title: Investigating tri-trophic interactions using bio-energetic demographic models

abstract:
A central debate in ecology has been the long running discussion on the role of apex predators in affecting the abundance and dynamics of their prey. In terrestrial systems, research has primarily relied on correlational approaches, due to the challenge of implementing robust experiments with replication and appropriate controls. A consequence of this is that we largely suffer from a lack of mechanistic understanding of the population dynamics of interacting species that can be surprisingly complex.

Mechanistic models offer an opportunity to examine the causes and consequences of some of this complexity. We present a bioenergetic mechanistic model of a tri-trophic system where the primary vegetation resource follows a seasonal growth function, and the herbivore and carnivore species are modelled using two integral projection models (IPMs) with body mass as the phenotypic trait. Within each IPM, the demographic functions are structured according to bioenergetic principles, describing how animals acquire and transform resources into body mass, energy reserves and breeding potential. We parameterise this model to reproduce the population dynamics of grass, elk and wolves in northern Yellowstone (USA), and investigate the impact of wolf reintroduction on the system.

Our model generated predictions that closely matched the observed population sizes of elk and wolf in Yellowstone prior to and post wolf reintroduction. The introduction of wolves into our basal grass-elk bioenergetic model resulted in a population of 99 wolves, and a reduction in elk numbers by 61% (from 14,948 to 5,823) at equilibrium. In turn, vegetation biomass increased by approximately 25% in the growing season and more than 3-fold in the non-growing season. The addition of wolves to the model caused the elk population to shift from being food-limited to being predator-limited, and had a stabilising effect on elk numbers across different years. Wolf predation also led to a shift in the phenotypic composition of the elk population, via a small increase in elk average body mass.

Our model represents a novel approach to the study of predator-prey interactions. Explicitly considering and linking bioenergetics, population demography and body mass phenotypes can provide novel insights into the mechanisms behind complex ecosystem processes.


title: Environmental filtering and habitat (mis)matching of riverine invertebrate metacommunities

abstract:
AimMetacommunities are assembled through a combination of local and regional processes, with the relative importance of the drivers of assembly depending on ecological context. Global change can alter community assembly at both local and regional levels, potentially shifting communities into disequilibrium with their local environmental conditions. In this study, we evaluated the spatial variation in environmental filtering and habitat matching of 1078 riverine macroinvertebrate communities distributed across nine ecoregions within the conterminous United States.

LocationConterminous United States.

TaxonFreshwater macroinvertebrates.

MethodsWe first quantified spatial patterns in environmental filtering, habitat matching, and functional trait diversity. We then used boosted regression trees to identify (1) functional trait predictors of environmental filtering and habitat match and (2) environmental, landscape, and network variables that predict functional trait abundances.

ResultsOur results demonstrated that environmental filtering but not habitat matching varied strongly by ecoregion. We also found that functional trait diversity varied by ecoregion, but not as strongly as the signatures of environmental filtering. We did not identify consistent functional trait predictors for both environmental filtering and habitat matching, with trait predictors instead varying by individual traits, trait categories, and ecoregions. Notwithstanding inconsistent trait predictors, environmental filtering was primarily influenced by habitat preference traits while habitat matching was primarily influenced by both habitat preference and dispersal traits. Predictors of functional traits also varied by trait category and ecoregion, with habitat preference and dispersal traits primarily influenced by network variables.

Main conclusionsOur study demonstrates the contingent patterns and drivers of environmental filtering and habitat matching on a macroecological scale. We aim for this work to provide the foundation on which trait-environment relationships can be further quantified and causal explanations established in the context of community disequilibrium and applied to conservation and management of freshwater systems.

category: ecology


title: CHD-associated enhancers shape human cardiomyocyte lineage commitment

abstract:
Enhancers orchestrate gene expression programs that drive multicellular development and lineage commitment. Thus, genetic variants at enhancers are thought to contribute to developmental diseases by altering cell fate commitment. However, while many variant-containing enhancers have been identified, studies to endogenously test the impact of these enhancers on lineage commitment have been lacking. We perform a single-cell CRISPRi screen to assess the endogenous roles of 25 enhancers and putative cardiac target genes implicated in genetic studies of congenital heart defects (CHD). We identify 16 enhancers whose repression leads to delayed differentiation of human cardiomyocytes (CMs). A focused CRISPRi validation screen shows that repression of TBX5 enhancers delays the transcriptional switch from mid-to late-stage CM states. Endogenous genetic manipulations of two TBX5 enhancers phenocopy epigenetic perturbations. Together, these results identify critical enhancers of cardiac development and suggest that misregulation of these enhancers could contribute to cardiac defects in human patients.

HIGHLIGHTSO_LISingle-cell enhancer perturbation screens during human cardiomyocyte differentiation.
C_LIO_LIPerturbation of CHD-associated enhancers and target genes delays CM maturation.
C_LIO_LIRepression or deletion of TBX5 enhancers delays transition from mid to late CM states.
C_LI

category: genomics


title: IMPatienT: an integrated web application to digitize, process and explore multimodal patient data.

abstract:
BackgroundMedical acts, such as imaging, generally lead to the production of several medical text reports that describe the relevant findings. Such processes induce multimodality in patient data by linking image data to free-text data and consequently, multimodal data have become central to drive research and improve diagnosis of patients. However, the exploitation of patient data is challenging as the ecosystem of available analysis tools is fragmented depending on the type of data (images, text, genetic sequences), the task to be performed (digitization, processing, exploration) and the domain of interest (clinical phenotype, histology...). To address the challenges, the analysis tools need to be integrated in a simple, comprehensive, and flexible platform.

ResultsHere, we present IMPatienT (dIgitize Multimodal PATIENt daTa), a free and open-source web application to digitize, process and explore multimodal patient data. IMPatienT has a modular architecture, including four components to: (i) create a standard vocabulary for a domain, (ii) digitize and process free-text data by mapping it to a set of standard terms, (iii) annotate images and perform image segmentation, and (iv) generate an automatic visualization dashboard to provide insight on the data and perform automatic diagnosis suggestions. Finally, we demonstrate the usefulness of IMPatienT on a corpus of 40 simulated muscle biopsy reports of congenital myopathy patients.

ConclusionsIMPatienT is a platform to digitize, process and explore patient data that can handle image and free-text data. As it relies on a user-designed vocabulary, it can be adapted to fit any domain of research and can be used as a patient registry for exploratory data analysis (EDA). A demo instance of the application is available at https://impatient.lbgi.fr.

category: bioinformatics


title: Inferring microRNA regulation: A proteome perspective

abstract: Post-transcriptional regulation in multicellular organisms is mediated by microRNAs. However, the mechanisms that determine if a gene is regulated by miRNAs are poorly understood. Previous works focused mostly on miRNA seed matches and other features of the 3-UTR of transcripts. These common approaches relied on knowledge of the miRNA families, and computational approaches still yield poor, inconsistent results, with many false positives. In this work, we present a different paradigm for predicting miRNA-regulated genes based on proteins. In a novel, automated machine learning framework, we use sequence as well as diverse functional annotations to train models on multiple organisms using experimentally validated data. We present insights from tens of millions of features extracted and ranked from different modalities. We show high predictive performance per organism and in generalization across species. We provide a list of novel predictions for Danio rerio (zebrafish) and Arabidopsis thaliana (mouse-ear cress). We compare genomic models, and observe that our protein model outperforms genomics, while a unified model improves on both. While most membranous and disease related proteins are regulated by miRNAs, we observe the G-protein coupled receptor (GPCR) family is an exception, being mostly unregulated by miRNAs, and we raise possible explanations for this. We further show that the evolutionary conservation among duplicated genes does not imply a coherence in miRNA regulation. We conclude that duplicated genes diverge in their tendency to be miRNA regulated. However, protein function is informative across species in predicting post-transcriptional miRNA regulation in living cells.


title: Peptide-RNA Coacervates as a Cradle for the Evolution of Folded Domains

abstract: Peptide-RNA coacervates can result in the concentration and compartmentalization of simple biopolymers. Given their primordial relevance, peptide-RNA coacervates may have also been a key site of early protein evolution. However, the extent to which such coacervates might promote or suppress the exploration of novel peptide conformations is fundamentally unknown. To this end, we used electron paramagnetic resonance (EPR) spectroscopy to characterize the structure and dynamics of an ancient and ubiquitous nucleic acid binding element, the helix-hairpin-helix (HhH) motif, alone and in the presence of RNA, with which it forms coacervates. Double electron-electron resonance (DEER) spectroscopy applied to singly labeled peptides containing one HhH motif reveals the presence of dimers, even in the absence of RNA, and transient -helical character. Moreover, dimer formation is promoted upon RNA binding and was detectable within peptide-RNA coacervates. The distance distributions between spin labels are consistent with the symmetric (HhH)2-Fold, which is generated upon duplication and fusion of a single HhH motif and traditionally associated with dsDNA binding. These results support the hypothesis that coacervates are a unique testing ground for peptide oligomerization and that phase-separating peptides could have been a resource for the construction of complex protein structures via common evolutionary processes, such as duplication and fusion.

category: biophysics


title: Unexpected proteinopathies in hippocampal PDE11A4 promote age-related cognitive decline of social associative memories

abstract: In humans, associative memories are more susceptible to age-related cognitive decline (ARCD) than are recognition memories. Reduced cAMP/cGMP signaling in the hippocampus may contribute to ARCD. Here, we found that both aging and traumatic brain injury-associated dementia increased expression of the cAMP/cGMP-degrading enzyme phosphodiesterase 11A (PDE11A) in the human hippocampus. Further, age-related increases in hippocampal PDE11A4 mRNA and protein were conserved in mice, as was the increased vulnerability of associative versus recognition memories to ARCD. Interestingly, mouse PDE11A4 protein in the aged ventral hippocampus (VHIPP) ectopically accumulated in the membrane fraction and filamentous structures we term "ghost axons". These age-related increases in expression were driven by reduced exoribonuclease-mediated degradation of PDE11A mRNA and increased PDE11A4-pS117/pS124, the latter of which also drove the punctate accumulation of PDE11A4. In contrast, PDE11A4-pS162 caused dispersal. Importantly, preventing age-related increases in PDE11 expression via genetic deletion protected mice from ARCD of short-term and remote long-term associative memory (aLTM) in the social transmission of food preference assay, albeit at the expense of recent aLTM. Further, mimicking age-related overexpression of PDE11A4 in CA1 of old KO mice caused aging-like impairments in CREB function and remote social--but not non-social--LTMs. RNA sequencing and phosphoproteomic analyses of VHIPP identified cGMP-PKG--as opposed to cAMP-PKA--as well as circadian entrainment, glutamatergic/cholinergic synapses, calcium signaling, oxytocin, and retrograde endocannabinoid signaling as mechanisms by which PDE11A deletion protects against ARCD. Together, these data suggest that PDE11A4 proteinopathies acutely impair signaling in the aged brain and contribute to ARCD of social memories.

category: neuroscience


title: HiFENS: High-throughput FISH detection of endogenous pre-mRNA splicing isoforms

abstract: Splicing factors play an essential role in regulation of alternative pre-mRNA splicing. While much progress has been made in delineating the mechanisms of the splicing machinery, the identity of signal transduction pathways and upstream factors that regulate splicing factor activity is less well understood. A major challenge in the discovery of upstream regulatory factors of pre-mRNA splicing is the scarcity of functional genomics screening methods to monitor splicing outcomes of endogenous genes. Here, we have developed HiFENS (High throughput FISH Detection of ENdogenous Splicing Isoforms), a high-throughput imaging assay based on hybridization chain reaction (HCR) and used HiFENS to screen for cellular factors that regulate alternative splicing of endogenous genes. We demonstrate optimized detection with high specificity of endogenous splicing isoforms and multiplexing of probes for accurate detection of splicing outcomes with single cell resolution. As proof-of-principle, we perform an RNAi screen of 702 human kinases and identify potential candidate upstream splicing regulators of the FGFR2 gene. HiFENS should be a useful tool for the unbiased delineation of cellular pathways involved in alternative splicing regulation.

category: cell biology


title: multiplestressR: An R package to analyse factorial multiple stressor data using the additive and multiplicative null models

abstract:
Globally, ecosystems are being affected by multiple simultaneous stressors (also termed drivers, factors, or perturbations). While the effects of single stressors are becoming increasingly well understood, there remains substantial uncertainty regarding how multiple stressors may interact to affect ecosystems. Accordingly, there is substantial interest in documenting how stressors combine to impact individuals through to entire communities. Indeed, understanding how stressors interact represents one of the grand challenges currently facing ecologists and conservationists.

Popular methods used to classify stressor interactions comprise multiple steps, including complex mathematical equations. Accordingly, there is the potential for errors to occur at multiple points, any of which can result in erroneous conclusions being drawn. Furthermore, there are frequently minor methodological differences between studies which may limit, or even prevent, direct comparisons of their results from being made.

Here, we introduce the multiplestressR R package, a statistical tool which addresses the above issues. The package allows researchers to easily conduct a rigorous analysis of their multiple stressor data and provides results which are simple to interpret. The multiplestressR package can implement either the additive or multiplicative null model using iterations of these tools which are commonplace within multiple stressor ecology. The multiplestressR package can classify interactions as being synergistic, antagonistic, reversal, or null and requires minimal experience in either R or statistics to implement. Additionally, we provide example R code which can be easily modified to analysis any given factorial multiple stressor dataset. Indeed, widespread use of this software will allow for an easier and more robust comparison of results. Ultimately, we hope that the multiplestressR package will provide a stronger understanding of how stressors combine to affect individuals, populations, communities, and ecosystems.


title: Periodic Environmental Disturbance Drives Repeated Ecomorphological Diversification in an Adaptive Radiation of Antarctic Fishes

abstract: The ecological theory of adaptive radiation has profoundly shaped our conceptualization of the rules that govern diversification. However, while many radiations follow classic early burst patterns of diversification as they fill ecological space, the longer-term fates of these radiations depend on many factors, such as climatic stability. In systems with periodic disturbances, species-rich clades can contain nested adaptive radiations of subclades with their own distinct diversification histories, and how adaptive radiation theory applies in these cases is less clear. Here, we investigated patterns of ecological and phenotypic diversification within two iterative adaptive radiations of cryonotothenioid fishes in Antarcticas Southern Ocean: crocodile icefishes and notoperches. For both clades, we observe evidence of repeated diversification into disparate regions of trait space between closely related taxa and into overlapping regions of trait space between distantly related taxa. We additionally find little evidence that patterns of ecological divergence are correlated with evolution of morphological disparity, suggesting that these axes of divergence may not be tightly linked. Finally, we reveal evidence of repeated convergence in sympatry that suggests niche complementarity. These findings reflect the dynamic history of Antarctic marine habitats, and may guide hypotheses of diversification dynamics in environments characterized by periodic disturbance.

category: evolutionary biology


title: MPI region of interest (ROI) analysis and quantification of iron in different volumes

abstract: MPI directly detects superparamagnetic iron oxides (SPIONs), which should enable precise, accurate, and linear quantification. However, selecting a region of interest (ROI) has strong effects on MPI quantification results. Ideally, ROI selection should be simple, user-independent, and widely applicable. In this work, we describe and compare four MPI ROI selection methods and assess their performance in vitro and in vivo. To explore the effect of ROI selection, ten ferucarbotran phantoms were imaged, each contained the same amount of iron but varied in volume. Three users tested the accuracy of the ROI methods for quantification of these samples. Lastly, the four ROI methods were applied to quantify ferucarbotran in vivo after intravenous, intramuscular, and subcutaneous injections in mice. We demonstrate that each ROI method has strengths. We conclude there is an important trade-off between ROI size and the accuracy of iron quantification, therefore the choice of ROI selection method for each study must be carefully informed.


title: Microbial Community Dynamics of a Sequentially Fed Anaerobic Digester Treating Solid Organic Waste

abstract:
A 50 kg-scale high solids anaerobic digestor comprising six sequentially-fed leach beds with a leachate recirculation system and an upflow anaerobic sludge blanket reactor was operated at 37{degrees}C for 88 weeks. The feedstock contained a constant fibre fraction (a mix of cardboard, boxboard, newsprint, and fine paper) and varying proportions of food waste. Significantly enhanced co-digestion and methane production from the fibres was observed as the proportion of FW was increased. The most abundant 16S rRNA amplicon sequence variant (ASV), classified as Clostridium butyricum, was correlated with the amount of FW in the system and total methane yield. However, methane yield specifically from the fibre fraction was significantly correlated with organisms classified as Candidatus Roizmanbacteria and Spirochaetaceae. These ASVs together with ASVs classified as Anaerovorax and Methanoculleus correlated strongly to other ASVs in the microbial community, suggesting these are vitally important for ecosystem function and methane production. In addition, tracing the fate of microbes derived from incoming food waste helped to diagnose a poor batch of bulking agent.

Table of Contents (TOC)/ Abstract Art

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category: bioengineering


title: A chemomechanical model of sperm locomotion reveals two modes of swimming

abstract: The propulsion of mammalian spermatozoa during reproduction relies on the spontaneous periodic oscillation of their flagella. These oscillations are driven internally by the coordinated action of ATP-powered dynein motors that exert active sliding forces between microtubule doublets, resulting in bending waves that propagate along the flagellum and enable locomotion of the cell through the viscous medium. In this work, we present a chemomechanical model of a freely swimming spermatozoon that uses a sliding-control model of the flagellar axoneme capturing the coupling of motor kinetics with elastic deformations and accounts for the effect of non-local hydrodynamic interactions between the sperm head and flagellum. Nonlinear simulations of the model equations are shown to produce realistic beating patterns and swimming trajectories, which we analyze as a function of sperm number and motor activity. Our results demonstrate that the swimming velocity does not vary monotonically with dynein activity, but instead displays two local maxima corresponding to distinct modes of swimming, each characterized by qualitatively different waveforms and trajectories.


title: An interplay between JA and SA modulates rapid systemic ROS signaling during responses to high light stress or wounding

abstract:
Plants can send long distance cell-to-cell signals from a single tissue subjected to stress to the entire plant. This ability is termed  systemic signaling and is essential for plant acclimation to stress and/or defense against pathogens. Several signaling mechanisms are associated with systemic signaling, including the reactive oxygen species (ROS) wave, calcium wave, hydraulic wave, and electric signals. The ROS wave coordinates multiple physiological, molecular, and metabolic responses among different parts of the plant, and is essential for systemic acquired acclimation (SAA) to stress. In addition, it is linked with several plants hormones, including jasmonic acid (JA), salicylic acid (SA), and abscisic acid (ABA). However, how these plant hormones modulate the ROS wave and whether they are required for SAA is not clear. Here we report that SA and JA play antagonistic roles in modulating the ROS wave. While SA augments the ROS wave, JA suppresses it, during responses to a local wounding or high light (HL) stress treatments. We further show that ethylene and ABA are essential for the regulation of the ROS wave during systemic responses to a local wounding treatment. Interestingly, we found that the redox-response protein NONEXPRESSOR OF PATHOGENESIS RELATED PROTEIN 1 (NPR1) is required for systemic ROS accumulation in response to wounding or HL stress, as well as for SAA to HL stress. Taken together, our findings suggests that an interplay between JA and SA could regulate systemic signaling and SAA during responses of plants to abiotic stress or wounding.

One sentence summaryAn antagonistic interaction between SA and JA attenuates the accumulation of ROS in local and systemic tissues during responses of plants to light stress or wounding.

category: plant biology


title: Visual Mode Switching: Improved General Compensation to Environmental Color Change Requires Only One Exposure Per Day

abstract: When the visual environment changes, vision adapts in order to maintain accurate perception. For repeatedly encountered environmental changes, the visual system may learn to adjust immediately, a process called "visual mode switching". For example, following experience with red glasses, participants report the glasses redness fades instantly when they put the glasses on. Here we tested: 1) whether once-daily experience suffices for learning to switch visual modes, and 2) whether effects of mode-switching apply to most stimuli affected by the environmental change. In Experiment 1, twelve participants wore bright red glasses for a single 5-hr period each day, for 5 days; and we tested for changes in the perception of unique yellow, which contains neither red nor green. In Experiment 2, we tested how mode switching affects larger parts of the color space. Thirteen participants donned and removed the glasses multiple times a day, for 5 days; and we used a dissimilarity rating task to measure and track perception of many different colors. Across days, immediately upon donning the glasses, the world appeared less and less reddish (Experiment 1), and colors across the whole color space appeared more and more normal (Experiment 2). These results indicate that mode switching can be learned from a once-daily experience, and it applies to most stimuli in a given environment. These findings may help to predict when and how mode switching occurs outside the laboratory.


title: Synaptic vesicle-bound molecular bridges organize sequential vesicle states along parallel pathways

abstract: Multiple complexes and biochemical pathways are involved in priming synaptic vesicles and subsequent neurotransmitter release. While atomic models of reconstituted complexes, interaction data and physiological experiments were essential for our understanding of the mechanisms underlying synaptic transmission, they lack the combination of the native preservation, comprehensive view and a high level of detail to resolve how the actions of individual complexes integrate to give rise to cellular function. We employed cryo-electron tomography to simultaneously image multiple presynaptic complexes at a single nanometer resolution in their native composition, conformation and environment, and to determine their spatial organization. Our results show that Munc13- and SNAP25-dependent tethers localize vesicles with a single nanometer precision, thus defining sequential vesicle states that immediately precede neurotransmitter release. The transition between the states involves two parallel biochemical pathways and is associated with a conversion to SNARE complex-dependent tethers and a loss of protein connectors that interlink vesicles. These results provide an example of a cellular function performed by a large molecular assembly comprising multiple, spatially separated complexes and provides a framework for further exploration of such assemblies.


title: The effect of different treatment durations with indole-3-acetic acid (IAA)-producing endophytic Bacillus spp. on tomato 'Aicha' under saline conditions

abstract: This study aimed to investigate the effect of indole-3-acetic acid (IAA)-producing endophytes from saline environments on survival and growth of tomato under salt stress, using different treatment times. Twenty-five endophytic bacteria were isolated from halophytes (Atriplex halimus L., Tamarix aphylla L.) issued from saline regions (Algeria). Five strains were selected based on tolerance to NaCl. A polyphasic taxonomic study was conducted. The selected strains were assigned to the Bacillus cereus group. Quantification of IAA production was done by high-performance liquid chromatography (HPLC). An in vitro test of growth promotion/protection of tomato  Aicha was conducted under saline conditions (50 mM, 75 mM, 100 mM, and 125 mM), for different durations of seed biopriming (1h, 3h, and 12h). Endophytes led to a significant amelioration of salt stress in tomato  Aicha at all salinity levels, depending on treatment times, indicating the necessity of optimizing this crucial factor.

category: microbiology


title: Puf3p facilitates fermentative mitochondrial functions via monosome-enriched nuclear-encoded mitochondrial mRNAs in budding yeast

abstract:
Yeasts generally grow with a highly glycolytic metabolism and restrain mitochondrial biogenesis except for some Fe/S proteins. Respiratory mitochondrial functions and biosynthesis pathways are well studied, however how cells coordinate basal fermentative mitochondrial functions is not fully understood. We show that a part of nuclear-encoded mitochondrial mRNAs, which preferentially translated in monosomes, are regulated by Puf3p upon glucose-rich media. Especially, of those monosome-enriched nuclear-encoded mitochondrial mRNAs, CAT5/COQ7 mRNA has a variant of the canonical Puf3p binding site on its 3-UTR. Western blot analysis showed that Puf3p represses the translation of Cat5p regardless of fermentable or respiratory media. In vitro binding assay revealed that Puf3p directly binds to CAT5 mRNA via the non-canonical Puf3p binding site.

Mutants harboring the substitution of the non-canonical Puf3p binding site in CAT5 mRNA grew normally but impaired Cat5p expressions apparently, indicating CAT5 mRNA is a bona fide Puf3p target. Overall, Puf3p, a general key modulator for nuclear-encoded mitochondrial mRNAs, fine-tunes translation of a subset of nuclear-encoded mitochondrial mRNAs including mRNAs with non-canonical Puf3p binding sites under the fermentation. This may be required to keeping the fundamental functions of yeast mitochondria at proper levels.

category: molecular biology


title: In situ single particle classification reveals distinct 60S maturation intermediates in cells

abstract: Electron cryo-microscopy (cryo-EM) can generate high-resolution views of cells with faithful preservation of molecular structure. In situ cryo-EM, therefore, has enormous potential to reveal the atomic details of biological processes in their native context. However, in practice, the utility of in situ cryo-EM is limited by the difficulty of reliably locating and confidently identifying molecular targets (particles) and their conformational states in the crowded cellular environment. We recently showed that 2DTM, a fine-grained template-based search applied to cryo-EM micrographs, can localize particles in two-dimensional views of cells with high precision. Here we demonstrate that the signal-to-noise ratio (SNR) observed with 2DTM can be used to differentiate related complexes in focused ion beam (FIB)-milled cell sections. We apply this method in two contexts to locate and classify related intermediate states of 60S ribosome biogenesis in the Saccharomyces cerevisiae cell nucleus. In the first, we separate the nuclear pre-60S population from the cytoplasmic mature 60S population, using the subcellular localization to validate assignment. In the second, we show that relative 2DTM SNRs can be used to separate mixed populations of nuclear pre-60S that are not visually separable. We use a maximum likelihood approach to define the probability of each particle belonging to each class, thereby establishing a statistic to describe the confidence of our classification. Without the need to generate 3D reconstructions, 2DTM can be applied even when only a few target particles exist in a cell.


title: Learning-related contraction of grey matter in rodent sensorimotor cortex is associated with adaptive myelination

abstract: From observations in rodents, it has been suggested that the cellular basis of learning-dependent changes, detected using structural magnetic resonance imaging (MRI), may be increased dendritic spine density, alterations in astrocyte volume, and adaptations within intracortical myelin. Myelin plasticity is crucial for neurological function and active myelination is required for learning and memory. However, the dynamics of myelin plasticity and how it relates to morphometric-based measurements of structural plasticity remains unknown. We used a motor skill learning paradigm to evaluate experience-dependent brain plasticity by voxel-based morphometry (VBM) in longitudinal MRI, combined with a cross-sectional immunohistochemical investigation. Whole brain VBM revealed non-linear decreases in grey matter (GM) juxtaposed to non-linear increases in white matter (WM) that were best modelled by an asymptotic time course. Using an atlas-based cortical mask, we found non-linear changes with learning in primary and secondary motor areas and in somatosensory cortex. Analysis of cross-sectional myelin immunoreactivity in forelimb somatosensory cortex confirmed an increase in myelin immunoreactivity followed by a return towards baseline levels. The absence of significant histological changes in cortical thickness further suggests that non-linear morphometric changes are likely due to changes in intracortical myelin for which morphometric WM volume (WMV) data significantly correlated with myelin immunoreactivity. Together, these observations indicate a non-linear increase of intracortical myelin during learning and support the hypothesis that myelin is a component of structural changes observed by VBM during learning.


title: Larger and more dentated hippocampal structure is associated with better memory in the oldest-old.

abstract:
Episodic memory is widely recognized as a critically important aspect of cognition that is often impacted by cognitive and brain aging. Prior work has shown that episodic memory is related to the presence of teeth-like folds on the dentate gyrus, called dentation. We hypothesized that episodic memory performance relates to overall hippocampal structure (i.e., dentation and volume) in an oldest-old cohort. We used data from the McKnight Brain Aging Registry, which consisted of cognitively healthy 85+-year-old adults. We conducted a canonical correlation analysis on 111 participants between a set of episodic memory tests and a set of characterizations of hippocampal structure. The analysis yielded a strong canonical correlation between episodic memory and hippocampal structure (r = 0.491, p = <0.001). The results suggest there is a connection between hippocampal morphology and function in the oldest-old. Our findings suggest that dentation may play an important role in relation to the individual differences observed in episodic memory performance among the oldest old and that hippocampal structure supports healthy cognitive aging.

HighlightsO_LIWe characterized hippocampal dentation in a healthy oldest-old sample.
C_LIO_LIHippocampal structure is related to episodic memory in healthy oldest-old adults.
C_LIO_LIMemory functioning is related to both hippocampal volume and dentation.
C_LI


title: Contrasting effects of reduced phosphatidylcholine synthesis in absence of seipin: embryonic lethality goes down while lipid droplets get even larger

abstract:
Seipin plays a vital role in lipid droplet homeostasis and its deficiency causes congenital generalized lipodystrophy type II in humans. It is not known whether the physiological defects are all caused by cellular lipid droplet defects. Loss-of-function mutation of seip-1, the C. elegans seipin ortholog, causes embryonic lethality and lipid droplet abnormality. We uncover nhr-114 and spin-4 as two suppressors of seip-1 embryonic lethality. Mechanistically, nhr-114 and spin-4 act in the "B12-one-carbon cycle-phosphatidylcholine (PC)" axis and reducing PC synthesis suppresses the embryonic lethality of seip-1 mutants. Conversely, PC deficiency enhances the lipid droplet abnormality of seip-1 mutants. The suppression of seip-1 embryonic lethality by PC reduction requires polyunsaturated fatty acid (PUFA). Therefore, seipin and phosphatidylcholine exhibit opposite actions in embryogenesis, while they function similarly in lipid droplet homeostasis. Our results demonstrate that seipin-mediated embryogenesis is independent of lipid droplet homeostasis.

HighlightsO_LIseip-1 suppressors act in the "B12-one-carbon cycle-PC" pathway.
C_LIO_LIReducing PC synthesis suppresses the embryonic lethality of seip-1 mutants.
C_LIO_LISuppression of the embryonic lethality by PC reduction requires PUFA.
C_LIO_LIReduced PC synthesis enhances the large lipid droplet of seip-1 mutants.
C_LI

category: developmental biology


title: Whole-genome duplication in an algal symbiont serendipitously confers thermal tolerance to corals

abstract: Coral reefs are fundamentally sustained by symbioses involving dinoflagellate algae in the Family Symbiodiniaceae. The coral symbiont Durusdinium trenchii is notable for enhancing the resilience of coral holobionts under thermal stress. Believed to have experienced whole-genome duplication (WGD), D. trenchii offers a valuable model system to understand how selection acts on the genome of a facultative symbiont after WGD. We present genome assemblies for two isolates of D. trenchii and confirm WGD in these taxa, providing the first example of this phenomenon in a single-celled eukaryotic symbiont. We assess how the facultative lifestyle has contributed to the retention and divergence of duplicated genes, and how these results intersect with the observed thermotolerance of corals hosting D. trenchii symbionts. Our findings reveal that the free-living lifestyle is the main driver of post-WGD evolution, however, they also implicate symbiosis in this process, with both lifestyles increasing algal fitness. Our results demonstrate that WGD, driven by selection in the free-living phase, has converted D. trenchii into a coral symbiont that serendipitously provides increased thermal stress protection to the host coral.


title: wenda_gpu: fast domain adaptation for genomic data

abstract:
MotivationDomain adaptation allows for development of predictive models even in cases with limited sample data. Weighted elastic net domain adaptation specifically leverages features of genomic data to maximize transferability but the method is too computationally demanding to apply to many genome-sized datasets.

ResultsWe developed wenda_gpu, which uses GPyTorch to train models on genomic data within hours on a single GPU-enabled machine. We show that wenda_gpu returns comparable results to the original wenda implementation, and that it can be used for improved prediction of cancer mutation status on small sample sizes than regular elastic net.

Availabilitywenda_gpu is available on GitHub at https://github.com/greenelab/wenda_gpu/.

Contactcasey.s.greene@cuanschutz.edu

Supplementary informationSupplementary data are available at Bioinformatics online.


title: First crystal structure of a non-canonical amino acid linked to a paramagnetic lanthanide tag facilitates protein structure determination using NMR-derived restraints

abstract: Site-directed spin labeling of proteins via non-canonical amino acids (ncAAs) is a non-traditional method for the measurement of pseudocontact shifts (PCSs) by nuclear magnetic resonance (NMR) spectroscopy. PCSs provide long-range distance and orientational information between a paramagnetic center and protein nuclei that can be used as restraints for computational structural modeling techniques. Here, we present the first experimental structure of an ncAA chemically linked to a lanthanide tag conjugated to the protein, T4-Lysozyme (T4L). T4L was crystallized with a cyclen-based C3 tag coordinated to the paramagnetic ion terbium (Tb3+). The paramagnetic C3-lanthanide tag generated PCSs measured at four different ncAA sites. We show that the addition of these restraints improves structure prediction protocols for T4L using the RosettaNMR framework. Generated models provide insight into T4L conformational flexibility sampled in solution. This integrative modeling protocol is readily transferable to larger proteins. Methods to predict protein structures are advancing into an exciting arena such that reliable experimental data will play important roles for evaluating the biophysical relevance of predicted structural models. Our contribution here caters to the growing interest in using ncAAs for a range of biophysical studies, and these methods can be readily transferred to larger protein systems of interest.


title: A cross-sectional study of the commercial plant-based landscape across the US, UK and Canada.

abstract: As plant-based foods comprise an ever-increasing proportion of the diet, understanding the nutritional composition of these products is critical. In this study we assess the nutritional content of all commercial plant-based products across multiple sectors (supermarkets, fast food & sit down restaurants, food delivery companies and manufacturers) in the US, UK and Canada. We identified 3488 unique products. Across all sectors, 45% of main meals had >15g protein, 60% had <10%kcal from saturated fat; 29% had >10g fibre per meal; 86% had <1000mg sodium. At restaurants, meat-based main meals were significantly higher in protein and sodium compared to vegetarian and vegan meals. The meat-based options were also significantly higher in saturated fat than the vegan but not vegetarian options. We conclude that plant-based items tend to be lower in saturated fat and sodium than their meat-based counterparts but improvements are needed to optimise their nutritional composition.

category: scientific communication and education


title: Efficient evolution of human antibodies from general protein language models and sequence information alone

abstract: Natural evolution must explore a vast landscape of possible sequences for desirable yet rare mutations, suggesting that learning from natural evolutionary strategies could accelerate artificial evolution. Here, we report that deep learning algorithms known as protein language models can evolve human antibodies with high efficiency, despite providing the models with no information about the target antigen, binding specificity, or protein structure, and also requiring no additional task-specific finetuning or supervision. We performed language-model-guided affinity maturation of seven diverse antibodies, screening 20 or fewer variants of each antibody across only two rounds of evolution. Our evolutionary campaigns improved the binding affinities of four clinically relevant antibodies up to 7-fold and three unmatured antibodies up to 160-fold across diverse viral antigens, with many designs also demonstrating improved thermostability and viral neutralization activity. Notably, our algorithm requires only a single wildtype sequence and computes recommended amino acid changes in less than a second. Moreover, the same models that improve antibody binding also guide efficient evolution across diverse protein families and selection pressures, indicating that these results generalize to many natural settings. Contrary to prevailing notions of evolution as difficult and resource-intensive, our results suggest that when constrained to a narrow manifold of evolutionary plausibility, evolution can become much easier, which we refer to as the "efficient manifold hypothesis."

category: synthetic biology


title: The Interplay of Attention and Conscious Perception: Evidence from Human Intracerebral Recordings and Computational Modeling

abstract: Competing theories of consciousness disagree on the role of frontoparietal networks. Here we recorded neural activity from 727 intracerebral contacts in 13 epileptic patients, while they detected near-threshold targets preceded by supra-threshold exogenous cues. Trajectory k-means clustering revealed three patterns: (1) Validly cued seen targets elicit sustained activity in right-hemisphere fronto-temporal regions, connected by superior longitudinal fasciculus (SLF) II/III, and late accumulation activity in bilateral dorsolateral prefrontal cortex and in right-hemisphere orbitofrontal cortex (SLF I/III). (2) Invalidly cued seen targets elicit early, sustained activity in the right-hemisphere reorienting network (SLF III). (3) Seen targets elicit late sustained left dorsolateral prefrontal activity. Task modeling with recurrent neural networks supported the causal contribution of these networks to conscious perception, and elucidated their interplay through excitatory-inhibitory mechanisms. We provide new, compelling evidence on the role of hemisphere-asymmetric frontoparietal networks associated with attentional enhancement and reorienting in conscious perception.


title: Sleep Disruption Selectively Weakens Reactivated Memories

abstract:
A widely accepted view in memory research is that recently stored information can be reactivated during sleep, leading to memory strengthening. Two recent studies have shown this effect can be reversed in participants with highly disrupted sleep. To test whether weakening of reactivated memories can result directly from sleep disruption, in this experiment we varied the intensity of memory reactivation cues, such that some produced sleep arousals. Prior to sleep, participants (local community members) learned the locations of 75 objects, each accompanied by a sound naturally related to that object. Location recall was tested before and after sleep, and a subset of the sounds were presented during sleep. Reactivation with arousal weakened memories, unlike the improvement typically found. We conclude that reactivated memories can be selectively weakened during sleep, and that memory reactivation may strengthen or weaken memories depending on additional factors such as concurrent sleep disruption.

Statement of RelevanceThe results of this study have implications for both human health and basic psychology. Sleep disorders like apnea are associated with memory problems; our results suggest a possible mechanism where frequent arousal may disrupt the naturally occurring reactivation of memory in sleep. These results also highlight the importance of avoiding brief sleep disruption for good sleep hygiene. Finally, we raise the possibility that reactivation with sleep disruption could be used therapeutically to weaken distressing memories.

Our observation that memories can also be either weakened or strengthened by sleep reactivation has implications for understanding the mechanisms of memory consolidation. In particular, we suggest that sleep memory reactivation may be a reconsolidation-like process with memory restabilization required after reactivation. Our findings also suggest avenues for future experiments; such as using sleep disruption to study the time course of memory reactivation.


title: CAPG is required for Ebola virus infection by controlling virus egress from infected cells.

abstract: Replication of Ebola virus (EBOV) is dependent upon actin functionality, especially at cell entry through macropinocytosis and at release of virus from cells. Previously, major actin-regulatory factors such as Rac1 and ARP2/3, involved in actin nucleation were shown important in both steps. However, downstream of nucleation, many other cell factors, are needed to control actin dynamics. How these regulate EBOV infection remains largely unknown. Here, we identified the actin-regulating protein, CAPG, as important for EBOV replication. Notably, knockdown (KD) of CAPG specifically inhibited viral infectivity and yield of infectious particles. Mechanistic analysis revealed a requirement of CAPG for virus production from infected cells. Proximity ligation and split GFP reconstitution assays revealed strong association of CAPG with VP40 that was mediated through the S1 domain of CAPG. Overall, CAPG is a novel host factor regulating EBOV infection through connecting actin filament stabilization to viral egress from cells.


title: Symbiosis between Patescibacteria and Archaea discovered in wastewater-treating bioreactors

abstract: Each prokaryotic domain, Bacteria and Archaea, contains a large and diverse group of organisms characterized with ultrasmall cell size and symbiotic lifestyles - Patescibacteria (also known as Candidate Phyla Radiation/CPR) and DPANN archaea. Cultivation-based approaches have revealed that Patesibacteria and DPANN symbiotically interact with bacterial and archaeal partners/hosts respectively, but cross-domain symbiosis/parasitism has never been observed. Here, we discovered physical interaction between ultramicrobacterial Patescibacteria and methanogenic archaea using cultures from anaerobic wastewater treatment sludge. In the cultures, we observed physical attachment of ultramicrobial cells to cells resembling Methanothrix and Methanospirillum using transmission electron microscopy and successfully detected physical association of Ca. Yanofskybacteria and Methanothrix using fluorescence in situ hybridization (FISH) (other ultramicrosized bacterial cells, presumably Patescibacteria, were also observed to attach on Methanospirillum). This was further confirmed to be a symbiosis rather than simple aggregation based on the observation that most ultramicrobacterial cells attached to Methanothrix were Ca. Yanofskybacteria and positive correlation (p < 0.05) between the relative abundance of Patescibacteria lineages and methanogenic archaea (e.g., Ca. Yanofskybacteria-Methanothrix and uncultured clade 32-520-Methanospirillum). The results shed light on a novel cross-domain symbiosis and inspire potential strategies for culturing CPR/DPANN.


title: DeepPerVar: a multimodal deep learning framework for functional interpretation of genetic variants in personal genome

abstract:
MotivationUnderstanding the functional consequence of genetic variants, especially the noncoding ones, is important but particularly challenging. Genome-wide association studies or quantitative trait locus analyses may be subject to limited statistical power and linkage disequilibrium, and thus are less optimal to pinpoint the causal variants. Moreover, most existing machine learning approaches, which exploit the functional annotations to interpret and prioritize putative causal variants, cannot accommodate the heterogeneity of personal genetic variations and traits in a population study, targeting a specific disease.

ResultsBy leveraging paired whole genome sequencing data and epigenetic functional assays in a population study, we propose a multi-modal deep learning framework to predict genome-wide quantitative epigenetic signals by considering both personal genetic variations and traits. The proposed approach can further evaluate the functional consequence of noncoding variants on an individual level by quantifying the allelic difference of predicted epigenetic signals. By applying the approach to the ROSMAP cohort studying Alzheimers disease (AD), we demonstrate that the proposed approach can accurately predict quantitative genome-wide epigenetic signals and in key genomic regions of AD causal genes, learn canonical motifs reported to regulate gene expression of AD causal genes, improve the partitioning heritability analysis, and prioritize putative causal variants in a GWAS risk locus. Finally, we release the proposed deep learning model as a stand-alone Python toolkit and a web server.

Availabilityhttps://github.com/lichen-lab/DeepPerVar


title: From Specification to Implementation: Assume-Guarantee Contracts for Synthetic Biology

abstract: We provide a new perspective on using formal methods to model specifications and synthesize implementations for the design of biological circuits. In synthetic biology, design objectives are rarely described formally. We present an assume-guarantee contract framework to describe biological circuit design objectives as formal specifications. In our approach, these formal specifications are implemented by circuits modeled by ordinary differential equations, yielding a design framework that can be used to design complex synthetic biological circuits at scale. We describe our approach using the design of a biological AND gate as a motivating, running example.


title: Core and accessory effectors of type VI secretion systems contribute differently to the intraspecific diversity of Pseudomonas aeruginosa

abstract: Bacteria use type VI secretion systems (T6SSs) to deliver effector proteins into other cells or the extracellular space. Those effectors kill microbes1, manipulate eukaryotic cells2, and sequester nutrients3. Which T6SS-mediated functions are generalisable across bacteria of a species or are specific to particular strains is little known. Here, we use genomics to test for the intraspecific diversity of T6SS effectors in the opportunistic pathogen Pseudomonas aeruginosa. We found effectors that are omnipresent and conserved across strains acting as  core effectors, while additional  accessory effectors vary. In vitro and in vivo experiments demonstrate different roles of the two types of effectors in bacterial killing and virulence. Further, effectors compose various effector combinations. Within one local population of clinical isolates, we observed 36 combinations among 52 bacterial lineages. These findings show the distinct contribution of T6SS effectors to strain-level variation of a bacterial pathogen and might reveal conserved targets for novel antibiotics.


title: Identification of a novel AP2 transcription factor in zygotes with an essential role in Plasmodium ookinete development.

abstract:
The sexual phase of Plasmodium represents a crucial step in malaria transmission, during which these parasites fertilize and form ookinetes to infect mosquitoes. Plasmodium development after fertilization is thought to proceed with female-stored mRNAs until the formation of a retort-form ookinete; thus, transcriptional activity in zygotes has previously been considered quiescent. In this study, we reveal the essential role of transcriptional activity in zygotes by investigating the function of a newly identified AP2 transcription factor, AP2-Z. ap2-z was previously reported as a female transcriptional regulator gene whose disruption resulted in developmental arrest at the retort stage of ookinetes. In this study, although ap2-z was transcribed in females, we show that it was translationally repressed by the DOZI complex and translated after fertilization with peak expression at the zygote stage. ChIP-seq analysis of AP2-Z shows that it binds on specific DNA motifs, targeting the majority of genes known as an essential component of ookinetes, which largely overlap with the AP2-O targets, as well as genes that are unique among the targets of other sexual transcription factors. The results of this study also indicate the existence of a cascade of transcription factors, beginning with AP2-G, that proceeds from gametocytogenesis to ookinete formation.

Author summarySexual development in Plasmodium parasites, a causative agent of malaria, is essential for their transmission from vertebrate hosts to mosquitoes. This important developmental process proceeds as follows: formation of a gametocyte/gamete, fertilization and conversion of the zygote into the mosquito midgut invasive stage, called the ookinete. As a target of transmission blocking strategies, it is important to understand the mechanisms regulating Plasmodium sexual development. In this study, we assessed transcriptional regulation after fertilization by investigating the function of a novel transcription factor, AP2-Z. The results revealed the essential role of de novo transcription activated by AP2-Z in zygotes for promoting ookinete development. As transcriptional activity during the zygote stage has previously been considered silent in Plasmodium, novel genes important for ookinete formation can now be explored in the target genes of AP2-Z. Investigating the functions of these genes can help us understand the mechanisms of Plasmodium zygote/ookinete development and identify new targets for transmission blocking vaccines.


title: Plant protection habits among Hungarian farmers and garden owners and their implications for pollinator protection

abstract: Pesticides are one of the most important anthropogenic-related stressors. In times of global pollinator decline, the role of integrated farming and that of urban gardens in supporting wild pollinators is becoming increasingly important. We circulated an online questionnaire to survey the plant protection practices among Hungarian farmers and garden owners with a particular emphasis on pollinator protection. We found that plant growers heavily rely on pesticide use, and pesticides are widely used in otherwise pollinator-friendly gardens. Whether pesticide use practices were driven by expert opinion and the respondents sex were the best predictors of pesticide use. Although most respondents supported pollinators, pesticides are also widely used among home garden owners, which can pose a non-evident ecological trap for pollinator populations in the gardens. Special attention should be paid to implementing measures to reduce pesticide, use not only in farmlands but also in home gardens. Environmental education and financial support through agroecological schemes could efficiently promote the transition. However, whereas farmers can be encouraged to reduce pesticide use mostly by expert advice, garden owners are likely to rely on more conventional information channels. The attitude of Hungarian plant growers can provide an insight into pesticide use practices of Central and Eastern European countries, but similar surveys are needed across Europe for a complete understanding of broad-scale processes. This work lays the foundations for similar studies which can inform and facilitate the transformation processes to pesticide-free farming and gardening.


title: Using large soybean historical data to study genotype by environment variation and identify mega-environments with the integration of genetic and non-genetic factors

abstract:
2Soybean (Glycine max (L.) Merr.) provides plant based protein for global food production and is extensively bred to create cultivars with greater productivity in distinct environments. Plant breeders evaluate new soybean genotypes using multi-environment trials (METs). Application of METs assume that trial sites provide representative environmental conditions that cultivars are likely to encounter when sold to farmers. Thus, it is important to understand the patterns of genotype by environment interactions (GEI) that occur in METs. In order to evaluate GEI for soybean seed yield and identify mega-environments, historical data were investigated with a retrospective analysis of 39,006 unique experimental soybean genotypes evaluated in preliminary and uniform trials conducted by public plant breeders from 1989-2019. Mega-environments (MEs) were identified using yield records of lines from the annual trials and geographic, soil, and meteorological records at the trial locations. Results indicate that yield variation was mostly explained by location and location by year interactions. The static portion of the GEI represented 26.30% of the total yield variance. Estimates of variance due to genotype by location were greater than estimates of variance due to genotype by year interaction effects. A trend analysis further indicated a two-fold increase in the genotypic variance. Furthermore, the heterogeneous estimates of genotypic, genotype by location, genotype by year, and genotype by location by year variances, were encapsulated by distinct probability distributions. The observed target population of environments (TPE) can be divided into at least two and at most three MEs, thereby suggesting improvements in the response to selection can be achieved when selecting directly for clustered (i.e. regions, ME) versus selecting across regions. Clusters obtained using phenotypic data, latitude, and soil variables plus elevation, were the most effective.

1 HighlightsO_LIA target population of environments can be split into mega-environments (MEs) according to phenotypic, geographic, and meteorological information.
C_LIO_LIReliable estimates of variance components are key to the identification of ME, which can be obtained by analyses of historical experimental data.
C_LIO_LIFrom experimental soybean seed yields evaluated across 31 years of field trials, the phenotypic variance was mostly attributed to location and location by year effects. In terms of genotype-by-environment interactions (GEI), estimated variances of genotype by location interactions was more important than the genotype by year interactions.
C_LIO_LIThe GEI trend was successfully captured in terms of parametric probability distributions of variance components, that can be incorporated in simulation studies.
C_LI

category: genetics


title: Privacy-Preserving Statistical Analysis of Genomic Data using Compressive Mechanism with Haar Wavelet Transform

abstract: To promote the use of personal genome information in medicine, it is important to analyze the relationship between diseases and the human genomes. Therefore, statistical analysis using genomic data is often conducted, but there is a privacy concern with respect to releasing the statistics as they are. Existing methods to address this problem using the concept of differential privacy cannot provide accurate outputs under strong privacy guarantees, making them less practical. In this study, for the first time we investigate the application of a compressive mechanism to genomic statistical data and propose two approaches. The first is to apply the normal compressive mechanism to the statistics vector along with an algorithm to determine the number of nonzero entries in a sparse representation. The second is to alter the mechanism based on the data, aiming to release significant SNPs with a high probability. In this algorithm, we apply the compressive mechanism with the input as a sparse vector for significant data and the Laplace mechanism for non-significant data. Using the Haar transform for the wavelet matrix in the compressive mechanism is advantageous to determine the number of nonzero elements and the amount of noise. In addition, we theoretically prove that our proposed method achieves{epsilon} -differential privacy. We evaluated our methods in terms of accuracy, rank error, and run time compared to the Laplace and exponential mechanisms. The results show that our second method in particular can guarantee both high privacy assurance as well as utility. The Python implementation of our experiments is available at https://github.com/ay0408/CompLaplace.


title: The conserved centrosomal motif, γTuNA, forms a dimer that directly activates microtubule nucleation by the γ-tubulin ring complex (γTuRC).

abstract: 1.To establish the microtubule cytoskeleton, the cell must tightly regulate when and where microtubules are nucleated. This regulation involves controlling the initial nucleation template, the {gamma}-tubulin ring complex ({gamma}TuRC). Although {gamma}TuRC is present throughout the cytoplasm, its activity is restricted to specific sites including the centrosome and Golgi. The well-conserved {gamma}-tubulin nucleation activator ({gamma}TuNA) domain has been reported to increase the number of microtubules generated by {gamma}TuRCs. Here we utilize Xenopus egg extract and in vitro single molecule imaging assays to show that {gamma}TuNA activates microtubule nucleation in extract and directly activates {gamma}TuRC in vitro. Via mutation analysis, we find that {gamma}TuNA is an obligate dimer. Moreover, efficient dimerization as well as {gamma}TuNAs L70, F75, and L77 residues are required for binding to and activation of {gamma}TuRC. Finally, we find that {gamma}TuNAs activating effect opposes inhibitory regulation by stathmin. In sum, our study illuminates how {gamma}TuRC is controlled in space and time in order to build specific cytoskeletal structures.

category: biochemistry


title: Tomographic-encoded multiphoton (TEMP) microscopy

abstract: Axial scanning in multiphoton microscopy (MPM) is typically realized by mechanically shifting either the objective or the sample. However, the scan speed is usually hindered by the mechanical inertia of the bulky mass. Although the extended depth of field provided by the non-diffracting beam allows fast volumetric imaging, it abandons the axial resolution. Here, we demonstrate a novel and powerful tomographic technique using the Bessel droplet in MPM, termed Tomographic-Encoded MultiPhoton (TEMP) microscopy. We show that benefiting from the high-order nonlinear excitation in MPM, the side-lobes cancellation and smaller beam focus of the Bessel droplet realize better image quality. The TEMP microscopy allows fast axial scanning, less risks of photodamage and photobleaching, and high-resolution and high-contrast imaging. Furthermore, fewer raw images are required for the 3D image reconstruction. To demonstrate its usability and advantages for scattering tissues and biomedical applications, we showcase the TEMP microscopy with highly scattering fluorescence microspheres and mouse brain slice. More details can be visualized by the Bessel droplet compared with the conventional Gaussian and Bessel beam. More importantly, the TEMP technique is an easy-plug-in method for the current microscopy system. The TEMP microscopy is promising for fast volumetric multiphoton imaging, especially for highly scattering tissues.


title: ReDisX: a Continuous Max Flow-based framework to redefine the diagnosis of diseases based on identified patterns of genomic signatures

abstract:
Diseases originate at the molecular-genetic layer, manifest through altered biochemical homeostasis, and develop symptoms later. Hence symptomatic diagnosis is inadequate to explain the underlying molecular-genetic abnormality and individual genomic disparities. The current trends include molecular-genetic information relying on algorithms to recognize the disease subtypes through gene expressions. Despite their disposition toward disease-specific heterogeneity and cross-disease homogeneity, a gap still exists to describe the extent of homogeneity within the heterogeneous subpopulation of different diseases. They are limited to obtaining the holistic sense of the whole genome-based diagnosis resulting in inaccurate diagnosis and subsequent management.

To fill those gaps, we proposed ReDisX framework, a scalable machine learning algorithm that uniquely classifies patients based on their genomic signatures. It was deployed to re-categorizes the patients with rheumatoid arthritis and coronary artery disease. It reveals heterogeneous subpopulations within a disease and homogenous subpopulations across different diseases. Besides, it identifies GZMB as a subpopulation-differentiation marker that plausibly serves as a prominent indicator for GZMB-targeted drug repurposing.

The ReDisX framework offers a novel strategy to redefine disease diagnosis through characterizing personalized genomic signatures. It may rejuvenate the landscape of precision and personalized diagnosis, and a clue to drug repurposing.


title: Single-cell colocalization analysis using a deep generative model

abstract: 1Analyzing colocalization of single cells with heterogeneous molecular phenotypes is essential for understanding cell-cell interactions, cellular responses to external stimuli, and their biological functions in diseases and tissues. However, high-throughput methods for identifying spatial proximity at single-cell resolution are practically unavailable. Here, we introduce DeepCOLOR, a computational framework based on a deep generative model that recovers inter-cellular colocalization networks with single cell resolution by the integration of single cell and spatial transcriptomes. It segregates cell populations defined by the colocalization relationships and predicts cell-cell interactions between colocalized single cells. DeepCOLOR could identify plausible cell-cell interaction candidates in mouse brain tissues, human squamous cell carcinoma samples, and human lung tissues infected with SARS-CoV-2 by reconstructing spatial colocalization maps at single-cell resolution. DeepCOLOR is typically applicable to studying cell-cell interactions in any spatial niche. Our newly developed computational framework could help uncover molecular pathways across single cells connected with colocalization networks.


title: Short-course but not prolonged treatment with ATR inhibitor AZD6738 integrates with radiotherapy to generate a tumor antigen-specific CD8+ T cell expansion in the periphery

abstract: ATR kinase is a central regulator of the DNA damage response. While ATR kinase inhibitors (ATRis) are known to sensitize cancer cells to DNA damage, their effect on immune cells is not known. Here we show in mice that short-course AZD6738 (ATRi) on days 1-3 decreases proliferating T cells in the tumor and periphery and that cessation of ATRi causes a proliferative rebound. Integrating radiation on days 1-2 (RT) with ATRi on days 1-3 increases IFN-{beta} in the tumor and activates tumor antigen-specific CD8+ T cells in the tumor-draining lymph node (DLN). RT with short-course ATRi induces an expansion of tumor antigen-specific CD8+ T cells in the DLN. In contrast, RT with prolonged daily ATRi blocks expansion of antigen-specific CD8+ T cells, despite increased IFN-{beta} and activation of CD8+ T cells. Our data identifies critical schedule considerations for ATRi with RT, immunotherapy and genotoxic therapies.

category: cancer biology


title: Ribosome stalling during selenoprotein translation exposes a ferroptosis vulnerability in cancer

abstract: Ferroptosis is a regulated, iron-dependent form of necrosis that is triggered by the accumulation of oxidatively damaged phospholipids1-3. Glutathione peroxidase 4 (GPX4) prevents ferroptosis by converting phospholipid hydroperoxides into non-toxic lipid alcohols4, 5. Ferroptosis has been implicated in the pathology of several degenerative conditions and inhibiting GPX4 activity has emerged as a therapeutic strategy to induce cancer cell death1, 2. However, many cancer cell lines are resistant to GPX4 inhibition6, and the mechanisms that regulate GPX4 activity and ferroptosis resistance remain incompletely understood. Here, employing a synthetic lethal CRISPR-Cas9 screen in a triple negative breast cancer (TNBC) cell line, we identify LRP8 (also known as ApoER2) as a ferroptosis resistance factor. LRP8 is upregulated in cancer, and we find that it promotes ferroptosis resistance in cancer cells in both 2-dimensional (2-D) cell culture and 3-dimensional (3-D) spheroid models. Mechanistically, loss of LRP8 decreases cellular selenium levels, resulting in the reduced expression of a subset of selenoproteins, including GPX4. Remarkably, the reduction in GPX4 is not due to the classic hierarchical selenoprotein regulatory program7, 8. Instead, our findings demonstrate that the translation of GPX4 is severely impaired in the selenium-deficient LRP8 knockout (KO) cells due to extensive ribosome stalling at the inefficiently decoded GPX4 selenocysteine (SEC) UGA codon, which results in ribosome collisions and early translation termination. Thus, our findings reveal ribosome stalling and collisions during GPX4 translation as targetable ferroptosis vulnerabilities in cancer cells.


title: Loss of the repressor REST affects progesterone receptor function and promotes uterine leiomyoma pathogenesis

abstract:
Uterine Leiomyomas (UL) are benign tumors that arise in the myometrial layer of the uterus. The standard treatment option for UL is hysterectomy, although hormonal therapies such as selective progesterone receptor modulators are often used as temporary treatment options to reduce symptoms or slow the growth of tumors. However, since the pathogenesis of UL is poorly understood and most hormonal therapies are not based on UL-specific, divergent hormone signaling pathways, hallmarks that predict long-term efficacy and safety of pharmacotherapies remain largely undefined. In a previous study, we reported aberrant expression of REST/NRSF target genes activate UL growth due to the near ubiquitous loss of REST. Here, we show that ablation of the Rest gene in mouse uterus leads to UL phenotype and gene expression patterns analogous to UL, including altered estrogen and progesterone signaling pathways. We demonstrate that many of the genes dysregulated in UL harbor cis-regulatory elements bound by REST and progesterone receptor (PGR) adjacent to each other. Crucially, we identify an interaction between REST and PGR in healthy myometrium and present a putative mechanism for the dysregulation of progesterone responsive genes in UL ensuing the loss of REST. Using three Rest conditional knockout mouse lines, we provide a comprehensive picture of the impact loss of REST has in UL pathogenesis and in altering the response of UL to steroid hormones.

Significance statementAblation of Rest gene in the mouse uterus, modelling the loss REST in uterine fibroids, results in tumor formation and gene expression patterns analogous to human UL, including altered estrogen and progesterone receptor (PGR) pathways. The current study provides a putative mechanism for the aberrant function of PGR in UL.

category: physiology


title: Linker histone H1 regulates defense priming and immunity in plants

abstract: Linker H1 histones play an important role in animal and human pathogenesis, but their function in plant immunity is poorly understood. Here, we analyzed mutants of the three canonical variants of Arabidopsis H1 histones, namely H1.1, H1.2 and H1.3. We observed that double h1.1h1.2 and triple h1.1h1.2h1.3 (3h1) mutants were resistant to Pseudomonas syringae and Botrytis cinerea infections. Transcriptome analysis of 3h1 mutant plants showed that histone H1s play a key role in regulating the expression of early and late defense genes upon pathogen challenge. Moreover, 3h1 mutant plants showed enhanced production of reactive oxygen species and activation of mitogen activated protein kinases upon pathogen-associated molecular pattern (PAMP) treatment. However, 3h1 mutant plants were insensitive to priming with flg22, a well-known bacterial PAMP (pathogen-associated molecular pattern) which induces enhanced resistance in WT plants. The defective defense response in 3h1 was correlated with the enhanced DNA methylation and reduced H3K56ac levels upon priming. Our data place H1 as a molecular gatekeeper in governing dynamic changes in the chromatin landscape of defense genes during plant pathogen interaction.


title: Genome-scale metabolic modelling enables deciphering ethanol metabolism via the acrylate pathway in the propionate-producer Anaerotignum neopropionicum

abstract:
BackgroundMicrobial production of propionate from diluted streams of ethanol (e.g., deriving from syngas fermentation) is a sustainable alternative to the petrochemical production route. Yet, few ethanol-fermenting propionigenic bacteria are known, and understanding of their metabolism is limited. Anaerotignum neopropionicum is a propionate-producing bacterium that uses the acrylate pathway to ferment ethanol and CO2 to propionate and acetate. In this work, we used computational and experimental methods to study the metabolism of A. neopropionicum and, in particular, the pathway for conversion of ethanol into propionate.

ResultsOur work describes iANEO_SB607, the first genome-scale metabolic model (GEM) of A. neopropionicum. The model was built combining the use of automatic tools with an extensive manual curation process, and it was validated with experimental data from this and published studies. The model predicted growth of A. neopropionicum on ethanol, lactate, sugars and amino acids, matching observed phenotypes. In addition, the model was used to implement a dynamic flux balance analysis (dFBA) approach that accurately predicted the fermentation profile of A. neopropionicum during batch growth on ethanol. A systematic analysis of the metabolism of A. neopropionicum combined with model simulations shed light into the mechanism of ethanol fermentation via the acrylate pathway, and revealed the presence of the electron-transferring complexes NADH-dependent reduced ferredoxin:NADP+ oxidoreductase (Nfn) and acryloyl-CoA reductase-EtfAB, identified for the first time in this bacterium.

ConclusionsThe realisation of the GEM iANEO_SB607 is a stepping stone towards the understanding of the metabolism of the propionate-producer A. neopropionicum. With it, we have gained insight into the functioning of the acrylate pathway and energetic aspects of the cell, with focus on the fermentation of ethanol. Overall, this study provides a basis to further exploit the potential of propionigenic bacteria as microbial cell factories.

category: systems biology


title: Variation in subcortical anatomy: relating interspecies differences, heritability, and brain-behavior relationships

abstract: There has been an immense research focus on the topic of cortical reorganization in human evolution, but much less is known regarding the reorganization of subcortical circuits which are intimate working partners of the cortex. Here, by combining advanced image analysis techniques with comparative neuroimaging data, we systematically map organizational differences in striatal, pallidal and thalamic anatomy between humans and chimpanzees. We relate interspecies differences, a proxy for evolutionary changes, to genetics and behavioral correlates. We show that highly heritable morphological measures are significantly expanded across species, in contrast to previous findings in the cortex. The identified morphological-cognitive latent variables were associated with striatal expansion, and affective latent variables were associated with more evolutionarily-conserved areas in the thalamus and globus pallidus. These findings provide new insight into the architecture of these subcortical hubs and can provide greater information on the role of these structures in health and illness.


title: Overcoming the Reproducibility Crisis - Results of the first Community Survey of the German National Research Data Infrastructure for Neuroscience.

abstract:
The lack of reproducibility of research results is a serious problem - known as "the reproducibility crisis". The German National Research Data Infrastructure (NFDI) initiative implemented by the German Research Foundation (DFG) aims to help overcoming this crisis by developing sustainable solutions for research data management (RDM). NFDI comprises domain specific consortia across all science disciplines. In the field of neuroscience, NFDI Neuroscience (NFDI-Neuro) contributes to the strengthening of systematic and standardized RDM in its research communities. NFDI-Neuro conducted a comprehensive survey amongst the neuroscience community to determine the current needs, challenges, and opinions with respect to RDM. The outcomes of this survey are presented here. The German neuroscience community perceives barriers with respect to RDM and data sharing mainly linked to (1) lack of data and metadata standards, (2) lack of community adopted provenance tracking methods, 3) lack of a privacy preserving research infrastructure for sensitive data (4) lack of RDM literacy and (5) lack of required time and resources for proper RDM. NFDI-Neuro aims to systematically address these barriers by leading and contributing to the development of standards, tools, and infrastructure and by providing training, education, and support, as well as additional resources for RDM to its research community. The RDM work of NFDI-Neuro is conducted in close collaboration with its partner EBRAINS AISBL, the coordinating entity of the EU Flagship Human Brain Project, and its Research Infrastructure (RI) EBRAINS with more than 5000 registered users and developers from more than 70 countries of all continents. While NFDI-Neuro aims to address the German national needs, it closely aligns with the international community and the topics of the Digital Europe Program and EU Data Spaces.

Significance StatementA comprehensive survey amongst the neuroscience community in Germany determined the current needs, challenges, and opinions with respect to standardized research data management (RDM) to overcome the reproducibility crisis. Significant deficits were pointed out concerning the perceived lack of standards for data and metadata, lack of provenance tracking and versioning of data, lack of protected digital research infrastructure for sensitive data and the lack of education and resources for proper RDM. Yet, at the same time, an overwhelming majority of community members indicated that they would be willing to share their data with other researchers and are interested to increase their RDM skills. Thus, the survey results suggest that training, the provision of standards, tools, infrastructure and additional resources for RDM holds the potential to significantly facilitate reproducible research in neuroscience.


title: Brainstem speech encoding is dynamically shaped online by fluctuations in cortical α state

abstract: Experimental evidence in animals demonstrates cortical neurons innervate subcortex bilaterally to tune brainstem auditory coding. Yet, the role of the descending (corticofugal) auditory system in modulating earlier sound processing in humans during speech perception remains unclear. Here, we measured EEG activity as listeners performed speech identification tasks in different noise backgrounds designed to tax perceptual and attentional processing. Brainstem speech coding might be tied to attention and arousal states (indexed by cortical  power) that actively modulate the interplay of brainstem-cortical signal processing. When speech-evoked brainstem frequency-following responses (FFRs) were categorized according to cortical  states, low  FFRs in noise were found to be weaker, correlated positively with behavioral response times, more "decodable" via classifiers, and associated indirectly with other signal-in-noise perceptual performance. Our data provide evidence for online corticofugal interplay in humans and establish that brainstem sensory representations are continuously yoked to the ebb and flow of cortical states to dynamically update perceptual processing.


title: Endogenous viral elements reveal associations between a non-retroviral RNA virus and symbiotic dinoflagellate genomes

abstract: Endogenous viral elements (EVEs) offer insight into the evolutionary histories and hosts of contemporary viruses. This study leveraged DNA metagenomics and genomics to detect and infer the host of a non-retroviral dinoflagellate-infecting +ssRNA virus (dinoRNAV) common in coral reefs. As part of the Tara Pacific Expedition, this study surveyed 269 newly sequenced cnidarians and their resident symbiotic dinoflagellates (Symbiodiniaceae), associated metabarcodes, and publicly available metagenomes, revealing 178 dinoRNAV EVEs, predominantly among hydrocoral-dinoflagellate metagenomes. Putative associations between Symbiodiniaceae and dinoRNAV EVEs were corroborated by the characterization of dinoRNAV-like sequences in 17 of 18 scaffold-scale and one chromosome-scale dinoflagellate genome assembly, flanked by characteristically cellular sequences and in proximity to retroelements, suggesting potential mechanisms of integration. EVEs were not detected in dinoflagellate-free (aposymbiotic) cnidarian genome assemblies, including stony corals, hydrocorals, jellyfish, or seawater. The pervasive nature of dinoRNAV EVEs within dinoflagellate genomes (especially Symbiodinium), as well as their inconsistent within-genome distribution and fragmented nature, suggest ancestral or recurrent integration of this virus with variable conservation. Broadly, these findings illustrate how +ssRNA viruses may obscure their genomes as members of nested symbioses, with implications for host evolution, exaptation, and immunity in the context of reef health and disease.


title: Human peroxiredoxin 6 is essential for malaria parasites and provides a host-based drug target

abstract:
The uptake and digestion of host hemoglobin by malaria parasites during blood stage growth leads to significant oxidative damage of membrane lipids. Repair of lipid peroxidation damage is crucial for parasite survival. Here, we demonstrate that Plasmodium falciparum imports a host antioxidant enzyme, peroxiredoxin 6 (PRDX6), during hemoglobin uptake from the red blood cell cytosol. PRDX6 is a lipid peroxidation repair enzyme with phospholipase A2 (PLA2) activity. Inhibition of PRDX6 with a PLA2 inhibitor, Darapladib, increases lipid peroxidation damage in the parasite and disrupts transport of hemoglobin-containing vesicles to the food vacuole, causing parasite death. Furthermore, inhibition of PRDX6 synergistically reduces the survival of artemisinin-resistant parasites following co-treatment of parasite cultures with artemisinin and Darapladib. Thus, PRDX6 is a unique host-derived drug target for development of antimalarial drugs that could help overcome artemisinin resistance.

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title: METTL3 regulates breast cancer-associated alternative splicing switches

abstract: Alternative splicing (AS) enables differential inclusion of exons from a given transcript, thereby contributing to the transcriptome and proteome diversity. Aberrant AS patterns play major roles in the development of different pathologies, including breast cancer. N6-methyladenosine (m6A), the most abundant internal modification of eukaryotic mRNA, influences tumor progression and metastasis of breast cancer, and it has been recently linked to AS regulation. Here, we identify a specific AS signature associated with breast tumorigenesis in vitro. We characterize for the first time the role of METTL3 in modulating breast cancer-associated AS programs, expanding the role of the m6A-methyltransferase in tumorigenesis. Specifically, we find that both m6A deposition in splice site boundaries and in splicing and transcription factor transcripts, such as PHF5A and MYC, direct AS switches of specific breast cancer-associated transcripts. Finally, we show that five of the AS events validated in vitro are associated with a poor overall survival rate for patients with breast cancer, suggesting the use of these AS events as a novel potential prognostic biomarker.


title: Novel frontier in wildlife monitoring: identification of small rodent species from faecal pellets using Near-Infrared Reflectance Spectroscopy (NIRS)

abstract:
Small rodents are prevalent and functionally important across worlds biomes, making their monitoring salient for ecosystem management, conservation, forestry and agriculture. Yet, there is a dearth of cost-effective and non-invasive methods for large-scale, intensive sampling. As one such method, fecal pellet counts readily provide relative abundance indices. Given available analytical methods, feces could also allow for determination of multiple ecological and physiological variables, including community composition. We developed calibration models for rodent taxonomic determination using fecal near-infrared reflectance spectroscopy (fNIRS).

Our results demonstrate fNIRS as an accurate and robust method for predicting genus and species identity of five co-existing subarctic microtine rodent species. We show that sample exposure to weathering did not reduce accuracy, indicating suitability of the method for samples collected from the field. Diet was not a major determinant of species prediction accuracy in our samples, as diet exhibited large variation and overlap between species. While regional calibration models predicted poorly samples from another region, calibration models including samples from two regions provided a good prediction accuracy for both regions.

We propose fNIRS as a fast and cost-efficient high-throughoutput method for rodent taxonomic determination, and highlight its potential for cross-regional calibrations and use on field-collected samples. FNIRS can facilitate rodent population censuses at larger spatial extent than before deemed feasible, if combined with pellet-count based abundance indices. Given the versatility of fNIRS analytics, developing such monitoring schemes can support ecosystem- and interaction-based approaches to monitoring.

category: ecology


title: Isolation and Divergence of Peromyscus melanotis Populations Across the Madrean Sky Islands in Arizona

abstract: The Madrean sky islands have been studied for decades due to their high biodiversity, which results from the intersection of biomes and their role as refugia for populations isolated on mountain tops during the last ice age. There has been controversy and confusion about the identification of Peromyscus sp. found in the montane forests on these sky islands, which is often assumed to be the widespread and ubiquitous P. maniculatus. Here, we provide mitochondrial phylogenetic data suggesting that all individuals of Peromyscus captured on three isolated mountains in southern Arizona are Peromyscus melanotis, a species previously thought endemic to Mexico. Furthermore, with molecular clock analyses on two mitochondrial loci we show these populations have been isolated from each other for [~]11,000-50,000 years, corresponding to the transition from the last ice age. These isolated populations represent important conservation targets due to habitat loss. In addition, we suggest that future genomic and ecological research is warranted to better understand these unique populations.


title: Protein engineering approach to enhance activity assays of mono-ADP-ribosyltransferases through proximity

abstract: Human mono-ADP-ribosylating PARP enzymes have been linked to several clinically relevant processes and many of these PARPs have been suggested as potential drug targets. Despite recent advances in the field, efforts to discover such compounds have been hindered by the lack of tools to rapidly screen for high potency compounds and profile them against the different PARP enzymes of the ARTD family. We here expanded the methods and engineered mono-ART catalytic fragments to be incorporated into a cellulosome-based octavalent scaffold. Compared to the free enzymes, the scaffold-based system results in an improved activity for the tested PARPs due to improved solubility, stability and the proximity of the catalytic domains, altogether boosting their activity beyond 10-fold in the case of PARP12. This allows us to measure their enhanced activity using a simple and easily accessible homogeneous NAD+ conversion assay, facilitating its automation to reduce the assay volume and lowering the assay costs. The approach will enable the discovery of more potent compounds due to increased assay sensitivity and it can be applied to compound screening campaigns as well as inhibitor profiling.


title: Phylogenetic-informed graph deep learning to classify dynamic transmission clusters in infectious disease epidemics

abstract: In the midst of an outbreak, identification of groups of individuals that represent risk for transmission of the pathogen under investigation is critical to public health efforts. Several approaches exist that utilize the evolutionary information from pathogen genomic data derived from infected individuals to distinguish these groups from the background population, comprised of primarily randomly sampled individuals with undetermined epidemiological linkage. These methods are, however, limited in their ability to characterize the dynamics of these groups, or clusters of transmission. Dynamic transmission patterns within these clusters, whether it be the result of changes at the level of the virus (e.g., infectivity) or host (e.g., vaccination implementation), are critical in strategizing public health interventions, particularly when resources are limited. Phylogenetic trees are widely used not only in the detection of transmission clusters, but the topological shape of the branches within can be useful sources of information regarding the dynamics of the represented population. We evaluate the limitation of existing tree shape statistics when dealing with smaller sub-trees containing transmission clusters and offer instead a phylogeny-based deep learning system -DeepDynaTree- for classification of transmission cluster. Comprehensive experiments carried out on a variety of simulated epidemic growth models indicate that this graph deep learning approach is effective in predicting cluster dynamics (balanced accuracy of 0.826 vs. 0.533 and Brier score of 0.234 vs. 0.466 in independent test set). Our deployment model in DeepDynaTree incorporates a primal-dual graph neural network principle using output from phylogenetic-based cluster identification tools (available from https://github.com/salemilab/DeepDynaTree).

category: bioinformatics


title: A maximum mean discrepancy approach reveals subtle changes in α-synuclein dynamics

abstract:
Numerous models have been developed to account for the complex properties of the random walks of biomolecules. However, when analysing experimental data, conditions are rarely met to ensure model identification. The dynamics may simultaneously be influenced by spatial and temporal heterogeneities of the environment, out-of-equilibrium fluxes and conformal changes of the tracked molecules. Recorded trajectories are often too short to reliably discern such multi-scale dynamics, which precludes unambiguous assessment of the type of random walk and its parameters. Furthermore, the motion of biomolecules may not be well described by a single, canonical random walk model. Here, we develop a methodology for comparing biomolecule dynamics observed in different experimental conditions without beforehand identifying the model generating the recorded random walks. We introduce a two-step statistical testing scheme. We first use simulation-based inference to train a graph neural network to learn a fixed-length latent representation of recorded random walks. As a second step, we use a maximum mean discrepancy statistical test on the vectors of learnt features to compare biological conditions. This procedure allows us to characterise sets of random walks regardless of their generating models. We initially tested our approach on numerical trajectories. We then demonstrated its ability to detect changes in -synuclein dynamics at synapses in cultured cortical neurons in response to membrane depolarisation. Using our methodology, we identify the domains in the latent space where the variations between conditions are the most significant, which provides a way of interpreting the detected differences in terms of single trajectory characteristics. Our data show that changes in -synuclein dynamics between the chosen conditions are largely driven by increased protein mobility in the depolarised state.

Author summaryThe continuous refinement of methods for single molecule tracking in live cells advance our understanding of how biomolecules move inside cells. Analysing the trajectories of single molecules is complicated by their highly erratic and noisy nature and thus requires the use of statistical models of their motion. However, it is often not possible to unambiguously determine a model from a set of short and noisy trajectories. Furthermore, the heterogeneous nature of the cellular environment means that the molecules motion is often not properly described by a single model. In this paper we develop a new statistical testing scheme to detect changes in biomolecule dynamics within organelles without needing to identify a model of their motion. We train a graph neural network on large-scale simulations of random walks to learn a latent representation that captures relevant physical properties of a trajectory. We use a kernel-based statistical test within that latent space to compare the properties of two sets of trajectories recorded under different biological conditions. We apply our approach to detect differences in the dynamics of -synuclein, a presynaptic protein, in axons and boutons during synaptic stimulation. This represents an important step towards automated single-molecule-based read-out of pharmacological action.

category: biophysics


title: Between-area communication through the lens of within-area neuronal dynamics

abstract: Cognition arises through the interaction of distributed, but connected, brain regions. Each region can exhibit neuronal dynamics ranging from asynchronous spiking to richly patterned spatiotemporal activity, where coordinated trial-to-trial fluctuations within the population can be described by a small number of shared latent variables. Even though recent technological advances have allowed simultaneous recordings from multiple brain areas, it is still unknown how diverse and complex within-area neuronal dynamics affect between-area interactions. Using a spiking network model exhibiting a wide range of neuronal dynamics, we show that communication efficacy, as assessed by linear measures, depends on the origin of low-dimensional shared variability. More specifically, a mismatch in within-area dimensionality or a misalignment of shared variability between upstream and downstream areas compromise communication. However, even in scenarios with seemingly weak linear communication, the downstream area is effectively driven by the upstream activity. These results expose the limitations of linear measures when analyzing between-area communication in circuits with diverse neuronal dynamics.

category: neuroscience