Differences in immune function and responses contribute to health- and life-span disparities between sexes. However, the role of sex in immune system aging is not well understood. Here, we ...characterize peripheral blood mononuclear cells from 172 healthy adults 22-93 years of age using ATAC-seq, RNA-seq, and flow cytometry. These data reveal a shared epigenomic signature of aging including declining naïve T cell and increasing monocyte and cytotoxic cell functions. These changes are greater in magnitude in men and accompanied by a male-specific decline in B-cell specific loci. Age-related epigenomic changes first spike around late-thirties with similar timing and magnitude between sexes, whereas the second spike is earlier and stronger in men. Unexpectedly, genomic differences between sexes increase after age 65, with men having higher innate and pro-inflammatory activity and lower adaptive activity. Impact of age and sex on immune phenotypes can be visualized at https://immune-aging.jax.org to provide insights into future studies.
Abstract
Advances in multiplex histology allow surveying millions of cells, dozens of cell types, and up to thousands of phenotypes within the spatial context of tissue sections. This leads to a ...combinatorial challenge in (a) summarizing the cellular and phenotypic architecture of tissues and (b) identifying phenotypes with interesting spatial architecture. To address this, we combine ideas from community ecology and machine learning into niche-phenotype mapping (NIPMAP). NIPMAP takes advantage of geometric constraints on local cellular composition imposed by the niche structure of tissues in order to automatically segment tissue sections into niches and their interfaces. Projecting phenotypes on niches and their interfaces identifies previously-reported and previously-unreported spatially-driven phenotypes, concisely summarizes the phenotypic architecture of tissues, and reveals fundamental properties of tissue architecture. NIPMAP is applicable to both protein and RNA multiplex histology of healthy and diseased tissue. An open-source R/Python package implements NIPMAP.
Cis-Regulatory elements (cis-REs) include promoters, enhancers, and insulators that regulate gene expression programs via binding of transcription factors. ATAC-seq technology effectively identifies ...active cis-REs in a given cell type (including from single cells) by mapping accessible chromatin at base-pair resolution. However, these maps are not immediately useful for inferring specific functions of cis-REs. For this purpose, we developed a deep learning framework (CoRE-ATAC) with novel data encoders that integrate DNA sequence (reference or personal genotypes) with ATAC-seq cut sites and read pileups. CoRE-ATAC was trained on 4 cell types (n = 6 samples/replicates) and accurately predicted known cis-RE functions from 7 cell types (n = 40 samples) that were not used in model training (mean average precision = 0.80, mean F1 score = 0.70). CoRE-ATAC enhancer predictions from 19 human islet samples coincided with genetically modulated gain/loss of enhancer activity, which was confirmed by massively parallel reporter assays (MPRAs). Finally, CoRE-ATAC effectively inferred cis-RE function from aggregate single nucleus ATAC-seq (snATAC) data from human blood-derived immune cells that overlapped with known functional annotations in sorted immune cells, which established the efficacy of these models to study cis-RE functions of rare cells without the need for cell sorting. ATAC-seq maps from primary human cells reveal individual- and cell-specific variation in cis-RE activity. CoRE-ATAC increases the functional resolution of these maps, a critical step for studying regulatory disruptions behind diseases.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Detecting multiplets in single nucleus (sn)ATAC-seq data is challenging due to data sparsity and limited dynamic range. AMULET (ATAC-seq MULtiplet Estimation Tool) enumerates regions with greater ...than two uniquely aligned reads across the genome to effectively detect multiplets. We evaluate the method by generating snATAC-seq data in the human blood and pancreatic islet samples. AMULET has high precision, estimated via donor-based multiplexing, and high recall, estimated via simulated multiplets, compared to alternatives and identifies multiplets most effectively when a certain read depth of 25K median valid reads per nucleus is achieved.
There is a need for prognostic markers which can predict the subset of patients who will not respond sufficiently to conservative management in non-muscle-invasive bladder carcinoma. We analyzed the ...association of clusterin (CLU) with clinicopathological factors.
Immunohistochemical CLU expression was investigated in paraffin-embedded archival tissues of initial transurethral resection specimens of 46 patients with non-muscle-invasive bladder carcinoma. The result was expressed as the proportion of the number of CLU-containing tumor cells to the total number of tumor cells detected in each slide and 'percent CLU expression' was calculated for each patient.
Of the 46 cases (35 male, 11 female), 18 were ≥ 65 years of age. CLU expression was significantly higher in male and elderly patients. Following the initial transurethral resection, 39 patients showed tumor recurrence, and progression was seen in 25 patients, of whom 17 progressed to muscle invasion during follow-up. Although there was no significant correlation between CLU expression and recurrence, significant correlation with overall progression and progression to muscle-invasive disease was observed in this cohort of patients (p = 0.001 and p = 0.014, respectively). Among the patients with progression to muscle invasion, 13 underwent radical cystectomy with pT2 tumor in 5 patients in the final pathology of surgical specimens and pT3 and higher in the remainder.
CLU immunoreactivity showed correlation with age, gender and progression, mainly progression to muscle invasion. Thus, CLU can be used as a molecular marker to predict the potential of progression to muscle-invasive disease in a particular tumor which in turn may prove useful in the decision-making process for early cystectomy without losing time with conservative management.
Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) is a simple and effective technique in genomic studies that shows the chromatin accessibility of the genome. The open regions of ...the genome play an important role in DNA replication and transcription. It has many practical applications such as nucleosome mapping, identifying regulatory elements, cancer research and immune system aging. With the development of the technology used, this technique is now applied at single cell level in the form of single nucleus ATAC-seq (snATAC-seq). Single cell level resolution helps further the possible implications of ATAC-seq by helping in detection of rare cell types that play roles in the regulatory networks. Like other single cell technologies, snATAC-seq suffers from the existence of doublet cells that occur when multiple cells are simultaneously captured and sequenced which confounds downstream analyses. A unique property of snATAC-seq data is that at a given loci in the genome there can be at most two overlapping reads, one from the maternal and other from the paternal chromosome. When a loci has more than 2 reads this can be due to doublets or alignment/sequencing errors. We propose a count-based method, DoubletDetector, that makes use of this property to detect doublets. It identifies doublets by counting the number of loci within the cell that has more than 2 ATAC-seq reads. It also finds the types of the cells that formed the doublets, to further help understand their nature. DoubletDetector achieved high recall near 90% for detecting simulated doublets in human PBMC and islet snATAC-seq samples. Artificial doublets were then traced back to their cells of origin with near 78% recall using a marker peak-based algorithm. DoubletDetector is the first method to effectively identify both homotypic and heterotypic doublets from snATAC-seq.
The aim of the present study was to compare the effects of artificial sweeteners (aspartame, saccharin, and sucralose) on rat brain. Twenty‐four adult male Sprague–Dawley rats were included in the ...study. The control group (n = 6) received regular tap water, whereas other groups received aspartame (3 mg/kg/day, n = 6,) or saccharin (3 mg/kg/day, n = 6) or sucralose (1.5 mg/kg/day, n = 6) in the drinking water. Following 6 weeks, the passive avoidance learning (PAL) test was performed to evaluate the neurobehavioral effects of sweeteners. The brains were assessed for lipid peroxides, neuron count, and Glial fibrillary acidic protein (GFAP) immunohistochemistry. Our results demonstrated that chronic intake of sweeteners significantly impaired PAL performance in all groups. Hippocampal CA1–CA3 areas revealed significantly lower neuronal count in aspartame and increased GFAP expression in all groups. Brain lipid peroxides were significantly higher in all groups. Our findings suggest that long‐term consumption of artificial sweeteners may have harmful effects on cognition and hippocampal integrity in rats.
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•COSMO-RS calculations performed over more than 36,000 ILs.•Experiments show a strong correlation between PS solubility and battery performance.•Machine learning models developed ...using experiment-guided target solubility limits.•XGBoost models successfully predict the PS solubility and IL properties.•ARM and feature importance analysis show that anion descriptors are more dominant.
The polysulfide (PS) shuttle mechanism (PSM) is one of the most significant challenges of lithium-sulfur (Li-S) batteries in achieving high capacity and cyclability. One way to minimize the shuttle effect is to limit the PS solubilities in the battery electrolyte. Ionic liquids (IL) are particularly suited as electrolyte solvents because of their tunable physical and chemical properties. In this work, thousands of ILs are screened to narrow down potentially viable candidates to be used as electrolytes in Li-S batteries. To that end, the COnductor-like Screening Model for Realistic Solvents (COSMO-RS) calculations are performed over more than 36,000 ILs. An extensive database containing PS solubilities and other relevant properties is constructed at 25 °C. First, the effectiveness of the COSMO-RS calculations is experimentally tested with six different ILs having a wide range of solubility and viscosity values; a strong correlation between the PS solubility and battery performance is obtained. After specifying the target limits for promising ILs using the experimental battery performance data, machine learning (ML) tools are used to predict and identify the relationship between IL properties and PS solubilities and structural and molecular descriptors of ILs. The extreme gradient boosting (XGBoost) method successfully predicts the solubility and property values. Association rule mining (ARM) and the feature importance analysis show that anion descriptors are more dominant, whereas cations have less impact on the solubilities and properties of ILs. Finally, the imidazolium and pyridinium ILs with bis_imide and borate anion groups are identified as the most promising ones.
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