German Preciat

Leiden University

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Ronan M. T. Fleming

Ollscoil na Gaillimhe – University of Galway

Ines Thiele

Ollscoil na Gaillimhe – University of Galway

Almut Heinken

Ollscoil na Gaillimhe – University of Galway

Hulda S. Haraldsdóttir

Leiden University

Dalia Marcela Lewi

National Agricultural Technology Institute

Cecilia Andrea Décima Oneto

National University of Mar del Plata

Alberto Noronha

University of Luxembourg

Stefanía Magnúsdóttir

Helmholtz Centre for Environmental Research

Jennifer Modamio

Helmholtz Zentrum München

Thomas Hankemeier

Leiden University

Cooperative Institutions

University of Luxembourg

National Agricultural Technology Institute

University of California, San Diego

Ollscoil na Gaillimhe – University of Galway

Leiden University

Luxembourg Institute of Health

La Jolla Bioengineering Institute

Instituto Nacional de Tecnologia

Instituto de Genética Veterinaria

Centre for Human Drug Research

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Biolistic maize transformation: Improving and simplifying the protocol efficiency

African Journal of Agricultural Research (2010)

Cecilia Andrea Décima Oneto German Preciat Dalia Marcela Lewi

Two decades have passed since the first maize transformation protocol. Genetic breeding has been decisive and essential to transform maize a major food crop worldwide. Biotechnology plays an important role in plant genetic breeding, particularly for the introduction of novel traits in order to improve agronomic performance, medical and industrial applications and food quality. In recent years, the development of efficient plant regeneration systems in cereal crops and the field of biotechnology have opened up new opportunities for genetic transformation of crop plants. Some monocot plants were initially considered difficult for genetic engineering, primarily due to their recalcitrance to in vitro regeneration and their resistance to Agrobacterium. Continuous efforts and studies of different tissues for regeneration potential, development of various DNA delivery methods, and optimization of gene expression cassettes have led to the development of reliable transformation protocols for major cereals, including maize. Consequently, this research group has focused its attention on maize transformation mediated by microprojectile bombardment as a device of DNA delivery into maize cells. This method offers a rapid and simple way of introgression of candidate genes into cells. However, there are some points that still need to be studied and improved in order to achieve appropriate transformation efficiency to optimize the processing conditions to obtain fertile plants. Key words: Biolistic, transient expression, reporter genes, plant genetic improvement.

Introgression

Molecular breeding

10.5897/ajar10.023

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Citations (15)

Conserved moiety fluxomics

bioRxiv (Cold Spring Harbor Laboratory) (2024)

Ronan M. T. Fleming Hulda S. Haraldsdóttir German Preciat Luojiao Huang Ines Thiele

Fluxomics seeks to infer reaction fluxes at genome-scale by introducing isotopically labelled metabolites into a living system and measuring the enrichment of isotopic tracers in downstream metabolites. This approach has the potential to quantify fluxes at genome-scale but current approaches to infer steady-state metabolic reaction fluxes are either not tractable or not efficient at genome-scale as the corresponding computational models are high-dimensional, involve nonlinear constraints and lack mathematical guarantees of convergence to a global optimum. Herein, we introduce conserved moiety fluxomics, which is a novel, efficient, mathematically transparent, and computationally efficient method to infer metabolic reaction flux at genome-scale. We demonstrate how identification of the set of conserved moieties for a given metabolic network leads to a novel moiety graph decomposition of a stoichiometric matrix that can be used to linearly relate metabolic reaction fluxes to the rate at which conserved moieties transition between metabolites. This linear formulation avoids combinatorial explosion because the number of conserved moieties is bounded, most reactions correspond to a small number of conserved moiety transitions, it is sufficient to represent the flow of moieties that have the potential to be labelled, and it is sufficient to represent constraints from those isotopologues that are actually measured. A non-linear yet strictly convex objective is used to ensure that inferred fluxes satisfy energy conservation and the second law of thermodynamics. Numerical results demonstrate the computational tractability of conserved moiety fluxomics at genome-scale, given liquid chromatography-mass spectrometry derived stationary mass isotopologue distribution data from an in vitro dopaminergic neuronal culture fed 13 C labelled glucose. Conserved moiety fluxomics unites the strengths of constraint-based modelling and metabolic flux analysis and has the potential to be further enhanced to enable inference of fluxes in whole-body metabolic models, including from non-stationary isotopic labelling data.

Moiety

Isotopologue

Metabolic flux analysis

10.1101/2024.11.21.624666

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The connectome is necessary but not sufficient for the spread of alpha-synuclein pathology in rats

bioRxiv (Cold Spring Harbor Laboratory) (2019)

Miguel A. P. Oliveira Sylvain Arreckx Donato A. Di Monte German Preciat Ayşe Ulusoy

Abstract Certain neuronal populations are selectively vulnerable to alpha -synuclein pathology in Parkinson’s Disease, yet the reasons for this selectivity are unclear. Pathology affects neuronal populations that are anatomically connected although the contribution of neuronal connectivity remains to be quantitatively explored. Herein, we simulate the contribution of the connectome alone to the spread of arbitrary aggregates using a computational model of temporal spread within an abstract representation of the mouse mesoscale connectome. Our simulations are compared with the neuron-to-neuron spread of alpha -synuclein that has been observed with in vivo spreading experiments in rats. We find that neuronal connectivity appears to be compatible with the spreading pattern of alpha -synuclein pathology however, it may be per se insufficient to determine the anatomical pattern of protein spreading observed in experimental animals, suggesting a role of selective vulnerability of neuronal pathways to alpha -synuclein diffusion, accumulation and pathology. Graphical abstract

Alpha (finance)

Representation

10.1101/567222

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Citations (3)

Mechanistic model-driven exometabolomic characterisation of human dopaminergic neuronal metabolism

bioRxiv (Cold Spring Harbor Laboratory) (2021)

German Preciat Agnieszka B. Wegrzyn Edinson Lucumi Moreno Cornelius C.W. Willacey Jennifer Modamio

Abstract Starting with a comprehensive generic reconstruction of human metabolism, we generated high-quality, constraint-based, genome-scale, cell-type and condition specific models of metabolism in human dopaminergic neurons, the cell type most vulnerable to degeneration in Parkinson ’ s disease. They are a synthesis of extensive manual curation of the biochemical literature on neuronal metabolism, together with novel, quantitative, transcriptomic and targeted exometabolomic data from human stem cell-derived, midbrainspecific, dopaminergic neurons in vitro . Thermodynamic constraint-based modelling enabled qualitatively accurate and moderately quantitatively accurate prediction of dopaminergic neuronal metabolite exchange fluxes, including predicting the consequences of metabolic perturbations in a manner also consistent with literature on monogenic mitochondrial Parkinson ’ s disease. These dopaminergic neurons models provide a foundation for a quantitative systems biochemistry approach to metabolic dysfunction in Parkinson ’ s disease. Moreover, the plethora of novel mathematical and computational approaches required to develop them are generalisable to study any other disease associated with metabolic dysfunction.

Cell metabolism

10.1101/2021.06.30.450562

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Citations (6)

Omics data integration suggests a potential idiopathic Parkinson’s disease signature

Communications Biology (2023)

Alise Žagare German Preciat Sarah L. Nickels Xi Luo Anna S. Monzel

The vast majority of Parkinson's disease cases are idiopathic. Unclear etiology and multifactorial nature complicate the comprehension of disease pathogenesis. Identification of early transcriptomic and metabolic alterations consistent across different idiopathic Parkinson's disease (IPD) patients might reveal the potential basis of increased dopaminergic neuron vulnerability and primary disease mechanisms. In this study, we combine systems biology and data integration approaches to identify differences in transcriptomic and metabolic signatures between IPD patient and healthy individual-derived midbrain neural precursor cells. Characterization of gene expression and metabolic modeling reveal pyruvate, several amino acid and lipid metabolism as the most dysregulated metabolic pathways in IPD neural precursors. Furthermore, we show that IPD neural precursors endure mitochondrial metabolism impairment and a reduced total NAD pool. Accordingly, we show that treatment with NAD precursors increases ATP yield hence demonstrating a potential to rescue early IPD-associated metabolic changes.

Pathogenesis

10.1038/s42003-023-05548-w

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Citations (10)

XomicsToModel: Omics data integration and generation of thermodynamically consistent metabolic models

bioRxiv (Cold Spring Harbor Laboratory) (2021)

German Preciat Agnieszka B. Wegrzyn Ines Thiele Thomas Hankemeier Ronan M. T. Fleming

Abstract Constraint-based modelling can mechanistically simulate the behaviour of a biochemical system, permitting hypotheses generation, experimental design and interpretation of experimental data, with numerous applications, including modelling of metabolism. Given a generic model, several methods have been developed to extract a context-specific, genome-scale metabolic model by incorporating information used to identify metabolic processes and gene activities in a given context. However, existing model extraction algorithms are unable to ensure that the context-specific model is thermodynamically feasible. This protocol introduces XomicsToModel , a semi-automated pipeline that integrates bibliomic, transcriptomic, proteomic, and metabolomic data with a generic genome-scale metabolic reconstruction, or model, to extract a context-specific, genome-scale metabolic model that is stoichiometrically, thermodynamically and flux consistent. The XomicsToModel pipeline is exemplified for extraction of a specific metabolic model from a generic metabolic model, but it enables omics data integration and extraction of physicochemically consistent mechanistic models from any generic biochemical network. With all input data fully prepared, algorithmic completion of the pipeline takes ~10 min, however manual review of intermediate results may also be required, e.g., when inconsistent input data lead to an infeasible model.

Metabolic network

Flux Balance Analysis

Experimental data

10.1101/2021.11.08.467803

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Citations (6)

The Virtual Metabolic Human database: integrating human and gut microbiome metabolism with nutrition and disease

Nucleic Acids Research (2018)

Alberto Noronha Jennifer Modamio Yohan Jarosz Elisabeth Guerard Nicolas Sompairac

A multitude of factors contribute to complex diseases and can be measured with 'omics' methods. Databases facilitate data interpretation for underlying mechanisms. Here, we describe the Virtual Metabolic Human (VMH, www.vmh.life) database encapsulating current knowledge of human metabolism within five interlinked resources 'Human metabolism', 'Gut microbiome', 'Disease', 'Nutrition', and 'ReconMaps'. The VMH captures 5180 unique metabolites, 17 730 unique reactions, 3695 human genes, 255 Mendelian diseases, 818 microbes, 632 685 microbial genes and 8790 food items. The VMH's unique features are (i) the hosting of the metabolic reconstructions of human and gut microbes amenable for metabolic modeling; (ii) seven human metabolic maps for data visualization; (iii) a nutrition designer; (iv) a user-friendly webpage and application-programming interface to access its content; (v) user feedback option for community engagement and (vi) the connection of its entities to 57 other web resources. The VMH represents a novel, interdisciplinary database for data interpretation and hypothesis generation to the biomedical community.

Human Microbiome Project

Human disease

10.1093/nar/gky992

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Citations (320)

Stress-induced expression of IPT gene in transgenic wheat reduces grain yield penalty under drought

Journal of Genetic Engineering and Biotechnology (2021)

Ailin Beznec Paula Faccio Daniel J. Miralles L. Gabriela Abeledo Cecilia Andrea Décima Oneto

The heterologous expression of isopentenyl transferase (IPT) under the transcriptional control of the senescence-associated receptor-like kinase (SARK) promoter delayed cellular senescence and, through it, increased drought tolerance in plants. To evaluate the effect of pSARK::IPT expression in bread wheat, six independent transgenic events were obtained through the biolistic method and evaluated transgene expression, phenology, grain yield and physiological biomass components in plants grown under both drought and well-irrigating conditions. Experiments were performed at different levels: (i) pots and (ii) microplots inside a biosafety greenhouse, as well as under (iii) field conditions. Two transgenic events, called TR1 and TR4, outperformed the wild-type control under drought conditions. Transgenic plants showed higher yield under both greenhouse and field conditions, which was positively correlated to grain number (given by more spikes and grains per spike) than wild type. Interestingly, this yield advantage of the transgenic events was observed under both drought and well-watered conditions. The results obtained allow us to conclude that the SARK promoter-regulated expression of the IPT gene in bread wheat not only reduced the yield penalty produced by water stress but also led to improved productivity under well-watered conditions.

Drought stress

10.1186/s43141-021-00171-w

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Citations (17)

Genome-scale metabolic reconstruction of 7,302 human microorganisms for personalized medicine

Nature Biotechnology (2023)

Almut Heinken Johannes Hertel Geeta Acharya Dmitry A. Ravcheev Malgorzata Nyga

The human microbiome influences the efficacy and safety of a wide variety of commonly prescribed drugs. Designing precision medicine approaches that incorporate microbial metabolism would require strain- and molecule-resolved, scalable computational modeling. Here, we extend our previous resource of genome-scale metabolic reconstructions of human gut microorganisms with a greatly expanded version. AGORA2 (assembly of gut organisms through reconstruction and analysis, version 2) accounts for 7,302 strains, includes strain-resolved drug degradation and biotransformation capabilities for 98 drugs, and was extensively curated based on comparative genomics and literature searches. The microbial reconstructions performed very well against three independently assembled experimental datasets with an accuracy of 0.72 to 0.84, surpassing other reconstruction resources and predicted known microbial drug transformations with an accuracy of 0.81. We demonstrate that AGORA2 enables personalized, strain-resolved modeling by predicting the drug conversion potential of the gut microbiomes from 616 patients with colorectal cancer and controls, which greatly varied between individuals and correlated with age, sex, body mass index and disease stages. AGORA2 serves as a knowledge base for the human microbiome and paves the way to personalized, predictive analysis of host-microbiome metabolic interactions.

Personalized Medicine

10.1038/s41587-022-01628-0

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Citations (148)

High and low pressure gene gun devices give similar transformation efficiencies in maize calluses

African Journal of Plant Science (2010)

Cecilia Andrea Décima Oneto Ezequiel Bossio German Preciat Paula Faccio Dalia Marcela Lewi

Maize (Zea mays) is a major food crop of the world. Biotechnology plays an important role in plant genetic improvement, particularly for the introduction of novel traits in order to improve agronomic performance, medical and industrial applications and food quality. Particle bombardment is a rapid and simple method that enables the generation of events and affords genes expression studies. Nonetheless, an appropriate reporter gene is necessary to visualize gene expression in the transformed cells. In this study, conditions for transient expression in maize calluses for high and low gene gun pressure devices were optimized and their efficiencies were compared. Performance of gus and gfpreporter genes, either bombarded alone or together, was measured and compared. In addition, the advantages and disadvantages of utilizing these reporter genes in maize calluses and immature wheat embryos are discussed. Finally, we report that for transient transgene expression studies, the particle inflow gun (or LPGG) caters the need while a commercial gene gun (HPGG) device is not of much need. Key words: Biolistic, transient expression, reporter genes, plant genetic improvement.

Gene gun

10.5897/ajps.9000138

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Citations (1)