title: Discovery of Clinically Relevant Fusions in Pediatric Cancer

abstract:
AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSPediatric cancers typically have a distinct genomic landscape when compared to adult cancers and frequently carry somatic gene fusion events that alter gene expression and drive tumorigenesis. Sensitive and specific detection of gene fusions through the analysis of next-generation-based RNA sequencing (RNA-Seq) data is computationally challenging and may be confounded by low tumor cellularity or underlying genomic complexity. Furthermore, numerous computational tools are available to identify fusions from supporting RNA-Seq reads, yet each algorithm demonstrates unique variability in sensitivity and precision, and no clearly superior approach currently exists. To overcome these challenges, we have developed an ensemble fusion calling approach to increase the accuracy of identifying fusions.

ResultsOur ensemble fusion detection approach utilizes seven fusion calling algorithms: Arriba, CICERO, FusionMap, FusionCatcher, JAFFA, MapSplice, and STAR-Fusion, which are packaged as a fully automated pipeline using Docker and AWS serverless technology. This method uses paired end RNA-Seq sequence reads as input, and the output from each algorithm is examined to identify fusions detected by a consensus of at least three algorithms. These consensus fusion results are filtered by comparison to an internal database to remove likely artifactual fusions occurring at high frequencies in our internal cohort, while a "known fusion list" prevents failure to report known pathogenic events. We have employed the ensemble fusion-calling pipeline on RNA-Seq data from 229 patients with pediatric cancer or blood disorders studied under an IRB-approved protocol. The samples consist of 138 central nervous system tumors, 73 solid tumors, and 18 hematologic malignancies or disorders. The combination of an ensemble fusion-calling pipeline and a knowledge-based filtering strategy identified 67 clinically relevant fusions among our cohort (diagnostic yield of 29.3%), including RBPMS-MET, BCAN-NTRK1, and TRIM22-BRAF fusions. Following clinical confirmation and reporting in the patients medical record, both known and novel fusions provided medically meaningful information.

ConclusionsOur ensemble fusion detection pipeline offers a streamlined approach to discover fusions in cancer, at higher levels of sensitivity and accuracy than single algorithm methods. Furthermore, this method accurately identifies driver fusions in pediatric cancer, providing clinical impact by contributing evidence to diagnosis and, when appropriate, indicating targeted therapies.


title: Stereo Slant Discrimination of Planar 3D Surfaces: Standard vs. Planar Cross-Correlation

abstract:
Binocular stereo cues are important for discriminating 3D surface orientation, especially at near distances. We devised a single-interval task where observers discriminated the slant of a densely textured planar test surface relative to a textured planar surround reference surface. Although surfaces were rendered with correct perspective, the stimuli were designed so that the binocular cues dominated performance. Slant discrimination performance was measured as a function of the reference slant and the level of uncorrelated white noise added to the test-plane images in the left and right eye. We compared human performance with an approximate ideal observer (planar cross correlation, PCC) and two sub-ideal observers. The PCC observer uses the image in one eye and back projection to predict the test image in the other eye for all possible slants, tilts, and distances. The estimated slant, tilt, and distance are determined by the prediction that most closely matches the measured image in the other eye. The first sub-ideal observer (local PCC, LPCC) applies planar cross correlation over local neighborhoods and then pools estimates across the test plane. The second sub-optimal observer (standard cross correlation, SCC), uses only positional disparity information. We find that the ideal observer (PCC) and the first sub-ideal observer (LPCC) outperform the second sub-ideal observer (SCC), demonstrating the benefits of structural disparities. We also find that all three model observers can account for human performance, if two free parameters are included: a fixed small level of internal estimation noise, and a fixed overall efficiency scalar on slant discriminability.

PrecisWe measured human stereo slant discrimination thresholds for accurately-rendered textured surfaces designed so that performance is dominated by binocular-disparity cues. We compared human performance with an approximate ideal observer and two sub-ideal observers.

category: animal behavior and cognition


title: Computational Elucidation of Recombinant Fusion Protein Effect on Peptide-Directed Nanoparticles

abstract: Nanoparticles synthesized using various peptides have optimized properties and functional abilities which can be achieved via peptide flexibility and site specificity. Using peptide Pd4 and other alanine substitution combinations of Pd4 attached to a green fluorescent protein (GFPuv), nanoparticles with well-defined sizes that are soluble in aqueous solutions can be produced. In this study, extensive molecular dynamics simulations explored the structural and functional differences between the free peptides and the peptides bound to the GFPuv used in nanoparticle production. Binding affinities of histidines of Pd4 peptide and its two mutants A6 and A11 to a palladium atom were calculated using the free energy perturbation method. Interestingly, the average particle sizes obtained from transmission electron microscopy (TEM) images correlated with our calculated free energies of different peptide sequences. Remarkably, when the peptide was bound to GFPuv, the free energies of histidine were very similar in the wild-type and other mutated peptides. However, this trend is not observed with free peptide simulations, where binding affinities differ by mutation of histidine residues. This study describes, at a molecular level, the role of amino acid sequence on binding affinity of the peptide to the surface of the palladium particles, and the functional ability of the GFPuv protein controlling these free energies irrespective of peptide sequence. Our study will provide a framework for designing free and protein attached peptides that facilitate peptide-mediated nanoparticle formation with well-regulated properties.

category: bioengineering


title: Gene-Gene Interaction Detection with Deep Learning

abstract: We do not know the extent to which genetic interactions affect the observed phenotype in diseases, because the current interaction detection approaches are limited: they only consider interactions between the top SNPs of each gene, and only simple forms of interaction. We introduce methods for increasing the statistical power of interaction detection by taking into account all SNPs and complex interactions between them, beyond only the currently considered multiplicative relationships. In brief, the relation between SNPs and a phenotype is captured by a gene interaction neural network (NN), and the interactions are quantified by the Shapley score between hidden nodes, which are gene representations that optimally combine information from all SNPs in the gene. Additionally, we design a new permutation procedure tailored for NNs to assess the significance of interactions. The new approach outperformed existing alternatives on simulated datasets, and in a cholesterol study on the UK Biobank it detected six interactions which replicated on an independent FINRISK dataset, four of them novel findings.

category: bioinformatics


title: Pheniqs 2.0: accurate, high performance Bayesian decoding and confidence estimation for combinatorial barcode indexing

abstract:
BackgroundSystems biology increasingly relies on deep sequencing with combinatorial index tags to associate biological sequences with their sample, cell, or molecule of origin. Accurate data interpretation depends on the ability to classify sequences based on correct decoding of these combinatorial barcodes. The probability of correct decoding is influenced by both sequence quality and the number and arrangement of barcodes. The rising complexity of experimental designs calls for a probability model that accounts for both sequencing errors and random noise, generalizes to multiple combinatorial tags, and can handle any barcoding scheme. The needs for reproducibility and community benchmark standards demand a peer-reviewed tool that preserves decoding quality scores and provides tunable control over classification confidence that balances precision and recall. Moreover, continuous improvements in sequencing throughput require a fast, parallelized and scalable implementation.

ResultsWe developed a flexible, robustly engineered software that performs probabilistic decoding and supports arbitrarily complex barcoding designs. Pheniqs computes the full posterior decoding error probability of observed barcodes by consulting basecalling quality scores and prior distributions, and reports sequences and confidence scores in Sequence Alignment/Map (SAM) fields. The product of posteriors for multiple independent barcodes provides an overall confidence score for each read. Pheniqs achieves greater accuracy than minimum edit distance or simple maximum likelihood estimation, and it scales linearly with core count to enable the classification of >11 billion reads in 1h15m using <50 megabytes of memory. Pheniqs has been in production use for seven years in our genomics core facility.

ConclusionsWe introduce a computationally efficient software that implements both probabilistic and minimum distance decoders and show that decoding barcodes using posterior probabilities is more accurate than available methods. Pheniqs allows fine-tuning of decoding sensitivity using intuitive confidence thresholds and is extensible with alternative decoders and new error models. Any arbitrary arrangement of barcodes is easily configured, enabling computation of combinatorial confidence scores for any barcoding strategy. An optimized multithreaded implementation assures that Pheniqs is faster and scales better with complex barcode sets than existing tools. Support for POSIX streams and multiple sequencing formats enables easy integration with automated analysis pipelines.


title: A Proposal of New Feature Selection Method Sensitive to Outliers and Correlation

abstract: In disease diagnosis classification, ensemble learning algorithms enable strong and successful models by training more than one learning function simultaneously. This study aimed to eliminate the irrelevant variable problem with the proposed new feature selection method and compare the ensemble learning algorithms classification performances after eliminating the problems such as missing observation, classroom noise, and class imbalance that may occur in the disease diagnosis data. According to the findings obtained; In the preprocessed data, it was seen that the classification performance of the algorithms was higher than the raw version of the data. When the algorithms classification performances for the new proposed advanced t-Score and the old t-Score method were compared, the feature selection made with the proposed method showed statistically higher performance in all data sets and all algorithms compared to the old t-Score method (p = 0.0001).


title: Structurally Distributed Surface Sites Tune Allosteric Regulation

abstract: Our ability to rationally optimize allosteric regulation is limited by incomplete knowledge of the mutations that tune allostery. Are these mutations few or abundant, structurally localized or distributed? To examine this, we conducted saturation mutagenesis of a synthetic allosteric switch in which Dihydrofolate reductase (DHFR) is regulated by a blue-light sensitive LOV2 domain. Using a high-throughput assay wherein DHFR catalytic activity is coupled to E. coli growth, we assessed the impact of 1548 viable DHFR single mutations on allostery. Despite most mutations being deleterious to activity, fewer than 5% of mutations had a statistically significant influence on allostery. Most allostery disrupting mutations were proximal to the LOV2 insertion site. In contrast, allostery enhancing mutations were structurally distributed and enriched on the protein surface. Combining several allostery enhancing mutations yielded near-additive improvements to dynamic range. Our results indicate a path towards optimizing allosteric function through variation at surface sites.

category: biophysics


title: Reconstitution of Kinesin-1 Activation

abstract: Autoinhibition is an important regulatory mechanism for cytoskeletal motor proteins. Kinesin-1 (kinesin hereafter), the ubiquitous plus-end directed microtubule motor, is thought to be controlled by a complicated autoinihibition mechanism, but the molecular details remain unclear. Conformational changes mediated by intramolecular interactions between the C-terminal tail and N-terminal motor domains of the kinesin heavy chain (KHC) are proposed to be one facet of motor regulation. The dimeric KHC also binds two copies of the kinesin light chains (KLCs), which have been implicated in both autoinhibition and cargo-dependent activation of the tetrameric motor complex, although the precise mechanisms remain opaque. Using in vitro reconstitution, we show that the KLC strongly inhibits the kinesin-microtubule interaction via an independent mechanism from the tail-motor interaction within KHC. Kinesin cargo-adaptor proteins that bind KLC activated processive movement of the kinesin tetramer but the landing rate of these activated complexes remained low. The addition of MAP7, which specifically binds to the KHC, strongly enhanced activated motor motility by dramatically increasing the landing rate and processivity of the activated kinesin motors. Our results support a model whereby the activity of the kinesin tetramer is regulated by independent tail- and KLC-based inhibition mechanisms, and that cargo-adaptor binding to the KLC directly releases both of these inhibitions. However, we find that a third component, a non-motor MAP is required for robust activity of the activated motor. Thus, human kinesin activity is regulated by a two-factor mechanism comprised of intramolecular allosteric regulation, as well as intermolecular kinesin-adaptor and kinesin-MAP interactions.


title: Markov state models of proton- and gate-dependent activation in a pentameric ligand-gated ion channel

abstract: Ligand-gated ion channels conduct currents in response to chemical stimuli, mediating electrochemical signaling in neurons and other excitable cells. For many channels the mechanistic details of gating remain unclear, partly due to limited structural data and simulation timescales. Here, we used enhanced sampling to simulate the pH-gated channel GLIC, and construct Markov state models (MSMs) of gating transitions. Consistent with new functional recordings reported here in oocytes, our analysis revealed differential effects of protonation and mutation on free-energy wells. Clustering of closed-versus open-like states enabled estimation of open probabilities and transition rates in each condition, while higher-order clustering affirmed conformational trends in gating. Furthermore, our models uncovered state- and protonation-dependent symmetrization among subunits. This demonstrates the applicability of MSMs to map energetic and conformational transitions between ion-channel functional states, and how they correctly reproduce shifts upon activation or mutation, with implications for modeling neuronal function and developing state-selective drugs.


title: TP53 loss initiates chromosomal instability in high-grade serous ovarian cancer

abstract:
High-grade serous ovarian cancer (HGSOC) originates in the fallopian tube epithelium and is characterized by ubiquitous TP53 mutation and extensive chromosomal instability (CIN). While the direct causes of CIN are errors during DNA replication and/or chromosome segregation, mutations in genes encoding DNA replication and mitotic factors are rare in HGSOC. Thus, the drivers of CIN remain undefined. We therefore asked whether the oncogenic lesions that are frequently observed in HGSOC are capable of driving CIN via indirect mechanisms. To address this question, we genetically manipulated non-transformed hTERT-immortalized human fallopian tube epithelial cells to model homologous recombination deficiency (HRD) and oncogenic signalling in HGSOC. Using CRISPR/Cas9-mediated gene editing, we sequentially mutagenized the tumour suppressors TP53 and BRCA1, followed by overexpression of the MYC oncogene. Single-cell shallow-depth whole-genome sequencing revealed that loss of p53 function was sufficient to lead to the emergence of heterogenous karyotypes harbouring whole chromosome and chromosome arm aneuploidies, a phenomenon exacerbated by subsequent loss of BRCA1 function. In addition, whole-genome doubling events were observed in independent p53/BRCA1-deficient subclones. Global transcriptomics showed that TP53 mutation was also sufficient to deregulate gene expression modules involved in cell cycle commitment, DNA replication, G2/M checkpoint control and mitotic spindle function, suggesting that p53-deficiency induces cell cycle distortions that could precipitate CIN. Again, loss of BRCA1 function and MYC overexpression exacerbated these patterns of transcriptional deregulation. Thus, our observations support a model whereby the initial loss of the key tumour suppressor TP53 is sufficient to deregulate gene expression networks governing multiple cell cycle controls, and that this in turn is sufficient to drive CIN in pre-malignant fallopian tube epithelial cells.

SUMMARY STATEMENTHigh-grade serous ovarian cancer is defined by TP53 mutation and chromosomal instability, the cause of which remains poorly understood. We developed a novel model system that implicates cell cycle deregulation upon p53-loss as cause of CIN.

category: cancer biology


title: In silico logical modelling to uncover cooperative interactions in cancer

abstract: The multistep development of cancer involves the cooperation between multiple molecular lesions, as well as complex interactions between cancer cells and the surrounding tumour microenvironment. The search for these synergistic interactions using experimental models made tremendous contributions to our understanding of oncogenesis. Yet, these approaches remain labour intensive and challenging. To tackle such a hurdle, an integrative, multidisciplinary effort is required. In this article, we highlight the use of logical computational models combined to experimental validations as an effective approach to identify cooperative mechanisms and therapeutic strategies in the context of cancer biology. In silico models overcome limitations of reductionist approaches by capturing tumour complexity, and by generating powerful testable hypotheses. We review representative examples of logical models reported in the literature and their validation. We then provide further analyses of our logical model of Epithelium to Mesenchymal Transition (EMT), searching for additional cooperative interactions involving inputs from the tumour microenvironment and gain of function mutations in NOTCH.


title: Systemic application of the TRPV4 antagonist GSK2193874 induces tail vasodilation in a mouse model of thermoregulation

abstract: In humans the skin is a primary thermoregulatory organ, with vasodilation leading to rapid body cooling, whereas in Rodentia the tail performs an analogous function. Many thermodetection mechanisms are likely to be involved including transient receptor potential vanilloid-type 4 (TRPV4), a widely distributed ion channel with both mechanical and thermosensitive properties. Previous studies have shown that TRPV4 can act as a vasodilator by local action in blood vessels, and in this study, we investigated whether TRPV4 activity effects mus muscularis tail vascular tone and thermoregulation. We measured tail blood flow by pressure plethysmography in lightly sedated mus muscularis (CD1 strain) at a range of ambient temperatures, with and without intraperitoneal administration of the blood brain barrier crossing TRPV4 antagonist GSK2193874. We also measured heart rate and blood pressure with and without GSK2193874. As expected for a thermoregulatory organ, we found that tail blood flow increased with temperature. However, unexpectedly we found that the TRPV4 antagonist GSK2193874 increased tail blood flow at all temperatures, and we observed changes in heart rate variability. Since TRPV4 activation stimulates the relaxation of peripheral resistance arteries (vasodilation) that would increase tail blood flow, these data suggest that increases in tail blood flow resulting from the TRPV4 antagonist may arise from a site other than the blood vessels themselves, perhaps in central cardiovascular control centres such as the hypothalamus.

category: physiology


title: The Sugar Porter gene family of Piriformospora indica: Nomenclature, Transcript Profiling and Characterization

abstract: Piriformospora indica is one of the prominent mutualistic root endophyte known to overcome phosphate and nitrogen limitation in a wide variety of plant species, reciprocally takes up carbohydrates for its survival and growth. A total of nineteen potential hexose transporters have been identified from P. indica genome, that may contributes to its potential of carbohydrate assimilation from host plant. Phylogenetic analysis assembles it in 10 groups within 3 clusters. To ease the study, systematic nomenclature were provided to 19 putative hexose transporters as "PiST1-PiST19" in accordance to their appearance on the supercontigs genome sequence of P. indica. The protein length ranges from 487 to 608 amino acids. Out of 19 putative hexose transporters, 9 have been predicted to contain 12 transmembrane domains (PiST1, PiST2, PiST5, PiST6, PiST9, PiST10, PiST11, PiST12 and PiST17), along with MFS family and Sugar porter subfamily motif. Therefore, transcripts were detected for these 9 genes. During colonization, three P. indica genes PiST1, PiST5 and PiST9 have shown induction as compared to axenic culture. Similarly during phosphate starvation, revealed PiST12 to be strongly enhanced. Carbon starvation study in liquid axenic culture resulted in induction of 4 genes, PiST6, PiST9, PiST12 and PiST17. We found co-relation in the expression pattern of PiPT and PiST12 during phosphate starvation. In silico analysis revealed the presence of functional conserved fucose permease (FucP) domain, involved in fructose transport. Phylogenetic analysis revealed that PiST12 groups closely with basidiomycetes hexose transporters. Further, functional complementation of {Delta}hxt null mutant revealed, PiST12 is able to complement growth on fructose and galactose but negligible on glucose.

category: plant biology


title: Mental health explains individual deviations from normative range in cognition-associated brain states

abstract: Links between cognitive deficits and psychiatric disorders have been studied predominantly at the group level, leaving unique individual characteristics largely elusive. Here, we applied normative modeling to UK Biobank data (N=18,634) and estimated the individual-level interplay of large-scale brain networks over time (i.e., dynamic brain state) as a function of general cognitive ability. Abnormality in such brain states was linked to individual variation in mental health. Specifically, brain state measures including fractional occupancy that indicates the brain state probability over time were estimated using a Hidden Markov Model, followed by a Gaussian process regression to estimate the normative range of these brain state measures from general cognitive ability. Abnormality scores per participant were quantified to represent the degree of deviations relative to the estimated population norm. We found significant associations between the abnormality scores of several brain states and individuals overall mental health. Our findings suggest potential impact of mental health on dynamic brain states that subserve cognitive functions and shed light on the relevant brain mechanisms underlying cognitive deficits in mental illness.

category: neuroscience


title: Introspection confidence correlates with EEG decoding of self-generated thoughts and meta-awareness

abstract: The neurophysiological bases of mind wandering (MW) - an experiential state wherein attention is disengaged from the external environment in favour of internal thoughts, and state meta-awareness are poorly understood. In parallel, the relationship between introspection confidence in experiential state judgements and neural representations remains unclear. Here, we recorded EEG whilst participants completed a listening task within which they made experiential state judgments and rated their confidence. Alpha power was reliably greater during MW episodes, with unaware MW further associated with greater delta and theta power. Multivariate pattern classification analysis revealed that MW, and meta-awareness can be decoded from the distribution of power in these three frequency bands. Critically, we show that individual decoding accuracies positively correlate with introspection confidence. Our results reaffirm the role of alpha oscillations in MW, implicate lower frequencies in meta-awareness, and are consistent with the proposal that introspection confidence indexes neurophysiological discriminability of representational states.


title: Introspection confidence predicts EEG decoding of self-generated thoughts and meta-awareness


title: Efficient high-resolution TMS mapping of the human motor cortex by nonlinear regression

abstract:
Transcranial magnetic stimulation (TMS) is a powerful tool to investigate causal structure-function relationships in the human brain. However, a precise delineation of the effectively stimulated neuronal populations is notoriously impeded by the widespread and complex distribution of the induced electric field.

Here, we propose a method that allows rapid and feasible cortical localization at the individual subject level. The functional relationship between electric field and behavioral effect is quantified by combining experimental data with numerically modelled fields to identify the cortical origin of the modulated effect. Motor evoked potentials (MEPs) from three finger muscles were recorded for a set of random stimulations around the primary motor area. All induced electric fields were nonlinearly regressed against the elicited MEPs to identify their cortical origin.

We could distinguish cortical muscle representation with high spatial resolution and localized them primarily on the crowns and rims of the precentral gyrus. A post-hoc analysis revealed exponential convergence of the method with the number of stimulations, yielding a minimum of about 180 random stimulations to obtain stable results.

Establishing a functional link between the modulated effect and the underlying mode of action, the induced electric field, is a fundamental step to fully exploit the potential of TMS. In contrast to previous approaches, the presented protocol is particularly easy to implement, fast to apply, and very robust due to the random coil positioning and therefore is suitable for practical and clinical applications.


title: Affinity selection in germinal centers: Cautionary tales and new opportunities

abstract: Our current quantitative knowledge of the kinetics of antibody-mediated immunity is partly based on idealized experiments throughout the last decades. However, new experimental techniques often render contradictory quantitative outcomes that shake previously uncontroversial assumptions. This has been the case in the field of T-cell receptors, where recent techniques for measuring the 2-dimensional rate constants of T-cell receptor-ligand interactions exposed contradictory results to those obtained with techniques measuring 3-dimensional interactions. Recently, we have developed a mathematical framework to rationalize those discrepancies focusing on the proper fine-grained description of the underlying kinetic steps involved in the immune synapse. In this perspective article, we apply this approach to unveil potential blind spots in the case of B-cell receptors (BCR) and to rethink the interactions between B cells and follicular dendritic cells (FDC) during the germinal center (GC) reaction. Also, we elaborate on the concept of "catch bonds" and on the recent observations that B-cell synapses retract and pull antigen generating a "retracting force", and propose some testable predictions that can lead to future research.

category: immunology


title: Generation of fluorescent HCV pseudoparticles to study early viral entry events- involvement of Rab1a in HCV entry

abstract:
Understanding the early events in viral biology holds the key to the development of preventives. In this study fluorescent Hepatitis C Virus pseudoparticles have been generated where the envelope glycoprotein has a GFP tag. Using these pseudoparticles entry assays were conducted where the entry of the pseudoparticles was tracked via confocal microscopy. Using this system, fusion of host and viral membranes is predicted to occur within 15 minutes of entry in HCV. Using cells with a knockdown for Rab1a, HCV trafficking was observed to be altered, indicating a role of Rab1a in HCV trafficking. In conclusion, this study reports the generation and use of fluorescent pseudoparticles which may be used to understand the early events of viral entry. This system may be adapted for the study of other enveloped viruses as well.

HighlightsO_LIFluorescent HCV pseudoparticles have been created to study early entry events.
C_LIO_LIHCV entry tracking via confocal microscopy reveals fusion within 15 minutes.
C_LIO_LIRab1a is important for HCV trafficking within the cell.
C_LI

category: microbiology


title: Chimeric spike mRNA vaccines protect against sarbecovirus challenge in mice

abstract:
The emergence of SARS-CoV in 2003 and SARS-CoV-2 in 2019 highlights the need to develop universal vaccination strategies against the broader Sarbecovirus subgenus. Using chimeric spike designs, we demonstrate protection against challenge from SARS-CoV, SARS-CoV-2, SARS-CoV-2 B.1.351, bat CoV (Bt-CoV) RsSHC014, and a heterologous Bt-CoV WIV-1 in vulnerable aged mice. Chimeric spike mRNAs induced high levels of broadly protective neutralizing antibodies against high-risk Sarbecoviruses. In contrast, SARS-CoV-2 mRNA vaccination not only showed a marked reduction in neutralizing titers against heterologous Sarbecoviruses, but SARS-CoV and WIV-1 challenge in mice resulted in breakthrough infection. Chimeric spike mRNA vaccines efficiently neutralized D614G, UK B.1.1.7., mink cluster five, and the South African B.1.351 variant of concern. Thus, multiplexed-chimeric spikes can prevent SARS-like zoonotic coronavirus infections with pandemic potential.

SentenceChimerized RBD, NTD, and S2 spike mRNA-LNPs protect mice against epidemic, zoonotic, and pandemic SARS-like viruses


title: Chimeric spike mRNA vaccines protect against Sarbecovirus challenge in mice


title: An ecological explanation for hyperallometric scaling of reproduction

abstract: In wild populations, large individuals have disproportionately higher reproductive output than smaller individuals. Some theoretical models explain this pattern - termed reproductive hyperallometry - by individuals allocating a greater fraction of available energy towards reproductive effort as they grow. Here, we propose an ecological explanation for this observation: differences between individuals in rates of resource assimilation, where greater assimilation causes both increased reproduction and body size, resulting in reproductive hyperallometry at the level of the population. We illustrate this effect by determining the relationship between size and reproduction in wild and lab-reared Trinidadian guppies. We show that (i) reproduction increased disproportionately with body size in the wild but not in the lab, where resource competition was eliminated and food availability restricted; (ii) in the wild, hyperallometry was greatest during the wet season, when resource competition is strongest; and (iii) detection of hyperallometric scaling of reproduction at the population level was inevitable if individual differences in assimilation were ignored. We propose that ecologically-driven variation in assimilation - caused by size-dependent resource competition, niche expansion, and chance - contributes substantially to hyperallometric scaling of reproduction in natural populations. We recommend that mechanistic models incorporate such ecologically-caused variation when seeking to explain reproductive hyperallometry.

category: ecology


title: FlywheelTools: Data Curation and Manipulation on the Flywheel Platform

abstract: The recent and growing focus on reproducibility in neuroimaging studies has led many major academic centers to use cloud-based imaging databases for storing, analyzing, and sharing complex imaging data. Flywheel is one such database platform that offers easily accessible, large-scale data management, along with a framework for reproducible analyses through containerized pipelines. The Brain Imaging Data Structure (BIDS) is a data storage specification for neuroimaging data, but curating neuroimaging data into BIDS can be a challenging and time-consuming task. In particular, standard solutions for BIDS curation are not designed for use on cloud-based systems such as Flywheel. To address these challenges, we developed "FlywheelTools", a software toolbox for reproducible data curation and manipulation on Flywheel. FlywheelTools includes two elements: fw-heudiconv, for heuristic-driven curation of data into BIDS, and flaudit, which audits and inventories projects on Flywheel. Together, these tools accelerate reproducible neuroscience research on the widely used Flywheel platform.


title: Familial thyroid follicular cell carcinomas in a large number of Dutch German longhaired pointers

abstract: Thyroid carcinomas originating from follicular cells of the thyroid gland occur in both humans and dogs and they have highly similar histomorphologic patterns. In dogs, thyroid carcinomas have not been extensively investigated, especially concerning the familial origin of thyroid carcinomas. Here we report familial thyroid follicular cell carcinomas confirmed by histology in 54 Dutch origin German longhaired pointers. From the pedigree, 45 of 54 histopathologically confirmed cases are closely related to a pair of first-half cousins in the past, indicating a familial disease. In addition, genetics contributed more to the thyroid follicular cell carcinoma than other factors by an estimated heritability of 0.62 based on pedigree. The age of diagnosis ranged between 4.5 and 13.5 years, and 76% of cases were diagnosed before 10 years of age, implying an early onset of disease. We observed a significant higher pedigree-based inbreeding coefficient in the affected dogs (mean F 0.23) compared to unaffected dogs (mean F 0.14), suggesting the contribution of inbreeding to tumour development. The unique occurrence of familial thyroid follicular cell carcinoma in this dog population and the large number of affected dogs make this population an important model to identify the genetic basis of familial thyroid follicular cell carcinoma in this breed and may contribute to the research into pathogenesis, prevention and treatment in humans.


title: A specialist flea beetle manipulates and tolerates the activated chemical defense in its host plant

abstract: Glucosinolates, the characteristic secondary metabolites of Brassicales, are hydrolyzed upon herbivory by myrosinases to toxic and deterrent defense metabolites. The specialist flea beetle, Phyllotreta armoraciae, sequesters glucosinolates in the body despite myrosinase activity, but it is unknown whether plant myrosinase activity influences sequestration and how beetles prevent the hydrolysis of ingested glucosinolates. In feeding experiments performed with the myrosinase-deficient Arabidopsis thaliana tgg1xtgg2 (tgg) mutant and the corresponding wild type, we found that plant myrosinases reduced the glucosinolate sequestration rate by up to 50% and hydrolyzed a fraction of ingested glucosinolates in adult beetles. Although these results show that P. armoraciae cannot fully prevent glucosinolate hydrolysis, we observed no negative influence on beetle performance. To understand how P. armoraciae can avoid the hydrolysis of some ingested glucosinolates, we analyzed their fate directly after ingestion. P. armoraciae rapidly absorbed glucosinolates across the gut epithelium, a strategy that has been proposed to prevent hydrolysis in the gut lumen of sequestering insects. Moreover, beetle gut content suppressed in vitro myrosinase activity, and almost no myrosinase activity was detectable in the feces, which indicates that ingested myrosinases are inactivated in the beetle gut. In summary, we show that P. armoraciae uses several strategies to prevent the hydrolysis of ingested glucosinolates but can also tolerate the formation of glucosinolate hydrolysis products.


title: TAPAS: an open-source software package for Translational Neuromodeling and Computational Psychiatry

abstract:
Psychiatry faces fundamental challenges with regard to mechanistically guided differential diagnosis, as well as prediction of clinical trajectories and treatment response of individual patients. This has motivated the genesis of two closely intertwined fields: (i) Translational Neuromodeling (TN), which develops "computational assays" for inferring patient-specific disease processes from neuroimaging, electrophysiological, and behavioral data; and (ii) Computational Psychiatry (CP), with the goal of incorporating computational assays into clinical decision making in everyday practice. In order to serve as objective and reliable tools for clinical routine, computational assays require end-to-end pipelines from raw data (input) to clinically useful information (output). While these are yet to be established in clinical practice, individual components of this general end-to-end pipeline are being developed and made openly available for community use.

In this paper, we present the Translational Algorithms for Psychiatry-Advancing Science (TAPAS) software package, an open-source collection of building blocks for computational assays in psychiatry. Collectively, the tools in TAPAS presently cover several important aspects of the desired end-to-end pipeline, including: (i) tailored experimental designs and optimization of measurement strategy prior to data acquisition, (ii) quality control during data acquisition, and (iii) artifact correction, statistical inference, and clinical application after data acquisition. Here, we review the different tools within TAPAS and illustrate how these may help provide a deeper understanding of neural and cognitive mechanisms of disease, with the ultimate goal of establishing automatized pipelines for predictions about individual patients. We hope that the openly available tools in TAPAS will contribute to the further development of TN/CP and facilitate the translation of advances in computational neuroscience into clinically relevant computational assays.


title: Immunoprofiling reveals novel mast cell receptors and a continuous nature of human lung mast cell heterogeneity

abstract:
BackgroundImmunohistochemical analysis of granule-associated proteases have revealed that human lungs mast cells constitute a heterogeneous population of cells, with distinct subpopulations identified. However, a systematic and comprehensive analysis of cell surface markers to study human lung mast cell heterogeneity is yet to be performed.

MethodsHuman lung mast cells were obtained from lung lobectomies and the expression of 332 cell surface markers were analyzed using flow cytometry and the LEGENDScreen kit. Markers that exhibited a high variance were selected for additional analyses to reveal whether they correlated and if discrete mast cell subpopulations were discernable.

ResultsWe identified expression of 102 surface markers on human lung mast cells. Several markers showed a high continuous variation of expression within the mast cell population. Six of these markers correlated: SUSD2, CD49a, CD326, CD34, CD66 and HLA-DR. The expression of these markers also correlated to the size and granularity of the mast cells. However, no marker produced an expression profile consistent with a bi- or multimodal distribution.

ConclusionsLEGENDScreen analysis identified more than 100 cell surface markers on mast cells, out of which 23 have to our knowledge not previously described on human mast cells. Several of the newly described markers are known to be involved in sensing the microenvironment, and their identification can shed new light on mast cell functions. The exhaustive expression profiling of the 332 surface markers failed to detect distinct mast cell subpopulations. Instead, we demonstrate a continuous nature of human lung mast cell heterogeneity.


title: Yeast proteins reversibly aggregate like amphiphilic molecules

abstract: More than a hundred proteins in yeast reversibly aggregate and phase-separate in response to various stressors, such as nutrient depletion and heat shock. We know little about the sequence and structural features behind this ability, which has not been characterized on a proteome-wide level. To identify the distinctive features of aggregation-prone regions, we apply machine learning algorithms to genome-scale limited proteolysis-mass spectrometry data from 96 yeast proteins that phase-separate upon heat shock. We find that the aggregation-prone regions (APRs) of our study proteins are significantly enriched in aliphatic residues and depleted in positively charged amino acids. Aggregator proteins with longer APRs show a greater propensity to aggregate, a relationship that can be explained by equilibrium statistical thermodynamics. Altogether, our observations suggest that proteome-wide reversible protein aggregation is mediated by sequence-encoded properties. Aggregating proteins resemble supra-molecular amphiphiles, where APRs are the hydrophobic parts, and non-APRs are the hydrophilic parts.

category: molecular biology


title: The PPR domain of mitochondrial RNA polymerase is a ribonuclease required for mtDNA replication

abstract: Mitochondrial DNA (mtDNA) replication and transcription are of paramount importance to cellular energy metabolism. Mitochondrial RNA polymerase (POLRMT) is thought to be the primase for mtDNA replication. However, it is unclear how POLRMT, which normally transcribes long polycistronic RNAs, can produce short RNA oligos to initiate mtDNA replication. Here we show that the PPR domain of Drosophila POLRMT is a 3 to 5 exoribonuclease. The exoribonuclease activity is indispensable for POLRMT to synthesize short RNA oligos and to prime DNA replication in vitro. An exoribonuclease deficient POLRMT, POLRMTE423P partially restores mitochondrial transcription but fails to support mtDNA replication when expressed in POLRMT mutant background, indicating that the exoribonuclease activity is necessary for mtDNA replication. Overexpression of POLRMTE423P in adult flies leads to severe neuromuscular defects and a marked increase of mtDNA transcripts errors, suggesting that exoribonuclease activity may contribute to the proofreading of mtDNA transcription. PPR domain of human POLRMT also has exoribonuclease activity, indicating evolutionarily conserved roles of PPR domain in mitochondrial DNA and RNA metabolism.


title: Epigenetic clocks reveal a rejuvenation event during embryogenesis followed by aging

abstract: The notion that germline cells do not age goes back to the 19th century ideas of August Weismann. However, being in a metabolically active state, they accumulate damage and other age-related changes over time, i.e., they age. For new life to begin in the same young state, they must be rejuvenated in the offspring. Here, we developed a new multi-tissue epigenetic clock and applied it, together with other aging clocks, to track changes in biological age during mouse and human prenatal development. This analysis revealed a significant decrease in biological age, i.e. rejuvenation, during early stages of embryogenesis, followed by an increase in later stages. We further found that pluripotent stem cells do not age even after extensive passaging and that the examined epigenetic age dynamics is conserved across species. Overall, this study uncovers a natural rejuvenation event during embryogenesis and suggests that the minimal biological age (the ground zero) marks the beginning of organismal aging.

category: developmental biology


title: Discriminative feature of cells characterizes cell populations of interest by a small subset of genes

abstract: Differentially expressed gene-based analysis have faced difficulties associated with the inflation of P-values because of both the large sample size and selection bias introduced by exploratory data analysis in single-cell transcriptomics. Here, we propose the concept of discriminative feature of cells (DFC), implemented by logistic regression with an adaptive LASSO penalty. Adaptive LASSO selects a small subset of genes to discriminate a population of interest. DFC well captured non-independent structure of expression patterns such as cell-type-specific markers, specific composition of gene expression, and subcategories of this cell population. DFC may complement existing methods for interpreting large data sets.


title: A metal ion orients mRNA to ensure accurate 2'-O ribosyl methylation of the first nucleotide of the SARS-CoV-2 genome

abstract: The SARS-CoV-2 nsp16/nsp10 enzyme complex modifies the 2-OH of the first transcribed nucleotide of the viral mRNA by covalently attaching a methyl group to it. The 2-O methylation of the first nucleotide converts the status of mRNA cap from Cap-0 to Cap-1, and thus, helps the virus evade immune surveillance in the host cell. Here, we report two structures of nsp16/nsp10 representing pre- and post-release states of the RNA product (Cap-1). We observe overall widening of the enzyme upon product formation, and an inward twisting motion in the substrate binding region upon product release. These conformational changes reset the enzyme for the next round of catalysis. The structures also identify a unique binding mode and the importance of a divalent metal ion for 2-O methylation. We also describe underlying structural basis for the perturbed enzymatic activity of a clinical variant of SARS-CoV-2, and a previous SARS-CoV outbreak strain.

category: biochemistry


title: Towards a More General Understanding of the Algorithmic Utility of Recurrent Connections

abstract:
Lateral and recurrent connections are ubiquitous in biological neural circuits. Yet while the strong computational abilities of feedforward networks have been extensively studied, our understanding of the role and advantages of recurrent computations that might explain their prevalence remains an important open challenge. Foundational studies by Minsky and Roelfsema argued that computations that require propagation of global information for local computation to take place would likely particularly benefit from the sequential, parallel nature of processing in recurrent networks. Such "tag propagation" algorithms perform repeated, local propagation of information and were originally introduced in the context of detecting connectedness, a task that is challenging for feedforward networks. Here, we advance the understanding of the utility of lateral and recurrent computation by first performing a large-scale empirical study of neural architectures for the computation of connectedness to explore feedforward solutions more fully and establish robustly the importance of recurrent architectures. In addition, we highlight a tradeoff between computation time and performance and demonstrate hybrid feedforward/recurrent models that perform well even in the presence of varying computational time limitations. We then generalize tag propagation architectures to multiple, interacting propagating tags, and demonstrate that these are efficient computational substrates for more general computations of connectedness by introducing and solving an abstracted biologically inspired decision-making task. Our work thus clarifies and expands the set of computational tasks that can be solved efficiently by recurrent computation, yielding hypotheses for structure in population activity that may be present in such tasks.

Author SummaryIn striking contrast to the majority of current-day artificial neural network research which primarily uses feedforward architectures, biological brains make extensive use of lateral and recurrent connections, raising the possibility that this difference makes a fundamental contribution to the gap in computational power between real neural circuits and artificial neural networks. Thus, despite the challenge of making effective comparisons between different network architectures, developing a more detailed understanding of the computational role played by such connections is a pressing need. Here, we leverage the computational capabilities of large-scale machine learning to robustly explore how differences in architectures affect a networks ability to learn tasks that require propagation of global information. We first focus on the task of determining whether two pixels are connected in an image which has an elegant and efficient recurrent solution: propagate a connected label or tag along paths. Inspired by this solution, we show that it can be generalized in many ways, including propagating multiple tags at once and changing the computation performed on the result of the propagation. Strikingly, this simple expansion of the tag propagation network is sufficient to solve a crucial abstraction to temporal connectedness at the core of many decision-making problems, which we illustrate for a an abstracted competitive foraging task Our results shed light on the set of computational tasks that can be solved efficiently by recurrent computation and how these solutions may relate to the structure of neural activity.


title: Exiguobacterium Sp. HA2, isolated from the Ilam Mountains of Iran

abstract: A motile, Gram-stain-positive, rod-shaped, non-sporing, tolerate up to 5% NaCl, grew at 0-25 {degrees}C, designated Exiguobacterium sp. HA2 was isolated from the soil of the Ilam Mountains of Iran during October 2016. The major isoprenoid quinone is MK-7 and in the smaller amount are MK-6 and MK-8. Polar lipids included diphosphatidylglycerol, phosphatidylglycerol, phosphatidylserine, phosphatidylinositol, phosphatidylethanolamine. Major fatty acids (>10 %) are isoC13:0, isoC15:0 and C16:0. The bacterial cell wall peptidoglycan layer was lysine-glycine. The 16S rRNA sequence was analyzed at the phylogenetic levels. Also, A supplemental comparison was made between five other genes including csp, gyrB, hsp70, rpoB, and citC. According to the results of genotypic and phenotypic characteristics, the strain was categorized in the genus Exiguobacterium. This bacterium had the closest relation with Exiguobacterium undae, and thus was dubbed Exiguobacterium sp. HA2. The different in the Phenotypic, functional characteristics and phylogenetic indicated Exiguobacterium sp. HA2 can be regarded as representing considered a novel species within the genus Exiguobacterium.


title: Tree phyllospheres are a habitat for diverse populations of CO-oxidising bacteria

abstract:
BackgroundCarbon monoxide (CO) is a naturally occurring and ubiquitous trace gas in the atmosphere. As a product of combustion processes, it can reach concentrations in the mg/m3 range in urban areas, contributing to air pollution. Aerobic CO-degrading microorganisms have been identified previously and are thought to remove ~370 Tg of CO in soils and oceans per year. Based on the presence of genes encoding subunits of the enzyme carbon monoxide dehydrogenase in metagenomes, a large fraction of soil bacteria may have the potential for CO degradation. The activity and diversity of CO-degrading microorganisms in above ground habitats such as the phyllosphere has not been addressed, however, and their potential role in global CO cycling remains unknown.

ResultsMonitoring of CO-degradation in leaf washes of two common British trees, Ilex aquifolium and Crataegus monogyna, demonstrated CO uptake in all samples investigated. Leaf washes of I. aquifolium had significantly higher CO oxidation rates than those of C. monogyna. A diverse range of bacterial taxa were identified as candidate CO-oxidising taxa based on high-throughput sequencing and multivariate statistical analysis of 16S rRNA amplicon data, as well as functional diversity analysis based on coxL, the gene encoding the large subunit of CO-dehydrogenase. Candidate CO-oxidising taxa included a range of Rhizobiales and Burkholderiales, of which the Burkholderiales OTUs were abundant colonisers of the phyllosphere at the time of sampling, as indicated by 16S rRNA gene sequencing. In addition, an estimated 12.4% of leaf OTUs in samples of this study contained coxL homologues, based on their predicted genomes. We also mined data of publicly available phyllosphere metagenomes for genes encoding subunits of CO-dehydrogenase which indicated that, on average, 25% of phyllosphere bacteria contained CO-dehydrogenase gene homologues. A CO-oxidising Phyllobacteriaceae strain was isolated from phyllosphere samples which contains genes encoding both CODH as well as a RuBisCO.

ConclusionsThe phyllosphere, a vast microbial habitat, supports diverse and potentially abundant CO-oxidising bacteria. These findings identify tree phyllosphere bacteria as a potential sink for atmospheric CO and highlight the need for a more detailed assessment of phyllosphere microbial communities in the global cycle of CO.


title: Niche partitioning facilitates coexistence of closely related gut bacteria

abstract: Ecological processes underlying bacterial coexistence in the gut are not well understood. Here, we disentangled the effect of the host and the diet on the coexistence of four closely related Lactobacillus species colonizing the honey bee gut. We serially passaged the four species through gnotobiotic bees and in liquid cultures in the presence of either pollen (bee diet) or simple sugars. Although the four species engaged in negative interactions, they were able to stably coexist, both in vivo and in vitro. However, coexistence was only possible in the presence of pollen, and not in simple sugars, independent of the environment. Using metatranscriptomics and metabolomics, we found that the four species utilize different pollen-derived carbohydrate substrates indicating resource partitioning as the basis of coexistence. Our results show that despite longstanding host association, gut bacterial interactions can be recapitulated in vitro providing insights about bacterial coexistence when combined with in vivo experiments.


title: The GT factor ZmGT-3b mediates growth-defense tradeoff by regulating photosynthesis and defense response

abstract:
Plant growth and development face constant threat from various environmental stresses. Transcription factors (TFs) are crucial for maintaining balance between plant growth and defense. Trihelix TFs display multifaceted functions in plant growth, development, and responses to various biotic and abiotic stresses. Here, we explore the role of a trihelix TF, ZmGT-3b, in regulating the growth-defense tradeoff in maize (Zea mays). ZmGT-3b is primed for instant response to Fusarium graminearum challenge by implementing a rapid and significant reduction of its expression to suppress seedling growth and enhance disease resistance. ZmGT-3b knockdown led to diminished growth, but improved disease resistance and drought tolerance in maize seedlings. In ZmGT-3b knockdown seedlings, the chlorophyll content and net photosynthetic rate were strongly reduced, whereas the contents of major cell wall components, such as lignin, were synchronically increased. Correspondingly, ZmGT-3b knockdown specifically downregulated photosynthesis-related genes, especially ZmHY5 (encoding a conserved central regulator of seedling development and light responses), but synchronically upregulated genes associated with secondary metabolite biosynthesis and defense-related functions. ZmGT-3b knockdown induced defense-related transcriptional reprogramming and increased biosynthesis of lignin without immune activation. These data suggest that ZmGT-3b is a regulator of plant growth-defense tradeoff that coordinates metabolism during growth-to-defense transitions by optimizing the temporal and spatial expression of photosynthesis- and defense-related genes.

One-sentence summaryZmGT-3b regulates photosynthesis activity and synchronically suppresses defense response.


title: Niche specificity, polygeny, and pleiotropy in herbivorous insects

abstract: Why do herbivorous insects tend to be host specialists? Population genetic models predict specialization when there is antagonistic pleiotropy at a gene for host-use performance. But empirically, host-use performance is governed by many genetic regions, and antagonistic pleiotropy is rare. Here, we use individual-based quantitative genetic simulations to investigate the role of pleiotropy in the evolution of host-use specialization when host-use performance is polygenic. We find that if host-preference is allowed to evolve without cost, parasite populations tend to evolve host-use specialization even without pleiotropy; thus, it would seem that for a polygenic trait, the benefit of maintaining adaptive combinations of conditionally-neutral alleles suffices to drive specialization. But if there is a fecundity cost for host-preference, or if host patches are demographically volatile, host-use generalists evolve, even with high levels of pleiotropy. In sum, if pleiotropy is much more pervasive than has been observed in nature, our simulations show that it could play a role in driving the evolution of polygenic specialization. But pleiotropy is not necessary, and even when it is extensive, selection can favor generalist genotypes.

category: evolutionary biology


title: Social selection and the evolution of maladaptation

abstract:
Evolution by natural selection is often viewed as a process that inevitably leads to adaptation, or an increase in population fitness over time. However, maladaptation, an evolved decrease in fitness, may also occur in response to natural selection under some conditions. Social selection, which arises from the effects of social partners on fitness, has been identified as a potential cause of maladaptation, but we lack a general rule identifying when social selection should lead to a decrease in population mean fitness. Here we use a quantitative genetic model to develop such a rule. We show that maladaptation is most likely to occur when social selection is strong relative to nonsocial selection and acts in an opposing direction. In this scenario, the evolution of traits that impose fitness costs on others may outweigh evolved gains in fitness for the individual, leading to a net decrease in population mean fitness. Further, we find that maladaptation may also sometimes occur when phenotypes of interacting individuals negatively covary. We outline the biological situations where maladaptation in response to social selection can be expected, provide both quantitative genetic and phenotypic versions of our derived result, and suggest what empirical work would be needed to test it. We also consider the effect of social selection on inclusive fitness and support previous work showing that inclusive fitness cannot suffer an evolutionary decrease. Taken together, our results show that social selection may decrease population mean fitness when it opposes individual-level selection, even as inclusive fitness increases.

Subject areaQuantitative genetics and Mendelian inheritance


title: Genomic epidemiology of Mycobacterium bovis infection in sympatric badger and cattle populations in Northern Ireland.

abstract:
BackgroundBovine tuberculosis (bTB) is a costly, epidemiologically complex, multi-host, endemic disease. Pathogen whole genome sequencing can improve the resolution of epidemiological tracing. We genome sequenced an exceptional data set of 619 Mycobacterium bovis isolates from badgers and cattle in a 100km2 bTB  hotspot. Historical molecular subtyping data permitted the targeting of an endemic pathogen lineage, whose long-term persistence provided an opportunity to study genome epidemiology in detail. To assess whether badger population genetic structure was associated with the spatial distribution of pathogen genetic diversity, we microsatellite genotyped hair samples from 769 badgers trapped in this area.

ResultsEight lineages of M. bovis were circulating in the study area, seven of which were likely non-endemic, and imported by animal movement. The endemic lineage exhibited low genetic diversity with an average inter-isolate genetic distance of 7.6 SNPs (s.d. {+/-} 4.0), consistent with contemporary transmission. Bayesian phylogenetic methods determined an evolutionary rate of 0.30 substitutions per genome per year for this lineage, estimating its emergence 40-50 years before present, while Bayesian Skyline analysis identified significant population expansion of the endemic lineage in the 1990s and again in 2011-2012. The phylogeny revealed distinct sub-lineages, all of which contained isolates from both cattle and badger hosts, indicative of the sharing of closely related strains and inter-species transmission. However, the presence of significant badger population genetic structure was not associated with the spatial distribution of M. bovis genetic diversity.

ConclusionsOur data provided unparalleled detail on the evolutionary history of an endemic M. bovis lineage. Findings are consistent with ongoing interspecies transmission in the study area but suggest that badger intra-species transmission may not be a major driver of persistence in this area. In addition, the data collected permitted the tracking of incursions of novel pathogen lineages into the study area and means to determine if they were involved in disease transmission.


title: Management programs as a key factor for genetic conservation of small populations : The case of French local chicken breeds

abstract: On-going climate change will drastically modify agriculture in the future, with a need for more sustainable systems, for animal production in particular. In this context, genetic diversity is a key factor for adaptation to new conditions: local breeds are likely to harbor unique adaptive features and represent a key component of diversity to reach resilience. Nevertheless, they are often suffering from small population size putting these valuable resources at risk of extinction. In chickens, management programs have been initiated a few decades ago in France, relying on a particular niche market aiming at promoting and protecting local breeds. We conducted a unique comprehensive study of 23 French local populations, along with 4 commercial lines, to evaluate their genetic conservation status and the efficiency of management programs. Using a 57K SNP chip we demonstrated that both between and within breeds genetic diversity were high in French populations. Diversity was mainly structured according to selection and breeds history. Nevertheless, we observed a prominent sub-structuring of breeds according to farmers practices in terms of exchange, leading to more or less isolated flocks. Analysing demographic parameters as well as molecular information, we showed the efficiency of consistent management programs to conserve genetic diversity, since the earlier the breeds integrated programs the lower was the inbreeding. Finally we stressed that management programs can benefit from molecular markers and runs of homozygosity, ROH, in particular, as a valuable and affordable tool to monitor genetic diversity of local breeds which often lack pedigree information.

category: genetics


title: Whole Genome Assembly and Annotation of Northern Wild Rice, Zizania palustris L., Supports a Whole Genome Duplication in the Zizania Genus

abstract: Northern Wild Rice (NWR; Zizania palustris L.) is an aquatic grass native to North America that is notable for its nutritious grain. This is an important species with ecological, cultural, and agricultural significance, specifically in the Great Lakes region of the United States. Using long- and short-range sequencing, Hi-C scaffolding, and RNA-seq data from eight tissues, we generated an annotated whole genome de novo assembly of NWR. The assembly is 1.29 Gb, highly repetitive ([~]76.0%), and contains 46,421 putative protein-coding genes. The expansion of retrotransposons within the genome and a whole genome duplication prior to the Zizania-Oryza speciation event have both led to an increase in genome size of NWR in comparison with O. sativa and Z. latifolia. Both events depict a genome rapidly undergoing change over a short evolutionary time. Comparative analyses revealed conservation of large syntenic blocks with Oryza sativa L., which were used to identify putative seed shattering genes. Estimates of divergence times revealed the Zizania genus diverged from Oryza [~]26-30 million years ago (MYA), while NWR and Zizania latifolia diverged from one another [~]6-8 MYA. Comparative genomics confirmed evidence of a whole genome duplication in the Zizania genus and provided support that the event was prior to the NWR-Z. latifolia speciation event. This high-quality genome assembly and annotation provides a valuable resource for comparative genomics in the Oryzeae tribe and provides an important resource for future conservation and breeding efforts of NWR.

category: genomics


title: DNA methylome-based validation of induced sputum as an effective protocol to study lung immunity: construction of a classifier of pulmonary cell types

abstract:
BackgroundFlow cytometry is a classical approach used to define cell types in peripheral blood. While DNA methylation signatures have been extensively employed in recent years as an alternative to flow cytometry to define cell populations in peripheral blood, this approach has not been tested in lung-derived samples. Here, we compared bronchoalveolar lavage with a more cost-effective and less invasive technique based on sputum induction and developed a DNA methylome-based algorithm that can be used to deconvolute the cell types in such samples.

ResultsWe analyzed the DNA methylome profiles of alveolar macrophages and lymphocytes cells isolated from the pulmonary compartment. The cells were isolated using two different methods, sputum induction and bronchoalveolar lavage. A strong positive correlation between the DNA methylome profiles of cells obtained with the two isolation methods was observed, and in two of the donors, in which the correlation was best, a later analyses demonstrated that those subjects the samples were consistently derived from the lower part of the lungs. We also identified unique patterns of CpG methylation in DNA obtained from the two cell populations, which can be used as a signature to discriminate between the alveolar macrophages and lymphocytes by means of open-source algorithms. We validated our findings with external data and obtained results consistent with the previous findings.

ConclusionsOur analysis opens up a new possibility to identify different cell populations from lung samples and promotes sputum induction as a tool to study immune cell populations from the lung.


title: SweepCluster: A SNP clustering tool for detecting gene-specific sweeps in prokaryotes

abstract:
BackgroundThe gene-specific sweep is a selection process where an advantageous mutation along with the nearby neutral sites in a gene region increases the frequency in the population. It has been demonstrated to play important roles in ecological differentiation or phenotypic divergence in microbial populations. Therefore, identifying gene-specific sweeps in microorganisms will not only provide insights into the evolutionary mechanisms, but also unravel potential genetic markers associated with biological phenotypes. However, current methods were mainly developed for detecting selective sweeps in eukaryotic data of sparse genotypes and are not readily applicable to prokaryotic data. Furthermore, some challenges have not been sufficiently addressed by the methods, such as the low spatial resolution of sweep regions and lack of consideration of the spatial distribution of mutations.

ResultsWe proposed a novel gene-centric and spatial-aware approach for identifying gene-specific sweeps in prokaryotes and implemented it in a python tool SweepCluster. Our method searches for gene regions with a high level of spatial clustering of pre-selected polymorphisms in genotype datasets assuming a null distribution model of neutral selection. The pre-selection of polymorphisms is based on their genetic signatures, such as elevated population subdivision, excessive linkage disequilibrium, or significant phenotype association. Performance evaluation using simulation data showed that the accuracy and sensitivity of the clustering algorithm in SweepCluster is above 90%. The application of SweepCluster in two real datasets from the bacteria Streptococcus pyogenes and Streptococcus suis showed that the impact of pre-selection was dramatic and significantly reduced the uninformative signals. We validated our method using the genotype data from Vibrio cyclitrophicus, the only available dataset of gene-specific sweeps in bacteria, and obtained a concordance rate of 78%. We noted that the concordance rate could be underestimated due to distinct reference genomes and clustering strategies. The application to the human genotype datasets showed that SweepCluster is also applicable to eukaryotic data and recovered the known sweep regions in a wide dynamic range of pre-selection parameters.

ConclusionsSweepCluster is applicable to a broad category of datasets. It will be valuable for detecting gene-specific sweeps in diverse genotypic data and provide novel insights on adaptive evolution.


title: SGI: Automatic clinical subgroup identification in omics datasets

abstract:
SummaryThe  Subgroup Identification (SGI) toolbox provides an algorithm to automatically detect clinical subgroups of samples in large-scale omics datasets. It is based on hierarchical clustering trees in combination with a specifically designed association testing and visualization framework that can process an arbitrary number of clinical parameters and outcomes in a systematic fashion. A multi-block extension allows for the simultaneous use of multiple omics datasets on the same samples. In this paper, we describe the functionality of the toolbox and demonstrate an application example on a blood metabolomics dataset with various clinical biochemistry readouts in a type 2 diabetes case-control study.

Availability and implementationSGI is an open-source package implemented in R. Package source codes and hands-on tutorials are available at https://github.com/krumsieklab/sgi. The QMdiab metabolomics data is included in the package and can be downloaded from https://doi.org/10.6084/m9.figshare.5904022.


title: Can offsetting the energetic cost of hibernation restore an active season phenotype in grizzly bears (Ursus arctos horribilis)?

abstract: Hibernation is characterized by suppression of many physiological processes. To determine if this state is reversible in a non-food caching species, we fed hibernating grizzly bears (Ursus arctos horribilis) glucose for 10 days to replace 53% or 100% of the estimated minimum daily energetic cost of hibernation. Feeding caused serum concentrations of glycerol and ketones ({beta}-hydroxybutyrate) to return to active season levels irrespective of the amount of glucose fed. By contrast, free-fatty acids and indices of metabolic rate, such as general activity, heart rate, and strength of the daily heart rate rhythm and insulin sensitivity were restored to roughly 50% of active season levels. Body temperature was unaffected by feeding. To determine the contribution of adipose to these metabolic effects of glucose feeding we cultured bear adipocytes collected at the beginning and end of the feeding and performed metabolic flux analysis. We found a roughly 33% increase in energy metabolism after feeding. Moreover, basal metabolism before feeding was 40% lower in hibernation cells compared to fed cells or active cells cultured at 37{degrees}C, thereby confirming the temperature independence of metabolic rate. The partial suppression of circulating FFA with feeding likely explains the incomplete restoration of insulin sensitivity and other metabolic parameters in hibernating bears. Further suppression of metabolic function is likely an active process. Together, the results provide a highly controlled model to examine the relationship between nutrient availability and metabolism on the hibernation phenotype in bears.


title: Kidney-Specific WNK1 Amplifies NCC Responsiveness to Potassium Imbalance

abstract: The distal convoluted tubule (DCT) NaCl cotransporter NCC is activated by phosphorylation, a process that is potassium-regulated and dependent on With-No-Lysine (WNK) kinases. KS-WNK1, a kidney-specific WNK1 isoform lacking the kinase domain, controls WNK signaling pathway localization in the DCT. Its role in NCC regulation, however, is unresolved: while early studies proposed that KS-WNK1 functions as an NCC inhibitor, recent work suggests that it activates NCC. To evaluate the role of KS-WNK1 on potassium-dependent NCC regulation, we studied KS-WNK1-KO mice across a wide range of plasma K+ (2.0-9.0 mmol/L), induced by dietary maneuvers and diuretic challenges. Potassium-deprived KS-WNK1-KO mice exhibited low WNK-dependent NCC phosphorylation compared to littermates, indicating that KS-WNK1 activates NCC during K+ deficiency. In contrast, relative NCC phosphorylation was high in potassium-loaded KS-WNK1-KO mice, consistent with KS-WNK1-mediated NCC inhibition during hyperkalemia. An integrated analysis revealed that KS-WNK1 expands the dynamic range of NCC responsiveness to potassium, steepening the linear inverse relationship between NCC phosphorylation and plasma [K+]. The effect of KS-WNK1 deletion was strongest in potassium-restricted females, as they developed exaggerated hypokalemia and thiazide insensitivity due to low NCC activity. Taken together, these findings indicate that KS-WNK1 is a potassium-responsive signaling amplifier that converts small changes in [K+] into large effects on NCC phosphorylation. This effect predominates in females during potassium deficiency, when high NCC activity is required to maintain salt reabsorption without exacerbating K+ losses. These observations define the role of KS-WNK1 in NCC regulation, and identify a novel mechanism that contributes to sexual dimorphism in the mammalian nephron.


title: Paper-and-pencil questionnaires analysis: a new automated technique to reduce analysis time and errors.

abstract:
Background and ObjectiveQuestionnaires are essential tools in many scientific fields, including health and medicine. However, the analysis of paper-and-pencil questionnaires is time consuming, source of errors and expensive, limiting its use in large cohort studies. Computer-based questionnaires might be a valuable alternative but they may introduce bias, especially for sensitive questions, and they require programming skills. The aim of this study is to develop a reliable and adaptable open-source technique (i.e. LightQuest) to automatically analyse various types of scanned paper-and-pencil questionnaires with closed questions, including those with inverted scale.

MethodsTo evaluate the usefulness of LightQuest, the time needed for 7 experimenters for manually code 10 sets of 4 frequently used questionnaires and the number of errors (i.e. reliability) were compared with the time and errors their made using LightQuest.

ResultsLightQuest was twice as fast as the manual analysis, even though the time to create the reference model was taken into account (933s vs. 1935s, t(2)=8.81, p<0.001). Without model creation, the reduced analysis time was more pronounced, with an average of 2.77s.question-1 for the manual technique versus 0.55s.question-1 for LightQuest (t(2)=22.5, p<0.001). Moreover, during correction of the 5180 questions performed by the 7 experimenters, LightQuest made a total of 2 errors versus 46 with the manual technique (q(2)=4.53, p<0.05).

ConclusionLightQuest demonstrated clear superiority both in terms of time and reliability. The script of this first open-source technique, which does not require programming skills, is downloadable in supplemental data and may become an asset for all studies using questionnaires.

category: scientific communication and education


title: Next-generation biocomputing: mimicking artificial neural network with genetic circuits

abstract: Artificial neural network (ANN) is nowadays one of the most used and researched computational methods. In the field of biocomputing, however, synthetic biologists are still using logic gate technologies to design genetic circuits. We here propose and computationally validate a novel method to mimic ANN with genetic circuits. We first describe the flow and the mathematical expression of this genetic circuit design and then we provide in silico proof to support the functionality of our method in regression and classification analyses. We believe that this de novo genetic circuit design method would have wide applications in biotechnology.

category: synthetic biology


title: Learning accurate path integration in a ring attractor model of the head direction system

abstract: Ring attractor models for angular path integration have recently received strong experimental support. To function as integrators, head-direction (HD) circuits require precisely tuned connectivity, but it is currently unknown how such tuning could be achieved. Here, we propose a network model in which a local, biologically plausible learning rule adjusts synaptic efficacies during development, guided by supervisory allothetic cues. Applied to the Drosophila HD system, the model learns to path-integrate accurately and develops a connectivity strikingly similar to the one reported in experiments. The mature network is a quasi-continuous attractor and reproduces key experiments in which optogenetic stimulation controls the internal representation of heading, and where the network remaps to integrate with different gains. Our model predicts that path integration requires supervised learning during a developmental phase. The model setting is general and also applies to architectures that lack the physical topography of a ring, like the mammalian HD system.


title: The geometry of face memory

abstract: The ability to recognize familiar visual objects is critical to survival. A central assumption of neuroscience is that long-term memories are represented by the same brain areas that encode sensory stimuli (1). Neurons in inferotemporal (IT) cortex represent the sensory percept of visual objects using a distributed axis code (2-4). Whether and how the same IT neural population represents the long-term memory of visual objects remains unclear. Here, we examined how familiar faces are encoded in face patch AM and perirhinal cortex. We found that familiar faces were represented in a distinct subspace from unfamiliar faces. The familiar face subspace was shifted relative to the unfamiliar face subspace at short latency and then distorted to increase neural distances between familiar faces at long latency. This distortion enabled markedly improved discrimination of familiar faces in both AM and PR. Inactivation of PR did not affect these memory traces in AM, suggesting that the memory traces arise from intrinsic recurrent processes within IT cortex or interactions with downstream regions outside the medial temporal lobe (5, 6). Overall, our results reveal that memories of familiar faces are represented in IT and perirhinal cortex by a distinct long-latency code that is optimized to distinguish familiar identities.


title: The neural code for face memory


title: Joint inference of adaptive and demographic history from temporal population genomic data

abstract: Disentangling the effects of selection and drift is a long-standing problem in population genetics. Recently, simulations shows that pervasive selection may bias the inference of demography. Ideally, models for the inference of demography and selection should account for the interaction between these two forces. With simulation-based likelihood-free methods such as Approximate Bayesian Computation, demography and selection parameters can be jointly estimated (ABC). We propose a ABC-Random Forests framework to jointly infer demographic and selection parameters from temporal population genomic data (e.g. experimental evolution, monitored populations, ancient DNA). Our framework allowed the separation of demography (census size, N) from the genetic drift (effective population size, Ne), and the estimation of genome-wide parameters of selection. Selection parameters informed us about the adaptive potential of a population (the scale mutation rate of beneficial mutations,{theta} b), the realized potential, as the number of strong beneficial under selection, and fitness diversity as the population genetic load. We applied this approach to a dataset of feral populations of honey bees (Apis mellifera) collected in California, and we estimated parameters consistent with the biology and the recent history of this species.


title: Performance comparison and in-silico harmonisation of commercial platforms for DNA methylome analysis by targeted bisulfite sequencing

abstract: DNA methylation is a key epigenetic modification in the regulation of cell fate and differentiation, and its analysis is gaining increasing importance in both basic and clinical research. Targeted Bisulfite Sequencing (TBS) has become the method of choice for the cost-effective, targeted analysis of the human methylome at base-pair resolution. Here we benchmarked five commercially available TBS platforms, including three hybridization capture-based (Agilent, Roche, and Illumina) and two RRBS-based (Diagenode and NuGen), across 16 samples. A subset of these were also compared to whole-genome DNA methylation sequencing with the Illumina and Oxford Nanopore platforms. We assessed performance with respect to workflow complexity, on/off-target performance, coverage, accuracy and reproducibility. We find all platforms able to produce usable data but major differences for some performance criteria, especially in the number and identity of the CpG sites covered, which affects the interoperability of datasets generated on these different platforms. To overcome this limitation, we used imputation and show that it improves the interoperability from an average of 10.35% (0.8M CpG sites) to 97% (7.6M CpG sites). Our study provides cross-validated guidance on which TBS platform to use for different features of the methylome and offers an imputation-based harmonization solution for improved interoperability between platforms, allowing comparative and integrative analysis.


title: Multi-compartment analysis of the complex gradient-echo signal quantifies myelin breakdown in premanifest Huntington's disease

abstract: White matter (WM) alterations have been identified as a relevant pathological feature of Huntingtons disease (HD). Increasing evidence suggests that WM changes in this disorder are due to alterations in myelin-associated biological processes. Multi-compartmental analysis of the complex gradient-echo MRI signal evolution in WM has been shown to quantify myelin in vivo, therefore pointing to the potential of this technique for the study of WM myelin changes in health and disease. This study first characterized the reproducibility of metrics derived from the complex multi-echo gradient-recalled echo (mGRE) signal across the corpus callosum in healthy participants, finding highest reproducibility in the posterior callosal segment. Subsequently, the same analysis pipeline was applied in this callosal region in a sample of premanifest HD patients (n = 19) and age, sex and education matched healthy controls (n = 21). In particular, we focused on two myelin-associated derivatives: i. the myelin water signal fraction (fm), a parameter dependent on myelin content; and ii. the difference in frequency between myelin and intra-axonal water pools ({Delta}{omega}), a parameter dependent on the ratio between the inner and the outer axonal radii. fm was found to be lower in HD patients ({beta} = -0.13, p = 0.03), while {Delta}{omega} did not show a group effect. Performance in tests of working memory, executive function, social cognition and movement was also assessed, and a greater age-related decline in executive function was detected in HD patients ({beta} = -0.06, p = 0.006), replicating previous evidence of executive dysfunction in HD. Finally, the correlation between fm, executive function, and proximity to disease onset was explored in patients, and a positive correlation between executive function and fm was detected (r = 0.542; p = 0.02). This study emphasises the potential of complex mGRE signal analysis for aiding understanding of HD pathogenesis and progression. Moreover, expanding on evidence from pathology and animal studies, it provides novel in vivo evidence supporting myelin breakdown as an early feature of HD.


title: Zetaproteobacteria pan-genome reveals candidate gene cluster for twisted stalk biosynthesis and export

abstract: Twisted stalks are morphologically unique bacterial extracellular organo-metallic structures containing Fe(III) oxyhydroxides that are produced by microaerophilic Fe(II)-oxidizers belonging to the Betaproteobacteria and Zetaproteobacteria. Understanding the underlying genetic and physiological mechanisms of stalk formation is of great interest based on their potential as novel biogenic nanomaterials and their relevance as putative biomarkers for microbial Fe(II) oxidation on ancient Earth. Despite the recognition of these special biominerals for over 150 years, the genetic foundation for the stalk phenotype has remained unresolved. Here we present a candidate gene cluster for the biosynthesis and secretion of the stalk organic matrix that we identified with a trait-based analyses of a pan-genome comprising 16 Zetaproteobacteria isolate genomes. The "stalk formation in Zetaproteobacteria" (sfz) cluster comprises six genes (sfz1-sfz6), of which sfz1 and sfz2 were predicted with functions in exopolysaccharide synthesis, regulation, and export, sfz4 and sfz6 with functions in cell wall synthesis manipulation and carbohydrate hydrolysis, and sfz3 and sfz5 with unknown functions. The stalk-forming Betaproteobacteria Ferriphaselus R-1 and OYT-1, as well as dread-forming Zetaproteobacteria Mariprofundus aestuarium CP-5 and Mariprofundus ferrinatatus CP-8 contain distant sfz gene homologues, whereas stalk-less Zetaproteobacteria and Betaproteobacteria lack the entire gene cluster. Our pan-genome analysis further revealed a significant enrichment of clusters of orthologous groups (COGs) across all Zetaproteobacteria isolate genomes that are associated with the regulation of a switch between sessile and motile growth controlled by the intracellular signaling molecule c-di-GMP. Potential interactions between stalk-former unique transcription factor genes, sfz genes, and c-di-GMP point towards a c-di-GMP regulated surface attachment function of stalks during sessile growth.


title: Crosstalk in oxygen homeostasis networks: SKN-1/NRF inhibits the HIF-1 hypoxia-inducible factor in Caenorhabditis elegans

abstract: During development, homeostasis, and disease, organisms must balance responses that allow adaptation to low oxygen (hypoxia) with those that protect cells from oxidative stress. The evolutionarily conserved hypoxia-inducible factors are central to these processes, as they orchestrate transcriptional responses to oxygen deprivation. Here, we employ genetic strategies in C. elegans to identify stress-responsive genes and pathways that modulate the HIF-1 hypoxia-inducible factor and facilitate oxygen homeostasis. Through a genome-wide RNAi screen, we show that RNAi-mediated mitochondrial or proteasomal dysfunction increases the expression of hypoxia-responsive reporter Pnhr-57:GFP in C. elegans. Interestingly, only a subset of these effects requires hif-1. Of particular importance, we found that skn-1 RNAi increases the expression of hypoxia-responsive reporter Pnhr-57:GFP and elevates HIF-1 protein levels. The SKN-1/NRF transcription factor has been shown to promote oxidative stress resistance. We present evidence that the crosstalk between HIF-1 and SKN-1 is mediated by EGL-9, the prolyl hydroxylase that targets HIF-1 for oxygen-dependent degradation. Treatment that induces SKN-1, such as heat, increases expression of a Pegl-9:GFP reporter, and this effect requires skn-1 function and a putative SKN-1 binding site in egl-9 regulatory sequences. Collectively, these data support a model in which SKN-1 promotes egl-9 transcription, thereby inhibiting HIF-1. We propose that this interaction enables animals to adapt quickly to changes in cellular oxygenation and to better survive accompanying oxidative stress.


title: Experience-related remapping of temporal encoding by striatal ensembles.

abstract: Temporal control of action is key for a broad range of behaviors and is disrupted in human diseases such as Parkinsons disease and schizophrenia. A brain structure that is critical for temporal control is the dorsal striatum. Experience and learning can influence dorsal striatal neuronal activity, but it is unknown how these neurons change with experience in contexts which require precise temporal control of movement. We investigated this question by recording from medium-spiny neurons (MSNs) in the dorsal striatum of mice as they gained experience controlling their actions in time. We leveraged an interval timing task optimized for mice which required them to "switch" response ports after enough time had passed without receiving a reward. We report three main results. First, we found that time-related ramping activity and response-related activity increased with more experience. Second, temporal decoding by MSN ensembles improved with experience and was predominantly driven by time-related ramping activity. Finally, we found that some MSNs had differential modulation on error trials. These findings enhance our understanding of dorsal striatal temporal processing by demonstrating how MSN ensembles can evolve with experience. Our results can be linked to temporal habituation and illuminate striatal flexibility during interval timing, which may be relevant for human disease.


title: Primed to Die: An Investigation of the Genetic Mechanisms Underlying Noise-Induced Hearing Loss and Cochlear Damage in Homozygous Foxo3-knockout Mice

abstract: The prevalence of noise-induced hearing loss (NIHL) continues to increase, with limited therapies available for individuals with cochlear damage. We have previously established that the transcription factor FOXO3 is necessary to preserve outer hair cells (OHCs) and hearing thresholds up to two weeks following a mild noise exposure in mice. The mechanisms by which FOXO3 preserves cochlear cells and function are unknown. In this study, we analyzed the immediate effects of mild noise exposure on wild-type, Foxo3 heterozygous (Foxo3+/KO), and Foxo3 knock-out (Foxo3KO/KO) mice to better understand FOXO3s role(s) in the mammalian cochlea. We used confocal and multiphoton microscopy to examine well-characterized components of noise-induced damage including calcium regulators, oxidative stress, necrosis, and caspase-dependent and -independent apoptosis. Lower immunoreactivity of the calcium buffer oncomodulin in Foxo3KO/KO OHCs correlated with cell loss beginning 4 hours post-noise exposure. Using immunohistochemistry, we identified parthanatos as the cell death pathway for OHCs. Oxidative stress response pathways were not significantly altered in FOXO3s absence. We used RNA sequencing to identify and RT-qPCR to confirm differentially expressed genes. We further investigated a gene downregulated in the unexposed Foxo3KO/KO mice that may contribute to OHC noise susceptibility. Glycerophosphodiester Phosphodiesterase Domain Containing 3 (GDPD3), a possible endogenous source of lysophosphatidic acid (LPA), has not previously been described in the cochlea. As LPA reduces OHC loss after severe noise exposure, we treated noise exposed Foxo3KO/KO mice with exogenous LPA. LPA treatment delayed immediate damage to OHCs but was insufficient to ultimately prevent their death or prevent hearing loss. These results suggest that FOXO3 acts prior to acoustic insult to maintain cochlear resilience, possibly through sustaining endogenous LPA levels.


title: Comparison of domain adaptation techniques for white matter hyperintensity segmentation in brain MR images

abstract: Robust automated segmentation of white matter hyperintensities (WMHs) in different datasets (domains) is highly challenging due to differences in acquisition (scanner, sequence), population (WMH amount and location) and limited availability of manual segmentations to train supervised algorithms. In this work we explore various domain adaptation techniques such as transfer learning and domain adversarial learning methods, including domain adversarial neural networks and domain unlearning, to improve the generalisability of our recently proposed triplanar ensemble network, which is our baseline model. We evaluated the domain adaptation techniques on source and target domains consisting of 5 different datasets with variations in intensity profile, lesion characteristics and acquired using different scanners. For transfer learning, we also studied various training options such as minimal number of unfrozen layers and subjects required for finetuning in the target domain. On comparing the performance of different techniques on the target dataset, unsupervised domain adversarial training of neural network gave the best performance, making the technique promising for robust WMH segmentation.


title: Rediscovering the musician's brain: a systematic review and meta-analysis

abstract: Through long-term training, music experts acquire complex and specialized sensorimotor skills, which are paralleled by continuous neuro-anatomical and -functional adaptations. The underlying neuroplasticity mechanisms have been extensively explored in decades of research in music, cognitive, and translational neuroscience. However, the absence of a comprehensive review and quantitative meta-analysis prevents the plethora of variegated findings to ultimately converge into a unified picture of the neuroanatomy of musical expertise. Here, we performed a comprehensive neuroimaging meta-analysis of publications investigating neuro-anatomical and -functional differences between musicians (M) and non-musicians (NM). Eighty-four studies were included in the qualitative synthesis. From these, 58 publications were included in coordinate-based meta-analyses using the anatomic/activation likelihood estimation (ALE) method. This comprehensive approach delivers a coherent cortico-subcortical network encompassing sensorimotor and limbic regions bilaterally. Particularly, M exhibited higher volume/activity in auditory, sensorimotor, interoceptive, and limbic brain areas and lower volume/activity in parietal areas as opposed to NM. Notably, we reveal topographical (dis-)similarities between the identified functional and anatomical networks and characterize their link to various cognitive functions by means of meta-analytic connectivity modelling. Overall, we effectively synthesized decades of research in the field and provide a consistent and controversies-free picture of the neuroanatomy of musical expertise.


title: An ALE meta-analytic review of musical expertise


title: Measuring context-dependent memory in rodents: a systematic review and meta-analysis of important variables in the object-in-context task.

abstract: Environmental information plays an important role in remembering events. Information about stable aspects of the environment (here referred to as  context) and the event are combined by the hippocampal system and stored as context-dependent memory. In rodents (such as rats and mice), context-dependent memory is often investigated with the object-in-context task. However, the implementation and interpretation of this task varies considerably across studies. This variation hampers the comparison between studies and - for those who design a new experiment or carry out pilot experiments - the estimation of whether observed behavior is within the expected range. Also, it is currently unclear which of the variables critically influence the outcome of the task. To address these issues, we carried out a preregistered systematic review (PROSPERO CRD42020191340) and provide an up-to-date overview of the animal-, task-, and protocol-related variations in the object-in-context task for rodents. Using a data-driven explorative meta-analysis we next identified critical factors influencing the outcome of this task, such as sex, testbox size and the delay between the learning trials. Based on these observations we provide recommendations to create more consensus in the set-up, procedure and interpretation of the object-in-context task for rodents. This could contribute to a more robust and evidence-based design in future animal experiments.