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Jenike AE, Bunkelman B, Perzel Mandell KA, Oduor CI, Chin D, Mair D, Jenike KM, Kim DH, Bailey JA, Rafailovich MH, Rosenberg AZ, Halushka MK. Expression Microdissection for the Analysis of miRNA in a Single-Cell Type. J Transl Med 2023; 103:100133. [PMID: 36990152 PMCID: PMC10524025 DOI: 10.1016/j.labinv.2023.100133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 02/19/2023] [Accepted: 03/02/2023] [Indexed: 03/30/2023] Open
Abstract
Cell-specific microRNA (miRNA) expression estimates are important in characterizing the localization of miRNA signaling within tissues. Much of these data are obtained from cultured cells, a process known to significantly alter miRNA expression levels. Thus, our knowledge of in vivo cell miRNA expression estimates is poor. We previously demonstrated expression microdissection-miRNA-sequencing (xMD-miRNA-seq) to acquire in vivo estimates, directly from formalin-fixed tissues, albeit with a limited yield. In this study, we optimized each step of the xMD process, including tissue retrieval, tissue transfer, film preparation, and RNA isolation, to increase RNA yields and ultimately show strong enrichment for in vivo miRNA expression by qPCR array. These method improvements, such as the development of a noncrosslinked ethylene vinyl acetate membrane, resulted in a 23- to 45-fold increase in miRNA yield, depending on the cell type. By qPCR, miR-200a increased by 14-fold in xMD-derived small intestine epithelial cells, with a concurrent 336-fold reduction in miR-143 relative to the matched nondissected duodenal tissue. xMD is now an optimized method to obtain robust in vivo miRNA expression estimates from cells. xMD will allow formalin-fixed tissues from surgical pathology archives to make theragnostic biomarker discoveries.
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Affiliation(s)
- Ana E Jenike
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Brady Bunkelman
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Kira A Perzel Mandell
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Cliff I Oduor
- Department of Pathology and Laboratory Medicine, Warren Alpert Medical School, Brown University, Providence, Rhode Island
| | - Deborah Chin
- Department of Pathology and Laboratory Medicine, Warren Alpert Medical School, Brown University, Providence, Rhode Island
| | - Devin Mair
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland
| | - Katharine M Jenike
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Deok-Ho Kim
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Jeffrey A Bailey
- Department of Pathology and Laboratory Medicine, Warren Alpert Medical School, Brown University, Providence, Rhode Island
| | - Miriam H Rafailovich
- Department of Materials Science and Chemical Engineering, Stony Brook University, Stony Brook, New York
| | - Avi Z Rosenberg
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Marc K Halushka
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
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Johann DJ, Shin IJ, Roberge A, Laun S, Peterson EA, Liu M, Steliga MA, Muesse J, Emmert-Buck MR, Tangrea MA. Effect of Antigen Retrieval on Genomic DNA From Immunodissected Samples. J Histochem Cytochem 2022; 70:643-658. [PMID: 36129255 PMCID: PMC9527476 DOI: 10.1369/00221554221124163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 08/12/2022] [Indexed: 11/22/2022] Open
Abstract
Immunohistochemical (IHC) staining is an established technique for visualizing proteins in tissue sections for research studies and clinical applications. IHC is increasingly used as a targeting strategy for procurement of labeled cells via tissue microdissection, including immunodissection, computer-aided laser dissection (CALD), expression microdissection (xMD), and other techniques. The initial antigen retrieval (AR) process increases epitope availability and improves staining characteristics; however, the procedure can damage DNA. To better understand the effects of AR on DNA quality and quantity in immunodissected samples, both clinical specimens (KRAS gene mutation positive cases) and model system samples (lung cancer patient-derived xenograft tissue) were subjected to commonly employed AR methods (heat induced epitope retrieval [HIER], protease digestion) and the effects on DNA were assessed by Qubit, fragment analysis, quantitative PCR, digital droplet PCR (ddPCR), library preparation, and targeted sequencing. The data showed that HIER resulted in optimal IHC staining characteristics, but induced significant damage to DNA, producing extensive fragmentation and decreased overall yields. However, neither of the AR methods combined with IHC prevented ddPCR amplification of small amplicons and gene mutations were successfully identified from immunodissected clinical samples. The results indicate for the first time that DNA recovered from immunostained slides after standard AR and IHC processing can be successfully employed for genomic mutation analysis via ddPCR and next-generation sequencing (NGS) short-read methods.
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Affiliation(s)
- Donald J. Johann
- Winthrop P. Rockefeller Cancer Institute,
University of Arkansas for Medical Sciences, Little Rock, Arkansas
| | - Ik Jae Shin
- Winthrop P. Rockefeller Cancer Institute,
University of Arkansas for Medical Sciences, Little Rock, Arkansas
| | | | - Sarah Laun
- Avoneaux Medical Institute, Baltimore,
Maryland
- Alvin & Lois Lapidus Cancer Institute,
Sinai Hospital of Baltimore, LifeBridge Health, Baltimore, Maryland
| | - Erich A. Peterson
- Winthrop P. Rockefeller Cancer Institute,
University of Arkansas for Medical Sciences, Little Rock, Arkansas
| | - Meei Liu
- Winthrop P. Rockefeller Cancer Institute,
University of Arkansas for Medical Sciences, Little Rock, Arkansas
| | - Matthew A. Steliga
- Winthrop P. Rockefeller Cancer Institute,
University of Arkansas for Medical Sciences, Little Rock, Arkansas
| | - Jason Muesse
- Winthrop P. Rockefeller Cancer Institute,
University of Arkansas for Medical Sciences, Little Rock, Arkansas
| | | | - Michael A. Tangrea
- Alvin & Lois Lapidus Cancer Institute,
Sinai Hospital of Baltimore, LifeBridge Health, Baltimore, Maryland
- Biology Department, Loyola University
Maryland, Baltimore, Maryland
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Patil AH, Baran A, Brehm ZP, McCall MN, Halushka MK. A curated human cellular microRNAome based on 196 primary cell types. Gigascience 2022; 11:6675300. [PMID: 36007182 PMCID: PMC9404528 DOI: 10.1093/gigascience/giac083] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 07/01/2022] [Accepted: 07/29/2022] [Indexed: 12/28/2022] Open
Abstract
Background An incomplete picture of the expression distribution of microRNAs (miRNAs) across human cell types has long hindered our understanding of this important regulatory class of RNA. With the continued increase in available public small RNA sequencing datasets, there is an opportunity to more fully understand the general distribution of miRNAs at the cell level. Results From the NCBI Sequence Read Archive, we obtained 6,054 human primary cell datasets and processed 4,184 of them through the miRge3.0 small RNA sequencing alignment software. This dataset was curated down, through shared miRNA expression patterns, to 2,077 samples from 196 unique cell types derived from 175 separate studies. Of 2,731 putative miRNAs listed in miRBase (v22.1), 2,452 (89.8%) were detected. Among reasonably expressed miRNAs, 108 were designated as cell specific/near specific, 59 as infrequent, 52 as frequent, 54 as near ubiquitous, and 50 as ubiquitous. The complexity of cellular microRNA expression estimates recapitulates tissue expression patterns and informs on the miRNA composition of plasma. Conclusions This study represents the most complete reference, to date, of miRNA expression patterns by primary cell type. The data are available through the human cellular microRNAome track at the UCSC Genome Browser (https://genome.ucsc.edu/cgi-bin/hgHubConnect) and an R/Bioconductor package (https://bioconductor.org/packages/microRNAome/).
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Affiliation(s)
- Arun H Patil
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Andrea Baran
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Zachary P Brehm
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Matthew N McCall
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Marc K Halushka
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
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4
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Eggeling F, Hoffmann F. Microdissection—An Essential Prerequisite for Spatial Cancer Omics. Proteomics 2020; 20:e2000077. [DOI: 10.1002/pmic.202000077] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 06/12/2020] [Indexed: 12/12/2022]
Affiliation(s)
- Ferdinand Eggeling
- Department of OtorhinolaryngologyMALDI Imaging and Core Unit Proteome AnalysisDFG Core Unit Jena Biophotonic and Imaging Laboratory (JBIL)Jena University Hospital Am Klinikum 1 Jena 07747 Germany
| | - Franziska Hoffmann
- Department of OtorhinolaryngologyMALDI Imaging and Core Unit Proteome AnalysisDFG Core Unit Jena Biophotonic and Imaging Laboratory (JBIL)Jena University Hospital Am Klinikum 1 Jena 07747 Germany
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Nieuwenhuis TO, Yang SY, Verma RX, Pillalamarri V, Arking DE, Rosenberg AZ, McCall MN, Halushka MK. Consistent RNA sequencing contamination in GTEx and other data sets. Nat Commun 2020; 11:1933. [PMID: 32321923 PMCID: PMC7176728 DOI: 10.1038/s41467-020-15821-9] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Accepted: 03/23/2020] [Indexed: 01/15/2023] Open
Abstract
A challenge of next generation sequencing is read contamination. We use Genotype-Tissue Expression (GTEx) datasets and technical metadata along with RNA-seq datasets from other studies to understand factors that contribute to contamination. Here we report, of 48 analyzed tissues in GTEx, 26 have variant co-expression clusters of four highly expressed and pancreas-enriched genes (PRSS1, PNLIP, CLPS, and/or CELA3A). Fourteen additional highly expressed genes from other tissues also indicate contamination. Sample contamination is strongly associated with a sample being sequenced on the same day as a tissue that natively expresses those genes. Discrepant SNPs across four contaminating genes validate the contamination. Low-level contamination affects ~40% of samples and leads to numerous eQTL assignments in inappropriate tissues among these 18 genes. This type of contamination occurs widely, impacting bulk and single cell (scRNA-seq) data set analysis. In conclusion, highly expressed, tissue-enriched genes basally contaminate GTEx and other datasets impacting analyses.
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Affiliation(s)
- Tim O Nieuwenhuis
- Department of Pathology, Johns Hopkins University SOM, Baltimore, MD, 21205, USA
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University SOM, Baltimore, MD, 21205, USA
| | - Stephanie Y Yang
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University SOM, Baltimore, MD, 21205, USA
| | - Rohan X Verma
- Department of Pathology, Johns Hopkins University SOM, Baltimore, MD, 21205, USA
| | - Vamsee Pillalamarri
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University SOM, Baltimore, MD, 21205, USA
| | - Dan E Arking
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University SOM, Baltimore, MD, 21205, USA
| | - Avi Z Rosenberg
- Department of Pathology, Johns Hopkins University SOM, Baltimore, MD, 21205, USA
| | - Matthew N McCall
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Marc K Halushka
- Department of Pathology, Johns Hopkins University SOM, Baltimore, MD, 21205, USA.
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Vychytilova-Faltejskova P, Slaby O. MicroRNA-215: From biology to theranostic applications. Mol Aspects Med 2019; 70:72-89. [DOI: 10.1016/j.mam.2019.03.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Revised: 03/10/2019] [Accepted: 03/17/2019] [Indexed: 02/07/2023]
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7
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Bagnasco SM. Beyond the microscope: interpreting renal biopsy findings in the era of precision medicine. Am J Physiol Renal Physiol 2018; 315:F1652-F1655. [PMID: 30280602 DOI: 10.1152/ajprenal.00407.2018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
As rapid progress in science and biotechnology is affecting the practice of renal medicine, increasingly precise diagnostic assessment is needed to select the most effective therapeutic approach for individual patients. The kidney biopsy remains the gold standard for the diagnosis of renal disease, but the field of renal pathology is evolving, classification of renal parenchyma lesions and histopathological diagnostic criteria are undergoing more validation and updates, and new technologies and assays are sought to improve efficiency and accuracy of the diagnostic process. How new knowledge and scientific advances may potentially affect renal pathology is discussed.
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Affiliation(s)
- Serena M Bagnasco
- Department of Pathology, Johns Hopkins School of Medicine , Baltimore, Maryland
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