Big Moose Basin: simulation of response to acidic deposition

The ILWAS model has been enhanced for application to multiple-lake hydrologic basins. This version of the model has been applied to the Big Moose basin, which includes Big Moose Lake and its tributary streams, lakes, and watersheds. The basin, as defined, includes an area of 96 km², with over 20 lakes and ponds, and 70 km of streams. Hydrologic and chemical calibrations have been made using data from seven sampling stations. When total atmospheric sulfur loading to the basin is halved, the model predicts, after four years of simulation, a decreasing sulfate concentration and to a lesser extent a rising alkalinity at Big Moose Lake outlet. At the end of four years, the results show an increase in pH of 0.1 to 0.5 pH units depending upon season.     

High level of divergence of male-reproductive-tract proteins, between Drosophila melanogaster and its sibling species, D. simulans

We compared male-reproductive-tract polypeptides of Drosophila melanogaster and D. simulans by using two-dimensional gel electrophoresis. Approximately 64% of male-reproductive-tract polypeptides were identical between two randomly chosen isofemale lines from these two species, compared with 83% identity for third-instar imaginal wing-disc polypeptides. Qualitatively similar differences were found between reproductive tracts and imaginal discs when D. sechellia was compared with D. melanogaster and with D. simulans. When genic polymorphism was taken into account, approximately 10% of male- reproductive-tract polypeptides were apparently fixed for different alleles between D. melanogaster and D. simulans; this proportion is the same as that found for soluble enzymes by one-dimensional gel electrophoresis. Strikingly, approximately 20% of male-reproductive- tract polypeptides of either D. melanogaster or D. simulans had no detectable homologue in the other species. We propose that proteins of the Drosophila male reproductive tract may have diverged more extensively between species than have other types of proteins and that much of this divergence may involve large changes in levels of polypeptide expression.      

Lipoproteins of Haemophilus influenzae type b.

Haemophilus influenzae type b Minn A produced 12 lipoproteins with apparent molecular weights of between 14,000 and 67,000. The lipoproteins were identified by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and fluorography of delipidated extracts of cells grown in [3H]palmitate. When the delipidated cell extracts were subjected to acid methanolysis, tritium was quantitatively recovered as palmitate and methyl palmitate, indicating that the [3H]palmitate had not been degraded and reincorporated into nonlipid material during cell growth. One of the lipoproteins comigrated with outer membrane protein (OMP) P6. OMP P6 was purified from [3H]palmitate-labeled cells. The purified protein preparation contained both amide- and ester-linked fatty acids. We conclude that (i) H. influenzae type b produces several lipoproteins, and (ii) one of these lipoproteins is OMP P6, a protein under consideration as a vaccine component.     

Nucleotide sequences of dnaE, the gene for the polymerase subunit of DNA polymerase III in Salmonella typhimurium, and a variant that facilitates growth in the absence of another polymerase subunit.

The dnaE gene of Salmonella typhimurium, like that of Escherichia coli, encodes the alpha subunit containing the polymerase activity of the principal replicative enzyme, DNA polymerase III. This gene, or one nearby, has been identified as the locus of suppressor mutations that promote growth by cells deleted for dnaQ, the gene for the editing subunit of this enzyme complex. Using a combination of nucleotide sequencing and marker rescue experiments, the alteration in one such suppressor was identified as a valine-to-glycine substitution at amino acid 832 of the 1,160-amino-acid alpha polypeptide. The alpha polypeptides of E. coli and S. typhimurium are identical in size and in 97% of their amino acid residues. Their identity includes the valine residue that was changed in the suppressor allele of S. typhimurium. We also localized a temperature-sensitive dnaE mutation to the 3' half of dnaE.     

The detection and attribution of extreme reductions in vegetation growth across the global land surface

Negative extreme anomalies in vegetation growth (NEGs) usually indicate severely impaired ecosystem services. These NEGs can result from diverse natural and anthropogenic causes, especially climate extremes (CEs). However, the relationship between NEGs and many types of CEs remains largely unknown at regional and global scales. Here, with satellite-derived vegetation index data and supporting tree-ring chronologies, we identify periods of NEGs from 1981 to 2015 across the global land surface. We find 70% of these NEGs are attributable to five types of CEs and their combinations, with compound CEs generally more detrimental than individual ones. More importantly, we find that dominant CEs for NEGs vary by biome and region. Specifically, cold and/or wet extremes dominate NEGs in temperate mountains and high latitudes, whereas soil drought and related compound extremes are primarily responsible for NEGs in wet tropical, arid and semi-arid regions. Key characteristics (e.g., the frequency, intensity and duration of CEs, and the vulnerability of vegetation) that determine the dominance of CEs are also region- and biome-dependent. For example, in the wet tropics, dominant individual CEs have both higher intensity and longer duration than non-dominant ones. However, in the dry tropics and some temperate regions, a longer CE duration is more important than higher intensity. Our work provides the first global accounting of the attribution of NEGs to diverse climatic extremes. Our analysis has important implications for developing climate-specific disaster prevention and mitigation plans among different regions of the globe in a changing climate.     

Statistical significance of hierarchical multi-body potentials based on Delaunay tessellation and their application in sequence-structure alignment.

Statistical potentials based on pairwise interactions between C alpha atoms are commonly used in protein threading/fold-recognition attempts. Inclusion of higher order interaction is a possible means of improving the specificity of these potentials. Delaunay tessellation of the C alpha-atom representation of protein structure has been suggested as a means of defining multi-body interactions. A large number of parameters are required to define all four-body interactions of 20 amino acid types (20(4) = 160,000). Assuming that residue order within a four-body contact is irrelevant reduces this to a manageable 8,855 parameters, using a nonredundant dataset of 608 protein structures. Three lines of evidence support the significance and utility of the four-body potential for sequence-structure matching. First, compared to the four-body model, all lower-order interaction models (three-body, two-body, one-body) are found statistically inadequate to explain the frequency distribution of residue contacts. Second, coherent patterns of interaction are seen in a graphic presentation of the four-body potential. Many patterns have plausible biophysical explanations and are consistent across sets of residues sharing certain properties (e.g., size, hydrophobicity, or charge). Third, the utility of the multi-body potential is tested on a test set of 12 same-length pairs of proteins of known structure for two protocols: Sequence-recognizes-structure, where a query sequence is threaded (without gap) through the native and a non-native structure; and structure-recognizes-sequence, where a query structure is threaded by its native and another non-native sequence. Using cross-validated training, protein sequences correctly recognized their native structure in all 24 cases. Conversely, structures recognized the native sequence in 23 of 24 cases. Further, the score differences between correct and decoy structures increased significantly using the three- or four-body potential compared to potentials of lower order.