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The first public release of the exRNA Atlas is now available via the ExRNA Atlas link in the Quick Links section of the exRNA Portal. The Atlas is produced by the NIH Common Fund’s Extracellular RNA Communication (ERC) Consortium and includes 519 small exRNA profiles from eight laboratories. Each profile in the exRNA Atlas acknowledges the contributing laboratory. The profiles were derived from about 6.4 billion reads uniformly processed using the exceRpt small RNA-seq pipeline. Faceted filtering and data navigation tools — hosted by GenboreeKB — are enabled by rich metadata standards developed by the consortium and metadata annotations contributed by the data producers. Uniform data quality metrics agreed by the consortium were applied to all datasets. On behalf of the Bioinformatics Research Lab at Baylor College of Medicine and the whole Data Management and Resource Repository (DMRR), I would like to thank the contributors and the consortium for the outstanding team effort required to reach this important milestone!

To balance the desire of data contributors to have a protected period of time to analyze and publish the data they have produced, the data access policy for datasets in the exRNA Atlas provides for a 12-month embargo period. The embargo period expires on 1 July, 2016 for the profiles in the current release. Researchers may analyze embargoed datasets from the Atlas but may not publish or make scientific presentations about them until the embargo period has ended. The Atlas will be updated regularly with new profiles, each new profile having its own 12-month embargo period per the data access policy. The read-level information for the profiles in the Atlas will be deposited in GEO (unrestricted access) or dbGaP (controlled access). The exRNA Atlas profiles will contain links to these archival records as the data are deposited.

The exRNA Atlas website is currently optimized for the Firefox browser. Extensive testing on other browsers is yet to be performed. Not too many problems are expected on other browsers, but if you do encounter a problem, consider using Firefox. Optimization for mobile devices is also yet to be completed.

Sai Subramanian of the DMRR highlighted the features of this new release of the exRNA Atlas on an ERCC webinar on 4 Feb, 2016 at 1pm ET. If you missed the live talk, it will be available soon afterwards at exRNA.org/About.

Where do we go from here? Of course, we are just at the beginning. By the end of 2016, the amount of data from the consortium’s reference profile projects will likely dwarf this first release. Our next focus here at the DMRR will be to “test drive” the data by performing a number of integrative analyses and to deploy analysis tools that may be applied both to the Atlas profiles and to profiles that are not yet public. Stay tuned and Happy New exRNA Year!

The exRNA portal at WikiPathways continues to grow. It now includes 46 exRNA-related pathways, including 15 from publications by the Extracellular RNA Communication consortium. We are committed to capturing every published pathway figure from the consortium as a properly modeled pathway at WikiPathways. If your work involves pathways, especially if you are publishing it, then look into contributing to WikiPathways.

The latest pathways to be curated from consortium publications are

• 1) EV release from cardiac cells and their functional effects (WP3297),
• 2) the Rac1/Pak1/p38/MMP-2 pathway (WP3303),
• 3) eIF5A regulation in response to inhibition of the nuclear export system (WP3302), and
• 4) MFAP5-mediated ovarian cancer cell motility and invasiveness (WP3301).

The goal of the Wikipathways exRNA portal is to build a collection of pathway models for exRNA researchers to use for illustration, data visualization, and analysis. Each pathway is a self-contained data model that connects to identifier and annotation databases. In addition to providing static images for figures and presentations, these pathways can also be used by bioinformatics and network analysis packages such as Cytoscape and PathVisio. Furthermore, as a wiki, anyone can sign up to improve and grow the content. We invite you all to edit, fix, and add to the pathway models in the exRNA portal at WikiPathways.

Salivary biomarkers such as extracellular RNA (exRNA) and other omics constituents can detect the onset and presence of cancers and diseases. However, saliva collection and biomarker stability, processing and storage at ambient temperature remain as key challenges. Oasis Diagnostics and UCLA collaborated to create a technology, RNAPro•SAL, to address this unmet need.

RNAPro•SAL condenses and streamlines the multistep saliva collection and processing procedure into a single integrated step. This new technology releases whole saliva from a collection pad by compressing and filtering unwanted cellular debris through the bifurcated filter unit. It delivers processed saliva supernatant into the collection tubes within minutes. Its simple operation can be used in the hands of anyone and eliminates specialized equipment and personnel. RNAPro•SAL allows collection from remote locations at ambient temperature. Most existing saliva collectors target a single analyte, whereas RNAPro•SAL stores both stabilized exRNA and protein samples during transport to laboratory for downstream analysis. Results show that the RNAPro•SAL technology yields samples that are suitable for direct transcriptomic and proteomic analysis and stable up to 14 days at ambient temperature. The RNAPro•SAL system extends salivary diagnostics to areas lacking laboratory facilities and provides point-of-care utility (Chiang et al. 2015).

It is well-known that exercise is good for you, but how exactly does physical activity improve the function of different tissues and organs in the body? What molecules underlie how physical activity is translated into better health? The National Institutes of Health’s Common Fund has launched a program that aims to catalogue extensively the biological molecules that are affected by physical activity in people, identify some of the key molecules that underlie the systemic effects of physical activity, and characterize the functions of these key molecules.

This program, Molecular Transducers of Physical Activity in Humans, is the largest targeted NIH investment of funds into the mechanisms of how physical activity improves health and prevents disease. Through the program, investigators at research institutions across the United States will receive about $170 million over five years, pending availability of funds.

A human cohort study (and a parallel animal study) will collect samples pre- and post-exercise and will then support genomic, epigenomic, transcriptomic, metabolomics, and proteomic analyses of the samples. The transcriptomic analysis will include profiling of extracellular RNAs. Data integration should allow molecular signatures of physical activity to be defined and correlated with benefit when possible. Mechanistic studies in animals will also be supported.

For more information, visit https://www.nih.gov/news/health/jun2015/nih-11.htm.

A Funding Opportunity Announcement (FOA) is now available for this program. See https://commonfund.nih.gov/MolecularTransducers.

In a perfect world, extracellular vesicles (EV) would be the same size, have the same contents, and have similar functional potential. However this is not a perfect world. A laboratory across the hallway, doing similar work, may isolate, characterize and thus define EVs differently than their neighbor laboratory. These differences are easy to understand when we consider that EVs are derived from different sources such as humans, mice, rats or even fruit. From each of these sources there may be many different sub-areas of isolation such as bone marrow, blood, serum, saliva, urine, CNS, whole organs and tissues or even immortalized cell lines. We then must consider that the process of isolation of these EV is also different. Ultracentrifugation is a typical and well documented method but variation in rotors, speed and time alter the final isolated EV population. Our laboratory, like others, has used differential centrifugation as our isolation technique and has been able to separate extracellular vesicles into those designated as exosomes with a size range of 40-120 nm and larger vesicles termed microvesicles, which range from 120 to 1000 nm. These ranges are, of course, inexact, but many published works have focused on either microvesicles or exosmes or in some the combined populations, and have shown various functional effects. Other methods for isolation include proprietary biotech kits or columns. Most of these kits isolate exosomes, however some do isolate into the microvesicle range.

EV source and method of isolation are two primary variables to consider when examining the heterogeneity of EV. Other considerations may be less obvious. For example that laboratory across the hallway likes to isolate their vesicles early in the morning from 12 week old female mice, while our lab isolates our EV from 6 week old male mice in the afternoon. Could changes like age, sex and timing of isolation make a difference in the EV population? We think so. Do we think that it could alter the EV potential to impart a functional change on a target cell? We do.

Historically, characterization of EV has been carried out by determining 1) transmembrane or lipid bound extracellular proteins including tetraspanins, integrins, growth factor receptors, heterotrimeric G proteins or phosphatidyl serine binding MFGE8, 2) cytosolic proteins such as TSG101, ANXA, RAB or syntenin, 3) intracellular proteins such as Grp94, CANX, GM130, cytochrome C, histones, and the Argonaute/RISC complex, and 4) extracellular proteins such as acetylcholinesterase, serum albumin, extracellular matrix and soluble secreted proteins. Here one can immediately see the potential for heterogeneity. Our approach has been to isolate EV by ultracentrifugation into three groups: everything (essentially an ultracentrifuged pellet), exosomes and microvesicles as described above. Our studies have focused on the function of these EV.

We have been investigating two separate functional models: 1) induction of pulmonary hypertension (PH) by lung derived vesicles from mice with monocrotaline-induced pulmonary hypertension, and 2) healing effects of mesenchymal derived stem cell vesicles on irradiation injured hematopoietic cells. In the PH studies, exosomes, but not microvesicles, were the functionally operative vesicle species, while with irradiation injury, the microvesicles were the predominantly active population. Heterogeneity with regard to functional effects can be characterized to some extent as relating to the basic nature of the originating cells, the trafficking of the vesicles and the nature of the responding cell.

If we look at the abstracts from the ISEV meeting held in April, 2015 in Bethesda, a large number emphasize various aspects of heterogeneity. Variables impacting these cells include physiologic variables such as cytokine exposure, ambient temperature, circadian rhythms, age, hormonal status, and sex, to cite a non-inclusive list. Also various pathologic conditions will impact the nature of vesicles emitting from different cell populations: ischemic and traumatic injury, smoking, hypoxia, heat, cancer, different infections, and autoimmunity — also a non-inclusive list. The basic nature of vesicles used in different functional studies is also impacted by the isolation approaches utilized, storage conditions, media choice, and the time between isolation and functional testing.

The heterogeneity of cell-derived vesicles is not surprising. These are not molecular entities but rather cellular components. They cannot be precisely defined in a molecular sense, just as bone marrow cells used in marrow transplantation cannot be precisely defined. Characteristics used to define these cells, such as surface markers, may be misleading as well. A good example is that while CD63, a classic exosome marker, is universally present when Western blot studies are carried out, when individual vesicles are queried, anywhere from 3 – 30% of the vesicles may express this epitope on their surface.

Now it may seem, with such heterogeneity, that it would be very difficult to perform good EV analysis and characterization. We would say that, despite not being a perfect world, as long as the experiment is well controlled and the analysis is well documented and presented clearly, then the observations and characteristics of one laboratory’s EV population is just as valid as the laboratory doing similar work across the hallway. Even if they do like to start work early!

This week, the Journal of Extracellular Vesicles has published a special issue focusing on the work of the Extracellular RNA Communication Consortium.

The NIH Common Fund has identified extracellular RNA as a promising new area of biology, and has put together a comprehensive program to explore it. The goal is to understand basic biology, develop new protocols for isolating exRNA, find out the levels of exRNAs in healthy biofluids, and then leverage that new knowledge to develop biomarkers and therapies to deal with a range of diseases. Everything the consortium develops will be made available to the wider scientific community so that we can push the field forward together.

Below are links to the six articles in the special issue:

• The NIH Extracellular RNA Communication Consortium
• Biogenesis, delivery, and function of extracellular RNA
• Extracellular RNAs: development as biomarkers of human disease
• Potential Functional Applications of Extracellular Vesicles: a report by the NIH Common Fund Extracellular RNA Communication Consortium
• Integration of extracellular RNA profiling data using metadata, biomedical ontologies, and Linked Data technologies
• Meeting report: Discussions and preliminary findings on Extracellular RNA measurement methods of laboratories in the NIH Extracellular RNA Communication Consortium

Cancer cells can undergo activating mutations in oncogenes or loss of function mutations in tumor suppressors that drive cancer progression. Many colorectal cancers have activating mutations in the small GTPase KRAS, which leads to more aggressive tumors. Such mutations can also prevent some cancers from responding to specific drug treatments. In our previous studies, we found that the contents of the exosomes released from these mutant KRAS colorectal cancer cells can influence cells with wild-type KRAS and promote oncogenesis in the tumor microenvironment (Beckler et al., 2013; Higginbotham et al., 2011). Furthermore, the exosomes released from KRAS mutant cells contain different proteins than those from cells with wild type KRAS. To test whether mutant KRAS might regulate the composition of secreted miRNAs that contributes to changes in gene expression in recipient cells, we compared small RNAs of cells and matched purified exosomes from isogenic CRC cell lines differing only in KRAS status. The results from this study were recently published in the journal elife (Cha et al., 2015).

We find that exosomes released by mutant KRAS cells contain miRNAs that are different from wild type KRAS cell-derived exosomes. In particular, several miRNAs that function to suppress cancer growth in a healthy cell are found at lower levels in mutant KRAS cells. One such miRNA is miR-100 and was highly represented in the exosomes that are released by KRAS mutant cells.

Reporter gene constructs that are targeted and downregulated by miRNAs were used to test for transfer of functional miRNA species between cells. When cells with a normal copy of the KRAS gene were exposed to the contents of the exosomes released from KRAS mutant cells, we found a reporter for the predicted miR-100 target mTOR was suppressed, indicating that the exported miRNAs from cancerous cells can influence gene expression in neighboring cells. Selective secretion of such cancer-suppressing miRNAs could give cancer cells with mutant KRAS an additional growth advantage over surrounding cells with wild type KRAS that retain such miRNAs. By monitoring the levels of circulating miRNAs in patients, it might be possible to create a non-invasive test to detect colorectal cancer and to influence potential efficacious treatments depending on a patient’s tumor mutational status.

The National Institute on Drug Abuse (NIDA) has two new special Program Announcements (PARs) that we at exRNA.org want to bring to the attention of the field. They are Extracellular Vesicles and Substance Abuse (R01 and R21) PAR-15-283 and PAR-15-284. Applications will be reviewed in a Special Emphasis Panel (SEP). Please share this information with any colleagues that might be interested in applying.

• Purpose: encourage research projects that investigate the interplay between extracellular vesicles (EVs) and addictive processes. In particular NIDA is interested in the potential utility of EVs with respect to understanding neuroplastic mechanisms relevant to substance abuse or as biomarkers or therapeutics.

• Proposed projects are expected to meet the following two criteria:
1. the major thrust of the application should involve extracellular vesicles or associated secretory machinery; and
2. at least one aim or sub-aim should involve exposure to substances of abuse, or analysis of samples from patients exposed to a drug of abuse. Substances of abuse of interest include: nicotine, cocaine, stimulants, opioids, abused prescription drugs, cannabinoids, or combinations of these drugs.

• Applicants with significant preliminary data may wish to apply to the R01 FOA. High risk/high payoff projects that lack significant preliminary data are most appropriate for the companion R21 FOA.

• For the R01, application budgets should not exceed $350,000 per year in direct costs and need to reflect the actual needs of the proposed. Project periods may not exceed 5 years. https://grants.nih.gov/grants/guide/pa-files/PAR-15-283.html

• For the R21, the combined budget for direct costs for the two year project period may not exceed $275,000. No more than $200,000 in direct costs may be requested in any single year. Applicants may request a project period of up to two years. https://grants.nih.gov/grants/guide/pa-files/PAR-15-284.html

• Application Receipt Date(s): early November 2015 and 2016.

If you have questions about applying, please email John Satterlee, Ph.D. (satterleej@nida.nih.gov), Program Director for Epigenetics, Model Organism Genetics, and Functional Genomics at NIDA.

We continue to add pathways from exRNA publications to the exRNA portal at WikiPathways. The latest pathways to be added are 1) miR-222 in Exercise-Induced Cardiac Growth (WP2928), 2) Hypoxia-mediated EMT and Stemness (WP2943) and 3) DDX1 as a regulatory component of the Drosha microprocessor (WP2942). These pathways were directly curated from publication figures.

As a parallel approach to our ongoing effort to curate pathways relevant to the exRNA community, we have recently added a set of relevant miRNA target interactions to WikiPathways, based on a hand-curated list of miRNAs that are being studied by consortia members (collected from presentations during the recent Extracellular RNA Communication Consortium (ERCC) conference). miRNA-target interactions were added based on mirRTarBase entries, restricted to those with strong evidence.

The goal of the Wikipathways exRNA portal is to build a collection of pathway models for exRNA researchers to use for illustration, data visualization, and analysis. Each pathway is a self-contained data model that connects to identifier and annotation databases. In addition to providing static images for figures and presentations, these pathways can also be used by bioinformatics and network analysis packages such as Cytoscape and PathVisio. Furthermore, as a wiki, anyone can sign up to improve and grow the content. We invite you all to edit, fix, and add to the pathway models in the exRNA portal at WikiPathways.