Algorithm for optimized mRNA design improves stability and immunogenicity.

Messenger RNA (mRNA) vaccines are being used to combat the spread of COVID-19 (refs. 1-3), but they still exhibit critical limitations caused by mRNA instability and degradation, which are major obstacles for the storage, distribution and efficacy of the vaccine products4. Increasing secondary structure lengthens mRNA half-life, which, together with optimal codons, improves protein expression5. Therefore, a principled mRNA design algorithm must optimize both structural stability and codon usage. However, owing to synonymous codons, the mRNA design space is prohibitively large-for example, there are around 2.4 × 10632 candidate mRNA sequences for the SARS-CoV-2 spike protein. This poses insurmountable computational challenges. Here we provide a simple and unexpected solution using the classical concept of lattice parsing in computational linguistics, where finding the optimal mRNA sequence is analogous to identifying the most likely sentence among similar-sounding alternatives6. Our algorithm LinearDesign finds an optimal mRNA design for the spike protein in just 11 minutes, and can concurrently optimize stability and codon usage. LinearDesign substantially improves mRNA half-life and protein expression, and profoundly increases antibody titre by up to 128 times in mice compared to the codon-optimization benchmark on mRNA vaccines for COVID-19 and varicella-zoster virus. This result reveals the great potential of principled mRNA design and enables the exploration of previously unreachable but highly stable and efficient designs. Our work is a timely tool for vaccines and other mRNA-based medicines encoding therapeutic proteins such as monoclonal antibodies and anti-cancer drugs7,8.

LinearTurboFold: Linear-time global prediction of conserved structures for RNA homologs with applications to SARS-CoV-2.

The constant emergence of COVID-19 variants reduces the effectiveness of existing vaccines and test kits. Therefore, it is critical to identify conserved structures in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes as potential targets for variant-proof diagnostics and therapeutics. However, the algorithms to predict these conserved structures, which simultaneously fold and align multiple RNA homologs, scale at best cubically with sequence length and are thus infeasible for coronaviruses, which possess the longest genomes (∼30,000 nt) among RNA viruses. As a result, existing efforts on modeling SARS-CoV-2 structures resort to single-sequence folding as well as local folding methods with short window sizes, which inevitably neglect long-range interactions that are crucial in RNA functions. Here we present LinearTurboFold, an efficient algorithm for folding RNA homologs that scales linearly with sequence length, enabling unprecedented global structural analysis on SARS-CoV-2. Surprisingly, on a group of SARS-CoV-2 and SARS-related genomes, LinearTurboFold's purely in silico prediction not only is close to experimentally guided models for local structures, but also goes far beyond them by capturing the end-to-end pairs between 5' and 3' untranslated regions (UTRs) (∼29,800 nt apart) that match perfectly with a purely experimental work. Furthermore, LinearTurboFold identifies undiscovered conserved structures and conserved accessible regions as potential targets for designing efficient and mutation-insensitive small-molecule drugs, antisense oligonucleotides, small interfering RNAs (siRNAs), CRISPR-Cas13 guide RNAs, and RT-PCR primers. LinearTurboFold is a general technique that can also be applied to other RNA viruses and full-length genome studies and will be a useful tool in fighting the current and future pandemics.

Genetic Regulatory Mechanisms of Smooth Muscle Cells Map to Coronary Artery Disease Risk Loci.

Coronary artery disease (CAD) is the leading cause of death globally. Genome-wide association studies (GWASs) have identified more than 95 independent loci that influence CAD risk, most of which reside in non-coding regions of the genome. To interpret these loci, we generated transcriptome and whole-genome datasets using human coronary artery smooth muscle cells (HCASMCs) from 52 unrelated donors, as well as epigenomic datasets using ATAC-seq on a subset of 8 donors. Through systematic comparison with publicly available datasets from GTEx and ENCODE projects, we identified transcriptomic, epigenetic, and genetic regulatory mechanisms specific to HCASMCs. We assessed the relevance of HCASMCs to CAD risk using transcriptomic and epigenomic level analyses. By jointly modeling eQTL and GWAS datasets, we identified five genes (SIPA1, TCF21, SMAD3, FES, and PDGFRA) that may modulate CAD risk through HCASMCs, all of which have relevant functional roles in vascular remodeling. Comparison with GTEx data suggests that SIPA1 and PDGFRA influence CAD risk predominantly through HCASMCs, while other annotated genes may have multiple cell and tissue targets. Together, these results provide tissue-specific and mechanistic insights into the regulation of a critical vascular cell type associated with CAD in human populations.

Coronary artery disease genes SMAD3 and TCF21 promote opposing interactive genetic programs that regulate smooth muscle cell differentiation and disease risk.

Although numerous genetic loci have been associated with coronary artery disease (CAD) with genome wide association studies, efforts are needed to identify the causal genes in these loci and link them into fundamental signaling pathways. Recent studies have investigated the disease mechanism of CAD associated gene SMAD3, a central transcription factor (TF) in the TGFß pathway, investigating its role in smooth muscle biology. In vitro studies in human coronary artery smooth muscle cells (HCASMC) revealed that SMAD3 modulates cellular phenotype, promoting expression of differentiation marker genes while inhibiting proliferation. RNA sequencing and chromatin immunoprecipitation sequencing studies in HCASMC identified downstream genes that reside in pathways which mediate vascular development and atherosclerosis processes in this cell type. HCASMC phenotype, and gene expression patterns promoted by SMAD3 were noted to have opposing direction of effect compared to another CAD associated TF, TCF21. At sites of SMAD3 and TCF21 colocalization on DNA, SMAD3 binding was inversely correlated with TCF21 binding, due in part to TCF21 locally blocking chromatin accessibility at the SMAD3 binding site. Further, TCF21 was able to directly inhibit SMAD3 activation of gene expression in transfection reporter gene studies. In contrast to TCF21 which is protective toward CAD, SMAD3 expression in HCASMC was shown to be directly correlated with disease risk. We propose that the pro-differentiation action of SMAD3 inhibits dedifferentiation that is required for HCASMC to expand and stabilize disease plaque as they respond to vascular stresses, counteracting the protective dedifferentiating activity of TCF21 and promoting disease risk.

Functional regulatory mechanism of smooth muscle cell-restricted LMOD1 coronary artery disease locus.

Recent genome-wide association studies (GWAS) have identified multiple new loci which appear to alter coronary artery disease (CAD) risk via arterial wall-specific mechanisms. One of the annotated genes encodes LMOD1 (Leiomodin 1), a member of the actin filament nucleator family that is highly enriched in smooth muscle-containing tissues such as the artery wall. However, it is still unknown whether LMOD1 is the causal gene at this locus and also how the associated variants alter LMOD1 expression/function and CAD risk. Using epigenomic profiling we recently identified a non-coding regulatory variant, rs34091558, which is in tight linkage disequilibrium (LD) with the lead CAD GWAS variant, rs2820315. Herein we demonstrate through expression quantitative trait loci (eQTL) and statistical fine-mapping in GTEx, STARNET, and human coronary artery smooth muscle cell (HCASMC) datasets, rs34091558 is the top regulatory variant for LMOD1 in vascular tissues. Position weight matrix (PWM) analyses identify the protective allele rs34091558-TA to form a conserved Forkhead box O3 (FOXO3) binding motif, which is disrupted by the risk allele rs34091558-A. FOXO3 chromatin immunoprecipitation and reporter assays show reduced FOXO3 binding and LMOD1 transcriptional activity by the risk allele, consistent with effects of FOXO3 downregulation on LMOD1. LMOD1 knockdown results in increased proliferation and migration and decreased cell contraction in HCASMC, and immunostaining in atherosclerotic lesions in the SMC lineage tracing reporter mouse support a key role for LMOD1 in maintaining the differentiated SMC phenotype. These results provide compelling functional evidence that genetic variation is associated with dysregulated LMOD1 expression/function in SMCs, together contributing to the heritable risk for CAD.

ParaMed: a parallel corpus for English-Chinese translation in the biomedical domain.

BACKGROUND: Biomedical language translation requires multi-lingual fluency as well as relevant domain knowledge. Such requirements make it challenging to train qualified translators and costly to generate high-quality translations. Machine translation represents an effective alternative, but accurate machine translation requires large amounts of in-domain data. While such datasets are abundant in general domains, they are less accessible in the biomedical domain. Chinese and English are two of the most widely spoken languages, yet to our knowledge, a parallel corpus does not exist for this language pair in the biomedical domain. DESCRIPTION: We developed an effective pipeline to acquire and process an English-Chinese parallel corpus from the New England Journal of Medicine (NEJM). This corpus consists of about 100,000 sentence pairs and 3,000,000 tokens on each side. We showed that training on out-of-domain data and fine-tuning with as few as 4000 NEJM sentence pairs improve translation quality by 25.3 (13.4) BLEU for en[Formula: see text]zh (zh[Formula: see text]en) directions. Translation quality continues to improve at a slower pace on larger in-domain data subsets, with a total increase of 33.0 (24.3) BLEU for en[Formula: see text]zh (zh[Formula: see text]en) directions on the full dataset. CONCLUSIONS: The code and data are available at https://github.com/boxiangliu/ParaMed .

Identifying causal variants and genes using functional genomics in specialized cell types and contexts.

A central goal in human genetics is the identification of variants and genes that influence the risk of polygenic diseases. In the past decade, genome-wide association studies (GWAS) have identified tens of thousands of genetic loci associated with various diseases. Since the majority of such loci lie within non-coding regions and have many candidate variants in linkage disequilibrium, it has been challenging to accurately identify specific causal variants and genes. To aid in their discovery a variety of statistical and experimental approaches have been developed. These approaches often borrow information from functional genomics assays such as ATAC-seq, ChIP-seq and RNA-seq to annotate functional variants and identify regulatory relationships between variants and genes. While such approaches are powerful, given the diversity of cell types and environments, it is paramount to select disease-relevant contexts for follow-up analyses. In this review, we discuss the latest developments, challenges, and best practices for determining the causal mechanisms of polygenic disease risk variants with functional genomics data from specialized cell types.

TCF21 and the environmental sensor aryl-hydrocarbon receptor cooperate to activate a pro-inflammatory gene expression program in coronary artery smooth muscle cells.

Both environmental factors and genetic loci have been associated with coronary artery disease (CAD), however gene-gene and gene-environment interactions that might identify molecular mechanisms of risk are not easily studied by human genetic approaches. We have previously identified the transcription factor TCF21 as the causal CAD gene at 6q23.2 and characterized its downstream transcriptional network that is enriched for CAD GWAS genes. Here we investigate the hypothesis that TCF21 interacts with a downstream target gene, the aryl hydrocarbon receptor (AHR), a ligand-activated transcription factor that mediates the cellular response to environmental contaminants, including dioxin and polycyclic aromatic hydrocarbons (e.g., tobacco smoke). Perturbation of TCF21 expression in human coronary artery smooth muscle cells (HCASMC) revealed that TCF21 promotes expression of AHR, its heterodimerization partner ARNT, and cooperates with these factors to upregulate a number of inflammatory downstream disease related genes including IL1A, MMP1, and CYP1A1. TCF21 was shown to bind in AHR, ARNT and downstream target gene loci, and co-localization was noted for AHR-ARNT and TCF21 binding sites genome-wide in regions of HCASMC open chromatin. These regions of co-localization were found to be enriched for GWAS signals associated with cardio-metabolic as well as chronic inflammatory disease phenotypes. Finally, we show that similar to TCF21, AHR gene expression is increased in atherosclerotic lesions in mice in vivo using laser capture microdissection, and AHR protein is localized in human carotid atherosclerotic lesions where it is associated with protein kinases with a critical role in innate immune response. These data suggest that TCF21 can cooperate with AHR to activate an inflammatory gene expression program that is exacerbated by environmental stimuli, and may contribute to the overall risk for CAD.

CoV-Seq, a New Tool for SARS-CoV-2 Genome Analysis and Visualization: Development and Usability Study.

BACKGROUND: COVID-19 became a global pandemic not long after its identification in late 2019. The genomes of SARS-CoV-2 are being rapidly sequenced and shared on public repositories. To keep up with these updates, scientists need to frequently refresh and reclean data sets, which is an ad hoc and labor-intensive process. Further, scientists with limited bioinformatics or programming knowledge may find it difficult to analyze SARS-CoV-2 genomes. OBJECTIVE: To address these challenges, we developed CoV-Seq, an integrated web server that enables simple and rapid analysis of SARS-CoV-2 genomes. METHODS: CoV-Seq is implemented in Python and JavaScript. The web server and source code URLs are provided in this article. RESULTS: Given a new sequence, CoV-Seq automatically predicts gene boundaries and identifies genetic variants, which are displayed in an interactive genome visualizer and are downloadable for further analysis. A command-line interface is available for high-throughput processing. In addition, we aggregated all publicly available SARS-CoV-2 sequences from the Global Initiative on Sharing Avian Influenza Data (GISAID), National Center for Biotechnology Information (NCBI), European Nucleotide Archive (ENA), and China National GeneBank (CNGB), and extracted genetic variants from these sequences for download and downstream analysis. The CoV-Seq database is updated weekly. CONCLUSIONS: We have developed CoV-Seq, an integrated web service for fast and easy analysis of custom SARS-CoV-2 sequences. The web server provides an interactive module for the analysis of custom sequences and a weekly updated database of genetic variants of all publicly accessible SARS-CoV-2 sequences. We believe CoV-Seq will help improve our understanding of the genetic underpinnings of COVID-19.

Clinical factors associated with mortality within three months after radiosurgery of asymptomatic brain metastases from non-small cell lung cancer.

PURPOSE: Routine brain MRI surveillance frequently diagnoses small, asymptomatic brain metastases from non-small cell lung cancer (NSCLC) that are effectively treated with stereotactic radiosurgery (SRS). A subset of patients, however, may die prior to the onset of symptoms. This study identifies clinical features that distinguish neurologically-asymptomatic NSCLC brain metastases patients that die prior to routine 3 month follow-up after SRS. METHODS: Retrospective chart review from 2007 to 2017 identified 18 patients with neurologically-asymptomatic NSCLC brain metastases who died < 3 months after SRS. Twenty-eight additional patients meeting criteria and surviving > 6 months after SRS were identified. Clinical factors were examined to determine characteristics correlated with survival using cox proportional hazards and nominal logistic regression models. Logistic regression models using salient factors were trained with 10-fold cross-validation and compared to the graded prognostic assessment (GPA) and score index of radiosurgery (SIR) using the AUC from receiver operant characteristic curves. RESULTS: The median survival following SRS was 1.4 and 9.2 months for the < 3 months and > 6 months groups, respectively. Age, number of brain metastases, and Karnofsky performance status were associated with overall survival while gender and interval between primary cancer and first brain metastasis diagnoses were associated with < 3 months and > 6 months survival, respectively. Models using GPA and SIR performed poorly compared to preliminary metrics generated in this study for prognosis of both < 3 months and > 6 months survival. CONCLUSION: Physicians require data to provide high-value, cost-conscious health care. Clinical metrics can screen patients with asymptomatic NSCLC brain metastases likely to die prior to the standard screening interval and observation could be considered.

KO tBu-Promoted C4 Selective Coupling Reaction of Phenols and [60]Fullerene: One-Pot Synthesis of 4-[60]Fullerephenols under Transition-Metal-Free Conditions.

A KO tBu-promoted direct coupling reaction of phenols and [60]fullerene was disclosed. The reaction occurs exclusively at the C4-position of phenols with high regioselectivity and provides an efficient and inexpensive manner to various 4-[60]fullerephenols in good yields. The electrochemical properties of the products render the method attractive and valuable.

Fenofibrate Recognition and Gq Protein Coupling Mechanisms of the Human Cannabinoid Receptor CB1.

The G-protein-coupled human cannabinoid receptor 1 (CB1) is a promising therapeutic target for pain management, inflammation, obesity, and substance abuse disorders. The structures of CB1-Gi complexes in synthetic agonist-bound forms have been resolved to date. However, the commercial drug recognition and Gq coupling mechanisms of CB1 remain elusive. Herein, the cryo-electron microscopy (cryo-EM) structure of CB1-Gq complex, in fenofibrate-bound form, at near-atomic resolution, is reported. The structure elucidates the delicate mechanisms of the precise fenofibrate recognition and Gq protein coupling by CB1 and will facilitate future drug discovery and design.

Quantification of escape from X chromosome inactivation with single-cell omics data reveals heterogeneity across cell types and tissues.

Several X-linked genes escape from X chromosome inactivation (XCI), while differences in escape across cell types and tissues are still poorly characterized. Here, we developed scLinaX for directly quantifying relative gene expression from the inactivated X chromosome with droplet-based single-cell RNA sequencing (scRNA-seq) data. The scLinaX and differentially expressed gene analyses with large-scale blood scRNA-seq datasets consistently identified the stronger escape in lymphocytes than in myeloid cells. An extension of scLinaX to a 10x multiome dataset (scLinaX-multi) suggested a stronger escape in lymphocytes than in myeloid cells at the chromatin-accessibility level. The scLinaX analysis of human multiple-organ scRNA-seq datasets also identified the relatively strong degree of escape from XCI in lymphoid tissues and lymphocytes. Finally, effect size comparisons of genome-wide association studies between sexes suggested the underlying impact of escape on the genotype-phenotype association. Overall, scLinaX and the quantified escape catalog identified the heterogeneity of escape across cell types and tissues.

Synthesis of vinyl-substituted alcohols using acetylene as a C2 building block.

Vinyl-substituted alcohols represent a highly useful class of molecular skeletons. The current method typically requires either stoichiometric metallic reagents or preformed precursors. Herein, we report a nickel catalysis-enabled synthesis of vinyl-substituted alcohols via a 5-membered oxa-metallacycle. In this protocol, acetylene, the simplest alkyne and abundant feedstock, is employed as an ideal C2 synthon. The reaction features mild conditions, good functional group tolerance and broad substrate scope. Mechanistic exploration implies that the oxa-metallacycle originated from the cyclometallation of aldehyde and acetylene is the key intermediate for this transformation, which is then terminated by a silane-mediated σ-bond metathesis and subsequent reductive elimination.

Correction: Synthesis of vinyl-substituted alcohols using acetylene as a C2 building block.

[This corrects the article DOI: 10.1039/D2SC06400F.].

Synthesis of E-Dienyl Esters Using Acetylene as C2 Synthon.

The stereoselective synthesis of dienyl esters with high atom- and step-economy has been largely unexplored. Herein, we report an efficient approach for the synthesis of E-dienyl esters via rhodium catalysis using carboxylic acid and acetylene as C2 synthon through the cascade of cyclometalation and C-O coupling. This protocol features mild conditions, excellent functional group tolerance, and exclusive E-stereoselectivity and utility in the late-stage modification of pharmaceuticals and natural products.

Molecular mechanisms of coronary artery disease risk at the PDGFD locus.

Platelet derived growth factor (PDGF) signaling has been extensively studied in the context of vascular disease, but the genetics of this pathway remain to be established. Genome wide association studies (GWAS) for coronary artery disease (CAD) have identified a risk locus at 11q22.3, and we have verified with fine mapping approaches that the regulatory variant rs2019090 and PDGFD represent the functional variant and putative functional gene. Further, FOXC1/C2 transcription factor (TF) binding at rs2019090 was found to promote PDGFD transcription through the CAD promoting allele. Employing a constitutive Pdgfd knockout allele along with SMC lineage tracing in a male atherosclerosis mouse model we mapped single cell transcriptomic, cell state, and lesion anatomical changes associated with gene loss. These studies revealed that Pdgfd promotes expansion, migration, and transition of SMC lineage cells to the chondromyocyte phenotype and vascular calcification. This is in contrast to protective CAD genes TCF21, ZEB2, and SMAD3 which we have shown to promote the fibroblast-like cell transition or perturb the pattern or extent of transition to the chondromyocyte phenotype. Further, Pdgfd expressing fibroblasts and pericytes exhibited greater expression of chemokines and leukocyte adhesion molecules, consistent with observed increased macrophage recruitment to the plaque. Despite these changes there was no effect of Pdgfd deletion on SMC contribution to the fibrous cap or overall lesion burden. These findings suggest that PDGFD mediates CAD risk through promoting SMC expansion and migration, in conjunction with deleterious phenotypic changes, and through promoting an inflammatory response that is primarily focused in the adventitia where it contributes to leukocyte trafficking to the diseased vessel wall.

Molecular mechanisms of coronary artery disease risk at the PDGFD locus.

Genome wide association studies for coronary artery disease (CAD) have identified a risk locus at 11q22.3. Here, we verify with mechanistic studies that rs2019090 and PDGFD represent the functional variant and gene at this locus. Further, FOXC1/C2 transcription factor binding at rs2019090 is shown to promote PDGFD transcription through the CAD promoting allele. With single cell transcriptomic and histology studies with Pdgfd knockdown in an SMC lineage tracing male atherosclerosis mouse model we find that Pdgfd promotes expansion, migration, and transition of SMC lineage cells to the chondromyocyte phenotype. Pdgfd also increases adventitial fibroblast and pericyte expression of chemokines and leukocyte adhesion molecules, which is linked to plaque macrophage recruitment. Despite these changes there is no effect of Pdgfd deletion on overall plaque burden. These findings suggest that PDGFD mediates CAD risk by promoting deleterious phenotypic changes in SMC, along with an inflammatory response that is primarily focused in the adventitia.

Cu-catalyzed carboboration of acetylene with Michael acceptors.

A copper-catalyzed three-component carboboration of acetylene with B2Pin2 and Michael acceptors is reported. In this reaction, a cheap and abundant C2 chemical feedstock, acetylene, was used as a starting material to afford cis-alkenyl boronates bearing a homoallylic carbonyl group. The reaction was robust and could be reliably performed on the molar scale. Furthermore, the resulting cis-alkenyl boronates could be converted to diverse functionalized molecules with ease.

Migratory insertion of copper-allenylidene from propargyl ester.

The highly efficient copper-catalyzed homo-dimerization and cross-coupling of propargyl esters have been developed. Various 1-en-3,5-diynes, [5]cumulenes and 1,3-diynes were successfully furnished via the copper-allenylidene intermediates with moderate to excellent yields. Migratory insertion is proposed as the key step to achieve the selectivity at the carbene carbon of the copper-allenylidene.