Distinct RNA profiles in subpopulations of extracellular vesicles: apoptotic bodies, microvesicles and exosomes

Introduction: In recent years, there has been an exponential increase in the number of studies aiming to understand the biology of exosomes, as well as other extracellular vesicles. However, classification of membrane vesicles and the appropriate protocols for their isolation are still under intense discussion and investigation. When isolating vesicles, it is crucial to use systems that are able to separate them, to avoid cross-contamination. Method: EVs released from three different kinds of cell lines: HMC-1, TF-1 and BV-2 were isolated using two centrifugation-based protocols. In protocol 1, apoptotic bodies were collected at 2,000×g, followed by filtering the supernatant through 0.8 µm pores and pelleting of microvesicles at 12,200×g. In protocol 2, apoptotic bodies and microvesicles were collected together at 16,500×g, followed by filtering of the supernatant through 0.2 µm pores and pelleting of exosomes at 120,000×g. Extracellular vesicles were analyzed by transmission electron microscopy, flow cytometry and the RNA profiles were investigated using a Bioanalyzer®. Results: RNA profiles showed that ribosomal RNA was primary detectable in apoptotic bodies and smaller RNAs without prominent ribosomal RNA peaks in exosomes. In contrast, microvesicles contained little or no RNA except for microvesicles collected from TF-1 cell cultures. The different vesicle pellets showed highly different distribution of size, shape and electron density with typical apoptotic body, microvesicle and exosome characteristics when analyzed by transmission electron microscopy. Flow cytometry revealed the presence of CD63 and CD81 in all vesicles investigated, as well as CD9 except in the TF-1-derived vesicles, as these cells do not express CD9. Conclusions: Our results demonstrate that centrifugation-based protocols are simple and fast systems to distinguish subpopulations of extracellular vesicles. Different vesicles show different RNA profiles and morphological characteristics, but they are indistinguishable using CD63-coated beads for flow cytometry analysis

Editorial Forward

With the availability of next generation sequencing technology, there is a tremendous need for development of novel tools, algorithms and methodologies for extracting useful information and knowledge from exponentially growing data.  This need has catalyzed active research in the overlapping fields of Machine Learning (ML) and Artificial Intelligence (AI). First issue of IJCB is bringing some very good research articles with a detailed view of the cutting edge machine learning algorithms

Microguards and micromessengers of the genome

The regulation of gene expression is of fundamental importance to maintain organismal function and integrity and requires a multifaceted and highly ordered sequence of events. The cyclic nature of gene expression is known as ‘transcription dynamics’. Disruption or perturbation of these dynamics can result in significant fitness costs arising from genome instability, accelerated ageing and disease. We review recent research that supports the idea that an important new role for small RNAs, particularly microRNAs (miRNAs), is in protecting the genome against short-term transcriptional fluctuations, in a process we term ‘microguarding’. An additional emerging role for miRNAs is as ‘micromessengers’—through alteration of gene expression in target cells to which they are trafficked within microvesicles. We describe the scant but emerging evidence that miRNAs can be moved between different cells, individuals and even species, to exert biologically significant responses. With these two new roles, miRNAs have the potential to protect against deleterious gene expression variation from perturbation and to themselves perturb the expression of genes in target cells. These interactions between cells will frequently be subject to conflicts of interest when they occur between unrelated cells that lack a coincidence of fitness interests. Hence, there is the potential for miRNAs to represent both a means to resolve conflicts of interest, as well as instigate them. We conclude by exploring this conflict hypothesis, by describing some of the initial evidence consistent with it and proposing new ideas for future research into this exciting topic

Doctor of Philosophy

dissertationThe bituminous sand deposits of Utah are estimated to contain 25 - 29 billion barrels of oil in place and are the largest petroleum resource of this type in the United States. There are six major deposits of commercial importance* some of them potentially amenable to surface mining techniques. In this investigation an experimental program was conducted to determine the feasibility of an aboveground fluidized bed thermal process rfor the recovery of - a synthetic crude from the minable bituminous sand deposits of Utah. A continuous bench-scale, fluidized bed reactor, designed for a maximum throughput capacity of 2.25 kilograms of feed sand per hour, was developed for this investigation. Bituminous sands of distinctly different origin were processed, that is, (i) the Sunnyside bituminous sand, a deposit of fresh water origin having a bitumen content of 8.5 percent by weight, and (ii) the Tarsand Triangle sand, a deposit of marine origin having a bitumen content of 4.5 percent by weight. The effects of the following variables on the synthetic liquid yield and on the liquid quality were studied: Reactor Temperature: 698 - 898 K Solids Retention Time: 20.4 - 31.4 minutes Particle Size of Feed Sand: 162 - 507.5 microns The maximum liquid yield for the Sunnyside sand, 70 weight percent of the bitumen fed, was obtained at 773 K and a solids retention time of 20.4 minutes for a feed sand particle size of 358.5 microns. The remaining 30 weight percent of the bitumen was converted to coke and light hydrocarbon gases. Increasing the solids retention time lowered the liquid yield and shifted the-temperature for maximum liquid yield to a lower value. The physical properties and chemical nature of the synthetic liquid obtained were correlated with the reactor temperature. The synthetic liquid obtained was paraffinic and contained a low percentage of heteroatoms. A mechanism for the thermal cracking of the bitumen has been developed to explain the results obtained. Extrapolation of the data to a solids retention time of 16 minutes predicts a yield of 80 weight percent synthetic liquid, 8 weight percent light hydrocarbon gases (C-j - C4 ), and 12 weight percent coke. The thermal processing of Tarsand Triangle sand was studied as a function reactor temperature in the range 723 - 898 K. It was found that the liquid yield was lower than that obtained with the Sunnyside feed. The maximum liquid yield of 51 weight percent based on bitumen fed was obtained at 798 K and a retention time of 27.2 minutes. Despite the differences in the origin of the feed sand and the operating temperature range, the yield of coke (19 - 22 wt %) was comparable to Sunnyside coke yields. The liquid product was more aromatic than the Sunnyside liquid product

MicroRNAs in pulmonary arterial remodeling

Pulmonary arterial remodeling is a presently irreversible pathologic hallmark of pulmonary arterial hypertension (PAH). This complex disease involves pathogenic dysregulation of all cell types within the small pulmonary arteries contributing to vascular remodeling leading to intimal lesions, resulting in elevated pulmonary vascular resistance and right heart dysfunction. Mutations within the bone morphogenetic protein receptor 2 gene, leading to dysregulated proliferation of pulmonary artery smooth muscle cells, have been identified as being responsible for heritable PAH. Indeed, the disease is characterized by excessive cellular proliferation and resistance to apoptosis of smooth muscle and endothelial cells. Significant gene dysregulation at the transcriptional and signaling level has been identified. MicroRNAs are small non-coding RNA molecules that negatively regulate gene expression and have the ability to target numerous genes, therefore potentially controlling a host of gene regulatory and signaling pathways. The major role of miRNAs in pulmonary arterial remodeling is still relatively unknown although research data is emerging apace. Modulation of miRNAs represents a possible therapeutic target for altering the remodeling phenotype in the pulmonary vasculature. This review will focus on the role of miRNAs in regulating smooth muscle and endothelial cell phenotypes and their influence on pulmonary remodeling in the setting of PAH

Characterization of RNA in exosomes secreted by human breast cancer cell lines using next-generation sequencing

Exosomes are nanosized (30–100 nm) membrane vesicles secreted by most cell types. Exosomes have been found to contain various RNA species including miRNA, mRNA and long non-protein coding RNAs. A number of cancer cells produce elevated levels of exosomes. Because exosomes have been isolated from most body fluids they may provide a source for non-invasive cancer diagnostics. Transcriptome profiling that uses deep-sequencing technologies (RNA-Seq) offers enormous amount of data that can be used for biomarkers discovery, however, in case of exosomes this approach was applied only for the analysis of small RNAs. In this study, we utilized RNA-Seq technology to analyze RNAs present in microvesicles secreted by human breast cancer cell lines.Exosomes were isolated from the media conditioned by two human breast cancer cell lines, MDA-MB-231 and MDA-MB-436. Exosomal RNA was profiled using the Ion Torrent semiconductor chip-based technology. Exosomes were found to contain various classes of RNA with the major class represented by fragmented ribosomal RNA (rRNA), in particular 28S and 18S rRNA subunits. Analysis of exosomal RNA content revealed that it reflects RNA content of the donor cells. Although exosomes produced by the two cancer cell lines shared most of the RNA species, there was a number of non-coding transcripts unique to MDA-MB-231 and MDA-MB-436 cells. This suggests that RNA analysis might distinguish exosomes produced by low metastatic breast cancer cell line (MDA-MB-436) from that produced by highly metastatic breast cancer cell line (MDA-MB-231). The analysis of gene ontologies (GOs) associated with the most abundant transcripts present in exosomes revealed significant enrichment in genes encoding proteins involved in translation and rRNA and ncRNA processing. These GO terms indicate most expressed genes for both, cellular and exosomal RNA.For the first time, using RNA-seq, we examined the transcriptomes of exosomes secreted by human breast cancer cells. We found that most abundant exosomal RNA species are the fragments of 28S and 18S rRNA subunits. This limits the number of reads from other RNAs. To increase the number of detectable transcripts and improve the accuracy of their expression level the protocols allowing depletion of fragmented rRNA should be utilized in the future RNA-seq analyses on exosomes. Present data revealed that exosomal transcripts are representative of their cells of origin and thus could form basis for detection of tumor specific markers

Implementing GIS to improve hospital efficiency in natural disasters

© Authors 2018. CC BY 4.0 License. Over the past decades, the number of natural disasters has been growing around the world. In addition to damaging communities and infrastructures, unexpected disasters also affect service providers such as hospitals and health centers. Markedly, hospital safety from disasters is a challenge in all countries. With disaster damage to health systems resulting in human tragedy, huge economic losses, devastating blows to developmental goals, and shaken social confidence. Ensuring that hospitals and health facilities are safe and secure from disasters depend on implementing an appropriate method to mitigate adverse impacts on hospitals during incidents. Thus, disaster management becomes even more significant, as the health sector has been particularly vulnerable to damages. So, it is crucial to develop appropriate mitigation and adoption method for healthcare facilities, to withstand the natural disasters such as earthquakes and floods. A comprehensive disaster plan is required to ensure a prompt disaster response and coordinated management of a multi causality incident. The aim of this research is to systemically and critically review the importance of hospitals in disaster events and this research attempts to reach a basic understanding to mitigate the risk of disasters in hospitals and improve the continuity of health services during or after disaster events. For this study, secondary information was retrieved from the literature review and document review on sudden-onset natural disasters in different parts of the world was collected. This study found some challenges and deliverables for disaster managers that could mitigate the risk of a natural disaster's impact on a hospital. Accordingly, this research will evaluate the importance of disaster management for hospitals and the challenges that need to be considered during the disaster response

Exosomes: Looking back three decades and into the future

Exosomes are extracellular membrane vesicles whose biogenesis by exocytosis of multivesicular endosomes was discovered in 1983. Since their discovery 30 years ago, it has become clear that exosomes contribute to many aspects of physiology and disease, including intercellular communication. We discuss the initial experiments that led to the discovery of exosomes and highlight some of the exciting current directions in the field

A Multi-class Machine Learning Framework to Predict Ampicillin-Sulbactam Resistance of Acinetobacter baumannii

Acinetobacter baumannii is a serious pathogen responsible for many of the hospital-acquired infections. The emergence of multi-drug and pan-drug resistant strains of A. baumannii has been a growing concern. Ampicillin-sulbactam combination has proven to be effective in treatment of several resistant strains. However, strains resistant to ampicillin-sulbactam combination have also emerged necessitating other combination therapy. Rapid and accurate identification of the phenotype of the organism is essential for starting the right treatment. To this end, genome-based approaches have garnered much attention. In this work, we report a multi-class machine-learning based approach to predict the ampicillin-sulbactam resistance phenotype and MIC of Acinetobacter baumannii based on the presence/absence of AMR genes in the genome of strains isolated in the USA region. Our model achieves an accuracy of about 94% indicating that the gene presence/absence itself can capture the resistance phenotype.  Further, we show that our model, built based on the USA strains, does not predict reliably the AMR phenotypes of Indian isolates pointing to the need for building machine learning models from region-specific data