Genome-wide association studies (GWASs) and expression analyses implicate noncoding regulatory regions as harboring risk factors for psychiatric disease, but functional characterization of these regions remains limited. Here, we perform capture STARR-sequencing of over 70,000 candidate regions to identify active enhancers in primary human neural progenitor cells (phNPCs). We select candidate regions by integrating data from NPCs, prefrontal cortex, developmental timepoints, and GWASs. Over 8000 regions demonstrate enhancer activity in the phNPCs, and we link these regions to over 2200 predicted target genes. These genes are involved in neuronal and psychiatric disease-associated pathways, including neuronal system, nervous system development, and developmental delay. We functionally validate a subset of these enhancers using mutation STARR-sequencing and CRISPR deletions, demonstrating the effects of genetic variation on enhancer activity and enhancer deletion on gene expression. Overall, we identify thousands of highly active enhancers and functionally validated a subset of these enhancers, improving our understanding of regulatory networks underlying brain function and disease.

Intranasal delivery of mRNA vaccines offers promising opportunities to combat airborne viruses like SARS-CoV-2 by provoking mucosal immunity, which not only defends against respiratory infection but also prevents contagious transmission. However, the development of nasal mRNA vaccines has been hampered by the lack of effective means to overcome the mucus barrier. Herein, ionizable lipid-incorporated liquid lipid nanoparticles (iLLNs) capable of delivering mRNA cargo across airway mucosa are designed. Adjusting the ratios of ionizable and cationic lipids allows fine-tuning of the pKa of iLLNs to the range of nasal mucosal pH (5.5-6.5), thus facilitating mucus penetration via the formation of near-neutral, PEGylated muco-inert surfaces. When nasally administered to mice, the top candidate iLLN-2/mRNA complexes enable about 60-fold greater reporter gene expression in the nasal cavity, compared to the benchmark mRNA-lipid nanoparticles (ALC-LNP) having the same lipid composition as that of BNT162b2 vaccine. Moreover, a prime-boost intranasal immunization of iLLN-2/mRNA complexes elicits a greater magnitude of SARS-CoV-2 spike-specific mucosal IgA and IgG response than ALC-LNP, without triggering any noticeable inflammatory reactions. Taken together, these results provide useful insights for the design of nasally deliverable mRNA formulations for prophylactic applications.

Multiple cellular pathways are dysregulated in autosomal dominant polycystic kidney disease (ADPKD), but mechanisms initiating cyst formation are unknown. ADPKD is caused by mutations in Pkd1/Pkd2 genes that encode for polycystins that localize to primary cilia. The primary cilium is a miniscule subcellular compartment for generating signaling outputs that profoundly affect cellular function. Severe cystogenesis from polycystin loss is mostly cilia dependent. However, the polycystin-repressed ciliary signals that promote cyst growth are unknown and have been challenging to uncouple from downstream cystogenic pathways. Here we aimed at differentiating ciliary adenylyl cyclase signaling from total cellular changes in second messenger cAMP implicated in cystogenesis. We studied an Ankyrin repeat and MYND domain protein, ANKMY2 that we previously implicated in maturation and ciliary localization of adenylyl cyclases in fibroblasts. We studied kidney-specific conditional knockout mouse models of Ankmy2/Pkd1 and ciliary localization of adenylyl cyclases in kidney epithelial cells. We found suppression of early postnatal renal cystogenesis and prolonged survival in an embryonic onset Pkd1 deletion model from ANKMY2 loss. Phosphorylated CREB formation, from elevated cellular cAMP levels, remained unaffected. Cyst load in male mice in an adult inducible conditional Pkd1 deletion model was suppressed from ANKMY2 loss. Mechanistically, ANKMY2 determined ciliary trafficking of adenylyl cyclases in kidney epithelial cells without disrupting cilia. Further, ANKMY2 loss prevented ciliary length increase in ADPKD mouse models irrespective of cyst load or sex. Cilia length increase was seen preceding cystogenesis. Our results suggest that targeting of adenylyl cyclases to renal epithelial cilia promotes PC1/2-inhibited cilia-dependent cyst activation distinct from cyst progression involving cellular cAMP.

Since their original description by Wiesner et al., the spectrum of clinical, histopathologic, and molecular findings of BAP1 (BRCA1-associated protein 1)-inactivated melanocytomas has been more fully characterized. Herein, we report an exceptional presentation of multiple junctional melanocytic BAP1-inactivated melanocytomas with a clinically hypopigmented appearance in a patient. Targeted DNA sequencing demonstrated the same BAP1 frameshift mutation (BAP1 p.R59f) in three different lesions. One of the specimens also displayed two truncating mutations in NF1 (NF1 p.Q129* and NF1 p.Q1801*) at 8%-9% mutant allele frequency. To our knowledge, BIM confined entirely to the epidermis, and multiple BIMs presenting in hypopigmented fashion have not been widely reported previously.

PURPOSE:NCI selected a network of Clinical Laboratory Improvement Amendments-certified laboratories performing routine next-generation sequencing (NGS) tumor testing to identify patients for the NCI Molecular Analysis for Therapy Choice (NCI-MATCH) trial. This large network provided a unique opportunity to compare variant detection and reporting between a wide range of testing platforms. EXPERIMENTAL DESIGN:Twenty-eight NGS assays from 26 laboratories within the NCI-MATCH Network, including the NCI-MATCH central laboratory (CL) and 11 commercial and 14 academic designated laboratories (DL), were used for this study. DNA from eight cell lines and two clinical samples were sequenced. Pairwise comparisons in variant detection and reporting between each DL and CL were performed for single-nucleotide variant, insertion and deletion, and copy-number variant classes. RESULTS:We observed high concordance in variant detection between CL and DL for single-nucleotide variants and insertions and deletions [average positive agreement (APA) > 95.4% for all pairwise comparisons] but lower concordance for variant reporting after analysis pipeline filtering. We observed much higher agreement between CL and assays using amplification as the target enrichment method (84.2% < APA ≤ 95.7%, average APA = 88.7%) than other assays using hybridization capture (69.7% < APA ≤ 93.8%, average APA = 77.4%) due to blacklisting of actionable variants in low complexity regions. For copy-number variant reporting, we observed high agreement (APA > 82%) except between CL and two assays (APA = 76.9% and 71.4%) due to differences in estimation of copy numbers. Notably, for all variants, differences in variant interpretation also contributed to reporting discrepancies. CONCLUSIONS:This study indicates that different NGS tumor profiling tests currently in widespread clinical use achieve high concordance between assays in variant detection. For variant reporting, observed discrepancies are mainly introduced during the bioinformatic analysis.

Climate change is occurring at an accelerated rate in high-elevation alpine and mountain ecosystems. Cold-adapted, mountain species are at risk due to forecasted change and knowledge is needed to respond to current and future conservation challenges. Mountain goats (Oreamnos americanus) are an iconic species of North American mountain cultures and landscapes, and due to specialized adaptations for life in cold, mountainous environments they are particularly sensitive to changes in weather and climate. As sentinels of change in alpine ecosystems, the study of mountain goats offers insight into the ecological effects and conservation challenges associated with climate change in these sensitive and biodiverse environments. Here, we synthesize existing knowledge about how climate change is expected to influence environmental conditions experienced by mountain goats and associated mechanistic changes to behavior, nutritional ecology, demography, health, and interspecific interactions. In many instances, climate change effects are likely to be negative and additive to existing threats (such as human disturbance, hunting, disease, predation) though benefits are expected in some cases. Changes in climate and mountain environments will necessitate re-examination and modification of population monitoring, management, and conservation strategies. Specifically, spatiotemporal (and other) aspects of monitoring and management may need to be adjusted to accommodate emerging and novel conservation challenges. Yet, key data and knowledge gaps remain and should be addressed to advance conservation and decision-making capabilities. For mountain goats and similarly climate-sensitive alpine herbivores, effective conservation will ultimately benefit from collaborations among diverse networks guided by well-planned, strategic visions focused on common ground – namely the resiliency and persistence of culturally and ecologically significant mountain species and the alpine environment they inhabit.

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type–specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

The advent of SARS-CoV-2 variants with defined mutations that augment pathogenicity and/or increase immune evasiveness continues to stimulate global efforts to improve vaccine formulation and efficacy. The extraordinary advantages of lipid nanoparticles (LNPs), including versatile design, scalability, and reproducibility, make them ideal candidates for developing next-generation mRNA vaccines against circulating SARS-CoV-2 variants. Here, we assess the efficacy of LNP-encapsulated mRNA booster vaccines encoding the spike protein of SARS-CoV-2 for variants of concern (Delta, Omicron) and using a predecessor (YN2016C isolated from bats) strain spike protein to elicit durable cross-protective neutralizing antibody responses. The mRNA-LNP vaccines have desirable physicochemical characteristics, such as small size (~78 nm), low polydispersity index (<0.13), and high encapsulation efficiency (>90%). We employ in vivo bioluminescence imaging to illustrate the capacity of our LNPs to induce robust mRNA expression in secondary lymphoid organs. In a BALB/c mouse model, a three-dose subcutaneous immunization of mRNA-LNPs vaccines achieved remarkably high levels of cross-neutralization against the Omicron B1.1.529 and BA.2 variants for extended periods of time (28 weeks) with good safety profiles for all constructs when used in a booster regime, including the YN2016C bat virus sequences. These findings have important implications for the design of mRNA-LNP vaccines that aim to trigger durable cross-protective immunity against the current and newly emerging variants.

Psychiatric disorders are highly heritable yet polygenic, potentially involving hundreds of risk genes. Genome-wide association studies have identified hundreds of genomic susceptibility loci with susceptibility to psychiatric disorders; however, the contribution of these loci to the underlying psychopathology and etiology remains elusive. Here we generated deep human brain proteomics data by quantifying 11,608 proteins across 268 subjects using 11-plex tandem mass tag coupled with two-dimensional liquid chromatography-tandem mass spectrometry. Our analysis revealed 788 cis-acting protein quantitative trait loci associated with the expression of 883 proteins at a genome-wide false discovery rate <5%. In contrast to expression at the transcript level and complex diseases that are found to be mainly influenced by noncoding variants, we found protein expression level tends to be regulated by non-synonymous variants. We also provided evidence of 76 shared regulatory signals between gene expression and protein abundance. Mediation analysis revealed that for most (88%) of the colocalized genes, the expression levels of their corresponding proteins are regulated by cis-pQTLs via gene transcription. Using summary data-based Mendelian randomization analysis, we identified 4 proteins and 19 genes that are causally associated with schizophrenia. We further integrated multiple omics data with network analysis to prioritize candidate genes for schizophrenia risk loci. Collectively, our findings underscore the potential of proteome-wide linkage analysis in gaining mechanistic insights into the pathogenesis of psychiatric disorders.

Despite global efforts on meeting sustainable development goals by 2030, persistent and widespread sanitation deficits in rural, underserved communities in high-income countries-including the United States (US)-challenge achieving this target. The recent US federal infrastructure funding, coupled with research efforts to explore innovative, alternative decentralized wastewater systems, are unprecedented opportunities for addressing basic sanitation gaps in these communities. Yet, understanding how to best manage these systems for sustainable operations and maintenance (O&M) is still a national need. Here, we develop an integrated management approach for achieving such sustainable systems, taking into account the utility structure, operational aspects, and possible barriers impeding effective management of decentralized wastewater infrastructure. We demonstrate this approach through a binomial logistic regression of survey responses from 114 public and private management entities (e.g., water and sewer utilities) operating in 27 states in the US, targeting the rural Alabama Black Belt wastewater issues. Our assessment introduces policy areas that support sustainable decentralized wastewater systems management and operations, including privatizing water-wastewater infrastructure systems, incentivizing/mandating the consolidation of utility management of these systems, federally funding the O&M, and developing and retaining water-wastewater workforce in rural, underserved communities. Our discussions give rise to a holistic empirical understanding of effective management of decentralized wastewater infrastructure for rural, underserved communities in the US, thereby contributing to global conversations on sustainable development.

Chitosan, a natural polysaccharide derived from chitin, possesses biocompatibility, biodegradability, and mucoadhesive characteristics, making it an attractive material for the delivery of mRNA payloads to the nasal mucosa and promoting their uptake by target cells such as epithelial and immune cells (e.g., dendritic cells and macrophages). In this project, we aimed at developing novel lipid-based nanoformulations for mRNA delivery to counteract the pandemic caused by SARS-CoV-2 virus. The formulations achieved a mRNA encapsulation efficiency of ~80.2% with chitosan-lipid nanoparticles, as measured by the RiboGreen assay. Furthermore, the evaluation of SARS-CoV-2 Spike (S) receptor-binding domain (RBD) expression via ELISA for our vaccine formulations showed transfection levels in human embryonic kidney cells (HEK 293), lung carcinoma cells (A549), and dendritic cells (DC 2.4) equal to 9.9 ± 0.1 ng/mL (174.7 ± 1.1 fold change from untreated cells (UT)), 7.0 ± 0.2 ng/mL (128.1 ± 4.9 fold change from UT), and 0.9 ± 0.0 ng/mL (18.0 ± 0.1 fold change from UT), respectively. Our most promising vaccine formulation was also demonstrated to be amenable to lyophilization with minimal degradation of loaded mRNA, paving the way towards a more accessible and stable vaccine. Preliminary in vivo studies in mice were performed to assess the systemic and local immune responses. Nasal bronchoalveolar lavage fluid (BALF) wash showed that utilizing the optimized formulation resulted in local antibody concentrations and did not trigger any systemic antibody response. However, if further improved and developed, it could potentially contribute to the management of COVID-19 through nasopharyngeal immunization strategies.

IntroductionQuantitative, multiplexed imaging is revealing complex spatial relationships between phenotypically diverse tumor infiltrating leukocyte populations and their prognostic implications. The underlying mechanisms and tissue structures that determine leukocyte distribution within and around tumor nests, however, remain poorly understood. While presumed players in metastatic dissemination, new preclinical data demonstrates that blood and lymphatic vessels (lymphovasculature) also dictate leukocyte trafficking within tumor microenvironments and thereby impact anti-tumor immunity. Here we interrogate these relationships in primary human cutaneous melanoma. MethodsWe established a quantitative, multiplexed imaging platform to simultaneously detect immune infiltrates and tumor-associated vessels in formalin-fixed paraffin embedded patient samples. We performed a discovery, retrospective analysis of 28 treatment-naïve, primary cutaneous melanomas. ResultsHere we find that the lymphvasculature and immune infiltrate is heterogenous across patients in treatment naïve, primary melanoma. We categorized five lymphovascular subtypes that differ by functionality and morphology and mapped their localization in and around primary tumors. Interestingly, the localization of specific vessel subtypes, but not overall vessel density, significantly associated with the presence of lymphoid aggregates, regional progression, and intratumoral T cell infiltrates. DiscussionWe describe a quantitative platform to enable simultaneous lymphovascular and immune infiltrate analysis and map their spatial relationships in primary melanoma. Our data indicate that tumor-associated vessels exist in different states and that their localization may determine potential for metastasis or immune infiltration. This platform will support future efforts to map tumor-associated lymphovascular evolution across stage, assess its prognostic value, and stratify patients for adjuvant therapy.

SUMMARY A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here we present the culmination of the modERN (model organism Encyclopedia of Regulatory Networks) consortium that systematically assayed TF binding events in vivo in two major model organisms, Drosophila melanogaster (fly) and Caenorhabditis elegans (worm). We describe key features of these datasets, comprising 604 TFs identifying 3.6M sites in the fly and 350 TFs identifying 0.9 M sites in the worm. Applying a machine learning model to these data identifies sets of TFs with a prominent role in promoting target gene expression in specific cell types. TF binding data are available through the ENCODE Data Coordinating Center and at https://epic.gs.washington.edu/modERNresource , which provides access to processed and summary data, as well as widgets to probe cell type-specific TF-target relationships. These data are a rich resource that should fuel investigations into TF function during development.

Tumor mutational burden (TMB), the total number of somatic mutations in the tumor, and copy number burden (CNB), the corresponding measure of aneuploidy, are established fundamental somatic features and emerging biomarkers for immunotherapy. However, the genetic and non-genetic influences on TMB/CNB and, critically, the manner by which they influence patient outcomes remain poorly understood. Here, we present a large germline-somatic study of TMB/CNB with >23,000 individuals across 17 cancer types, of which 12,000 also have extensive clinical, treatment, and overall survival (OS) measurements available. We report dozens of clinical associations with TMB/CNB, observing older age and male sex to have a strong effect on TMB and weaker impact on CNB. We additionally identified significant germline influences on TMB/CNB, including fine-scale European ancestry and germline polygenic risk scores (PRSs) for smoking, tanning, white blood cell counts, and educational attainment. We quantify the causal effect of exposures on somatic mutational processes using Mendelian randomization. Many of the identified features associated with TMB/CNB were additionally associated with OS for individuals treated at a single tertiary cancer center. For individuals receiving immunotherapy, we observed a complex relationship between PRSs for educational attainment, self-reported college attainment, TMB, and survival, suggesting that the influence of this biomarker may be substantially modified by socioeconomic status. While the accumulation of somatic alterations is a stochastic process, our work demonstrates that it can be shaped by host characteristics including germline genetics.

AbstractSnow is a major, climate-sensitive feature of the Earth’s surface and catalyst of fundamentally important ecosystem processes. Understanding how snow influences sentinel species in rapidly changing mountain ecosystems is particularly critical. Whereas effects of snow on food availability, energy expenditure, and predation are well documented, we report how avalanches exert major impacts on an ecologically significant mountain ungulate - the coastal Alaskan mountain goat (Oreamnos americanus). Using long-term GPS data and field observations across four populations (421 individuals over 17 years), we show that avalanches caused 23−65% of all mortality, depending on area. Deaths varied seasonally and were directly linked to spatial movement patterns and avalanche terrain use. Population-level avalanche mortality, 61% of which comprised reproductively important prime-aged individuals, averaged 8% annually and exceeded 22% when avalanche conditions were severe. Our findings reveal a widespread but previously undescribed pathway by which snow can elicit major population-level impacts and shape demographic characteristics of slow-growing populations of mountain-adapted animals.

A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here, we present the culmination of the efforts of the modENCODE (model organism Encyclopedia of DNA Elements) and modERN (model organism Encyclopedia of Regulatory Networks) consortia to systematically assay TF binding events in vivo in two major model organisms, Drosophila melanogaster (fly) and Caenorhabditis elegans (worm). These data sets comprise 605 TFs identifying 3.6 M sites in the fly and 356 TFs identifying 0.9 M sites in the worm, and represent the majority of the regulatory space in each genome. We demonstrate that TFs associate with chromatin in clusters termed "metapeaks," that larger metapeaks have characteristics of high-occupancy target (HOT) regions, and that the importance of consensus sequence motifs bound by TFs depends on metapeak size and complexity. Combining ChIP-seq data with single-cell RNA-seq data in a machine-learning model identifies TFs with a prominent role in promoting target gene expression in specific cell types, even differentiating between parent-daughter cells during embryogenesis. These data are a rich resource for the community that should fuel and guide future investigations into TF function. To facilitate data accessibility and utility, all strains expressing green fluorescent protein (GFP)-tagged TFs are available at the stock centers for each organism. The chromatin immunoprecipitation sequencing data are available through the ENCODE Data Coordinating Center, GEO, and through a direct interface that provides rapid access to processed data sets and summary analyses, as well as widgets to probe the cell-type-specific TF-target relationships.

Decentralized wastewater treatment systems are utilized in areas where sewer systems are not feasible and septic service is unaffordable. Approximately 25% of the US population uses decentralized wastewater systems for their wastewater treatment. The Black Belt, which extends from the East Coast of the US from Virginia through the Carolinas, Georgia, Alabama, and Mississippi is an area that has a large population that depends on decentralized wastewater systems. In the State of Alabama, the Black Belt area is a 17-county region where, depending on the county, up to 85% of the residents rely on decentralized wastewater treatment. These decentralized systems are largely unaffordable for the residents in this region due to a median household income of $29K, which is half of the national average. One proposed system is a low-cost lab-scale hybrid evapotranspiration/lateral flow sand filter. The hybrid sand filter system is designed to treat 55 gallon per day (GPD) of septic tank effluent, sized at 13 ft x 12 ft x 3 ft. The influent is treated physically, chemically, and biologically within the sand layers of the system. Hydraulically, influent flows laterally and rises via capillary action within the sand layers. The system has a correlation to ambient temperature and humidity. Lower discharge rates are directly proportional to higher temperature and humidity. The following data represents the percent reduction for our wastewater treatment system: Ammonia (64%), Phosphorus (92%), COD (76%), and BOD (96%). The hydraulic and treatment data for the hybrid sand filter system are promising. In this analysis, the authors identify sociotechnical factors that can affect the performance and useful life of the system in a multiple decision matrix. Sociotechnical factors, such as persons per residence, electricity usage, and distance of the decentralized system from the residence, are analyzed to build a simple agent-based model (ABM) which will determine the impacts on the overall performance of the system.