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Wu Y, Judge MT, Arnold J, Bhandarkar SM, Edison AS. RTExtract: time-series NMR spectra quantification based on 3D surface ridge tracking. Bioinformatics 2021; 36:5068-5075. [PMID: 32653900 PMCID: PMC7755419 DOI: 10.1093/bioinformatics/btaa631] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 05/28/2020] [Accepted: 07/06/2020] [Indexed: 12/23/2022] Open
Abstract
MOTIVATION Time-series nuclear magnetic resonance (NMR) has advanced our knowledge about metabolic dynamics. Before analyzing compounds through modeling or statistical methods, chemical features need to be tracked and quantified. However, because of peak overlap and peak shifting, the available protocols are time consuming at best or even impossible for some regions in NMR spectra. RESULTS We introduce Ridge Tracking-based Extract (RTExtract), a computer vision-based algorithm, to quantify time-series NMR spectra. The NMR spectra of multiple time points were formulated as a 3D surface. Candidate points were first filtered using local curvature and optima, then connected into ridges by a greedy algorithm. Interactive steps were implemented to refine results. Among 173 simulated ridges, 115 can be tracked (RMSD < 0.001). For reproducing previous results, RTExtract took less than 2 h instead of ∼48 h, and two instead of seven parameters need tuning. Multiple regions with overlapping and changing chemical shifts are accurately tracked. AVAILABILITY AND IMPLEMENTATION Source code is freely available within Metabolomics toolbox GitHub repository (https://github.com/artedison/Edison_Lab_Shared_Metabolomics_UGA/tree/master/metabolomics_toolbox/code/ridge_tracking) and is implemented in MATLAB and R. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Yue Wu
- Institute of Bioinformatics
| | | | | | | | - Arthur S Edison
- Institute of Bioinformatics.,Department of Genetics.,Complex Carbohydrate Research Center.,Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602, USA
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52
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Amer B, Baidoo EEK. Omics-Driven Biotechnology for Industrial Applications. Front Bioeng Biotechnol 2021; 9:613307. [PMID: 33708762 PMCID: PMC7940536 DOI: 10.3389/fbioe.2021.613307] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 01/11/2021] [Indexed: 12/11/2022] Open
Abstract
Biomanufacturing is a key component of biotechnology that uses biological systems to produce bioproducts of commercial relevance, which are of great interest to the energy, material, pharmaceutical, food, and agriculture industries. Biotechnology-based approaches, such as synthetic biology and metabolic engineering are heavily reliant on "omics" driven systems biology to characterize and understand metabolic networks. Knowledge gained from systems biology experiments aid the development of synthetic biology tools and the advancement of metabolic engineering studies toward establishing robust industrial biomanufacturing platforms. In this review, we discuss recent advances in "omics" technologies, compare the pros and cons of the different "omics" technologies, and discuss the necessary requirements for carrying out multi-omics experiments. We highlight the influence of "omics" technologies on the production of biofuels and bioproducts by metabolic engineering. Finally, we discuss the application of "omics" technologies to agricultural and food biotechnology, and review the impact of "omics" on current COVID-19 research.
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Affiliation(s)
- Bashar Amer
- Lawrence Berkeley National Laboratory, Joint BioEnergy Institute, Emeryville, CA, United States
- Biological Systems and Engineering, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Edward E. K. Baidoo
- Lawrence Berkeley National Laboratory, Joint BioEnergy Institute, Emeryville, CA, United States
- Biological Systems and Engineering, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
- U.S. Department of Energy, Agile BioFoundry, Emeryville, CA, United States
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53
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Blasche S, Kim Y, Mars RAT, Machado D, Maansson M, Kafkia E, Milanese A, Zeller G, Teusink B, Nielsen J, Benes V, Neves R, Sauer U, Patil KR. Metabolic cooperation and spatiotemporal niche partitioning in a kefir microbial community. Nat Microbiol 2021; 6:196-208. [PMID: 33398099 PMCID: PMC7610452 DOI: 10.1038/s41564-020-00816-5] [Citation(s) in RCA: 128] [Impact Index Per Article: 42.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Accepted: 10/19/2020] [Indexed: 01/28/2023]
Abstract
Microbial communities often undergo intricate compositional changes yet also maintain stable coexistence of diverse species. The mechanisms underlying long-term coexistence remain unclear as system-wide studies have been largely limited to engineered communities, ex situ adapted cultures or synthetic assemblies. Here, we show how kefir, a natural milk-fermenting community of prokaryotes (predominantly lactic and acetic acid bacteria) and yeasts (family Saccharomycetaceae), realizes stable coexistence through spatiotemporal orchestration of species and metabolite dynamics. During milk fermentation, kefir grains (a polysaccharide matrix synthesized by kefir microorganisms) grow in mass but remain unchanged in composition. In contrast, the milk is colonized in a sequential manner in which early members open the niche for the followers by making available metabolites such as amino acids and lactate. Through metabolomics, transcriptomics and large-scale mapping of inter-species interactions, we show how microorganisms poorly suited for milk survive in-and even dominate-the community, through metabolic cooperation and uneven partitioning between grain and milk. Overall, our findings reveal how inter-species interactions partitioned in space and time lead to stable coexistence.
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Affiliation(s)
- Sonja Blasche
- European Molecular Biology Laboratory, Heidelberg, Germany
| | - Yongkyu Kim
- European Molecular Biology Laboratory, Heidelberg, Germany
| | - Ruben A T Mars
- Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Daniel Machado
- European Molecular Biology Laboratory, Heidelberg, Germany
| | | | - Eleni Kafkia
- European Molecular Biology Laboratory, Heidelberg, Germany
- The Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, UK
| | | | - Georg Zeller
- European Molecular Biology Laboratory, Heidelberg, Germany
| | - Bas Teusink
- Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Jens Nielsen
- Chalmers University of Technology, Gothenburg, Sweden
| | - Vladimir Benes
- European Molecular Biology Laboratory, Heidelberg, Germany
| | | | - Uwe Sauer
- Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Kiran Raosaheb Patil
- European Molecular Biology Laboratory, Heidelberg, Germany.
- The Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, UK.
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54
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van Rosmalen RP, Smith RW, Martins Dos Santos VAP, Fleck C, Suarez-Diez M. Model reduction of genome-scale metabolic models as a basis for targeted kinetic models. Metab Eng 2021; 64:74-84. [PMID: 33486094 DOI: 10.1016/j.ymben.2021.01.008] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 01/05/2021] [Accepted: 01/15/2021] [Indexed: 11/26/2022]
Abstract
Constraint-based, genome-scale metabolic models are an essential tool to guide metabolic engineering. However, they lack the detail and time dimension that kinetic models with enzyme dynamics offer. Model reduction can be used to bridge the gap between the two methods and allow for the integration of kinetic models into the Design-Built-Test-Learn cycle. Here we show that these reduced size models can be representative of the dynamics of the original model and demonstrate the automated generation and parameterisation of such models. Using these minimal models of metabolism could allow for further exploration of dynamic responses in metabolic networks.
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Affiliation(s)
- R P van Rosmalen
- Laboratory of Systems and Synthetic Biology, Department of Agrotechnology and Food Sciences, Wageningen University & Research, Wageningen, the Netherlands
| | - R W Smith
- Laboratory of Systems and Synthetic Biology, Department of Agrotechnology and Food Sciences, Wageningen University & Research, Wageningen, the Netherlands
| | - V A P Martins Dos Santos
- Laboratory of Systems and Synthetic Biology, Department of Agrotechnology and Food Sciences, Wageningen University & Research, Wageningen, the Netherlands; Lifeglimmer GmbH, Berlin, Germany
| | - C Fleck
- Freiburg Center for Data Analysis and Modelling University of Freiburg Freiburg Germany; Control Theory and Systems Biology Laboratory, Department of Biosystems Science and En- gineering, ETH Zürich, Basel, Switzerland
| | - M Suarez-Diez
- Laboratory of Systems and Synthetic Biology, Department of Agrotechnology and Food Sciences, Wageningen University & Research, Wageningen, the Netherlands.
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55
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(p)ppGpp-Dependent Regulation of the Nucleotide Hydrolase PpnN Confers Complement Resistance in Salmonella enterica Serovar Typhimurium. Infect Immun 2021; 89:IAI.00639-20. [PMID: 33139383 DOI: 10.1128/iai.00639-20] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 10/23/2020] [Indexed: 12/11/2022] Open
Abstract
The stringent response is an essential mechanism of metabolic reprogramming during environmental stress that is mediated by the nucleotide alarmones guanosine tetraphosphate and pentaphosphate [(p)ppGpp]. In addition to physiological adaptations, (p)ppGpp also regulates virulence programs in pathogenic bacteria, including Salmonella enterica serovar Typhimurium. S Typhimurium is a common cause of acute gastroenteritis, but it may also spread to systemic tissues, resulting in severe clinical outcomes. During infection, S Typhimurium encounters a broad repertoire of immune defenses that it must evade for successful host infection. Here, we examined the role of the stringent response in S Typhimurium resistance to complement-mediated killing and found that the (p)ppGpp synthetase-hydrolase, SpoT, is required for bacterial survival in human serum. We identified the nucleotide hydrolase, PpnN, as a target of the stringent response that is required to promote bacterial fitness in serum. Using chromatography and mass spectrometry, we show that PpnN hydrolyzes purine and pyrimidine monophosphates to generate free nucleobases and ribose 5'-phosphate, and that this metabolic activity is required for conferring resistance to complement killing. In addition to PpnN, we show that (p)ppGpp is required for the biosynthesis of the very long and long O-antigen in the outer membrane, known to be important for complement resistance. Our results provide new insights into the role of the stringent response in mediating evasion of the innate immune system by pathogenic bacteria.
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Castillo Alfonso F, Vigueras-Ramírez G, Rosales-Colunga LM, Del Monte-Martínez A, Olivares Hernández R. Propionate as the preferred carbon source to produce 3-indoleacetic acid in B. subtilis: comparative flux analysis using five carbon sources. Mol Omics 2021; 17:554-564. [PMID: 33972977 DOI: 10.1039/d1mo00039j] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
3-Indoleacetic acid (IAA) is a phytohormone that promotes plant root growth, improving the use of nutrients and crop yield and it is been reported that bacteria of the genus Bacillus are capable of producing this phytohormone under various growth conditions. Considering this metabolic capability, in this work, Bacillus subtilis was cultivated in five different carbon sources: glucose, acetate, propionate, citrate and glycerol; and l-tryptophan (Trp) was used as an inducer for the IAA production. Based on the experimental results it was observed that the highest growth rate was achieved using glucose as a carbon source (μ = 0.12 h-1) and the lowest value was for citrate (μ = 0.08 h-1). On the other hand, the highest IAA production was obtained using propionate Yp/s = 0.975 (gIAA gTrp-1) and the lowest was when glucose was the substrate Yp/s = 0.803 (gIAA gTrp-1). In order to explore the metabolism and understand these differences, the experimental data was used to calculate the flux distribution using the genomic-scale metabolic model of Bacillus subtilis. Performing a comparative analysis it is observed that the fluxes towards precursors increase when propionate is the carbon source.
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Affiliation(s)
- Freddy Castillo Alfonso
- Posgrado en Ciencias Naturales e Ingeniería, Universidad Autónoma Metropolitana, Unidad Cuajimalpa, Av. Vasco de Quiroga 4871, Col. Santa Fe Cuajimalpa, Delegación Cuajimalpa, Ciudad de Mexico, 05348, Mexico
| | - Gabriel Vigueras-Ramírez
- Departamento de Procesos y Tecnología, Universidad Autónoma Metropolitana, Unidad Cuajimalpa, Av. Vasco de Quiroga 4871, Col. Santa Fe Cuajimalpa, Delegación Cuajimalpa, Ciudad de Mexico, 05348, Mexico.
| | - Luis Manuel Rosales-Colunga
- Facultad de Ingeniería, Universidad Autónoma de San Luis Potosí, Av. Dr Manuel Nava 8, Zona Universitaria, 78290, San Luis Potosí, S.L.P, Mexico
| | - Alberto Del Monte-Martínez
- Centro de Estudios de Proteínas, Univerisdad de La Habana, Calle 25 #455, e/J e I, vedado, 10400, Havana, Cuba
| | - Roberto Olivares Hernández
- Departamento de Procesos y Tecnología, Universidad Autónoma Metropolitana, Unidad Cuajimalpa, Av. Vasco de Quiroga 4871, Col. Santa Fe Cuajimalpa, Delegación Cuajimalpa, Ciudad de Mexico, 05348, Mexico.
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57
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Chodkowski JL, Shade A. Exometabolite Dynamics over Stationary Phase Reveal Strain-Specific Responses. mSystems 2020; 5:e00493-20. [PMID: 33361318 PMCID: PMC7762789 DOI: 10.1128/msystems.00493-20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 11/25/2020] [Indexed: 11/20/2022] Open
Abstract
Microbial exponential growth is expected to occur infrequently in environments that have long periods of nutrient starvation punctuated by short periods of high nutrient flux. These conditions likely impose nongrowth states for microbes. However, nongrowth states are uncharacterized for the majority of environmental bacteria, especially in regard to exometabolite production. We compared exometabolites produced over stationary phase across three environmental bacteria: Burkholderia thailandensis E264 (ATCC 700388), Chromobacterium violaceum ATCC 31532, and Pseudomonas syringae pv. tomato DC3000 (ATCC BAA-871). We grew each strain in monoculture and investigated exometabolite dynamics from mid-exponential to stationary phases. We focused on exometabolites that were released into the medium and accumulated over 45 h, including approximately 20 h of stationary phase. We also analyzed transcripts (transcriptome sequencing [RNA-seq]) to interpret exometabolite output. We found that the majority of exometabolites released were strain specific, with a subset of identified exometabolites involved in both central and secondary metabolism. Transcript analysis supported that exometabolites were released from intact cells, as various transporters had either increased or consistent transcripts through time. Interestingly, we found that succinate was one of the most abundant identifiable exometabolites for all strains and that each strain rerouted their metabolic pathways involved in succinate production during stationary phase. These results show that nongrowth states can be metabolically dynamic and that environmental bacteria can enrich a minimal environment with diverse chemical compounds as a consequence of growth and postgrowth maintenance in stationary phase. This work provides insights into microbial community interactions via exometabolites under conditions of growth cessation or limitation.IMPORTANCE Nongrowth states are common for bacteria that live in environments that are densely populated and predominantly nutrient exhausted, and yet these states remain largely uncharacterized in cellular metabolism and metabolite output. Here, we investigated and compared stationary-phase exometabolites and RNA transcripts for each of three environmental bacterial strains. We observed that diverse exometabolites were produced and provide evidence that these exometabolites accumulate over time through release by intact cells. Additionally, each bacterial strain had a characteristic exometabolite profile and exhibited dynamics in exometabolite composition. This work affirms that stationary phase is metabolically dynamic, with each strain tested creating a unique chemical signature in the extracellular space and altering metabolism in stationary phase. These findings set the stage for understanding how bacterial populations can support surrounding neighbors in environments with prolonged nutrient exhaustion through exometabolite-mediated interspecies interactions.
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Affiliation(s)
- John L Chodkowski
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan, USA
| | - Ashley Shade
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan, USA
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, Michigan, USA
- Program in Ecology, Evolution, and Behavior, Michigan State University, East Lansing, Michigan, USA
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58
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Predicting By-Product Gradients of Baker’s Yeast Production at Industrial Scale: A Practical Simulation Approach. Processes (Basel) 2020. [DOI: 10.3390/pr8121554] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Scaling up bioprocesses is one of the most crucial steps in the commercialization of bioproducts. While it is known that concentration and shear rate gradients occur at larger scales, it is often too risky, if feasible at all, to conduct validation experiments at such scales. Using computational fluid dynamics equipped with mechanistic biochemical engineering knowledge of the process, it is possible to simulate such gradients. In this work, concentration profiles for the by-products of baker’s yeast production are investigated. By applying a mechanistic black-box model, concentration heterogeneities for oxygen, glucose, ethanol, and carbon dioxide are evaluated. The results suggest that, although at low concentrations, ethanol is consumed in more than 90% of the tank volume, which prevents cell starvation, even when glucose is virtually depleted. Moreover, long exposure to high dissolved carbon dioxide levels is predicted. Two biomass concentrations, i.e., 10 and 25 g/L, are considered where, in the former, ethanol production is solely because of overflow metabolism while, in the latter, 10% of the ethanol formation is due to dissolved oxygen limitation. This method facilitates the prediction of the living conditions of the microorganism and its utilization to address the limitations via change of strain or bioreactor design or operation conditions. The outcome can also be of value to design a representative scale-down reactor to facilitate strain studies.
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59
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Edison AS, Colonna M, Gouveia GJ, Holderman NR, Judge MT, Shen X, Zhang S. NMR: Unique Strengths That Enhance Modern Metabolomics Research. Anal Chem 2020; 93:478-499. [DOI: 10.1021/acs.analchem.0c04414] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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60
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Sailwal M, Das AJ, Gazara RK, Dasgupta D, Bhaskar T, Hazra S, Ghosh D. Connecting the dots: Advances in modern metabolomics and its application in yeast system. Biotechnol Adv 2020; 44:107616. [DOI: 10.1016/j.biotechadv.2020.107616] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 08/15/2020] [Accepted: 08/17/2020] [Indexed: 12/15/2022]
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61
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Petchiappan A, Gottesman S. How Does the Alarmone ppGpp Change Bacterial Cell Metabolism? From Genome-wide Approaches to Structure to Physiology. Mol Cell 2020; 80:1-2. [PMID: 33007252 DOI: 10.1016/j.molcel.2020.09.019] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Wang et al. (2020) show that binding of the second messenger ppGpp to inosine-guanosine kinase (Gsk) in E. coli modulates the levels of the key metabolite phosphoribosyl pyrophosphate (pRpp), decreasing purine synthesis to favor amino acid synthesis during stress adaptation.
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Affiliation(s)
- Anushya Petchiappan
- Laboratory of Molecular Biology, National Cancer Institute, Bethesda, MD 20892, USA
| | - Susan Gottesman
- Laboratory of Molecular Biology, National Cancer Institute, Bethesda, MD 20892, USA.
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62
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Liu Y, Su A, Li J, Ledesma-Amaro R, Xu P, Du G, Liu L. Towards next-generation model microorganism chassis for biomanufacturing. Appl Microbiol Biotechnol 2020; 104:9095-9108. [DOI: 10.1007/s00253-020-10902-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 09/03/2020] [Accepted: 09/10/2020] [Indexed: 11/29/2022]
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63
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Larson-Casey JL, Gu L, Fiehn O, Carter AB. Cadmium-mediated lung injury is exacerbated by the persistence of classically activated macrophages. J Biol Chem 2020; 295:15754-15766. [PMID: 32917723 DOI: 10.1074/jbc.ra120.013632] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 09/09/2020] [Indexed: 12/15/2022] Open
Abstract
Heavy metals released into the environment have a significant effect on respiratory health. Lung macrophages are important in mounting an inflammatory response to injury, but they are also involved in repair of injury. Macrophages develop mixed phenotypes in complex pathological conditions and polarize to a predominant phenotype depending on the duration and stage of injury and/or repair. Little is known about the reprogramming required for lung macrophages to switch between these divergent functions; therefore, understanding the mechanism(s) by which macrophages promote metabolic reprogramming to regulate lung injury is essential. Here, we show that lung macrophages polarize to a pro-inflammatory, classically activated phenotype after cadmium-mediated lung injury. Because metabolic adaptation provides energy for the diverse macrophage functions, these classically activated macrophages show metabolic reprogramming to glycolysis. RNA-Seq revealed up-regulation of glycolytic enzymes and transcription factors regulating glycolytic flux in lung macrophages from cadmium-exposed mice. Moreover, cadmium exposure promoted increased macrophage glycolytic function with enhanced extracellular acidification rate, glycolytic metabolites, and lactate excretion. These observations suggest that cadmium mediates the persistence of classically activated lung macrophages to exacerbate lung injury.
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Affiliation(s)
- Jennifer L Larson-Casey
- Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA.
| | - Linlin Gu
- Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Oliver Fiehn
- National Institutes of Health West Coast Metabolomics Center, University of California Davis, Davis, California, USA
| | - A Brent Carter
- Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA; Birmingham Veterans Administration Medical Center, Birmingham, Alabama, USA
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64
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Han YY, Lin YC, Cheng WC, Lin YT, Teng LJ, Wang JK, Wang YL. Rapid antibiotic susceptibility testing of bacteria from patients' blood via assaying bacterial metabolic response with surface-enhanced Raman spectroscopy. Sci Rep 2020; 10:12538. [PMID: 32719444 PMCID: PMC7385103 DOI: 10.1038/s41598-020-68855-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Accepted: 06/03/2020] [Indexed: 12/20/2022] Open
Abstract
Blood stream infection is one of the major public health issues characterized with high cost and high mortality. Timely effective antibiotics usage to control infection is crucial for patients’ survival. The standard microbiological diagnosis of infection however can last days. The delay in accurate antibiotic therapy would lead to not only poor clinical outcomes, but also to a rise in antibiotic resistance due to widespread use of empirical broad-spectrum antibiotics. An important measure to tackle this problem is fast determination of bacterial antibiotic susceptibility to optimize antibiotic treatment. We show that a protocol based on surface-enhanced Raman spectroscopy can obtain consistent antibiotic susceptibility test results from clinical blood-culture samples within four hours. The characteristic spectral signatures of the obtained spectra of Staphylococcus aureus and Escherichia coli—prototypic Gram-positive and Gram-negative bacteria—became prominent after an effective pretreatment procedure removed strong interferences from blood constituents. Using them as the biomarkers of bacterial metabolic responses to antibiotics, the protocol reported the susceptibility profiles of tested drugs against these two bacteria acquired from patients’ blood with high specificity, sensitivity and speed.
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Affiliation(s)
- Yin-Yi Han
- Department of Anesthesia, National Taiwan University Hospital, Taipei, Taiwan. .,Department of Traumatology, National Taiwan University Hospital, Taipei, Taiwan.
| | - Yi-Chun Lin
- Institute of Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan
| | - Wei-Chih Cheng
- Institute of Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan
| | - Yu-Tzu Lin
- Department of Clinical Laboratory Sciences and Medical Biotechnology, National Taiwan University, Taipei, Taiwan.,Department of Medical Laboratory Science and Biotechnology, China Medical University, Taichung, Taiwan
| | - Lee-Jene Teng
- Department of Clinical Laboratory Sciences and Medical Biotechnology, National Taiwan University, Taipei, Taiwan
| | - Juen-Kai Wang
- Institute of Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan. .,Center for Condensed Matter Sciences, National Taiwan University, Taipei, Taiwan. .,Center of Atomic Initiative for New Materials, National Taiwan University, Taipei, Taiwan.
| | - Yuh-Lin Wang
- Institute of Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan. .,Department of Physics, National Taiwan University, Taipei, Taiwan.
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65
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Li N, Zeng W, Xu S, Zhou J. Toward fine-tuned metabolic networks in industrial microorganisms. Synth Syst Biotechnol 2020; 5:81-91. [PMID: 32542205 PMCID: PMC7283098 DOI: 10.1016/j.synbio.2020.05.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Revised: 03/30/2020] [Accepted: 05/06/2020] [Indexed: 12/11/2022] Open
Abstract
There are numerous microorganisms in nature capable of synthesizing diverse useful compounds; however, these natural microorganisms are generally inefficient in the production of target products on an industrial scale, relative to either chemical synthesis or extraction methods. To achieve industrial production of useful compounds, these natural microorganisms must undergo a certain degree of mutation or effective fine-tuning strategies. This review describes how to achieve an ideal metabolic fine-tuned process, including static control strategies and dynamic control strategies. The static control strategies mainly focus on various matabolic engineering strategies, including protein engineering, upregulation/downregulation, and combinatrorial control of these metabolic engineering strategies, to enhance the flexibility of their application in fine-tuned metabolic metworks. Then, we focus on the dynamic control strategies for fine-tuned metabolic metworks. The design principles derived would guide us to construct microbial cell factories for various useful compounds.
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Affiliation(s)
- Ning Li
- Key Laboratory of Industrial Biotechnology, Ministry of Education and School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu, 214122, China.,National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu, 214122, China.,Jiangsu Provisional Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu, 214122, China
| | - Weizhu Zeng
- Key Laboratory of Industrial Biotechnology, Ministry of Education and School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu, 214122, China.,National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu, 214122, China.,Jiangsu Provisional Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu, 214122, China
| | - Sha Xu
- Key Laboratory of Industrial Biotechnology, Ministry of Education and School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu, 214122, China.,National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu, 214122, China.,Jiangsu Provisional Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu, 214122, China
| | - Jingwen Zhou
- Key Laboratory of Industrial Biotechnology, Ministry of Education and School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu, 214122, China.,National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu, 214122, China.,Jiangsu Provisional Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu, 214122, China
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66
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Weber CA, Sekar K, Tang JH, Warmer P, Sauer U, Weis K. β-Oxidation and autophagy are critical energy providers during acute glucose depletion in S accharomyces cerevisiae. Proc Natl Acad Sci U S A 2020; 117:12239-12248. [PMID: 32430326 PMCID: PMC7275744 DOI: 10.1073/pnas.1913370117] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
The ability to tolerate and thrive in diverse environments is paramount to all living organisms, and many organisms spend a large part of their lifetime in starvation. Upon acute glucose starvation, yeast cells undergo drastic physiological and metabolic changes and reestablish a constant-although lower-level of energy production within minutes. The molecules that are rapidly metabolized to fuel energy production under these conditions are unknown. Here, we combine metabolomics and genetics to characterize the cells' response to acute glucose depletion and identify pathways that ensure survival during starvation. We show that the ability to respire is essential for maintaining the energy status and to ensure viability during starvation. Measuring the cells' immediate metabolic response, we find that central metabolites drastically deplete and that the intracellular AMP-to-ATP ratio strongly increases within 20 to 30 s. Furthermore, we detect changes in both amino acid and lipid metabolite levels. Consistent with this, both bulk autophagy, a process that frees amino acids, and lipid degradation via β-oxidation contribute in parallel to energy maintenance upon acute starvation. In addition, both these pathways ensure long-term survival during starvation. Thus, our results identify bulk autophagy and β-oxidation as important energy providers during acute glucose starvation.
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Affiliation(s)
- Carmen A Weber
- Department of Biology, Institute of Biochemistry, ETH (Eidgenössische Technische Hochschule) Zurich, 8093 Zurich, Switzerland
| | - Karthik Sekar
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland
| | - Jeffrey H Tang
- Department of Biology, Institute of Biochemistry, ETH (Eidgenössische Technische Hochschule) Zurich, 8093 Zurich, Switzerland
| | - Philipp Warmer
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland
| | - Uwe Sauer
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland
| | - Karsten Weis
- Department of Biology, Institute of Biochemistry, ETH (Eidgenössische Technische Hochschule) Zurich, 8093 Zurich, Switzerland;
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Cao J, Shi X, Gurav DD, Huang L, Su H, Li K, Niu J, Zhang M, Wang Q, Jiang M, Qian K. Metabolic Fingerprinting on Synthetic Alloys for Medulloblastoma Diagnosis and Radiotherapy Evaluation. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2020; 32:e2000906. [PMID: 32342553 DOI: 10.1002/adma.202000906] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Accepted: 03/17/2020] [Indexed: 05/25/2023]
Abstract
Diagnostics is the key in screening and treatment of cancer. As an emerging tool in precision medicine, metabolic analysis detects end products of pathways, and thus is more distal than proteomic/genetic analysis. However, metabolic analysis is far from ideal in clinical diagnosis due to the sample complexity and metabolite abundance in patient specimens. A further challenge is real-time and accurate tracking of treatment effect, e.g., radiotherapy. Here, Pd-Au synthetic alloys are reported for mass-spectrometry-based metabolic fingerprinting and analysis, toward medulloblastoma diagnosis and radiotherapy evaluation. A core-shell structure is designed using magnetic core particles to support Pd-Au alloys on the surface. Optimized synthetic alloys enhance the laser desorption/ionization efficacy and achieve direct detection of 100 nL of biofluids in seconds. Medulloblastoma patients are differentiated from healthy controls with average diagnostic sensitivity of 94.0%, specificity of 85.7%, and accuracy of 89.9%, by machine learning of metabolic fingerprinting. Furthermore, the radiotherapy process of patients is monitored and a preliminary panel of serum metabolite biomarkers is identified with gradual changes. This work will lead to the application-driven development of novel materials with tailored structural design and establishment of new protocols for precision medicine in near future.
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Affiliation(s)
- Jing Cao
- State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Cancer Institute, 160 Pujian Road, Shanghai, 200127, P. R. China
| | - Xuejiao Shi
- Department of Oncology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, P. R. China
| | - Deepanjali D Gurav
- State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Cancer Institute, 160 Pujian Road, Shanghai, 200127, P. R. China
| | - Lin Huang
- State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Cancer Institute, 160 Pujian Road, Shanghai, 200127, P. R. China
| | - Haiyang Su
- State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Cancer Institute, 160 Pujian Road, Shanghai, 200127, P. R. China
| | - Keke Li
- Department of Oncology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, P. R. China
| | - Jingyang Niu
- State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Cancer Institute, 160 Pujian Road, Shanghai, 200127, P. R. China
| | - Mengji Zhang
- State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Cancer Institute, 160 Pujian Road, Shanghai, 200127, P. R. China
| | - Qian Wang
- State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Cancer Institute, 160 Pujian Road, Shanghai, 200127, P. R. China
| | - Mawei Jiang
- Department of Oncology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, P. R. China
| | - Kun Qian
- State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Cancer Institute, 160 Pujian Road, Shanghai, 200127, P. R. China
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Qiu ZD, Chen JL, Zeng W, Ma Y, Chen T, Tang JF, Lai CJS, Huang LQ. Real-time toxicity prediction of Aconitum stewing system using extractive electrospray ionization mass spectrometry. Acta Pharm Sin B 2020; 10:903-912. [PMID: 32528836 PMCID: PMC7276682 DOI: 10.1016/j.apsb.2019.08.012] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2019] [Revised: 08/20/2019] [Accepted: 08/23/2019] [Indexed: 12/16/2022] Open
Abstract
Due to numerous obstacles such as complex matrices, real-time monitoring of complex reaction systems (e.g., medicinal herb stewing system) has always been a challenge though great values for safe and rational use of drugs. Herein, facilitated by the potential ability on the tolerance of complex matrices of extractive electrospray ionization mass spectrometry, a device was established to realize continuous sampling and real-time quantitative analysis of herb stewing system for the first time. A complete analytical strategy, including data acquisition, data mining, and data evaluation was proposed and implemented with overcoming the usual difficulties in real-time mass spectrometry quantification. The complex Fuzi (the lateral root of Aconitum)–meat stewing systems were real-timely monitored in 150 min by qualitative and quantitative analysis of the nine key alkaloids accurately. The results showed that the strategy worked perfectly and the toxicity of the systems were evaluated and predicated accordingly. Stewing with trotters effectively accelerated the detoxification of Fuzi soup and reduced the overall toxicity to 68%, which was recommended to be used practically for treating rheumatic arthritis and enhancing immunity. The established strategy was versatile, simple, and accurate, which would have a wide application prospect in real-time analysis and evaluation of various complex reaction systems.
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Bacterial Glycogen Provides Short-Term Benefits in Changing Environments. Appl Environ Microbiol 2020; 86:AEM.00049-20. [PMID: 32111592 DOI: 10.1128/aem.00049-20] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Accepted: 02/26/2020] [Indexed: 11/20/2022] Open
Abstract
Changing nutritional conditions challenge microbes and shape their evolutionary optimization. Here, we used real-time metabolomics to investigate the role of glycogen in the dynamic physiological adaptation of Escherichia coli to fluctuating nutrients following carbon starvation. After the depletion of environmental glucose, we found significant metabolic activity remaining, which was linked to rapid utilization of intracellular glycogen. Glycogen was depleted by 80% within minutes of glucose starvation and was similarly replenished within minutes of glucose availability. These fast time scales of glycogen utilization correspond to the short-term benefits that glycogen provided to cells undergoing various physiological transitions. Cells capable of utilizing glycogen exhibited shorter lag times than glycogen mutants when starved between periods of exposure to different carbon sources. The ability to utilize glycogen was also important for the transition between planktonic and biofilm lifestyles and enabled increased glucose uptake during pulses of limited glucose availability. While wild-type and mutant strains exhibited comparable growth rates in steady environments, mutants deficient in glycogen utilization grew more poorly in environments that fluctuated on minute scales between carbon availability and starvation. Taken together, these results highlight an underappreciated role of glycogen in rapidly providing carbon and energy in changing environments, thereby increasing survival and competition capabilities under fluctuating and nutrient-poor conditions.IMPORTANCE Nothing is constant in life, and microbes in particular have to adapt to frequent and rapid environmental changes. Here, we used real-time metabolomics and single-cell imaging to demonstrate that the internal storage polymer glycogen plays a crucial role in such dynamic adaptations. Glycogen is depleted within minutes of glucose starvation and similarly is replenished within minutes of glucose availability. Cells capable of utilizing glycogen exhibited shorter lag times than glycogen mutants when starved between periods of exposure to different carbon sources. While wild-type and mutant strains exhibited comparable growth rates in steady environments, mutants deficient in glycogen utilization grew more poorly in environments that fluctuated on minute scales between carbon availability and starvation. These results highlight an underappreciated role of glycogen in rapidly providing carbon and energy in changing environments, thereby increasing survival and competition capabilities under fluctuating and nutrient-poor conditions.
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70
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Li N, Li S, Li T, Yang H, Zhang Y, Zhao Z. Co-Incorporated Mesoporous Carbon Material-Assisted Laser Desorption/Ionization Ion Source as an Online Interface of In Vivo Microdialysis Coupled with Mass Spectrometry. Anal Chem 2020; 92:5482-5491. [PMID: 32181652 DOI: 10.1021/acs.analchem.0c00227] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
The combination of microdialysis and mass spectrometry (MS) provides the potential for rapidly monitoring diverse metabolites in vivo. Unfortunately, the high concentration of salt in biological microdialysates hindered the sensitive and online detection of these small molecular compounds. In this study, we synthesized Co-incorporated mesoporous carbon material (Co-NC) and developed a Co-NC-assisted laser desorption/ionization (LDI) ion source as an online interface of in vivo microdialysis coupled with MS for the direct analysis of diverse metabolites in microdialysates. The Co-NC could be used as a matrix for surface-assisted laser desorption/ionization mass spectrometry (SALDI MS) analysis of small molecular compounds, even under high concentration salt conditions. The Co-NC possessed the adsorption ability for small molecular compounds, and it was believed that the adsorption ability of Co-NC might separate the analytes from the salt in microdialysates at a microscopic level, which might facilitate the desorption and ionization of the analytes and finally improved the salt-tolerance ability as a matrix. Furthermore, the Co-NC-assisted LDI ion source as a novel interface of in vivo microdialysis coupled with MS has been applied to the online monitoring of liver metabolites from the CCl4-induced liver injury rat model for the first time.
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Affiliation(s)
- Na Li
- Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Beijing Mass Spectrum Center, Institute of Chemistry Chinese Academy of Sciences, Beijing 100190, China.,Graduate School, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shumu Li
- Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Beijing Mass Spectrum Center, Institute of Chemistry Chinese Academy of Sciences, Beijing 100190, China
| | - Tuo Li
- Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Beijing Mass Spectrum Center, Institute of Chemistry Chinese Academy of Sciences, Beijing 100190, China.,Graduate School, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hui Yang
- Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Beijing Mass Spectrum Center, Institute of Chemistry Chinese Academy of Sciences, Beijing 100190, China.,Graduate School, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yangyang Zhang
- Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Beijing Mass Spectrum Center, Institute of Chemistry Chinese Academy of Sciences, Beijing 100190, China.,Graduate School, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhenwen Zhao
- Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Beijing Mass Spectrum Center, Institute of Chemistry Chinese Academy of Sciences, Beijing 100190, China.,Graduate School, University of Chinese Academy of Sciences, Beijing 100049, China
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71
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Metabolomic change and pathway profiling reveal enhanced ansamitocin P-3 production in Actinosynnema pretiosum with low organic nitrogen availability in culture medium. Appl Microbiol Biotechnol 2020; 104:3555-3568. [PMID: 32114676 DOI: 10.1007/s00253-020-10463-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 12/07/2019] [Accepted: 02/12/2020] [Indexed: 10/24/2022]
Abstract
Ansamitocin P-3 (AP-3), a 19-membered polyketide macrocyclic lactam, has potent antitumor activity. Our previous study showed that a relatively low organic nitrogen concentration in culture medium could significantly improve AP-3 production of Actinosynnema pretiosum. In the present study, we aimed to reveal the possible reasons for this improvement through metabolomic and gene transcriptional analytical methods. At the same time, a metabolic pathway profile based on metabolome data and pathway correlation information was performed to obtain a systematic view of the metabolic network modulations of A. pretiosum. Orthogonal partial least squares discriminant analysis showed that nine and eleven key metabolites directly associated with AP-3 production at growth phase and ansamitocin production phase, respectively. In-depth pathway analysis results highlighted that low organic nitrogen availability had significant impacts on central carbon metabolism and amino acid metabolic pathways of A. pretiosum and these metabolic responses were found to be beneficial to precursor supply and ansamitocin biosynthesis. Furthermore, real-time PCR results showed that the transcription of genes involved in precursor and ansamitocin biosynthetic pathways were remarkably upregulated under low organic nitrogen condition thus directing increased carbon flux toward ansamitocin biosynthesis. More importantly, the metabolic pathway analysis demonstrated a competitive relationship between fatty acid and AP-3 biosynthesis could significantly affect the accumulation of AP-3. Our findings provided new knowledge on the organic nitrogen metabolism and ansamitocin biosynthetic precursor in A. pretiosum and identified several important rate-limiting steps involved in ansamitocin biosynthesis thus providing a theoretical basis of further improvement in AP-3 production.
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72
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Dromms RA, Lee JY, Styczynski MP. LK-DFBA: a linear programming-based modeling strategy for capturing dynamics and metabolite-dependent regulation in metabolism. BMC Bioinformatics 2020; 21:93. [PMID: 32122331 PMCID: PMC7053146 DOI: 10.1186/s12859-020-3422-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 02/17/2020] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND The systems-scale analysis of cellular metabolites, "metabolomics," provides data ideal for applications in metabolic engineering. However, many of the computational tools for strain design are built around Flux Balance Analysis (FBA), which makes assumptions that preclude direct integration of metabolomics data into the underlying models. Finding a way to retain the advantages of FBA's linear structure while relaxing some of its assumptions could allow us to account for metabolite levels and metabolite-dependent regulation in strain design tools built from FBA, improving the accuracy of predictions made by these tools. We designed, implemented, and characterized a modeling strategy based on Dynamic FBA (DFBA), called Linear Kinetics-Dynamic Flux Balance Analysis (LK-DFBA), to satisfy these specifications. Our strategy adds constraints describing the dynamics and regulation of metabolism that are strictly linear. We evaluated LK-DFBA against alternative modeling frameworks using simulated noisy data from a small in silico model and a larger model of central carbon metabolism in E. coli, and compared each framework's ability to recapitulate the original system. RESULTS In the smaller model, we found that we could use regression from a dynamic flux estimation (DFE) with an optional non-linear parameter optimization to reproduce metabolite concentration dynamic trends more effectively than an ordinary differential equation model with generalized mass action rate laws when tested under realistic data sampling frequency and noise levels. We observed detrimental effects across all tested modeling approaches when metabolite time course data were missing, but found these effects to be smaller for LK-DFBA in most cases. With the E. coli model, we produced qualitatively reasonable results with similar properties to the smaller model and explored two different parameterization structures that yield trade-offs in computation time and accuracy. CONCLUSIONS LK-DFBA allows for calculation of metabolite concentrations and considers metabolite-dependent regulation while still retaining many computational advantages of FBA. This provides the proof-of-principle for a new metabolic modeling framework with the potential to create genome-scale dynamic models and the potential to be applied in strain engineering tools that currently use FBA.
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Affiliation(s)
- Robert A Dromms
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Justin Y Lee
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Mark P Styczynski
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
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73
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Quek LE, Krycer JR, Ohno S, Yugi K, Fazakerley DJ, Scalzo R, Elkington SD, Dai Z, Hirayama A, Ikeda S, Shoji F, Suzuki K, Locasale JW, Soga T, James DE, Kuroda S. Dynamic 13C Flux Analysis Captures the Reorganization of Adipocyte Glucose Metabolism in Response to Insulin. iScience 2020; 23:100855. [PMID: 32058966 PMCID: PMC7005519 DOI: 10.1016/j.isci.2020.100855] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 11/26/2019] [Accepted: 01/15/2020] [Indexed: 12/22/2022] Open
Abstract
Cellular metabolism is dynamic, but quantifying non-steady metabolic fluxes by stable isotope tracers presents unique computational challenges. Here, we developed an efficient 13C-tracer dynamic metabolic flux analysis (13C-DMFA) framework for modeling central carbon fluxes that vary over time. We used B-splines to generalize the flux parameterization system and to improve the stability of the optimization algorithm. As proof of concept, we investigated how 3T3-L1 cultured adipocytes acutely metabolize glucose in response to insulin. Insulin rapidly stimulates glucose uptake, but intracellular pathways responded with differing speeds and magnitudes. Fluxes in lower glycolysis increased faster than those in upper glycolysis. Glycolysis fluxes rose disproportionally larger and faster than the tricarboxylic acid cycle, with lactate a primary glucose end product. The uncovered array of flux dynamics suggests that glucose catabolism is additionally regulated beyond uptake to help shunt glucose into appropriate pathways. This work demonstrates the value of using dynamic intracellular fluxes to understand metabolic function and pathway regulation.
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Affiliation(s)
- Lake-Ee Quek
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia; School of Mathematics and Statistics, The University of Sydney, Sydney, NSW 2006, Australia.
| | - James R Krycer
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia; School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
| | - Satoshi Ohno
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Katsuyuki Yugi
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan; Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan; YCI Laboratory for Trans-Omics, Young Chief Investigator Program, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045 Japan
| | - Daniel J Fazakerley
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia; School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
| | - Richard Scalzo
- Faculty of Engineering and Information Technologies, The University of Sydney, Sydney, NSW 2006, Australia
| | - Sarah D Elkington
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia; School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
| | - Ziwei Dai
- Department of Pharmacology and Cancer Biology, Duke University School of Medicine, Duke University, Durham, NC 27710, USA
| | - Akiyoshi Hirayama
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan; AMED-CREST, AMED, 1-7-1 Otemachi, Chiyoda-Ku, Tokyo 100-0004, Japan
| | - Satsuki Ikeda
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan
| | - Futaba Shoji
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan
| | - Kumi Suzuki
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan
| | - Jason W Locasale
- Department of Pharmacology and Cancer Biology, Duke University School of Medicine, Duke University, Durham, NC 27710, USA
| | - Tomoyoshi Soga
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan; AMED-CREST, AMED, 1-7-1 Otemachi, Chiyoda-Ku, Tokyo 100-0004, Japan
| | - David E James
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia; School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia; Sydney Medical School, The University of Sydney, Sydney, NSW 2006, Australia.
| | - Shinya Kuroda
- Department of Biological Sciences, Graduate School of Science, University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan; Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan; CREST, Japan Science and Technology Agency, Bunkyo-ku, Tokyo 113-0033, Japan.
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74
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Harris T, Uppala S, Lev-Cohain N, Adler-Levy Y, Shaul D, Nardi-Schreiber A, Sapir G, Azar A, Gamliel A, Sosna J, Gomori JM, Katz-Brull R. Hyperpolarized product selective saturating-excitations for determination of changes in metabolic reaction rates in real-time. NMR IN BIOMEDICINE 2020; 33:e4189. [PMID: 31793111 DOI: 10.1002/nbm.4189] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Revised: 08/04/2019] [Accepted: 08/16/2019] [Indexed: 06/10/2023]
Abstract
Investigation of hyperpolarized substrate metabolism has been showing utility in real-time determination of in-cell and in vivo enzymatic activities. Intracellular reaction rates may vary during the course of a measurement, even on the very short time scales of visibility on hyperpolarized MR, due to many factors such as the availability of the substrate and co-factors in the intracellular space. Despite this potential variation, the kinetic analysis of hyperpolarized signals typically assumes that the same rate constant (and in many cases, the same rate) applies throughout the course of the reaction as observed via the build-up and decay of the hyperpolarized signals. We demonstrate here an acquisition approach that can null the need for such an assumption and enable the detection of instantaneous changes in the rate of the reaction during an ex vivo hyperpolarized investigation, (i.e. in the course of the decay of one hyperpolarized substrate dose administered to a viable tissue sample ex vivo). This approach utilizes hyperpolarized product selective saturating-excitation pulses. Similar pulses have been previously utilized in vivo for spectroscopic imaging. However, we show here favorable consequences to kinetic rate determinations in the preparations used. We implement this acquisition strategy for studies on perfused tissue slices and develop a theory that explains why this particular approach enables the determination of changes in enzymatic rates that are monitored via the chemical conversions of hyperpolarized substrates. Real-time changes in intracellular reaction rates are demonstrated in perfused brain, liver, and xenograft breast cancer tissue slices and provide another potential differentiation parameter for tissue characterization.
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Affiliation(s)
- Talia Harris
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - Sivaranjan Uppala
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - Naama Lev-Cohain
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - Yael Adler-Levy
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - David Shaul
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - Atara Nardi-Schreiber
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - Gal Sapir
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - Assad Azar
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - Ayelet Gamliel
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - Jacob Sosna
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - J Moshe Gomori
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - Rachel Katz-Brull
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
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75
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McKinlay JB, Cook GM, Hards K. Microbial energy management-A product of three broad tradeoffs. Adv Microb Physiol 2020; 77:139-185. [PMID: 34756210 DOI: 10.1016/bs.ampbs.2020.09.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Wherever thermodynamics allows, microbial life has evolved to transform and harness energy. Microbial life thus abounds in the most unexpected places, enabled by profound metabolic diversity. Within this diversity, energy is transformed primarily through variations on a few core mechanisms. Energy is further managed by the physiological processes of cell growth and maintenance that use energy. Some aspects of microbial physiology are streamlined for energetic efficiency while other aspects seem suboptimal or even wasteful. We propose that the energy that a microbe harnesses and devotes to growth and maintenance is a product of three broad tradeoffs: (i) economic, trading enzyme synthesis or operational cost for functional benefit, (ii) environmental, trading optimization for a single environment for adaptability to multiple environments, and (iii) thermodynamic, trading energetic yield for forward metabolic flux. Consideration of these tradeoffs allows one to reconcile features of microbial physiology that seem to opposingly promote either energetic efficiency or waste.
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Affiliation(s)
- James B McKinlay
- Department of Biology, Indiana University, Bloomington, IN, United States.
| | - Gregory M Cook
- Department of Microbiology and Immunology, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand; Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand
| | - Kiel Hards
- Department of Microbiology and Immunology, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand; Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand
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Open-Source Software Tools, Databases, and Resources for Single-Cell and Single-Cell-Type Metabolomics. Methods Mol Biol 2020; 2064:191-217. [PMID: 31565776 DOI: 10.1007/978-1-4939-9831-9_15] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
In this age of -omics data-guided big data revolution, metabolomics has received significant attention as compared to genomics, transcriptomics, and proteomics for its proximity to the phenotype, the promises it makes and the challenges it throws. Although metabolomes of entire organisms, organs, biofluids, and tissues are of immense interest, a cell-specific resolution is deemed critical for biomedical applications where a granular understanding of cellular metabolism at cell-type and subcellular resolution is desirable. Mass spectrometry (MS) is a versatile technique that is used to analyze a broad range of compounds from different species and cell-types, with high accuracy, resolution, sensitivity, selectivity, and fast data acquisition speeds. With recent advances in MS and spectroscopy-based platforms, the research community is able to generate high-throughput data sets from single cells. However, it is challenging to handle, store, process, analyze, and interpret data in a routine manner. In this treatise, I present a workflow of metabolomics data generation from single cells and single-cell types to their analysis, visualization, and interpretation for obtaining biological insights.
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77
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Chen X, Ma D, Liu J, Luo Q, Liu L. Engineering the transmission efficiency of the noncyclic glyoxylate pathway for fumarate production in Escherichia coli. BIOTECHNOLOGY FOR BIOFUELS 2020; 13:132. [PMID: 32760446 PMCID: PMC7379832 DOI: 10.1186/s13068-020-01771-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 07/15/2020] [Indexed: 05/16/2023]
Abstract
BACKGROUND Fumarate is a multifunctional dicarboxylic acid in the tricarboxylic acid cycle, but microbial engineering for fumarate production is limited by the transmission efficiency of its biosynthetic pathway. RESULTS Here, pathway engineering was used to construct the noncyclic glyoxylate pathway for fumarate production. To improve the transmission efficiency of intermediate metabolites, pathway optimization was conducted by fluctuating gene expression levels to identify potential bottlenecks and then remove them, resulting in a large increase in fumarate production from 8.7 to 16.2 g/L. To further enhance its transmission efficiency of targeted metabolites, transporter engineering was used by screening the C4-dicarboxylate transporters and then strengthening the capacity of fumarate export, leading to fumarate production up to 18.9 g/L. Finally, the engineered strain E. coli W3110△4-P(H)CAI(H)SC produced 22.4 g/L fumarate in a 5-L fed-batch bioreactor. CONCLUSIONS In this study, we offered rational metabolic engineering and flux optimization strategies for efficient production of fumarate. These strategies have great potential in developing efficient microbial cell factories for production of high-value added chemicals.
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Affiliation(s)
- Xiulai Chen
- State Key Laboratory of Food Science and Technology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122 China
- Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122 China
- International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, 214122 China
| | - Danlei Ma
- State Key Laboratory of Food Science and Technology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122 China
- Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122 China
- International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, 214122 China
| | - Jia Liu
- State Key Laboratory of Food Science and Technology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122 China
- Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122 China
- International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, 214122 China
| | - Qiuling Luo
- State Key Laboratory of Food Science and Technology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122 China
- Wuxi Chenming Biotechnology Co. Ltd, Wuxi, 214100 China
| | - Liming Liu
- State Key Laboratory of Food Science and Technology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122 China
- Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122 China
- International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, 214122 China
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78
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Vavricka CJ, Hasunuma T, Kondo A. Dynamic Metabolomics for Engineering Biology: Accelerating Learning Cycles for Bioproduction. Trends Biotechnol 2020; 38:68-82. [DOI: 10.1016/j.tibtech.2019.07.009] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2019] [Revised: 07/18/2019] [Accepted: 07/19/2019] [Indexed: 12/15/2022]
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79
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Wang G, Haringa C, Tang W, Noorman H, Chu J, Zhuang Y, Zhang S. Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses. Biotechnol Bioeng 2019; 117:844-867. [PMID: 31814101 DOI: 10.1002/bit.27243] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 11/28/2019] [Accepted: 11/30/2019] [Indexed: 12/13/2022]
Abstract
Metabolomics aims to address what and how regulatory mechanisms are coordinated to achieve flux optimality, different metabolic objectives as well as appropriate adaptations to dynamic nutrient availability. Recent decades have witnessed that the integration of metabolomics and fluxomics within the goal of synthetic biology has arrived at generating the desired bioproducts with improved bioconversion efficiency. Absolute metabolite quantification by isotope dilution mass spectrometry represents a functional readout of cellular biochemistry and contributes to the establishment of metabolic (structured) models required in systems metabolic engineering. In industrial practices, population heterogeneity arising from fluctuating nutrient availability frequently leads to performance losses, that is reduced commercial metrics (titer, rate, and yield). Hence, the development of more stable producers and more predictable bioprocesses can benefit from a quantitative understanding of spatial and temporal cell-to-cell heterogeneity within industrial bioprocesses. Quantitative metabolomics analysis and metabolic modeling applied in computational fluid dynamics (CFD)-assisted scale-down simulators that mimic industrial heterogeneity such as fluctuations in nutrients, dissolved gases, and other stresses can procure informative clues for coping with issues during bioprocessing scale-up. In previous studies, only limited insights into the hydrodynamic conditions inside the industrial-scale bioreactor have been obtained, which makes case-by-case scale-up far from straightforward. Tracking the flow paths of cells circulating in large-scale bioreactors is a highly valuable tool for evaluating cellular performance in production tanks. The "lifelines" or "trajectories" of cells in industrial-scale bioreactors can be captured using Euler-Lagrange CFD simulation. This novel methodology can be further coupled with metabolic (structured) models to provide not only a statistical analysis of cell lifelines triggered by the environmental fluctuations but also a global assessment of the metabolic response to heterogeneity inside an industrial bioreactor. For the future, the industrial design should be dependent on the computational framework, and this integration work will allow bioprocess scale-up to the industrial scale with an end in mind.
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Affiliation(s)
- Guan Wang
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, People's Republic of China
| | - Cees Haringa
- Transport Phenomena, Chemical Engineering Department, Delft University of Technology, Delft, The Netherlands.,DSM Biotechnology Center, Delft, The Netherlands
| | - Wenjun Tang
- DSM Biotechnology Center, Delft, The Netherlands
| | - Henk Noorman
- DSM Biotechnology Center, Delft, The Netherlands.,Bioprocess Engineering, Department of Biotechnology, Delft University of Technology, Delft, The Netherlands
| | - Ju Chu
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, People's Republic of China
| | - Yingping Zhuang
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, People's Republic of China
| | - Siliang Zhang
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, People's Republic of China
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80
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Yang J, Wang R, Huang L, Zhang M, Niu J, Bao C, Shen N, Dai M, Guo Q, Wang Q, Wang Q, Fu Q, Qian K. Urine Metabolic Fingerprints Encode Subtypes of Kidney Diseases. Angew Chem Int Ed Engl 2019; 59:1703-1710. [PMID: 31829520 DOI: 10.1002/anie.201913065] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Indexed: 12/11/2022]
Abstract
Metabolic fingerprints of biofluids encode diverse diseases and particularly urine detection offers complete non-invasiveness for diagnostics of the future. Present urine detection affords unsatisfactory performance and requires advanced materials to extract molecular information, due to the limited biomarkers and high sample complexity. Herein, we report plasmonic polymer@Ag for laser desorption/ionization mass spectrometry (LDI-MS) and sparse-learning-based metabolic diagnosis of kidney diseases. Using only 1 μL of urine without enrichment or purification, polymer@Ag afforded urine metabolic fingerprints (UMFs) by LDI-MS in seconds. Analysis by sparse learning discriminated lupus nephritis from various other non-lupus nephropathies and controls. We combined UMFs with urine protein levels (UPLs) and constructed a new diagnostic model to characterize subtypes of kidney diseases. Our work guides urine-based diagnosis and leads to new personalized analytical tools for other diseases.
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Affiliation(s)
- Jing Yang
- School of Biomedical Engineering, Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Ran Wang
- Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200001, P. R. China
| | - Lin Huang
- iMS Clinic, Hangzhou, 310052, P. R. China
| | - Mengji Zhang
- School of Biomedical Engineering, Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Jingyang Niu
- School of Biomedical Engineering, Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Chunde Bao
- Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200001, P. R. China
| | - Nan Shen
- Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200001, P. R. China
| | - Min Dai
- Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200001, P. R. China
| | - Qiang Guo
- Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200001, P. R. China
| | - Qian Wang
- School of Biomedical Engineering, Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Qin Wang
- Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200001, P. R. China
| | - Qiong Fu
- Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200001, P. R. China
| | - Kun Qian
- School of Biomedical Engineering, Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
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81
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Yang J, Wang R, Huang L, Zhang M, Niu J, Bao C, Shen N, Dai M, Guo Q, Wang Q, Wang Q, Fu Q, Qian K. Urine Metabolic Fingerprints Encode Subtypes of Kidney Diseases. Angew Chem Int Ed Engl 2019. [DOI: 10.1002/ange.201913065] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Jing Yang
- School of Biomedical Engineering Med-X Research Institute Shanghai Jiao Tong University Shanghai 200030 P. R. China
| | - Ran Wang
- Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai 200001 P. R. China
| | - Lin Huang
- iMS Clinic Hangzhou 310052 P. R. China
| | - Mengji Zhang
- School of Biomedical Engineering Med-X Research Institute Shanghai Jiao Tong University Shanghai 200030 P. R. China
| | - Jingyang Niu
- School of Biomedical Engineering Med-X Research Institute Shanghai Jiao Tong University Shanghai 200030 P. R. China
| | - Chunde Bao
- Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai 200001 P. R. China
| | - Nan Shen
- Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai 200001 P. R. China
| | - Min Dai
- Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai 200001 P. R. China
| | - Qiang Guo
- Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai 200001 P. R. China
| | - Qian Wang
- School of Biomedical Engineering Med-X Research Institute Shanghai Jiao Tong University Shanghai 200030 P. R. China
| | - Qin Wang
- Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai 200001 P. R. China
| | - Qiong Fu
- Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai 200001 P. R. China
| | - Kun Qian
- School of Biomedical Engineering Med-X Research Institute Shanghai Jiao Tong University Shanghai 200030 P. R. China
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82
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Boschetto F, Adachi T, Horiguchi S, Marin E, Paccotti N, Asai T, Zhu W, McEntire BJ, Yamamoto T, Kanamura N, Mazda O, Ohgitani E, Pezzotti G. In situ molecular vibration insights into the antibacterial behavior of silicon nitride bioceramic versus gram-negative Escherichia coli. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2019; 223:117299. [PMID: 31277027 DOI: 10.1016/j.saa.2019.117299] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 06/11/2019] [Accepted: 06/20/2019] [Indexed: 06/09/2023]
Abstract
Gram-negative bacteria represent a substantial fraction of pathogens responsible for periprosthetic infections. Given the increasing resistance of such bacteria to antibiotics, significant efforts are nowadays paid in developing new biomaterial surfaces, which offer resistance against bacterial adhesion and/or possess inherent antibacterial effects. Non-oxide silicon nitride (Si3N4) bioceramic in its polycrystalline form is a biomaterial with inherent antibacterial properties. Building upon previous phenomenological findings, the present study focuses on vibrational analyses of the metabolic response of Escherichia coli at the molecular level. A time-lapse study is conducted upon exposing the bacteria in vitro to Si3N4 bioceramic surfaces. A comparison is carried out with the as-cultured bacterial strain and with bacteria exposed to other commercially available biomaterials, namely, Ti-alloy (Ti6Al4V-ELI) and zirconia-toughened alumina (ZTA) oxide bioceramic tested under exactly the same experimental conditions. The metabolic pathways before and after exposure to different substrates were monitored by means of Raman and FTIR spectroscopies. Results indicated the development of significant osmotic stress in the bacterial strain and constant concentration decreases of its cellular compounds markers over time upon exposure to Si3N4. This ultimately led to bacterial lysis (also confirmed by conventional fluorescence microscopy assays). The main antibacterial effect was of chemical origin and driven by the elution of nitrogen ions from the Si3N4 surface, successively converted into ammonia (NH3) or ammonium (NH4)+ in aqueous solution, depending on environmental pH. The presence of these nitrogen species created osmotic stress in the cytoplasmic space. In answer to the osmotic stress, metabolic rates changed rapidly, the bacterial membrane was damaged, and lysis occurred almost completely within 48 h exposure. The antibacterial behavior exerted by the Si3N4 substrate on E. coli was more effective than that observed on the biomedical Ti6Al4V alloy. Conversely, no lysis but bacterial proliferation was recorded for E. coli exposed to ZTA bioceramic oxide substrates.
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Affiliation(s)
- Francesco Boschetto
- Ceramic Physics Laboratory, Kyoto Institute of Technology, Sakyo-ku, Matsugasaki, 606-8585 Kyoto, Japan; Department of Immunology, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan
| | - Tetsuya Adachi
- Department of Dental Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan
| | - Satoshi Horiguchi
- Department of Dental Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan
| | - Elia Marin
- Ceramic Physics Laboratory, Kyoto Institute of Technology, Sakyo-ku, Matsugasaki, 606-8585 Kyoto, Japan; Department of Dental Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan
| | - Niccolò Paccotti
- Department of Applied Science and Technology, Politecnico di Torino, C.so Duca degli Abruzzi 24, 10129 Turin, Italy
| | - Tenma Asai
- Ceramic Physics Laboratory, Kyoto Institute of Technology, Sakyo-ku, Matsugasaki, 606-8585 Kyoto, Japan
| | - Wenliang Zhu
- Ceramic Physics Laboratory, Kyoto Institute of Technology, Sakyo-ku, Matsugasaki, 606-8585 Kyoto, Japan
| | - Bryan J McEntire
- SINTX, Technologies, Co. 1885 West 2100 South, Salt Lake City, UT 84119, USA
| | - Toshiro Yamamoto
- Department of Dental Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan
| | - Narisato Kanamura
- Department of Dental Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan
| | - Osam Mazda
- Department of Immunology, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan
| | - Eriko Ohgitani
- Department of Immunology, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan
| | - Giuseppe Pezzotti
- Ceramic Physics Laboratory, Kyoto Institute of Technology, Sakyo-ku, Matsugasaki, 606-8585 Kyoto, Japan; Department of Immunology, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan; Department of Orthopedic Surgery, Tokyo Medical University, 6-7-1 Nishi-Shinjuku, Shinjuku-ku, 160-0023 Tokyo, Japan; The Center for Advanced Medical Engineering and Informatics, Osaka University, Yamadaoka, Suita, 565-0871 Osaka, Japan.
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83
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Liu X, Zhou L, Shi X, Xu G. New advances in analytical methods for mass spectrometry-based large-scale metabolomics study. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2019.115665] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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84
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Lempp M, Farke N, Kuntz M, Freibert SA, Lill R, Link H. Systematic identification of metabolites controlling gene expression in E. coli. Nat Commun 2019; 10:4463. [PMID: 31578326 PMCID: PMC6775132 DOI: 10.1038/s41467-019-12474-1] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 09/11/2019] [Indexed: 01/07/2023] Open
Abstract
Metabolism controls gene expression through allosteric interactions between metabolites and transcription factors. These interactions are usually measured with in vitro assays, but there are no methods to identify them at a genome-scale in vivo. Here we show that dynamic transcriptome and metabolome data identify metabolites that control transcription factors in E. coli. By switching an E. coli culture between starvation and growth, we induce strong metabolite concentration changes and gene expression changes. Using Network Component Analysis we calculate the activities of 209 transcriptional regulators and correlate them with metabolites. This approach captures, for instance, the in vivo kinetics of CRP regulation by cyclic-AMP. By testing correlations between all pairs of transcription factors and metabolites, we predict putative effectors of 71 transcription factors, and validate five interactions in vitro. These results show that combining transcriptomics and metabolomics generates hypotheses about metabolism-transcription interactions that drive transitions between physiological states. Interactions between metabolites and transcription factors are known to control gene expression but analyzing these events at genome-scale is challenging. Here, the authors integrate dynamic metabolome and transcriptome data from E.coli to predict regulatory metabolite-transcription factor interactions.
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Affiliation(s)
- Martin Lempp
- Max Planck Institute for Terrestrial Microbiology, Marburg, 35043, Germany
| | - Niklas Farke
- Max Planck Institute for Terrestrial Microbiology, Marburg, 35043, Germany
| | - Michelle Kuntz
- Max Planck Institute for Terrestrial Microbiology, Marburg, 35043, Germany
| | - Sven Andreas Freibert
- Institut für Zytobiologie und Zytopathologie, Philipps-Universität Marburg, 35033, Marburg, Germany
| | - Roland Lill
- Institut für Zytobiologie und Zytopathologie, Philipps-Universität Marburg, 35033, Marburg, Germany.,LOEWE Zentrum für Synthetische Mikrobiologie SYNMIKRO, Philipps-Universität Marburg, 35032, Marburg, Germany
| | - Hannes Link
- Max Planck Institute for Terrestrial Microbiology, Marburg, 35043, Germany. .,LOEWE Zentrum für Synthetische Mikrobiologie SYNMIKRO, Philipps-Universität Marburg, 35032, Marburg, Germany.
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85
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Microfluidic Irreversible Electroporation-A Versatile Tool to Extract Intracellular Contents of Bacteria and Yeast. Metabolites 2019; 9:metabo9100211. [PMID: 31574935 PMCID: PMC6835232 DOI: 10.3390/metabo9100211] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Revised: 09/25/2019] [Accepted: 09/27/2019] [Indexed: 02/06/2023] Open
Abstract
Exploring the dynamic behavior of cellular metabolism requires a standard laboratory method that guarantees rapid sampling and extraction of the cellular content. We propose a versatile sampling technique applicable to cells with different cell wall and cell membrane properties. The technique is based on irreversible electroporation with simultaneous quenching and extraction by using a microfluidic device. By application of electric pulses in the millisecond range, permanent lethal pores are formed in the cell membrane of Escherichia coli and Saccharomyces cerevisiae, facilitating the release of the cellular contents; here demonstrated by the measurement of glucose-6-phosphate and the activity of the enzyme glucose-6-phosphate dehydrogenase. The successful application of this device was demonstrated by pulsed electric field treatment in a flow-through configuration of the microfluidic chip in combination with sampling, inactivation, and extraction of the intracellular content in a few seconds. Minimum electric field strengths of 10 kV/cm for E. coli and 7.5 kV/cm for yeast S. cerevisiae were required for successful cell lysis. The results are discussed in the context of applications in industrial biotechnology, where metabolomics analyses are important.
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86
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Sun Z, Ji Q, Evans AR, Lewis MJ, Mo J, Hu P. High-throughput LC-MS quantitation of cell culture metabolites. Biologicals 2019; 61:44-51. [DOI: 10.1016/j.biologicals.2019.07.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 07/29/2019] [Indexed: 10/26/2022] Open
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87
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Stokes JM, Lopatkin AJ, Lobritz MA, Collins JJ. Bacterial Metabolism and Antibiotic Efficacy. Cell Metab 2019; 30:251-259. [PMID: 31279676 PMCID: PMC6990394 DOI: 10.1016/j.cmet.2019.06.009] [Citation(s) in RCA: 289] [Impact Index Per Article: 57.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 06/06/2019] [Accepted: 06/10/2019] [Indexed: 02/07/2023]
Abstract
Antibiotics target energy-consuming processes. As such, perturbations to bacterial metabolic homeostasis are significant consequences of treatment. Here, we describe three postulates that collectively define antibiotic efficacy in the context of bacterial metabolism: (1) antibiotics alter the metabolic state of bacteria, which contributes to the resulting death or stasis; (2) the metabolic state of bacteria influences their susceptibility to antibiotics; and (3) antibiotic efficacy can be enhanced by altering the metabolic state of bacteria. Altogether, we aim to emphasize the close relationship between bacterial metabolism and antibiotic efficacy as well as propose areas of exploration to develop novel antibiotics that optimally exploit bacterial metabolic networks.
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Affiliation(s)
- Jonathan M Stokes
- Institute for Medical Engineering & Science, Department of Biological Engineering, and Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Infectious Disease & Microbiome Program, Broad Institute of MIT & Harvard, Cambridge, MA 02142, USA; Machine Learning for Pharmaceutical Discovery and Synthesis Consortium, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Allison J Lopatkin
- Institute for Medical Engineering & Science, Department of Biological Engineering, and Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Infectious Disease & Microbiome Program, Broad Institute of MIT & Harvard, Cambridge, MA 02142, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA
| | - Michael A Lobritz
- Roche Pharma Research and Early Development, Roche Innovation Center Basel, 4070 Basel, Switzerland
| | - James J Collins
- Institute for Medical Engineering & Science, Department of Biological Engineering, and Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Infectious Disease & Microbiome Program, Broad Institute of MIT & Harvard, Cambridge, MA 02142, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA; Harvard-MIT Program in Health Sciences and Technology, Cambridge, MA 02139, USA.
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88
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Zampieri M, Hörl M, Hotz F, Müller NF, Sauer U. Regulatory mechanisms underlying coordination of amino acid and glucose catabolism in Escherichia coli. Nat Commun 2019; 10:3354. [PMID: 31350417 PMCID: PMC6659692 DOI: 10.1038/s41467-019-11331-5] [Citation(s) in RCA: 74] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Accepted: 07/05/2019] [Indexed: 02/06/2023] Open
Abstract
How microbes dynamically coordinate uptake and simultaneous utilization of nutrients in complex nutritional ecosystems is still an open question. Here, we develop a constraint-based modeling approach that exploits non-targeted exo-metabolomics data to unravel adaptive decision-making processes in dynamic nutritional environments. We thereby investigate metabolic adaptation of Escherichia coli to continuously changing conditions during batch growth in complex medium. Unexpectedly, model-based analysis of time resolved exo-metabolome data revealed that fastest growth coincides with preferred catabolism of amino acids, which, in turn, reduces glucose uptake and increases acetate overflow. We show that high intracellular levels of the amino acid degradation metabolites pyruvate and oxaloacetate can directly inhibit the phosphotransferase system (PTS), and reveal their functional role in mediating regulatory decisions for uptake and catabolism of alternative carbon sources. Overall, the proposed methodology expands the spectrum of possible applications of flux balance analysis to decipher metabolic adaptation mechanisms in naturally occurring habitats and diverse organisms.
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Affiliation(s)
- Mattia Zampieri
- Institute of Molecular Systems Biology, ETH Zürich, Zürich, 8093, Switzerland.
| | - Manuel Hörl
- Institute of Molecular Systems Biology, ETH Zürich, Zürich, 8093, Switzerland
| | - Florian Hotz
- Institute of Molecular Systems Biology, ETH Zürich, Zürich, 8093, Switzerland
| | - Nicola F Müller
- Institute of Molecular Systems Biology, ETH Zürich, Zürich, 8093, Switzerland
| | - Uwe Sauer
- Institute of Molecular Systems Biology, ETH Zürich, Zürich, 8093, Switzerland.
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89
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Schink SJ, Biselli E, Ammar C, Gerland U. Death Rate of E. coli during Starvation Is Set by Maintenance Cost and Biomass Recycling. Cell Syst 2019; 9:64-73.e3. [DOI: 10.1016/j.cels.2019.06.003] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Revised: 04/09/2019] [Accepted: 06/06/2019] [Indexed: 11/16/2022]
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90
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Dynamic 13C Labeling of Fast Turnover Metabolites for Analysis of Metabolic Fluxes and Metabolite Channeling. Methods Mol Biol 2019; 1859:301-316. [PMID: 30421238 DOI: 10.1007/978-1-4939-8757-3_18] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
Abstract
Dynamic or isotopically nonstationary 13C labeling experiments are a powerful tool not only for precise carbon flux quantification (e.g., metabolic flux analysis of photoautotrophic organisms) but also for the investigation of pathway bottlenecks, a cell's phenotype, and metabolite channeling. In general, isotopically nonstationary metabolic flux analysis requires three main components: (1) transient isotopic labeling experiments; (2) metabolite quenching and isotopomer analysis using LC-MS; (3) metabolic network construction and flux quantification. Labeling dynamics of key metabolites from 13C-pulse experiments allow flux estimation of key central pathways by solving ordinary differential equations to fit time-dependent isotopomer distribution data. Additionally, it is important to provide biomass requirements, carbon uptake rates, specific growth rates, and carbon excretion rates to properly and precisely balance the metabolic network. Labeling dynamics through cascade metabolites may also identify channeling phenomena in which metabolites are passed between enzymes without mixing with the bulk phase. In this chapter, we outline experimental protocols to probe metabolic pathways through dynamic labeling. We describe protocols for labeling experiments, metabolite quenching and extraction, LC-MS analysis, computational flux quantification, and metabolite channeling observations.
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91
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Wang G, Chu J, Zhuang Y, van Gulik W, Noorman H. A dynamic model-based preparation of uniformly-13C-labeled internal standards facilitates quantitative metabolomics analysis of Penicillium chrysogenum. J Biotechnol 2019; 299:21-31. [DOI: 10.1016/j.jbiotec.2019.04.021] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Revised: 04/03/2019] [Accepted: 04/25/2019] [Indexed: 01/03/2023]
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92
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Koendjbiharie JG, Wevers K, van Kranenburg R. Assessing Cofactor Usage in Pseudoclostridium thermosuccinogenes via Heterologous Expression of Central Metabolic Enzymes. Front Microbiol 2019; 10:1162. [PMID: 31178853 PMCID: PMC6543838 DOI: 10.3389/fmicb.2019.01162] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Accepted: 05/07/2019] [Indexed: 11/13/2022] Open
Abstract
Pseudoclostridium thermosuccinogenes and Hungateiclostridium thermocellum are being studied for their potential to contribute to a more sustainable bio-based economy. Both species were shown previously to rely on GTP or pyrophosphate instead of ATP as cofactors in specific reactions of central energy metabolism for reasons that are not well understood yet. Since it is often impossible to predict cofactor specificity from the primary protein structure, thirteen enzymes from P. thermosuccinogenes were cloned and heterologous expressed in Escherichia coli to assess the cofactor usage in vitro and paint a more complete picture of the cofactor usage in the central metabolism of P. thermosuccinogenes. The assays were conducted with heat-treated E. coli cell-free extract devoid of background activity to allow the quick assessment of a relatively large number of (thermophilic) enzymes. Selected enzymes were also purified to allow the determination of the enzyme kinetics for competing cofactors. Following the results of the glucokinase (GK), galactokinase, xylulokinase (XK), and ribokinase assays, it seems that phosphorylation of monosaccharides by and large is mainly GTP-dependent. Some possible implications of this relating to the adenylate/guanylate energy charge are discussed here. Besides the highly expressed pyrophosphate-dependent 6-phosphofructokinase, another 6-phosphofructokinase was found to be equally dependent on ATP and GTP, while no 6-phosphofructokinase activity could be demonstrated for a third. Both type I glyceraldehyde 3-phosphate dehydrogenases were found to be NAD+-dependent, and further, acetate kinase, isocitrate dehydrogenase, and three enzymes predicted to be responsible for the interconversion of phosphoenolpyruvate and pyruvate (i.e., pyruvate kinase; pyruvate, phosphate dikinase; phosphoenolpyruvate synthase), were also assessed.
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Affiliation(s)
| | - Kimberly Wevers
- Laboratory of Microbiology, Wageningen University & Research, Wageningen, Netherlands
| | - Richard van Kranenburg
- Corbion, Gorinchem, Netherlands
- Laboratory of Microbiology, Wageningen University & Research, Wageningen, Netherlands
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93
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Judge MT, Wu Y, Tayyari F, Hattori A, Glushka J, Ito T, Arnold J, Edison AS. Continuous in vivo Metabolism by NMR. Front Mol Biosci 2019; 6:26. [PMID: 31114791 PMCID: PMC6502900 DOI: 10.3389/fmolb.2019.00026] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2019] [Accepted: 04/04/2019] [Indexed: 01/10/2023] Open
Abstract
Dense time-series metabolomics data are essential for unraveling the underlying dynamic properties of metabolism. Here we extend high-resolution-magic angle spinning (HR-MAS) to enable continuous in vivo monitoring of metabolism by NMR (CIVM-NMR) and provide analysis tools for these data. First, we reproduced a result in human chronic lymphoid leukemia cells by using isotope-edited CIVM-NMR to rapidly and unambiguously demonstrate unidirectional flux in branched-chain amino acid metabolism. We then collected untargeted CIVM-NMR datasets for Neurospora crassa, a classic multicellular model organism, and uncovered dynamics between central carbon metabolism, amino acid metabolism, energy storage molecules, and lipid and cell wall precursors. Virtually no sample preparation was required to yield a dynamic metabolic fingerprint over hours to days at ~4-min temporal resolution with little noise. CIVM-NMR is simple and readily adapted to different types of cells and microorganisms, offering an experimental complement to kinetic models of metabolism for diverse biological systems.
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Affiliation(s)
- Michael T. Judge
- Department of Genetics, University of Georgia, Athens, GA, United States
| | - Yue Wu
- Institute of Bioinformatics, University of Georgia, Athens, GA, United States
| | - Fariba Tayyari
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA, United States
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA, United States
| | - Ayuna Hattori
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA, United States
- Division of Hematological Malignancy, National Cancer Center Research Institute, Tokyo, Japan
| | - John Glushka
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA, United States
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA, United States
| | - Takahiro Ito
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA, United States
| | - Jonathan Arnold
- Department of Genetics, University of Georgia, Athens, GA, United States
- Institute of Bioinformatics, University of Georgia, Athens, GA, United States
| | - Arthur S. Edison
- Department of Genetics, University of Georgia, Athens, GA, United States
- Institute of Bioinformatics, University of Georgia, Athens, GA, United States
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA, United States
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA, United States
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94
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Zhang YE, Bærentsen RL, Fuhrer T, Sauer U, Gerdes K, Brodersen DE. (p)ppGpp Regulates a Bacterial Nucleosidase by an Allosteric Two-Domain Switch. Mol Cell 2019; 74:1239-1249.e4. [PMID: 31023582 DOI: 10.1016/j.molcel.2019.03.035] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 03/07/2019] [Accepted: 03/27/2019] [Indexed: 01/17/2023]
Abstract
The stringent response alarmones pppGpp and ppGpp are essential for rapid adaption of bacterial physiology to changes in the environment. In Escherichia coli, the nucleosidase PpnN (YgdH) regulates purine homeostasis by cleaving nucleoside monophosphates and specifically binds (p)ppGpp. Here, we show that (p)ppGpp stimulates the catalytic activity of PpnN both in vitro and in vivo causing accumulation of several types of nucleobases during stress. The structure of PpnN reveals a tetramer with allosteric (p)ppGpp binding sites located between subunits. pppGpp binding triggers a large conformational change that shifts the two terminal domains to expose the active site, providing a structural rationale for the stimulatory effect. We find that PpnN increases fitness and adjusts cellular tolerance to antibiotics and propose a model in which nucleotide levels can rapidly be adjusted during stress by simultaneous inhibition of biosynthesis and stimulation of degradation, thus achieving a balanced physiological response to constantly changing environments.
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Affiliation(s)
- Yong Everett Zhang
- Department of Biology, Centre of Excellence for Bacterial Stress Response and Persistence (BASP), University of Copenhagen, 2200 Copenhagen, Denmark.
| | - René Lysdal Bærentsen
- Department of Molecular Biology and Genetics, Centre of Excellence for Bacterial Stress Response and Persistence (BASP), Aarhus University, 8000 Aarhus C, Denmark
| | - Tobias Fuhrer
- Department of Biology, Institute of Molecular Systems Biology, ETH, Zurich, Switzerland
| | - Uwe Sauer
- Department of Biology, Institute of Molecular Systems Biology, ETH, Zurich, Switzerland
| | - Kenn Gerdes
- Department of Biology, Centre of Excellence for Bacterial Stress Response and Persistence (BASP), University of Copenhagen, 2200 Copenhagen, Denmark
| | - Ditlev Egeskov Brodersen
- Department of Molecular Biology and Genetics, Centre of Excellence for Bacterial Stress Response and Persistence (BASP), Aarhus University, 8000 Aarhus C, Denmark.
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95
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Very rapid flow cytometric assessment of antimicrobial susceptibility during the apparent lag phase of microbial (re)growth. Microbiology (Reading) 2019; 165:439-454. [DOI: 10.1099/mic.0.000777] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
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96
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Jang C, Chen L, Rabinowitz JD. Metabolomics and Isotope Tracing. Cell 2019; 173:822-837. [PMID: 29727671 DOI: 10.1016/j.cell.2018.03.055] [Citation(s) in RCA: 467] [Impact Index Per Article: 93.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Revised: 02/21/2018] [Accepted: 03/21/2018] [Indexed: 12/15/2022]
Abstract
Great strides have been made over the past decade toward comprehensive study of metabolism. Mass spectrometry (MS) has played a central role by enabling measurement of many metabolites simultaneously. Tracking metabolite labeling from stable isotope tracers can in addition reveal pathway activities. Here, we describe the basics of metabolite measurement by MS, including sample preparation, metabolomic analysis, and data interpretation. In addition, drawing on examples of successful experiments, we highlight the ways in which metabolomics and isotope tracing can illuminate biology.
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Affiliation(s)
- Cholsoon Jang
- Lewis Sigler Institute for Integrative Genomics and Department of Chemistry, Princeton University, Washington Rd, Princeton, NJ 08544, USA
| | - Li Chen
- Lewis Sigler Institute for Integrative Genomics and Department of Chemistry, Princeton University, Washington Rd, Princeton, NJ 08544, USA
| | - Joshua D Rabinowitz
- Lewis Sigler Institute for Integrative Genomics and Department of Chemistry, Princeton University, Washington Rd, Princeton, NJ 08544, USA.
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97
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In plaque-mass spectrometry imaging of a bloom-forming alga during viral infection reveals a metabolic shift towards odd-chain fatty acid lipids. Nat Microbiol 2019; 4:527-538. [PMID: 30718847 PMCID: PMC6420086 DOI: 10.1038/s41564-018-0336-y] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2018] [Accepted: 12/04/2018] [Indexed: 01/02/2023]
Abstract
Tapping into the metabolic cross-talk between a host and its virus can reveal unique strategies employed during infection. Viral infection is a dynamic process that generates an evolving metabolic landscape. Gaining a continuous view into the infection process is highly challenging and is limited by current metabolomics approaches, which typically measure the average of the entire population at various stages of infection. Here, we took an innovative approach to study the metabolic basis of host-virus interactions between the bloom-forming alga Emiliania huxleyi and its specific virus. We combined a classical method in virology, the plaque assay, with advanced mass spectrometry imaging (MSI), an approach we termed ‘in plaque-MSI’. Taking advantage of the spatial characteristics of the plaque, we mapped the metabolic landscape induced during infection in a high spatiotemporal resolution, unfolding the infection process in a continuous manner. Further unsupervised spatially-aware clustering, combined with known lipid biomarkers, revealed a systematic metabolic shift during infection towards lipids containing the odd-chain fatty acid pentadecanoic acid (C15:0). Applying ‘in plaque-MSI’ might facilitate the discovery of bioactive compounds that mediate the chemical arms race of host-virus interactions in diverse model systems.
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98
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Baidoo EEK, Teixeira Benites V. Mass Spectrometry-Based Microbial Metabolomics: Techniques, Analysis, and Applications. Methods Mol Biol 2019; 1859:11-69. [PMID: 30421222 DOI: 10.1007/978-1-4939-8757-3_2] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
The demand for understanding the roles genes play in biological systems has steered the biosciences into the direction the metabolome, as it closely reflects the metabolic activities within a cell. The importance of the metabolome is further highlighted by its ability to influence the genome, transcriptome, and proteome. Consequently, metabolomic information is being used to understand microbial metabolic networks. At the forefront of this work is mass spectrometry, the most popular metabolomics measurement technique. Mass spectrometry-based metabolomic analyses have made significant contributions to microbiological research in the environment and human disease. In this chapter, we break down the technical aspects of mass spectrometry-based metabolomics and discuss its application to microbiological research.
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Affiliation(s)
- Edward E K Baidoo
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA.
- Joint BioEnergy Institute, Emeryville, California, USA.
| | - Veronica Teixeira Benites
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
- Joint BioEnergy Institute, Emeryville, California, USA
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99
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Allard PM, Bisson J, Azzollini A, Pauli GF, Cordell GA, Wolfender JL. Pharmacognosy in the digital era: shifting to contextualized metabolomics. Curr Opin Biotechnol 2018; 54:57-64. [PMID: 29499476 PMCID: PMC6110999 DOI: 10.1016/j.copbio.2018.02.010] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Revised: 01/26/2018] [Accepted: 02/13/2018] [Indexed: 01/01/2023]
Abstract
Humans have co-evolved alongside numerous other organisms, some having a profound effect on health and nutrition. As the earliest pharmaceutical subject, pharmacognosy has evolved into a meta-discipline devoted to natural biomedical agents and their functional properties. While the acquisition of expanding data volumes is ongoing, contextualization is lagging. Thus, we assert that the establishment of an integrated and open databases ecosystem will nurture the discipline. After proposing an epistemological framework of knowledge acquisition in pharmacognosy, this study focuses on recent computational and analytical approaches. It then elaborates on the flux of research data, where good practices could foster the implementation of more integrated systems, which will in turn help shaping the future of pharmacognosy and determine its constitutional societal relevance.
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Affiliation(s)
- Pierre-Marie Allard
- School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Rue Michel-Servet 1, CH-1211 Geneva 4, Switzerland.
| | - Jonathan Bisson
- Center for Natural Product Technologies, Program for Collaborative Research in the Pharmaceutical Sciences (PCRPS), and Department of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, University of Illinois at Chicago, 833 South Wood Street, Chicago, IL 60612, United States
| | - Antonio Azzollini
- School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Rue Michel-Servet 1, CH-1211 Geneva 4, Switzerland
| | - Guido F Pauli
- Center for Natural Product Technologies, Program for Collaborative Research in the Pharmaceutical Sciences (PCRPS), and Department of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, University of Illinois at Chicago, 833 South Wood Street, Chicago, IL 60612, United States
| | - Geoffrey A Cordell
- Natural Products Inc., Evanston, IL 60203, United States; Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, FL 32610, United States
| | - Jean-Luc Wolfender
- School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Rue Michel-Servet 1, CH-1211 Geneva 4, Switzerland
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100
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Hollywood KA, Schmidt K, Takano E, Breitling R. Metabolomics tools for the synthetic biology of natural products. Curr Opin Biotechnol 2018; 54:114-120. [DOI: 10.1016/j.copbio.2018.02.015] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Revised: 02/22/2018] [Accepted: 02/27/2018] [Indexed: 12/15/2022]
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