MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments

Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than transient background and artefactual interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly identifies statistically significant interactions in both Hi-C and capture Hi-C experiments. MaxHiC uses a negative binomial distribution model and a maximum likelihood technique to correct biases in both Hi-C and capture Hi-C libraries. We systematically benchmark MaxHiC against major Hi-C background correction tools including Hi-C significant interaction callers (SIC) and Hi-C loop callers using published Hi-C, capture Hi-C, and Micro-C datasets. Our results demonstrate that 1) Interacting regions identified by MaxHiC have significantly greater levels of overlap with known regulatory features (e.g. active chromatin histone marks, CTCF binding sites, DNase sensitivity) and also disease-associated genome-wide association SNPs than those identified by currently existing models, 2) the pairs of interacting regions are more likely to be linked by eQTL pairs and 3) more likely to link known regulatory features including known functional enhancer-promoter pairs validated by CRISPRi than any of the existing methods. We also demonstrate that interactions between different genomic region types have distinct distance distributions only revealed by MaxHiC. MaxHiC is publicly available as a python package for the analysis of Hi-C, capture Hi-C and Micro-C data.     

Effects of microbial volatile organic compounds on Ganoderma lucidum growth and ganoderic acids production in Co-v-cultures (volatile co-cultures)

Abstract

Co-v-culture (co-cultivations of physically separated microbes that only interact through the air) systems were designed to investigate the effects of microbial volatile organic compounds (mVOCs) from about 20 different microbes, on a medicinal fungus, Ganoderma lucidum. For more accuracy in co-cultivations, a novel synchronized cultivation approach was tested for culturing G. lucidum. The hyphal growth of G. lucidum and the content of its ganoderic acids (GAs) were measured. In almost all of the co-v-cultures, there was an inhibiting effect on hyphal growth and a promoting effect on GAs contents. In inducing GAs production, Bacillus cereus PTCC 1247 and Pseudomonas aeruginosa UTMC 1404 were the most effective ones, as, compared to control cultures, GAs content increased 2.8 fold. Comparing different co-v-cultivations demonstrated that the concentrations of mVOCs, oxygen, and carbon dioxide were the main players in co-v-cultures. No correlation was found between hyphal growth and GAs production. Strains of the same species imposed totally different effects on hyphal growth or GAs production. This study has investigated the effects of mVOCs on G. lucidum for the first time. Moreover, it suggests that co-v-cultivation may be a promising biotechnological approach to improve the production in G. lucidum.     

Review and future prospects on the mechanisms related to cold stress resistance and tolerance in medicinal plants

Medicinal plants play important role in industrial production of medicines. Moreover, they consume without complicated processes around the world. They are considered as healthy cure without any harmful side effects at least among ordinary people. Cold stress is one the harmful abiotic stresses and constrains medicinal plants yielding geographically. Cold acclimation is a process that induces cold stress resistance in temperate plants. Various structural and morphological alterations are involved in this process. Also, enzymatic and non-enzymatic agents play role in cold acclimation. Cell membrane modification and compatible solutes accumulation and so many other changes occur through cold acclimation. Growing under different stressful conditions, medicinal plants synthesize different components such as metabolites. Moreover, ROS can be generated in plant cells under stressful conditions. The accumulation of bioactive components, biosynthesis of phytohormones, ion hemostasis, osmolyte (compatible solutes) accumulation and changes in nutrient uptake, root system modification and systemic resistance are some of new investigations that are considered in this review.     

Reviewing the role of cardiac exosomes in myocardial repair at a glance

Exosome-based therapy is an emerging novel approach for myocardial infarction (MI) treatment. Exosomes are identified as extracellular vesicles that are produced within multivesicular bodies in the cells' cytosols and then are secreted from the cells. Exosomes are 30–100 nm in diameter that are released from viable cells and are different from other secreted vesicles such as apoptotic bodies and microvesicles in their origin and contents such as RNAs, proteins, and nucleic acid. The recent advances in exosome research have demonstrated the role of these bionanovesicles in the physiological, pathological, and molecular aspects of the heart. The results of in vitro and preclinical models have shown that exosomes from different cardiac cells can improve cardiac function following MI. For example, mesenchymal stem cells (MSCs) and cardiac progenitor cells (CPCs) containing exosomes can affect the proliferation, survival, and differentiation of cardiac fibroblasts and cardiomyocytes. Moreover, MSCs- and CPCs-derived exosomes can enhance the migration of endothelial cells. Exosome-based therapy approaches augment the cardiac function by multiple means, such as reducing fibrosis, stimulation of vascular angiogenesis, and proliferation of cardiomyocytes that result in replacing damaged heart tissue with newly generated functional myocytes. This review article aims to briefly discuss the recent advancements in the role of secreted exosomes in myocardial repair by focusing on cardiac cells-derived exosomes.     

Influence of Magnetic Field on Brain Activity During Administration of Caffeine

The aim of the present work is to evaluate the effect of caffeine, the world’s most popular psychoactive drug, on the electric activity of the rat’s brain that exposed to extremely low-frequency magnetic field (ELF-MF), during 15 days. The obtained results showed that administration of caffeine in a group of rats by dose of 10 mg/kg (equivalent to human daily consumption) caused a reduction in the mean power amplitude of electroencephalogram (EEG) trace for almost all frequency bands especially α (8–12 Hz). It was observed that the influence of caffeine was more evident in motor cortex than in visual cortex. While the exposure of another group to ELF-MF of intensity 0.2 mT during the same period caused an enhancement in the mean power amplitude of most EEG frequency bands; this was more observed in the right hemisphere of the brain than that of the left hemisphere. The administration of caffeine while rats were exposed to ELF-MF, led, after 5 days of exposure, to a great increase in the mean power amplitude of α band at all places of recording electrodes. It may be concluded that caffeine administration was more effective in reducing the hazardous of ELF-MF in motor cortex than in visual cortex.     

Bag-of-words representation for biomedical time series classification

Automatic analysis of biomedical time series such as electroencephalogram (EEG) and electrocardiographic (ECG) signals has attracted great interest in the community of biomedical engineering due to its important applications in medicine. In this work, a simple yet effective bag-of-words representation that is originally developed for text document analysis is extended for biomedical time series representation. In particular, similar to the bag-of-words model used in text document domain, the proposed method treats a time series as a text document and extracts local segments from the time series as words. The biomedical time series is then represented as a histogram of codewords, each entry of which is the count of a codeword appeared in the time series. Although the temporal order of the local segments is ignored, the bag-of-words representation is able to capture high-level structural information because both local and global structural information are well utilized. The performance of the bag-of-words model is validated on three datasets extracted from real EEG and ECG signals. The experimental results demonstrate that the proposed method is not only insensitive to parameters of the bag-of-words model such as local segment length and codebook size, but also robust to noise.     

An evaluation of sequencing coverage and genotyping strategies to assess neutral and adaptive diversity

Whole genome sequences (WGS) greatly increase our ability to precisely infer population genetic parameters, demographic processes, and selection signatures. However, WGS may still be not affordable for a representative number of individuals/populations. In this context, our goal was to assess the efficiency of several SNP genotyping strategies by testing their ability to accurately estimate parameters describing neutral diversity and to detect signatures of selection. We analysed 110 WGS at 12× coverage for four different species, i.e., sheep, goats and their wild counterparts. From these data we generated 946 data sets corresponding to random panels of 1K to 5M variants, commercial SNP chips and exome capture, for sample sizes of five to 48 individuals. We also extracted low‐coverage genome resequencing of 1×, 2× and 5× by randomly subsampling reads from the 12× resequencing data. Globally, 5K to 10K random variants were enough for an accurate estimation of genome diversity. Conversely, commercial panels and exome capture displayed strong ascertainment biases. Besides the characterization of neutral diversity, the detection of the signature of selection and the accurate estimation of linkage disequilibrium (LD) required high‐density panels of at least 1M variants. Finally, genotype likelihoods increased the quality of variant calling from low coverage resequencing but proportions of incorrect genotypes remained substantial, especially for heterozygote sites. Whole genome resequencing coverage of at least 5× appeared to be necessary for accurate assessment of genomic variations. These results have implications for studies seeking to deploy low‐density SNP collections or genome scans across genetically diverse populations/species showing similar genetic characteristics and patterns of LD decay for a wide variety of purposes.     

Cecal microbial transplantation attenuates hyperthyroid-induced thermogenesis in Mongolian gerbils

Endothermic mammals have a high energy cost to maintain a stable and high body temperature (T_b, around 37°C). Thyroid hormones are a major regulator for energy metabolism and T_b. The gut microbiota is involved in modulating host energy metabolism. However, whether the interaction between the gut microbiota and thyroid hormones is involved in metabolic and thermal regulations is unclear. We hypothesized that thyroid hormones via an interaction with gut microbiota orchestrate host thermogenesis and T_b. l -thyroxine-induced hyperthyroid Mongolian gerbils (Meriones unguiculatus) increased resting metabolic rate (RMR) and T_b, whereas Methimazole-induced hypothyroid animals decreased RMR. Both hypothyroid and hyperthyroid animals differed significantly in faecal bacterial community. Hyperthyroidism increased the relative abundance of pathogenic bacteria, such as Helicobacter and Rikenella, and decreased abundance of beneficial bacteria Butyricimonas and Parabacteroides, accompanied by reduced total bile acids and short-chain fatty acids. Furthermore, the hyperthyroid gerbils transplanted with the microbiota from control donors increased type 2 deiodinase (DIO2) expression in the liver and showed a greater rate of decline of both serum T3 and T4 levels and, consequently, a more rapid recovery of normal RMR and T_b. These findings indicate that thyroid hormones regulate thermogenesis depending on gut microbiota and colonization with normal microbiota by caecal microbial transplantation attenuates hyperthyroid-induced thermogenesis. This work reveals the functional consequences of the gut microbiota-thyroid axis in controlling host metabolic physiology and T_b in endotherms.