title: Social mobility and biological aging among older adults in the United States

abstract:
Lower socioeconomic status is associated with faster biological aging, the gradual and progressive decline in system integrity that accumulates with advancing age. Efforts to promote upward social mobility may therefore extend healthy lifespan. However, recent studies suggest that upward mobility may also have biological costs related to the stresses of crossing social boundaries. We analyzed blood-chemistry and DNA methylation (DNAm) data from n=9286 participants in the 2016 Health and Retirement Study (HRS) Venous Blood Study to test associations of life-course social mobility with biological aging. We quantified social mobility from childhood to later-life using data on childhood family characteristics, educational attainment, and wealth accumulation. We quantified biological aging using three DNA methylation "clocks" and three blood-chemistry algorithms. We observed substantial social mobility among study participants. Those who achieved upward mobility exhibited less-advanced and slower biological aging. Associations of upward mobility with less-advanced and slower aging were consistent for blood-chemistry and DNAm measures of biological aging and were similar for men and women and for Black and White Americans (Pearson-r effect-sizes ~0.2 for blood-chemistry measures and the DNAm GrimAge clock and DunedinPoAm pace-of-aging measures; effect-sizes were smaller for the DNAm PhenoAge clock). Analysis restricted to educational mobility revealed differential effects by racial identity, suggesting that mediating links between educational mobility and healthy aging may be disrupted by structural racism. In contrast, mobility producing accumulation of wealth appeared to benefit White and Black Americans equally, suggesting economic intervention to reduce wealth inequality may have potential to heal disparities in healthy aging.

Significance StatementUpward social mobility may disrupt effects of early-life disadvantage on aging-related health decline. However, the stresses of crossing social boundaries can have biological costs. To investigate the balance of these forces, we analyzed social mobility from reports of childhood circumstances, education, and later-life wealth in 9,286 older adults in the US Health and Retirement Study. We quantified life-course health impacts of social mobility from blood-chemistry and DNA-methylation analysis of biological aging. We found that educational mobility alone benefited Black Americans less than White Americans, whereas mobility that produced accumulation of wealth into later-life was associated with delayed biological aging across social categories. Black-White disparities in healthy-aging outcomes of educational mobility may reflect inequalities in social gains realized from education.

category: physiology


title: Crustacean cardiac ganglion model reveals constraints on morphology and conductances

abstract: The crustacean cardiac ganglion (CG) network coordinates the rhythmic contractions of the heart muscle to control the circulation of blood. The network consists of 9 cells, 5 large motor cells (LC1-5) and 4 small endogenous pacemaker cells (SCs). We report a new three-compartmental biophysical model of an LC that is morphologically realistic and includes provision for inputs from the SCs via a gap-junction coupled spike-initiation-zone (SIZ) compartments. To determine physiologically viable LC models in this realistic configuration, maximal conductances in three compartments of an LC are determined by random sampling from a biologically-characterized 9D-parameter space, followed by a three-stage rejection protocol that checks for conformity with electrophysiological features from single cell traces. LC models that pass the single cell rejection protocol are then incorporated into a network model which is then used in a final rejection protocol stage. Using disparate experimental data, the study provides hitherto unknown structure-function insights related to the crustacean cardiac ganglion large cell, including predictions about morphology including the role of its SIZ, and the differential roles of active conductances in the three compartments. Further, we extend analyses of emergent conductance relationships and correlations in model neurons relative to their biological counterparts, allowing us to make inferences both with respect to the biological system as well as the implications of the ability to detect such relationships in populations of model neurons going forward.

category: neuroscience


title: Evaluating test-retest reliability and sex/age-related effects on temporal clustering coefficient of dynamic functional brain networks

abstract: The multilayer dynamic network model has been proposed as an effective method to understand how the brain functions dynamically. Specially, derived from the definition of clustering coefficient in static networks, the temporal clustering coefficient provides a direct measure of topological stability of dynamic brain networks and shows potential in predicting altered brain functions in both normal and pathological conditions. However, test-retest reliability and demographic-related effects on this measure remain to be evaluated. Using a publicly available dataset from the Human Connectome Project consisting of 337 young healthy adults (157 males/180 females; 22 to 37 years old), the present study investigated: (1) the test-retest reliability of temporal clustering coefficient across four repeated resting-state functional magnetic resonance imaging scans as measured by intraclass correlation coefficient (ICC); and (2) sex- and age-related effects on temporal clustering coefficient. The results showed that (1) the temporal clustering coefficient had overall moderate test-retest reliability (ICC > 0.40 over a wide range of densities) at both global and subnetwork levels; (2) female subjects showed significantly higher temporal clustering coefficient than males at both global and subnetwork levels, in particular within the default-mode and subcortical regions; (3) temporal clustering coefficient of the subcortical subnetwork was negatively correlated with age in young adults. Our findings suggest that temporal clustering coefficient is a reliable and reproducible approach for the identification of individual differences in brain function, and provide evidence for sex and age effects on human brain dynamic connectome.


title: Real-Time Structure Search and Structure Classification for AlphaFold Protein Models

abstract: AlphaFold2 showed a substantial improvement in the accuracy of protein structure prediction. Following the release of the software, whole-proteome protein structure predictions by AlphaFold2 for 21 organisms were made publicly available. Here, we developed the infrastructure, 3D-AF-Surfer, to enable real-time structure-based search for the AlphaFold2 models by combining molecular surface representation with 3D Zernike descriptors and deep neural networks.

category: bioinformatics


title: Resistance to chemical carcinogenesis induction via a dampened inflammatory response in naked mole-rats

abstract:
Naked mole-rats (NMRs) have a very low spontaneous carcinogenesis rate, which has prompted scientists to study their cancer resistance mechanisms in order to provide clues for human cancer prevention. Although cancer resistance in NMRs has been intensively investigated at the cellular level, it is still unknown how strongly resistant NMR individuals are to carcinogenesis and how NMR tissues respond to experimental carcinogenesis induction. Here, we show that NMRs exhibit extraordinary resistance against potent chemical carcinogenesis induction through a dampened inflammatory response. Although carcinogenic insults damaged skin cells of both NMRs and mice, NMR skin showed markedly lower immune cell infiltration and reduced induction of inflammatory genes. NMRs harbor loss-of-function mutations in receptor-interacting protein kinase 3 (RIPK3) and mixed lineage kinase domain-like (MLKL) genes, which are essential for necroptosis, a type of necrotic cell death that activates strong inflammation. A necroptosis-inducing stimulus did not increase death of NMR cells. After carcinogenic insults, leakage of the HMGB1, a marker of necrotic cell death, was not increased in NMR skin. In mice, inhibition or knockout of RIPK3 reduced immune cell infiltration and delayed the onset of chemical carcinogenesis. Therefore, necroptosis deficiency may serve as a cancer resistance mechanism via attenuating the inflammatory response in NMRs. Our study sheds light on the importance of a dampened inflammatory response as a non-cell-autonomous cancer resistance mechanism in NMRs. Further in vivo study of the unusual tissue immune system and carcinogenesis resistance of NMRs may lead to the development of new strategies to prevent carcinogenesis in humans.

Significance StatementIn contrast with intensive studies of cancer resistance mechanisms in naked mole-rats (NMRs) at the cellular level, little is known about how NMR individuals respond to carcinogenesis induction, despite the fact that cell-to-cell interactions in tissues regulate carcinogenesis in vivo. Here, we demonstrate that NMRs are remarkably resistant to chemical carcinogenesis induction and characteristically have attenuated tissue inflammatory responses to carcinogenic insults. NMRs have loss-of-function mutations in RIPK3 and MLKL genes and thus cannot activate necroptosis, a type of inflammation-inducing cell death. RIPK3 inhibition in mice reduced immune cell infiltration in response to carcinogenic insults and delayed the onset of chemical-induced carcinogenesis. Our results highlight the importance of studies on dampened tissue inflammatory responses to understand cancer resistance of NMRs.

category: cancer biology


title: Structural Knowledge Transfer of Panoptic Kidney Segmentation to Other Stains, Organs, and Species

abstract:
BackgroundPanoptic segmentation networks are a newer class of image segmentation algorithms that are constrained to understand the difference between instance-type objects (objects that are discrete countable entities, such as renal tubules) and group-type objects (uncountable, amorphous regions of texture such as renal interstitium). This class of deep networks has unique advantages for biological datasets, particularly in computational pathology.

MethodsWe collected 126 periodic acid Schiff whole slide images of native diabetic nephropathy, lupus nephritis, and transplant surveillance kidney biopsies, and fully annotated them for the following micro-compartments: interstitium, glomeruli, globally sclerotic glomeruli, tubules, and arterial tree (arteries/arterioles). Using this data, we trained a panoptic feature pyramid network. We compared performance of the network against a renal pathologists annotations, and the methods transferability to other computational pathology domain tasks was investigated.

ResultsThe panoptic feature pyramid networks showed high performance as compared to renal pathologist for all of the annotated classes in a testing set of transplant kidney biopsies. The network was not only able to generalize its object understanding across different stains and species of kidney data, but also across several organ types.

ConclusionsPanoptic networks have unique advantages for computational pathology; namely, these networks internally model structural morphology, which aids bootstrapping of annotations for new computational pathology tasks.

category: pathology


title: A multiscale model of the cardiovascular system that incorporates baroreflex control of chronotropism, cell-level contractility, and vascular tone

abstract: Multiscale models of the cardiovascular system can provide new insights into physiological and pathological processes. Models that incorporate molecular-level effects may be particularly useful for clinical applications because they can predict the functional consequences of pharmaceuticals that modulate the properties of molecules and/or the rate at which they undergo reactions. PyMyoVent is a computer model that bridges from molecular to organ-level function and simulates a left ventricle pumping blood through the systemic circulation. Initial work with PyMyoVent focused on the End Systolic Pressure Volume Relationship and ranked potential therapeutic strategies by their impact on contractility. This manuscript extends PyMyoVent by adding baroreflex control of arterial pressure. The reflex algorithm is inspired by the underlying biology. It uses an afferent signal derived from arterial pressure to drive a kinetic model that mimics the net result of neural processing in the medulla and cell-level responses to autonomic drive. The kinetic model outputs control signals that are constrained between limits that represent maximum parasympathetic and maximum sympathetic drive and which modulate heart rate, intracellular Ca2+ dynamics, the molecular-level function of both the thick and the thin myofilaments, and vascular tone. Simulations show that the algorithm can regulate mean arterial pressure at set-points ranging from [~]30 to [~]150 mmHg as well as maintaining arterial pressure when challenged by rapid changes in blood volume or sudden increases in aortic resistance.


title: Short term treatment with a cocktail of rapamycin, acarbose and phenylbutyrate slows aging in mice

abstract: Pharmaceutical intervention of aging requires targeting multiple pathways, thus there is rationale to test combinations of drugs each targeting different but overlapping processes. In order to determine if combining drugs previously shown to improve lifespan would have greater impact than any individuyal drug, a diet containing rapamycin at 14 ppm, acarbose at 1000 ppm, and phenylbutyrate at 1000 ppm was fed to 20-month-old C57BL/6 and HET3 4-way cross mice of both sexes for three months. Mice fed the cocktail diet showed a strain and gender-dependent phenotype consistent with healthy aging including decreased body fat and blood glucose, improved cognition, and increased grip strength and walking ability compared to mice fed individual drug or control diets. A cocktail diet containing [1/2] dosing of each compound was overall less effective than the full dose. The composite age-related lesion score of heart, lungs, liver and kidney was decreased in mice fed the cocktail diet compared to mice fed individual drug or control diets suggesting an interactive advantage of the three drugs. Senescence and inflammatory cytokine levels in kidneys from mice fed the cocktail diet were lower than in kidneys from mice fed control diet, and consistent with low expression levels in kidneys from young untreated mice, suggesting the cocktail diet delayed aging partly by senolytic and anti-inflammatory effects.

category: systems biology


title: The many layers of BOLD. On the contribution of different vascular compartments to laminar fMRI.

abstract: Ultra-high field functional Magnetic Resonance Imaging (fMRI) offers the spatial resolution to measure neural activity at the scale of cortical layers. Most fMRI studies make use of the Blood-Oxygen-Level Dependent (BOLD) signal, arising from a complex interaction of changes in cerebral blood flow (CBF) and volume (CBV), and venous oxygenation. However, along with cyto- and myeloarchitectural changes across cortical depth, laminar fMRI is confronted with additional confounds related to vascularization differences that exist across cortical depth. In the current study, we quantify how the non-uniform distribution of macro- and micro-vascular compartments, as measured with Gradient-Echo (GE) and Spin-Echo (SE) scan sequences, respectively, affect laminar BOLD fMRI responses following evoked hypercapnic and hyperoxic breathing conditions. We find that both macro- and micro-vascular compartments are capable of comparable theoretical maximum signal intensities, as represented by the M-scaling parameter. However, the capacity for vessel dilation, as reflected by the cerebrovascular reactivity (CVR), is approximately three times larger for the macro-compared to the micro-vasculature at superficial layers. Finally, there is roughly a 35% difference in CBV estimates between the macro- and micro-vascular compartments, although this relative difference is approximately uniform across cortical depth.


title: Neural knowledge assembly in humans and deep networks

abstract: Human understanding of the world can change rapidly when new information comes to light, such as when a plot twist occurs in a work of fiction. This flexible "knowledge assembly" requires few-shot reorganisation of neural codes for relations among objects and events. However, existing computational theories are largely silent about how this could occur. Here, participants learned a transitive ordering among novel objects within two distinct contexts, before exposure to new knowledge that revealed how they were linked. BOLD signals in dorsal frontoparietal cortical areas revealed that objects were rapidly and dramatically rearranged on the neural manifold after minimal exposure to linking information. We then adapt stochastic online gradient descent to permit similar rapid knowledge assembly in a neural network model.


title: Oxytocin reduces interoceptive influences on empathy-for-pain in the anterior insula

abstract:
Empathy-for-pain states are underpinned by interoception, i.e the central representation of internal states. Cardiac signals occur in a phasic manner; baroreceptor discharges at systole communicate the heartbeats strength. These signals modulate pain and emotion processing. We tested whether these phasic interoceptive signals modulate empathy-for-pain. As oxytocin (OT) enhances empathy and modulates interoceptive signals precision, we also tested if OT administration impacts empathy-for-pain via interoceptive mechanisms.

Male subjects (N=32) attended three sessions to perform psychometric tests and an fMRI empathy-for-pain task, after intranasal administration of OT or placebo (40IU). Pictures of hands in painful or non-painful context were presented at systole or diastole. Effects of drug, emotion and cardiac timing on behaviour and brain activity was tested using general and mixed-effects linear models.

Across conditions, activation was observed within regions implicated in pain and empathy-for-pain, with insula activation greater in the right than left hemisphere. OT administration, compared to placebo, attenuated the reactivity of some regions, including anterior cingulate cortex, but presentation of stimuli at systole blocked the OT attenuating effect.

Our data suggest that OT alters the processing of motivationally-salient social cues, interacting with interoceptive signals. Our findings may inform targeted use of OT in psychiatric conditions linked to aberrant interoceptive processing.


title: Longitudinal single-cell transcriptional dynamics throughout neurodegeneration in SCA1

abstract: Neurodegeneration is a protracted process involving progressive changes in myriad cell types that ultimately result in neuronal death. Changes in vulnerable neuronal populations are highly influenced by concomitant changes in surrounding cells, complicating experimental approaches to interrogate the simultaneous events that underlie neurodegeneration. To dissect how individual cell types within a heterogeneous tissue contribute to the pathogenesis and progression of a neurodegenerative disorder, we performed longitudinal single-nucleus RNA sequencing of the mouse and human spinocerebellar ataxia type 1 (SCA1) cerebellum, establishing continuous dynamic trajectories of each population. Furthermore, we defined the precise transcriptional changes that precede loss of Purkinje cells and identified early oligodendroglial impairments that can profoundly impact cerebellar function. Finally, we applied a deep learning method to accurately predict disease state and identify drivers of disease. Together, this work uncovers new roles for diverse cerebellar cell types in SCA1 and provides a generalizable analysis framework for studying neurodegeneration.


title: Tickle contagion in the somatosensory cortex

abstract: The cellular mechanisms of emotional contagion are unknown. We investigated tickle contagion and the underlying neuronal representations in rats. We recorded trunk somatosensory cortex activity of observer rats while they received tickling, audio-visual playback of tickling footage, and while they witnessed tickling of demonstrator rats. Observers vocalized, and showed "Freudensprunge" ("joy jumps") during witnessing live tickling, while they showed little behavioral responses to playbacks. A fraction of trunk somatosensory neurons responded to both direct and witnessed tickling in action-specific manner. The correlation between direct and witnessed tickling responses increased towards deeper cortical layers. Tickle-mirror neurons but not non-mirror neurons discharged prior to and during vocalizations and hence might drive contagious  laughter. We conclude that trunk somatosensory cortex represents mirrored ticklishness.


title: Structural basis of malaria transmission blockade by a monoclonal antibody to gamete fusogen HAP2

abstract: HAP2 is a transmembrane gamete fusogen found in multiple eukaryotic kingdoms and is structurally homologous to viral class II fusogens. Studies in Plasmodium have suggested that HAP2 is an attractive target for vaccines that block transmission of malaria. HAP2 has three extracellular domains, arranged in the order D2, D1, and D3. Here, we report monoclonal antibodies against the D3 fragment of Plasmodium berghei HAP2 and crystal structures of D3 in complex with Fab fragments of two of these antibodies, one of which blocks fertilization of Plasmodium berghei in vitro and transmission of malaria in mosquitos. We also show how this Fab binds the complete HAP2 ectodomain with electron microscopy. The two antibodies cross-react with HAP2 among multiple plasmodial species. Our characterization of the Plasmodium D3 structure, HAP2 ectodomain architecture, and mechanism of inhibition provide insights for the development of a vaccine to block malaria transmission.

category: immunology


title: In-vitro cellular reprogramming to model gonad development and its disorders

abstract: During embryonic development, mutually antagonistic signaling cascades determine the fate of the bipotential gonad towards a testicular or ovarian identity. Errors in this process result in human Disorders of Sex Development (DSDs), where there is discordance between chromosomal, gonadal, and anatomical sex. The absence of an appropriate, accessible in-vitro system is a major obstacle in understanding mechanisms of sex-determination/DSDs. Here, we describe protocols for differentiation of mouse and human pluripotent cells towards gonadal progenitors. Transcriptomic analysis reveals that the in-vitro-derived murine gonadal cells are equivalent to E11.5 in-vivo progenitors. Using similar conditions, Sertoli-like cells derived from 46,XY human induced pluripotent stem cells (hiPSCs) exhibit sustained expression of testis-specific genes, secrete AMH, migrate and form tubular structures. The cells derived from a 46,XY DSD female hiPSCs, carrying a NR5A1 variant, show aberrant gene expression and absence of tubule formation. CRISPR/Cas9-mediated correction of the variant rescued the phenotype. This is a robust tool to understand mechanisms of sex-determination and model DSDs.

category: developmental biology


title: Environmental DNA analysis needs local reference data to inform taxonomy-based conservation policy:A case study from Aotearoa / New Zealand

abstract: Effective management of biodiversity requires regular surveillance of multiple species. Analysis of environmental DNA by metabarcoding (eDNA) holds promise to achieve this relatively easily. However, taxonomic inquiries into eDNA data need suitable molecular reference data, which are often lacking. We evaluate the impact of this reference data void in a case study of fish diversity in the remote fiords of New Zealand. We compared eDNA-derived species identifications against Baited Remote Underwater Video (BRUV) data collected at the same time and locations as the eDNA data. Furthermore, we cross referenced both eDNA and BRUV data against species lists for the same region obtained from literature surveys and the Ocean Biodiversity Information System (OBIS). From all four data sources, we obtained a total of 116 species records (106 ray-finned fishes, 10 cartilaginous fishes; 59 from literature, 44 from eDNA, 25 from BRUV, 25 from OBIS). Concordance of taxonomies between the data sources dissolved with lowering taxonomic levels, most decisively so for eDNA data. BRUV agreed with local biodiversity information much better and fared better in detecting regional biodiversity dissimilarities. We provide evidence that eDNA metabarcoding will remain a powerful but impaired tool for species-level biodiversity management without locally generated reference data.

category: ecology


title: Multi-species mechanistic model of functional response provides new insights into predator-mediated interactions in a vertebrate community

abstract: 1.AO_SCPLOWBSTRACTC_SCPLOWPrey handling processes are considered a key driver of short-term positive indirect effects between prey sharing the same predator. However, a growing body of research indicates that predators are rarely limited by such processes in the wild. Density-dependent changes in predator foraging be-havior can also generate positive indirect effects but they are rarely included as explicit functions of prey densities in functional response models. With the aim of untangling proximate drivers of species interactions in natural communities and improve our ability to quantify interaction strength, we extended the Holling multi-species model by including density-dependent changes in predator foraging behavior. Our model, based on species traits and behavior, was inspired by the verte-brate community of the arctic tundra, where the main predator (the arctic fox) is an active forager feeding primarily on cyclic small rodent (lemming) populations and eggs of various tundra-nesting bird species. Short-term positive indirect effects of lemmings on birds have been documented over the circumpolar Arctic but the underlying proximate mechanisms remain poorly known. We used a unique data set, containing high-frequency GPS tracking, accelerometer, behavioral, and experimental data to parameterize the multi-species model, and a 15-year time series of prey densities and bird nesting success to evaluate inter-action strength between species. Our results showed that: (i) prey handling processes play a minor role in our system and (ii) density-dependent changes in predator foraging behavior can be the proximate drivers of a predominant predator-mediated interaction observed in the arctic tundra. Mechanisms outlined in our study have been little studied and may play a significant role in natural systems. We hope that our study will provide a useful starting point to build mechanistic models of predation, and we think that our approach could conceivably be applied to a broad range of food webs.


title: Predominance of clonal propagation conceals extinction risks of the highly endangered floodplain herb Cnidium dubium

abstract:
Habitat loss and degradation due to human-induced landscape alterations are considered to be a major threat to biodiversity. The decline of biodiversity may occur with a time delay leading to a so called extinction debt. Therefore, determining extinction risks and conservation status is not always straightforward. Several life history traits might play a role for the accumulation of an extinction debt. Thus, perennial plant species capable of vegetative propagation might be able to persist temporarily in degraded habitats even though sexual and evolutionary processes are effectively halted.

We studied Cnidium dubium, which occurs in scattered patches along river corridors in Central Europe and is critically endangered in Germany. It is a perennial species which is able to propagate clonally. Our aims were to reconstruct demographic processes regarding clonal propagation and gene flow along 400 km of river stretch and with respect to the position in the flooplain, i.e. before or behind dykes. We also wanted to determine whether there is evidence for an extinction debt in C. dubium and to use our insights for conservation recommendations.

For this, we used nuclear microsatellites and maternally inherited chloroplast DNA markers and applied a systematic grid based sampling strategy for small scale geographic structures.

We observed a high level of clonal propagation. In 935 analysed plants we observed only 121 different genotypes and of 50 studied patches of C. dubium the majority (31 patches) consisted of one single genotype each. Patch size and position were correlated with clonal diversity. Large patches and patches behind dykes exhibited higher clonal diversity. There was no evidence for a large scale genetic substructuring of the study area and no differences in overall genetic diversity between upstream and downstream patches as well as between patches before and behind the dykes. High levels of heterozygosity and a high number of 18 chloroplast DNA haplotypes togetherwith a slightly elevated inbreeding coefficient (Fis) point toward a high level of ancestral polymorphism in an out of equilibrium population due to high levels of clonal propagation and low levels of gene flow and recombination. Therefore, we assume that an extinction debt is present in C. dubium. As a management strategy, we propose to transplant ramets between multiple patches to increase the number of mating partners and therefore restore sexual reproduction.


title: Geographic distribution and future expansion of Aedes albopictus in the Democratic Republic of the Congo

abstract: Aedes albopictus with an Asian origin has been reported from central African countries. The establishment of this mosquito species poses a serious threat as the vector of various infectious diseases. Since information about Ae. albopictus in Democratic Republic of the Congo (DRC) is scarce, we investigated the current distribution of this mosquito species. Based on the factors affecting the distribution, we predicted future distribution. We conduced entomological surveys in Kinshasa and three neighboring cities from May 2017 to September 2019. The survey was extended to seven inland cities. A total of 19 environmental variables were examined using the maximum entropy method to identify areas suitable for Ae. albopictus to establish a population. We found Ae. albopictus at 21 of 23 sites in Kinshasa and three neighboring cities. For the first time Ae. albopictus was also found from three of seven inland cities, while it was not found in four cities located in the eastern and southeastern parts of DRC. A maximum entropy model revealed that the occurrence of Ae. albopictus was positively associated with maximum temperature of the warmest month, and negatively associated with wider mean diurnal temperature range and enhanced vegetation index. The model predicted that most parts of DRC are suitable for the establishment of the mosquito. The unsuitable areas were the eastern and southeastern highlands, which have low temperatures and long dry seasons. We confirmed that Ae. albopictus is well established in Kinshasa and its neighboring cities. The expansion of Ae. albopictus to the inland is ongoing, and in the future the mosquito may establish in most parts of DRC.


title: Eurasian lynx populations in Western Europe: What prospects for the next 50 years?

abstract: Persistence of viable populations may be uncertain for large carnivore species, especially for those established in human-dominated landscapes. Here, we studied the Eurasian lynx in Western Europe established in the Upper Rhine metapopulation (i.e., Jura, Vosges-Palatinian and Black Forest populations) and in the Alpine population. These populations are currently considered as endangered or critically endangered due to high anthropogenic mortality and isolation. We assessed lynx persistence over a 50-year time horizon by implementing a spatially-explicit individual-based model while accounting for road mortality and habitat selection. Forecasts showed a steady growth rapidly reaching a stabilization phase with high resident female occupancy for the Alpine and Jura populations, and a positive growth for the newly re-established Vosges-Palatinian population. Moreover, this population showed a difference in female occupancy between the northern part, where a recent reintroduction program was conducted in the Palatinate Forest, and the southern part. Only the group of individuals in the Black Forest had an irregular growth probably due to the small number of only male lynx at start of the simulation and poor connectivity to surrounding populations. Exchanges of individuals between populations were limited, the Jura population playing the role of a crossroad. Persistence of lynx in Western Europe seems likely on a large scale over the next 50 years. However, lynx persistence in the southern part of the Vosges-Palatinian population and in the Black Forest appears challenging without long-term conservation management.


title: transferGWAS: GWAS of images using deep transfer learning

abstract:
MotivationMedical images can provide rich information about diseases and their biology. However, investigating their association with genetic variation requires non-standard methods. We propose transferGWAS, a novel approach to perform genome-wide association studies directly on full medical images. First, we learn semantically meaningful representations of the images based on a transfer learning task, during which a deep neural network is trained on independent but similar data. Then, we perform genetic association tests with these representations.

ResultsWe validate the type I error rates and power of transferGWAS in simulation studies of synthetic images. Then we apply transferGWAS in a genome-wide association study of retinal fundus images from the UK Biobank. This first-of-a-kind GWAS of full imaging data yielded 60 genomic regions associated with retinal fundus images, of which 7 are novel candidate loci for eye-related traits and diseases.

Availability and ImplementationOur method is implemented in Python and available at https://github.com/mkirchler/transferGWAS/

category: genetics


title: High-precision spatial analysis of mouse courtship vocalization behavior reveals sex and strain differences

abstract:
Mice display a wide repertoire of vocalizations that varies with sex, strain, and context. Especially during social interaction, mice emit sequences of ultrasonic vocalizations (USVs) of high complexity. As animals of both sexes vocalize, a reliable attribution of USVs to their emitter is essential.

The state-of-the-art in sound localization for USVs in 2D allows spatial localization at a resolution of multiple centimeters. However, animals interact at closer ranges, e.g. snout-to-snout. Hence, improved algorithms are required to reliably assign USVs. We present a novel algorithm, SLIM (Sound Localization via Intersecting Manifolds), that achieves a 3-fold improvement in accuracy (12-14.3mm) using only 4 microphones and extends to many microphones and localization in 3D. This accuracy allows reliable assignment of 84.3% of all USVs in our dataset.

We apply SLIM to courtship interactions between adult C57Bl/6J wildtype mice and those carrying a heterozygous Foxp2 variant (R552H). The improved spatial accuracy reveals detailed vocalization preferences for specific spatial relations between the mice. Specifically, vocalization probability, duration, Wiener entropy, and frequency level differed in particular spatial relations between WT females, Foxp2-R552H and WT males.

In conclusion, the improved attribution of vocalizations to their emitters provides a foundation for better understanding social vocal behaviors.

category: animal behavior and cognition


title: Dissecting tumor cell programs through group biology estimation in clinical single-cell transcriptomics

abstract: Given the growing number of clinically integrated cancer single-cell transcriptomic studies, robust differential enrichment methods for gene signatures to dissect tumor cellular states for discovery and translation are critical. Current analysis strategies neither adequately represent the hierarchical structure of clinical single-cell transcriptomic datasets nor account for the variability in the number of recovered cells per sample, leading to results potentially confounded by sample-driven biology with high false positives instead of accurately representing true differential enrichment of group-level biology (e.g., treatment responders vs. non-responders). This problem is especially prominent for single-cell analyses of the tumor compartment, because high intra-patient similarity (as opposed to inter-patient similarity) results in stricter hierarchical structured data that confounds enrichment analysis. Furthermore, to identify signatures which are truly representative of the entire group, there is a need to quantify the robustness of otherwise statistically significant signatures to sample exclusion. Here, we present a new nonparametric statistical method, BEANIE, to account for these issues, and demonstrate its utility in two cancer cohorts stratified by clinical groups to reduce biological hypotheses and guide translational investigations. Using BEANIE, we show how the consideration of sample-specific versus group biology greatly decreases the false positive rate and guides identification of robust signatures that can also be corroborated across different cell type compartments.


title: scGAD: single-cell gene associating domain scores for exploratory analysis of scHi-C data

abstract:
SummaryQuantitative tools are needed to leverage the unprecedented resolution of single-cell high-throughput chromatin conformation (scHi-C) data and to integrate it with other single-cell data modalities. We present single-cell gene associating domain (scGAD) scores as a dimension reduction and exploratory analysis tool for scHi-C data. scGAD enables summarization at the gene level while accounting for inherent gene-level genomic biases. Low-dimensional projections with scGAD capture clustering of cells based on their 3D structures. scGAD enables identifying genes with significant chromatin interactions within and between cell types. We further show that scGAD facilitates the integration of scHi-C data with other single-cell data modalities by enabling its projection onto reference low-dimensional embeddings.

AvailabilityscGAD is part of the BandNorm R package at https://sshen82.github.io/BandNorm/articles/scGAD-tutorial.html.

Contactkeles@stat.wisc.edu, yzheng23@fredhutch.org

Supplementary informationSupplementary data are available at Bioinformatics online.


title: Extrachromosomal Amplification of Human Papillomavirus Episomes as a Mechanism of Cervical Carcinogenesis

abstract: Integration of Human Papillomaviruses (HPV) is an important mechanism of carcinogenesis but is absent in a significant fraction of HPV16+ tumors. We applied long-read whole-genome sequencing (WGS) to cervical cancer cell lines and tumors. In two HPV16+ cell lines, we identified large tandem arrays of full-length and truncated viral genomes integrated into multiple locations indicating formation as extrachromosomal DNA (HPV superspreading). An HPV16+ cell line with episomal DNA has tandem arrays of full-length, truncated, and rearranged HPV16 genomes (multimer episomes). WGS of HPV16+ cervical tumors revealed that 11/20 with only episomal HPV (EP) have intact monomer episomes. The remaining nine EP tumors have multimer and rearranged HPV genomes. Most HPV rearrangements disrupt the E1 and E2 genes, and EP tumors overexpress the E6 and E7 viral oncogenes. Tumors with both episomal and integrated HPV16 display multimer episomes and concatemers of human and viral sequences. One tumor has a recurrent deletion of an inhibitory site regulating E6 and E7 expression, and another has a recurrent duplication consistent with HPV superspreading. Therefore, HPV16 can cause cancer without integration through aberrant episomal replication, forming rearranged and multimer episomes.


title: Loss of epigenetic regulation disrupts lineage integrity, reactivatesmultipotency and promotes breast cancer

abstract:
Systematically investigating the scores of genes mutated in cancer and discerning real drivers from inconsequential bystanders is a prerequisite for Precision Medicine, but remains challenging. Here, we developed a somatic CRISPR/Cas9 mutagenesis screen to study 215 recurrent  long-tail breast cancer genes, which revealed epigenetic regulation as major tumor suppressive mechanism. We report that core or accessory components of the COMPASS histone methylase complex including KMT2C, KDM6A, BAP1 and ASXL2 ("EpiDrivers") cooperate with PIK3CAH1047R to transform mouse and human breast epithelial cells. Mechanistically, we find that Cre-mediated activation of PIK3CAH1047R elicited an aberrant alveolar lactation program in luminal cells, which was exacerbated upon loss of EpiDrivers. Remarkably, EpiDriver loss in basal cells also triggered an alveolar-like lineage conversion and accelerated formation of luminal-like tumors, suggesting a basal origin for luminal tumors. As EpiDrivers are mutated in 39% of human breast cancers, lineage infidelity and lactation mimicry may significantly contribute to early steps of breast cancer progression.

Statement of significanceInfrequently mutated genes comprise most of the mutational burden in breast tumors but are poorly understood. In-vivo CRISPR screening identified functional tumor suppressors that converged on epigenetic regulation. Loss of epigenetic regulators accelerated tumorigenesis and revealed lineage infidelity and aberrant expression of lactation genes as potential early events in tumorigenesis.


title: The behavioral effects of gestational and lactational benzopyrene exposure vary by sex and genotype in mice with differences at the Ahr and Cyp1a2 loci

abstract:
Benzo[a]pyrene (BaP) is a polycyclic aromatic hydrocarbon (PAH) and known carcinogen in the Top 10 on the United States list of priority pollutants. Humans are exposed through a variety of sources including tobacco smoke, grilled foods and fossil fuel combustion. Recent studies of children exposed to higher levels of PAHs during pregnancy and early life have identified numerous adverse effects on the brain and behavior that persist into school age and adolescence. Our studies were designed to look for genotype and sex differences in susceptibility to gestational and lactational exposure to BaP using a mouse model with allelic differences in the aryl hydrocarbon receptor and the xenobiotic metabolizing enzyme CYP1A2. Pregnant dams were exposed to 10 mg/kg/day of BaP in corn oil-soaked cereal or the corn oil vehicle alone from gestational day 10 until weaning at postnatal day 25. Neurobehavioral testing began at P60 using one male and one female per litter. We found main effects of sex, genotype and treatment as well as significant gene x treatment and sex x treatment interactions. BaP-treated female mice had shorter latencies to fall in the Rotarod test. High-affinity AhrbCyp1a2(-/-) mice had greater impairments in Morris water maze. Interestingly, poor-affinity AhrdCyp1a2(-/-) mice also had deficits in spatial learning and memory regardless of treatment. We believe our findings provide future directions in identifying human populations at highest risk of early life BaP exposure, because our model mimics known human variation in our genes of interest. Our studies also highlight the value of testing both males and females in all neurobehavioral studies.

HighlightsO_LIGestational and lactational benzo[a]pyrene (BaP) exposure has sex and genotype-specific neurobehavioral effects in mice.
C_LIO_LIFemale mice were more susceptible to motor deficits following developmental BaP exposure. Males were more susceptible to deficits in reversal learning and memory.
C_LIO_LIAhrbCyp1a2(-/-) knockout mice were more susceptible to spatial learning and memory deficits following developmental BaP exposure.
C_LIO_LIPoor-affinity AhrdCyp1a2(-/-) mice had deficits in spatial learning and memory regardless of treatment.
C_LI

category: pharmacology and toxicology


title: Polar lipids are linked to nanoparticles in xylem sap of temperate angiosperm species

abstract: Xylem sap of angiosperm species has been found to include low concentrations of polar lipids and nanoparticles, including surfactant-coated nanobubbles. Although the nanoparticles have been suggested to consist of polar lipids, no attempt has been made to determine if nanoparticle and lipid concentrations are related. Here, we examined concentrations of nanoparticles and lipids in xylem sap and contamination control samples of six temperate angiosperm species with a NanoSight device and based on mass spectrometry. We found (1) that the concentration of nanoparticles and lipids were both diluted when an increasing amount of sap was extracted, (2) that their concentrations were significantly correlated in three species, (3) that their concentrations were affected by vessel anatomy, and (4) that concentrations of nanoparticles and lipids were very low in contamination-control samples. Moreover, there was little seasonal difference, no freezing-thawing effect on nanoparticles, and little seasonal variation in lipid composition. These findings indicate that lipids and nanoparticles are related to each other, and largely do not pass interconduit pit membranes. Further research is needed to examine the formation and stability of nanoparticles in xylem sap in relation to lipid composition, and the complicated interactions among the gas, liquid, and solid phases in xylem conduits.

category: plant biology


title: Altered collective mitochondrial dynamics in an Arabidopsis msh1 mutant compromising organelle DNA maintenance

abstract: Mitochondria form highly dynamic populations in the cells of plants (and all eukaryotes). The characteristics of this collective behaviour, and how it is influenced by nuclear features, remain to be fully elucidated. Here, we use a recently-developed quantitative approach to reveal and analyse the physical and collective "social" dynamics of mitochondria in an Arabidopsis msh1 mutant where organelle DNA maintenance machinery is compromised. We use a newly-created line combining the msh1 mutant with mitochondrially-targeted GFP, and characterise mitochondrial dynamics with a combination of single-cell timelapse microscopy, computational tracking and network analysis. The collective physical behaviour of msh1 mitochondria is altered from wildtype in several ways: mitochondria become less evenly spread, and networks of inter-mitochondrial encounters become more connected with greater potential efficiency for inter-organelle exchange. We find that these changes are similar to those observed in friendly, where mitochondrial dynamics are altered by a physical perturbation, suggesting that this shift to higher connectivity may reflect a general response to mitochondrial challenges.


title: Heterogeneity of Rift Valley fever virus transmission potential across livestock hosts, quantified through a model-based analysis of host viral load and vector infection

abstract: Rift Valley fever (RVF) is a viral, vector-borne, zoonotic disease. The relative contributions of livestock species to RVFV transmission has not been previously quantified. To estimate their potential to transmit the virus over the course of their infection, we 1) fitted a within-host model to viral RNA and infectious virus measures, obtained daily from infected lambs, calves, and young goats, 2) estimated the relationship between vertebrate host infectious titers and probability to infect mosquitoes, and 3) estimated the net infectiousness of each host species over the duration of their infectious periods, taking into account different survival outcomes for lambs. Our results indicate that the efficiency of viral replication, along with the lifespan of infectious particles, could be sources of heterogeneity between hosts. For similar infectious titers, we found that infection rates in Aedes spp. vectors were significantly higher than in Culex spp. vectors. Consequently, for Aedes infections, we estimated the net infectiousness of lambs to be 2.93 (median) and 3.65 times higher than that of calves and goats, respectively. Among lambs, individuals which eventually died from the infection were 1.93 times more infectious than lambs recovering. Beyond infectiousness, the relative contributions of host species to transmission depend on local ecological factors, including relative abundances and vector host-feeding preferences. Quantifying these contributions will ultimately help design efficient, targeted, surveillance and vaccination strategies.


title: Fine-tuning of RecBCD expression by post-transcriptional regulation is required for optimal DNA repair in Escherichia coli

abstract: To preserve genome integrity, all living organisms have developed strategies to respond to chromosomal damage. One such response is the repair of DNA double-strand breaks (DSBs), one of the most toxic forms of DNA lesions. In E. coli, DSBs are repaired via the homologous recombination pathway, initiated by the RecBCD enzyme. RecBCD is essential for accurate chromosome maintenance but its over-expression can lead to reduced DNA repair ability. This apparent paradox suggests that RecBCD copy number may need to be tightly controlled within an optimal range. Using single-molecule fluo-rescence microscopy, we have established that RecB is present in very low abundance at mRNA and protein levels. RecB transcription shows high levels of fluctuations yet cell-to-cell protein variability remains remarkably low. We show that the post-transcriptional regulator Hfq binds to recBCD mRNAs and down-regulates RecB protein expression in vivo. Furthermore, when Hfq-mediated regulation is perturbed, we observe less effective noise reduction and reduced DNA repair capacity. Taken together, our results suggest a post-transcriptional regulatory mechanism where Hfq fine-tunes RecB expression by inhibiting RecB translation. This fine-tuning of RecB expression contributes to reducing noise in RecB protein expression and protects cells against the toxic consequences of too high RecBCD numbers.


title: Quantitative fragmentomics allow affinity mapping of interactomes

abstract: Human protein networks have been widely explored but most binding affinities remain unknown, hindering quantitative interactome-function studies. Yet interactomes rely on minimal interacting fragments displaying quantifiable affinities. Here we measured the affinities of 65,000 interactions involving PDZ domains and their target PDZ-binding motifs (PBM) within a human interactome region particularly relevant for viral infection and cancer. We calculate interactomic distances, identify hot spots for viral interference, generate binding profiles and specificity logos, and explain selected cases by crystallographic studies. Mass spectrometry experiments on cell extracts and literature surveys show that quantitative fragmentomics effectively complement protein interactomics by providing affinities and completeness of coverage, putting a full human interactome affinity survey within realistic reach. Finally, we show that interactome hijacking by the viral PBM of human papillomavirus (HPV) E6 oncoprotein deeply impacts the host cell proteome way beyond immediate E6 binders, illustrating the complex system-wide relationship between interactome and function.


title: Hierarchical Bayesian Modeling of the Relationship between Task Related Hemodynamic Responses and Neuronal Excitability: a Simultaneous fNIRS/TMS Study

abstract:
BackgroundInvestigating the relationship between task-related cortical hemodynamic activity and brain excitability is challenging because it requires simultaneous measurement of brain hemodynamic activity while applying non-invasive brain stimulation. There is also considerable inter-/intra-subject variability which both brain excitability and task-related hemodynamic responses are associated with. Here we proposed hierarchical Bayesian modeling to taking into account variability in the data at the individual and group levels, aiming to provide accurate and reliable statistical inferences on this research question.

MethodsWe performed a study on 16 healthy subjects with simultaneous Paired Associative Stimulation (Inhibitory PAS10, Excitatory PAS25, Sham) and functional Near-Infrared Spectroscopy (fNIRS) targeting the primary motor cortex (M1). PAS was applied to modulate the cortical function and induce plasticity. Before and after each intervention cortical excitability was measured by motor evoked potentials (MEPs), and the motor task-related hemodynamic response was measured using fNIRS. We constructed three models to encode 1) PAS effects on the M1 excitability; 2) PAS effects on the whole-time course of fNIRS hemodynamic responses to finger tapping tasks, and 3) the correlation between PAS effects on M1 excitability and PAS effects on task-related hemodynamic responses.

ResultsSignificant increase of the cortical excitability was found after PAS25, whereas a small reduction of the cortical excitability was shown after PAS10 and no changes after sham. We found PAS effects on finger tapping evoked HbO/HbR within M1, around the peak of the hemodynamic time courses. Both HbO and HbR absolute amplitudes increased after PAS25 and decreased after PAS10. Cortical excitability changes and task-related HbO/HbR changes showed a high probability of being positively correlated, 0.77 and 0.79, respectively. The corresponding Pearsons correlations were 0.58 (p<.0001, HbO with MEP) and 0.56 (p<.001, HbR with MEP), respectively.

ConclusionBenefiting from this original Bayesian data analysis, our results showed that PAS modulates task-related cortical hemodynamic responses in addition to M1 excitability. The fact that PAS effects on hemodynamic response were exhibited mainly around the peak of the hemodynamic time course may indicate that the intervention only increases metabolic demanding rather than modulating hemodynamic response function per se. Moreover, the positive correlation between PAS modulations of excitability and hemodynamic brings insights to understand the fundamental properties of cortical function and cortical excitability.

HighlightsO_LIHierarchical Bayesian Modeling of PAS effects on M1 excitability and hemodynamic
C_LIO_LIDemonstrated PAS effects on the whole time-course of task-related hemodynamic
C_LIO_LIIncreased/reduced task-related hemodynamic corresponds to higher/lower M1 excitability
C_LIO_LIHigh probability of positive relationships between excitability and HbO/HbR changes
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title: Visual occipito-temporal sensitivity to digits through elementary school

abstract: Number processing abilities are important for academic and personal development. The course of initial specialization of ventral occipito-temporal cortex (vOTC) for visual number processing is crucial for the development of numeric and arithmetic skills. We examined the visual N1, the electrophysiological correlate of vOTC activations across five time points in kindergarten (T1), middle and end of first grade (T2, T3), second (T4) and fifth grade (T5). 62 children (35 female) performed a target detection task which included visual presentation of digits, false fonts, and letters. Arithmetic skills were measured at T4 and T5 with standardized math tests. Stronger N1 amplitudes for digits than false fonts were found across all 5 measurements. Arithmetic skills correlated negatively with visual N1 sensitivity to digits at T4 (2nd grade, mean age 8.3 yrs) over the left hemisphere, possibly reflecting allocation of more attentional or cognitive resources with poorer arithmetic skills. Our main result shows persistent visual N1 sensitivity to digits that is already present early on in pre-school and remains stable until fifth grade. This differs from the relatively sharp rise and fall of the visual N1 sensitivity to words or letters between kindergarten and middle of elementary school. The present study thus indicates different trajectories in the development of visual processing for written characters that are relevant to numeracy and literacy.


title: Distribution of multi-unit pitch responses recorded intracranially from human auditory cortex

abstract:
The perception of pitch requires the abstraction of stimulus properties related to the spectrotemporal structure of sound. Previous studies utilizing both animal electrophysiology and human imaging have indicated the presence of a center for pitch representation in the auditory cortex. Recent data from our own group - examining local field potentials (LFPs) in humans - indicate more widely distributed pitch-associated responses within the auditory cortex (Gander et al., 2019). To probe this with greater spatial resolution, we examined multi-unit activity related to three different auditory stimuli, in seven epilepsy patients who were implanted with high-impedance electrodes in auditory cortex for the clinical purpose of localizing seizures. The stimuli were regular-interval noise (RIN) with a pitch strength that is related to the temporal regularity, and pitch value determined by repetition rate, and harmonic complexes with missing fundamentals. We demonstrated increases in spiking activity in 69 of 104 (66%) responsive multiunit activity in auditory cortex due to pitch-associated stimuli. Importantly, these responses were distributed across the entire extent of Heschls gyrus (HG), in both primary and non-primary areas, rather than isolated to a specific region, and this finding was evident regardless of the stimulus presented. These findings are the first multi-unit pitch responses recorded from humans, and align with a recent study in macaques (Kikuchi et al., 2019) demonstrating that both local field potential and unit responses to pitch-inducing stimuli are distributed throughout auditory cortex.

Significance StatementThe perception of pitch is a fundamental acoustic attribute that is mediated by the auditory system. Despite its importance, there is still debate as to the precise areas responsible for its encoding, which may be due to differences in the recording measures and choices of stimuli used in previous studies. Here, we present the first study to measure multi-unit pitch responses in the auditory cortices of intracranially-implanted humans. Importantly, we demonstrate reliable responses to three different pitch-inducing paradigms that are distributed throughout Heschls gyrus, rather than being localized to a particular region. These data provide a bridge across animal and human studies, and aid in our understanding of the processing of a critical attribute of acoustic stimuli.


title: Decoding individualized motor cortical excitability states from whole-brain electroencephalography

abstract: Brain state-dependent transcranial magnetic stimulation (TMS) requires real-time identification of cortical excitability states. Current approaches deliver TMS during brain states that correlate with motor cortex (M1) excitability at the group level. Here, we hypothesized that machine learning classifiers could successfully discriminate between high and low M1 excitability states in individual participants using information obtained from low-density electroencephalography (EEG) signals. To test this, we analyzed a publicly available dataset that delivered 600 single TMS pulses to the right M1 during EEG and electromyography (EMG) recordings in 20 healthy adults. Multivariate pattern classification was used to discriminate between brain states during which TMS evoked small and large motor-evoked potentials (MEPs). Results show that personalized classifiers successfully discriminated between low and high M1 excitability states in 80% of tested participants. MEPs elicited during classifier-predicted high excitability states were significantly larger than those elicited during classifier-predicted low excitability states in 90% of tested participants. Personalized classifiers did not generalize across participants. Overall, results show that individual participants exhibit unique brain activity patterns which predict low and high M1 excitability states and that these patterns can be efficiently captured using low-density EEG signals. Our findings suggest that deploying individualized classifiers during brain state-dependent TMS may enable fully personalized neuromodulation in the future.


title: Decoding personalized motor cortical excitability states from human electroencephalography


title: E-Cannula reveals anatomical diversity in sharp-wave ripples as a driver for the recruitment of distinct hippocampal assemblies

abstract: The hippocampus plays a critical role in spatial navigation and episodic memory. However, research on in vivo hippocampal activity dynamics has mostly relied on single modalities such as electrical recordings or optical imaging, with respectively limited spatial and temporal resolution. This technical difficulty greatly impedes multi-level investigations into network state-related changes in cellular activity. To overcome these limitations, we developed the E-Cannula integrating fully transparent graphene microelectrodes with imaging-cannula. The E-Cannula enables the simultaneous electrical recording and two-photon calcium imaging from the exact same population of neurons across an anatomically extended region of the mouse hippocampal CA1 stably across several days. These large-scale simultaneous optical and electrical recordings showed that local hippocampal sharp wave ripples (SWRs) are associated with synchronous calcium events involving large neural populations in CA1. We show that SWRs exhibit spatiotemporal wave patterns along multiple axes in 2D space with different spatial extents (local or global) and temporal propagation modes (stationary or travelling). Notably, distinct SWR wave patterns were associated with, and decoded from, the selective recruitment of orthogonal CA1 cell assemblies. These results suggest that the diversity in the anatomical progression of SWRs may serve as a mechanism for the selective activation of the unique hippocampal cell assemblies extensively implicated in the encoding of distinct memories. Through these results we demonstrate the utility of the E-Cannula as a versatile neurotechnology with the potential for future integration with other optical components such as green lenses, fibers or prisms enabling the multi-modal investigation of cross-time scale population-level neural dynamics across brain regions.


title: Fatigue induces behavioural improvements in the unfatigued hand via altered functional connectivity and neurochemicals in cortical motor areas

abstract:
In humans, motor learning is underpinned by changes in functional connectivity (FC) across the sensorimotor network. Unilateral exercise-induced fatigue increases FC in the ipsilateral primary motor cortex (M1) and supplementary motor area (SMA); areas involved in motor planning and execution of the contralateral hand. Unilateral fatiguing exercise is therefore a promising potential approach to augment motor performance in the non-fatigued, contralateral, hand. In a within-participant, controlled, randomized, cross-over design, 15 right-handed adults had two magnetic resonance imaging (MRI) sessions, where functional MRI and MR Spectroscopic Imaging were acquired before and after repeated right-hand contractions at either 5% or 50% maximum voluntary contraction (MVC). Before and after scanning, response times (RTs) were determined in both hands, and after scanning, participants performed a serial reaction time task (SRTT) with their left, unfatigued, hand. Nine minutes of 50% MVC contractions resulted in fatigue. This unimanual fatigue improved motor performance, as indexed by decreased RTs, in the contralateral hand. Although fatigue had no significant effects on sequence learning, fatigue led to a significant increase in the transfer of the learned skill to the untrained hand. These behavioural effects were supported by significant neural changes: an increase in SMA-SMA functional connectivity, and increased connectivity between right M1 and right Orbitofrontal Cortex. At a neurochemical level, the degree of fatigue-induced decrease in GABA in left M1, left and right SMA correlated with subsequent behavioural improvements in the left-hand. These results support unilateral fatiguing exercise as a potential therapeutic intervention in a range of neurological and orthopedic conditions.

Key points summaryO_LIRight handgrip contractions at 50% MVC improve left hand response times.
C_LIO_LIRepeated handgrip contractions at 50% MVC alter interhemispheric functional connectivity.
C_LIO_LIUnilateral exercise may be an effective method for enhancing contralateral limb motor performance in rehabilitation settings.
C_LI


title: An Unsupervised Machine Learning Paradigm for Artifact Removal from Electrodermal Activity in an Uncontrolled Clinical Setting

abstract:
ObjectiveElectrodermal activity (EDA) reflects sympathetic nervous system activity through sweating-related changes in skin conductance. To enable EDA data to be used robustly in clinical settings, we need to develop artifact detection and removal frameworks that can handle the types of interference experienced in clinical settings.

MethodsWe collected EDA data from 69 subjects while they were undergoing surgery in the operating room. We then built an artifact removal framework using unsupervised learning methods and informed features to remove the heavy artifact that resulted from the use of surgical electrocautery during the surgery and compared it to other existing methods for artifact removal from EDA data.

ResultsOur framework was able to remove the vast majority of artifact from the EDA data across all subjects with high sensitivity (94%) and specificity (90%). In contrast, existing methods used for comparison struggled to be sufficiently sensitive and specific, and none effectively removed artifact even if it was identifiable. In addition, the use of unsupervised learning methods in our framework removes the need for manually labeled datasets for training.

ConclusionOur framework allows for robust removal of heavy artifact from EDA data in clinical settings such as surgery. Since this framework only relies on a small set of informed features, it can be expanded to other modalities such as ECG and EEG.

SignificanceRobust artifact removal from EDA data is the first step to enable clinical integration of EDA as part of standard monitoring in settings such as the operating room.


title: The Listening Zone of Human Electrocorticographic Field Potential Recordings

abstract: Intracranial electroencephalographic (icEEG) recordings provide invaluable insights into neural dynamics in humans due to their unmatched spatiotemporal resolution. Yet, such recordings reflect the combined activity of multiple underlying generators, confounding the ability to resolve spatially distinct neural sources. To empirically quantify the listening zone of icEEG recordings, we computed the correlations between signals as a function of distance (expressed as full width at half maximum; FWHM) between 8,752 recording sites in 71 patients implanted with either subdural electrodes (SDE), stereo-encephalography electrodes (sEEG), or high-density sEEG electrodes. As expected, for both SDE and sEEG electrodes, higher frequency signals exhibited a sharper fall off relative to lower frequency signals. For broadband high gamma (BHG) activity, the mean FWHM of SDEs (6.6 {+/-} 2.5 mm) and sEEGs in gray matter (7.14 {+/-} 1.7 mm) was not significantly different, however the FWHM for low frequencies recorded by sEEGs was 2.45 mm smaller than SDEs. White matter sEEG electrodes showed much lower power for frequencies 17 to 200 Hz (q < 0.01) and a much broader decay (11.3 {+/-} 3.2 mm) than gray matter electrodes (7.14 {+/-} 1.7 mm). The use of a bipolar referencing scheme significantly lowered FWHM for sEEG electrodes, as compared with a white matter reference or a common average reference. These results outline the influence of array design, spectral bands, and referencing schema on local field potential recordings and source localization in icEEG recordings in humans. The metrics we derive have immediate relevance to the analysis and interpretation of both cognitive and epileptic data.


title: Generating accurate 3D gaze vectors using synchronized eye tracking and motion capture

abstract: Assessing gaze behaviour during real-world tasks is difficult; dynamic bodies moving through dynamic worlds make gaze analysis difficult. Current approaches involve laborious coding of pupil positions. In settings where motion capture and mobile eye tracking are used concurrently in naturalistic tasks, it is critical that data collection be simple, efficient, and systematic. One solution is to combine eye tracking with motion capture to generate 3D gaze vectors. When combined with tracked or known object locations, 3D gaze vector generation can be automated. Here we use combined eye and motion capture and explore how linear regression models generate accurate 3D gaze vectors. We compare spatial accuracy of models derived from four short calibration routines across three pupil data inputs: the efficacy of calibration routines were assessed, a validation task requiring short fixations on taskrelevant locations, and a naturalistic object interaction task to bridge the gap between laboratory and "in the wild" studies. Further, we generated and compared models using spherical and cartesian coordinate systems and monocular (Left or Right) or binocular data. All calibration routines performed similarly, with the best performance (i.e., sub-centimetre errors) coming from the naturalistic task trials when the participant is looking at an object in front of them. We found that spherical coordinate systems generate the most accurate gaze vectors with no differences in accuracy when using monocular or binocular data. Overall, we recommend one-minute calibration routines using binocular pupil data combined with a spherical world coordinate system to produce the highest quality gaze vectors.


title: Clostridioides difficile infection increases circulating p-cresol levels and dysregulates brain dopamine metabolism: linking gut-brain axis to autism and other neurologic disorders?

abstract: Gastrointestinal illnesses are one of the most common comorbidities reported in patients with neurodevelopmental diseases, including autism spectrum disorders (ASD). Gut dysbiosis, overgrowth of C. difficile, and gut microbiota-associated alterations in central neurotransmission have been implicated in ASD, where the dopaminergic axis plays an important role in the disease pathogenesis. Human C. difficile strains produce a significant amount of the toxic metabolite p-cresol, an inhibitor of dopamine beta-hydroxylase (DBH), which catalyzes the conversion of dopamine (DA) to norepinephrine (NE). p-Cresol is known to precipitate and exacerbate autistic behavior in rodents by increasing DA levels and altering DA receptor sensitivity in brain regions relevant to ASD. Therefore, we hypothesized that C. difficile infection dysregulates dopaminergic metabolism by increasing p-cresol levels in the gut and systemic circulation, and by inhibiting brain DBH, ultimately leading to elevated DA in different brain regions. For testing this hypothesis, we induced antibiotic-associated C. difficile infection in mice and determined the gut and serum p-cresol levels, serum DBH activity, and dopamine and its metabolite levels in different brain regions relevant to ASD. The results showed that C. difficile infection causes a significant increase in striatal DA, accompanied by significantly altered levels of DA metabolites and NE in different brain regions (p < 0.05). In addition, significantly increased circulating p-cresol levels and reduced DBH activity were observed in C. difficile infected mice (p < 0.05). Therefore, the results from this study suggest a potential link between C. difficile infection and alterations in the dopaminergic axis implicated in the precipitation and aggravation of ASD.


title: Verbena officinalis L. regulates killing efficiency of natural killer cells

abstract:
BackgroundNatural killer (NK) cells play a key role in eliminating tumorigenic and pathogen-infected cells. Verbena officinalis (V. officinalis) has been used as a medical plant in traditional and modern medicine, exhibiting anti-tumor and anti-inflammation activity, but its role in NK cells remains unclear.

PurposeThe impact of bioactive constituents of V. officinalis on immune responses remains largely elusive. In this work we investigated the potential targets of V. officinalis and focused on killing efficiency and related functions of NK cells regulated by bioactive constituents of V. officinalis.

Study design/methodsWe used primary human NK cells from peripheral blood mononuclear cells. Potential regulatory roles of selected compounds in NK killing function-related genes were first analyzed by network pharmacology approaches. Potential engagement between compounds and NK receptors was examined by molecular docking assay. Killing efficiency of NK cells was determined with real-time killing assay and live-cell imaging. Proliferation was examined by CFSE staining. Expression of cytotoxic proteins was analyzed using flow cytometry. Lytic granule release was quantified by CD107a degranulation assay. Contact time required for killing and determination of serial killers were analyzed using live cell imaging results.

ResultsResults from network pharmacology approaches and molecular docking analyses predicted that the five bioactive compounds (acteoside, apigenin, kaempferol, verbenalin and hastatoside) from V. officinalis can regulated various key genes essential for NK effector functions and can bind to NK inhibitory receptors as well as activating receptors, indicating their potential role in regulating NK killing capacity. Analyses of NK killing efficiency revealed that out of these five compounds verbenalin exhibited an encouraging potency to enhance NK killing efficiency. Further investigation showed that verbenalin did not affect proliferation, expression of cytotoxic proteins, or lytic granule degranulation, but rather reduced contact time required for killing, enhanced total killing events per NK cell, and elevated the fraction of killing competent NK cells.

ConclusionsIn this work, we have identified verbenalin as the most potent bioactive constituent from V. officinalis to enhance NK cell killing efficiency via accelerating killing processes and converting non-killers to killing competent NK cells without affecting the lytic granule pathway.


title: Bioactive constituents of Verbena officinalis regulate killing efficiency of primary human natural killer cells by accelerating killing processes


title: A Segmentation-Free Machine Learning Architecture for Immune Landscape Phenotyping in Solid Tumors by Multichannel Imaging

abstract: Tissue specimens taken from primary tumors or metastases contain important information for diagnosis and treatment of cancer patients. Multispectral imaging allows in situ visualization of heterogeneous cell subsets, such as lymphocytes, in tissue samples. Many image processing pipelines first segment cell boundaries and then measure marker expression to assign cell phenotypes. In dense tissue environments such as solid tumors, segmentation-based phenotyping can be inaccurate due to segmentation errors or overlapping cell boundaries. Here we introduce a machine learning pipeline design called ImmuNet that directly identifies the positions and phenotypes of immune cells without determining their exact boundaries. ImmuNet is easy to train: human annotators only need to click on immune cells and rank their expression of each marker; full annotation of tissue regions is not necessary. We demonstrate that ImmuNet is a suitable approach for immune cell detection and phenotyping in multiplex im-munohistochemistry: it compares favourably to segmentation-based methods, especially in dense tissues, and we externally validate ImmuNet results by comparing them to flow cytometric measurements from the same tissue. In summary, ImmuNet performs well on diverse tissue specimens, takes relatively little effort to train and implement, and is a simpler alternative to segmentation-based approaches when only cell positions and phenotypes, but not their shapes are required for downstream analyses. We hope that ImmuNet will help cancer researchers to analyze multichannel tissue images more easily and accurately.


title: The epidemiology and genomics of a virulent emerging fungal pathogen in an Australian reptile

abstract: Emerging infectious fungal diseases (EIFDs) represent a major conservation concern worldwide. Here, we provide early insights into the potential threat that Nannizziopsis barbatae (Nb), a novel EIFD, poses to Australian herpetological biodiversity. First known to the reptile pet trade as a primary pathogen causing untreatable severe dermatomycosis, since 2013, Nb has emerged in a growing number of phylogenetically and ecologically distant free-living reptiles across Australia. Observing its emergence in a long-term study population of wild eastern water dragons (Intellagama lesueurii), we demonstrate the pathogens virulence-related genomic features, within-population spatiotemporal spread, and survival costs, all of which imply that Nb could pose a threat to Australian reptiles in the future. Our findings highlight the need to closely monitor this pathogen in Australian ecosystems.


title: NetGAM: Using generalized additive models to improve the predictive power of ecological network analyses constructed using time-series data

abstract: Ecological network analyses are used to identify potential biotic interactions between microorganisms from species abundance data. These analyses are often carried out using time-series data; however, time-series networks have unique statistical challenges. Time-dependent species abundance data can lead to species co-occurrence patterns that are not a result of direct, biotic associations and may therefore result in inaccurate network predictions. Here, we describe a generalize additive model (GAM)-based data transformation that removes time-series signals from species abundance data prior to running network analyses. Validation of the transformation was carried out by generating mock, time-series datasets, with an underlying covariance structure, running network analyses on these datasets with and without our GAM transformation, and comparing the network outputs to the known covariance structure of the simulated data. The results revealed that seasonal abundance patterns substantially decreased the accuracy of the inferred networks. Additionally, the GAM transformation increased the F1 score of inferred ecological networks on average and improved the ability of network inference methods to capture important features of network structure. This study underscores the importance of considering temporal features when carrying out network analyses and describes a simple, effective tool that can be used to improve results.


title: Disentangling the role of poultry farms and wild birds in the spread of highly pathogenic avian influenza virus H5N8 in Europe

abstract:
Recent outbreaks of highly pathogenic avian influenza H5N8 virus in Europe have caused severe damage to animal health, wildlife conservation and livestock economic sustainability. While epidemiological and phylogenetic studies have generated important clues about the virus spread in Europe, they remained opaque to the specific role of poultry farms and wild birds. Using a phylodynamic framework, we inferred the H5N8 virus transmission dynamics among poultry farms and wild birds in four severely affected countries and investigated drivers of spread between farms across borders during the 2016-17 epidemic. Based on existing genetic data, we showed that the virus was likely introduced into poultry farms during the autumn, in line with the timing of arrival of migratory wild birds. Then, transmission was mainly driven by farm-to-farm transmission in Germany, Hungary and Poland, suggesting that better understanding of how infected farms are connected in those countries would greatly help control efforts. In contrast, the epidemic was dominated by wild bird-to-farm transmission in Czech Republic, meaning that more sustainable prevention strategies should be developed to reduce virus exposure from wild birds. We inferred effective reproduction number Re estimates among poultry farms and wild birds. We expect those estimates being useful to parameterize predictive models of virus spread aiming at optimising control strategies. None of the investigated predictors related to live poultry trade, poultry census and geographic proximity were identified as supportive predictors of the viral spread between farms across borders, suggesting that other drivers should be considered in future studies.

Significance statementIn winter 2016-17, Europe was severely hit by an unprecedented epidemic of highly pathogenic avian influenza (HPAI) H5N8 virus, causing significant impact on animal health, wildlife conservation and livestock economic sustainability. By applying phylodynamic tools to H5N8 sequence data collected from poultry farms and wild birds during the epidemic, we quantified how effectively the first infections were detected, how fast the virus spread, how many infections were missed and how many transmission events occurred at the wildlife-domestic interface. Also, we investigated predictors of the virus spread between farms across borders. These results are crucial to better understand the virus transmission dynamics, with the view to inform policy decision-making and reduce the impact of future epidemics of HPAI viruses.


title: selscan 2.0: scanning for sweeps in unphased data

abstract: Haplotype-based scans to identify recent and ongoing positive selection have become commonplace in evolutionary genomics studies of numerous species across the tree of life. However, the most widely adopted approaches require phased haplotypes to compute the key statistics. Here we release a major update to the selscan software that re-defines popular haplotype-based statistics for use with unphased "multi-locus genotype" data. We provide unphased implementations of iHS, nSL, XP-EHH, and XP-nSL and evaluate their performance across a range of important parameters in a generic demographic history. Source code and executables are available at https://www.github.com/szpiech/selscan.

category: evolutionary biology


title: Structure and dynamics of Odinarchaeota tubulin and the implications for eukaryotic microtubule evolution

abstract: Tubulins are critical for the internal organization of eukaryotic cells, and understanding their emergence is an important question in eukaryogenesis. Asgard archaea are the closest known prokaryotic relatives to eukaryotes. Here, we elucidated the apo and nucleotide-bound X-ray structures of an Asgard tubulin from hydrothermal-living Odinarchaeota (OdinTubulin). The GTP-bound structure resembles a microtubule protofilament, with GTP bound between subunits, coordinating the "+" end subunit through a network of water molecules and unexpectedly by two cations. A water molecule is located suitable for GTP hydrolysis. Time course crystallography and electron microscopy revealed conformational changes on GTP hydrolysis. OdinTubulin forms tubules at high temperatures, with short curved protofilaments coiling around the tubule circumference, more similar to FtsZ, rather than running parallel to its length, as in microtubules. Thus, OdinTubulin represents an evolution intermediate between prokaryotic FtsZ and eukaryotic microtubule-forming tubulins.


title: Drift on holey landscapes as a dominant evolutionary process

abstract: Phenotypes typically display integration, i.e. correlations between traits. For quantitative traits--like many behaviors, physiological processes, and life-history traits--patterns of integration are often assumed to have been shaped by the combination of linear, non-linear, and correlated selection, with trait correlations representative of optimal combinations. Unfortunately, this assumption has rarely been critically tested, in part due to a lack of clear alternatives. Here we show that trait integration across 6 phyla and 60 species (including both Plantae and Animalia) is consistent with evolution across high dimensional "holey landscapes" rather than classical models of selection. This suggests that the leading conceptualizations and modeling of the evolution of trait integration fail to capture how phenotypes are shaped. Instead, traits are integrated in a manner contrary to predictions of dominant evolutionary theory.


title: Inference of cell state transitions and cell fate plasticity from single-cell with MARGARET

abstract: Despite recent advances in inferring cellular dynamics using single-cell RNA-seq data, existing trajectory inference (TI) methods face difficulty in accurately reconstructing cell-state manifold and inferring trajectory and cell fate plasticity for complex topologies. We present MARGARET, a novel TI method that utilizes a deep unsupervised metric learning-based approach for inferring the cellular embeddings and employs a novel measure of connectivity between cell clusters and a graph-partitioning approach to reconstruct complex trajectory topologies. MARGARET utilizes the inferred trajectory for determining terminal states and inferring cell-fate plasticity using a scalable absorbing Markov Chain model. On a diverse simulated benchmark, MARGARET out-performed state-of-the-art methods in recovering global topology and cell pseudotime ordering. When applied to experimental datasets from hematopoiesis, embryogenesis, and colon differentiation, MARGARET reconstructed major lineages and associated gene expression trends, better characterized key branching events and transitional cell types, and identified novel cell types, and branching events that were previously uncharacterized.

category: genomics


title: Green notes: The rhythms of cyanobacteria exoelectrogenesis as de-composed by the Hilbert-Huang transform

abstract: 1Electrons from cyanobacteria photosynthetic and respiratory systems are implicated in current generated in biophotovoltaic (BPV) devices. However, the pathway that electrons follow to electrodes remains largely unknown, limiting progress of applied research. Here we use Hilbert-Huang transforms to decompose Synechococcus elongatus sp. PCC7942 BPV current density profiles into physically meaningful oscillatory components, and compute their instantaneous frequencies. We develop hypotheses for the genesis of the oscillations via repeat experiments with iron-depleted and 20% CO2 enriched biofilms. The oscillations exhibit rhythms that are consistent with the state of the art cyanobacteria circadian model, and putative exoelectrogenic pathways. In particular, we observe oscillations consistent with: rhythmic D1:1 (photosystem II core) expression; circadian-controlled glycogen accumulation; circadian phase shifts under modified intracellular %ATP; and circadian period shortening in the absence of the iron-sulphur protein LdpA. We suggest that the extracted oscillations may be used to reverse-identify proteins and/or metabolites responsible for cyanobacteria exoelectrogenesis.

category: biochemistry


title: Versatile Encapsulation and Synthesis of Potent Therapeutic Liposomes by Thermal Equilibration

abstract: The wide-scale use of liposomal delivery systems is hampered by difficulties in obtaining potent liposomal suspensions. Passive and active loading strategies have been proposed to formulate drug encapsulated liposomes, but are limited by low efficiencies (passive) or high drug specificities (active). Here, we present an efficient and universal loading strategy for synthesizing therapeutic liposomes. Integrating a thermal equilibration technique with our unique liposome synthesis approach, co-loaded targeting liposomes can be engineered in an efficient and scalable manner with potencies 200-fold higher than typical passive encapsulation techniques. We demonstrate this capability through simultaneous co-loading of hydrophilic and hydrophobic small molecules and through targeted delivery of liposomal Doxorubicin to a metastatic breast cancer cell line MDA-MB-231. Molecular dynamic simulations are used to explain interactions between Doxorubicin and liposome membrane during thermal equilibration. By addressing the existing challenges, we have developed an unparalleled approach that will facilitate the formulation of novel theranostic and pharmaceutical strategies.

category: bioengineering


title: Accurate estimation of intrinsic biases for improved analysis of chromatin accessibility sequencing data using SELMA

abstract: Genome-wide profiling of chromatin accessibility by DNase-seq or ATAC-seq has been widely used to identify regulatory DNA elements and transcription factor binding sites. However, enzymatic DNA cleavage exhibits intrinsic sequence biases that confound chromatin accessibility profiling data analysis. Existing computational tools are limited in their ability to account for such intrinsic biases. Here, we present Simplex Encoded Linear Model for Accessible Chromatin (SELMA), a computational method for systematic estimation of intrinsic cleavage biases from genomic chromatin accessibility profiling data. We demonstrate that SELMA yields accurate and robust bias estimation from both bulk and single-cell DNase-seq and ATAC-seq data. We show that transcription factor binding inference from DNase footprints can be improved by incorporating estimated biases using SELMA. We also demonstrate improved cell clustering of single-cell ATAC-seq data by considering the SELMA-estimated bias effect. SELMA can be applied to existing bioinformatics tools to improve the analysis of chromatin accessibility sequencing data.


title: DeePVP: Identification and classification of phage virion protein using deep learning

abstract: The poor annotation of phage virion protein (PVP) is the bottleneck of many areas of viral research, such as viral phylogenetic analysis, viral host identification and antibacterial drug design. Because of the high diversity of the PVP sequences, the PVP annotation remains a great challenging bioinformatic task. Based on deep learning, we present DeePVP that contains a main module and an extended module. The main module aims to identify the PVPs from non-PVP over a phage genome, while the extended module can further classify the predicted PVP into one of the ten major classes of PVP. Compared with the state-of-the-art tools that can distinguish PVP from non-PVP, DeePVPs main module performs much better, with an F1-score 9.05% higher in the PVP identification task. Compared with PhANNs, a tool that can further classify the predicted PVP into a specific class, the overall accuracy of DeePVPs extended module is approximately 3.72% higher in the PVP classification task. Two application cases on the genome of mycobacteriophage PDRPxv and Escherichia phage HP3 show that the predictions of DeePVP are much more reliable and can better reveal the compact PVP-enriched region, which may be conserved during the viral evolution process, over the phage genome.


title: Retinal self-organization: a model of RGC and SAC mosaic formation

abstract:
Individual retinal cell types exhibit semi-regular spatial patterns called retinal mosaics. These mosaics enable uniform sampling of visual information and are formed to varying degrees across cell types. Retinal ganglion cells (RGC) and amacrine cells (including starburst amacrine cells (SAC)) are notably known to exhibit such layouts. Mechanisms responsible for the formation of such organised structures and their requirements are still not well understood. Mosaic formation follows three main principles: (1) homotypic cells prevent nearby cells from adopting the same type, (2) cell tangential migration, with homotypic cell repulsion, (3) cell death (with RGCs exhibiting high rates of apoptosis).

Here, we use BioDynaMo, an agent-based simulation framework, to build a detailed and mechanistic model of mosaic formation. In particular, we investigate the implications of the three theories for RGCs mosaic formation. We report that the cell migration mechanism yields the most regular mosaics and that cell death can create regular mosaics only if the death rate is kept below 30%, after which cell death has a negative impact on mosaic regularity. In addition, and in accordance with recent studies, we propose here that low density RGC type mosaics exhibit on average low regularities, and thus we question the relevance of regular spacing as a criterion for a group of RGCs to form a RGC type.

We also investigate SAC mosaics formation and possible interactions between the ganglion cell layer (GCL) and inner nuclear layer (INL) populations. Investigations are conducted both experimentally and by applying our simulation model to the SAC population. We report that homotypic interactions between the GCL and INL populations during mosaics creation are required to reproduce the observed SAC mosaics characteristics. This suggests that the GCL and INL populations of SACs might not be independent during retinal development.

Author SummaryRetinal function depends on cells self-organisation during early development. Understanding the mechanisms underlying this self-organisation could improve not only our comprehension of the retina and its development but also of the cortex. Ultimately, this could lead to novel therapeutic approaches for developmental diseases. Computational models can be of precious help to study this process of self-organisation, given that they are biologically plausible. In this sense, it is important that implemented developmental mechanisms follow the principle of locally available information, without any global knowledge or external supervisor. Here, we follow this principle to investigate mosaic formation during retinal development. In this work, we demonstrate that tangential migration is the only mechanism able to form regular mosaics and that the GCL/INL SAC populations might not be independent during their mosaic formation. More, we question the relevance of regular spacing for RGC types classification.


title: End-to-end learning of multiple sequence alignments with differentiable Smith-Waterman

abstract: Multiple Sequence Alignments (MSAs) of homologous sequences contain information on structural and functional constraints and their evolutionary histories. Despite their importance for many downstream tasks, such as structure prediction, MSA generation is often treated as a separate pre-processing step, without any guidance from the application it will be used for. Here, we implement a smooth and differentiable version of the Smith-Waterman pairwise alignment algorithm that enables jointly learning an MSA and a downstream machine learning system in an end-to-end fashion. To demonstrate its utility, we introduce SMURF (Smooth Markov Unaligned Random Field), a new method that jointly learns an alignment and the parameters of a Markov Random Field for unsupervised contact prediction. We find that SMURF learns MSAs that mildly improve contact prediction on a diverse set of protein and RNA families. As a proof of concept, we demonstrate that by connecting our differentiable alignment module to AlphaFold and maximizing predicted confidence, we can learn MSAs that improve structure predictions over the initial MSAs. Interestingly, the alignments that improve AlphaFold predictions are self-inconsistent and can be viewed as adversarial. This work highlights the potential of differentiable dynamic programming to improve neural network pipelines that rely on an alignment and the potential dangers of relying on black-box methods for optimizing predictions of protein sequences.


title: Loss-of-function, gain-of-function and dominant-negative mutations have profoundly different effects on protein structure: implications for variant effect prediction

abstract: Most known pathogenic mutations occur in protein-coding regions of DNA and change the way proteins are made. Taking protein structure into account has therefore provided great insight into the molecular mechanisms underlying human genetic disease. While there has been much focus on how mutations can disrupt protein structure and thus cause a loss of function (LOF), alternative mechanisms, specifically dominant-negative (DN) and gain-of-function (GOF) effects, are less understood. Here, we have investigated the protein-level effects of pathogenic missense mutations associated with different molecular mechanisms. We observe striking differences between recessive vs dominant, and LOF vs non-LOF mutations, with dominant, non-LOF disease mutations having much milder effects on protein structure, and DN mutations being highly enriched at protein interfaces. We also find that nearly all computational variant effect predictors underperform on non-LOF mutations, even those based solely on sequence conservation. However, we do find that non-LOF mutations could potentially be identified by their tendency to cluster in three-dimensional space. Overall, our work suggests that many pathogenic mutations that act via DN and GOF mutations are likely being missed by current variant prioritisation strategies, but that there is considerable scope to improve computational predictions through consideration of molecular disease mechanisms.