Biology subjects

Ernst, J.

Publications and source records attributed to Ernst, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

Circularization of rv0678 for genotypic bedaquiline resistance testing of Mycobacterium tuberculosis

Circular DNA offers benefits over linear DNA in diagnostic and field assays, but currently, circular DNA generation is lengthy, inefficient, highly dependent on the length and sequence of DNA, and can result in unwanted chimeras. We present streamlined methods for generating PCR-targeted circular DNA from a 700bp amplicon of rv0678, the high GC content (65%) gene implicated in Mycobacterium tuberculosis bedaquiline resistance, and demonstrate that these methods work as desired. We employ self-circularization with and without splints, a Gibson cloning-based approach, and novel two novel methods for generating pseudocircular DNA. The circular DNA can be used as a template for rolling circle PCR followed by long-read sequencing, allowing for the error correction of sequence data, and improving the confidence in the drug resistance determination and strain identification; and ultimately improving patient treatment.

molecular biology↗

bioRxiv2022

Chromatin state modeling across individuals reveals global patterns of histone modifications

Epigenetic mapping studies across individuals have identified many positions of epigenetic variation in various human tissues and conditions. However the relationships between these positions, and in particular global patterns that recur in many regions of the genome remains understudied. In this study, we use a stacked chromatin state model to systematically learn global patterns of epigenetic variation across individuals and annotate the human genome based on them. We applied this framework to histone modification data across individuals in lymphoblastoid cell lines and across autism spectrum disorder cases and controls in prefrontal cortex tissue. We find that global patterns are correlated across multiple histone modifications and with gene expression. We used the global patterns as a framework to predict transregulators, identify trans-QTL, and study complex disease. The frameworks for identifying and analyzing global patterns of epigenetic variation are general and we expect will be useful in other systems.

bioinformatics↗

bioRxiv2022

ChromGene: Gene-Based Modeling of Epigenomic Data

BackgroundVarious computational approaches have been developed to annotate epigenomes on a per-position basis by modeling combinatorial and spatial patterns within epigenomic data. However, such annotations are less suitable for gene-based analyses, in which a single annotation for each gene is desired. ResultsTo address this, we developed ChromGene, which annotates genes based on the combinatorial and spatial patterns of multiple epigenomic marks across the gene body and flanking regions. Specifically, ChromGene models the epigenomics maps using a mixture of hidden Markov models learned de novo. Using ChromGene, we generated annotations for the human protein-coding genes for over 100 cell and tissue types. We characterize the different mixture components and their associated gene sets in terms of gene expression, constraint, and other gene annotations. We also characterize variation in ChromGene gene annotations across cell and tissue types. ConclusionsWe expect that the ChromGene method and provided annotations will be a useful resource for gene-based epigenomic analyses.

bioinformatics↗

bioRxiv2022

Bacterial strain-dependent dissociation of cell recruitment and cell-to-cell spread in early M. tuberculosis infection

In the initial stage of respiratory infection, Mycobacterium tuberculosis traverses from alveolar macrophages to phenotypically diverse monocyte-derived phagocytes and neutrophils in the lung parenchyma. Here, we compare the in vivo kinetics of early bacterial growth and cell-to-cell spread of two strains of M. tuberculosis: a lineage 2 strain, 4334, and the widely studied lineage 4 strain H37Rv. Using flow cytometry, live cell sorting of phenotypic subsets, and quantitation of bacteria in cells of the distinct subsets, we found that 4334 induces less leukocyte influx into the lungs but demonstrates earlier population expansion and cell-to-cell spread. The earlier spread of 4334 to recruited cells, including monocyte-derived dendritic cells, is accompanied by earlier and greater magnitude of CD4+ T cell activation. The results provide evidence that strain-specific differences in interactions with lung leukocytes can shape adaptive immune responses in vivo. IMPORTANCETuberculosis is a leading infectious disease killer world-wide and is caused by Mycobacterium tuberculosis. After exposure to M. tuberculosis, outcomes range from apparent elimination to active disease. Early innate immune responses may contribute to differences in outcomes, yet it is not known how bacterial strains alter the early dynamics of innate immune and T cell responses. We infected mice with distinct strains of M. tuberculosis and discovered striking differences in innate cellular recruitment, cell- to-cell spread of bacteria in the lungs, and kinetics of initiation of antigen-specific CD4 T cell responses. We also found that M. tuberculosis can spread beyond alveolar macrophages even before a large influx of inflammatory cells. These results provide evidence that distinct strains of M. tuberculosis can exhibit differential kinetics in cell-to- cell spread which is not directly linked to early recruitment of phagocytes but is subsequently linked to adaptive immune responses.

immunology↗

bioRxiv2022

A framework for summarizing chromatin state annotations within and identifying differential annotations across groups of samples

MotivationGenome-wide maps of epigenetic modifications are powerful resources for non-coding genome annotation. Maps of multiple epigenetics marks have been integrated into cell or tissue type-specific chromatin state annotations for many cell or tissue types. With the increasing availability of multiple chromatin state maps for biologically similar samples, there is a need for methods that can effectively summarize the information about chromatin state annotations within groups of samples and identify differences across groups of samples at a high resolution. ResultsWe developed CSREP, which takes as input chromatin state annotations for a group of samples and then probabilistically estimates the state at each genomic position and derives a representative chromatin state map for the group. CSREP uses an ensemble of multi-class logistic regression classifiers to predict the chromatin state assignment of each sample given the state maps from all other samples. The difference of CSREPs probability assignments for two groups can be used to identify genomic locations with differential chromatin state patterns. Using groups of chromatin state maps of a diverse set of cell and tissue types, we demonstrate the advantages of using CSREP to summarize chromatin state maps and identify biologically relevant differences between groups at a high resolution. Availability and implementationThe CSREP source code is openly available under http://github.com/ernstlab/csrep. Contact: jason.ernst@ucla.edu

bioinformatics↗

bioRxiv2021

Genome-wide DNA methylation and multi-omics study of human chondrocyte ontogeny and an epigenetic clock analysis of adult chondrocytes

Articular chondrocytes undergo functional changes and their regenerative potential declines with age. Although the molecular mechanisms guiding articular cartilage aging is poorly understood, DNA methylation is known to play a mechanistic role in aging. However, our understanding of DNA methylation in chondrocyte development across human ontogeny is limited. To better understand DNA methylome changes, methylation profiling was performed in human chondrocytes. This study reveals association between methylation of specific CpG sites and chondrocyte age. We also determined the putative binding targets of STAT3, a key age-patterned transcription factor in fetal chondrocytes and genetic ablation of STAT3 induced a global genomic hypermethylation. Moreover, an epigenetic clock built for adult human chondrocytes revealed that exposure of aged adult human chondrocytes to STAT3 agonist, decreased epigenetic age. Taken together, this work will serve as a foundation to understand development and aging of chondrocytes with a new perspective for development of rejuvenation agents for synovial joints.

molecular biology↗

bioRxiv2021

DNA Methylation Networks Underlying Mammalian Traits

Epigenetics has hitherto been studied and understood largely at the level of individual organisms. Here, we report a multi-faceted investigation of DNA methylation across 11,117 samples from 176 different species. We performed an unbiased clustering of individual cytosines into 55 modules and identified 31 modules related to primary traits including age, species lifespan, sex, adult species weight, tissue type and phylogenetic order. Analysis of the correlation between DNA methylation and species allowed us to construct phyloepigenetic trees for different tissues that parallel the phylogenetic tree. In addition, while some stable cytosines reflect phylogenetic signatures, others relate to age and lifespan, and in many cases responding to anti-aging interventions in mice such as caloric restriction and ablation of growth hormone receptors. Insights uncovered by this investigation have important implications for our understanding of the role of epigenetics in mammalian evolution, aging and lifespan.

evolutionary biology↗

bioRxiv2021

A mammalian methylation array for profiling methylation levels at conserved sequences

Infinium methylation arrays are not available for the vast majority of non-human mammals. Moreover, even if species-specific arrays were available, probe differences between them would confound cross-species comparisons. To address these challenges, we developed the mammalian methylation array, a single custom array that measures 36k CpGs that are well conserved across mammalian species. We designed a set of probes on the array that can tolerate specific cross-species mutations. We annotate the array in over 200 species and report CpG island status and chromatin states in select species. Calibration experiments demonstrate the high fidelity in humans, rats, and mice. The mammalian methylation array has several strengths: it applies to all mammalian species even those that have not yet been sequenced, it provides deep coverage of conserved cytosines facilitating the development epigenetic biomarkers, and it increases the probability that biological insights gained in one species will translate to others.

bioinformatics↗

bioRxiv2020

DNA methylation study of age and sex in baboons and four other primates

DNA methylation data have been successfully used to develop highly accurate estimators of age ("epigenetic clocks") in many mammalian species. With a view of extending such epigenetic clocks to all primate species, we analyzed DNA methylation profiles of 2400 tissues derived from 37 primate species including 11 haplorhine species (baboons, marmosets, vervets, rhesus macaque, chimpanzees, gorillas, orangutan, humans) and 26 strepsirrhine species (suborders Lemuriformes and Lorisiformes). From these we present here, pan-primate epigenetic clocks which are highly accurate for all primates including humans (age correlation R=0.98). We also carried out in-depth analysis of baboon DNA methylation profiles and generated five epigenetic clocks for baboons (Olive-yellow baboon hybrid), one of which, the pan-tissue epigenetic clock, was trained on seven tissue types (fetal cerebral cortex, adult cerebral cortex, cerebellum, adipose, heart, liver, and skeletal muscle) with ages ranging from late fetal life to 22.8 years of age. To facilitate translation of findings in baboons to humans, we further constructed two dual-species, human-baboon clocks. We also identified and present here, epigenetic predictors of sex that apply to all primate species. Low overlap can be observed between age- and sex-related CpGs. Overall, this study advances our understanding of conserved age- and sex-related epigenetic changes in primates, and provides biomarkers to study the aging of all primate species with the facility to readily translate any findings between primate species.

developmental biology↗

bioRxiv2020

Universal annotation of the human genome through integration of over a thousand epigenomic datasets

BackgroundGenome-wide maps of chromatin marks such as histone modifications and open chromatin sites provide valuable information for annotating the non-coding genome, including identifying regulatory elements. Computational approaches such as ChromHMM have been applied to discover and annotate chromatin states defined by combinatorial and spatial patterns of chromatin marks within the same cell type. An alternative stacked modeling approach was previously suggested, where chromatin states are defined jointly from datasets of multiple cell types to produce a single universal genome annotation based on all datasets. Despite its potential benefits for applications that are not specific to one cell type, such an approach was previously applied only for small-scale specialized purposes. Large-scale applications of stacked modeling have previously posed scalability challenges. ResultsUsing a version of ChromHMM enhanced for large-scale applications, we applied the stacked modeling approach to produce a universal chromatin state annotation of the human genome using over 1000 datasets from more than 100 cell types, with the learned model denoted as the full-stack model. The full-stack model states show distinct enrichments for external genomic annotations, which we used in characterizing each state. Compared to per-cell-type annotations, the full-stack annotations directly differentiate constitutive from cell type specific activity and is more predictive of locations of external genomic annotations. ConclusionsThe full-stack ChromHMM model provides a universal chromatin state annotation of the genome and a unified global view of over 1000 datasets. We expect this to be a useful resource that complements existing per-cell-type annotations for studying the non-coding human genome.

bioinformatics↗

bioRxiv2020

Epigenetic clock and methylation studies in the rhesus macaque

Methylation levels at specific CpG positions in the genome have been used to develop accurate estimators of chronological age in humans, mice, and other species. Although epigenetic clocks are generally species-specific, the principles underpinning them appear to be conserved at least across the mammalian class. This is exemplified by the successful development of epigenetic clocks for mice and several other mammalian species. Here, we describe epigenetic clocks for the rhesus macaque (Macaca mulatta), the most widely used nonhuman primate in biological research. Using a custom methylation array (HorvathMammalMethylChip40), we profiled n=281 tissue samples (blood, skin, adipose, kidney, liver, lung, muscle, and cerebral cortex). From these data, we generated five epigenetic clocks for macaques. These clocks differ with regards to applicability to different tissue types (pan-tissue, blood, skin), species (macaque only or both humans and macaques), and measure of age (chronological age versus relative age). Additionally, the age-based human-macaque clock exhibits a high age correlation (R=0.89) with the vervet monkey (Chlorocebus sabaeus), another Old World species. Four CpGs within the KLF14 promoter were consistently altered with age in four tissues (adipose, blood, cerebral cortex, skin). It is expected that the macaque clocks will reveal an epigenetic aging rate associated with a host of health conditions and thus lend themselves for identifying and validating anti-aging interventions.

developmental biology↗

bioRxiv2020

Epigenetic clock and methylation studies in vervet monkeys

DNA methylation-based biomarkers of aging have been developed for many mammals but not yet for the vervet monkey (Chlorocebus sabaeus), which is a valuable non-human primate model for biomedical studies. We generated novel DNA methylation data from vervet cerebral cortex, blood, and liver using highly conserved mammalian CpGs represented on a custom array (HorvathMammalMethylChip40). We present six DNA methylation-based estimators of age: vervet multi-tissue epigenetic clock and tissue-specific clocks for brain cortex, blood, and liver. In addition, two dual species clocks (human-vervet clocks) for measuring chronological age and relative age, respectively. Relative age was defined as ratio of chronological age to maximum lifespan to address the species differences in maximum lifespan. The high accuracy of the human-vervet clocks demonstrates that epigenetic aging processes are evolutionary conserved in primates. When applying these vervet clocks to tissue samples from another primate species, rhesus macaque, we observed high age correlations but strong offsets. We characterized CpGs that correlate significantly with age in the vervet. CpG probes hypermethylated with age across tissues were located near the targets of Polycomb proteins SUZ12 and EED, and genes possessing the trimethylated H3K27 mark in their promoters. The epigenetic clocks are expected to be useful for age estimation of wild-born animals and anti-aging studies in vervets.

developmental biology↗

bioRxiv2020

Learning a genome-wide score of human-mouse conservation at the functional genomics level

Identifying genomic regions with functional genomic properties that are conserved between human and mouse is an important challenge in the context of mouse model studies. To address this, we take a novel approach and learn a score of evidence of conservation at the functional genomics level by integrating large-scale information in a compendium of epigenomic, transcription factor binding, and transcriptomic data from human and mouse. The computational method we developed to do this, Learning Evidence of Conservation from Integrated Functional genomic annotations (LECIF), trains a neural network, which is then used to generate a genome-wide score in human and mouse. The resulting LECIF score highlights human and mouse regions with shared functional genomic properties and captures correspondence of biologically similar human and mouse annotations even though it was not explicitly given such information. LECIF will be a resource for mouse model studies.

bioinformatics↗

bioRxiv2020

Single-nucleotide conservation state annotation of SARS-CoV-2 genome

Given the global impact and severity of COVID-19, there is a pressing need for a better understanding of the SARS-CoV-2 genome and mutations. Multi-strain sequence alignments of coronaviruses (CoV) provide important information for interpreting the genome and its variation. We apply a comparative genomics method, ConsHMM, to the multi-strain alignments of CoV to annotate every base of the SARS-CoV-2 genome with conservation states based on sequence alignment patterns among CoV. The learned conservation states show distinct enrichment patterns for genes, protein domains, and other regions of interest. Certain states are strongly enriched or depleted of SARS-CoV-2 mutations, which can be used to predict potentially consequential mutations. We expect the conservation states to be a resource for interpreting the SARS-CoV-2 genome and mutations.

genomics↗

bioRxiv2020

ConsHMM Atlas: conservation state annotations for major genomes and human genetic variation

ConsHMM is a method recently introduced to annotate genomes into conservation states, which are defined based on the combinatorial and spatial patterns of which species align to and match a reference genome in a multi-species DNA sequence alignment. Previously, ConsHMM was only applied to a single genome for one multi-species sequence alignment. Here we apply ConsHMM to produce 22 additional genome annotations covering human and seven other organisms for a variety of multi-species alignments. Additionally, we have extended ConsHMM to generate allele specific annotations, which we used to produce conservation state annotations for every possible single nucleotide mutation in the human genome. Finally, we provide a web interface to interactively visualize parameters and annotation enrichments for ConsHMM models. These annotations and visualizations comprise the ConsHMM Atlas, which we expect will be a valuable resource for analyzing a variety of major genomes and genetic variation.

bioinformatics↗

bioRxiv2019

Identification and characterization of constrained non-exonic bases lacking predictive epigenomic and transcription factor binding annotations

Annotations of evolutionarily constraint provide important information for variant prioritization. Genome-wide maps of epigenomic marks and transcription factor binding provide complementary information for interpreting a subset of such prioritized variants. Here we developed the Constrained Non-Exonic Predictor (CNEP) to quantify the evidence of each base in the human genome being in a constrained non-exonic element from over 60,000 epigenomic and transcription factor binding features. We find that the CNEP score outperforms baseline and related existing scores at predicting constrained non-exonic bases from such data. However, a subset of such bases are still not well predicted by CNEP. We developed a complementary Conservation Signature Score by CNEP (CSS-CNEP) using conservation state and constrained element annotations that is predictive of those bases. Using human genetic variation, regulatory sequence motifs, mouse epigenomic data, and retrospectively considered additional human data we further characterize the nature of constrained non-exonic bases with low CNEP scores.

genomics↗

bioRxiv2019

An Integrative Approach for Fine-Mapping Chromatin Interactions

Chromatin interactions play an important role in genome architecture and regulation. The Hi-C assay generates such interactions maps genome-wide, but at relatively low resolutions (e.g., 5-25kb), which is substantially larger than the resolution of transcription factor binding sites or open chromatin sites that are potential sources of such interactions. To predict the sources of Hi-C identified interactions at a high resolution (e.g., 100bp), we developed a computational method that integrates ChIP-seq data of transcription factors and histone marks and DNase-seq data. Our method,{chi} -SCNN, uses this data to first train a Siamese Convolutional Neural Network (SCNN) to discriminate between called Hi-C interactions and non-interactions.{chi} -SCNN then predicts the high-resolution source of each Hi-C interaction using a feature attribution method. We show these predictions recover original Hi-C peaks after extending them to be coarser. We also show{chi} -SCNN predictions enrich for evolutionarily conserved bases, eQTLs, and CTCF motifs, supporting their biological significance.{chi} -SCNN provides an approach for analyzing important aspects of genome architecture and regulation at a higher resolution than previously possible.\n\n{chi}-SCNN software is available on GitHub (https://github.com/ernstlab/X-SCNN).

bioinformatics↗

bioRxiv2019

Dynamics of Mycobacterium tuberculosis Ag85B revealed by sensitive ELISA

Secretion of specific proteins contributes to pathogenesis and immune responses in tuberculosis and other bacterial infections, yet the kinetics of protein secretion and fate of secreted proteins in vivo are poorly understood. We generated new monoclonal antibodies that recognize the M. tuberculosis secreted protein, Ag85B, and used them to establish and characterize a sensitive ELISA to quantitate Ag85B in samples generated in vitro and in vivo. We found that nutritional or culture conditions had little impact on secretion of Ag85B, and that there is considerable variation in Ag85B secretion by distinct strains in the M. tuberculosis complex: compared with the commonly-used H37Rv strain (Lineage 4), M. africanum (Lineage 6) secretes less, and two strains from Lineage 2 secrete more Ag85B. We also used the ELISA to determine that the rate of secretion of Ag85B is 10-to 100-fold lower than that of proteins secreted by gram-negative and gram-positive bacteria, respectively. ELISA quantitation of Ag85B in lung homogenates of M. tuberculosis H37Rv-infected mice revealed that although Ag85B accumulates in the lungs as the bacterial population expands, the amount of Ag85B per bacterium decreases nearly 10,000-fold at later stages of infection, coincident with development of T cell responses and arrest of bacterial population growth. These results indicate that bacterial protein secretion in vivo is dynamic and regulated, and quantitation of secreted bacterial proteins can contribute to understanding pathogenesis and immunity in tuberculosis and other infections. ImportanceBacterial protein secretion contributes to host-pathogen interactions, yet the process and consequences of bacterial protein secretion during infection are poorly understood. We developed a sensitive ELISA to quantitate a protein (termed Ag85B) secreted by M. tuberculosis and used it to find that Ag85B secretion occurs with slower kinetics than for proteins secreted by gram positive and gram negative bacteria, and that accumulation of Ag85B in the lungs is markedly regulated as a function of the bacterial population density. Our results demonstrate that quantitation of bacterial proteins during infection can reveal novel insights into host-pathogen interactions.

microbiology↗