title: Hybridization disrupts growth-defense strategies and reveals trade-offs masked in unadmixed populations of a perennial plant

abstract: Organisms are constantly challenged by pathogens and pests which can drive the evolution of growth-defense strategies. Plant stomata are essential for gas-exchange during photosynthesis and conceptually lie at the intersection of the physiological demands of growth and exposure to foliar fungal. Generations of natural selection for locally adapted growth-defense strategies can eliminate variation between traits, potentially masking trade-offs and selection conflicts that may have existed in the past. Hybrid populations offer a unique opportunity to reset the clock on selection and to study potentially maladaptive trait variation before selection removes it. We study the interactions of growth, stomatal, ecopysiological, and disease resistance traits in Poplars (Populus) after infection by the leaf rust Melampsora medusae. Phenotypes were measured in a common garden and genotyped at 227K SNPs. We isolate the effects of hybridization on trait variance, discover correlations between stomatal, ecophysiology and disease resistance, examine trade-offs and selection conflicts, and explore the evolution of growth-defense strategies potentially mediated by selection for stomatal traits on the upper leaf surface. These results suggest an important role for stomata in determining growth-defense strategies in organisms susceptible to foliar pathogens, and reinforces the contribution of hybridization studies towards our understanding of trait evolution.


title: Information Enhanced Model Selection for Gaussian Graphical Model with Application to Metabolomic Data

abstract: In light of the low signal-to-noise nature of many large biological data sets, we propose a novel method to learn the structure of association networks using Gaussian graphical models combined with prior knowledge. Our strategy includes two parts. In the first part, we propose a model selection criterion called structural Bayesian information criterion (SBIC), in which the prior structure is modeled and incorporated into Bayesian information criterion (BIC). It is shown that the popular extended BIC (EBIC) is a special case of SBIC. In the second part, we propose a two-step algorithm to construct the candidate model pool. The algorithm is data-driven and the prior structure is embedded into the candidate model automatically. Theoretical investigation shows that under some mild conditions SBIC is a consistent model selection criterion for high-dimensional Gaussian graphical model. Simulation studies validate the superiority of the proposed algorithm over the existing ones and show the robustness to the model misspecification. Application to relative concentration data from infant feces collected from subjects enrolled in a large molecular epidemiological cohort study validates that metabolic pathway involvement is a statistically significant factor for the conditional dependence between metabolites. Furthermore, new relationships among metabolites are discovered which can not be identified by the conventional methods of pathway analysis. Some of them have been widely recognized in biological literature.

category: bioinformatics


title: Whole genome sequencing and the application of a SNP panel reveal primary evolutionary lineages and genomic diversity in the lion (Panthera leo)

abstract:
BackgroundPrevious phylogeographic studies of the lion (Panthera leo) have improved our insight into the distribution of genetic variation, as well as a revised taxonomy which now recognizes a northern (Panthera leo leo) and a southern (Panthera leo melanochaita) subspecies. However, existing whole range phylogeographic studies on lions either consist of very limited numbers of samples, or are focused on mitochondrial DNA and/or a limited set of microsatellites. The geographic extent of genetic lineages and their phylogenetic relationships remain uncertain, clouded by massive sampling gaps, sex-biased dispersal and incomplete lineage sorting.

ResultsIn this study we present results of low depth whole genome sequencing and subsequent variant calling in ten lions sampled throughout the geographic range, resulting in the discovery of >150,000 Single Nucleotide Polymorphisms (SNPs). Phylogenetic analyses revealed the same basal split between northern and southern populations as well as four population clusters on a more local scale. Further, we designed a SNP panel, including 125 autosomal and 14 mitochondrial SNPs, which was tested on >200 lions from across their range. Results allow us to assign individuals to one of these four major clades (West & Central Africa, India, East Africa, or Southern Africa) and delineate these clades in more detail.

ConclusionsThe results presented here, particularly the validated SNP panel, have important applications, not only for studying populations on a local geographic scale, but also for tracing samples of unknown origin for forensic purposes, and for guiding conservation management of ex situ populations. Thus, these genomic resources not only contribute to our understanding of the evolutionary history of the lion, but may also play a crucial role in conservation efforts aimed at protecting the species in its full diversity.

category: evolutionary biology


title: Learning Your Heart Actions From Pulse: ECG Waveform Reconstruction From PPG

abstract: This paper studies the relation between electrocardiogram (ECG) and photoplethysmogram (PPG) and infers the waveform of ECG via the PPG signals that can be obtained from affordable wearable Internet-of-Things (IoT) devices for mobile health. In order to address this inverse problem, a transform is proposed to map the discrete cosine transform (DCT) coefficients of each PPG cycle to those of the corresponding ECG cycle based on our proposed cardiovascular signal model. The proposed method is evaluated with different morphologies of the PPG and ECG signals on three benchmark datasets with a variety of combinations of age, weight, and health conditions using different training setups. Experimental results show that the proposed method can achieve a high prediction accuracy greater than 0.92 in averaged correlation for each dataset when the model is trained subject-wise. With a signal processing and learning system that is designed synergistically, we are able to reconstruct ECG signals by exploiting the relation of these two types of cardiovascular measurement. The reconstruction capability of the proposed method can enable low-cost ECG screening from affordable wearable IoT devices for continuous and long-term monitoring. This work may open up a new research direction to transfer the understanding of the clinical ECG knowledge base to build a knowledge base for PPG and data from wearable devices.


title: Interictal Signatures of Human Periventricular Nodular Heterotopia

abstract:
Periventricular nodular heterotopia (PNH) is a malformation of cortical development that frequently causes drug-resistant epilepsy. The epileptogenicity of ectopic neurons in PNH as well as their role in generating interictal and ictal activity is still a matter of debate. We report the first in vivo microelectrode recording of heterotopic neurons in humans. Highly consistent interictal patterns (IPs) were identified within the nodules: 1) Periodic Discharges PLUS Fast activity (PD+F), Sporadic discharges PLUS Fast activity (SD+F), and 3) epileptic spikes (ES). Neuronal firing rates were significantly modulated during all IPs, suggesting that multiple IPs were generated by the same local neuronal populations. Furthermore, firing rates closely followed IP morphologies. Among the different IPs, SD+FA pattern was found only in the three nodules that were actively involved in seizure generation, but was never observed in the nodule that did not take part in ictal discharges. On the contrary, PD+F and ES were identified in all nodules. Units that were modulated during the IPs were also found to participate in seizures, increasing their firing rate at seizure onset and maintaining an elevated rate during the seizures. Together, nodules in PNH are highly epileptogenic, and show several IPs that provide promising pathognomonic signatures of PNH. Furthermore, our results show that PNH nodules may well initiate seizures.

HighlightsO_LIFirst in vivo microelectrode description of local epileptic activities in human PNH
C_LIO_LIRecordings revealed multiple microscopic epileptic interictal patterns
C_LIO_LIFiring rates of all detected units were significantly modulated during all interictal patterns
C_LIO_LISeizures recruited the same units that are involved in interictal activity
C_LI

category: pathology


title: A CTP-dependent gating mechanism enables ParB spreading on DNA in Caulobacter crescentus

abstract: Proper chromosome segregation is essential in all living organisms. The ParA-ParB-parS system is widely employed for chromosome segregation in bacteria. Previously, we showed that Caulobacter crescentus ParB requires cytidine triphosphate to escape the nucleation site parS and spread by sliding to the neighboring DNA 1. Here, we provide the structural basis for this transition from nucleation to spreading by solving co-crystal structures of a C-terminal domain truncated C. crescentus ParB with parS and with a CTP analog. Nucleating ParB is an open clamp, in which parS is captured at the DNA-binding domain (the DNA-gate). Upon binding CTP, the N-terminal domain (NTD) self-dimerizes to close the NTD-gate of the clamp. The DNA-gate also closes, thus driving parS into a compartment between the DNA-gate and the C-terminal domain. CTP hydrolysis and/or the release of hydrolytic products are likely associated with re-opening of the gates to release DNA and to recycle ParB. Overall, we suggest a CTP-operated gating mechanism that regulates ParB nucleation, spreading, and recycling.

category: microbiology


title: A CTP-dependent gating mechanism enables ParB spreading on DNA


title: A Francisella tularensis L,D-carboxypeptidase plays important roles in cell morphology, envelope integrity, and virulence.

abstract: Francisella tularensis is a Gram-negative, intracellular bacterium that causes the zoonotic disease tularemia. Intracellular pathogens, including F. tularensis, have evolved mechanisms to survive in the harsh environment of macrophages and neutrophils, where they are exposed to cell envelope-damaging molecules. The bacterial cell wall, primarily composed of peptidoglycan (PG), maintains cell morphology, structure, and membrane integrity. Intracellular Gram-negative bacteria protect themselves from macrophage and neutrophil killing by recycling and repairing damaged PG - a process that involves over 50 different PG synthesis and recycling enzymes. Here, we identified a PG recycling enzyme, L,D-carboxypeptidase A (LdcA), of F. tularensis that is responsible for converting PG tetrapeptide stems to tripeptide stems. Unlike E. coli LdcA and most other orthologs, F. tularensis LdcA does not localize to the cytoplasm and also exhibits L,D-endopeptidase activity, converting PG pentapeptide stems to tripeptide stems. Loss of F. tularensis LdcA led to altered cell morphology and membrane integrity, as well as attenuation in a mouse pulmonary infection model and in primary and immortalized macrophages. Finally, an F. tularensis ldcA mutant protected mice against virulent Type A F. tularensis SchuS4 pulmonary challenge.


title: Learning to learn persistently modifies an entorhinal-hippocampal excitatory-inhibitory subcircuit

abstract: Cognitive control, the judicious use of relevant information while ignoring distractions, is a feature of everyday cognitive experience, but its neurobiology is understudied. We investigated whether cognitive control training (CCT) changes hippocampal neural circuit function in mice, beyond the changes caused by place learning and memory formation. Mice learned and remembered a conditioned place avoidance during CCT that required ignoring irrelevant locations of shock. They were compared to controls that learned the same place avoidance under lower cognitive control demands. Weeks after CCT, mice learn new tasks in novel environments faster than controls; they learned to learn. We investigated entorhinal cortex-to-dentate gyrus neural circuit changes and report that CCT rapidly changes synaptic circuit function, resulting in an excitatory-inhibitory subcircuit change that persists for months. CCT increases inhibition that attenuates the dentate response to medial entorhinal cortical input, and through disinhibition, potentiates the response to strong inputs, pointing to overall signal-to-noise enhancement. These neurobiological findings support a neuroplasticity hypothesis that, beyond storing item/event associations, CCT persistently optimizes neural circuit information processing.

category: neuroscience


title: Male genital lobe morphology affects the chance to copulate in Drosophila pachea

abstract:
IntroductionMale genitalia are thought to ensure transfer of sperm through direct physical contact with female during copulation. However, little attention has been given to their pre-copulatory role with respect to sexual selection and sexual conflict. Males of the fruitfly Drosophila pachea have a pair of asymmetric external genital lobes, which are primary sexual structures and stabilize the copulatory complex of female and male genitalia. We wondered if genital lobes in D. pachea may have a role before or at the onset of copulation, before genitalia contacts are made.

ResultsWe tested this hypothesis with a D. pachea stock where males have variable lobe lengths. In 92 mate competition trials with a single female and two males, females preferentially engaged into a first copulation with males that had a longer left lobe and that displayed increased courtship vigor. In 53 additional trials with both males having partially amputated left lobes of different lengths, we observed a weaker and non-significant effect of left lobe length on copulation success. Courtship durations significantly increased with female age and when two males courted the female simultaneously, compared to trials with only one courting male. In addition, lobe length did not affect sperm transfer once copulation was established.

ConclusionLeft lobe length affects the chance of a male to engage into copulation. The morphology of this primary sexual trait may affect reproductive success by mediating courtship signals or by facilitating the establishment of genital contacts at the onset of copulation.


title: A memory-based theory of emotional disorders

abstract: Learning and memory play a central role in emotional disorders, particularly in depression and posttraumatic stress disorder. We present a new, transdiagnostic theory of how memory and mood interact in emotional disorders. Drawing upon retrieved-context models of episodic memory, we propose that memories form associations with the contexts in which they are encoded, including emotional valence and arousal. Later, encountering contextual cues retrieves their associated memories, which in turn reactivate the context that was present during encoding. We first show how our retrieved-context model accounts for findings regarding the organization of emotional memories in list-learning experiments. We then show how this model predicts clinical phenomena, including persistent negative mood after chronic stressors, intrusive memories of painful events, and the efficacy of cognitive-behavioral therapies.


title: A conserved enzyme found in diverse human gut bacteria interferes with anticancer drug efficacy

abstract: Pharmaceuticals are the top predictor of inter-individual variations in gut microbial community structure1, consistent with in vitro evidence that host-targeted drugs inhibit gut bacterial growth2 and are extensively metabolized by the gut microbiome3,4. In oncology, bacterial metabolism has been implicated in both drug efficacy5,6 and toxicity7,8; however, the degree to which bacterial drug sensitivity and metabolism can be driven by conserved pathways also found in mammalian cells remains poorly understood. Here, we show that anticancer fluoropyrimidine drugs inhibit the growth of diverse gut bacterial strains by disrupting pyrimidine metabolism, as in mammalian cells. Select bacteria metabolized 5-fluorouracil (5-FU) to its inactive metabolite dihydrofluorouracil (DHFU), mimicking the major host pathway for drug clearance. The preTA operon was necessary and sufficient for 5-FU inactivation in Escherichia coli, exhibited high catalytic efficiency for the reductive reaction, decreased the bioavailability and efficacy of oral fluoropyrimidine treatment in mice, and was prevalent in the gut microbiomes of colorectal cancer patients prior to and during treatment. The observed conservation of both the targets and pathways for metabolism of therapeutics across domains highlights the need to distinguish the relative contributions of human and microbial cells to drug disposition9, efficacy, and side effect profiles.


title: Targeted gene correction and functional recovery in achondroplasia patient-derived iPSCs

abstract:
BackgroundAchondroplasia (ACH) is the most common genetic form of dwarfism and belongs to dominant monogenic disorder caused by a gain-of-function point mutation in the transmembrane region of FGFR3. There are no effective treatments for ACH. Stem cells and gene-editing technology provide us with effective methods and ideas for ACH research and treatment.

MethodsWe generated non-integrated iPSCs from an ACH girls skin and an ACH boys urine by Sendai virus. The mutation of ACH iPSCs was precisely corrected by CRISPR-Cas9.

ResultsChondrogenic differentiation ability of ACH iPSCs was confined compared with that of healthy iPSCs. Chondrogenic differentiation ability of corrected ACH iPSCs could be restored. These corrected iPSCs displayed pluripotency, maintained normal karyotype, and demonstrated none of off-target indels.

ConclusionsThis study may provide an important theoretical and experimental basis for the ACH research and treatment.

category: developmental biology


title: PLETHORA-WOX5 interaction and subnuclear localisation control Arabidopsis root stem cell maintenance

abstract: Maintenance and homeostasis of the stem cell niche (SCN) in the Arabidopsis root is essential for growth and development of all root cell types. The SCN is organized around a quiescent center (QC) maintaining the stemness of cells in direct contact. The key transcription factors (TFs) WUSCHEL-RELATED HOMEOBOX 5 (WOX5) and PLETHORAs (PLTs) are expressed in the SCN where they maintain the QC and regulate distal columella stem cell (CSC) fate. Here, we describe the concerted mutual regulation of the key TFs WOX5 and PLTs on a transcriptional and protein interaction level. Additionally, by applying a novel SCN staining method, we demonstrate that both WOX5 and PLTs regulate root SCN homeostasis as they control QC quiescence and CSC fate interdependently. Moreover, we uncover that some PLTs, especially PLT3, contain intrinsically disordered prion-like domains (PrDs) that are necessary for complex formation with WOX5 and its recruitment to subnuclear microdomains/nuclear bodies (NBs) in the CSCs. We propose that this partitioning of PLT-WOX5 complexes to NBs, possibly by phase separation, is important for CSC fate determination.

category: plant biology


title: High-Throughput Translational Profiling with riboPLATE-seq

abstract: Protein synthesis is dysregulated in many diseases, but we lack a systems-level picture of how signaling molecules and RNA binding proteins interact with the translational machinery, largely due to technological limitations. Here we present riboPLATE-seq, a scalable method for generating paired libraries of ribosome-associated and total mRNA. As an extension of the PLATE-seq protocol, riboPLATE-seq utilizes barcoded primers for pooled library preparation, but additionally leverages rRNA immunoprecipitation on whole polysomes to measure ribosome association (RA). We compare RA to its analogue in ribosome profiling and RNA sequencing, translation efficiency, and demonstrate both the performance of riboPLATE-seq and its utility in detecting translational alterations induced by specific inhibitors of protein kinases.

category: systems biology


title: Incorporating Gene Expression in Genome-wide Prediction of Chromatin Accessibility via Deep Learning

abstract: Although computational approaches have been complementing high-throughput biological experiments for the identification of functional regions in the human genome, it remains a great challenge to systematically decipher interactions between transcription factors and regulatory elements to achieve interpretable annotations of chromatin accessibility across diverse cellular contexts. Towards this problem, we propose DeepCAGE, a deep learning framework that integrates sequence information and binding status of transcription factors, for the accurate prediction of chromatin accessible regions at a genome-wide scale in a variety of cell types. DeepCAGE takes advantage of a densely connected deep convolutional neural network architecture to automatically learn sequence signatures of known chromatin accessible regions, and then incorporates such features with expression levels and binding activities of human core transcription factors to predict novel chromatin accessible regions. In a series of systematic comparisons with existing methods, DeepCAGE exhibits superior performance in not only the classification but also the regression of chromatin accessibility signals. In detailed analysis of transcription factor activities, DeepCAGE successfully extracts novel binding motifs and measures the contribution of a transcription factor to the regulation with respect to a specific locus in a certain cell type. When applied to whole-genome sequencing data analysis, our method successfully prioritizes putative deleterious variants underlying a human complex trait, and thus provides insights into the understanding of disease-associated genetic variants. DeepCAGE can be downloaded from https://github.com/kimmo1019/DeepCAGE.


title: Identification of neural oscillations and epileptiform changes in human brain organoids

abstract: Brain organoids represent a powerful tool for the study of human neurological diseases, particularly those impacting brain growth and structure. However, many diseases manifest with clear evidence of physiological and network abnormality in the absence of anatomical changes. This raises the question of whether organoids possess sufficient neural network complexity to model these conditions. Here, we explore the network level functions of brain organoids using calcium sensor imaging and extracellular recording approaches that together reveal the existence of complex network behaviors reminiscent of intact brain preparations. We demonstrate highly abnormal and epileptiform-like activity in organoids derived from MECP2 mutant patients compared to isogenic controls accompanied by modest transcriptomic differences revealed by single cell analyses. We also rescue key physiological activities with an unconventional neuromodulatory drug, Pifithrin-. Together, these findings provide an essential foundation for the utilization of brain organoids to study intact and disordered human brain network formation and illustrate their utility in therapeutic discovery.


title: Coordination through inhibition: control of stabilizing and updating circuits in spatial orientation working memory

abstract:
Spatial orientation memory plays a crucial role in animal navigation. Recent studies of tethered Drosophila melanogaster (fruit fly) in a virtual reality setting showed that the head direction is encoded in the form of an activity bump, i.e. localized neural activity, in the torus-shaped ellipsoid body (EB). However, how this system is involved in orientation working memory is not well understood. We investigated this question using free moving flies (Drosophila melanogaster) in a spatial orientation memory task by manipulating two EB subsystems, C and P circuits, which are hypothesized for stabilizing and updating the activity bump, respectively. To this end, we suppressed or activated two types of inhibitory ring neurons (EIP and P) which innervate EB, and we discovered that manipulating the two inhibitory neuron types produced distinct behavioral deficits, suggesting specific roles of the inhibitory neurons in coordinating the stabilization and updating functions of the EB circuits. We further elucidate the neural mechanisms underlying such control circuits using a connectome-constrained spiking neural network model.

Significance statementHead-direction (HD) system has been discovered in rodents for decades. But the detailed neural circuit mechanisms underlying the HD system were only described recently by studies of fruit flies on the similar HD system. However, how this fruit fly HD system involves in orientation memory was not well investigated. The present study addresses this question by investigating free moving flies in a spatial orientation working memory task. By combining neural functional experiments and neural circuit modelling, the study shows how disrupting either of the two subcircuits, one stabilizing and the other updating the neural activity, in the HD system leads to different behavioral impairments. The result suggests specific roles of the HD subcircuits in the spatial orientation working memory.

Visual Abstract

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title: The NTD of Eukaryotic Initiation Factor 4B Drives Yeast Translational Control in Response to Urea

abstract: The yeast eukaryotic initiation factor 4B binds the 40S subunit in translation preinitiation complexes (PICs), promoting mRNA binding. Recent evidence suggests mRNAs have variable dependence on eIF4B, suggesting this factor could promote changes in mRNA selection for translation, in order to adapt to stressors. However, the importance of eIF4B and its constituent domains for mRNA selection under diverse cellular and environmental conditions remain undefined. Here we compared the effects of disrupting eIF4B RNA- and ribosome-binding motifs under ~1400 growth conditions. The RNA-Recognition Motif (RRM) was dispensable for stress responses, but the 40S-binding N-terminal Domain (NTD) promoted growth in response to various stressors. In particular, the NTD conferred a strong growth advantage in the presence of urea. Ribosome profiling revealed that the NTD promoted translation of mRNAs with long and highly structured 5-prime untranslated regions, both with and without urea exposure. Our results suggest eIF4B controls mRNA loading and scanning as a part of the PIC, rather than by activating mRNPs prior to ribosome binding. Furthermore, our data indicate the yeast response to urea includes a translational component, driven by production of proteins associated with the cellular periphery. Together our analyses suggest general eIFs can promote diverse cellular responses.

category: molecular biology


title: Ten-eleven translocation 1 Mediated-DNA Hydroxymethylation is Required for Myelination and Remyelination in the Mouse Brain

abstract: Ten-eleven translocation (TET) proteins, the dioxygenase for DNA hydroxymethylation, are important players in nervous system development and diseases. However, their role in myelination and remyelination after injury remains elusive. Here, we identify a genome-wide and locus-specific DNA hydroxymethylation landscape shift during differentiation of oligodendrocyte-progenitor cells (OPC). Ablation of Tet1 results in stage-dependent defects in oligodendrocyte (OL) development and myelination in the mouse brain. The mice lacking Tet1 in the oligodendrocyte lineage develop behavioral deficiency. We also show that TET1 is required for remyelination in adulthood. Transcriptomic, genomic occupancy, and DNA hydroxymethylation profiling reveal a critical TET1-regulated epigenetic program for oligodendrocyte differentiation that includes genes associated with myelination, cell division, and calcium transport. Tet1-deficient OPCs exhibit reduced calcium activity, increasing calcium activity rescues the differentiation defects in vitro. Deletion of a TET1-5hmC target gene, Itpr2 impairs the onset of OPC differentiation. Together, our results suggest that stage-specific TET1-mediated epigenetic programming and intracellular signaling are important for proper myelination and remyelination in mice.


title: Roles of adenine methylation and genetic mutations in adaptation to different temperatures in Serratia marcescens

abstract: Epigenetic modifications can contribute to adaptation, but the relative contributions of genetic and epigenetic variation are unknown. Previous studies on the role of epigenetic changes in adaptation in eukaryotes have nearly exclusively focused on cytosine methylation (m5C), while prokaryotes exhibit a richer system of methyltransferases targetting adenines (m6A) or cytosines (m4C, m5C). DNA methylation in prokaryotes has many roles, but its potential role in adaptation still needs further investigation. We collected phenotypic, genetic, and epigenetic data using single molecule real-time sequencing of clones of the bacterium Serratia marcescens that had undergone experimental evolution in contrasting temperatures to investigate the relationship between environment and genetic, epigenetic, and phenotypic changes. This data provided a detailed description of the methylation landscape of S. marcescens and allowed us to examine the potential contributions of genetic and epigenetic changes to phenotypic adaptation. The genomic distribution of GATC motifs, which are the main target for m6A methylation, and of partially methylated epiloci pointed to a link between m6A methylation and regulation of gene expression in S. marcescens. Evolved strains, while genetically homogeneous, exhibited many polymorphic m6A epiloci. There was no strong support for a genetic control of methylation changes in our experiment, and no clear evidence of parallel environmentally-induced or environmentally-selected methylation changes at specific epiloci was found. Both some genetic and epigenetic variants were associated with some phenotypic traits. Overall, our results suggest that both genetic and adenine methylation changes have potential to contribute to phenotypic adaptation in S. marcescens, but that any environmentally-induced epigenetic change occurring in our experiment would probably have been quite labile.


title: Broadband Signal Rather than Frequency-Specific Rhythms Underlie Prediction Error in the Primate Auditory Cortex

abstract:
Detection of statistical irregularities, measured as a prediction error response, is fundamental to the perceptual monitoring of the environment. We studied whether prediction error response is associated with neural oscillations or asynchronous broadband activity. Electrocorticography (ECoG) was carried out in three male monkeys, who passively listened to the auditory roving oddball stimuli. Local field potentials (LFP) recorded over the auditory cortex underwent spectral principal component analysis, which decoupled broadband and rhythmic components of the LFP signal. We found that the broadband component captured the prediction error response, whereas none of the rhythmic components were associated with statistical irregularities of sounds. The broadband component displayed more stochastic, asymmetrical multifractal properties than the rhythmic components, which revealed more self-similar dynamics. We thus conclude that the prediction error response is captured by neuronal populations generating asynchronous broadband activity, defined by irregular dynamical states which, unlike oscillatory rhythms, appear to enable the neural representation of auditory prediction error response.

Significance StatementThis study aimed to examine the contribution of oscillatory and asynchronous components of auditory local field potentials in the generation of prediction error responses to sensory irregularities, as this has not been directly addressed in the previous studies. Here, we show that mismatch negativity - an auditory prediction error response - is driven by the asynchronous broadband component of potentials recorded in the auditory cortex. This finding highlights the importance of non-oscillatory neural processes in the predictive monitoring of the environment. At a more general level, the study demonstrates that stochastic neural processes, which are often disregarded as neural noise, do have a functional role in the processing of sensory information.


title: Cerebellar lesions disrupt spatial and temporal visual attention.

abstract: The current study represents the first comprehensive examination of spatial, temporal and sustained attention following cerebellar damage. Results indicated that, compared to controls, cerebellar damage resulted in a larger cueing effect at the longest SOA - possibly reflecting a slowed the onset of inhibition of return (IOR) during a reflexive covert attention task, and reduced the ability to detect successive targets during an attentional blink task. However, there was little evidence to support the notion that cerebellar damage disrupted voluntary covert attention or the sustained attention to response task (SART). Lesion overlay data and supplementary voxel-based lesion symptom mapping (VLSM) analyses indicated that impaired performance on the reflexive covert attention and attentional blink tasks were related to damage to Crus II of the left posterior cerebellum. In addition, subsequent analyses indicated our results are not due to either general motor impairments or to damage to the deep cerebellar nuclei. Collectively these data demonstrate, for the first time, that the same cerebellar regions may be involved in both spatial and temporal visual attention.


title: Host-microbiome protein-protein interactions capture mechanisms in human disease

abstract:
Host-microbe interactions are crucial for normal physiological and immune system development and are implicated in a wide variety of diseases, including inflammatory bowel disease (IBD), colorectal cancer (CRC), obesity, and type 2 diabetes (T2D). Despite large-scale case-control studies aimed at identifying microbial taxa or specific genes involved in pathogeneses, the mechanisms linking them to disease have thus far remained elusive. To identify potential mechanisms through which human-associated bacteria impact host health, we leveraged publicly-available interspecies protein-protein interaction (PPI) data to find clusters of microbiome-derived proteins with high sequence identity to known human protein interactors. We observe differential targeting of putative human-interacting bacterial genes in metagenomic case-control microbiome studies. In nine independent case studies, we find evidence that the microbiome broadly targets human proteins involved in immune, oncogenic, apoptotic, and endocrine signaling pathways in relation to IBD, CRC, obesity and T2D diagnoses. This host-centric analysis strategy provides a mechanistic hypothesis-generating platform for any metagenomics cohort study and extensively adds human functional annotation to commensal bacterial proteins.

One-sentence summaryMicrobiome-derived proteins are linked to disease-associated human pathways by metagenomic and protein-protein interaction analyses.


title: Species richness increases fitness differences, but does not affect niche differences

abstract: A key question in ecology is what limits species richness. Modern coexistence theory presents the persistence of species as a balance between niche differences and fitness differences that favor and hamper coexistence, respectively. With most applications focusing on species pairs, however, we know little about if and how this balance changes with species richness. Here, we present the first mathematical proof that the average fitness difference among species increases with richness, while the average niche difference stays constant. Extensive simulations with more complex models and analyses of empirical data confirmed these mathematical results. Taken together, our work suggests that, as species accumulate in ecosystems, ever-increasing fitness differences will at some point exceed constant niche differences, limiting species richness. Our results contribute to the expansion of modern coexistence theory towards multi-species communities.

category: ecology


title: Non-selective response inhibition in Go/NoGo task: Bayesian analysis of fMRI data

abstract:
Response inhibition is typically considered a brain mechanism selectively triggered by particular "inhibitory" stimuli or events. Based on recent research, an alternative non-selective mechanism was proposed by several authors. Presumably, the inhibitory brain activity may be triggered not only by the presentation of "inhibitory" stimuli but also by any imperative stimuli, including Go stimuli, when the context is uncertain. Earlier support for this notion was mainly based on the absence of a significant difference between neural activity evoked by equiprobable Go and NoGo stimuli. Equiprobable Go/NoGo design with a simple response time task limits potential confounds between response inhibition and accompanying cognitive processes while not preventing prepotent automaticity. However, previous neuroimaging studies utilized classical null hypothesis significance testing, making it impossible to accept the null hypothesis. Therefore, the current research aimed to provide evidence for practical equivalence of neuronal activity in Go and NoGo trials using Bayesian analysis of functional magnetic resonance imaging (fMRI) data. Thirty-four healthy participants performed a cued Go/NoGo task with an equiprobable presentation of Go and NoGo stimuli. To independently localize brain areas associated with response inhibition in similar experimental conditions, we performed a meta-analysis of fMRI studies using equal probability Go/NoGo tasks. As a result, we observed overlap between response inhibition areas and areas demonstrating the practical equivalence of neuronal activity located in the right dorsolateral prefrontal cortex, parietal cortex, premotor cortex, and left inferior frontal gyrus. Thus, obtained results favour the existence of non-selective response inhibition, which can act in settings of contextual uncertainty induced by the equal probability of Go and NoGo stimuli.

Highlights O_LINon-selective response inhibition was assessed by equiprobable Go/NoGo task
C_LIO_LIBayesian analysis of fMRI data was combined with a meta-analysis of fMRI studies
C_LIO_LISeveral nodes of response inhibition system were equally involved in Go and NoGo trials
C_LIO_LIEvidence for non-selective response inhibition in uncertain context was found
C_LI


title: Non-selective response inhibition in equiprobable Go/NoGo task: Bayesian analysis of fMRI data


title: Activation of G-protein coupled estradiol receptor 1 in the dorsolateral striatum attenuates preference for cocaine and saccharin in male but not female rats

abstract: There are sex differences in the response to psychomotor stimulants, where females exhibit a greater response than males, due to the presence of the gonadal hormone estradiol (E2). Extensive research has shown that E2 enhances drug-seeking and the rewarding properties of cocaine for females. The role of E2 in male drug-seeking, however, is not well understood. The current study investigated pharmacological manipulation of E2 receptors in the dorsolateral striatum (DLS) on preference for cocaine in gonad-intact male and female rats. In males, activation of G-protein coupled E2 receptor 1 (GPER1), via administration of ICI 182,780 or G1, attenuated conditioned place preference for 10mg/kg cocaine, while inhibition of GPER1, via G15, enhanced preference at a 5mg/kg cocaine dose. Similarly, GPER1 activation, via G1, prevented males from forming a preference for 0.1% saccharin (SACC) versus plain water. Surprisingly, activation of GPER1 did not alter preference for cocaine or SACC in females. These studies also examined the quantity of E2 receptor mRNA in the dorsal striatum, using qPCR. No sex differences in relative mRNA expression of ER, ER{beta}, and GPER1 were observed. However, there was greater GPER1 mRNA, relative to ER and ER{beta}, in both males and females. The results presented here indicate that E2, acting via GPER1, may be protective against drug preference in male rats.


title: NHR-8 regulated P-glycoproteins uncouple xenobiotic stress resistance from longevity in chemosensory C. elegans mutants

abstract: Longevity is often associated with stress resistance, but whether they are causally linked is incompletely understood. Here we investigate chemosensory defective Caenorhabditis elegans mutants that are long-lived and stress resistant. We find that mutants in the intraflagellar transport protein gene osm-3 were significantly protected from tunicamycin-induced ER stress. While osm-3 lifespan extension is dependent on the key longevity factor DAF-16/FOXO, tunicamycin resistance was not. osm-3 mutants are protected from bacterial pathogens, which is pmk-1 p38 MAP kinase dependent while TM resistance was pmk-1 independent. Expression of P-glycoprotein (PGP) xenobiotic detoxification genes was elevated in osm-3 mutants and their knockdown or inhibition with verapamil suppressed tunicamycin resistance. The nuclear hormone receptor nhr-8 was necessary to regulate PGPs and tunicamycin resistance in a cholesterol-dependent fashion. We thus identify a cell-nonautonomous regulation of xenobiotic detoxification and show that separate pathways are engaged to mediate longevity, pathogen resistance, and xenobiotic detoxification in osm-3 mutants.

category: genetics


title: Distinct roles for dopamine clearance mechanisms in regulating behavioral flexibility

abstract: Dopamine plays a crucial role in adaptive behavior, and dysfunctional dopamine is implicated in multiple psychiatric conditions characterized by inflexible or inconsistent choices. However, the precise relationship between dopamine and flexible decision making remains unclear. One reason is that, while many studies have focused on the activity of dopamine neurons, efficient dopamine signaling also relies on clearance mechanisms, notably the dopamine transporter (DAT), which predominates in striatum, and catechol-O-methyltransferase (COMT), which predominates in cortex. The exact locus, extent, and timescale of the effects of DAT and COMT are uncertain. Moreover, there is limited data on how acute disruption of either mechanism affects flexible decision making strategies mediated by cortico-striatal networks. To address these issues, we combined pharmacological modulation of DAT and COMT with electrochemistry and behavior in mice. DAT blockade, but not COMT inhibition, regulated sub-second dopamine release in the nucleus accumbens core, but surprisingly neither clearance mechanism affected evoked release in prelimbic cortex. This was not due to a lack of sensitivity, as both amphetamine and atomoxetine changed the kinetics of sub-second release. In a multi-step decision making task where mice had to respond to reversals in either reward probabilities or the choice sequence to reach the goal, DAT blockade selectively impaired, and COMT inhibition improved, performance after reward reversals, but neither manipulation affected the adaptation of choices after actionstate transition reversals. Together, our data suggest that DAT and COMT shape specific aspects of behavioral flexibility by regulating striatal and cortical dopamine, respectively, at fast and slow timescales.


title: Using the Tea Bag Index to determine how two human pharmaceuticals affect litter decomposition by aquatic microorganisms.

abstract: This study demonstrates that independent additive effects of two human pharmaceuticals, the antibiotic trimethoprim and the artificial estrogen 17a-Ethinylestradiol (EE2), inhibit plant litter decomposition by aquatic microorganisms. The constant release of pharmaceuticals, such as these, has the potential to affect aquatic microbial metabolism and alter biogeochemical cycling of carbon and nutrients. Here we advance the Tea Bag Index (TBI) for decomposition by using it in a series of contaminant exposure experiments testing how interactions between trimethoprim and EE2 affect aquatic microbial activity. The TBI is a citizen science tool used to test microbial activity by measuring the differential degradation of green and rooibos tea as proxies for respectively labile and recalcitrant litter decomposition. Exposure to either trimethoprim or EE2 decreased decomposition of green tea, suggesting additive effects upon microbial activity. Exposure to EE2 alone decreased rooibos tea decomposition. Consequently, trimethoprim and EE2 stabilized labile organic matter against microbial degradation and restricted decomposition. We propose that the method outlined could provide a powerful tool for testing the impacts of multiple interacting pollutants upon microbial activity, at a range of scales, across aquatic systems and over ecologically relevant time scales.


title: CloneSig: Joint inference of intra-tumor heterogeneity and mutational signatures' activity in tumor bulk sequencing data

abstract: Systematic DNA sequencing of cancer samples has highlighted the importance of two aspects of cancer genomics: intra-tumor heterogeneity (ITH) and mutational processes. These two aspects may not always be independent, as different mutational processes could be involved in different stages or regions of the tumor, but existing computational approaches to study them largely ignore this potential dependency. Here, we present CloneSig, a computational method to jointly infer ITH and mutational processes in a tumor from bulk-sequencing data. Extensive simulations show that CloneSig outperforms current methods for ITH inference and detection of mutational processes when the distribution of mutational signatures changes between clones. Applied to a large cohort of 8,951 tumors with whole-exome sequencing data from The Cancer Genome Atlas, and on a pan-cancer dataset of 2,632 whole-genome sequencing tumor samples from the Pan-Cancer Analysis of Whole Genomes initiative, CloneSig obtains results overall coherent with previous studies.


title: CloneSig can jointly infer intra-tumor heterogeneity and mutational signature activity in bulk tumor sequencing data


title: A rationally designed oral vaccine induces Immunoglobulin A in the murine gut that directs the evolution of attenuated Salmonella variants

abstract: Introductory paragraphThe ability of gut bacterial pathogens to escape immunity by antigenic variation, particularly via changes to surface-exposed antigens, is a major barrier to immune clearance1. However, not all variants are equally fit in all environments2, 3. It should therefore be possible to exploit such immune escape mechanisms to direct an evolutionary trade-off. Here we demonstrated this phenomenon using Salmonella enterica subspecies enterica serovar Typhimurium (S.Tm). A dominant surface antigen of S.Tm is its O-antigen: A long, repetitive glycan that can be rapidly varied by mutations in biosynthetic pathways or by phase-variation4, 5. We quantified the selective advantage of O-antigen variants in the presence and absence of O-antigen specific IgA and identified a set of evolutionary trajectories allowing immune escape without an associated fitness cost in naive mice. Through the use of oral vaccines, we rationally induced IgA responses blocking all of these trajectories, which selected for Salmonella mutants carrying deletions of the O-antigen polymerase wzyB. Due to their short O-antigen, these evolved mutants were more susceptible to environmental stressors (detergents, complement), predation (bacteriophages), and were impaired in gut colonization and virulence in mice. Therefore, a rationally induced cocktail of intestinal antibodies can direct an evolutionary trade-off in S.Tm. This lays the foundations for the exploration of mucosal vaccines capable of setting evolutionary traps as a prophylactic strategy.

category: immunology


title: Regulation of apical constriction via microtubule- and Rab11-dependent apical transport during tissue invagination

abstract: The formation of an epithelial tube is a fundamental process for organogenesis. During Drosophila embryonic salivary gland (SG) invagination, Folded gastrulation (Fog)- dependent Rho-associated kinase (Rok) promotes contractile apical myosin formation to drive apical constriction. Microtubules (MTs) are also crucial for this process and are required for forming and maintaining apicomedial myosin. However, the underlying mechanism that coordinates actomyosin and MT networks still remains elusive. Here, we show that MT-dependent intracellular trafficking regulates apical constriction during SG invagination. Key components involved in protein trafficking, such as Rab11 and Nuclear fallout (Nuf), are apically enriched near the SG invagination pit in a MT-dependent manner. Disruption of the MT networks or knockdown of Rab11 impairs apicomedial myosin formation and apical constriction. We show that MTs and Rab11 are required for apical enrichment of the Fog ligand and the continuous distribution of the apical determinant protein Crumbs (Crb) and the key adherens junction protein E-Cadherin (E-Cad) along junctions. Targeted knockdown of crb or E-Cad in the SG disrupts apical myosin networks and results in apical constriction defects. Our data suggest a role of MT- and Rab11-dependent intracellular trafficking in regulating actomyosin networks and cell junctions, to coordinate cell behaviors during tubular organ formation.


title: Ebselen attenuates mycobacterial virulence through inhibition of ESX-1 secretion

abstract: The type VII secretion system ESX-1 mediates virulence in Mycobacterium tuberculosis and Mycobacterium marinum. We find that in M. marinum, the synthetic organoselenium compound ebselen inhibits secretion of ESAT-6, a major ESX-1 substrate. We find that ebselen inhibits the in vitro activity of the ESX-1 AAA+ ATPase EccA1, which potentiates ESX-1 substrate secretion and function. Ebselen modifies a cysteine in its N-terminal tetratricopeptide repeat domain that is required for EccA1s in vitro ATPase activity. Surprisingly, mutational analyses show this this cysteine is not required for ESX-1 secretion or ebselens activity, showing that ebselen inhibits ESX-1 secretion independently of inhibiting EccA1 activity in vitro. While the mechanism by which ebselen inhibits ESX-1 secretion remains elusive, we show that it attenuates ESX-1-mediated damage of M. marinum-containing macrophage phagosomes and inhibits intramacrophage growth. Extending our studies to M. tuberculosis, we find that ebselen inhibits ESX-1 secretion and phagosomal membrane damage in this organism. This work provides insight into EccA1 biology. Ebselen is an orally active drug in clinical trials for other conditions and this work suggests its potential in tuberculosis therapy.


title: Low-disturbance Farming Regenerates Healthy Deep Soil towards Sustainable Agriculture

abstract: Intensive conventional farming has degraded farmland topsoil and seriously threaten food and environment security globally. Although low-disturbance practices have been widely adapted to restore soil health, whether this measure in a long run can potentially recover the critical deep soil to meet sustainable intensification of crop production are still unclear. Here we compared soil microbiome, physicochemical parameters along 3-m deep soil profiles, and crop yield in Northeast China subjected to ten years of farming practices at 3 levels of disturbance, including conventional tillage (CT), no-tillage without stover mulching (NTNS), and no-tillage with stover mulching (NTSM). We found that low-disturbance practices (NTNS and NTSM) promoted the ability of the deep soil to retain water, nitrogen and salt-extractable organic, regenerated whole-soil microbial diversity and metabolic function, improved topsoil organic carbon stock and corn yield in the drought year, showed the potential to reduce energy consumption and greenhouse gas emissions, thus regenerating highly efficient, sustainable agriculture.


title: Population structure of chum salmon and selection on the markers collected for stock identification

abstract: Genetic stock identification (GSI) is a major management tool of Pacific salmon (Oncorhynchus Spp.) that has provided rich genetic baseline data of allozymes, microsatellites, and single nucleotide polymorphisms (SNPs) across the Pacific Rim. Here, we analyzed published data sets for adult chum salmon (Oncorhynchus keta), namely 10 microsatellites, 53 SNPs, and a mitochondrial DNA locus (mtDNA3, control region and NADH-3 combined) from 495 locations in the same distribution range (n = 61,813). TreeMix analysis of the microsatellite loci identified the highest level of genetic drift towards Japanese/Korean populations and suggested two admixture events from Japan/Korea to Russia and the Alaskan Peninsula. The SNPs had been purposively collected from rapidly evolving genes to increase the power of GSI. The highest expected heterozygosity was observed in Japanese/Korean populations for microsatellites, whereas it was highest in Western Alaskan populations for SNPs, reflecting the SNP discovery process. By regressing the SNP population structures on those of the microsatellites, we estimated the selection on the SNP loci according to deviations from the predicted structures. Specifically, we matched the sampling locations of the SNPs with those of the microsatellites according to geographical information and performed regression analyses of SNP allele frequencies on the two coordinates of multi-dimensional scaling (MDS) of matched locations obtained from microsatellite pairwise FST values. The MDS first axis indicated a latitudinal cline in American and Russian populations, whereas the second axis found a differentiation of Japanese/Korean populations. The top five outlier SNPs were mtDNA3 (combined locus of the control region and NADH-3), U502241 (unknown), GnRH373, ras1362, and TCP178, which were consistently identified by principal component analysis. We summarized the functions of the 53 nuclear SNPs and mtDNA3 locus by referring to a gene database system and discussed the functions of the outlier SNPs and fitness of chum salmon.


title: Stability of neocortical synapses across sleep and wake

abstract: Sleep is important for brain plasticity, but its exact function remains mysterious. An influential but controversial idea is that a crucial function of sleep is to drive widespread downscaling of excitatory synaptic strengths. Here we used real-time sleep classification, ex vivo measurements of postsynaptic strength, and in vivo optogenetic monitoring of thalamocortical synaptic efficacy to ask whether sleep and wake states can constitutively drive changes in synaptic strength within the neocortex of juvenile rats. We found that miniature EPSC amplitudes onto L4 and L2/3 pyramidal neurons were stable across sleep and wake dense epochs in both primary visual (V1) and prefrontal cortex (PFC). Further, chronic monitoring of thalamocortical synaptic efficacy in V1 of freely behaving animals revealed stable responses across even prolonged periods of natural sleep and wake. Together these data demonstrate that neocortical synaptic strengths are remarkably stable across sleep and wake states, and provide strong evidence against the view that sleep drives widespread synaptic downscaling at neocortical synapses.


title: Prefrontal deep projection neurons enable cognitive flexibility via persistent feedback monitoring

abstract: Cognitive flexibility, the ability to alter ones strategy according to changing stimulus-response-reward relationships, is critical for acquiring and updating learned behavior. Attentional set-shifting, a test of cognitive flexibility, depends on the activity of prefrontal cortex (PFC). It remains unclear, however, what specific role PFC neurons play and how they interact to support set-shifting. One widely held view is that prefrontal activity biases sensorimotor responses by mediating attention. Using optogenetics and 2-photon calcium imaging, we demonstrate that, while PFC activity does encode attentional sets, this activity does not bias sensorimotor responses. Rather, PFC activity enables set-shifting by encoding trial feedback information, a role it has been known to play in other contexts. We identify a circuit-level mechanism that supports feedback monitoring through persistent, recurring activity bridging multiple trials. Unexpectedly, the functional properties of PFC cells did not vary with their efferent projection targets in this context. Instead, representations of trial feedback formed a topological gradient, with cells more strongly selective for feedback information located further from the pial surface and receiving denser afferent inputs from the anterior cingulate cortex. Together, these findings identify a critical role for deep PFC projection neurons in enabling set-shifting through behavioral feedback monitoring.


title: Dietary fat promotes antibiotic-induced Clostridioides difficile mortality in mice

abstract:
Clostridioides difficile infection (CDI), is the leading cause of hospital-acquired diarrhea and emerging evidence has linked dietary components with CDI pathogenesis, suggesting that dietary modulation may be an effective strategy for prevention. Here, we show that mice fed a high-fat/low-fiber "Western type" diet (WD) had dramatically increased mortality in a murine model of antibiotic-induced CDI compared to a low-fat/low-fiber (LF/LF) diet and standard mouse chow controls. We found that the WD had a pro- C. difficile bile acid composition that was driven in part by higher levels of primary bile acids that are produced to digest fat, and a lower level of secondary bile acids that are produced by the gut microbiome. This lack of secondary bile acids was associated with a greater disturbance to the gut microbiome with antibiotics in both the WD and LF/LF diet compared to mouse chow. Mice fed the WD also had the highest level of toxin TcdA just prior to the onset of mortality, but not of TcdB or increased inflammation. These findings indicate that dietary intervention to decrease fat may complement previously proposed dietary intervention strategies to prevent CDI in high-risk individuals.

One Sentence SummaryA high-fat/low-fiber Western type diet promoted mortality in a mouse model of antibiotic-induced C. difficile infection compared to a low-fat/low-fiber diet and chow diet, suggesting that lower dietary fat may be an effective strategy for preventing C. difficile pathology.


title: Automaticity in the reading circuitry

abstract: Skilled reading requires years of practice associating visual symbols with speech sounds. Over the course of the learning process, this association becomes effortless and automatic. Here we test whether automatic activation of spoken-language circuits in response to visual words is a hallmark of skilled reading. Magnetoencephalography was used to measure word-selective responses under multiple cognitive tasks (N = 42, 7-12 years of age). Even when attention was drawn away from the words by performing an attention-demanding fixation task, strong word-selective responses were found in a language region (i.e., superior temporal gyrus) starting at ~300 ms after stimulus onset. Critically, this automatic word-selective response was indicative of reading skill: the magnitude of word-selective responses correlated with individual reading skill. Our results suggest that automatic recruitment of spoken-language circuits is a hallmark of skilled reading; with practice, reading becomes effortless as the brain learns to automatically translate letters into sounds and meaning.


title: Towards Practical and Robust DNA-based Data Archiving Using "Yin-Yang Codec" System

abstract: DNA is a promising data storage medium due to its remarkable durability and space-efficient storage. Early bit-to-base transcoding schemes have primarily pursued information density, at the expense however of introducing biocompatibility challenges or at the risk of decoding failure. Here, we propose a robust transcoding algorithm named the "Yin-Yang Codec" (YYC), using two rules to encode two binary bits into one nucleotide, to generate DNA sequences highly compatible with synthesis and sequencing technologies. We encoded two representative file formats and stored them in vitro as 200-nt oligo pools and in vivo as an ~54-kb DNA fragment in yeast cells. Sequencing results show that YYC exhibits high robustness and reliability for a wide variety of data types, with an average recovery rate of 99.94% at 104 molecule copies and an achieved recovery rate of 87.53% at 100 copies. In addition, the in vivo storage demonstration achieved for the first time an experimentally measured physical information density of 198.8 EB per gram of DNA (44% of the theoretical maximum for DNA).

category: synthetic biology


title: Mutations in Auxilin cause parkinsonism via impaired clathrin-mediated trafficking at the Golgi apparatus and synapse

abstract: Parkinsons disease (PD) is a common neurodegenerative motor disorder characterized in part by neuropathological lesions in the nigrostriatal pathway. Loss of function mutations in Auxilin, the major neuronal clathrin uncoating protein, cause an aggressive form of juvenile onset PD. How mutations in Auxilin cause PD, is currently not understood. Here, we generated a novel mouse model carrying an endogenous pathogenic Auxilin mutation that phenocopies neurological features observed in patients, including motor impairments and seizures. Unbiased mapping of the Auxilin interactome identified synaptic and Golgi-resident clathrin adaptor proteins as novel interactors. Impaired clathrin-mediated trafficking in mutant Auxilin mice, both at the Golgi and the synapse, results in neuropathological lesions in the nigrostriatal pathway. Collectively, these results provide molecular mechanisms of PD pathogenesis in Auxilin mutation carriers, reinforcing a key role for clathrin-mediated trafficking in PD, and expand our understanding of the cellular function of Auxilin.


title: Genomic Background Governs Opposing Responses to Nalidixic Acid Upon Megaplasmid Acquisition in Pseudomonas

abstract:
Horizontal gene transfer is a significant driver of evolutionary dynamics across microbial populations. Although the benefits of the acquisition of new genetic material are often quite clear, experiments across systems have demonstrated that gene transfer events can cause significant phenotypic changes and entail fitness costs in a way that is dependent on the genomic and environmental context. Here we test for the generality of one previously identified cost, sensitization of cells to the antibiotic nalidixic acid after acquisition of a [~]1Mb megaplasmid, across Pseudomonas strains and species. Overall, we find that the presence of this megaplasmid sensitizes many different Pseudomonas strains to nalidixic acid, but that this same horizontal gene transfer event increases resistance of Pseudomonas putida KT2440 to nalidixic acid across assays as well as to ciprofloxacin under competitive conditions. These phenotypic results are not easily explained away as secondary consequences of overall fitness effects and appear to occur independently of another cost associated with this megaplasmid, sensitization to higher temperatures. Lastly, we draw parallels between these reported results and the phenomenon of sign epistasis for de novo mutations and explore how context dependence of effects of plasmid acquisition could impact overall evolutionary dynamics and the evolution of antimicrobial resistance.

ImportanceNumerous studies have demonstrated that gene transfer events (e.g. plasmid acquisition) can entail a variety of costs that arise as byproducts of the incorporation of foreign DNA into established physiological and genetic systems. These costs can be ameliorated through evolutionary time by the occurrence of compensatory mutations, which stabilize presence of a horizontally transferred region within the genome but which also may skew future adaptive possibilities for these lineages. Here we demonstrate another possible outcome, that phenotypic changes arising as a consequence of the same horizontal gene transfer event are costly to some strains but may actually be beneficial in other genomic backgrounds under the right conditions. These results provide new a new viewpoint for considering conditions that promote plasmid maintenance and highlight the influence of genomic and environmental contexts when considering amelioration of fitness costs after HGT events.


title: Attenuated directed exploration during reinforcement learning in gambling disorder

abstract:
Gambling disorder is a behavioral addiction associated with impairments in value-based decision-making and behavioral flexibility and might be linked to changes in the dopamine system. Maximizing long-term rewards requires a flexible trade-off between the exploitation of known options and the exploration of novel options for information gain. This exploration-exploitation trade-off is thought to depend on dopamine neurotransmission. We hypothesized that human gamblers would show a reduction in directed (uncertainty-based) exploration, accompanied by changes in brain activity in a fronto-parietal exploration-related network.

Twenty-three frequent, non-treatment seeking gamblers and twenty-three healthy matched controls (all male) performed a four-armed bandit task during functional magnetic resonance-imaging. Computational modeling using hierarchical Bayesian parameter estimation revealed signatures of directed exploration, random exploration, and perseveration in both groups. Gamblers showed a reduction in directed exploration, whereas random exploration and perseveration were similar between groups.

Neuroimaging revealed no evidence for group differences in neural representations of basic task variables (expected value, prediction errors). Our hypothesis of reduced frontal pole recruitment in gamblers was not supported. Exploratory analyses revealed that during directed exploration, gamblers showed reduced parietal cortex and substantia-nigra / ventral-tegmental-area activity. Cross-validated classification analyses revealed that connectivity in an exploration-related network was predictive of group status, suggesting that connectivity patterns might be more predictive of problem gambling than univariate effects.

Findings reveal specific reductions in strategic exploration gamblers that might be linked to altered processing in a fronto-parietal network and/or changes in dopamine neurotransmission implicated in gambling disorder.

Significance statementWiehler et al. report that gamblers rely less on the strategic exploration of unknown, but potentially better rewards during reward learning. This is reflected in a related network of brain activity. Parameters of this network can be used to predict the presence of problem gambling behavior in participants.


title: LiGIoNs: A Computational Method for the Detection and Classification of Ligand-Gated Ion Channels

abstract:
Ligand-Gated Ion Channels (LGICs) are one of the largest groups of transmembrane proteins. Due to their major role in synaptic transmission, both in the nervous system and the somatic neuromuscular junction, LGICs present attractive therapeutic targets. During the last few years several computational methods for the detection of LGICs have been developed. These methods are based on machine learning approaches utilizing features extracted solely from amino acid composition. Here we report the development of LiGIoNs, a profile Hidden Markov Model (pHMM) method for the prediction and ligand-based classification of LGICs. The method consists of a library of 10 pHMMs, one per LGIC subfamily, built from the alignment of representative LGIC sequences. In addition, 14 Pfam pHMMs are used to further annotate and classify unknown protein sequences into one of the 10 LGIC subfamilies. Evaluation of the method showed that it outperforms existent methods in the detection of LGICs. On top of that, LiGIoNs is the only currently available method that classifies LGICs into subfamilies.

The method is available online at http://bioinformatics.biol.uoa.gr/ligions/.


title: Blinking Statistics and Molecular Counting in direct Stochastic Reconstruction Microscopy (dSTORM)

abstract:
MotivationMany recent advancements in single molecule localisation microscopy exploit the stochastic photo-switching of fluorophores to reveal complex cellular structures beyond the classical diffraction limit. However, this same stochasticity makes counting the number of molecules to high precision extremely challenging, preventing key insight into the cellular structures and processes under observation.

ResultsModelling the photo-switching behaviour of a fluorophore as an unobserved continuous time Markov process transitioning between a single fluorescent and multiple dark states, and fully mitigating for missed blinks and false positives, we present a method for computing the exact probability distribution for the number of observed localisations from a single photo-switching fluorophore. This is then extended to provide the probability distribution for the number of localisations in a dSTORM experiment involving an arbitrary number of molecules. We demonstrate that when training data is available to estimate photo-switching rates, the unknown number of molecules can be accurately recovered from the posterior mode of the number of molecules given the number of localisations. Finally, we demonstrate the method on experimental data by quantifying the number of adapter protein Linker for Activation of T cells (LAT) on the cell surface of the T cell immunological synapse.

AvailabilitySoftware available at https://github.com/lp1611/mol_count_dstorm.

category: biophysics


title: Linear B-cell epitope prediction for in silico vaccine design: a performance review of methods available via command-line interface

abstract: Linear B-cell epitope prediction research has received a steadily growing interest ever since the first method was developed in 1981. B-cell epitope identification with the help of an accurate prediction method can lead to an overall faster and cheaper vaccine design process, a crucial necessity in the covid-19 era. Consequently, several B-cell epitope prediction methods have been developed over the past few decades, but without significant success. In this study, we review the current performance and methodology of some of the most widely used linear B-cell epitope predictors which are available via a command-line interface, namely BcePred, BepiPred, ABCpred, COBEpro, SVMTriP, LBtope, and LBEEP. Additionally, we attempted to remedy performance issues of the individual methods by developing a consensus classifier, which combines the separate predictions of these methods into a single output, accelerating the epitope-based vaccine design. While the method comparison was performed with some necessary caveats and individual methods might perform much better for specialized datasets, we hope that this update in performance can aid researchers towards the choice of a predictor, for the development of biomedical applications such as designed vaccines, diagnostic kits, immunotherapeutics, immunodiagnostic tests, antibody production, and disease diagnosis and therapy.


title: Matrix Inversion and Subset Selection (MISS): A novel pipeline for quantitative mapping of diverse cell types across the murine brain

abstract: The advent of increasingly sophisticated imaging platforms has allowed for the visualization of the murine nervous system at single-cell resolution. However, current experimental approaches have not yet produced whole-brain maps of a comprehensive set of neuronal and nonneuronal types that approaches the cellular diversity of the mammalian cortex. Here we aim to fill in this gap in knowledge with an open-source computational pipeline, Matrix Inversion with Subset Selection (MISS), that can infer quantitatively validated distributions of diverse collections of neural cell types at 200m resolution using a combination of single-cell RNAseq and in situ hybridization datasets. We rigorously demonstrate the accuracy of MISS against literature expectations. Importantly, we show that gene subset selection, a procedure by which we filter out low-information genes prior to performing deconvolution, is a critical pre-processing step that distinguishes MISS from its predecessors and facilitates the production of cell type maps with significantly higher accuracy. We also show that MISS is generalizable by generating high-quality cell type maps from a second, independently curated single-cell RNAseq dataset. Together, our results illustrate the viability of computational approaches for determining the spatial distributions of a wide variety of cell types from genetic data alone.


title: Estradiol-induced progesterone synthesis develops post-puberty in the rostral hypothalamus and coincides with post-pubertal changes in the steroidogenic pathway in female mouse hypothalamic astrocytes

abstract:
The development of estrogen positive feedback is a hallmark of female puberty. Both estrogen and progesterone signaling are required for the functioning of this neuroendocrine feedback loop but the physiological changes that underlie the emergence of positive feedback remain unknown. Only after puberty does estradiol (E2) facilitate progesterone synthesis in the rat female hypothalamus (neuroP), an event critical for positive feedback and the LH surge. We hypothesize that prior to puberty, these astrocytes have low levels of membrane estrogen receptor alpha (ER), which is needed for facilitation of neuroP synthesis. Thus, we hypothesized that prepubertal astrocytes are unable to respond to E2 with increased neuroP synthesis due a lack of membrane ER. To test this, hypothalamic tissues and enriched primary hypothalamic astrocyte cultures were acquired from pre-pubertal (postnatal week 3) and post- pubertal (week 8) female mice. E2-facilitated progesterone was measured in the hypothalamus pre- and post-puberty, and hypothalamic astrocyte responses were measured after treatment with E2. Prior to puberty, E2-facilitated progesterone synthesis did not occur in the hypothalamus, and mER expression was low in hypothalamic astrocytes, but E2-facilitated progesterone synthesis in the rostral hypothalamus and mER expression increased post- puberty. The increase in mER expression in hypothalamic astrocytes corresponded with an increase in caveolin-1 protein, PKA phosphorylation, and a more rapid [Ca2+]i flux in response to E2. Together, results from the present study indicate that E2-facilitated neuroP synthesis occurs in the rostral hypothalamus, develops during puberty, and corresponds to a post-pubertal increase in mER levels in hypothalamic astrocytes.

SIGNIFICANCE STATEMENTEstradiol facilitation of hypothalamic neuroprogesterone synthesis is necessary for the positive feedback of the LH surge. The present study localized the increase of neuroprogesterone to the rostral hypothalamus, a region that mediates estrogen positive feedback. Across pubertal development, hypothalamic astrocytes increase levels of membrane ER and the cell signaling responses needed to facilitate neuroprogesterone synthesis that triggers the LH surge demonstrating a mechanism for pubertal maturation resulting in reproductive competence.


title: Unravelling the genetic architecture of musical rhythm: a large-scale genome-wide association study of beat synchronization

abstract: Moving in synchrony to the beat is a fundamental component of musicality. Here, we conducted a genome-wide association study (GWAS) to identify common genetic variants associated with beat synchronization in 606,825 individuals. Beat synchronization exhibited a highly polygenic architecture, with sixty-nine loci reaching genome-wide significance (p<5x10-8) and SNP-based heritability (on the liability scale) of 13%-16%. Heritability was enriched for genes expressed in brain tissues, and for fetal and adult brain-specific gene regulatory elements, underscoring the role of central nervous system-expressed genes linked to the genetic basis of the trait. We performed validations of the self-report phenotype (through internet-based experiments) and of the GWAS (polygenic scores for beat synchronization were associated with patients algorithmically classified as musicians in medical records of a separate biobank). Genetic correlations with breathing function, motor function, processing speed, and chronotype suggest shared genetic architecture with beat synchronization and provide avenues for new phenotypic and genetic explorations.


title: Genome-wide association study of musical beat synchronization demonstrates high polygenicity


title: Integrative nascent RNA methods to reveal cell-type specific transcription programs in peripheral blood and its derivative cells

abstract: Nascent RNA sequencing is a powerful method to measure transcription with high resolution, sensitivity, and directional information, which gives distinctive information about transcription from other methods such as chromatin immunoprecipitation or mRNA sequencing. We present an integrated package of nascent RNA-seq methods - ultrafast Precision Run On (uPRO) combined with computational procedures to discover cell type specific enhancers, promoters, and transcription factor networks. uPRO is composed of adaptor ligation and reverse transcription reactions, which is reduced to a one-day procedure and makes nascent RNA-seq more feasible and flexible for a widespread use. We generated genome-wide profiles of nascent transcription in human blood derived cell lines and clinical samples of ~1 ml of untreated whole blood. We integrated these data into deep learning and hierarchical network analysis to detect enhancers, promoters, and co-expression networks to define cell-type specific transcription programs. We found conservation of position but variation of expression in cell type specific enhancers and transcription start sites. Transcription factors (TFs) such as TCF-3 and OCT1 were pivotally associated with TF-enhancer-gene networks across cell types. Intriguingly, we also discovered that TFs related to cell stress and inflammation - such as SRF, ATF, CHOP, and NF-kB - are associated with inter-individual variation of leukocyte transcription in whole blood. Our integration of experimental and computational nascent RNA methods will provide an efficient strategy to identify specific transcriptional programs, both in cell-type and patient/disease-associated, with minimal sample requirements.


title: Temperature predicts the maximum tree-species richness and water and frost shape the residual variation

abstract: The kinetic hypothesis of biodiversity proposes that temperature is the main driver of variation in species richness, given its exponential effect on biological activity and, potentially, on rates of diversification. However, limited support for this hypothesis has been found to date. I tested the fit of this model on the variation of tree-species richness along a continuous latitudinal gradient in the Americas. I found that the kinetic hypothesis accurately predicts the upper bound of the relationship between the inverse of mean annual temperature (1/kK) and the natural logarithm of species richness, at a broad scale. In addition, I found that water availability and the number of days with freezing temperatures organize a part of the residual variation of the upper bound model. The finding of the model fitting on the upper bound rather than on the mean values suggest that the kinetic hypothesis is modeling the variation of the potential maximum species richness per unit of temperature. Likewise, the distribution of the residuals of the upper bound model in function of the number of days with freezing temperatures suggest the importance of environmental thresholds rather than gradual variation driving the observable variation in species richness.


title: Trading Mental Effort for Confidence in the Metacognitive Control of Value-Based Decision-Making

abstract: Why do we sometimes opt for actions or items that we do not value the most? Under current neurocomputational theories, such preference reversals are typically interpreted in terms of errors that arise from the unreliable signaling of value to brain decision systems. But, an alternative explanation is that people may change their mind because they are reassessing the value of alternative options while pondering the decision. So, why do we carefully ponder some decisions, but not others? In this work, we derive a computational model of the metacognitive control of decisions or MCD. In brief, we assume that fast and automatic processes first provide initial (and largely uncertain) representations of options values, yielding prior estimates of decision difficulty. These uncertain value representations are then refined by deploying cognitive (e.g., attentional, mnesic) resources, the allocation of which is controlled by an effort-confidence tradeoff. Importantly, the anticipated benefit of allocating resources varies in a decision-by-decision manner according to the prior estimate of decision difficulty. The ensuing MCD model predicts response time, subjective feeling of effort, choice confidence, changes of mind, and choice-induced preference change and certainty gain. We test these predictions in a systematic manner, using a dedicated behavioral paradigm. Our results provide a quantitative link between mental effort, choice confidence, and preference reversals, which could inform interpretations of related neuroimaging findings.


title: A multi-measure approach for assessing the performance of fMRI preprocessing strategies in resting-state functional connectivity

abstract: It is well established that head motion and physiological processes (e.g. cardiac and breathing activity) should be taken into consideration when analyzing and interpreting results in fMRI studies. However, even though recent studies aimed to evaluate the performance of different preprocessing pipelines there is still no consensus on the optimal strategy. This is partly due to the fact that the quality control (QC) metrics used to evaluate differences in performance across pipelines have often yielded contradictory results. Furthermore, preprocessing techniques based on physiological recordings or data decomposition techniques (e.g. aCompCor) have not been comprehensively examined. Here, to address the aforementioned issues, we propose a framework that summarizes the scores from eight previously proposed and novel QC metrics to a reduced set of two QC metrics that reflect the signal-to-noise ratio and the reduction in motion artifacts and biases in the preprocessed fMRI data. Using this framework, we evaluate the performance of three commonly used practices on the quality of data: 1) Removal of nuisance regressors from fMRI data, 2) discarding motion-contaminated volumes (i.e., scrubbing) before regression, and 3) low-pass filtering the data and the nuisance regressors before their removal. Using resting-state fMRI data from the Human Connectome Project, we show that the scores of the examined QC metrics improve the most when the global signal (GS) and about 17% of principal components from white matter (WM) are removed from the data. Finally, we observe a small further improvement with low-pass filtering at 0.20 Hz and milder variants of WM denoising, but not with scrubbing.


title: Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient

abstract:
BackgroundThe last decade has seen a major increase in the availability of genomic data. This includes expert-curated databases that describe the biological activity of genes, as well as high-throughput assays that measure gene expression in bulk tissue and single cells. Integrating these heterogeneous data sources can generate new hypotheses about biological systems. Our primary objective is to combine population-level drug-response data with patient-level single-cell expression data to predict how any gene will respond to any drug for any patient.

MethodsWe take 2 approaches to benchmarking a "dual-channel" random walk with restart (RWR) for data integration. First, we evaluate how well RWR can predict known gene functions from single-cell gene co-expression networks. Second, we evaluate how well RWR can predict known drug responses from individual cell networks. We then present two exploratory applications. In the first application, we combine the Gene Ontology database with glioblastoma single cells from 5 individual patients to identify genes whose functions differ between cancers. In the second application, we combine the LINCS drug-response database with the same glioblastoma data to identify genes that may exhibit patient-specific drug responses.

ConclusionsOur manuscript introduces two innovations to the integration of heterogeneous biological data. First, we use a "dual-channel" method to predict up-regulation and down-regulation separately. Second, we use individualized single-cell gene co-expression networks to make personalized predictions. These innovations let us predict gene function and drug response for individual patients. Taken together, our work shows promise that single-cell co-expression data could be combined in heterogeneous information networks to facilitate precision medicine.


title: PharmOmics: A Species- and Tissue-specific Drug Signature Database and Online Tool for Drug Repurposing

abstract: Drug development has been hampered by a high failure rate in clinical trials due to efficacy or safety issues not predicted by preclinical studies in model systems. A key contributor is our incomplete understanding of drug functions across organ systems and species. Therefore, elucidating species- and tissue-specific actions of drugs can provide systems level insights into therapeutic efficacy, potential adverse effects, and interspecies differences that are necessary for more effective translational medicine. Here, we present a comprehensive drug knowledgebase and analytical tool, PharmOmics, comprised of genomic footprints of drugs in individual tissues from human, mouse, and rat transcriptome data from GEO, ArrayExpress, TG-GATEs, and DrugMatrix. Using multi-species and multi-tissue gene expression signatures as molecular indicators of drug functions, we developed gene network-based approaches for drug repositioning. We demonstrate the potential of PharmOmics to predict drugs for new disease indications and validated two predicted drugs for non-alcoholic fatty liver disease in mice. We also examined the potential of PharmOmics to identify drugs related to hepatoxicity and nephrotoxicity. By combining tissue- and species-specific in vivo drug signatures with biological networks, PharmOmics serves as a complementary tool to support drug characterization.


title: A small-molecule antagonist for the Tudor domain of SMN disrupts the interaction between SMN and RNAP II

abstract: Survival of motor neuron (SMN), a Tudor-domain-containing protein, plays an important role in diverse biological pathways via recognition of symmetrically dimethylated arginine (Rme2s) on proteins by its Tudor domain, and deficiency of SMN leads to the motor neuron degenerative disease spinal muscular atrophy (SMA). Here we report a potent and selective antagonist with a 4-iminopyridine scaffold targeting the Tudor domain of SMN. Our structural and mutagenesis studies indicate that the sandwich stacking interactions of SMN and compound 1 play a critical role in selective binding to SMN. Various on-target engagement assays support that compound 1 recognizes SMN specifically in a cellular context. In cell studies display that the SMN antagonist prevent the interaction of SMN with R1810me2s of DNA-directed RNA polymerase II subunit POLR2A and results in transcription termination and R-loop accumulation, mimicking depletion of SMN. Thus, in addition to the antisense, RNAi and CRISPR/Cas9 techniques, the potent SMN antagonist could be used as an efficient tool in understanding the biological functions of SMN and molecular etiology in SMA.

category: biochemistry


title: Interrogating theoretical models of neural computation with emergent property inference

abstract: 1A cornerstone of theoretical neuroscience is the circuit model: a system of equations that captures a hypothesized neural mechanism. Such models are valuable when they give rise to an experimentally observed phenomenon - whether behavioral or a pattern of neural activity - and thus can offer insights into neural computation. The operation of these circuits, like all models, critically depends on the choice of model parameters. A key step is then to identify the model parameters consistent with observed phenomena: to solve the inverse problem. In this work, we present a novel technique, emergent property inference (EPI), that brings the modern probabilistic modeling toolkit to theoretical neuroscience. When theorizing circuit models, theoreticians predominantly focus on reproducing computational properties rather than a particular dataset. Our method uses deep neural networks to learn parameter distributions with these computational properties. This methodology is introduced through a motivational example inferring conductance parameters in a circuit model of the stomatogastric ganglion. Then, with recurrent neural networks of increasing size, we show that EPI allows precise control over the behavior of inferred parameters, and that EPI scales better in parameter dimension than alternative techniques. In the remainder of this work, we present novel theoretical findings gained through the examination of complex parametric structure captured by EPI. In a model of primary visual cortex, we discovered how connectivity with multiple inhibitory subtypes shapes variability in the excitatory population. Finally, in a model of superior colliculus, we identified and characterized two distinct regimes of connectivity that facilitate switching between opposite tasks amidst interleaved trials, characterized each regime via insights afforded by EPI, and found conditions where these circuit models reproduce results from optogenetic silencing experiments. Beyond its scientific contribution, this work illustrates the variety of analyses possible once deep learning is harnessed towards solving theoretical inverse problems.


title: Metabolic signatures of regulation by phosphorylation and acetylation

abstract:
Acetylation and phosphorylation are highly conserved post-translational modifications (PTMs) that regulate cellular metabolism, yet how metabolic control is shared between these PTMs is unknown. Here we analyze transcriptome, proteome, acetylome, and phosphoproteome datasets in E.coli, S.cerevisiae, and mammalian cells across diverse conditions using CAROM, a new approach that uses genome-scale metabolic networks and machine-learning to classify regulation by PTMs. We built a single machine-learning model that accurately distinguished reactions controlled by each PTM in a condition across all three organisms based on reaction attributes (AUC>0.8). Our model uncovered enzymes regulated by phosphorylation during a mammalian cell-cycle, which we validate using phosphoproteomics. Interpreting the machine-learning model using game-theory uncovered enzyme properties including network connectivity, essentiality, and condition-specific factors such as maximum flux that differentiate regulation by phosphorylation from acetylation. The conserved and predictable partitioning of metabolic regulation identified here between these PTMs can enable rational engineering of regulatory circuits.

Graphical Abstract

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title: ERBB2 is a Key Mediator in Hearing Restoration in Noise-Deafened Young Adult Mice

abstract: Noise-induced hearing loss (NIHL) affects over ten million adults in the United States, and has no biological treatment. We hypothesized that activation of signaling from ERBB2 receptors in cochlear supporting cells could mitigate cochlear damage. We adopted a new timeline for assessing mitigation that parallels hearing recovery from damage in avians. We drove expression of a constitutively active variant of ERBB2 (CA-ERBB2) in cochlear supporting cells three days after permanent noise damage in young adult mice. Between 100-200 supporting cells in the apical cochlea expressed a lineage marker, indicating competence to express CA-ERBB2. Hearing thresholds were assessed with auditory brainstem response tests, and hearing recovery was assessed over a ninety-day period. Mice harboring CA-ERBB2 capability had similar hearing thresholds to control littermates prior to noise exposure, immediately after, and 30-days after. Sixty and ninety days after noise exposure, CA-ERBB2+ mice demonstrated a partial but significant reversal of NIHL threshold shifts at one in five frequencies tested, which was in the region of CA-ERBB2 expression. We evaluated inner and outer hair cell (IHC and OHC) survival, synaptic preservation, stereociliary morphology, and IHC cytoskeletal alterations with histological techniques. Improved IHC and OHC survival were observed in the basal cochlea. No differences were seen in synaptic numbers or IHC cytoskeletal alterations, but more stereocilia may have been preserved. These data indicate, for the first time, that ERBB2 signaling in supporting cells can promote hair cell survival and partial functional recovery, and that permanent threshold shifts from noise may be partially reversed in mice.


title: Privacy-preserving quality control of neuroimaging datasets in federated environments

abstract: Privacy concerns for rare disease data, institutional or IRB policies, access to local computational or storage resources or download capabilities are among the reasons that may preclude analyses that pool data to a single site. A growing number of multi-site projects and consortia were formed to function in the federated environment to conduct productive research under constraints of this kind. In this scenario, a quality control tool that visualizes decentralized data in its entirety via global aggregation of local computations is especially important, as it would allow the screening of samples that cannot be jointly evaluated otherwise. To solve this issue, we present two algorithms: decentralized data stochastic neighbor embedding, dSNE, and its differentially private counterpart, DP-dSNE. We leverage publicly available datasets to simultaneously map data samples located at different sites according to their similarities. Even though the data never leaves the individual sites, dSNE does not provide any formal privacy guarantees. To overcome that, we rely on differential privacy: a formal mathematical guarantee that protects individuals from being identified as contributors to a dataset. We implement DP-dSNE with AdaCliP, a method recently proposed to add less noise to the gradients per iteration. We introduce metrics for measuring the embedding quality and validate our algorithms on these metrics against their centralized counterpart on two toy datasets. Our validation on six multi-site neuroimaging datasets shows promising results for the quality control tasks of visualization and outlier detection, highlighting the potential of our private, decentralized visualization approach.


title: Long-term warming effects on the microbiome and nitrogen fixation of a common moss species in sub-Arctic tundra

abstract:
O_LIBacterial communities form the basis of biogeochemical processes and determine plant growth and health. Mosses, an abundant plant group in Arctic ecosystems, harbour diverse bacterial communities that are involved in nitrogen fixation and carbon cycling. Global climate change is causing changes in aboveground plant biomass and shifting species composition in the Arctic, but little is known about the response of moss microbiomes.
C_LIO_LIHere, we studied the total and potentially active bacterial community associated with Racomitrium lanuginosum, in response to 20-year in situ warming in an Icelandic heathland. We evaluated the effect of warming and warming-induced shrub expansion on the moss bacterial community composition and diversity, nifH gene abundance and nitrogen-fixation rates.
C_LIO_LIWarming changed both the total and the potentially active bacterial community structure, while litter abundance only affected the total bacterial community structure. The relative abundance of Proteobacteria increased, while the relative abundance of Cyanobacteria and Acidobacteria decreased. NifH gene abundance and nitrogen-fixation rates were negatively affected by litter and Betula nana abundance, respectively. We also found shifts in the potentially nitrogen-fixing community, with Nostoc decreasing and non-cyanobacterial diazotrophs increasing in relative abundance. Our data suggests that the moss microbial community including the potentially nitrogen-fixing taxa is sensitive to future warming.
C_LIO_LISynthesis. Long-term warming led to a shift in moss-associated bacterial community composition, while the abundance of nitrogen-fixing bacteria and nitrogen-fixation rates were negatively affected by increased litter and Betula nana abundance respectively. Warming and increased shrub abundance as a result of warming can affect moss-associated bacterial communities and nitrogen fixation rates in tundra ecosystems.
C_LI