Publications

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7 Publications visible to you, out of a total of 7

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Background The ecological niche occupied by a fungal species, its pathogenicity and its usefulness as a microbial cell factory to a large degree depends on its secretome. Protein secretion usuallyy requires the presence of a N-terminal signal peptide (SP) and by scanning for this feature using available highly accurate SP-prediction tools, the fraction of potentially secreted proteins can be directly predicted. However, prediction of a SP does not guarantee that the protein is actually secreted and current in silico prediction methods suffer from gene-model errors introduced during genome annotation. Results A majority rule based classifier that also evaluates signal peptide predictions from the best homologs of three neighbouring Aspergillus species was developed to create an improved list of potential signal peptide containing proteins encoded by the Aspergillus niger genome. As a complement to these in silico predictions, the secretome associated with growth and upon carbon source depletion was determined using a shotgun proteomics approach. Overall, some 200 proteins with a predicted signal peptide were identified to be secreted proteins. Concordant changes in the secretome state were observed as a response to changes in growth/culture conditions. Additionally, two proteins secreted via a non-classical route operating in A. niger were identified. Conclusions We were able to improve the in silico inventory of A. niger secretory proteins by combining different gene-model predictions from neighbouring Aspergilli and thereby avoiding prediction conflicts associated with inaccurate gene-models. The expected accuracy of signal peptide prediction for proteins that lack homologous sequences in the proteomes of related species is 85%. An experimental validation of the predicted proteome confirmed in silico predictions.

Authors: Machtelt Braaksma, Elena S Martens-Uzunova, Peter J Punt, Peter J Schaap

Date Published: 1st Dec 2010

Publication Type: Journal

Abstract

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Authors: Machtelt Braaksma, Elsa Arcalís, Elena S Martens-Uzunova, Emanuela Pedrazzini, Peter J Punt, Ulrike Hörmann-Dietrich, Peter J Schaap, Alessandro Vitale, Eva Stoger

Date Published: 2022

Publication Type: Journal

Abstract

Not specified

Authors: Melchior du Lac, Thomas Duigou, Joan Hérisson, Pablo Carbonell, Neil Swainston, Valentin Zulkower, Forum Shah, Léon Faure, Mostafa Mahdy, Paul Soudier, Jean-Loup Faulon

Date Published: 15th Jun 2020

Publication Type: Journal

Abstract (Expand)

Abstract Background Cyanobacteria receive huge interest as green catalysts. While exploiting energy from sunlight, they co-utilize sugar and CO 2 . This photomixotrophic mode enables fast growth andze sugar and CO 2 . This photomixotrophic mode enables fast growth and high cell densities, opening perspectives for sustainable biomanufacturing. The model cyanobacterium Synechocystis sp. PCC 6803 possesses a complex architecture of glycolytic routes for glucose breakdown that are intertwined with the CO 2 -fixing Calvin-Benson-Bassham (CBB) cycle. To date, the contribution of these pathways to photomixotrophic metabolism has remained unclear. Results Here, we developed a comprehensive approach for 13 C metabolic flux analysis of Synechocystis sp. PCC 6803 during steady state photomixotrophic growth. Under these conditions, the Entner-Doudoroff (ED) and phosphoketolase (PK) pathways were found inactive but the microbe used the phosphoglucoisomerase (PGI) (63.1%) and the oxidative pentose phosphate pathway (OPP) shunts (9.3%) to fuel the CBB cycle. Mutants that lacked the ED pathway, the PK pathway, or phosphofructokinases were not affected in growth under metabolic steady-state. An ED pathway-deficient mutant ( Δeda ) exhibited an enhanced CBB cycle flux and increased glycogen formation, while the OPP shunt was almost inactive (1.3%). Under fluctuating light, ∆eda showed a growth defect, different to wild type and the other deletion strains. Conclusions The developed approach, based on parallel 13 C tracer studies with GC–MS analysis of amino acids, sugars, and sugar derivatives, optionally adding NMR data from amino acids, is valuable to study fluxes in photomixotrophic microbes to detail. In photomixotrophic cells, PGI and OPP form glycolytic shunts that merge at switch points and result in synergistic fueling of the CBB cycle for maximized CO 2 fixation. However, redirected fluxes in an ED shunt-deficient mutant and the impossibility to delete this shunt in a GAPDH2 knockout mutant, indicate that either minor fluxes (below the resolution limit of 13 C flux analysis) might exist that could provide catalytic amounts of regulatory intermediates or alternatively, that EDA possesses additional so far unknown functions. These ideas require further experiments.

Authors: Dennis Schulze, Michael Kohlstedt, Judith Becker, Edern Cahoreau, Lindsay Peyriga, Alexander Makowka, Sarah Hildebrandt, Kirstin Gutekunst, Jean-Charles Portais, Christoph Wittmann

Date Published: 1st Dec 2022

Publication Type: Journal

Abstract

Not specified

Authors: Ramón Román, Nikola Lončar, Antoni Casablancas, Marco W. Fraaije, Glòria Gonzalez

Date Published: 1st Jun 2020

Publication Type: Journal

Abstract (Expand)

Synthetic biology applied to industrial biotechnology is transforming the way we produce chemicals. However, despite advances in the scale and scope of metabolic engineering, the research and development process still remains costly. In order to expand the chemical repertoire for the production of next generation compounds, a major engineering biology effort is required in the development of novel design tools that target chemical diversity through rapid and predictable protocols. Addressing that goal involves retrosynthesis approaches that explore the chemical biosynthetic space. However, the complexity associated with the large combinatorial retrosynthesis design space has often been recognized as the main challenge hindering the approach. Here, we provide RetroPath2.0, an automated open source workflow for retrosynthesis based on generalized reaction rules that perform the retrosynthesis search from chassis to target through an efficient and well-controlled protocol. Its easiness of use and the versatility of its applications make this tool a valuable addition to the biological engineer bench desk. We show through several examples the application of the workflow to biotechnological relevant problems, including the identification of alternative biosynthetic routes through enzyme promiscuity or the development of biosensors. We demonstrate in that way the ability of the workflow to streamline retrosynthesis pathway design and its major role in reshaping the design, build, test and learn pipeline by driving the process toward the objective of optimizing bioproduction. The RetroPath2.0 workflow is built using tools developed by the bioinformatics and cheminformatics community, because it is open source we anticipate community contributions will likely expand further the features of the workflow.

Authors: B. Delepine, T. Duigou, P. Carbonell, J. L. Faulon

Date Published: No date defined

Publication Type: Not specified

Abstract (Expand)

RetroRules is a database of reaction rules for metabolic engineering (https://retrorules.org). Reaction rules are generic descriptions of chemical reactions that can be used in retrosynthesis workflows in order to enumerate all possible biosynthetic routes connecting a target molecule to its precursors. The use of such rules is becoming increasingly important in the context of synthetic biology applied to de novo pathway discovery and in systems biology to discover underground metabolism due to enzyme promiscuity. Here, we provide for the first time a complete set containing >400 000 stereochemistry-aware reaction rules extracted from public databases and expressed in the community-standard SMARTS (SMIRKS) format, augmented by a rule representation at different levels of specificity (the atomic environment around the reaction center). Such numerous representations of reactions expand natural chemical diversity by predicting de novo reactions of promiscuous enzymes.

Authors: T. Duigou, M. du Lac, P. Carbonell, J. L. Faulon

Date Published: No date defined

Publication Type: Not specified

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