underlying neuroimmune interactions remain elusive. Here, we investigated whether inappropriate macrophage-evoked inflammation alters CNS control of daily-life animal locomotion using a set of zebrafish mutants selected for specific macrophage dysfunction and microglia deficiency. Large-scale genetic and computational analyses revealed that NOD-like receptor nlrc3l mutants are capable of normal motility and visuomotor response, but preferentially swim less in the daytime, suggesting low motivation rather than physical impairment. Examining their brain activities and structures implicate impaired dopaminergic descending circuits, where neutrophils abnormally infiltrate. Furthermore, neutrophil depletion recovered daytime locomotion. Restoring wild-type macrophages reversed behavioral and neutrophil aberrations, while three other microglia-lacking mutants failed to phenocopy nlrc3l mutants. Overall, we reveal how peripheral inflammatory macrophages with elevated pro-inflammatory cues (including il1b, tnfa, cxcl8a) in the absence of microglia co-opt neutrophils to infiltrate the brain, thereby enabling local modulation of neural circuits affecting spontaneous locomotion.

category: immunology


title: Hematopoietic stem and progenitor cells improve survival from sepsis by boosting immunomodulatory cells

abstract: New therapeutic strategies to reduce sepsis-related mortality are urgently needed, as sepsis accounts for 1 in 5 deaths worldwide. Since hematopoietic stem and progenitor cells (HSPCs) are responsible for producing blood and immune cells, including in response to immunological stress, we explored their potential for treating sepsis. In a mouse model of Group A Streptococcus (GAS)-induced sepsis, severe immunological stress was associated with significant depletion of bone marrow HSPCs and mortality within approximately 5-7 days. We hypothesized that the inflammatory environment of GAS infection drives rapid HSPC differentiation and depletion that can be rescued by infusion of donor HSPCs. Indeed, infusion of 10,000 naive HSPCs into GAS-infected mice resulted in rapid myelopoiesis and a 50-60% increase in overall survival. Surprisingly, mice receiving donor HSPCs displayed a similar pathogen load compared to untreated mice. Flow cytometric analysis revealed a significantly increased number of myeloid-derived suppressor cells in HSPC-infused mice, which correlated with reduced inflammatory cytokine levels and restored HSPC levels. These findings suggest that HSPCs play an essential immunomodulatory role that may translate into new therapeutic strategies for sepsis.


title: Phototroph-heterotroph interactions during growth and long-term starvation across Prochlorococcus and Alteromonas diversity

abstract:
Microbial interactions such as those between phytoplankton and bacteria been studied intensively using specific model organisms, due to their potential impact on ecosystems and biogeochemistry. Yet, to what extent interactions differ between closely related organisms, or how these interactions change over time or culture conditions, remains unclear. Here, we characterize the interactions between five strains each of two globally abundant marine microorganisms, Prochlorococcus (a phototroph) and Alteromonas (a heterotroph), from the first encounter between individual strains and over more than a year of repeated cycles of exponential growth and long-term nitrogen starvation. Prochlorococcus-Alteromonas interactions had little effect on traditional growth parameters such as Prochlorococcus growth rate, maximal fluorescence or lag phase, affecting primarily the dynamics of culture decline, which we interpret as representing cell mortality and lysis. The shape of the Prochlorococcus decline curve and the carrying capacity of the co-cultures were determined by the phototroph and not the heterotroph strains involved. Comparing various mathematical models of culture mortality suggests that Prochlorococcus death rate increases over time in mono-cultures but decreases in co-cultures, with cells potentially becoming more resistant to stress. Our results demonstrate intra-species differences in ecologically-relevant co-culture outcomes. These include the recycling efficiency of N and whether the interactions are mutually synergistic or competitive. They also highlight the information-rich growth and death curves as a useful readout of the interaction phenotype.

Significance StatementInteractions between phytoplankton and marine bacteria impact global ecosystems and biogeochemistry. Here, we explore how intra-species variability affects the interactions between Prochlorococcus, a globally abundant photosynthetic cyanobacetrium and Alteromonas, a heterotrophic bacterium that lives off and recycles organic matter. Under nitrogen starvation, Prochlorococcus growing alone increasingly accumulate damage and die, whereas in co-culture with Alteromonas they become increasingly resilient. The specific Prochlorococcus strain had a much larger effect on co-culture behavior than the Alteromonas strain, determining whether the interactions are mutually synergistic or potentially competitive. These results show how ecologically relevant outcomes of interactions may vary between closely related microorganisms, and highlight growth and death curves from laboratory (co)-cultures as information-rich views of microbial growth and death.

category: microbiology


title: Genomic diversity of hospital-acquired infections revealed through prospective whole genome sequencing-based surveillance

abstract:
Healthcare-associated infections (HAIs) cause mortality, morbidity, and waste of healthcare resources. HAIs are also an important driver of antimicrobial resistance, which is increasing around the world. Beginning in November 2016, we instituted an initiative to detect outbreaks of HAI using prospective whole genome sequencing-based surveillance of bacterial pathogens collected from hospitalized patients. Here we describe the biodiversity of bacteria sampled from hospitalized patients at a single center, as revealed through systematic analysis of their genomes. We sequenced the genomes of 3,004 bacterial isolates from hospitalized patients collected over a 25-month period. We identified bacteria belonging to 97 distinct species, which were distributed among 14 species groups. Within these groups, isolates could be distinguished from one another by both average nucleotide identity (ANI) and principal component analysis of accessory genes (PCA-A). Genetic distances between isolates and rates of evolution varied between different species, which has implications for the selection of distance cut-offs for outbreak analysis. Antimicrobial resistance genes and the sharing of mobile genetic elements between different species were frequently observed. Overall, this study describes the population structure of pathogens circulating in a single healthcare setting, and shows how investigating microbial population dynamics can inform genomic epidemiology studies.

ImportanceHospitalized patients are at increased risk of becoming infected with antibiotic-resistant organisms. We used whole-genome sequencing to survey and compare over 3,000 bacterial isolates collected from hospitalized patients at a large medical center over a two-year period. We identified nearly 100 different bacterial species, suggesting that patients can be infected with a wide variety of different organisms. When we examined how genetic relatedness differed between species, we found that different species are likely evolving at different rates within our hospital. This is significant because the identification of bacterial outbreaks in the hospital currently relies on genetic similarity cut-offs, which are often applied uniformly across organisms. Finally, we found that antibiotic resistance genes and mobile genetic elements were abundant among the bacterial isolates we sampled. Overall, this study provides an in-depth view of the genomic diversity and evolution of bacteria sampled from hospitalized patients, as well as genetic similarity estimates that can inform hospital outbreak detection and prevention efforts.


title: Patient-derived endometrial organoids from MRKH patients: Insight in disease causing pathways

abstract: The uterus is responsible for the nourishment and mechanical protection of the developing embryo and fetus and is an essential part in mammalian reproduction. The Mayer-Rokitansky-Kuster-Hauser (MRKH) syndrome is characterized by agenesis of the uterus and upper part of the vagina in females with normal ovarian function. Although heavily studied, the cause of the disease is still enigmatic. Current research in the field of MRKH mainly focusses on DNA-sequencing efforts and, so far, failed to decipher the nature and heterogeneity of the disease, thereby holding back scientific and clinical progress. Here, we developed long-term expandable organoid cultures from endometrium found in uterine rudiment horns of MRKH patients. Phenotypically, they share great similarity with healthy control organoids and are surprisingly fully hormone responsive. Transcriptome analyses, however, identified an array of dysregulated genes that point at potentially disease-causing pathways altered during the development of the female reproductive tract. We consider the endometrial organoid cultures to be a powerful research tool that promise to enable an array of studies into the pathogenic origins of MRKH syndrome and possible treatment opportunities to improve patient quality of life.

category: developmental biology


title: Plant secondary metabolite diversity reflects both phylogeny and ecological adaptation

abstract: A phylogenetic framework explaining plant secondary metabolite diversity is lacking, but metabolite classes could represent adaptations to habitat resource availability. We test the hypothesis that primary adaptive strategies (competitors, C; stress-tolerators, S; ruderals, R) are associated, respectively, with nitrogenous metabolites synthesized in persistent organs (alkaloids), nitrogen-lacking aromatic terpenes and phenolics, and nitrogenous compounds prevalent in reproductive tissues (cyanogenic glucosides and glucosinolates). A matrix was compiled of 1019 species for which secondary metabolite pathways and CSR strategies are known. Accounting for phylogenetic relatedness and native biomes, we found that most phytochemical pathways did not correlate with strategy axes, but certain key associations were evident. C-selection was positively associated with amino acid-derived phenylpropanoids (low phylogenetic relatedness; {lambda} <0.5) and pyrrolizidine alkaloids and galloyl derivatives (high {lambda}), and negatively with N-lacking linear monoterpenes (low {lambda}). Nitrogenous cyanogenic glucosides positively correlated with R-selection (low {lambda}). Terpenoids were widely distributed, but correlated positively with S- and negatively with R-selection (low {lambda}). Twenty-six correlations between phytochemicals and biomes (low {lambda}) were evident. Most secondary metabolite synthesis pathways are widespread, reflecting common roles and obligate defence, and strong phylogenetic effects are often evident. However, the character of phytochemical/adaptive strategy associations agrees with ecological theory and thus reflects adaptation.

category: ecology


title: Different mycorrhizal nutrient acquisition strategies shape tree species competition and coexistence dynamics

abstract: Mycorrhizal fungi with different nutrient acquisition strategies influence the functional separation among plant species. This might drive resource competition dynamics that cumulatively impact tree species coexistence, but few manipulative experiments have directly tested this. Combining surveys and experiments in a modern coexistence theory framework, we tested how variation in mycorrhizal strategies and nutrient conditions affect competitive outcomes between co-occurring ectomycorrhizal (EM) and arbuscular mycorrhizal (AM) tree species. The dependency on EM symbioses increased with latitude and nitrogen (N) limitation, matching global trends. Host-specific soil microbiome conditioning and N fertilization combined to qualitatively affect coexistence outcomes. Lower N conditions favored EM over AM trees, but N fertilization reversed this outcome for southern species, consistent with regional-scale forest mycorrhizal transitions. As the magnitude and outcome of microbially-mediated competition depends on mycorrhizal differentiation and soil nutrient availability, this strongly supports the importance of mycorrhizal symbioses in driving large-scale biogeographic patterns of tree species.


title: How far to build it before they come? Analyzing the use of the Field of Dreams hypothesis in bull kelp restoration

abstract:
In restoration ecology, the Field of Dreams Hypothesis posits that restoration efforts that create a suitable environment could lead to eventual recovery of the remaining aspects of the ecosystem through natural processes. Natural processes following partial restoration has lead to ecosystem recovery in both terrestrial and aquatic systems. However, understanding the efficacy of a "field of dreams" approach requires comparison of different approaches to partial restoration in terms of spatial, temporal, and ecological scale to what would happen with more comprehensive restoration efforts. We explore the relative effect of partial restoration and ongoing recovery on restoration efficacy with a dynamical model based on temperate rocky reefs in Northern California. We analyze our model for both the ability and rate of bull kelp forest recovery under different restoration strategies. We compare the efficacy of a partial restoration approach with a more comprehensive restoration effort by exploring how kelp recovery likelihood and rate change with varying intensities of urchin removal and kelp outplanting over different time periods and spatial scales. We find that, for the case of bull kelp forests, setting more favorable initial conditions for kelp recovery through implementing both urchin harvesting and kelp outplanting at the start of the restoration project has a bigger impact on the kelp recovery rate than applying restoration efforts through a longer period of time. Therefore partial restoration efforts, in terms of spatial and temporal scale, can be significantly more effective when applied across multiple ecological scales in terms of both the capacity and rate of achieving the target outcomes.

Open Research StatementThe data used in this work is presented in McPherson et al. (2021). The code used to run the simulations can be found in https://github.com/jarroyoe/kelp-restoration-modeling


title: Cryptic individual-level variation in propensity for selfing in a hermaphroditic snail

abstract:
For mating-system evolution, individual-level variation is essential. In self-compatible hermaphrodites, individuals may vary in their lifetime propensity for selfing, which consists of an individual and environmental component. According to the reproductive assurance hypothesis explaining partial selfing, a key environmental factor is mate availability, which fluctuates with population density.

We quantified individual variation in selfing propensity in a hermaphroditic snail by manipulating mate availability, recording mating behaviour, estimating selfing rates from progeny arrays, and measuring female lifetime fitness. We found four classes of individuals: pure outcrossers, pure selfers, and two types of plastic individuals. These classes only became apparent in the laboratory; the field population is outcrossing. All classes were present both under low and increased mate availability. This large variation in selfing propensities rendered effects of differential mate availability on selfing rates non-significant despite large effect sizes and sufficient statistical power.

We suspect that selfing propensities have a genetic component and when selected on cause mean selfing rates to evolve. We propose that heritable variation in selfing propensities offers a reconciliation between the reproductive assurance hypothesis and its weak empirical support: distributions of selfing propensities vary temporally and spatially, thus obscuring the relationship between population density and realised selfing rates.

category: evolutionary biology


title: Shift-inducible  increase in recombination rate as an evolving strategy in a periodic environment: a numerical model

abstract: Numerous empirical studies have witnessed a plastic increase in meiotic recombination rate in organisms experiencing physiological stress due to unfavourable environmental conditions. Yet, it is not clear enough which characteristics of an ecological factor (intensity, duration, variability, etc.) make it stressogenic and therefore recombinogenic for an organism. Several previous theoretical models proceeded from the assumption that organisms increase their recombination rate when the environment becomes more severe, and demonstrated the evolutionary advantage of such recombination strategy. Here we explore another stress-associated recombination strategy, implying a reversible increase in recombination rate each time when the environment alternates. We allow such plastic changes in the organisms, grown in an environment different from that of their parents, and, optionally, also in their offspring. We show that such shift-inducible recombination is always favoured over intermediate constant optimal recombination. Besides, it sometimes outcompetes also zero and free optimal constant recombination, therefore making selection on recombination less polarized. Shift-inducible strategies with a longer, transgenerational plastic effect, are favoured under slightly stronger selection and longer period. These results hold for both panmixia and partial selfing, although selfing makes the dynamics of recombination modifier alleles faster. Our results suggest that epigenetic factors, presumably underlying the environmental plasticity of recombination, may play an important evolutionary role.


title: Using the UK Biobank as a global reference of worldwide populations: application to measuring ancestry diversity from GWAS summary statistics

abstract: The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on almost 500,000 individuals from across the United Kingdom. Within this dataset, we carefully define 21 distinct ancestry groups from all four corners of the world. These ancestry groups can serve as a global reference of worldwide populations, with a handful of applications. As an example application here, we use allele frequencies derived from these ancestry groups to effectively measure diversity from summary statistics of any genetic dataset. Measuring genetic diversity is an important problem because increasing genetic diversity is key to making new genetic discoveries, while also being a major source of confounding to be aware of in genetics studies.

category: genetics


title: Major sex differences in allele frequencies for X chromosome variants in the 1000 Genomes Project data

abstract: An unexpectedly high proportion of SNPs on the X chromosome in the 1000 Genomes Project phase 3 data were identified with significant sex differences in minor allele frequencies (sdMAF). sdMAF persisted for many of these SNPs in the recently released high coverage whole genome sequence, and it was consistent between the five super-populations. Among the 245,825 common biallelic SNPs in phase 3 data presumed to be high quality, 2,039 have genome-wide significant sdMAF (p-value <5e-8). sdMAF varied by location: (NPR)=0.83%, pseudo-autosomal region (PAR1)=0.29%, PAR2=13.1%, and PAR3=0.85% of SNPs had sdMAF, and they were clustered at the NPR-PAR boundaries, among others. sdMAF at the NPR-PAR boundaries are biologically expected due to sex-linkage, but have generally been ignored in association studies. For comparison, similar analyses found only 6, 1 and 0 SNPs with significant sdMAF on chromosomes 1, 7 and 22, respectively. Future X chromosome analyses need to take sdMAF into account.


title: Integration of GWAS and TWAS to elucidate the genetic architecture of natural variation for leaf cuticular conductance in maize

abstract:
The cuticle, a hydrophobic layer of cutin and waxes synthesized by plant epidermal cells, is the major barrier to water loss when stomata are closed. Dissecting the genetic architecture of natural variation for maize leaf cuticular conductance (gc) is important for identifying genes relevant to improving crop productivity in drought-prone environments. To this end, we performed an integrated genome- and transcriptome-wide association study (GWAS/TWAS) to identify candidate genes putatively regulating variation in leaf gc. Of the 22 plausible candidate genes identified, five were predicted to be involved in cuticle precursor biosynthesis and export, two in cell wall modification, nine in intracellular membrane trafficking, and seven in the regulation of cuticle development. A gene encoding an INCREASED SALT TOLERANCE1-LIKE1 (ISTL1) protein putatively involved in intracellular protein and membrane trafficking was identified in GWAS and TWAS as the strongest candidate causal gene. A set of maize nested near-isogenic lines that harbor the ISTL1 genomic region from eight donor parents were evaluated for gc, confirming the association between gc and ISTL1 in a haplotype-based association analysis. The findings of this study provide novel insights into the role of regulatory variants in the development of the maize leaf cuticle, and will ultimately assist breeders to develop drought-tolerant maize for target environments.

Sentence summaryWe performed an integrated GWAS/TWAS and identified 22 candidate genes putatively regulating variation in maize leaf gc. The association between gc and the strongest candidate causal gene, ISTL1, was validated with maize nested near-isogenic lines.


title: Actinosomes: condensate-templated proteinaceous containers for engineering synthetic cells

abstract: Engineering synthetic cells has a broad appeal, from understanding living cells to designing novel biomaterials for therapeutics, biosensing, and hybrid interfaces. A key prerequisite to creating synthetic cells is a functional three-dimensional container capable of orchestrating biochemical reactions. In this study, we present an easy and effective technique to make cell-sized porous containers crafted using the interactions between biomolecular condensates and actin cytoskeleton - we coin them actinosomes. This approach uses polypeptide/nucleoside triphosphate condensates and localizes actin monomers on their surface. By triggering actin polymerization at the expense of sequestered ATP and using osmotic gradients, the condensates are structurally transformed into containers with the boundary made up of actin filaments and polylysine polymers. We show that the GTP-to-ATP ratio is a crucial parameter for forming actinosomes: insufficient ATP prevents condensate dissolution while excess ATP leads to undesired crumpling. The surface of actinosomes lacks any structural order and is porous. We show the functionality of the actinosomes by using them as bioreactors capable of protein synthesis. Actinosomes are a handy addition to the synthetic cell platform, with appealing properties like ease-of-production, inherent encapsulation capacity, and an active surface which holds the potential to trigger signaling cascades and form multicellular assemblies, with potential for medical and biotechnological applications.


title: DLA-Ranker: Evaluating protein docking conformations with many locally oriented cubes.

abstract: Proteins ensure their biological functions by interacting with each other, and with other molecules. Determining the relative position and orientation of protein partners in a complex remains challenging. Here, we address the problem of ranking candidate complex conformations toward identifying near-native conformations. We propose a deep learning approach relying on a local representation of the protein interface with an explicit account of its geometry. We show that the method is able to recognise certain pattern distributions in specific locations of the interface. We compare and combine it with a physics-based scoring function and a statistical pair potential.


title: LungCancer3D: A Comprehensive Database for Integrating Lung Cancer Chromatin Architecture with Other Multi-omics

abstract: With the breakthrough of chromatin conformation capture technologies in recent years, the importance of three-dimensional (3D) genome structure in gene expression, cell function regulation, disease occurrence, and development has been gradually recognized. To provide a comprehensive visualization of chromatin architecture and other multi-omics data for lung cancer research, we have constructed a comprehensive database, LungCancer3D (http://www.lungcancer3d.net). This web-based tool focuses on displaying human lung cancer-related HiC data along with a variety of other publicly available data, such as RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, DNA methylation, DNA mutation, and copy number variations. Researchers can visualize these diverse multi-omics data directly through the genome browser and discover how the genes expression is regulated at diverse levels. For example, we have demonstrated that the high expression level of C-MYC in lung cancer may be caused by the distant enhancer introduced by the de novo chromatin loops in lung cancer cells to bind the C-MYC promoter. The integrated multi-omics analyses through the LungCancer3D website can reveal the mechanisms underlying lung cancer development and provide potential targets for lung cancer therapy.


title: RCX - an R package adapting the Cytoscape Exchange format for biological networks

abstract:
MotivationThe Cytoscape Exchange (CX) format is a JSON-based data structure designed for the transmission of biological networks using standard web technologies. It was developed by the network data exchange (NDEx), which itself serves as online commons to share and collaborate on biological networks. Furthermore, the Cytoscape software for the analysis and visualization of biological networks contributes structure elements to capture the visual layout within the CX format. However, there is a fundamental difference between data handling in web standards and R. A manual conversion requires detailed knowledge of the CX format to reproduce and work with the networks.

ResultsHere we present a software package to create, handle, validate, visualize and convert networks in CX format to standard data types and objects within R. Networks in this format can serve as a source for biological knowledge, and also capture the results of the analysis of those while preserving the visual layout across all platforms. The RCX package connects the R environment for statistical computing with outside platforms for storage and collaboration, as well as further analysis and visualization of biological networks.

AvailabilityRCX is a free and open-source R package, available on Bioconductor from release 3.15 (https://bioconductor.org/packages/RCX) and via GitHub (https://github.com/frankkramer-lab/RCX).

Contactflorian.auer@informatik.uni-augsburg.de

Supplementary informationSupplementary data are available at Bioinformatics Advances online.


title: Curated Single Cell Multimodal Landmark Datasets for R/Bioconductor

abstract:
BackgroundThe majority of high-throughput single-cell molecular profiling methods quantify RNA expression; however, recent multimodal profiling methods add simultaneous measurement of genomic, proteomic, epigenetic, and/or spatial information on the same cells. The development of new statistical and computational methods in Bioconductor for such data will be facilitated by easy availability of landmark datasets using standard data classes.

ResultsWe collected, processed, and packaged publicly available landmark datasets from important single-cell multimodal protocols, including CITE-Seq, ECCITE-Seq, SCoPE2, scNMT, 10X Multiome, seqFISH, and G&T. We integrate data modalities via the MultiAssayExperiment Bioconductor class, document and re-distribute datasets as the SingleCellMultiModal package in Bioconductors Cloud-based ExperimentHub. The result is single-command actualization of landmark datasets from seven single-cell multimodal data generation technologies, without need for further data processing or wrangling in order to analyze and develop methods within Bioconductors ecosystem of hundreds of packages for single-cell and multimodal data.

ConclusionsWe provide two examples of integrative analyses that are greatly simplified by SingleCellMultiModal. The package will facilitate development of bioinformatic and statistical methods in Bioconductor to meet the challenges of integrating molecular layers and analyzing phenotypic outputs including cell differentiation, activity, and disease.


title: A BERT-Based Hybrid System for Chemical Identification and Indexing in Full-Text Articles

abstract: Identification and indexing of chemical compounds in full-text articles are essential steps in biomedical article categorization, information extraction, and biological text mining. BioCreative Challenge was established to evaluate methods for biological text mining and information extraction. Track 2 of BioCreative VII (summer 2021) consists of two subtasks: chemical identification and chemical indexing in full-text PubMed articles. The chemical identification subtask also includes two parts: chemical named entity recognition (NER) and chemical normalization. In this paper, we present our work on developing a hybrid pipeline for chemical named entity recognition, chemical normalization, and chemical indexing in full-text PubMed articles. Specifically, we applied BERT-based methods for chemical NER and chemical indexing, and a sieve-based dictionary matching method for chemical normalization. For subtask 1, we used PubMedBERT with data augmentation on the chemical NER task. Several chemical-MeSH dictionaries including MeSH.XML, SUPP.XML, MRCONSO.RFF, and PubTator chemical annotations are used in a specific order to get the best performance on chemical normalization. We achieved an F1 score of 0.86 and 0.7668 on chemical NER and chemical normalization, respectively. For subtask 2, we formulated it as a binary prediction problem for each individual chemical compound name. We then used a BERT-based model with engineered features and achieved a strict F1 score of 0.4825 on the test set, which is substantially higher than the median F1 score (0.3971) of all the submissions.


title: DyScore: A Boosting Scoring Method with Dynamic Properties for Identifying True Binders and Non-binders in Structure-based Drug Discovery

abstract:
The accurate prediction of protein-ligand binding affinity is critical for the success of computer-aided drug discovery. However, the accuracy of current scoring functions is usually unsatisfactory due to their rough approximation or sometimes even omittance of many factors involved in protein-ligand binding. For instance, the intrinsic dynamic of the protein-ligand binding state is usually disregarded in scoring function because these rapid binding affinity prediction approaches are only based on a representative complex structure of the protein and ligand in the binding state. That is, the dynamic protein-ligand binding complex ensembles are simplified as a static snapshot in calculation. In this study, two novel features were proposed for characterizing the dynamic properties of protein-ligand binding based on the static structure of the complex, which is expected to be a valuable complement to the current scoring functions. The two features demonstrate the geometry-shape matching between a protein and a ligand as well as the dynamic stability of protein-ligand binding. We further combined these two novel features with several classical scoring functions to develop a binary classification model called DyScore that uses the Extreme Gradient Boosting algorithm to classify compound poses as binders or non-binders. We have found that DyScore achieves state-of-the-art performance in distinguishing active and decoy ligands on both enhanced DUD dataset and external test set with both proposed novel features showing significant contributions to the improved performance. Especially, DyScore exhibits superior performance on early recognition, a crucial requirement for success in virtual screening and de novo drug design. The DyScore webserver is freely available to all at: http://dyscore.deepdrug.net.

Key PointsO_LITwo novel binding features were proposed for characterizing the dynamic properties of protein-ligand binding only based on a static snapshot of complex.
C_LIO_LIBased on the XGBoost machine learning method, the DyScore recognition model was proposed to accurately classify compound binding poses as binders or non-binders. DyScore consistently outperforms all the state-of-the-art published models on three different metrics by a large margin.
C_LIO_LIDyScore showed superior performance in early recognition with an average of 73.3% success rate for the top three ranked compounds for each protein target.
C_LIO_LIThe DyScore web-server is freely available to all at the following website: http://dyscore.deepdrug.net.
C_LI


title: Loss of p16INK4a in neuroblastoma cells induces shift to an immature state with mesenchymal characteristics and increases sensitivity to EGFR inhibitors

abstract: Homozygous inactivation of the CDKN2A locus is one of the most common genomic aberrations in human cancer. The locus codes for two unrelated and distinctly regulated proteins: p14ARF and p16INK4a, which inhibit MDM2 and CDK4/6, respectively. Loss of CDKN2A is also a recurrent event in relapsed neuroblastoma, a childhood tumour that arises from neural crest cells. To examine the consequences of the loss of the two distinct gene transcripts in neuroblastoma, we used the CRISPR-Cas9 system to knockout p14, p16 and p14+p16 in SY5Y cells. RNA sequencing of the transcriptome revealed a striking shift towards an immature Schwann cell precursor-like phenotype with mesenchymal characteristics, specifically in the p16 and p14+p16 knockouts. High-throughput drug screening of p16 and p14+p16 knockout clones identified a large increase in sensitivity to EGFR inhibitors. On protein level, we were able to confirm that EGFR pathway activation is higher in p14+p16 knockout cells and that treatment with the EGFR inhibitor afatinib resulted in higher levels of apoptosis. Afatinib also reduced tumour growth in vivo in xenografts transplanted with p14+p16 knockout SY5Y cells. Overall, our study suggests that CDKN2A deletion in neuroblastoma relates to a phenotypic shift towards a more progenitor like state and increases sensitivity to EGFR inhibitors.


title: Automated Hyperspectral Vegetation Index Derivation Using A Hyperparameter Optimization Framework for High-Throughput Plant Phenotyping

abstract:
O_LIHyperspectral vegetation indices (VIs) are widely deployed in agriculture remote sensing and plant phenotyping to estimate plant biophysical and biochemical traits. However, existing VIs consist mainly of simple 2-band indices which limits the net performance and often do not generalize well for other traits than they were originally designed for.
C_LIO_LIWe present an automated hyperspectral vegetation index (AutoVI) system for the rapid generation of novel 2- to 6-band trait-specific indices in a streamlined process covering model selection, optimization and evaluation driven by the tree parzen estimator algorithm. Its performance was tested in generating novel indices to estimate chlorophyll and sugar contents in wheat.
C_LIO_LIResults show that AutoVI can rapidly generate complex novel VIs ([≥]4-band index) which correlated strongly (R2 > 0.8) with measured chlorophyll and sugar contents in wheat. AutoVI-derived indices were used as features in simple and stepwise multiple linear regression for chlorophyll and sugar content estimation, and outperformed results achieved with existing 47 VIs and those provided by partial least squares regression.
C_LIO_LIThe AutoVI system can deliver novel trait-specific VIs readily adoptable in high-throughput plant phenotyping platforms and should appeal to plant scientists and breeders. A graphical user interface of AutoVI is herein provided.
C_LI

category: plant biology


title: Activating natural product synthesis using CRISPR interference and activation systems in Streptomyces

abstract: The rise of antibiotic-resistant bacteria represents a major threat to global health, creating an urgent need to discover new antibiotics. Natural products derived from the genus Streptomyces represent a rich and diverse repertoire of chemical molecules from which new antibiotics are likely to be found. However, a major challenge is that the biosynthetic gene clusters (BGCs) responsible for natural product synthesis are often poorly expressed under laboratory culturing conditions, thus preventing isolation and screening of novel chemicals. To address this, we describe a novel approach to activate silent BGCs through rewiring endogenous regulation using synthetic gene regulators based upon CRISPR-Cas. First, we create CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) systems that allow for highly programmable and effective gene repression and activation in Streptomyces. We then harness these tools to activate a silent BGC through perturbing its endogenous regulatory network. Together, this work advances the synthetic regulatory toolbox for Streptomyces and facilitates the programmable activation of silent BGCs for novel chemical discovery.

category: synthetic biology


title: Reduced myofibroblast transdifferentiation and fibrotic scarring in ischemic stroke after imatinib treatment

abstract: The tyrosine kinase inhibitor imatinib has been reported to improve outcome in patients following ischemic stroke but the exact mechanism remains elusive. Here, utilizing a photothrombotic murine model of middle cerebral artery occlusion (MCAO), we show that imatinib-mediated inhibition of stroke-induced blood-brain barrier (BBB) dysfunction coincided with decreased expression of genes associated with inflammation and fibrosis in the cerebrovasculature. We found that imatinib effectively dampened stroke-induced reactive gliosis and myofibroblast transdifferentiation, whilst having very limited effect on the rest of the glia scar and on peripheral leukocyte infiltration. Further, our data suggest that consolidation of the PDGFR+ portion of the fibrotic scar in imatinib-treated mice contributes to the improvement in functional outcome compared to the vehicle controls, where the PDGFR+ scar is expanding. Comparison with human stroke transcriptome databases revealed significant overlap with imatinib-regulated genes, suggesting imatinib may modulate reactive gliosis and fibrotic scarring also in human stroke.


title: Microglia-specific promoter activities of human HexB gene

abstract:
Adeno-associated virus (AAV)-mediated genetic targeting of microglia remains challenging. Overcoming this hurdle is essential for gene editing in the central nervous system (CNS). Here, we characterized the minimal/native promoter of the HexB gene, which is known to be specifically and stably expressed in the microglia during homeostatic and pathological conditions. Dual reporter and serial deletion assays identified the critical role of the natural 5 untranslated region (-97 bp related to the first ATG) in driving transcriptional activity of the mouse HexB gene. The native promoter region of mouse, human and monkey HexB located at -135, -134 and -170 bp to the first ATG, respectively. These promoters were highly active and specific in microglia with strong cross-species transcriptional activities, but had no activities in primary astrocytes. In addition, we identified a 135 bp promoter of CD68 gene was also highly active in microglia but not in astrocytes. Considering that HexB is specifically expressed in microglia, not in monocytes/macrophages or other neuronal cells, these data suggest that the newly characterized 134 bp microglia-specific HexB promoter can be an ideal candidate for microglia-targeting AAV gene therapy, which could be developed for HIV eradication in the brain wherein microglia harbor the main HIV reservoirs in the CNS.

SummaryIt is hard to overstate the importance of gene therapy that can remove viral genes from human cells. A cure for HIV would mean a lifetime free of treatment for patients who now must maintain a strict regimen of ART indefinitely. In order to develop a cure using AAV delivery, payload DNA must meet the AAV vector size limitations, and the payload genes must be expressed appropriately. Previous studies have identified microglia-specific HexB gene that shows stable expression during neural homeostasis and pathogenesis. Our study identified the essential HexB gene promoter (134 bp) as a strong candidate for AAV gene therapy to specifically target the brain microglia, the main cellular reservoirs of HIV in the central nervous system. Our studies continue to move us closer to identifying target-specific gene therapy for NeuroAIDS.


title: Brain macrophages acquire distinct transcriptomes prior to demyelination in multiple sclerosis

abstract: Multiple sclerosis (MS) is a disease of the central nervous system (CNS) that is characterized by inflammation and focal areas of demyelination, ultimately resulting in axonal degradation and neuronal loss. Several lines of evidence point towards a role for microglia and other brain macrophages in disease initiation and progression, but exactly how lesion formation is triggered is currently unknown. Here, we characterized early changes in MS brain tissue through transcriptomic analysis of normal appearing white matter (NAWM). We found that NAWM was characterized by enriched expression of genes associated with inflammation and cellular stress derived from brain macrophages. Single cell RNA sequencing confirmed an early stress response in brain macrophages in NAWM and identified specific macrophage subsets that associate with different stages of demyelinating lesions. These early changes associated with lesion development in MS brain tissue may provide therapeutic targets to limit lesion progression and demyelination.


title: Parameter and model recovery of reinforcement learning models for restless bandit problems

abstract:
Multi-armed restless bandit tasks are regularly applied in psychology and cognitive neuroscience to assess exploration and exploitation behavior in structured environments. These models are also readily applied to examine effects of (virtual) brain lesions on performance, and to infer neurocomputational mechanisms using neuroimaging or pharmacological approaches. However, to infer individual, psychologically meaningful parameters from such data, computational cognitive modeling is typically applied. Recent studies indicate that softmax (SM) decision rule models that include a representation of environmental dynamics (e.g. the Kalman Filter) and additional parameters for modeling exploration and perseveration (Kalman SMEP) fit human bandit task data better than competing models. Parameter and model recovery are two central requirements for computational models: parameter recovery refers to the ability to recover true data-generating parameters; model recovery refers to the ability to correctly identify the true data generating model using model comparison techniques. Here we comprehensively examined parameter and model recovery of the Kalman SMEP model as well as nested model versions, i.e. models without the additional parameters, using simulation and Bayesian inference. Parameter recovery improved with increasing trial numbers, from around .8 for 100 trials to around .93 for 300 trials. Model recovery analyses likewise confirmed acceptable recovery of the Kalman SMEP model. Model recovery was lower for nested Kalman filter models as well as delta rule models with fixed learning rates.

Exploratory analyses examined associations of model parameters with model-free performance metrics. Random exploration, captured by the inverse softmax temperature, was associated with lower accuracy and more switches. For the exploration bonus parameter modeling directed exploration, we confirmed an inverse-U-shaped association with accuracy, such that both an excess and a lack of directed exploration reduced accuracy. Taken together, these analyses underline that the Kalman SMEP model fulfills basic requirements of a cognitive model.


title: Diverse B-cell specific transcriptional contexts of the BCL2 oncogene in mouse models impacts pre-malignant development

abstract: Follicular lymphoma (FL) is the most common indolent form of non-Hodgkin lymphoma arising from malignant germinal center (GC) B-cells. The genetic hallmark that leads to the development of FL is the t(14:18) which occurs early in the bone marrow during B cell development, thereby placing the anti-apoptotic BCL2 gene under the direct control of the transcriptional enhancers in 3 of immunoglobulin heavy chain locus (IgH 3RR) and leading to the constitutive expression of the BCL2 protein. To assess the impact of the BCL2 deregulation on B-cell fate and try to reproduce FL development in mice, two models were designed: the Ig{kappa}-BCL2 (Knock in of the BCL2 in the light chain Ig kappa locus) and the 3RR-BCL2 (Transgene containing BCL2 and a micro-3RR), both containing the full BCL2 promoter region.


title: Longitudinal clonal dynamics of HIV-1 latent reservoirs measured by combination quadruplex polymerase chain reaction and sequencing

abstract:
HIV-1 infection produces a long-lived reservoir of latently infected CD4+ T cells that represents the major barrier to HIV-1 cure. The reservoir contains both intact and defective proviruses, but only the proviruses that are intact can re-initiate infection upon cessation of antiretroviral therapy (ART). Here we combine 4 color quantitative polymerase chain reaction and next-generation sequencing (Q4PCR) to distinguish intact and defective proviruses and measure reservoir content longitudinally in 12 infected individuals. Q4PCR differs from other PCR based methods in that the amplified proviruses are sequence verified as intact or defective. Samples were collected systematically over the course of up to 10 years beginning shortly after the initiation of ART. The size of the defective reservoir was relatively stable with minimal decay during the 10-year observation period. In contrast, the intact proviral reservoir decayed with estimated half-life of 4.9 years. Nevertheless, both intact and defective proviral reservoirs are dynamic. As a result, the fraction of intact proviruses found in expanded clones of CD4+ T cells increases overtime with a concomitant decrease in overall reservoir complexity. Thus, reservoir decay measurements by Q4PCR are quantitatively similar to viral outgrowth (VOA) and intact proviral DNA PCR (IPDA) with the addition of sequence information that distinguishes intact and defective proviruses and informs reservoir dynamics. The data is consistent with the notion that intact and defective proviruses are under distinct selective pressure, and that the intact proviral reservoir is progressively enriched in expanded clones of CD4+ T cells resulting in diminishing complexity over time.

SignificanceHIV-1 infection requires lifelong treatment with antiretroviral therapy (ART) due to viral rebound of a latent reservoir of intact, transcriptionally silent provirus found to persist in the genome of CD4+ T cells. One of the major challenges to understanding the nature of the latent reservoir is accurately characterizing the measuring the size of the reservoir. Herein, we use quadruplex polymerase chain reaction (Q4PCR) to assess the dynamics of the latent reservoir in HIV+ individuals who have been on long-term ART for up to 10 years. Our results show that Q4PCR can be used to accurately measure the latent reservoir, while providing the added benefit of assessing the genetic diversity of the reservoir to better understand changes to clonal dynamics overtime.


title: Salmonella exploits OmpR to switch essential morphogenetic peptidoglycan synthases in response to intracellular cues

abstract:
Essential peptidoglycan synthases, like penicillin binding proteins 2 and 3 (PBP2/PBP3) of Escherichia coli, define shape by orchestrating cell elongation and division, respectively. Despite being intensively studied as drug targets, the regulatory rules governing their production remain poorly understood. During infection, the closely related pathogen Salmonella enterica serovar Typhimurium downregulates PBP2/PBP3 production and replace them with alternative peptidoglycan synthases, PBP2SAL/PBP3SAL, absent in E. coli. The bases for such switch in morphogenetic proteins are unknown. Here, we show that the S. Typhimurium regulator OmpR triggers PBP2SAL and PBP3SAL expression responding solely to acid pH and define a shared motif present in upstream regions of the PBP2SAL- and PBP3SAL-coding genes sufficient for such control. The elimination of PBP2/PBP3 in infection conditions is however multifactorial, requiring acidity, high osmolarity and being favoured by OmpR and the Prc protease. Remarkably, we found that E. coli loses the essential PBP3 required for cell division when exposed to both acidity and high osmolarity, the environmental cues encountered by intracellular S. Typhimurium. Therefore, OmpR played a central role in the evolution of this pathogen when co-opting the regulation of PBP2SAL/PBP3SAL and, consequently, promoting a new morphogenetic cycle that made possible increasing progeny inside acidic eukaryotic phagosomes.

SignificanceSome enzymes that participate in peptidoglycan metabolism are present exclusively in bacterial pathogens and modify its structure to limit immune recognition. The intracellular pathogen Salmonella enterica serovar Typhimurium is the only example known to date in which a "substitution" of essential peptidoglycan enzymes involved in cell division and elongation takes place during infection. The data presented here support instability of PBP3 in environments with acidity and high osmolarity as a probable selective pressure that promoted the fixation of alternative morphogenetic enzymes. This was possible due to the control that OmpR exerted over these new foreign functions. The acquisition of enzymes like PBP2SAL and PBP3SAL therefore represent a "quantum leap" evolutionary event in S. Typhimurium that made possible the colonization of acidic intracellular niches.


title: Investigating pathogenicity and virulence of Staphylococcus pettenkoferi: an emerging pathogen

abstract: Staphylococcus pettenkoferi is a coagulase-negative Staphylococcus identified in 2002 that has been implicated in human diseases as an opportunistic pathogenic bacterium. Its multiresistant character is becoming a major health problem, yet the pathogenicity of S. pettenkoferi is poorly characterized. In this study, pathogenicity of a S. pettenkoferi clinical isolate from diabetic foot osteomyelitis was compared to a Staphylococcus aureus strain in various in vitro and in vivo experiments. Growth kinetics were compared against S. aureus and bacteria survival was assessed in the RAW 264.7 murine macrophage cell line, the THP-1 human leukemia monocytic cell line and the HaCaT human keratinocyte cell line. Ex vivo analysis were performed in whole blood survival assays, and in vivo assays via the infection model of zebrafish embryos. Moreover, whole-genome analysis was performed. Our results showed that S. pettenkoferi was able to survive in human blood, human keratinocytes, murine macrophages, and human macrophages. S. pettenkoferi demonstrated its virulence by causing substantial embryo mortality in the zebrafish model. Genomic analysis revealed virulence factors such as biofilm- (e.g., icaABCD; rsbUVW) and regulator- (e.g., agr, mgrA, sarA, saeS) encoding genes well characterized in S. aureus. This study thus advances the knowledge of this under investigated pathogen and validates the zebrafish infection model for this bacterium.


title: Daily feeding rhythm linked to microbiome composition in two zooplankton species

abstract: Host-associated microbial communities are impacted by external and within-host factors, i.e., diet and feeding behavior. For organisms known to have a circadian rhythm in feeding behavior, microbiome composition is likely impacted by the different rates of microbe introduction and removal across a daily cycle, in addition to any diet-induced changes in microbial interactions. Here, we measured feeding behavior and used 16S rRNA sequencing to compare the microbial community across a diel cycle in two distantly related species of Daphnia, that differ in their life history traits, to assess how daily feeding patterns impact microbiome composition. We find that Daphnia species reared under similar laboratory conditions have significantly different microbial communities. Additionally, we reveal that Daphnia have daily differences in their microbial composition that correspond with feeding behavior, such that there is greater microbiome diversity at night during the host's active feeding phase. These results highlight that zooplankton microbiomes are relatively distinct and are likely influenced by host phylogeny.


title: Co-expression Patterns Explain how a Basic Transcriptional Role for MYC Modulates Wnt and MAPK Pathways in Colon and Lung Adenocarcinomas

abstract:
Genome duplication begins at many epigenetically determined sites by pre-replication, pre-initiation, and replisome complexes; co-expression of their components must be optimally timed for S phase to occur. Oscillations of cyclin dependent kinases (Cdks) and regulator cyclins control cell cycling, many are pharmacological targets in cancer. This study examines gene expression relationships between drivers, cell cycle components, and a subset of proliferation genes in colon (COAD) and lung (LUAD) adenocarcinomas. Several known drivers of COAD and LUAD including APC, CTNNB1, KRAS, MYC, Braf, TP53, Rb1, and EGFR are also observed with focus on Wnt and MAPK signaling activation. Wnt signaling activation has relevance for immune checkpoint inhibitor therapy, as it provides cancer cells with escape mechanisms.

MYC and KRAS co-expressed directly with far fewer proliferation genes in LUAD than COAD, suggesting their expression is ectopic to S phase in lung tumors. APC indirectly co-expressed with the same factors in both COAD and LUAD, but was found co-expressed indirectly with MYC and mutated only in COAD. Other Wnt signaling components also co-expressed in low MYC context in COAD, had significantly higher mutation frequencies. These data suggest Wnt signaling activation to be the indirect result of decreased MYC availability in COAD, and ectopic overexpression of MYC in LUAD. Cyclins CCNH, CCNC, and CCNK, co-expressed with far fewer proliferation genes in LUAD. Conversely, Braf had direct co-expression with many proliferation factors in non EGFR activated LUAD. Proliferation in EGFR activated LUAD was completely deregulated with E2F(s) 4/5/6 expression, potentially explaining their low proliferative ability.

category: molecular biology


title: ACTN2 missense variant causes proteopathy in human iPSC-derived cardiomyocytes

abstract:
RationaleGenetic variants in ACTN2, encoding -actinin 2 (ACTN2), are associated with several forms of (cardio)myopathy in the heterozygous state, and can cause progressive, severe cardiomyopathy in the homozygous state. We previously reported a heterozygous missense (c.740C>T) ACTN2 variant, associated with hypertrophic cardiomyopathy (HCM), which induced an electro-mechanical phenotype in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs).

ObjectiveTo evaluate the impact of heterozygosity and homozygosity of the c.740C>T ACTN2 variant on cardiomyocyte structure and function.

Methods and ResultsNext to the previously established hiPSC line carrying the heterozygous ACTN2 variant (ACTN2het), we created a homozygous line (ACTN2hom) with CRISPR/Cas9. Differentiation into cardiomyocytes revealed myofibrillar disarray, increased cell area and volume, multinucleation, and ACTN2 aggregates in mutant hiPSC-CMs. Live cell imaging in hiPSC-CMs showed an inverse correlation between sarcomeric incorporation and aggregation of exogenously expressed mutant ACTN2. RNA-seq and proteomic analyses showed alteration of several canonical pathways involved in metabolism, oxidative and cellular stress, and proteostasis, including the ubiquitin-proteasome system (UPS) and autophagy-lysosomal pathway (ALP) in mutant hiPSC-CMs. Detailed evaluation of the UPS and ALP, including a high-content screening with a mWasabi-mTagRFP-hLC3 tandem construct, revealed a global activation of these systems in mutant hiPSC-CMs. The ACTN2 missense variant caused allele dose-dependent and -independent effects on several cardiomyocyte features. ACTN2hom exhibited markedly lower levels of sarcomere-associated proteins, and hypocontractility in engineered heart tissues, resembling a dilated cardiomyopathy phenotype.

ConclusionThis study showed allele dose-independent effects of the ACTN2 variant on multinucleation, ACTN2 aggregation, and UPS activation, and allele dose-dependent effects of the variant on cellular hypertrophy, myofibrillar disarray, and ALP activation. Activation of the proteolytic systems is likely to cope with ACTN2 aggregation. Our data indicates proteopathy as an additional cellular feature caused by the c.740C>T ACTN2 variant, which may contribute to human ACTN2-associated inherited cardiomyopathy.

category: cell biology


title: Repression of CENP-A assembly in metaphase requires HJURP phosphorylation and inhibition by M18BP1

abstract:
Centromeres are the foundation for mitotic kinetochore assembly and thus are essential for chromosome segregation. Centromeres are epigenetically defined by nucleosomes containing the histone H3 variant CENP-A. CENP-A nucleosome assembly is uncoupled from replication and occurs in G1 but how cells control this timing is incompletely understood. The formation of CENP-A nucleosomes in vertebrates requires CENP-C and the Mis18 complex which recruit the CENP-A chaperone HJURP to centromeres. Using a cell-free system for centromere assembly in X. laevis egg extracts, we discover two activities that inhibit CENP-A assembly in metaphase. HJURP phosphorylation prevents the interaction between HJURP and CENP-C in metaphase, blocking the delivery of soluble CENP-A to centromeres. Non-phosphorylatable mutants of HJURP constitutively bind CENP-C in metaphase but are not sufficient for new CENP-A assembly. We find that the M18BP1.S subunit of the Mis18 complex also binds to CENP-C to competitively inhibit HJURPs access to centromeres. Removal of these two inhibitory activities causes CENP-A assembly in metaphase.

SUMMARYVertebrate CENP-A assembly is normally restricted to G1 phase. Two inhibitory activities, phosphorylation of HJURP and competitive binding of M18BP1.S to CENP-C, block HJURPs access to the metaphase centromere. Removal of these inhibitory activities causes CENP-A assembly in metaphase.


title: Effects of perfluoroalkyl and polyfluoroalkyl substances on soil structure and function

abstract:
Soils are impacted at a global scale by several anthropogenic factors, including chemical pollutants. Among those, perfluoroalkyl and polyfluoroalkyl substances (PFAS) are of concern due to their high environmental persistence, and as they might affect soil health and functions. However, data on impacts of PFASs on soil structure and microbially-driven processes are currently lacking. This study explored the effects of perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA) and perfluorobutanesulfonic acid (PFBS) at environmental-relevant nominal concentrations (1 ~ 1000 ng g-1) on soil functions, using a 6-week microcosm experiment. We measured soil respiration, litter decomposition, enzyme and microbial activities, soil aggregates, and bacterial abundance. PFAS (even at 1 ng g-1 for PFBS) significantly increased litter decomposition, associated with positive effects on bacterial abundance, and {beta}-glucosidase activities. This effect increased with PFAS concentrations. Soil respiration was significantly inhibited by PFAS in the 3rd week, while this effect was more variable in week 6. Water-stable aggregates were negatively affected by PFOS and PFOA, possibly related to microbial shifts. The general microbial activities and {beta}-D-cellobiosidase and phosphatase activities were barely affected by PFAS treatments. Our work highlights the potential effects of PFAS on soil health, and we argue that this substance class could be a factor of environmental change of potentially broad relevance in terrestrial ecosystem functioning.

SynopsisPFAS are likely to affect soil health.

Abstract Art

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title: CHD4 is recruited by GATA4 and NKX2-5 silencers to repress non-cardiac gene programs in the developing heart

abstract: The Nucleosome Remodeling and Deacetylase (NuRD) complex is one of the central chromatin remolding complexes that mediate gene repression. NuRD is essential for numerous developmental events, including heart development. Clinical and genetic studies have provided direct evidence for the role of chromodomain helicase DNA-binding protein 4 (CHD4), the catalytic component of NuRD, in congenital heart disease (CHD), including atrial and ventricular septal defects. Further, it has been demonstrated that CHD4 is essential for mammalian cardiomyocyte formation and function. A key unresolved question is how CHD4/NuRD is localized to specific cardiac targets genes, as neither CHD4 nor NuRD can directly bind DNA. Here, we coupled a bioinformatics-based approach with mass spectrometry analyses to demonstrate that CHD4 interacts with the core cardiac transcription factors GATA4, NKX2-5 and TBX5 during embryonic heart development. Using transcriptomics and genome-wide occupancy data, we have characterized the genomic landscape of GATA4, NKX2-5 and TBX5 repression and defined the direct cardiac gene targets of GATA4-CHD4, NKX2-5-CHD4 and TBX5-CHD4 complexes. These data were used to identify putative cis-regulatory elements regulated controlled by these complexes. We genetically interrogated two of these silencers in vivo, Acta1 and Myh11. We show that deletion of these silencers leads to inappropriate skeletal and smooth muscle gene mis-expression, respectively, in the embryonic heart. These results delineate how CHD4/NuRD is localized to specific cardiac loci and explicates how mutations in the broadly expressed CHD4 protein lead to cardiac specific disease states.

category: genomics


title: Telescoping bimodal latent Dirichlet allocation to identify expression QTLs across tissues

abstract: Expression quantitative trait loci (eQTLs), or single nucleotide polymorphisms (SNPs) that affect average gene expression levels, provide important insights into context-specific gene regulation. Classic eQTL analyses use one-to-one association tests, which test gene-variant pairs individually and ignore correlations induced by gene regulatory networks and linkage disequilibrium. Probabilistic topic models, such as latent Dirichlet allocation, estimate latent topics for a collection of count observations. Prior multi-modal frameworks that bridge genotype and expression data assume matched sample numbers between modalities. However, many data sets have a nested structure where one individual has several associated gene expression samples and a single germline genotype vector. Here, we build a telescoping bimodal latent Dirichlet allocation (TBLDA) framework to learn shared topics across gene expression and genotype data that allows multiple RNA-sequencing samples to correspond to a single individuals genotype. By using raw count data, our model avoids possible adulteration via normalization procedures. Ancestral structure is captured in a genotype-specific latent space, effectively removing it from shared components. Using GTEx v8 expression data across ten tissues and genotype data, we show that the estimated topics capture meaningful and robust biological signal in both modalities, and identify associations within and across tissue types. We identify 53,358 cis-eQTLs and 1,173 trans-eQTLs by conducting eQTL mapping between the most informative features in each topic. Our TBLDA model is able to identify associations using raw sequencing count data when the samples in two separate data modalities are matched one-to-many, as is often the case in biological data.


title: Glycosylated proteins identified for the first time in the alga Euglena gracilis

abstract: Protein glycosylation, and in particular N-linked glycans, is a hall mark of Eukaryotic cells and has been well studied in mammalian cells and parasites. However, little research has been conducted to investigate the conservation and variation of protein glycosylation pathways in other eukaryotic organisms. Euglena gracilis is an industrially important microalga, used in the production of biofuels and nutritional supplements. It is evolutionarily highly divergent from green algae and more related to Kinetoplastid pathogens. It was recently shown that E. gracilis possesses the machinery for producing a range of protein glycosylations and make simple N-glycans, but the modified proteins were not identified. This study identifies the glycosylated proteins, including transporters, extra cellular proteases and those involved in cell surface signalling. Notably, many of the most highly expressed and glycosylated proteins are not related to any known sequences and are therefore likely to be involved in important novel functions in Euglena.

category: biochemistry


title: Disordered yet functional atrial t-tubules on recovery from heart failure

abstract:
Transverse (t)-tubules drive the rapid and synchronous Ca2+ rise in cardiac myocytes. The virtual complete loss of atrial t-tubules in heart failure (HF) decreases Ca2+ release. It is unknown if or how atrial t-tubules can be restored and if restored t-tubules are functional.

Sheep were tachypaced to induce HF and recovered when pacing was stopped. Serial block face Scanning Electron Microscopy and confocal imaging were used to understand t-tubule ultrastructure and function. Candidate proteins involved in atrial t-tubule recovery were identified by western blot and causality determined using expression studies.

Sheep atrial t-tubules reappeared following recovery from HF. Despite being disordered (branched, longer and longitudinally arranged) recovered t-tubules triggered Ca2+ release and were associated with restoration of systolic Ca2+. Telethonin and myotubularin abundance correlated with t-tubule density and altered the density and structure of BIN1-driven tubules in neonatal myocytes. Myotubularin had a greater effect, increasing tubule length and branching, replicating that seen in the recovery atria.

Recovery from HF restores atrial t-tubules and systolic Ca2+ and myotubularin facilitates this process. Atrial t-tubule restoration could present a new and viable therapeutic strategy.

Brief SummaryThe loss of atrial transverse (t)-tubules and the associated dysfunction in heart failure is reversible and the protein myotubularin plays an important role.

category: physiology


title: Comparative transcriptome analysis of Cryptomeria japonica between solid and liquid culture.

abstract: This manuscript has been withdrawn by the authors as it was submitted and made public without the appropriate authorizations. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.


title: Of Biofilms and Beehives: An Analogy-Based Instructional Tool to Introduce Biofilms to High-School and Undergraduate Students

abstract: The concept of biofilms and biofilm-based research is largely absent or minimally described in high school and undergraduate life science curriculum. While it is well-established that microbes, such as bacteria and fungi most often exist in multicellular biofilm communities, descriptions in standard biology textbooks continue to focus on the single-celled form of microbial life. We have developed an analogy-based instructional tool to introduce and explain biofilms to high school and undergraduate students. The module employs an analogy with beehives, given that biofilms and beehives are both  superorganism states, to explain key biofilm features such as development and structure, chemical communication, division of labor and emergent properties. We delivered this analogy based learning tool to a cohort of 49 high school and undergraduate students, and based on participant feedback and learnings, present a formal evaluation of the instructional tool. Further, we outline prerequisites and learning approaches that can enable the delivery of this module in classroom and virtual learning settings, including suggestions for pre-lesson reading, student-centred interactive activities, and specific learning objectives. Taken together, this instructional analogy holds potential to serve as an educational tool to introduce biofilms in high school and undergraduate curricula in a relatable and comprehensible manner.

category: scientific communication and education