Portal de Periódicos da CAPES

The Extracellular RNA Communication Consortium: Establishing Foundational Knowledge and Technologies for Extracellular RNA Research

2019; Cell Press; Volume: 177; Issue: 2 Linguagem: Inglês

10.1016/j.cell.2019.03.023

1097-4172

Saumya Das, K. Mark Ansel, Markus Bitzer, Xandra O. Breakefield, Alain Charest, David J. Galas, Mark Gerstein, Mihir Gupta, Aleksandar Milosavljević, Michael T. McManus, Tushar Patel, Robert L. Raffaı̈, Joel Rozowsky, Matthew E. Roth, Julie A. Saugstad, Kendall Van Keuren‐Jensen, Alissa M. Weaver, Louise C. Laurent, Asim B. Abdel‐Mageed, Catherine Adamidi, P. David Adelson, Kemal M. Akat, Eric Alsop, K. Mark Ansel, Jorge Arango, Neil Aronin, Seda Kilinc Avsaroglu, Azadeh Azizian, Leonora Balaj, Iddo Z. Ben‐Dov, Karl Bertram, Markus Bitzer, Robert Blelloch, Kimberly A. Bogardus, Xandra O. Breakefield, George A. Călin, Bob S. Carter, Al Charest, Clark C. Chen, Tanuja Chitnis, Robert J. Coffey, Amanda Courtright-Lim, Saumya Das, Amrita Datta, Peter DeHoff, Thomas G. Diacovo, David J. Erle, Alton Etheridge, Marc Ferrer, Jeffrey L. Franklin, Jane E. Freedman, David J. Galas, Timur R. Galeev, Roopali Gandhi, Aitor Garcia, Mark Gerstein, Vikas Ghai, Ionita Ghiran, María D. Giraldez, Andrei Goga, Tasos Gogakos, Béatrice Goilav, Stephen J. Gould, Peixuan Guo, Mihir Gupta, Fred H. Hochberg, Bo Huang, Matt Huentelman, Craig P. Hunter, Elizabeth Hutchins, Andrew R. Jackson, M. Yashar S. Kalani, Pınar Kanlikilicer, Reka Agnes Karaszti, Kendall Van Keuren‐Jensen, Anastasia Khvorova, Yong Kim, Hogyoung Kim, Taek‐Kyun Kim, Robert R. Kitchen, Richard P. Kraig, Anna M. Krichevsky, Raymond Y. Kwong, Louise C. Laurent, Min Young Lee, Noëlle D. L’Étoile, Shawn Levy, Feng Li, Jenny Li, Xin Li, Gabriel López-Berestein, Rocco Lucero, Bogdan Mateescu, A. Matin, Klaas E.A. Max, Michael T. McManus, Thorsten R. Mempel, Cindy Meyer, Aleksandar Milosavljević, Debasis Mondal, Kenneth J. Mukamal, Oscar Murillo, Thangamani Muthukumar, Deborah A. Nickerson, Christopher J. O’Donnell, Dinshaw J. Patel, Tushar Patel, James G. Patton, Anu Paul, Elaine R. Peskind, Mitch A. Phelps, Chaim Putterman, Peter J. Quesenberry, Joseph F. Quinn, Robert L. Raffaı̈, Saritha Ranabothu, Shannon Jiang Rao, Cristian Rodriguez‐Aguayo, Anthony Rosenzweig, Matthew E. Roth, Joel Rozowsky, Marc S. Sabatine, Nikita A. Sakhanenko, Julie A. Saugstad, Thomas D. Schmittgen, Neethu Shah, Ravi V. Shah, Kerby Shedden, Jian Shi, Anil K. Sood, Anuoluwapo Sopeyin, Ryan M. Spengler, Robert Spetzler, Srimeenakshi Srinivasan, Sai Lakshmi Subramanian, Manikkam Suthanthiran, Kahraman Tanrıverdi, Yun Teng, Muneesh Tewari, William Thistlethwaite, Thomas Tuschl, Karolina Kaczor Urbanowicz, Kasey C. Vickers, Olivier Voinnet, Kai Wang, Alissa M. Weaver, Zhiyun Wei, Howard L. Weiner, Zachary R. Weiss, Zev Williams, David T. Wong, Prescott G. Woodruff, Xinshu Xiao, Irene K. Yan, Ashish Yeri, Bing Zhang, Huang‐Ge Zhang,

RNA regulation and disease

The Extracellular RNA Communication Consortium (ERCC) was launched to accelerate progress in the new field of extracellular RNA (exRNA) biology and to establish whether exRNAs and their carriers, including extracellular vesicles (EVs), can mediate intercellular communication and be utilized for clinical applications. Phase 1 of the ERCC focused on exRNA/EV biogenesis and function, discovery of exRNA biomarkers, development of exRNA/EV-based therapeutics, and construction of a robust set of reference exRNA profiles for a variety of biofluids. Here, we present progress by ERCC investigators in these areas, and we discuss collaborative projects directed at development of robust methods for EV/exRNA isolation and analysis and tools for sharing and computational analysis of exRNA profiling data. The Extracellular RNA Communication Consortium (ERCC) was launched to accelerate progress in the new field of extracellular RNA (exRNA) biology and to establish whether exRNAs and their carriers, including extracellular vesicles (EVs), can mediate intercellular communication and be utilized for clinical applications. Phase 1 of the ERCC focused on exRNA/EV biogenesis and function, discovery of exRNA biomarkers, development of exRNA/EV-based therapeutics, and construction of a robust set of reference exRNA profiles for a variety of biofluids. Here, we present progress by ERCC investigators in these areas, and we discuss collaborative projects directed at development of robust methods for EV/exRNA isolation and analysis and tools for sharing and computational analysis of exRNA profiling data. The discovery that extracellular vesicles (EVs) can transport RNAs between cells (Skog et al., 2008Skog J. Würdinger T. van Rijn S. Meijer D.H. Gainche L. Sena-Esteves M. Curry Jr., W.T. Carter B.S. Krichevsky A.M. Breakefield X.O. Glioblastoma microvesicles transport RNA and proteins that promote tumour growth and provide diagnostic biomarkers.Nat. Cell Biol. 2008; 10: 1470-1476Crossref PubMed Scopus (2321) Google Scholar, Valadi et al., 2007Valadi H. Ekström K. Bossios A. Sjöstrand M. Lee J.J. Lötvall J.O. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells.Nat. Cell Biol. 2007; 9: 654-659Crossref PubMed Scopus (4957) Google Scholar) suggested that RNAs carried by EVs may play a previously unrecognized role in intercellular communication and launched the field of extracellular RNA (exRNA) biology. It was quickly recognized that exRNAs might also have utility as biomarkers of disease and as therapeutic agents. There were, however, many gaps in knowledge and technical challenges to overcome. The mechanisms of EV biogenesis and uptake, exRNA cargo selection, and exRNA function were largely unknown. Moreover, efficient and reproducible methods for isolation and analysis of exRNAs were not available, further complicated by early findings that suggesting that exRNAs can associate with multiple subtypes of EVs, as well as with ribonucleoproteins (RNPs) (Arroyo et al., 2011Arroyo J.D. Chevillet J.R. Kroh E.M. Ruf I.K. Pritchard C.C. Gibson D.F. Mitchell P.S. Bennett C.F. Pogosova-Agadjanyan E.L. Stirewalt D.L. et al.Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma.Proc. Natl. Acad. Sci. USA. 2011; 108: 5003-5008Crossref PubMed Scopus (1628) Google Scholar) and lipoprotein (LPP) complexes (Vickers et al., 2011Vickers K.C. Palmisano B.T. Shoucri B.M. Shamburek R.D. Remaley A.T. MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins.Nat. Cell Biol. 2011; 13: 423-433Crossref PubMed Scopus (1375) Google Scholar), indicating that heterogeneity of exRNA carriers would be an important challenge. The first phase of the NIH Common Fund-supported Extracellular RNA Communication Consortium (ERCC1), launched in 2013, was designed to jump-start progress in this nascent field by addressing five major scientific challenges identified by the exRNA research community (Ainsztein et al., 2015Ainsztein A.M. Brooks P.J. Dugan V.G. Ganguly A. Guo M. Howcroft T.K. Kelley C.A. Kuo L.S. Labosky P.A. Lenzi R. et al.The NIH Extracellular RNA Communication Consortium.J. Extracell. Vesicles. 2015; 4: 27493Crossref PubMed Scopus (15) Google Scholar), which were adopted as the major goals of the program. Labs participating in the 30 funded ERCC1 projects have worked individually and collaboratively to work toward these goals, resulting in 480 manuscripts to date, including 18 manuscripts now presented by Cell Press, with more to come, and producing a variety of shared resources (Table 1). The exRNA Portal (http://exRNA.org/) provides descriptions of ERCC projects, a continuously updated list of ERCC publications, and links to these shared resources, as well as a calendar of exRNA-related events and an exRNA-focused blog. Throughout this Perspective, citations for ERCC1 manuscripts are designated with a “†”, and “††” indicates a paper now presented by Cell Press.Table 1Resources Developed by the ERCC1 ProgramResourceApplicationReferencesPlasmidsMembrane/vesicle labeling with fluorescent proteins(Chen et al., 2016Chen B. Hu J. Almeida R. Liu H. Balakrishnan S. Covill-Cooke C. Lim W.A. Huang B. Expanding the CRISPR imaging toolset with Staphylococcus aureus Cas9 for simultaneous imaging of multiple genomic loci.Nucleic Acids Res. 2016†; 44: e75Crossref PubMed Scopus (74) Google Scholar†; Higginbotham et al., 2016Higginbotham J.N. Zhang Q. Jeppesen D.K. Scott A.M. Manning H.C. Ochieng J. Franklin J.L. Coffey R.J. Identification and characterization of EGF receptor in individual exosomes by fluorescence-activated vesicle sorting.J. Extracell. Vesicles. 2016; 5: 29254Crossref PubMed Scopus (0) Google Scholar†; Kamiyama et al., 2016Kamiyama D. Sekine S. Barsi-Rhyne B. Hu J. Chen B. Gilbert L.A. Ishikawa H. Leonetti M.D. Marshall W.F. Weissman J.S. Huang B. Versatile protein tagging in cells with split fluorescent protein.Nat. Commun. 2016†; 7: 11046Crossref PubMed Google Scholar†; Lai et al., 2015Lai C.P. Kim E.Y. Badr C.E. Weissleder R. Mempel T.R. Tannous B.A. Breakefield X.O. Visualization and tracking of tumour extracellular vesicle delivery and RNA translation using multiplexed reporters.Nat. Commun. 2015†; 6: 7029Crossref PubMed Scopus (116) Google Scholar†; Lai et al., 2014aLai C.P. Mardini O. Ericsson M. Prabhakar S. Maguire C. Chen J.W. Tannous B.A. Breakefield X.O. Dynamic biodistribution of extracellular vesicles in vivo using a multimodal imaging reporter.ACS Nano. 2014†; 8: 483-494Crossref PubMed Scopus (151) Google Scholar†, Lai et al., 2014bLai C.P. Tannous B.A. Breakefield X.O. Noninvasive in vivo monitoring of extracellular vesicles.Methods Mol. Biol. 2014†; 1098: 249-258Crossref PubMed Scopus (12) Google Scholar†; Leonetti et al., 2016Leonetti M.D. Sekine S. Kamiyama D. Weissman J.S. Huang B. A scalable strategy for high-throughput GFP tagging of endogenous human proteins.Proc. Natl. Acad. Sci. USA. 2016†; 113: E3501-E3508Crossref PubMed Google Scholar†; Ong et al., 2017Ong W.Q. Citron Y.R. Sekine S. Huang B. Live Cell Imaging of Endogenous mRNA Using RNA-Based Fluorescence “Turn-On” Probe.ACS Chem. Biol. 2017†; 12: 200-205Crossref PubMed Scopus (9) Google Scholar†)CRISPR/Cas9 mediated KO of EV markers and biogenesis components (e.g., Rab27a, nSMase2)(Poggio et al., 2019Poggio M. Hu T.J. Pai C.C. Chu B. Belair C.D. Chang A. Maontabana E. Lang U.E. Fu Q. Fong L. et al.Suppression of PD-L1 secreted in exosomes promotes systemic anti-tumor immunity and memory.Cell. 2019††; 177 (this issue): 414-427Abstract Full Text Full Text PDF Scopus (0) Google Scholar††)CellsSensor cells that report on exRNA activity(Kamiyama et al., 2016Kamiyama D. Sekine S. Barsi-Rhyne B. Hu J. Chen B. Gilbert L.A. Ishikawa H. Leonetti M.D. Marshall W.F. Weissman J.S. Huang B. Versatile protein tagging in cells with split fluorescent protein.Nat. Commun. 2016†; 7: 11046Crossref PubMed Google Scholar†)Mouse ModelsModels of cancer with secretion of fluorescently tagged tumor-derived EVs(Bronevetsky et al., 2013Bronevetsky Y. Villarino A.V. Eisley C.J. Barbeau R. Barczak A.J. Heinz G.A. Kremmer E. Heissmeyer V. McManus M.T. Erle D.J. et al.T cell activation induces proteasomal degradation of Argonaute and rapid remodeling of the microRNA repertoire.J. Exp. Med. 2013†; 210: 417-432Crossref PubMed Scopus (92) Google Scholar†; Farmer et al., 2017†Farmer D.T. Nathan S. Finley J.K. Shengyang Yu K. Emmerson E. Byrnes L.E. Sneddon J.B. McManus M.T. Tward A.D. Knox S.M. Defining epithelial cell dynamics and lineage relationships in the developing lacrimal gland.Development. 2017†; 144: 2517-2528Crossref PubMed Scopus (5) Google Scholar†; Lim et al., 2014Lim L. Balakrishnan A. Huskey N. Jones K.D. Jodari M. Ng R. Song G. Riordan J. Anderton B. Cheung S.T. et al.MicroRNA-494 within an oncogenic microRNA megacluster regulates G1/S transition in liver tumorigenesis through suppression of mutated in colorectal cancer.Hepatology. 2014†; 59: 202-215Crossref PubMed Scopus (79) Google Scholar†; van der Vos et al., 2016van der Vos K.E. Abels E.R. Zhang X. Lai C. Carrizosa E. Oakley D. Prabhakar S. Mardini O. Crommentuijn M.H. Skog J. et al.Directly visualized glioblastoma-derived extracellular vesicles transfer RNA to microglia/macrophages in the brain.Neuro-oncol. 2016†; 18: 58-69Crossref PubMed Scopus (66) Google Scholar†)Conditional (cre-Lox) fluorescent exosomal reporter strainsStrains to study miRNA functionProtocolsEV and exRNA isolation protocolsNature Protocol Exchange: 2015.003,004,006,097-100,107-120; 2016.057; 2017.071-079,084; 2018.049,050,052,081, (Hinger et al., 2018Hinger S.A. Cha D.J. Franklin J.L. Higginbotham J.N. Dou Y. Ping J. Shu L. Prasad N. Levy S. Zhang B. et al.Diverse Long RNAs Are Differentially Sorted into Extracellular Vesicles Secreted by Colorectal Cancer Cells.Cell Rep. 2018††; 25: 715-725Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar††; Lee et al., 2018Lee K. Fraser K. Ghaddar B. Yang K. Kim E. Balaj L. Chiocca E.A. Breakefield X.O. Lee H. Weissleder R. Multiplexed Profiling of Single Extracellular Vesicles.ACS Nano. 2018†; 12: 494-503Crossref PubMed Scopus (5) Google Scholar†; Li et al., 2018cLi K. Wong D.K. Hong K.Y. Raffai R.L. Cushioned-Density Gradient Ultracentrifugation (C-DGUC): A Refined and High Performance Method for the Isolation, Characterization, and Use of Exosomes.Methods Mol. Biol. 2018†; 1740: 69-83Crossref PubMed Scopus (5) Google Scholar†; Li et al., 2018dLi K. Wong D.K. Luk F.S. Kim R.Y. Raffai R.L. Isolation of Plasma Lipoproteins as a Source of Extracellular RNA.Methods Mol. Biol. 2018†; 1740: 139-153Crossref PubMed Scopus (3) Google Scholar†; Li et al., 2015Li X. Mauro M. Williams Z. Comparison of plasma extracellular RNA isolation kits reveals kit-dependent biases.Biotechniques. 2015†; 59: 13-17Crossref PubMed Scopus (5) Google Scholar†; Majem et al., 2017Majem B. Li F. Sun J. Wong D.T. RNA Sequencing Analysis of Salivary Extracellular RNA.Methods Mol. Biol. 2017†; 1537: 17-36Crossref PubMed Scopus (1) Google Scholar†; Max et al., 2018†Max K.E.A. Bertram K. Akat K.M. Bogardus K.A. Li J. Morozov P. Ben-Dov I.Z. Li X. Weiss Z.R. Azizian A. et al.Human plasma and serum extracellular small RNA reference profiles and their clinical utility.Proc. Natl. Acad. Sci. USA. 2018†; 115: E5334-E5343Crossref PubMed Scopus (6) Google Scholar†; Patel, 2018Patel T. First Edition. Extracellular RNA: Methods and Protocols. Humana Press, 2018†Google Scholar†; Reátegui et al., 2018Reátegui E. van der Vos K.E. Lai C.P. Zeinali M. Atai N.A. Aldikacti B. Floyd Jr., F.P. H Khankhel A. Thapar V. Hochberg F.H. et al.Engineered nanointerfaces for microfluidic isolation and molecular profiling of tumor-specific extracellular vesicles.Nat. Commun. 2018††; 9: 175Crossref PubMed Scopus (0) Google Scholar†; Srinivasan et al., 2019Srinivasan S. Yeri A. Cheah P.S. Chung A. Danielson K. DeHoff P. Filant J. Laurent C.D. Laurent L.D. Magee R. et al.Small RNA sequencing across diverse biofluids identifies optimal methods for exRNA isolation.Cell. 2019††; 177 (this issue): 446-462Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar††)exRNA detection and quantification protocols(Akat et al., 2014†Akat K.M. Moore-McGriff D. Morozov P. Brown M. Gogakos T. Correa Da Rosa J. Mihailovic A. Sauer M. Ji R. Ramarathnam A. et al.Comparative RNA-sequencing analysis of myocardial and circulating small RNAs in human heart failure and their utility as biomarkers.Proc. Natl. Acad. Sci. USA. 2014†; 111: 11151-11156Crossref PubMed Scopus (0) Google Scholar†; Belair et al., 2019Belair C.D. Hu T. Chu B. Freimer J.W. Cooperberg M.R. Blelloch R.H. High-throughput, Efficient, and Unbiased Capture of Small RNAs from Low-input Samples for Sequencing.Sci. Rep. 2019†; 9: 2262Crossref PubMed Scopus (1) Google Scholar†; Ben-Dov et al., 2016Ben-Dov I.Z. Whalen V.M. Goilav B. Max K.E. Tuschl T. Cell and Microvesicle Urine microRNA Deep Sequencing Profiles from Healthy Individuals: Observations with Potential Impact on Biomarker Studies.PLoS ONE. 2016†; 11: e0147249Crossref PubMed Scopus (0) Google Scholar†; Giraldez et al., 2018Giraldez M.D. Spengler R.M. Etheridge A. Godoy P.M. Barczak A.J. Srinivasan S. De Hoff P.L. Tanriverdi K. Courtright A. Lu S. et al.Comprehensive multi-center assessment of small RNA-seq methods for quantitative miRNA profiling.Nat. Biotechnol. 2018†; 36: 746-757Crossref PubMed Scopus (1) Google Scholar†; Gogakos et al., 2017Gogakos T. Brown M. Garzia A. Meyer C. Hafner M. Tuschl T. Characterizing Expression and Processing of Precursor and Mature Human tRNAs by Hydro-tRNAseq and PAR-CLIP.Cell Rep. 2017†; 20: 1463-1475Abstract Full Text Full Text PDF PubMed Scopus (7) Google Scholar†; Hafner et al., 2012Hafner M. Renwick N. Farazi T.A. Mihailović A. Pena J.T. Tuschl T. Barcoded cDNA library preparation for small RNA profiling by next-generation sequencing.Methods. 2012†; 58: 164-170Crossref PubMed Scopus (71) Google Scholar†; Majem et al., 2017Majem B. Li F. Sun J. Wong D.T. RNA Sequencing Analysis of Salivary Extracellular RNA.Methods Mol. Biol. 2017†; 1537: 17-36Crossref PubMed Scopus (1) Google Scholar†; Patel, 2018Patel T. First Edition. Extracellular RNA: Methods and Protocols. Humana Press, 2018†Google Scholar†; Yeri et al., 2018Yeri A. Courtright A. Danielson K. Hutchins E. Alsop E. Carlson E. Hsieh M. Ziegler O. Das A. Shah R.V. et al.Evaluation of commercially available small RNASeq library preparation kits using low input RNA.BMC Genomics. 2018†; 19: 331Crossref PubMed Scopus (0) Google Scholar†)Datasets and Computational Tools & ResourcesexRNA Portal, a centralized access point for information, data, and resources about exRNAs.http://exRNA.orgexceRpt, a comprehensive analytic platform for extracellular RNA profiling.(Rozowsky and Gerstein, 2019Rozowsky J. Kitchen R.R. Park J.J. Galeev T.R. Diao J. Warrell J. Thistlethwaite W. Subramanian S.L. Milosavljevic A. Gerstein M. exceRpt: A Comprehensive Analytic Platform for Extracellular RNA Profiling.Cell Syst. 2019††; 8 (Published online April 4, 2018)https://doi.org/10.1016/j.cels.2019.03.004Google Scholar††)Virtual BioRepository (VBR), a distributed web-based system for biosample search and exchange between collaborating groups.https://genboree.org/vbr-hub/exRNA Atlas, an on-line resource for exRNA data analysis and sharing.(Ben-Dov et al., 2016Ben-Dov I.Z. Whalen V.M. Goilav B. Max K.E. Tuschl T. Cell and Microvesicle Urine microRNA Deep Sequencing Profiles from Healthy Individuals: Observations with Potential Impact on Biomarker Studies.PLoS ONE. 2016†; 11: e0147249Crossref PubMed Scopus (0) Google Scholar†; Freedman et al., 2016Freedman J.E. Gerstein M. Mick E. Rozowsky J. Levy D. Kitchen R. Das S. Shah R. Danielson K. Beaulieu L. et al.Diverse human extracellular RNAs are widely detected in human plasma.Nat. Commun. 2016†; 7: 11106Crossref PubMed Scopus (56) Google Scholar†; Godoy et al., 2018Godoy P.M. Bhakta N.R. Barczak A.J. Cakmak H. Fisher S. MacKenzie T.C. Patel T. Price R.W. Smith J.F. Woodruff P.G. Erle D.J. Large Differences in Small RNA Composition Between Human Biofluids.Cell Rep. 2018††; 25: 1346-1358Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar††; Murillo et al., 2019††Murillo O.D. Thistlethwaite W. Rozowsky J. Subramanian S.L. Lucero R. Shah N. Jackson A.R. Srinivasan S. Chung A. Laurent C.D. et al.exRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids.Cell. 2019††; 177 (this issue): 463-477Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar††; Saugstad et al., 2017Saugstad J.A. Lusardi T.A. Van Keuren-Jensen K.R. Phillips J.I. Lind B. Harrington C.A. McFarland T.J. Courtright A.L. Reiman R.A. Yeri A.S. et al.Analysis of extracellular RNA in cerebrospinal fluid.J. Extracell. Vesicles. 2017†; 6: 1317577Crossref PubMed Scopus (5) Google Scholar†; Shah et al., 2017aShah R. Murthy V. Pacold M. Danielson K. Tanriverdi K. Larson M.G. Hanspers K. Pico A. Mick E. Reis J. et al.Extracellular RNAs Are Associated With Insulin Resistance and Metabolic Phenotypes.Diabetes Care. 2017†; 40: 546-553Crossref PubMed Scopus (18) Google Scholar†, Shah et al., 2017bShah R. Yeri A. Das A. Courtright-Lim A. Ziegler O. Gervino E. Ocel J. Quintero-Pinzon P. Wooster L. Bailey C.S. et al.Small RNA-seq during acute maximal exercise reveal RNAs involved in vascular inflammation and cardiometabolic health: brief report.Am. J. Physiol. Heart Circ. Physiol. 2017†; 313: H1162-H1167Crossref PubMed Scopus (4) Google Scholar†)Small RNaseq data from biofluids and cell culture conditioned mediaqPCR data from biofluids Open table in a new tab The first goal of ERCC1 was to address the critical need to develop a better understanding of the mechanisms underlying exRNA biogenesis and export, mechanisms of secretion from source cells, uptake into recipient cells, and functions inside recipient cells. Research efforts by ERCC1 investigators have considerably improved our understanding of these processes. Many of these studies also resulted in the development of molecular and informatics tools, technologies, model systems, and imaging modalities, which are available to the broader scientific community, and will enable investigators to more readily approach related studies (Table 1). The second goal was to provide a reliable and reproducible catalog of the exRNA species present in healthy human biofluids. Thus far, exRNA reference profiles for a variety of body fluids, in some cases collected at rest and after physical exercise, have been generated (Ben-Dov et al., 2016Ben-Dov I.Z. Whalen V.M. Goilav B. Max K.E. Tuschl T. Cell and Microvesicle Urine microRNA Deep Sequencing Profiles from Healthy Individuals: Observations with Potential Impact on Biomarker Studies.PLoS ONE. 2016†; 11: e0147249Crossref PubMed Scopus (0) Google Scholar†; Freedman et al., 2016Freedman J.E. Gerstein M. Mick E. Rozowsky J. Levy D. Kitchen R. Das S. Shah R. Danielson K. Beaulieu L. et al.Diverse human extracellular RNAs are widely detected in human plasma.Nat. Commun. 2016†; 7: 11106Crossref PubMed Scopus (56) Google Scholar†; Godoy et al., 2018Godoy P.M. Bhakta N.R. Barczak A.J. Cakmak H. Fisher S. MacKenzie T.C. Patel T. Price R.W. Smith J.F. Woodruff P.G. Erle D.J. Large Differences in Small RNA Composition Between Human Biofluids.Cell Rep. 2018††; 25: 1346-1358Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar††; Saugstad et al., 2017Saugstad J.A. Lusardi T.A. Van Keuren-Jensen K.R. Phillips J.I. Lind B. Harrington C.A. McFarland T.J. Courtright A.L. Reiman R.A. Yeri A.S. et al.Analysis of extracellular RNA in cerebrospinal fluid.J. Extracell. Vesicles. 2017†; 6: 1317577Crossref PubMed Scopus (5) Google Scholar†; Shah et al., 2017bShah R. Yeri A. Das A. Courtright-Lim A. Ziegler O. Gervino E. Ocel J. Quintero-Pinzon P. Wooster L. Bailey C.S. et al.Small RNA-seq during acute maximal exercise reveal RNAs involved in vascular inflammation and cardiometabolic health: brief report.Am. J. Physiol. Heart Circ. Physiol. 2017†; 313: H1162-H1167Crossref PubMed Scopus (4) Google Scholar†; Yeri et al., 2017Yeri A. Courtright A. Reiman R. Carlson E. Beecroft T. Janss A. Siniard A. Richholt R. Balak C. Rozowsky J. et al.Total Extracellular Small RNA Profiles from Plasma, Saliva, and Urine of Healthy Subjects.Sci. Rep. 2017; 7: 44061Crossref PubMed Scopus (0) Google Scholar†). These datasets, along with all other exRNA profiling datasets generated by ERCC1, are accessible at the exRNA Atlas (https://exRNA-Atlas.org). The third goal was to develop computational technologies and tools to enable effective distribution of knowledge and utilization of exRNA profiling data. To accomplish this, the Data Management Resource Repository (DMRR), with input from ERCC1 members, established the exRNA Portal (http://exRNA.org) to serve as a central access point for exRNA resources. The fourth and fifth goals were to rigorously establish the clinical utility of exRNAs as disease biomarkers and therapeutic agents. Several ERCC1 groups worked to establish the utility of exRNAs in diverse biofluids as biomarkers for a broad range of diseases (Table S1, tabs 1–4). Efforts have also been directed at development of exRNA- and EV-based therapeutic agents (Table S1, tab 5), devising mechanisms for the delivery of therapeutic exRNAs (Table S1, tab 6), and screening of drug libraries for exosome biogenesis inhibitors that can be repurposed for cancer treatment (Datta et al., 2017Datta A. Kim H. Lal M. McGee L. Johnson A. Moustafa A.A. Jones J.C. Mondal D. Ferrer M. Abdel-Mageed A.B. Manumycin A suppresses exosome biogenesis and secretion via targeted inhibition of Ras/Raf/ERK1/2 signaling and hnRNP H1 in castration-resistant prostate cancer cells.Cancer Lett. 2017†; 408: 73-81Crossref PubMed Scopus (0) Google Scholar†, Datta et al., 2018Datta A. Kim H. McGee L. Johnson A.E. Talwar S. Marugan J. Southall N. Hu X. Lal M. Mondal D. et al.High-throughput screening identified selective inhibitors of exosome biogenesis and secretion: A drug repurposing strategy for advanced cancer.Sci. Rep. 2018†; 8: 8161Crossref PubMed Scopus (10) Google Scholar†). Interactions among ERCC1 investigators were promoted by twice yearly meetings and monthly conference calls, resulting in the establishment of several collaborative Working Groups to address fundamental gaps in knowledge and technology, and to promote broad dissemination of methods, samples, and data (Figure 1). The sample and assay standards working group focused on standardization of exRNA isolation and profiling methods. The low concentrations of exRNAs in biofluids, their vulnerability to contamination (Wei et al., 2016Wei Z. Batagov A.O. Carter D.R. Krichevsky A.M. Fetal Bovine Serum RNA Interferes with the Cell Culture derived Extracellular RNA.Sci. Rep. 2016; 6: 31175Crossref PubMed Scopus (19) Google Scholar†), the presence of exogenous RNA, and heterogeneity in composition among samples of the same biofluid due to variable contributions from different cell types and exRNA carrier subclasses (Laurent et al., 2015Laurent L.C. Abdel-Mageed A.B. Adelson P.D. Arango J. Balaj L. Breakefield X. Carlson E. Carter B.S. Majem B. Chen C.C. et al.Meeting report: discussions and preliminary findings on extracellular RNA measurement methods from laboratories in the NIH Extracellular RNA Communication Consortium.J. Extracell. Vesicles. 2015; 4: 26533Crossref PubMed Scopus (31) Google Scholar†) all pose challenges to accurate and reproducible measurement. Recognizing that standardization could not be done in a principled manner without understanding the comparative performance of exRNA isolation and measurement methods, this working group embarked upon highly replicated collaborative projects to systematically compare the robustness, inter- and intra-lab reproducibility, and performance of exRNA isolation and measurement methods. An exRNA isolation project involved six ERCC1 labs and consisted of systematic evaluation of the reproducibility and performance of multiple exRNA isolation methods across standardized samples of diverse biofluids, using quantitative reverse transcription PCR (qPCR) and small RNA-seq as the readouts (Srinivasan et al., 2019Srinivasan S. Yeri A. Cheah P.S. Chung A. Danielson K. DeHoff P. Filant J. Laurent C.D. Laurent L.D. Magee R. et al.Small RNA sequencing across diverse biofluids identifies optimal methods for exRNA isolation.Cell. 2019††; 177 (this issue): 446-462Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar††). A key finding of this study was that the reproducibility within methods and concordance among methods varied widely, within and among both biofluids (with the exception of plasma and serum, which were extremely similar) and RNA biotypes. Using computational deconvolution, this study showed that exRNA isolation methods differ substantially in the efficiency and reproducibility with which they access the extracellular exRNAs associated with various carrier subclasses (EVs, RNPs, and LPPs). These results help to explain the low reproducibility observed among published studies and lead to the conclusion that results obtained from a given combination of exRNA isolation method, biofluid, and RNA biotype cannot be assumed to hold true for other combinations. To enable customized selection of the optimal exRNA isolation method for a specific set of miRNAs in a given biofluid, an interactive web-based application, miRDaR (miRNA detection- and reproducibility-based selection of exRNA isolation methods, https://exrna.org/resources/software/mirdar), was developed, which extracts, analyzes, and displays the relevant data from this dataset based on users’ selections. Two other collaborative projects focused on small RNA measurement. The first project compared three small RNA-seq library preparation methods (NEBNext [NEB], NEXTFlex [Bioo], TruSeq [Illumina]), and three targeted miRNA profiling platforms—hybridization-based Fireplex (Abcam), next-generation sequencing-based EdgeSeq (HTG), and qPCR-based miRNome (QIAGEN)—to examine varying input amounts of standardized tissue RNA (from brain, liver, and placenta) and plasma exRNA (Yeri et al., 2018Yeri A. Courtright A. Danielson K. Hutchins E. Alsop E. Carlson E. Hsieh M. Ziegler O. Das A. Shah R.V. et al.Evaluation of commercially available small RNASeq library preparation kits using low input RNA.BMC Genomics. 2018†; 19: 331Crossref PubMed Scopus (0) Google Scholar†). Biological differences among the three tissue miRNA profiles were preserved across all input amounts and profiling methods, particularly for highly expressed miRNAs. For plasma exRNA, the variability attributable to differences among small RNA measurement methods was stronger than that associated with different RNA input amounts. The second project compared four small RNaseq library preparation methods, including methods with fixed and degenerate adapters, using equimolar and ratiometric pools of synthesized small RNAs, to evaluate the absolute and relative bias of each method, and a standardized plasma exRNA sample, to assess inter- and intra-lab reproducibility on a biologically relevant sample type (Giraldez et al., 2018Giraldez M.D. Spengler R.M. Etheridge A. Godoy P.M. Barczak A.J. Srinivasan S. De Hoff P.L. Tanriverdi K. Courtright A. Lu S. et al.Comprehensive multi-center assessment of small RNA-seq methods for quantitative miRNA profiling.Nat. Biotechnol. 2018†; 36: 746-757Crossref PubMed Scopus (1) Google Scholar†). Degenerate adapters markedly decreased sequence-dependent bias, thereby improving library complexity. Despite systematic differences among all methods, relative quantification of any given miRNA with a ≥ 1.5-fold difference in concentration between samples was accurately and reproducibly measured by all methods. The results of these two studies indicate that although there were clear systematic differences among protocols, the overall reproducibility of all of the tested methods was excellent, and relative quantification was preserved among methods. Thus, while a single measurement method should be used for a given study, relevant differences between biological groups should generally be reproducible among studies, even if they used different small RNA measurement methods. The metadata and data standards and analysis working group included computational and data scientists at the DMRR and Data Coordination Center (DCC), as well as other ERCC1 investigators, who focused on development and implementation of computational tools, data quality and metadata standards, workflows for data deposition, and sharing and integrative analysis of data from multiple studies. To address the critical need for a standardized workflow optimized for exRNA data processing, mapping, and normalization, members of this working group developed the exceRpt (extracellular RNA processing toolkit) pipeline (Kaczor-Urbanowicz et al., 2018Kaczor-Urbanowicz K.E. Trivedi H.M. Lima P.O. Camargo P.M. Giannobile W.V. Grogan T.R. Gleber-Netto F.O. Whiteman Y. Li F. Lee H.J. et al.Salivary exRNA biomarkers to detect gingivitis and monitor disease regression.J. Clin. Periodontol. 2018†; 45: 806-817Crossref PubMed Scopus (1) Google Scholar†; Rozowsky and Gerstein, 2019Rozowsky J. Kitchen R.R. Park J.J. Galeev T.R. Diao J. Warrell J. Thistlethwaite W. Subramanian S.L. Milosavljevic A. Gerstein M. exceRpt: A Comprehensive Analytic Platform for Extracellular RNA Profiling.Cell Syst. 2019††; 8 (Published online April 4, 2018)https://doi.org/10.1016/j.cels.2019.03.004Google Scholar††). exceRpt includes a modular cascade of alignments/quantifications against multiple RNA biotypes from diverse species. The default order o