Epigenetic marks such as DNA methylation have generated great interest in the study of human disease. However, studies of DNA methylation have not established population-epigenetics principles to ...guide design, efficient statistics, or interpretation. Here, we show that the clustering of correlated DNA methylation at CpGs was similar to that of linkage-disequilibrium (LD) correlation in genetic SNP variation but for much shorter distances. Some clustering of methylated CpGs appeared to be genetically driven. Further, a set of correlated methylated CpGs related to a single SNP-based LD block was not always physically contiguous—segments of uncorrelated methylation as long as 300 kb could be interspersed in the cluster. Thus, we denoted these sets of correlated CpGs as GeMes, defined as potentially noncontiguous methylation clusters under the control of one or more methylation quantitative trait loci. This type of correlated methylation structure has implications for both biological functions of DNA methylation and for the design, analysis, and interpretation of epigenome-wide association studies.
Community-wide mass antibiotic treatment is a central component of trachoma control. The optimum frequency and duration of treatment are unknown. We measured the effect of mass treatment on the ...conjunctival burden of Chlamydia trachomatis in a Gambian community with low to medium trachoma prevalence and investigated the rate, route, and determinants of re-emergent infection.
14 trachoma-endemic villages in rural Gambia were examined and conjunctival swabs obtained at baseline, 2, 6, 12, and 17 months. Mass antibiotic treatment with azithromycin was given to the community at baseline. C trachomatis was detected by qualitative PCR and individual infection load then estimated by real-time quantitative PCR.
C trachomatis was detected in 95 (7%) of 1319 individuals at baseline. Treatment coverage was 83% of the population (1328 of 1595 people). The effect of mass treatment was heterogeneous. In 12 villages all baseline infections (34 3% of 1062 individuals) resolved, and prevalence (three 0·3%) and infection load remained low throughout the study. Two villages (baseline infection: 61 24% of 257 individuals) had increased infection 2 months after treatment (74 30%), after extensive contact with other untreated communities. Subsequently, this value reduced to less than half of that before treatment (25 11%).
Mass antibiotic treatment generally results in effective, longlasting control of C trachomatis in this environment. For low prevalence regions, one treatment episode might be sufficient. Infection can be reintroduced through contact with untreated populations. Communities need to be monitored for treatment failure and control measures implemented over wide geographical areas.
The epigenome consists of non-sequence-based modifications, such as DNA methylation, that are heritable during cell division and that may affect normal phenotypes and predisposition to disease. Here, ...we have performed an unbiased genome-scale analysis of ~4 million CpG sites in 74 individuals with comprehensive array-based relative methylation (CHARM) analysis. We found 227 regions that showed extreme interindividual variability variably methylated regions (VMRs) across the genome, which are enriched for developmental genes based on Gene Ontology analysis. Furthermore, half of these VMRs were stable within individuals over an average of 11 years, and these VMRs defined a personalized epigenomic signature. Four of these VMRs showed covariation with body mass index consistently at two study visits and were located in or near genes previously implicated in regulating body weight or diabetes. This work suggests an epigenetic strategy for identifying patients at risk of common disease.
Antibiotic-resistant Gram-negative bacteraemias (GNB) are increasing in incidence. We aimed to investigate the impact of empirical antibiotic therapy on clinical outcomes by carrying out an ...observational 6-year cohort study of patients at a teaching hospital with community-onset Escherichia coli bacteraemia (ECB), Klebsiella pneumoniae bacteraemia (KPB) and Pseudomonas aeruginosa bacteraemia (PsAB). Antibiotic therapy was considered concordant if the organism was sensitive in vitro and discordant if resistant. We estimated the association between concordant vs. discordant empirical antibiotic therapy on odds of in-hospital death and ICU admission for KPB and ECB. Of 1380 patients, 1103 (79.9%) had ECB, 189 (13.7%) KPB and 88 (6.4%) PsAB. Discordant therapy was not associated with increased odds of either outcome. For ECB, severe illness and non-urinary source were associated with increased odds of both outcomes (OR of in-hospital death for non-urinary source 3.21, 95% CI 1.73–5.97). For KPB, discordant therapy was associated with in-hospital death on univariable but not multivariable analysis. Illness severity was associated with increased odds of both outcomes. These findings suggest broadening of therapy for low-risk patients with community-onset GNB is not warranted. Future research should focus on the relationship between patient outcomes, clinical factors, infection focus and causative organism and resistance profile.
Normalization has been recognized as a necessary preprocessing step in a variety of high-throughput biotechnologies. A number of normalization methods have been developed specifically for ...microarrays, some general and others tailored for certain experimental designs. All methods rely on assumptions about data characteristics that are expected to stay constant across samples, although some make it more explicit than others. Most methods make assumptions that certain quantities related to the biological signal of interest stay the same; this is reasonable for many experiments but usually not verifiable. Recently, several platforms have begun to include a large number of negative control probes that nonetheless cover nearly the entire range of the measured signal intensity. Using these probes as a normalization basis makes it possible to normalize without making assumptions about the behavior of the biological signal. We present a subset quantile normalization (SQN) procedure that normalizes based on the distribution of non-specific control features, without restriction on the behavior of specific signals. We illustrate the performance of this method using three different platforms and experimental settings. Compared to two other leading nonlinear normalization procedures, the SQN method preserves more biological variation after normalization while reducing the noise observed on control features. Although the illustration datasets are from microarray experiments, this method is general for all high throughput technologies that include a large set of control features that have constant expectations across samples. It does not require an equal number of features in all samples and tolerates missing data.
DNA methylation is a key regulator of gene function in a multitude of both normal and abnormal biological processes, but tools to elucidate its roles on a genome-wide scale are still in their ...infancy. Methylation sensitive restriction enzymes and microarrays provide a potential high-throughput, low-cost platform to allow methylation profiling. However, accurate absolute methylation estimates have been elusive due to systematic errors and unwanted variability. Previous microarray preprocessing procedures, mostly developed for expression arrays, fail to adequately normalize methylation-related data since they rely on key assumptions that are violated in the case of DNA methylation. We develop a normalization strategy tailored to DNA methylation data and an empirical Bayes percentage methylation estimator that together yield accurate absolute methylation estimates that can be compared across samples. We illustrate the method on data generated to detect methylation differences between tissues and between normal and tumor colon samples.
Human hematopoiesis involves cellular differentiation of multipotent cells into progressively more lineage-restricted states. While the chromatin accessibility landscape of this process has been ...explored in defined populations, single-cell regulatory variation has been hidden by ensemble averaging. We collected single-cell chromatin accessibility profiles across 10 populations of immunophenotypically defined human hematopoietic cell types and constructed a chromatin accessibility landscape of human hematopoiesis to characterize differentiation trajectories. We find variation consistent with lineage bias toward different developmental branches in multipotent cell types. We observe heterogeneity within common myeloid progenitors (CMPs) and granulocyte-macrophage progenitors (GMPs) and develop a strategy to partition GMPs along their differentiation trajectory. Furthermore, we integrated single-cell RNA sequencing (scRNA-seq) data to associate transcription factors to chromatin accessibility changes and regulatory elements to target genes through correlations of expression and regulatory element accessibility. Overall, this work provides a framework for integrative exploration of complex regulatory dynamics in a primary human tissue at single-cell resolution.
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•Single-cell chromatin accessibility reveals a heterogeneous hematopoietic landscape•TF motif-associated chromatin variability in HSCs follows erythroid/lymphoid paths•Characterization of two GMP subsets with chromatin and transcriptome differences•Integrative analysis enables regulatory insights into cis- and trans-acting factors
Integrative analysis of single-cell transcriptomics and chromatin accessibility provides insights into regulatory features and dynamics in human hematopoiesis.
Trachoma is the leading cause of infectious blindness worldwide. Control strategies target antibiotic therapy to individuals likely to be infected with Chlamydia trachomatis on the basis of clinical ...signs. However, many studies have found chlamydial infection in the absence of clinical disease. It has been unclear whether such individuals represent a significant reservoir of infection. In the current study, a quantitative polymerase chain reaction (PCR) assay was used to investigate the distribution and determinants of chlamydial infection load in an endemic community, and the findings were used to evaluate the potential effectiveness of different control strategies.
Members of a trachoma-endemic community (n = 1319) in a rural area of The Gambia were examined for signs of disease, and tarsal conjunctival swab samples were collected. C. trachomatis was initially detected by qualitative PCR. The load of infection was then estimated by real-time quantitative PCR.
Chlamydial infection was detected in 7.2% of the population. The distribution of infection load was skewed, with a few individuals having high loads. Only 24% of infected individuals had signs of active trachoma. Infection loads were higher in those with clinically active disease and were highest among those with severe inflammatory trachoma. High infection loads were associated with having no accessible latrine and living with a person with active disease.
In this low-prevalence setting, infected individuals without signs of active trachoma constitute a significant reservoir of infection. Treatment of a defined unit of people who live with someone with clinically active trachoma would effectively target antibiotic treatment to infected people without signs of disease.
The activities and genome-wide specificities of CRISPR-Cas Cpf1 nucleases are not well defined. We show that two Cpf1 nucleases from Acidaminococcus sp. BV3L6 and Lachnospiraceae bacterium ND2006 ...(AsCpf1 and LbCpf1, respectively) have on-target efficiencies in human cells comparable with those of the widely used Streptococcus pyogenes Cas9 (SpCas9). We also report that four to six bases at the 3' end of the short CRISPR RNA (crRNA) used to program Cpf1 nucleases are insensitive to single base mismatches, but that many of the other bases in this region of the crRNA are highly sensitive to single or double substitutions. Using GUIDE-seq and targeted deep sequencing analyses performed with both Cpf1 nucleases, we were unable to detect off-target cleavage for more than half of 20 different crRNAs. Our results suggest that AsCpf1 and LbCpf1 are highly specific in human cells.
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