Showing papers on "Gene expression published in 2022"

Ultra‐high sensitivity mass spectrometry quantifies single‐cell proteome changes upon perturbation

Abstract: Single-cell technologies are revolutionizing biology but are today mainly limited to imaging and deep sequencing. However, proteins are the main drivers of cellular function and in-depth characterization of individual cells by mass spectrometry (MS)-based proteomics would thus be highly valuable and complementary. Here, we develop a robust workflow combining miniaturized sample preparation, very low flow-rate chromatography, and a novel trapped ion mobility mass spectrometer, resulting in a more than 10-fold improved sensitivity. We precisely and robustly quantify proteomes and their changes in single, FACS-isolated cells. Arresting cells at defined stages of the cell cycle by drug treatment retrieves expected key regulators. Furthermore, it highlights potential novel ones and allows cell phase prediction. Comparing the variability in more than 430 single-cell proteomes to transcriptome data revealed a stable-core proteome despite perturbation, while the transcriptome appears stochastic. Our technology can readily be applied to ultra-high sensitivity analyses of tissue material, posttranslational modifications, and small molecule studies from small cell counts to gain unprecedented insights into cellular heterogeneity in health and disease.

Dissection of artifactual and confounding glial signatures by single-cell sequencing of mouse and human brain

Abstract: A key aspect of nearly all single-cell sequencing experiments is dissociation of intact tissues into single-cell suspensions. While many protocols have been optimized for optimal cell yield, they have often overlooked the effects that dissociation can have on ex vivo gene expression. Here, we demonstrate that use of enzymatic dissociation on brain tissue induces an aberrant ex vivo gene expression signature, most prominently in microglia, which is prevalent in published literature and can substantially confound downstream analyses. To address this issue, we present a rigorously validated protocol that preserves both in vivo transcriptional profiles and cell-type diversity and yield across tissue types and species. We also identify a similar signature in postmortem human brain single-nucleus RNA-sequencing datasets, and show that this signature is induced in freshly isolated human tissue by exposure to elevated temperatures ex vivo. Together, our results provide a methodological solution for preventing artifactual gene expression changes during fresh tissue digestion and a reference for future deeper analysis of the potential confounding states present in postmortem human samples.

Molecular signatures of antitumor neoantigen-reactive T cells from metastatic human cancers

Abstract: The accurate identification of antitumor T cell receptors (TCRs) represents a major challenge for the engineering of cell-based cancer immunotherapies. By mapping 55 neoantigen-specific TCR clonotypes (NeoTCRs) from 10 metastatic human tumors to their single-cell transcriptomes, we identified signatures of CD8+ and CD4+ neoantigen-reactive tumor-infiltrating lymphocytes (TILs). Neoantigen-specific TILs exhibited tumor-specific expansion with dysfunctional phenotypes, distinct from blood-emigrant bystanders and regulatory TILs. Prospective prediction and testing of 73 NeoTCR signature–derived clonotypes demonstrated that half of the tested TCRs recognized tumor antigens or autologous tumors. NeoTCR signatures identified TCRs that target driver neoantigens and nonmutated viral or tumor-associated antigens, suggesting a common metastatic TIL exhaustion program. NeoTCR signatures delineate the landscape of TILs across metastatic tumors, enabling successful TCR prediction based purely on TIL transcriptomic states for use in cancer immunotherapy. Description Shared states of tumor-specific T cells Adoptive cell therapy is a type of cancer immunotherapy in which an individual’s immune system is trained to eliminate their tumor. This process involves genetically engineering T cells, but it requires the challenging identification of T cell receptors (TCRs) that can recognize cancer-specific alterations. Lowery and Krishna examined TCRs from human metastatic tumors, including those of breast, melanoma, and colon origin. Using TCR and single-cell sequencing technology, the authors found a conserved phenotypic state common to known tumor mutation-specific T cells. Gene signatures were able to predict the tumor reactivity of TCRs from independent samples and discriminate them from bystander T cells. Such strategies may enable more streamlined identification of tumor-specific TCRs for patient immunotherapy. —PNK The transcriptomic landscape of tumor mutation–reactive T cells is elucidated for cancer immunotherapy

Facilitating In Situ Tumor Imaging with a Tetrahedral DNA Framework‐Enhanced Hybridization Chain Reaction Probe

Abstract: Rapid and efficient tools for early cancer detection have diagnostic and therapeutic value. Given that the DNA hairpin‐based hybridization chain reaction (HCR) is effective in detecting various biological targets, a tetrahedral framework DNA‐enhanced (TDN‐enhanced) HCR detection system (T‐probe system) is introduced for cancer‐related targets and its versatility is demonstrated by detecting intracellular target miRNA 21 and cellular membrane target nucleolin. Benefiting from the spatial confinement of the TDN, the T‐probe system demonstrates a high detection rate. It increases the reaction efficiency of nude hairpins in vitro while accurately and rapidly recognizing both membrane and intracellular cancer‐related targets in living cells. Furthermore, it exhibits superior fluorescence in vivo within 15 s of peripheral‐tumor injection and 10 min of tail‐vein injection. The T‐probe system efficiently and accurately images tumor‐related biomarkers in vitro and in vivo, thereby demonstrating great potential for clinical diagnosis and therapeutic applications.

Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19

Abstract: Abstract Dysregulated immune responses against the SARS-CoV-2 virus are instrumental in severe COVID-19. However, the immune signatures associated with immunopathology are poorly understood. Here we use multi-omics single-cell analysis to probe the dynamic immune responses in hospitalized patients with stable or progressive course of COVID-19, explore V(D)J repertoires, and assess the cellular effects of tocilizumab. Coordinated profiling of gene expression and cell lineage protein markers shows that S100A hi /HLA-DR lo classical monocytes and activated LAG-3 hi T cells are hallmarks of progressive disease and highlights the abnormal MHC-II/LAG-3 interaction on myeloid and T cells, respectively. We also find skewed T cell receptor repertories in expanded effector CD8 + clones, unmutated IGHG + B cell clones, and mutated B cell clones with stable somatic hypermutation frequency over time. In conclusion, our in-depth immune profiling reveals dyssynchrony of the innate and adaptive immune interaction in progressive COVID-19.

The immunoregulatory landscape of human tuberculosis granulomas

Abstract: Tuberculosis (TB) in humans is characterized by formation of immune-rich granulomas in infected tissues, the architecture and composition of which are thought to affect disease outcome. However, our understanding of the spatial relationships that control human granulomas is limited. Here, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) to image 37 proteins in tissues from patients with active TB. We constructed a comprehensive atlas that maps 19 cell subsets across 8 spatial microenvironments. This atlas shows an IFN-γ-depleted microenvironment enriched for TGF-β, regulatory T cells and IDO1+ PD-L1+ myeloid cells. In a further transcriptomic meta-analysis of peripheral blood from patients with TB, immunoregulatory trends mirror those identified by granuloma imaging. Notably, PD-L1 expression is associated with progression to active TB and treatment response. These data indicate that in TB granulomas, there are local spatially coordinated immunoregulatory programs with systemic manifestations that define active TB.

Young CSF restores oligodendrogenesis and memory in aged mice via Fgf17

Abstract: Recent understanding of how the systemic environment shapes the brain throughout life has led to numerous intervention strategies to slow brain ageing1-3. Cerebrospinal fluid (CSF) makes up the immediate environment of brain cells, providing them with nourishing compounds4,5. We discovered that infusing young CSF directly into aged brains improves memory function. Unbiased transcriptome analysis of the hippocampus identified oligodendrocytes to be most responsive to this rejuvenated CSF environment. We further showed that young CSF boosts oligodendrocyte progenitor cell (OPC) proliferation and differentiation in the aged hippocampus and in primary OPC cultures. Using SLAMseq to metabolically label nascent mRNA, we identified serum response factor (SRF), a transcription factor that drives actin cytoskeleton rearrangement, as a mediator of OPC proliferation following exposure to young CSF. With age, SRF expression decreases in hippocampal OPCs, and the pathway is induced by acute injection with young CSF. We screened for potential SRF activators in CSF and found that fibroblast growth factor 17 (Fgf17) infusion is sufficient to induce OPC proliferation and long-term memory consolidation in aged mice while Fgf17 blockade impairs cognition in young mice. These findings demonstrate the rejuvenating power of young CSF and identify Fgf17 as a key target to restore oligodendrocyte function in the ageing brain.

APOE4 impairs myelination via cholesterol dysregulation in oligodendrocytes

Abstract: APOE4 is the strongest genetic risk factor for Alzheimer’s disease1–3. However, the effects of APOE4 on the human brain are not fully understood, limiting opportunities to develop targeted therapeutics for individuals carrying APOE4 and other risk factors for Alzheimer’s disease4–8. Here, to gain more comprehensive insights into the impact of APOE4 on the human brain, we performed single-cell transcriptomics profiling of post-mortem human brains from APOE4 carriers compared with non-carriers. This revealed that APOE4 is associated with widespread gene expression changes across all cell types of the human brain. Consistent with the biological function of APOE2–6, APOE4 significantly altered signalling pathways associated with cholesterol homeostasis and transport. Confirming these findings with histological and lipidomic analysis of the post-mortem human brain, induced pluripotent stem-cell-derived cells and targeted-replacement mice, we show that cholesterol is aberrantly deposited in oligodendrocytes—myelinating cells that are responsible for insulating and promoting the electrical activity of neurons. We show that altered cholesterol localization in the APOE4 brain coincides with reduced myelination. Pharmacologically facilitating cholesterol transport increases axonal myelination and improves learning and memory in APOE4 mice. We provide a single-cell atlas describing the transcriptional effects of APOE4 on the aging human brain and establish a functional link between APOE4, cholesterol, myelination and memory, offering therapeutic opportunities for Alzheimer’s disease. APOE4 is associated with widespread gene expression changes across all cell types of the human brain, altered cholesterol homeostasis and transport signalling pathways, and decreased myelination in the brain.

Advances in mixed cell deconvolution enable quantification of cell types in spatial transcriptomic data

Abstract: Abstract Mapping cell types across a tissue is a central concern of spatial biology, but cell type abundance is difficult to extract from spatial gene expression data. We introduce SpatialDecon, an algorithm for quantifying cell populations defined by single cell sequencing within the regions of spatial gene expression studies. SpatialDecon incorporates several advancements in gene expression deconvolution. We propose an algorithm harnessing log-normal regression and modelling background, outperforming classical least-squares methods. We compile cell profile matrices for 75 tissue types. We identify genes whose minimal expression by cancer cells makes them suitable for immune deconvolution in tumors. Using lung tumors, we create a dataset for benchmarking deconvolution methods against marker proteins. SpatialDecon is a simple and flexible tool for mapping cell types in spatial gene expression studies. It obtains cell abundance estimates that are spatially resolved, granular, and paired with highly multiplexed gene expression data.

ICE-CBF-COR Signaling Cascade and Its Regulation in Plants Responding to Cold Stress

Abstract: Cold stress limits plant geographical distribution and influences plant growth, development, and yields. Plants as sessile organisms have evolved complex biochemical and physiological mechanisms to adapt to cold stress. These mechanisms are regulated by a series of transcription factors and proteins for efficient cold stress acclimation. It has been established that the ICE-CBF-COR signaling pathway in plants regulates how plants acclimatize to cold stress. Cold stress is perceived by receptor proteins, triggering signal transduction, and Inducer of CBF Expression (ICE) genes are activated and regulated, consequently upregulating the transcription and expression of the C-repeat Binding Factor (CBF) genes. The CBF protein binds to the C-repeat/Dehydration Responsive Element (CRT/DRE), a homeopathic element of the Cold Regulated genes (COR gene) promoter, activating their transcription. Transcriptional regulations and post-translational modifications regulate and modify these entities at different response levels by altering their expression or activities in the signaling cascade. These activities then lead to efficient cold stress tolerance. This paper contains a concise summary of the ICE-CBF-COR pathway elucidating on the cross interconnections with other repressors, inhibitors, and activators to induce cold stress acclimation in plants.

ChIP-Atlas 2021 update: a data-mining suite for exploring epigenomic landscapes by fully integrating ChIP-seq, ATAC-seq and Bisulfite-seq data

Abstract: Abstract ChIP-Atlas (https://chip-atlas.org) is a web service providing both GUI- and API-based data-mining tools to reveal the architecture of the transcription regulatory landscape. ChIP-Atlas is powered by comprehensively integrating all data sets from high-throughput ChIP-seq and DNase-seq, a method for profiling chromatin regions accessible to DNase. In this update, we further collected all the ATAC-seq and whole-genome bisulfite-seq data for six model organisms (human, mouse, rat, fruit fly, nematode, and budding yeast) with the latest genome assemblies. These together with ChIP-seq data can be visualized with the Peak Browser tool and a genome browser to explore the epigenomic landscape of a query genomic locus, such as its chromatin accessibility, DNA methylation status, and protein–genome interactions. This epigenomic landscape can also be characterized for multiple genes and genomic loci by querying with the Enrichment Analysis tool, which, for example, revealed that inflammatory bowel disease-associated SNPs are the most significantly hypo-methylated in neutrophils. Therefore, ChIP-Atlas provides a panoramic view of the whole epigenomic landscape. All datasets are free to download via either a simple button on the web page or an API.

Advances in mixed cell deconvolution enable quantification of cell types in spatial transcriptomic data

Abstract: Abstract Mapping cell types across a tissue is a central concern of spatial biology, but cell type abundance is difficult to extract from spatial gene expression data. We introduce SpatialDecon, an algorithm for quantifying cell populations defined by single cell sequencing within the regions of spatial gene expression studies. SpatialDecon incorporates several advancements in gene expression deconvolution. We propose an algorithm harnessing log-normal regression and modelling background, outperforming classical least-squares methods. We compile cell profile matrices for 75 tissue types. We identify genes whose minimal expression by cancer cells makes them suitable for immune deconvolution in tumors. Using lung tumors, we create a dataset for benchmarking deconvolution methods against marker proteins. SpatialDecon is a simple and flexible tool for mapping cell types in spatial gene expression studies. It obtains cell abundance estimates that are spatially resolved, granular, and paired with highly multiplexed gene expression data.

Meningioma DNA methylation groups identify biological drivers and therapeutic vulnerabilities

Abstract: Meningiomas are the most common primary intracranial tumors. There are no effective medical therapies for meningioma patients, and new treatments have been encumbered by limited understanding of meningioma biology. Here, we use DNA methylation profiling on 565 meningiomas integrated with genetic, transcriptomic, biochemical, proteomic and single-cell approaches to show meningiomas are composed of three DNA methylation groups with distinct clinical outcomes, biological drivers and therapeutic vulnerabilities. Merlin-intact meningiomas (34%) have the best outcomes and are distinguished by NF2/Merlin regulation of susceptibility to cytotoxic therapy. Immune-enriched meningiomas (38%) have intermediate outcomes and are distinguished by immune infiltration, HLA expression and lymphatic vessels. Hypermitotic meningiomas (28%) have the worst outcomes and are distinguished by convergent genetic and epigenetic mechanisms driving the cell cycle and resistance to cytotoxic therapy. To translate these findings into clinical practice, we show cytostatic cell cycle inhibitors attenuate meningioma growth in cell culture, organoids, xenografts and patients. DNA methylation profiling of 565 meningiomas highlights three groups associated with distinct molecular, clinical and therapeutic features.

Automated assembly scaffolding using RagTag elevates a new tomato system for high-throughput genome editing

Abstract: Abstract Advancing crop genomics requires efficient genetic systems enabled by high-quality personalized genome assemblies. Here, we introduce RagTag, a toolset for automating assembly scaffolding and patching, and we establish chromosome-scale reference genomes for the widely used tomato genotype M82 along with Sweet-100, a new rapid-cycling genotype that we developed to accelerate functional genomics and genome editing in tomato. This work outlines strategies to rapidly expand genetic systems and genomic resources in other plant species.

Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology

Abstract: Abstract Inferring single-cell compositions and their contributions to global gene expression changes from bulk RNA sequencing (RNA-seq) datasets is a major challenge in oncology. Here we develop Bayesian cell proportion reconstruction inferred using statistical marginalization (BayesPrism), a Bayesian method to predict cellular composition and gene expression in individual cell types from bulk RNA-seq, using patient-derived, scRNA-seq as prior information. We conduct integrative analyses in primary glioblastoma, head and neck squamous cell carcinoma and skin cutaneous melanoma to correlate cell type composition with clinical outcomes across tumor types, and explore spatial heterogeneity in malignant and nonmalignant cell states. We refine current cancer subtypes using gene expression annotation after exclusion of confounding nonmalignant cells. Finally, we identify genes whose expression in malignant cells correlates with macrophage infiltration, T cells, fibroblasts and endothelial cells across multiple tumor types. Our work introduces a new lens to accurately infer cellular composition and expression in large cohorts of bulk RNA-seq data.

Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies

Abstract: Pathogenic variants in genes that cause dilated cardiomyopathy (DCM) and arrhythmogenic cardiomyopathy (ACM) convey high risks for the development of heart failure through unknown mechanisms. Using single-nucleus RNA sequencing, we characterized the transcriptome of 880,000 nuclei from 18 control and 61 failing, nonischemic human hearts with pathogenic variants in DCM and ACM genes or idiopathic disease. We performed genotype-stratified analyses of the ventricular cell lineages and transcriptional states. The resultant DCM and ACM ventricular cell atlas demonstrated distinct right and left ventricular responses, highlighting genotype-associated pathways, intercellular interactions, and differential gene expression at single-cell resolution. Together, these data illuminate both shared and distinct cellular and molecular architectures of human heart failure and suggest candidate therapeutic targets. Description A close-up look at cardiomyopathies Cardiomyopathies are diseases of the heart muscle that interfere with its ability to pump blood effectively and can result in heart failure. They are divided into different categories based on the clinical presentation. Reichart et al. performed single-nucleus RNA sequencing on heart samples from patients with cardiomyopathies with or without known genetic causes, as well as samples from controls without structural heart disease. The authors identified key cell types and their locations in the heart, cellular interactions, and biological signaling pathways, offering insights into the biology of the heart in healthy and diseased states. —YN A single-cell atlas of the heart identifies cellular interactions and pathways involved in two types of cardiomyopathy. INTRODUCTION Human heart failure is a highly morbid condition that affects 23 million individuals worldwide. It emerges in the setting of an array of different cardiovascular disorders, which has propelled the notion that diverse stimuli converge on a common final pathway. Consistent with this, initiating etiologies do not direct heart failure treatments, which are often inadequate and necessitate mechanical interventions and cardiac transplantation. The recent application of single-nucleus RNA sequencing (snRNAseq) transcriptional analyses to characterize the cellular composition and molecular states in the healthy adult human heart provides an emerging benchmark by which disease-related changes can be assessed. Moreover, the discovery of human pathogenic variants that cause dilated cardiomyopathy (DCM) and arrhythmogenic cardiomyopathy (ACM), disorders associated with high rates of heart failure, provides direct opportunities to evaluate whether genotype influences heart failure pathways. RATIONALE A systematic identification of shared and distinct molecules and pathways involved in heart failure is lacking, and knowledge of these fundamental data could propel the development of more effective treatments. To enable these discoveries, we performed snRNAseq of explanted ventricular tissues from 18 healthy donors and 61 heart failure patients. By focusing analyses on multiple samples with pathogenic variants in DCM genes (LMNA, RBM20, and TTN), ACM genes (PKP2), or pathogenic variant–negative (PV negative) samples, we characterized genotype-stratified and common heart failure responses. RESULTS From 881,081 nuclei isolated from left and right diseased and healthy ventricles, we identified 10 major cell types and 71 distinct transcriptional states. DCM and ACM tissues showed significant depletion of cardiomyocytes and increased endothelial and immune cells. Fibrosis was expanded in disease hearts, but, unexpectedly, fibroblasts were not increased, and instead showed altered transcriptional states that indicated activated remodeling of the extracellular matrix. Genotype-stratified analyses identified multiple transcriptional changes shared only among the hearts harboring pathogenic variants or distinctive for individual and subsets of DCM and ACM genotypes. We validated many of these by single-molecule fluorescent in situ hybridization. Through analyses of receptor and ligand expression across all cells, we observed changes in intercellular signaling and communications, such as increased endothelin signaling in LMNA hearts, tumor necrosis factor in PKP2 hearts, and others. We also identified specific cardiac cell lineages expressing genes with common polymorphisms that were identified in validated association studies of DCM. Because our findings indicated genotype-enriched transcripts and cell states, we harnessed machine learning to develop a graph attention network for the multinomial classification of genotypes. This network showed remarkably high prediction of the genotypes for each cardiac sample, thereby reinforcing our conclusion that genotypes activate very specific heart failure pathways. CONCLUSION snRNAseq of human ventricular samples illuminated cell types and states, molecular signals, and intercellular communications that characterize DCM and ACM. The cellular and molecular architectures that induce heart failure are both shared and distinct across genotypes. These data provide candidate therapeutic targets for future research and interventional opportunities to improve and personalize treatments for cardiomyopathies and heart failure. Genotype-stratified analyses of heart failure at the single-nuclei level. The transcriptomes of 881,081 nuclei from 61 heart failure patients were profiled and compared with the transcriptional signatures of 18 healthy controls. Genotype-stratified analyses of cell types and cell state compositions, differential gene expression, cell-cell interactions, and machine learning illuminated the shared and distinct transcriptional signatures resulting from pathogenic variants in DCM and ACM.

Inflammation and Brain Structure in Schizophrenia and Other Neuropsychiatric Disorders

Abstract: Key Points Question Is there evidence for a potential relationship between inflammation and brain structure, and is this relevant for schizophrenia and other neuropsychiatric disorders? Findings In this mendelian randomization study including 20 688 participants in the UK Biobank, genetically predicted levels of interleukin 6 were associated with gray matter volume and cortical thickness primarily in the middle temporal gyrus and superior frontal region. The middle temporal gyrus overexpressed a number of genes relevant to interleukin 6 pathway proteins and neuropsychiatric disorder ontologies, including schizophrenia and autism spectrum disorder. Meaning This study found that inflammation may be associated with brain structure and may be an early predeterminant of neuropsychiatric conditions, which has important implications for identification of risk and novel treatments.

Compatibility rules of human enhancer and promoter sequences

Abstract: Gene regulation in the human genome is controlled by distal enhancers that activate specific nearby promoters1. A proposed model for this specificity is that promoters have sequence-encoded preferences for certain enhancers, for example, mediated by interacting sets of transcription factors or cofactors2. This ‘biochemical compatibility’ model has been supported by observations at individual human promoters and by genome-wide measurements in Drosophila3–9. However, the degree to which human enhancers and promoters are intrinsically compatible has not yet been systematically measured, and how their activities combine to control RNA expression remains unclear. Here we design a high-throughput reporter assay called enhancer × promoter self-transcribing active regulatory region sequencing (ExP STARR-seq) and applied it to examine the combinatorial compatibilities of 1,000 enhancer and 1,000 promoter sequences in human K562 cells. We identify simple rules for enhancer–promoter compatibility, whereby most enhancers activate all promoters by similar amounts, and intrinsic enhancer and promoter activities multiplicatively combine to determine RNA output (R2 = 0.82). In addition, two classes of enhancers and promoters show subtle preferential effects. Promoters of housekeeping genes contain built-in activating motifs for factors such as GABPA and YY1, which decrease the responsiveness of promoters to distal enhancers. Promoters of variably expressed genes lack these motifs and show stronger responsiveness to enhancers. Together, this systematic assessment of enhancer–promoter compatibility suggests a multiplicative model tuned by enhancer and promoter class to control gene transcription in the human genome. A new high-throughput assay applied to 1,000 enhancers and 1,000 promoters in human cells reveals how different classes of enhancers and promoters control RNA expression.

Sequence determinants of human gene regulatory elements

Abstract: DNA can determine where and when genes are expressed, but the full set of sequence determinants that control gene expression is unknown. Here, we measured the transcriptional activity of DNA sequences that represent an ~100 times larger sequence space than the human genome using massively parallel reporter assays (MPRAs). Machine learning models revealed that transcription factors (TFs) generally act in an additive manner with weak grammar and that most enhancers increase expression from a promoter by a mechanism that does not appear to involve specific TF-TF interactions. The enhancers themselves can be classified into three types: classical, closed chromatin and chromatin dependent. We also show that few TFs are strongly active in a cell, with most activities being similar between cell types. Individual TFs can have multiple gene regulatory activities, including chromatin opening and enhancing, promoting and determining transcription start site (TSS) activity, consistent with the view that the TF binding motif is the key atomic unit of gene expression.

A computational solution for bolstering reliability of epigenetic clocks: implications for clinical trials and longitudinal tracking

Abstract: Epigenetic clocks are widely used aging biomarkers calculated from DNA methylation data, but this data can be surprisingly unreliable. Here we show that technical noise produces deviations up to 9 years between replicates for six prominent epigenetic clocks, limiting their utility. We present a computational solution to bolster reliability, calculating principal components (PCs) from CpG-level data as input for biological age prediction. Our retrained PC versions of six clocks show agreement between most replicates within 1.5 years, improved detection of clock associations and intervention effects, and reliable longitudinal trajectories in vivo and in vitro. This method entails only one additional step compared to traditional clocks, requires no replicates or previous knowledge of CpG reliabilities for training, and can be applied to any existing or future epigenetic biomarker. The high reliability of PC-based clocks is critical for applications to personalized medicine, longitudinal tracking, in vitro studies and clinical trials of aging interventions. Epigenetic clocks are widely used aging biomarkers, but their utility is limited by technical noise. The authors report a method for producing high-reliability clocks for applications such as longitudinal studies and intervention trials.

Critical assessment of DNA adenine methylation in eukaryotes using quantitative deconvolution

Abstract: The discovery of N6-methyldeoxyadenine (6mA) across eukaryotes led to a search for additional epigenetic mechanisms. However, some studies have highlighted confounding factors that challenge the prevalence of 6mA in eukaryotes. We developed a metagenomic method to quantitatively deconvolve 6mA events from a genomic DNA sample into species of interest, genomic regions, and sources of contamination. Applying this method, we observed high-resolution 6mA deposition in two protozoa. We found that commensal or soil bacteria explained the vast majority of 6mA in insect and plant samples. We found no evidence of high abundance of 6mA in Drosophila, Arabidopsis, or humans. Plasmids used for genetic manipulation, even those from Dam methyltransferase mutant Escherichia coli, could carry abundant 6mA, confounding the evaluation of candidate 6mA methyltransferases and demethylases. On the basis of this work, we advocate for a reassessment of 6mA in eukaryotes. Description Reassessment of DNA 6mA in eukaryotes Certain forms of chemical modifications to DNA play important roles across the kingdoms of life; some forms have been widely studied and others are relatively new. DNA N6-methyldeoxyadenosine (6mA), which was recently reported to be prevalent across eukaryotes, created excitement for a new dimension to study biology and diseases. However, some studies have highlighted confounding factors, and there is an active debate over 6mA in eukaryotes. Kong et al. describe a method for quantitative 6mA deconvolution and report that bacterial contamination explains the vast majority of 6mA in DNA samples from insects and plants; the method also found no evidence for high 6mA levels in humans (see the Perspective by Boulias and Greer). This work advocates for a reassessment of 6mA in eukaryotes and provides an actionable approach. —DJ A metagenomic method called 6mASCOPE is developed to help clarify how limited DNA adenine methylation may be in eukaryotes.

An aluminum hydroxide:CpG adjuvant enhances protection elicited by a SARS-CoV-2 receptor binding domain vaccine in aged mice

Abstract: Global deployment of vaccines that can provide protection across several age groups is still urgently needed to end the COVID-19 pandemic, especially in low- and middle-income countries. Although vaccines against SARS-CoV-2 based on mRNA and adenoviral vector technologies have been rapidly developed, additional practical and scalable SARS-CoV-2 vaccines are required to meet global demand. Protein subunit vaccines formulated with appropriate adjuvants represent an approach to address this urgent need. The receptor binding domain (RBD) is a key target of SARS-CoV-2 neutralizing antibodies but is poorly immunogenic. We therefore compared pattern recognition receptor (PRR) agonists alone or formulated with aluminum hydroxide (AH) and benchmarked them against AS01B and AS03-like emulsion-based adjuvants for their potential to enhance RBD immunogenicity in young and aged mice. We found that an AH and CpG adjuvant formulation (AH:CpG) produced an 80-fold increase in anti-RBD neutralizing antibody titers in both age groups relative to AH alone and protected aged mice from the SARS-CoV-2 challenge. The AH:CpG-adjuvanted RBD vaccine elicited neutralizing antibodies against both wild-type SARS-CoV-2 and the B.1.351 (beta) variant at serum concentrations comparable to those induced by the licensed Pfizer-BioNTech BNT162b2 mRNA vaccine. AH:CpG induced similar cytokine and chemokine gene enrichment patterns in the draining lymph nodes of both young adult and aged mice and enhanced cytokine and chemokine production in human mononuclear cells of younger and older adults. These data support further development of AH:CpG-adjuvanted RBD as an affordable vaccine that may be effective across multiple age groups.

Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders

Abstract: To date, most expression quantitative trait loci (eQTL) studies, which investigate how genetic variants contribute to gene expression, have been performed in heterogeneous brain tissues rather than specific cell types. In this study, we performed an eQTL analysis using single-nuclei RNA sequencing from 192 individuals in eight brain cell types derived from the prefrontal cortex, temporal cortex and white matter. We identified 7,607 eGenes, a substantial fraction (46%, 3,537/7,607) of which show cell-type-specific effects, with strongest effects in microglia. Cell-type-level eQTLs affected more constrained genes and had larger effect sizes than tissue-level eQTLs. Integration of brain cell type eQTLs with genome-wide association studies (GWAS) revealed novel relationships between expression and disease risk for neuropsychiatric and neurodegenerative diseases. For most GWAS loci, a single gene co-localized in a single cell type, providing new clues into disease etiology. Our findings demonstrate substantial contrast in genetic regulation of gene expression among brain cell types and reveal potential mechanisms by which disease risk genes influence brain disorders. Bryois et al. mapped genetic variants regulating gene expression in eight major brain cell types. They found a large number of cell-type-specific genetic effects and leveraged their results to identify novel putative risk genes for brain disorders.

Insights into N6-methyladenosine and programmed cell death in cancer

Abstract: N6-methyladenosine (m6A) methylation, the most common form of internal RNA modification in eukaryotes, has gained increasing attention and become a hot research topic in recent years. M6A plays multifunctional roles in normal and abnormal biological processes, and its role may vary greatly depending on the position of the m6A motif. Programmed cell death (PCD) includes apoptosis, autophagy, pyroptosis, necroptosis and ferroptosis, most of which involve the breakdown of the plasma membrane. Based on the implications of m6A methylation on PCD, the regulators and functional roles of m6A methylation were comprehensively studied and reported. In this review, we focus on the high-complexity links between m6A and different types of PCD pathways, which are then closely associated with the initiation, progression and resistance of cancer. Herein, clarifying the relationship between m6A and PCD is of great significance to provide novel strategies for cancer treatment, and has a great potential prospect of clinical application.