Miracle-dz/UniFAR-FTUs huggingface dataset:
Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary Statistics

Proprietary genetic datasets are valuable for boosting the statistical power of genome-wide association studies (GWASs), but their use can restrict investigators from publicly sharing the resulting summary statistics. Although researchers can resort to sharing down-sampled versions that exclude restricted data, down-sampling reduces power and might change the genetic etiology of the phenotype being studied. These problems are further complicated when using multivariate GWAS methods, such as genomic structural equation modeling (Genomic SEM), that model genetic correlations across multiple traits. Here, we propose a systematic approach to assess the comparability of GWAS summary statistics that include versus exclude restricted data. Illustrating this approach with a multivariate GWAS of an externalizing factor, we assessed the impact of down-sampling on (1) the strength of the genetic signal in univariate GWASs, (2) the factor loadings and model fit in multivariate Genomic SEM, (3) the strength of the genetic signal at the factor level, (4) insights from gene-property analyses, (5) the pattern of genetic correlations with other traits, and (6) polygenic score analyses in independent samples. For the externalizing GWAS, down-sampling resulted in a loss of genetic signal and fewer genome-wide significant loci, while the factor loadings and model fit, gene-property analyses, genetic correlations, and polygenic score analyses are robust. Given the importance of data sharing for the advancement of open science, we recommend that investigators who share down-sampled summary statistics report these analyses as accompanying documentation to support other researchers’ use of the summary statistics.
The ER membrane protein complex governs lysosomal turnover of a mitochondrial tail-anchored protein, BNIP3, to restrict mitophagy

Lysosomal degradation of autophagy receptors is a common proxy for selective autophagy. However, we find that two established mitophagy receptors, BNIP3 and BNIP3L/NIX, violate this assumption. Rather, BNIP3 and NIX are constitutively delivered to lysosomes in an autophagy-independent manner. This alternative lysosomal delivery of BNIP3 accounts for nearly all of its lysosome-mediated degradation, even upon mitophagy induction. To identify how BNIP3, a tail-anchored protein in the outer mitochondrial membrane, is delivered to lysosomes, we performed a genome-wide CRISPR screen for factors influencing BNIP3 flux. By this approach, we revealed both known modifiers of BNIP3 stability as well as a pronounced reliance on endolysosomal components, including the ER membrane protein complex (EMC). Importantly, the endolysosomal system regulates BNIP3 alongside, but independent of, the ubiquitin-proteosome system (UPS). Perturbation of either mechanism is sufficient to modulate BNIP3-associated mitophagy and affect underlying cellular physiology. In short, while BNIP3 can be cleared by parallel and partially compensatory quality control pathways, non-autophagic lysosomal degradation of BNIP3 is a strong post-translational modifier of BNIP3 function. More broadly, these data reveal an unanticipated connection between mitophagy and TA protein quality control, wherein the endolysosomal system provides a critical axis for regulating cellular metabolism. Moreover, these findings extend recent models for tail-anchored protein quality control and install endosomal trafficking and lysosomal degradation in the canon of pathways that ensure tight regulation of endogenous TA protein localization.
DIP-MS: A novel ultra-deep interaction proteomics for the deconvolution of protein complexes

Most, if not all, proteins are organized in macromolecular assemblies, which represent key functional units regulating and catalyzing the majority of cellular processes in health and disease. Ever-advancing analytical capabilities promise to pinpoint lesions in proteome modularity driving disease phenotypes. Affinity purification of the protein of interest combined with LC-MS/MS (AP-MS) represents the method of choice to identify interacting proteins. The composition of complex isoforms concurrently present in the AP sample can however not be resolved from a single AP-MS experiment but requires computational inference from multiple time-and resource-intensive reciprocal AP-MS experiments. In this study we introduce Deep Interactome Profiling by Mass Spectrometry (DIP-MS) which combines affinity enrichment with BN-PAGE separation, DIA mass spectrometry and deep-learning-based signal processing to resolve complex isoforms sharing the same bait protein in a single experiment. We applied DIP-MS to probe the organisation of the human prefoldin (PFD) family of complexes, resolving distinct PFD holo- and sub-complex variants, complex-complex interactions and complex isoforms with new subunits that were experimentally validated. Our results demonstrate that DIP-MS can reveal proteome modularity at unprecedented depth and resolution and thus represents a critical steppingstone to relate a proteome state to phenotype in both healthy and diseased conditions.
Prophage maintenance is determined by environment-dependent selective sweeps rather than mutational availability

Prophages, viral sequences integrated into bacterial genomes, can be beneficial and costly. Despite the risk of prophage activation and subsequent bacterial death, active prophages are present in most bacterial genomes. However, our understanding of the selective forces that maintain prophages in bacterial populations is limited. Combining experimental evolution with stochastic modelling, we show that prophage maintenance and loss are primarily determined by environmental conditions that alter the net fitness effect of a prophage. When prophages are too costly, they are rapidly lost through environment-specific sequences of selective sweeps. Conflicting selection pressures that select against the prophage but for a prophage-encoded accessory gene can maintain prophages. The dynamics of prophage maintenance additionally depends on the sociality of this accessory gene. Non-cooperative genes maintain prophages at higher frequencies than cooperative genes, which can protect phage-free ‘cheaters’ that may emerge if prophage costs outweigh their benefits. Our simulations suggest that environmental variation plays a larger role than mutation rates in determining prophage maintenance. These findings highlight the complexity of selection pressures that act on mobile genetic elements and challenge our understanding of the role of environmental factors relative to random chance events in shaping the evolutionary trajectory of bacterial populations.
Her6 and Prox1 are novel regulators of photoreceptor regeneration in the zebrafish retina

Damage to light-sensing photoreceptors (PRs) occurs in highly prevalent retinal diseases. As humans cannot regenerate new PRs, these diseases often lead to irreversible blindness. Intriguingly, animals, such as the zebrafish, have the ability to regenerate PRs efficiently and restore functional vision. Upon injury, mature Müller glia (MG) undergo reprogramming to adopt a stem cell-like state. This process is similar to cellular dedifferentiation, and results in the generation of progenitor cells, which, in turn, proliferate and differentiate to replace lost retinal neurons. In this study, we tested whether factors involved in dedifferentiation of Drosophila CNS are implicated in the regenerative response in the zebrafish retina. We found that hairy-related 6 (her6) negatively regulates of PR production by regulating the rate of cell divisions in the MG-derived progenitors. prospero homeobox 1 (prox1) is expressed in differentiated PRs, and likely promotes PR differentiation through phase separation. Interestingly, upon Her6 downregulation, Prox1 is precociously upregulated in the PRs, to promote PR differentiation; conversely, loss of Prox1 also induces a downregulation of Her6. Together, we identified two novel candidates of PR regeneration that cross regulate each other, and may be exploited to promote human retinal regeneration and vision recovery.
Adaptive therapy for ovarian cancer: An integrated approach to PARP inhibitor scheduling

Toxicity and emerging drug resistance are important challenges in PARP inhibitor (PARPi) treatment of ovarian cancer. Recent research has shown that evolutionary-inspired treatment algorithms which adapt treatment to the tumor’s treatment response (adaptive therapy) can help to mitigate both. Here, we present a first step in developing an adaptive therapy protocol for PARPi treatment by combining mathematical modelling and wet-lab experiments to characterize the cell population dynamics under different PARPi schedules. Using data from in vitro Incucyte Zoom time-lapse microscopy experiments and a step-wise model selection process we derive a calibrated and validated ordinary differential equation model, which we then use to test different plausible adaptive treatment schedules. Our model can accurately predict the in vitro treatment dynamics, even to new schedules, and suggests that treatment modifications need to be carefully timed, or one risks losing control over tumour growth, even in the absence of any resistance. This is because our model predicts that multiple rounds of cell division are required for cells to acquire sufficient DNA damage to induce apoptosis. As a result, adaptive therapy algorithms that modulate treatment but never completely withdraw it are predicted to perform better in this setting than strategies based on treatment interruptions. Pilot experiments in vivo confirm this conclusion. Overall, this study contributes to a better understanding of the impact of scheduling on treatment outcome for PARPis and showcases some of the challenges involved in developing adaptive therapies for new treatment settings.
Infant recognition of infant vocal signals

Most of the speech accessible to infants who are not yet babbling will not have infant vocal properties; yet their perception of infant vocal signals is critical for speech development. We report three experiments designed to assess whether 4- to 5-month-olds recognize and preferentially attend to vowels produced by infant talkers over vowels produced by adult talkers. Infants were tested in a sequential preferential looking procedure using isolated vowels synthesized by VLAM. In experiment 1, infants listened significantly longer to vowels produced by an infant talker than an adult (female). In experiment 2, infants failed to show any listening preference for infant versus adult vowels synthesized with matching (infant-appropriate) f0 values, suggesting that infants either recognized the un-natural pairing of f0 and formant structure in these adult vowels or are attracted to high f0 values. Failing to support the latter interpretation, infants in experiment 3 showed no listening preference when presented.
Time-dependent neural arbitration between cue associative and episodic fear memories

After traumatic events, simple cue-threat associative memories strengthen while episodic memories become fragmented. However, how the brain prioritizes cue associations over episodic coding of traumatic events remains unclear. Here, we developed a new episodic threat conditioning paradigm in which participants concurrently form two memory representations: cue associations and episodic cue sequence. We discovered that these two distinct memories compete for physiological fear expression, reorganizing overnight from an overgeneralized cue-based to a precise sequence-based expression. With multivariate fMRI, we track inter-area communication of the memory representations and demonstrate that a shift from hippocampal-dominant to prefrontal-dominant control of the fear regulatory circuit governs this memory maturation. Critically, this overnight reorganization is altered in individuals with heightened trait anxiety. Together, these findings suggest the brain prioritizes generalizable associative memories under recent traumatic stress, but resorts to selective episodic memories 24 hrs later. Time-dependent memory competition provides a unifying account for memory dysfunctions in posttraumatic stress disorders.
A dynamic foot model for predictive simulations of gait reveals causal relations between foot structure and whole body mechanics

The unique structure of the human foot is seen as a crucial adaptation for bipedalism. Its arched shape makes it possible to stiffen the foot to withstand high loads when pushing off, without compromising the range of motion. Experimental studies demonstrated that manipulating foot stiffness had considerable effects on gait. In clinical practise, altered foot structure is associated with pathological gait. Yet our understanding of how foot structure influences gait mechanics is still poor. Here we used predictive simulations to explore causal relations between foot properties and whole-body gait. Our dynamic three-segment foot model with longitudinal arch improved gait predictions compared to one- and two-segment foot models and can explain measured ankle-foot kinematics and energetics. We identified three properties of the ankle-foot complex that are crucial for healthy walking: (1) compliant Achilles tendon, (2) stiff heel pad, (3) the ability to stiffen the foot. The latter requires sufficient arch height and contributions of plantar fascia, intrinsic and extrinsic foot muscles. Insufficient foot stiffness results in walking patterns with reduced push-off power. During terminal stance plantar fascia and intrinsic foot muscles transfer energy from the metatarsophalangeal to midtarsal joint, which further increases push-off power.
flashfmZoom: a tool for joint fine-mapping and exploration of GWAS results in the UK Biobank

Summary flashfmZoom is an all-in-one tool for analysis and interactive visualisation of potential causal genetic variants that underlie associations with quantitative traits from the UK Biobank. It offers a user-friendly interface and guides users in the selection of pleiotropic regions among subsets of 134 quantitative traits, such as cardiometabolic, hematologic, and respiratory traits. Users may then run single-trait fine-mapping, allowing for multiple causal variants, and leverage information between the traits using multi-trait fine-mapping to improve resolution. A series of interactive plots and downloadable tables are generated within flashfmZoom to identify potential causal variants that are shared or distinct between the traits; it also lists relevant literature for the traits and/or variants. Besides exploring traits that are well-known to be related, flashfmZoom encourages interactive exploration for the joint analysis of traits that may not often be considered together. This may reveal common aetiological pathways between traits related to different disorders. Availability and Implementation flashfmZoom is an interactive open-source R shiny app software available online directly at https://mrc-bsu.shinyapps. io/flashfmZoomOnline/, with source code in GitHub under the MIT license https://github.com/fz-cambridge/flashfmZoom and at https://doi.org/10.5281/zenodo.7756205. Contact feng.zhou@mrc-bsu.cam. ac.uk or jennifer.asimit@mrc-bsu.cam. ac.uk
Overview of Alfvén eigenmode experiments in JET

Results from the first experiments to drive Alfven eigenmodes (AEs) with antennas external to a tokamak plasma are presented. In ohmically heated plasma discharges, direct experimental measurements of the damping of toroidicity induced AEs (TAEs) have allowed an identification of different regimes corresponding to different dominant TAE absorption mechanisms with a wide range of damping rates, 10-3 ≤ γ/w ≤ 10-1. In plasmas heated by ion cyclotron resonance heating, neutral beam injection heating, lower hybrid heating and high plasma current ohmic heating, a new class of weakly damped Alfven eigenmodes, the kinetic Alfven eigenmodes, predicted in theoretical models that include finite Larmor radius and finite parallel electric field effects, has been identified experimentally
Transformations of sensory information in the brain reflect a changing definition of optimality

Neurons throughout the brain modulate their firing rate lawfully in response to changes in sensory input. Theories of neural computation posit that these modulations reflect the outcome of a constrained optimization: neurons aim to efficiently and robustly represent sensory information under resource limitations. Our understanding of how this optimization varies across the brain, however, is still in its infancy. Here, we show that neural responses transform along the dorsal stream of the visual system in a manner consistent with a transition from optimizing for information preservation to optimizing for perceptual discrimination. Focusing on binocular disparity – the slight differences in how objects project to the two eyes – we re-analyze measurements from neurons characterizing tuning curves in macaque monkey brain regions V1, V2, and MT, and compare these to measurements of the natural visual statistics of binocular disparity. The changes in tuning curve characteristics are computationally consistent with a shift in optimization goals from maximizing the information encoded about naturally occurring binocular disparities to maximizing the ability to support fine disparity discrimination. We find that a change towards tuning curves preferring larger disparities is a key driver of this shift. These results provide new insight into previously-identified differences between disparity-selective regions of cortex and suggest these differences play an important role in supporting visually-guided behavior. Our findings support a key re-framing of optimal coding in regions of the brain that contain sensory information, emphasizing the need to consider not just information preservation and neural resources, but also relevance to behavior. Significance A major role of the brain is to transform information from the sensory organs into signals that can be used to guide behavior. Neural activity is noisy and can consume large amount of energy, so sensory neurons must optimize their information processing so as to limit energy consumption while maintaining key behaviorally-relevant information. In this report, we re-examine classically-defined brain areas in the visual processing hierarchy, and ask whether neurons in these areas vary lawfully in how they represent sensory information. Our results suggest that neurons in these brain areas shift from being an optimal conduit of sensory information to optimally supporting perceptual discrimination during natural tasks.
Live Cell Imaging of ATP Levels Reveals Metabolic Compartmentalization within Motoneurons and Early Metabolic Changes in FUS ALS Motoneurons

Motoneurons are one of the highest energy demanding cell types and a primary target in Amyotrophic lateral sclerosis (ALS), a debilitating and lethal neurodegenerative disorder without currently available effective treatments. Disruption of mitochondrial ultra-structure, transport and metabolism is a commonly reported phenotype in ALS models and can critically affect survival and proper function of motor neurons. However, how changes in metabolic rates contribute to ALS progression are not fully understood yet. Here we utilize hiPCS derived motoneuron cultures and live imaging quantitative techniques to evaluate metabolic rates in Fused in Sarcoma (FUS)-ALS model cells. We show that differentiation and maturation of motoneurons is accompanied by an overall upregulation of mitochondrial components and significant increase in metabolic rates that corresponds to their high energy-demanding state. Detailed compartment-specific live measurements using a fluorescent ATP sensor and FLIM imaging show significantly lower levels of ATP in the somas of cells carrying FUS-ALS mutations. These changes lead to the increased vulnerability of disease motoneurons to further metabolic challenges with mitochondrial inhibitors and could be due to the disruption of mitochondrial inner membrane integrity and an increase in its proton leakage. Furthermore, our measurements demonstrate heterogeneity between axonal and somatic compartments with lower relative levels of ATP in axons. Our observations strongly support the hypothesis that mutated FUS impacts metabolic states of motoneurons and makes them more susceptible to further neurodegenerative mechanisms.
Manifold Learning Enables Interpretable Analysis of Raman Spectra from Extracellular Vesicle and Other Mixtures

Extracellular vesicles (EVs) have emerged as promising diagnostic and therapeutic candidates in many biomedical applications. However, EV research continues to rely heavily on in vitro cell cultures for EV production, where the exogenous EVs present in fetal bovine (FBS) or other required serum supplementation can be difficult to remove entirely. Despite this and other potential applications involving EV mixtures, there are currently no rapid, robust, inexpensive, and label-free methods for determining the relative concentrations of different EV subpopulations within a sample. In this study, we demonstrate that surface-enhanced Raman spectroscopy (SERS) can biochemically fingerprint fetal bovine serum-derived and bioreactor-produced EVs, and after applying a novel manifold learning technique to the acquired spectra, enables the quantitative detection of the relative amounts of different EV populations within an unknown sample. We first developed this method using known ratios of Rhodamine B to Rhodamine 6G, then using known ratios of FBS EVs to breast cancer EVs from a bioreactor culture. In addition to quantifying EV mixtures, the proposed deep learning architecture provides some knowledge discovery capabilities which we demonstrate by applying it to dynamic Raman spectra of a chemical milling process. This label-free characterization and analytical approach should translate well to other EV SERS applications, such as monitoring the integrity of semipermeable membranes within EV bioreactors, ensuring the quality or potency of diagnostic or therapeutic EVs, determining relative amounts of EVs produced in complex co-culture systems, as well as many Raman spectroscopy applications.
Piperidine CD4-Mimetic Compounds Expose Vulnerable Env Epitopes Sensitizing HIV-1-Infected Cells to ADCC

The ability of HIV-1 accessory proteins Nef and Vpu to decrease CD4 levels contributes to the protection of infected cells from antibody-dependent cellular cytotoxicity (ADCC) by preventing the exposure of Env vulnerable epitopes. Small-molecule CD4 mimetics (CD4mc) based on the indane and piperidine scaffolds such as (+)-BNM-III-170 and (S)-MCG-IV-210 sensitize HIV-1 infected cells to ADCC by exposing CD4-induced (CD4i) epitopes recognized by non-neutralizing antibodies abundantly present in plasma from people living with HIV. Here, we characterize a new family of CD4mc, (S)-MCG-IV-210 derivatives, based on the piperidine scaffold which engage the gp120 within the Phe43 cavity by targeting the highly-conserved Asp368 Env residue. We utilized structure-based approaches and developed a series of piperidine analogs with improved activity to inhibit infection of difficult-to-neutralize tier-2 viruses and sensitize infected cells to ADCC mediated by HIV+ plasma. Moreover, the new analogs formed an H-bond with the α-carboxylic acid group of Asp368, opening a new avenue to enlarge the breadth of this family of anti-Env small molecules. Overall, the new structural and biological attributes of these molecules make them good candidates for strategies aimed at the elimination HIV-1-infected cells.