Methane is an essential component of the global carbon cycle and one of the most powerful greenhouse gases, yet it is also a promising alternative source of carbon for the biological production of value-added chemicals. Aerobic methane-consuming bacteria (methanotrophs) represent a potential biological platform for methane-based biocatalysis. Here we use a multipronged systems-level approach to reassess the metabolic functions for methane utilization in a promising bacterial biocatalyst. We demonstrate that methane assimilation is coupled with a highly efficient pyrophosphate-mediated glycolytic pathway, which under oxygen limitation participates in a novel form of fermentation-based methanotrophy. This surprising discovery suggests a novel mode of methane utilization in oxygen-limited environments, and opens new opportunities for a modular approach towards producing a variety of excreted chemical products using methane as a feedstock.

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Here, we compare the distributions of main chain (⌽,⌿) angles (i.e., Ramachandran maps) of the 20 naturally occurring amino acids in three contexts: (i) molecular dynamics (MD) simulations of GlyGly-X-Gly-Gly pentapeptides in water at 298 K with exhaustive sampling, where X ‫؍‬ the amino acid in question; (ii) 188 independent protein simulations in water at 298 K from our Dynameomics Project; and (iii) static crystal and NMR structures from the Protein Data Bank. The GGXGG peptide series is often used as a model of the unstructured denatured state of proteins. The sampling in the peptide MD simulations is neither random nor uniform. Instead, individual amino acids show preferences for particular conformations, but the peptide is dynamic, and interconversion between conformers is facile. For a given amino acid, the (⌽,⌿) distributions in the protein simulations and the Protein Data Bank are very similar and often distinct from those in the peptide simulations. Comparison between the peptide and protein simulations shows that packing constraints, solvation, and the tendency for particular amino acids to be used for specific structural motifs can overwhelm the ''intrinsic propensities'' of amino acids for particular (⌽,⌿) conformations. We also compare our helical propensities with experimental consensus values using the host-guest method, which appear to be determined largely by context and not necessarily the intrinsic conformational propensities of the guest residues. These simulations represent an improved coil library free from contextual effects to better model intrinsic conformational propensities and provide a detailed view of conformations making up the ''random coil'' state.coil library ͉ Dynameomics ͉ molecular dynamics ͉ protein folding ͉ host-guest P rotein secondary structure was predicted before the atomic structures of protein were determined (1-3). Conformational preferences of the amino acids were also estimated very early on, beginning with Ramachandran's ''map'' in 1963, ''based solely on repulsive van der Waals'' forces in dipeptides (4, 5). Remarkably, these predictions regarding structure and conformational preferences were later largely validated in protein crystal structures (6-8).In the protein folding field, these preferences are seen as both means of excluding regions of conformational space and as driving forces for the formation of secondary structure, both of which limit and bias the necessary search of conformational space required during protein folding.(⌽,⌿) dihedral angle distributions are increasingly used to check the validity of structures. Although there can be no doubt about the general tendency of amino acids in globular proteins to populate some regions of (⌽,⌿) space relative to others, the use of such distributions to judge and refine structures leads to dangerous circular reasoning. That is, (⌽,⌿) preferences are used as tests of crystal structures, and those very crystal structures are then used to define and support the Ramachandran (⌽,⌿) angle distributions.Many exper...

We report observations on the dynamics of bacterial communities in response to methane stimulus in laboratory microcosm incubations prepared with lake sediment samples. We first measured taxonomic compositions of long-term enrichment cultures and determined that, although dominated by Methylococcaceae types, these cultures also contained accompanying types belonging to a limited number of bacterial taxa, methylotrophs and non-methylotrophs. We then followed the shortterm community dynamics, in two oxygen tension regimens (150 lM and 15 lM), observing rapid loss of species diversity. In all microcosms, a single type of Methylobacter represented the major methane-oxidizing partner. The accompanying members of the communities revealed different trajectories in response to different oxygen tensions, with Methylotenera species being the early responders to methane stimulus under both conditions. The communities in both conditions were convergent in terms of their assemblage, suggesting selection for specific taxa. Our results support prior observations from metagenomics on distribution of carbon from methane among diverse bacterial populations and further suggest that communities are likely responsible for methane cycling, rather than a single type of microbe.