THE-DB: a threading model database for comparative protein structure analysis of the E. coli K12 and human proteomes

Mechanistic insights into phenanthrene acropetal translocation via wheat xylem: Separation and identification of transfer proteins

Polycyclic aromatic hydrocarbons (PAHs) have the potential to cause cancer, teratogenicity, and mutagenesis in humans. Long-term plant safe production relies on how PAHs are transported and coordinated across organs. However, the acropetal transfer mechanism of PAHs in staple crop stems, particularly in xylem, a critical path, is unknown. Herein, we first confirmed the presence of specific interaction between the proteins and phenanthrene by employing the magnetic phenanthrene-bound bead immunoassay and label free liquid chromatograph mass spectrometer (LC-MS/MS), suggesting that peroxidase (uniprot accession: A0A3B5XXD0) and unidentified proteins (uniprot accession: A0A3B6LUC6) may function as the carriers to load and acropetally translocate phenanthrene (a model PAH) in wheat xylem. This specified binding of protein-phenanthrene may form through hydrophobic interactions in the conservative binding region, as revealed by protein structural investigations and molecular docking. To further investigate the role of these proteins in phenanthrene solubilization, phenanthrene exposure was conducted: a substantial quantity of peroxidase was produced; an unusually high expression of uncharacterized proteins was observed, indicating their positive effects in the acropetal transfer of phenanthrene in wheat xylem. These data confirmed that the two proteins are crucial in the solubilization of phenanthrene in wheat xylem sap. Our findings provide fresh light on the molecular mechanism of PAH loading in plant xylem and techniques for ensuring the security of staple crops and improving the efficacy of phytoremediation in a PAH-contaminated environment.

Cross-Kingdom Comparative Transcriptomics Reveals Conserved Genetic Modules in Response to Cadmium Stress

It is known that organisms have developed various mechanisms to cope with cadmium (Cd) stress, while we still lack a system-level understanding of the functional isomorphy among them. In the present study, a cross-kingdom comparison was conducted among Escherichia coli, Saccharomyces cerevisiae, and Chlamydomonas reinhardtii, through toxicological tests, comparative transcriptomics, as well as conventional functional genomics. An equivalent level of Cd stress was determined via inhibition tests. Through transcriptome comparison, the three organisms exhibited differential gene expression under the same Cd stress relative to the corresponding no-treatment control. Results from functional enrichment analysis of differentially expressed genes (DEGs) showed that four metabolic pathways responsible for combating Cd stress were commonly regulated in the three organisms, including antioxidant reactions, sulfur metabolism, cell wall remodeling, and metal transport. In vivo expression patterns of 43 DEGs from the four pathways were further examined using quantitative PCR and resulted in a relatively comparable dynamic of gene expression patterns with transcriptome sequencing (RNA-seq). Cross-kingdom comparison of typical Cd stress-responding proteins resulted in the detection of 12 groups of homologous proteins in the three species. A class of potential metal transporters were subjected to cross-transformation to test their functional complementation. An ABC transporter gene in E. coli, possibly homologous to the yeast ycf1, was heterologously expressed in S. cerevisiae, resulting in enhanced Cd tolerance. Overall, our findings indicated that conserved genetic modules against Cd toxicity were commonly regulated among distantly related microbial species, which will be helpful for utilizing them in modifying microbial traits for bioremediation.

IMPORTANCE Research is establishing a systems biology view of biological response to Cd stress. It is meaningful to explore whether there is regulatory isomorphy among distantly related organisms. A transcriptomic comparison was done among model microbes, leading to the identification of a conserved cellular model pinpointing the generic strategies utilized by microbes for combating Cd stress. A novel E. coli transporter gene substantially increased yeast’s Cd tolerance. Knowledge on systems understanding of the cellular response to metals provides the basis for developing bioengineering remediation technology.

Protein structure prediction using sparse NOE and RDC restraints with Rosetta in CASP13

Computational methods that produce accurate protein structure models from limited experimental data, for example, from nuclear magnetic resonance (NMR) spectroscopy, hold great potential for biomedical research. The NMR-assisted modeling challenge in CASP13 provided a blind test to explore the capabilities and limitations of current modeling techniques in leveraging NMR data which had high sparsity, ambiguity, and error rate for protein structure prediction. We describe our approach to predict the structure of these proteins leveraging the Rosetta software suite. Protein structure models were predicted de novo using a two-stage protocol. First, low-resolution models were generated with the Rosetta de novo method guided by nonambiguous nuclear Overhauser effect (NOE) contacts and residual dipolar coupling (RDC) restraints. Second, iterative model hybridization and fragment insertion with the Rosetta comparative modeling method was used to refine and regularize models guided by all ambiguous and nonambiguous NOE contacts and RDCs. Nine out of 16 of the Rosetta de novo models had the correct fold (global distance test total score > 45) and in three cases high-resolution models were achieved (root-mean-square deviation < 3.5 å). We also show that a meta-approach applying iterative Rosetta + NMR refinement on server-predicted models which employed non-NMR-contacts and structural templates leads to substantial improvement in model quality. Integrating these data-assisted refinement strategies with innovative non-data-assisted approaches which became possible in CASP13 such as high precision contact prediction will in the near future enable structure determination for large proteins that are outside of the realm of conventional NMR.