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Desponds E, Croci D, Wosika V, Hadadi N, Fonseca Costa SS, Ciarloni L, Ongaro M, Zdimerova H, Leblond MM, Hosseinian Ehrensberger S, Romero P, Verdeil G. Immuno-Transcriptomic Profiling of Blood and Tumor Tissue Identifies Gene Signatures Associated with Immunotherapy Response in Metastatic Bladder Cancer. Cancers (Basel) 2024; 16:433. [PMID: 38275874 PMCID: PMC10814931 DOI: 10.3390/cancers16020433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 01/11/2024] [Accepted: 01/15/2024] [Indexed: 01/27/2024] Open
Abstract
Blood-based biomarkers represent ideal candidates for the development of non-invasive immuno-oncology-based assays. However, to date, no blood biomarker has been validated to predict clinical responses to immunotherapy. In this study, we used next-generation sequencing (RNAseq) on bulk RNA extracted from whole blood and tumor samples in a pre-clinical MIBC mouse model. We aimed to identify biomarkers associated with immunotherapy response and assess the potential application of simple non-invasive blood biomarkers as a therapeutic decision-making assay compared to tissue-based biomarkers. We established that circulating immune cells and the tumor microenvironment (TME) display highly organ-specific transcriptional responses to ICIs. Interestingly, in both, a common lymphocytic activation signature can be identified associated with the efficient response to immunotherapy, including a blood-specific CD8+ T cell activation/proliferation signature which predicts the immunotherapy response.
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Affiliation(s)
- Emma Desponds
- Department of Oncology UNIL CHUV, University of Lausanne, 1015 Lausanne, Switzerland; (E.D.); (M.O.); (H.Z.); (M.M.L.)
- Ludwig Institute for Cancer Research, University of Lausanne, 1015 Lausanne, Switzerland
| | - Davide Croci
- Novigenix SA, 1066 Epalinges, Switzerland; (D.C.); (N.H.); (S.S.F.C.); (L.C.); (S.H.E.); (P.R.)
| | - Victoria Wosika
- Novigenix SA, 1066 Epalinges, Switzerland; (D.C.); (N.H.); (S.S.F.C.); (L.C.); (S.H.E.); (P.R.)
| | - Noushin Hadadi
- Novigenix SA, 1066 Epalinges, Switzerland; (D.C.); (N.H.); (S.S.F.C.); (L.C.); (S.H.E.); (P.R.)
| | - Sara S. Fonseca Costa
- Novigenix SA, 1066 Epalinges, Switzerland; (D.C.); (N.H.); (S.S.F.C.); (L.C.); (S.H.E.); (P.R.)
| | - Laura Ciarloni
- Novigenix SA, 1066 Epalinges, Switzerland; (D.C.); (N.H.); (S.S.F.C.); (L.C.); (S.H.E.); (P.R.)
| | - Marco Ongaro
- Department of Oncology UNIL CHUV, University of Lausanne, 1015 Lausanne, Switzerland; (E.D.); (M.O.); (H.Z.); (M.M.L.)
- Ludwig Institute for Cancer Research, University of Lausanne, 1015 Lausanne, Switzerland
| | - Hana Zdimerova
- Department of Oncology UNIL CHUV, University of Lausanne, 1015 Lausanne, Switzerland; (E.D.); (M.O.); (H.Z.); (M.M.L.)
- Ludwig Institute for Cancer Research, University of Lausanne, 1015 Lausanne, Switzerland
| | - Marine M. Leblond
- Department of Oncology UNIL CHUV, University of Lausanne, 1015 Lausanne, Switzerland; (E.D.); (M.O.); (H.Z.); (M.M.L.)
- Ludwig Institute for Cancer Research, University of Lausanne, 1015 Lausanne, Switzerland
| | | | - Pedro Romero
- Novigenix SA, 1066 Epalinges, Switzerland; (D.C.); (N.H.); (S.S.F.C.); (L.C.); (S.H.E.); (P.R.)
| | - Grégory Verdeil
- Department of Oncology UNIL CHUV, University of Lausanne, 1015 Lausanne, Switzerland; (E.D.); (M.O.); (H.Z.); (M.M.L.)
- Ludwig Institute for Cancer Research, University of Lausanne, 1015 Lausanne, Switzerland
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Ehrensberger SH, Wosika V, Hadadi N, Fonseca Costa S, Durandau E, Monnier-Benoit S, Ciarloni L, Scherer SJ, Tejpar S. Next-generation whole blood transcriptome-based assay for advanced adenoma detection. J Clin Oncol 2023. [DOI: 10.1200/jco.2023.41.4_suppl.77] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
77 Background: Colorectal Cancer (CRC) is the second leading cause of cancer mortality worldwide although highly curable if detected early. An accurate liquid biopsy test for early cancer and precancerous lesion, detection is key to promote prevention and reduce mortality. We previously developed a liquid biopsy test based on immune cells response to the tumor, commercialised under the name of Colox, with best-in-class clinical performances for AA detection (52% sensitivity and 92% specificity) (Ciarloni L et al, Clin Cancer Res, 2016). An improved second generation of the test, leveraging transcriptome profiling and advanced machine learning tools, is under development and first results are presented. Methods: Prospective peripheral whole-blood (PAXgene) samples from subjects diagnosed with CRC, advanced adenoma (AA), non-advanced adenoma, other types of cancer as well as controls without colorectal neoplasia (CON) were divided into discovery and validation sets. Transcriptome profiles were generated by RNA-seq and gene expression signatures identified leveraging Novigenix’s proprietary LITOseek platform, which integrates several advanced Machine Learning (ML) methods into a ranking systems. Biological functional analysis was performed by over-representation (ORA), gene set enrichment (GSEA) and gene network analyses (STRINGdb). Results: Significant changes in the whole blood transcriptome profile of AA compared to CON were identified. Functional analysis highlighted upregulation of fatty acid derivative biosynthesis, interferon signaling, tryptophan catabolism to kynurenine, and downregulation of DNA repair in AA blood samples compared to CON. A novel gene classifier was generated, showing for AA detection 71% sensitivity, 94% specificity and an AUC of 74% by cross-validation on the discovery set. Validation of the gene classifier in an independent set is currently ongoing and will be presented at the congress. Conclusions: Capturing immune-related information using whole blood trascriptome profiling and applying cutting-edge machine learning technologies demonstrated to be valuable for identifying gene signatures for advanced adenoma detection. This differentiated solution has demonstrated best-in-class potential to significantly improve patient outcomes by detecting precancerous lesions with a simple non-invasive blood test.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Sabine Tejpar
- UZ Gasthuisberg - Katholieke University Leuven, Leuven, Belgium
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Hassaïne R, Durandau E, Ciarloni L, Hadadi N, Hosseinian Ehrensberger S, van Wilpe S, de Vet B, Mehra N. 855P Whole blood transcriptomic profiling to predict response to immunotherapy in metastatic melanoma. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
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Hadadi N, Spiljar M, Steinbach K, Çolakoğlu M, Chevalier C, Salinas G, Merkler D, Trajkovski M. Comparative multi-tissue profiling reveals extensive tissue-specificity in transcriptome reprogramming during thermal adaptation. eLife 2022; 11:78556. [PMID: 35578890 PMCID: PMC9113744 DOI: 10.7554/elife.78556] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 04/24/2022] [Indexed: 12/02/2022] Open
Abstract
Thermal adaptation is an extensively used intervention for enhancing or suppressing thermogenic and mitochondrial activity in adipose tissues. As such, it has been suggested as a potential lifestyle intervention for body weight maintenance. While the metabolic consequences of thermal acclimation are not limited to the adipose tissues, the impact on the rest of the tissues in context of their gene expression profile remains unclear. Here, we provide a systematic characterization of the effects in a comparative multi-tissue RNA sequencing approach following exposure of mice to 10 °C, 22 °C, or 34 °C in a panel of organs consisting of spleen, bone marrow, spinal cord, brain, hypothalamus, ileum, liver, quadriceps, subcutaneous-, visceral- and brown adipose tissues. We highlight that transcriptional responses to temperature alterations exhibit a high degree of tissue-specificity both at the gene level and at GO enrichment gene sets, and show that the tissue-specificity is not directed by the distinct basic gene expression pattern exhibited by the various organs. Our study places the adaptation of individual tissues to different temperatures in a whole-organism framework and provides integrative transcriptional analysis necessary for understanding the temperature-mediated biological programming. Humans, mice and most other mammals are constantly exposed to fluctuations in the temperature of their environment. These fluctuations cause striking metabolic effects in the body, for example, exposure to cold promotes burning of calories to generate heat, thereby reducing how much fat accumulates in the body. On the other hand, warmer temperatures strengthen the bones and protect against a bone disease known as osteoporosis. As such, it has been suggested that exposure to alternating warm or cold temperatures could be a potential lifestyle intervention that conveys various benefits to our health. Our body stores fat in tissues known as adipose tissues, which are found all over the body including under the skin and around our major organs and muscles. Exposure to cold triggers changes in the activities of some genes in the adipose tissues to burn more calories. But it remains unclear how temperature affects the activities of other organs with respect to their expression of genes in the whole-body context. Hadadi, Spiljar et al. used an RNA sequencing approach to study the activities of genes in various tissues of mice exposed to cold (10°C), room temperature (22°C), or mild warm (34°C). The experiments revealed numerous genes whose levels were different in the various organs and temperatures tested. Overall, adipose tissues experienced the biggest changes in gene levels between different temperatures, followed by tissues involved in immune responses, and the brain and spinal cord tissues. Each organ changed gene expression levels in its own way. , and this was not due to the different intimate gene expression profile between the various organs. These findings improve our understanding of how changes in temperature affect mammals by putting the responses of individual tissues into the context of the whole body. Hadadi, Spiljar et al. also generated a web-based, free-to-use application to allow others to view and further analyze the data collected in this work for gene levels in the various organs of interest.
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Affiliation(s)
- Noushin Hadadi
- Department of Cell Physiology and Metabolism, Faculty of Medicine, Centre Medical Universitaire (CMU), University of Geneva, Geneva, Switzerland.,Diabetes center, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Martina Spiljar
- Department of Cell Physiology and Metabolism, Faculty of Medicine, Centre Medical Universitaire (CMU), University of Geneva, Geneva, Switzerland.,Diabetes center, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Karin Steinbach
- Department of Pathology and Immunology, Faculty of Medicine, Centre Medical Universitaire (CMU), University of Geneva, Geneva, Switzerland
| | - Melis Çolakoğlu
- Department of Cell Physiology and Metabolism, Faculty of Medicine, Centre Medical Universitaire (CMU), University of Geneva, Geneva, Switzerland.,Diabetes center, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Claire Chevalier
- Department of Cell Physiology and Metabolism, Faculty of Medicine, Centre Medical Universitaire (CMU), University of Geneva, Geneva, Switzerland.,Diabetes center, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Gabriela Salinas
- NGS- Integrative Genomics Core Unit (NIG), Institute of Human Genetics, University Medical Center, Göttingen, Germany
| | - Doron Merkler
- Department of Pathology and Immunology, Faculty of Medicine, Centre Medical Universitaire (CMU), University of Geneva, Geneva, Switzerland
| | - Mirko Trajkovski
- Department of Cell Physiology and Metabolism, Faculty of Medicine, Centre Medical Universitaire (CMU), University of Geneva, Geneva, Switzerland.,Diabetes center, Faculty of Medicine, University of Geneva, Geneva, Switzerland
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Spiljar M, Steinbach K, Rigo D, Suárez-Zamorano N, Wagner I, Hadadi N, Vincenti I, Page N, Klimek B, Rochat MA, Kreutzfeldt M, Chevalier C, Stojanović O, Bejuy O, Colin D, Mack M, Cansever D, Greter M, Merkler D, Trajkovski M. Cold exposure protects from neuroinflammation through immunologic reprogramming. Cell Metab 2021; 33:2231-2246.e8. [PMID: 34687652 PMCID: PMC8570411 DOI: 10.1016/j.cmet.2021.10.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 07/24/2021] [Accepted: 10/01/2021] [Indexed: 02/07/2023]
Abstract
Autoimmunity is energetically costly, but the impact of a metabolically active state on immunity and immune-mediated diseases is unclear. Ly6Chi monocytes are key effectors in CNS autoimmunity with an elusive role in priming naive autoreactive T cells. Here, we provide unbiased analysis of the immune changes in various compartments during cold exposure and show that this energetically costly stimulus markedly ameliorates active experimental autoimmune encephalomyelitis (EAE). Cold exposure decreases MHCII on monocytes at steady state and in various inflammatory mouse models and suppresses T cell priming and pathogenicity through the modulation of monocytes. Genetic or antibody-mediated monocyte depletion or adoptive transfer of Th1- or Th17-polarized cells for EAE abolishes the cold-induced effects on T cells or EAE, respectively. These findings provide a mechanistic link between environmental temperature and neuroinflammation and suggest competition between cold-induced metabolic adaptations and autoimmunity as energetic trade-off beneficial for the immune-mediated diseases.
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Affiliation(s)
- Martina Spiljar
- Department of Cell Physiology and Metabolism, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Karin Steinbach
- Department of Pathology and Immunology, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland
| | - Dorothée Rigo
- Department of Cell Physiology and Metabolism, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Nicolas Suárez-Zamorano
- Department of Cell Physiology and Metabolism, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Ingrid Wagner
- Department of Pathology and Immunology, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland
| | - Noushin Hadadi
- Department of Cell Physiology and Metabolism, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Ilena Vincenti
- Department of Pathology and Immunology, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland
| | - Nicolas Page
- Department of Pathology and Immunology, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland
| | - Bogna Klimek
- Department of Pathology and Immunology, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland
| | - Mary-Aude Rochat
- Department of Cell Physiology and Metabolism, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Mario Kreutzfeldt
- Department of Pathology and Immunology, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland
| | - Claire Chevalier
- Department of Cell Physiology and Metabolism, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Ozren Stojanović
- Department of Cell Physiology and Metabolism, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Olivia Bejuy
- CIBM Centre for BioMedical Imaging, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
| | - Didier Colin
- Small Animal Preclinical Imaging Platform, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
| | - Matthias Mack
- Department of Internal Medicine II - Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Dilay Cansever
- Institute of Experimental Immunology, University of Zurich, Zurich, Switzerland
| | - Melanie Greter
- Institute of Experimental Immunology, University of Zurich, Zurich, Switzerland
| | - Doron Merkler
- Department of Pathology and Immunology, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland; Division of Clinical Pathology, Geneva University Hospitals, Geneva, Switzerland.
| | - Mirko Trajkovski
- Department of Cell Physiology and Metabolism, Faculty of Medicine, Centre Médical Universitaire (CMU), University of Geneva, Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
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Abstract
The deficiency of micronutrients, including vitamins and minerals, is estimated to affect two billion people worldwide and can have devastating immediate and long-term consequences. Major causes range from inadequate micronutrient consumption mostly owing to a lack of dietary diversity, to poor nutrient absorption in the gastrointestinal tract as a result of clinical or pathological conditions. Recent studies in model organisms and humans demonstrated that intestinal microbiota plays an important role in the de novo biosynthesis and bioavailability of several micronutrients and might be a major determinant of human micronutrient status. Here, we address the importance of the gut microbiome for maintaining the balance of host vitamins and minerals and explore its potential therapeutic benefits and implications on human health.
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Affiliation(s)
- Noushin Hadadi
- Department of Cell Physiology and Metabolism, Centre Médical Universitaire (CMU), Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
- Diabetes Centre, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
| | - Vincent Berweiler
- Department of Cell Physiology and Metabolism, Centre Médical Universitaire (CMU), Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
- Diabetes Centre, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
| | - Haiping Wang
- Department of Cell Physiology and Metabolism, Centre Médical Universitaire (CMU), Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
- Diabetes Centre, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
| | - Mirko Trajkovski
- Department of Cell Physiology and Metabolism, Centre Médical Universitaire (CMU), Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
- Diabetes Centre, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
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MohammadiPeyhani H, Chiappino-Pepe A, Haddadi K, Hafner J, Hadadi N, Hatzimanikatis V. NICEdrug.ch, a workflow for rational drug design and systems-level analysis of drug metabolism. eLife 2021; 10:e65543. [PMID: 34340747 PMCID: PMC8331181 DOI: 10.7554/elife.65543] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 07/07/2021] [Indexed: 12/30/2022] Open
Abstract
The discovery of a drug requires over a decade of intensive research and financial investments - and still has a high risk of failure. To reduce this burden, we developed the NICEdrug.ch resource, which incorporates 250,000 bioactive molecules, and studied their enzymatic metabolic targets, fate, and toxicity. NICEdrug.ch includes a unique fingerprint that identifies reactive similarities between drug-drug and drug-metabolite pairs. We validated the application, scope, and performance of NICEdrug.ch over similar methods in the field on golden standard datasets describing drugs and metabolites sharing reactivity, drug toxicities, and drug targets. We use NICEdrug.ch to evaluate inhibition and toxicity by the anticancer drug 5-fluorouracil, and suggest avenues to alleviate its side effects. We propose shikimate 3-phosphate for targeting liver-stage malaria with minimal impact on the human host cell. Finally, NICEdrug.ch suggests over 1300 candidate drugs and food molecules to target COVID-19 and explains their inhibitory mechanism for further experimental screening. The NICEdrug.ch database is accessible online to systematically identify the reactivity of small molecules and druggable enzymes with practical applications in lead discovery and drug repurposing.
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Affiliation(s)
- Homa MohammadiPeyhani
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne, EPFLLausanneSwitzerland
| | - Anush Chiappino-Pepe
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne, EPFLLausanneSwitzerland
| | - Kiandokht Haddadi
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne, EPFLLausanneSwitzerland
| | - Jasmin Hafner
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne, EPFLLausanneSwitzerland
| | - Noushin Hadadi
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne, EPFLLausanneSwitzerland
| | - Vassily Hatzimanikatis
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne, EPFLLausanneSwitzerland
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Morales M, Sentchilo V, Hadadi N, van der Meer JR. Genome-wide gene expression changes of Pseudomonas veronii 1YdBTEX2 during bioaugmentation in polluted soils. Environ Microbiome 2021; 16:8. [PMID: 33926576 PMCID: PMC8082905 DOI: 10.1186/s40793-021-00378-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Accepted: 04/10/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Bioaugmentation aims to use the capacities of specific bacterial strains inoculated into sites to enhance pollutant biodegradation. Bioaugmentation results have been mixed, which has been attributed to poor inoculant growth and survival in the field, and, consequently, moderate catalytic performance. However, our understanding of biodegradation activity mostly comes from experiments conducted under laboratory conditions, and the processes occurring during adaptation and invasion of inoculants into complex environmental microbiomes remain poorly known. The main aim of this work was thus to study the specific and different cellular reactions of an inoculant for bioaugmentation during adaptation, growth and survival in natural clean and contaminated non-sterile soils, in order to better understand factors limiting bioaugmentation. RESULTS As inoculant we focused on the monoaromatic compound-degrading bacterium Pseudomonas veronii 1YdBTEX2. The strain proliferated in all but one soil types in presence and in absence of exogenously added toluene. RNAseq and differential genome-wide gene expression analysis illustrated both a range of common soil responses such as increased nutrient scavenging and recycling, expression of defense mechanisms, as well as environment-specific reactions, notably osmoprotection and metal homeostasis. The core metabolism of P. veronii remained remarkably constant during exponential growth irrespective of the environment, with slight changes in cofactor regeneration pathways, possibly needed for balancing defense reactions. CONCLUSIONS P. veronii displayed a versatile global program, enabling it to adapt to a variety of soil environments in the presence and even in absence of its target pollutant toluene. Our results thus challenge the widely perceived dogma of poor survival and growth of exogenous inoculants in complex microbial ecosystems such as soil and provide a further basis to developing successful bioaugmentation strategies.
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Affiliation(s)
- Marian Morales
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Vladimir Sentchilo
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Noushin Hadadi
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Jan Roelof van der Meer
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland.
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Dubey M, Hadadi N, Pelet S, Carraro N, Johnson DR, van der Meer JR. Environmental connectivity controls diversity in soil microbial communities. Commun Biol 2021; 4:492. [PMID: 33888858 PMCID: PMC8062517 DOI: 10.1038/s42003-021-02023-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 03/24/2021] [Indexed: 01/03/2023] Open
Abstract
Interspecific interactions are thought to govern the stability and functioning of microbial communities, but the influence of the spatial environment and its structural connectivity on the potential of such interactions to unfold remain largely unknown. Here we studied the effects on community growth and microbial diversity as a function of environmental connectivity, where we define environmental connectivity as the degree of habitat fragmentation preventing microbial cells from living together. We quantitatively compared growth of a naturally-derived high microbial diversity community from soil in a completely mixed liquid suspension (high connectivity) to growth in a massively fragmented and poorly connected environment (low connectivity). The low connectivity environment consisted of homogenously-sized miniature agarose beads containing random single or paired founder cells. We found that overall community growth was the same in both environments, but the low connectivity environment dramatically reduced global community-level diversity compared to the high connectivity environment. Experimental observations were supported by community growth modeling. The model predicts a loss of diversity in the low connectivity environment as a result of negative interspecific interactions becoming more dominant at small founder species numbers. Counterintuitively for the low connectivity environment, growth of isolated single genotypes was less productive than that of random founder genotype cell pairs, suggesting that the community as a whole profited from emerging positive interspecific interactions. Our work demonstrates the importance of environmental connectivity for growth of natural soil microbial communities, which aids future efforts to intervene in or restore community composition to achieve engineering and biotechnological objectives. Manupriyam Dubey et al. use experimental systems with naturally derived soil microbiomes in liquid suspensions and encapsulated beads to compare community dynamics in well-connected and poorly connected environments. While their results show that microbial growth does not vary between conditions, they report that low connectivity led to reduced microbial diversity and suggest that these reductions in microbial diversity may be due to increased negative interspecific interactions.
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Affiliation(s)
- Manupriyam Dubey
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Noushin Hadadi
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Serge Pelet
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Nicolas Carraro
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - David R Johnson
- Department of Environmental Microbiology, Swiss Federal Institute of Aquatic Science and Technology, Eawag, Dübendorf, Switzerland
| | - Jan R van der Meer
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland.
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10
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Chevalier C, Kieser S, Çolakoğlu M, Hadadi N, Brun J, Rigo D, Suárez-Zamorano N, Spiljar M, Fabbiano S, Busse B, Ivanišević J, Macpherson A, Bonnet N, Trajkovski M. Warmth Prevents Bone Loss Through the Gut Microbiota. Cell Metab 2020; 32:575-590.e7. [PMID: 32916104 PMCID: PMC7116155 DOI: 10.1016/j.cmet.2020.08.012] [Citation(s) in RCA: 75] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 06/25/2020] [Accepted: 08/18/2020] [Indexed: 12/15/2022]
Abstract
Osteoporosis is the most prevalent metabolic bone disease, characterized by low bone mass and microarchitectural deterioration. Here, we show that warmth exposure (34°C) protects against ovariectomy-induced bone loss by increasing trabecular bone volume, connectivity density, and thickness, leading to improved biomechanical bone strength in adult female, as well as in young male mice. Transplantation of the warm-adapted microbiota phenocopies the warmth-induced bone effects. Both warmth and warm microbiota transplantation revert the ovariectomy-induced transcriptomics changes of the tibia and increase periosteal bone formation. Combinatorial metagenomics/metabolomics analysis shows that warmth enhances bacterial polyamine biosynthesis, resulting in higher total polyamine levels in vivo. Spermine and spermidine supplementation increases bone strength, while inhibiting polyamine biosynthesis in vivo limits the beneficial warmth effects on the bone. Our data suggest warmth exposure as a potential treatment option for osteoporosis while providing a mechanistic framework for its benefits in bone disease.
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Affiliation(s)
- Claire Chevalier
- Department of Cell Physiology and Metabolism, Centre Médical Universitaire (CMU), Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
| | - Silas Kieser
- Department of Cell Physiology and Metabolism, Centre Médical Universitaire (CMU), Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
| | - Melis Çolakoğlu
- Department of Cell Physiology and Metabolism, Centre Médical Universitaire (CMU), Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
| | - Noushin Hadadi
- Department of Cell Physiology and Metabolism, Centre Médical Universitaire (CMU), Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
| | - Julia Brun
- Division of Bone Diseases, Geneva University Hospitals, 1211 Geneva, Switzerland
| | - Dorothée Rigo
- Department of Cell Physiology and Metabolism, Centre Médical Universitaire (CMU), Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
| | - Nicolas Suárez-Zamorano
- Department of Cell Physiology and Metabolism, Centre Médical Universitaire (CMU), Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
| | - Martina Spiljar
- Department of Cell Physiology and Metabolism, Centre Médical Universitaire (CMU), Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
| | - Salvatore Fabbiano
- Department of Cell Physiology and Metabolism, Centre Médical Universitaire (CMU), Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland
| | - Björn Busse
- Institute for Osteology and Biomechanics, University Clinics Hamburg, 22529 Hamburg, Germany
| | - Julijana Ivanišević
- Metabolomics Unit, Faculty of Biology and Medicine, University of Lausanne, 1005 Lausanne, Switzerland
| | - Andrew Macpherson
- Department for Biomedical Research, University of Bern, University Clinics for Visceral Surgery and Medicine, Inselspital, Bern University Hospitals, 3008 Bern, Switzerland
| | - Nicolas Bonnet
- Diabetes Center, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland; Division of Bone Diseases, Geneva University Hospitals, 1211 Geneva, Switzerland
| | - Mirko Trajkovski
- Department of Cell Physiology and Metabolism, Centre Médical Universitaire (CMU), Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland; Diabetes Center, Faculty of Medicine, University of Geneva, 1211 Geneva, Switzerland.
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Özel Duygan BD, Hadadi N, Babu AF, Seyfried M, van der Meer JR. Rapid detection of microbiota cell type diversity using machine-learned classification of flow cytometry data. Commun Biol 2020; 3:379. [PMID: 32669688 PMCID: PMC7363847 DOI: 10.1038/s42003-020-1106-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Accepted: 06/24/2020] [Indexed: 11/09/2022] Open
Abstract
The study of complex microbial communities typically entails high-throughput sequencing and downstream bioinformatics analyses. Here we expand and accelerate microbiota analysis by enabling cell type diversity quantification from multidimensional flow cytometry data using a supervised machine learning algorithm of standard cell type recognition (CellCognize). As a proof-of-concept, we trained neural networks with 32 microbial cell and bead standards. The resulting classifiers were extensively validated in silico on known microbiota, showing on average 80% prediction accuracy. Furthermore, the classifiers could detect shifts in microbial communities of unknown composition upon chemical amendment, comparable to results from 16S-rRNA-amplicon analysis. CellCognize was also able to quantify population growth and estimate total community biomass productivity, providing estimates similar to those from 14C-substrate incorporation. CellCognize complements current sequencing-based methods by enabling rapid routine cell diversity analysis. The pipeline is suitable to optimize cell recognition for recurring microbiota types, such as in human health or engineered systems. Duygan et al. develop a supervised machine learning algorithm, CellCognize, to quantify cell type diversity from multidimensional flow cytometry data. Their model achieves 80% prediction accuracy, detects shifts in microbial communities of unknown composition and quantifies population growth and biomass productivity. Their work will be useful to study microbiota in human health or engineered systems.
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Affiliation(s)
- Birge D Özel Duygan
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland.
| | - Noushin Hadadi
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland.,Department of Cell Physiology and Metabolism, Faculty of Medicine, University of Geneva, CH-1211, Geneva, Switzerland
| | - Ambrin Farizah Babu
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
| | | | - Jan R van der Meer
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland.
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12
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Brun T, Jiménez-Sánchez C, Madsen JGS, Hadadi N, Duhamel D, Bartley C, Oberhauser L, Trajkovski M, Mandrup S, Maechler P. AMPK Profiling in Rodent and Human Pancreatic Beta-Cells under Nutrient-Rich Metabolic Stress. Int J Mol Sci 2020; 21:ijms21113982. [PMID: 32492936 PMCID: PMC7312098 DOI: 10.3390/ijms21113982] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 05/28/2020] [Accepted: 05/29/2020] [Indexed: 12/13/2022] Open
Abstract
Chronic exposure of pancreatic β-cells to elevated nutrient levels impairs their function and potentially induces apoptosis. Like in other cell types, AMPK is activated in β-cells under conditions of nutrient deprivation, while little is known on AMPK responses to metabolic stresses. Here, we first reviewed recent studies on the role of AMPK activation in β-cells. Then, we investigated the expression profile of AMPK pathways in β-cells following metabolic stresses. INS-1E β-cells and human islets were exposed for 3 days to glucose (5.5–25 mM), palmitate or oleate (0.4 mM), and fructose (5.5 mM). Following these treatments, we analyzed transcript levels of INS-1E β-cells by qRT-PCR and of human islets by RNA-Seq; with a special focus on AMPK-associated genes, such as the AMPK catalytic subunits α1 (Prkaa1) and α2 (Prkaa2). AMPKα and pAMPKα were also evaluated at the protein level by immunoblotting. Chronic exposure to the different metabolic stresses, known to alter glucose-stimulated insulin secretion, did not change AMPK expression, either in insulinoma cells or in human islets. Expression profile of the six AMPK subunits was marginally modified by the different diabetogenic conditions. However, the expression of some upstream kinases and downstream AMPK targets, including K-ATP channel subunits, exhibited stress-specific signatures. Interestingly, at the protein level, chronic fructose treatment favored fasting-like phenotype in human islets, as witnessed by AMPK activation. Collectively, previously published and present data indicate that, in the β-cell, AMPK activation might be implicated in the pre-diabetic state, potentially as a protective mechanism.
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Affiliation(s)
- Thierry Brun
- Department of Cell Physiology and Metabolism & Faculty Diabetes Center, University of Geneva Medical Center, 1206 Geneva, Switzerland; (T.B.); (C.J.-S.); (N.H.); (D.D.); (C.B.); (L.O.); (M.T.)
| | - Cecilia Jiménez-Sánchez
- Department of Cell Physiology and Metabolism & Faculty Diabetes Center, University of Geneva Medical Center, 1206 Geneva, Switzerland; (T.B.); (C.J.-S.); (N.H.); (D.D.); (C.B.); (L.O.); (M.T.)
| | - Jesper Grud Skat Madsen
- Functional Genomics and Metabolism Research Unit, Department of Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense, Denmark; (J.G.S.M.); (S.M.)
| | - Noushin Hadadi
- Department of Cell Physiology and Metabolism & Faculty Diabetes Center, University of Geneva Medical Center, 1206 Geneva, Switzerland; (T.B.); (C.J.-S.); (N.H.); (D.D.); (C.B.); (L.O.); (M.T.)
| | - Dominique Duhamel
- Department of Cell Physiology and Metabolism & Faculty Diabetes Center, University of Geneva Medical Center, 1206 Geneva, Switzerland; (T.B.); (C.J.-S.); (N.H.); (D.D.); (C.B.); (L.O.); (M.T.)
| | - Clarissa Bartley
- Department of Cell Physiology and Metabolism & Faculty Diabetes Center, University of Geneva Medical Center, 1206 Geneva, Switzerland; (T.B.); (C.J.-S.); (N.H.); (D.D.); (C.B.); (L.O.); (M.T.)
| | - Lucie Oberhauser
- Department of Cell Physiology and Metabolism & Faculty Diabetes Center, University of Geneva Medical Center, 1206 Geneva, Switzerland; (T.B.); (C.J.-S.); (N.H.); (D.D.); (C.B.); (L.O.); (M.T.)
| | - Mirko Trajkovski
- Department of Cell Physiology and Metabolism & Faculty Diabetes Center, University of Geneva Medical Center, 1206 Geneva, Switzerland; (T.B.); (C.J.-S.); (N.H.); (D.D.); (C.B.); (L.O.); (M.T.)
| | - Susanne Mandrup
- Functional Genomics and Metabolism Research Unit, Department of Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense, Denmark; (J.G.S.M.); (S.M.)
| | - Pierre Maechler
- Department of Cell Physiology and Metabolism & Faculty Diabetes Center, University of Geneva Medical Center, 1206 Geneva, Switzerland; (T.B.); (C.J.-S.); (N.H.); (D.D.); (C.B.); (L.O.); (M.T.)
- Correspondence:
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Hadadi N, Pandey V, Chiappino-Pepe A, Morales M, Gallart-Ayala H, Mehl F, Ivanisevic J, Sentchilo V, van der Meer JR. Author Correction: Mechanistic insights into bacterial metabolic reprogramming from omics-integrated genome-scale models. NPJ Syst Biol Appl 2020; 6:4. [PMID: 32001701 PMCID: PMC6992694 DOI: 10.1038/s41540-020-0123-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Affiliation(s)
- Noushin Hadadi
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland.
| | - Vikash Pandey
- Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
| | - Anush Chiappino-Pepe
- Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
| | - Marian Morales
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
| | | | - Florence Mehl
- Metabolomics Platform, University of Lausanne, 1015, Lausanne, Switzerland
| | | | - Vladimir Sentchilo
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Jan R van der Meer
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
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14
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Hadadi N, Pandey V, Chiappino-Pepe A, Morales M, Gallart-Ayala H, Mehl F, Ivanisevic J, Sentchilo V, Meer JRVD. Mechanistic insights into bacterial metabolic reprogramming from omics-integrated genome-scale models. NPJ Syst Biol Appl 2020; 6:1. [PMID: 32001719 PMCID: PMC6946695 DOI: 10.1038/s41540-019-0121-4] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 11/28/2019] [Indexed: 11/18/2022] Open
Abstract
Understanding the adaptive responses of individual bacterial strains is crucial for microbiome engineering approaches that introduce new functionalities into complex microbiomes, such as xenobiotic compound metabolism for soil bioremediation. Adaptation requires metabolic reprogramming of the cell, which can be captured by multi-omics, but this data remains formidably challenging to interpret and predict. Here we present a new approach that combines genome-scale metabolic modeling with transcriptomics and exometabolomics, both of which are common tools for studying dynamic population behavior. As a realistic demonstration, we developed a genome-scale model of Pseudomonas veronii 1YdBTEX2, a candidate bioaugmentation agent for accelerated metabolism of mono-aromatic compounds in soil microbiomes, while simultaneously collecting experimental data of P. veronii metabolism during growth phase transitions. Predictions of the P. veronii growth rates and specific metabolic processes from the integrated model closely matched experimental observations. We conclude that integrative and network-based analysis can help build predictive models that accurately capture bacterial adaptation responses. Further development and testing of such models may considerably improve the successful establishment of bacterial inoculants in more complex systems.
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Affiliation(s)
- Noushin Hadadi
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland.
| | - Vikash Pandey
- Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
| | - Anush Chiappino-Pepe
- Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
| | - Marian Morales
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
| | | | - Florence Mehl
- Metabolomics Platform, University of Lausanne, 1015, Lausanne, Switzerland
| | | | - Vladimir Sentchilo
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Jan R van der Meer
- Department of Fundamental Microbiology, University of Lausanne, 1015, Lausanne, Switzerland
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Ellegaard KM, Brochet S, Bonilla‐Rosso G, Emery O, Glover N, Hadadi N, Jaron KS, Meer JR, Robinson‐Rechavi M, Sentchilo V, Tagini F, Engel P. Genomic changes underlying host specialization in the bee gut symbiont
Lactobacillus
Firm5. Mol Ecol 2019; 28:2224-2237. [DOI: 10.1111/mec.15075] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Revised: 02/21/2019] [Accepted: 03/04/2019] [Indexed: 01/08/2023]
Affiliation(s)
- Kirsten M. Ellegaard
- Department of Fundamental Microbiology University of Lausanne Lausanne Switzerland
| | - Silvia Brochet
- Department of Fundamental Microbiology University of Lausanne Lausanne Switzerland
| | - German Bonilla‐Rosso
- Department of Fundamental Microbiology University of Lausanne Lausanne Switzerland
| | - Olivier Emery
- Department of Fundamental Microbiology University of Lausanne Lausanne Switzerland
| | - Natasha Glover
- Department of Ecology and Evolution University of Lausanne Lausanne Switzerland
| | - Noushin Hadadi
- Department of Fundamental Microbiology University of Lausanne Lausanne Switzerland
| | - Kamil S. Jaron
- Department of Ecology and Evolution University of Lausanne Lausanne Switzerland
- Swiss Institute of Bioinformatics Lausanne Switzerland
| | - Jan R. Meer
- Department of Fundamental Microbiology University of Lausanne Lausanne Switzerland
| | - Marc Robinson‐Rechavi
- Department of Ecology and Evolution University of Lausanne Lausanne Switzerland
- Swiss Institute of Bioinformatics Lausanne Switzerland
| | - Vladimir Sentchilo
- Department of Fundamental Microbiology University of Lausanne Lausanne Switzerland
| | - Florian Tagini
- Institute of Microbiology, Department of Laboratory Medicine University of Lausanne & Lausanne University Hospital Lausanne Switzerland
| | - Philipp Engel
- Department of Fundamental Microbiology University of Lausanne Lausanne Switzerland
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Pandey V, Hadadi N, Hatzimanikatis V. Enhanced flux prediction by integrating relative expression and relative metabolite abundance into thermodynamically consistent metabolic models. PLoS Comput Biol 2019; 15:e1007036. [PMID: 31083653 PMCID: PMC6532942 DOI: 10.1371/journal.pcbi.1007036] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 05/23/2019] [Accepted: 04/19/2019] [Indexed: 11/19/2022] Open
Abstract
The ever-increasing availability of transcriptomic and metabolomic data can be used to deeply analyze and make ever-expanding predictions about biological processes, as changes in the reaction fluxes through genome-wide pathways can now be tracked. Currently, constraint-based metabolic modeling approaches, such as flux balance analysis (FBA), can quantify metabolic fluxes and make steady-state flux predictions on a genome-wide scale using optimization principles. However, relating the differential gene expression or differential metabolite abundances in different physiological states to the differential flux profiles remains a challenge. Here we present a novel method, named REMI (Relative Expression and Metabolomic Integrations), that employs genome-scale metabolic models (GEMs) to translate differential gene expression and metabolite abundance data obtained through genetic or environmental perturbations into differential fluxes to analyze the altered physiology for any given pair of conditions. REMI allows for gene-expression, metabolite abundance, and thermodynamic data to be integrated into a single framework, then uses optimization principles to maximize the consistency between the differential gene-expression levels and metabolite abundance data and the estimated differential fluxes and thermodynamic constraints. We applied REMI to integrate into the Escherichia coli GEM publicly available sets of expression and metabolomic data obtained from two independent studies and under wide-ranging conditions. The differential flux distributions obtained from REMI corresponding to the various perturbations better agreed with the measured fluxomic data, and thus better reflected the different physiological states, than a traditional model. Compared to the similar alternative method that provides one solution from the solution space, REMI was able to enumerate several alternative flux profiles using a mixed-integer linear programming approach. Using this important advantage, we performed a high-frequency analysis of common genes and their associated reactions in the obtained alternative solutions and identified the most commonly regulated genes across any two given conditions. We illustrate that this new implementation provides more robust and biologically relevant results for a better understanding of the system physiology.
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Affiliation(s)
- Vikash Pandey
- Laboratory of Computational Systems Biotechnology, EPFL, Lausanne, Switzerland
| | - Noushin Hadadi
- Laboratory of Computational Systems Biotechnology, EPFL, Lausanne, Switzerland
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17
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Tokic M, Hadadi N, Ataman M, Neves D, Ebert BE, Blank LM, Miskovic L, Hatzimanikatis V. Discovery and Evaluation of Biosynthetic Pathways for the Production of Five Methyl Ethyl Ketone Precursors. ACS Synth Biol 2018; 7:1858-1873. [PMID: 30021444 DOI: 10.1021/acssynbio.8b00049] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The limited supply of fossil fuels and the establishment of new environmental policies shifted research in industry and academia toward sustainable production of the second generation of biofuels, with methyl ethyl ketone (MEK) being one promising fuel candidate. MEK is a commercially valuable petrochemical with an extensive application as a solvent. However, as of today, a sustainable and economically viable production of MEK has not yet been achieved despite several attempts of introducing biosynthetic pathways in industrial microorganisms. We used BNICE.ch as a retrobiosynthesis tool to discover all novel pathways around MEK. Out of 1325 identified compounds connecting to MEK with one reaction step, we selected 3-oxopentanoate, but-3-en-2-one, but-1-en-2-olate, butylamine, and 2-hydroxy-2-methylbutanenitrile for further study. We reconstructed 3 679 610 novel biosynthetic pathways toward these 5 compounds. We then embedded these pathways into the genome-scale model of E. coli, and a set of 18 622 were found to be the most biologically feasible ones on the basis of thermodynamics and their yields. For each novel reaction in the viable pathways, we proposed the most similar KEGG reactions, with their gene and protein sequences, as candidates for either a direct experimental implementation or as a basis for enzyme engineering. Through pathway similarity analysis we classified the pathways and identified the enzymes and precursors that were indispensable for the production of the target molecules. These retrobiosynthesis studies demonstrate the potential of BNICE.ch for discovery, systematic evaluation, and analysis of novel pathways in synthetic biology and metabolic engineering studies.
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Affiliation(s)
- Milenko Tokic
- Laboratory of Computational Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland
| | - Noushin Hadadi
- Laboratory of Computational Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland
| | - Meric Ataman
- Laboratory of Computational Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland
| | - Dário Neves
- Institute of Applied Microbiology (iAMB), Aachen Biology and Biotechnology (ABBt), RWTH Aachen University, D-52056 Aachen, Germany
| | - Birgitta E. Ebert
- Institute of Applied Microbiology (iAMB), Aachen Biology and Biotechnology (ABBt), RWTH Aachen University, D-52056 Aachen, Germany
| | - Lars M. Blank
- Institute of Applied Microbiology (iAMB), Aachen Biology and Biotechnology (ABBt), RWTH Aachen University, D-52056 Aachen, Germany
| | - Ljubisa Miskovic
- Laboratory of Computational Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland
| | - Vassily Hatzimanikatis
- Laboratory of Computational Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland
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18
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Islam MA, Hadadi N, Ataman M, Hatzimanikatis V, Stephanopoulos G. Exploring biochemical pathways for mono-ethylene glycol (MEG) synthesis from synthesis gas. Metab Eng 2017; 41:173-181. [PMID: 28433737 DOI: 10.1016/j.ymben.2017.04.005] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Revised: 12/28/2016] [Accepted: 04/16/2017] [Indexed: 10/19/2022]
Abstract
Mono-ethylene glycol (MEG) is an important petrochemical with widespread use in numerous consumer products. The current industrial MEG-production process relies on non-renewable fossil fuel-based feedstocks, such as petroleum, natural gas, and naphtha; hence, it is useful to explore alternative routes of MEG-synthesis from gases as they might provide a greener and more sustainable alternative to the current production methods. Technologies of synthetic biology and metabolic engineering of microorganisms can be deployed for the expression of new biochemical pathways for MEG-synthesis from gases, provided that such promising alternative routes are first identified. We used the BNICE.ch algorithm to develop novel and previously unknown biological pathways to MEG from synthesis gas by leveraging the Wood-Ljungdahl pathway of carbon fixation of acetogenic bacteria. We developed a set of useful pathway pruning and analysis criteria to systematically assess thousands of pathways generated by BNICE.ch. Published genome-scale models of Moorella thermoacetica and Clostridium ljungdahlii were used to perform the pathway yield calculations and in-depth analyses of seven (7) newly developed biological MEG-producing pathways from gases, including CO2, CO, and H2. These analyses helped identify not only better candidate pathways, but also superior chassis organisms that can be used for metabolic engineering of the candidate pathways. The pathway generation, pruning, and detailed analysis procedures described in this study can also be used to develop biochemical pathways for other commodity chemicals from gaseous substrates.
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Affiliation(s)
- M Ahsanul Islam
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
| | - Noushin Hadadi
- Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Meric Ataman
- Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Vassily Hatzimanikatis
- Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland.
| | - Gregory Stephanopoulos
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
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Hadadi N, Hafner J, Soh KC, Hatzimanikatis V. Reconstruction of biological pathways and metabolic networks from in silico labeled metabolites. Biotechnol J 2017; 12. [DOI: 10.1002/biot.201600464] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2016] [Revised: 11/21/2016] [Accepted: 11/28/2016] [Indexed: 12/13/2022]
Affiliation(s)
- Noushin Hadadi
- Laboratory of Computational Systems Biotechnology (LCSB); Swiss Federal Institute of Technology (EPFL); Lausanne Switzerland
| | - Jasmin Hafner
- Laboratory of Computational Systems Biotechnology (LCSB); Swiss Federal Institute of Technology (EPFL); Lausanne Switzerland
| | - Keng Cher Soh
- Laboratory of Computational Systems Biotechnology (LCSB); Swiss Federal Institute of Technology (EPFL); Lausanne Switzerland
| | - Vassily Hatzimanikatis
- Laboratory of Computational Systems Biotechnology (LCSB); Swiss Federal Institute of Technology (EPFL); Lausanne Switzerland
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Hadadi N, Hafner J, Shajkofci A, Zisaki A, Hatzimanikatis V. ATLAS of Biochemistry: A Repository of All Possible Biochemical Reactions for Synthetic Biology and Metabolic Engineering Studies. ACS Synth Biol 2016; 5:1155-1166. [PMID: 27404214 DOI: 10.1021/acssynbio.6b00054] [Citation(s) in RCA: 96] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Because the complexity of metabolism cannot be intuitively understood or analyzed, computational methods are indispensable for studying biochemistry and deepening our understanding of cellular metabolism to promote new discoveries. We used the computational framework BNICE.ch along with cheminformatic tools to assemble the whole theoretical reactome from the known metabolome through expansion of the known biochemistry presented in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. We constructed the ATLAS of Biochemistry, a database of all theoretical biochemical reactions based on known biochemical principles and compounds. ATLAS includes more than 130 000 hypothetical enzymatic reactions that connect two or more KEGG metabolites through novel enzymatic reactions that have never been reported to occur in living organisms. Moreover, ATLAS reactions integrate 42% of KEGG metabolites that are not currently present in any KEGG reaction into one or more novel enzymatic reactions. The generated repository of information is organized in a Web-based database ( http://lcsb-databases.epfl.ch/atlas/ ) that allows the user to search for all possible routes from any substrate compound to any product. The resulting pathways involve known and novel enzymatic steps that may indicate unidentified enzymatic activities and provide potential targets for protein engineering. Our approach of introducing novel biochemistry into pathway design and associated databases will be important for synthetic biology and metabolic engineering.
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Affiliation(s)
- Noushin Hadadi
- Laboratory of Computational
Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland
| | - Jasmin Hafner
- Laboratory of Computational
Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland
| | - Adrian Shajkofci
- Laboratory of Computational
Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland
| | - Aikaterini Zisaki
- Laboratory of Computational
Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland
| | - Vassily Hatzimanikatis
- Laboratory of Computational
Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland
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Hadadi N, Ataman M, Hatzimanikatis V, Panayiotou C. Molecular thermodynamics of metabolism: quantum thermochemical calculations for key metabolites. Phys Chem Chem Phys 2016; 17:10438-53. [PMID: 25799954 DOI: 10.1039/c4cp05825a] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The present work is the first of a series of papers aiming at a coherent and unified development of the thermodynamics of metabolism and the rationalization of feasibility analysis of metabolic pathways. The focus in this part is on high-level quantum chemical calculations of the thermochemical quantities of relatively heavy metabolites such as amino acids/oligopeptides, nucleosides, saccharides and their derivatives in the ideal gas state. The results of this study will be combined with the corresponding hydration/solvation results in subsequent parts of this work in order to derive the desired thermochemical quantities in aqueous solutions. The above metabolites exist in a vast conformational/isomerization space including rotational conformers, tautomers or anomers exhibiting often multiple or cooperative intramolecular hydrogen bonding. We examine the challenges posed by these features for the reliable estimation of thermochemical quantities. We discuss conformer search, conformer distribution and averaging processes. We further consider neutral metabolites as well as protonated and deprotonated metabolites. In addition to the traditional presentation of gas-phase acidities, basicities and proton affinities, we also examine heats and free energies of ionic species. We obtain simple linear relations between the thermochemical quantities of ions and the formation quantities of their neutral counterparts. Furthermore, we compare our calculations with reliable experimental measurements and predictive calculations from the literature, when available. Finally, we discuss the next steps and perspectives for this work.
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Affiliation(s)
- N Hadadi
- Laboratory of Computational Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland
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Panayiotou C, Mastrogeorgopoulos S, Ataman M, Hadadi N, Hatzimanikatis V. Molecular thermodynamics of metabolism: hydration quantities and the equation-of-state approach. Phys Chem Chem Phys 2016; 18:32570-32592. [DOI: 10.1039/c6cp06281d] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Comprehensive and consistent calculations of hydration quantities, including conformational contributions.
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Affiliation(s)
- C. Panayiotou
- Department of Chemical Engineering
- University of Thessaloniki
- 54124 Thessaloniki
- Greece
| | - S. Mastrogeorgopoulos
- Department of Chemical Engineering
- University of Thessaloniki
- 54124 Thessaloniki
- Greece
| | - M. Ataman
- Laboratory of Computational Systems Biotechnology (LCSB)
- Swiss Federal Institute of Technology (EPFL)
- CH-1015 Lausanne
- Switzerland
- Swiss Institute of Bioinformatics (SIB)
| | - N. Hadadi
- Laboratory of Computational Systems Biotechnology (LCSB)
- Swiss Federal Institute of Technology (EPFL)
- CH-1015 Lausanne
- Switzerland
- Swiss Institute of Bioinformatics (SIB)
| | - V. Hatzimanikatis
- Laboratory of Computational Systems Biotechnology (LCSB)
- Swiss Federal Institute of Technology (EPFL)
- CH-1015 Lausanne
- Switzerland
- Swiss Institute of Bioinformatics (SIB)
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Hadadi N, Hatzimanikatis V. Design of computational retrobiosynthesis tools for the design of de novo synthetic pathways. Curr Opin Chem Biol 2015; 28:99-104. [DOI: 10.1016/j.cbpa.2015.06.025] [Citation(s) in RCA: 90] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2015] [Revised: 06/16/2015] [Accepted: 06/21/2015] [Indexed: 12/28/2022]
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Hadadi N, Cher Soh K, Seijo M, Zisaki A, Guan X, Wenk MR, Hatzimanikatis V. A computational framework for integration of lipidomics data into metabolic pathways. Metab Eng 2014; 23:1-8. [DOI: 10.1016/j.ymben.2013.12.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2013] [Revised: 11/26/2013] [Accepted: 12/24/2013] [Indexed: 10/25/2022]
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