Genetic dissection of cyclic pyranopterin monophosphate biosynthesis in plant mitochondria

Mitochondria play a key role in the biosynthesis of two metal cofactors, iron-sulfur (FeS) clusters and molybdenum cofactor (Moco). The two pathways intersect at several points, but a scarcity of mutants has hindered studies to better understand these links. We screened a collection of sirtinol-resistant Arabidopsis thaliana mutants for lines with decreased activities of cytosolic FeS enzymes and Moco enzymes. We identified a new mutant allele of ATM3 , encoding the ATP-binding cassette Transporter of the Mitochondria 3 (systematic name ABCB25), confirming the previously reported role of ATM3 in both FeS cluster and Moco biosynthesis. We also identified a mutant allele in CNX2, Cofactor of Nitrate reductase and Xanthine dehydrogenase 2 , encoding GTP 3′,8-cyclase, the first step in Moco biosynthesis which is localized in the mitochondria. A single nucleotide polymorphism in cnx2-2 leads to substitution of Arg88 with Gln in the N-terminal FeS cluster-binding motif. cnx2-2 plants are small and chlorotic, with severely decreased Moco enzyme activities, but they performed better than a cnx2-1 knockout mutant, which could only survive with ammonia as nitrogen source. Measurement of cyclic pyranopterin monophosphate (cPMP) levels by LC-MS/MS showed that this Moco intermediate was below the limit of detection in both cnx2-1 and cnx2-2 , and accumulated more than 10-fold in seedlings mutated in the downstream gene CNX5 . Interestingly, atm3-1 mutants had less cPMP than wild type, correlating with previous reports of a similar decrease in nitrate reductase activity. Taken together, our data functionally characterise CNX2 and suggest that ATM3 is indirectly required for cPMP synthesis

Metabolic reconstruction of sulfur assimilation in the extremophile Acidithiobacillus ferrooxidans based on genome analysis

BACKGROUND: Acidithiobacillus ferrooxidans is a gamma-proteobacterium that lives at pH2 and obtains energy by the oxidation of sulfur and iron. It is used in the biomining industry for the recovery of metals and is one of the causative agents of acid mine drainage. Effective tools for the study of its genetics and physiology are not in widespread use and, despite considerable effort, an understanding of its unusual physiology remains at a rudimentary level. Nearly complete genome sequences of A. ferrooxidans are available from two public sources and we have exploited this information to reconstruct aspects of its sulfur metabolism. RESULTS: Two candidate mechanisms for sulfate uptake from the environment were detected but both belong to large paralogous families of membrane transporters and their identification remains tentative. Prospective genes, pathways and regulatory mechanisms were identified that are likely to be involved in the assimilation of sulfate into cysteine and in the formation of Fe-S centers. Genes and regulatory networks were also uncovered that may link sulfur assimilation with nitrogen fixation, hydrogen utilization and sulfur reduction. Potential pathways were identified for sulfation of extracellular metabolites that may possibly be involved in cellular attachment to pyrite, sulfur and other solid substrates. CONCLUSIONS: A bioinformatic analysis of the genome sequence of A. ferrooxidans has revealed candidate genes, metabolic process and control mechanisms potentially involved in aspects of sulfur metabolism. Metabolic modeling provides an important preliminary step in understanding the unusual physiology of this extremophile especially given the severe difficulties involved in its genetic manipulation and biochemical analysis

Production paradigms for additive manufacturing systems: A simulation-based analysis

There is nowadays a lack of knowledge and structured approaches concerning the transition of additive manufacturing systems from rapid prototyping to large scale production. The fundamental advantage of additive manufacturing to produce at virtually no additional cost complex, one-of-a-kind parts suggest addressing their integration in the direction of arranging them into the consolidated Flexible Manufacturing Systems (FMS) paradigm. In this regard, this paper presents a procedure for the simulation-based analysis of FMS hosting additive manufacturing stations, supporting their planning, design as well as performance evaluation. A discrete-event simulation model was developed and applied for the operational evaluation of an industrial case comprising 3D-printing, automated transport, and storage systems. It has been found that simulation experiments can support planning and design decision-making, allowing for a better choice among alternative set-ups. However, the present research explored an application carried out in an academic environment where the simulation model was employed for evaluating the behaviour of new additive manufacturing technologies

Solving the Job-Shop Scheduling Problem in the Industry 4.0 Era

Technological developments along with the emergence of Industry 4.0 allow for new approaches to solve industrial problems, such as the Job-shop Scheduling Problem (JSP). In this sense, embedding Multi-Agent Systems (MAS) into Cyber-Physical Systems (CPS) is a highly promising approach to handle complex and dynamic JSPs. This paper proposes a data exchange framework in order to deal with the JSP considering the state-of-the-art technology regarding MAS, CPS and industrial standards. The proposed framework has self-configuring features to deal with disturbances in the production line. This is possible through the development of an intelligent system based on the use of agents and the Internet of Things (IoT) to achieve real-time data exchange and decision making in the job-shop. The performance of the proposed framework is tested in a simulation study based on a real industrial case. The results substantiate gains in flexibility, scalability and efficiency through the data exchange between factory layers. Finally, the paper presents insights regarding industrial applications in the Industry 4.0 era in general and in particular with regard to the framework implementation in the analyzed industrial case

Proposal of a Reconfigurability Index Using Analytic Network Process

This paper proposes a reconfigurability index. Its development is based on five core characteristics, namely modularity, integrability, diagnosability, adaptability and customization. The index takes into consideration the interdependencies that may exist among them. The analytic network process (ANP) method is used to attribute importance weights to each core characteristic. This index can be very useful in practice since it can guide manufacturing companies to a better understanding of the various enablers of reconfigurability, as well as in the decision-making process, to decide which core characteristic requires more attention, in order to further improve the reconfigurability in existing manufacturing systems