Microorganisms produce a wide range of natural products (NPs) with clinically and agriculturally relevant biological activities. In bacteria and fungi, genes encoding successive steps in a biosynthetic pathway tend to be clustered on the chromosome as biosynthetic gene clusters (BGCs). Historically, “activity-guided” approaches to NP discovery have focused on bioactivity screening of NPs produced by culturable microbes. In contrast, recent “genome mining” approaches first identify candidate BGCs, express these biosynthetic genes using synthetic biology methods, and finally test for the production of NPs. Fungal genome mining efforts and the exploration of novel sequence and NP space are limited, however, by the lack of a comprehensive catalog of BGCs encoding experimentally-validated products. In this study, we generated a comprehensive reference set of fungal NPs whose biosynthetic gene clusters are described in the published literature. To generate this dataset, we first identified NCBI records that included both a peer-reviewed article and an associated nucleotide record. We filtered these records by text and homology criteria to identify putative NP-related articles and BGCs. Next, we manually curated the resulting articles, chemical structures, and protein sequences. The resulting catalog contains 197 unique NP compounds covering several major classes of fungal NPs, including polyketides, non-ribosomal peptides, terpenoids, and alkaloids. The distribution of articles published per compound shows a bias towards the study of certain popular compounds, such as the aflatoxins. Phylogenetic analysis of biosynthetic genes suggests that much chemical and enzymatic diversity remains to be discovered in fungi. Our catalog was incorporated into the recently launched Minimum Information about Biosynthetic Gene cluster (MIBiG) repository to create the largest known set of fungal BGCs and associated NPs, a resource that we anticipate will guide future genome mining and synthetic biology efforts toward discovering novel fungal enzymes and metabolites.
Carbon
dioxide (CO
2
) is becoming more attractive as
a renewable feedstock for chemical synthesis. In this study, CO
2
was incorporated into poly(ether carbonate) (PEC) polyols
by using a double-metal-cyanide catalyst. By adjusting the CO
2
pressure, the content of propylene carbonate units in the
PEC polyols was controlled, indicating successful and semiquantitative
incorporation of CO
2
into the PEC polyols. Polyurethane
foams (PUFs) with different propylene carbonate content were easily
prepared at room temperature by employing the PEC polyols due to their
adequate viscosity under ambient conditions. The firmness of the PUFs
increased as the amount of propylene carbonate units increased due
to the rigidity of the carbonate linkage, representing predictable
mechanical properties. Interestingly, reduced generation of volatile
organic compounds (VOCs) from the PUFs, namely acetaldehyde, was observed
with a high content of propylene carbonate units at 120 °C, indicating
good stability of the carbonate units against thermo-oxidative decomposition.
This study demonstrates the importance of CO
2
as an environmental-friendly
and renewable resource that can provide not only industrially important
but also problem-solving products in terms of processability and low
generation of VOCs.
The reaction of Cl2 with the (100) face of a GaAs single crystal was studied in the temperature range from 25 to 150 °C. The reaction was found to be first order in Cl2 at low pressures with an activation energy of 23.6 kcal. At pressures above 10 Torr it was found to reach a limiting rate with an activation energy of 14.2 kcal, attributable to the enthalpy of desorption of the GaCl3 product from this surface.
We study the level spacing distribution p(s) in the spectrum of random networks. According to our numerical results, the shape of p(s) in the Erdős-Rényi (E-R) random graph is determined by the average degree k and p(s) undergoes a dramatic change when k is varied around the critical point of the percolation transition, k = 1. When k 1, the p(s) is described by the statistics of the Gaussian orthogonal ensemble (GOE), one of the major statistical ensembles in Random Matrix Theory, whereas at k = 1 it follows the Poisson level spacing distribution. Closely above the critical point, p(s) can be described in terms of an intermediate distribution between Poisson and the GOE, the Brodydistribution. Furthermore, below the critical point p(s) can be given with the help of the regularized Gamma-function. Motivated by these results, we analyse the behaviour of p(s) in real networks such as the internet, a word association network and a protein-protein interaction network as well. When the giant component of these networks is destroyed in a node deletion process simulating the networks subjected to intentional attack, their level spacing distribution undergoes a similar transition to that of the E-R graph.
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