Host cell environments and antibiotic efficacy in tuberculosis.

The aetiologic agent of tuberculosis (TB), Mycobacterium tuberculosis (Mtb), can survive, persist, and proliferate in a variety of heterogeneous subcellular compartments. Therefore, TB chemotherapy requires antibiotics crossing multiple biological membranes to reach distinct subcellular compartments and target these bacterial populations. These compartments are also dynamic, and our understanding of intracellular pharmacokinetics (PK) often represents a challenge for antitubercular drug development. In recent years, the development of high-resolution imaging approaches in the context of host-pathogen interactions has revealed the intracellular distribution of antibiotics at a new level, yielding discoveries with important clinical implications. In this review, we describe the current knowledge regarding cellular PK of antibiotics and the complexity of drug distribution within the context of TB. We also discuss the recent advances in quantitative imaging and highlight their applications for drug development in the context of how intracellular environments and microbial localisation affect TB treatment efficacy.

Convolutional Neural Networks for Classifying Chromatin Morphology in Live-Cell Imaging.

Chromatin is highly structured, and changes in its organization are essential in many cellular processes, including cell division. Recently, advances in machine learning have enabled researchers to automatically classify chromatin morphology in fluorescence microscopy images. In this protocol, we develop user-friendly tools to perform this task. We provide an open-source annotation tool, and a cloud-based computational framework to train and utilize a convolutional neural network to automatically classify chromatin morphology. Using cloud compute enables users without significant resources or computational experience to use a machine learning approach to analyze their own microscopy data.

Gravidity-dependent associations between interferon response and birth weight in placental malaria.

BACKGROUND: Maternal malarial infection leads to poor perinatal outcomes, including low birth weight from preterm delivery and/or fetal growth restriction, particularly in primigravidas. In placental malaria, Plasmodium falciparum-infected red blood cells cause an inflammatory response that can interfere with maternal-fetal exchange, leading to poor growth. The type I interferon (IFN-I) pathway plays an immunomodulatory role in viral and bacterial infections, usually by suppressing inflammatory responses. However, its role in placental malaria is unknown. This study examines the cytokine responses in placental tissue from subsets of malaria-infected and uninfected women, and attempts to correlate them with particular birth outcomes. METHODS: 40 whole placental biopsy samples were obtained from pregnant women at least 16 years of age recruited to a larger prospective chemoprevention trial against malaria. These were patients at Tororo District Hospital in Uganda, an area of high malaria endemicity where approximately 40% of women have evidence of malaria infection at delivery. They were regularly followed at a local clinic and monitored for fever, with blood smears performed then and at time of delivery to diagnose malaria infection. Placenta biopsies were taken for histological diagnosis of placental malaria, as well as quantitative PCR analysis of genes in the IFN-I pathway (IFN-ß, IL-10 and MX-1). Parameters such as infant birth weight and gestational age were also recorded. RESULTS: Histological analysis revealed placental malaria in 18 samples, while 22 were found to be uninfected. RT-PCR analysis showed a four-fold increase in IFN-ß and IL-10 expression in multigravidas with placental malaria when compared to gravidity-matched, uninfected controls. This effect was not observed in primigravidas. Interestingly, linear regression analysis showed a positive association between IFN-ß levels and higher birth weights (ß = 101.2 g per log2-fold increase in IFN-ß expression, p = 0.042). This association was strongest in primigravidas with placental malaria (ß = 339.0, p = 0.006). CONCLUSIONS: These results demonstrate differential regulation of the IFN-I pathway in placental malaria according to gravidity, with the greatest anti-inflammatory response seen in multigravidas. The association between IFN-ß levels and higher birth weight also suggests a protective role for IFN-I against fetal growth restriction in placental malaria.

Biochemical and anaplerotic applications of in vitro models of propionic acidemia and methylmalonic acidemia using patient-derived primary hepatocytes.

Propionic acidemia (PA) and methylmalonic acidemia (MMA) are autosomal recessive disorders of propionyl-CoA (P-CoA) catabolism, which are caused by a deficiency in the enzyme propionyl-CoA carboxylase or the enzyme methylmalonyl-CoA (MM-CoA) mutase, respectively. The functional consequence of PA or MMA is the inability to catabolize P-CoA to MM-CoA or MM-CoA to succinyl-CoA, resulting in the accumulation of P-CoA and other metabolic intermediates, such as propionylcarnitine (C3), 3-hydroxypropionic acid, methylcitric acid (MCA), and methylmalonic acid (only in MMA). P-CoA and its metabolic intermediates, at high concentrations found in PA and MMA, inhibit enzymes in the first steps of the urea cycle as well as enzymes in the tricarboxylic acid (TCA) cycle, causing a reduction in mitochondrial energy production. We previously showed that metabolic defects of PA could be recapitulated using PA patient-derived primary hepatocytes in a novel organotypic system. Here, we sought to investigate whether treatment of normal human primary hepatocytes with propionate would recapitulate some of the biochemical features of PA and MMA in the same platform. We found that high levels of propionate resulted in high levels of intracellular P-CoA in normal hepatocytes. Analysis of TCA cycle intermediates by GC-MS/MS indicated that propionate may inhibit enzymes of the TCA cycle as shown in PA, but is also incorporated in the TCA cycle, which does not occur in PA. To better recapitulate the disease phenotype, we obtained hepatocytes derived from livers of PA and MMA patients. We characterized the PA and MMA donors by measuring key proximal biomarkers, including P-CoA, MM-CoA, as well as clinical biomarkers propionylcarnitine-to-acetylcarnitine ratios (C3/C2), MCA, and methylmalonic acid. Additionally, we used isotopically-labeled amino acids to investigate the contribution of relevant amino acids to production of P-CoA in models of metabolic stability or acute metabolic crisis. As observed clinically, we demonstrated that the isoleucine and valine catabolism pathways are the greatest sources of P-CoA in PA and MMA donor cells and that each donor showed differential sensitivity to isoleucine and valine. We also studied the effects of disodium citrate, an anaplerotic therapy, which resulted in a significant increase in the absolute concentration of TCA cycle intermediates, which is in agreement with the benefit observed clinically. Our human cell-based PA and MMA disease models can inform preclinical drug discovery and development where mouse models of these diseases are inaccurate, particularly in well-described species differences in branched-chain amino acid catabolism.

Identifying risk factors for perinatal death at Tororo District Hospital, Uganda: a case-control study.

BACKGROUND: Sub-Saharan Africa faces a disproportionate burden of perinatal deaths globally. However, data to inform targeted interventions on an institutional level is lacking, especially in rural settings. The objective of this study is to identify risk factors for perinatal death at a resource-limited hospital in Uganda. METHODS: This is a retrospective case-control study at a district hospital in eastern Uganda using birth registry data. Cases were admissions with stillbirths at or beyond 24 weeks or neonatal deaths within 28 days of birth. Controls were admissions that resulted in deliveries immediately preceding and following each case. We compared demographic and obstetric factors between cases and controls to identify risk factors for perinatal death. Subgroup analysis of type of perinatal death was also performed. Chi square, Fisher's exact, t-test, and Wilcoxon-Mann-Whitney rank sum tests were utilized for bivariate analysis, and multiple logistic regression for multivariate analysis. RESULTS: From January 2014 to December 2014, there were 185 cases of perinatal death, of which 36% (n = 69) were macerated stillbirths, 40% (n = 76) were fresh stillbirths, and 25% (n = 47) were neonatal deaths. The rate of perinatal death among all deliveries at the institution was 35.5 per 1000 deliveries. Factors associated with increased odds perinatal death included: prematurity (adjusted odds ratio (aOR) 19.7, 95% confidence interval (CI) 7.2-49.2), breech presentation (aOR 7.0, CI 1.4-35.5), multiple gestation (aOR 4.0, CI 1.1-13.9), cesarean delivery (aOR 3.8, CI 2.3-6.4) and low birth weight (aOR 2.5, CI 1.1-5.3). Analysis by subtype of perinatal death revealed distinct associations with the aforementioned risk factors, in particular for antepartum hemorrhage, which was only associated with fresh stillbirths (aOR 6.7, CI 1.6-28.8), and low birth weight. CONCLUSIONS: The rate of perinatal death at our rural hospital site was higher than national targets, and these deaths were associated with prematurity, low birth weight, breech presentation, multiple gestation, and cesarean delivery. This data and the approach utilized to acquire it can be leveraged to inform targeted interventions to reduce the rate of stillbirths and neonatal deaths in similar low resource settings.

Gene Expression Predicts Histological Severity and Reveals Distinct Molecular Profiles of Nonalcoholic Fatty Liver Disease.

The heterogeneity of biological processes driving the severity of nonalcoholic fatty liver disease (NAFLD) as reflected in the transcriptome and the relationship between the pathways involved are not well established. Well-defined associations between gene expression profiles and disease progression would benefit efforts to develop novel therapies and to understand disease heterogeneity. We analyzed hepatic gene expression in controls and a cohort with the full histological spectrum of NAFLD. Protein-protein interaction and gene set variation analysis revealed distinct sets of coordinately regulated genes and pathways whose expression progressively change over the course of the disease. The progressive nature of these changes enabled us to develop a framework for calculating a disease progression score for individual genes. We show that, in aggregate, these scores correlate strongly with histological measures of disease progression and can thus themselves serve as a proxy for severity. Furthermore, we demonstrate that the expression levels of a small number of genes (~20) can be used to infer disease severity. Finally, we show that patient subgroups can be distinguished by the relative distribution of gene-level scores in specific gene sets. While future work is required to identify the specific disease characteristics that correspond to patient clusters identified on this basis, this work provides a general framework for the use of high-content molecular profiling to identify NAFLD patient subgroups.

Membrane lipid order of sub-synaptic T cell vesicles correlates with their dynamics and function.

During an immune response, T cells survey antigen presenting cells for antigenic peptides via the formation of an interface known as an immunological synapse. Among the complex and dynamic biophysical phenomena occurring at this interface is the trafficking of sub-synaptic vesicles carrying a variety of proximal signalling molecules. Here, we show that rather than being a homogeneous population, these vesicles display a diversity of membrane lipid order profiles, as measured using the environmentally sensitive dye di-4-ANEPPDHQ and multi-spectral TIRF microscopy. Using live-cell imaging, vesicle tracking and a variety of small molecule drugs to manipulate components of the actin and tubulin cytoskeleton, we show that the membrane lipid order of these vesicles correlate with their dynamics. Furthermore, we show that the key proximal signalling molecule Linker for Activation of T cells (LAT) is enriched in specific vesicle populations as defined by their higher membrane order. These results imply that vesicle lipid order may represent a novel regulatory mechanism for the sorting and trafficking of signalling molecules at the immunological synapse, and, potentially, other cellular structures.

Community-wide Prevalence of Malaria Parasitemia in HIV-Infected and Uninfected Populations in a High-Transmission Setting in Uganda.

BACKGROUND: Malaria control strategies depend on identifying individuals with parasitemia, who may be asymptomatic but retain the ability to transmit disease. Population-level survey data on parasitemia are limited and traditionally exclude adults and human immunodeficiency virus (HIV)-infected individuals. METHODS: We performed a cross-sectional survey of residents aged 18 months to 94 years in Nankoma, Uganda. Blood specimens were collected using the dried blood spot technique from 9629 residents (87.6%), and samples from a subset of 4131 were tested for malaria parasites, using loop-mediated isothermal amplification. Population-level prevalence was estimated using a weighted proportion, and predictors of parasitemia were identified using a multivariate Poisson regression model. RESULTS: The community prevalence of parasitemia was 83.8% (95% confidence interval [CI], 82.9%-84.6%). Parasite prevalence was highest among children aged 5-14 years (94.7%) and lowest among adults (61.9%). In analysis that controlled for age, HIV-infected individuals with an undetectable viral load had a lower risk of parasitemia, compared with HIV-uninfected individuals (adjusted relative risk, 0.16; 95% CI, .10-.27; P < .001). CONCLUSIONS: In a rural Ugandan community, 2 years after distribution of long-lasting insecticide-treated bed nets, the prevalence of malaria parasitemia was high across all ages, peaking in school-aged children. Persons with well-controlled HIV infection had a lower risk of parasitemia, presumably reflecting access to HIV care.

Phamerator: a bioinformatic tool for comparative bacteriophage genomics.

BACKGROUND: Bacteriophage genomes have mosaic architectures and are replete with small open reading frames of unknown function, presenting challenges in their annotation, comparative analysis, and representation. RESULTS: We describe here a bioinformatic tool, Phamerator, that assorts protein-coding genes into phamilies of related sequences using pairwise comparisons to generate a database of gene relationships. This database is used to generate genome maps of multiple phages that incorporate nucleotide and amino acid sequence relationships, as well as genes containing conserved domains. Phamerator also generates phamily circle representations of gene phamilies, facilitating analysis of the different evolutionary histories of individual genes that migrate through phage populations by horizontal genetic exchange. CONCLUSIONS: Phamerator represents a useful tool for comparative genomic analysis and comparative representations of bacteriophage genomes.

Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project.

We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.

Identification of higher-order functional domains in the human ENCODE regions.

It has long been posited that human and other large genomes are organized into higher-order (i.e., greater than gene-sized) functional domains. We hypothesized that diverse experimental data types generated by The ENCODE Project Consortium could be combined to delineate active and quiescent or repressed functional domains and thereby illuminate the higher-order functional architecture of the genome. To address this, we coupled wavelet analysis with hidden Markov models for unbiased discovery of "domain-level" behavior in high-resolution functional genomic data, including activating and repressive histone modifications, RNA output, and DNA replication timing. We find that higher-order patterns in these data types are largely concordant and may be analyzed collectively in the context of HeLa cells to delineate 53 active and 62 repressed functional domains within the ENCODE regions. Active domains comprise approximately 44% of the ENCODE regions but contain approximately 75%-80% of annotated genes, transcripts, and CpG islands. Repressed domains are enriched in certain classes of repetitive elements and, surprisingly, in evolutionarily conserved nonexonic sequences. The functional domain structure of the ENCODE regions appears to be largely stable across different cell types. Taken together, our results suggest that higher-order functional domains represent a fundamental organizing principle of human genome architecture.

Unsupervised segmentation of continuous genomic data.

UNLABELLED: The advent of high-density, high-volume genomic data has created the need for tools to summarize large datasets at multiple scales. HMMSeg is a command-line utility for the scale-specific segmentation of continuous genomic data using hidden Markov models (HMMs). Scale specificity is achieved by an optional wavelet-based smoothing operation. HMMSeg is capable of handling multiple datasets simultaneously, rendering it ideal for integrative analysis of expression, phylogenetic and functional genomic data. AVAILABILITY: http://noble.gs.washington.edu/proj/hmmseg