A chloroplast protein atlas reveals punctate structures and spatial organization of biosynthetic pathways.

Chloroplasts are eukaryotic photosynthetic organelles that drive the global carbon cycle. Despite their importance, our understanding of their protein composition, function, and spatial organization remains limited. Here, we determined the localizations of 1,034 candidate chloroplast proteins using fluorescent protein tagging in the model alga Chlamydomonas reinhardtii. The localizations provide insights into the functions of poorly characterized proteins; identify novel components of nucleoids, plastoglobules, and the pyrenoid; and reveal widespread protein targeting to multiple compartments. We discovered and further characterized cellular organizational features, including eleven chloroplast punctate structures, cytosolic crescent structures, and unexpected spatial distributions of enzymes within the chloroplast. We also used machine learning to predict the localizations of other nuclear-encoded Chlamydomonas proteins. The strains and localization atlas developed here will serve as a resource to accelerate studies of chloroplast architecture and functions.

Serum Amyloid A Proteins Induce Pathogenic Th17 Cells and Promote Inflammatory Disease.

Lymphoid cells that produce interleukin (IL)-17 cytokines protect barrier tissues from pathogenic microbes but are also prominent effectors of inflammation and autoimmune disease. T helper 17 (Th17) cells, defined by RORγt-dependent production of IL-17A and IL-17F, exert homeostatic functions in the gut upon microbiota-directed differentiation from naive CD4+ T cells. In the non-pathogenic setting, their cytokine production is regulated by serum amyloid A proteins (SAA1 and SAA2) secreted by adjacent intestinal epithelial cells. However, Th17 cell behaviors vary markedly according to their environment. Here, we show that SAAs additionally direct a pathogenic pro-inflammatory Th17 cell differentiation program, acting directly on T cells in collaboration with STAT3-activating cytokines. Using loss- and gain-of-function mouse models, we show that SAA1, SAA2, and SAA3 have distinct systemic and local functions in promoting Th17-mediated inflammatory diseases. These studies suggest that T cell signaling pathways modulated by the SAAs may be attractive targets for anti-inflammatory therapies.

Spectroscopic identification of water emission from a main-belt comet.

Main-belt comets are small Solar System bodies located in the asteroid belt that repeatedly exhibit comet-like activity (that is, dust comae or tails) during their perihelion passages, strongly indicating ice sublimation1,2. Although the existence of main-belt comets implies the presence of extant water ice in the asteroid belt, no gas has been detected around these objects despite intense scrutiny with the world's largest telescopes3. Here we present James Webb Space Telescope observations that clearly show that main-belt comet 238P/Read has a coma of water vapour, but lacks a significant CO2 gas coma. Our findings demonstrate that the activity of comet Read is driven by water-ice sublimation, and implies that main-belt comets are fundamentally different from the general cometary population. Whether or not comet Read experienced different formation circumstances or evolutionary history, it is unlikely to be a recent asteroid belt interloper from the outer Solar System. On the basis of these results, main-belt comets appear to represent a sample of volatile material that is currently unrepresented in observations of classical comets and the meteoritic record, making them important for understanding the early Solar System's volatile inventory and its subsequent evolution.

A median fin derived from the lateral plate mesoderm and the origin of paired fins.

The development of paired appendages was a key innovation during evolution and facilitated the aquatic to terrestrial transition of vertebrates. Largely derived from the lateral plate mesoderm (LPM), one hypothesis for the evolution of paired fins invokes derivation from unpaired median fins via a pair of lateral fin folds located between pectoral and pelvic fin territories1. Whilst unpaired and paired fins exhibit similar structural and molecular characteristics, no definitive evidence exists for paired lateral fin folds in larvae or adults of any extant or extinct species. As unpaired fin core components are regarded as exclusively derived from paraxial mesoderm, any transition presumes both co-option of a fin developmental programme to the LPM and bilateral duplication2. Here, we identify that the larval zebrafish unpaired pre-anal fin fold (PAFF) is derived from the LPM and thus may represent a developmental intermediate between median and paired fins. We trace the contribution of LPM to the PAFF in both cyclostomes and gnathostomes, supporting the notion that this is an ancient trait of vertebrates. Finally, we observe that the PAFF can be bifurcated by increasing bone morphogenetic protein signalling, generating LPM-derived paired fin folds. Our work provides evidence that lateral fin folds may have existed as embryonic anlage for elaboration to paired fins.

Direct measurement of dynamic attractant gradients reveals breakdown of the Patlak-Keller-Segel chemotaxis model.

Chemotactic bacteria not only navigate chemical gradients, but also shape their environments by consuming and secreting attractants. Investigating how these processes influence the dynamics of bacterial populations has been challenging because of a lack of experimental methods for measuring spatial profiles of chemoattractants in real time. Here, we use a fluorescent sensor for aspartate to directly measure bacterially generated chemoattractant gradients during collective migration. Our measurements show that the standard Patlak-Keller-Segel model for collective chemotactic bacterial migration breaks down at high cell densities. To address this, we propose modifications to the model that consider the impact of cell density on bacterial chemotaxis and attractant consumption. With these changes, the model explains our experimental data across all cell densities, offering insight into chemotactic dynamics. Our findings highlight the significance of considering cell density effects on bacterial behavior, and the potential for fluorescent metabolite sensors to shed light on the complex emergent dynamics of bacterial communities.

Attenuating midline thalamus bursting to mitigate absence epilepsy.

Advancing the mechanistic understanding of absence epilepsy is crucial for developing new therapeutics, especially for patients unresponsive to current treatments. Utilizing a recently developed mouse model of absence epilepsy carrying the BK gain-of-function channelopathy D434G, here we report that attenuating the burst firing of midline thalamus (MLT) neurons effectively prevents absence seizures. We found that enhanced BK channel activity in the BK-D434G MLT neurons promotes synchronized bursting during the ictal phase of absence seizures. Modulating MLT neurons through pharmacological reagents, optogenetic stimulation, or deep brain stimulation effectively attenuates burst firing, leading to reduced absence seizure frequency and increased vigilance. Additionally, enhancing vigilance by amphetamine, a stimulant medication, or physical perturbation also effectively suppresses MLT bursting and prevents absence seizures. These findings suggest that the MLT is a promising target for clinical interventions. Our diverse approaches offer valuable insights for developing next generation therapeutics to treat absence epilepsy.

Improved Outcomes with Enzalutamide in Biochemically Recurrent Prostate Cancer.

BACKGROUND: Patients with prostate cancer who have high-risk biochemical recurrence have an increased risk of progression. The efficacy and safety of enzalutamide plus androgen-deprivation therapy and enzalutamide monotherapy, as compared with androgen-deprivation therapy alone, are unknown. METHODS: In this phase 3 trial, we enrolled patients with prostate cancer who had high-risk biochemical recurrence with a prostate-specific antigen doubling time of 9 months or less. Patients were randomly assigned, in a 1:1:1 ratio, to receive enzalutamide (160 mg) daily plus leuprolide every 12 weeks (combination group), placebo plus leuprolide (leuprolide-alone group), or enzalutamide monotherapy (monotherapy group). The primary end point was metastasis-free survival, as assessed by blinded independent central review, in the combination group as compared with the leuprolide-alone group. A key secondary end point was metastasis-free survival in the monotherapy group as compared with the leuprolide-alone group. Other secondary end points were patient-reported outcomes and safety. RESULTS: A total of 1068 patients underwent randomization: 355 were assigned to the combination group, 358 to the leuprolide-alone group, and 355 to the monotherapy group. The patients were followed for a median of 60.7 months. At 5 years, metastasis-free survival was 87.3% (95% confidence interval [CI], 83.0 to 90.6) in the combination group, 71.4% (95% CI, 65.7 to 76.3) in the leuprolide-alone group, and 80.0% (95% CI, 75.0 to 84.1) in the monotherapy group. With respect to metastasis-free survival, enzalutamide plus leuprolide was superior to leuprolide alone (hazard ratio for metastasis or death, 0.42; 95% CI, 0.30 to 0.61; P<0.001); enzalutamide monotherapy was also superior to leuprolide alone (hazard ratio for metastasis or death, 0.63; 95% CI, 0.46 to 0.87; P = 0.005). No new safety signals were observed, with no substantial between-group differences in quality-of-life measures. CONCLUSIONS: In patients with prostate cancer with high-risk biochemical recurrence, enzalutamide plus leuprolide was superior to leuprolide alone with respect to metastasis-free survival; enzalutamide monotherapy was also superior to leuprolide alone. The safety profile of enzalutamide was consistent with that shown in previous clinical studies, with no apparent detrimental effect on quality of life. (Funded by Pfizer and Astellas Pharma; EMBARK ClinicalTrials.gov number, NCT02319837.).

Themis: advancing precision oncology through comprehensive molecular subtyping and optimization.

Recent advances in tumor molecular subtyping have revolutionized precision oncology, offering novel avenues for patient-specific treatment strategies. However, a comprehensive and independent comparison of these subtyping methodologies remains unexplored. This study introduces 'Themis' (Tumor HEterogeneity analysis on Molecular subtypIng System), an evaluation platform that encapsulates a few representative tumor molecular subtyping methods, including Stemness, Anoikis, Metabolism, and pathway-based classifications, utilizing 38 test datasets curated from The Cancer Genome Atlas (TCGA) and significant studies. Our self-designed quantitative analysis uncovers the relative strengths, limitations, and applicability of each method in different clinical contexts. Crucially, Themis serves as a vital tool in identifying the most appropriate subtyping methods for specific clinical scenarios. It also guides fine-tuning existing subtyping methods to achieve more accurate phenotype-associated results. To demonstrate the practical utility, we apply Themis to a breast cancer dataset, showcasing its efficacy in selecting the most suitable subtyping methods for personalized medicine in various clinical scenarios. This study bridges a crucial gap in cancer research and lays a foundation for future advancements in individualized cancer therapy and patient management.

Antibody stabilization for thermally accelerated deep immunostaining.

Antibodies have diverse applications due to their high reaction specificities but are sensitive to denaturation when a higher working temperature is required. We have developed a simple, highly scalable and generalizable chemical approach for stabilizing off-the-shelf antibodies against thermal and chemical denaturation. We demonstrate that the stabilized antibodies (termed SPEARs) can withstand up to 4 weeks of continuous heating at 55 °C and harsh denaturants, and apply our method to 33 tested antibodies. SPEARs enable flexible applications of thermocycling and denaturants to dynamically modulate their binding kinetics, reaction equilibrium, macromolecular diffusivity and aggregation propensity. In particular, we show that SPEARs permit the use of a thermally facilitated three-dimensional immunolabeling strategy (termed ThICK staining), achieving whole mouse brain immunolabeling within 72 h, as well as nearly fourfold deeper penetration with threefold less antibodies in human brain tissue. With faster deep-tissue immunolabeling and broad compatibility with tissue processing and clearing methods without the need for any specialized equipment, we anticipate the wide applicability of ThICK staining with SPEARs for deep immunostaining.

MpbPPI: a multi-task pre-training-based equivariant approach for the prediction of the effect of amino acid mutations on protein-protein interactions.

The accurate prediction of the effect of amino acid mutations for protein-protein interactions (PPI $\Delta \Delta G$) is a crucial task in protein engineering, as it provides insight into the relevant biological processes underpinning protein binding and provides a basis for further drug discovery. In this study, we propose MpbPPI, a novel multi-task pre-training-based geometric equivariance-preserving framework to predict PPI  $\Delta \Delta G$. Pre-training on a strictly screened pre-training dataset is employed to address the scarcity of protein-protein complex structures annotated with PPI $\Delta \Delta G$ values. MpbPPI employs a multi-task pre-training technique, forcing the framework to learn comprehensive backbone and side chain geometric regulations of protein-protein complexes at different scales. After pre-training, MpbPPI can generate high-quality representations capturing the effective geometric characteristics of labeled protein-protein complexes for downstream $\Delta \Delta G$ predictions. MpbPPI serves as a scalable framework supporting different sources of mutant-type (MT) protein-protein complexes for flexible application. Experimental results on four benchmark datasets demonstrate that MpbPPI is a state-of-the-art framework for PPI $\Delta \Delta G$ predictions. The data and source code are available at https://github.com/arantir123/MpbPPI.

Parallel pathways for serotonin biosynthesis and metabolism in C. elegans.

The neurotransmitter serotonin plays a central role in animal behavior and physiology, and many of its functions are regulated via evolutionarily conserved biosynthesis and degradation pathways. Here we show that in Caenorhabditis elegans, serotonin is abundantly produced in nonneuronal tissues via phenylalanine hydroxylase, in addition to canonical biosynthesis via tryptophan hydroxylase in neurons. Combining CRISPR-Cas9 genome editing, comparative metabolomics and synthesis, we demonstrate that most serotonin in C. elegans is incorporated into N-acetylserotonin-derived glucosides, which are retained in the worm body and further modified via the carboxylesterase CEST-4. Expression patterns of CEST-4 suggest that serotonin or serotonin derivatives are transported between different tissues. Last, we show that bacterial indole production interacts with serotonin metabolism via CEST-4. Our results reveal a parallel pathway for serotonin biosynthesis in nonneuronal cell types and further indicate that serotonin-derived metabolites may serve distinct signaling functions and contribute to previously described serotonin-dependent phenotypes.

Collective behavior and nongenetic inheritance allow bacterial populations to adapt to changing environments.

Collective behaviors require coordination among a group of individuals. As a result, individuals that are too phenotypically different from the rest of the group can be left out, reducing heterogeneity, but increasing coordination. If individuals also reproduce, the offspring can have different phenotypes from their parent(s). This raises the question of how these two opposing processes-loss of diversity by collective behaviors and generation of it through growth and inheritance-dynamically shape the phenotypic composition of an isogenic population. We examine this question theoretically using collective migration of chemotactic bacteria as a model system, where cells of different swimming phenotypes are better suited to navigate in different environments. We find that the differential loss of phenotypes caused by collective migration is environment-dependent. With cell growth, this differential loss enables migrating populations to dynamically adapt their phenotype compositions to the environment, enhancing migration through multiple environments. Which phenotypes are produced upon cell division depends on the level of nongenetic inheritance, and higher inheritance leads to larger composition adaptation and faster migration at steady state. However, this comes at the cost of slower responses to new environments. Due to this trade-off, there is an optimal level of inheritance that maximizes migration speed through changing environments, which enables a diverse population to outperform a nondiverse one. Growing populations might generally leverage the selection-like effects provided by collective behaviors to dynamically shape their own phenotype compositions, without mutations.

Increased genetic contribution to wellbeing during the COVID-19 pandemic.

Physical and mental health are determined by an interplay between nature, for example genetics, and nurture, which encompasses experiences and exposures that can be short or long-lasting. The COVID-19 pandemic represents a unique situation in which whole communities were suddenly and simultaneously exposed to both the virus and the societal changes required to combat the virus. We studied 27,537 population-based biobank participants for whom we have genetic data and extensive longitudinal data collected via 19 questionnaires over 10 months, starting in March 2020. This allowed us to explore the interaction between genetics and the impact of the COVID-19 pandemic on individuals' wellbeing over time. We observe that genetics affected many aspects of wellbeing, but also that its impact on several phenotypes changed over time. Over the course of the pandemic, we observed that the genetic predisposition to life satisfaction had an increasing influence on perceived quality of life. We also estimated heritability and the proportion of variance explained by shared environment using variance components methods based on pedigree information and household composition. The results suggest that people's genetic constitution manifested more prominently over time, potentially due to social isolation driven by strict COVID-19 containment measures. Overall, our findings demonstrate that the relative contribution of genetic variation to complex phenotypes is dynamic rather than static.

Actin cytoskeletal regulation of ciliogenesis in development and disease.

Primary cilia are antenna-like sensory organelles that are evolutionarily conserved in nearly all modern eukaryotes, from the single-celled green alga, Chlamydomonas reinhardtii, to vertebrates and mammals. Cilia are microtubule-based cellular projections that have adapted to perform a broad range of species-specific functions, from cell motility to detection of light and the transduction of extracellular mechanical and chemical signals. These functions render cilia essential for organismal development and survival. The high conservation of cilia has allowed for discoveries in C. reinhardtii to inform our understanding of the basic biology of mammalian primary cilia, and to provide insight into the genetic etiology of ciliopathies. Over the last two decades, a growing number of studies has revealed that multiple aspects of ciliary homeostasis are regulated by the actin cytoskeleton, including centrosome migration and positioning, vesicle transport to the basal body, ectocytosis, and ciliary-mediated signaling. Here, we review actin regulation of ciliary homeostasis, and highlight conserved and divergent mechanisms in C. reinhardtii and mammalian cells. Further, we compare the disease manifestations of patients with ciliopathies to those with mutations in actin and actin-associated genes, and propose that primary cilia defects caused by genetic alteration of the actin cytoskeleton may underlie certain birth defects.

Selective Activation of Subthalamic Nucleus Output Quantitatively Scales Movements.

The subthalamic nucleus (STN) is a common target for deep brain stimulation (DBS) treatments of Parkinsonian motor symptoms. According to the dominant model, the STN output can suppress movement by enhancing inhibitory basal ganglia (BG) output via the indirect pathway, and disrupting STN output using DBS can restore movement in Parkinson's patients. But the mechanisms underlying STN DBS remain poorly understood, as previous studies usually relied on electrical stimulation, which cannot selectively target STN output neurons. Here, we selectively stimulated STN projection neurons using optogenetics and quantified behavior in male and female mice using 3D motion capture. STN stimulation resulted in movements with short latencies (10-15 ms). A single pulse of light was sufficient to generate movement, and there was a highly linear relationship between stimulation frequency and kinematic measures. Unilateral stimulation caused movement in the ipsiversive direction (toward the side of stimulation) and quantitatively determined head yaw and head roll, while stimulation of either STN raises the head (pitch). Bilateral stimulation does not cause turning but raised the head twice as high as unilateral stimulation of either STN. Optogenetic stimulation increased the firing rate of STN neurons in a frequency-dependent manner, and the increased firing is responsible for stimulation-induced movements. Finally, stimulation of the STN's projection to the brainstem mesencephalic locomotor region was sufficient to reproduce the behavioral effects of STN stimulation. These results question the common assumption that the STN suppresses movement, and instead suggest that STN output can precisely specify action parameters via direct projections to the brainstem.SIGNIFICANCE STATEMENT Our results question the common assumption that the subthalamic nucleus (STN) suppresses movement, and instead suggest that STN output can precisely specify action parameters via direct projections to the brainstem.

The slow-release adiponectin analog ALY688-SR modifies early-stage disease development in the D2.mdx mouse model of Duchenne muscular dystrophy.

Fibrosis is associated with respiratory and limb muscle atrophy in Duchenne muscular dystrophy (DMD). Current standard of care partially delays the progression of this myopathy but there remains an unmet need to develop additional therapies. Adiponectin receptor agonism has emerged as a possible therapeutic target to lower inflammation and improve metabolism in mdx mouse models of DMD but the degree to which fibrosis and atrophy are prevented remain unknown. Here, we demonstrate that the recently developed slow-release peptidomimetic adiponectin analog, ALY688-SR, remodels the diaphragm of murine model of DMD on DBA background (D2.mdx) mice treated from days 7-28 of age during early stages of disease. ALY688-SR also lowered interleukin-6 (IL-6) mRNA but increased IL-6 and transforming growth factor-ß1 (TGF-ß1) protein contents in diaphragm, suggesting dynamic inflammatory remodeling. ALY688-SR alleviated mitochondrial redox stress by decreasing complex I-stimulated H2O2 emission. Treatment also attenuated fibrosis, fiber type-specific atrophy, and in vitro diaphragm force production in diaphragm suggesting a complex relationship between adiponectin receptor activity, muscle remodeling, and force-generating properties during the very early stages of disease progression in murine model of DMD on DBA background (D2.mdx) mice. In tibialis anterior, the modest fibrosis at this young age was not altered by treatment, and atrophy was not apparent at this young age. These results demonstrate that short-term treatment of ALY688-SR in young D2.mdx mice partially prevents fibrosis and fiber type-specific atrophy and lowers force production in the more disease-apparent diaphragm in relation to lower mitochondrial redox stress and heterogeneous responses in certain inflammatory markers. These diverse muscle responses to adiponectin receptor agonism in early stages of DMD serve as a foundation for further mechanistic investigations.NEW & NOTEWORTHY There are limited therapies for the treatment of Duchenne muscular dystrophy. As fibrosis involves an accumulation of collagen that replaces muscle fibers, antifibrotics may help preserve muscle function. We report that the novel adiponectin receptor agonist ALY688-SR prevents fibrosis in the diaphragm of D2.mdx mice with short-term treatment early in disease progression. These responses were related to altered inflammation and mitochondrial functions and serve as a foundation for the development of this class of therapy.

Future of Endovascular and Surgical Treatments of Atherosclerotic Intracranial Stenosis.

Intracranial atherosclerotic disease and resultant intracranial stenosis is a global leading cause of stroke, and poses an ongoing treatment challenge. Among patients with intracranial stenosis, those with hemodynamic compromise are at high risk for recurrent stroke despite medical therapy and risk factor modification. Revascularization of the hypoperfused territory is the most plausible treatment strategy for these high-risk patients, yet surgical and endovascular therapies have not yet shown to be sufficiently safe and effective in randomized controlled trials. Advances in diagnostic and therapeutic technologies have led to a resurgence of interest in surgical and endovascular treatment strategies, with a growing body of evidence to support their further evaluation in the treatment of select patient populations. This review outlines the current and emerging endovascular and surgical treatments and highlights promising future management strategies.

MetDIT: Transforming and Analyzing Clinical Metabolomics Data with Convolutional Neural Networks.

Clinical metabolomics is growing as an essential tool for precision medicine. However, classical machine learning algorithms struggle to comprehensively encode and analyze the metabolomics data due to their high dimensionality and complex intercorrelations. This article introduces a new method called MetDIT, designed to analyze intricate metabolomics data effectively using deep convolutional neural networks (CNN). MetDIT comprises two components: TransOmics and NetOmics. Since CNN models have difficulty in processing one-dimensional (1D) sequence data efficiently, we developed TransOmics, a framework that transforms sequence data into two-dimensional (2D) images while maintaining a one-to-one correspondence between the sequences and images. NetOmics, the second component, leverages a CNN architecture to extract more discriminative representations from the transformed samples. To overcome the overfitting due to the small sample size and class imbalance, we introduced a feature augmentation module (FAM) and a loss function to improve the model performance. Furthermore, we systematically optimized the model backbone and image resolution to balance the model parameters and computational costs. To demonstrate the performance of the proposed MetDIT, we conducted extensive experiments using three different clinical metabolomics data sets and achieved better classification performance than classical machine learning methods used in metabolomics, including Random Forest, SVM, XGBoost, and LightGBM. The source code is available at the GitHub repository at https://github.com/Li-OmicsLab/MetDIT, and the WebApp can be found at http://metdit.bioinformatics.vip/.

Consensus guidelines for the diagnosis and management of succinic semialdehyde dehydrogenase deficiency.

Succinic semialdehyde dehydrogenase deficiency (SSADHD) (OMIM #271980) is a rare autosomal recessive metabolic disorder caused by pathogenic variants of ALDH5A1. Deficiency of SSADH results in accumulation of γ-aminobutyric acid (GABA) and other GABA-related metabolites. The clinical phenotype of SSADHD includes a broad spectrum of non-pathognomonic symptoms such as cognitive disabilities, communication and language deficits, movement disorders, epilepsy, sleep disturbances, attention problems, anxiety, and obsessive-compulsive traits. Current treatment options for SSADHD remain supportive, but there are ongoing attempts to develop targeted genetic therapies. This study aimed to create consensus guidelines for the diagnosis and management of SSADHD. Thirty relevant statements were initially addressed by a systematic literature review, resulting in different evidence levels of strength according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria. The highest level of evidence (level A), based on randomized controlled trials, was unavailable for any of the statements. Based on cohort studies, Level B evidence was available for 12 (40%) of the statements. Thereupon, through a process following the Delphi Method and directed by the Appraisal of Guidelines for Research and Evaluation (AGREE II) criteria, expert opinion was sought, and members of an SSADHD Consensus Group evaluated all the statements. The group consisted of neurologists, epileptologists, neuropsychologists, neurophysiologists, metabolic disease specialists, clinical and biochemical geneticists, and laboratory scientists affiliated with 19 institutions from 11 countries who have clinical experience with SSADHD patients and have studied the disorder. Representatives from parent groups were also included in the Consensus Group. An analysis of the survey's results yielded 25 (83%) strong and 5 (17%) weak agreement strengths. These first-of-their-kind consensus guidelines intend to consolidate and unify the optimal care that can be provided to individuals with SSADHD.