The recent discovery of the Entner-Doudoroff (ED) pathway as a third glycolytic route beside Embden-Meyerhof-Parnas (EMP) and oxidative pentose phosphate (OPP) pathway in oxygenic photoautotrophs requires a revision of their central carbohydrate metabolism. In this study, unexpectedly, we observed that deletion of the ED pathway alone, and even more pronounced in combination with other glycolytic routes, diminished photoautotrophic growth in continuous light in the cyanobacterium Synechocystis sp. PCC 6803. Furthermore, we found that the ED pathway is required for optimal glycogen catabolism in parallel to an operating Calvin-Benson-Bassham (CBB) cycle. It is counter-intuitive that glycolytic routes, which are a reverse to the CBB cycle and do not provide any additional biosynthetic intermediates, are important under photoautotrophic conditions. However, observations on the ability to reactivate an arrested CBB cycle revealed that they form glycolytic shunts that tap the cellular carbohydrate reservoir to replenish the cycle. Taken together, our results suggest that the classical view of the CBB cycle as an autocatalytic, completely autonomous cycle that exclusively relies on its own enzymes and CO2 fixation to regenerate ribulose-1,5-bisphosphate for Rubisco is an oversimplification. We propose that in common with other known autocatalytic cycles, the CBB cycle likewise relies on anaplerotic reactions to compensate for the depletion of intermediates, particularly in transition states and under fluctuating light conditions that are common in nature.

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Human untargeted metabolomics studies annotate only ~10% of molecular features. We introduce reference-data-driven analysis to match metabolomics tandem mass spectrometry (MS/MS) data against metadata-annotated source data as a pseudo-MS/MS reference library. Applying this approach to food source data, we show that it increases MS/MS spectral usage 5.1-fold over conventional structural MS/MS library matches and allows empirical assessment of dietary patterns from untargeted data.Complex sequence data from metagenomic (see Box 1 for definition of terms) or metatranscriptomic experiments require for interpretation both databases of curated genes and reference data, such as whole genomes or other sequence data with carefully curated metadata (developmental stage, tissue location, phenotype, etc.) [1][2][3][4] . Such reference data-driven (RDD) analysis increases understanding of complex communities by using matches between genes or transcripts of known and unknown origin. The RDD strategy is essential for the successful analysis of most metatranscriptomics or metagenomics data. By analogy, interpreting liquid chromatography-tandem mass spectromtery (LC-MS/MS)-based untargeted metabolomics data is performed by searching structural MS/MS libraries. However, leveraging reference data with curated and structured controlled vocabulary metadata to improve insights obtainable from untargeted MS/MS-based metabolomics is not yet done.RDD analysis uses not only annotated MS/MS-spectra but also all unannotated spectra. The gas chromatography-mass spectrometry (GC-MS) BinBase resource has made a step in the direction of RDD. With BinBase one can annotate if a spectrum match has been observed in a non-public GC-MS dataset. However, the metadata is not well controlled and lacks the ability to add contextualized metadata 5,6 . In addition, as we have previously demonstrated, using structural annotations, the source can be determined by literature mining 7 . However, owing to the above mentioned limitations and/ or inability to link related spectra in the case of metabolism, the above strategies to annotate unknowns cannot be used to systematically to interpret the source information at the dataset level. We therefore introduce the RDD approach for metabolomics (Fig. 1), followed by a use case demonstrating empirical food readouts from untargeted human data (Fig. 2).Untargeted MS/MS-based metabolomics experiments involve searching MS/MS structural libraries since the late 1970's 8,9 , or, more recently, for investigating the distribution of a MS/MS spectrum across public untargeted data 10 . Instead of only leveraging a single MS/MS spectrum to obtain an annotation, RDD metabolomics uses all MS/MS spectra from untargeted metabolomics files, which con-

The decarboxylation of pyruvate is a central reaction in the carbon metabolism of all organisms. It is catalyzed by the pyruvate:ferredoxin oxidoreductase (PFOR) and the pyruvate dehydrogenase (PDH) complex. Whereas PFOR reduces ferredoxin, the PDH complex utilizes NAD+. Anaerobes rely on PFOR, which was replaced during evolution by the PDH complex found in aerobes. Cyanobacteria possess both enzyme systems. Our data challenge the view that PFOR is exclusively utilized for fermentation. Instead, we show, that the cyanobacterial PFOR is stable in the presence of oxygen in vitro and is required for optimal photomixotrophic growth under aerobic and highly reducing conditions while the PDH complex is inactivated. We found that cells rely on a general shift from utilizing NAD(H)-dependent to ferredoxin-dependent enzymes under these conditions. The utilization of ferredoxins instead of NAD(H) saves a greater share of the Gibbs free energy, instead of wasting it as heat. This obviously simultaneously decelerates metabolic reactions as they operate closer to their thermodynamic equilibrium. It is common thought that during evolution, ferredoxins were replaced by NAD(P)H due to their higher stability in an oxidizing atmosphere. However, utilization of NAD(P)H could also have been favored due to a higher competitiveness because of an accelerated metabolism.

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