title: OptoRheo: Simultaneous in situ micro-mechanical sensing and 3D imaging of live cell cultures

abstract: Biomechanical cues from the extracellular matrix (ECM) are essential for directing many cellular processes, from normal development and repair to disease progression. To better understand cell-matrix interactions, we have developed an optical instrument combining light sheet fluorescence microscopy with particle tracking microrheology. We name this new instrument OptoRheo. OptoRheo lets us image cells in 3D as they proliferate over several days while simultaneously sensing the biomechanical properties of the surrounding extracellular and pericellular matrix at a sub-cellular scale. OptoRheo can be used in two operational modalities to extend the dynamic range of microrheology measurements, making the instrument suitable for different cell culture systems. We corroborated this by characterising the ECM surrounding live breast cancer cells in two distinct culture systems, 3D hydrogels and suspension culture. This cutting-edge instrument will transform the exploration of drug transport through complex cell culture matrices and optimise the design of the next-generation disease models.


title: CAPG: Comprehensive Allopolyploid Genotyper

abstract:
MotivationGenotyping by sequencing is a powerful tool for investigating genetic variation in plants, but many economically important plants are allopolyploids, where homoeologous similarity obscures the subgenomic origin of reads and confounds allelic and homoeologous SNPs. Recent polyploid genotyping methods use allelic frequencies, rate of heterozygosity, parental cross or other information to resolve read assignment, but good subgenomic references offer the most direct information. The typical strategy aligns reads to the joint reference, performs diploid genotyping within each subgenome, and filters the results, but persistent read misassignment results in an excess of false heterozygous calls.

ResultsWe introduce the Comprehensive Allopolyploid Genotyper (CAPG), which formulates an explicit likelihood to weight read alignments against both subgenomic references and genotype individual allopolyploids from whole genome resequencing (WGS) data. We demonstrate CAPG in allotetraploids, where it performs better than GATKs HaplotypeCaller applied to reads aligned to the combined subgenomic references.

AvailabilityCode and tutorials are available at https://github.com/Kkulkarni1/CAPG.git.

category: bioinformatics


title: Glucagon-Like Peptide-1 Receptor Activation Stimulates PKA-Mediated Phosphorylation of Raptor and this Contributes to the Weight Loss Effects of Liraglutide

abstract:
ObjectiveGlucagon-like peptide 1 (GLP-1) receptor (GLP-1R) agonists are approved for obesity management, yet surprisingly little is known about the signaling mechanisms mediating GLP-1R agonist-induced anorexia and weight loss. We have shown that GLP-1R activation in the ventromedial hypothalamus (VMH) stimulates mechanistic Target of Rapamycin Complex 1 (mTORC1) activity, and this is necessary for the ability of VMH GLP-1R agonism to reduce food intake and body weight. Here, we aim to define the signaling mechanisms by which GLP-1R activation induces mTORC1 activity to regulate body weight. Although mTORC1 is classically activated by Akt, previous studies show that the canonical target of the GLP-1R, Protein Kinase A (PKA), stimulates mTORC1 signaling by phosphorylating the mTOR-regulating protein Raptor at Ser791 following {beta}-adrenergic stimulation. Thus, we tested whether GLP-1R agonists similarly stimulate mTORC1 activity via PKA phosphorylation of Raptor at Ser791 and whether this phosphorylation event is relevant to the weight loss effect of the therapeutic GLP-1R agonist liraglutide.

MethodsWe treated Chinese Hamster Ovary (CHO-K1) cells stably expressing the human GLP-1R (hGLP1R) with the GLP-1R agonist liraglutide in combination with either of the PKA inhibitors H89 or KT5720 and measured phosphorylation of the mTORC1 signaling target ribosomal protein S6. To test whether PKA phosphorylates Raptor at Ser791 in response to liraglutide, we expressed myc-tagged wild-type (WT) Raptor or a PKA-resistant (Ser791Ala) Raptor mutant in hGLP1R-stably expressing CHO-K1 cells, treated them with vehicle or liraglutide, immunoprecipitated myc-WT or myc-Ser791Ala Raptor, and immunoblotted for phosphorylation of the PKA substrate RRXS*/T* motif, as previously described by Liu et al.1. To assess the physiological relevance of GLP-1R agonist-induced PKA phosphorylation of Raptor, we measured the body weight response to vehicle or liraglutide in WT mice and mice with a targeted knock-in of PKA-resistant Ser791Ala Raptor.

ResultsIn CHO-K1 cells stably expressing the hGLP1R, liraglutide significantly increased phosphorylation of S6 and PKA phosphorylation of myc-tagged WT Raptor, both of which were blocked by PKA inhibition. Liraglutide also failed to stimulate phosphorylation of the PKA-targeting motif in cells expressing myc-Ser791Ala Raptor. In addition, knock-in mice expressing Ser791Ala Raptor were partially resistant to GLP-1R agonist-induced weight loss.

ConclusionOur results demonstrate that PKA activation downstream of the GLP-1R leads to phosphorylation of Raptor at Ser791, which activates mTORC1 signaling in a non-canonical fashion to facilitate the weight lowering effects of liraglutide.

category: physiology


title: Resilience in soil bacterial communities of the boreal forest from one to five years after wildfire across a severity gradient

abstract: Wildfires can represent a major disturbance to ecosystems, including soil microbial communities belowground. Furthermore, fire regimes are changing in many parts of the world, altering and often increasing fire severity, frequency, and size. The boreal forest and taiga plains ecoregions of northern Canada are characterized by naturally-occurring stand-replacing wildfires on a 40-350 year basis. We previously studied the effects of wildfire on soil microbial communities one year post-fire across 40 sites, spanning a range of burn severity. Here, we return to the same sites five years post-fire to test a series of hypotheses about the effects of fire on bacterial community composition. We ask the following questions: (1a) Do the fundamental factors structuring bacterial community composition remain the same five years post-fire? (1b) Do the effects of fire on bacterial community composition decrease between one and five years post-fire? (1c) Do shifts in bacterial community composition between one and five years post-fire suggest resilience? (2a) Does the importance of fast growth diminish between one and five years post-fire? (2b) Do short-term post-fire responders continue to dominate the community five years post-fire? We find the following: (1a) Five years post-fire, vegetation community, moisture regime, pH, total carbon, texture, and burned/unburned all remained significant predictors of bacterial community composition with similar predictive value (R2). (1b and 1c) Bacterial communities became more similar to unburned sites five years post-fire, across the range of severity, suggesting resilience, while general structure of co-occurrence networks remained similar one and five years post-fire. (2a) Fast growth potential, as estimated using predicted 16S rRNA copy numbers, was no longer significantly correlated with burn severity five years post-fire, indicating the importance of this trait for structuring bacterial community composition may be limited to relatively short timescales. (2b) Many taxa that were enriched in burned sites one year post-fire remained enriched five years post-fire, although the degree to which they were enriched generally decreased. Specific taxa of interest from the genera Massilia, Blastococcus, and Arthrobacter all remained significantly enriched, suggesting that they may have traits that allow them to continue to flourish in the post-fire environment, such as tolerance to increased pH or ability to degrade pyrogenic organic matter. This hypothesis-based work expands our understanding of the post-fire recovery of soil bacterial communities and raises new hypotheses to test in future studies.

category: ecology


title: Accurate and sensitive mutational signature analysis with MuSiCal

abstract: Mutational signature analysis is a recent computational approach for interpreting somatic mutations in the genome. Its application to cancer data has enhanced our understanding of mutational forces driving tumorigenesis and demonstrated its potential to inform prognosis and treatment decisions. However, methodological challenges remain for discovering new signatures and assigning proper weights to existing signatures, thereby hindering broader clinical applications. We present MuSiCal (Mutational Signature Calculator), a rigorous analytical framework with novel algorithms that solves fundamental problems in the standard workflow. Our simulation studies demonstrate that MuSiCal outperforms state-of-the-art algorithms for both signature discovery and assignment. By reanalyzing over 2,700 cancer genomes, we provide an improved reference catalog of signatures and their assignments, discover nine indel signatures absent in the current catalog, resolve long-standing issues with the ambiguous  flat signatures, and give insights into signatures with unknown etiologies. We expect MuSiCal and the improved catalog to be a step towards establishing best practices for mutational signature analysis.

category: genomics


title: Computational modeling of deep tissue heating by an automatic thermal massage bed: predicting the effects on circulation

abstract: Automatic thermal and mechanical massage beds support selfmanaged treatment, including reduction of pain and stress, enhanced circulation, and improved mobility. As the devices become more sophisticated (increasing the degrees of freedom), it is essential to identify the settings that best target the desired tissue. To that end, we developed an MRI-derived model of the lower back and simulated the physiological effects of a commercial thermal-mechanical massage bed. Here we specifically estimated the tissue temperature and increased circulation under steady-state conditions for typical thermal actuator settings (i.e., 45-65{degrees}C). Energy transfer across nine tissues was simulated with finite element modeling (FEM) and the resulting heating was coupled to blood flow with an empirically-guided model of temperature-dependent circulation. Our findings indicate that thermal massage increases tissue temperature by 3-8{degrees}C and 1-3{degrees}C at depths of 2 and 3 cm, respectively. Importantly, due to the rapid (non-linear) increase of circulation with local temperature, this is expected to increase blood flow four-fold (4x) at depths occupied by deep tissue and muscle. These predictions are consistent with prior clinical observations of therapeutic benefits derived from spinal thermal massage.

category: bioengineering


title: Odorant molecular feature mining by diverse deep neural networks for prediction of odor perception categories

abstract: The prediction of structure-odor-relationship (SOR) by deep neural networks (DNN) via the structural features of odorants has attracted great attention during the past decade. Due to the limited knowledge on binding mechanism between odorant molecules and olfactory receptors, however, it is not sure what kind of structural features play the most important role in smell recognition. Here, diverse DNNs, including molecular parameters neural network, molecular graphic convolution neural network (MG-CNN), molecular graph transformer neural network, and atom interaction neural network, were used to extract the structure features of molecules and to predict the categorized odor perception. The experimental results demonstrated that an MG-CNN combined with a multi-label DNN classifier produced the best results, with an area under the receiver operating characteristic curve and F1-score of 0.877{+/-}0.028 and 0.726{+/-}0.028, respectively. This is the first systematic study for molecular structure features extracted by different deep neural network and their predictive effect for SOR. We believe that these insights regarding the use of DNN-based odorant molecular feature extraction for odor sensory identification will be useful for introducing biologically interpretable artificial intelligence into olfactometry, and thus contribute to our understanding of the mechanisms underlying human olfaction.


title: Great tits differ in glucocorticoid plasticity in response to spring temperature

abstract: Fluctuations in environmental temperature affect energy metabolism, stimulating the expression of phenotypic plasticity in behavioral and physiological traits. Vertebrate hormonal signals like glucocorticoids underpin environmentally-induced phenotypic plasticity, with changes in circulating concentrations orchestrating plastic changes in diverse traits. Climate change is predicted to alter temperature variation globally, making it imperative to evaluate whether free-living animal populations can cope adaptively. To evaluate their potential to respond to ongoing global change, we quantified individual variation in glucocorticoid plasticity to ambient temperature in wild great tits (Parus major). Using a reaction norm approach, we repeatedly sampled individuals for circulating glucocorticoid concentrations across five years. As expected, baseline and stress-induced glucocorticoid concentrations increased with lower ambient temperatures at the population and within-individual level. Moreover, we provide unique evidence that free-living individuals differ significantly in their plastic responses to temperature variation for both glucocorticoid traits, with some displaying greater plasticity than others. Average concentrations and degree of plasticity covaried for baseline glucocorticoids, indicating that these two reaction norm components are linked. Hence, individual variation in glucocorticoid plasticity to an important environmental factor exists in a wild population, representing a crucial step to assess the adaptive potential of vertebrates to endure current temperature fluctuations.


title: Learning High-Order Interactions for Polygenic Risk Prediction

abstract:
Within the framework of precision medicine, the stratification of individual genetic susceptibility based on inherited DNA variation has paramount relevance. However, one of the most relevant pitfalls of traditional Polygenic Risk Scores (PRS) approaches is their inability to model complex high-order non-linear SNP-SNP interactions and their effect on the phenotype (e.g. epistasis). Indeed, they incur in a computational challenge as the number of possible interactions grows exponentially with the number of SNPs considered, affecting the statistical reliability of the model parameters as well. In this work, we address this issue by proposing a novel PRS approach, called High-order Interactions-aware Polygenic Risk Score (hiPRS), that incorporates high-order interactions in modeling polygenic risk. The latter combines an interaction search routine based on frequent itemsets mining and a novel interaction selection algorithm based on Mutual Information, to construct a simple and interpretable weighted model of user-specified dimensionality that can predict a given binary phenotype. Compared to traditional PRSs methods, hiPRS does not rely on GWAS summary statistics nor any external information. Moreover, hiPRS differs from Machine Learning-based approaches that can include complex interactions in that it provides a readable and interpretable model and it is able to control overfitting, even on small samples. In the present work we demonstrate through a comprehensive simulation study the superior performance of hiPRS w.r.t. state of the art methods, both in terms of scoring performance and interpretability of the resulting model. We also test hiPRS against small sample size, class imbalance and the presence of noise, showcasing its robustness to extreme experimental settings. Finally, we apply hiPRS to a case study on real data from DACHS cohort, defining an interaction-aware scoring model to predict mortality of stage II-III Colon-Rectal Cancer patients treated with oxaliplatin.

Author summaryIn the precision medicine era, understanding how genetic variants affect the susceptibility to complex diseases is key, and great attention has been posed to Single Nucleotide Polymorphisms (SNPs) and their role in disease risk or clinical treatments outomes. Several approaches to quantify and model this impact have been proposed, called Polygenic Risk Scores (PRSs), but they traditionally do not account for possible interactions among SNPs. This is a significant drawback, as complex high-order SNP-SNP interactions can play an important role in determining the phenotype (a phenomenon called epistasis). Nevertheless, the number of possible combinations grows exponentially with the number of SNPs considered and including them in a predictive model becomes computationally challenging and affects the statistical reliability of the model. Some Machine Learning algorithms can answer this problem, but they are hardly interpretable. Here, we tackle these and other drawbacks of existing approaches proposing our novel PRS approach, hiPRS, that provides an interpretable weighted model with a user-defined number of predictive interactions. We designed it to handle typical real-life research scenarios, like small sample sizes and class imbalance, and we demonstrate here its superiority with respect to state-of-the-art methods.


title: Benchmarking brain organoid recapitulation of fetal corticogenesis

abstract: Brain organoids are becoming increasingly relevant to dissect the molecular mechanisms underlying psychiatric and neurological conditions. The in vitro recapitulation of key features of human brain development affords the unique opportunity of investigating the developmental antecedents of neuropsychiatric conditions in the context of the actual patients genetic backgrounds. Specifically, multiple strategies of brain organoid (BO) differentiation have enabled the investigation of human cerebral corticogenesis in vitro with increasing accuracy. However, the field lacks a systematic investigation of how closely the gene co-expression patterns seen in cultured BO from different protocols match those observed in fetal cortex, a paramount information for ensuring the sensitivity and accuracy of modeling disease trajectories. Here we benchmark BO against fetal corticogenesis by integrating transcriptomes from in-house differentiated cortical BO (CBO), other BO systems, human fetal brain samples processed in-house, and prenatal cortices from the BrainSpan Atlas. We identified co-expression patterns and prioritized hubs of human corticogenesis and CBO differentiation, highlighting both well-preserved and discordant trends across BO protocols, including different degrees of heterochronicity in differentiation across BO models compared to fetal cortex. Our approach provides a framework to directly compare the extent of in vivo/in vitro alignment of neurodevelopmentally relevant processes and their attending temporalities, structured as an accessible resource to query for modelling human corticogenesis and the neuropsychiatric outcomes of its alterations.

category: developmental biology


title: Gene Transfer based Phylogenetics: Analytical Expressions and Additivity via Birth/Death Theory

abstract:
The genomic era has opened up vast opportunities in molecular systematics, one of which is deciphering the evolutionary history in fine detail. Under this mass of data, analysing the point mutations of standard markers is too crude and slow for fine-scale phylogenetics. Nevertheless, genome dynamics events provide far richer information. The synteny index (SI) between a pair of genomes combines gene order and gene content information, allowing the comparison of genomes of unequal gene content, together with order considerations of their common genes. Recently, genome dynamics has been modelled as a continuous-time Markov process, and gene distance in the genome as a birth-death-immigration process. Nevertheless, due to complexities arising in this setting such as overlapping neighbourhoods and other confounding factors, no precise and provably consistent estimators could be derived.

Here, we extend this modelling approach by using techniques from birth-death theory to derive explicit expressions of the systems probabilistic dynamics in the form of rational functions of the model parameters. This, in turn, allows us to infer analytically the expected distances between organisms based on a transformation of their SI. Despite the complexity of the expressions obtained, we establish additivity of this estimated evolutionary distance (a desirable property yielding phylogenetic consistency).

Applying the new measure in simulation studies shows that it attains very accurate results in realistic settings and even under model extensions. In the real-data realm, we applied the new formulation to unique data structure that we constructed - the ordered orthology DB - based on a new version of the EggNOG database, to construct a tree with more than 4.5K taxa. The resulted tree was compared it with a NCBI taxonomy for these organisms. To the best of our knowledge, this is the largest gene-order-based tree constructed and it overcomes flaws found in previous approaches.

category: evolutionary biology


title: Does fatigue influence joint-specific work and ground force production during the first steps of maximal accelerative running?

abstract: The rate of initial acceleration during the first steps of a maximal-effort (sprint) run often determines success or failure in prey capture and predator evasion, and is a vital factor of success in many modern sports. However, accelerative events are commonly performed after having already run considerable distances, and the associated fatigue should impair muscle force production and thus reduce acceleration rate. Despite this, the effects of running-induced fatigue on our ability to accelerate as well as the running technique used to achieve it has been incompletely studied. We recorded 3-D kinematics and ground reaction forces during the first three steps of the acceleration phase from a standing start before and after performing a high-speed, multi-directional, fatiguing run-walk protocol in well-trained running athletes who were habituated to accelerative sprinting. We found that the athletes were able to maintain their rate of initial acceleration despite changing running technique, which was associated with use of a more upright posture, longer ground contact time, increased vertical ground reaction impulse, decreased hip flexion and extension velocities, and a shift in peak joint moments, power, and positive work from the hip to the knee joint; no changes were detected in ankle joint function. Thus, a compensatory increase in knee joint function alleviated the reduction in hip flexor-extensor capacity. These acute adaptations may indicate that the hip extensors (gluteal and hamstring muscle groups) were more susceptible to fatigue than the ankle and knee musculature, and may thus be a primary target for interventions promoting fatigue resistance.

category: biophysics


title: Deceptive learning in histopathology

abstract: Deep learning holds immense potential for histopathology, automating tasks that are simple for expert pathologists, and revealing novel biology for tasks that were previously considered difficult or impossible to solve by eye alone. However, the extent to which the visual strategies learned by deep learning models in histopathological analysis are trustworthy or not has yet to be systematically analyzed. In this work, we address this problem and discover new limits on the histopathological tasks for which deep learning models learn trustworthy versus deceptive solutions. While tasks that have been extensively studied in the field like tumor detection are reliable and trustworthy, recent advances demonstrating the ability to learn molecular profiling from hematoxylin and eosin (H&E) stained slides do not hold up to closer scrutiny. Our analysis framework represents a new approach in understanding the capabilities of deep learning models, which should be incorporated into the computational pathologists toolkit.

category: pathology


title: Heavy metals in moss guide environmental justice investigation: a case study using community science in Seattle, WA, USA

abstract: Heavy metals concentrations often vary at small spatial scales not captured by air monitoring networks, with implications for environmental justice in industrial-adjacent communities. Pollutants measured in moss tissues are commonly used as a screening tool to guide use of more expensive resources, like air monitors. Such studies, however, rarely address environmental justice issues or involve the residents and other decision-makers expected to utilize results. Here, we piloted a community science approach, engaging over 55 people from nine institutions, to map heavy metals using moss in two industrial-adjacent neighborhoods. This area, long known for disproportionately poor air quality, health outcomes, and racial inequities, has only one monitor for heavy metals. Thus, an initial understanding of spatial patterns is critical for gauging whether, where, and how to invest further resources towards investigating heavy metals. Local youth led sampling of the moss Orthotrichum lyellii from trees across a 250x250-m sampling grid (n = 79) and generated data comparable to expert-collected samples (n = 19). We mapped 21 chemical elements measured in moss, including 6 toxic  priority metals: arsenic, cadmium, chromium, cobalt, lead, and nickel. Compared to other urban O. lyellii studies, local moss had substantially higher priority metals, especially arsenic and chromium, encouraging community members to investigate further. Potential hotspots of priority metals varied somewhat but tended to peak near the central industrial core where many possible emissions sources, including legacy contamination, converge. Informed by these findings, community members successfully advocated regulators for a second study phase - a community-directed air monitoring campaign to evaluate residents exposure to heavy metals - as is needed to connect moss results back to the partnerships core goal of understanding drivers of health disparities. This follow-up campaign will measure metals in the PM10 fraction owing to clues in the current study that airborne soil and dust may be locally important carriers of priority metals. Future work will address how our approach combining bioindicators and community science ultimately affects success addressing longstanding environmental justice concerns. For now, we illustrate the potential to co-create new knowledge, to help catalyze and strategize next steps, in a complex air quality investigation.

category: scientific communication and education


title: Cluster-Based Inference for Memory-Based Cognition

abstract: This paper proposes a model of hippocampal-based category learning using a cluster-based inference framework which produces two systems (i) an extendable cluster-based memory module (CMM) that provides representations of learning episodes with strong pattern separation, and supports online decision making during that learning, (ii) cluster-based task modules (CTMs) which consolidate clusters learnt by CMM to support higher-accuracy decision making in the mid-term. Learning in CMMs optimises the joint probability of stimuli and category labels, whereas learning in CTMs optimises the probability of categories given stimuli. The latter system learns from the former via a process of "cluster consolidation". We apply the model to data from a behavioral learning task and find that, as well as improving categorisation performance, cluster consolidation decreases recognition scores for old cues but increases them for novel cues. This model-based perspective explains forgetting and false memory effects as serving future categorisation performance. The paper also expresses a view that models of memorybased cognition should provide human-level performance on complex categorisation tasks, and do so with minimal labelled data. In working toward this goal we therefore compared the accuracy of CMM- and CTM-based decision making to standard Softmax Regression approaches on benchmark machine learning datasets. This produced mixed results. We found some significant improvements of CMM over Softmax Regression and of CTM over CMM. Overall, our framework reconciles complementary learning systems theory with more recent findings from cognitive neuroscience of generative replay and hippocampal-based generalisation.

category: neuroscience


title: VelcroVax: a bolt-on vaccine platform technology improves antibody titres against a viral glycoprotein in mice

abstract: Having varied approaches to the design and manufacture of vaccines is critical in being able to respond to worldwide needs and to newly emerging pathogens. Virus-like particle (VLP) vaccines form the basis of two of the most successful licensed vaccines (against hepatitis B virus (HBV) and human papillomavirus). They are produced by recombinant expression of viral structural proteins, which self-assemble into immunogenic nanoparticles. VLPs can also be modified to present unrelated antigens, and here we describe a universal  bolt-on vaccine platform (termed VelcroVax) where the capturing VLP and the target antigen (hapten) are produced separately. We utilise a modified HBV core (HBcAg) VLP, with surface expression of a high-affinity binding sequence (Affimer) directed against a SUMO tag and use this to capture SUMO-tagged gp1 glycoprotein from the arenavirus, Junin virus (JUNV). Using this model system, we have solved high-resolution structures of VelcroVax VLPs, and shown that the VelcroVax-JUNV gp1 complex induces superior humoral immune responses compared to the non-complexed viral protein. We propose that this system could be modified to present a range of haptens and therefore form the foundation of future rapid-response vaccination strategies.

category: immunology


title: enclone: precision clonotyping and analysis of immune receptors

abstract:
Half a billion years of evolutionary battle forged the vertebrate adaptive immune system, an astonishingly versatile factory for molecules that can adapt to arbitrary attacks. The history of an individual encounter is chronicled within a clonotype: the descendants of a single fully rearranged adaptive immune cell. For B cells, reading this immune history for an individual remains a fundamental challenge of modern immunology. Identification of such clonotypes is a magnificently challenging problem for three reasons: O_LIThe cell history is inferred rather than directly observed: the only available data are the sequences of V(D)J molecules occurring in a sample of cells.
C_LIO_LIEach immune receptor is a pair of V(D)J molecules. Identifying these pairs at scale is a technological challenge and cannot be done with perfect accuracy--real samples are mixtures of cells and fragments thereof.
C_LIO_LIThese molecules can be intensely mutated during the optimization of the response to particular antigens, blurring distinctions between kindred molecules.
C_LI

It is thus impossible to determine clonotypes exactly. All solutions to this problem make a trade-off between sensitivity and specificity; useful solutions must address actual artifacts found in real data.

We present enclone1, a system for computing approximate clonotypes from single cell data, and demonstrate its use and value with the 10x Genomics Immune Profiling Solution. To test it, we generate data for 1.6 million individual B cells, from four humans, including deliberately enriched memory cells, to tax the algorithm and provide a resource for the community. We analytically determine the specificity of enclones clonotyping algorithm, showing that on this dataset the probability of co-clonotyping two unrelated B cells is around 10-9. We prove that using only heavy chains increases the error rate by two orders of magnitude.

enclone comprises a comprehensive toolkit for the analysis and display of immune receptor data. It is ultra-fast, easy to install, has public source code, comes with public data, and is documented at bit.ly/enclone. It has three "flavors" of use: (1) as a command-line tool run from a terminal window, that yields visual output; (2) as a command-line tool that yields parseable output that can be fed to other programs; and (3) as a graphical version (GUI).


title: Sex differences in NK cells mediated by the X-linked epigenetic regulator UTX

abstract: Viral infection outcomes are sex-biased, with males generally more susceptible than females. Paradoxically, the numbers of anti-viral natural killer (NK) cells are increased in males compared to females. Using samples from mice and humans, we demonstrate that while numbers of male NK cells are increased compared to females, they display impaired production of the anti-viral cytokine IFN-{gamma}. These sex differences were not due solely to divergent levels of gonadal hormones, since these differences persisted in gonadectomized mice. Instead, these differences can be attributed to lower male expression of X-linked Kdm6a (UTX), an epigenetic regulator which escapes X inactivation in female NK cells. NK cell-specific UTX deletion in females phenocopied multiple features of male NK cells, which include increased numbers and reduced IFN-{gamma} production. Integrative ATAC-seq and RNA-seq analysis revealed a critical role for UTX in the regulation of chromatin accessibility and gene expression at loci important in NK cell homeostasis and effector function. Consequently, NK cell-intrinsic UTX levels are critical for optimal anti-viral immunity, since mice with NK cell-intrinsic UTX deficiency show increased lethality to mouse cytomegalovirus (MCMV) challenge. Taken together, these data implicate UTX as a critical molecular determinant of NK cell sex differences and suggest enhancing UTX function as a new strategy to boost endogenous NK cell anti-viral responses.


title: Targeted single-cell genomics reveals novel host adaptation strategies of the symbiotic bacteria Endozoicomonas in Acropora tenuis coral

abstract: Endozoicomonas bacteria symbiose with various marine organisms and are known to be beneficial for coral health. However, genome analysis of coral-associated Endozoicomonas has been limited owing to the difficulty in cultivation and metagenomic approach by contamination of host-derived sequences. In this study, we applied a novel single-cell genomics technique using droplet microfluidics to obtain single-cell amplified genome (SAGs) for coral-associated Endozoicomonas spp. genome. We obtained seven novel Endozoicomonas genomes from Acropora tenuis coral. These genomes revealed that Endozoicomonas bacteria played host-associated functions in host corals and had undergone independent host-adaptive evolution in different clades. These adaptive evolutions were mediated by host-derived eukaryotic-like genes, some of which were speculated to influence host immune mechanisms. These genes are speculated to enhance coral tolerance to environmental stresses. This study suggests the possibility of host adaptation of Endozoicomonas spp. in symbiosis with corals and their contribution to coral bleaching tolerance.

category: microbiology


title: HIV-linked gut dysbiosis associates with cytokine production capacity in viral-suppressed people living with HIV

abstract:
People living with HIV (PLHIV) are exposed to chronic immune dysregulation, even when virus replication is suppressed by antiretroviral therapy (ART). Given the emerging role of the gut microbiome in immunity, we hypothesized that the gut microbiome may be related to the cytokine production capacity of PLHIV. To test this hypothesis, we collected metagenomic data from 143 ART-treated PLHIV and assessed the ex vivo production capacity of eight different cytokines (IL-1{beta}, IL-6, IL-1Ra, IL-10, IL17, IL22, TNF and IFN-{gamma}) in response to different stimuli. We also characterized CD4+ T cell-counts, HIV reservoir and other clinical parameters. Compared to 190 age- and sex-matched controls and a second independent control cohort, PLHIV showed microbial dysbiosis that was correlated with viral reservoir levels, cytokine production capacity and sexual behavior. Notably, we identified two genetically different P. copri strains that were enriched in either PLHIV or healthy controls. The control-enriched strain was negatively associated with IL-10, IL-6 and TNF production, independent of age, sex and sexual behavior, and positively associated with CD4+ T cell-level, whereas the PLHIV-enriched strain showed no associations. Our findings suggest that modulating the gut microbiome may be a strategy to modulate immune response in PLHIV.

Novel PointsO_LIWe identified compositional and functional changes in the gut microbiome of PLHIV that were strongly related to sexual behavior.
C_LIO_LIHIV-associated bacterial changes are negatively associated with HIV reservoir. The relative abundance of Firmicutes bacterium CAG 95 and Prevotella sp CAG 5226 both show a negative association with CD4+ T cell-associated HIV-1 DNA.
C_LIO_LIPrevotella copri and Bacteroides vulgatus show association with PBMC production capacity of IL-1{beta} and IL-10 that is independent of age, sex, BMI and sexual behavior.
C_LIO_LIWe observed two genetically different P. copri strains that are enriched in PLHIV and healthy individuals, respectively.
C_LIO_LIThe control-related P. copri strain specifically shows a negative association with IL-10, IL-6 and TNF production and a positive association with CD4+ T cell-level. This suggests it plays a potential protective role in chronic inflammation, which may be related to enrichment of a specific epitope peptide.
C_LI


title: Oral rabies vaccination of dogs - experiences from a field trial in Namibia

abstract:
Dog-mediated rabies is responsible for tens of thousands of human deaths annually, and in resource-constrained settings, vaccinating dogs to control the disease at source remains challenging. Currently, rabies elimination efforts rely on mass dog vaccination by the parenteral route. To increase the herd immunity, free-roaming and stray dogs need to be specifically addressed in the vaccination campaigns, with oral rabies vaccination (ORV) of dogs being a possible solution. Using a third-generation vaccine and a standardized egg-flavoured bait, bait uptake and vaccination was assessed under field conditions in Namibia. During this trial, both veterinary staff as well as dog owners expressed their appreciation to this approach of vaccination. Of 1,115 dogs offered a bait, 90% (n=1,006, 95%CI:91-94) consumed the bait and 72.9% (n=813, 95%CI:70.2-75.4) of dogs were assessed as being vaccinated, while for (11.7%, n=130, 95%CI:9.9-17.7) the status was recorded as "unkown" and 15.4% (n=172, 95%CI: 13.4-17.7) were considered as being not vaccinated. Smaller dogs and dogs offered a bait with multiple other dogs had significantly higher vaccination rates, while other factors, e.g. sex, confinement status and time had no influence.

The favorable results of this first large-scale field trial further support the strategic integration of ORV into dog rabies control programmes. Given the acceptance of the egg-flavored bait under various settings worldwide, ORV of dogs could become a game-changer in countries, where control strategies using parenteral vaccination alone failed to reach sufficient vaccination coverage in the dog population.


title: Formation of multiple flagella caused by a mutation of the flagellar rotor protein FliM in Vibrio alginolyticus

abstract:
The marine bacterium Vibrio alginolyticus forms only a single flagellum at the cell pole. In Vibrio, two proteins (GTPase FlhF and ATPase FlhG) regulate flagellar number at the cell pole. We previously isolated a mutant strain characterized as NMB155 that forms multiple flagella despite the absence of mutations in flhF and flhG. NMB155 also exhibited straight swimming without a directional change in flagellar rotation. Whole-genome sequencing of NMB155 identified an E9K mutation in FliM that is a component of the C-ring in the flagellar rotor. Mutations in FliM result in defects in flagellar formation (fla) and flagellar rotation (che or mot); however, there are few reports indicating that FliM mutations increase the number of flagella. Here, we determined that the E9K mutation confers the multi-flagellar phenotype and also the che phenotype. The co-expression of wild-type FliM and FliM-E9K indicated that they were competitive in regard to determining the flagellar number. It had been shown that the ATPase activity of FlhG corresponds to the flagellar number. We observed that the ATPase activity of FlhG was increased by the addition of FliM but not by the addition of FliM-E9K. This indicates that the N-terminal region of FliM that includes the E9 residue interacts with FlhG to increase its ATPase activity, and the E9K mutation may inhibit this interaction. We concluded that FliM downregulate FlhG activity to inhibit the formation of additional flagella.

ImportanceThe flagellar rotor generates a driving force to rotate the flagellum and is not involved in controlling the number of flagella in Vibrio. However, we observed that the E9K mutation in the rotor protein FliM confers multiple flagella. Our findings reveal a novel regulatory mechanism controlling flagellar number.


title: Structure-based discovery and in vitro validation of selective inhibitors of Chloride Intracellular Channel 4 protein.

abstract: Chloride Intracellular Channel Protein 4 (CLIC4) is a novel class of intracellular ion channel highly implicated in tumour and vascular biology. It regulates cell proliferation, apoptosis and angiogenesis; and is involved in multiple pathologic signaling pathways. Absence of specific inhibitors impedes its advancement to translational research. Here, we integrate structural bioinformatics and experimental research approach for the discovery and validation of small-molecule inhibitors of CLIC4. High-affinity allosteric binders were identified from a library of 1615 Food and Drug Administration (FDA)-approved drugs via a high-performance computing-powered blind-docking approach, resulting in the selection of amphotericin B and rapamycin. NMR assays confirmed the binding of the drugs. Both drugs reversed stress-induced membrane translocation of CLIC4 and inhibited endothelial cell migration. Structural and dynamics simulation studies further revealed that the inhibitory mechanisms of these compounds were hinged on the allosteric modulation of the catalytic glutathione (GSH)-like site loop and the extended catalytic {beta} loop which may elicit interference with the catalytic activities of CLIC4. Structure-based insights from this study provide the basis for the selective targeting of CLIC4 to treat the associated pathologies.

category: molecular biology


title: Machine-Learning-Based Olfactometry: Odor Descriptor Clustering Analysis for Olfactory Perception Prediction of Odorant Molecules

abstract: Although gas chromatography/olfactometry (GC/O) has been employed as a powerful analytical tool in odor measurement, its application is limited by the variability, subjectivity, and high cost of the trained panelists who are used as detectors in the system. The advancements in data-driven science have made it possible to predict structure-odor-relationship (SOR) and thus to develop machine-learning-based olfactometry (ML-GCO) in which the human panelists may be replaced by machine learning models to obtain the sensory information of GC-separated chemical compounds. However, one challenge remained in ML-GCO is that there are too many odor descriptors (ODs) being used to describe the sensory characteristics of odorants. It is impractical to build a corresponding model for each OD. To solve this issue, we propose a SOR prediction approach based on odor descriptor clustering. 256 representative ODs are firstly classified into 20 categories using a co-occurrence Bayesian embedding model. The categorization effect is explained according to the semantic relationships using a pre-trained Word2Vec model. Various molecular structure features including molecularly parameters, molecular fingerprints, and molecular 2D graphic features extracted by convolutional neural networks, are employed to predict the aforementioned odor categories. High prediction accuracies (Area under ROC curve was 0.800{+/-}0.004) demonstrate the rationality of the proposed clustering scenario and molecular feature extraction. This study makes the ML-GCO models much closer to the practical application since they can be expected as either an auxiliary system or complete replacement of human panelists to perform the olfactory evaluation.


title: The ciliopathy protein CCDC66 controls mitotic progression and cytokinesis by promoting microtubule nucleation and organization

abstract: Precise spatiotemporal control of microtubule nucleation and organization is critical for faithful segregation of cytoplasmic and genetic material during cell division and signaling via the primary cilium in quiescent cells. Microtubule-associated proteins (MAPs) govern assembly, maintenance, and remodeling of diverse microtubule arrays. While a set of conserved MAPs are only active during cell division, an emerging group of MAPs acts as dual regulators in dividing and non-dividing cells. Here, we elucidated the nonciliary functions and molecular mechanism of action of the ciliopathy-linked protein CCDC66, which we previously characterized as a regulator of ciliogenesis in quiescent cells. We showed that CCDC66 dynamically localizes to the spindle poles, the bipolar spindle, the spindle midzone, the central spindle and the midbody in dividing cells and interacts with the core machinery of centrosome maturation and MAPs involved in cell division. Loss-of-function experiments revealed its functions during mitotic progression and cytokinesis. Specifically, CCDC66 depletion resulted in defective spindle assembly and positioning, kinetochore fiber stability, chromosome alignment in metaphase as well as central spindle and midbody assembly and organization in anaphase and cytokinesis. Notably, CCDC66 regulates mitotic microtubule nucleation via noncentrosomal and centrosomal pathways via recruitment of gamma-tubulin to the spindle poles and the spindle. Additionally, CCDC66 bundles microtubules in vitro and in cells by its C-terminal microtubule-binding domain. Phenotypic rescue experiments showed that the microtubule and centrosome-associated pools of CCDC66 individually or cooperatively mediate its mitotic and cytokinetic functions. Collectively, our findings identify CCDC66 as a multifaceted regulator of the nucleation and organization of the diverse mitotic and cytokinetic microtubule arrays and provides new insight into nonciliary defects that underlie ciliopathies.

category: cell biology


title: Paracrine factors of stressed peripheral blood mononuclear cells activate pro-angiogenic and anti- proteolytic processes in whole blood cells and protect the endothelial barrier

abstract:
Tissue regenerative properties have been attributed to secreted paracrine factors derived from stem cells and other cell types. Especially, the secretome of {gamma}-irradiated peripheral blood mononuclear cells (PBMCsec) has been shown to possess high tissue-regenerative and pro-angiogenic capacities in a variety of preclinical studies. In the light of future therapeutic intravenous applications of PBMCsec, we investigated possible effects of PBMCsec on circulating white blood cells and endothelial cells lining the vasculature.

MethodsTo identify changes in the transcriptional profile of white blood cells treated with PBMCSec, whole blood was drawn from healthy individuals and stimulated with PBMCsec for 8 hours ex vivo before further processing for single cell RNA sequencing (scRNAseq). In addition, we performed in vitro assay to confirm findings arising from the transcriptional profiling.

ResultsAddition of PBMCsec to whole blood significantly altered the gene signature of granulocytes (17 genes), T-cells (45 genes), B-cells (72 genes) and most prominently monocytes (322 genes). We detected a strong upregulation of several tissue-regenerative and pro-angiogenic cyto- and chemokines in monocytes, including VEGFA, CXCL1 and CXCL5. Intriguingly, inhibitors of endopeptidase activity, such as SERPINB2, were also strongly induced. Measurement of the trans-endothelial electrical resistance of primary human microvascular endothelial cells revealed a strong barrier-protective effect of PBMCsec after barrier disruption.

ConclusionTogether, we show that PBMCsec induces angiogenic and proteolytic processes in the blood and is able to attenuate endothelial barrier damage. These regenerative properties suggest that systemic application of PBMCsec might be a promising novel strategy to restore damaged organs.


title: Inactivation of histone chaperone HIRA unmasks a link between normal embryonic development of melanoblasts and maintenance of adult melanocyte stem cells

abstract: Histone chaperone HIRA is thought to play a role in both early development and aging, but little is known about connections between the two processes. Here, we explore this relationship using a lineage-specific knockout mouse model, TyrCre::Hirafl/fl, in which HIRA is deficient in the pigmentary system consisting of embryonic melanoblasts, postnatal melanocytes and melanocyte stem cells (McSCs). Hira knockout leads to reduced melanoblast numbers during embryogenesis, but wild type numbers of melanocytes at birth, normally functioning juvenile and young adult McSCs, and only a very mildly hypopigmented first hair coat. However, on closer analysis, Hira knockout melanocytic cells of newborn mice exhibit molecular markers characteristic of cell aging and proliferative deficits. As they age, TyrCre::Hirafl/fl mice display marked defects in McSC maintenance and premature hair graying. Importantly, these defects are only observed when HIRA is inactivated during embryogenesis, not post-natally. This genetic model illustrates how normal embryonic development lays the foundation for maintenance of adult tissue specific stem cells and so suppression of degenerative phenotypes of aging.


title: Interspecific allometric scaling in eDNA production in fishes reflects physiological and surface area allometry

abstract: Relating environmental DNA (eDNA) signal strength to organism abundance requires a fundamental understanding of eDNA production. A number of studies have demonstrated that eDNA production may scale allometrically - that is, larger organisms tend to exhibit lower mass-specific eDNA production rates, likely due to allometric scaling in key processes related to eDNA production (e.g. surface area, excretion/egestion). While most previous studies have examined intra-specific allometry, physiological rates and organism surface area also scale allometrically across species. We therefore hypothesize that eDNA production will similarly exhibit inter-specific allometric scaling. To evaluate this hypothesis, we reanalyzed previously published eDNA data from Stoeckle et al. (2021) which compared metabarcoding read count to organism count and biomass data obtained from trawl surveys. Using a Bayesian model we empirically estimated the value of the allometric scaling coefficient ( b) for bony fishes to be 0.67 (credible interval = 0.58 - 0.77), although our model failed to converge for chondrichthyan species. We found that integrating allometry significantly improved correlations between organism abundance and metabarcoding read count relative to traditional metrics of abundance (density and biomass) for bony fishes. Although substantial unexplained variation remains in the relationship between read count and organism abundance, our study provides evidence that eDNA production tends to scale allometrically across species. Future studies investigating the relationship between eDNA signal strength and metrics of fish abundance could potentially be improved by accounting for allometry - a scaling coefficient value of [~]2/3 appears to be both theoretically and empirically justified.


title: Will The Grass Be Greener On The Other Side Of Climate Change?

abstract:
Increasing atmospheric [CO2] is stimulating photosynthesis and plant production, increasing the demand for nitrogen relative to soil supply with declining global foliar nitrogen concentrations as a consequence. The effect of such oligotrophication on the forage quality of sweetveld, mixedveld, and sourveld grasslands in South Africa, which support livestock production and native ungulates, are unknown. Soil characteristics and the herbage quality of an abundant grass are described from baseline historical (mid 1980s) data collected across a sweet-mixed-sour grassland gradient in KwaZulu-Natal. Sourveld occurred on the most acidic, dystrophic soils and exhibited a pronounced decline in leaf N, digestibility, and other macronutrients during winter, in sharp contrast to sweetveld, on nutrient-rich soils, where forage quality varied little seasonally. In a carbon enriched, warmer, and most likely drier future climate, we predict that forage quality will be little altered in sweetveld where soil nutrients and temperature are not limiting but that sourveld could become  sourer because soil nutrients will be inadequate to match higher plant production promoted by elevated [CO2] and warmer and longer growing seasons. Reassessing historical data and seasonal and spatial monitoring of forage quality will enable past and future impacts of climate change on grassland forage quality to be assessed.

SignificanceO_LIGrassland forage quality will likely decline with elevated [CO2] and warming, particularly in sourveld.
C_LIO_LIClimate change could deepen and widen the sourveld winter forage bottleneck, necessitating greater supplementary feeding of livestock.
C_LI


title: Evolutionary history of metazoan TMEM16 family

abstract: Transmembrane protein 16 (TMEM16) functions as either a Ca2+-activated Cl- channel (CaCC) or phospholipid scramblase (CaPLSase) and plays diverse physiological roles. It is well conserved in eukaryotes; however, the origin and evolution of different subfamilies in Metazoa are not yet understood. To uncover the evolutionary history of the TMEM16 family, we analyzed 412 proteins from 74 invertebrate species using evolutionary genomics. We found that the TMEM16C-F and J subfamilies are vertebrate-specific, but the TMEM16A/B, G, H, and K subfamilies are ancient and present in many, but not all metazoan species. The most ancient subfamilies in Metazoa, TMEM16L and M, are only maintained in limited species. TMEM16N and O are Cnidaria- and Ecdysozoa-specific subfamilies, respectively, and Ctenophora, Xenacoelomorpha, and Rotifera contain species-specific proteins. We also identified TMEM16 genes that are closely linked together in the genome, suggesting that they have been generated via recent gene duplication. The anoctamin domain structures of invertebrate-specific TMEM16 proteins predicted by AlphaFold2 contain conserved Ca2+-binding motifs and permeation pathways with either narrow or wide inner gates. The inner gate distance of TMEM16 protein may have frequently switched during metazoan evolution, and thus determined the function of the protein as either CaCC or CaPLSase. These results demonstrate that TMEM16 family has evolved by gene gain and loss in metazoans, and the genes have been generally under purifying selection to maintain protein structures and physiological functions.


title: A revised perspective on the evolution of troponin I and troponin T in vertebrates

abstract: The troponin (Tn) complex, responsible for the Ca2+ activation of striated muscle, is composed of three interacting protein subunits: TnC, TnI, and TnT, encoded by TNNC, TNNI, and TNNT genes. TNNI and TNNT are sister gene families, and in mammals the three TNNI paralogs (TNNI1, TNNI2, TNNI3), which encode proteins with tissue-specific expression, are each in close genomic proximity with one of the three TNNT paralogs (TNNT2, TNNT3, TNNT1, respectively). It has been widely presumed that all vertebrates broadly possess genes of these same three classes, although earlier work has overlooked jawless fishes (cyclostomes) and cartilaginous fishes (chimaeras, rays and sharks), which are distantly related to other jawed vertebrates. With a new phylogenetic and synteny analysis of a diverse array of vertebrates including these taxonomic groups, we define five distinct TNNI classes (TNNI1-5), with TNNI4 and TNNI5 being only present in non-mammalian vertebrates and typically found in tandem, and four classes of TNNT (TNNT1-4). These genes are located in four genomic loci that were generated by the 2R whole-genome duplication events. TNNI3, encoding  cardiac TnI in mammals, was independently lost in cartilaginous and ray-finned fishes. Ray-finned fishes predominantly express TNNI1 in the heart. TNNI5 is highly expressed in shark hearts and contains an N-terminal extension similar to that of TNNI3 found in tetrapod hearts. Given that TNNI3 and TNNI5 are distantly related, this supports the hypothesis that the N-terminal extension may be an ancestral feature of vertebrate TNNI and not an innovation unique to TNNI3, as has been commonly believed.


title: Secondary reversion to sexual monomorphism associated with tissue-specific loss of doublesex expression

abstract: Animal evolution is characterized by frequent turnover of sexually dimorphic traits - new sex- specific characters are gained, and some ancestral sex-specific characters are lost, in many lineages. In insects, sexual differentiation is predominantly cell-autonomous and depends on the expression of the doublesex (dsx) transcription factor. In most cases, cells that transcribe dsx have the potential to undergo sex-specific differentiation, while those that lack dsx expression do not. Consistent with this mode of development, comparative research has shown that the origin of new sex-specific traits can be associated with the origin of new spatial domains of dsx expression. In this report, we examine the opposite situation - a secondary loss of the sex comb, a male-specific grasping structure that develops on the front legs of some drosophilid species. We show that, while the origin of the sex comb is linked to an evolutionary gain of dsx expression in the leg, sex comb loss in a newly identified species of Lordiphosa (Drosophilidae) is associated with a secondary loss of dsx expression. We discuss how the developmental control of sexual dimorphism affects the mechanisms by which sex-specific traits can evolve.


title: A transcriptional program shared across lineages underlies cell differentiation during metazoan development

abstract:
BackgroundDuring development, most cells undergo striking changes in order to develop into functional tissues. All along this process, the identity of each tissue arises from the particular combination of regulatory transcription factors that specifically control the expression of relevant genes for growth, pattern formation and differentiation. In this scenario, regulation of gene expression turns out to be essential to determine cell fate and tissue specificity.

ResultsTo characterize the dynamic transcriptional profiles during cellular differentiation, we tracked down the transcriptome of committed cells in different Drosophila melanogaster tissues and compartments at a number of developmental stages. We found that during fly development, temporal transcriptional changes shared across lineages are much larger than spatial lineage-specific transcriptional changes, and that cellular differentiation is dominated by a transcriptional program, common to multiple lineages, that governs the transition from undifferentiated to fully differentiated cells independently from the differentiation end point. The program is under weak epigenetic regulation, and it is characterized by downregulation of genes associated with cell cycle, and concomitant activation of genes involved in oxidative metabolism. Largely orthogonal to this program, tissue specific transcriptional programs, defined by a comparatively small number of genes are responsible for lineage specification. Transcriptome comparisons with worm, mouse and human, reveal that this transcriptional differentiation program is broadly conserved within metazoans.

ConclusionsOur data provides a novel perspective to metazoan development, and strongly suggest a model, in which the main transcriptional drive during cell type and tissue differentiation is the transition from precursor undifferentiated to terminally differentiated cells, irrespective of cell type.


title: An intrinsic oscillator underlies visual navigation in ants.

abstract: Controlling behavior implies a constant balance between exploration - to gather information - and exploitation - to use this information to reach ones goal. However, how this tradeoff is achieved in navigating animals is unclear. Here we recorded the paths of two phylogenetically distant visually navigating ant species (Myrmecia croslandi and Iridomyrmex purpureus) using a trackball-treadmill directly in their habitat. We show that both species continuously produce regular lateral oscillations with bursts of forward movement when facing the general direction of travel, providing a remarkable tradeoff between visual exploration across directions and movement areas. This dynamical signature is conserved across navigational contexts but requires certain visual cues to be fully expressed. Rotational feedback regulates the extent of turns, but is not required to produce them, indicating that oscillations are generated intrinsically. Learnt visual information modulates the oscillations amplitudes to fit the task at hand in a continuous manner: an unfamiliar panorama enhances the amplitude of oscillations in both naive and experienced ants, favoring visual exploration; while a learnt familiar panorama reduces them, favoring exploitation through. The observed dynamical signature readily emerges from a simple neural-circuit model of the insects conserved pre-motor area known as the lateral accessory lobe, endorsing oscillations as a core, ancestral way of moving in insects. We discuss the importance and evolution of self-generated behaviors and how such an oscillator has been exapted to various modalities, behaviors and way of moving.

category: animal behavior and cognition


title: De novo phytosterol synthesis in animals

abstract: Sterols are lipids that regulate multiple processes in eukaryotic cells, and are essential components of cellular membranes. Sterols are currently assumed to be kingdom specific, with phytosterol synthesis restricted to plants while animals are only able to synthesize cholesterol. Here, we challenge this assumption by demonstrating that the marine annelids Olavius and Inanidrilus synthesize the phytosterol sitosterol de novo. Using multi-omics, high-resolution metabolite imaging, heterologous gene expression and enzyme assays, we characterized the biosynthetic pathway of sitosterol and showed that it is the most abundant sterol in these worms (60%). We show that phytosterol synthesis partially overlaps with cholesterol synthesis and involves a non-canonical sterol methyltransferase (SMT), C24-SMT, an essential enzyme for sitosterol synthesis in plants, but not known from bilaterians. Our comparative phylogenetic analyses of C24-SMT homologs revealed that these are widely distributed across annelids and other animal phyla, including sponges and rotifers. Our findings show that phytosterol synthesis and use is not restricted to the plant kingdom, and indicate that the evolution of sterols in animals is more complex than previously assumed.

category: biochemistry


title: How does data structure impact cell-cell similarity? Evaluating the influence of structural properties on proximity metric performance in single cell RNA-seq data

abstract: Accurately identifying cell populations is paramount to the quality of downstream analyses and overall interpretations of single-cell RNA-seq (scRNA-seq) datasets but remains a challenge. The quality of single-cell clustering depends on the proximity metric used to generate cell-to-cell distances. Accordingly, proximity metrics have been benchmarked for scRNA-seq clustering, typically with results averaged across datasets to identify a highest performing metric. However, the  best-performing metric varies between studies, with the performance differing significantly between datasets. This suggests that the unique structural properties of a scRNA-seq dataset, specific to the biological system under study, has a substantial impact on proximity metric performance. Previous benchmarking studies have omitted to factor the structural properties into their evaluations. To address this gap, we developed a framework for the in-depth evaluation of the performance of 17 proximity metrics with respect to core structural properties of scRNA-seq data, including sparsity, dimensionality, cell population distribution and rarity. We find that clustering performance can be improved substantially by the selection of an appropriate proximity metric and neighbourhood size for the structural properties of a dataset, in addition to performing suitable pre-processing and dimensionality reduction. Furthermore, popular metrics such as Euclidean and Manhattan distance performed poorly in comparison to several lessor applied metrics, suggesting the default metric for many scRNA-seq methods should be re-evaluated. Our findings highlight the critical nature of tailoring scRNA-seq analyses pipelines to the system under study and provide practical guidance for researchers looking to optimise cell similarity search for the structural properties of their own data.

category: bioinformatics


title: scTagger: Fast and accurate matching of cellular barcodes across short- and long-reads of single-cell RNA-seq experiments

abstract: Single-cell RNA sequencing allows for characterizing the gene expression landscape at the cell type level. However, because of its use of short-reads, it is severely limited at detecting full-length features of transcripts such as alternative splicing. New library preparation techniques attempt to extend single-cell sequencing by utilizing both long-and short-reads. These techniques split the library material, after it is tagged with cellular barcodes, into two pools: one for short-read sequencing and one for long-read sequencing. However, the challenge of utilizing these techniques is that they require matching the cellular barcodes sequenced by the erroneous long-reads to the cellular barcodes detected by the short-reads. To overcome this challenge, we introduce scTagger, a computational method to match cellular barcodes data from long-and short-reads. We tested scTagger against another state-of-the-art tool on both real and simulated datasets and we demonstrate that scTagger has both significantly better accuracy and time efficiency.


title: METAbolomics data Balancing with Over-sampling Al-gorithms (META-BOA): an online resource for addressing class imbalance

abstract:
MotivationClass imbalance, or unequal sample sizes between classes, is an increasing concern in machine learning for metabolomic and lipidomic data mining, which can result in overfitting for the over-represented class. Numerous methods have been developed for handling class imbalance, but they are not readily accessible to users with limited computational experience. Moreover, there is no resource that enables users to easily evaluate the effect of different over-sampling algorithms.

ResultsMETAbolomics data Balancing with Over-sampling Algorithms (META-BOA) is a web-based application that enables users to select between four different methods for class balancing, followed by data visualization and classification of the sample to observe the augmentation effects. META-BOA outputs a newly balanced dataset, generating additional samples in the minority class, according to the users choice of Synthetic Minority Over-sampling Technique (SMOTE), Borderline-SMOTE (BSMOTE), Adaptive Synthetic (ADASYN), or Random Over-Sampling Examples (ROSE). META-BOA further displays both principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) visualization of data pre- and post-over-sampling. Random forest classification is utilized to compare sample classification in both the original and balanced datasets, enabling users to select the most appropriate method for their analyses.

Availability and implementationMETA-BOA is available at https://complimet.ca/meta-boa.

Supplementary InformationSupplementary material is available at Bioinformatics online.


title: METAbolomics data Balancing with Over-sampling Algorithms (META-BOA): an online resource for addressing class imbalance


title: Hi-LASSO: High-performance Python and Apache spark packages for feature selection with high-dimensional data

abstract:
High-dimensional LASSO (Hi-LASSO) is a powerful feature selection tool for high-dimensional data. Our previous study showed that Hi-LASSO outperformed the other state-of-the-art LASSO methods. However, the substantial cost of bootstrapping and the lack of experiments for a parametric statistical test for feature selection have impeded to apply Hi-LASSO for practical application. In this paper, the Python package and its Spark library are efficiently implemented in a parallel manner for practice with real-world problems, as well as providing the capability of the parametric statistical tests for feature selection on high-dimensional data. We demonstrate Hi-LASSOs outperformance with various intensive experiments in a practical manner. Hi-LASSO will be efficiently and easily performed by using the packages for feature selection. Hi-LASSO packages are publicly available at https://github.com/datax-lab/Hi-LASSO under the MIT license. The packages can be easily installed by Python PIP, and additional documentation is available at https://pypi.org/project/hi-lasso and https://pypi.org/project/Hi-LASSO-spark.

Author summaryWe provide the brief presentation in the literature of Hi-LASSO comparing to Random LASSO. Then, we describe Hi-LASSOs open-source packages in Python and Apache Spark, specifying parameters. The open-source packages improves efficiency and scalability of Hi-LASSO, so that the time-consuming bootstrapping-based parametric statistical test can be practically applied for high-dimensional data. We conducted intensive experiments to assess the performance of the packages with the parametric statistical test using simulation data, semi-real datasets, and TCGA cancer dataset. The Hi-LASSO packages showed outstanding and robust performance in feature selection. The packages are available through PyPI and can be easily installed using Python PIP.


title: Statistical analysis of spatially resolved transcriptomic data by incorporating multi-omics auxiliary information

abstract: Effective control of false discovery rate is key for multiplicity problems. Here, we consider incorporating informative covariates from external datasets in the multiple testing procedure to boost statistical power while maintaining false discovery rate control. In particular, we focus on the statistical analysis of innovative high-dimensional spatial transcriptomic data while incorporating external multi-omics data that provide distinct but complementary information to the detection of spatial expression patterns. We extend OrderShapeEM, an efficient covariate-assisted multiple testing procedure that incorporates one auxiliary study, to make it permissible to incorporate multiple external omics studies, to boost statistical power of spatial expression pattern detection. Specifically, we first use a recently proposed computationally efficient statistical analysis method, spatial pattern recognition via kernels, to produce the primary test statistics for spatial transcriptomic data. Afterwards, we construct the auxiliary covariate by combining information from multiple external omics studies, such as bulk or single-cell RNA-seq data and genome wise association study data, using the Cauchy combination rule. Finally, we extend and implement the integrative analysis method OrderShapeEM on the primary p-values along with auxiliary data incorporating multi-omics information for efficient covariate-assisted spatial expression analysis. We conduct a series of realistic simulations to evaluate the performance of our method with known ground truth. Four case studies in mouse olfactory bulb, mouse cerebellum, human breast cancer and human heart tissues further demonstrate the substantial power gain of our method in detecting genes with spatial expression patterns compared to existing classic approaches that do not utilize any external information.


title: Biomolecular condensates can both accelerate and suppress aggregation of α-synuclein

abstract: Biomolecular condensates present in cells can fundamentally affect the aggregation of amyloidogenic proteins and play a role in the regulation of this process. While liquid-liquid phase separation of amyloidogenic proteins by themselves can act as an alternative nucleation pathway, interaction of partly disordered aggregation-prone proteins with pre-existing condensates that act as localization centers could be a far more general mechanism of altering their aggregation behavior. Here, we show that so-called host biomolecular condensates can both accelerate and slow down amyloid formation. We study the amyloidogenic protein -synuclein and two truncated -synuclein variants in the presence of three types of condensates composed of non-aggregating peptides, RNA or ATP. Our results demonstrate that condensates can dramatically speed up amyloid formation when proteins localize to their interface. However, condensates can also significantly suppress aggregation by sequestering and stabilizing amyloidogenic proteins, thereby providing living cells with a possible protection mechanism against amyloid formation.


title: Crosslinker design determines microtubule network organization by opposing motors

abstract:
During cell division, crosslinking motors determine the architecture of the spindle, a dynamic microtubule network that segregates the chromosomes. It is unclear how motors with opposite directionality coordinate to drive both contractile and extensile behaviors in the spindle. Particularly, the impact of different crosslinker designs on network self-organization is not understood, limiting our understanding of self-organizing structures in cells, but also our ability to engineer new active materials. Here, we use experiment and theory to examine active microtubule networks driven by mixtures of motors with opposite directionality and different crosslinker design. We find that although the kinesin-14 HSET causes network contraction when dominant, it can also assist the opposing kinesin-5 KIF11 to generate extensile networks. This bifunctionality results from HSETs asymmetric design, distinct from symmetric KIF11. These findings expand the set of rules underlying patterning of active microtubule assemblies and allow a better understanding of motor cooperation in the spindle.

SIGNIFICANCE STATEMENTDuring cell division, the spindle apparatus segregates duplicated chromosomes for their inheritance by the daughter cells. The spindle is a highly interconnected network of microtubule filaments that are crosslinked by different types of molecular motors. How the different motors cooperate to organize the spindle network is not understood. Here, we show that an asymmetric crosslinker design can confer bifunctionality to a mitotic motor in the presence of other motors. The asymmetric motor supports both extensile and contractile microtubule network behaviors as observed in different parts of the spindle. These findings define new rules controlling the generation of active microtubule networks and allow us to better understand how motors cooperate to organize the correct spindle architecture when a cell divides.


title: Designing multiphase biomolecular condensates by coevolution of protein mixtures

abstract: Control of biomolecular condensates may hold considerable therapeutic potential. Intracellular condensates are highly multi-component systems in which complex phase behaviour can ensue, including the formation of architectures comprising multiple immiscible condensed phases. Conceivable avenues for manipulating condensates to bypass pathologies thus extend beyond merely controlling their stability and material properties, and relying solely on physical intuition to manipulate them is difficult because of the complexity of their composition. We address this challenge by developing an efficient computational approach to design pairs of protein sequences that result in well-separated multilayered condensates. Our method couples a genetic algorithm to a residue-resolution coarse-grained protein model. We demonstrate that we can design protein partners to form multiphase condensates containing naturally occurring proteins, such as the low-complexity domain of hnRNPA1 and its mutants, and show how homo- and heterotypic interactions must differ between proteins to result in multiphasicity.


title: Improved antiproliferative activity of doxorubicin-loaded calcium phosphate nanoparticles against melanoma cells

abstract: The high incidence of melanoma has received significant attention. Despite advances in early detection and standard treatment options, new strategies that improve therapy with reduced side effects are highly desirable. Several studies have demonstrated the efficiency of doxorubicin (Dox) to treat melanoma, however, side effects limit its clinical use. Drug delivery systems, especially nanostructured ones, are a useful approach to enhance antitumor activity and reduce the toxicity of drugs. Here, we report the use of calcium phosphate nanoparticles functionalized with Dox and hyaluronic acid (N-Dox) to enhance Dox antiproliferative activity. The effects were accessed in A-375 melanoma cells, in which N-Dox significantly decreased IC50 over 48 hours (0.142 {+/-} 0.07) compared to the free drug (0.44 {+/-} 0.25). Treatment triggered DNA damage, increased nuclear area, and senescent phenotype. Furthermore, it did not form colonies after 14 days of incubation preceded by short exposure treatment. These preliminary results indicate that N-Dox hold promise for melanoma treatment, reducing the minimum effective dose and perhaps a reduction in the cost of treatment.

category: cancer biology


title: A Quantum Dot Biomimetic for SARS-CoV-2 to Interrogate Dysregulation of the Neurovascular Unit Relevant to Brain Inflammation

abstract: Despite limited evidence for competent infection and viral replication of SARS-CoV-2 in the central nervous system (CNS), neurologic dysfunction is a common post-acute medical condition reported in "recovered" COVID-19 patients. To identify a potential noninfectious route for SARS-CoV-2-mediated neurological damage, we constructed colloidal nanocrystal quantum dots linked to micelles decorated with spike protein (COVID-QDs) as a biomimetic to interrogate how blood-brain barrier (BBB) dysregulation may subsequently induce neuroinflammation in the absence of infection. In transwell co-culture of endothelial bEnd.3 monolayers and primary neuroglia, we exposed only the bEnd.3 monolayers to COVID-QDs and examined by fluorescence microscopy whether such treatment led to (i) increased inflammation and leakage across the bEnd.3 monolayers, (ii) permeability of the COVID-QDs across the monolayers, and (iii) induction of neuroinflammation in neuroglial cultures. The results of our study provide evidence of neuroinflammatory hallmarks in cultured neurons and astrocytes without direct exposure to SARS-CoV-2-like nanoparticles. Additionally, we found that pre-treatment of our co-cultures with a small-molecule, broad-spectrum inhibitor of mixed lineage and leucine rich repeat kinases led to reversal of the observed dysregulation in endothelial monolayers and resulted in neuroglial protection. The results reported here may serve to guide future studies into the potential mechanisms by which SARS-CoV-2 mediates neurologic dysfunction.


title: CASK and FARP coordinately control pre- and post-synaptic function

abstract: Synaptic proteins are immobilized at synapses via interactions with scaffolding proteins. Scaffolding proteins for glutamatergic and GABAergic synapses have been extensively studied; however, far less is known about how scaffolds shape the function of cholinergic synapses. Here we analyze the role of two C. elegans post-synaptic scaffolding proteins (LIN-2/CASK and FRM-3/FARP) at cholinergic neuromuscular junctions. Constitutive knockouts or muscle specific inactivation of lin-2 and frm-3 dramatically reduced spontaneous and evoked post-synaptic currents. These synaptic defects resulted from decreased abundance of post-synaptic ionotropic acetylcholine receptors (AChRs) and decreased presynaptic ACh release. Thus, our findings show that post-synaptic LIN-2/FRM-3 complexes coordinately control pre- and post-synaptic function, thereby promoting cholinergic synaptic transmission.


title: Multisite imaging of neural activity using a genetically encoded calcium sensor in the honey bee Apis mellifera

abstract: Sociality is classified as one of the major transitions in evolution, and the most advanced level of sociality is found in eusocial insects such as the honey bees. This sophisticated social behavior seems to be associated with higher cognitive abilities in these insects, however the study of their neural bases has been limited by the lack of tools that allow measuring neuronal activity simultaneously in different brain regions of the honey bee brain. Here, we developed the first pan-neuronal genetic driver in a Hymenopteran model organism, the honey bee, and expressed the calcium indicator GCaMP6f under the control of the honey bee synapsin promoter. We show that GCaMP6f is widely expressed in the honey bee brain, allowing to record neural activity from multiple brain regions simultaneously, including from poorly investigated brain regions such as the mushroom body calyces or the lateral horn. Our recordings show that while odorant quality (chemical structure) and quantity are faithfully encoded in the honeybee antennal lobe, odor coding in the lateral horn departs from this simple physico-chemical coding, in line with the role of this structure in coding the biological value of odorants. These brain recordings represent the first use of a neurogenetic tool for recording neural activity in a eusocial insect.


title: Targeting diverse operational regimes in recurrent spiking networks

abstract: Neural computations emerge from recurrent neural circuits that comprise hundreds to a few thousand neurons. Continuous progress in connectomics, electrophysiology, and calcium imaging require tractable spiking network models that can consistently incorporate new information about the network structure and reproduce the recorded neural activity features. However, it is challenging to predict which spiking network connectivity configurations and neural properties can generate fundamental operational states and specific experimentally reported nonlinear cortical computations. Theoretical descriptions for the computational state of cortical spiking circuits are diverse, including the balanced state where excitatory and inhibitory inputs balance almost perfectly or the inhibition stabilized state (ISN) where the excitatory part of the circuit is unstable. It remains an open question whether these states can co-exist with experimentally reported nonlinear computations and whether they can be recovered in biologically realistic implementations of spiking networks. Here, we show how to identify spiking network connectivity patterns underlying diverse nonlinear computations such as XOR, bistability, inhibitory stabilization, supersaturation, and persistent activity. We established a mapping between the stabilized supralinear network (SSN) and spiking activity which allowed us to pinpoint the location in parameter space where these activity regimes occur. Notably, we found that biologically-sized spiking networks can have irregular asynchronous activity that does not require strong excitation-inhibition balance or large feedforward input and we showed that the dynamic firing rate trajectories in spiking networks can be precisely targeted without error-driven training algorithms.


title: Circulating U13 small nucleolar RNA as a candidate biomarker for Huntington's disease

abstract:
Background and ObjectivesFluid biomarkers are a recent field of interest in Huntington disease (HD). We focused on small circulating RNAs from plasma of subjects with prodromal (pre-HD) and overt disease by a two-stage approach: an unbiased investigation by an array method and a validation study to quantify a significant small nucleolar RNA.

MethodsThrough Affymetrix Gene-Chip-miRNA-Array we performed an exploratory study on 9 HD patients, 8 healthy subjects (HS) and 5 psychiatric patients (PP; who share drugs with HD patients, to control for iatrogenic effects). Through real time PCR we validated the results in an independent population of 24 HD patients, 15 pre-HD, 24 PP, 28 Alzheimers disease (AD) patients (added to control the disease-specificity of our finding) and 23 HS. A bioinformatic analysis was also performed to interpret our finding.

ResultsThe microarray results showed a significant signal for U13 small nucleolar RNA (SNORD13) that was increased in plasma of HD patients compared to controls (fold change, 1.54, p =0.003 HD vs. HS, and fold change 1.44 p = 0.0026 HD vs. PP). In the validation population the significant increase in HD patients was evident compared to both pre-HD and the three control groups (p<0.00001). The plasma levels of SNORD13 correlated with the status of mutant huntingtin carrier and the disease duration (respectively R=0.69; p<0.000001; R=0.49; p=0.015). Through receiver operating characteristic (ROC) curve analysis, we showed high accuracy of plasmatic SNORD13 in discriminating HD patients from pre-HD and control groups (AUC=0.963), outperforming values reported in another study for intrathecal or plasmatic mutant huntingtin and neurofilament light chain as biomarkers of overt HD. The bioinformatic analysis on SNORD13 interactome and pathway analysis showed enrichments for factors involved in nuclear functions beyond the ribosome biogenesis.

DiscussionWe report the unprecedented finding of a potential role of small nucleolar RNAs in HD. Circulating SNORD13 seems a good biomarker for clinical purposes. It seems to be specific for HD and to peripherally report a plausible  tipping point in the pathogenic cascade at neuronal level, possibly paving the way for new therapeutic targets.


title: Enhanced Mirror Neuron Network Activity and Effective Connectivity during Live Interaction

abstract: Facial expressions are indispensable for daily communication. Previous neuroimaging studies investigating facial expression processing presented pre-recorded stimuli and lacked live face-to-face interactions. Our paradigm alternated between presentations of models real-time performance and pre-recorded videos of dynamic facial expressions to participants. Simultaneous fMRI and facial electromyography activity recordings, as well as post-scan valence and arousal ratings were acquired. Live facial expressions enhanced the subjective valence and arousal ratings as well as facial muscular responses. Live performances showed greater engagement of the right posterior superior temporal sulcus (pSTS) and right inferior frontal gyrus (IFG) more, and modulated the effective connectivity between them. A support vector machine reliably classified multivoxel activation patterns in brain regions involved in dynamic facial expression processing in mentalizing and salience networks. The results suggest that live social interaction modulates the activity and connectivity of the right mirror neuron system and enhances spontaneous mimicry, further facilitating emotional contagion.


title: Phenotypic characterization and analysis of complete genomes of two distinct strains of the proposed species "L. swaminathanii"

abstract: Recently, a new Listeria species, "Listeria swaminathanii", was proposed. Here, we phenotypically and genotypically characterize two additional strains that were previously obtained from soil samples and compare the results to the type strain. Complete genomes for both strains were assembled from hybrid Illumina and Nanopore sequencing reads and annotated. Further genomic analysis including average nucleotide identity (ANI) and detection of mobile genetic elements and genes of interest (e.g., virulence-associated) were conducted. The strains showed 98.7-98.8% ANI with the type strain. The UTK C1-0015 genome contained a partial monocin locus and a plasmid while the UTK C1-0024 genome contained a full monocin locus and a prophage. Phenotypic characterization consistent with those performed on the proposed type strain was conducted to assess consistency of phenotypes across a greater diversity of the proposed species (n=3 instead of n=1). Only a few findings were notably different from those of the type strain, such as catalase activity, glycerol metabolism, starch metabolism, and growth at 41{degrees}C. This study further expands our understanding of this newly proposed sensu stricto Listeria species.


title: Exceptional yield vesicle packaged recombinant protein production from E. coli.

abstract: We describe a novel system that exports diverse recombinant proteins in extracellular vesicles from E. coli. The vesicles not only compartmentalise toxic, insoluble and disulphide bond containing proteins in a soluble and functional form (e.g. DNaseI, nanobodies and IgG-fusions), but the continued release of the inducible vesicle packaged proteins into the media supports continuous isolation of protein from active culture within a micro-environment allowing stable long-term storage. This technology results in unprecedented yields of vesicle packaged functional proteins for efficient downstream processing for a wide range of applications from discovery science to applied biotechnology and medicine.


title: Spt4 drives cellular senescence by activating non-coding RNA transcription in ribosomal RNA gene clusters

abstract: Genome instability can drive aging in many organisms. The ribosomal RNA gene (rDNA) cluster is one of the most unstable regions in the genome. Replicative lifespan in budding yeast is correlated to rDNA stability, suggesting that the rDNA locus produces an aging signal. To understand the underlying mechanism, we looked for yeast mutants with more stable rDNA and longer lifespan than wild-type cells. We reveal that absence of a transcription elongation factor, Spt4, resulted in an increased rDNA stability, a reduced activity of the regulatory E-pro promoter in the rDNA, and extended replicative lifespan in a SIR2-dependent manner. Spt4-dependent lifespan restriction was abolished in the absence of non-coding RNA transcription at the E-pro locus. The amount of Spt4 increases and its function becomes more important as cells age. These findings suggest that Spt4 is a promising aging factor that accelerates cellular senescence through rDNA instability driven by non-coding RNA transcription


title: Nodal signaling establishes a competency window for stochastic cell fate switching

abstract: Specification of the germ layers by Nodal signaling has long been regarded as an archetype of how graded morphogens induce different cell fates. However, this deterministic model cannot explain why only a subset of cells at the margin of the early zebrafish embryo adopt the endodermal fate, while their immediate neighbours, experiencing similar signaling profiles, become mesoderm. Combining pharmacology, quantitative imaging and single cell transcriptomics, we demonstrate that sustained Nodal signaling establishes a bipotential progenitor state where cells initially fated to become mesoderm can switch to an endodermal fate. Switching is a random event, the likelihood of which is modulated by Fgf signaling. This inherently imprecise mechanism nevertheless leads to robust endoderm formation because of buffering at later stages. Thus, in contrast to previous deterministic models of morphogen action, Nodal establishes a temporal window when cells are competent to undergo a stochastic cell fate switch, rather than determining fate itself.


title: Pharmacological intervention of the FGF-PTH axis as a potential therapeutic for ciliopathies

abstract:
Ciliopathies represent a disease class characterized by a broad range of phenotypes including polycystic kidneys and skeletal anomalies. Ciliopathic skeletal phenotypes are among the most common and most difficult to treat due to a poor understanding of the pathological mechanisms leading to disease. Using an avian model (talpid2) for a human ciliopathy with skeletal anomalies (Orofaciodigital syndrome 14), we identified disruptions in the FGF23-PTH axis that resulted in reduced calcium uptake in the developing mandible and subsequent micrognathia. While pharmacological intervention with the FDA-approved pan-FGFR inhibitor AZD4547 alone rescued expression of the FGF target Sprouty2, it did not significantly rescue micrognathia. In contrast, treatment with a cocktail of AZD4547 and Teriparatide acetate, a PTH agonist and FDA-approved treatment for osteoporosis, resulted in a molecular, cellular, and phenotypic rescue of ciliopathic micrognathia in talpid2 mutants. Together, these data provide novel insight into pathological molecular mechanisms associated with ciliopathic skeletal phenotypes and a potential therapeutic strategy for a pleiotropic disease class with limited to no treatment options.

Summary StatementTreatment options for ciliopathic phenotypes are very limited. Using an avian model, we report a novel molecular mechanism and potential therapeutic treatment for ciliopathic micrognathia.


title: The contribution of mate-choice, couple convergence and confounding to assortative mating

abstract: Increased phenotypic similarity between partners, termed assortative mating (AM), has been observed for many traits. However, it is currently unclear if these observations are due to mate choice for certain phenotypes, post-mating convergence, or a result of confounding factors such as shared environment or indirect assortment. To dissect these underlying phenomena, we applied Mendelian randomisation (MR) to 51,664 couples in the UK biobank to a panel of 118 phenotypes under AM. We found that 54% (64 of 118) of the tested traits had a causal relationship between partners, with female-to-male effects on average being larger. Forty traits, including systolic blood pressure, basal metabolic rate, weight and height, showed significantly larger phenotypic correlation than MR-estimates, suggesting the presence of confounders. Subsequent analyses revealed household income, overall health rating, education and tobacco smoking as major overall confounders, accounting for 29.8, 14.1, 11.6, and 4.78%, of cross-partner phenotypic correlations, respectively. We detected limited evidence for couple-correlation convergence (e.g. increased similarity with respect to smoking and medication use), measured by stratifying couples by their time spent together. Finally, mediation analysis revealed that the vast majority (>77%) of causal associations between one trait of an individual and a different trait of their partner is indirect. For example, the causal effect of the BMI of an individual on the overall health rating of their partner is entirely acting through the BMI of their partner. In summary, this study revealed many novel causal effects within couples, shedding light on the impact of confounding on couple phenotypic similarity.

category: genetics


title: Metatranscriptomic comparison of viromes in endemic and introduced passerines in New Zealand

abstract: New Zealand has many endemic passerine birds vulnerable to emerging infectious diseases. Yet little is known about viruses in passerines, and in some countries, including New Zealand, the virome of wild passerines has received little research attention. Using metatranscriptomic sequencing we characterised the virome of New Zealand endemic and introduced species of passerine. Accordingly, we identified 34 possible avian viruses from cloacal swabs of 12 endemic and introduced bird species not showing signs of disease. These included a novel siadenovirus, iltovirus and avastrovirus in the Eurasian blackbird (Turdus merula, an introduced species), song thrush (Turdus philomelos, introduced) and silvereye (Zosterops lateralis, introduced), respectively. This is the first time novel viruses from these genera have been identified in New Zealand, likely reflecting prior undersampling. It also represents the first identification of an iltovirus and siadenovirus in blackbirds and thrushes globally. These three viruses were found only in introduced species and may pose a risk to endemic species if they were to jump species boundaries, particularly the iltoviruses and siadenoviruses that have a prior history of disease associations. Further virus study and surveillance is needed in New Zealand avifauna, particularly in Turdus populations and endemic species.