Rapid and automated design of two-component protein nanomaterials using ProteinMPNN.

The design of protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. Deep learning methods promise to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here, we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

Prevalence and Impact of Workplace Sexual Harassment Experienced by Medical Sonographers.

OBJECTIVE: To assess the prevalence and impact of sexual harassment among a nationwide sample of medical sonographers. METHODS: A survey was distributed anonymously to a convenience sample of medical sonographers via email contacts and sonographer-specific social media pages. Data were analyzed to determine respondent demographics, the prevalence of sexual harassment in the last 2 years, the type and severity of harassment experienced, demographics of perpetrators, personal and institutional responses to such experiences, and the impact of sexual harassment on sonographer physical and mental health and job satisfaction. RESULTS: Of the 220 sonographers (83% female) most (45%) were between 18 and 34 years and identified as white (81%). A total of 192 (87%) reported experiencing at least 1 incident of harassment within the last 2 years. Female respondents experienced higher harassment rates (76%) compared to males (50%, P = .02). The most common forms of harassment were verbal, including suggestive or sexist jokes (69%) and offensive sexist remarks (61%). Perpetrators were predominantly male (78%) and most commonly patients (89%) or their friends/family members (46%). The majority of respondents either ignored the harassing behavior (70%) or treated it like a joke (50%), with only a minority (12%) officially reporting incidents. Of those who reported, 44% were unsatisfied with their institution's response. Among respondents, 34% reported negative impacts of workplace sexual harassment, such as anxiety, depression, sleep loss, or adverse workplace consequences. DISCUSSION: Workplace sexual harassment is a common occurrence for sonographers and often leads to negative health and career outcomes. Further institutional policies to prevent harassment and mitigate its effects are needed.

Quantitative diffusion imaging and genotype-by-sex interactions in a rat model of Alexander disease.

PURPOSE: The clinical diagnosis and classification of Alexander disease (AxD) relies in part on qualitative neuroimaging biomarkers; however, these biomarkers fail to distinguish and discriminate different subtypes of AxD, especially in the presence of overlap in clinical symptoms. To address this gap in knowledge, we applied neurite orientation dispersion and density imaging (NODDI) to an innovative CRISPR-Cas9 rat genetic model of AxD to gain quantitative insights into the neural substrates and brain microstructural changes seen in AxD and to potentially identify novel quantitative NODDI biomarkers of AxD. METHODS: Multi-shell DWI of age- and sex-matched AxD and wild-type Sprague Dawley rats (n = 6 per sex per genotype) was performed and DTI and NODDI measures calculated. A 3 × 2 × 2 analysis of variance model was used to determine the effect of genotype, biological sex, and laterality on quantitative measures of DTI and NODDI across regions of interest implicated in AxD. RESULTS: There is a significant effect of genotype in the amygdala, hippocampus, neocortex, and thalamus in measures of both DTI and NODDI brain microstructure. A genotype by biological sex interaction was identified in DTI and NODDI measures in the corpus callosum, hippocampus, and neocortex. CONCLUSION: We present the first application of NODDI to the study of AxD using a rat genetic model of AxD. Our analysis identifies alterations in NODDI and DTI measures to large white matter tracts and subcortical gray nuclei. We further identified genotype by sex interactions, suggesting a possible role for biological sex in the neuropathogenesis of AxD.

Rapid and automated design of two-component protein nanomaterials using ProteinMPNN.

The design of novel protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. A new generation of deep learning methods promises to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

Patient, Provider, and Practice Characteristics Predicting Use of Diagnostic Imaging in Primary Care: Cross-Sectional Data From the National Ambulatory Medical Care Survey.

OBJECTIVE: To determine imaging utilization rates in outpatient primary care visits and factors influencing likelihood of imaging use. METHODS: We used 2013 to 2018 National Ambulatory Medical Care Survey cross-sectional data. All visits to primary care clinics during the study period were included in the sample. Descriptive statistics on visit characteristics including imaging utilization were calculated. Logistic regression analyses evaluated the influence of a variety of patient-, provider-, and practice-level variables on the odds of obtaining diagnostic imaging, further subdivided by modality (radiographs, CT, MRI, and ultrasound). The data's survey weighting was accounted for to produce valid national-level estimates of imaging use for US office-based primary care visits. RESULTS: Using survey weights, approximately 2.8 billion patient visits were included. Diagnostic imaging was ordered at 12.5% of visits with radiographs the most common (4.3%) and MRI the least common (0.8%). Imaging utilization was similar or greater among minority patients compared with White, non-Hispanic patients. Physician assistants used imaging at higher rates than physicians, in particular CT at 6.5% of visits compared with 0.7% for doctors of medicine and doctors of osteopathic medicine (odds ratio 5.67, 95% confidence interval 4.07-7.88). CONCLUSION: Disparities in rates of imaging utilization for minorities seen in other health care settings were not present in this sample of primary care visits, supporting that access to primary care is a path to promote health equity. Higher rates of imaging utilization among advanced-level practitioners highlight an opportunity to evaluate imaging appropriateness and promote equitable, high-value imaging among all practitioners.

Increased expression of SLC25A1/CIC causes an autistic-like phenotype with altered neuron morphology.

N ε-lysine acetylation within the lumen of the endoplasmic reticulum is a recently characterized protein quality control system that positively selects properly folded glycoproteins in the early secretory pathway. Overexpression of the endoplasmic reticulum acetyl-CoA transporter AT-1 in mouse forebrain neurons results in increased dendritic branching, spine formation and an autistic-like phenotype that is attributed to altered glycoprotein flux through the secretory pathway. AT-1 overexpressing neurons maintain the cytosolic pool of acetyl-CoA by upregulation of SLC25A1, the mitochondrial citrate/malate antiporter and ATP citrate lyase, which converts cytosolic citrate into acetyl-CoA. All three genes have been associated with autism spectrum disorder, suggesting that aberrant cytosolic-to-endoplasmic reticulum flux of acetyl-CoA can be a mechanistic driver for the development of autism spectrum disorder. We therefore generated a SLC25A1 neuron transgenic mouse with overexpression specifically in the forebrain neurons. The mice displayed autistic-like behaviours with a jumping stereotypy. They exhibited increased steady-state levels of citrate and acetyl-CoA, disrupted white matter integrity with activated microglia and altered synaptic plasticity and morphology. Finally, quantitative proteomic and acetyl-proteomic analyses revealed differential adaptations in the hippocampus and cortex. Overall, our study reinforces the connection between aberrant cytosolic-to-endoplasmic reticulum acetyl-CoA flux and the development of an autistic-like phenotype.

SLC13A5/sodium-citrate co-transporter overexpression causes disrupted white matter integrity and an autistic-like phenotype.

Endoplasmic reticulum-based N ɛ-lysine acetylation serves as an important protein quality control system for the secretory pathway. Dysfunctional endoplasmic reticulum-based acetylation, as caused by overexpression of the acetyl coenzyme A transporter AT-1 in the mouse, results in altered glycoprotein flux through the secretory pathway and an autistic-like phenotype. AT-1 works in concert with SLC25A1, the citrate/malate antiporter in the mitochondria, SLC13A5, the plasma membrane sodium/citrate symporter and ATP citrate lyase, the cytosolic enzyme that converts citrate into acetyl coenzyme A. Here, we report that mice with neuron-specific overexpression of SLC13A5 exhibit autistic-like behaviours with a jumping stereotypy. The mice displayed disrupted white matter integrity and altered synaptic structure and function. Analysis of both the proteome and acetyl-proteome revealed unique adaptations in the hippocampus and cortex, highlighting a metabolic response that likely plays an important role in the SLC13A5 neuron transgenic phenotype. Overall, our results support a mechanistic link between aberrant intracellular citrate/acetyl coenzyme A flux and the development of an autistic-like phenotype.

18F-SynVesT-1 PET/MR Imaging of the Effect of Gut Microbiota on Synaptic Density and Neurite Microstructure: A Preclinical Pilot Study.

The gut microbiome profoundly influences brain structure and function. The gut microbiome is hypothesized to play a key role in the etiopathogenesis of neuropsychiatric and neurodegenerative illness; however, the contribution of an intact gut microbiome to quantitative neuroimaging parameters of brain microstructure and function remains unknown. Herein, we report the broad and significant influence of a functional gut microbiome on commonly employed neuroimaging measures of diffusion tensor imaging (DTI), neurite orientation dispersion and density (NODDI) imaging, and SV2A 18F-SynVesT-1 synaptic density PET imaging when compared to germ-free animals. In this pilot study, we demonstrate that mice, in the presence of a functional gut microbiome, possess higher neurite density and orientation dispersion and decreased synaptic density when compared to age- and sex-matched germ-free mice. Our results reveal the region-specific structural influences and synaptic changes in the brain arising from the presence of intestinal microbiota. Further, our study highlights important considerations for the development of quantitative neuroimaging biomarkers for precision imaging in neurologic and psychiatric illness.

Clinical translational neuroimaging of the antioxidant effect of N-acetylcysteine on neural microstructure.

PURPOSE: Oxidative stress and downstream effectors have emerged as important pathological processes that drive psychiatric illness, suggesting that antioxidants may have a therapeutic role in psychiatric disease. However, no imaging biomarkers are currently available to track therapeutic response. The purpose of this study was to examine whether advanced DWI techniques are able to sensitively detect the potential therapeutic effects of the antioxidant N-acetylcysteine (NAC) in a Disc1 svΔ2 preclinical rat model of psychiatric illness. METHODS: Male and female Disc1 svΔ2 rats and age-matched, sex-matched Sprague-Dawley wild-type controls were treated with a saline vehicle or NAC before ex vivo MRI acquisition at P50. Imaging data were fit to DTI and neurite orientation dispersion and density imaging models and analyzed for region-specific changes in quantitative diffusion metrics. Brains were further processed for cellular quantification of microglial density and morphology. All experiments were repeated for Disc1 svΔ2 rats exposed to chronic early-life stress to test how gene-environment interactions might alter effectiveness of NAC therapy. RESULTS: The DTI and neurite orientation dispersion and density imaging analyses demonstrated amelioration of early-life, sex-specific neural microstructural deficits with concomitant differences in microglial morphology across multiple brain regions relevant to neuropsychiatric illness with NAC treatment, but only in male Disc1 svΔ2 rats. Addition of chronic early-life stress reduced the ability of NAC to restore microstructural deficits. CONCLUSION: These findings provide evidence for a treatment pathway targeting endogenous antioxidant capacity, and the clinical translational utility of neurite orientation dispersion and density imaging microstructural imaging to sensitively detect microstructural alterations resulting from antioxidant treatment.

Mapping Sex-Specific Neurodevelopmental Alterations in Neurite Density and Morphology in a Rat Genetic Model of Psychiatric Illness.

Neurite orientation dispersion and density imaging (NODDI) is an emerging magnetic resonance (MR) diffusion-weighted imaging (DWI) technique that permits non-invasive quantitative assessment of neurite density and morphology. NODDI has improved our ability to image neuronal microstructure over conventional techniques such as diffusion tensor imaging (DTI) and is particularly suited for studies of the developing brain as it can measure and characterize the dynamic changes occurring in dendrite cytoarchitecture that are critical to early brain development. Neurodevelopmental alterations to the diffusion tensor have been reported in psychiatric illness, but it remains unknown whether advanced DWI techniques such as NODDI are able to sensitively and specifically detect neurodevelopmental changes in brain microstructure beyond those provided by DTI. We show, in an extension of our previous work with a Disc1 svΔ2 rat genetic model of psychiatric illness, the enhanced sensitivity and specificity of NODDI to identify neurodevelopmental and sex-specific changes in brain microstructure that are otherwise difficult to observe with DTI and further corroborate observed changes in brain microstructure to differences in sex-specific systems-level animal behavior. Together, these findings inform the potential application and clinical translational utility of NODDI in studies of brain microstructure in psychiatric illness throughout neurodevelopment and further, the ability of advanced DWI methods such as NODDI to examine the role of biological sex and its influence on brain microstructure in psychiatric illness.

Microglial Density Alters Measures of Axonal Integrity and Structural Connectivity.

Diffusion tensor imaging (DTI) has fundamentally transformed how we interrogate diseases and disorders of the brain in neuropsychiatric illness. DTI and recently developed multicompartment diffusion-weighted imaging (MC-DWI) techniques, such as NODDI (neurite orientation dispersion and density imaging), measure diffusion anisotropy presuming a static neuroglial environment; however, microglial morphology and density are highly dynamic in psychiatric illness, and how alterations in microglial density might influence intracellular measures of diffusion anisotropy in DTI and MC-DWI brain microstructure is unknown. To address this question, DTI and MC-DWI studies of murine brains depleted of microglia were performed, revealing significant alterations in axonal integrity and fiber tractography in DTI and in commonly used MC-DWI models. With accumulating evidence of the role of microglia in neuropsychiatric illness, our findings uncover the unexpected contribution of microglia to measures of axonal integrity and structural connectivity and provide unanticipated insights into the potential influence of microglia in diffusion imaging studies of neuropsychiatric disease.

Metabolic Changes in Synaptosomes in an Animal Model of Schizophrenia Revealed by 1H and 1H,13C NMR Spectroscopy.

Synaptosomes are isolated nerve terminals that contain synaptic components, including neurotransmitters, metabolites, adhesion/fusion proteins, and nerve terminal receptors. The essential role of synaptosomes in neurotransmission has stimulated keen interest in understanding both their proteomic and metabolic composition. Mass spectrometric (MS) quantification of synaptosomes has illuminated their proteomic composition, but the determination of the metabolic composition by MS has been met with limited success. In this study, we report a proof-of-concept application of one- and two-dimensional nuclear magnetic resonance (NMR) spectroscopy for analyzing the metabolic composition of synaptosomes. We utilize this approach to compare the metabolic composition synaptosomes from a wild-type rat with that from a newly generated genetic rat model (Disc1 svΔ2), which qualitatively recapitulates clinically observed early DISC1 truncations associated with schizophrenia. This study demonstrates the feasibility of using NMR spectroscopy to identify and quantify metabolites within synaptosomal fractions.

Exercise ameliorates deficits in neural microstructure in a Disc1 model of psychiatric illness.

Recent studies have investigated the effectiveness of aerobic exercise to improve physical and mental health outcomes in schizophrenia; however, few have explicitly explored the impact of aerobic exercise on neural microstructure, which is hypothesized to mediate the behavioral changes observed. Neural microstructure is influenced by numerous genetic factors including DISC1, which is a major molecular scaffold protein that interacts with partners like GSK3ß, NDEL1, and PDE4. DISC1 has been shown to play a role in neurogenesis, neuronal migration, neuronal maturation, and synaptic signaling. As with other genetic variants that present an increased risk for disease, mutations of the DISC1 gene have been implicated in the molecular intersection of schizophrenia and numerous other major psychiatric illnesses. This study investigated whether short-term exercise recovers deficits in neural microstructure in a novel genetic Disc1 svΔ2 rat model. Disc1 svΔ2 animals and age- and sex-matched controls were subjected to a treadmill exercise protocol. Subsequent ex-vivo diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) compared neural microstructure in regions of interest (ROI) between sedentary and exercise wild-type animals and between sedentary and exercise Disc1 svΔ2 animals. Short-term exercise uncovered no significant differences in neural microstructure between sedentary and exercise control animals but did lead to significant differences between sedentary and exercise Disc1 svΔ2 animals in neocortex, basal ganglia, corpus callosum, and external capsule, suggesting a positive benefit derived from a short-term exercise regimen. Our findings suggest that Disc1 svΔ2 animals are more sensitive to the effects of short-term exercise and highlight the ameliorating potential of positive treatment interventions such as exercise on neural microstructure in genetic backgrounds of psychiatric disease susceptibility.

Preclinical neuroimaging of gene-environment interactions in psychiatric disease.

Psychiatric disease is one of the leading causes of disability worldwide. Despite the global burden and need for accurate diagnosis and treatment of mental illness, psychiatric diagnosis remains largely based on patient-reported symptoms, allowing for immense symptomatic heterogeneity within a single disease. In renewed efforts towards improved diagnostic specificity and subsequent evaluation of treatment response, a greater understanding of the underlying of the neuropathology and neurobiology of neuropsychiatric disease is needed. However, dissecting these mechanisms of neuropsychiatric illness in clinical populations are problematic with numerous experimental hurdles limiting hypothesis-driven studies including genetic confounds, variable life experiences, different environmental exposures, therapeutic histories, as well as the inability to investigate deeper molecular changes in vivo . Preclinical models, where many of these confounding factors can be controlled, can serve as a crucial experimental bridge for studying the neurobiological origins of mental illness. Furthermore, although behavioral studies and molecular studies are relatively common in these model systems, focused neuroimaging studies are very rare and represent an opportunity to link the molecular changes in psychiatric illness with advanced quantitative neuroimaging studies. In this review, we present an overview of well-validated genetic and environmental models of psychiatric illness, discuss gene-environment interactions, and examine the potential role of neuroimaging towards understanding genetic, environmental, and gene-environmental contributions to psychiatric illness.

Detecting Microglial Density With Quantitative Multi-Compartment Diffusion MRI.

Neuroinflammation plays a central role in the neuropathogenesis of a wide-spectrum of neurologic and psychiatric disease, but current neuroimaging methods to detect and characterize neuroinflammation are limited. We explored the sensitivity of quantitative multi-compartment diffusion MRI, and specifically neurite orientation dispersion and density imaging (NODDI), to detect changes in microglial density in the brain. Monte Carlo simulations of water diffusion using a NODDI acquisition scheme were performed to measure changes in a virtual MRI signal following modeled cellular changes within the extra-neurite space. 12-week-old C57BL/6J male mice (n = 48; 24 control, 24 treated with colony stimulating factor 1 receptor (CSF1R) inhibitor, PLX5622) were sacrificed at 0, 1, 3, and 7 days following withdrawal of CSF1R inhibition and were imaged ex-vivo to obtain measures of the orientation dispersion index (ODI). Following imaging, all brains were immunostained with Iba-1, NeuN, and GFAP for quantitative fluorescence microscopy. Cell populations were calculated with the ImageJ particle analyzer tool; correlation between microglial density and mean ODI values were calculated with Kendall's tau. Monte Carlo simulations demonstrate the sensitivity and positive correlation of ODI to increased occupancy in the extra-neurite space. Commensurate with our simulation data, ex-vivo NODDI imaging demonstrates an increase in ODI as microglia repopulate the brain following the withdrawal of CSF1R inhibition. Quantitative immunofluorescence of microglial density reveals that microglial density is positively correlated with ODI and greater hindered diffusion in the extra-neurite space (τ = 0.386, p < 0.05). Our results demonstrate that clinically feasible multi-compartment diffusion weighted imaging techniques such as NODDI are sensitive to microglial density and the cellular changes associated with microglial activation and highlights its potential to improve clinical diagnostic accuracy, patient risk stratification, and therapeutic monitoring of neuroinflammation in neurologic and psychiatric disease.

Sex-specific deficits in neurite density and white matter integrity are associated with targeted disruption of exon 2 of the Disc1 gene in the rat.

Diffusion tensor imaging (DTI) has provided remarkable insight into our understanding of white matter microstructure and brain connectivity across a broad spectrum of psychiatric disease. While DTI and other diffusion weighted magnetic resonance imaging (MRI) methods have clarified the axonal contribution to the disconnectivity seen in numerous psychiatric diseases, absent from these studies are quantitative indices of neurite density and orientation that are especially important features in regions of high synaptic density that would capture the synaptic contribution to the psychiatric disease state. Here we report the application of neurite orientation dispersion and density imaging (NODDI), an emerging microstructure imaging technique, to a novel Disc1 svΔ2 rat model of psychiatric illness and demonstrate the complementary and more specific indices of tissue microstructure found in NODDI than those reported by DTI. Our results demonstrate global and sex-specific changes in white matter microstructural integrity and deficits in neurite density as a consequence of the Disc1 svΔ2 genetic variation and highlight the application of NODDI and quantitative measures of neurite density and neurite dispersion in psychiatric disease.