Precision medicine in 2030-seven ways to transform healthcare.

Precision medicine promises improved health by accounting for individual variability in genes, environment, and lifestyle. Precision medicine will continue to transform healthcare in the coming decade as it expands in key areas: huge cohorts, artificial intelligence (AI), routine clinical genomics, phenomics and environment, and returning value across diverse populations.

Affirming NIH's commitment to addressing structural racism in the biomedical research enterprise.

NIH has acknowledged and committed to ending structural racism. The framework for NIH's approach, summarized here, includes understanding barriers; developing robust health disparities/equity research; improving its internal culture; being transparent and accountable; and changing the extramural ecosystem so that diversity, equity, and inclusion are reflected in funded research and the biomedical workforce.

Non-catalytic ubiquitin binding by A20 prevents psoriatic arthritis-like disease and inflammation.

A20 is an anti-inflammatory protein that is strongly linked to human disease. Here, we find that mice expressing three distinct targeted mutations of A20's zinc finger 7 (ZF7) ubiquitin-binding motif uniformly developed digit arthritis with features common to psoriatic arthritis, while mice expressing point mutations in A20's OTU or ZF4 motifs did not exhibit this phenotype. Arthritis in A20ZF7 mice required T cells and MyD88, was exquisitely sensitive to tumor necrosis factor and interleukin-17A, and persisted in germ-free conditions. A20ZF7 cells exhibited prolonged IκB kinase activity that drove exaggerated transcription of late-phase nuclear factor-κB response genes in vitro and in prediseased mouse paws in vivo. In addition, mice expressing double-mutant A20 proteins in A20's ZF4 and ZF7 motifs died perinatally with multi-organ inflammation. Therefore, A20's ZF4 and ZF7 motifs synergistically prevent inflammatory disease in a non-catalytic manner.

Rare coding variants in ten genes confer substantial risk for schizophrenia.

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, P < 2.14 × 10-6) and 32 genes at a false discovery rate of <5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure and function of the synapse. The associations of the NMDA (N-methyl-D-aspartate) receptor subunit GRIN2A and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptor subunit GRIA3 provide support for dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We observe an overlap of rare variant risk among schizophrenia, autism spectrum disorders1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach.

In vivo base editing rescues Hutchinson-Gilford progeria syndrome in mice.

Hutchinson-Gilford progeria syndrome (HGPS or progeria) is typically caused by a dominant-negative C•G-to-T•A mutation (c.1824 C>T; p.G608G) in LMNA, the gene that encodes nuclear lamin A. This mutation causes RNA mis-splicing that produces progerin, a toxic protein that induces rapid ageing and shortens the lifespan of children with progeria to approximately 14 years1-4. Adenine base editors (ABEs) convert targeted A•T base pairs to G•C base pairs with minimal by-products and without requiring double-strand DNA breaks or donor DNA templates5,6. Here we describe the use of an ABE to directly correct the pathogenic HGPS mutation in cultured fibroblasts derived from children with progeria and in a mouse model of HGPS. Lentiviral delivery of the ABE to fibroblasts from children with HGPS resulted in 87-91% correction of the pathogenic allele, mitigation of RNA mis-splicing, reduced levels of progerin and correction of nuclear abnormalities. Unbiased off-target DNA and RNA editing analysis did not detect off-target editing in treated patient-derived fibroblasts. In transgenic mice that are homozygous for the human LMNA c.1824 C>T allele, a single retro-orbital injection of adeno-associated virus 9 (AAV9) encoding the ABE resulted in substantial, durable correction of the pathogenic mutation (around 20-60% across various organs six months after injection), restoration of normal RNA splicing and reduction of progerin protein levels. In vivo base editing rescued the vascular pathology of the mice, preserving vascular smooth muscle cell counts and preventing adventitial fibrosis. A single injection of ABE-expressing AAV9 at postnatal day 14 improved vitality and greatly extended the median lifespan of the mice from 215 to 510 days. These findings demonstrate the potential of in vivo base editing as a possible treatment for HGPS and other genetic diseases by directly correcting their root cause.

Activation of the GLP-1 receptor by a non-peptidic agonist.

Class B G-protein-coupled receptors are major targets for the treatment of chronic diseases, including diabetes and obesity1. Structures of active receptors reveal peptide agonists engage deep within the receptor core, leading to an outward movement of extracellular loop 3 and the tops of transmembrane helices 6 and 7, an inward movement of transmembrane helix 1, reorganization of extracellular loop 2 and outward movement of the intracellular side of transmembrane helix 6, resulting in G-protein interaction and activation2-6. Here we solved the structure of a non-peptide agonist, TT-OAD2, bound to the glucagon-like peptide-1 (GLP-1) receptor. Our structure identified an unpredicted non-peptide agonist-binding pocket in which reorganization of extracellular loop 3 and transmembrane helices 6 and 7 manifests independently of direct ligand interaction within the deep transmembrane domain pocket. TT-OAD2 exhibits biased agonism, and kinetics of G-protein activation and signalling that are distinct from peptide agonists. Within the structure, TT-OAD2 protrudes beyond the receptor core to interact with the lipid or detergent, providing an explanation for the distinct activation kinetics that may contribute to the clinical efficacy of this compound series. This work alters our understanding of the events that drive the activation of class B receptors.

Human pancreatic islet microRNAs implicated in diabetes and related traits by large-scale genetic analysis.

Genetic studies have identified ≥240 loci associated with the risk of type 2 diabetes (T2D), yet most of these loci lie in non-coding regions, masking the underlying molecular mechanisms. Recent studies investigating mRNA expression in human pancreatic islets have yielded important insights into the molecular drivers of normal islet function and T2D pathophysiology. However, similar studies investigating microRNA (miRNA) expression remain limited. Here, we present data from 63 individuals, the largest sequencing-based analysis of miRNA expression in human islets to date. We characterized the genetic regulation of miRNA expression by decomposing the expression of highly heritable miRNAs into cis- and trans-acting genetic components and mapping cis-acting loci associated with miRNA expression [miRNA-expression quantitative trait loci (eQTLs)]. We found i) 84 heritable miRNAs, primarily regulated by trans-acting genetic effects, and ii) 5 miRNA-eQTLs. We also used several different strategies to identify T2D-associated miRNAs. First, we colocalized miRNA-eQTLs with genetic loci associated with T2D and multiple glycemic traits, identifying one miRNA, miR-1908, that shares genetic signals for blood glucose and glycated hemoglobin (HbA1c). Next, we intersected miRNA seed regions and predicted target sites with credible set SNPs associated with T2D and glycemic traits and found 32 miRNAs that may have altered binding and function due to disrupted seed regions. Finally, we performed differential expression analysis and identified 14 miRNAs associated with T2D status-including miR-187-3p, miR-21-5p, miR-668, and miR-199b-5p-and 4 miRNAs associated with a polygenic score for HbA1c levels-miR-216a, miR-25, miR-30a-3p, and miR-30a-5p.

Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits.

Genetic association studies have identified hundreds of independent signals associated with type 2 diabetes (T2D) and related traits. Despite these successes, the identification of specific causal variants underlying a genetic association signal remains challenging. In this study, we describe a deep learning (DL) method to analyze the impact of sequence variants on enhancers. Focusing on pancreatic islets, a T2D relevant tissue, we show that our model learns islet-specific transcription factor (TF) regulatory patterns and can be used to prioritize candidate causal variants. At 101 genetic signals associated with T2D and related glycemic traits where multiple variants occur in linkage disequilibrium, our method nominates a single causal variant for each association signal, including three variants previously shown to alter reporter activity in islet-relevant cell types. For another signal associated with blood glucose levels, we biochemically test all candidate causal variants from statistical fine-mapping using a pancreatic islet beta cell line and show biochemical evidence of allelic effects on TF binding for the model-prioritized variant. To aid in future research, we publicly distribute our model and islet enhancer perturbation scores across ~67 million genetic variants. We anticipate that DL methods like the one presented in this study will enhance the prioritization of candidate causal variants for functional studies.

Subcutaneous adipose tissue splice quantitative trait loci reveal differences in isoform usage associated with cardiometabolic traits.

Alternate splicing events can create isoforms that alter gene function, and genetic variants associated with alternate gene isoforms may reveal molecular mechanisms of disease. We used subcutaneous adipose tissue of 426 Finnish men from the METSIM study and identified splice junction quantitative trait loci (sQTLs) for 6,077 splice junctions (FDR < 1%). In the same individuals, we detected expression QTLs (eQTLs) for 59,443 exons and 15,397 genes (FDR < 1%). We identified 595 genes with an sQTL and exon eQTL but no gene eQTL, which could indicate potential isoform differences. Of the significant sQTL signals, 2,114 (39.8%) included at least one proxy variant (linkage disequilibrium r2 > 0.8) located within an intron spanned by the splice junction. We identified 203 sQTLs that colocalized with 141 genome-wide association study (GWAS) signals for cardiometabolic traits, including 25 signals for lipid traits, 24 signals for body mass index (BMI), and 12 signals for waist-hip ratio adjusted for BMI. Among all 141 GWAS signals colocalized with an sQTL, we detected 26 that also colocalized with an exon eQTL for an exon skipped by the sQTL splice junction. At a GWAS signal for high-density lipoprotein cholesterol colocalized with an NR1H3 sQTL splice junction, we show that the alternative splice product encodes an NR1H3 transcription factor that lacks a DNA binding domain and fails to activate transcription. Together, these results detect splicing events and candidate mechanisms that may contribute to gene function at GWAS loci.

Integrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk.

Transcriptomics data have been integrated with genome-wide association studies (GWASs) to help understand disease/trait molecular mechanisms. The utility of metabolomics, integrated with transcriptomics and disease GWASs, to understand molecular mechanisms for metabolite levels or diseases has not been thoroughly evaluated. We performed probabilistic transcriptome-wide association and locus-level colocalization analyses to integrate transcriptomics results for 49 tissues in 706 individuals from the GTEx project, metabolomics results for 1,391 plasma metabolites in 6,136 Finnish men from the METSIM study, and GWAS results for 2,861 disease traits in 260,405 Finnish individuals from the FinnGen study. We found that genetic variants that regulate metabolite levels were more likely to influence gene expression and disease risk compared to the ones that do not. Integrating transcriptomics with metabolomics results prioritized 397 genes for 521 metabolites, including 496 previously identified gene-metabolite pairs with strong functional connections and suggested 33.3% of such gene-metabolite pairs shared the same causal variants with genetic associations of gene expression. Integrating transcriptomics and metabolomics individually with FinnGen GWAS results identified 1,597 genes for 790 disease traits. Integrating transcriptomics and metabolomics jointly with FinnGen GWAS results helped pinpoint metabolic pathways from genes to diseases. We identified putative causal effects of UGT1A1/UGT1A4 expression on gallbladder disorders through regulating plasma (E,E)-bilirubin levels, of SLC22A5 expression on nasal polyps and plasma carnitine levels through distinct pathways, and of LIPC expression on age-related macular degeneration through glycerophospholipid metabolic pathways. Our study highlights the power of integrating multiple sets of molecular traits and GWAS results to deepen understanding of disease pathophysiology.

The microbiota regulate neuronal function and fear extinction learning.

Multicellular organisms have co-evolved with complex consortia of viruses, bacteria, fungi and parasites, collectively referred to as the microbiota1. In mammals, changes in the composition of the microbiota can influence many physiologic processes (including development, metabolism and immune cell function) and are associated with susceptibility to multiple diseases2. Alterations in the microbiota can also modulate host behaviours-such as social activity, stress, and anxiety-related responses-that are linked to diverse neuropsychiatric disorders3. However, the mechanisms by which the microbiota influence neuronal activity and host behaviour remain poorly defined. Here we show that manipulation of the microbiota in antibiotic-treated or germ-free adult mice results in significant deficits in fear extinction learning. Single-nucleus RNA sequencing of the medial prefrontal cortex of the brain revealed significant alterations in gene expression in excitatory neurons, glia and other cell types. Transcranial two-photon imaging showed that deficits in extinction learning after manipulation of the microbiota in adult mice were associated with defective learning-related remodelling of postsynaptic dendritic spines and reduced activity in cue-encoding neurons in the medial prefrontal cortex. In addition, selective re-establishment of the microbiota revealed a limited neonatal developmental window in which microbiota-derived signals can restore normal extinction learning in adulthood. Finally, unbiased metabolomic analysis identified four metabolites that were significantly downregulated in germ-free mice and have been reported to be related to neuropsychiatric disorders in humans and mouse models, suggesting that microbiota-derived compounds may directly affect brain function and behaviour. Together, these data indicate that fear extinction learning requires microbiota-derived signals both during early postnatal neurodevelopment and in adult mice, with implications for our understanding of how diet, infection, and lifestyle influence brain health and subsequent susceptibility to neuropsychiatric disorders.

Structural determinants of dual incretin receptor agonism by tirzepatide.

SignificanceTirzepatide is a dual agonist of the glucose-dependent insulinotropic polypeptide receptor (GIPR) and the glucagon-like peptide-1 receptor (GLP-1R), which are incretin receptors that regulate carbohydrate metabolism. This investigational agent has proven superior to selective GLP-1R agonists in clinical trials in subjects with type 2 diabetes mellitus. Intriguingly, although tirzepatide closely resembles native GIP in how it activates the GIPR, it differs markedly from GLP-1 in its activation of the GLP-1R, resulting in less agonist-induced receptor desensitization. We report how cryogenic electron microscopy and molecular dynamics simulations inform the structural basis for the unique pharmacology of tirzepatide. These studies reveal the extent to which fatty acid modification, combined with amino acid sequence, determines the mode of action of a multireceptor agonist.

Single-cell transcriptomic profiling of human pancreatic islets reveals genes responsive to glucose exposure over 24 h.

AIMS/HYPOTHESIS: Disruption of pancreatic islet function and glucose homeostasis can lead to the development of sustained hyperglycaemia, beta cell glucotoxicity and subsequently type 2 diabetes. In this study, we explored the effects of in vitro hyperglycaemic conditions on human pancreatic islet gene expression across 24 h in six pancreatic cell types: alpha; beta; gamma; delta; ductal; and acinar. We hypothesised that genes associated with hyperglycaemic conditions may be relevant to the onset and progression of diabetes. METHODS: We exposed human pancreatic islets from two donors to low (2.8 mmol/l) and high (15.0 mmol/l) glucose concentrations over 24 h in vitro. To assess the transcriptome, we performed single-cell RNA-seq (scRNA-seq) at seven time points. We modelled time as both a discrete and continuous variable to determine momentary and longitudinal changes in transcription associated with islet time in culture or glucose exposure. Additionally, we integrated genomic features and genetic summary statistics to nominate candidate effector genes. For three of these genes, we functionally characterised the effect on insulin production and secretion using CRISPR interference to knock down gene expression in EndoC-ßH1 cells, followed by a glucose-stimulated insulin secretion assay. RESULTS: In the discrete time models, we identified 1344 genes associated with time and 668 genes associated with glucose exposure across all cell types and time points. In the continuous time models, we identified 1311 genes associated with time, 345 genes associated with glucose exposure and 418 genes associated with interaction effects between time and glucose across all cell types. By integrating these expression profiles with summary statistics from genetic association studies, we identified 2449 candidate effector genes for type 2 diabetes, HbA1c, random blood glucose and fasting blood glucose. Of these candidate effector genes, we showed that three (ERO1B, HNRNPA2B1 and RHOBTB3) exhibited an effect on glucose-stimulated insulin production and secretion in EndoC-ßH1 cells. CONCLUSIONS/INTERPRETATION: The findings of our study provide an in-depth characterisation of the 24 h transcriptomic response of human pancreatic islets to glucose exposure at a single-cell resolution. By integrating differentially expressed genes with genetic signals for type 2 diabetes and glucose-related traits, we provide insights into the molecular mechanisms underlying glucose homeostasis. Finally, we provide functional evidence to support the role of three candidate effector genes in insulin secretion and production. DATA AVAILABILITY: The scRNA-seq data from the 24 h glucose exposure experiment performed in this study are available in the database of Genotypes and Phenotypes (dbGap; https://www.ncbi.nlm.nih.gov/gap/ ) with accession no. phs001188.v3.p1. Study metadata and summary statistics for the differential expression, gene set enrichment and candidate effector gene prediction analyses are available in the Zenodo data repository ( https://zenodo.org/ ) under accession number 11123248. The code used in this study is publicly available at https://github.com/CollinsLabBioComp/publication-islet_glucose_timecourse .

Genetic effects on liver chromatin accessibility identify disease regulatory variants.

Identifying the molecular mechanisms by which genome-wide association study (GWAS) loci influence traits remains challenging. Chromatin accessibility quantitative trait loci (caQTLs) help identify GWAS loci that may alter GWAS traits by modulating chromatin structure, but caQTLs have been identified in a limited set of human tissues. Here we mapped caQTLs in human liver tissue in 20 liver samples and identified 3,123 caQTLs. The caQTL variants are enriched in liver tissue promoter and enhancer states and frequently disrupt binding motifs of transcription factors expressed in liver. We predicted target genes for 861 caQTL peaks using proximity, chromatin interactions, correlation with promoter accessibility or gene expression, and colocalization with expression QTLs. Using GWAS signals for 19 liver function and/or cardiometabolic traits, we identified 110 colocalized caQTLs and GWAS signals, 56 of which contained a predicted caPeak target gene. At the LITAF LDL-cholesterol GWAS locus, we validated that a caQTL variant showed allelic differences in protein binding and transcriptional activity. These caQTLs contribute to the epigenomic characterization of human liver and help identify molecular mechanisms and genes at GWAS loci.

Towards a youth mental health paradigm: a perspective and roadmap.

Most mental disorders have a typical onset between 12 and 25 years of age, highlighting the importance of this period for the pathogenesis, diagnosis, and treatment of mental ill-health. This perspective addresses interactions between risk and protective factors and brain development as key pillars accounting for the emergence of psychopathology in youth. Moreover, we propose that novel approaches towards early diagnosis and interventions are required that reflect the evolution of emerging psychopathology, the importance of novel service models, and knowledge exchange between science and practitioners. Taken together, we propose a transformative early intervention paradigm for research and clinical care that could significantly enhance mental health in young people and initiate a shift towards the prevention of severe mental disorders.

Mutual Cooperativity of Three Allosteric Sites on the Dopamine D1 Receptor.

An amine-containing molecule called Compound A has been reported by a group from Bristol-Myers Squibb to act as a positive allosteric modulator (PAM) at the dopamine D1 receptor. We synthesized the more active enantiomer of Compound A (BMS-A1) and compared it with the D1 PAMs DETQ and MLS6585, which are known to bind to intracellular loop 2 and the extracellular portion of transmembrane helix 7, respectively. Results from D1/D5 chimeras indicated that PAM activity of BMS-A1 tracked with the presence of D1 sequence in the N-terminal/extracellular region of the D1 receptor, a unique location compared with either of the other PAMs. In pairwise combinations, BMS-A1 potentiated the small allo-agonist activity of each of the other PAMs, while the triple PAM combination (in the absence of dopamine) produced a cAMP response about 64% of the maximum produced by dopamine. Each of the pairwise PAM combinations produced a much larger leftward shift of the dopamine EC50 than either single PAM alone. All three PAMs in combination produced a 1000-fold leftward shift of the dopamine curve. These results demonstrate the presence of three non-overlapping allosteric sites that cooperatively stabilize the same activated state of the human D1 receptor. SIGNIFICANCE STATEMENT: Deficiencies in dopamine D1 receptor activation are seen in Parkinson disease and other neuropsychiatric disorders. In this study, three positive allosteric modulators of the dopamine D1 receptor were found to bind to distinct and separate sites, interacting synergistically with each other and dopamine, with the triple combination causing a 1000-fold leftward shift of the response to dopamine. These results showcase multiple opportunities to modulate D1 tone and highlight new pharmacological approaches for allosteric modulation of G-protein-coupled receptors.

Remotely sensed localised primary production anomalies predict the burden and community structure of infection in long-term rodent datasets.

The increasing frequency and cost of zoonotic disease emergence due to global change have led to calls for the primary surveillance of wildlife. This should be facilitated by the ready availability of remotely sensed environmental data, given the importance of the environment in determining infectious disease dynamics. However, there has been little evaluation of the temporal predictiveness of remotely sensed environmental data for infection reservoirs in vertebrate hosts due to a deficit of corresponding high-quality long-term infection datasets. Here we employ two unique decade-spanning datasets for assemblages of infectious agents, including zoonotic agents, in rodents in stable habitats. Such stable habitats are important, as they provide the baseline sets of pathogens for the interactions within degrading habitats that have been identified as hotspots for zoonotic emergence. We focus on the enhanced vegetation index (EVI), a measure of vegetation greening that equates to primary productivity, reasoning that this would modulate infectious agent populations via trophic cascades determining host population density or immunocompetence. We found that EVI, in analyses with data standardised by site, inversely predicted more than one-third of the variation in an index of infectious agent total abundance. Moreover, in bipartite host occupancy networks, weighted network statistics (connectance and modularity) were linked to total abundance and were also predicted by EVI. Infectious agent abundance and, perhaps, community structure are likely to influence infection risk and, in turn, the probability of transboundary emergence. Thus, the present results, which were consistent in disparate forest and desert systems, provide proof-of-principle that within-site fluctuations in satellite-derived greenness indices can furnish useful forecasting that could focus primary surveillance. In relation to the well-documented global greening trend of recent decades, the present results predict declining infection burden in wild vertebrates in stable habitats; but if greening trends were to be reversed, this might magnify the already upwards trend in zoonotic emergence.

Identification and characterization of motile Aeromonas spp. isolated from farmed Nile tilapia (Oreochromis niloticus) in the Philippines.

AIMS: Motile Aeromonas septicaemia (MAS) caused by motile Aeromonas species is an important disease in farmed freshwater fish due to intensification of culture and improper farm practices. This study characterized and profiled motile Aeromonas species recovered from clinically sick tilapia farmed in the Philippines, with a view to identifying targeted disease prevention and control measures against MAS in farmed tilapia species. METHODS AND RESULTS: Sixteen isolates from diseased farmed Nile tilapia were identified as Aeromonas veronii (n = 14), Aeromonas caviae (n = 1), and Aeromonas dhakensis (n = 1). Five biochemical profiles using API 20E were exhibited by the A. veronii strains giving an unreliable identification. A high level of agreement was observed in identifying the Aeromonas strains using 16S rRNA and rpoD gene sequencing, although the latter has a higher discriminatory value. Three or more virulence genes dominated by cytotoxic enterotoxin act and aerolysin aer were detected. Different genotypes based on virulence gene clustering suggested varied mechanisms used by Aeromonas to colonize and infect or to mutualistically co-exist with the fish. Acquired multiple antibiotic resistance was found in a single A. veronii isolate. All were susceptible to enrofloxacin, oxolinic acid, florfenicol, and chloramphenicol. Tetracycline and sulfonamide resistances and class 1 integron were detected in three A. veronii isolates. CONCLUSION: Several strains of motile aeromonads, especially A. veronii, which have varied genotypes based on virulence, biochemical profile, and antibiotic resistance, are involved in MAS in natural disease outbreaks in farmed Nile tilapia in the Philippines.

Update on and Future Directions for Use of Anti-SARS-CoV-2 Antibodies: National Institutes of Health Summit on Treatment and Prevention of COVID-19.

As the fourth wave of the SARS-CoV-2 pandemic encircles the globe, there remains an urgent challenge to identify safe and effective treatment and prevention strategies that can be implemented in a range of health care and clinical settings. Substantial advances have been made in the use of anti-SARS-CoV-2 antibodies to mitigate the morbidity and mortality associated with COVID-19. On 15 June 2021, the National Institutes of Health, in collaboration with the U.S. Food and Drug Administration, convened a virtual summit to summarize existing knowledge on anti-SARS-CoV-2 antibodies and to identify key unanswered scientific questions to further catalyze the clinical development and implementation of antibodies.

mGreenLantern: a bright monomeric fluorescent protein with rapid expression and cell filling properties for neuronal imaging.

Although ubiquitous in biological studies, the enhanced green and yellow fluorescent proteins (EGFP and EYFP) were not specifically optimized for neuroscience, and their underwhelming brightness and slow expression in brain tissue limits the fidelity of dendritic spine analysis and other indispensable techniques for studying neurodevelopment and plasticity. We hypothesized that EGFP's low solubility in mammalian systems must limit the total fluorescence output of whole cells, and that improving folding efficiency could therefore translate into greater brightness of expressing neurons. By introducing rationally selected combinations of folding-enhancing mutations into GFP templates and screening for brightness and expression rate in human cells, we developed mGreenLantern, a fluorescent protein having up to sixfold greater brightness in cells than EGFP. mGreenLantern illuminates neurons in the mouse brain within 72 h, dramatically reducing lag time between viral transduction and imaging, while its high brightness improves detection of neuronal morphology using widefield, confocal, and two-photon microscopy. When virally expressed to projection neurons in vivo, mGreenLantern fluorescence developed four times faster than EYFP and highlighted long-range processes that were poorly detectable in EYFP-labeled cells. Additionally, mGreenLantern retains strong fluorescence after tissue clearing and expansion microscopy, thereby facilitating superresolution and whole-brain imaging without immunohistochemistry. mGreenLantern can directly replace EGFP/EYFP in diverse systems due to its compatibility with GFP filter sets, recognition by EGFP antibodies, and excellent performance in mouse, human, and bacterial cells. Our screening and rational engineering approach is broadly applicable and suggests that greater potential of fluorescent proteins, including biosensors, could be unlocked using a similar strategy.