Systems Biotechnology Group



Juan Nogales

Group Leader


 Logo SBG 1

Research summary

Our goal is deciphering the complexity of microbial metabolism, its evolutionary and biotechnological implications through a multidisciplinary approach. By assuming that the whole is greater than the sum of its parts, we aim to contribute to a better understanding of the emergent properties of microbial systems at subcellular, cellular and supracellular levels. We pursuit the rational re-design of these system properties towards novel biotechnological and medical applications.



Nogales J and Garmendia J. Bacterial metabolism and pathogenesis intimate intertwining: time for metabolic modelling to come into action Microb Biotechnol. 2021 Oct 21.doi: 10.1111/1751-7915.13942.

Gudmundsson S and Nogales J.  Recent advances in model-assisted metabolic engineering. Curr Opin Syst Biol. 2021; Vol 28,100392

Torres-Bacete J, García JL, and Nogales J. A portable library of phosphate-depletion based synthetic promoters for customable and automata control of gene expression in bacteria. Microb Biotechnol. 2021 Mar 30.doi: 10.1111/1751-7915.13808.

García-Jiménez B, Torres-Bacete J, Nogales J. Metabolic modelling approaches for describing and engineering microbial communities. Comput. Struct. Biotechnol. J. 2021. 19, 226-246

Goris T, Pérez-Valero A, Martínez I, Yi D, Fernández-Calleja L, San León D, Bornscheuer UT, Magadán-Corpas P, Lombó G, Nogales J. 2020. Repositioning microbial biotechnology against COVID-19: the case of microbial production of flavonoids. Microb Biotechnol. 2021 Jan;14(1):94-110 doi: 10.1111/1751-7915.13675.

Monk J, Nogales J, Palsson BO. Optimizing genome-scale network reconstructionsOptimizing genome-scale network reconstructions. Nat Biotechnol. 2014 May;32(5):447-52.

More publications


logo ministerio eco com2017-2024: INFRAIA-02-2017 and H2020-INFRADEV-2019-2. Industrial Biotechnology Innovation and Synthetic Biology Accelerator, IBISBA nº GA 730976 and 871118.

2019-2023: H2020-NMBP-BIO-2018-two-stage. Synthetic microbial consortia-based platform for flavonoids production using synthetic biology, SynBio4Flav nº GA 814650.

2020-2023: ERA CoBioTech, 2nd Joint Call on Biotechnologies. Microbial Conversion of lignin to monomers for bio-based plastic using synthetic biology MILIMO.

2020-2024: H2020-NMBP-BIO-CN-2019. MIXed plastics biodegradation and UPcycling using microbial communities, MIXUP nº GA 870294.

2020-2023: MCIU. System analysis and biotechnological applications of bacterial metabolic robustness at supracellular level (RobExplode). PID2019-108458RB-I00.

2021-2025: H2020-FNR-2020-2. Harnessing the power of nature through productive microbial consortia in biotechnology: Measure, Model, Master, PROMICOM , nº GA 101000733

logo CSIC

Interdisciplinary Platform for Sustainable Plastics towards a Circular Economy‐Spanish National Research Council (SusPlast-CSIC).




 Our foundational aim is the system-level understanding of microbial metabolism as a framework for developing a broad range of novel and non-intuitive biotechnological processes, ranging from industrial biotechnology to unconventional computing and living architecture. Taking advantage of metabolic modelling, systems and synthetic biology we are addressing, at different levels, the understanding and full taming of bacterial systems emergence.

Increasing the completeness and scope of metabolic reconstructions

Since we are largely committed in increasing the available computable reactome, we are involved in the high-quality metabolic modeling of a large set of metabolically diverse bacteria including P. putida KT2440, Synechocystis PCC6803, S. elongatus PCC7942, A. platensis, Azoarcus sp.CIB, S. granuli sp.TFA, P. pseudoalcaligenes CECT5344 and B. bacteriovorus HD100. This effort is enabling the system-level analysis of new metabolic processes while providing new computational test-beds for biotechnological applications. We are also interested in the inclusion of new metabolic modules and modelling approaches. Current efforts are targeted on i) the modeling of endogenous reactive oxygen species (ROS), ii) the implementation of dynamic condition-specific models and iii) the inclusion of posttranslational regulation.

System level analysis of Metabolic Robustness in bacteria

The robustness of a system is the property that allows it to maintain its functions despite external and internal perturbations. Through the metabolic modeling analysis of P. putida, we have recently identified metabolic cycles providing robustness to this bacterium. By using synthetic biology, ongoing efforts are focused on the rational engineering of such cycles under diverse biotechnological scenarios. In addition, we are increasing the metabolic robustness of P. putida by expanding its metabolic performance under oxygen limitation.

System level analysis and designing of microbial communities

The division of labor in microbial consortia allows an expanded complexity and functionality in bacteria. We are interested in: i) understanding how these expanded capabilities emerge within a community and ii) how we can engineer this community-level functionality towards biotechnological endeavors. To address these two fundamental questions we have developed a computational platform for modeling and engineering synthetic microbial consortia. Further implementation of these model-based designs is allowing us to develop new synthetic biology tools suitable for engineering microbial communities.

Fig. 1 PlatformSBG

Systems metabolic modeling and engineering platform developed by SBG.



Fig. 2 SyntheticCorsortia SBG

Multitasks synthetic microbial consortia being developed by SBG in the context of Living Architecture project





Juan Nogales Principal investigator
Igor Martínez Postdoctoral scientist
Jesús Torres Bacete Postdoctoral scientist
Marcela Villegas Plazas Postdoctoral scientist
Blas Blázquez Castiñeira Postdoctoral scientist
Erika González Álvarez Postdoctoral scientist
David San León Granado Predoctoral scientist
Álvaro Gómez Luengo Predoctoral scientist
Francisco J Canalejo Molero Predoctoral scientist
Álvaro Gargantilla Becerra Predoctoral scientist
Ana del Ramo Galián Predoctoral scientist
Clive A. Dove Lab manager
Fadipe Temitope Visiting Professor

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