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We report here the complete genome sequence of Sphingobium xenophagum strain PH3-15, which was isolated from La Roche-Posay thermal water sources. The assembled 4.6-Mbp genome consisted of two chromosomes and three plasmids. These data will provide valuable information and important insights into the physiology and metabolism of this Sphingobium organism.

The use of methanol as carbon source for biotechnological processes has recently attracted great interest due to its relatively low price, high abundance, high purity, and the fact that it is a non-food raw material. In this study, methanol-based production of 5-aminovalerate (5AVA) was established using recombinant Bacillus methanolicus strains. 5AVA is a building block of polyamides and a candidate to become the C5 platform chemical for the production of, among others, δ-valerolactam, 5-hydroxy-valerate, glutarate, and 1,5-pentanediol. In this study, we test five different 5AVA biosynthesis pathways, whereof two directly convert L-lysine to 5AVA and three use cadaverine as an intermediate. The conversion of L-lysine to 5AVA employs lysine 2-monooxygenase (DavB) and 5-aminovaleramidase (DavA), encoded by the well-known Pseudomonas putida cluster davBA, among others, or lysine α-oxidase (RaiP) in the presence of hydrogen peroxide. Cadaverine is converted either to γ-glutamine-cadaverine by glutamine synthetase (SpuI) or to 5-aminopentanal through activity of putrescine oxidase (Puo) or putrescine transaminase (PatA). Our efforts resulted in proof-of-concept 5AVA production from methanol at 50°C, enabled by two pathways out of the five tested with the highest titer of 0.02 g l–1. To our knowledge, this is the first report of 5AVA production from methanol in methylotrophic bacteria, and the recombinant strains and knowledge generated should represent a valuable basis for further improved 5AVA production from methanol.

Methanol is inexpensive, is easy to transport, and can be produced both from renewable and from fossil resources without mobilizing arable lands. As such, it is regarded as a potential carbon source to transition toward a greener industrial chemistry. Metabolic engineering of bacteria and yeast able to efficiently consume methanol is expected to provide cell factories that will transform methanol into higher-value chemicals in the so-called methanol economy. Toward that goal, the study of natural methylotrophs such as Bacillus methanolicus is critical to understand the origin of their efficient methylotrophy. This knowledge will then be leveraged to transform such natural strains into new cell factories or to design methylotrophic capability in other strains already used by the industry., Bacillus methanolicus MGA3 is a thermotolerant and relatively fast-growing methylotroph able to secrete large quantities of glutamate and lysine. These natural characteristics make B. methanolicus a good candidate to become a new industrial chassis organism, especially in a methanol-based economy. Intriguingly, the only substrates known to support B. methanolicus growth as sole sources of carbon and energy are methanol, mannitol, and, to a lesser extent, glucose and arabitol. Because fluxomics provides the most direct readout of the cellular phenotype, we hypothesized that comparing methylotrophic and nonmethylotrophic metabolic states at the flux level would yield new insights into MGA3 metabolism. In this study, we designed and performed a 13C metabolic flux analysis (13C-MFA) of the facultative methylotroph B. methanolicus MGA3 growing on methanol, mannitol, and arabitol to compare the associated metabolic states. On methanol, results showed a greater flux in the ribulose monophosphate (RuMP) pathway than in the tricarboxylic acid (TCA) cycle, thus validating previous findings on the methylotrophy of B. methanolicus. New insights related to the utilization of cyclic RuMP versus linear dissimilation pathways and between the RuMP variants were generated. Importantly, we demonstrated that the linear detoxification pathways and the malic enzyme shared with the pentose phosphate pathway have an important role in cofactor regeneration. Finally, we identified, for the first time, the metabolic pathway used to assimilate arabitol. Overall, those data provide a better understanding of this strain under various environmental conditions. IMPORTANCE Methanol is inexpensive, is easy to transport, and can be produced both from renewable and from fossil resources without mobilizing arable lands. As such, it is regarded as a potential carbon source to transition toward a greener industrial chemistry. Metabolic engineering of bacteria and yeast able to efficiently consume methanol is expected to provide cell factories that will transform methanol into higher-value chemicals in the so-called methanol economy. Toward that goal, the study of natural methylotrophs such as Bacillus methanolicus is critical to understand the origin of their efficient methylotrophy. This knowledge will then be leveraged to transform such natural strains into new cell factories or to design methylotrophic capability in other strains already used by the industry.

Bio-based plastics represent an increasing percentage of the plastics economy. The fermentative production of bioplastic monomer 5-aminovalerate (5AVA), which can be converted to polyamide 5 (PA 5), has been established in Corynebacterium glutamicum via two metabolic pathways. l-lysine can be converted to 5AVA by either oxidative decarboxylation and subsequent oxidative deamination or by decarboxylation to cadaverine followed by transamination and oxidation. Here, a new three-step pathway was established by using the monooxygenase putrescine oxidase (Puo), which catalyzes the oxidative deamination of cadaverine, instead of cadaverine transaminase. When the conversion of 5AVA to glutarate was eliminated and oxygen supply improved, a 5AVA titer of 3.7 ± 0.4 g/L was reached in microcultivation that was lower than when cadaverine transaminase was used. The elongation of the new pathway by 5AVA transamination by GABA/5AVA aminotransferase (GabT) and oxidation by succinate/glutarate semialdehyde dehydrogenase (GabD) allowed for glutarate production. Flux enforcement by the disruption of the l-glutamic acid dehydrogenase-encoding gene gdh rendered a single transaminase (GabT) in glutarate production via the new pathway responsible for nitrogen assimilation, which increased the glutarate titer to 7.7 ± 0.7 g/L, i.e., 40% higher than with two transaminases operating in glutarate biosynthesis. Flux enforcement was more effective with one coupling site, thus highlighting requirements regarding the modularity and stoichiometry of pathway-specific flux enforcement for microbial production.

Summary Mass spectrometry (MS) is widely used for isotopic studies of metabolism and other (bio)chemical processes. Quantitative applications in systems and synthetic biology require to correct the raw MS data for the contribution of naturally occurring isotopes. Several tools are available to correct low-resolution MS data, and recent developments made substantial improvements by introducing resolution-dependent correction methods, hence opening the way to the correction of high-resolution MS (HRMS) data. Nevertheless, current HRMS correction methods partly fail to determine which isotopic species are resolved from the tracer isotopologues and should thus be corrected. We present an updated version of our isotope correction software (IsoCor) with a novel correction algorithm which ensures to accurately exploit any chemical species with any isotopic tracer, at any MS resolution. IsoCor v2 also includes a novel graphical user interface for intuitive use by end-users and a command-line interface to streamline integration into existing pipelines. Availability and implementation IsoCor v2 is implemented in Python 3 and was tested on Windows, Unix and MacOS platforms. The source code and the documentation are freely distributed under GPL3 license at https://github.com/MetaSys-LISBP/IsoCor/ and https://isocor.readthedocs.io/.

Bacteria rely on allosteric transcription factors (aTFs) to sense a wide range of chemicals. The variety of effectors has contributed in making aTFs the most used input system in synthetic biological circuits. Considering their enabling role in biotechnology, an important question concerns the size of the chemical space that can potentially be detected by these biosensors. From digging into the ever changing repertoire of natural regulatory circuits, to advances in aTF engineering, we review here different strategies that are pushing the boundaries of this chemical space. We also review natural and synthetic cases of indirect sensing, where aTFs work in combination with metabolism to enable detection of new molecules.

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 bioproduction 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 of this tool a valuable addition into 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.HighlightsState-of-the-art Computer-Aided Design retrosynthesis solutions lack open source and ease of useWe propose RetroPath2.0 a modular and open-source workflow to perform retrosynthesisRetroPath2.0 computes reaction network between Source and Sink sets of compoundsRetroPath2.0 is distributed as a KNIME workflow for desktop computersRetroPath2.0 is ready-for-use and distributed with reaction rulesFundingThis work was supported by the French National Research Agency [ANR-15-CE1-0008], the Biotechnology and Biological Sciences Research Council, Centre for synthetic biology of fine and speciality chemicals [BB/M017702/1]; Synthetic Biology Applications for Protective Materials [EP/N025504/1], and GIP Genopole.

Determining the fraction of the chemical space that can be processed in vivo by using natural and synthetic biology devices is crucial for the development of advanced synthetic biology applications. The extended metabolic space is a coding system based on molecular signatures that enables the derivation of reaction rules for metabolic reactions and the enumeration of all possible substrates and products corresponding to the rules. The extended metabolic space expands capabilities for controlling the production, processing, sensing, and the release of specific molecules in chassis organisms.

Determining the fraction of the chemical space that can be processed in vivo by using natural and synthetic biology devices is crucial for the development of advanced synthetic biology applications. The extended metabolic space is a coding system based on molecular signatures that enables the derivation of reaction rules for metabolic reactions and the enumeration of all possible substrates and products corresponding to the rules. The extended metabolic space expands capabilities for controlling the production, processing, sensing, and the release of specific molecules in chassis organisms.

This month: AI that learns patterns and facts, new protein-RNA and protein-protein relationships, engineering signaling and metabolism, and more variants of Cas9.