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Jiang D, Cope AL, Zhang J, Pennell M. On the Decoupling of Evolutionary Changes in mRNA and Protein Levels. Mol Biol Evol 2023; 40:msad169. [PMID: 37498582 PMCID: PMC10411491 DOI: 10.1093/molbev/msad169] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 06/19/2023] [Accepted: 07/14/2023] [Indexed: 07/28/2023] Open
Abstract
Variation in gene expression across lineages is thought to explain much of the observed phenotypic variation and adaptation. The protein is closer to the target of natural selection but gene expression is typically measured as the amount of mRNA. The broad assumption that mRNA levels are good proxies for protein levels has been undermined by a number of studies reporting moderate or weak correlations between the two measures across species. One biological explanation for this discrepancy is that there has been compensatory evolution between the mRNA level and regulation of translation. However, we do not understand the evolutionary conditions necessary for this to occur nor the expected strength of the correlation between mRNA and protein levels. Here, we develop a theoretical model for the coevolution of mRNA and protein levels and investigate the dynamics of the model over time. We find that compensatory evolution is widespread when there is stabilizing selection on the protein level; this observation held true across a variety of regulatory pathways. When the protein level is under directional selection, the mRNA level of a gene and the translation rate of the same gene were negatively correlated across lineages but positively correlated across genes. These findings help explain results from comparative studies of gene expression and potentially enable researchers to disentangle biological and statistical hypotheses for the mismatch between transcriptomic and proteomic data.
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Affiliation(s)
- Daohan Jiang
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Alexander L Cope
- Department of Genetics, Rutgers University, Piscataway, NJ, USA
- Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ, USA
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA
| | - Jianzhi Zhang
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA
| | - Matt Pennell
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
- Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA
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52
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Glass MR, Waxman EA, Yamashita S, Lafferty M, Beltran A, Farah T, Patel NK, Matoba N, Ahmed S, Srivastava M, Drake E, Davis LT, Yeturi M, Sun K, Love MI, Hashimoto-Torii K, French DL, Stein JL. Cross-site reproducibility of human cortical organoids reveals consistent cell type composition and architecture. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.28.550873. [PMID: 37546772 PMCID: PMC10402155 DOI: 10.1101/2023.07.28.550873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Background Reproducibility of human cortical organoid (hCO) phenotypes remains a concern for modeling neurodevelopmental disorders. While guided hCO protocols reproducibly generate cortical cell types in multiple cell lines at one site, variability across sites using a harmonized protocol has not yet been evaluated. We present an hCO cross-site reproducibility study examining multiple phenotypes. Methods Three independent research groups generated hCOs from one induced pluripotent stem cell (iPSC) line using a harmonized miniaturized spinning bioreactor protocol. scRNA-seq, 3D fluorescent imaging, phase contrast imaging, qPCR, and flow cytometry were used to characterize the 3 month differentiations across sites. Results In all sites, hCOs were mostly cortical progenitor and neuronal cell types in reproducible proportions with moderate to high fidelity to the in vivo brain that were consistently organized in cortical wall-like buds. Cross-site differences were detected in hCO size and morphology. Differential gene expression showed differences in metabolism and cellular stress across sites. Although iPSC culture conditions were consistent and iPSCs remained undifferentiated, primed stem cell marker expression prior to differentiation correlated with cell type proportions in hCOs. Conclusions We identified hCO phenotypes that are reproducible across sites using a harmonized differentiation protocol. Previously described limitations of hCO models were also reproduced including off-target differentiations, necrotic cores, and cellular stress. Improving our understanding of how stem cell states influence early hCO cell types may increase reliability of hCO differentiations. Cross-site reproducibility of hCO cell type proportions and organization lays the foundation for future collaborative prospective meta-analytic studies modeling neurodevelopmental disorders in hCOs.
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Affiliation(s)
- Madison R Glass
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Elisa A Waxman
- Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA
| | - Satoshi Yamashita
- Center for Neuroscience Research, Children's National Hospital, Washington, DC
| | - Michael Lafferty
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Alvaro Beltran
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Tala Farah
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Niyanta K Patel
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Nana Matoba
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Sara Ahmed
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Mary Srivastava
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Emma Drake
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Liam T Davis
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Meghana Yeturi
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Kexin Sun
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Michael I Love
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Departments of Pediatrics, and Pharmacology & Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC
| | - Kazue Hashimoto-Torii
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA
| | - Deborah L French
- Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA
| | - Jason L Stein
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
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53
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Cain A, Taga M, McCabe C, Green GS, Hekselman I, White CC, Lee DI, Gaur P, Rozenblatt-Rosen O, Zhang F, Yeger-Lotem E, Bennett DA, Yang HS, Regev A, Menon V, Habib N, De Jager PL. Multicellular communities are perturbed in the aging human brain and Alzheimer's disease. Nat Neurosci 2023; 26:1267-1280. [PMID: 37336975 PMCID: PMC10789499 DOI: 10.1038/s41593-023-01356-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 05/10/2023] [Indexed: 06/21/2023]
Abstract
The role of different cell types and their interactions in Alzheimer's disease (AD) is a complex and open question. Here, we pursued this question by assembling a high-resolution cellular map of the aging frontal cortex using single-nucleus RNA sequencing of 24 individuals with a range of clinicopathologic characteristics. We used this map to infer the neocortical cellular architecture of 638 individuals profiled by bulk RNA sequencing, providing the sample size necessary for identifying statistically robust associations. We uncovered diverse cell populations associated with AD, including a somatostatin inhibitory neuronal subtype and oligodendroglial states. We further identified a network of multicellular communities, each composed of coordinated subpopulations of neuronal, glial and endothelial cells, and we found that two of these communities are altered in AD. Finally, we used mediation analyses to prioritize cellular changes that might contribute to cognitive decline. Thus, our deconstruction of the aging neocortex provides a roadmap for evaluating the cellular microenvironments underlying AD and dementia.
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Affiliation(s)
- Anael Cain
- Edmond & Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Mariko Taga
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Cristin McCabe
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Gilad S Green
- Edmond & Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Idan Hekselman
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | | | - Dylan I Lee
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Pallavi Gaur
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Orit Rozenblatt-Rosen
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Genentech, South San Francisco, CA, USA
| | - Feng Zhang
- Broad Institute, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Esti Yeger-Lotem
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Hyun-Sik Yang
- Broad Institute, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Aviv Regev
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biology, Koch Institute of Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Genentech, South San Francisco, CA, USA
| | - Vilas Menon
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA.
| | - Naomi Habib
- Edmond & Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Philip L De Jager
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA.
- Broad Institute, Cambridge, MA, USA.
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54
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Burns J, Wilding CP, Krasny L, Zhu X, Chadha M, Tam YB, Ps H, Mahalingam AH, Lee ATJ, Arthur A, Guljar N, Perkins E, Pankova V, Jenks A, Djabatey V, Szecsei C, McCarthy F, Ragulan C, Milighetti M, Roumeliotis TI, Crosier S, Finetti M, Choudhary JS, Judson I, Fisher C, Schuster EF, Sadanandam A, Chen TW, Williamson D, Thway K, Jones RL, Cheang MCU, Huang PH. The proteomic landscape of soft tissue sarcomas. Nat Commun 2023; 14:3834. [PMID: 37386008 PMCID: PMC10310735 DOI: 10.1038/s41467-023-39486-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 06/15/2023] [Indexed: 07/01/2023] Open
Abstract
Soft tissue sarcomas (STS) are rare and diverse mesenchymal cancers with limited treatment options. Here we undertake comprehensive proteomic profiling of tumour specimens from 321 STS patients representing 11 histological subtypes. Within leiomyosarcomas, we identify three proteomic subtypes with distinct myogenesis and immune features, anatomical site distribution and survival outcomes. Characterisation of undifferentiated pleomorphic sarcomas and dedifferentiated liposarcomas with low infiltrating CD3 + T-lymphocyte levels nominates the complement cascade as a candidate immunotherapeutic target. Comparative analysis of proteomic and transcriptomic profiles highlights the proteomic-specific features for optimal risk stratification in angiosarcomas. Finally, we define functional signatures termed Sarcoma Proteomic Modules which transcend histological subtype classification and show that a vesicle transport protein signature is an independent prognostic factor for distant metastasis. Our study highlights the utility of proteomics for identifying molecular subgroups with implications for risk stratification and therapy selection and provides a rich resource for future sarcoma research.
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Affiliation(s)
- Jessica Burns
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | | | - Lukas Krasny
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Xixuan Zhu
- Division of Clinical Studies, The Institute of Cancer Research, London, UK
| | - Madhumeeta Chadha
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Yuen Bun Tam
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Hari Ps
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | | | - Alexander T J Lee
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Amani Arthur
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Nafia Guljar
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Emma Perkins
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
- The Royal Marsden NHS Foundation Trust, London, UK
| | - Valeriya Pankova
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Andrew Jenks
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Vanessa Djabatey
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Cornelia Szecsei
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Frank McCarthy
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Chanthirika Ragulan
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Martina Milighetti
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | | | - Stephen Crosier
- Wolfson Childhood Cancer Research Centre, Translational and Clinical Research Institute, Newcastle University Centre for Cancer, Newcastle University, Newcastle upon Tyne, UK
| | - Martina Finetti
- Leeds Institute of Medical Research at St James's, St James's University Hospital, Leeds, UK
| | - Jyoti S Choudhary
- Division of Cancer Biology, The Institute of Cancer Research, London, UK
| | - Ian Judson
- The Royal Marsden NHS Foundation Trust, London, UK
| | - Cyril Fisher
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Eugene F Schuster
- Ralph Lauren Centre for Breast Cancer Research, The Royal Marsden NHS Foundation Trust, London, UK
- Division of Breast Cancer Research, The Institute of Cancer Research, London, UK
| | - Anguraj Sadanandam
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Tom W Chen
- Department of Oncology, National Taiwan University Hospital, Taipei City, Taiwan
- Graduate Institute of Oncology, National Taiwan University College of Medicine Taipei, Taipei City, Taiwan
| | - Daniel Williamson
- Wolfson Childhood Cancer Research Centre, Translational and Clinical Research Institute, Newcastle University Centre for Cancer, Newcastle University, Newcastle upon Tyne, UK
| | - Khin Thway
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
- The Royal Marsden NHS Foundation Trust, London, UK
| | - Robin L Jones
- Division of Clinical Studies, The Institute of Cancer Research, London, UK
- The Royal Marsden NHS Foundation Trust, London, UK
| | - Maggie C U Cheang
- Division of Clinical Studies, The Institute of Cancer Research, London, UK
| | - Paul H Huang
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK.
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55
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Guise AJ, Misal SA, Carson R, Boekweg H, Watt DVD, Truong T, Liang Y, Chu JH, Welsh NC, Gagnon J, Payne SH, Plowey ED, Kelly RT. TDP-43-stratified single-cell proteomic profiling of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.08.544233. [PMID: 37333094 PMCID: PMC10274884 DOI: 10.1101/2023.06.08.544233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Unbiased proteomics has been employed to interrogate central nervous system (CNS) tissues (brain, spinal cord) and fluid matrices (CSF, plasma) from amyotrophic lateral sclerosis (ALS) patients; yet, a limitation of conventional bulk tissue studies is that motor neuron (MN) proteome signals may be confounded by admixed non-MN proteins. Recent advances in trace sample proteomics have enabled quantitative protein abundance datasets from single human MNs (Cong et al., 2020b). In this study, we leveraged laser capture microdissection (LCM) and nanoPOTS (Zhu et al., 2018c) single-cell mass spectrometry (MS)-based proteomics to query changes in protein expression in single MNs from postmortem ALS and control donor spinal cord tissues, leading to the identification of 2515 proteins across MNs samples (>900 per single MN) and quantitative comparison of 1870 proteins between disease groups. Furthermore, we studied the impact of enriching/stratifying MN proteome samples based on the presence and extent of immunoreactive, cytoplasmic TDP-43 inclusions, allowing identification of 3368 proteins across MNs samples and profiling of 2238 proteins across TDP-43 strata. We found extensive overlap in differential protein abundance profiles between MNs with or without obvious TDP-43 cytoplasmic inclusions that together point to early and sustained dysregulation of oxidative phosphorylation, mRNA splicing and translation, and retromer-mediated vesicular transport in ALS. Our data are the first unbiased quantification of single MN protein abundance changes associated with TDP-43 proteinopathy and begin to demonstrate the utility of pathology-stratified trace sample proteomics for understanding single-cell protein abundance changes in human neurologic diseases.
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Affiliation(s)
| | - Santosh A. Misal
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602
| | - Richard Carson
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602
| | - Hannah Boekweg
- Biology Department, Brigham Young University, Provo, UT 84602, USA
| | | | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602
| | - Yiran Liang
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602
| | | | | | | | - Samuel H. Payne
- Biology Department, Brigham Young University, Provo, UT 84602, USA
| | | | - Ryan T. Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602
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56
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Mouratidis I, Chan CY, Chantzi N, Tsiatsianis G, Hemberg M, Ahituv N, Georgakopoulos-Soares I. Quasi-prime peptides: identification of the shortest peptide sequences unique to a species. NAR Genom Bioinform 2023; 5:lqad039. [PMID: 37101657 PMCID: PMC10124967 DOI: 10.1093/nargab/lqad039] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 03/02/2023] [Accepted: 04/06/2023] [Indexed: 04/28/2023] Open
Abstract
Determining the organisms present in a biosample has many important applications in agriculture, wildlife conservation, and healthcare. Here, we develop a universal fingerprint based on the identification of short peptides that are unique to a specific organism. We define quasi-prime peptides as sequences that are found in only one species, and we analyzed proteomes from 21 875 species, from viruses to humans, and annotated the smallest peptide kmer sequences that are unique to a species and absent from all other proteomes. We also perform simulations across all reference proteomes and observe a lower than expected number of peptide kmers across species and taxonomies, indicating an enrichment for nullpeptides, sequences absent from a proteome. For humans, we find that quasi-primes are found in genes enriched for specific gene ontology terms, including proteasome and ATP and GTP catalysis. We also provide a set of quasi-prime peptides for a number of human pathogens and model organisms and further showcase its utility via two case studies for Mycobacterium tuberculosis and Vibrio cholerae, where we identify quasi-prime peptides in two transmembrane and extracellular proteins with relevance for pathogen detection. Our catalog of quasi-prime peptides provides the smallest unit of information that is specific to a single organism at the protein level, providing a versatile tool for species identification.
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Affiliation(s)
- Ioannis Mouratidis
- Department of Biochemistry and Molecular Biology, Penn State College of Medicine, Hershey, PA, USA
- Department of Engineering Science, KU Leuven, Leuven, Belgium
| | - Candace S Y Chan
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Nikol Chantzi
- Department of Biochemistry and Molecular Biology, Penn State College of Medicine, Hershey, PA, USA
| | - Georgios Christos Tsiatsianis
- Department of Biochemistry and Molecular Biology, Penn State College of Medicine, Hershey, PA, USA
- National Technical University of Athens, School of Electrical and Computer Engineering, Athens, Greece
| | - Martin Hemberg
- Evergrande Center for Immunologic Diseases, Harvard Medical School and Brigham and Women's Hospital, Boston, USA
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
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57
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van den Berg PR, Bérenger-Currias NMLP, Budnik B, Slavov N, Semrau S. Integration of a multi-omics stem cell differentiation dataset using a dynamical model. PLoS Genet 2023; 19:e1010744. [PMID: 37167320 DOI: 10.1371/journal.pgen.1010744] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 05/23/2023] [Accepted: 04/14/2023] [Indexed: 05/13/2023] Open
Abstract
Stem cell differentiation is a highly dynamic process involving pervasive changes in gene expression. The large majority of existing studies has characterized differentiation at the level of individual molecular profiles, such as the transcriptome or the proteome. To obtain a more comprehensive view, we measured protein, mRNA and microRNA abundance during retinoic acid-driven differentiation of mouse embryonic stem cells. We found that mRNA and protein abundance are typically only weakly correlated across time. To understand this finding, we developed a hierarchical dynamical model that allowed us to integrate all data sets. This model was able to explain mRNA-protein discordance for most genes and identified instances of potential microRNA-mediated regulation. Overexpression or depletion of microRNAs identified by the model, followed by RNA sequencing and protein quantification, were used to follow up on the predictions of the model. Overall, our study shows how multi-omics integration by a dynamical model could be used to nominate candidate regulators.
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Affiliation(s)
| | | | - Bogdan Budnik
- Mass Spectrometry and Proteomics Resource Laboratory, Harvard University, Cambridge, Massachusetts, United States of America
| | - Nikolai Slavov
- Department of Bioengineering, Northeastern University, Boston, Massachusetts, United States of America
| | - Stefan Semrau
- Leiden Institute of Physics, Leiden University, Leiden, Zuid-Holland, The Netherlands
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58
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Bonnett SA, Rosenbloom AB, Ong GT, Conner M, Rininger AB, Newhouse D, New F, Phan CQ, Ilcisin S, Sato H, Lyssand JS, Geiss G, Beechem JM. Ultra High-plex Spatial Proteogenomic Investigation of Giant Cell Glioblastoma Multiforme Immune Infiltrates Reveals Distinct Protein and RNA Expression Profiles. CANCER RESEARCH COMMUNICATIONS 2023; 3:763-779. [PMID: 37377888 PMCID: PMC10155752 DOI: 10.1158/2767-9764.crc-22-0396] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 01/20/2023] [Accepted: 04/04/2023] [Indexed: 06/29/2023]
Abstract
A deeper understanding of complex biological processes, including tumor development and immune response, requires ultra high-plex, spatial interrogation of multiple "omes". Here we present the development and implementation of a novel spatial proteogenomic (SPG) assay on the GeoMx Digital Spatial Profiler platform with next-generation sequencing readout that enables ultra high-plex digital quantitation of proteins (>100-plex) and RNA (whole transcriptome, >18,000-plex) from a single formalin-fixed paraffin-embedded (FFPE) sample. This study highlighted the high concordance, R > 0.85 and <15% change in sensitivity between the SPG assay and the single-analyte assays on various cell lines and tissues from human and mouse. Furthermore, we demonstrate that the SPG assay was reproducible across multiple users. When used in conjunction with advanced cellular neighborhood segmentation, distinct immune or tumor RNA and protein targets were spatially resolved within individual cell subpopulations in human colorectal cancer and non-small cell lung cancer. We used the SPG assay to interrogate 23 different glioblastoma multiforme (GBM) samples across four pathologies. The study revealed distinct clustering of both RNA and protein based on pathology and anatomic location. The in-depth investigation of giant cell glioblastoma multiforme (gcGBM) revealed distinct protein and RNA expression profiles compared with that of the more common GBM. More importantly, the use of spatial proteogenomics allowed simultaneous interrogation of critical protein posttranslational modifications alongside whole transcriptomic profiles within the same distinct cellular neighborhoods. Significance We describe ultra high-plex spatial proteogenomics; profiling whole transcriptome and high-plex proteomics on a single FFPE tissue section with spatial resolution. Investigation of gcGBM versus GBM revealed distinct protein and RNA expression profiles.
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Affiliation(s)
| | | | | | - Mark Conner
- NanoString Technologies, Seattle, Washington
| | | | | | - Felicia New
- NanoString Technologies, Seattle, Washington
| | - Chi Q. Phan
- NanoString Technologies, Seattle, Washington
| | | | - Hiromi Sato
- NanoString Technologies, Seattle, Washington
| | | | - Gary Geiss
- NanoString Technologies, Seattle, Washington
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59
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Boyle TA, Bossler AD. RNA sequencing steps toward the first line. Cancer 2023. [PMID: 37096746 DOI: 10.1002/cncr.34801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2023]
Abstract
DNA is the sequence that codes for proteins. Messenger RNA is transcribed from the DNA sequence of genes and translated into protein. It can be difficult to predict how a change in the DNA sequence will affect messenger RNA and protein quantity and quality. DNA translocation changes can cause the joining of sequences from two different genes or different parts of the same gene. DNA sequencing is often used clinically to predict how DNA changes might affect proteins. Alternatively, RNA sequencing can be used as a more direct measure of the effect of DNA changes on the protein products. This sequencing is important for identifying changes in cancer that may indicate response to targeted therapy, prognosis, or diagnosis.
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Affiliation(s)
- Theresa A Boyle
- Department of Pathology, Moffitt Cancer Center, Tampa, Florida, USA
| | - Aaron D Bossler
- Department of Pathology, Moffitt Cancer Center, Tampa, Florida, USA
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60
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Jiang D, Cope AL, Zhang J, Pennell M. Decoupling of evolutionary changes in mRNA and protein levels. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.08.536110. [PMID: 37066157 PMCID: PMC10104238 DOI: 10.1101/2023.04.08.536110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Variation in gene expression across lineages is thought to explain much of the observed phenotypic variation and adaptation. The protein is closer to the target of natural selection but gene expression is typically measured as the amount of mRNA. The broad assumption that mRNA levels are good proxies for protein levels has been undermined by a number of studies reporting moderate or weak correlations between the two measures across species. One biological explanation for this discrepancy is that there has been compensatory evolution between the mRNA level and regulation of translation. However, we do not understand the evolutionary conditions necessary for this to occur nor the expected strength of the correlation between mRNA and protein levels. Here we develop a theoretical model for the coevolution of mRNA and protein levels and investigate the dynamics of the model over time. We find that compensatory evolution is widespread when there is stabilizing selection on the protein level, which is true across a variety of regulatory pathways. When the protein level is under directional selection, the mRNA level of a gene and its translation rate of the same gene were negatively correlated across lineages but positively correlated across genes. These findings help explain results from comparative studies of gene expression and potentially enable researchers to disentangle biological and statistical hypotheses for the mismatch between transcriptomic and proteomic studies.
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Affiliation(s)
- Daohan Jiang
- Department of Quantitative and Computational Biology, University of Southern California, USA
| | | | - Jianzhi Zhang
- Department of Ecology and Evolutionary Biology, University of Michigan, USA
| | - Matt Pennell
- Department of Quantitative and Computational Biology, University of Southern California, USA
- Department of Biological Sciences, University of Southern California, USA
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Muckenhuber M, Seufert I, Müller-Ott K, Mallm JP, Klett LC, Knotz C, Hechler J, Kepper N, Erdel F, Rippe K. Epigenetic signals that direct cell type-specific interferon beta response in mouse cells. Life Sci Alliance 2023; 6:e202201823. [PMID: 36732019 PMCID: PMC9900254 DOI: 10.26508/lsa.202201823] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 01/14/2023] [Accepted: 01/16/2023] [Indexed: 02/04/2023] Open
Abstract
The antiviral response induced by type I interferon (IFN) via the JAK-STAT signaling cascade activates hundreds of IFN-stimulated genes (ISGs) across human and mouse tissues but varies between cell types. However, the links between the underlying epigenetic features and the ISG profile are not well understood. We mapped ISGs, binding sites of the STAT1 and STAT2 transcription factors, chromatin accessibility, and histone H3 lysine modification by acetylation (ac) and mono-/tri-methylation (me1, me3) in mouse embryonic stem cells and fibroblasts before and after IFNβ treatment. A large fraction of ISGs and STAT-binding sites was cell type specific with promoter binding of a STAT1/2 complex being a key driver of ISGs. Furthermore, STAT1/2 binding to putative enhancers induced ISGs as inferred from a chromatin co-accessibility analysis. STAT1/2 binding was dependent on the chromatin context and positively correlated with preexisting H3K4me1 and H3K27ac marks in an open chromatin state, whereas the presence of H3K27me3 had an inhibitory effect. Thus, chromatin features present before stimulation represent an additional regulatory layer for the cell type-specific antiviral response.
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Affiliation(s)
- Markus Muckenhuber
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Isabelle Seufert
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Katharina Müller-Ott
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Jan-Philipp Mallm
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
- Single Cell Open Lab, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Lara C Klett
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Caroline Knotz
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Jana Hechler
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Nick Kepper
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Fabian Erdel
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Karsten Rippe
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
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Mar D, Babenko IM, Zhang R, Noble WS, Denisenko O, Vaisar T, Bomsztyk K. MultiomicsTracks96: A high throughput PIXUL-Matrix-based toolbox to profile frozen and FFPE tissues multiomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.16.533031. [PMID: 36993219 PMCID: PMC10055122 DOI: 10.1101/2023.03.16.533031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Background The multiome is an integrated assembly of distinct classes of molecules and molecular properties, or "omes," measured in the same biospecimen. Freezing and formalin-fixed paraffin-embedding (FFPE) are two common ways to store tissues, and these practices have generated vast biospecimen repositories. However, these biospecimens have been underutilized for multi-omic analysis due to the low throughput of current analytical technologies that impede large-scale studies. Methods Tissue sampling, preparation, and downstream analysis were integrated into a 96-well format multi-omics workflow, MultiomicsTracks96. Frozen mouse organs were sampled using the CryoGrid system, and matched FFPE samples were processed using a microtome. The 96-well format sonicator, PIXUL, was adapted to extract DNA, RNA, chromatin, and protein from tissues. The 96-well format analytical platform, Matrix, was used for chromatin immunoprecipitation (ChIP), methylated DNA immunoprecipitation (MeDIP), methylated RNA immunoprecipitation (MeRIP), and RNA reverse transcription (RT) assays followed by qPCR and sequencing. LC-MS/MS was used for protein analysis. The Segway genome segmentation algorithm was used to identify functional genomic regions, and linear regressors based on the multi-omics data were trained to predict protein expression. Results MultiomicsTracks96 was used to generate 8-dimensional datasets including RNA-seq measurements of mRNA expression; MeRIP-seq measurements of m6A and m5C; ChIP-seq measurements of H3K27Ac, H3K4m3, and Pol II; MeDIP-seq measurements of 5mC; and LC-MS/MS measurements of proteins. We observed high correlation between data from matched frozen and FFPE organs. The Segway genome segmentation algorithm applied to epigenomic profiles (ChIP-seq: H3K27Ac, H3K4m3, Pol II; MeDIP-seq: 5mC) was able to recapitulate and predict organ-specific super-enhancers in both FFPE and frozen samples. Linear regression analysis showed that proteomic expression profiles can be more accurately predicted by the full suite of multi-omics data, compared to using epigenomic, transcriptomic, or epitranscriptomic measurements individually. Conclusions The MultiomicsTracks96 workflow is well suited for high dimensional multi-omics studies - for instance, multiorgan animal models of disease, drug toxicities, environmental exposure, and aging as well as large-scale clinical investigations involving the use of biospecimens from existing tissue repositories.
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Koch F, Otten W, Sauerwein H, Reyer H, Kuhla B. Mild heat stress-induced adaptive immune response in blood mononuclear cells and leukocytes from mesenteric lymph nodes of primiparous lactating Holstein cows. J Dairy Sci 2023; 106:3008-3022. [PMID: 36894431 DOI: 10.3168/jds.2022-22520] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 11/12/2022] [Indexed: 03/09/2023]
Abstract
Heat stress negatively affects the metabolism and physiology of the bovine gut. However, it is not known whether heat stress induces an inflammatory response in mesenteric lymph nodes (MLN), the primary origin of gut immune cells, and thus contributes to inflammatory processes in the circulation. Therefore, our objective was to elucidate the effects of chronic heat stress on the systemic activation of acute-phase response in blood, proinflammatory cytokine production in peripheral blood mononuclear cells (PBMC), and the activation of the toll-like receptor signaling (TLR) 2/4 pathway in MLN leucocytes and their chemokines and chemokine receptor profiles in Holstein cows. Primiparous Holstein cows (n = 30; 169 ± 9 d in milk) were exposed to a temperature-humidity index (THI) of 60 [16°C, 63% relative humidity (RH)] for 6 d. Thereafter, cows were evenly assigned to 3 groups: heat-stressed (HS; 28°C, 50% RH, THI = 76), control (CON; 16°C, 69% RH, THI = 60), or pair-feeding (PF; 16°C, 69% RH, THI = 60) for 7 d. On d 6, PBMC were isolated and on d 7 MLN. Plasma haptoglobin, TNFα, and IFNγ concentrations increased more in HS than CON cows. Concomitantly, TNFA mRNA abundance was higher in PBMC and MLN leucocytes of HS than PF cows, whereas IFNG mRNA abundance tended to be higher in MLN leucocytes of HS than PF cows, but not for chemokines (CCL20, CCL25) or chemokine receptors (ITGB7, CCR6, CCR7, CCR9). Furthermore, the TLR2 protein expression tended to be more abundant in MLN leucocytes of HS than PF cows. These results suggest that heat stress induced an adaptive immune response in blood, PBMC, and MLN leukocytes involving the acute-phase protein haptoglobin, proinflammatory cytokine production, and TLR2 signaling in MLN leucocytes. However, chemokines regulating the leucocyte trafficking between MLN and gut seem not to be involved in the adaptive immune response to heat stress.
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Affiliation(s)
- Franziska Koch
- Research Institute for Farm Animal Biology (FBN), Institute of Nutritional Physiology "Oskar Kellner," Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
| | - Winfried Otten
- Research Institute for Farm Animal Biology (FBN), Institute of Behavioural Physiology, Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
| | - Helga Sauerwein
- University of Bonn, Institute of Animal Science, Katzenburgweg 7-9, 53115 Bonn, Germany
| | - Henry Reyer
- Research Institute for Farm Animal Biology (FBN), Institute of Genome Biology, Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
| | - Björn Kuhla
- Research Institute for Farm Animal Biology (FBN), Institute of Nutritional Physiology "Oskar Kellner," Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany.
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Neely BA, Dorfer V, Martens L, Bludau I, Bouwmeester R, Degroeve S, Deutsch EW, Gessulat S, Käll L, Palczynski P, Payne SH, Rehfeldt TG, Schmidt T, Schwämmle V, Uszkoreit J, Vizcaíno JA, Wilhelm M, Palmblad M. Toward an Integrated Machine Learning Model of a Proteomics Experiment. J Proteome Res 2023; 22:681-696. [PMID: 36744821 PMCID: PMC9990124 DOI: 10.1021/acs.jproteome.2c00711] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
In recent years machine learning has made extensive progress in modeling many aspects of mass spectrometry data. We brought together proteomics data generators, repository managers, and machine learning experts in a workshop with the goals to evaluate and explore machine learning applications for realistic modeling of data from multidimensional mass spectrometry-based proteomics analysis of any sample or organism. Following this sample-to-data roadmap helped identify knowledge gaps and define needs. Being able to generate bespoke and realistic synthetic data has legitimate and important uses in system suitability, method development, and algorithm benchmarking, while also posing critical ethical questions. The interdisciplinary nature of the workshop informed discussions of what is currently possible and future opportunities and challenges. In the following perspective we summarize these discussions in the hope of conveying our excitement about the potential of machine learning in proteomics and to inspire future research.
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Affiliation(s)
- Benjamin A Neely
- National Institute of Standards and Technology, Charleston, South Carolina 29412, United States
| | - Viktoria Dorfer
- Bioinformatics Research Group, University of Applied Sciences Upper Austria, Softwarepark 11, 4232 Hagenberg, Austria
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, VIB, 9000 Ghent, Belgium.,Department of Biomolecular Medicine, Faculty of Health Sciences and Medicine, Ghent University, 9000 Ghent, Belgium
| | - Isabell Bludau
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
| | - Robbin Bouwmeester
- VIB-UGent Center for Medical Biotechnology, VIB, 9000 Ghent, Belgium.,Department of Biomolecular Medicine, Faculty of Health Sciences and Medicine, Ghent University, 9000 Ghent, Belgium
| | - Sven Degroeve
- VIB-UGent Center for Medical Biotechnology, VIB, 9000 Ghent, Belgium.,Department of Biomolecular Medicine, Faculty of Health Sciences and Medicine, Ghent University, 9000 Ghent, Belgium
| | - Eric W Deutsch
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | | | - Lukas Käll
- Science for Life Laboratory, KTH - Royal Institute of Technology, 171 21 Solna, Sweden
| | - Pawel Palczynski
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense, Denmark
| | - Samuel H Payne
- Department of Biology, Brigham Young University, Provo, Utah 84602, United States
| | - Tobias Greisager Rehfeldt
- Institute for Mathematics and Computer Science, University of Southern Denmark, 5230 Odense, Denmark
| | | | - Veit Schwämmle
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense, Denmark
| | - Julian Uszkoreit
- Medical Proteome Analysis, Center for Protein Diagnostics (ProDi), Ruhr University Bochum, 44801 Bochum, Germany.,Medizinisches Proteom-Center, Medical Faculty, Ruhr University Bochum, 44801 Bochum, Germany
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Mathias Wilhelm
- Computational Mass Spectrometry, Technical University of Munich (TUM), 85354 Freising, Germany
| | - Magnus Palmblad
- Leiden University Medical Center, Postbus 9600, 2300 RC Leiden, The Netherlands
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Hettinger ZR, Hu S, Mamiya H, Sahu A, Iijima H, Wang K, Gilmer G, Miller A, Nasello G, Dâ Amore A, Vorp DA, Rando TA, Xing J, Ambrosio F. Dynamical modeling reveals RNA decay mediates the effect of matrix stiffness on aged muscle stem cell fate. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.24.529950. [PMID: 36865124 PMCID: PMC9980169 DOI: 10.1101/2023.02.24.529950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2023]
Abstract
Loss of muscle stem cell (MuSC) self-renewal with aging reflects a combination of influences from the intracellular (e.g., post-transcriptional modifications) and extracellular (e.g., matrix stiffness) environment. Whereas conventional single cell analyses have revealed valuable insights into factors contributing to impaired self-renewal with age, most are limited by static measurements that fail to capture nonlinear dynamics. Using bioengineered matrices mimicking the stiffness of young and old muscle, we showed that while young MuSCs were unaffected by aged matrices, old MuSCs were phenotypically rejuvenated by young matrices. Dynamical modeling of RNA velocity vector fields in silico revealed that soft matrices promoted a self-renewing state in old MuSCs by attenuating RNA decay. Vector field perturbations demonstrated that the effects of matrix stiffness on MuSC self-renewal could be circumvented by fine-tuning the expression of the RNA decay machinery. These results demonstrate that post-transcriptional dynamics dictate the negative effect of aged matrices on MuSC self-renewal.
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Impact of Growth Rate on the Protein-mRNA Ratio in Pseudomonas aeruginosa. mBio 2023; 14:e0306722. [PMID: 36475772 PMCID: PMC9973009 DOI: 10.1128/mbio.03067-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Our understanding of how bacterial pathogens colonize and persist during human infection has been hampered by the limited characterization of bacterial physiology during infection and a research bias toward in vitro, fast-growing bacteria. Recent research has begun to address these gaps in knowledge by directly quantifying bacterial mRNA levels during human infection, with the goal of assessing microbial community function at the infection site. However, mRNA levels are not always predictive of protein levels, which are the primary functional units of a cell. Here, we used carefully controlled chemostat experiments to examine the relationship between mRNA and protein levels across four growth rates in the bacterial pathogen Pseudomonas aeruginosa. We found a genome-wide positive correlation between mRNA and protein abundances across all growth rates, with genes required for P. aeruginosa viability having stronger correlations than nonessential genes. We developed a statistical method to identify genes whose mRNA abundances poorly predict protein abundances and calculated an RNA-to-protein (RTP) conversion factor to improve mRNA predictions of protein levels. The application of the RTP conversion factor to publicly available transcriptome data sets was highly robust, enabling the more accurate prediction of P. aeruginosa protein levels across strains and growth conditions. Finally, the RTP conversion factor was applied to P. aeruginosa human cystic fibrosis (CF) infection transcriptomes to provide greater insights into the functionality of this bacterium in the CF lung. This study addresses a critical problem in infection microbiology by providing a framework for enhancing the functional interpretation of bacterial human infection transcriptome data. IMPORTANCE Our understanding of bacterial physiology during human infection is limited by the difficulty in assessing bacterial function at the infection site. Recent studies have begun to address this question by quantifying bacterial mRNA levels in human-derived samples using transcriptomics. One challenge for these studies is the poor predictivity of mRNA for protein levels for some genes. Here, we addressed this challenge by measuring the transcriptomes and proteomes of P. aeruginosa grown at four growth rates. Our results revealed that the growth rate does not impact the genome-wide correlation of mRNA and protein levels. We used statistical methods to identify the genes for which mRNA and protein were poorly correlated and developed an RNA-to-protein (RTP) conversion factor that improved the predictivity of protein levels across strains and growth conditions. Our results provide new insights into mRNA-protein correlations and tools to enhance our understanding of bacterial physiology from transcriptome data.
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Santos L, Nascimento R, Duarte A, Railean V, Amaral MD, Harrison PT, Gama-Carvalho M, Farinha CM. Mutation-class dependent signatures outweigh disease-associated processes in cystic fibrosis cells. Cell Biosci 2023; 13:26. [PMID: 36759923 PMCID: PMC9912517 DOI: 10.1186/s13578-023-00975-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 01/28/2023] [Indexed: 02/11/2023] Open
Abstract
BACKGROUND The phenotypic heterogeneity observed in Cystic Fibrosis (CF) patients suggests the involvement of other genes, besides CFTR. Here, we combined transcriptome and proteome analysis to understand the global gene expression patterns associated with five prototypical CFTR mutations. RESULTS Evaluation of differentially expressed genes and proteins unveiled common and mutation-specific changes revealing functional signatures that are much more associated with the specific molecular defects associated with each mutation than to the CFTR loss-of-function phenotype. The combination of both datasets revealed that mutation-specific detected translated-transcripts (Dtt) have a high level of consistency. CONCLUSIONS This is the first combined transcriptomic and proteomic study focusing on prototypical CFTR mutations. Analysis of Dtt provides novel insight into the pathophysiology of CF, and the mechanisms through which each mutation class causes disease and will likely contribute to the identification of new therapeutic targets and/or biomarkers for CF.
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Affiliation(s)
- Lúcia Santos
- grid.9983.b0000 0001 2181 4263BioISI – Instituto de Biossistemas e Ciências Integrativas, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal ,grid.7872.a0000000123318773Department of Physiology, University College Cork, Cork, T12 K8AF Ireland
| | - Rui Nascimento
- grid.9983.b0000 0001 2181 4263BioISI – Instituto de Biossistemas e Ciências Integrativas, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal
| | - Aires Duarte
- grid.9983.b0000 0001 2181 4263BioISI – Instituto de Biossistemas e Ciências Integrativas, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal
| | - Violeta Railean
- grid.9983.b0000 0001 2181 4263BioISI – Instituto de Biossistemas e Ciências Integrativas, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal
| | - Margarida D. Amaral
- grid.9983.b0000 0001 2181 4263BioISI – Instituto de Biossistemas e Ciências Integrativas, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal
| | - Patrick T. Harrison
- grid.7872.a0000000123318773Department of Physiology, University College Cork, Cork, T12 K8AF Ireland
| | - Margarida Gama-Carvalho
- grid.9983.b0000 0001 2181 4263BioISI – Instituto de Biossistemas e Ciências Integrativas, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal
| | - Carlos M. Farinha
- grid.9983.b0000 0001 2181 4263BioISI – Instituto de Biossistemas e Ciências Integrativas, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal
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Fornasiero EF, Savas JN. Determining and interpreting protein lifetimes in mammalian tissues. Trends Biochem Sci 2023; 48:106-118. [PMID: 36163144 PMCID: PMC9868050 DOI: 10.1016/j.tibs.2022.08.011] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 08/29/2022] [Accepted: 08/30/2022] [Indexed: 01/26/2023]
Abstract
The orchestration of protein production and degradation, and the regulation of protein lifetimes, play a central role in the majority of biological processes. Recent advances in proteomics have enabled the estimation of protein half-lives for thousands of proteins in vivo. What is the utility of these measurements, and how can they be leveraged to interpret the proteome changes occurring during development, aging, and disease? This opinion article summarizes leading technical approaches and highlights their strengths and weaknesses. We also disambiguate frequently used terminology, illustrate recent mechanistic insights, and provide guidance for interpreting and validating protein turnover measurements. Overall, protein lifetimes, coupled to estimates of protein levels, are essential for obtaining a deep understanding of mammalian biology and the basic processes defining life itself.
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Affiliation(s)
- Eugenio F Fornasiero
- Department of Neuro-Sensory Physiology, University Medical Center Göttingen, 37073 Göttingen, Germany.
| | - Jeffrey N Savas
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
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ECPPF (E2F1, CCNA2, POLE, PPP2R1A, FBXW7) stratification: Profiling high-risk subtypes of histomorphologically low-risk and treatment-insensitive endometrioid endometrial cancer. PLoS One 2022; 17:e0278408. [PMID: 36454788 PMCID: PMC9714733 DOI: 10.1371/journal.pone.0278408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 11/15/2022] [Indexed: 12/03/2022] Open
Abstract
In endometrial cancer, occult high-risk subtypes (rooted in histomorphologically low-risk disease) with insensitivity to adjuvant therapies impede improvements in therapeutic efficacy. Therefore, we aimed to assess the ability of molecular high-risk (MHR) and low-risk (MLR) ECPPF (E2F1, CCNA2, POLE, PPP2R1A, FBXW7) stratification to profile recurrence in early, low-risk endometrioid endometrial cancer (EEC) and insensitivity to platinum-based chemotherapy or radiotherapy (or both) in high-risk EEC. Using The Cancer Genome Atlas endometrial cancer database, we identified 192 EEC cases with available DNA sequencing and RNA expression data. Molecular parameters were integrated with clinicopathologic risk factors and adverse surveillance events. MHR was defined as high (-H) CCNA2 or E2F1 log2 expression (≥2.75), PPP2R1A mutations (-mu), or FBXW7mu; MLR was defined as low (-L) CCNA2 and E2F1 log2 expression (<2.75). We assessed 164 cases, plus another 28 with POLEmu for favorable-outcomes comparisons. MHR and MLR had significantly different progression-free survival (PFS) rates (P < .001), independent of traditional risk factors (eg, TP53mu), except for stage IV disease. PFS of CCNA2-L/E2F1-L paralleled that of POLEmu. ECPPF status stratified responses to adjuvant therapy in stage III-IV EEC (P < .01) and profiled stage I, grade 1-2 cases with risk of recurrence (P < .001). MHR was associated with CTNNB1mu-linked treatment failures (P < .001). Expression of homologous recombination repair (HR) and cell cycle genes was significantly elevated in CCNA2-H/E2F1-H compared with CCNA2-L/E2F1-L (P<1.0E-10), suggesting that HR deficiencies may underlie the favorable PFS in MLR. HRmu were detected in 20.7%. No treatment failures were observed in high-grade or advanced EEC with HRmu (P = .02). Favorable PFS in clinically high-risk EEC was associated with HRmu and MLR ECPPF (P < .001). In summary, MLR ECPPF and HRmu were associated with therapeutic efficacy in EEC. MHR ECPPF was associated with low-risk, early-stage recurrences and insensitivity to adjuvant therapies.
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Chou J, Trepka K, Sjöström M, Egusa EA, Chu CE, Zhu J, Chan E, Gibb EA, Badura ML, Contreras-Sanz A, Stohr BA, Meng MV, Pruthi RS, Lotan Y, Black PC, Porten SP, Koshkin VS, Friedlander TW, Feng FY. TROP2 Expression Across Molecular Subtypes of Urothelial Carcinoma and Enfortumab Vedotin-resistant Cells. Eur Urol Oncol 2022; 5:714-718. [PMID: 35216942 PMCID: PMC10262920 DOI: 10.1016/j.euo.2021.11.005] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 11/06/2021] [Accepted: 11/17/2021] [Indexed: 02/02/2023]
Abstract
Sacituzumab govitecan (SG) is an antibody-drug conjugate (ADC) targeting TROP2, which has recently been approved for treatment-refractory metastatic urothelial cancer (UC). However, the variability of TROP2 expression across different bladder cancer (BC) subtypes, as well as after enfortumab vedotin (EV) exposure, remains unknown. Using gene expression data from four clinical cohorts with >1400 patient samples of muscle-invasive BC and a BC tissue microarray, we found that TROP2 mRNA and protein are highly expressed across basal, luminal, and stroma-rich subtypes, but depleted in the neuroendocrine subtype. In addition, TROP2 mRNA levels are correlated with NECTIN4 mRNA but are more highly expressed than NECTIN4 mRNA in patient cohorts and BC cell lines. Moreover, CRISPR/Cas9-mediated knockdown of TROP2 demonstrates that its expression is one factor governing SG sensitivity. After prolonged EV exposure, cells can downregulate NECTIN4, leading to EV resistance, but retain TROP2 expression and remain sensitive to SG, suggesting nonoverlapping resistance mechanisms to these ADCs. While our findings warrant further validation, they have significant implications for biomarker development, patient selection, and treatment sequencing in the clinic as well as clinical trial design and stratification for metastatic BC patients. PATIENT SUMMARY: In this report, we investigated the expression levels of the drug target TROP2 across different molecular subtypes of bladder cancer in multiple patient cohorts and cell lines. We found high levels of TROP2 in most subtypes except in the neuroendocrine subtype. Overall, TROP2 gene expression is higher than NECTIN4 gene expression, and cells resistant to enfortumab vedotin (EV), a NECTIN4-targeting antibody-drug conjugate, remain sensitive to sacituzumab govitecan (SG). Our findings suggest that SG may be effective across most bladder cancer subtypes, including the bladder cancers previously treated with EV.
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Affiliation(s)
- Jonathan Chou
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, CA, USA; UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA.
| | - Kai Trepka
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, CA, USA; UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA; Department of Radiation Oncology, University of California, San Francisco, CA, USA; Medical Scientist Training Program, University of California, San Francisco, CA, USA
| | - Martin Sjöström
- UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA; Department of Radiation Oncology, University of California, San Francisco, CA, USA
| | - Emily A Egusa
- UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA; Department of Radiation Oncology, University of California, San Francisco, CA, USA
| | - Carissa E Chu
- UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, CA, USA
| | - Jun Zhu
- UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA; Department of Radiation Oncology, University of California, San Francisco, CA, USA
| | - Emily Chan
- UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA; Department of Pathology, University of California, San Francisco, CA, USA
| | - Ewan A Gibb
- Decipher Biosciences, Inc., San Diego, CA, USA
| | - Michelle L Badura
- UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA; Department of Radiation Oncology, University of California, San Francisco, CA, USA
| | | | - Bradley A Stohr
- UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA; Department of Pathology, University of California, San Francisco, CA, USA
| | - Maxwell V Meng
- UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, CA, USA
| | - Raj S Pruthi
- UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, CA, USA
| | - Yair Lotan
- Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Peter C Black
- Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Sima P Porten
- UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, CA, USA
| | - Vadim S Koshkin
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, CA, USA; UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA
| | - Terence W Friedlander
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, CA, USA; UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA
| | - Felix Y Feng
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, CA, USA; UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA; Department of Radiation Oncology, University of California, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, CA, USA.
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Differential expression of immune-regulatory proteins C5AR1, CLEC4A and NLRP3 on peripheral blood mononuclear cells in early-stage non-small cell lung cancer patients. Sci Rep 2022; 12:18439. [PMID: 36323738 PMCID: PMC9630369 DOI: 10.1038/s41598-022-21891-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 10/05/2022] [Indexed: 01/06/2023] Open
Abstract
Changes in gene expression profiling of peripheral blood mononuclear cells (PBMC) appear to represent the host's response to the cancer cells via paracrine signaling. We speculated that protein expression on circulating T-lymphocytes represent T-lymphocyte trafficking before infiltration into the tumor microenvironment. The possibility of using protein expression on circulating T-lymphocytes as a biomarker to discriminate early-stage non-small cell lung cancer (NSCLC) was explored. Four independent PBMC gene expression microarray datasets (GSE12771, GSE13255, GSE20189 and GSE3934) were analyzed. We selected C5AR1, CLEC4A and NLRP3 based on their significant protein expression in tumor-infiltrating lymphocytes, but not in normal lymphoid tissue. A validation study using automated flow cytometry was conducted in 141 study participants including 76 treatment-naive early-stage non-small cell lung cancer patients (NSCLC), 12 individuals with non-malignant pulmonary diseases, and 53 healthy individuals. Median ratios of C5AR1, CLEC4A and NLRP3 specific antibody staining to CD3 positive cells in early-stage NSCLC patients compared to healthy controls were 0.014 [0-0.37] vs. 0.01 [0-0.07, p = 0.13], 0.03 [0-0.87] vs. 0.02 [0-0.13, p = 0.10] and 0.19 [0-0.60] vs. 0.09 [0.02-0.31, p < 0.0001], respectively. Median fluorescence intensity (MFI) of CD3+C5AR1+, CD3+CLEC4A+ and CD3+NLRP3+ expression in early-stage NSCLC patients compared to healthy volunteers was 185 [64.2-4801] vs. 107.5 [27-229, p < 0.0001], 91.2 [42.4-2355] vs. 71.25 [46.2-103, p = 0.0005], and 1585 [478-5224] vs. 758.5 [318-1976, p < 0.0001], respectively. NLRP3:CD3 ratio, CD3+C5AR1+, CD3+CLEC4A+ and CD3+NLRP3+ MFI were significantly higher in early-stage NSCLC than healthy volunteers with an area under the ROC curve of 0.69-0.76. The CD3+NLRP3+ MFI provided the most distinguishable expression at 71.5% sensitivity and 70% specificity. Furthermore, CD3+NLRP3+ MFI potentially discriminated between early-stage NSCLC from malignant-mimic inflammation and infection pulmonary disease. Further validation in various pulmonary inflammatory disease might be warranted. Our proof-of-principle findings strengthen the hypothesis that malignancies generate distinctive protein expression fingerprints on circulating T-lymphocytes.
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Gambichler T, Elfering J, Meyer T, Bruckmüller S, Stockfleth E, Skrygan M, Käfferlein HU, Brüning T, Lang K, Wagener D, Schröder S, Nick M, Susok L. Protein expression of prognostic genes in primary melanoma and benign nevi. J Cancer Res Clin Oncol 2022; 148:2673-2680. [PMID: 34757537 PMCID: PMC9470607 DOI: 10.1007/s00432-021-03779-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 08/25/2021] [Indexed: 11/22/2022]
Abstract
PURPOSE To evaluate the protein expression characteristics of genes employed in a recently introduced prognostic gene expression assay for patients with cutaneous melanoma (CM). METHODS We studied 37 patients with CM and 10 with benign (melanocytic) nevi (BN). Immunohistochemistry of primary tumor tissue was performed for eight proteins: COL6A6, DCD, GBP4, KLHL41, KRT9, PIP, SCGB1D2, SCGB2A2. RESULTS The protein expression of most markers investigated was relatively low (e.g., DCD, KRT9, SCGB1D2) and predominantly cytoplasmatic in melanocytes and keratinocytes. COL6A6, GBP4, and KLHL41 expression was significantly enhanced in CM when compared to BN. DCD protein expression was significantly correlated with COL6A6, GBP4, and KLHL41. GBP4 was positively correlated with KLHL41 and inversely correlated with SCGB2B2. The latter was also inversely correlated with serum S100B levels at time of initial diagnosis. The presence of SCGB1D2 expression was significantly associated with ulceration of the primary tumor. KRT9 protein expression was significantly more likely found in acral lentiginous melanoma. The presence of DCD expression was less likely associated with superficial spreading melanoma subtype but significantly associated with non-progressive disease. The absence of SCGB2A2 expression was significantly more often observed in patients who did not progress to stage III or IV. CONCLUSIONS The expression levels observed were relatively low but differed in part with those found in BN. Even though we detected some significant correlations between the protein expression levels and clinical parameters (e.g., CM subtype, course of disease), there was no major concordance with the protective or risk-associated functions of the corresponding genes included in a recently introduced prognostic gene expression assay.
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Affiliation(s)
- T Gambichler
- Skin Cancer Center, Department of Dermatology, Ruhr-University Bochum, Bochum, Germany.
| | - J Elfering
- Skin Cancer Center, Department of Dermatology, Ruhr-University Bochum, Bochum, Germany
| | - T Meyer
- Skin Cancer Center, Department of Dermatology, Ruhr-University Bochum, Bochum, Germany
| | - S Bruckmüller
- Skin Cancer Center, Department of Dermatology, Ruhr-University Bochum, Bochum, Germany
| | - E Stockfleth
- Skin Cancer Center, Department of Dermatology, Ruhr-University Bochum, Bochum, Germany
| | - M Skrygan
- Skin Cancer Center, Department of Dermatology, Ruhr-University Bochum, Bochum, Germany
| | - H U Käfferlein
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurances, Ruhr-University Bochum (IPA), Bochum, Germany
| | - T Brüning
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurances, Ruhr-University Bochum (IPA), Bochum, Germany
| | - K Lang
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurances, Ruhr-University Bochum (IPA), Bochum, Germany
| | - D Wagener
- Pathology/Labor Lademannbogen MVZ GmbH, Hamburg, Germany
| | - S Schröder
- Pathology/Labor Lademannbogen MVZ GmbH, Hamburg, Germany
| | - M Nick
- Skin Cancer Center, Department of Dermatology, Ruhr-University Bochum, Bochum, Germany
| | - L Susok
- Skin Cancer Center, Department of Dermatology, Ruhr-University Bochum, Bochum, Germany
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73
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Theillet FX, Luchinat E. In-cell NMR: Why and how? PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2022; 132-133:1-112. [PMID: 36496255 DOI: 10.1016/j.pnmrs.2022.04.002] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 04/19/2022] [Accepted: 04/27/2022] [Indexed: 06/17/2023]
Abstract
NMR spectroscopy has been applied to cells and tissues analysis since its beginnings, as early as 1950. We have attempted to gather here in a didactic fashion the broad diversity of data and ideas that emerged from NMR investigations on living cells. Covering a large proportion of the periodic table, NMR spectroscopy permits scrutiny of a great variety of atomic nuclei in all living organisms non-invasively. It has thus provided quantitative information on cellular atoms and their chemical environment, dynamics, or interactions. We will show that NMR studies have generated valuable knowledge on a vast array of cellular molecules and events, from water, salts, metabolites, cell walls, proteins, nucleic acids, drugs and drug targets, to pH, redox equilibria and chemical reactions. The characterization of such a multitude of objects at the atomic scale has thus shaped our mental representation of cellular life at multiple levels, together with major techniques like mass-spectrometry or microscopies. NMR studies on cells has accompanied the developments of MRI and metabolomics, and various subfields have flourished, coined with appealing names: fluxomics, foodomics, MRI and MRS (i.e. imaging and localized spectroscopy of living tissues, respectively), whole-cell NMR, on-cell ligand-based NMR, systems NMR, cellular structural biology, in-cell NMR… All these have not grown separately, but rather by reinforcing each other like a braided trunk. Hence, we try here to provide an analytical account of a large ensemble of intricately linked approaches, whose integration has been and will be key to their success. We present extensive overviews, firstly on the various types of information provided by NMR in a cellular environment (the "why", oriented towards a broad readership), and secondly on the employed NMR techniques and setups (the "how", where we discuss the past, current and future methods). Each subsection is constructed as a historical anthology, showing how the intrinsic properties of NMR spectroscopy and its developments structured the accessible knowledge on cellular phenomena. Using this systematic approach, we sought i) to make this review accessible to the broadest audience and ii) to highlight some early techniques that may find renewed interest. Finally, we present a brief discussion on what may be potential and desirable developments in the context of integrative studies in biology.
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Affiliation(s)
- Francois-Xavier Theillet
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198 Gif-sur-Yvette, France.
| | - Enrico Luchinat
- Dipartimento di Scienze e Tecnologie Agro-Alimentari, Alma Mater Studiorum - Università di Bologna, Piazza Goidanich 60, 47521 Cesena, Italy; CERM - Magnetic Resonance Center, and Neurofarba Department, Università degli Studi di Firenze, 50019 Sesto Fiorentino, Italy
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74
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Wang SY, Huang YH, Liang YJ, Wu JC. Gene coexpression network analysis identifies hubs in hepatitis B virus-associated hepatocellular carcinoma. J Chin Med Assoc 2022; 85:972-980. [PMID: 35801949 DOI: 10.1097/jcma.0000000000000772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is among the leading causes of cancer-related death worldwide. The molecular pathogenesis of HCC involves multiple signaling pathways. This study utilizes systems and bioinformatic approaches to investigate the pathogenesis of HCC. METHODS Gene expression microarray data were obtained from 50 patients with chronic hepatitis B and HCC. There were 1649 differentially expressed genes inferred from tumorous and nontumorous datasets. Weighted gene coexpression network analysis (WGCNA) was performed to construct clustered coexpressed gene modules. Statistical analysis was used to study the correlation between gene coexpression networks and demographic features of patients. Functional annotation and pathway inference were explored for each coexpression network. Network analysis identified hub genes of the prognostic gene coexpression network. The hub genes were further validated with a public database. RESULT Five distinct gene coexpression networks were identified by WGCNA. A distinct coexpressed gene network was significantly correlated with HCC prognosis. Pathway analysis of this network revealed extensive integration with cell cycle regulation. Ten hub genes of this gene network were inferred from protein-protein interaction network analysis and further validated in an external validation dataset. Survival analysis showed that lower expression of the 10-gene signature had better overall survival and recurrence-free survival. CONCLUSION This study identified a crucial gene coexpression network associated with the prognosis of hepatitis B virus-related HCC. The identified hub genes may provide insights for HCC pathogenesis and may be potential prognostic markers or therapeutic targets.
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Affiliation(s)
- Shen-Yung Wang
- Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Division of Gastroenterology and Hepatology, Department of Medicine, MacKay Memorial Hospital, Taipei, Taiwan, ROC
| | - Yen-Hua Huang
- Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Center for Systems and Synthetic Biology, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
| | - Yuh-Jin Liang
- Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Cancer Progression Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Medical Research Department, Taipei Veterans General Hospital, Taipei, Taiwan, ROC
| | - Jaw-Ching Wu
- Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Cancer Progression Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Medical Research Department, Taipei Veterans General Hospital, Taipei, Taiwan, ROC
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75
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Chakraborty S, Andrieux G, Kastl P, Adlung L, Altamura S, Boehm ME, Schwarzmüller LE, Abdullah Y, Wagner MC, Helm B, Gröne HJ, Lehmann WD, Boerries M, Busch H, Muckenthaler MU, Schilling M, Klingmüller U. Erythropoietin-driven dynamic proteome adaptations during erythropoiesis prevent iron overload in the developing embryo. Cell Rep 2022; 40:111360. [PMID: 36130519 DOI: 10.1016/j.celrep.2022.111360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 06/22/2022] [Accepted: 08/23/2022] [Indexed: 11/26/2022] Open
Abstract
Erythropoietin (Epo) ensures survival and proliferation of colony-forming unit erythroid (CFU-E) progenitor cells and their differentiation to hemoglobin-containing mature erythrocytes. A lack of Epo-induced responses causes embryonic lethality, but mechanisms regulating the dynamic communication of cellular alterations to the organismal level remain unresolved. By time-resolved transcriptomics and proteomics, we show that Epo induces in CFU-E cells a gradual transition from proliferation signature proteins to proteins indicative for differentiation, including heme-synthesis enzymes. In the absence of the Epo receptor (EpoR) in embryos, we observe a lack of hemoglobin in CFU-E cells and massive iron overload of the fetal liver pointing to a miscommunication between liver and placenta. A reduction of iron-sulfur cluster-containing proteins involved in oxidative phosphorylation in these embryos leads to a metabolic shift toward glycolysis. This link connecting erythropoiesis with the regulation of iron homeostasis and metabolic reprogramming suggests that balancing these interactions is crucial for protection from iron intoxication and for survival.
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Affiliation(s)
- Sajib Chakraborty
- Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; Systems Cell-Signalling Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka 1000, Bangladesh
| | - Geoffroy Andrieux
- Institute of Medical Bioinformatics and Systems Medicine, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79110 Freiburg, Germany; German Cancer Consortium (DKTK), Freiburg, Germany and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Philipp Kastl
- Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Lorenz Adlung
- Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; Department of Medicine & Hamburg Center for Translational Immunology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | - Sandro Altamura
- Center for Translational Biomedical Iron Research (CeTBI), Department of Pediatric Hematology, Oncology and Immunology, Heidelberg University, 69120 Heidelberg, Germany
| | - Martin E Boehm
- Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Luisa E Schwarzmüller
- Division Molecular Genome Analysis, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Yomn Abdullah
- Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Marie-Christine Wagner
- Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Barbara Helm
- Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Hermann-Josef Gröne
- Division Cellular and Molecular Pathology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Wolf D Lehmann
- Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Melanie Boerries
- Institute of Medical Bioinformatics and Systems Medicine, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79110 Freiburg, Germany; German Cancer Consortium (DKTK), Freiburg, Germany and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; Comprehensive Cancer Center Freiburg (CCCF), Medical Center-University of Freiburg, University of Freiburg, 79106 Freiburg im Breisgau, Germany.
| | - Hauke Busch
- Institute of Medical Bioinformatics and Systems Medicine, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79110 Freiburg, Germany; Institute of Experimental Dermatology, University of Lübeck, 23562 Lübeck, Germany.
| | - Martina U Muckenthaler
- Center for Translational Biomedical Iron Research (CeTBI), Department of Pediatric Hematology, Oncology and Immunology, Heidelberg University, 69120 Heidelberg, Germany; Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), 69120 Heidelberg, Germany; German Center for Cardiovascular Research, Partner Site Heidelberg/Mannheim, 69120 Heidelberg, Germany.
| | - Marcel Schilling
- Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
| | - Ursula Klingmüller
- Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), 69120 Heidelberg, Germany.
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Marklund M, Schultz N, Friedrich S, Berglund E, Tarish F, Tanoglidi A, Liu Y, Bergenstråhle L, Erickson A, Helleday T, Lamb AD, Sonnhammer E, Lundeberg J. Spatio-temporal analysis of prostate tumors in situ suggests pre-existence of treatment-resistant clones. Nat Commun 2022; 13:5475. [PMID: 36115838 PMCID: PMC9482614 DOI: 10.1038/s41467-022-33069-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 08/30/2022] [Indexed: 11/25/2022] Open
Abstract
The molecular mechanisms underlying lethal castration-resistant prostate cancer remain poorly understood, with intratumoral heterogeneity a likely contributing factor. To examine the temporal aspects of resistance, we analyze tumor heterogeneity in needle biopsies collected before and after treatment with androgen deprivation therapy. By doing so, we are able to couple clinical responsiveness and morphological information such as Gleason score to transcriptome-wide data. Our data-driven analysis of transcriptomes identifies several distinct intratumoral cell populations, characterized by their unique gene expression profiles. Certain cell populations present before treatment exhibit gene expression profiles that match those of resistant tumor cell clusters, present after treatment. We confirm that these clusters are resistant by the localization of active androgen receptors to the nuclei in cancer cells post-treatment. Our data also demonstrates that most stromal cells adjacent to resistant clusters do not express the androgen receptor, and we identify differentially expressed genes for these cells. Altogether, this study shows the potential to increase the power in predicting resistant tumors.
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Affiliation(s)
- Maja Marklund
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Solna, Sweden
| | - Niklas Schultz
- Division of Translational Medicine & Chemical Biology, Karolinska Institute, Science for Life Laboratory, Solna, Sweden
| | - Stefanie Friedrich
- Department of Biochemistry and Biophysics, Stockholm University, Science for Laboratory, Solna, Sweden
| | - Emelie Berglund
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Solna, Sweden
| | - Firas Tarish
- Division of Translational Medicine & Chemical Biology, Karolinska Institute, Science for Life Laboratory, Solna, Sweden
| | - Anna Tanoglidi
- Department of Pathology, Evangelismos General Hospital, 45-47 Ipsilantou str, Athens, Greece
| | - Yao Liu
- Division of Translational Medicine & Chemical Biology, Karolinska Institute, Science for Life Laboratory, Solna, Sweden
| | - Ludvig Bergenstråhle
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Solna, Sweden
| | - Andrew Erickson
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Thomas Helleday
- Division of Translational Medicine & Chemical Biology, Karolinska Institute, Science for Life Laboratory, Solna, Sweden
| | - Alastair D Lamb
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Erik Sonnhammer
- Department of Biochemistry and Biophysics, Stockholm University, Science for Laboratory, Solna, Sweden.
| | - Joakim Lundeberg
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Solna, Sweden.
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Schneider EH, Fitzgerald AC, Ponnapula SS, Dopico AM, Bukiya AN. Differential distribution of cholesterol pools across arteries under high-cholesterol diet. Biochim Biophys Acta Mol Cell Biol Lipids 2022; 1867:159235. [PMID: 36113825 DOI: 10.1016/j.bbalip.2022.159235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 08/26/2022] [Accepted: 09/05/2022] [Indexed: 11/19/2022]
Abstract
Excessive cholesterol constitutes a major risk factor for vascular disease. Within cells, cholesterol is distributed in detergent-sensitive and detergent-resistant fractions, with the largest amount of cholesterol residing in cellular membranes. We set out to determine whether various arteries differ in their ability to accumulate esterified and non-esterified cholesterol in detergent-sensitive versus detergent-resistant fractions throughout the course of a high-cholesterol diet. Male Sprague-Dawley rats were placed on 2 % cholesterol diet while a control group was receiving iso-caloric standard chow. Liver, aorta, and pulmonary, mesenteric, and cerebral arteries were collected at 2-6, 8-12, 14-18, and 20-24 weeks from the start of high-cholesterol diet. After fraction separation, esterified and free non-esterified cholesterol levels were measured. In all arteries, largest cholesterol amounts were present in detergent-sensitive fractions in the non-esterified form. Overall, cholesterol in aorta and cerebral arteries was elevated during 14-18 weeks of high-cholesterol diet. Cerebral arteries also exhibited increase in esterified cholesterol within detergent-sensitive domains, as well as increase in cholesterol level in the detergent-resistant fraction at earlier time-points of diet. Pulmonary artery and mesenteric artery were largely resistant to cholesterol accumulation. Quantitative polymerase chain reaction (qPCR) analysis revealed up-regulation of low-density lipoprotein receptor (Ldlr) and low-density lipoprotein receptor-related protein 1 (Lrp1) gene expression in cerebral arteries when compared to mesenteric and pulmonary arteries, respectively. In summary, we unveiled the differential ability of arteries to accumulate cholesterol over the course of a high-cholesterol diet. The differential accumulation of cholesterol seems to correlate with the up-regulated gene expression of proteins responsible for cholesterol uptake.
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Affiliation(s)
- Elizabeth H Schneider
- Department of Pharmacology, Addiction Science and Toxicology, College of Medicine, The University of Tennessee Health Science Center, Memphis, TN 38163, United States
| | - Amanda C Fitzgerald
- Department of Pharmacology, Addiction Science and Toxicology, College of Medicine, The University of Tennessee Health Science Center, Memphis, TN 38163, United States
| | - Supriya Suzy Ponnapula
- Department of Pharmacology, Addiction Science and Toxicology, College of Medicine, The University of Tennessee Health Science Center, Memphis, TN 38163, United States
| | - Alex M Dopico
- Department of Pharmacology, Addiction Science and Toxicology, College of Medicine, The University of Tennessee Health Science Center, Memphis, TN 38163, United States
| | - Anna N Bukiya
- Department of Pharmacology, Addiction Science and Toxicology, College of Medicine, The University of Tennessee Health Science Center, Memphis, TN 38163, United States.
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The Activity of Chelidonium majus L. Latex and Its Components on HPV Reveal Insights into the Antiviral Molecular Mechanism. Int J Mol Sci 2022; 23:ijms23169241. [PMID: 36012505 PMCID: PMC9409487 DOI: 10.3390/ijms23169241] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/10/2022] [Accepted: 08/11/2022] [Indexed: 11/21/2022] Open
Abstract
Yellow-orange latex of Chelidonium majus L. has been used in folk medicine as a therapeutic agent against warts and other visible symptoms of human papillomavirus (HPV) infections for centuries. The observed antiviral and antitumor properties of C. majus latex are often attributed to alkaloids contained therein, but recent studies indicate that latex proteins may also play an important role in its pharmacological activities. Therefore, the aim of the study was to investigate the effect of the crude C. majus latex and its protein and alkaloid-rich fractions on different stages of the HPV replication cycle. The results showed that the latex components, such as alkaloids and proteins, decrease HPV infectivity and inhibit the expression of viral oncogenes (E6, E7) on mRNA and protein levels. However, the crude latex and its fractions do not affect the stability of structural proteins in HPV pseudovirions and they do not inhibit the virus from attaching to the cell surface. In addition, the protein fraction causes increased TNFα secretion, which may indicate the induction of an inflammatory response. These findings indicate that the antiviral properties of C. majus latex arise both from alkaloids and proteins contained therein, acting on different stages of the viral replication cycle.
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79
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Manes NP, Calzola JM, Kaplan PR, Fraser IDC, Germain RN, Meier-Schellersheim M, Nita-Lazar A. Absolute protein quantitation of the mouse macrophage Toll-like receptor and chemotaxis pathways. Sci Data 2022; 9:491. [PMID: 35961990 PMCID: PMC9374760 DOI: 10.1038/s41597-022-01612-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 08/04/2022] [Indexed: 11/24/2022] Open
Abstract
The Toll-like receptor (TLR) and chemotaxis pathways are key components of the innate immune system. Subtle variation in the concentration, timing, and molecular structure of the ligands are known to affect downstream signaling and the resulting immune response. Computational modeling and simulation at the molecular interaction level can be used to study complex biological pathways, but such simulations require protein concentration values as model parameters. Here we report the development and application of targeted mass spectrometry assays to measure the absolute abundance of proteins of the mouse macrophage Toll-like receptor 4 (TLR4) and chemotaxis pathways. Two peptides per protein were quantified, if possible. The protein abundance values ranged from 1,332 to 227,000,000 copies per cell. They moderately correlated with transcript abundance values from a previously published mouse macrophage RNA-seq dataset, and these two datasets were combined to make proteome-wide abundance estimates. The datasets produced during this investigation can be used for pathway modeling and simulation, as well as for other studies of the TLR and chemotaxis pathways. Measurement(s) | molecules per cell | Technology Type(s) | nanoflow high-performance liquid chromatography-electrospray ionisation tandem mass spectrometry | Sample Characteristic - Organism | Mus musculus |
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Affiliation(s)
- Nathan P Manes
- Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Jessica M Calzola
- Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Pauline R Kaplan
- Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Iain D C Fraser
- Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Ronald N Germain
- Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Martin Meier-Schellersheim
- Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Aleksandra Nita-Lazar
- Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA.
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80
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Nam KH, Ordureau A. Quantitative proteome remodeling characterization of two human reference pluripotent stem cell lines during neurogenesis and cardiomyogenesis. Proteomics 2022; 22:e2100246. [PMID: 35871287 PMCID: PMC10389174 DOI: 10.1002/pmic.202100246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 07/05/2022] [Accepted: 07/18/2022] [Indexed: 11/08/2022]
Abstract
Human pluripotent stem cells (PSCs) have become popular tools within the research community to study developmental and model diseases. While many induced-PSCs (iPSCs) from various genetic background sources are currently available, scientific advancement has been hampered by the considerable phenotypic variations observed between different iPSC lines. A recent collaborative effort selected a novel iPSC line to address this and encourage the adoption of a standardized iPSC line termed KOLF2.1J. Here, leveraging the multiplexing power of isobaric labeling, we systematically investigate, at the 10k proteome level, the relative protein abundance profiles of the KOLF2.1J reference iPSC line upon two distinct cell state differentiation trajectories. In addition, we side-by-side systematically compare this line with the H9 line, an established embryonically derived PSC line that we previously characterized. We noticed differences in the basal proteome of the two cell lines and highlighted the differentially expressed proteins. While the difference between the cell line's proteome subsisted upon differentiation, the global proteome remodeling trajectory was highly similar during the tested differentiation routes. We thus conclude that the KOLF2.1J line performs well at the proteome level upon the neuro and cardiomyogenesis differentiation protocol used. We believe this dataset will serve as a resource of value for the research community.
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Affiliation(s)
- Ki Hong Nam
- Cell Biology Program Sloan Kettering Institute Memorial Sloan Kettering Cancer Center New York New York 10065 USA
| | - Alban Ordureau
- Cell Biology Program Sloan Kettering Institute Memorial Sloan Kettering Cancer Center New York New York 10065 USA
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81
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Miedema SSM, Mol MO, Koopmans FTW, Hondius DC, van Nierop P, Menden K, de Veij Mestdagh CF, van Rooij J, Ganz AB, Paliukhovich I, Melhem S, Li KW, Holstege H, Rizzu P, van Kesteren RE, van Swieten JC, Heutink P, Smit AB. Distinct cell type-specific protein signatures in GRN and MAPT genetic subtypes of frontotemporal dementia. Acta Neuropathol Commun 2022; 10:100. [PMID: 35799292 PMCID: PMC9261008 DOI: 10.1186/s40478-022-01387-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 05/22/2022] [Indexed: 11/16/2022] Open
Abstract
Frontotemporal dementia is characterized by progressive atrophy of frontal and/or temporal cortices at an early age of onset. The disorder shows considerable clinical, pathological, and genetic heterogeneity. Here we investigated the proteomic signatures of frontal and temporal cortex from brains with frontotemporal dementia due to GRN and MAPT mutations to identify the key cell types and molecular pathways in their pathophysiology. We compared patients with mutations in the GRN gene (n = 9) or with mutations in the MAPT gene (n = 13) with non-demented controls (n = 11). Using quantitative proteomic analysis on laser-dissected tissues we identified brain region-specific protein signatures for both genetic subtypes. Using published single cell RNA expression data resources we deduced the involvement of major brain cell types in driving these different protein signatures. Subsequent gene ontology analysis identified distinct genetic subtype- and cell type-specific biological processes. For the GRN subtype, we observed a distinct role for immune processes related to endothelial cells and for mitochondrial dysregulation in neurons. For the MAPT subtype, we observed distinct involvement of dysregulated RNA processing, oligodendrocyte dysfunction, and axonal impairments. Comparison with an in-house protein signature of Alzheimer’s disease brains indicated that the observed alterations in RNA processing and oligodendrocyte function are distinct for the frontotemporal dementia MAPT subtype. Taken together, our results indicate the involvement of different brain cell types and biological mechanisms in genetic subtypes of frontotemporal dementia. Furthermore, we demonstrate that comparison of proteomic profiles of different disease entities can separate general neurodegenerative processes from disease-specific pathways, which may aid the development of disease subtype-specific treatment strategies.
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Affiliation(s)
- Suzanne S M Miedema
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, W&N Building, C314. De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands.
| | - Merel O Mol
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Frank T W Koopmans
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, W&N Building, C314. De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands
| | - David C Hondius
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, W&N Building, C314. De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands
| | - Pim van Nierop
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, W&N Building, C314. De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands
| | - Kevin Menden
- German Center for Neurodegenerative Diseases (DZNE)-Tübingen, Tübingen, Germany
| | - Christina F de Veij Mestdagh
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, W&N Building, C314. De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands.,Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, Groningen, the Netherlands.,Alzheimer Center, Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
| | - Jeroen van Rooij
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands.,Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Andrea B Ganz
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, W&N Building, C314. De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands.,Alzheimer Center, Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
| | - Iryna Paliukhovich
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, W&N Building, C314. De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands
| | - Shamiram Melhem
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ka Wan Li
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, W&N Building, C314. De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands
| | - Henne Holstege
- Alzheimer Center, Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands.,Department of Clinical Genetics, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
| | - Patrizia Rizzu
- German Center for Neurodegenerative Diseases (DZNE)-Tübingen, Tübingen, Germany
| | - Ronald E van Kesteren
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, W&N Building, C314. De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands
| | - John C van Swieten
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands.,Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Peter Heutink
- German Center for Neurodegenerative Diseases (DZNE)-Tübingen, Tübingen, Germany
| | - August B Smit
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, W&N Building, C314. De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands
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82
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Liu ZSJ, Truong TTT, Bortolasci CC, Spolding B, Panizzutti B, Swinton C, Kim JH, Kidnapillai S, Richardson MF, Gray L, Dean OM, McGee SL, Berk M, Walder K. Effects of Psychotropic Drugs on Ribosomal Genes and Protein Synthesis. Int J Mol Sci 2022; 23:ijms23137180. [PMID: 35806181 PMCID: PMC9266764 DOI: 10.3390/ijms23137180] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 06/26/2022] [Accepted: 06/26/2022] [Indexed: 02/04/2023] Open
Abstract
Altered protein synthesis has been implicated in the pathophysiology of several neuropsychiatric disorders, particularly schizophrenia. Ribosomes are the machinery responsible for protein synthesis. However, there remains little information on whether current psychotropic drugs affect ribosomes and contribute to their therapeutic effects. We treated human neuronal-like (NT2-N) cells with amisulpride (10 µM), aripiprazole (0.1 µM), clozapine (10 µM), lamotrigine (50 µM), lithium (2.5 mM), quetiapine (50 µM), risperidone (0.1 µM), valproate (0.5 mM) or vehicle control for 24 h. Transcriptomic and gene set enrichment analysis (GSEA) identified that the ribosomal pathway was altered by these drugs. We found that three of the eight drugs tested significantly decreased ribosomal gene expression, whilst one increased it. Most changes were observed in the components of cytosolic ribosomes and not mitochondrial ribosomes. Protein synthesis assays revealed that aripiprazole, clozapine and lithium all decreased protein synthesis. Several currently prescribed psychotropic drugs seem to impact ribosomal gene expression and protein synthesis. This suggests the possibility of using protein synthesis inhibitors as novel therapeutic agents for neuropsychiatric disorders.
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Affiliation(s)
- Zoe S. J. Liu
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong 3220, Australia; (Z.S.J.L.); (T.T.T.T.); (C.C.B.); (B.S.); (B.P.); (C.S.); (J.H.K.); (S.K.); (L.G.); (O.M.D.); (S.L.M.); (M.B.)
| | - Trang T. T. Truong
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong 3220, Australia; (Z.S.J.L.); (T.T.T.T.); (C.C.B.); (B.S.); (B.P.); (C.S.); (J.H.K.); (S.K.); (L.G.); (O.M.D.); (S.L.M.); (M.B.)
| | - Chiara C. Bortolasci
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong 3220, Australia; (Z.S.J.L.); (T.T.T.T.); (C.C.B.); (B.S.); (B.P.); (C.S.); (J.H.K.); (S.K.); (L.G.); (O.M.D.); (S.L.M.); (M.B.)
| | - Briana Spolding
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong 3220, Australia; (Z.S.J.L.); (T.T.T.T.); (C.C.B.); (B.S.); (B.P.); (C.S.); (J.H.K.); (S.K.); (L.G.); (O.M.D.); (S.L.M.); (M.B.)
| | - Bruna Panizzutti
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong 3220, Australia; (Z.S.J.L.); (T.T.T.T.); (C.C.B.); (B.S.); (B.P.); (C.S.); (J.H.K.); (S.K.); (L.G.); (O.M.D.); (S.L.M.); (M.B.)
| | - Courtney Swinton
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong 3220, Australia; (Z.S.J.L.); (T.T.T.T.); (C.C.B.); (B.S.); (B.P.); (C.S.); (J.H.K.); (S.K.); (L.G.); (O.M.D.); (S.L.M.); (M.B.)
| | - Jee Hyun Kim
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong 3220, Australia; (Z.S.J.L.); (T.T.T.T.); (C.C.B.); (B.S.); (B.P.); (C.S.); (J.H.K.); (S.K.); (L.G.); (O.M.D.); (S.L.M.); (M.B.)
- Florey Institute of Neuroscience and Mental Health, Parkville 3010, Australia
| | - Srisaiyini Kidnapillai
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong 3220, Australia; (Z.S.J.L.); (T.T.T.T.); (C.C.B.); (B.S.); (B.P.); (C.S.); (J.H.K.); (S.K.); (L.G.); (O.M.D.); (S.L.M.); (M.B.)
| | - Mark F. Richardson
- Genomics Centre, School of Life and Environmental Sciences, Deakin University, Burwood 3125, Australia;
| | - Laura Gray
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong 3220, Australia; (Z.S.J.L.); (T.T.T.T.); (C.C.B.); (B.S.); (B.P.); (C.S.); (J.H.K.); (S.K.); (L.G.); (O.M.D.); (S.L.M.); (M.B.)
- Florey Institute of Neuroscience and Mental Health, Parkville 3010, Australia
| | - Olivia M. Dean
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong 3220, Australia; (Z.S.J.L.); (T.T.T.T.); (C.C.B.); (B.S.); (B.P.); (C.S.); (J.H.K.); (S.K.); (L.G.); (O.M.D.); (S.L.M.); (M.B.)
- Florey Institute of Neuroscience and Mental Health, Parkville 3010, Australia
| | - Sean L. McGee
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong 3220, Australia; (Z.S.J.L.); (T.T.T.T.); (C.C.B.); (B.S.); (B.P.); (C.S.); (J.H.K.); (S.K.); (L.G.); (O.M.D.); (S.L.M.); (M.B.)
| | - Michael Berk
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong 3220, Australia; (Z.S.J.L.); (T.T.T.T.); (C.C.B.); (B.S.); (B.P.); (C.S.); (J.H.K.); (S.K.); (L.G.); (O.M.D.); (S.L.M.); (M.B.)
- Florey Institute of Neuroscience and Mental Health, Parkville 3010, Australia
| | - Ken Walder
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong 3220, Australia; (Z.S.J.L.); (T.T.T.T.); (C.C.B.); (B.S.); (B.P.); (C.S.); (J.H.K.); (S.K.); (L.G.); (O.M.D.); (S.L.M.); (M.B.)
- Correspondence:
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83
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Cai ML, Gui L, Huang H, Zhang YK, Zhang L, Chen Z, Sheng YJ. Proteomic Analyses Reveal Higher Levels of Neutrophil Activation in Men Than in Women With Systemic Lupus Erythematosus. Front Immunol 2022; 13:911997. [PMID: 35799787 PMCID: PMC9254905 DOI: 10.3389/fimmu.2022.911997] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Accepted: 05/26/2022] [Indexed: 11/15/2022] Open
Abstract
Objective Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease that displays a significant gender difference in terms of incidence and severity. However, the underlying mechanisms accounting for sexual dimorphism remain unclear. The aim of this work was to reveal the heterogeneity in the pathogenesis of SLE between male and female patients. Methods PBMC were collected from 15 patients with SLE (7 males, 8 females) and 15 age-matched healthy controls (7 males, 8 females) for proteomic analysis. The proteins of interest were validated in independent samples (6 male SLE, 6 female SLE). Biomarkers for neutrophil activation (calprotectin), neutrophil extracellular traps (cell-free DNA and elastase), and reactive oxygen species (glutathione) were measured, using enzyme-linked immunosorbent assay, in plasma obtained from 52 individuals. Results Enrichment analysis of proteomic data revealed that type I interferon signaling and neutrophil activation networks mapped to both male and female SLE, while male SLE has a higher level of neutrophil activation compared with female SLE. Western blot validated that PGAM1, BST2, and SERPINB10 involved in neutrophil activation are more abundant in male SLE than in female SLE. Moreover, biomarkers of neutrophil activation and reactive oxygen species were increased in male SLE compared with female SLE. Conclusion Type I interferon activation is a common signature in both male and female SLE, while neutrophil activation is more prominent in male SLE compared with female SLE. Our findings define gender heterogeneity in the pathogenesis of SLE and may facilitate the development of gender-specific treatments.
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Affiliation(s)
- Ming-long Cai
- Department of Rheumatology and Immunology, the First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Lan Gui
- Institute of Dermatology and Department of Dermatology of the First Affiliated Hospital, Anhui Medical University, Hefei, China
| | - He Huang
- Institute of Dermatology and Department of Dermatology of the First Affiliated Hospital, Anhui Medical University, Hefei, China
| | - Yu-kun Zhang
- Institute of Dermatology and Department of Dermatology of the First Affiliated Hospital, Anhui Medical University, Hefei, China
| | - Li Zhang
- Institute of Dermatology and Department of Dermatology of the First Affiliated Hospital, Anhui Medical University, Hefei, China
| | - Zhu Chen
- Department of Rheumatology and Immunology, the First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Yu-jun Sheng
- Institute of Dermatology and Department of Dermatology of the First Affiliated Hospital, Anhui Medical University, Hefei, China
- *Correspondence: Yu-jun Sheng,
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84
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Giansanti P, Samaras P, Bian Y, Meng C, Coluccio A, Frejno M, Jakubowsky H, Dobiasch S, Hazarika RR, Rechenberger J, Calzada-Wack J, Krumm J, Mueller S, Lee CY, Wimberger N, Lautenbacher L, Hassan Z, Chang YC, Falcomatà C, Bayer FP, Bärthel S, Schmidt T, Rad R, Combs SE, The M, Johannes F, Saur D, de Angelis MH, Wilhelm M, Schneider G, Kuster B. Mass spectrometry-based draft of the mouse proteome. Nat Methods 2022; 19:803-811. [PMID: 35710609 DOI: 10.1038/s41592-022-01526-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 05/17/2022] [Indexed: 01/06/2023]
Abstract
The laboratory mouse ranks among the most important experimental systems for biomedical research and molecular reference maps of such models are essential informational tools. Here, we present a quantitative draft of the mouse proteome and phosphoproteome constructed from 41 healthy tissues and several lines of analyses exemplify which insights can be gleaned from the data. For instance, tissue- and cell-type resolved profiles provide protein evidence for the expression of 17,000 genes, thousands of isoforms and 50,000 phosphorylation sites in vivo. Proteogenomic comparison of mouse, human and Arabidopsis reveal common and distinct mechanisms of gene expression regulation and, despite many similarities, numerous differentially abundant orthologs that likely serve species-specific functions. We leverage the mouse proteome by integrating phenotypic drug (n > 400) and radiation response data with the proteomes of 66 pancreatic ductal adenocarcinoma (PDAC) cell lines to reveal molecular markers for sensitivity and resistance. This unique atlas complements other molecular resources for the mouse and can be explored online via ProteomicsDB and PACiFIC.
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Affiliation(s)
- Piero Giansanti
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Patroklos Samaras
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Yangyang Bian
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany.,College of Life Science, Northwest University, Xi'an, China
| | - Chen Meng
- Bavarian Biomolecular Mass Spectrometry Center, Technical University of Munich, Freising, Germany
| | - Andrea Coluccio
- Division of Translational Cancer Research, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.,Chair of Translational Cancer Research and Institute for Experimental Cancer Therapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.,Department of Internal Medicine II, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,Center for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, Munich, Germany
| | - Martin Frejno
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Hannah Jakubowsky
- Division of Translational Cancer Research, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.,Chair of Translational Cancer Research and Institute for Experimental Cancer Therapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.,Department of Internal Medicine II, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,Center for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, Munich, Germany
| | - Sophie Dobiasch
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,Institute of Radiation Medicine, Department of Radiation Sciences, Helmholtz Zentrum München, Neuherberg, Germany.,German Cancer Consortium (DKTK), Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rashmi R Hazarika
- Population epigenetics and epigenomics, Technical University of Munich, Freising, Germany.,Institute of Advanced Study (IAS), Technical University of Munich, Freising, Germany
| | - Julia Rechenberger
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Julia Calzada-Wack
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Johannes Krumm
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Sebastian Mueller
- Department of Internal Medicine II, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,Center for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, Munich, Germany.,Institute of Molecular Oncology and Functional Genomics, School of Medicine, Technical University of Munich, Munich, Germany
| | - Chien-Yun Lee
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Nicole Wimberger
- Division of Translational Cancer Research, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.,Chair of Translational Cancer Research and Institute for Experimental Cancer Therapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.,Department of Internal Medicine II, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,Center for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, Munich, Germany
| | - Ludwig Lautenbacher
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Zonera Hassan
- Medical Clinic and Policlinic II, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Yun-Chien Chang
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Chiara Falcomatà
- Division of Translational Cancer Research, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.,Chair of Translational Cancer Research and Institute for Experimental Cancer Therapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.,Department of Internal Medicine II, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,Center for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, Munich, Germany
| | - Florian P Bayer
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Stefanie Bärthel
- Division of Translational Cancer Research, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.,Chair of Translational Cancer Research and Institute for Experimental Cancer Therapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.,Department of Internal Medicine II, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,Center for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, Munich, Germany
| | - Tobias Schmidt
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Roland Rad
- Division of Translational Cancer Research, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.,Department of Internal Medicine II, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,Center for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, Munich, Germany.,Institute of Molecular Oncology and Functional Genomics, School of Medicine, Technical University of Munich, Munich, Germany
| | - Stephanie E Combs
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,Institute of Radiation Medicine, Department of Radiation Sciences, Helmholtz Zentrum München, Neuherberg, Germany.,German Cancer Consortium (DKTK), Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Matthew The
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
| | - Frank Johannes
- Population epigenetics and epigenomics, Technical University of Munich, Freising, Germany.,Institute of Advanced Study (IAS), Technical University of Munich, Freising, Germany
| | - Dieter Saur
- Division of Translational Cancer Research, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.,Chair of Translational Cancer Research and Institute for Experimental Cancer Therapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.,Department of Internal Medicine II, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,Center for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, Munich, Germany
| | - Martin Hrabe de Angelis
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.,Chair of Experimental Genetics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.,German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Mathias Wilhelm
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany.,Computational Mass Spectrometry, Technical University of Munich, Freising, Germany
| | - Günter Schneider
- Medical Clinic and Policlinic II, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,University Medical Center Göttingen, Department of General, Visceral and Pediatric Surgery, Göttingen, Germany
| | - Bernhard Kuster
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany. .,Bavarian Biomolecular Mass Spectrometry Center, Technical University of Munich, Freising, Germany. .,German Cancer Consortium (DKTK), Munich, Germany. .,German Cancer Research Center (DKFZ), Heidelberg, Germany. .,Institute of Advanced Study (IAS), Technical University of Munich, Freising, Germany.
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85
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Nguyen LT, Lau LY, Fortes MRS. Proteomic Analysis of Hypothalamus and Pituitary Gland in Pre and Postpubertal Brahman Heifers. Front Genet 2022; 13:935433. [PMID: 35774501 PMCID: PMC9237413 DOI: 10.3389/fgene.2022.935433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 05/25/2022] [Indexed: 11/28/2022] Open
Abstract
The hypothalamus and the pituitary gland are directly involved in the complex systemic changes that drive the onset of puberty in cattle. Here, we applied integrated bioinformatics to elucidate the critical proteins underlying puberty and uncover potential molecular mechanisms from the hypothalamus and pituitary gland of prepubertal (n = 6) and postpubertal (n = 6) cattle. Proteomic analysis in the hypothalamus and pituitary gland revealed 275 and 186 differentially abundant (DA) proteins, respectively (adjusted p-value < 0.01). The proteome profiles found herein were integrated with previously acquired transcriptome profiles. These transcriptomic studies used the same tissues harvested from the same heifers at pre- and post-puberty. This comparison detected a small number of matched transcripts and protein changes at puberty in each tissue, suggesting the need for multiple omics analyses for interpreting complex biological systems. In the hypothalamus, upregulated DA proteins at post-puberty were enriched in pathways related to puberty, including GnRH, calcium and oxytocin signalling pathways, whereas downregulated proteins were observed in the estrogen signalling pathway, axon guidance and GABAergic synapse. Additionally, this study revealed that ribosomal pathway proteins in the pituitary were involved in the pubertal development of mammals. The reported molecules and derived protein-protein networks are a starting point for future experimental approaches that might dissect with more detail the role of each molecule to provide new insights into the mechanisms of puberty onset in cattle.
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Affiliation(s)
- Loan To Nguyen
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, Australia
- *Correspondence: Loan To Nguyen,
| | - Li Yieng Lau
- Agency of Science, Technology and Research, Singapore, Singapore
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86
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Chae SA, Son JS, Zhao L, Gao Y, Liu X, Marie de Avila J, Zhu MJ, Du M. Exerkine apelin reverses obesity-associated placental dysfunction by accelerating mitochondrial biogenesis in mice. Am J Physiol Endocrinol Metab 2022; 322:E467-E479. [PMID: 35403440 PMCID: PMC9126223 DOI: 10.1152/ajpendo.00023.2022] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Maternal exercise (ME) protects against adverse effects of maternal obesity (MO) on fetal development. As a cytokine stimulated by exercise, apelin (APN) is elevated due to ME, but its roles in mediating the effects of ME on placental development remain to be defined. Two studies were conducted. In the first study, 18 female mice were assigned to control (CON), obesogenic diet (OB), or OB with exercise (OB/Ex) groups (n = 6); in the second study, the same number of female mice were assigned to three groups; CON with PBS injection (CD/PBS), OB/PBS, or OB with apelin injection (OB/APN). In the exercise study, daily treadmill exercise during pregnancy significantly elevated the expression of PR domain 16 (PRDM16; P < 0.001), which correlated with enhanced oxidative metabolism and mitochondrial biogenesis in the placenta (P < 0.05). More importantly, these changes were partially mirrored in the apelin study. Apelin administration upregulated PRDM16 protein level (P < 0.001), mitochondrial biogenesis (P < 0.05), placental nutrient transporter expression (P < 0.001), and placental vascularization (P < 0.01), which were impaired due to MO (P < 0.05). In summary, MO impairs oxidative phosphorylation in the placenta, which is improved by ME; apelin administration partially mimics the beneficial effects of exercise on improving placental function, which prevents placental dysfunction due to MO.NEW & NOTEWORTHY Maternal exercise prevents metabolic disorders of mothers and offspring induced by high-fat diet. Exercise intervention enhances PRDM16 activation, oxidative metabolism, and vascularization of placenta, which are inhibited due to maternal obesity. Similar to maternal exercise, apelin administration improves placental function of obese dams.
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Affiliation(s)
- Song Ah Chae
- Nutrigenomics and Growth Biology Laboratory, Department of Animal Sciences, Washington State University, Pullman, Washington
| | - Jun Seok Son
- Laboratory of Perinatal Kinesioepigenetics, Department of Obstetrics, Gynecology & Reproductive Sciences, University of Maryland School of Medicine, Baltimore, Maryland
| | - Liang Zhao
- Nutrigenomics and Growth Biology Laboratory, Department of Animal Sciences, Washington State University, Pullman, Washington
| | - Yao Gao
- Nutrigenomics and Growth Biology Laboratory, Department of Animal Sciences, Washington State University, Pullman, Washington
| | - Xiangdong Liu
- Nutrigenomics and Growth Biology Laboratory, Department of Animal Sciences, Washington State University, Pullman, Washington
| | - Jeanene Marie de Avila
- Nutrigenomics and Growth Biology Laboratory, Department of Animal Sciences, Washington State University, Pullman, Washington
| | - Mei-Jun Zhu
- School of Food Science, Washington State University, Pullman, Washington
| | - Min Du
- Nutrigenomics and Growth Biology Laboratory, Department of Animal Sciences, Washington State University, Pullman, Washington
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87
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Abondio P, De Intinis C, da Silva Gonçalves Vianez Júnior JL, Pace L. SINGLE CELL MULTIOMIC APPROACHES TO DISENTANGLE T CELL HETEROGENEITY. Immunol Lett 2022; 246:37-51. [DOI: 10.1016/j.imlet.2022.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 04/16/2022] [Accepted: 04/26/2022] [Indexed: 11/29/2022]
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88
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Fanter C, Madelaire C, Genereux DP, van Breukelen F, Levesque D, Hindle A. Epigenomics as a paradigm to understand the nuances of phenotypes. J Exp Biol 2022; 225:274619. [PMID: 35258621 DOI: 10.1242/jeb.243411] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Quantifying the relative importance of genomic and epigenomic modulators of phenotype is a focal challenge in comparative physiology, but progress is constrained by availability of data and analytic methods. Previous studies have linked physiological features to coding DNA sequence, regulatory DNA sequence, and epigenetic state, but few have disentangled their relative contributions or unambiguously distinguished causative effects ('drivers') from correlations. Progress has been limited by several factors, including the classical approach of treating continuous and fluid phenotypes as discrete and static across time and environment, and difficulty in considering the full diversity of mechanisms that can modulate phenotype, such as gene accessibility, transcription, mRNA processing and translation. We argue that attention to phenotype nuance, progressing to association with epigenetic marks and then causal analyses of the epigenetic mechanism, will enable clearer evaluation of the evolutionary path. This would underlie an essential paradigm shift, and power the search for links between genomic and epigenomic features and physiology. Here, we review the growing knowledge base of gene-regulatory mechanisms and describe their links to phenotype, proposing strategies to address widely recognized challenges.
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Affiliation(s)
- Cornelia Fanter
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Carla Madelaire
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Diane P Genereux
- Vertebrate Genome Biology, Broad Institute, Cambridge, MA 02142, USA
| | - Frank van Breukelen
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Danielle Levesque
- School of Biology and Ecology, University of Maine, Orono, ME 04469, USA
| | - Allyson Hindle
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
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89
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Marchant JS, Gunaratne GS, Cai X, Slama JT, Patel S. NAADP-binding proteins find their identity. Trends Biochem Sci 2022; 47:235-249. [PMID: 34810081 PMCID: PMC8840967 DOI: 10.1016/j.tibs.2021.10.008] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 10/19/2021] [Accepted: 10/26/2021] [Indexed: 02/07/2023]
Abstract
Nicotinic acid adenine dinucleotide phosphate (NAADP) is a second messenger that releases Ca2+ from endosomes and lysosomes by activating ion channels called two-pore channels (TPCs). However, no NAADP-binding site has been identified on TPCs. Rather, NAADP activates TPCs indirectly by engaging NAADP-binding proteins (NAADP-BPs) that form part of the TPC complex. After a decade of searching, two different NAADP-BPs were recently identified: Jupiter microtubule associated homolog 2 (JPT2) and like-Sm protein 12 (LSM12). These discoveries bridge the gap between NAADP generation and NAADP activation of TPCs, providing new opportunity to understand and manipulate the NAADP-signaling pathway. The unmasking of these NAADP-BPs will catalyze future studies to define the molecular choreography of NAADP action.
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Affiliation(s)
- Jonathan S. Marchant
- Department of Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA,Correspondence: (J.S. Marchant) and (S. Patel)
| | - Gihan S. Gunaratne
- Department of Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA
| | - Xinjiang Cai
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - James T. Slama
- Department of Medicinal and Biological Chemistry, University of Toledo College of Pharmacy and Pharmaceutical Sciences, 3000 Arlington Avenue, Toledo, OH 43614, USA
| | - Sandip Patel
- Department of Cell and Developmental Biology, University College London, Gower Street, London WC1E 6BT, UK.
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90
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Raven N, Klaassen M, Madsen T, Thomas F, Hamede R, Ujvari B. Transmissible cancer influences immune gene expression in an endangered marsupial, the Tasmanian devil (Sarcophilus harrisii). Mol Ecol 2022; 31:2293-2311. [PMID: 35202488 PMCID: PMC9310804 DOI: 10.1111/mec.16408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 02/14/2022] [Indexed: 11/28/2022]
Abstract
Understanding the effects of wildlife diseases on populations requires insight into local environmental conditions, host defence mechanisms, host life‐history trade‐offs, pathogen population dynamics, and their interactions. The survival of Tasmanian devils (Sarcophilus harrisii) is challenged by a novel, fitness limiting pathogen, Tasmanian devil facial tumour disease (DFTD), a clonally transmissible, contagious cancer. In order to understand the devils’ capacity to respond to DFTD, it is crucial to gain information on factors influencing the devils’ immune system. By using RT‐qPCR, we investigated how DFTD infection in association with intrinsic (sex and age) and environmental (season) factors influences the expression of 10 immune genes in Tasmanian devil blood. Our study showed that the expression of immune genes (both innate and adaptive) differed across seasons, a pattern that was altered when infected with DFTD. The expression of immunogbulins IgE and IgM:IgG showed downregulation in colder months in DFTD infected animals. We also observed strong positive association between the expression of an innate immune gene, CD16, and DFTD infection. Our results demonstrate that sampling across seasons, age groups and environmental conditions are beneficial when deciphering the complex ecoevolutionary interactions of not only conventional host‐parasite systems, but also of host and diseases with high mortality rates, such as transmissible cancers.
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Affiliation(s)
- N Raven
- Deakin University, Geelong, School of Life and Environmental Sciences, Centre for Integrative Ecology, Waurn Ponds, Vic, 3216, Australia
| | - M Klaassen
- Deakin University, Geelong, School of Life and Environmental Sciences, Centre for Integrative Ecology, Waurn Ponds, Vic, 3216, Australia
| | - T Madsen
- Deakin University, Geelong, School of Life and Environmental Sciences, Centre for Integrative Ecology, Waurn Ponds, Vic, 3216, Australia
| | - F Thomas
- CREEC/CANECEV (CREES), Montpellier, France.,MIVEGEC, Université de Montpellier, CNRS, IRD, Montpellier, France
| | - R Hamede
- Deakin University, Geelong, School of Life and Environmental Sciences, Centre for Integrative Ecology, Waurn Ponds, Vic, 3216, Australia.,School of Natural Sciences, University of Tasmania, Private Bag 55, Hobart, Tasmania, 7001, Australia
| | - B Ujvari
- Deakin University, Geelong, School of Life and Environmental Sciences, Centre for Integrative Ecology, Waurn Ponds, Vic, 3216, Australia
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91
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Jain AP, Sambath J, Sathe G, George IA, Pandey A, Thompson EW, Kumar P. Pan-cancer quantitation of epithelial-mesenchymal transition dynamics using parallel reaction monitoring-based targeted proteomics approach. J Transl Med 2022; 20:84. [PMID: 35148768 PMCID: PMC8832824 DOI: 10.1186/s12967-021-03227-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 12/30/2021] [Indexed: 12/31/2022] Open
Abstract
Epithelial–mesenchymal transition (EMT) is a dynamic and complex cellular process that is known to be hijacked by cancer cells to facilitate invasion, metastasis and therapeutic resistance. Several quantitative measures to assess the interplay between EMT and cancer progression are available, based on large scale genome and transcriptome data. However, these large scale multi-omics studies have repeatedly illustrated a lack of correlation in mRNA and protein abundances that may be influenced by diverse post-translational regulation. Hence, it is imperative to understand how changes in the EMT proteome are associated with the process of oncogenic transformation. To this effect, we developed a parallel reaction monitoring-based targeted proteomics method for quantifying abundances of EMT-associated proteins across cancer cell lines. Our study revealed that quantitative measurement of EMT proteome which enabled a more accurate assessment than transcriptomics data and revealed specific discrepancies against a backdrop of generally strong concordance between proteomic and transcriptomic data. We further demonstrated that changes in our EMT proteome panel might play a role in tumor transformation across cancer types. In future, this EMT panel assay has the potential to be used for clinical samples to guide treatment choices and to congregate functional information for the development and advancing novel therapeutics.
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Affiliation(s)
- Ankit P Jain
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, Karnataka, India
| | - Janani Sambath
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, Karnataka, India.,Manipal Academy of Higher Education (MAHE), Manipal, 576104, India
| | - Gajanan Sathe
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, Karnataka, India.,Manipal Academy of Higher Education (MAHE), Manipal, 576104, India.,Center for Molecular Medicine, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, 560029, India
| | - Irene A George
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, Karnataka, India.,Manipal Academy of Higher Education (MAHE), Manipal, 576104, India
| | - Akhilesh Pandey
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, Karnataka, India.,Manipal Academy of Higher Education (MAHE), Manipal, 576104, India.,Center for Molecular Medicine, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, 560029, India.,Department of Laboratory Medicine and Pathology, Centre for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA
| | - Erik W Thompson
- Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, 4059, Australia. .,School-Biomedical Sciences, Translational Research Institute, Woolloongabba, QLD, 4102, Australia.
| | - Prashant Kumar
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, Karnataka, India. .,Manipal Academy of Higher Education (MAHE), Manipal, 576104, India. .,Somaiya Institute of Research and Consultancy (SIRAC), Somaiya Vidyavihar University (SVU), Vidyavihar, Mumbai, 400077, Maharashtra, India.
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92
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Inferring protein expression changes from mRNA in Alzheimer's dementia using deep neural networks. Nat Commun 2022; 13:655. [PMID: 35115553 PMCID: PMC8814036 DOI: 10.1038/s41467-022-28280-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 01/19/2022] [Indexed: 12/30/2022] Open
Abstract
Identifying the molecular systems and proteins that modify the progression of Alzheimer's disease and related dementias (ADRD) is central to drug target selection. However, discordance between mRNA and protein abundance, and the scarcity of proteomic data, has limited our ability to advance candidate targets that are mainly based on gene expression. Therefore, by using a deep neural network that predicts protein abundance from mRNA expression, here we attempt to track the early protein drivers of ADRD. Specifically, by applying the clei2block deep learning model to 1192 brain RNA-seq samples, we identify protein modules and disease-associated expression changes that were not directly observed at the mRNA level. Moreover, pseudo-temporal trajectory inference based on the predicted proteome became more closely correlated with cognitive decline and hippocampal atrophy compared to RNA-based trajectories. This suggests that the predicted changes in protein expression could provide a better molecular representation of ADRD progression. Furthermore, overlaying clinical traits on protein pseudotime trajectory identifies protein modules altered before cognitive impairment. These results demonstrate how our method can be used to identify potential early protein drivers and possible drug targets for treating and/or preventing ADRD.
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93
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Feng X, Zhang T, Chou J, Liu L, Miller LD, Sullivan CA, Browne JD. Comprehensive gene cluster analysis of head and neck squamous cell carcinoma TCGA RNA-seq data defines B cell immunity-related genes as a robust survival predictor. Head Neck 2022; 44:443-452. [PMID: 34841601 PMCID: PMC8766919 DOI: 10.1002/hed.26944] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 10/14/2021] [Accepted: 11/18/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The authors aimed to define novel gene expression signatures that are associated with patients' survival with head and neck squamous cell carcinoma (HNSCC). METHODS TCGA RNA-seq data were used for gene expression clusters extraction from 499 tumor samples by the "EPIG" method. Tumor samples were then partitioned into lower and higher than median level groups for survival relevant analysis by Kaplan-Meier estimator. RESULTS We found that two gene clusters (_1, _2) are favorably, while two (_3, _4) are unfavorably, associated with patients' survival with HNSCC. Notably, most genes on the top lists of cluster_2 are associated with B cells. A gene expression signature with combined genes from cluster_2 and _4 was further determined to be associated with HNSCC survival rate. CONCLUSION Our work strongly supported a favorable role of B cells in patients' survival with HNSCC and identified a novel coexpressed gene signature as prognostic biomarker for patients' survival with HNSCC estimation.
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Affiliation(s)
- Xin Feng
- Departments of Otolaryngology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Tan Zhang
- Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Jeff Chou
- Center for Cancer Genomics and Precision Oncology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Liang Liu
- Center for Cancer Genomics and Precision Oncology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Lance D. Miller
- Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Christopher A. Sullivan
- Departments of Otolaryngology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - James D. Browne
- Departments of Otolaryngology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
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94
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Lewandowski D, Foik AT, Smidak R, Choi EH, Zhang J, Hoang T, Tworak A, Suh S, Leinonen H, Dong Z, Pinto AF, Tom E, Luu JC, Lee JY, Ma X, Bieberich E, Blackshaw S, Saghatelian A, Lyon DC, Skowronska-Krawczyk D, Tabaka M, Palczewski K. Inhibition of ceramide accumulation in AdipoR1-/- mice increases photoreceptor survival and improves vision. JCI Insight 2022; 7:156301. [PMID: 35015730 PMCID: PMC8876453 DOI: 10.1172/jci.insight.156301] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 01/05/2022] [Indexed: 11/20/2022] Open
Abstract
Adiponectin receptor 1 (ADIPOR1) is a lipid and glucose metabolism regulator that possesses intrinsic ceramidase activity. Mutations of the ADIPOR1 gene have been associated with nonsyndromic and syndromic retinitis pigmentosa. Here, we show that the absence of AdipoR1 in mice leads to progressive photoreceptor degeneration, significant reduction of electroretinogram amplitudes, decreased retinoid content in the retina, and reduced cone opsin expression. Single-cell RNA-Seq results indicate that ADIPOR1 encoded the most abundantly expressed ceramidase in mice and one of the 2 most highly expressed ceramidases in the human retina, next to acid ceramidase ASAH1. We discovered an accumulation of ceramides in the AdipoR1–/– retina, likely due to insufficient ceramidase activity for healthy retina function, resulting in photoreceptor death. Combined treatment with desipramine/L-cycloserine (DC) lowered ceramide levels and exerted a protective effect on photoreceptors in AdipoR1–/– mice. Moreover, we observed improvement in cone-mediated retinal function in the DC-treated animals. Lastly, we found that prolonged DC treatment corrected the electrical responses of the primary visual cortex to visual stimuli, approaching near-normal levels for some parameters. These results highlight the importance of ADIPOR1 ceramidase in the retina and show that pharmacological inhibition of ceramide generation can provide a therapeutic strategy for ADIPOR1-related retinopathy.
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Affiliation(s)
- Dominik Lewandowski
- Department of Ophthalmology, University of California, Irvine, Irvine, United States of America
| | - Andrzej T Foik
- International Center for Translational Eye Research, Institute of Physical Chemistry PAS, Warsaw, Poland
| | - Roman Smidak
- Department of Ophthalmology, University of California, Irvine, Irvine, United States of America
| | - Elliot H Choi
- Department of Pharmacology, Case Western Reserve University, Cleveland, United States of America
| | - Jianye Zhang
- Department of Ophthalmology, University of California, Irvine, Irvine, United States of America
| | - Thanh Hoang
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, United States of America
| | - Aleksander Tworak
- Department of Ophthalmology, University of California, Irvine, Irvine, United States of America
| | - Susie Suh
- Department of Pharmacology, Case Western Reserve University, Cleveland, United States of America
| | - Henri Leinonen
- Department of Ophthalmology, University of California, Irvine, Irvine, United States of America
| | - Zhiqian Dong
- Department of Medical Devices, Polgenix Inc., Cleveland, United States of America
| | - Antonio Fm Pinto
- Clayton Foundation Laboratories for Peptide Biology, Salk Institute for Biological Studies, La Jolla, United States of America
| | - Emily Tom
- Department of Ophthalmology, University of California, Irvine, Irvine, United States of America
| | - Jennings C Luu
- Department of Ophthalmology, University of California, Irvine, Irvine, United States of America
| | - Joan Y Lee
- MetroHealth Medical Center, Case Western Reserve University, Cleveland, United States of America
| | - Xiuli Ma
- Department of Medical Devices, Polgenix Inc, Cleveland, United States of America
| | - Erhard Bieberich
- Department of Physiology, University of Kentucky, Lexington, United States of America
| | - Seth Blackshaw
- Solomon H. Snyder Department of Neuroscience, John Hopkins School of Medicine, Baltimore, United States of America
| | - Alan Saghatelian
- Clayton Foundation Laboratories for Peptide Biology, Salk Institute for Biological Studies, La Jolla, United States of America
| | - David C Lyon
- Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, United States of America
| | | | - Marcin Tabaka
- International Center for Translational Eye Research, Institute of Physical Chemistry PAS, Warsaw, Poland
| | - Krzysztof Palczewski
- Department of Ophthalmology, University of California, Irvine, Irvine, United States of America
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95
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Shichkova P, Coggan JS, Markram H, Keller D. A Standardized Brain Molecular Atlas: A Resource for Systems Modeling and Simulation. Front Mol Neurosci 2021; 14:604559. [PMID: 34858137 PMCID: PMC8631404 DOI: 10.3389/fnmol.2021.604559] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 10/05/2021] [Indexed: 12/12/2022] Open
Abstract
Accurate molecular concentrations are essential for reliable analyses of biochemical networks and the creation of predictive models for molecular and systems biology, yet protein and metabolite concentrations used in such models are often poorly constrained or irreproducible. Challenges of using data from different sources include conflicts in nomenclature and units, as well as discrepancies in experimental procedures, data processing and implementation of the model. To obtain a consistent estimate of protein and metabolite levels, we integrated and normalized data from a large variety of sources to calculate Adjusted Molecular Concentrations. We found a high degree of reproducibility and consistency of many molecular species across brain regions and cell types, consistent with tight homeostatic regulation. We demonstrated the value of this normalization with differential protein expression analyses related to neurodegenerative diseases, brain regions and cell types. We also used the results in proof-of-concept simulations of brain energy metabolism. The standardized Brain Molecular Atlas overcomes the obstacles of missing or inconsistent data to support systems biology research and is provided as a resource for biomolecular modeling.
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Affiliation(s)
- Polina Shichkova
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Jay S Coggan
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Henry Markram
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland.,Laboratory of Neural Microcircuitry, Brain Mind Institute, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Daniel Keller
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
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96
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Zhang X, Grimes HL. Why Single-Cell Sequencing Has Promise in MDS. Front Oncol 2021; 11:769753. [PMID: 34926276 PMCID: PMC8675176 DOI: 10.3389/fonc.2021.769753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 11/16/2021] [Indexed: 11/22/2022] Open
Abstract
Myelodysplastic syndromes (MDS) are a heterogeneous group of diseases characterized by ineffective hematopoiesis. The risk of MDS is associated with aging and the accumulation of somatic mutations in hematopoietic stem cells and progenitors (HSPC). While advances in DNA sequencing in the past decade unveiled clonal selection driven by mutations in MDS, it is unclear at which stage the HSPCs are trapped or what prevents mature cells output. Single-cell-sequencing techniques in recent years have revolutionized our understanding of normal hematopoiesis by identifying the transitional cell states between classical hematopoietic hierarchy stages, and most importantly the biological activities behind cell differentiation and lineage commitment. Emerging studies have adapted these powerful tools to investigate normal hematopoiesis as well as the clonal heterogeneity in myeloid malignancies and provide a progressive description of disease pathogenesis. This review summarizes the potential of growing single-cell-sequencing techniques, the evolving efforts to elucidate hematopoiesis in physiological conditions and MDS at single-cell resolution, and discuss how they may fill the gaps in our current understanding of MDS biology.
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Affiliation(s)
- Xuan Zhang
- Division of Immunobiology and Center for Systems Immunology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
| | - H. Leighton Grimes
- Division of Immunobiology and Center for Systems Immunology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
- Division of Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
- Department of Pediatrics, University of Cincinnati, Cincinnati, OH, United States
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97
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Klein B, Holmér L, Smith KM, Johnson MM, Swain A, Stolp L, Teufel AI, Kleppe AS. A computational exploration of resilience and evolvability of protein-protein interaction networks. Commun Biol 2021; 4:1352. [PMID: 34857859 PMCID: PMC8639913 DOI: 10.1038/s42003-021-02867-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 11/03/2021] [Indexed: 11/09/2022] Open
Abstract
Protein-protein interaction (PPI) networks represent complex intra-cellular protein interactions, and the presence or absence of such interactions can lead to biological changes in an organism. Recent network-based approaches have shown that a phenotype's PPI network's resilience to environmental perturbations is related to its placement in the tree of life; though we still do not know how or why certain intra-cellular factors can bring about this resilience. Here, we explore the influence of gene expression and network properties on PPI networks' resilience. We use publicly available data of PPIs for E. coli, S. cerevisiae, and H. sapiens, where we compute changes in network resilience as new nodes (proteins) are added to the networks under three node addition mechanisms-random, degree-based, and gene-expression-based attachments. By calculating the resilience of the resulting networks, we estimate the effectiveness of these node addition mechanisms. We demonstrate that adding nodes with gene-expression-based preferential attachment (as opposed to random or degree-based) preserves and can increase the original resilience of PPI network in all three species, regardless of gene expression distribution or network structure. These findings introduce a general notion of prospective resilience, which highlights the key role of network structures in understanding the evolvability of phenotypic traits.
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Affiliation(s)
- Brennan Klein
- Network Science Institute, Northeastern University, Boston, MA, USA. .,Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, MA, USA.
| | - Ludvig Holmér
- grid.419684.60000 0001 1214 1861Center for Data Analytics, Stockholm School of Economics, Stockholm, Sweden
| | - Keith M. Smith
- grid.12361.370000 0001 0727 0669Department of Physics and Mathematics, Nottingham Trent University, Nottingham, UK
| | - Mackenzie M. Johnson
- grid.89336.370000 0004 1936 9924Department of Integrative Biology, University of Texas at Austin, Austin, TX USA
| | - Anshuman Swain
- grid.164295.d0000 0001 0941 7177Department of Biology, University of Maryland, College Park, MD USA
| | - Laura Stolp
- grid.7177.60000000084992262Graduate School of Science, University of Amsterdam, Amsterdam, The Netherlands
| | - Ashley I. Teufel
- grid.89336.370000 0004 1936 9924Department of Integrative Biology, University of Texas at Austin, Austin, TX USA ,grid.209665.e0000 0001 1941 1940Santa Fe Institute, Santa Fe, NM USA ,grid.469272.c0000 0001 0180 5693Texas A&M University, San Antonio, San Antonio, TX USA
| | - April S. Kleppe
- grid.5949.10000 0001 2172 9288Institute for Evolution and Biodiversity, University of Münster, Münster, Germany ,grid.7048.b0000 0001 1956 2722Department of Clinical Medicine (MOMA), Aarhus University, Aarhus, Denmark
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98
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Sinha N, van Schothorst EM, Hooiveld GJEJ, Keijer J, Martins Dos Santos VAP, Suarez-Diez M. Exploring the associations between transcript levels and fluxes in constraint-based models of metabolism. BMC Bioinformatics 2021; 22:574. [PMID: 34839828 PMCID: PMC8628452 DOI: 10.1186/s12859-021-04488-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 11/15/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Several computational methods have been developed that integrate transcriptomics data with genome-scale metabolic reconstructions to increase accuracy of inferences of intracellular metabolic flux distributions. Even though existing methods use transcript abundances as a proxy for enzyme activity, each method uses a different hypothesis and assumptions. Most methods implicitly assume a proportionality between transcript levels and flux through the corresponding function, although these proportionality constant(s) are often not explicitly mentioned nor discussed in any of the published methods. E-Flux is one such method and, in this algorithm, flux bounds are related to expression data, so that reactions associated with highly expressed genes are allowed to carry higher flux values. RESULTS Here, we extended E-Flux and systematically evaluated the impact of an assumed proportionality constant on model predictions. We used data from published experiments with Escherichia coli and Saccharomyces cerevisiae and we compared the predictions of the algorithm to measured extracellular and intracellular fluxes. CONCLUSION We showed that detailed modelling using a proportionality constant can greatly impact the outcome of the analysis. This increases accuracy and allows for extraction of better physiological information.
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Affiliation(s)
- Neeraj Sinha
- Nutrition, Metabolism and Genomics Group, Division of Human Nutrition and Health, Wageningen University & Research, Stippeneng 4, 6708 WE, Wageningen, The Netherlands.,Human and Animal Physiology, Wageningen University & Research, De Elst 1, 6708 WD, Wageningen, The Netherlands.,Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Stippeneng 4, 6708 WE, Wageningen, The Netherlands
| | - Evert M van Schothorst
- Human and Animal Physiology, Wageningen University & Research, De Elst 1, 6708 WD, Wageningen, The Netherlands
| | - Guido J E J Hooiveld
- Nutrition, Metabolism and Genomics Group, Division of Human Nutrition and Health, Wageningen University & Research, Stippeneng 4, 6708 WE, Wageningen, The Netherlands
| | - Jaap Keijer
- Human and Animal Physiology, Wageningen University & Research, De Elst 1, 6708 WD, Wageningen, The Netherlands
| | - Vitor A P Martins Dos Santos
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Stippeneng 4, 6708 WE, Wageningen, The Netherlands.,LifeGlimmer GmbH., Markelstrasse 38, 12163, Berlin, Germany.,Bioprocess Engineering Group, Wageningen University & Research, PO Box 16, 6700 AA, Wageningen, The Netherlands
| | - Maria Suarez-Diez
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Stippeneng 4, 6708 WE, Wageningen, The Netherlands.
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99
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Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction. Cells 2021; 10:cells10123268. [PMID: 34943776 PMCID: PMC8699769 DOI: 10.3390/cells10123268] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 11/18/2021] [Accepted: 11/20/2021] [Indexed: 02/01/2023] Open
Abstract
Specific proteins and processes have been identified in post-myocardial infarction (MI) pathological remodeling, but a comprehensive understanding of the complete molecular evolution is lacking. We generated microarray data from swine heart biopsies at baseline and 6, 30, and 45 days after infarction to feed machine-learning algorithms. We cross-validated the results using available clinical and experimental information. MI progression was accompanied by the regulation of adipogenesis, fatty acid metabolism, and epithelial-mesenchymal transition. The infarct core region was enriched in processes related to muscle contraction and membrane depolarization. Angiogenesis was among the first morphogenic responses detected as being sustained over time, but other processes suggesting post-ischemic recapitulation of embryogenic processes were also observed. Finally, protein-triggering analysis established the key genes mediating each process at each time point, as well as the complete adverse remodeling response. We modeled the behaviors of these genes, generating a description of the integrative mechanism of action for MI progression. This mechanistic analysis overlapped at different time points; the common pathways between the source proteins and cardiac remodeling involved IGF1R, RAF1, KPCA, JUN, and PTN11 as modulators. Thus, our data delineate a structured and comprehensive picture of the molecular remodeling process, identify new potential biomarkers or therapeutic targets, and establish therapeutic windows during disease progression.
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100
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Corcoran J, Goodman CL, Saathoff S, Ringbauer JA, Guo Y, Bonning B, Stanley D. Cell lines derived from the small hive beetle, Aethina tumida, express insecticide targets. In Vitro Cell Dev Biol Anim 2021; 57:849-855. [PMID: 34792733 DOI: 10.1007/s11626-021-00633-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 11/05/2021] [Indexed: 10/19/2022]
Affiliation(s)
- Jacob Corcoran
- Biological Control of Insects Research Laboratory, USDA - Agricultural Research Service, 1503 S. Providence Rd, Columbia, MO, 65203, USA.
| | - Cynthia L Goodman
- Biological Control of Insects Research Laboratory, USDA - Agricultural Research Service, 1503 S. Providence Rd, Columbia, MO, 65203, USA
| | - Stephen Saathoff
- Biological Control of Insects Research Laboratory, USDA - Agricultural Research Service, 1503 S. Providence Rd, Columbia, MO, 65203, USA
| | - Joseph A Ringbauer
- Biological Control of Insects Research Laboratory, USDA - Agricultural Research Service, 1503 S. Providence Rd, Columbia, MO, 65203, USA
| | - Ya Guo
- Entomology and Nematology Department, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL, USA
| | - Bryony Bonning
- Entomology and Nematology Department, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL, USA
| | - David Stanley
- Biological Control of Insects Research Laboratory, USDA - Agricultural Research Service, 1503 S. Providence Rd, Columbia, MO, 65203, USA
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