Miracle-dz/UniFAR-FTUs huggingface dataset:
BonA from Acinetobacter baumannii Forms a Divisome-Localized Decamer That Supports Outer Envelope Function

The pathogen Acinetobacter baumannii is considered an urgent threat to human health. A. baumannii is highly resistant to treatment with antibiotics, in part due to its protective cell envelope. This bacterium is only distantly related to other bacterial pathogens, so its cell envelope has distinct properties and contains components distinct from those of other bacteria that support its function. ABSTRACT Acinetobacter baumannii is a high-risk pathogen due to the rapid global spread of multidrug-resistant lineages. Its phylogenetic divergence from other ESKAPE pathogens means that determinants of its antimicrobial resistance can be difficult to extrapolate from other widely studied bacteria. A recent study showed that A. baumannii upregulates production of an outer membrane lipoprotein, which we designate BonA, in response to challenge with polymyxins. Here, we show that BonA has limited sequence similarity and distinct structural features compared to lipoproteins from other bacterial species. Analyses through X-ray crystallography, small-angle X-ray scattering, electron microscopy, and multiangle light scattering demonstrate that BonA has a dual BON (Bacterial OsmY and Nodulation) domain architecture and forms a decamer via an unusual oligomerization mechanism. This analysis also indicates this decamer is transient, suggesting dynamic oligomerization plays a role in BonA function. Antisera recognizing BonA shows it is an outer membrane protein localized to the divisome. Loss of BonA modulates the density of the outer membrane, consistent with a change in its structure or link to the peptidoglycan, and prevents motility in a clinical strain (ATCC 17978). Consistent with these findings, the dimensions of the BonA decamer are sufficient to permeate the peptidoglycan layer, with the potential to form a membrane-spanning complex during cell division. IMPORTANCE The pathogen Acinetobacter baumannii is considered an urgent threat to human health. A. baumannii is highly resistant to treatment with antibiotics, in part due to its protective cell envelope. This bacterium is only distantly related to other bacterial pathogens, so its cell envelope has distinct properties and contains components distinct from those of other bacteria that support its function. Here, we report the discovery of BonA, a protein that supports A. baumannii outer envelope function and is required for cell motility. We determine the atomic structure of BonA and show that it forms part of the cell division machinery and functions by forming a complex, features that mirror those of distantly related homologs from other bacteria. By improving our understanding of the A. baumannii cell envelope this work will assist in treating this pathogen.
Comparison of transparency and shrinkage of insect brains using novel and traditional clearing methods

Improvement of imaging quality has the potential to visualize previously unseen building blocks of the brain and is therefore one of the great challenges in neuroscience. Rapid development of new tissue clearing techniques in recent years have attempted to solve imaging compromises in thick brain samples, particularly for high resolution optical microscopy, where the clearing medium needs to match the refractive index of the objective immersion medium. These problems are exacerbated in insect tissue, where numerous (initially air-filled) tracheal tubes branching throughout the brain increase the scattering of light. To date, surprisingly few studies have systematically quantified the benefits of such clearing methods using objective transparency and tissue shrinkage measurements. In this study we compare a traditional and widely used insect clearing medium, methyl salicylate combined with permanent mounting in Permount (‘MS/P’) with several more recently applied clearing media that offer tunable refractive index (n): 2,2-thiodiethanol (TDE), ‘SeeDB2’ (in variants SeeDB2S & SeeDB2G matched to oil and glycerol immersion, n=1.52 & 1.47 respectively) and Rapiclear (also with n=1.52 & 1.47). We measured transparency and tissue shrinkage by comparing freshly dissected brains with cleared brains from dipteran flies, with or without addition of vacuum or ethanol pre-treatments (dehydration and rehydration) to evacuate air from the tracheal system. The results show that ethanol pre-treatment is very effective for improving transparency, regardless of the subsequent clearing medium, while vacuum treatment offers little measurable benefit. Ethanol pre-treated SeeDB2G and Rapiclear brains show much less shrinkage than using the traditional MS/P method. Furthermore, these newly developed media offer outstanding transparency compared to TDE and MS/P. Rapiclear protocols were less laborious compared to SeeDB2, but both offer sufficient transparency and refractive index tunability to permit super-resolution imaging of local volumes in whole mount brains from large insects, and even light-sheet microscopy. Although long-term permanency of Rapiclear stored samples remains to be established, our samples still showed good preservation of fluorescence after storage for more than a year at room temperature.
Esco2 and cohesin regulate CRL4 ubiquitin ligase ddb1 expression and thalidomide teratogenicity

Cornelia de Lange syndrome (CdLS) and Roberts syndrome (RBS) are severe developmental maladies that arise from mutation of cohesin (including SMC3, CdLS) and ESCO2 (RBS). Though ESCO2 activate cohesin, CdLS and RBS etiologies are currently considered non-synonymous and for which pharmacological treatments are unavailable. Here, we identify a unifying mechanism that integrates these genetic maladies to pharmacologically-induced teratogenicity via thalidomide. Our results reveal that Esco2 and cohesin co-regulate a component of CRL4 ubiquitin ligase through which thalidomide exerts teratogenic effects. These findings are the first to link RBS and CdLS to thalidomide teratogenicity and offers new insights into treatments.
Impact of Model Order Choice on the Results of Parallel Independent Component Analysis

Parallel independent component analysis (pICA) is a data-driven method that identifies the maximally independent components of multiple imaging modalities while simultaneously investigating the strength of their correlations. Researchers using pICA are given the option to use the suggested model order calculated by the minimum descriptive length (MDL) algorithm, or they can choose their own model order. To date, there are no suggested guidelines for this choice. To test the sensitivity of pICA to the selection of model order, we applied it to a well-researched brain disorder, schizophrenia, looking at the correlations between patterns of grey matter volume (GM) volume and white matter integrity, measured using fractional anisotropy (FA). We varied model orders from low to high, and tested the sensitivity to disorder effects (cases vs controls), similarity of spatial maps identified across model orders, consolidation or distribution effects related to model order selection, and the performance of the minimum descriptive length (MDL) algorithm. The pICA results (multimodal analysis) were also compared to the ICA (unimodal analysis) for each imaging modality. Across model orders, there was consistent sensitivity to disorder effects, and clustered patterns of spatial maps for both the GM and FA reflecting those differences. The MDL-estimated model order captured the majority, but not all, of the spatial patterns present in the GM and FA. There was not the expected consolidation of spatial maps at lower model orders, nor the distribution of spatial maps at higher model orders. The spatial patterns identified in the ICA closely resemble those found in the pICA, although lacking the benefit of the optimization algorithm, were not as highly correlated. This offers some insight and guidance for researchers interested in using pICA with regard to selecting model order for their particular analysis of multiple imaging modalities.
Influence of Exogenous Gonadotropin and Sexual Steroids on Ovary Development in Japanese Eel Anguilla japonica

This study examines Japanese eel ovary responded to the administration of exogenous sexual hormone throughout the reproductive process. In short-term experiment, ovarian follicle exhibited sensitivity to salmon pituitary homogenate (SPH) and sexual steroids (E2 and MT) in the early vitellogenic stages. The apoptotic signals were exclusively localized in the outer theca layer which was detected from in situ TUNEL, furthermore, the appearance of the apoptotic signal in the early vitellogenic stage seems to correlate with a reduction of oocyte numbers in long-term experiment. In long-term experiment, the mean GSI and total oocyte numbers indicated that multiple injections of E2 or MT were not of much benefit to promote the gonadal development of those fish. Despite SPH treatment was an effective and indispensable method to hasten artificially sexual maturation, and the size-frequency distribution indicated that the most developed oocytes of those were growing from the vitellogenic stage to the final maturational phase. However, the treatment of SPH plus E2 failed to promote the ovarian development and exhibited a remarkable reduction of total oocyte numbers. Of interest is the synergistic effect of SPH plus MT revealed that MT, a potent, aromatizable androgen, provides a potential usefulness to participate the process of vitellogenesis when it combines with SPH treatments, furthermore, the synergistic effect actually enhances the survival and synchronous development of ovarian follicle throughout the reproductive process.
Knockdown of the E3 Ubiquitin ligase UBR5 and its role in skeletal muscle anabolism

UBR5 is an E3-ubiquitin-ligase positively associated with anabolism, hypertrophy and recovery from atrophy in skeletal muscle. The precise mechanisms underpinning UBR5’s role in the regulation of skeletal muscle mass remain unknown. The present study aimed to elucidate these mechanisms by silencing the UBR5 gene in-vitro and in-vivo. The siRNA-induced reduction (−77%) in UBR5 gene expression in human myotubes was prevented by mechanical loading, suggesting that UBR5 gene expression may be regulated via mechano-transduction signalling. Therefore, we electroporated a UBR5-RNAi plasmid into mouse tibialis anterior muscle in-vivo to investigate the impact of reduced UBR5 on mechano-transduction signalling MEK/ERK/p90RSK and Akt/p70S6K/4E-BP1/rpS6 pathways. Seven days post UBR5 RNAi electroporation, while reductions in overall muscle mass were not detected, mean CSA of GFP-positive fibers was reduced (−9.5%) and the number of large fibers was lower versus the control. Importantly, UBR5-RNAi significantly reduced total RNA, muscle protein synthesis, ERK1/2 and Akt phosphorylation. Whilst p90RSK phosphorylation significantly increased, total p90RSK protein levels demonstrated a 45% reduction with UBR5-RNAi. Finally, these early signalling events after 7 days of UBR5 knockdown culminated in significant reductions in muscle mass (−4.6%) and larger reductions in fiber CSA (−18.5%) after 30 days. This was associated with increased levels of the phosphatase, PP2Ac, and inappropriate chronic elevation of p70S6K and rpS6 between 7 and 30 days, and corresponding reductions in eIF4e. This study demonstrates UBR5 plays an important role in anabolism/hypertrophy, whereby knockdown of UBR5 culminates in skeletal muscle atrophy.
SLEAP: Multi-animal pose tracking

The desire to understand how the brain generates and patterns behavior has driven rapid methodological innovation to quantify and model natural animal behavior. This has led to important advances in deep learning-based markerless pose estimation that have been enabled in part by the success of deep learning for computer vision applications. Here we present SLEAP (Social LEAP Estimates Animal Poses), a framework for multi-animal pose tracking via deep learning. This system is capable of simultaneously tracking any number of animals during social interactions and across a variety of experimental conditions. SLEAP implements several complementary approaches for dealing with the problems inherent in moving from single-to multi-animal pose tracking, including configurable neural network architectures, inference techniques, and tracking algorithms, enabling easy specialization and tuning for particular experimental conditions or performance requirements. We report results on multiple datasets of socially interacting animals (flies, bees, and mice) and describe how dataset-specific properties can be leveraged to determine the best configuration of SLEAP models. Using a high accuracy model (<2.8 px error on 95% of points), we were able to track two animals from full size 1024 × 1024 pixel frames at up to 320 FPS. The SLEAP framework comes with a sophisticated graphical user interface, multi-platform support, Colab-based GPU-free training and inference, and complete tutorials available, in addition to the datasets, at sleap.ai.
OpSeF: Open Source Python Framework for Collaborative Instance Segmentation of Bioimages

Various pre-trained deep learning models for the segmentation of bioimages have been made available as ‘developer-to-end-user’ solutions. They usually require neither knowledge of machine learning nor coding skills, are optimized for ease of use, and deployability on laptops. However, testing these tools individually is tedious and success is uncertain. Here, we present the ‘Op’en ‘Se’gmentation ‘F’ramework (OpSeF), a Python framework for deep learning-based instance segmentation. OpSeF aims at facilitating the collaboration of biomedical users with experienced image analysts. It builds on the analysts’ knowledge in Python, machine learning, and workflow design to solve complex analysis tasks at any scale in a reproducible, well-documented way. OpSeF defines standard inputs and outputs, thereby facilitating modular workflow design and interoperability with other software. Users play an important role in problem definition, quality control, and manual refinement of results. All analyst tasks are optimized for deployment on Linux workstations or GPU clusters, all user tasks may be performed on any laptop in ImageJ. OpSeF semi-automates preprocessing, convolutional neural network (CNN)-based segmentation in 2D or 3D, and post-processing. It facilitates benchmarking of multiple models in parallel. OpSeF streamlines the optimization of parameters for pre- and post-processing such, that an available model may frequently be used without retraining. Even if sufficiently good results are not achievable with this approach, intermediate results can inform the analysts in the selection of the most promising CNN-architecture in which the biomedical user might invest the effort of manually labeling training data. We provide Jupyter notebooks that document sample workflows based on various image collections. Analysts may find these notebooks useful to illustrate common segmentation challenges, as they prepare the advanced user for gradually taking over some of their tasks and completing their projects independently. The notebooks may also be used to explore the analysis options available within OpSeF in an interactive way and to document and share final workflows. Currently, three mechanistically distinct CNN-based segmentation methods, the U-Net implementation used in Cellprofiler 3.0, StarDist, and Cellpose have been integrated within OpSeF. The addition of new networks requires little, the addition of new models requires no coding skills. Thus, OpSeF might soon become both an interactive model repository, in which pre-trained models might be shared, evaluated, and reused with ease.
Integration of brief light flashes varying in intensity and duration by the human circadian system

The human circadian system is exquisitely sensitive to light, through a pathway connecting the melanopsin-expressing intrinsically photosensitive retinal ganglion cells (ipRGCs) to the hypothalamic suprachiasmatic nuclei (SCN). ipRGCs are characterised by a delayed off-time following cessation of light exposure; we exploited this unusual physiologic property and examined how a sequence of flashes of bright light differing in intensity or duration presented in the biological night could delay the human circadian clock in vivo in healthy young participants (n=54). To understand the mechanism underlying circadian photoreception, we probed temporal integration by manipulating flash intensity and duration independently. In a 34-hour in-laboratory between-subjects design, we examined variable-intensity (3, 30, 95, 300, 950, 3000, or 9500 photopic lux; n=28 participants) flashes at fixed duration (2 ms), and variable-duration (10 μs, 100 μs, 1 ms, 10 ms, 100 ms, 1 sec, 10 sec) flashes at fixed intensity (2000 photopic lux; n=31 participants). We measured the phase shift of dim-light melatonin onset on the subsequent evening, and acute melatonin suppression and alertness during the flash sequence. In the variable-intensity study, we find a clear sigmoidal dose-response relationship for flash intensity and the induced circadian phase shift. In the variable-duration study, we find no parametric relationship between flash duration and induced circadian phase shift, indicating a relative insensitivity of the circadian system to flashes varying in duration. As the intermittent periods of darkness in our stimulation paradigm supports the recovery of extrinsic rod-cone signalling into the ipRGCs, our results strongly suggest rod-cone contributions into circadian photoreception.
Loss of the conserved Alveolate kinase MAPK2 decouples Toxoplasma cell growth from the cell cycle

Mitogen-activated protein kinases (MAPKs) are a conserved family of protein kinases that regulate signal transduction, proliferation, and development throughout eukaryotes. The Apicomplexan parasite Toxoplasma gondii expresses three MAPKs. Two of these, ERK7 and MAPKL1, have been respectively implicated in the regulation of conoid biogenesis and centrosome duplication. The third kinase, MAPK2, is specific to and conserved throughout Alveolata, though its function is unknown. We used the auxin-inducible degron system to determine phenotypes associated with MAPK2 loss-of-function in Toxoplasma. We observed that parasites lacking MAPK2 failed to duplicate their centrosomes and therefore did not initiate daughter-cell budding, which ultimately led to parasite death. MAPKL2-deficient parasites initiated, but did not complete DNA replication, and arrested prior to mitosis. Surprisingly, the parasites continued to grow in size and to replicate their Golgi, mitochondria, and apicoplasts. We found that the failure in centrosome duplication is distinct from the phenotype caused by depletion of MAPKL1. As we did not observe MAPK2 localization at the centrosome at any point in the cell cycle, our data suggest MAPK2 regulates a process at a distal site that is required for completion of centrosome duplication and initiation of parasite mitosis. Importance Toxoplasma gondii is a ubiquitous intracellular protozoan parasite that can cause severe and fatal disease in immunocompromised patients and the developing fetus. Rapid parasite replication is critical for establishing a productive infection. Here, we demonstrate that a Toxoplasma protein kinase called MAPK2 is conserved throughout Alveolata and essential for parasite replication. We found that parasites lacking MAPK2 protein were defective in the initiation of daughter cell budding and were rendered inviable. Specifically, TgMAPK2 appears to be required for centrosome replication at the basal end of the nucleus, and its loss causes arrest early in parasite division. MAPK2 is unique to Alveolata and not found in metazoa, and likely is a critical component of an essential parasite-specific signaling network.
Trunk sensory and motor cortex is preferentially integrated with hindlimb sensory information that supports trunk stabilization

Sensorimotor integration in the trunk system has been poorly studied despite its importance for examining functional recovery after neurological injury or disease. Here, we mapped the relationship between thoracic dorsal root ganglia and trunk sensory cortex (S1) to create a detailed map of the extent and internal organization of trunk primary sensory cortex, and trunk primary motor cortex (M1) and showed that both cortices are somatotopically complex structures that are larger than previously described. Surprisingly, projections from trunk S1 to trunk M1 were not anatomically organized. We found relatively weak sensorimotor integration between trunk M1 and S1 and between trunk M1 and forelimb S1 compared to extensive integration between trunk M1 and hindlimb S1 and M1. This strong trunk/hindlimb connection was identified for high intensity stimuli that activated proprioceptive pathways. To assess the implication of this integration, the responses in sensorimotor cortex were examined during a postural control task and supported sensorimotor integration between hindlimb sensory and lower trunk motor cortex. Together, these data suggest that trunk M1 is guided predominately by hindlimb proprioceptive information that reached the cortex directly via the thalamus. This unique sensorimotor integration suggests an essential role for the trunk system in postural control, and its consideration could be important for understanding studies regarding recovery of function after spinal cord injury. Significance This work identifies extensive sensorimotor integration between trunk and hindlimb cortices, demonstrating that sensorimotor integration is an operational mode of the trunk cortex in intact animals. The functional role of this integration was demonstrated for postural control when the animal was subjected to lateral tilts. Furthermore, these results provide insight into cortical reorganization after spinal cord injury making clear that sensorimotor integration after SCI is an attempt to restore sensorimotor integration that existed in the intact system. These results could be used to tailor rehabilitative strategies to optimize sensorimotor integration for functional recovery.
Simulating the outcome of amyloid treatments in Alzheimer’s Disease from multi-modal imaging and clinical data

Recent failures of clinical trials in Alzheimer’s Disease underline the critical importance of identifying optimal intervention time to maximize cognitive benefit. While several models of disease progression have been proposed, we still lack quantitative approaches simulating the effect of treatment strategies on the clinical evolution. In this work, we present a data-driven method to model dynamical relationships between imaging and clinical biomarkers. Our approach allows simulating intervention at any stage of the pathology by modulating the progression speed of the biomarkers, and by subsequently assessing the impact on disease evolution. When applied to multi-modal imaging and clinical data from the Alzheimer’s Disease Neuroimaging Initiative our method enables to generate hypothetical scenarios of amyloid lowering interventions. Our results show that in a study with 1000 individuals per arm, accumulation should be completely arrested at least 5 years before Alzheimer’s dementia diagnosis to lead to statistically powered improvement of clinical endpoints.