title: Preserved executive control in ageing: The role of literacy experience

abstract: Healthy ageing is commonly accompanied by cognitive decline affecting several domains such as executive control, whereas certain verbal skills remain relatively preserved. Interestingly, recent scientific research has shown that some intellectual activities may be linked to beneficial effects, delaying or even alleviating cognitive decline in the elderly. Thirty young (age: M = 23) and thirty old (age: M = 66) adults were assessed in executive control (switching) and literacy experience (print exposure). First, we tried to confirm whether healthy ageing was generally associated with deficits in switching by looking at mixing cost effects, to then investigate if individual differences in print exposure explained variation in that age-related mixing costs. Both accuracy and reaction times mixing cost indexes demonstrated larger cost in old (but not in young) adults when switching from local to global information. More importantly, this cost effect disappeared in old adults with higher print exposure (reaction times). Our findings suggest literacy experience accumulated across the life-span may act as a cognitive reserve proxy to prevent executive control decline.


title: Explaining and Predicting the Effects of Neurostimulation via Neuronal Excitation/Inhibition

abstract: Previous research has highlighted the role of the excitation/inhibition ratio (E/I) for typical and atypical development, mental health, cognition, and learning. Parallel research has highlighted the benefits of high-frequency random noise stimulation (tRNS)--an excitatory form of neurostimulation--on learning. We examined the E/I as a potential mechanism and whether tRNS effect on learning depends on E/I as measured by the aperiodic exponent. In addition to manipulating E/I using tRNS, we also manipulated the level of learning (learning/overlearning) that has been shown to influence E/I. One hundred and two participants received either sham stimulation or 20 min DLPFC tRNS during a mathematical learning task. We showed a lower aperiodic exponent, which reflects higher E/I, after tRNS, and that higher baseline aperiodic exponent, which reflects lower E/I, predicted greater benefit from tRNS specifically for the learning task. In contrast to previous MRS-based E/I studies, we found no effect of the learning manipulation on E/I. Our results highlight the role of E/I as a marker for neurostimulation efficacy and learning. This mechanistic understanding could provide stronger potential to augment learning. At the same time, we offer new insights on the quantification of E/I using EEG vs MRS to foster better theoretical understanding and its utilisation in future research.

category: neuroscience


title: Hippocampal cAMP-dependent synaptic potentiation, ERK-dependent immediate-early gene activation, and context-dependent fear conditioning in mice are linked through dependence on the guanine nucleotide exchange factor RapGEF2

abstract: The MAP kinase ERK is important for neuronal plasticity underlying associative learning, yet specific molecular pathways for ERK activation in hippocampus are still largely undetermined. RapGEF2 has emerged as a neuron-specific cAMP sensor that mediates ERK activation. We investigated whether RapGEF2 might also be required for cAMP-dependent ERK activation leading to synaptic potentiation, and how this involvement might be penetrant to hippocampus-dependent learned behavior. We demonstrate that conditional knockout of Rapgef2 in forebrain neurons, specifically in dentate gyrus and CA1 of the hippocampus, leads to an attenuation of context-dependent fear conditioning, but not of cue-dependent fear conditioning, in mice. RapGEF2 knockout is associated with a reduction in cAMP-dependent synaptic potentiation at two central hippocampal synapses-the entorhinal cortex-granule cell synapse and the CA3-CA1 synapse. Furthermore, cAMP-induced postsynaptic potentiation requires both RapGEF2 and activation of ERK. Induction of Egr-1/Zif268 (and pERK), but not of c-Fos, immediately following fear conditioning, was abolished in CA1 and detate gyrus, in the absence of RapGEF2 expression in these hippocampal regions, thus revealing a link between learning (conditioning) and molecular pathways activated during conditioned fear memory formation. Hence, we suggest that contextual fear conditioning is mediated via RapGEF2-dependent ERK activation and downstream induction of Egr-1, via an underlying mechanism of cAMP-dependent long-term potentiation at hippocampal synapses. Cyclic AMP-dependent GEFs have been genetically associated as risk factors for schizophrenia, a disorder associated with cognitive deficits. This study provides a functional link between one of these cAMP-dependent GEFs, RapGEF2, and cognitive processes involved in associative learning.


title: Learning to suppress likely distractor locations in visual search is driven by the local distractor frequency

abstract:
Salient but task-irrelevant distractors interfere less with visual search when they appear in a display region where distractors have appeared more frequently in the past ( distractor-location probability cueing). This effect could reflect the (re-)distribution of a global, limited attentional  inhibition resource. Accordingly, changing the frequency of distractor appearance in one display region should also affect the magnitude of interference generated by distractors in a different region. Alternatively, distractor-location learning may reflect a local response (e.g.,  habituation) to distractors occurring at a particular location. In this case, the local distractor frequency in one display region should not affect distractor interference in a different region. To decide between these alternatives, we conducted three experiments in which participants searched for an orientation-defined target while ignoring a more salient orientation distractor that occurred more often in one vs. another display region. Experiment 1 varied the ratio of distractors appearing in the frequent vs. rare regions (60/40-90/10), with a fixed global distractor frequency. The results revealed the cueing effect to increase with increasing probability ratio. In Experiments 2 and 3, one ( test) region was assigned the same local distractor frequency as in one of the conditions of Experiment 1, but a different frequency in the other region - dissociating local from global distractor frequency. Together, the three experiments showed that distractor interference in the test region was not significantly influenced by the frequency in the other region, consistent with purely local learning. We discuss the implications for theories of statistical distractor-location learning.

Public Significance StatementWe are frequently distracted by salient visual stimuli which are irrelevant to the task at hand. Previous studies have shown that  knowledge of the location(s) where a distractor is most likely to occur helps the observer to mitigate distraction. In this study we compared different theories of how the frequency and spatial distribution of distractor occurrence in different locations could influence the ability to avoid distraction. The results favored a local learning account: the ability to avoid distraction by distractors occuring in a particular spatial region is primarily influenced by how often distractors have occurred in that region.


title: NMDA-receptor-Fc-fusion constructs neutralize anti- NMDA receptor antibodies

abstract: N-methyl-D-aspartate receptor (NMDAR) encephalitis is the most common subtype of autoimmune encephalitis characterized by a complex neuropsychiatric syndrome ranging from memory impairment and psychosis to coma. Patients develop an intrathecal immune response against NMDARs with antibodies that presumably bind to the amino-terminal domain (ATD) of the GluN1 subunit. The therapeutic response to immunotherapy is often delayed and does not directly interfere with intrathecal synthesis of pathogenic antibodies. Therefore, new therapeutic approaches for fast neutralization of NMDAR antibodies are needed. Here, we developed fusion constructs consisting of the Fc part of immunoglobulin G and the ATDs of either GluN1 or GluN2B or both, GluN1 and GluN2B, subunits. Surprisingly, both subunits were required to generate high-affinity epitopes. The construct with both subunits efficiently prevented NMDAR binding of patient-derived monoclonal antibodies and of patient cerebrospinal fluid containing high-titer NMDAR antibodies. Furthermore, it inhibited the internalization of NMDARs in rodent dissociated neurons and human induced pluripotent stem cells (iPSC)-derived neurons. Finally, the construct stabilized NMDAR currents recorded in rodent neurons. Our results demonstrate that both GluN1 and GluN2B subunits contribute to the main immunogenic region of the NMDAR and provide a promising strategy for fast and specific treatment of NMDAR encephalitis, which can complement immunotherapy.


title: Recurrent neural network model of human event-related potentials in response to intensity oddball stimulation

abstract: The mismatch negativity (MMN) component of the human event-related potential (ERP) is frequently interpreted as a sensory prediction-error signal. However, there is ambiguity concerning the neurophysiology underlying hypothetical prediction and prediction-error signalling components, and whether these can be dissociated from overlapping obligatory components of the ERP that are sensitive to physical properties of sounds. In the present study, a hierarchical recurrent neural network (RNN) was fitted to ERP data from 38 subjects. After training the model to reproduce ERP waveforms evoked by 80 dB standard and 70 dB deviant stimuli, it was used to simulate a response to 90 dB deviant stimuli. Internal states of the RNN effectively combine to generate synthetic ERPs, where individual hidden units are loosely analogous to population-level sources. Model behaviour was characterised using principal component analysis of stimulus condition, layer, and individual unit responses. Hidden units were categorised according to their temporal response fields, and statistically significant differences among stimulus conditions were observed for amplitudes of units peaking in the 0 to 75 ms (P50), 75 to 125 ms (N1), and 250 to 400 ms (N3) latency ranges, surprisingly not including the measurement window of MMN. The model demonstrated opposite polarity changes in MMN amplitude produced by falling (70 dB) and rising (90 dB) intensity deviant stimuli, consistent with loudness dependence of sensory ERP components. Although perhaps less parsimoniously, these observations could be interpreted within the context of predictive coding theory, as examples of negative and positive prediction errors, respectively.


title: An in situ quantitative map of initial human colorectal HIV transmission

abstract:
The initial immune response to HIV is critical in determining transmission. However, due to technical limitations we still do not have a comparative map of early mucosal transmission events. We combined RNAscope, cyclic-immunofluorescence and novel image analysis tools to quantify HIV transmission dynamics in intact human colorectal tissue. We mapped HIV enrichment to mucosal dendritic cells (DC) and submucosal macrophages, but not CD4+ T-cells, the primary targets of downstream infection. DCs appeared to funnel virus to lymphoid aggregates which acted as early sanctuaries of high viral titres whilst facilitating HIV passage to the submucosa. Finally, HIV entry induced rapid recruitment and clustering of target cells, facilitating DC and macrophage mediated HIV transfer and enhanced infection of CD4+ T-cells. These data demonstrate a rapid response to HIV structured to maximise the likelihood of mucosal infection, and provide a framework for in situ studies of host pathogen interactions and immune mediated pathologies.

Highlights- in situ quantification of host cellular microenvironment response to pathogen invasion in human colorectal tissue.
- HIV first localises to mucosal DCs and submucosal macrophages, but not CD4+ T cells.
- Viral enrichment first occurs in lymphoid aggregates which is associated with passage into the submucosa.
- Early localisation of HIV to CD4+ T cells is associated with interactions with DCs and macrophages.

Graphical Abstract

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category: immunology


title: INFLAMMATION INDUCED DOWNREGULATION OF SUCCINATE DEHYDROGENASE REGULATES ADRENOCORTICAL FUNCTION

abstract: The hypothalamus-pituitary-adrenal (HPA) axis is activated in response to inflammation leading to increased production of glucocorticoids by the adrenal cortex. In turn, glucocorticoids exert potent anti-inflammatory effects. Severe inflammation may reduce adrenal gland responsiveness to adrenocorticotropic hormone (ACTH) although the underlying molecular mechanisms are poorly understood. Here, we show by transcriptomic, proteomics and metabolomics analysis that lipopolysaccharide (LPS)-induced systemic inflammation triggers profound metabolic changes in steroidogenic adrenocortical cells, including downregulation of the tricarboxylic acid (TCA) cycle and oxidative phosphorylation, decreased ATP production and induction of oxidative stress. We demonstrate that although inflammation disrupts the TCA cycle at the levels of succinate dehydrogenase (SDH) and isocitrate dehydrogenase 2 (IDH2) leading to accumulation of succinate and isocitrate, respectively, only reduced SDH activity and increased succinate levels associate with disturbed steroidogenic capacity of adrenocortical cells. Specifically, IL1{beta} reduces Sdhb expression and steroidogenesis in adrenocortical cells. These findings suggest that SDH activity is important for adrenocortical steroidogenesis and provide a link between inflammation and adrenocortical dysfunction through alterations in the TCA cycle.


title: The dual character of the inhibitory functions of CD6

abstract: T-cell membrane scaffold proteins play important roles in T cell biology, functioning as multi-functional signaling hubs. CD6 assembles a large intracellular signalosome but, unlike typical membrane-attached scaffolds like LAT or PAG, it has a sizeable ectodomain that binds a well-characterized ligand, CD166. It is unclear whether CD6 has net inhibitory or costimulatory functions or how its ectodomain influences these activities. To explore these questions, we dissected the signaling functions of the extracellular and cytoplasmic regions of CD6. We found that CD6 was delivered to the immunological synapse and suppressed T cell responsiveness in vitro wholly dependently of its cytoplasmic domain, indicating that CD6 very potently imposes tonic inhibition, acting as a structural and signaling inhibitory hub. However, the cell-intrinsic suppression of autoimmunity by CD6 in vivo was also impacted by extracellular interactions, demonstrated by the increased susceptibility of mice to experimental autoimmune encephalomyelitis after removal of the ligand binding region of the ectodomain of CD6. Our work identifies CD6 as a new class of  on/off switching scaffold-receptor that constrains immune responsiveness at two speeds. First, it sets signaling thresholds via tonic inhibition, functioning as a cytoplasmic membrane-bound scaffold and, second, by cycling between signaling-enabling and signalinginhibiting ectodomain isoforms it functions as an immune checkpoint.


title: Genome-wide identification of SINA gene family in sugarcane and functional analysis of SsSINA1a in drought response

abstract: Sugarcane (Saccharum spp. hybrid) is a crucial sugar and energy crop that provides majority of the raw material for sugar and ethanol production globally. Drought represents one of the most critical constraints of sugarcane production in the subtropical parts of China. SEVEN IN ABSENTIA (SINA) act as an important E3 ubiquitin ligase and play a significant role in plant stress responses. However, the characteristics of the sugarcane SINA gene family have not been previously studied currently. Here, we identified 15 SsSINA in Saccharum spontaneum, 5 ShSINA in Saccharum spp. hybrid and 6 SbSINA in Sorghum bicolor based on their conserved N{square}terminal RING and C-terminal SINA domains, and these genes were distributed into three phylogenetic groups (I, {square} and {square}). Collinearity analysis showed a close genetic relationship between the SINA genes of S. spontaneum and S. bicolor. The cis-regulatory elements in the promoter regions of the SINA genes were involved in a variety of plant physiological responses. Further, we identified a SINA gene SsSINA1a that significantly induced by drought stress. Overexpression of SsSINA1a enhanced drought tolerance in Arabidopsis through reducing leaf water loss rate. These finding indicate that SsSINA1a mediates plant drought tolerance and this study provides a new potential candidate gene for sugarcane drought-resistant breeding.

category: molecular biology


title: Sequential functional differentiation of luminal epithelial cells regulated by maternal and embryonic signaling in the mouse endometrium

abstract: Embryo implantation requires temporospatial maternal-embryo dialog to regulate the interactions between an activated blastocyst and a receptive endometrium; however, the details of the related cell-specific coordination is largely unknown because of the cellular complexity and dynamic developmental processes of both the embryo and endometrium during peri-implantation. By comparing single-cell RNA (scRNA) data obtained from entire uteri of pregnant and pseudo-pregnant mice with embryos that were in the oviduct (dpc2.5 days post-coitum [dpc]) or had entered the uterus (after 3.5 dpc), we found a maternal estrogen and progesterone signaling-dependent functional differentiation process in which progesterone induced estrogen-responsive luminal epithelial cells to differentiate into two new types of epithelial cells: adhesion epithelial cells (AECs) and supporting epithelial cells (SECs) on 2.5 dpc. In addition to maternal signaling data, the uterine scRNA and corresponding embryo bulk sequencing data were obtained, and analyses revealed that embryonic Pdgfa and Efna3/4 signaling activated AECs and SECs, enhancing the attachment of embryos to the endometrium after implantation. Specifically, embryonic signaling induced additional transformation of AECs by preventing adjacent AECs, but not AECs away from the embryo in the implantation chamber, from undergoing apoptosis. Furthermore, we demonstrated that epithelial cell differentiation and related regulatory signaling were largely conserved in humans and mice. In the human endometrium, developmental defects of SOX9-positive epithelial cells similar to luminal epithelial cells were related to thin endometrium. Our work provides comprehensive and systematic information on endometrial luminal epithelial cell development directed by maternal and embryonic signaling, which is important for endometrial receptivity and embryo implantation.

category: cell biology


title: Cellular orientational fluctuations, rotational diffusion and nematic order under periodic driving

abstract: The ability of living cells to sense the physical properties of their microenvironment and to respond to dynamic forces acting on them plays a central role in regulating their structure, function and fate. Of particular importance is the cellular sensitivity and response to periodic driving forces in noisy environments, encountered in vital physiological conditions such as heart beating, blood vessels pulsation and breathing. Here, we first test and validate two predictions of a mean-field theory of cellular reorientation under periodic driving, which combines the minimization of cellular anisotropic elastic energy with active remodeling forces. We then extend the mean-field theory to include uncorrelated, additive nonequilibrium fluctuations, and show that the theory quantitatively agrees with the experimentally observed stationary probability distributions of the cell body orientation, under a range of biaxial periodic driving forces. The fluctuations theory allows to extract the dimensionless active noise amplitude of various cell types, and consequently their rotational diffusion coefficient. We then focus on intra-cellular nematic order, i.e. on orientational fluctuations of actin stress fibers around the cell body orientation, and show experimentally that intra-cellular nematic order increases with both the magnitude of the driving forces and the biaxiality strain ratio. These results are semi-quantitatively explained by applying the same cell body fluctuations theory to orientationally correlated actin stress fiber domains. The implications of these findings, which make the quantitative analysis of cell mechanosensitivity more accessible, are discussed.


title: Toxicology assessment of manganese oxide nanomaterials with enhanced electrochemical properties using human in vitro models representing different exposure routes

abstract: In the present study, a comparative human toxicity assessment between newly developed Mn3O4 nanoparticles with enhanced electrochemical properties (GNA35) and their precursor material (Mn3O4) was performed, employing different in vitro cellular models representing alveolar, oral and dermal exposure routes, namely the human alveolar carcinoma epithelial cell line (A549), the human colorectal adenocarcinoma cell line (HT29), and the reconstructed 3D human epidermal model EpiDerm (RhE). The obtained results showed that Mn3O4 and GNA35 harbour similar morphological characteristics, while differences were observed in relation to their thermal stability and electrochemical properties. In regard to their toxicological properties, both nanomaterials induced oxidative stress in the A549 and HT29 cell lines that have demonstrated that manganese oxide nanoparticles reduce the cell viability in A549 cells while they do not produce any negative effect on that of HT29 cells. On the other hand, it was observed that Mn3O4 and GNA35 induce oxidative stress in both cell lines. Finally, it was noticed that none of the nanoparticles caused a reduction of the viability on the skin tissue so that they could not be classified as irritants. Our findings demonstrate that the evaluation of the toxicity of nanoparticles using different models is a critical aspect to increase the knowledge on their potential impact on human health.


title: A ratchet-like apical constriction drives cell ingression during the mouse gastrulation EMT

abstract: Epithelial-to-Mesenchymal Transition (EMT) is a hallmark of gastrulation, an evolutionarily conserved developmental process. In mammals epiblast cells lose pluripotency and ingress at the primitive streak to form mesoderm. Cell exit from the epiblast epithelial layer and the associated EMT are dynamically regulated processes involving a stereotypical sequence of cell behaviors. 3D time-lapse imaging combined with cell and tissue scale data analyses of gastrulating mouse embryos revealed the stochastic ingression of epiblast cells at the primitive streak. Ingressing cells asynchronously constrict their apical surfaces in a pulsed ratchet-like fashion through asynchronous shrinkage of apical junctions. Quantitative analyses of the distribution of apical proteins, revealed the anisotropic and complementary distribution of members of the actomyosin network and Crumbs2 complex, potential regulators of asynchronous shrinkage of cell junctions. Analysis of mutants revealed a requirement for Crumbs2 in Myosin2 localization and activity at apical junctions, and as a candidate for regulating actomyosin anisotropy.

category: developmental biology


title: A CXCL12 morphogen gradient uncovers lung endothelial heterogeneity and promotes distal vascular growth

abstract: In adults, there is a growing amount of data uncovering the cellular diversity of the pulmonary circulation and mechanisms governing vascular repair after injury, however, molecular and cellular mechanisms contributing to the morphogenesis and growth of the pulmonary vasculature during embryonic development are less clear. Importantly, deficits in vascular development lead to a large number of lung diseases in children, indicating a need to uncover fetal programs that promote pulmonary vascular growth. To address this, we used a transgenic mouse reporter for expression of Cxcl12, an arterial hallmark gene, and performed single-cell RNA sequencing on isolated Cxcl12-DsRed+ endothelium to assess cellular heterogeneity within pulmonary endothelium. Combining cell annotation, gene ontology analysis, and spatial transcriptomics allowed us to segregate the developing artery into spatially and functionally distinct novel subpopulations. In addition, expression of Cxcl12 suggests a morphogen gradient from arteries to capillaries, suggesting directed cell migration for pulmonary vascular development. Disruption of this gradient led to abnormal branching and pulmonary vascular hypoplasia. These data provide evidence for arterial endothelial functional heterogeneity and reveal conserved signaling mechanisms essential for pulmonary vascular development.


title: Variant Polycomb complexes in Drosophila consistent with ancient functional diversity

abstract: Polycomb group (PcG) mutants were first identified in Drosophila based on their failure to maintain proper Hox gene repression during development. The proteins encoded by the corresponding fly genes mainly assemble into one of two discrete Polycomb Repressive Complexes: PRC1 or PRC2. However, biochemical analyses in mammals have revealed alternative forms of PRC2, and multiple distinct types of non-canonical or variant PRC1. Through a series of proteomic analyses, we identify analogous PRC2 and variant PRC1 complexes in Drosophila, as well as a broader repertoire of interactions implicated in early development. Our data provide strong support for the ancient diversity of PcG complexes, and a framework for future analysis in a longstanding and versatile genetic system.


title: Long-term population decline of a genetically homogenous continental-wide top Arctic predator

abstract: Genetic analysis can provide valuable information for conservation programs by unraveling the demographic trajectory of populations, by estimating effective population size, or by inferring genetic differentiation between populations. Here, we investigated the genetic differentiation within the Snowy Owl (Bubo scandiacus), a species identified as vulnerable by the IUCN, to (i) quantify connectivity among wintering areas, (ii) to evaluate current genetic diversity and effective population size and (iii) to infer changes in the historical effective population size changes from the last millennia to the recent past. The Snowy Owl, a highly mobile top predator, breeds across the Arctic tundra which is a region especially sensitive to current climate change. Using SNP-based analyses on Snowy Owls sampled across the North American nonbreeding range, we found an absence of genetic differentiation among individuals located up to 4,650 km apart. Our results suggest high genetic intermixing and effective dispersal at the continental scale despite documented philopatry to nonbreeding sites in winter. Reconstructing the population demographic indicated that North American Snowy Owls have been steadily declining since the Last Glacial Maximum ca 20,000 years ago and concurrently with global increases in temperature. Conservation programs should now consider North American Snowy Owls as a single, genetically homogenous continental-wide population which is most likely sensitive to the long-term global warming occurring since the Last Glacial Maximum.

category: ecology


title: Heterogeneity of Interaction Strengths and Its Consequences on Ecological Systems

abstract: Ecosystems are formed by networks of species and their interactions. Traditional models of such interactions assume a constant interaction strength between a given pair of species. However, there is often significant trait variation among individual organisms even within the same species, causing heterogeneity in their interaction strengths with other species. The consequences of such heterogeneous interactions for the ecosystem have not been studied systematically. As a theoretical exploration, we analyze a simple ecosystem with trophic interactions between two predators and a shared prey, which would exhibit competitive exclusion in models with homogeneous interactions. We consider several scenarios where individuals of the prey species differentiate into subpopulations with different interaction strengths. We show that in all these cases, whether the heterogeneity is inherent, reversible, or adaptive, the ecosystem can stabilize at a new equilibrium where all three species coexist. Moreover, the prey population that has heterogeneous interactions with its predators reaches a higher density than it would without heterogeneity, and can even reach a higher density in the presence of two predators than with just one. Our results suggest that heterogeneity may be a naturally selected feature of ecological interactions that have important consequences for the stability and diversity of ecosystems.


title: Evolution is not uniform along protein sequences

abstract: Amino acids evolve at different speeds within protein sequences, because their functional and structural roles are different. However, the position of an amino-acid within the sequence is not known to influence this evolutionary speed. Here we discovered that amino-acid evolve almost twice faster at protein termini than in their centre, hinting at a strong topological bias along the sequence length. We further show that the distribution of functional domains and of solvent-accessible residues in proteins readily explain how functional constrains are weaker at their termini, leading to the observed excess of amino-acid substitutions. Finally, we show that methods inferring sites under positive selection are strongly biased towards protein termini, suggesting that they may confound positive selection with weak negative selection. These results suggest that accounting for positional information should improve evolutionary models.

category: evolutionary biology


title: Distinct Effects of the Male-Killing Bacteria Wolbachia and Spiroplasma and a Partiti-Like Virus in the Tea Pest Moth, Homona magnanima

abstract:
Male killing, the phenomenon of male death during development, is considered to be one of the advantageous strategies exerted by maternally transmitted microbes. Male killing has attracted interest in the fields of evolutionary biology and ecology for decades; however, little is known about its mechanism and origin. Here, we characterized and compared the effects of three distinct male killers, Wolbachia (Alphaproteobacteria), Spiroplasma (Mollicutes), and Osugoroshi virus (OGV) (Partitiviridae) in the tea pest moth Homona magnanima (Lepidoptera, Tortricidae). Regardless of the genetic sex (male: ZZ; female: ZW), female specific splice variants of the doublesex gene (dsx), a downstream regulator of the sex-determining gene cascade, was expressed in H. magnanima harbored either male-killing Wolbachia or Spiroplasma. However, OGV and non-male-killing Wolbachia did not alter dsx splicing. RNA sequencing and quantitative PCR assays demonstrated that male-killing Wolbachia impaired the hosts dosage compensation system by altering the global gene expression of the Z chromosome (corresponding to Bombyx mori chromosome 1 and 15) in males, whereas Spiroplasma did not affect dosage compensation. In contrast, the partiti-like virus OGVs did not affect sex-determination cascades or dosage compensation systems. Besides, male killers distinctly altered host gene expression and metabolomes associated with physiology, morphology, and diverse metabolic pathways. Moreover, Wolbachia and Spiroplasma infections triggered abnormal apoptosis only in male embryos. These findings suggest that distantly related microbes employ distinct machineries to kill identical host males, which have been acquired through independent evolutionary processes.

ImportanceMale-killing caused by diverse microbes has attracted substantial attention. However, it remains unclear how such male killers have evolved similar phenotypes, in part because male-killing mechanisms have been studied using different insect models. Here, by comparing three phylogenetically distinct male killers, Wolbachia, Spiroplasma, and a partiti-like virus, in an identical host, we provide evidence that microbes can affect male viability through distinct machinery, demonstrating distinct evolutionary scenarios for microbes to acquire make-killing ability. These findings provide insight into new directions for studying microbe-host interactions.


title: Leveraging spatio-temporal genomic breeding value estimates of dry matter yield and herbage quality in ryegrass via random regression models

abstract: Joint modeling of correlated multi-environment and multi-harvest data of perennial crop species may offer advantages in prediction schemes and a better understanding of the underlying dynamics in space and time. The goal of the present study was to investigate the relevance of incorporating the longitudinal dimension of within-season multiple harvests of biomass yield and nutritive quality traits of forage perennial ryegrass (Lolium perenne L.) in a reaction norm model setup that additionally accounts for genotype-environment interactions. Genetic parameters and accuracy of genomic breeding value predictions were investigated by fitting three random regression (random coefficients) linear mixed models (gRRM) using Legendre polynomial functions to the data. All models accounted for heterogeneous residual variance and moving average-based spatial adjustments within environments. The plant material consisted of 381 bi-parental family pools and four check varieties of diploid perennial ryegrass evaluated in eight environments for biomass yield and nutritive quality traits. The longitudinal dimension of the data arose from multiple harvests performed four times annually. The specified design generated a total of 16,384 phenotypic data points for each trait. Genomic DNA sequencing was performed using DNA nanoball-based technology (DNBseq) and yielded 56,645 single nucleotide polymorphisms (SNPs) which were used to calculate the allele frequency-based genomic relationship matrix used in all genomic random regression models. Biomass yields estimated additive genetic variance and heritability values were higher in later harvests. The additive genetic correlations were moderate to low in early measurements and peaked at intermediates, with fairly stable values across the environmental gradient, except for the initial harvest data collection. This led to the conclusion that complex genotype-by-environment interaction (GxE) arises from spatial and temporal dimensions in the early season, with lower re-ranking trends thereafter. In general, modeling the temporal dimension with a second-order orthogonal polynomial in the reaction norm mixed model framework improved the accuracy of genomic estimated breeding value prediction for nutritive quality traits, but no gain in prediction accuracy was detected for dry matter yield. This study leverages the flexibility and usefulness of gRRM models for perennial ryegrass research and breeding and can be readily extended to other multi-harvest crops.

category: genetics


title: An automated approach to quantify chemotaxis index in Caenorhabditis nematodes

abstract: Chemotaxis assays are used extensively to study behavioral responses of Caenorhabditis nematodes to environmental cues. These assays result in a chemotaxis index (CI) that denotes the behavioral response of a population of nematodes to a particular compound and can range from 1 (maximum attraction) to -1 (maximum avoidance). Traditional chemotaxis assays have low throughput because researchers must manually setup experimental populations and score CIs. Here, we describe an automated methodology that increases throughput by using liquid-handling robots to setup experimental populations and a custom image analysis package, ct, to automate the scoring of CIs from plate images.


title: Hybridization drives mitochondrial DNA degeneration and metabolic shift in a species with biparental mitochondrial inheritance

abstract: Mitochondrial DNA (mtDNA) is a cytoplasmic genome that is essential for respiratory metabolism. While uniparental maternal mtDNA inheritance is most common in animals and plants, distinct mtDNA haplotypes can coexist in a state of heteroplasmy, either because of paternal leakage or de novo mutations. MtDNA integrity and the resolution of heteroplasmy have important implications, notably for mitochondrial genetic disorders, genome evolution and speciation. However, knowledge on the factors driving heteroplasmy resolution is sparse. Here, we use Saccharomyces yeasts, fungi with constitutive biparental mtDNA inheritance, to investigate the resolution of mtDNA heteroplasmy in a variety of hybrid genotypes. We analyzed mtDNA sequence evolution and growth phenotypes in a collection of 864 hybrid yeast lines that were experimentally evolved under relaxed selection for mitochondrial function, allowing us to explore the near-neutral evolution of mtDNAs. The lines were subdivided into 11 different hybrid crosses among natural lineages of Saccharomyces paradoxus and its sister species Saccharomyces cerevisiae, yielding a variety of hybrid genotypes along a gradient of parental divergence. We observed extensive mtDNA recombination, but recombination rates were not predicted by parental divergence and were genotype-specific. However, we found a strong positive relationship between parental divergence and the rate of large-scale mtDNA deletions, which lead to the loss of respiratory metabolism. We also uncovered associations between mtDNA recombination, deletion, and genome instability that were genotype-specific. Our results show that hybridization in yeast induces mtDNA degeneration, with deep consequences for mtDNA evolution, metabolism and the emergence of reproductive isolation between species.

category: genomics


title: Heritability of Urinary Amines, Organic Acids, and Steroid Hormones in Children

abstract: Variation in metabolite levels reflects individual differences in genetic and environmental factors. Here, we investigated the role of these factors in urinary metabolomics data in children. We examined the effects of sex and age on 86 metabolites, as measured on three metabolomics platforms that target amines, organic acids, and steroid hormones. Next, we estimated their heritability in a twin cohort of 1300 twins (age range: 5.7 - 12.9 years). We observed associations between age and 50 metabolites and between sex and 21 metabolites. The mean monozygotic (MZ) and dizygotic (DZ) correlations for urinary metabolites were 0.51 (range: 0.25-0.75) and 0.16 (range: 0.01-0.46) for the amines, 0.52 (range: 0.33-0.64) and 0.23 (range: 0.07-0.35) for the organic acids, and 0.61 (range: 0.43-0.81) and 0.25 (range: 0.11-0.44) for the steroids. Broad-sense heritability was 0.49 (range: 0.25-0.64), 0.50 (range: 0.33-0.62), and 0.64 (range: 0.43-0.81) for 50 amines, 13 organic acids, and 6 steroids, and narrow-sense heritability was 0.50 (range: 0.37-0.68), 0.50 (0.23-0.61), and 0.47 (range: 0.32-0.70) for 6 amines, 7 organic acids, and 4 steroids. We conclude that urinary metabolites in children have substantial heritability, with similar estimates for amines and organic acids, and higher estimates for steroid hormones.


title: Qualification of Identity, Quality-Attribute Monitoring and New Peak Detection in An Improved Multi-Attribute Method with Lys-C Digestion for Characterization and Quality Control of Therapeutic Monoclonal Antibodies

abstract: The use of Multi-attribute method (MAM) for identity and purity testing of biopharmaceuticals offers the ability to complement and replace multiple conventional analytical technologies with a single mass spectrometry (MS) method. Method qualification and phase-appropriate validation is one major consideration for the implementation of MAM in a current Good Manufacturing Practice (cGMP) environment. We developed an improved MAM workflow with optimized sample preparation using Lys-C digestion for therapeutic monoclonal antibodies. In this study, we qualified the enhanced MAM workflow for mAb-1 identity, product quality attributes (PQAs) monitoring and new peak detection (NPD). The qualification results demonstrated the full potential of the MAM for its intended use in mAb-1 characterization and quality control in regulated labs. To the best of our knowledge, this is the first report of MAM qualification for mAb identity, PQA monitoring, and new peak detection (NPD) in a single assay, featuring 1) the first full qualification of MAM using Lys-C digestion without desalting using a high-resolution MS, 2) a new approach for mAb identity testing using MAM, and 3) the first qualification of NPD for MAM. The developed MAM workflow and the approaches for MAM qualification may serve as a reference for other labs in the industry.

category: biochemistry


title: Deep mutational scanning and machine learning reveal structural and molecular rules governing allosteric hotspots in homologous proteins

abstract: A fundamental question in protein science is where allosteric hotspots - residues critical for allosteric signaling - are located, and what properties differentiate them. We carried out deep mutational scanning (DMS) of four homologous bacterial allosteric transcription factors (aTF) to identify hotspots and built a machine learning model with this data to glean the structural and molecular properties of allosteric hotspots. We found hotspots to be distributed protein-wide rather than being restricted to "pathways" linking allosteric and active sites as is commonly assumed. Despite structural homology, the location of hotspots was not superimposable across the aTFs. However, common signatures emerged when comparing hotspots coincident with long-range interactions, suggesting that the allosteric mechanism is conserved among the homologs despite differences in molecular details. Machine learning with our large DMS datasets revealed that global structural and dynamic properties to be a strong predictor of whether a residue is a hotspot than local and physicochemical properties. Furthermore, a model trained on one protein can predict hotspots in a homolog. In summary, the overall allosteric mechanism is embedded in the structural fold of the aTF family, but the finer, molecular details are sequence-specific.


title: Magnetic Enrichment of Immuno-Specific Extracellular Vesicles for Mass Spectrometry Using Biofilm-Derived Iron Oxide Nanowires

abstract: Immuno-specific enrichment of extracellular vesicles (EVs) originating from specific cells/tissues is a promising source of information towards improving insights into cellular pathways underpinning various pathologies and developing novel non-invasive diagnostic methods. Enrichment is an important aspect in mass spectrometry-based analyses of EVs. Herein, we report a protocol for immuno-magnetic enrichment of subtype specific EVs and their subsequent processing for mass spectrometry. Specifically, we conjugated placental alkaline phosphatase (PLAP) antibodies to magnetic iron oxide nanowires (NWs) derived from bacterial biofilms and demonstrated the utility of this approach by enriching placental specific EVs (containing PLAP) from cell culture media. We demonstrate efficient PLAP+ve EV enrichment for both NW-PLAP and Dynabeads-PLAP, with PLAP protein recovery (83.7{+/-}8.9% and 83.2{+/-}5.9%, respectively), high particle-to-protein ratio (7.5{+/-}0.7x109 and 7.1 {+/-} 1.2x109, respectively), and low non-specific binding of non-target EVs (7{+/-}3.2% and 5.4{+/-}2.2%, respectively). Furthermore, our optimized EV enrichment and processing approach identified 2518 and 2545 protein groups with mass spectrometry for NW-PLAP and Dynabead-PLAP, respectively, with excellent reproducibility (Pearson correlation 0.986 and 0.988). The proposed immuno-specific EVs enrichment and liquid chromatography-tandem mass spectrometry method using naturally occurring iron oxide magnetic NWs or gold-standard Dynabeads enables high-quality EV proteomic studies.

category: bioengineering


title: Imaging the structure and dynamic activity of retinal microglia and macrophage-like cells in the living human eye

abstract:
PurposeWe recently showed how a refined sequential detection pattern and image processing pipeline for multi-offset adaptive optics scanning light ophthalmoscopy (AOSLO) can increase the contrast of weakly scattering inner retinal structures, including microglia. However, sequential detection was still time-consuming, preventing dynamics from being monitored over short intervals (< 3 mins). Here we show that simultaneous fiber-bundle (FB) detection can overcomes this limitation to reveal the structure and dynamic activity of microglia and macrophage-like cells in healthy and diseased retinae.

MethodsWe designed and implemented a custom 7-fiber optical FB with one central confocal fiber and six larger fibers for multi-offset detection in AOSLO at a single focal plane. We imaged the ganglion cell layer at several locations at multiple timepoints (from minutes to weeks) in 8 healthy participants and in 4 patients with ocular infections or inflammation, including ocular syphilis and posterior uveitis. Microglia and immune cells were manually segmented to quantify cell morphometry and motility.

ResultsFiber-bundle detection reduced single acquisition time to 20-30 seconds, enabling imaging over larger areas and monitoring of dynamics over shorter intervals. Presumed microglia in healthy retinas had an average diameter of 12.8 m and with a spectrum of morphologies including circular cells and elongated cells with visible processes. We also detected the somas of putative macroglia, potentially astrocytes, near the optic nerve head. Microglia moved slowly in normal eyes (0.02m/sec, on average) but speed increased in patients with active infections or inflammation (up to 2.37m/sec). Microglia activity was absent in a patient with chronic uveitis that was quiescent but apparent over short intervals in an active uveitis retina. In a patient with ocular syphilis imaged at multiple timepoints during treatment, macrophage-like cells containing granular internal structures were seen. Decreases in the quantity and motility of these immune cells were correlated with improvements to vision and other structural and systemic biomarkers.

ConclusionsFB-AOSLO enable simplified optical setup with easy alignment and implementation. We imaged the fine-scale structure and dynamics of microglia and macrophage-like cells during active infection and inflammation in the living eye for the first time. In healthy eyes we also detected putative glia cell near the optic nerve head. FB-AOSLO offers promise as a powerful tool for detecting and monitoring retinal inflammation and infection in the living eye over short response to treatment.


title: Rebound Excitation of Epileptiform Activities by Transcranial Focused Ultrasound Stimulation

abstract:
BackgroundConventional neurostimulations to treat epilepsy have adverse effects caused by post-inhibitory rebound excitations. Although ultrasound brain stimulation is feasible in inducing anticonvulsant effects, its association with paradoxical rebound excitations is unknown.

ObjectiveThis study aimed at demonstrating rebound excitations with transcranial focused ultrasound. The modulations of epileptiform activities toward both suppressive and excitatory responses were investigated by changing ultrasonic transmit sequences.

MethodsIn a pentylenetetrazol-injected acute epilepsy rat model, transcranial focused ultrasound stimulation was applied on the thalamus to modulate epileptiform activities. The parameters differentiated for pulse sequences were the pulse length, pulse pressure, and interval between the pulses. Sonication effects were assessed by electroencephalography (n=38), immuno-histochemical analysis (n=24), and optical measurement of cerebral blood volume changes (n=18).

ResultsWhile ultrasonic patterns of stimuli at long intervals showed antiepileptic effects on electroencephalography, those at short intervals showed rebound excitatory responses followed by inhibitory activities. Further, suppressive states induced by inhibitory stimulations were transformed into excitatory states by applying a consecutive series of short bursts at higher acoustic pressure. Cerebral blood volume changes demonstrated consistent results with electroencephalography. Immunohistochemistry revealed that both inhibitory and excitatory neuronal cells were activated to generate rebound excitatory conditions, while inhibitory cells were activated for suppressive conditions.

ConclusionsIn our study, variations in ultrasound stimulation patterns could modulate epileptiform activities in both upregulated and downregulated directions.


title: A new computational framework like Google identifies therapeutic targets based on machine learning unveiling influential genes in pancreatic islet cells

abstract: Pancreatic islets comprise a group of cells that produce hormones regulating blood glucose levels. Particularly, the alpha and beta islet cells produce glucagon and insulin to stabilize blood glucose. When beta islet cells are dysfunctional, insulin is not secreted, inducing a glucose metabolic disorder. Identifying effective therapeutic targets against the disease is a complicated task and is yet not conclusive. To close the wide gap between understanding the molecular mechanism of pancreatic islet cells and providing effective therapeutic targets, we present a computational framework to identify potential therapeutic targets against pancreatic disorders. First, we downloaded three transcriptome expression profiling datasets pertaining to pancreatic islet cells (GSE87375, GSE79457, GSE110154) from the Gene Expression Omnibus database. For each dataset, we extracted expression profiles for two cell types. We then provided the extracted expression profile along with the cell types to our proposed constrained optimization problem of a support vector machine and to other existing methods, selecting important genes from the expression profiles. Finally, we performed (1) an evaluation from a classification perspective showing the superiority of our methods against the baseline; and (2) an enrichment analysis showing that our methods achieved better outcomes. Results for the three datasets included 44 unique genes and 10 unique transcription factors (SP1, HDAC1, EGR1, E2F1, AR, STAT6, RELA, SP3, NFKB1, and ESR1) that have been reported related to pancreatic islet functions, diseases, and therapeutic targets.

category: bioinformatics


title: The reprogrammed mouse heart phosphoproteome in response to the chronic stress of markedly high cardiac-specific adenylyl cyclase type 8 overexpression

abstract: An appropriate intensity and duration of increased AC-cAMP-PKA-Ca2+ signaling is the quintessential component of acute adaptation to cardiac stress. Our previous work demonstrated the existence of an exquisite heart performance and protection profile in response to chronically increased cardiac AC-cAMP-PKA-Ca2+ signaling in young adult mice with cardiac-specific overexpression of adenylyl cyclase type 8 (AC8) (TGAC8). Here, we conducted an unbiased phosphoproteomics analysis in order to determine the role of altered protein phosphorylation in the chronic adaptive heart performance and protection profile of left ventricle (LV) of adult TGAC8 at 3-4 months of age. We identified 12,963 phospho-peptides and 3646 phosphoproteins, including 4990 upregulated phosphopeptides and 781 differentially regulated (741 Up and 40 Down) phosphoproteins in TGAC8 vs. WT. Based on differentially regulated phosphoproteins by genotype, we discovered the enrichment of numerous stress response canonical pathways within reprogrammed TGAC8 LV, including protein kinase A (PKA) signaling, PI3K signaling, and AMPK signaling, predicted upstream regulators, e.g., PDPK1, PAK1 and PTK2B, and downstream functions, e.g., cell viability, protein quality control, and metabolism. In addition to PKA, numerous kinases (83) and phosphatases (30) were hyper-phosphorylated in TGAC8 vs. WT. By combining the phosphoproteome with its proteome and with the previously published TGAC8 transcriptome, we determined which cardiac performance and adaptive protection profiles were coordinately regulated at post-translational modification (PTM) (phosphorylation), translational and transcriptional levels. In order to assess the impact of phosphorylation on mRNA transcription, we determined the phosphorylation states of transcriptional factors (TFs) that differed by genotype. Hyper-phosphorylated TFs in TGAC8 were associated with increased mRNA transcription, and immune responses and metabolism pathways. To determine the coordination of proteome and phosphoproteome in reprogramming the TGAC8 LV, we normalized its phosphoproteome to its proteome (by dividing the protein phosphorylation abundance by protein abundance). In functional enrichment analysis of 229 normalized phosphoproteins that were differentially regulated by genotype, enriched IPA canonical pathways in the phosphoproteome of TGAC8 LV before and after normalization showed high consistency. The combination of aforementioned analyses indicated that many stress response signaling pathways, i.e., PI3K/AKT signaling and ubiquitin labeling, were consistently enriched at transcriptional, translational and PTM levels, and that PI3K/AKT signaling was also activated in the TGAC8 LV. Thus, PTM of protein by phosphorylation, per se, contributes immensely to the heart performance and protection profile of TGAC8 LV, and is coordinately regulated with altered transcription and translation in the TGAC8 to activate critical stress response pathways.


title: A deep learning framework for structural variant discovery and genotyping

abstract: Structural variants (SV) are a major driver of genetic diversity and disease in the human genome and their discovery is imperative to advances in precision medicine and our understanding of human genetics. Existing SV callers rely on hand-engineered features and heuristics to model SVs, which cannot easily scale to the vast diversity of SV types nor fully harness all the information available in sequencing datasets. Since deep neural networks can learn complex abstractions directly from the data, they offer a promising approach for general SV discovery. Here we propose an extensible deep learning framework, Cue, to call and genotype SVs. At a high level, Cue converts sequence alignments to multi-channel images that capture multiple SV-informative signals and uses a stacked hourglass convolutional neural network to predict the type, genotype, and genomic locus of the SVs captured in each image. We show that Cue outperforms the state of the art in the detection of five classes of SVs (including two types of complex SVs and subclonal SVs) on synthetic and real short-read data and that it can be easily extended to other sequencing platforms, such as long and linked read sequencing technologies, while achieving competitive performance. By design, Cue can also be automatically extended to support new SV classes: this versatility is crucial as novel SV types are discovered in ongoing population-scale sequencing initiatives.


title: Single cell transcriptional landscape of long non-coding RNAs orchestrating mouse heart development

abstract: Long non-coding RNAs (lncRNAs) comprise the most representative transcriptional units of the mammalian genome, and theyre associated with organ development that can be associated with the emergence of diseases, such as cardiovascular diseases. Thus, we used bioinformatic approaches, machine learning algorithms and statistical techniques to define lncRNAs involved in mammalian cardiac development. We used a single-cell transcriptome dataset generated from 4 embryonic and 4 postnatal stages. Our study identified 8 distinct cell types, novel marker transcripts (coding/lncRNAs) and also, differential expression and functional enrichment analysis reveal cardiomyocyte subpopulations associated with cardiac function; meanwhile modular co-expression analysis reveals cell-specific functional insights for lncRNAs during myocardial development, including a potential association with key genes related to disease and the "fetal gene program". Our results evidence the role of particular lncRNAs in heart development, and highlights the usage of co-expression modular approaches in the cell-type functional definition.


title: DysRegNet: Patient-specific and confounder-aware dysregulated network inference

abstract:
Gene regulation is frequently altered in diseases in unique and often patient-specific ways. Hence, personalized strategies have been proposed to infer patient-specific gene-regulatory networks. However, existing methods do not focus on disease-specific dysregulation or lack assessments of statistical significance. Moreover, they do not account for clinically important confounders such as age, sex or treatment history.

To overcome these shortcomings, we present DysRegNet, a novel method for inferring patient-specific regulatory alterations (dysregulations) from gene expression profiles. We compared DysRegNet to state-of-the-art methods and demonstrated that DysRegNet produces more interpretable and biologically meaningful networks. Independent information on promoter methylation and single nucleotide variants further corroborate our results. We apply DysRegNet to eleven TCGA cancer types and illustrate how the inferred networks can be used for down-stream analysis. We show that unique as well as cancer-type-specific dysregulation patterns exist and highlight immune-related mechanisms that are not obvious when focusing on individual genes rather than their interactions.

DysRegNet is available as a Python package (https://github.com/biomedbigdata/DysRegNet_package) and analysis results for eleven TCGA cancer types are further available through an interactive web interface (https://exbio.wzw.tum.de/dysregnet).


title: Effects of Full-cycle Exposure to Difenoconazole in Parental Zebrafish on the Liver-gut Axis of F0 and F1 Generations

abstract: To explore the effects of long-term exposure to low-dose difenoconazole (DCZ) on lipid metabolism in the liver-gut axis, we exposed zebrafish embryos to ambient concentrations of DCZ for 120 days and comprehensively analyzed the metabolic and microbial networks of the F0 and F1 generations using biochemical, metabolomic and metagenomics approaches. The changes of biochemical indexes indicated that DCZ exposure inhibited lipid synthesis, lipolysis and lipid transport of F0 males and females. In addition, the composition of gut microbes in males and females was significantly changed, which corresponds to changes in biochemical parameters in liver, intestine and serum. Metabolome analysis showed that pathways related to amino acid metabolism, ATP-binding cassette transporters, carbohydrate metabolism, and energy metabolism were downregulated in the gut of males and females. At 120 days post-fertilization, lipid synthesis, lipolysis and lipid transport of F1 males was upregulated; the composition of microbiota and metabolome of the F1males gut was significantly altered. Overall, we found that long-term exposure to low doses of DCZ inhibited the liver-gut axis in males and females, and the liver-gut axis in F1 males were disturbed even in F1 generation without DCZ exposure.


title: Evaluating deep learning for predicting epigenomic profiles

abstract: Deep learning has been successful at predicting epigenomic profiles from DNA sequences. Most approaches frame this task as a binary classification relying on peak callers to define functional activity. Recently, quantitative models have emerged to directly predict the experimental coverage values as a regression. As new models continue to emerge with different architectures and training configurations, a major bottleneck is forming due to the lack of ability to fairly assess the novelty of proposed models and their utility for downstream biological discovery. Here we introduce a unified evaluation framework and use it to compare various binary and quantitative models trained to predict chromatin accessibility data. We highlight various modeling choices that affect generalization performance, including a downstream application of predicting variant effects. In addition, we introduce a robustness metric that can be used to enhance model selection and improve variant effect predictions. Our empirical study largely supports that quantitative modeling of epigenomic profiles leads to better generalizability and interpretability.


title: Robust Normalization and Integration of Single-cell Protein Expression across CITE-seq Datasets

abstract:
CITE-seq technology enables the direct measurement of protein expression, known as antibody-derived tags (ADT), in addition to RNA expression. The increase in the copy number of protein molecules leads to a more robust detection of protein features compared to RNA, providing a deep definition of cell types. However, due to added discrepancies of antibodies, such as the different types or concentrations of IgG antibodies, the batch effects of the ADT component of CITE-seq can dominate over biological variations, especially for the across-study integration. We present ADTnorm as a normalization and integration method designed explicitly for the ADT counts of CITE-seq data. Benchmarking with existing scaling and normalization methods, ADTnorm achieves a fast and accurate matching of the negative and positive peaks of the ADT counts across samples, efficiently removing technical variations across batches. Further quantitative evaluations confirm that ADTnorm achieves the best cell-type separation while maintaining the minimal batch effect. Therefore, ADTnorm facilitates the scalable ADT count integration of massive public CITE-seq datasets with distinguished experimental designs, which are essential for creating a corpus of well-annotated single-cell data with deep and standardized annotations.

Contactraphael.gottardo@chuv.ch

Supplementary informationSupplementary data are available online.


title: Changes in protonation states of in-pathway residues can alter ligand binding pathways obtained from spontaneous binding molecular dynamics simulations

abstract: Protein-ligand binding processes often involve changes in protonation states that can be key to recognize and orient the ligand in the binding site. The pathways through which (bio)molecules interplay to attain productively bound complexes are intricate and involve a series of interconnected intermediate and transition states. Molecular dynamics (MD) simulations and enhanced sampling techniques are commonly used to characterize the spontaneous binding of a ligand to its receptor. However, the effect of protonation state changes of in-pathway residues in spontaneous binding MD simulations remained mostly unexplored. Here, we used molecular dynamics simulations to reconstruct the trypsin-benzamidine binding pathway considering different protonation states of His57. This residue is part of the trypsin catalytic triad and is located more than 10 [A] away from Asp189, which is responsible for benzamidine binding in the trypsin S1 pocket. Our MD simulations showed that the binding pathways that benzamidine follow to target the S1 binding site are critically dependent on the His57 protonation state. Binding of benzamidine frequently occurs when His57 is protonated in the delta nitrogen while the binding process is significantly less frequent when His57 is positively charged. Constant-pH MD simulations retrieved the equilibrium populations of His57 protonation states at trypsin active pH offering a clearer picture of benzamidine recognition and binding. These results indicate that properly accounting for protonation states of distal residues can be important in spontaneous binding MD simulations.

category: biophysics


title: Transcription-induced active forces suppress chromatin motion by inducing a transient disorder-to-order transition

abstract: Recent experiments have shown that the mobility of human interphase chromosome decreases during transcription, and increases upon inhibiting transcription, a finding that is counter-intuitive because it is thought that the active mechanical force (F) generated by RNA polymerase II (RNAPII) on chromatin would render it more open and mobile. We use a polymer model to investigate how F, derived from transcriptional activity, affects the dynamical properties of chromatin. The movements of the loci in the gene-rich region are suppressed in an intermediate range of F, and are enhanced at small and large F values. In the intermediate F, the bond length between consecutive loci increases, becoming commensurate with the location of the minimum in the attractive interaction between the active loci in the chromatin. This results in a disorder-to-order transition, leading to the decreased mobility during transcription. Our results suggest that transient ordering of the loci in the generich region might be a mechanism for nucleating a dynamic network involving transcription factors, RNAPII, and chromatin.


title: Compressive stress drives adhesion-dependent unjamming transitions in breast cancer cell migration

abstract: Cellular unjamming is the collective fluidization of cell motion and has been linked to many biological processes, including development, wound repair, and tumor growth. In tumor growth, the uncontrolled proliferation of cancer cells in a confined space generates mechanical compressive stress. However, because multiple cellular and molecular mechanisms may be operating simultaneously, the role of compressive stress in unjamming transitions during cancer progression remains unknown. Here we investigate which mechanism dominates in a dense, mechanically stressed monolayer. We find that long-term mechanical compression triggers cell arrest in benign epithelial cells and enhances cancer cell migration in transitions correlated with cell shape, leading us to examine the contributions of cell-cell adhesion and substrate traction in shape-dependent unjamming transitions. We show that cadherin-mediated cell-cell adhesion regulates differential cellular responses to compressive stress and predominantly controls unjamming transitions in dense monolayers. Importantly, compressive stress does not induce the epithelial--mesenchymal transition in unjammed cells. Using traction force microscopy, traction forces are attenuated in compressed cells in the bulk of the monolayer regardless of cell type and motility. Intercellular adhesion thus is the dominant regulator of compression-induced unjamming transitions and may impact collective cell motion in tumor development and breast cancer progression.


title: Sexually dimorphic activation of innate antitumour immunity prevents adrenocortical carcinoma development

abstract: In contrast with most cancers, adrenocortical carcinomas (ACC) are more frequent in women than men, but the underlying mechanisms of this sexual dimorphism remain elusive. Homozygous deletion of the negative WNT pathway regulator ZNRF3 is the most frequent alteration in ACC patients. Here, we show that Cre-mediated inactivation of Znrf3 in steroidogenic cells of the mouse adrenal cortex is associated with sexually dimorphic tumour progression. Indeed, although most knockout female mice develop metastatic carcinomas over an 18 month-time course, adrenal hyperplasia gradually regresses in male knockout mice. This male-specific regression is associated with induction of senescence and recruitment of macrophages, which differentiate as active phagocytes that clear-out senescent preneoplastic cells. Macrophage recruitment is also observed in female mice. However, it is delayed and dampened compared to males, which allows for tumour progression. Interestingly, testosterone treatment of female knockouts is sufficient to induce senescence, recruitment of phagocytic macrophages and regression of hyperplasia. We further show that although macrophages are present within adrenal tumours at 18 months, MERTKhigh active phagocytes are mostly found in indolent lesions in males but not in aggressive tumours in females. Consistent with our observations in mice, analysis of RNA sequencing data from the TCGA cohort of ACC shows that phagocytic macrophages are more prominent in men than women and associated with better prognosis. Altogether, these data establish that phagocytic macrophages prevent aggressive ACC development in male mice and suggest that they may play a key role in the unusual sexual dimorphism of ACC in patients.

category: cancer biology


title: Glutamine is essential for overcoming theimmunosuppressive microenvironment in malignant salivary gland tumors

abstract:
RationaleImmunosuppression in the tumor microenvironment (TME) is key to the pathogenesis of solid tumors. Tumor cell-intrinsic autophagy is critical for sustaining both tumor cell metabolism and survival. However, the role of autophagy in the host immune system that allows cancer cells to escape immune destruction remains poorly understood. Here, we determined if attenuated host autophagy is sufficient to induce tumor rejection through reinforced adaptive immunity. Furthermore, we determined whether dietary glutamine supplementation, mimicking attenuated host autophagy, is capable of promoting antitumor immunity.

MethodsA syngeneic orthotopic tumor model in Atg5+/+ and Atg5flox/flox mice was established to determine the impact of host autophagy on the antitumor effects against mouse malignant salivary gland tumors (MSTs). Multiple cohorts of immunocompetent mice were used for oncoimmunology studies, including inflammatory cytokine levels, macrophage, CD4+, and CD8+ cells tumor infiltration at 14 days and 28 days after MST inoculation. In vitro differentiation and in vivo dietary glutamine supplementation were used to assess the effects of glutamine on Treg differentiation and tumor expansion.

ResultsWe showed that mice deficient in the essential autophagy gene, Atg5, rejected orthotopic allografts of isogenic MST cells. An enhanced antitumor immune response evidenced by reduction of both M1 and M2 macrophages, increased infiltration of CD8+ T cells, elevated IFN-{gamma} production, as well as decreased inhibitory Tregs within TME and spleens of tumor-bearing Atg5flox/flox mice. Mechanistically, ATG5 deficiency increased glutamine level in tumors. We further demonstrated that dietary glutamine supplementation partially increased glutamine levels and restored potent antitumor responses in Atg5+/+ mice.

ConclusionsDietary glutamine supplementation exposes a previously undefined difference in plasticity between cancer cells, cytotoxic CD8+ T cells and Tregs.


title: TME induced TRAIL secretion from engineered macrophages for anti-tumor therapy

abstract: Capacity of tumor niche chemotaxis and long-term persistency making macrophage as great vehicles for anti-tumor factor delivery. Macrophages-based delivery of chemokines or cytokines have been tested for tissue homeostasis and cancer repression. TRAIL as a promising anti-tumor cytokine, made little clinical progress due to limited stability and off-target toxicity. Here we engineered macrophages with tumor micro-environment (TME)-induced trimerized CP1-TRAIL secretion under the TME specific promoter Arg1 (Tri-TRAIL-iM). The Tri-TRAIL-iM cells displayed high specific inducible activity in both cell-based co-culture assay and in tumor baring mice models. Compared to normal TRAIL over-expressed macrophages under none-inducible promoter, Tri-TRAIL-iM infiltrated to tumor sites and showed superior apoptosis induction of cancer cells and tumor growth repression as well as less systemic side effect. This inducible delivery TRAIL strategy can be effectively further applied in clinical studies and can be coupled with other engineered methods to maximize the therapeutic outcomes for solid tumors.


title: Increased glucose availability sensitizes pancreatic cancer to chemotherapy

abstract: Pancreatic cancer (Pancreatic Ductal Adenocarcinoma; PDAC) is highly resistant to chemotherapy. Effective alternative therapies have yet to emerge, leaving chemotherapy as the best available systematic treatment. The discovery of safe and available adjuncts that improve chemotherapeutic efficacy would potentially improve survival outcomes. We show that a hyperglycemic state enhances the efficacy of conventional single- and multi-agent chemotherapies against PDAC. Molecular analyses of tumors exposed to relatively high glucose levels revealed that a key metabolic pathway, glutathione biosynthesis, is diminished and underlies chemo-sensitization by enhancing oxidative injury to cancer cells. Inhibition of this pathway under normal conditions phenocopied a hyperglycemic state by enhancing chemotherapeutic efficacy in mouse PDAC, while rescuing the pathway under high glucose abrogated the anti-tumor effects observed with chemotherapy.


title: BRCA1 Hypermethylation In Sporadic Breast Cancers: Discovering A Novel Pathway To Tumorigenesis Via Coordinate NBR2 Deregulation And TNBC Transformation

abstract:
Women with a family history of mutations in the Breast cancer susceptibility gene, BRCA1 will have an increased risk of developing breast neoplasms. However, majority of the breast cancers are sporadic where BRCA1 mutations are very rare. Instead, 5-65% of sporadic cases manifest BRCA1 promoter hypermethylation and 30-40% of such cases are develop into Triple Negative Breast Cancers. Even then, the molecular mechanism of BRCA1 hypermethylation mediated breast tumorigenesis has remained an enigma till date. Here, we present a novel tumorigenesis pathway for breast cancers that engenders from BRCA1 hypermethylation by using a modified version of CRISPR technology.

We report that induction of site-specific methylation on BRCA1 promoter  effectuates a downregulation in BRCA1 expression via alteration in the balance between its alternate transcripts {beta} and . Induced BRCA1 hypermethylation is also responsible for the attenuation of a long noncoding RNA, NBR2 (Neighbour of BRCA1 gene 2), which is transcribed through the bidirectional BRCA1 promoter  in the reverse direction. Downregulation of NBR2 activates a feedback loop by leading to further downregulation of BRCA1 which is more evident under glucose starvation conditions and is associated with an impaired DNA damage repair pathway. Further, BRCA1 hypermethylation also results in significant overexpression of {beta}-hCG (human chorionic gonadotrophin), which was found to be associated with highly aggressive and drug-resistant forms of BRCA1 mutated breast cancers invitro & in vivo in our previous study. Finally, we report a variation in the hormone receptor levels as the tumor progresses which suggests how BRCA1 deficient cells modulate their expression of ER- and ER-{beta} to promote their proliferation in early stages of tumor development and at later stages, transform to a basal tumor subtype by shedding down the expression of ER- & PR.

GRAPHICAL ABSTRACT

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title: Isotope-based visualization of element distribution in phloem provides functional evidence for the operation of SOS1 Na+/H+ exchangers in mature zones of Arabidopsis root

abstract: In the phloem, various solutes such as photosynthates, mineral nutrients, or toxic elements move from the source organs to sinks. One of them is the root. While this process may mediate significant quantities of solutes delivered to the root, it is unclear how the solutes are distributed along the root axis. To elucidate the distributing pattern of solutes, we visually analyzed the movement of solutes in Arabidopsis roots using a radioisotope imaging technique. The distribution patterns fell into four different groups: (1) root tip accumulation for 14C-photosynthates, 28Mg2+, 32PO43-, and 35SO42-; (2) homogenous distribution along the root axis for 42K+ and 137Cs+; (3) no detectable accumulation in the root for 45Ca2+ and 59Fe2+; and (4) transient accumulation in the root for 22Na+. The latter phenomenon was explored in more detail using Arabidopsis knockout mutants lacking functional sodium efflux transporter SOS1 (operating as Na+/H+ exchanger). By utilizing a non-invasive microelectrode MIFE ion flux measuring technique, we found that Na+ efflux was active in the mature root zone of wild-type Arabidopsis plants but not in root apex as initially thought, and that in sos1 mutants lacking functional Na+/H+ exchangers, shoot-derived 22Na+ remained in the root. These findings challenge the notion that Na+ exclusion via SOS1 is confined to the root apex and demonstrates the power of combining the radioisotope imaging technique and the MIFE ion flux measuring technique to study the kinetics of ion transport in the root and root-to-shoot communication.

category: plant biology


title: Modelling mouse auditory response dynamics along a continuum of consciousness using a deep recurrent neural network

abstract:
ObjectiveUnderstanding neurophysiological changes that accompany transitions between anaesthetized and conscious states is a key objective of anesthesiology and consciousness science. This study aimed to characterize the dynamics of auditory-evoked potential morphology in mice along a continuum of consciousness.

ApproachEpidural field potentials were recorded from above the primary auditory cortices of two groups of laboratory mice: urethane-anaesthetized (A, n = 14) and conscious (C, n = 17). Both groups received auditory stimulation in the form of a repeated pure-tone stimulus, before and after receiving 10 mg/kg i.p. ketamine (AK and CK). Evoked responses were then ordered by ascending sample entropy into AK, A, CK, and C, considered to reflect physiological correlates of awareness. These data were used to train a recurrent neural network (RNN) with an input parameter encoding state. Model outputs were compared with grand-average event-related potential (ERP) waveforms. Subsequently, the state parameter was varied to simulate changes in the ERP that occur during transitions between states, and relationships with dominant peak amplitudes were quantified.

Main resultsThe RNN synthesized output waveforms that were in close agreement with grand-average ERPs for each group (r2 > 0.9, p < 0.0001). Varying the input state parameter generated model outputs reflecting changes in ERP morphology predicted to occur between states. Positive peak amplitudes within 25 to 50 ms, and negative peak amplitudes within 50 to 75 ms post-stimulus-onset, were found to display a sigmoidal characteristic during the transition from anaesthetized to conscious states. In contrast, negative peak amplitudes within 0 to 25 ms displayed greater linearity.

SignificanceThis study demonstrates a method for modelling changes in ERP morphology that accompany transitions between states of consciousness using a RNN. In future studies, this approach may be applied to human data to support the clinical use of ERPs to predict transition to consciousness.


title: Beneficial effects of cellular coinfection resolve inefficiency in influenza A virus transcription

abstract:
For diverse viruses, cellular infection with single vs. multiple virions can yield distinct biological outcomes. We previously found that influenza A/guinea fowl/Hong Kong/WF10/99 (H9N2) virus (GFHK99) displays a particularly high reliance on multiple infection in mammalian cells. Here, we sought to uncover the viral processes underlying this phenotype. We found that the need for multiple infection maps amino acid 26K of the viral PA protein. PA 26K suppresses endonuclease activity and viral transcription, specifically within cells infected at low multiplicity. In the context of the higher functioning PA 26E, inhibition of PA using baloxavir acid augments reliance on multiple infection. Together, these data suggest a model in which sub-optimal activity of the GFHK99 endonuclease results in inefficient priming of viral transcription, an insufficiency which can be overcome with the introduction of additional viral templates to the cell. These findings offer rare mechanistic insight into the benefits of viral collective dispersal.

Graphical Abstract

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category: microbiology


title: Inter-organ Wingless/Ror/Akt signaling regulates nutrient-dependent hyperarborization of somatosensory neurons

abstract: Nutrition in early life has profound effects on an organism, altering processes such as organogenesis. However, little is known about how specific nutrients affect neuronal development. Dendrites of class IV neurons in Drosophila larvae become more complex when the larvae are reared on a low-yeast diet compared to a high-yeast diet. Our systematic search for key nutrients revealed that the neurons increase their dendrite densities in response to a combined deficiency in vitamins, metal ions, and cholesterol. These nutrients affect dendrite branching through the Wingless/Ror/Akt pathway between the neuron and closely located muscles, and this short range-pathway is regulated by a systemic Upd2-Stat92E pathway between the fat body and muscles. Additionally, the low-yeast diet blunts neuronal light responsiveness and light avoidance behavior, which may help larvae optimize their survival strategies under low-nutritional conditions. Together, our studies illustrate how the availability of specific nutrients affects neuronal development through inter-organ signaling.


title: Tree diversity and density affect damage caused by the invasive pest Cameraria ohridella in urban areas

abstract:
Invasive, non-native invasive pests pose a growing threat to urban trees and the services they provide to urban residents. With the reluctance to use chemical insecticides in cities, environmentally friendly methods of pest management are needed. Tree diversity is known to affect insect herbivory in forest, with higher tree species diversity leading to lower level of damage. However, the validity of those findings for a non-native insect in an urban environment remains to be demonstrated.

We monitored 54 horse chestnut trees attacked by the invasive horse chestnut leafminer Cameraria ohridella in the city of Bordeaux, France. We analyzed the effects of neighboring tree diversity and density on the abundance, damage and parasitism rate of these leafminers.

We showed that the abundance and damage of C. ohridella significantly increased with higher local tree canopy cover. We found that the parasitism rate of C. ohridella increased with the species diversity of neighboring trees. However, this increase in parasitism rate was not associated with a decrease in leaf area damaged.

Our results pave the way for the management of exotic insect pests in cities based on the manipulation of spatial distribution and species diversity of urban trees.


title: Discordant effects of resource limitation on host survival and systemic pathogen growth in Drosophila-bacteria infection models: resistance vs. tolerance

abstract: In the experiments presented here, we explore the effect of resource limitation, in form of starvation (which leads to decrease in accessible resources and depletion of reserves) and sexual activity (which leads to reallocation of resources from somatic defence towards reproduction), on immune function of female Drosophila melanogaster flies. We infected females with five bacterial pathogens and measured their post-infection survival when subjected to either starvation or sexual activity (mating). Additionally, we measured within host pathogen levels in case of three of these pathogens. Based on previous literature, we predicted that both modes of resource limitation will increase post-infection mortality, but only sexual activity will lead to increase of pathogen load (because of compromised immune function), while starvation will either not affect or reduce pathogen loads (because of reduced availability of resources for the pathogen to proliferate within the host). Our results indicate that both starvation and sexual activity can lead to increased within-host pathogen levels, in addition to increased post-infection mortality, but in a pathogen-specific manner.


title: Phylogenomics provides insights into the evolution of cactophily and host plant shifts in Drosophila

abstract: Cactophilic species of the Drosophila buzzatii cluster (repleta group) comprise an excellent model group to investigate genomic changes underlying adaptation to extreme climate conditions and host plants. In particular, these species offer a subject to study the transition from chemically simpler breeding sites (like prickly pears of the genus Opuntia) to chemically more complex hosts (columnar cacti). Here, we report four highly contiguous genome assemblies of three species of the buzzatii cluster. Based on this genomic data and inferred phylogenetic relationships, we identified candidate taxonomically restricted genes (TRGs) likely involved in the evolution of cactophily and cactus host specialization in internal branches of the subgenus Drosophila. Functional enrichment analyses of TRGs within the buzzatii cluster identified genes involved in detoxification, water preservation, immune system response, anatomical structure development, and morphogenesis. In contrast, processes that regulate responses to stress, as well as the metabolism of nitrogen compounds, transport, and secretion were found in the set of species that are columnar cacti dwellers. These findings are in line with the hypothesis that those genomic innovations brought about instrumental mechanisms underlying adaptation in a group of species that speciated in the arid regions of South America.


title: Gene expression signatures underlying inbreeding depression as revealed by whole-transcriptome analysis of selectively bred strains of the Pacific Oyster (Crassostrea gigas)

abstract: Exploring molecular mechanisms of inbreeding depression is significant for the conservation and sustainable use of the rare breed with a specific trait of high production value. In this work, we conducted whole-transcriptome analysis of two selectively bred Pacific oyster strains with one inbred strain showing significant growth depression. A total of 7980, 2677, and 28 differentially expressed protein-coding genes (DEGs), lncRNAs (DELs), and miRNAs (DEMs) were identified, respectively. The majority of DEGs and predicted target genes of DELs and DEMs were significantly enriched in biological process including immune response, cell proliferation, and apoptosis pathways. A set of genes with specific expression patterns as revealed by cluster profiling and enrichment analysis were identified, which may underlie inbreeding depression of the inbred strain. Furthermore, a competing endogenous RNA (ceRNA) network was constructed by integrative analysis of DEGs, DELs, and DEMs, supporting that ncRNAs, as regulators of gene expression, could be critical modulators in multiple subsystems involved in inbreeding depression.


title: Combined MD and QM/MM Calculations reveal Allostery Driven Promiscuity in Dipeptide Epimerases of Enolase Family

abstract: The adaptability of the active site to amplify the secondary function is supposed to be the fundamental cause of the promiscuity and the evolution of new functions in the enzymes. In most cases, mutations occur close to the active site and/or in the catalytic site to change the active site plasticity to accommodate the non-native substrate. In the present study, using MD simulations and hybrid QM/MM calculations, we have shown a new way to enhance the promiscuity, i.e., the allostery-driven promiscuity. Using a case study of the AEE enzyme where the capping loop recognizes the substrate, herein, we show that a single site mutation (D321G) far from the capping loop can induce a large conformational change in the capping loop to recognize different substrates for different functions. The QM/MM calculations for the WT and mutated enzyme provide a first validation of the mechanism of 1,1-proton transfer and dehydration by the AEE enzyme. Since AEE epimerase possesses a highly conserved TIM-barrel fold, we believe that our study provides a crucial lead to understanding the mechanism of emergence of secondary function which can be useful to repurpose ancient enzymes for modern usage.


title: Boosting polygenic risk scores

abstract:
Polygenic risk scores (PRS) evaluate the individual genetic liability to a certain trait and are expected to play an increasingly important role in the field of clinical risk stratification. Most often, PRS are estimated based on summary statistics of univariate effects derived from genome-wide association studies. To improve the predictive performance of PRS, it is desirable to fit multivariable models directly on the genetic data. Due to the large and high-dimensional data, a direct application of existing methods is often not feasible and new efficient algorithms are required to overcome the computational burden regarding efficiency and memory demands.

We develop an adapted component-wise L2-boosting algorithm to fit genotype data from large cohort studies to continuous outcomes using linear base-learners for the genetic variants. Similar to the snpnet approach implementing lasso regression, the proposed snpboost approach iteratively works on smaller batches of variants. By restricting the set of possible base-learners in each boosting step to variants most correlated with the residuals from previous iterations, the computational efficiency can be substantially increased without losing prediction accuracy. Furthermore, for large-scale data based on various traits from the UK Biobank we show that our method yields competitive prediction accuracy and computational efficiency compared to the snpnet approach. Due to the modular structure of boosting, our framework can be further extended to construct PRS for different outcome data and effect types.


title: Transcriptome analysis reveals hepatotoxicity in zebrafish induced by cyhalofop-butyl

abstract:
Cyhalofop-butyl is a highly effective aryloxyphenoxypropionate herbicide and widely used for weed control in paddy fields. With the increasing residue of herbicides, it poses a threat to the survival of aquatic organisms. Here, we evaluated the effect of cyhalofop-butyl on zebrafish to explore its potential hepatotoxic mechanism. The results showed that cyhalofop-butyl (0.1, 0.2 and 0.4 mg/L) induced hepatocyte degeneration, vacuolation and necrosis of larvae after embryonic exposure for 4 days and caused liver atrophy after exposure for 5 days. Meanwhile, the activities of enzymes related to liver function named alanine transaminase (ALT), aspartate transaminase (AST) were significantly increased by 0.2 mg/L cyhalofop-butyl and higher. And the contents of triglyceride (TG) involved in lipid metabolism was significantly decreased by 0.4 mg/L cyhalofop-buty. The effects of cyhalofop-butyl on zebrafish larvae were further demonstrated by GO (Gene Ontology) and KEGG pathway analysis. Cyhalofop-butyl (0.1, 0.2, 0.4 mg/L) altered the expression of 116, 154, 397 genes in liver,these genes are mainly enriched in metabolism (such as lipid metabolism, amino acid metabolism), immune system (Toll-like receptor signaling pathway) and endocrine system (PPAR signaling pathway). Furthermore, the expression of key genes related to liver development combined with RNA-Seq results, indicated that cyhalofop-butyl might damage the liver development of zebrafish larvae and cause metabolic disorders. To sum up, our research results reveal the physiological and molecular responses of zebrafish liver to cyhalofop-butyl and provide new insights for further studying the mechanism of cyhalofop-butyl toxicity to aquatic organisms.

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=69 SRC="FIGDIR/small/490149v1_ufig1.gif" ALT="Figure 1">
View larger version (20K):
org.highwire.dtl.DTLVardef@503814org.highwire.dtl.DTLVardef@91b99eorg.highwire.dtl.DTLVardef@1316ed5org.highwire.dtl.DTLVardef@638155_HPS_FORMAT_FIGEXP  M_FIG C_FIG HighlightsO_LICyhalofop-butyl induced liver damage of zebrafish larvae and caused liver atrophy
C_LIO_LICyhalofop-butyl affected liver function by increasing the activities of ALT and AST.
C_LIO_LICyhalofop-butyl disturbed the lipid metabolism of liver in zebrafish via inhibition TG levels.
C_LIO_LICyhalofop-butyl exposure induced metabolism and immune system disturbance at transcriptional levels.
C_LI


title: HiCognition: a visual exploration and hypothesis testing tool for 3D genomics

abstract: The 3D organization of the genome and epigenetic marks play important roles in gene expression, DNA repair, and chromosome segregation. Understanding how structure and composition of the chromatin fiber contribute to function requires integrated analysis of multiple genomics datasets from various techniques, experimental conditions, and cell states. Genome browsers facilitate such analysis, yet currently visualize only a few regions at a time and lack statistical functions that are often necessary to extract meaningful information. Here, we present HiCognition, a visual exploration and machine-learning tool based on a new genomic region set concept, which enables detection of patterns and associations between 3D chromosome conformation and collections of 1D genomics profiles of any type. By revealing how transcriptional activity and cohesin subunit isoforms contribute to chromosome conformation, we showcase how the flexible user interface and machine learning tools of HiCognition can help understand the relationship between structure and function of the genome.


title: Exploratory Meta-Analysis of Hypoxic Transcriptomes Using a Precise Transcript Reference Sequence Set

abstract: Gene expression studies are intrinsically biased with many being influenced by concomitant information such as the gene-disease association. However, this can be overcome using a data-driven analysis approach, which can provide insights without relying on ancillary information. This is exemplified by the FANTOM CAGE Associated Transcriptome (FANTOM-CAT) project, which provides a comprehensive meta-assembly of the human transcriptome using coding and non-coding genes. Various studies have shown that hypoxia has a significant effect on gene expression, with several of these reports suggesting that non-coding RNA (ncRNA) metabolism is downregulated in response to hypoxic stimuli. We aimed to interrogate the differential response of various transcripts to hypoxia by determining their hypoxia responsiveness score. We performed these evaluations using enrichment analysis, which revealed that several genes associated with ncRNA metabolism, especially those involved in ribosomal RNA processing, were significantly downregulated in response to hypoxia. Then, we used previously published information from the FANTOM-CAT project to create a novel reference file suitable for the meta-analysis of transcriptome sequencing data from both coding and ncRNAs and used this to evaluate the hypoxia responsiveness of target transcripts, while also evaluating the relationship between sense-antisense transcripts from the same locus. These evaluations revealed that these transcript pairs often exhibit similar regulatory patterns, but that this is largely reliant on their specific function. We believe that this study will facilitate the functional annotation of various transcripts including ncRNAs, allowing for both sense and antisense and coding and non-coding evaluations.


title: ChemPert: mapping between chemical perturbation and transcriptional response for non-cancer cells

abstract: Prior knowledge of perturbation data can significantly assist in inferring the relationship between chemical perturbations and their specific transcriptional response. However, current databases mostly contain cancer cell lines, which are unsuitable for the aforementioned inference in non-cancer cells. Here we present ChemPert (https://chempert.uni.lu/), a database consisting of 82270 transcriptional signatures across 167 non-cancer cell types, enabling more accurate predictions of perturbation responses and drugs compared to cancer databases in non-cancer cells. In particular, ChemPert correctly predicted drug effects for treating non-alcoholic steatohepatitis and novel drugs for osteoarthritis. Overall, ChemPert provides a valuable resource for drug discovery in non-cancer diseases.


title: A mutation-level covariate model for mutational signatures

abstract: Mutational processes and their exposures in particular genomes are key to our understanding of how these genomes are shaped. However, current analyses assume that these processes are uniformly active across the genome without accounting for potential covariates such as strand or genomic region that could impact such activities. Here we suggest the first mutation-covariate models that explicitly model the effect of different covariates on the exposures of mutational processes. We apply these models to test the impact of replication strand on these processes and compare them to strand-oblivious models across a range of data sets. Our models capture replication strand specificity, point to signatures affected by it, and score better on held-out data compared to standard models that do not account for mutation-level covariate information.