Miracle-dz/UniFAR-FTUs huggingface dataset:
Inferring sparse structure in genotype-phenotype maps

Correlation among multiple phenotypes across related individuals may reflect some pattern of shared genetic architecture: individual genetic loci affect multiple phenotypes (an effect known as pleiotropy), creating observable relationships between phenotypes. A natural hypothesis is that pleiotropic effects reflect a relatively small set of common “core” cellular processes: each genetic locus affects one or a few core processes, and these core processes in turn determine the observed phenotypes. Here, we propose a method to infer such structure in genotype-phenotype data. Our approach, sparse structure discovery (SSD) is based on a penalized matrix decomposition designed to identify latent structure that is low-dimensional (many fewer core processes than phenotypes and genetic loci), locus-sparse (each locus affects few core processes) and/or phenotype-sparse (each phenotype is influenced by few core processes). Our use of sparsity as a guide in the matrix decomposition is motivated by the results of a novel empirical test indicating evidence of sparse structure in several recent genotype-phenotype data sets. First, we use synthetic data to show that our SSD approach can accurately recover core processes if each genetic locus affects few core processes or if each phenotype is affected by few core processes. Next, we apply the method to three datasets spanning adaptive mutations in yeast, genotoxin robustness assay in human cell lines, and genetic loci identified from a yeast cross, and evaluate the biological plausibility of the core process identified. More generally, we propose sparsity as a guiding prior for resolving latent structure in empirical genotype-phenotype maps.
AAV-delivered gene editing for latent genital or orofacial herpes simplex virus infection reduces ganglionic viral load and minimizes subsequent viral shedding in mice

Herpes simplex virus (HSV) establishes latency in ganglionic neurons of the peripheral nervous system, from which it can reactivate, causing recurrent disease and possible transmission to a new host. Current anti-HSV therapy does not eliminate latent HSV, and thus is only suppressive rather than curative. We developed a potentially curative approach to latent HSV infection and pathogenesis, based on gene editing using HSV-specific meganucleases delivered by adeno-associated virus (AAV) vectors. Our results demonstrated that a dual meganuclease therapy, composed of two anti-HSV-1 meganucleases delivered by a triple AAV serotype combination (AAV9, AAV-Dj/8, AAV-Rh10), can eliminate up to 97% of latent HSV DNA from ganglia in both ocular and vaginal mouse models of latent HSV infection. Using a novel pharmacological approach to reactivate latent HSV-1 in mice with the bromodomain inhibitor JQ-1, we demonstrated that this reduction in ganglionic viral load leads to a significant reduction of viral shedding from treated vs. control mice, with many treated mice showing no detectable virus shedding. In general, therapy was well tolerated, although dose-ranging studies showed hepatotoxicity at high AAV doses, consistent with previous observations in animals and humans. Also in agreement with previous literature, we observed subtle histological evidence of neuronal injury in some experimental mice, although none of the mice demonstrated observable neurological signs or deficits. These results reinforce the curative potential of gene editing for latent orofacial and genital HSV disease, and provide a framework for additional safety studies before human trials can begin.
A full computational model of cell motility: Early spreading, cell migration and competing taxis

Cell motility represents one of the most fundamental function in mechanobiology. Cell motility is directly implicated in development, cancer or tissue regeneration, but it also plays a key role in the future of tissue and biomedical engineering. Here, we derived a computational model of cell motility that incorporates the most important mechanisms toward cell motility: cell protrusion, polarization and retrograde flow. We first validate our model to explain two important types of cell migration, i.e. confined and ameboid cell migration, as well as all phases of the latter cell migration type, i.e. symmetric cell spreading, cell polarization and latter migration. Then, we use our model to investigate durotaxis and chemotaxis. The model predicts that chemotaxis alone induces larger migration velocities than durotaxis and that durotaxis is activated in soft matrices but not in stiff ones. More importantly, we analyze the competition between chemical and mechanical signals. We show that chemotaxis rules over durotaxis in most situations although durotaxis diminishes chemotaxis. Moreover, we show that inhibiting the effect of GTPases in actin polymerization at the cell front may allow durotaxis to take control over chemotaxis in soft substrates. Understanding how the main forces in cell motility cooperate, and how a precise manipulation of external cues may control directed cell migration is not only key for a fundamental comprehension of cell biology but also to engineer better biomimetic tissues. To this end, we provide a freely-available platform to predict all phases and modes of cell motility analyzed in this work.
Intelligibility improves perception of timing changes in speech

Auditory rhythms are ubiquitous in music, speech, and other everyday sounds. Yet, it is unclear how perceived rhythms arise from the repeating structure of sounds. For speech, it is unclear whether rhythm is solely derived from acoustic properties (e.g., rapid amplitude changes), or if it is also influenced by the linguistic units (syllables, words, etc.) that listeners extract from intelligible speech. Here, we present three experiments in which participants were asked to detect an irregularity in rhythmically spoken speech sequences. In each experiment, we reduce the number of possible stimulus properties that differ between intelligible and unintelligible speech sounds and show that these acoustically-matched intelligibility conditions nonetheless lead to differences in rhythm perception. In Experiment 1, we replicate a previous study showing that rhythm perception is improved for intelligible (16-channel vocoded) as compared to unintelligible (1-channel vocoded) speech – despite near-identical broadband amplitude modulations. In Experiment 2, we use spectrally-rotated 16-channel speech to show the effect of intelligibility cannot be explained by differences in spectral complexity. In Experiment 3, we compare rhythm perception for sine-wave speech signals when they are heard as non-speech (for naïve listeners), and subsequent to training, when identical sounds are perceived as speech. In all cases, detection of rhythmic regularity is enhanced when participants perceive the stimulus as speech compared to when they do not. Together, these findings demonstrate that intelligibility enhances the perception of timing changes in speech, which is hence linked to processes that extract abstract linguistic units from sound.
Cell type-independent profiling of interactions between intracellular pathogens and the human phosphoproteome

Interactions between proteins from intracellular pathogens and host proteins in an infected cell are often mediated by post-translational modifications encoded in the host proteome. Identifying protein modifications, such as phosphorylation, that dictate these interactions remains a defining challenge in unraveling the molecular mechanisms of pathogenesis. We have developed a platform in engineered bacteria that displays over 110,000 phosphorylated human proteins coupled to a fluorescent reporter system capable of identifying the host-pathogen interactome of phosphoproteins (H-PIP). This resource broadly enables cell-type independent interrogation and discovery of proteins from intracellular pathogens capable of binding phosphorylated human proteins. As an example of the H-PIP platform, we generated a unique, high-resolution SARS-CoV-2 interaction network which expanded our knowledge of viral protein function and identified understudied areas of host pathology.
Complex plumages spur rapid color diversification in island kingfishers (Aves: Alcedinidae)

Oceanic islands are cradles for diversity. Differences in predation pressures and lack of competition on islands are thought to drive both phenotypic and species diversification. While most work exploring these patterns has focused on life history, behavioral and morphological traits, many island species are uniquely colorful. Yet, a recent study of island bird coloration found that insular species are duller than continental species. Whether such shifts in color are associated with increased rates of color evolution on islands remains unknown. Here, we incorporate geometric morphometric techniques to study plumage color diversity in a speciose clade of colorful birds that inhabit nearly all areas of the globe—kingfishers (Aves: Alcedinidae). In particular, we test two hypotheses: (i) that plumage complexity enhances interspecific rates of color evolution and (ii) that plumage color diversity is elevated on islands. Our results show that more complex plumages result in more diverse colors among species and plumage color evolves faster on islands. Importantly, we found that insular species did not have more complex plumages than their continental relatives. Thus, complexity may be a key innovation that facilitates response to divergent (or relaxed) selection pressures on islands. Lack of support for competition driving rates of evolution along different color axes hints at an allopatric model of color evolution in which species adapt to local conditions on different islands. This work demonstrates how a truly multivariate treatment of color data can reveal evolutionary patterns that might otherwise go unnoticed.
High-resolution analysis of individual Drosophila melanogaster larvae within groups uncovers inter- and intra-individual variability in locomotion and its neurogenetic modulation

Neuronally orchestrated muscular movement and locomotion are defining faculties of multicellular animals. Due to its numerically simple brain and neuromuscular system and its genetic accessibility, the larva of the fruit fly Drosophila melanogaster is an established model to study these processes at tractable levels is an established model for studying these processes at tractable levels of complexity. However, although the faculty of locomotion clearly pertains to the individual animal, present studies of locomotion in larval Drosophila mostly use group assays and measurements aggregated across individual animals. The alternative is to measure animals one at a time, an extravagance for larger-scale analyses. In principle or in practice, this in particular rules out grasping the inter- and intra-individual variability in locomotion and its genetic and neuronal determinants. Here we present the IMBA (Individual Maggot Behaviour Analyser) for tracking and analysing the behaviour of individual larvae within groups. Using a combination of computational modelling and statistical approaches, the IMBA reliably resolves individual identity across collisions. It does not require specific hardware and can therefore be used in non-expert labs. We take advantage of the IMBA first to systematically describe the inter- and intra-individual variability in free, unconstrained locomotion in wild-type animals. We then report the discovery of a novel, complex locomotion phenotype of a mutant lacking an adhesion-type GPCR. The IMBA further allows us to determine, at the level of individual animals, the modulation of locomotion across repeated activations of dopamine neurons. Strikingly, IMBA can also be used to analyse ‘silly walks’, that is patterns of locomotion it was not originally designed to investigate. This is shown for the transient backward locomotion induced by brief optogenetic activation of the brain-descending ‘mooncrawler’ neurons, and the variability in this behaviour. Thus, the IMBA is an easy-to-use toolbox allowing an unprecedentedly rich view of the behaviour and behavioural variability of individual Drosophila larvae, with utility in multiple biomedical research contexts.
Targeting neuroinflammation by pharmacologic down-regulation of inflammatory pathways is neuroprotective in protein misfolding disorders

Neuroinflammation plays a crucial role in the development of neurodegenerative protein misfolding disorders. This category of progressive diseases includes, but is not limited to, Alzheimer’s disease, Parkinson’s disease, and prion diseases. Shared pathogenesis involves the accumulation of misfolded proteins, chronic neuroinflammation, and synaptic dysfunction, ultimately leading to irreversible neuronal loss, measurable cognitive deficits, and death. Presently, there are little to no effective treatments to halt the advancement of neurodegenerative diseases. We hypothesized directly targeting neuroinflammation by downregulating the transcription factor, NF-κB and the inflammasome protein, NLRP3, with the brain-penetrant, non-toxic, SB_NI_112, would be neuroprotective. To achieve this, we used a cocktail of RNA targeting therapeutics (SB_NI_112) shown to be brain-penetrant, non-toxic, and targeting both NF-|B and NLRP3. We utilized a mouse-adapted prion strain as a model for neurodegenerative diseases to assess aggregation of misfolded proteins, glial inflammation, neuronal loss, cognitive deficits, and lifespan. Prion-diseased mice were treated either intraperitoneally or intranasally with SB_NI_112. Behavioral and cognitive deficits were significantly protected by this combination of NF-κB and NLRP3 down-regulators. Treatment reduced glial inflammation, protected against neuronal loss, prevented spongiotic change, rescued cognitive deficits, and significantly lengthened lifespan of prion-diseased mice. We have identified a non-toxic, systemic pharmacologic that down-regulates NF-|B and NLRP3, prevents neuronal death and slows the progression of neurodegenerative disease. Though mouse models do not always predict human patient success, and the study was limited due to sample size and number of dosing methods utilized, these findings serve as a proof of principle for continued translation of the therapeutic SB_NI_112 for prion disease and other neurodegenerative diseases. Based on success in a murine prion model, we will be continual testing SB_NI_112 in a variety of neurodegenerative disease models, including Alzheimer’s Disease and Parkinson’s Disease.
A Conserved Role for Stomatin Domain Genes in Olfactory Behavior

Abstract The highly-conserved stomatin domain has been identified in genes throughout all classes of life. In animals, different stomatin domain-encoding genes have been implicated in the function of the kidney, red blood cells, and specific neuron types, although the underlying mechanisms remain unresolved. In one well-studied example of stomatin domain gene function, the Caenorhabditis elegans gene mec-2 and its mouse homolog Stoml3 are required for the function of mechanosensory neurons, where they modulate the activity of mechanosensory ion channels on the plasma membrane. Here, we identify an additional shared function for mec-2 and Stoml3 in a very different sensory context, that of olfaction. In worms, we find that a subset of stomatin domain genes are expressed in olfactory neurons, but only mec-2 is strongly required for olfactory behavior. mec-2 acts cell-autonomously and multiple alternatively-spliced isoforms of mec-2 can be substituted for each other. We generate a Stoml3 knock-out (KO) mouse and demonstrate that, like its worm homolog mec-2, it is required for olfactory behavior. In mice, Stoml3 is not required for odor detection, but is required for odor discrimination. Therefore, in addition to their shared roles in mechanosensory behavior, mec-2 and Stoml3 also have a shared role in olfactory behavior.
Vesicles driven by dynein and kinesin exhibit directional reversals without external regulators

Intracellular transport along cytoskeletal filaments propelled by molecular motors ensures the targeted delivery of cargoes to their destinations. Such transport is rarely unidirectional but rather bidirectional, including intermittent pauses and directional reversals owing to the simultaneous presence of opposite-polarity motors. It has been unclear whether such a complex motility pattern results from the sole mechanical interplay between opposite-polarity motors or requires external regulators. Here, we addressed this outstanding question by reconstituting cargo motility along microtubules in vitro by attaching purified Dynein-Dynactin-BICD2 (DDB) and kinesin-3 (KIF16B) to large unilamellar vesicles. Strikingly, we found that this minimal system is sufficient to recapitulate runs, pauses and reversals similar to in vivo cargo motility. In our experiments, reversals were always preceded by vesicle pausing and the transport directionality could be tuned by the relative numbers of opposite-polarity motors on the vesicles. Unexpectedly, during all runs the vesicle velocity was not influenced by the presence of the opposing motors. To gain mechanistic insight into bidirectional transport, we developed a mathematical model which predicts that low numbers of engaged motors are critical to transition between runs and pauses. Taken together, our results suggest that motors diffusively anchored to membranous cargo transiently engage in a tug-of-war during pauses where stochastic motor attachment and detachment events can lead to directional reversals without the necessity of external regulators.
GOLVEN peptides regulate lateral root spacing as part of a negative feedback loop on the establishment of auxin maxima

The initiation of lateral roots in Arabidopsis requires the accumulation of auxin in lateral root founder cells, yielding a local auxin maximum. The positioning of these auxin maxima along the primary root determines the density and spacing of lateral roots. The GOLVEN6 (GLV6) and GLV10 signaling peptides and their receptors have been established as regulators of lateral root spacing via an inhibitory effect on lateral root initiation. However, it remained unclear how these GLV peptides interfere with auxin signaling or homeostasis. Here we show that GLV6/10 signaling regulates the expression of a subset of auxin response genes during lateral root initiation, downstream of the canonical auxin signaling pathway, while simultaneously inhibiting the establishment of auxin maxima in xylem-pole pericycle cells. We present genetic evidence that this inhibitory effect relies on the activity of the PIN3 and PIN7 auxin export proteins. Furthermore, GLV6/10 peptide signaling was found to enhance PIN7 abundance in the plasma membrane of xylem-pole pericycle cells, which likely stimulates auxin efflux from these cells. Based on these findings, we propose a model in which the GLV6/10 signaling pathway serves as a negative feedback loop that contributes to the robust patterning of auxin maxima along the primary root.
The TBX20-TLE Interaction is Essential for the Second Heart Field

Tbx20 plays a multifaceted role in cardiac morphogenesis and controls a broad gene regulatory network. However, the mechanism by which Tbx20 activates and represses target genes in a tissue-specific and temporal manner remains unclear. Studies show that Tbx20 directly interacts with the Transducin-like Enhancer of Split (TLE) family of proteins to mediate transcriptional repression of downstream target genes. However, a functional role for the Tbx20-TLE transcriptional repression complex during heart development is not established. To this end, we generated a mouse model with a two-amino acid substitution in the Tbx20 EH1 domain, thereby disrupting the Tbx20-TLE interaction (Tbx20EH1mut). We demonstrate that disruption of this interaction impairs critical morphogenic events, including cardiac looping and chamber formation, and ultimately leads to embryonic lethality. Transcriptional profiling of Tbx20EH1mut hearts and analysis of putative Tbx20 direct targets reveals misexpression of the retinoic acid pathway and cardiac progenitor genes, demonstrating that the Tbx20-TLE interaction serves to inhibit cardiac progenitor programs in the developing heart. We find that loss of this interaction also results in perturbations of the second heart field progenitor population, implying that altered cardiac progenitor function may underly the observed cardiac defects in our model. Our studies indicate that TLE-mediated repression is a primary mechanism by which Tbx20 systematically controls gene expression.
Spatially Resolved Single-cell Translatomics at Molecular Resolution

The precise control of mRNA translation is a crucial step in post-transcriptional gene regulation of cellular physiology. However, it remains a major challenge to systematically study mRNA translation at the transcriptomic scale with spatial and single-cell resolutions. Here, we report the development of RIBOmap, a three-dimensional (3D) in situ profiling method to detect mRNA translation for thousands of genes simultaneously in intact cells and tissues. By applying RIBOmap to 981 genes in HeLa cells, we revealed remarkable dependency of translation on cell-cycle stages and subcellular localization. Furthermore, we profiled single-cell translatomes of 5,413 genes in the adult mouse brain tissue with a spatial cell atlas of 62,753 cells. This spatial translatome profiling detected widespread patterns of localized translation in neuronal and glial cells in intact brain tissue networks. Together, RIBOmap presents the first spatially resolved single-cell translatomics technology, accelerating our understanding of protein synthesis in the context of subcellular architecture, cell types, and tissue anatomy.
Biological age and brain age in midlife: relationship to multimorbidity and mental health

Multimorbidity, co-occurrence of two or more chronic conditions, is one of the top priorities in global health research and has emerged as the gold standard approach to study disease accumulation. As aging underlies the development of many chronic conditions, surrogate aging biomarkers are not disease-specific and capture health at the whole person level, having the potential to improve our understanding of multimorbidity. Biological age has been examined in recent years as a surrogate biomarker to capture the process of aging. However, relatively few studies have investigated the relationship between biological age and multimorbidity. More research is needed to quantify biological age using a broad range of biological markers and multimorbidity based on a comprehensive set of chronic conditions. Brain age estimated by neuroimaging data and machine learning models is another surrogate aging biomarker predictive of a wide range of health outcomes. Little is known about the relationship between brain age and multimorbidity. To answer these questions, our study investigates whether elevated biological age and accelerated brain age are associated with an increased risk of multimorbidity using a large dataset from the Midlife in the United States (MIDUS) Refresher study. Ensemble learning is utilized to combine multiple machine learning models to estimate biological age using a comprehensive set of biological markers. Brain age is obtained using convolutional neural networks and neuroimaging data. Our study is the first to examine the relationship between accelerated brain age and multimorbidity and presents the first effort to test whether sex moderates the relationship between these surrogate aging biomarkers and multimorbidity. Furthermore, it is the first attempt to explore how biological age and brain age are related to multimorbidity in mental health. Our findings hold the potential to advance the understanding of the accumulation of physical and mental health conditions, which may contribute to new strategies to improve the treatment of multimorbidity and detection of at-risk individuals.