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Jeyananthan P. Performance comparison between multi-level gene expression data in cancer subgroup classification. Pathol Res Pract 2024; 260:155419. [PMID: 38955118 DOI: 10.1016/j.prp.2024.155419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 06/06/2024] [Accepted: 06/19/2024] [Indexed: 07/04/2024]
Abstract
Cancer is a serious disease that can affect various parts of the body such as breast, colon, lung or stomach. Each of these cancers has their own treatment dependent historical subgroups. Hence, the correct identification of cancer subgroup has almost same importance as the timely diagnosis of cancer. This is still a challenging task and a system with highest accuracy is essential. Current researches are moving towards analyzing the gene expression data of cancer patients for various purposes including biomarker identification and studying differently expressed genes, using gene expression data measured in a single level (selected from different gene levels including genome, transcriptome or translation). However, previous studies showed that information carried by one level of gene expression is not similar to another level. This shows the importance of integrating multi-level omics data in these studies. Hence, this study uses tumor gene expression data measured from various levels of gene along with the integration of those data in the subgroup classification of nine different cancers. This is a comprehensive analysis where four different gene expression data such as transcriptome, miRNA, methylation and proteome are used in this subgrouping and the performances between models are compared to reveal the best model.
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2
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Xie Y, Wang R, McClatchy DB, Ma Y, Diedrich J, Sanchez-Alavez M, Petrascheck M, Yates JR, Cline HT. Activity-dependent synthesis of Emerin gates neuronal plasticity by regulating proteostasis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.30.600712. [PMID: 38979362 PMCID: PMC11230442 DOI: 10.1101/2024.06.30.600712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Neurons dynamically regulate their proteome in response to sensory input, a key process underlying experience-dependent plasticity. We characterized the visual experience-dependent nascent proteome within a brief, defined time window after stimulation using an optimized metabolic labeling approach. Visual experience induced cell type-specific and age-dependent alterations in the nascent proteome, including proteostasis-related processes. We identified Emerin as the top activity-induced candidate plasticity protein and demonstrated that its rapid activity-induced synthesis is transcription-independent. In contrast to its nuclear localization and function in myocytes, activity-induced neuronal Emerin is abundant in the endoplasmic reticulum and broadly inhibits protein synthesis, including translation regulators and synaptic proteins. Downregulating Emerin shifted the dendritic spine population from predominantly mushroom morphology to filopodia and decreased network connectivity. In mice, decreased Emerin reduced visual response magnitude and impaired visual information processing. Our findings support an experience-dependent feed-forward role for Emerin in temporally gating neuronal plasticity by negatively regulating translation.
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3
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Guan Q, Kong W, Tan B, Zhu W, Akter T, Li J, Tian J, Chen S. Multiomics unravels potential molecular switches in the C 3 to CAM transition of Mesembryanthemum crystallinum. J Proteomics 2024; 299:105145. [PMID: 38431086 DOI: 10.1016/j.jprot.2024.105145] [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: 01/08/2024] [Revised: 02/21/2024] [Accepted: 02/28/2024] [Indexed: 03/05/2024]
Abstract
Mesembryanthemum crystallinum (common ice plant), a facultative CAM plant, shifts from C3 to CAM photosynthesis under salt stress, enhancing water use efficiency. Here we used transcriptomics, proteomics, and targeted metabolomics to profile molecular changes during the diel cycle of C3 to CAM transition. The results confirmed expected changes associated with CAM photosynthesis, starch biosynthesis and degradation, and glycolysis/gluconeogenesis. Importantly, they yielded new discoveries: 1) Transcripts displayed greater circadian regulation than proteins. 2) Oxidative phosphorylation and inositol methylation may play important roles in initiating the transition. 3) V-type H+-ATPases showed consistent transcriptional regulation, aiding in vacuolar malate uptake. 4) A protein phosphatase 2C, a major component in the ABA signaling pathway, may trigger the C3 to CAM transition. Our work highlights the potential molecular switches in the C3 to CAM transition, including the potential role of ABA signaling. SIGNIFICANCE: The common ice plant is a model facultative CAM plant, and under stress conditions it can shift from C3 to CAM photosynthesis within a three-day period. However, knowledge about the molecular changes during the transition and the molecular switches enabling the transition is lacking. Multi-omic analyses not only revealed the molecular changes during the transition, but also highlighted the importance of ABA signaling, inositol methylation, V-type H+-ATPase in initiating the shift. The findings may explain physiological changes and nocturnal stomatal opening, and inform future synthetic biology effort in improving crop water use efficiency and stress resilience.
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Affiliation(s)
- Qijie Guan
- Department of Biology, University of Mississippi, Oxford, MS 38677, USA
| | - Wenwen Kong
- College of Life Sciences, Northeast Agricultural University, Harbin 150040, China
| | - Bowen Tan
- Department of Biology, University of Mississippi, Oxford, MS 38677, USA
| | - Wei Zhu
- Institute of Basic Medicine and Cancer, Chinese Academy of Sciences, Hangzhou 310002, China
| | - Tahmina Akter
- Department of Biology, University of Mississippi, Oxford, MS 38677, USA
| | - Jing Li
- College of Life Sciences, Northeast Agricultural University, Harbin 150040, China
| | - Jingkui Tian
- Institute of Basic Medicine and Cancer, Chinese Academy of Sciences, Hangzhou 310002, China
| | - Sixue Chen
- Department of Biology, University of Mississippi, Oxford, MS 38677, USA.
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4
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Kudapa H, Ghatak A, Barmukh R, Chaturvedi P, Khan A, Kale S, Fragner L, Chitikineni A, Weckwerth W, Varshney RK. Integrated multi-omics analysis reveals drought stress response mechanism in chickpea (Cicer arietinum L.). THE PLANT GENOME 2024; 17:e20337. [PMID: 37165696 DOI: 10.1002/tpg2.20337] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 03/04/2023] [Accepted: 03/09/2023] [Indexed: 05/12/2023]
Abstract
Drought is one of the major constraints limiting chickpea productivity. To unravel complex mechanisms regulating drought response in chickpea, we generated transcriptomics, proteomics, and metabolomics datasets from root tissues of four contrasting drought-responsive chickpea genotypes: ICC 4958, JG 11, and JG 11+ (drought-tolerant), and ICC 1882 (drought-sensitive) under control and drought stress conditions. Integration of transcriptomics and proteomics data identified enriched hub proteins encoding isoflavone 4'-O-methyltransferase, UDP-d-glucose/UDP-d-galactose 4-epimerase, and delta-1-pyrroline-5-carboxylate synthetase. These proteins highlighted the involvement of pathways such as antibiotic biosynthesis, galactose metabolism, and isoflavonoid biosynthesis in activating drought stress response mechanisms. Subsequently, the integration of metabolomics data identified six metabolites (fructose, galactose, glucose, myoinositol, galactinol, and raffinose) that showed a significant correlation with galactose metabolism. Integration of root-omics data also revealed some key candidate genes underlying the drought-responsive "QTL-hotspot" region. These results provided key insights into complex molecular mechanisms underlying drought stress response in chickpea.
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Affiliation(s)
- Himabindu Kudapa
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Arindam Ghatak
- Molecular Systems Biology Lab (MOSYS), Department of Functional and Evolutionary Ecology, University of Vienna, Vienna, Austria
| | - Rutwik Barmukh
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Palak Chaturvedi
- Molecular Systems Biology Lab (MOSYS), Department of Functional and Evolutionary Ecology, University of Vienna, Vienna, Austria
| | - Aamir Khan
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Sandip Kale
- The Leibniz-Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Lena Fragner
- Molecular Systems Biology Lab (MOSYS), Department of Functional and Evolutionary Ecology, University of Vienna, Vienna, Austria
| | - Annapurna Chitikineni
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
- Centre for Crop & Food Innovation, WA State Agricultural Biotechnology Centre, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
| | - Wolfram Weckwerth
- Molecular Systems Biology Lab (MOSYS), Department of Functional and Evolutionary Ecology, University of Vienna, Vienna, Austria
- Vienna Metabolomics Centre (VIME), University of Vienna, Vienna, Austria
| | - Rajeev K Varshney
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
- Centre for Crop & Food Innovation, WA State Agricultural Biotechnology Centre, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
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5
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Gleason LU, Fekete FJ, Tanner RL, Dowd WW. Multi-omics reveals largely distinct transcript- and protein-level responses to the environment in an intertidal mussel. J Exp Biol 2023; 226:jeb245962. [PMID: 37902141 PMCID: PMC10690110 DOI: 10.1242/jeb.245962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 10/12/2023] [Indexed: 10/31/2023]
Abstract
Organismal responses to stressful environments are influenced by numerous transcript- and protein-level mechanisms, and the relationships between expression changes at these levels are not always straightforward. Here, we used paired transcriptomic and proteomic datasets from two previous studies from gill of the California mussel, Mytilus californianus, to explore how simultaneous transcript and protein abundance patterns may diverge under different environmental scenarios. Field-acclimatized mussels were sampled from two disparate intertidal sites; individuals from one site were subjected to three further treatments (common garden, low-intertidal or high-intertidal outplant) that vary in temperature and feeding time. Assessing 1519 genes shared between the two datasets revealed that both transcript and protein expression patterns differentiated the treatments at a global level, despite numerous underlying discrepancies. There were far more instances of differential expression between treatments in transcript only (1451) or protein only (226) than of the two levels shifting expression concordantly (68 instances). Upregulated expression of cilium-associated transcripts (likely related to feeding) was associated with relatively benign field treatments. In the most stressful treatment, transcripts, but not proteins, for several molecular chaperones (including heat shock proteins and endoplasmic reticulum chaperones) were more abundant, consistent with a threshold model for induction of translation of constitutively available mRNAs. Overall, these results suggest that the relative importance of transcript- and protein-level regulation (translation and/or turnover) differs among cellular functions and across specific microhabitats or environmental contexts. Furthermore, the degree of concordance between transcript and protein expression can vary across benign versus acutely stressful environmental conditions.
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Affiliation(s)
- Lani U. Gleason
- Department of Biological Sciences, California State University Sacramento, Sacramento, CA 95819, USA
| | - Florian J. Fekete
- Department of Biological Sciences, California State University Sacramento, Sacramento, CA 95819, USA
| | - Richelle L. Tanner
- School of Biological Sciences, Washington State University, Pullman, WA 99163, USA
| | - W. Wesley Dowd
- School of Biological Sciences, Washington State University, Pullman, WA 99163, USA
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6
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Hartke J, Ceron-Noriega A, Stoldt M, Sistermans T, Kever M, Fuchs J, Butter F, Foitzik S. Long live the host! Proteomic analysis reveals possible strategies for parasitic manipulation of its social host. Mol Ecol 2023; 32:5877-5889. [PMID: 37795937 DOI: 10.1111/mec.17155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 09/15/2023] [Accepted: 09/19/2023] [Indexed: 10/06/2023]
Abstract
Parasites with complex life cycles often manipulate the phenotype of their intermediate hosts to increase the probability of transmission to their definitive hosts. Infection with Anomotaenia brevis, a cestode that uses Temnothorax nylanderi ants as intermediate hosts, leads to a multiple-fold extension of host lifespan and to changes in behaviour, morphology and colouration. The mechanisms behind these changes are unknown, as is whether the increased longevity is achieved through parasite manipulation. Here, we demonstrate that the parasite releases proteins into its host with functions that might explain the observed changes. These parasitic proteins make up a substantial portion of the proteome of the hosts' haemolymph, and thioredoxin peroxidase and superoxide dismutase, two antioxidants, exhibited the highest abundances among them. The largest part of the secreted proteins could not be annotated, indicating they are either novel or severely altered during recent coevolution to function in host manipulation. We also detected shifts in the hosts' proteome with infection, in particular an overabundance of vitellogenin-like A in infected ants, a protein that regulates division of labour in Temnothorax ants, which could explain the observed behavioural changes. Our results thus suggest two different strategies that might be employed by this parasite to manipulate its host: secreting proteins with immediate influence on the host's phenotype and altering the host's translational activity. Our findings highlight the intricate molecular interplay required to influence the phenotype of a host and point to potential signalling pathways and genes involved in parasite-host communication.
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Affiliation(s)
- Juliane Hartke
- Institute of Organismic and Molecular Evolution, Johannes Gutenberg University Mainz, Mainz, Germany
| | | | - Marah Stoldt
- Institute of Organismic and Molecular Evolution, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Tom Sistermans
- Institute of Organismic and Molecular Evolution, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Marion Kever
- Institute of Organismic and Molecular Evolution, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Jenny Fuchs
- Institute of Organismic and Molecular Evolution, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Falk Butter
- Institute of Molecular Biology, Mainz, Germany
| | - Susanne Foitzik
- Institute of Organismic and Molecular Evolution, Johannes Gutenberg University Mainz, Mainz, Germany
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7
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Aknouch I, Sridhar A, Freeze E, Giugliano FP, van Keulen BJ, Romijn M, Calitz C, García-Rodríguez I, Mulder L, Wildenberg ME, Muncan V, van Gils MJ, van Goudoever JB, Stittelaar KJ, Wolthers KC, Pajkrt D. Human milk inhibits some enveloped virus infections, including SARS-CoV-2, in an intestinal model. Life Sci Alliance 2022; 5:e202201432. [PMID: 35926873 PMCID: PMC9354649 DOI: 10.26508/lsa.202201432] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 07/13/2022] [Accepted: 07/14/2022] [Indexed: 11/24/2022] Open
Abstract
Human milk is important for antimicrobial defense in infants and has well demonstrated antiviral activity. We evaluated the protective ability of human milk against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in a human fetal intestinal cell culture model. We found that, in this model, human milk blocks SARS-CoV-2 replication, irrespective of the presence of SARS-CoV-2 spike-specific antibodies. Complete inhibition of both enveloped Middle East respiratory syndrome coronavirus and human respiratory syncytial virus infections was also observed, whereas no inhibition of non-enveloped enterovirus A71 infection was seen. Transcriptome analysis after 24 h of the intestinal monolayers treated with human milk showed large transcriptomic changes from human milk treatment, and subsequent analysis suggested that <i>ATP1A1</i> down-regulation by milk might be of importance. Inhibition of ATP1A1 blocked SARS-CoV-2 infection in our intestinal model, whereas no effect on EV-A71 infection was seen. Our data indicate that human milk has potent antiviral activity against particular (enveloped) viruses by potentially blocking the ATP1A1-mediated endocytic process.
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Affiliation(s)
- Ikrame Aknouch
- Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, OrganoVIR Labs, Amsterdam, The Netherlands
- Department of Pediatric Infectious Diseases, Amsterdam UMC, University of Amsterdam, Vrije Universiteit, Emma Children's Hospital, Amsterdam, The Netherlands
- Viroclinics Xplore, Schaijk, The Netherlands
| | - Adithya Sridhar
- Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, OrganoVIR Labs, Amsterdam, The Netherlands
- Department of Pediatric Infectious Diseases, Amsterdam UMC, University of Amsterdam, Vrije Universiteit, Emma Children's Hospital, Amsterdam, The Netherlands
| | - Eline Freeze
- Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, OrganoVIR Labs, Amsterdam, The Netherlands
- Department of Pediatric Infectious Diseases, Amsterdam UMC, University of Amsterdam, Vrije Universiteit, Emma Children's Hospital, Amsterdam, The Netherlands
| | - Francesca Paola Giugliano
- Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology Endocrinology and Metabolism, Tytgat Institute for Intestinal and Liver Research, Amsterdam, The Netherlands
| | - Britt J van Keulen
- Department of Pediatrics, Amsterdam UMC, University of Amsterdam, Vrije Universiteit Emma Children's Hospital, Dutch National Human Milk Bank, Amsterdam, The Netherlands
| | - Michelle Romijn
- Department of Pediatrics, Amsterdam UMC, University of Amsterdam, Vrije Universiteit Emma Children's Hospital, Dutch National Human Milk Bank, Amsterdam, The Netherlands
| | - Carlemi Calitz
- Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, OrganoVIR Labs, Amsterdam, The Netherlands
- Department of Pediatric Infectious Diseases, Amsterdam UMC, University of Amsterdam, Vrije Universiteit, Emma Children's Hospital, Amsterdam, The Netherlands
| | - Inés García-Rodríguez
- Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, OrganoVIR Labs, Amsterdam, The Netherlands
- Department of Pediatric Infectious Diseases, Amsterdam UMC, University of Amsterdam, Vrije Universiteit, Emma Children's Hospital, Amsterdam, The Netherlands
| | - Lance Mulder
- Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, OrganoVIR Labs, Amsterdam, The Netherlands
- Department of Pediatric Infectious Diseases, Amsterdam UMC, University of Amsterdam, Vrije Universiteit, Emma Children's Hospital, Amsterdam, The Netherlands
| | - Manon E Wildenberg
- Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology Endocrinology and Metabolism, Tytgat Institute for Intestinal and Liver Research, Amsterdam, The Netherlands
| | - Vanesa Muncan
- Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology Endocrinology and Metabolism, Tytgat Institute for Intestinal and Liver Research, Amsterdam, The Netherlands
| | - Marit J van Gils
- Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, The Netherlands
| | - Johannes B van Goudoever
- Department of Pediatrics, Amsterdam UMC, University of Amsterdam, Vrije Universiteit Emma Children's Hospital, Dutch National Human Milk Bank, Amsterdam, The Netherlands
| | - Koert J Stittelaar
- Department of Epidemiology, Bioinformatics and Animals Models, Wageningen University, Wageningen Bioveterinary Research, Wageningen, The Netherlands
| | - Katja C Wolthers
- Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, OrganoVIR Labs, Amsterdam, The Netherlands
| | - Dasja Pajkrt
- Department of Pediatric Infectious Diseases, Amsterdam UMC, University of Amsterdam, Vrije Universiteit, Emma Children's Hospital, Amsterdam, The Netherlands
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8
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Ward B, Yombi JC, Balligand JL, Cani PD, Collet JF, de Greef J, Dewulf JP, Gatto L, Haufroid V, Jodogne S, Kabamba B, Pyr dit Ruys S, Vertommen D, Elens L, Belkhir L. HYGIEIA: HYpothesizing the Genesis of Infectious Diseases and Epidemics through an Integrated Systems Biology Approach. Viruses 2022; 14:1373. [PMID: 35891354 PMCID: PMC9318602 DOI: 10.3390/v14071373] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 06/13/2022] [Accepted: 06/21/2022] [Indexed: 12/13/2022] Open
Abstract
More than two years on, the COVID-19 pandemic continues to wreak havoc around the world and has battle-tested the pandemic-situation responses of all major global governments. Two key areas of investigation that are still unclear are: the molecular mechanisms that lead to heterogenic patient outcomes, and the causes of Post COVID condition (AKA Long-COVID). In this paper, we introduce the HYGIEIA project, designed to respond to the enormous challenges of the COVID-19 pandemic through a multi-omic approach supported by network medicine. It is hoped that in addition to investigating COVID-19, the logistics deployed within this project will be applicable to other infectious agents, pandemic-type situations, and also other complex, non-infectious diseases. Here, we first look at previous research into COVID-19 in the context of the proteome, metabolome, transcriptome, microbiome, host genome, and viral genome. We then discuss a proposed methodology for a large-scale multi-omic longitudinal study to investigate the aforementioned biological strata through high-throughput sequencing (HTS) and mass-spectrometry (MS) technologies. Lastly, we discuss how a network medicine approach can be used to analyze the data and make meaningful discoveries, with the final aim being the translation of these discoveries into the clinics to improve patient care.
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Affiliation(s)
- Bradley Ward
- Integrated Pharmacometrics, Pharmacogenomics and Pharmacokinetics Group (PMGK), Louvain Drug Research Institute (LDRI), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (B.W.); (S.P.d.R.)
- Louvain Center for Toxicology and Applied Pharmacology (LTAP), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (J.d.G.); (J.P.D.); (V.H.)
| | - Jean Cyr Yombi
- Department of Internal Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Jean-Luc Balligand
- WELBIO (Walloon Excellence in Life Sciences and Biotechnology), Pole of Pharmacology and Therapeutics (FATH), Institut de Recherche Experimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Patrice D. Cani
- WELBIO (Walloon Excellence in Life Sciences and Biotechnology), Metabolism and Nutrition Research Group, Louvain Drug Research Institute (LDRI), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Jean-François Collet
- WELBIO (Walloon Excellence in Life Sciences and Biotechnology), de Duve Institute, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Julien de Greef
- Louvain Center for Toxicology and Applied Pharmacology (LTAP), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (J.d.G.); (J.P.D.); (V.H.)
- Department of Internal Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Joseph P. Dewulf
- Louvain Center for Toxicology and Applied Pharmacology (LTAP), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (J.d.G.); (J.P.D.); (V.H.)
- Department of Laboratory Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
- Department of Biochemistry, de Duve Institute, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium
| | - Laurent Gatto
- Computational Biology and Bioinformatics Unit (CBIO), de Duve Institute, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Vincent Haufroid
- Louvain Center for Toxicology and Applied Pharmacology (LTAP), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (J.d.G.); (J.P.D.); (V.H.)
- Department of Laboratory Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Sébastien Jodogne
- Computer Science and Engineering Department (INGI), Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM), UCLouvain, Université Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium;
| | - Benoît Kabamba
- Department of Laboratory Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
- Pôle de Microbiologie, Institut de Recherche Expérimentale et Clinique, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium
| | - Sébastien Pyr dit Ruys
- Integrated Pharmacometrics, Pharmacogenomics and Pharmacokinetics Group (PMGK), Louvain Drug Research Institute (LDRI), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (B.W.); (S.P.d.R.)
| | - Didier Vertommen
- De Duve Institute, and MASSPROT Platform, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Laure Elens
- Integrated Pharmacometrics, Pharmacogenomics and Pharmacokinetics Group (PMGK), Louvain Drug Research Institute (LDRI), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (B.W.); (S.P.d.R.)
- Louvain Center for Toxicology and Applied Pharmacology (LTAP), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (J.d.G.); (J.P.D.); (V.H.)
| | - Leïla Belkhir
- Louvain Center for Toxicology and Applied Pharmacology (LTAP), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; (J.d.G.); (J.P.D.); (V.H.)
- Department of Internal Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium;
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9
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Wang Y, Tian X, Zhang W, Zhang Z, Lazcano R, Hingorani P, Roth ME, Gill JD, Harrison DJ, Xu Z, Jusu S, Kannan S, Wang J, Lazar AJ, Earley EJ, Erickson SW, Gelb T, Huxley P, Lahdenranta J, Mudd G, Kurmasheva RT, Houghton PJ, Smith MA, Kolb EA, Gorlick R. Comprehensive surfaceome profiling to identify and validate novel cell-surface targets in osteosarcoma. Mol Cancer Ther 2022; 21:903-913. [PMID: 35312779 DOI: 10.1158/1535-7163.mct-21-0836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 12/31/2021] [Accepted: 03/08/2022] [Indexed: 11/16/2022]
Abstract
Immunoconjugates targeting cell-surface antigens have demonstrated clinical activity to enable regulatory approval in several solid and hematologic malignancies. We hypothesize that a rigorous and comprehensive surfaceome profiling approach to identify osteosarcoma-specific cell-surface antigens can similarly enable development of effective therapeutics in this disease. Herein, we describe an integrated proteomic and transcriptomic surfaceome profiling approach to identify cell-surface proteins that are highly expressed in osteosarcoma but minimally expressed on normal tissues. Using this approach, we identified targets that are highly expressed in osteosarcoma. Three targets, MT1-MMP, CD276, and MRC2, were validated as overexpressed in osteosarcoma. Further, we tested BT1769, an MT1-MMP-targeted Bicycle toxin conjugate, in osteosarcoma PDX models. The results showed BT1769 had encouraging anti-tumor activity, high affinity for its target and a favorable pharmacokinetic profile. This confirms the hypothesis that our approach identifies novel targets with significant therapeutic potential in osteosarcoma.
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Affiliation(s)
- Yifei Wang
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Xiangjun Tian
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Wendong Zhang
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Zhongting Zhang
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Rossana Lazcano
- The University of Texas MD Anderson Cancer Center, United States
| | - Pooja Hingorani
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Michael E Roth
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jonathan D Gill
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Douglas J Harrison
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Zhaohui Xu
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Sylvester Jusu
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | | | - Jing Wang
- The University of Texas MD Anderson Cancer Center, ´Houston, TX, United States
| | - Alexander J Lazar
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Eric J Earley
- RTI International, Research Triangle Park, NC, United States
| | | | - Tara Gelb
- Bicycle Therapeutics, Lexington, MA, United States
| | | | | | - Gemma Mudd
- Bicycle Therapeutics, Cambridge, United Kingdom
| | - Raushan T Kurmasheva
- The University of Texas Health Science Center at San Antonio, San Antonio, TX, United States
| | - Peter J Houghton
- The University of Texas Health Science Center at San Antonio, San Antonio, TX, United States
| | | | - Edward A Kolb
- Nemours Children's Health System, Wilmington, DE, United States
| | - Richard Gorlick
- The University of Texas MD Anderson Cancer Center, Houston, TX, United States
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10
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Rueda-Mejia MP, Nägeli L, Lutz S, Hayes RD, Varadarajan AR, Grigoriev IV, Ahrens CH, Freimoser FM. Genome, transcriptome and secretome analyses of the antagonistic, yeast-like fungus Aureobasidium pullulans to identify potential biocontrol genes. MICROBIAL CELL 2021; 8:184-202. [PMID: 34395586 PMCID: PMC8329847 DOI: 10.15698/mic2021.08.757] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 05/21/2021] [Accepted: 05/26/2021] [Indexed: 12/27/2022]
Abstract
Aureobasidium pullulans is an extremotolerant, cosmopolitan yeast-like fungus that successfully colonises vastly different ecological niches. The species is widely used in biotechnology and successfully applied as a commercial biocontrol agent against postharvest diseases and fireblight. However, the exact mechanisms that are responsible for its antagonistic activity against diverse plant pathogens are not known at the molecular level. Thus, it is difficult to optimise and improve the biocontrol applications of this species. As a foundation for elucidating biocontrol mechanisms, we have de novo assembled a high-quality reference genome of a strongly antagonistic A. pullulans strain, performed dual RNA-seq experiments, and analysed proteins secreted during the interaction with the plant pathogen Fusarium oxysporum. Based on the genome annotation, potential biocontrol genes were predicted to encode secreted hydrolases or to be part of secondary metabolite clusters (e.g., NRPS-like, NRPS, T1PKS, terpene, and β-lactone clusters). Transcriptome and secretome analyses defined a subset of 79 A. pullulans genes (among the 10,925 annotated genes) that were transcriptionally upregulated or exclusively detected at the protein level during the competition with F. oxysporum. These potential biocontrol genes comprised predicted secreted hydrolases such as glycosylases, esterases, and proteases, as well as genes encoding enzymes, which are predicted to be involved in the synthesis of secondary metabolites. This study highlights the value of a sequential approach starting with genome mining and consecutive transcriptome and secretome analyses in order to identify a limited number of potential target genes for detailed, functional analyses.
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Affiliation(s)
- Maria Paula Rueda-Mejia
- Agroscope, Research Division Plant Protection, Müller-Thurgau-Strasse 29, 8820 Wädenswil, Switzerland
| | - Lukas Nägeli
- Agroscope, Research Division Plant Protection, Müller-Thurgau-Strasse 29, 8820 Wädenswil, Switzerland
| | - Stefanie Lutz
- Agroscope, Competence Division Method Development and Analytics, Müller-Thurgau-Strasse 29, 8820, Wädenswil, Switzerland
| | - Richard D Hayes
- U.S. Department of Energy Joint Genome Institute (JGI), Lawrence Berkeley National Laboratory, 1 Cyclotron Rd., Berkeley, California 94720, USA
| | - Adithi R Varadarajan
- Agroscope, Competence Division Method Development and Analytics, Müller-Thurgau-Strasse 29, 8820, Wädenswil, Switzerland
| | - Igor V Grigoriev
- U.S. Department of Energy Joint Genome Institute (JGI), Lawrence Berkeley National Laboratory, 1 Cyclotron Rd., Berkeley, California 94720, USA.,Department of Plant and Microbial Biology, University of California Berkeley, Koshland Hall, Berkeley, CA, USA
| | - Christian H Ahrens
- Agroscope, Competence Division Method Development and Analytics, Müller-Thurgau-Strasse 29, 8820, Wädenswil, Switzerland.,SIB, Swiss Institute of Bioinformatics, Wädenswil, Switzerland
| | - Florian M Freimoser
- Agroscope, Research Division Plant Protection, Müller-Thurgau-Strasse 29, 8820 Wädenswil, Switzerland
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11
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Kanza S, Bird CL, Niranjan M, McNeill W, Frey JG. The AI for Scientific Discovery Network . PATTERNS (NEW YORK, N.Y.) 2021; 2:100162. [PMID: 33511363 PMCID: PMC7815949 DOI: 10.1016/j.patter.2020.100162] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The Artificial Intelligence and Augmented Intelligence for Automated Investigation for Scientific Discovery Network+ (AI3SD) was established in response to the UK Engineering and Physical Sciences Research Council (EPSRC) late-2017 call for a Network+ to promote cutting-edge research in artificial intelligence to accelerate groundbreaking scientific discoveries. This article provides the philosophical, scientific, and technical underpinnings of the Network+, the history of the different domains represented in the Network+, and the specific focus of the Network+. The activities, collaborations, and research covered in the first year of the Network+ have highlighted the significant challenges in the chemistry and augmented and artificial intelligence space. These challenges are shaping the future directions of the Network+. The article concludes with a summary of the lessons learned in running this Network+ and introduces our plans for the future in a landscape redrawn by COVID-19, including rebranding into the AI 4 Scientific Discovery Network (www.ai4science.network).
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Affiliation(s)
- Samantha Kanza
- School of Chemistry, University of Southampton, Southampton SO17 1BJ, UK
| | - Colin Leonard Bird
- School of Chemistry, University of Southampton, Southampton SO17 1BJ, UK
| | - Mahesan Niranjan
- School of Electronics and Computer Science and University of Southampton, Southampton SO17 1BJ, UK
| | - William McNeill
- School of Humanities, University of Southampton, Southampton SO17 1BJ, UK
| | - Jeremy Graham Frey
- School of Chemistry, University of Southampton, Southampton SO17 1BJ, UK
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12
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Shetta O, Niranjan M. Robust subspace methods for outlier detection in genomic data circumvents the curse of dimensionality. ROYAL SOCIETY OPEN SCIENCE 2020; 7:190714. [PMID: 32257299 PMCID: PMC7062061 DOI: 10.1098/rsos.190714] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Accepted: 12/12/2019] [Indexed: 06/11/2023]
Abstract
The application of machine learning to inference problems in biology is dominated by supervised learning problems of regression and classification, and unsupervised learning problems of clustering and variants of low-dimensional projections for visualization. A class of problems that have not gained much attention is detecting outliers in datasets, arising from reasons such as gross experimental, reporting or labelling errors. These could also be small parts of a dataset that are functionally distinct from the majority of a population. Outlier data are often identified by considering the probability density of normal data and comparing data likelihoods against some threshold. This classical approach suffers from the curse of dimensionality, which is a serious problem with omics data which are often found in very high dimensions. We develop an outlier detection method based on structured low-rank approximation methods. The objective function includes a regularizer based on neighbourhood information captured in the graph Laplacian. Results on publicly available genomic data show that our method robustly detects outliers whereas a density-based method fails even at moderate dimensions. Moreover, we show that our method has better clustering and visualization performance on the recovered low-dimensional projection when compared with popular dimensionality reduction techniques.
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Affiliation(s)
- Omar Shetta
- Author for correspondence: Omar Shetta e-mail:
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13
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Parkes GM, Niranjan M. Uncovering extensive post-translation regulation during human cell cycle progression by integrative multi-'omics analysis. BMC Bioinformatics 2019; 20:536. [PMID: 31664894 PMCID: PMC6820968 DOI: 10.1186/s12859-019-3150-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Accepted: 10/04/2019] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Analysis of high-throughput multi-'omics interactions across the hierarchy of expression has wide interest in making inferences with regard to biological function and biomarker discovery. Expression levels across different scales are determined by robust synthesis, regulation and degradation processes, and hence transcript (mRNA) measurements made by microarray/RNA-Seq only show modest correlation with corresponding protein levels. RESULTS In this work we are interested in quantitative modelling of correlation across such gene products. Building on recent work, we develop computational models spanning transcript, translation and protein levels at different stages of the H. sapiens cell cycle. We enhance this analysis by incorporating 25+ sequence-derived features which are likely determinants of cellular protein concentration and quantitatively select for relevant features, producing a vast dataset with thousands of genes. We reveal insights into the complex interplay between expression levels across time, using machine learning methods to highlight outliers with respect to such models as proteins associated with post-translationally regulated modes of action. CONCLUSIONS We uncover quantitative separation between modified and degraded proteins that have roles in cell cycle regulation, chromatin remodelling and protein catabolism according to Gene Ontology; and highlight the opportunities for providing biological insights in future model systems.
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Affiliation(s)
- Gregory M Parkes
- University of Southampton, University Road, Southampton, SO17 1BJ, UK.
| | - Mahesan Niranjan
- University of Southampton, University Road, Southampton, SO17 1BJ, UK
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14
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Bauer I, Lechner L, Pidroni A, Petrone AM, Merschak P, Lindner H, Kremser L, Graessle S, Golderer G, Allipour S, Brosch G. Type I and II PRMTs regulate catabolic as well as detoxifying processes in Aspergillus nidulans. Fungal Genet Biol 2019; 129:86-100. [PMID: 31145992 DOI: 10.1016/j.fgb.2019.05.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2018] [Revised: 05/03/2019] [Accepted: 05/24/2019] [Indexed: 11/28/2022]
Abstract
In filamentous fungi, arginine methylation has been implicated in morphogenesis, mycotoxin biosynthesis, pathogenicity, and stress response although the exact role of this posttranslational modification in these processes remains obscure. Here, we present the first genome-wide transcriptome analysis in filamentous fungi that compared expression levels of genes regulated by type I and type II protein arginine methyltransferases (PRMTs). In Aspergillus nidulans, three conserved type I and II PRMTs are present that catalyze asymmetric or symmetric dimethylation of arginines. We generated a double type I mutant (ΔrmtA/rmtB) and a combined type I and type II mutant (ΔrmtB/rmtC) to perform genome-wide comparison of their effects on gene expression, but also to monitor putative overlapping activities and reciprocal regulations of type I and type II PRMTs in Aspergillus. Our study demonstrates, that rmtA and rmtC as type I and type II representatives act together as repressors of proteins that are secreted into the extracellular region as the majority of up-regulated genes are mainly involved in catabolic pathways that constitute the secretome of Aspergillus. In addition to a strong up-regulation of secretory genes we found a significant enrichment of down-regulated genes involved in processes related to oxidation-reduction, transmembrane transport and secondary metabolite biosynthesis. Strikingly, nearly 50% of down-regulated genes in both double mutants correspond to redox reaction/oxidoreductase processes, a remarkable finding in light of our recently observed oxidative stress phenotypes of ΔrmtA and ΔrmtC. Finally, analysis of nuclear and cytoplasmic extracts for mono-methylated proteins revealed the presence of both, common and specific substrates of RmtA and RmtC. Thus, our data indicate that type I and II PRMTs in Aspergillus seem to co-regulate the same biological processes but also specifically affect other pathways in a non-redundant fashion.
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Affiliation(s)
- Ingo Bauer
- Division of Molecular Biology, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Lukas Lechner
- Division of Molecular Biology, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Angelo Pidroni
- Division of Molecular Biology, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Anna-Maria Petrone
- Division of Molecular Biology, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Petra Merschak
- Division of Molecular Biology, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Herbert Lindner
- Division of Clinical Biochemistry, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Leopold Kremser
- Division of Clinical Biochemistry, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Stefan Graessle
- Division of Molecular Biology, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Georg Golderer
- Division of Biological Chemistry, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Shadab Allipour
- Division of Molecular Biology, Medical University of Innsbruck, 6020 Innsbruck, Austria.
| | - Gerald Brosch
- Division of Molecular Biology, Medical University of Innsbruck, 6020 Innsbruck, Austria.
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15
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Haldar R, Shaashua L, Lavon H, Lyons YA, Zmora O, Sharon E, Birnbaum Y, Allweis T, Sood AK, Barshack I, Cole S, Ben-Eliyahu S. Perioperative inhibition of β-adrenergic and COX2 signaling in a clinical trial in breast cancer patients improves tumor Ki-67 expression, serum cytokine levels, and PBMCs transcriptome. Brain Behav Immun 2018; 73:294-309. [PMID: 29800703 DOI: 10.1016/j.bbi.2018.05.014] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Revised: 05/10/2018] [Accepted: 05/18/2018] [Indexed: 12/18/2022] Open
Abstract
Catecholamines and prostaglandins are secreted abundantly during the perioperative period in response to stress and surgery, and were shown by translational studies to promote tumor metastasis. Here, in a phase-II biomarker clinical trial in breast cancer patients (n = 38), we tested the combined perioperative use of the β-blocker, propranolol, and the COX2-inhibitor, etodolac, scheduled for 11 consecutive perioperative days, starting 5 days before surgery. Blood samples were taken before treatment (T1), on the mornings before and after surgery (T2&T3), and after treatment cessation (T4). Drugs were well tolerated. Results based on a-priori hypotheses indicated that already before surgery (T2), serum levels of pro-inflammatory IL-6, CRP, and IFNγ, and anti-inflammatory, cortisol and IL-10, increased. At T2 and/or T3, drug treatment reduced serum levels of the above pro-inflammatory cytokines and of TRAIL, as well as activity of multiple inflammation-related transcription factors (including NFκB, STAT3, ISRE), but not serum levels of cortisol, IL-10, IL-18, IL-8, VEGF and TNFα. In the excised tumor, treatment reduced the expression of the proliferation marker Ki-67, and positively affected its transcription factors SP1 and AhR. Exploratory analyses of transcriptome modulation in PBMCs revealed treatment-induced improvement at T2/T3 in several transcription factors that in primary tumors indicate poor prognosis (CUX1, THRa, EVI1, RORa, PBX1, and T3R), angiogenesis (YY1), EMT (GATA1 and deltaEF1/ZEB1), proliferation (GATA2), and glucocorticoids response (GRE), while increasing the activity of the oncogenes c-MYB and N-MYC. Overall, the drug treatment may benefit breast cancer patients through reducing systemic inflammation and pro-metastatic/pro-growth biomarkers in the excised tumor and PBMCs.
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Affiliation(s)
- Rita Haldar
- Sagol School of Neuroscience and School of Psychological Sciences, Tel Aviv University, Israel
| | - Lee Shaashua
- Sagol School of Neuroscience and School of Psychological Sciences, Tel Aviv University, Israel
| | - Hagar Lavon
- Sagol School of Neuroscience and School of Psychological Sciences, Tel Aviv University, Israel
| | - Yasmin A Lyons
- Department of Gynecologic Oncology and Reproductive Medicine, Division of Surgery, M.D. Anderson Cancer Center at University of Texas, Huston, TX, USA
| | - Oded Zmora
- Department of Surgery and Transplantation, Sheba Medical Center, Ramat Gan, Israel
| | - Eran Sharon
- Department of Surgery, Rabin Medical Center, Beilinson Hospital, Petach-Tikva, Israel
| | - Yehudit Birnbaum
- Department of Surgery, Rabin Medical Center, Beilinson Hospital, Petach-Tikva, Israel
| | - Tanir Allweis
- Department of Surgery, Kaplan Medical Center, Rehovot, Israel
| | - Anil K Sood
- Department of Gynecologic Oncology and Reproductive Medicine, Division of Surgery, M.D. Anderson Cancer Center at University of Texas, Huston, TX, USA
| | - Iris Barshack
- Department of Pathology, Sheba Medical Center, Ramat Gan, Israel
| | - Steve Cole
- Department of Medicine, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Shamgar Ben-Eliyahu
- Sagol School of Neuroscience and School of Psychological Sciences, Tel Aviv University, Israel.
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16
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Hofmann JD, Otto A, Berges M, Biedendieck R, Michel AM, Becher D, Jahn D, Neumann-Schaal M. Metabolic Reprogramming of Clostridioides difficile During the Stationary Phase With the Induction of Toxin Production. Front Microbiol 2018; 9:1970. [PMID: 30186274 PMCID: PMC6110889 DOI: 10.3389/fmicb.2018.01970] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 08/03/2018] [Indexed: 12/20/2022] Open
Abstract
The obligate anaerobe, spore forming bacterium Clostridioides difficile (formerly Clostridium difficile) causes nosocomial and community acquired diarrhea often associated with antibiotic therapy. Major virulence factors of the bacterium are the two large clostridial toxins TcdA and TcdB. The production of both toxins was found strongly connected to the metabolism and the nutritional status of the growth environment. Here, we systematically investigated the changes of the gene regulatory, proteomic and metabolic networks of C. difficile 630Δerm underlying the adaptation to the non-growing state in the stationary phase. Integrated data from time-resolved transcriptome, proteome and metabolome investigations performed under defined growth conditions uncovered multiple adaptation strategies. Overall changes in the cellular processes included the downregulation of ribosome production, lipid metabolism, cold shock proteins, spermine biosynthesis, and glycolysis and in the later stages of riboflavin and coenzyme A (CoA) biosynthesis. In contrast, different chaperones, several fermentation pathways, and cysteine, serine, and pantothenate biosynthesis were found upregulated. Focusing on the Stickland amino acid fermentation and the central carbon metabolism, we discovered the ability of C. difficile to replenish its favored amino acid cysteine by a pathway starting from the glycolytic 3-phosphoglycerate via L-serine as intermediate. Following the growth course, the reductive equivalent pathways used were sequentially shifted from proline via leucine/phenylalanine to the central carbon metabolism first to butanoate fermentation and then further to lactate fermentation. The toxin production was found correlated mainly to fluxes of the central carbon metabolism. Toxin formation in the supernatant was detected when the flux changed from butanoate to lactate synthesis in the late stationary phase. The holistic view derived from the combination of transcriptome, proteome and metabolome data allowed us to uncover the major metabolic strategies that are used by the clostridial cells to maintain its cellular homeostasis and ensure survival under starvation conditions.
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Affiliation(s)
- Julia D Hofmann
- Department of Bioinformatics and Biochemistry, Technische Universität Braunschweig, Braunschweig, Germany.,Braunschweig Integrated Centre of Systems Biology (BRICS), Braunschweig, Germany
| | - Andreas Otto
- Department for Microbial Proteomics, University of Greifswald, Greifswald, Germany
| | - Mareike Berges
- Braunschweig Integrated Centre of Systems Biology (BRICS), Braunschweig, Germany.,Institute of Microbiology, Technische Universität Braunschweig, Braunschweig, Germany
| | - Rebekka Biedendieck
- Braunschweig Integrated Centre of Systems Biology (BRICS), Braunschweig, Germany.,Institute of Microbiology, Technische Universität Braunschweig, Braunschweig, Germany
| | - Annika-Marisa Michel
- Braunschweig Integrated Centre of Systems Biology (BRICS), Braunschweig, Germany.,Institute of Microbiology, Technische Universität Braunschweig, Braunschweig, Germany
| | - Dörte Becher
- Department for Microbial Proteomics, University of Greifswald, Greifswald, Germany
| | - Dieter Jahn
- Braunschweig Integrated Centre of Systems Biology (BRICS), Braunschweig, Germany.,Institute of Microbiology, Technische Universität Braunschweig, Braunschweig, Germany
| | - Meina Neumann-Schaal
- Department of Bioinformatics and Biochemistry, Technische Universität Braunschweig, Braunschweig, Germany.,Braunschweig Integrated Centre of Systems Biology (BRICS), Braunschweig, Germany.,Leibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany
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17
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Ramalho RF, Li S, Radivojac P, Hahn MW. Proteomic Evidence for In-Frame and Out-of-Frame Alternatively Spliced Isoforms in Human and Mouse. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2018; 15:1284-1289. [PMID: 26394435 DOI: 10.1109/tcbb.2015.2480068] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
In order to find evidence for translation of alternatively spliced transcripts, especially those that result in a change in reading frame, we collected exon-skipping cases previously found by RNA-Seq and applied a computational approach to screen millions of mass spectra. These spectra came from seven human and six mouse tissues, five of which are the same between the two organisms: liver, kidney, lung, heart, and brain. Overall, we detected 4 percent of all exon-skipping events found in RNA-seq data, regardless of their effect on reading frame. The fraction of alternative isoforms detected did not differ between out-of-frame and in-frame events. Moreover, the fraction of identified alternative exon-exon junctions and constitutive junctions were similar. Together, our results suggest that both in-frame and out-of-frame translation may be actively used to regulate protein activity or localization.
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18
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Martinez-Nunez RT, Rupani H, Platé M, Niranjan M, Chambers RC, Howarth PH, Sanchez-Elsner T. Genome-Wide Posttranscriptional Dysregulation by MicroRNAs in Human Asthma as Revealed by Frac-seq. THE JOURNAL OF IMMUNOLOGY 2018; 201:251-263. [PMID: 29769273 DOI: 10.4049/jimmunol.1701798] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Received: 12/29/2017] [Accepted: 04/17/2018] [Indexed: 12/07/2022]
Abstract
MicroRNAs are small noncoding RNAs that inhibit gene expression posttranscriptionally, implicated in virtually all biological processes. Although the effect of individual microRNAs is generally studied, the genome-wide role of multiple microRNAs is less investigated. We assessed paired genome-wide expression of microRNAs with total (cytoplasmic) and translational (polyribosome-bound) mRNA levels employing subcellular fractionation and RNA sequencing (Frac-seq) in human primary bronchoepithelium from healthy controls and severe asthmatics. Severe asthma is a chronic inflammatory disease of the airways characterized by poor response to therapy. We found genes (i.e., isoforms of a gene) and mRNA isoforms differentially expressed in asthma, with novel inflammatory and structural pathophysiological mechanisms related to bronchoepithelium disclosed solely by polyribosome-bound mRNAs (e.g., IL1A and LTB genes or ITGA6 and ITGA2 alternatively spliced isoforms). Gene expression (i.e., isoforms of a gene) and mRNA expression analysis revealed different molecular candidates and biological pathways, with differentially expressed polyribosome-bound and total mRNAs also showing little overlap. We reveal a hub of six dysregulated microRNAs accounting for ∼90% of all microRNA targeting, displaying preference for polyribosome-bound mRNAs. Transfection of this hub in bronchial epithelial cells from healthy donors mimicked asthma characteristics. Our work demonstrates extensive posttranscriptional gene dysregulation in human asthma, in which microRNAs play a central role, illustrating the feasibility and importance of assessing posttranscriptional gene expression when investigating human disease.
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Affiliation(s)
- Rocio T Martinez-Nunez
- School of Immunology and Microbial Sciences, Medical Research Council and Asthma UK Centre in Allergic Mechanisms of Asthma, King's College London, London SE19RT, United Kingdom; .,Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton SO16 6YD, United Kingdom
| | - Hitasha Rupani
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton SO16 6YD, United Kingdom.,Southampton National Institute for Health Research Respiratory Biomedical Research Unit, Southampton Centre for Biomedical Research, University Hospital Southampton National Health Service Foundation Trust, Southampton SO16 6YD, United Kingdom
| | - Manuela Platé
- Centre for Inflammation and Tissue Repair, Department of Respiratory Medicine, Rayne Institute, University College London, London WC1E 6JF, United Kingdom; and
| | - Mahesan Niranjan
- School of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - Rachel C Chambers
- Centre for Inflammation and Tissue Repair, Department of Respiratory Medicine, Rayne Institute, University College London, London WC1E 6JF, United Kingdom; and
| | - Peter H Howarth
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton SO16 6YD, United Kingdom.,Southampton National Institute for Health Research Respiratory Biomedical Research Unit, Southampton Centre for Biomedical Research, University Hospital Southampton National Health Service Foundation Trust, Southampton SO16 6YD, United Kingdom
| | - Tilman Sanchez-Elsner
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton SO16 6YD, United Kingdom
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19
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Omics Approaches for Identifying Physiological Adaptations to Genome Instability in Aging. Int J Mol Sci 2017; 18:ijms18112329. [PMID: 29113067 PMCID: PMC5713298 DOI: 10.3390/ijms18112329] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Revised: 10/25/2017] [Accepted: 10/29/2017] [Indexed: 12/25/2022] Open
Abstract
DNA damage causally contributes to aging and age-related diseases. The declining functioning of tissues and organs during aging can lead to the increased risk of succumbing to aging-associated diseases. Congenital syndromes that are caused by heritable mutations in DNA repair pathways lead to cancer susceptibility and accelerated aging, thus underlining the importance of genome maintenance for withstanding aging. High-throughput mass-spectrometry-based approaches have recently contributed to identifying signalling response networks and gaining a more comprehensive understanding of the physiological adaptations occurring upon unrepaired DNA damage. The insulin-like signalling pathway has been implicated in a DNA damage response (DDR) network that includes epidermal growth factor (EGF)-, AMP-activated protein kinases (AMPK)- and the target of rapamycin (TOR)-like signalling pathways, which are known regulators of growth, metabolism, and stress responses. The same pathways, together with the autophagy-mediated proteostatic response and the decline in energy metabolism have also been found to be similarly regulated during natural aging, suggesting striking parallels in the physiological adaptation upon persistent DNA damage due to DNA repair defects and long-term low-level DNA damage accumulation occurring during natural aging. These insights will be an important starting point to study the interplay between signalling networks involved in progeroid syndromes that are caused by DNA repair deficiencies and to gain new understanding of the consequences of DNA damage in the aging process.
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20
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Tacchi JL, Raymond BBA, Haynes PA, Berry IJ, Widjaja M, Bogema DR, Woolley LK, Jenkins C, Minion FC, Padula MP, Djordjevic SP. Post-translational processing targets functionally diverse proteins in Mycoplasma hyopneumoniae. Open Biol 2016; 6:150210. [PMID: 26865024 PMCID: PMC4772806 DOI: 10.1098/rsob.150210] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Mycoplasma hyopneumoniae is a genome-reduced, cell wall-less, bacterial pathogen with a predicted coding capacity of less than 700 proteins and is one of the smallest self-replicating pathogens. The cell surface of M. hyopneumoniae is extensively modified by processing events that target the P97 and P102 adhesin families. Here, we present analyses of the proteome of M. hyopneumoniae-type strain J using protein-centric approaches (one- and two-dimensional GeLC–MS/MS) that enabled us to focus on global processing events in this species. While these approaches only identified 52% of the predicted proteome (347 proteins), our analyses identified 35 surface-associated proteins with widely divergent functions that were targets of unusual endoproteolytic processing events, including cell adhesins, lipoproteins and proteins with canonical functions in the cytosol that moonlight on the cell surface. Affinity chromatography assays that separately used heparin, fibronectin, actin and host epithelial cell surface proteins as bait recovered cleavage products derived from these processed proteins, suggesting these fragments interact directly with the bait proteins and display previously unrecognized adhesive functions. We hypothesize that protein processing is underestimated as a post-translational modification in genome-reduced bacteria and prokaryotes more broadly, and represents an important mechanism for creating cell surface protein diversity.
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Affiliation(s)
- Jessica L Tacchi
- The ithree Institute, University of Technology Sydney, PO Box 123, Broadway, New South Wales 2007, Australia
| | - Benjamin B A Raymond
- The ithree Institute, University of Technology Sydney, PO Box 123, Broadway, New South Wales 2007, Australia
| | - Paul A Haynes
- Department of Chemistry and Biomolecular Sciences, Macquarie University, North Ryde, New South Wales 2109, Australia
| | - Iain J Berry
- The ithree Institute, University of Technology Sydney, PO Box 123, Broadway, New South Wales 2007, Australia
| | - Michael Widjaja
- The ithree Institute, University of Technology Sydney, PO Box 123, Broadway, New South Wales 2007, Australia
| | - Daniel R Bogema
- The ithree Institute, University of Technology Sydney, PO Box 123, Broadway, New South Wales 2007, Australia NSW Department of Primary Industries, Elizabeth Macarthur Agricultural Institute, Menangle, New South Wales 2568, Australia
| | - Lauren K Woolley
- NSW Department of Primary Industries, Elizabeth Macarthur Agricultural Institute, Menangle, New South Wales 2568, Australia School of Biological Sciences, University of Wollongong, Wollongong, New South Wales 2522, Australia
| | - Cheryl Jenkins
- NSW Department of Primary Industries, Elizabeth Macarthur Agricultural Institute, Menangle, New South Wales 2568, Australia
| | - F Chris Minion
- Department of Veterinary Microbiology and Preventative Medicine, Iowa State University, Ames, IA 50011, USA
| | - Matthew P Padula
- The ithree Institute, University of Technology Sydney, PO Box 123, Broadway, New South Wales 2007, Australia Proteomics Core Facility, University of Technology Sydney, PO Box 123, Broadway, New South Wales 2007, Australia
| | - Steven P Djordjevic
- The ithree Institute, University of Technology Sydney, PO Box 123, Broadway, New South Wales 2007, Australia Proteomics Core Facility, University of Technology Sydney, PO Box 123, Broadway, New South Wales 2007, Australia
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21
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Lauria F, Tebaldi T, Lunelli L, Struffi P, Gatto P, Pugliese A, Brigotti M, Montanaro L, Ciribilli Y, Inga A, Quattrone A, Sanguinetti G, Viero G. RiboAbacus: a model trained on polyribosome images predicts ribosome density and translational efficiency from mammalian transcriptomes. Nucleic Acids Res 2015; 43:e153. [PMID: 26240374 PMCID: PMC4678843 DOI: 10.1093/nar/gkv781] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2015] [Accepted: 07/20/2015] [Indexed: 01/14/2023] Open
Abstract
Fluctuations in mRNA levels only partially contribute to determine variations in mRNA availability for translation, producing the well-known poor correlation between transcriptome and proteome data. Recent advances in microscopy now enable researchers to obtain high resolution images of ribosomes on transcripts, providing precious snapshots of translation in vivo. Here we propose RiboAbacus, a mathematical model that for the first time incorporates imaging data in a predictive model of transcript-specific ribosome densities and translational efficiencies. RiboAbacus uses a mechanistic model of ribosome dynamics, enabling the quantification of the relative importance of different features (such as codon usage and the 5′ ramp effect) in determining the accuracy of predictions. The model has been optimized in the human Hek-293 cell line to fit thousands of images of human polysomes obtained by atomic force microscopy, from which we could get a reference distribution of the number of ribosomes per mRNA with unmatched resolution. After validation, we applied RiboAbacus to three case studies of known transcriptome-proteome datasets for estimating the translational efficiencies, resulting in an increased correlation with corresponding proteomes. RiboAbacus is an intuitive tool that allows an immediate estimation of crucial translation properties for entire transcriptomes, based on easily obtainable transcript expression levels.
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Affiliation(s)
- Fabio Lauria
- Institute of Biophysics, CNR Unit at Trento, Via alla Cascata, 56/C-38123 Povo (TN), Italy
| | - Toma Tebaldi
- Laboratory of Translational Genomics, Centre for Integrative Biology, Via delle Regole, 101-38123 Mattarello (TN), Italy
| | - Lorenzo Lunelli
- Laboratory of Biomolecular Sequence and Structure Analysis for Health, Fondazione Bruno Kessler, Via Sommarive, 18-38123 Povo (TN), Italy
| | - Paolo Struffi
- Laboratory of Translational Genomics, Centre for Integrative Biology, Via delle Regole, 101-38123 Mattarello (TN), Italy
| | - Pamela Gatto
- Laboratory of Translational Genomics, Centre for Integrative Biology, Via delle Regole, 101-38123 Mattarello (TN), Italy
| | - Andrea Pugliese
- Mathematics Department, University of Trento, Via Sommarive, 14-38123 Povo (TN), Italy
| | - Maurizio Brigotti
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Via S. Giacomo, 14-40126 Bologna, Italy
| | - Lorenzo Montanaro
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Via S. Giacomo, 14-40126 Bologna, Italy
| | - Yari Ciribilli
- Laboratory of Transcriptional Networks, Centre for Integrative Biology, Via delle Regole, 101-38123 Mattarello (TN), Italy
| | - Alberto Inga
- Laboratory of Transcriptional Networks, Centre for Integrative Biology, Via delle Regole, 101-38123 Mattarello (TN), Italy
| | - Alessandro Quattrone
- Laboratory of Translational Genomics, Centre for Integrative Biology, Via delle Regole, 101-38123 Mattarello (TN), Italy
| | - Guido Sanguinetti
- School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh, Midlothian EH8 9AB, UK
| | - Gabriella Viero
- Institute of Biophysics, CNR Unit at Trento, Via alla Cascata, 56/C-38123 Povo (TN), Italy
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22
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Emri T, Szarvas V, Orosz E, Antal K, Park H, Han KH, Yu JH, Pócsi I. Core oxidative stress response in Aspergillus nidulans. BMC Genomics 2015; 16:478. [PMID: 26115917 PMCID: PMC4482186 DOI: 10.1186/s12864-015-1705-z] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2014] [Accepted: 06/15/2015] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND The b-Zip transcription factor AtfA plays a key role in regulating stress responses in the filamentous fungus Aspergillus nidulans. To identify the core regulons of AtfA, we examined genome-wide expression changes caused by various stresses in the presence/absence of AtfA using A. nidulans microarrays. We also intended to address the intriguing question regarding the existence of core environmental stress response in this important model eukaryote. RESULTS Examination of the genome wide expression changes caused by five different oxidative stress conditions in wild type and the atfA null mutant has identified a significant number of stereotypically regulated genes (Core Oxidative Stress Response genes). The deletion of atfA increased the oxidative stress sensitivity of A. nidulans and affected mRNA accumulation of several genes under both unstressed and stressed conditions. The numbers of genes under the AtfA control appear to be specific to a stress-type. We also found that both oxidative and salt stresses induced expression of some secondary metabolite gene clusters and the deletion of atfA enhanced the stress responsiveness of additional clusters. Moreover, certain clusters were down-regulated by the stresses tested. CONCLUSION Our data suggest that the observed co-regulations were most likely consequences of the overlapping physiological effects of the stressors and not of the existence of a general environmental stress response. The function of AtfA in governing various stress responses is much smaller than anticipated and/or other regulators may play a redundant or overlapping role with AtfA. Both stress inducible and stress repressive regulations of secondary metabolism seem to be frequent features in A. nidulans.
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Affiliation(s)
- Tamás Emri
- Department of Biotechnology and Microbiology, Faculty of Science and Technology, University of Debrecen, P.O. Box 63, H-4032, Debrecen, Hungary.
| | - Vera Szarvas
- Department of Biotechnology and Microbiology, Faculty of Science and Technology, University of Debrecen, P.O. Box 63, H-4032, Debrecen, Hungary.
| | - Erzsébet Orosz
- Department of Biotechnology and Microbiology, Faculty of Science and Technology, University of Debrecen, P.O. Box 63, H-4032, Debrecen, Hungary.
| | - Károly Antal
- Department of Zoology, Faculty of Sciences, Eszterházy Károly College, Eszterházy út 1, H-3300, Eger, Hungary.
| | - HeeSoo Park
- Department of Bacteriology, University of Wisconsin, 1550 Linden Dr, Madison, WI, 53706, USA.
| | - Kap-Hoon Han
- Department of Pharmaceutical Engineering, Woosuk University, 565-701, Wanju, Republic of Korea.
| | - Jae-Hyuk Yu
- Department of Bacteriology, University of Wisconsin, 1550 Linden Dr, Madison, WI, 53706, USA.
| | - István Pócsi
- Department of Biotechnology and Microbiology, Faculty of Science and Technology, University of Debrecen, P.O. Box 63, H-4032, Debrecen, Hungary.
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23
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Gunawardana Y, Fujiwara S, Takeda A, Woo J, Woelk C, Niranjan M. Outlier detection at the transcriptome-proteome interface. Bioinformatics 2015; 31:2530-6. [PMID: 25819671 DOI: 10.1093/bioinformatics/btv182] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2014] [Accepted: 03/24/2015] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND In high-throughput experimental biology, it is widely acknowledged that while expression levels measured at the levels of transcriptome and the corresponding proteome do not, in general, correlate well, messenger RNA levels are used as convenient proxies for protein levels. Our interest is in developing data-driven computational models that can bridge the gap between these two levels of measurement at which different mechanisms of regulation may act on different molecular species causing any observed lack of correlations. To this end, we build data-driven predictors of protein levels using mRNA levels and known proxies of translation efficiencies as covariates. Previous work showed that in such a setting, outliers with respect to the model are reliable candidates for post-translational regulation. RESULTS Here, we present and compare two novel formulations of deriving a protein concentration predictor from which outliers may be extracted in a systematic manner. The first approach, outlier rejecting regression, allows explicit specification of a certain fraction of the data as outliers. In a regression setting, this is a non-convex optimization problem which we solve by deriving a difference of convex functions algorithm (DCA). With post-translationally regulated proteins, one expects their concentrations to be affected primarily by disruption of protein stability. Our second algorithm exploits this observation by minimizing an asymmetric loss using quantile regression and extracts outlier proteins whose measured concentrations are lower than what a genome-wide regression would predict. We validate the two approaches on a dataset of yeast transcriptome and proteome. Functional annotation check on detected outliers demonstrate that the methods are able to identify post-translationally regulated genes with high statistical confidence.
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Affiliation(s)
- Yawwani Gunawardana
- School of Electronics and Computer Science, University of Southampton, Southampton, UK
| | - Shuhei Fujiwara
- Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan and
| | - Akiko Takeda
- Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan and
| | - Jeongmin Woo
- Faculty of Medicine, Southampton General Hospital, University of Southampton, Southampton, UK
| | - Christopher Woelk
- Faculty of Medicine, Southampton General Hospital, University of Southampton, Southampton, UK
| | - Mahesan Niranjan
- School of Electronics and Computer Science, University of Southampton, Southampton, UK
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24
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López García de Lomana A, Schäuble S, Valenzuela J, Imam S, Carter W, Bilgin DD, Yohn CB, Turkarslan S, Reiss DJ, Orellana MV, Price ND, Baliga NS. Transcriptional program for nitrogen starvation-induced lipid accumulation in Chlamydomonas reinhardtii. BIOTECHNOLOGY FOR BIOFUELS 2015; 8:207. [PMID: 26633994 PMCID: PMC4667458 DOI: 10.1186/s13068-015-0391-z] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Accepted: 11/17/2015] [Indexed: 05/08/2023]
Abstract
BACKGROUND Algae accumulate lipids to endure different kinds of environmental stresses including macronutrient starvation. Although this response has been extensively studied, an in depth understanding of the transcriptional regulatory network (TRN) that controls the transition into lipid accumulation remains elusive. In this study, we used a systems biology approach to elucidate the transcriptional program that coordinates the nitrogen starvation-induced metabolic readjustments that drive lipid accumulation in Chlamydomonas reinhardtii. RESULTS We demonstrate that nitrogen starvation triggered differential regulation of 2147 transcripts, which were co-regulated in 215 distinct modules and temporally ordered as 31 transcriptional waves. An early-stage response was triggered within 12 min that initiated growth arrest through activation of key signaling pathways, while simultaneously preparing the intracellular environment for later stages by modulating transport processes and ubiquitin-mediated protein degradation. Subsequently, central metabolism and carbon fixation were remodeled to trigger the accumulation of triacylglycerols. Further analysis revealed that these waves of genome-wide transcriptional events were coordinated by a regulatory program orchestrated by at least 17 transcriptional regulators, many of which had not been previously implicated in this process. We demonstrate that the TRN coordinates transcriptional downregulation of 57 metabolic enzymes across a period of nearly 4 h to drive an increase in lipid content per unit biomass. Notably, this TRN appears to also drive lipid accumulation during sulfur starvation, while phosphorus starvation induces a different regulatory program. The TRN model described here is available as a community-wide web-resource at http://networks.systemsbiology.net/chlamy-portal. CONCLUSIONS In this work, we have uncovered a comprehensive mechanistic model of the TRN controlling the transition from N starvation to lipid accumulation. The program coordinates sequentially ordered transcriptional waves that simultaneously arrest growth and lead to lipid accumulation. This study has generated predictive tools that will aid in devising strategies for the rational manipulation of regulatory and metabolic networks for better biofuel and biomass production.
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Affiliation(s)
| | - Sascha Schäuble
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
- />Jena University Language and Information Engineering (JULIE) Lab, Friedrich-Schiller-University Jena, Jena, Germany
- />Research Group Theoretical Systems Biology, Friedrich-Schiller-University Jena, Jena, Germany
| | - Jacob Valenzuela
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
| | - Saheed Imam
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
| | - Warren Carter
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
| | | | | | - Serdar Turkarslan
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
| | - David J. Reiss
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
| | - Mónica V. Orellana
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
- />Polar Science Center, University of Washington, Seattle, WA USA
| | - Nathan D. Price
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
- />Departments of Bioengineering and Computer Science and Engineering, University of Washington, Seattle, WA USA
- />Molecular and Cellular Biology Program, University of Washington, Seattle, WA USA
| | - Nitin S. Baliga
- />Institute for Systems Biology, 401 Terry Ave N, Seattle, 98109 WA USA
- />Departments of Biology and Microbiology, University of Washington, Seattle, WA USA
- />Molecular and Cellular Biology Program, University of Washington, Seattle, WA USA
- />Lawrence Berkeley National Lab, Berkeley, CA USA
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25
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Wang X, Liu Q, Zhang B. Leveraging the complementary nature of RNA-Seq and shotgun proteomics data. Proteomics 2014; 14:2676-87. [PMID: 25266668 DOI: 10.1002/pmic.201400184] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2014] [Revised: 08/22/2014] [Accepted: 09/25/2014] [Indexed: 12/22/2022]
Abstract
RNA sequencing (RNA-Seq) and MS-based shotgun proteomics are powerful high-throughput technologies for identifying and quantifying RNA transcripts and proteins, respectively. With the increasing affordability of these technologies, many projects have started to apply both to the same samples to achieve a more comprehensive understanding of biological systems. A major analytical challenge for such integrative projects is how to effectively leverage the complementary nature of RNA-Seq and shotgun proteomics data. RNA-Seq provides comprehensive information on mRNA abundance, alternative splicing, nucleotide variation, and structure alteration. Sample-specific protein databases derived from RNA-Seq data can better approximate the real protein pools in cell and tissue samples and thus improve protein identification. Meanwhile, proteomics data provide essential confirmation of the validity and functional relevance of novel findings from RNA-Seq data. At the quantitative level, mRNA and protein levels are only modestly correlated, suggesting strong involvement of posttranscriptional regulation in controlling gene expression. Here, we review recent studies at the interface of RNA-Seq and proteomics data. We discuss goals, accomplishments, and challenges in RNA-Seq-based proteogenomics. We also examine the current status and future potential of parallel transcriptome and proteome quantification in revealing posttranscriptional regulatory mechanisms.
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Affiliation(s)
- Xiaojing Wang
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN
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